diff --git a/.gitignore b/.gitignore
new file mode 100644
index 0000000000000000000000000000000000000000..b9c45e842b0ff3b65e1e30a28491c0eff94f5f8c
--- /dev/null
+++ b/.gitignore
@@ -0,0 +1,108 @@
+venv/*
+.vscode/*
+
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+#custom
+log/*
+log*-*/*
+*.zip
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+
+# PyInstaller
+# Usually these files are written by a python script from a template
+# before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+.hypothesis/
+.pytest_cache/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# pyenv
+.python-version
+
+# celery beat schedule file
+celerybeat-schedule
+
+# SageMath parsed files
+*.sage.py
+
+# dotenv
+.env
+
+# virtualenv
+.venv
+venv/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
diff --git a/GPRL/MCTS/MCTS.py b/GPRL/MCTS/MCTS.py
new file mode 100644
index 0000000000000000000000000000000000000000..2b7bb175ad06d0c072fc68575bd5866f8c69603f
--- /dev/null
+++ b/GPRL/MCTS/MCTS.py
@@ -0,0 +1,128 @@
+from ..reprenstation.linearGP import Instruction
+import numpy as np
+
+import copy
+import random
+
+from collections import deque
+from itertools import product
+
+class TreeNMCS(object):
+ def __init__(self, pset, max_len, fitness, nb_playout=1):
+ self.max_len = max_len
+ self.pset = pset
+ self.ops = copy.deepcopy(pset.terminals)
+ for k, v in pset.primitives.items():
+ if k in self.ops:
+ self.ops[k] += copy.deepcopy(v)
+ else:
+ self.ops[k] = copy.deepcopy(v)
+ self.nb_playout = nb_playout
+ self.fitness = fitness
+
+ def possible_primitives(self, individual, leaves):
+ l = []
+ for op in self.ops[leaves[0]]:
+ if isinstance(op, type):
+ op = op()
+ if len(individual) + len(leaves) + op.arity <= self.max_len:
+ l.append(op)
+ return l
+
+ def play(self, individual, leaves, op):
+ individual.append(op)
+ leaves.pop(0)
+ if op.arity > 0:
+ leaves = op.args + leaves
+ return individual, leaves
+
+ def playout(self, individual, leaves):
+ while len(leaves) != 0:
+ op = random.choice(self.possible_primitives(individual, leaves))
+ individual, leaves = self.play(individual, leaves, op)
+ return individual
+
+ def compute_fitness(self, individual):
+ #f = gp.compile(gp.PrimitiveTree(individual), pset=self.pset)
+ return self.fitness(individual)
+
+ def run(self, individual, leaves, level):
+ best_individual = None
+ best_fitness = np.NINF
+ #idx = 0
+ while len(leaves) != 0:
+ ops = self.possible_primitives(individual, leaves)
+ for op in ops:
+ cp_ind, cp_leaves = copy.deepcopy(individual), copy.deepcopy(leaves)
+ cp_ind, cp_leaves = self.play(cp_ind, cp_leaves, op)
+ if level == 1:
+ cp_ind = self.playout(cp_ind, cp_leaves)
+ else:
+ cp_ind = self.run(cp_ind, cp_leaves, level-1)
+ fitness = self.compute_fitness(cp_ind)
+
+ if fitness > best_fitness:
+ best_individual = copy.deepcopy(cp_ind)
+ best_fitness = fitness
+ individual, leaves = self.play(individual, leaves, best_individual[len(individual)])
+ #idx += 1
+ return individual
+
+class LinearNCMS(object):#/!\ never been tested
+ def __init__(self, interpreter, regCalcSize, regSize, max_len, fitness, nb_playout=1):
+ self.max_len = max_len
+ self.interpreter = interpreter
+ self.nb_playout = nb_playout
+ self.fitness = fitness
+
+ self.regCalcSize = regCalcSize
+ self.regSize = regSize
+
+ def play(self, individual, instruction, R_eff):
+ if not self.interpreter.branch[instruction.opcode]: R_eff.remove(instruction.dst)
+
+ R_eff.add(instruction.inpt1)
+ if self.interpreter.arity[instruction.opcode] == 2:
+ R_eff.add(instruction.inpt2)
+
+ individual.appendleft(instruction)
+ return individual
+
+ def possible_primitives(self, individual, R_eff, opsOnly=False):
+ instructions = []
+ out = R_eff.intersection(set(range(self.regCalcsize)))
+ if not bool(out):
+ out = range(self.regCalcsize)
+ inpt = range(self.regSize) if len(individual) < self.max_size else range(self.regCalcSize, self.regSize)
+ for opcode, dst, in1, in2 in product(self.interpreter.ops, R_eff, inpt, inpt):
+ instructions.append(Instruction(opcode, dst, in1, in2))
+ return instructions
+
+ def playout(self, individual, R_eff):
+ while len(individual) < self.max_len:
+ instr = random.choice(self.possible_primitives(individual, R_eff))
+ individual = self.play(individual, instr)
+ return individual
+
+ def compute_fitness(self, individual):
+ return self.fitness(individual)
+
+ def run(self, individual, level):
+ best_individual = None
+ best_fitness = np.NINF
+ while len(individual) < self.max_len:
+ instructions = self.possible_primitives(individual)
+ for instr in instructions:
+ cp_ind = copy.deepcopy(individual)
+ cp_ind = self.play(cp_ind, instr)
+ if level == 1:
+ cp_ind = self.playout(cp_ind)
+ else:
+ cp_ind = self.run(cp_ind, level-1)
+ fitness = self.compute_fitness(cp_ind)
+
+ if fitness > best_fitness:
+ best_individual = copy.deepcopy(cp_ind)
+ best_fitness = fitness
+ individual, leaves = self.play(individual, leaves, best_individual[len(individual)])
+ return individual
\ No newline at end of file
diff --git a/GPRL/MCTS/__init__.py b/GPRL/MCTS/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/GPRL/UCB.py b/GPRL/UCB.py
new file mode 100644
index 0000000000000000000000000000000000000000..666f3429182e2588d1e1a305375d3e4a1933e65e
--- /dev/null
+++ b/GPRL/UCB.py
@@ -0,0 +1,169 @@
+from copy import deepcopy
+from functools import partial
+import heapq
+from operator import attrgetter, eq
+import random
+from bisect import bisect_right
+
+from deap.base import Fitness
+from deap import tools
+import numpy as np
+
+class UCBFitness(Fitness):
+
+ c=np.sqrt(2)
+ sigma=1.0
+
+ def __init__(self, offset=0, values=(), **kwargs):
+ super().__init__(values=values, **kwargs)
+ self.rewards = []
+ self.offset = offset
+
+ def add_reward(self, reward):
+ self.rewards.append(reward)
+
+ def update_offset(self):
+ self.offset = len(self.rewards)
+
+ def calc_fitness(self, budget):
+ if self.rewards:
+ return np.mean(self.rewards, axis=0) + self.sigma*self.c*np.sqrt(np.log(budget+self.offset+1)/len(self.rewards))
+
+ def reset(self):
+ self.rewards = []
+ self.offset = 0
+
+class HeapWithKey(list):
+ def __init__(self, initial=[], key=lambda x:x):
+ super(HeapWithKey, self).__init__([(key(item), i, item) for i, item in enumerate(initial)])
+ self.key = key
+ self.idx = 0
+ if initial:
+ self.idx = len(self)
+ heapq.heapify(self)
+ else:
+ self = []
+
+ def push(self, item):
+ heapq.heappush(self, (self.key(item), self.idx, item))
+ self.idx += 1
+
+ def pop(self):
+ return heapq.heappop(self)[2]
+
+def selDoubleTournament(individuals, k, fitness_size, parsimony_size, fitness_first=True, fit_attr="fitness"):
+ assert (0.0 < parsimony_size <= 2), "Parsimony tournament size has to be in the range [1, 2]."
+
+ def _sizeTournament(individuals, k, select):
+ chosen = []
+ for i in range(k):
+ prob = parsimony_size / 2.
+ ind1, ind2 = select(individuals, k=2)
+
+ if len(ind1.fitness.rewards) < len(ind2.fitness.rewards):
+ ind1, ind2 = ind2, ind1
+ elif len(ind1) == len(ind2):
+ prob = 0.5
+
+ chosen.append(ind1 if random.random() < prob else ind2)
+
+ return chosen
+
+ def _fitTournament(individuals, k, select):
+ chosen = []
+ for i in range(k):
+ aspirants = select(individuals, k=fitness_size)
+ chosen.append(max(aspirants, key=attrgetter(fit_attr)))
+ return chosen
+
+ if fitness_first:
+ tfit = partial(_fitTournament, select=tools.selRandom)
+ return _sizeTournament(individuals, k, tfit)
+ else:
+ tsize = partial(_sizeTournament, select=tools.selRandom)
+ return _fitTournament(individuals, k, tsize)
+
+
+class ArmHof(tools.HallOfFame):
+ def __init__(self, maxsize):
+ super().__init__(maxsize, similar=eq)
+
+ def update(self, population):
+ for ind in population:
+ if len(self) == 0 and self.maxsize !=0:
+ # Working on an empty hall of fame is problematic for the
+ # "for else"
+ self.insert(population[0])
+ continue
+ if len(ind.fitness.rewards) > len(self[-1].fitness.rewards) or len(self) < self.maxsize:
+ if len(self) >= self.maxsize:
+ self.remove(-1)
+ self.insert(ind)
+
+ def insert(self, item):
+ item = deepcopy(item)
+ i = bisect_right(self.keys, len(item.fitness.rewards))
+ self.items.insert(len(self) - i, item)
+ self.keys.insert(i, len(item.fitness.rewards))
+
+
+class UpdateFitnessHof(tools.HallOfFame):
+ def __init__(self, maxsize, similar=eq, maxsize_arm=None):
+ super().__init__(maxsize, similar=similar)
+ self.maxsize_arm = maxsize_arm
+ if maxsize_arm is not None:
+ self.arm_hof = ArmHof(self.maxsize_arm)
+
+ def update(self, population):
+ for ind in population:
+ if len(self) == 0 and self.maxsize !=0:
+ # Working on an empty hall of fame is problematic for the
+ # "for else"
+ self.insert(population[0])
+ continue
+ idx = 0
+ while idx < len(self):
+ if self.similar(ind, self[idx]):
+ self.remove(idx)
+ break
+ idx+=1
+ if ind.fitness > self[-1].fitness or len(self) < self.maxsize:
+ # The individual is unique and strictly better than
+ # the worst
+ if len(self) >= self.maxsize:
+ self.remove(-1)
+ self.insert(ind)
+ if self.maxsize_arm is not None:
+ self.arm_hof.update(population)
+
+class UpdateFitnessParetoFront(tools.ParetoFront):
+ def __init__(self, similar, maxsize_arm=None):
+ super().__init__(similar=similar)
+ self.maxsize_arm = maxsize_arm
+ if maxsize_arm:
+ self.arm_hof = ArmHof(self.maxsize_arm)
+
+ def update(self, population):
+ for ind in population:
+ is_dominated = False
+ dominates_one = False
+ has_twin = False
+ to_remove = []
+ for i, hofer in enumerate(self): # hofer = hall of famer
+ if not dominates_one and hofer.fitness.dominates(ind.fitness):
+ is_dominated = True
+ break
+ elif ind.fitness.dominates(hofer.fitness):
+ dominates_one = True
+ to_remove.append(i)
+ elif ind.fitness == hofer.fitness and self.similar(ind, hofer):#Ã corriger!
+ has_twin = True
+ break
+
+ for i in reversed(to_remove): # Remove the dominated hofer
+ self.remove(i)
+ if not is_dominated and not has_twin:
+ self.insert(ind)
+
+ if self.maxsize_arm is not None:
+ self.arm_hof.update()
\ No newline at end of file
diff --git a/GPRL/__init__.py b/GPRL/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/GPRL/algorithms.py b/GPRL/algorithms.py
new file mode 100644
index 0000000000000000000000000000000000000000..79b2869db5f9b24732c9b672e97d41711cdb1155
--- /dev/null
+++ b/GPRL/algorithms.py
@@ -0,0 +1,247 @@
+from collections import deque
+from deap import tools, algorithms
+import heapq
+from timeit import default_timer as timer
+
+from .UCB import UCBFitness, HeapWithKey
+
+#warning ucb on first objective !
+def eaMuPlusLambdaUCB(population, toolbox, simulation_budget, parallel_update, mu, lambda_, cxpb, mutpb, ngen,
+ select=False, stats=None, halloffame=None, verbose=__debug__, budget_scheduler=None):
+ assert all([isinstance(ind.fitness, UCBFitness) for ind in population])
+
+ logbook = tools.Logbook()
+ logbook.header = ['gen', 'nevals'] + (stats.fields if stats else [])
+
+ # Evaluate the individuals with an invalid fitness
+ invalid_ind = [ind for ind in population if not ind.fitness.valid]
+ fitnesses = toolbox.map(toolbox.evaluate, invalid_ind)
+ for ind, fit in zip(invalid_ind, fitnesses):
+ ind.fitness.add_reward(fit[0])
+ ind.fitness.values = ind.fitness.calc_fitness(simulation_budget), *fit[1:]
+
+ if select:
+ get_individual = lambda inds: toolbox.select(inds, parallel_update)
+ else:
+ popoff = HeapWithKey(population, lambda x: -x.fitness.values[0])
+ get_individual = lambda _: [popoff.pop() for _ in range(parallel_update)]
+ tmp = 0
+ while(tmp < simulation_budget):
+ inds = get_individual(population)
+ fitnesses = toolbox.map(toolbox.evaluate, inds)
+ for ind, fit in zip(inds, fitnesses):
+ ind.fitness.add_reward(fit[0])
+ ind.fitness.values = ind.fitness.calc_fitness(simulation_budget), *fit[1:]
+ if not select:
+ popoff.push(ind)
+ tmp+=1
+
+ if halloffame is not None:
+ halloffame.update(population)
+
+ record = stats.compile(population) if stats is not None else {}
+ logbook.record(gen=0, nevals=len(invalid_ind), **record)
+ if verbose:
+ print(logbook.stream)
+
+ # Begin the generational process
+ for gen in range(1, ngen + 1):
+ if budget_scheduler is not None:
+ simulation_budget = budget_scheduler(ngen, population)
+ # Vary the population
+ offspring = algorithms.varOr(population, toolbox, lambda_, cxpb, mutpb)
+
+ # Evaluate the individuals with an invalid fitness
+ invalid_ind = [ind for ind in offspring if not ind.fitness.valid]
+ fitnesses = toolbox.map(toolbox.evaluate, invalid_ind)
+ for ind, fit in zip(invalid_ind, fitnesses):
+ ind.fitness.reset()
+ ind.fitness.add_reward(fit[0])
+ ind.fitness.values = ind.fitness.calc_fitness(simulation_budget), *fit[1:]
+
+ for ind in population:
+ ind.fitness.update_offset()
+
+ popoff = population+offspring
+ if not select:
+ popoff = HeapWithKey(popoff, lambda x: -x.fitness.values[0])
+ get_individual = lambda _: [popoff.pop() for _ in range(parallel_update)]
+
+ tmp = 0
+ while(tmp < simulation_budget):
+ inds = get_individual(popoff)
+ fitnesses = toolbox.map(toolbox.evaluate, inds)
+ for ind, fit in zip(inds, fitnesses):
+ ind.fitness.add_reward(fit[0])
+ ind.fitness.values = ind.fitness.calc_fitness(simulation_budget), *fit[1:]
+ if not select:
+ popoff.push(ind)
+ tmp+=1
+
+ # Update the hall of fame with the generated individuals
+ if halloffame is not None:
+ halloffame.update(offspring)
+
+ # Select the next generation population
+ population[:] = toolbox.select(population + offspring, mu)
+
+ # Update the statistics with the new population
+ record = stats.compile(population) if stats is not None else {}
+ logbook.record(gen=gen, nevals=len(invalid_ind), **record)
+ if verbose:
+ print(logbook.stream)
+
+ return population, logbook
+
+# "Deapified" version of :
+# Regularized Evolution for Image Classifier Architecture Search ; https://ojs.aaai.org/index.php/AAAI/article/view/4405
+# based code from : https://github.com/google-research/google-research/tree/master/evolution/regularized_evolution_algorithm
+def regularized_evolution(population, toolbox, mu, lambda_, cxpb, mutpb, cycles, stats=None, halloffame=None, verbose=__debug__):
+ """Algorithm for regularized evolution (i.e. aging evolution).
+
+ Follows "Algorithm 1" in Real et al. "Regularized Evolution for Image
+ Classifier Architecture Search".
+
+ Args:
+ cycles: the number of cycles the algorithm should run for.
+
+ Returns:
+ history: a list of `Model` instances, representing all the models computed
+ during the evolution experiment.
+ """
+ assert mu <= len(population)
+ if isinstance(deque, population):
+ remove = lambda pop: pop.popleft()
+ else:
+ remove = lambda pop: pop.pop(0)
+
+ logbook = tools.Logbook()
+ logbook.header = ['gen', 'nevals'] + (stats.fields if stats else [])
+
+ invalid_ind = [ind for ind in population if not ind.fitness.valid]
+ fitnesses = toolbox.map(toolbox.evaluate, invalid_ind)
+ for ind, fit in zip(invalid_ind, fitnesses):
+ ind.fitness.values = fit
+
+ record = stats.compile(population) if stats is not None else {}
+ logbook.record(gen=0, nevals=len(invalid_ind), **record)
+ if verbose:
+ print(logbook.stream)
+
+ history = [] # Not used by the algorithm, only used to report results.
+
+ # Carry out evolution in cycles.
+ while len(history) < cycles:
+ parents = toolbox.select(population, k=mu)
+
+ # Create offspring and store it.
+ offspring = algorithms.varOr(parents, lambda_, cxpb, mutpb)
+
+ invalid_ind = [ind for ind in offspring if not ind.fitness.valid]
+ fitnesses = toolbox.map(toolbox.evaluate, invalid_ind)
+ for ind, fit in zip(invalid_ind, fitnesses):
+ ind.fitness.values = fit
+
+ population.extend(offspring)
+ history.extend(offspring)
+
+ # Withdrawal of oldest individuals
+ for _ in range(len(invalid_ind)):
+ remove(population)
+
+ record = stats.compile(population) if stats is not None else {}
+ logbook.record(gen=len(history), nevals=len(invalid_ind), **record)
+ if verbose:
+ print(logbook.stream)
+
+ return history, logbook
+
+
+#objectif at zero
+def qdLambda(init_batch, toolbox, container, batch_size, ngen, lambda_, cxpb = 0.0, mutpb = 1.0, stats = None, halloffame = None, verbose = False, show_warnings = False, start_time = None, iteration_callback = None):
+ """The simplest QD algorithm using DEAP.
+ :param init_batch: Sequence of individuals used as initial batch.
+ :param toolbox: A :class:`~deap.base.Toolbox` that contains the evolution operators.
+ :param batch_size: The number of individuals in a batch.
+ :param niter: The number of iterations.
+ :param stats: A :class:`~deap.tools.Statistics` object that is updated inplace, optional.
+ :param halloffame: A :class:`~deap.tools.HallOfFame` object that will
+ contain the best individuals, optional.
+ :param verbose: Whether or not to log the statistics.
+ :param show_warnings: Whether or not to show warnings and errors. Useful to check if some individuals were out-of-bounds.
+ :param start_time: Starting time of the illumination process, or None to take the current time.
+ :param iteration_callback: Optional callback funtion called when a new batch is generated. The callback function parameters are (iteration, batch, container, logbook).
+ :returns: The final batch
+ :returns: A class:`~deap.tools.Logbook` with the statistics of the
+ evolution
+ """
+ if start_time is None:
+ start_time = timer()
+ logbook = tools.Logbook()
+ logbook.header = ["iteration", "containerSize", "evals", "nbUpdated"] + (stats.fields if stats else []) + ["elapsed"]
+
+ if len(init_batch) == 0:
+ raise ValueError("``init_batch`` must not be empty.")
+
+ # Evaluate the individuals with an invalid fitness
+ invalid_ind = [ind for ind in init_batch if not ind.fitness.valid]
+ fitnesses = toolbox.map(toolbox.evaluate, invalid_ind)
+ for ind, fit in zip(invalid_ind, fitnesses):
+ ind.fitness.values = fit[0],
+ ind.features = fit[1:]
+
+ if len(invalid_ind) == 0:
+ raise ValueError("No valid individual found !")
+
+ # Update halloffame
+ if halloffame is not None:
+ halloffame.update(init_batch)
+
+ # Store batch in container
+ nb_updated = container.update(init_batch, issue_warning=show_warnings)
+ if nb_updated == 0:
+ raise ValueError("No individual could be added to the container !")
+
+ # Compile stats and update logs
+ record = stats.compile(container) if stats else {}
+ logbook.record(iteration=0, containerSize=container.size_str(), evals=len(invalid_ind), nbUpdated=nb_updated, elapsed=timer()-start_time, **record)
+ if verbose:
+ print(logbook.stream)
+ # Call callback function
+ if iteration_callback is not None:
+ iteration_callback(0, init_batch, container, logbook)
+
+ # Begin the generational process
+ for i in range(1, ngen + 1):
+ start_time = timer()
+ # Select the next batch individuals
+ batch = toolbox.select(container, batch_size)
+
+ ## Vary the pool of individuals
+ offspring = algorithms.varOr(batch, toolbox, lambda_, cxpb=cxpb, mutpb=mutpb)
+
+ # Evaluate the individuals with an invalid fitness
+ invalid_ind = [ind for ind in offspring if not ind.fitness.valid]
+ fitnesses = toolbox.map(toolbox.evaluate, invalid_ind)
+ for ind, fit in zip(invalid_ind, fitnesses):
+ ind.fitness.values = fit[0],
+ ind.features = fit[1:]
+
+ # Replace the current population by the offspring
+ nb_updated = container.update(offspring, issue_warning=show_warnings)
+
+ # Update the hall of fame with the generated individuals
+ if halloffame is not None:
+ halloffame.update(container)
+
+ # Append the current generation statistics to the logbook
+ record = stats.compile(container) if stats else {}
+ logbook.record(iteration=i, containerSize=container.size_str(), evals=len(invalid_ind), nbUpdated=nb_updated, elapsed=timer()-start_time, **record)
+ if verbose:
+ print(logbook.stream)
+ # Call callback function
+ if iteration_callback is not None:
+ iteration_callback(i, batch, container, logbook)
+
+ return batch, logbook
+
diff --git a/GPRL/factory.py b/GPRL/factory.py
new file mode 100644
index 0000000000000000000000000000000000000000..515cb6ed4a0cbb7502fcbc181bd563ea618af485
--- /dev/null
+++ b/GPRL/factory.py
@@ -0,0 +1,21 @@
+from abc import ABC, abstractmethod
+
+class EvolveFactory(ABC):
+ def __init__(self, conf):
+ self.conf = conf
+
+ @abstractmethod
+ def init_global_var(self):
+ pass
+
+ @abstractmethod
+ def make_toolbox(self):
+ pass
+
+ @abstractmethod
+ def get_stats(self):
+ pass
+
+ @ abstractmethod
+ def close(self):
+ pass
diff --git a/GPRL/genetic_programming/__init__.py b/GPRL/genetic_programming/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/GPRL/genetic_programming/linearGP.py b/GPRL/genetic_programming/linearGP.py
new file mode 100644
index 0000000000000000000000000000000000000000..2c831fb452c49db74b95a5791a979b2b8f52363c
--- /dev/null
+++ b/GPRL/genetic_programming/linearGP.py
@@ -0,0 +1,584 @@
+import random
+from functools import partial
+import copy
+
+from abc import ABC, abstractmethod
+
+import numpy as np
+
+from collections import namedtuple
+
+#/!\ warning authorized dst in effective mutINstr and mutInsert (range(regCalcSize))
+
+NUM_OPS = 12
+
+opcode_complexity = np.array([1, 1, 1, 2, 2, 4, 4, 4, 3, 4, 4, 4])
+
+class Interpreter(ABC):
+
+ @abstractmethod
+ def opcode(code, x1, x2):
+ pass
+
+ @abstractmethod
+ def to_string(opcode):
+ pass
+
+
+class BasicInterpreter:
+ data_type="float"
+ def __init__(self, mask=np.ones(NUM_OPS, dtype=bool)):
+ self.num_ops = NUM_OPS
+ self.arity = np.array([2]*6 + [1]*3 + [2]*3)
+ self.branch = np.zeros(self.num_ops, dtype=bool)
+ self.branch[10:] = True
+ self.masked_branch = self.branch[mask].copy()
+ self.ops = np.arange(0, self.num_ops)[mask]
+
+ def opcode(self, code, x1, x2):
+ c_undef = 1e7
+ if code==0:
+ return np.add(x1, x2)
+ elif code==1:
+ return np.subtract(x1, x2)
+ elif code==2:
+ return np.multiply(x1, x2)
+ elif code==3:
+ return np.float_power(np.abs(x1),x2, where=np.logical_and(np.abs(x2) <= 10, np.logical_and(np.abs(x1) > 0.001, np.abs(x1) < 1000)), out=np.full_like(x1, c_undef))
+ #return np.where(np.logical_and(np.abs(x2) <= 10, np.abs(x1) != 0), np.float_power(np.abs(x1), x2), x1 + c_undef)
+ elif code==4:
+ return np.divide(x1, x2, where=np.abs(x2) > 0.001, out=np.full_like(x1, c_undef))
+ elif code==5:
+ return np.fmod(x1, x2, where=np.abs(x2) > 0.001, out=np.zeros_like(x1))
+ elif code==6:
+ return np.sin(x1)
+ elif code==7:
+ return np.exp(x1, where=np.abs(x1)<32, out=np.full_like(x1, c_undef))
+ #return np.where(np.abs(x1)<32, np.exp(x1), x1 + c_undef)
+ elif code==8:
+ return np.log(np.abs(x1), where=np.abs(x1) > 0.00001, out=np.full_like(x1, c_undef))
+ #return np.where(np.abs(x1) > 0.001, np.log(x1), x1 + c_undef)
+ elif code==9:
+ return np.where(x1 > x2, -x1, x1)
+ elif code==10:
+ return x1>x2
+ elif code==11:
+ return x1<x2
+ raise ValueError("Code not found")
+
+ def toString(self, x):
+ if x==0:
+ return "+"
+ elif x==1:
+ return "-"
+ elif x==2:
+ return "*"
+ elif x==3:
+ return "^"
+ elif x==4:
+ return "/"
+ elif x==5:
+ return "%"
+ elif x==6:
+ return "sin"
+ elif x==7:
+ return "exp"
+ elif x==8:
+ return "log"
+ elif x==9:
+ return "if neg"
+ elif x==10:
+ return ">"
+ elif x==11:
+ return "<"
+
+class id(object):
+ id = 0
+ def __call__(self):
+ self.id +=1
+ return self.id
+
+Instruction = namedtuple('Instruction', ['opcode', 'dst', 'inpt1', 'inpt2'])
+
+class Program(list):
+ instruction_type = [('opcode', 'u8'), ('dst', 'u8'), ('inpt1','u8'),('inpt2','u8')]
+ Instruction = Instruction
+
+ ID = id()
+
+ def __init__(self, content=[], regCalcSize=None, regInputSize=None, regConstSize=None, regConst=None, interpreter=BasicInterpreter()):
+ super(Program, self).__init__(content)
+ self.regCalcSize = regCalcSize
+ self.regInputSize = regInputSize
+ self.regConstSize = regConstSize
+
+ self.regConst = regConst
+
+ self.interpreter = interpreter
+
+ self.id = self.ID()
+
+ def to_effective(self, outputIdxs, stopAt=0):
+ effective = []
+ idxs = []
+ R_eff = set(outputIdxs)
+ k = len(self)-1
+ while k >= stopAt:
+ instr = self[k]
+ if instr.dst in R_eff and not self.interpreter.branch[instr.opcode]:
+ effective.insert(0, instr)
+ idxs.append(k)
+ if k>0 and not self.interpreter.branch[self[k-1].opcode]: R_eff.remove(instr.dst)
+ arity = self.interpreter.arity[instr.opcode]
+ R_eff.add(instr.inpt1)
+ if arity == 2:
+ R_eff.add(instr.inpt2)
+ i = k-1
+ while i>=0 and self.interpreter.branch[self[i].opcode]:
+ R_eff.add(self[i].inpt1)
+ R_eff.add(self[i].inpt2)
+ effective.insert(0, self[i])
+ idxs.append(i)
+ i-=1
+ k = i+1
+ k-=1
+ return Program(effective, self.regCalcSize, self.regInputSize, self.regConstSize, self.regConst, interpreter=self.interpreter), R_eff, idxs
+
+ def get_used_regConstIdxs(self):
+ regConstIdx = set()
+ for instr in self:
+ if instr.inpt1 >= self.regCalcSize+self.regInputSize:
+ regConstIdx.add(instr.inpt1)
+ elif self.interpreter.arity[instr.opcode] == 2 and instr.inpt2 >= self.regCalcSize+self.regInputSize:
+ regConstIdx.add(instr.inpt2)
+ return regConstIdx
+
+ def get_constIdxs(self):
+ constIdxs = []
+ for idx, instr in enumerate(self):
+ if instr.inpt1 >= self.regCalcSize+self.regInputSize:
+ constIdxs.append((idx, instr.inpt1))
+ elif self.interpreter.arity[instr.opcode] == 2 and instr.inpt2 >= self.regCalcSize+self.regInputSize:
+ constIdxs.append((idx, instr.inpt2))
+ return constIdxs
+
+ def to_numpy(self):
+ return np.array(self, dtype=self.instruction_type)
+
+ def __str__(self):
+ string = " op dst inpt1 inpt2\n"
+ for line, instr in enumerate(self):
+ string+= f"{line} {self.interpreter.toString(instr.opcode)} {instr.dst} {instr.inpt1} {instr.inpt2}\n"
+ return string
+
+ def init_register(self, random=lambda nb:np.arange(1, nb+1, dtype="float")):
+ register_length = self.regCalcSize + self.regConstSize + self.regInputSize
+ register = np.zeros(register_length, dtype="float")
+ register[self.regCalcSize:] = 100.0
+ register[self.regCalcSize:self.regCalcSize+self.regInputSize] = np.random.uniform(-1,1, self.regInputSize)
+ # initialize constant
+ j = self.regCalcSize + self.regInputSize
+ if self.regConst is not None:
+ register[j:] = self.regConst.copy()
+ else:
+ register[j:] = random(self.regConstSize)
+ return register
+
+ @classmethod
+ def randomProgram(cls, regCalcSize, regInputSize, regConstSize, length, pConst, pBranch, random=lambda nb:np.arange(1, nb+1, dtype="float"), ops=np.array([True, True, True, False, True, False, False, False, False, False, True, True])):
+ interpreter = BasicInterpreter(mask=ops)
+ prgm = [cls.randomInstruction(regCalcSize, regInputSize, regConstSize, pConst, pBranch, interpreter) for _
+ in range(length - 1)]
+ prgm.append(cls.randomInstruction(regCalcSize, regInputSize, regConstSize, pConst, 0.0, interpreter))
+ return cls(prgm, regCalcSize, regInputSize, regConstSize, random(regConstSize), interpreter)
+
+ @classmethod
+ def randomInstruction(cls, numberOfVariable, numberOfInput, numberOfConstant, pConst, pBranch, interpreter):
+ if np.random.random() >= pConst: # reg1 will be a variable or input
+ r1 = np.random.randint(numberOfVariable + numberOfInput)
+ reg1Index = r1
+ if np.random.random() >= pConst: # reg2 will be a variable or input
+ r2 = np.random.randint(numberOfVariable + numberOfInput)
+ reg2Index = r2
+ else: # reg2 will be a constant
+ r2 = np.random.randint(numberOfConstant)
+ reg2Index = numberOfVariable + numberOfInput + r2
+ else: # reg1 will be a constant and reg2 will be a variable or input
+ r1 = np.random.randint(numberOfConstant)
+ reg1Index = numberOfVariable + numberOfInput + r1
+ r2 = np.random.randint(numberOfVariable + numberOfInput)
+ reg2Index = r2
+ if np.random.random() < pBranch:
+ branch_ops = np.random.choice(interpreter.ops[interpreter.masked_branch])
+ return cls.Instruction(branch_ops, 255, reg1Index, reg2Index)
+ else:
+ operIndex = np.random.choice(interpreter.ops[~interpreter.masked_branch])
+ # since zero is return register in calculation, make sure there are enough zeros by increasing its chance
+ #pZero = 0.0004 * numberOfInput
+ #returnRegIndex = 0 if pZero > np.random.random_sample() else np.random.randint(numberOfVariable)
+ returnRegIndex = np.random.randint(numberOfVariable)
+ return cls.Instruction(operIndex, returnRegIndex, reg1Index, reg2Index)
+
+ @staticmethod
+ #MicroMutation
+ def mutInstr(prog, pReg, pOp, pConst, pBranch, sigma=1.0, effective=None):
+ if not prog: return prog
+
+ if effective:#revoir
+ eff, _, idxs =prog.to_effective(effective)
+ idx = random.choice(idxs) if idxs else random.randint(0, len(prog)-1)
+ else:
+ idx = random.randint(0, len(prog)-1)
+
+ opcode, dst, inpt1, inpt2 = prog[idx]
+
+ mut = random.choices(range(0,3), weights=[pReg, pOp, pConst])[0]
+
+ if mut == 0:
+ if random.random() < 0.5 and not prog.interpreter.branch[prog[idx].opcode]:
+ if effective:
+ authorized_dst = set(range(prog.regCalcSize))
+ _, R_eff, _ = prog.to_effective(effective, stopAt=idx)
+ R_eff.intersection_update(authorized_dst)
+ if bool(R_eff):
+ dst = np.random.choice(tuple(R_eff))
+ else:
+ dst = np.random.randint(prog.regCalcSize)
+ else:
+ dst = np.random.randint(prog.regCalcSize)
+ else:
+ if random.random() >= pConst:
+ if prog.interpreter.arity[prog[idx].opcode]==1 or random.random() < 0.5:
+ inpt1 = np.random.randint(prog.regCalcSize + prog.regInputSize)
+ else:
+ inpt2 = np.random.randint(prog.regCalcSize + prog.regInputSize)
+ else:
+ r = prog.regCalcSize + prog.regInputSize
+ if prog.interpreter.arity[prog[idx].opcode]==1 or random.random() < 0.5:
+ inpt1 = r + np.random.randint(prog.regConstSize)
+ else:
+ inpt2 = r + np.random.randint(prog.regConstSize)
+ elif mut == 1:
+ if random.random() < pBranch:# attention si ops interpreter aucune branch
+ opcode = np.random.choice(prog.interpreter.ops[prog.interpreter.masked_branch])
+ else:
+ if prog.interpreter.branch[opcode] and dst>prog.regCalcSize: dst = np.random.randint(prog.regCalcSize)
+ opcode = np.random.choice(prog.interpreter.ops[~prog.interpreter.masked_branch])
+ elif mut == 2:
+ if effective:
+ constIdxs = eff.get_constIdxs()
+ else:
+ constIdxs = prog.get_constIdxs()
+ if constIdxs:
+ _, inpt = random.choice(constIdxs)
+ prog.regConst[inpt-(prog.regCalcSize+prog.regInputSize)] += np.random.normal(loc=0.0, scale=sigma)
+
+ if mut!=2:
+ prog[idx] = prog.Instruction(opcode, dst, inpt1, inpt2)
+
+ return prog
+
+ @staticmethod
+ def execute(program, inputs, register, outputIdxs):
+ if inputs.ndim == 1:
+ assert inputs.size == program.regInputSize
+ register[program.regCalcSize:program.regCalcSize+inputs.shape[0]] = inputs.copy()
+ output = Program._execute(program, register)
+ return output[outputIdxs]
+ elif inputs.ndim == 2:
+ assert inputs.shape[1] == program.regInputSize
+ ndim_register = np.zeros((register.shape[0], inputs.shape[0]))
+ for k in range(inputs.shape[0]):
+ ndim_register[:program.regCalcSize, k] = register[:program.regCalcSize].copy()
+ ndim_register[program.regCalcSize:program.regCalcSize+inputs.shape[1], k] = inputs[k].copy()
+ ndim_register[program.regCalcSize+inputs.shape[1]:, k] = register[program.regCalcSize+inputs.shape[1]:].copy()
+ output = Program._execute(program, ndim_register)
+ return output[outputIdxs,:].T
+ raise ValueError("Unsuported inputs dimension")
+
+ @staticmethod
+ def _execute(program, register):
+ check_float_range = lambda x: np.clip(x , -np.sqrt(np.finfo(program.interpreter.data_type).max), np.sqrt(np.finfo(program.interpreter.data_type).max))
+ branch_flag = False
+ i = 0
+ while i < len(program):
+ instr = program[i]
+ if program.interpreter.branch[instr.opcode]: # branch Instruction
+ tmp = program.interpreter.opcode(instr.opcode, register[instr.inpt1], register[instr.inpt2])
+
+ if branch_flag:# consecutive if
+ np.logical_and(tmp, mask)
+ else:
+ mask = tmp
+
+ if ~mask.all():
+ branch_flag = False
+ while i < len(program) - 1 and program.interpreter.branch[program[i + 1].opcode]: # if next is still a branch
+ i += 1
+ i += 2
+ else: # if branch true, execute next instruction
+ branch_flag = True
+ i += 1
+ else: # not a branch Instruction
+ if branch_flag:
+ register[instr.dst] = np.where(mask, check_float_range(program.interpreter.opcode(instr.opcode, register[instr.inpt1], register[instr.inpt2])), register[instr.dst])
+
+ branch_flag = False
+ else:
+ register[instr.dst] = check_float_range(program.interpreter.opcode(instr.opcode, register[instr.inpt1], register[instr.inpt2]))
+ i += 1
+ return register
+
+def graph(prog, outputIdxs, debug=False, terminals_name=None):
+ prgm, _, _ = prog.to_effective(outputIdxs)
+ start = prog.regCalcSize + prog.regInputSize + prog.regConstSize
+ nodes = []
+ edges = []
+ branch_edges = []
+ labels = {}
+
+ nodes_dst = {}
+ terminal_nodes = set()
+
+ branch_flag = False
+ for k, instr in enumerate(prgm):
+ nodes.append(k+start)
+ if debug:
+ labels[k+start] = str(k)+ "\n" + prog.interpreter.toString(instr.opcode)
+ else:
+ labels[k+start] = prog.interpreter.toString(instr.opcode)
+
+ arity = prog.interpreter.arity[instr.opcode]
+ if instr.inpt1 in nodes_dst.keys():
+ edges.append((nodes_dst[instr.inpt1], k+start))
+ else:
+ terminal_nodes.add(instr.inpt1)
+ edges.append((instr.inpt1, k+start))
+
+ if arity==2:
+ if instr.inpt2 in nodes_dst.keys():
+ edges.append((nodes_dst[instr.inpt2], k+start))
+ else:
+ terminal_nodes.add(instr.inpt2)
+ edges.append((instr.inpt2, k+start))
+
+
+ if not prog.interpreter.branch[instr.opcode]:
+ if branch_flag and instr.dst in nodes_dst.keys():
+ branch_edges.append((nodes_dst[instr.dst], k+start))
+ nodes_dst[instr.dst] = k+start
+ branch_flag = False
+ elif k<len(prgm)-1:
+ branch_flag = True
+ edges.append((k+start, k+1+start))
+
+ for k in outputIdxs:
+ if k in nodes_dst.keys():
+ labels[nodes_dst[k]] += '\n Out'+str(k)
+
+ for k in terminal_nodes:
+ nodes.append(k)
+ if terminals_name:
+ labels[k] = terminals_name[k]
+ elif k < prog.regCalcSize:
+ labels[k] = "Calc" + str(k)
+ elif k >= prog.regCalcSize and k < prog.regCalcSize+prog.regInputSize:
+ labels[k] = "ARG" + str(k-prog.regCalcSize)
+ else:
+ labels[k] = 'Const' + str(k-prog.regCalcSize-prog.regInputSize)
+
+ return nodes, edges, labels, branch_edges
+
+
+def edit_distance(p1, p2):
+ def to_string(program):
+ repr = ""
+ for instr in program:
+ repr+=str(instr.opcode)+str(instr.dst)+str(instr.inpt1)
+ if program.interpreter.arity[instr.opcode] == 2:
+ repr+=str(instr.inpt2)
+ return repr
+ s1, s2 = to_string(p1), to_string(p2)
+ if len(s1) > len(s2):
+ s1, s2 = s2, s1
+
+ distances = range(len(s1) + 1)
+ for i2, c2 in enumerate(s2):
+ distances_ = [i2+1]
+ for i1, c1 in enumerate(s1):
+ if c1 == c2:
+ distances_.append(distances[i1])
+ else:
+ distances_.append(1 + min((distances[i1], distances[i1 + 1], distances_[-1])))
+ distances = distances_
+ return distances[-1]
+
+def sementic_introns(prog, block_size=None):
+ import copy
+ if not block_size:
+ block_size = len(prog)
+ for block in range(1, block_size):
+ for k in range(len(prog)-block):
+ prgm = copy.deepcopy(prog)
+ del prgm[k:k+block]
+ yield prgm
+
+def initProgam(pcls, regCalcSize, regInputSize, regConstSize, pConst, pBranch, min_, max_, rnd=None, ops=None):
+ kwargs = dict()
+ if rnd is not None:
+ kwargs['random'] = rnd
+ if ops is not None:
+ kwargs['ops'] = ops
+ prgm = Program.randomProgram(regCalcSize, regInputSize, regConstSize, random.randint(min_, max_), pConst, pBranch, **kwargs)
+ return pcls(prgm, prgm.regCalcSize, prgm.regInputSize, prgm.regConstSize, prgm.regConst, prgm.interpreter)
+
+def semantic_introns(evaluate, programm, max_block_size=None, lower_bound=None, test=lambda x,y: x<=y):
+ if lower_bound is None:
+ base_score = evaluate(programm)
+ else:
+ base_score = lower_bound
+
+ if max_block_size is None:
+ max_block_size = len(programm)
+ block_size = 1
+
+ while block_size<max_block_size and block_size<=len(programm):
+ cursor = 0
+ while cursor<len(programm)-block_size:
+ tmp = copy.deepcopy(programm)
+ del tmp[cursor:cursor+block_size]
+ score = evaluate(tmp)
+ if test(base_score, score):
+ #base_score = score
+ programm = tmp
+ else:
+ cursor+=1
+ block_size+=1
+
+ return programm
+
+#Selection
+from deap import tools
+from operator import attrgetter
+from copy import deepcopy
+def selDoubleTournament(individuals, k, fitness_size, diversity_size, fitness_first=True, fit_attr="fitness", effective=None):
+ assert (1 <= diversity_size <= 2), "Parsimony tournament size has to be in the range [1, 2]."
+
+ def _editDistTournament(individuals, k, select):
+ chosen = []
+ for i in range(k):
+ # Select two individuals from the population
+ # The first individual has to be the shortest
+ prob = diversity_size / 2.
+ inds = select(individuals, k=3)
+ if effective:
+ tmp = inds
+ inds = deepcopy([ind.to_effective(effective)[0] for ind in inds])
+
+ edist12 = edit_distance(inds[0], inds[1])/(max(len(inds[0]), len(inds[1]), 1))
+ edist13 = edit_distance(inds[0], inds[2])/(max(len(inds[0]), len(inds[2]), 1))
+ edist23 = edit_distance(inds[1], inds[2])/(max(len(inds[1]), len(inds[2]), 1))
+
+ edist = [
+ edist12 + edist13,
+ edist12 + edist23,
+ edist13+ edist23
+ ]
+
+ scores = np.argsort(edist)[::-1]
+ if edist[scores[0]]==edist[scores[1]]:
+ prob=0.5
+
+ if effective:
+ inds = tmp
+ chosen.append(inds[scores[0]] if random.random() < prob else inds[scores[random.randint(1,2)]])
+
+ return chosen
+ def _fitTournament(individuals, k, select):
+ chosen = []
+ for i in range(k):
+ aspirants = select(individuals, k=fitness_size)
+ chosen.append(max(aspirants, key=attrgetter(fit_attr)))
+ return chosen
+
+ if fitness_first:
+ tfit = partial(_fitTournament, select=tools.selRandom)
+ return _editDistTournament(individuals, k, tfit)
+ else:
+ tsize = partial(_editDistTournament, select=tools.selRandom)
+ return _fitTournament(individuals, k, tsize)
+
+#CrossOver
+def cxLinear(ind1, ind2, l_min, l_max, l_smax, dc_max, ds_max):
+ if len(ind1)>len(ind2):
+ ind1, ind2 = ind2, ind1
+ if len(ind1)<2: return ind1, ind2
+ i1 = random.randint(0, len(ind1)-2)
+ i2 = random.randint(0, min(dc_max, len(ind1)-2))
+ l1 = random.randint(1, min(len(ind1)-1-i1, l_smax))
+ l2 = random.randint(max(1, min(l1-ds_max, len(ind2)-1-i2)), min(len(ind2)-1-i2, l_smax, l1+ds_max))
+
+ if l1 > l2:
+ l2 = l1
+ if i2 + l2 >= len(ind2): i2 = len(ind2)-1 - l2
+ if (len(ind2) - (l2-l1) < l_min) or (len(ind1) - (l2-l1) > l_max):
+ l1 = l2 = l1 if random.random() < 0.5 else l2
+ if i1 + l1 > len(ind1):
+ l1 = l2 = len(ind1) - i1 -1
+
+ s1, s2 = ind1[i1:i1+l1], ind2[i2:i2+l2]
+ del ind1[i1:i1+l1]
+ del ind2[i2:i2+l2]
+ ind1[i1:i1], ind2[i2:i2] = s2, s1
+
+ return ind1, ind2
+
+#MacroMutation
+def mutInsert(prog, pConst, pBranch, effective=None):
+ idx = random.randint(0, len(prog))
+ instr = prog.randomInstruction(prog.regCalcSize, prog.regInputSize, prog.regConstSize, pConst, pBranch, prog.interpreter)
+ if effective:
+ authorized_dst = set(range(prog.regCalcSize))
+ _, R_eff, _ = prog.to_effective(effective, stopAt=idx)
+ R_eff.intersection_update(authorized_dst)
+ if bool(R_eff):
+ instr = prog.Instruction(instr.opcode, random.choice(tuple(R_eff)), instr.inpt1, instr.inpt2)
+ prog.insert(idx, instr)
+ return prog
+
+def mutDelete(prog, effective=None):
+ if len(prog)<2: return prog
+ if effective:
+ idxs=effective
+ if not idxs: return prog
+ idx = random.choice(idxs)
+ else:
+ idx = random.randint(0, len(prog)-1)
+ del prog[idx]
+ return prog
+
+def mutSwap(prog, effective=None):
+ if len(prog)<2: return prog
+ if effective:
+ idxs=effective
+ if len(idxs)>2 and random.random()<0.5:
+ i1, i2 = random.sample(idxs, 2)
+ elif idxs:
+ i1 = random.choice(idxs)
+ i2 = random.randint(0, len(prog)-1)
+ else:
+ return prog
+ else:
+ i1 = random.randint(0, len(prog)-1)
+ i2 = random.randint(0, len(prog)-1)
+ prog[i1], prog[i2] = prog[i2], prog[i1]
+ return prog
+
+if __name__ == "__main__":
+ test = Program.randomProgram(8, 2, 11, 20, 0.3, 0.5)
+ eff, _, _ = test.to_effective([0])
+ print(eff)
+ print(Program.mutInstr(eff, 0.5, 0.5, 0.0, 0.1))
+ #Program.interpreter.opcode(4, np.array(10.0), np.array(11.0))
+ register = eff.init_register()
+ #print(Program.execute(eff, np.array([[0.5, 1.0], [0.5, 1.0]]), register, np.array([0])))
\ No newline at end of file
diff --git a/GPRL/genetic_programming/team.py b/GPRL/genetic_programming/team.py
new file mode 100644
index 0000000000000000000000000000000000000000..48739930d4f0d5ec49874e3431304ef7c13ac31c
--- /dev/null
+++ b/GPRL/genetic_programming/team.py
@@ -0,0 +1,92 @@
+import random
+import numpy as np
+from sklearn.linear_model import LinearRegression
+
+class MGGP(list):
+ def __init__(self, content):
+ list.__init__(self, content)
+ self.linear = None
+
+ def fit(self, func, x, target):
+ features = func(*x).T
+ self.linear = LinearRegression()
+ self.linear = self.linear.fit(features, y=target)
+
+ def predict(self, func, x):
+ return self.linear.predict(func(*x).T)
+
+def mutate(team, unit_mut):
+ idx = random.randint(0, len(team)-1)
+ team[idx] = unit_mut(team[idx])
+ return team,
+
+def fixed_mate(team1, team2, unit_cx):
+ assert len(team1)==len(team2)
+ idx = random.randint(0, len(team1)-1)
+ team1[idx], team2[idx] = unit_cx(team1[idx], team2[idx])
+ return team1, team2
+
+def cx_low_level(team1, team2, unit_cx):
+ idx1 = random.randint(0, len(team1)-1)
+ idx2 = random.randint(0, len(team2)-1)
+ team1[idx1], team2[idx2] = unit_cx(team1[idx1], team2[idx2])
+ return team1, team2
+
+def cx_hight_level(team1, team2, cxprb):
+ add_team1 = []
+ k = 0
+ while k<len(team2):
+ if random.random() < cxprb:
+ add_team1.append(team2.pop(k))
+ k-=1
+ k+=1
+ k=0
+ team2
+ while k<len(team1):
+ if random.random() < cxprb:
+ team2.append(team1.pop(k))
+ k-=1
+ k+=1
+ team1.extend(add_team1)
+ if not team1:
+ team1.append(team2[-1])
+ elif not team2:
+ team2.append(team1[-1])
+ return team1, team2
+
+def mutation_del(team):
+ team.pop(random.randint(0, len(team)-1))
+ return team
+
+def init_team(size, unit_init):
+ team = [unit_init() for _ in range(size)]
+ return team
+
+def init_randomSize_team(max_size, unit_init):
+ size = random.randint(1, max_size-1)
+ return init_team(size, unit_init)
+
+def team_complexity(team, unit_complexity):
+ return sum(map(unit_complexity, team))
+
+def team_size_constraint(team, size):
+ while len(team)>= size:
+ mutation_del(team)
+ return team
+
+def team_compile(team, unit_compile):
+ funcs = list(map(unit_compile, team))
+ def func(*args):
+ #ret = np.zeros((len(funcs), len(args[0])))
+ #for k, f in enumerate(funcs):
+ # res = f(*args)
+ # if isinstance(res, float) or res.size == 1:
+ # ret[k, : ] = res
+ # else:
+ # ret[k,:] = res[:]
+ #return ret
+ return [f(*args) for f in funcs]
+ return func
+
+def height(team, op):
+ return max(map(op, team))
\ No newline at end of file
diff --git a/GPRL/policy.py b/GPRL/policy.py
new file mode 100644
index 0000000000000000000000000000000000000000..8987864087acfca36a28f650debbf5d1d8fbf014
--- /dev/null
+++ b/GPRL/policy.py
@@ -0,0 +1,20 @@
+import json
+
+class Policy(object):
+ def __init__(self, program) -> None:
+ super().__init__()
+ self.policy_type = type(program)
+ self.repr = str(program)
+ #args
+
+ def __call__(self, inputs):
+ pass
+
+ def __str__(self):
+ return self.repr
+
+ def save_policy(self):
+ pass
+
+ def load_policy(self):
+ pass
\ No newline at end of file
diff --git a/GPRL/utils/FEC.py b/GPRL/utils/FEC.py
new file mode 100644
index 0000000000000000000000000000000000000000..4a0fe66ebd561c9c12e7d816d0b71afba8bd7e7d
--- /dev/null
+++ b/GPRL/utils/FEC.py
@@ -0,0 +1,64 @@
+from collections import OrderedDict
+from functools import reduce
+import numpy as np
+
+#code from : https://www.geeksforgeeks.org/lru-cache-in-python-using-ordereddict/
+class LRUCache:
+ def __init__(self, capacity: int):
+ self.cache = OrderedDict()
+ self.capacity = capacity
+
+ def get(self, key):
+ value = self.cache.get(key, None)
+ if value:
+ self.cache.move_to_end(key)
+ return self.cache[key]
+
+ def put(self, key, value):
+ self.cache[key] = value
+ self.cache.move_to_end(key)
+ if len(self.cache) > self.capacity:
+ self.cache.popitem(last = False)
+
+class FEC(object):#Functionnal Equuivalence Checking
+ def __init__(self, data: np.ndarray, cache_size: int):
+ self.data = data
+ self.cache = LRUCache(cache_size)
+
+ def _fingerprint(self, func):
+ return hash(func(self.data).data.tobytes())
+
+ def add_to_cache(self, func, fitness, fingerprint=None):
+ if fingerprint is None:
+ fingerprint = self._fingerprint(func)
+ self.cache.put(fingerprint, fitness)
+
+ def fec(self, func, fingerprint=None):
+ if fingerprint is None:
+ fingerprint = self._fingerprint(func)
+ fitness = self.cache.get(fingerprint)
+ return fitness
+
+ @staticmethod
+ def _cartesian_product_transpose(arrays):
+ broadcastable = np.ix_(*arrays)
+ broadcasted = np.broadcast_arrays(*broadcastable)
+ rows, cols = reduce(np.multiply, broadcasted[0].shape), len(broadcasted)
+ dtype = np.find_common_type([a.dtype for a in arrays], [])
+
+ out = np.empty(rows * cols, dtype=dtype)
+ start, end = 0, rows
+ for a in broadcasted:
+ out[start:end] = a.reshape(-1)
+ start, end = end, end + rows
+ return out.reshape(cols, rows).T
+
+ @staticmethod
+ def uniform_domain_dataset(num, *domains):
+ vec = []
+
+ for (min_, max_) in domains:
+ vec.append(np.linspace(min_, max_, num))
+ return FEC._cartesian_product_transpose(vec)
+
+
\ No newline at end of file
diff --git a/GPRL/utils/__init__.py b/GPRL/utils/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/GPRL/utils/gp_utils.py b/GPRL/utils/gp_utils.py
new file mode 100644
index 0000000000000000000000000000000000000000..317a57f5892f403a4d417ca85b913c491e9a20b9
--- /dev/null
+++ b/GPRL/utils/gp_utils.py
@@ -0,0 +1,80 @@
+import numpy as np
+import random
+from deap import gp
+import heapq
+
+operator_complexity = {
+ 'add':1 , 'substract':1, 'const':1, 'multiply':1, 'divide':2, 'abs':2, 'or_':4, 'and_':4, 'gt':4, 'if_then_else':5, 'tanh':4, 'tan':4,
+ 'cos':4, 'sin':4, 'power':3, 'cube':3, 'square':3, 'sqrt':3, 'inv':2, 'log':3, 'exp':3
+}
+
+def similar(i1, i2):
+ return complexity(i1)==complexity(i2)
+
+def complexity(individual):
+ return sum(map(lambda x: operator_complexity.get(x.name, 1), individual))
+
+def div(x1, x2):
+ with np.errstate(divide='ignore', invalid='ignore', over='ignore'):
+ return np.where(np.abs(x2) > 0.001, np.divide(x1, x2), 1000.)
+
+def if_then_else(cond, true, false):
+ return true if cond else false
+
+def classification(*args):
+ return np.argmax(args)
+
+def intervales(x):
+ if x>0.33:
+ return 1
+ elif x<-0.33:
+ return -1
+ return 0
+
+def exp(x):
+ return np.exp(x, where=np.abs(x)<32, out=np.ones_like(x))
+
+def log(x):
+ return np.log(np.abs(x), where=np.abs(x) > 0.00001, out=np.ones_like(x))
+
+def power(x, n):
+ with np.errstate(over='ignore', divide='ignore', invalid='ignore'):
+ if n < 0.0:
+ return np.where(np.logical_and(np.abs(x) < 1e6, np.abs(x)>0.001), np.sign(x) * (np.abs(x)) ** (n), 0.0)
+ return np.where(np.abs(x) < 1e6, np.sign(x) * (np.abs(x)) ** (n), 0.0)
+
+def ephemeral_mut(individual, mode, mu=0, std=1):
+ ephemerals_idx = [index for index, node in enumerate(individual) if isinstance(node, gp.Ephemeral)]
+ if len(ephemerals_idx) > 0:
+ if mode == "one":
+ ephemerals_idx = (random.choice(ephemerals_idx),)
+ for i in ephemerals_idx:
+ new = type(individual[i])()
+ new.value = individual[i].value + random.gauss(mu, 0.1*abs(individual[i].value))
+ individual[i] = new
+ return individual,
+
+def mutate(individual, expr=None, pset=None, mode="one", mu=0, std=1):
+ #mut = gp.mutEphemeral(mut, mode)
+ if random.random() < 0.3:
+ return ephemeral_mut(individual, mode=mode, mu=mu, std=std)
+ else:
+ return gp.mutUniform(individual, expr=expr, pset=pset)
+
+class MyHeap(object):
+ def __init__(self, initial=None, key=lambda x:x):
+ self.key = key
+ self.index = 0
+ if initial:
+ self._data = [(key(item), i, item) for i, item in enumerate(initial)]
+ self.index = len(self._data)
+ heapq.heapify(self._data)
+ else:
+ self._data = []
+
+ def push(self, item):
+ heapq.heappush(self._data, (self.key(item), self.index, item))
+ self.index += 1
+
+ def pop(self):
+ return heapq.heappop(self._data)[2]
\ No newline at end of file
diff --git a/GPRL/utils/optim.py b/GPRL/utils/optim.py
new file mode 100644
index 0000000000000000000000000000000000000000..7dbdf641cd8aa8b1066ad021097c3ced45a9d776
--- /dev/null
+++ b/GPRL/utils/optim.py
@@ -0,0 +1,15 @@
+import numpy as np
+
+from functools import partial
+
+def eval(epsi, F, w):
+ return F(w+epsi)
+
+def Open_AI_ES(map, F, weights, n, steps, alpha=0.001, sigma=0.1):
+ for _ in range(steps):
+ epsi = np.random.normal(loc=0.0, scale=sigma, size=(n, weights.size)).reshape((n, *weights.shape))
+ evaluate = partial(eval, F=F, w=weights)
+ R = np.array(map(evaluate, epsi))
+ A = (R - np.mean(R)) / (np.std(R)+ 1e-4)
+ weights += (alpha/(n*sigma))*np.dot(A.T, epsi).flatten()
+ return weights
\ No newline at end of file
diff --git a/GPRL/utils/policy.py b/GPRL/utils/policy.py
new file mode 100644
index 0000000000000000000000000000000000000000..e448802ee16377dfc473340360ee5c6cd255cf5a
--- /dev/null
+++ b/GPRL/utils/policy.py
@@ -0,0 +1,32 @@
+import json
+
+class Policy(object):# generic class that handle different policy representation (Tree or Linear) for serealization purpose
+ def __init__(self, programm) -> None:
+ super().__init__()
+ self.policy_type = str(type(programm))
+ self.repr = str(programm)
+
+ self.policy = programm
+ #env id
+ def __call__(self):
+ pass
+
+ def save_policy(self, path):
+ data = {}
+ data['policy_type'] = self.policy_type
+ data['policy'] = self.repr
+ #kwargs from policy
+ with open(path, 'w') as outfile:
+ json.dump(data, outfile)
+
+ def load_policy(self, path):
+ with open(path) as json_file:
+ data = json.load(json_file)
+
+ self.policy_type = data['policy_type']
+ self.repr = data['policy']
+
+ self.policy
+
+ def __str__(self):
+ return self.repr
\ No newline at end of file
diff --git a/GPRL/utils/utils.py b/GPRL/utils/utils.py
new file mode 100644
index 0000000000000000000000000000000000000000..e06baec7f7c6fd47a884ba983a3bdf6b476e7459
--- /dev/null
+++ b/GPRL/utils/utils.py
@@ -0,0 +1,35 @@
+from functools import reduce
+from operator import add, itemgetter
+import numpy as np
+import pandas as pd
+
+def convert_logbook_to_dataframe(logbook):
+ chapter_keys = logbook.chapters.keys()
+ sub_chaper_keys = [c[0].keys() for c in logbook.chapters.values()]
+
+ data = [list(map(itemgetter(*skey), chapter)) for skey, chapter
+ in zip(sub_chaper_keys, logbook.chapters.values())]
+
+ tmp = []
+ for a in zip(*data):
+ flat = []
+ for e in a:
+ flat+=[*e]
+ tmp.append(flat)
+ data = np.array(tmp)
+
+ columns = reduce(add, [["_".join([x, y]) for y in s]
+ for x, s in zip(chapter_keys, sub_chaper_keys)])
+ df = pd.DataFrame(data, columns=columns)
+
+ keys = logbook[0].keys()
+ data = [[d[k] for d in logbook] for k in keys]
+ for d, k in zip(data, keys):
+ df[k] = d
+ return df
+
+def basic_budget_scheduler(gen_threshold):
+ dico = {k:v for k,v in gen_threshold}
+ def scheduler(gen, pop):
+ return dico(gen)
+ return scheduler
diff --git a/conf/conf_gp.yml b/conf/conf_gp.yml
new file mode 100644
index 0000000000000000000000000000000000000000..4c0f1645deee085997821eb0f04edb732c6ee0ae
--- /dev/null
+++ b/conf/conf_gp.yml
@@ -0,0 +1,28 @@
+algorithm:
+ name: algorithms.eaSimple
+ args:
+ #mu: 10
+ #lambda: 10
+ ngen: 5
+ cxpb: 0.1
+ mutpb: 0.9
+
+population:
+ init_size: 100
+
+selection:
+ name: selNSGA2
+ args:
+
+individual: Tree
+
+params:
+ env: "MountainCarContinuous-v0"
+ function_set: small
+ c: 0.0
+ n_episodes: 1
+ n_steps: 100
+ gamma: 1.0
+ n_thread: 1
+
+seed: 42
\ No newline at end of file
diff --git a/conf/conf_lingp.yml b/conf/conf_lingp.yml
new file mode 100644
index 0000000000000000000000000000000000000000..7bab3a07a32303fea2a81254dc9c002a0f71e471
--- /dev/null
+++ b/conf/conf_lingp.yml
@@ -0,0 +1,39 @@
+algorithm:
+ name: algorithms.eaSimple
+ args:
+ #mu: 10
+ #lambda: 10
+ ngen: 5
+ cxpb: 0.1
+ mutpb: 0.9
+
+population:
+ init_size: 100
+
+selection:
+ name: selTournament
+ args:
+ tournsize: 5
+
+individual: Linear
+
+params:
+ env: "MountainCarContinuous-v0"
+ function_set: small
+ c: 0.0
+ n_episodes: 1
+ n_steps: 100
+ gamma: 1.0
+ regCalcSize: 8
+ regConstSize: 10
+ init_size_min: 2
+ init_size_max: 5
+ pConst: 0.3
+ pBranch: 0.3
+ pIns: 0.3
+ pDel: 0.6
+ pSwap: 0.1
+ pMut: 0.5
+ n_thread: 1
+
+seed: 42
\ No newline at end of file
diff --git a/conf/conf_qd-lingp-BipedalWalker.yml b/conf/conf_qd-lingp-BipedalWalker.yml
new file mode 100644
index 0000000000000000000000000000000000000000..43e91af87b434fc76812a844425b7b212fbe4403
--- /dev/null
+++ b/conf/conf_qd-lingp-BipedalWalker.yml
@@ -0,0 +1,46 @@
+algorithm:
+ name: algo.qdLambda
+ args:
+ batch_size: 100
+ lambda_: 500
+ ngen: 5
+ cxpb: 0.0
+ mutpb: 1.0
+ show_warnings: True
+ verbose: True
+
+population:
+ init_size: 1000
+ args:
+ shape: [10, 10]
+ max_items_per_bin: 10
+ features_domain: [[0, 100], [0., 10.0], [0., 2.5], [0., 2.5], [0., 2.5], [0., 2.5], [0., 1.0], [0., 1.0]]
+ fitness_domain: [[-200_000.0, 350.0],]
+
+selection:
+ name: selRandom
+ args:
+
+individual: Linear
+
+params:
+ env: BipedalWalker-v3
+ function_set: extended
+ c: 0.0
+ n_episodes: 1
+ n_steps: 100
+ gamma: 1.0
+ features_kept: [False, False, True, False, True, False, False, False]
+ regCalcSize: 8
+ regConstSize: 10
+ init_size_min: 2
+ init_size_max: 5
+ pConst: 0.3
+ pBranch: 0.3
+ pIns: 0.3
+ pDel: 0.6
+ pSwap: 0.1
+ pMut: 0.5
+ n_thread: 16
+
+seed: 42
\ No newline at end of file
diff --git a/evolve.py b/evolve.py
new file mode 100644
index 0000000000000000000000000000000000000000..65392d8ebb9331659f01f725628e5b6bfae7b5af
--- /dev/null
+++ b/evolve.py
@@ -0,0 +1,74 @@
+import pandas as pd
+import numpy as np
+import random
+from deap import tools
+
+if "__main__" == __name__:
+ import yaml
+ import argparse
+ import multiprocessing
+ from deap import algorithms
+ from GPRL import algorithms as algo
+ from GPRL.utils.utils import convert_logbook_to_dataframe
+
+ parser = argparse.ArgumentParser(description='Main programm to launch experiments from yaml configuration file')
+ parser.add_argument("--conf", required=True, help="configuration file path", type=str)
+ parser.add_argument("--path", help="directory for results", default="", type=str)
+ parser.add_argument("--name", help="name for saving results", default="", type=str)
+
+ args = parser.parse_args()
+
+ with open(args.conf) as f:
+ conf = yaml.load(f, Loader=yaml.SafeLoader)
+
+ if args.name == "":
+ args.name = hash(conf.values())
+
+
+ if conf["individual"] == "Tree":
+ import experiments.gp as evoTool
+ elif conf["individual"] == "Linear":
+ import experiments.linGP as evoTool
+
+ factory = evoTool.Factory(conf["params"])
+
+ factory.init_global_var()# Prepare toolbox and creator
+
+ mstats = factory.get_stats()
+
+ pool = multiprocessing.Pool(conf["params"]["n_thread"], initializer=factory.init_global_var)
+ evoTool.toolbox.register("map", pool.map)
+
+
+ if conf.get("seed", None):
+ np.random.seed(conf["seed"])
+ random.seed(conf["seed"])
+
+ if "qd" in conf["algorithm"]["name"]:
+ from qdpy.containers import Grid
+ conf["population"]["args"]["features_domain"] = np.array(conf["population"]["args"]["features_domain"])[conf["params"]["features_kept"]]
+ conf["algorithm"]["args"]["container"] = Grid(**conf["population"]["args"])
+
+ if conf["individual"] == "Tree":
+ from experiments.qdgp import MC_fitness
+ elif conf["individual"] == "Linear":
+ from experiments.qdlinGP import MC_fitness
+
+ evoTool.toolbox.register('evaluate', MC_fitness, n_steps=conf["params"]["n_steps"], num_episodes=conf["params"]["n_episodes"], gamma=conf["params"]["gamma"], features_kept=conf["params"]["features_kept"])
+
+
+ pop = evoTool.toolbox.population(n=conf["population"]["init_size"])
+ hof = tools.HallOfFame(10)
+
+ algorithm = eval(conf["algorithm"]["name"])#/!\ not good from a security point of view but flexible
+ pop, log = algorithm(pop, evoTool.toolbox, halloffame=hof, stats=mstats, **conf["algorithm"]["args"])
+
+ name = "log_"+ str(args.name) + ".csv"
+
+ convert_logbook_to_dataframe(log).to_csv(name, index=False)
+
+ print("Experiment is saved at : ", name)
+
+ factory.close()
+ pool.close()
+
diff --git a/experiments/MCTS.py b/experiments/MCTS.py
new file mode 100644
index 0000000000000000000000000000000000000000..48e282ee4ea6bf183c4d3489868ef7dc51790a8d
--- /dev/null
+++ b/experiments/MCTS.py
@@ -0,0 +1,83 @@
+from functools import partial
+import operator
+import numpy as np
+
+import gym
+
+from deap import gp
+
+from GPRL.utils import gp_utils
+from GPRL.MCTS.MCTS import TreeNMCS
+
+def init(env_name, func_set):
+ global ENV, pset
+ ENV = gym.make(env_name)
+
+ INPUT = ENV.observation_space.shape[0]
+
+ core_function = [ (np.add, [float]*2, float), (np.subtract, [float]*2, float), (np.multiply, [float]*2, float), (gp_utils.div, [float]*2, float)]
+ exp_function = [ (gp_utils.exp, [float], float), (gp_utils.log, [float], float)]
+ trig_function = [(np.sin, [float], float)]
+ if_function = [ (gp_utils.if_then_else, [bool, float, float], float), (operator.gt, [float, float], bool), (operator.and_, [bool, bool], bool), (operator.or_, [bool, bool], bool) ]
+ classification_func = [(gp_utils.classification, [float, float, float], int)] #(gp_utils.intervales, [float], int)
+
+ if func_set == "small":
+ function_set = core_function + if_function
+ elif func_set == "extended":
+ function_set = core_function + exp_function + trig_function
+
+ pset = gp.PrimitiveSetTyped("MAIN", [float]*INPUT, bool)
+ for primitive in function_set:
+ pset.addPrimitive(*primitive)
+ pset.addTerminal(0.1, float)
+ for i in range(10):
+ pset.addTerminal(float(i), float)
+ pset.addTerminal(True, bool)
+ pset.addTerminal(1, int)
+
+
+def fitness(individual, n_steps, gamma):
+ agent = gp.compile(gp.PrimitiveTree(individual), pset=pset)
+ s = 0
+ state = ENV.reset()
+ for _ in range(n_steps):
+ #state, reward, done, _ = env.step(int(agent(*state)))
+ state, reward, done, _ = ENV.step([agent(*state)])
+ s+= gamma*reward
+ if done:
+ return s
+ return s
+
+def n_fitness(individual, func, n, map=map):
+ arg = [individual for _ in range(n)]
+ return sum(map(func, arg))/n
+
+if __name__ == "__main__":
+ import argparse
+ from multiprocessing import Pool
+
+ parser = argparse.ArgumentParser(description='Nested Monte-Carlo script')
+ parser.add_argument("--env", required=True, help="environment ID", type=str)
+ parser.add_argument("--n-episodes", help="Number of episodes per playout", default=1, type=int)
+ parser.add_argument("--n-steps", help="Number of step per episode per episodes", default=500, type=int)
+ parser.add_argument("--gamma", help="discount factor", default=1.0, type=float)
+ parser.add_argument("--max-size", help="max size of the tree for playout", default=6, type=int)
+ parser.add_argument("--level", help="nested monte carlo level", default=3, type=int)
+ parser.add_argument("--n-thread", help="number of thread to use for episode parallelization", default=1, type=int)
+ parser.add_argument("--function-set", help="function set", default="small", type=str)
+ parser.add_argument("--path", help="path to save the results", default="", type=str)
+
+ args = parser.parse_args()
+
+ init()
+ pool = Pool(args.n_thread, initializer=init)
+
+ func = partial(fitness, n_steps=args.n_steps, gamma=args.gamma)
+
+ evaluate = partial(n_fitness, func=func, n=args.n_episodes, map=pool.map)
+
+ nmcs = TreeNMCS(pset, args.max_size, evaluate)
+ result = gp.PrimitiveTree(nmcs.run([], [pset.ret], 3))
+
+ print(result)
+ pool.close()
\ No newline at end of file
diff --git a/experiments/bench.py b/experiments/bench.py
new file mode 100644
index 0000000000000000000000000000000000000000..9838a54db17844a090f1824fb3e148d7de00931e
--- /dev/null
+++ b/experiments/bench.py
@@ -0,0 +1,317 @@
+from UCB import ArmHof, selDoubleTournament
+from functools import partial
+import operator
+import random
+
+from deap import base, creator, tools, algorithms
+
+import gp_utils
+import team
+
+import numpy as np
+from numba import njit
+
+from algorithms import eaMuPlusLambdaUCB
+
+tools.selUCBDoubleTounament = selDoubleTournament
+
+#benchmark bandit :
+# - budget
+# - best cumreward/stability
+# - solution complexity
+# - maybe constant effect sigma/c
+# compare too fixed sample and maybe big size pop (implicite vs explicite)
+# One max+noise (various dim) & maybe one openai env (an easy/fast one)
+
+def evalOneMax(individual, DIMS, STD, n_eval=1):
+ if STD == 0.0:
+ n_eval=1
+ return numba_evalOneMax(np.array(individual, dtype=int), DIMS, STD, n_eval=n_eval),
+
+@njit
+def numba_evalOneMax(individual, DIMS, STD, n_eval):
+ std = np.random.normal(0.0, STD, n_eval)
+ return (np.sum(individual)/DIMS) + std.mean()
+
+def oneMax(conf, STD, DIMS, N_EVAL):
+ DIMS = 2**DIMS
+ if "UCB" in conf["algorithm"]["name"]:
+ from UCB import UCBFitness
+ creator.create("FitnessMax", UCBFitness, weights=(1.0,), sigma=STD)
+ else:
+ creator.create("FitnessMax", base.Fitness, weights=(1.0,))
+
+ creator.create("Individual", list, fitness=creator.FitnessMax)
+
+ toolbox = base.Toolbox()
+
+ toolbox.register("attr_bool", random.randint, 0, 1)
+ toolbox.register("individual", tools.initRepeat, creator.Individual, toolbox.attr_bool, DIMS)
+ toolbox.register("population", tools.initRepeat, list, toolbox.individual)
+
+ toolbox.register("evaluate", evalOneMax, DIMS=DIMS, STD=STD, n_eval=N_EVAL)
+ toolbox.register("mate", tools.cxTwoPoint)
+ toolbox.register("mutate", tools.mutFlipBit, indpb=0.05)
+ toolbox.register("select", eval("tools."+conf["population"]["selection"]), **conf["population"]["args"])
+
+ return toolbox, creator
+
+def check_env():
+ return 'ENV' in globals()
+
+def MC_fitness(individual, env, n_steps, num_episodes, gamma):
+ if check_env() and env is None:
+ env = ENV
+ agent = toolbox.compile(individual)
+ s = 0
+ steps = 0
+ for _ in range(num_episodes):
+ state = env.reset()
+ for k in range(n_steps):
+ state, reward, done, _ = env.step(agent(*state))
+ s+= gamma*reward
+ steps += 1
+ if done:
+ break
+ return s/num_episodes, team.team_complexity(individual, gp_utils.complexity)
+
+def env(conf, UCB_SIGMA, NUM_EPISODE, tmp=0):
+ import gym
+ from deap import gp
+
+ global ENV
+
+ ENV = gym.make(conf["problem"]["env"])
+
+ INPUT = ENV.observation_space.shape[0]
+ OUTPUT = ENV.action_space.shape[0]
+
+ function_set = [ (np.add, [float]*2, float), (np.subtract, [float]*2, float), (np.multiply, [float]*2, float), (gp_utils.div, [float]*2, float), (np.sin, [float], float),
+ (partial(gp_utils.power, n=0.5), [float], float, 'sqrt'), (partial(gp_utils.power, n=2), [float], float, 'square'), (partial(gp_utils.power, n=3), [float], float, 'cube')]
+
+ pset = gp.PrimitiveSetTyped("MAIN", [float]*INPUT, float)
+ for primitive in function_set:
+ pset.addPrimitive(*primitive)
+ pset.addEphemeralConstant("const"+str(tmp), lambda: np.random.uniform(-10.0, 10.0), float)
+
+ # for k in range(INPUT): # For large input space
+ # pset.addEphemeralConstant("const_"+str(k), lambda: np.random.uniform(-10.0, 10.0), float)
+
+ if "UCB" in conf["algorithm"]["name"]:
+ from UCB import UCBFitness
+ creator.create("FitnessMax", UCBFitness, weights=(1.0, -1.0), sigma=UCB_SIGMA)
+ else:
+ creator.create("FitnessMax", base.Fitness, weights=(1.0, -1.0))
+
+ creator.create("Individual", list, fitness=creator.FitnessMax)
+
+ toolbox = base.Toolbox()
+ toolbox.register("expr", gp.genHalfAndHalf, pset=pset, min_=3, max_=8)
+ toolbox.register("team_grow", team.init_team, size=OUTPUT, unit_init=lambda: gp.PrimitiveTree(toolbox.expr()))
+ toolbox.register("individual", tools.initIterate, creator.Individual, toolbox.team_grow)
+
+ toolbox.register("population", tools.initRepeat, list, toolbox.individual)
+ toolbox.register("compile_gp", gp.compile, pset=pset)
+ toolbox.register("compile", team.team_compile, unit_compile=toolbox.compile_gp)
+
+ toolbox.register("evaluate", MC_fitness, env=None, n_steps=conf["problem"]["n_step"], num_episodes=NUM_EPISODE, gamma=conf["problem"]["gamma"])
+
+ if conf["population"]["args"]:
+ toolbox.register("select", eval("tools."+conf["population"]["selection"]), **conf["population"]["args"])
+ else:
+ toolbox.register("select", eval("tools."+conf["population"]["selection"]))
+
+ def cx(x1, x2):
+ tmp1, tmp2 = gp.cxOnePoint(x1, x2)
+ return gp.PrimitiveTree(tmp1), gp.PrimitiveTree(tmp2)
+
+ toolbox.register("mate", team.fixed_mate, unit_cx=cx)
+ toolbox.register("expr_mut", gp.genFull, min_=0, max_=2)
+ toolbox.register("mutate_gp", gp_utils.mutate, expr=toolbox.expr_mut, pset=pset, mode="all", mu=0, std=1)
+ toolbox.register("mutate", team.mutate, unit_mut=lambda x: gp.PrimitiveTree(toolbox.mutate_gp(x)[0]))
+
+ toolbox.decorate("mate", gp.staticLimit(key=lambda x: team.height(x, operator.attrgetter("height")), max_value=17))
+ toolbox.decorate("mutate", gp.staticLimit(key=lambda x: team.height(x, operator.attrgetter("height")), max_value=17))
+
+ return toolbox, creator
+
+def initializer(func, seed=None):
+ global toolbox
+
+ toolbox, _ = func()
+ if seed:
+ np.random.seed(seed)
+ random.seed(seed)
+
+if __name__ == "__main__":
+ import multiprocessing
+ import time
+ import pandas as pd
+ import parser
+ from algorithms import eaMuPlusLambdaUCB
+ from UCB import UpdateFitnessHof, selDoubleTournament
+
+ import yaml
+
+ with open("results/Bench/env/conf/mu+lambdaUCB-mountaincar.yml") as f:
+ conf = yaml.load(f, Loader=yaml.FullLoader)
+
+ algo = eval(conf["algorithm"]["name"])
+ pbm = conf["problem"]["name"]
+ nb_runs = conf["problem"]["nb_runs"]
+ if conf["seed"]:
+ np.random.seed(conf["seed"])
+ random.seed(conf["seed"])
+
+ if pbm == "oneMax":
+ results = {"best_pop":[], "best_hof":[], "best_arm":[], "std":[], "dim":[],
+ "n_eval":[], "run_number":[], "UCB_sigma":[], "ngen":[], "mu":[], "lambda":[],
+ "n_thread":[], "time":[]}#n_eval or simulation_buget
+
+ ngen = conf["algorithm"]["args"]["ngen"]
+ simulation_budget = conf["algorithm"]["args"].get("simulation_budget", [None])
+ tmp=0
+ for n_eval in conf["problem"]["n_eval"]:
+ for std in conf["problem"]["std"]:
+ for idx, dim in enumerate(conf["problem"]["dims"]):
+ for sim_budg in simulation_budget:
+ for run_number in range(nb_runs):
+ tmp+=1
+ func = partial(oneMax, conf=conf, STD=std, DIMS=dim, N_EVAL=n_eval)
+ toolbox, creator = func()
+
+ pop=toolbox.population(n=conf["population"]["init_size"])
+ if "UCB" in conf["algorithm"]["name"]:
+ hof = UpdateFitnessHof(20, maxsize_arm=20)
+ conf["algorithm"]["args"]["simulation_budget"] = sim_budg
+ else:
+ hof = tools.HallOfFame(20)
+
+ if isinstance(ngen, list):
+ conf["algorithm"]["args"]["ngen"] = ngen[idx]
+
+ with multiprocessing.Pool(conf["algorithm"]["n_thread"], initializer=initializer, initargs=(func, conf["seed"])) as p:
+ toolbox.register("map", p.map)
+ start = time.time()
+ pop, log = algo(pop, toolbox, halloffame=hof, **conf["algorithm"]["args"])
+
+ toolbox.unregister("evaluate")
+ toolbox.register("evaluate", evalOneMax, DIMS=2**dim, STD=0.0, n_eval=1)
+ pops = [hof, pop, hof.arm_hof] if isinstance(hof, UpdateFitnessHof) else [hof, pop]
+ for l in pops:
+ fitnesses = toolbox.map(toolbox.evaluate, l)
+ for ind, fit in zip(l, fitnesses):
+ ind.fitness.values = fit
+
+ del creator.Individual
+ del creator.FitnessMax
+
+ print("Run ", str(tmp))
+
+ results["time"].append(time.time()-start)
+ results["best_pop"].append(tools.selBest(pop, 1)[0].fitness.values[0])
+ results["best_hof"].append(tools.selBest(hof, 1)[0].fitness.values[0])
+ results["std"].append(std)
+ results["dim"].append(dim)
+ results["ngen"].append(conf["algorithm"]["args"]["ngen"])
+ results["run_number"].append(run_number)
+ results["n_thread"].append(conf["algorithm"]["n_thread"])
+
+ if "UCB" in conf["algorithm"]["name"]:
+ results["n_eval"].append(sim_budg)
+ else:
+ results["n_eval"].append(n_eval)
+
+
+ results["mu"].append(conf["algorithm"]["args"].get("mu", None))
+ results["lambda"].append(conf["algorithm"]["args"].get("lambda", None))
+
+ results["UCB_sigma"].append(conf["algorithm"].get("UCB_sigma", None))
+ if isinstance(hof, UpdateFitnessHof):
+ results["best_arm"].append(hof.arm_hof[0].fitness.values[0])
+ else:
+ results["best_arm"].append(None)
+ pd.DataFrame(results).to_csv("results/mu+lambdaUCB-pop=100.csv", index=False)
+
+ elif pbm == "env":
+
+ results = {"best_pop":[], "best_hof":[], "best_arm":[], "env":[], "n_step": [],
+ "num_episode":[], "run_number":[], "UCB_sigma":[], "ngen":[], "mu":[], "lambda":[],
+ "n_thread":[], "complexity_pop":[], "complexity_hof":[], "complexity_arm":[], "time":[]}#num_episode or simulation_buget depending on UCB alg or not
+
+ simulation_budget = conf["algorithm"]["args"].get("simulation_budget", [None])
+ tmp=0
+
+ for num_episode in conf["problem"]["num_episode"]:
+ for UCB_sigma in conf["algorithm"].get("UCB_sigma", [None]):
+ for sim_budg in simulation_budget:
+ for run_number in range(nb_runs):
+ tmp+=1
+ func = partial(env, conf=conf, UCB_SIGMA=UCB_sigma, NUM_EPISODE=num_episode, tmp=tmp)
+
+ toolbox, creator = func()
+
+ pop=toolbox.population(n=conf["population"]["init_size"])
+ if "UCB" in conf["algorithm"]["name"]:
+ hof = UpdateFitnessHof(20, maxsize_arm=20)
+ conf["algorithm"]["args"]["simulation_budget"] = sim_budg
+ else:
+ hof = tools.ParetoFront()
+
+
+ with multiprocessing.Pool(conf["algorithm"]["n_thread"], initializer=initializer, initargs=(func, conf["seed"])) as p:
+ toolbox.register("map", p.map)
+ start = time.time()
+ pop, log = algo(pop, toolbox, halloffame=hof, **conf["algorithm"]["args"])
+
+ toolbox.unregister("evaluate")
+ toolbox.register("evaluate", MC_fitness, env=None, n_steps=conf["problem"]["n_step"], num_episodes=50, gamma=1.0)
+ pops = [hof, pop, hof.arm_hof] if isinstance(hof, UpdateFitnessHof) else [hof, pop]
+ for l in pops:
+ fitnesses = toolbox.map(toolbox.evaluate, l)
+ for ind, fit in zip(l, fitnesses):
+ del ind.fitness.values
+ ind.fitness.values = fit
+
+ del creator.Individual
+ del creator.FitnessMax
+
+ print("Run ", str(tmp))
+
+ best_pop = tools.selBest(pop, 1)[0]
+ best_hof = tools.selBest(hof, 1)[0]
+
+ results["time"].append(time.time()-start)
+ results["best_pop"].append(best_pop.fitness.values[0])
+ results["best_hof"].append(best_hof.fitness.values[0])
+ results["complexity_pop"].append(best_pop.fitness.values[1])
+ results["complexity_hof"].append(best_hof.fitness.values[1])
+ results["ngen"].append(conf["algorithm"]["args"]["ngen"])
+ results["env"].append(conf["problem"]["env"])
+ results["run_number"].append(run_number)
+ results["n_thread"].append(conf["algorithm"]["n_thread"])
+ results["n_step"].append(conf["problem"]["n_step"])
+
+ if "UCB" in conf["algorithm"]["name"]:
+ results["num_episode"].append(sim_budg)
+ else:
+ results["num_episode"].append(num_episode)
+
+
+ results["mu"].append(conf["algorithm"]["args"].get("mu", None))
+ results["lambda"].append(conf["algorithm"]["args"].get("lambda", None))
+
+ results["UCB_sigma"].append(UCB_sigma if conf["algorithm"].get("UCB_sigma", None) else None)
+ if isinstance(hof, UpdateFitnessHof):
+ best_arm = tools.selBest(hof.arm_hof, 1)[0]
+ results["best_arm"].append(best_arm.fitness.values[0])
+ results["complexity_arm"].append(best_arm.fitness.values[1])
+ else:
+ results["best_arm"].append(None)
+ results["complexity_arm"].append(None)
+
+ pd.DataFrame(results).to_csv("results/UCBmu+lambda.csv", index=False)
+
+
+ #amoeba net 2**6 => 2**9, sigma 0.01 on accruracy (sum(bits)/dimensions) averaged on 100 runs
+ # design stats !
\ No newline at end of file
diff --git a/experiments/bench/env/conf/easimple-mountaincar.yml b/experiments/bench/env/conf/easimple-mountaincar.yml
new file mode 100644
index 0000000000000000000000000000000000000000..1d5c2b759b829e67ae1e4a671768ba2bfe68e033
--- /dev/null
+++ b/experiments/bench/env/conf/easimple-mountaincar.yml
@@ -0,0 +1,24 @@
+algorithm:
+ name: algorithms.eaSimple
+ n_thread: 16
+ args:
+ ngen: 100
+ cxpb: 0.0
+ mutpb: 1.0
+ verbose: False
+
+population:
+ init_size: 100
+ selection: selNSGA2
+ args:
+ #tournsize: 3
+
+problem:
+ name: "env"
+ env: "MountainCarContinuous-v0"
+ n_step: 500
+ num_episode: [1, 2, 5, 10]
+ gamma: 1.0
+ nb_runs: 10
+
+seed: 42
diff --git a/experiments/bench/env/conf/mu+lambda-mountaincar.yml b/experiments/bench/env/conf/mu+lambda-mountaincar.yml
new file mode 100644
index 0000000000000000000000000000000000000000..2c8b3858dc1967b1a85e3abb223e159994cbe380
--- /dev/null
+++ b/experiments/bench/env/conf/mu+lambda-mountaincar.yml
@@ -0,0 +1,26 @@
+algorithm:
+ name: algorithms.eaMuPlusLambda
+ n_thread: 16
+ args:
+ ngen: 100
+ cxpb: 0.0
+ mutpb: 1.0
+ mu: 100
+ lambda_: 100
+ verbose: False
+
+population:
+ init_size: 100
+ selection: selNSGA2
+ args:
+ #tournsize: 3
+
+problem:
+ name: "env"
+ env: "MountainCarContinuous-v0"
+ n_step: 500
+ num_episode: [1, 2, 5, 10]
+ gamma: 1.0
+ nb_runs: 10
+
+seed: 42
diff --git a/experiments/bench/env/conf/mu+lambdaUCB-mountaincar.yml b/experiments/bench/env/conf/mu+lambdaUCB-mountaincar.yml
new file mode 100644
index 0000000000000000000000000000000000000000..3fe9d9da0e3f727cdf5f23bbda32ddee87f74612
--- /dev/null
+++ b/experiments/bench/env/conf/mu+lambdaUCB-mountaincar.yml
@@ -0,0 +1,30 @@
+algorithm:
+ name: eaMuPlusLambdaUCB
+ n_thread: 16
+ UCB_sigma: [1, 2, 5, 10]
+ args:
+ ngen: 100
+ cxpb: 0.0
+ mutpb: 1.0
+ mu: 100
+ lambda_: 100
+ simulation_budget: [0, 7, 25, 57]
+ parallel_update: 16
+ select: True
+ verbose: False
+
+population:
+ init_size: 100
+ selection: selNSGA2
+ args:
+ #tournsize: 3
+
+problem:
+ name: "env"
+ env: "MountainCarContinuous-v0"
+ n_step: 500
+ num_episode: [1]
+ gamma: 1.0
+ nb_runs: 10
+
+seed: 42
diff --git a/experiments/bench/env/data/UCBmu+lambda-mountaincar.csv b/experiments/bench/env/data/UCBmu+lambda-mountaincar.csv
new file mode 100644
index 0000000000000000000000000000000000000000..ee07bd4f82f98aa4bc33f49cbf47af2d2aafd575
--- /dev/null
+++ b/experiments/bench/env/data/UCBmu+lambda-mountaincar.csv
@@ -0,0 +1,161 @@
+best_pop,best_hof,best_arm,env,n_step,num_episode,run_number,UCB_sigma,ngen,mu,lambda,n_thread,complexity_pop,complexity_hof,complexity_arm,time
+69.20891037833911,67.2263346705136,19.554692065515965,MountainCarContinuous-v0,500,0,0,1,100,100,,16,4.0,10.0,3.0,25.04941415786743
+69.22248612579709,79.03458690606077,97.80471026610536,MountainCarContinuous-v0,500,0,1,1,100,100,,16,8.0,14.0,10.0,28.10206627845764
+69.2253634270904,65.23134762845237,63.24126973866052,MountainCarContinuous-v0,500,0,2,1,100,100,,16,12.0,8.0,4.0,27.303120613098145
+67.23529168844875,77.19762762953616,55.221185483399466,MountainCarContinuous-v0,500,0,3,1,100,100,,16,4.0,12.0,4.0,33.27259016036987
+73.2273093643042,67.24359971972748,98.67232840746283,MountainCarContinuous-v0,500,0,4,1,100,100,,16,24.0,19.0,6.0,35.65710735321045
+71.23192356152066,69.21713715394615,97.48326912993885,MountainCarContinuous-v0,500,0,5,1,100,100,,16,4.0,12.0,7.0,27.640100955963135
+69.01116476857608,63.23674657112647,61.231682416407146,MountainCarContinuous-v0,500,0,6,1,100,100,,16,3.0,18.0,4.0,36.024561166763306
+73.1978957136376,61.217726509527076,97.49144413746345,MountainCarContinuous-v0,500,0,7,1,100,100,,16,4.0,8.0,7.0,36.94113373756409
+67.2166533320035,98.67916564045194,55.23322095795571,MountainCarContinuous-v0,500,0,8,1,100,100,,16,4.0,6.0,4.0,24.991070985794067
+67.22579022958791,61.234599076188005,59.22219594711314,MountainCarContinuous-v0,500,0,9,1,100,100,,16,4.0,8.0,4.0,28.7480890750885
+98.91718799719776,98.96098322419076,98.71687022010283,MountainCarContinuous-v0,500,7,0,1,100,100,,16,8.0,16.0,6.0,68.3975658416748
+98.9966202195083,98.91746858503342,98.77039407805023,MountainCarContinuous-v0,500,7,1,1,100,100,,16,30.0,23.0,16.0,97.55417394638062
+98.92444986241131,98.73263997709624,98.86119882684447,MountainCarContinuous-v0,500,7,2,1,100,100,,16,21.0,21.0,8.0,90.34074091911316
+98.73180593691333,98.7581007353849,98.71287237064979,MountainCarContinuous-v0,500,7,3,1,100,100,,16,6.0,8.0,14.0,63.7143120765686
+99.04832777403908,98.98191418035977,98.48232042884,MountainCarContinuous-v0,500,7,4,1,100,100,,16,17.0,28.0,8.0,90.27202486991882
+98.87535054644009,96.56134238306005,90.83053423800835,MountainCarContinuous-v0,500,7,5,1,100,100,,16,6.0,14.0,12.0,67.07640051841736
+98.90696334525515,98.71720780022886,98.80781599603125,MountainCarContinuous-v0,500,7,6,1,100,100,,16,9.0,45.0,34.0,84.40091586112976
+98.91666983890849,98.9157465823791,98.73198891379069,MountainCarContinuous-v0,500,7,7,1,100,100,,16,14.0,18.0,18.0,87.15925145149231
+98.87442050124834,98.88756513285087,98.68754901126367,MountainCarContinuous-v0,500,7,8,1,100,100,,16,14.0,24.0,6.0,66.1295063495636
+98.74433480080366,98.95875242231133,98.71980093369699,MountainCarContinuous-v0,500,7,9,1,100,100,,16,6.0,18.0,6.0,66.89012217521667
+98.99149390007221,98.9337516206693,98.95462191983455,MountainCarContinuous-v0,500,25,0,1,100,100,,16,28.0,36.0,13.0,220.88166093826294
+99.0068372236952,98.98445702944154,99.00063941767382,MountainCarContinuous-v0,500,25,1,1,100,100,,16,27.0,33.0,21.0,231.93528413772583
+98.9978959238536,98.89551178731315,98.72032814463346,MountainCarContinuous-v0,500,25,2,1,100,100,,16,31.0,31.0,44.0,210.59205985069275
+98.9683739077446,98.93851901439777,98.8660140051903,MountainCarContinuous-v0,500,25,3,1,100,100,,16,36.0,71.0,44.0,379.944988489151
+98.93567619069809,98.85831350595086,98.8416949461891,MountainCarContinuous-v0,500,25,4,1,100,100,,16,6.0,14.0,6.0,182.74081683158875
+98.71533246776508,98.85443388354248,98.68163017276343,MountainCarContinuous-v0,500,25,5,1,100,100,,16,6.0,13.0,10.0,139.1044521331787
+99.02043844980777,99.01642375923116,98.95909220915114,MountainCarContinuous-v0,500,25,6,1,100,100,,16,60.0,70.0,47.0,371.123411655426
+98.9277483522522,98.86531985063843,98.700474038501,MountainCarContinuous-v0,500,25,7,1,100,100,,16,6.0,6.0,6.0,153.2961528301239
+98.95001598761526,98.92000937805494,98.75702411250792,MountainCarContinuous-v0,500,25,8,1,100,100,,16,18.0,33.0,26.0,216.92863655090332
+98.75679571806432,98.88644796842021,98.70335704013955,MountainCarContinuous-v0,500,25,9,1,100,100,,16,6.0,10.0,10.0,143.6819462776184
+99.01210221213465,98.87248888282227,98.89312439389818,MountainCarContinuous-v0,500,57,0,1,100,100,,16,33.0,29.0,43.0,472.3529999256134
+98.74006522956273,98.83473527301985,98.68031860311416,MountainCarContinuous-v0,500,57,1,1,100,100,,16,10.0,8.0,6.0,292.2082495689392
+98.79793938472568,98.86333373196139,98.68681543423243,MountainCarContinuous-v0,500,57,2,1,100,100,,16,14.0,16.0,6.0,355.0124900341034
+98.97650092303589,98.95902658037677,98.93660890317526,MountainCarContinuous-v0,500,57,3,1,100,100,,16,40.0,36.0,31.0,452.5095546245575
+98.73322100270953,98.74246727023684,98.69130361985954,MountainCarContinuous-v0,500,57,4,1,100,100,,16,6.0,14.0,6.0,296.66587924957275
+98.74877248757652,98.76119776714805,98.72036680723748,MountainCarContinuous-v0,500,57,5,1,100,100,,16,8.0,8.0,6.0,290.71839141845703
+98.71826156121031,98.77862264160225,98.71363491544251,MountainCarContinuous-v0,500,57,6,1,100,100,,16,6.0,25.0,6.0,304.37462759017944
+98.82179372843963,98.90463826029034,98.69358749710082,MountainCarContinuous-v0,500,57,7,1,100,100,,16,8.0,12.0,6.0,310.4432466030121
+98.74045550169372,98.74329434088234,98.69125517069337,MountainCarContinuous-v0,500,57,8,1,100,100,,16,6.0,15.0,6.0,323.15963196754456
+98.94119328603433,98.88148968949494,98.92698237883447,MountainCarContinuous-v0,500,57,9,1,100,100,,16,8.0,20.0,8.0,347.47426199913025
+65.2195996756409,64.84496372625468,57.22006963039552,MountainCarContinuous-v0,500,0,0,2,100,100,,16,8.0,3.0,4.0,28.65256094932556
+74.67737388767686,71.22247942393511,29.386553085229533,MountainCarContinuous-v0,500,0,1,2,100,100,,16,3.0,12.0,3.0,29.48770236968994
+69.20449495185134,75.20254908543706,71.21675972933565,MountainCarContinuous-v0,500,0,2,2,100,100,,16,4.0,11.0,4.0,33.992560386657715
+67.25085318502909,63.013175606353386,59.19577246816596,MountainCarContinuous-v0,500,0,3,2,100,100,,16,8.0,3.0,8.0,26.56763505935669
+65.23719362686447,59.24831341193013,59.22175370584909,MountainCarContinuous-v0,500,0,4,2,100,100,,16,4.0,8.0,4.0,27.721176385879517
+61.205056364896,98.89172012630343,0.0,MountainCarContinuous-v0,500,0,5,2,100,100,,16,4.0,8.0,3.0,25.505845546722412
+75.22137424713364,65.2421228560201,87.54304867940488,MountainCarContinuous-v0,500,0,6,2,100,100,,16,8.0,23.0,18.0,30.964574813842773
+71.21454951384213,61.18646347882268,61.23188611116123,MountainCarContinuous-v0,500,0,7,2,100,100,,16,4.0,8.0,4.0,26.090627193450928
+57.21050942938764,98.92909674088371,0.0,MountainCarContinuous-v0,500,0,8,2,100,100,,16,4.0,8.0,3.0,27.013073205947876
+75.22855868127697,71.20605847570351,98.39552621143801,MountainCarContinuous-v0,500,0,9,2,100,100,,16,4.0,16.0,6.0,31.680106163024902
+98.82206353926475,98.75554346857716,98.70226134519473,MountainCarContinuous-v0,500,7,0,2,100,100,,16,8.0,6.0,6.0,68.24454855918884
+98.9698999431829,98.7534886120866,98.76732232254327,MountainCarContinuous-v0,500,7,1,2,100,100,,16,14.0,32.0,26.0,79.8115086555481
+98.77411346953505,98.62958439867967,98.68965741157655,MountainCarContinuous-v0,500,7,2,2,100,100,,16,25.0,45.0,6.0,116.6934564113617
+98.72055246994849,98.71221953936616,98.69505521653856,MountainCarContinuous-v0,500,7,3,2,100,100,,16,6.0,14.0,6.0,63.89925932884216
+98.94994362698259,98.93346323553611,98.94412019576956,MountainCarContinuous-v0,500,7,4,2,100,100,,16,30.0,44.0,27.0,127.04459500312805
+98.99354818809529,98.90727718271636,98.88407853702223,MountainCarContinuous-v0,500,7,5,2,100,100,,16,19.0,19.0,25.0,83.22900080680847
+98.93741676083951,98.92382316360246,98.87974358224358,MountainCarContinuous-v0,500,7,6,2,100,100,,16,10.0,36.0,32.0,83.46218514442444
+98.89566825221124,98.66863027166978,98.85278599472163,MountainCarContinuous-v0,500,7,7,2,100,100,,16,23.0,30.0,10.0,112.93997001647949
+98.93391021976184,98.72140308307334,98.70614671581507,MountainCarContinuous-v0,500,7,8,2,100,100,,16,34.0,27.0,11.0,91.50662517547607
+98.85380387254891,98.930707927093,98.72469332667079,MountainCarContinuous-v0,500,7,9,2,100,100,,16,10.0,10.0,6.0,63.880728006362915
+98.92410318212276,98.9234417564816,98.87404880622579,MountainCarContinuous-v0,500,25,0,2,100,100,,16,46.0,30.0,20.0,222.34294772148132
+98.73718620348832,98.69589115369101,94.91899231805718,MountainCarContinuous-v0,500,25,1,2,100,100,,16,6.0,15.0,5.0,147.0886082649231
+98.8896289717974,98.85834969980911,98.77033993997189,MountainCarContinuous-v0,500,25,2,2,100,100,,16,41.0,32.0,24.0,183.97219967842102
+98.91113290067798,98.83884820742942,98.94225737564726,MountainCarContinuous-v0,500,25,3,2,100,100,,16,21.0,23.0,25.0,210.36255168914795
+98.93222619467836,98.93717607585549,98.88305771040754,MountainCarContinuous-v0,500,25,4,2,100,100,,16,20.0,31.0,8.0,215.67915391921997
+98.73247002259073,98.71590402870214,98.68010220029836,MountainCarContinuous-v0,500,25,5,2,100,100,,16,14.0,18.0,14.0,146.8640832901001
+98.96403221095444,98.91581347065039,98.8048174503728,MountainCarContinuous-v0,500,25,6,2,100,100,,16,55.0,63.0,52.0,259.546315908432
+98.72260629714181,98.74047591104488,98.69225977878587,MountainCarContinuous-v0,500,25,7,2,100,100,,16,6.0,6.0,6.0,146.81792569160461
+98.71513685620883,98.71220172701489,98.68322894326835,MountainCarContinuous-v0,500,25,8,2,100,100,,16,6.0,10.0,6.0,147.92880630493164
+99.00987493851925,98.96415582640735,98.99844428037594,MountainCarContinuous-v0,500,25,9,2,100,100,,16,30.0,53.0,27.0,200.29693245887756
+98.75040421219676,98.68021263123447,98.69200154188238,MountainCarContinuous-v0,500,57,0,2,100,100,,16,6.0,12.0,6.0,348.6264705657959
+98.77478991237966,98.69738034307181,98.71133615550049,MountainCarContinuous-v0,500,57,1,2,100,100,,16,6.0,12.0,6.0,298.9058885574341
+98.74895610363403,98.76884167974983,98.73068221900415,MountainCarContinuous-v0,500,57,2,2,100,100,,16,6.0,9.0,6.0,335.08175325393677
+98.73677997240085,98.794038567111,98.6951495849527,MountainCarContinuous-v0,500,57,3,2,100,100,,16,20.0,40.0,29.0,352.1501815319061
+99.00408863407264,99.0320893590198,98.98415977005833,MountainCarContinuous-v0,500,57,4,2,100,100,,16,13.0,13.0,13.0,381.9920918941498
+98.88926722565148,98.93164715275854,98.90578888861833,MountainCarContinuous-v0,500,57,5,2,100,100,,16,16.0,34.0,20.0,390.61468958854675
+98.72939343604602,98.71723424879606,98.72929203635329,MountainCarContinuous-v0,500,57,6,2,100,100,,16,6.0,10.0,6.0,294.5884654521942
+98.7088737406193,98.83089142171757,98.66726996168819,MountainCarContinuous-v0,500,57,7,2,100,100,,16,6.0,6.0,6.0,302.2198097705841
+98.71680607998798,98.80924251040436,98.66815337019032,MountainCarContinuous-v0,500,57,8,2,100,100,,16,6.0,16.0,6.0,301.74198722839355
+99.03291268329504,99.02290079132501,99.02592996407299,MountainCarContinuous-v0,500,57,9,2,100,100,,16,62.0,82.0,62.0,797.3828094005585
+71.21007807865928,69.21580435843322,67.24697468606921,MountainCarContinuous-v0,500,0,0,5,100,100,,16,8.0,17.0,4.0,33.80000138282776
+69.21846560781937,65.23163339922623,63.2213945801062,MountainCarContinuous-v0,500,0,1,5,100,100,,16,4.0,8.0,4.0,29.379088640213013
+71.24305202416889,73.03055917883007,57.23386929555489,MountainCarContinuous-v0,500,0,2,5,100,100,,16,4.0,10.0,4.0,28.035593509674072
+75.21231076136472,57.27494131572619,73.0181735919188,MountainCarContinuous-v0,500,0,3,5,100,100,,16,4.0,8.0,6.0,33.97458839416504
+73.22683765052334,65.2520824534813,67.22723665013312,MountainCarContinuous-v0,500,0,4,5,100,100,,16,4.0,14.0,9.0,33.89209246635437
+63.21816510992901,98.69278167988972,0.0,MountainCarContinuous-v0,500,0,5,5,100,100,,16,4.0,6.0,3.0,24.15152859687805
+71.251576334369,51.32765233583847,92.85053436510074,MountainCarContinuous-v0,500,0,6,5,100,100,,16,23.0,31.0,8.0,66.90768885612488
+75.21666924038448,73.2067400784613,57.232634182366425,MountainCarContinuous-v0,500,0,7,5,100,100,,16,4.0,10.0,9.0,29.265411138534546
+71.24213142774158,67.22654477797406,59.24876107882394,MountainCarContinuous-v0,500,0,8,5,100,100,,16,4.0,14.0,8.0,28.462876319885254
+73.22329599339513,69.16773573512674,97.53195479769393,MountainCarContinuous-v0,500,0,9,5,100,100,,16,8.0,8.0,7.0,29.9116427898407
+98.72496342187333,98.86976388541858,98.69611756510031,MountainCarContinuous-v0,500,7,0,5,100,100,,16,6.0,17.0,6.0,65.12212491035461
+98.80261140861491,98.06459277536695,98.8665411496623,MountainCarContinuous-v0,500,7,1,5,100,100,,16,24.0,25.0,21.0,84.17392420768738
+98.92986182377928,98.6990241357044,98.70827104607737,MountainCarContinuous-v0,500,7,2,5,100,100,,16,28.0,32.0,6.0,100.40806436538696
+98.76977471998187,98.76408226381615,98.70840582848373,MountainCarContinuous-v0,500,7,3,5,100,100,,16,24.0,25.0,6.0,71.9120032787323
+98.89736511740746,98.60019222228952,98.8050382856551,MountainCarContinuous-v0,500,7,4,5,100,100,,16,21.0,34.0,6.0,95.2537214756012
+98.79233100444725,98.57073331442012,98.52896583243228,MountainCarContinuous-v0,500,7,5,5,100,100,,16,10.0,24.0,12.0,74.21706008911133
+98.86052854709044,98.90153067494637,98.71255072755024,MountainCarContinuous-v0,500,7,6,5,100,100,,16,13.0,17.0,6.0,76.32328963279724
+98.89529720214041,98.44909492777931,98.76439949506735,MountainCarContinuous-v0,500,7,7,5,100,100,,16,30.0,15.0,37.0,82.84709215164185
+98.7616118355788,98.71578750901375,98.68318096222467,MountainCarContinuous-v0,500,7,8,5,100,100,,16,14.0,22.0,30.0,70.92700576782227
+98.86443417874852,98.83006544326007,98.70059206071555,MountainCarContinuous-v0,500,7,9,5,100,100,,16,9.0,16.0,20.0,83.03400683403015
+98.8090178968243,98.66151513982264,98.67346908717008,MountainCarContinuous-v0,500,25,0,5,100,100,,16,27.0,33.0,6.0,229.263249874115
+98.81598817281183,98.85491947891296,98.87178287850683,MountainCarContinuous-v0,500,25,1,5,100,100,,16,6.0,6.0,6.0,171.71175694465637
+98.94214172465313,98.9019635347212,98.81493270596945,MountainCarContinuous-v0,500,25,2,5,100,100,,16,26.0,30.0,25.0,212.15431141853333
+98.75597826436778,98.62608394716268,98.6945082447137,MountainCarContinuous-v0,500,25,3,5,100,100,,16,6.0,53.0,6.0,292.81284523010254
+98.75834368252266,98.49769341235776,98.69540486200472,MountainCarContinuous-v0,500,25,4,5,100,100,,16,18.0,38.0,12.0,194.9914345741272
+98.7343265713061,98.94086678416951,98.71260201546164,MountainCarContinuous-v0,500,25,5,5,100,100,,16,6.0,25.0,6.0,147.96591353416443
+98.84513004428759,98.77866972572843,98.81993869781556,MountainCarContinuous-v0,500,25,6,5,100,100,,16,14.0,35.0,19.0,230.54754161834717
+98.73569203015163,98.67338953733775,98.71409289380439,MountainCarContinuous-v0,500,25,7,5,100,100,,16,6.0,6.0,6.0,165.63551664352417
+98.96534872264554,98.7806898502856,98.97088289025658,MountainCarContinuous-v0,500,25,8,5,100,100,,16,25.0,48.0,25.0,217.29856324195862
+98.8387832363336,98.76156030222879,98.79743671894947,MountainCarContinuous-v0,500,25,9,5,100,100,,16,20.0,45.0,20.0,226.59851932525635
+98.74338014066728,98.70861601739676,96.79978368654811,MountainCarContinuous-v0,500,57,0,5,100,100,,16,6.0,11.0,5.0,294.95186281204224
+98.89391465148773,98.64944066012589,98.69755669170848,MountainCarContinuous-v0,500,57,1,5,100,100,,16,36.0,47.0,52.0,474.0295433998108
+98.79177228728358,98.8069058265871,98.70021470216165,MountainCarContinuous-v0,500,57,2,5,100,100,,16,16.0,16.0,31.0,322.7195427417755
+98.96792410264491,98.90101551516385,98.73259704090196,MountainCarContinuous-v0,500,57,3,5,100,100,,16,9.0,54.0,54.0,586.5045690536499
+98.9028279493208,98.88613703191051,98.68096892179848,MountainCarContinuous-v0,500,57,4,5,100,100,,16,17.0,8.0,6.0,311.04497385025024
+98.73268894908861,98.70599334832083,98.69904680985368,MountainCarContinuous-v0,500,57,5,5,100,100,,16,6.0,12.0,6.0,298.78405261039734
+98.83034464117586,98.92622776468744,98.65558779168533,MountainCarContinuous-v0,500,57,6,5,100,100,,16,6.0,21.0,21.0,395.9035863876343
+98.88762458438487,98.72518825241073,98.71678792036066,MountainCarContinuous-v0,500,57,7,5,100,100,,16,11.0,17.0,22.0,356.68235754966736
+98.88713204730422,98.90740137412294,98.7650516702523,MountainCarContinuous-v0,500,57,8,5,100,100,,16,32.0,30.0,17.0,442.5115668773651
+98.91093770775272,98.88873114079875,98.84046208872843,MountainCarContinuous-v0,500,57,9,5,100,100,,16,14.0,14.0,14.0,373.8010456562042
+70.90448266770497,63.24278399772642,59.22099933328094,MountainCarContinuous-v0,500,0,0,10,100,100,,16,3.0,8.0,4.0,27.988595247268677
+71.24499237916723,98.69404480926433,95.46071745823272,MountainCarContinuous-v0,500,0,1,10,100,100,,16,4.0,6.0,9.0,30.16657066345215
+69.23675364640573,85.04730872072338,61.22221434275554,MountainCarContinuous-v0,500,0,2,10,100,100,,16,4.0,11.0,4.0,26.311991214752197
+69.21918387112645,96.48904374247573,65.2293614288307,MountainCarContinuous-v0,500,0,3,10,100,100,,16,4.0,6.0,8.0,29.345098972320557
+67.24053457471828,65.24758446685549,67.21473984263382,MountainCarContinuous-v0,500,0,4,10,100,100,,16,12.0,12.0,4.0,30.64752960205078
+71.22395318183165,58.9558341500235,61.23703147091268,MountainCarContinuous-v0,500,0,5,10,100,100,,16,8.0,3.0,4.0,28.318668365478516
+75.23112703727661,69.22162891551856,55.220628286952866,MountainCarContinuous-v0,500,0,6,10,100,100,,16,4.0,6.0,6.0,28.426650762557983
+81.21759348787117,63.231777151348545,67.23490583899617,MountainCarContinuous-v0,500,0,7,10,100,100,,16,4.0,34.0,29.0,51.09123635292053
+70.78834465978048,67.2246906845499,96.82678316149232,MountainCarContinuous-v0,500,0,8,10,100,100,,16,3.0,26.0,12.0,49.84318447113037
+73.2222497497592,69.20584134013252,65.23571899857026,MountainCarContinuous-v0,500,0,9,10,100,100,,16,4.0,13.0,10.0,32.302921295166016
+99.03715909884589,99.01658940689148,98.86007103187121,MountainCarContinuous-v0,500,7,0,10,100,100,,16,43.0,76.0,31.0,142.63465785980225
+98.41097892660237,98.36716884430051,98.35763030116179,MountainCarContinuous-v0,500,7,1,10,100,100,,16,23.0,35.0,32.0,97.41353297233582
+98.98076709611112,98.678976992939,98.7649874195826,MountainCarContinuous-v0,500,7,2,10,100,100,,16,33.0,25.0,19.0,88.72038745880127
+98.76798909589218,97.85638279825774,97.83556069282648,MountainCarContinuous-v0,500,7,3,10,100,100,,16,6.0,33.0,30.0,85.50951361656189
+98.88840360310347,97.90265631260907,98.89072885479682,MountainCarContinuous-v0,500,7,4,10,100,100,,16,39.0,34.0,34.0,92.55532479286194
+98.88127251664999,97.75090566758492,98.82874923751702,MountainCarContinuous-v0,500,7,5,10,100,100,,16,17.0,29.0,14.0,78.24009895324707
+98.85530606640526,98.49891552616984,98.76462975278837,MountainCarContinuous-v0,500,7,6,10,100,100,,16,16.0,20.0,16.0,65.65575051307678
+98.76077306593041,98.1906718096111,98.73481926739879,MountainCarContinuous-v0,500,7,7,10,100,100,,16,31.0,31.0,18.0,76.5910747051239
+98.73068715411209,98.64202150288533,97.51106793585367,MountainCarContinuous-v0,500,7,8,10,100,100,,16,10.0,16.0,7.0,63.90028667449951
+98.8501624408346,97.65954500447879,98.67841798630421,MountainCarContinuous-v0,500,7,9,10,100,100,,16,9.0,34.0,6.0,78.38602685928345
+98.7341262008197,98.42924249718251,98.44123086532804,MountainCarContinuous-v0,500,25,0,10,100,100,,16,6.0,37.0,23.0,190.1473400592804
+98.89944894834754,98.82034200999716,98.69150703123451,MountainCarContinuous-v0,500,25,1,10,100,100,,16,55.0,49.0,54.0,258.1635022163391
+98.84664858840783,98.73769751304977,98.6994633954559,MountainCarContinuous-v0,500,25,2,10,100,100,,16,33.0,29.0,30.0,181.15705585479736
+98.7317269177252,98.60938059344056,98.74110306930795,MountainCarContinuous-v0,500,25,3,10,100,100,,16,6.0,36.0,6.0,188.6474061012268
+98.82365926240774,98.74453534398846,98.69914670374651,MountainCarContinuous-v0,500,25,4,10,100,100,,16,17.0,35.0,15.0,225.28909635543823
+98.83718257596652,98.85728926264078,98.98987496699502,MountainCarContinuous-v0,500,25,5,10,100,100,,16,14.0,14.0,14.0,143.28201842308044
+98.74683302002867,98.52987227508618,98.69054159796104,MountainCarContinuous-v0,500,25,6,10,100,100,,16,6.0,13.0,6.0,147.95791244506836
+98.84606558756782,98.83599977338169,98.72782262017556,MountainCarContinuous-v0,500,25,7,10,100,100,,16,30.0,19.0,14.0,151.3524293899536
+98.8028561581743,98.71295887825201,98.71036192919188,MountainCarContinuous-v0,500,25,8,10,100,100,,16,14.0,34.0,26.0,225.14151000976562
+98.78677853982846,98.7530664182722,98.6917468175867,MountainCarContinuous-v0,500,25,9,10,100,100,,16,14.0,14.0,6.0,160.349125623703
+98.83788700287678,98.77779965809422,98.70747875497673,MountainCarContinuous-v0,500,57,0,10,100,100,,16,20.0,18.0,14.0,400.789972782135
+98.77946625627432,98.73750032722415,98.74841740245326,MountainCarContinuous-v0,500,57,1,10,100,100,,16,24.0,35.0,19.0,408.5616066455841
+98.96440806739264,98.82559567361882,98.80319394010647,MountainCarContinuous-v0,500,57,2,10,100,100,,16,27.0,31.0,33.0,393.68632674217224
+98.74756808415913,98.70924299961369,94.49643162138426,MountainCarContinuous-v0,500,57,3,10,100,100,,16,6.0,10.0,9.0,310.5317323207855
+98.73382767403531,98.7686681315048,98.70921642825489,MountainCarContinuous-v0,500,57,4,10,100,100,,16,9.0,23.0,6.0,402.986515045166
+98.91158085966687,98.73535041335585,98.7272152851113,MountainCarContinuous-v0,500,57,5,10,100,100,,16,35.0,39.0,25.0,458.5652949810028
+99.02036217526852,99.01825768120497,98.94545356528509,MountainCarContinuous-v0,500,57,6,10,100,100,,16,39.0,16.0,26.0,374.7511122226715
+98.92993628954635,98.8177354864726,98.94899911861577,MountainCarContinuous-v0,500,57,7,10,100,100,,16,8.0,20.0,8.0,381.87264466285706
+98.93280553843987,98.86618770639501,98.69017832378181,MountainCarContinuous-v0,500,57,8,10,100,100,,16,22.0,26.0,32.0,401.03144693374634
+98.93419756366674,98.680564361589,98.70022481271532,MountainCarContinuous-v0,500,57,9,10,100,100,,16,8.0,40.0,10.0,478.70466232299805
diff --git a/experiments/bench/env/data/easimple-mountaincar.csv b/experiments/bench/env/data/easimple-mountaincar.csv
new file mode 100644
index 0000000000000000000000000000000000000000..e6edc54e6e7ce4fc2d7dc4eddeb40fd06cd2c9a1
--- /dev/null
+++ b/experiments/bench/env/data/easimple-mountaincar.csv
@@ -0,0 +1,41 @@
+best_pop,best_hof,best_arm,env,n_step,num_episode,run_number,UCB_sigma,ngen,mu,lambda,n_thread,complexity_pop,complexity_hof,complexity_arm,time
+97.44832590314304,72.60452666579586,,MountainCarContinuous-v0,500,1,0,,100,,,16,7.0,3.0,,47.972792625427246
+-1.6665320613947943e-39,67.23399135964894,,MountainCarContinuous-v0,500,1,1,,100,,,16,26.0,4.0,,58.26824140548706
+63.214762393244904,41.25197838110228,,MountainCarContinuous-v0,500,1,2,,100,,,16,10.0,4.0,,55.386287450790405
+53.139431749442814,79.2364848057828,,MountainCarContinuous-v0,500,1,3,,100,,,16,7.0,8.0,,61.55098509788513
+88.0436746409211,68.72525908257586,,MountainCarContinuous-v0,500,1,4,,100,,,16,32.0,3.0,,55.960163831710815
+94.25802597660373,57.228628802102556,,MountainCarContinuous-v0,500,1,5,,100,,,16,19.0,4.0,,57.6178719997406
+93.27028022696146,68.76958342903947,,MountainCarContinuous-v0,500,1,6,,100,,,16,6.0,3.0,,51.0644211769104
+67.98507240469507,78.67518456802372,,MountainCarContinuous-v0,500,1,7,,100,,,16,10.0,3.0,,55.12784242630005
+81.53160992701761,64.87608883595222,,MountainCarContinuous-v0,500,1,8,,100,,,16,15.0,3.0,,53.8493070602417
+65.23348575010577,67.21257833960574,,MountainCarContinuous-v0,500,1,9,,100,,,16,4.0,8.0,,51.95567870140076
+63.21809589668614,78.60992830279596,,MountainCarContinuous-v0,500,2,0,,100,,,16,4.0,3.0,,101.64212465286255
+0.0,51.11421273923466,,MountainCarContinuous-v0,500,2,1,,100,,,16,3.0,3.0,,105.23664331436157
+95.11582020502954,74.716868842859,,MountainCarContinuous-v0,500,2,2,,100,,,16,19.0,3.0,,90.19597172737122
+85.57195180582781,57.2232724107686,,MountainCarContinuous-v0,500,2,3,,100,,,16,29.0,4.0,,89.56645917892456
+63.44857217268694,63.20912465025853,,MountainCarContinuous-v0,500,2,4,,100,,,16,8.0,4.0,,86.94392538070679
+98.69822137549176,45.223013489710226,,MountainCarContinuous-v0,500,2,5,,100,,,16,6.0,4.0,,100.87071132659912
+51.23278533492742,59.20896729730024,,MountainCarContinuous-v0,500,2,6,,100,,,16,4.0,4.0,,84.00480461120605
+97.53082951664537,57.236291856217996,,MountainCarContinuous-v0,500,2,7,,100,,,16,10.0,4.0,,108.4891505241394
+90.8432207589931,5.7542802902852905,,MountainCarContinuous-v0,500,2,8,,100,,,16,8.0,3.0,,114.82001733779907
+85.05111152245425,59.21549796154786,,MountainCarContinuous-v0,500,2,9,,100,,,16,14.0,4.0,,84.56748175621033
+91.85073537005772,59.24638412523278,,MountainCarContinuous-v0,500,5,0,,100,,,16,19.0,4.0,,199.06508779525757
+55.23145132959729,66.72112108710004,,MountainCarContinuous-v0,500,5,1,,100,,,16,8.0,3.0,,229.06081008911133
+63.21272155444091,69.23307515729775,,MountainCarContinuous-v0,500,5,2,,100,,,16,12.0,8.0,,182.41887831687927
+98.18866800112438,72.6120102364192,,MountainCarContinuous-v0,500,5,3,,100,,,16,17.0,3.0,,207.27172088623047
+97.184912761048,57.214836955287794,,MountainCarContinuous-v0,500,5,4,,100,,,16,28.0,4.0,,217.80593967437744
+61.19583656506087,66.89442891755871,,MountainCarContinuous-v0,500,5,5,,100,,,16,4.0,3.0,,249.42358708381653
+15.617864694374429,82.98616610429202,,MountainCarContinuous-v0,500,5,6,,100,,,16,3.0,6.0,,190.53744745254517
+63.245220618723735,82.47479246444227,,MountainCarContinuous-v0,500,5,7,,100,,,16,4.0,3.0,,179.60723519325256
+98.67127332724338,67.22269910743242,,MountainCarContinuous-v0,500,5,8,,100,,,16,18.0,4.0,,205.9422106742859
+98.66678742433494,75.2039491745162,,MountainCarContinuous-v0,500,5,9,,100,,,16,10.0,4.0,,176.50460124015808
+23.55684495707335,98.67452007620969,,MountainCarContinuous-v0,500,10,0,,100,,,16,7.0,6.0,,386.1846158504486
+61.221291670903504,53.19775463957987,,MountainCarContinuous-v0,500,10,1,,100,,,16,4.0,4.0,,371.18853521347046
+92.99160827348842,98.67546156807963,,MountainCarContinuous-v0,500,10,2,,100,,,16,16.0,6.0,,407.9270701408386
+89.87349253807196,83.00594318227571,,MountainCarContinuous-v0,500,10,3,,100,,,16,24.0,6.0,,370.84945845603943
+97.47398015620774,94.96882241135282,,MountainCarContinuous-v0,500,10,4,,100,,,16,7.0,6.0,,384.70016956329346
+97.40290657181339,88.24470028122303,,MountainCarContinuous-v0,500,10,5,,100,,,16,8.0,3.0,,402.5732262134552
+97.50728823096985,70.87132818108523,,MountainCarContinuous-v0,500,10,6,,100,,,16,11.0,3.0,,347.78934478759766
+97.2106173290883,98.36940042177815,,MountainCarContinuous-v0,500,10,7,,100,,,16,17.0,6.0,,357.0341167449951
+76.42546269753,96.92919905027053,,MountainCarContinuous-v0,500,10,8,,100,,,16,11.0,29.0,,356.57151460647583
+93.36477526784967,79.00240263050814,,MountainCarContinuous-v0,500,10,9,,100,,,16,33.0,6.0,,371.14211082458496
diff --git a/experiments/bench/env/data/mu+lambda-mountaincar.csv b/experiments/bench/env/data/mu+lambda-mountaincar.csv
new file mode 100644
index 0000000000000000000000000000000000000000..3ef7e397140a24d92614647926a366a71a656c3e
--- /dev/null
+++ b/experiments/bench/env/data/mu+lambda-mountaincar.csv
@@ -0,0 +1,41 @@
+best_pop,best_hof,best_arm,env,n_step,num_episode,run_number,UCB_sigma,ngen,mu,lambda,n_thread,complexity_pop,complexity_hof,complexity_arm,time
+69.23373508421133,9.776646774573182,,MountainCarContinuous-v0,500,1,0,,100,100,,16,4.0,3.0,,22.011539936065674
+69.21711347093068,1.7768966436140072,,MountainCarContinuous-v0,500,1,1,,100,100,,16,4.0,3.0,,23.60527014732361
+77.2085383539554,9.72430173334077,,MountainCarContinuous-v0,500,1,2,,100,100,,16,4.0,3.0,,23.677063465118408
+71.21531994083942,13.741693992670696,,MountainCarContinuous-v0,500,1,3,,100,100,,16,4.0,9.0,,24.418054342269897
+73.21930576087307,5.794305209556147,,MountainCarContinuous-v0,500,1,4,,100,100,,16,4.0,5.0,,22.95009207725525
+71.23655256680917,13.73527752161377,,MountainCarContinuous-v0,500,1,5,,100,100,,16,8.0,3.0,,24.167996168136597
+97.56654741725589,3.7789022229890357,,MountainCarContinuous-v0,500,1,6,,100,100,,16,7.0,3.0,,33.19070219993591
+75.22024738471059,9.706621664639963,,MountainCarContinuous-v0,500,1,7,,100,100,,16,4.0,3.0,,26.245072841644287
+73.22048525686358,7.776411859374028,,MountainCarContinuous-v0,500,1,8,,100,100,,16,4.0,3.0,,26.474632263183594
+69.19351846460319,11.691423163404561,,MountainCarContinuous-v0,500,1,9,,100,100,,16,4.0,3.0,,27.56999659538269
+73.20620505666086,63.22125097049255,,MountainCarContinuous-v0,500,2,0,,100,100,,16,8.0,8.0,,46.75613784790039
+73.22631183020152,57.22527082475982,,MountainCarContinuous-v0,500,2,1,,100,100,,16,4.0,4.0,,39.734620809555054
+73.2255288712226,57.218249015285394,,MountainCarContinuous-v0,500,2,2,,100,100,,16,33.0,23.0,,77.34960699081421
+72.76977821059913,59.22393303410319,,MountainCarContinuous-v0,500,2,3,,100,100,,16,3.0,8.0,,47.21554923057556
+84.30332786108661,67.23340186660505,,MountainCarContinuous-v0,500,2,4,,100,100,,16,3.0,18.0,,59.82014775276184
+79.21522373319031,75.22783162120597,,MountainCarContinuous-v0,500,2,5,,100,100,,16,4.0,4.0,,42.33665728569031
+93.90439098069132,53.256181154175735,,MountainCarContinuous-v0,500,2,6,,100,100,,16,3.0,4.0,,36.53817868232727
+71.20109696218493,55.24751697713172,,MountainCarContinuous-v0,500,2,7,,100,100,,16,10.0,4.0,,44.695587158203125
+72.86632416723577,69.20567469824421,,MountainCarContinuous-v0,500,2,8,,100,100,,16,3.0,4.0,,41.4212532043457
+76.57796479189342,65.23827005356603,,MountainCarContinuous-v0,500,2,9,,100,100,,16,3.0,8.0,,43.14051294326782
+80.53424921851547,68.62684447849333,,MountainCarContinuous-v0,500,5,0,,100,100,,16,3.0,3.0,,86.63547849655151
+76.82364816523092,64.80687113083148,,MountainCarContinuous-v0,500,5,1,,100,100,,16,3.0,3.0,,85.64211463928223
+91.97288807888759,79.21571514426502,,MountainCarContinuous-v0,500,5,2,,100,100,,16,3.0,4.0,,93.30192613601685
+85.06814361125473,59.21017255346039,,MountainCarContinuous-v0,500,5,3,,100,100,,16,8.0,4.0,,105.22844386100769
+86.24167461415259,70.82126589966317,,MountainCarContinuous-v0,500,5,4,,100,100,,16,3.0,3.0,,88.84379482269287
+88.29706267435496,61.20598191314643,,MountainCarContinuous-v0,500,5,5,,100,100,,16,3.0,4.0,,88.38264465332031
+92.99559768989705,66.66558770753831,,MountainCarContinuous-v0,500,5,6,,100,100,,16,6.0,3.0,,80.14226245880127
+76.67330771298269,60.83799426412711,,MountainCarContinuous-v0,500,5,7,,100,100,,16,3.0,3.0,,134.47545862197876
+89.98004554072396,63.240923613723155,,MountainCarContinuous-v0,500,5,8,,100,100,,16,3.0,4.0,,105.3435754776001
+78.62794179718014,67.22142272314184,,MountainCarContinuous-v0,500,5,9,,100,100,,16,3.0,4.0,,91.14647245407104
+99.04974415005277,98.65587132314771,,MountainCarContinuous-v0,500,10,0,,100,100,,16,9.0,6.0,,212.8638153076172
+96.06896640435596,67.14166778631032,,MountainCarContinuous-v0,500,10,1,,100,100,,16,3.0,6.0,,155.63527870178223
+99.059543611822,98.6977756088864,,MountainCarContinuous-v0,500,10,2,,100,100,,16,9.0,6.0,,203.48708629608154
+98.8618218023085,86.22496101406853,,MountainCarContinuous-v0,500,10,3,,100,100,,16,14.0,3.0,,281.1963424682617
+95.04429919751121,68.65765471705348,,MountainCarContinuous-v0,500,10,4,,100,100,,16,6.0,3.0,,167.70896124839783
+98.93992384277861,63.227314980255294,,MountainCarContinuous-v0,500,10,5,,100,100,,16,13.0,12.0,,187.128643989563
+98.81207941181802,74.62462332996556,,MountainCarContinuous-v0,500,10,6,,100,100,,16,8.0,3.0,,178.3403434753418
+98.74183790583618,89.85595994050198,,MountainCarContinuous-v0,500,10,7,,100,100,,16,6.0,3.0,,173.8602635860443
+98.95525460371059,62.95487970937899,,MountainCarContinuous-v0,500,10,8,,100,100,,16,6.0,3.0,,164.93298316001892
+98.90844021106732,45.069554352453196,,MountainCarContinuous-v0,500,10,9,,100,100,,16,22.0,3.0,,186.94894456863403
diff --git a/experiments/bench/env/easimple.yml b/experiments/bench/env/easimple.yml
new file mode 100644
index 0000000000000000000000000000000000000000..ad56765dfb34489a30b80ad659bae41a00aa6288
--- /dev/null
+++ b/experiments/bench/env/easimple.yml
@@ -0,0 +1,22 @@
+algorithm:
+ name: algorithms.eaSimple
+ n_thread: 16
+ args:
+ ngen: 100
+ cxpb: 0.5
+ mutpb: 0.2
+ verbose: False
+
+population:
+ init_size: 100
+ selection: selTournament
+ args:
+ tournsize: 3
+
+problem:
+ name: "gym"
+ env: "Pendulum-v0|MountainCarContinuous-v0"
+ n_evals: 1
+ nb_runs: 25
+
+seed: 42
diff --git a/experiments/bench/oneMax/conf/easimple-pop=100-n_evals.yml b/experiments/bench/oneMax/conf/easimple-pop=100-n_evals.yml
new file mode 100644
index 0000000000000000000000000000000000000000..89699206036bb2022eb83c9001f2b69386a0b3be
--- /dev/null
+++ b/experiments/bench/oneMax/conf/easimple-pop=100-n_evals.yml
@@ -0,0 +1,23 @@
+algorithm:
+ name: algorithms.eaSimple
+ n_thread: 16
+ args:
+ ngen: [100, 200, 400, 800]
+ cxpb: 0.5
+ mutpb: 0.2
+ verbose: False
+
+population:
+ init_size: 100
+ selection: selTournament
+ args:
+ tournsize: 3
+
+problem:
+ name: "oneMax"
+ dims: [6, 7, 8, 9]
+ std: [0.0, 0.01, 0.1, 0.2]
+ n_eval: [1, 2, 5, 10]
+ nb_runs: 25
+
+seed: 42
diff --git a/experiments/bench/oneMax/conf/easimple-pop=100.yml b/experiments/bench/oneMax/conf/easimple-pop=100.yml
new file mode 100644
index 0000000000000000000000000000000000000000..e4a2780c70857388b184be2d11897364e53ffa15
--- /dev/null
+++ b/experiments/bench/oneMax/conf/easimple-pop=100.yml
@@ -0,0 +1,23 @@
+algorithm:
+ name: algorithms.eaSimple
+ n_thread: 16
+ args:
+ ngen: [100, 200, 400, 800]
+ cxpb: 0.5
+ mutpb: 0.2
+ verbose: False
+
+population:
+ init_size: 100
+ selection: selTournament
+ args:
+ tournsize: 3
+
+problem:
+ name: "oneMax"
+ dims: [6, 7, 8, 9]
+ std: [0.0, 0.01, 0.1, 0.2]
+ n_eval: [1]
+ nb_runs: 25
+
+seed: 42
diff --git a/experiments/bench/oneMax/conf/easimple-pop=1000.yml b/experiments/bench/oneMax/conf/easimple-pop=1000.yml
new file mode 100644
index 0000000000000000000000000000000000000000..f6847827b05ccc9224751c399069a3e8d4211db7
--- /dev/null
+++ b/experiments/bench/oneMax/conf/easimple-pop=1000.yml
@@ -0,0 +1,23 @@
+algorithm:
+ name: algorithms.eaSimple
+ n_thread: 16
+ args:
+ ngen: [100, 200, 400, 800]
+ cxpb: 0.5
+ mutpb: 0.2
+ verbose: False
+
+population:
+ init_size: 1000
+ selection: selTournament
+ args:
+ tournsize: 3
+
+problem:
+ name: "oneMax"
+ dims: [6, 7, 8, 9]
+ std: [0.0, 0.01, 0.1, 0.2]
+ n_eval: [1]
+ nb_runs: 25
+
+seed: 42
diff --git a/experiments/bench/oneMax/conf/mu+lambda-pop=100.yml b/experiments/bench/oneMax/conf/mu+lambda-pop=100.yml
new file mode 100644
index 0000000000000000000000000000000000000000..58155c60cc3c8e1a8b7c80f44ef72f28756498d3
--- /dev/null
+++ b/experiments/bench/oneMax/conf/mu+lambda-pop=100.yml
@@ -0,0 +1,25 @@
+algorithm:
+ name: algorithms.eaMuPlusLambda
+ n_thread: 16
+ args:
+ ngen: [100, 200, 400, 800]
+ cxpb: 0.65
+ mutpb: 0.35
+ mu: 100
+ lambda_: 100
+ verbose: False
+
+population:
+ init_size: 100
+ selection: selTournament
+ args:
+ tournsize: 3
+
+problem:
+ name: "oneMax"
+ dims: [6, 7, 8, 9]
+ std: [0.0, 0.01, 0.1, 0.2]
+ n_eval: [1, 2, 5, 10]
+ nb_runs: 25
+
+seed: 42
diff --git a/experiments/bench/oneMax/conf/mu+lambda-pop=1000.yml b/experiments/bench/oneMax/conf/mu+lambda-pop=1000.yml
new file mode 100644
index 0000000000000000000000000000000000000000..2a2ecac397e677cc958552e41c2b5993068bffd7
--- /dev/null
+++ b/experiments/bench/oneMax/conf/mu+lambda-pop=1000.yml
@@ -0,0 +1,25 @@
+algorithm:
+ name: algorithms.eaMuPlusLambda
+ n_thread: 16
+ args:
+ ngen: [100, 200, 400, 800]
+ cxpb: 0.65
+ mutpb: 0.35
+ mu: 1000
+ lambda_: 1000
+ verbose: False
+
+population:
+ init_size: 100
+ selection: selTournament
+ args:
+ tournsize: 3
+
+problem:
+ name: "oneMax"
+ dims: [6, 7, 8, 9]
+ std: [0.0, 0.01, 0.1, 0.2]
+ n_eval: [1]
+ nb_runs: 25
+
+seed: 42
diff --git a/experiments/bench/oneMax/conf/mu+lambdaUCB-pop=100-n_evals-buget=0.yml b/experiments/bench/oneMax/conf/mu+lambdaUCB-pop=100-n_evals-buget=0.yml
new file mode 100644
index 0000000000000000000000000000000000000000..9c7e33c4a968d0b943744c60012cd682ec96d89d
--- /dev/null
+++ b/experiments/bench/oneMax/conf/mu+lambdaUCB-pop=100-n_evals-buget=0.yml
@@ -0,0 +1,29 @@
+algorithm:
+ name: eaMuPlusLambdaUCB
+ n_thread: 16
+ args:
+ ngen: [100, 200, 400, 800]
+ cxpb: 0.65
+ mutpb: 0.35
+ mu: 100
+ lambda_: 100
+ simulation_budget: [0] #[100/16, 400/16, 900/16]
+ parallel_update: 16
+ verbose: False
+
+population:
+ init_size: 100
+ selection: selUCBDoubleTounament #selTournament
+ args:
+ #tournsize: 3
+ fitness_size: 3
+ parsimony_size: 1.0
+
+problem:
+ name: "oneMax"
+ dims: [6, 7, 8, 9]
+ std: [0.01, 0.1, 0.2]
+ n_eval: [1]
+ nb_runs: 25
+
+seed: 42
diff --git a/experiments/bench/oneMax/conf/mu+lambdaUCB-pop=100-n_evals.yml b/experiments/bench/oneMax/conf/mu+lambdaUCB-pop=100-n_evals.yml
new file mode 100644
index 0000000000000000000000000000000000000000..94049e86ca613e3f64b709de5252ce64f291403d
--- /dev/null
+++ b/experiments/bench/oneMax/conf/mu+lambdaUCB-pop=100-n_evals.yml
@@ -0,0 +1,29 @@
+algorithm:
+ name: eaMuPlusLambdaUCB
+ n_thread: 16
+ args:
+ ngen: [100, 200, 400, 800]
+ cxpb: 0.65
+ mutpb: 0.35
+ mu: 100
+ lambda_: 100
+ simulation_budget: [7, 25, 57]
+ parallel_update: 16
+ verbose: False
+
+population:
+ init_size: 100
+ selection: selUCBDoubleTounament #selTournament
+ args:
+ #tournsize: 3
+ fitness_size: 3
+ parsimony_size: 0.75
+
+problem:
+ name: "oneMax"
+ dims: [6, 7, 8, 9]
+ std: [0.01, 0.1, 0.2]
+ n_eval: [1]
+ nb_runs: 25
+
+seed: 42
diff --git a/experiments/bench/oneMax/data/easimple-pop=100-n_evals.csv b/experiments/bench/oneMax/data/easimple-pop=100-n_evals.csv
new file mode 100644
index 0000000000000000000000000000000000000000..86e115de6673a1411da3540794948e3979e2e652
--- /dev/null
+++ b/experiments/bench/oneMax/data/easimple-pop=100-n_evals.csv
@@ -0,0 +1,1601 @@
+,best_pop,best_hof,best_arm,std,dim,n_eval,run_number,UCB_sigma,ngen,mu,lambda,n_thread,time
+0,1.0,1.0,,0.0,6,1,0,,100,,,16,3.5939950942993164
+1,1.0,1.0,,0.0,6,1,1,,100,,,16,3.55764102935791
+2,1.0,1.0,,0.0,6,1,2,,100,,,16,3.6715714931488037
+3,1.0,1.0,,0.0,6,1,3,,100,,,16,4.331178665161133
+4,1.0,1.0,,0.0,6,1,4,,100,,,16,3.7390027046203613
+5,1.0,1.0,,0.0,6,1,5,,100,,,16,3.611298084259033
+6,1.0,1.0,,0.0,6,1,6,,100,,,16,3.5280065536499023
+7,1.0,1.0,,0.0,6,1,7,,100,,,16,3.6220245361328125
+8,1.0,1.0,,0.0,6,1,8,,100,,,16,3.688995838165283
+9,1.0,1.0,,0.0,6,1,9,,100,,,16,3.576540231704712
+10,1.0,1.0,,0.0,6,1,10,,100,,,16,3.554006338119507
+11,1.0,1.0,,0.0,6,1,11,,100,,,16,3.5710108280181885
+12,1.0,1.0,,0.0,6,1,12,,100,,,16,3.6480019092559814
+13,1.0,1.0,,0.0,6,1,13,,100,,,16,3.4949896335601807
+14,1.0,1.0,,0.0,6,1,14,,100,,,16,3.4659934043884277
+15,1.0,1.0,,0.0,6,1,15,,100,,,16,3.4662656784057617
+16,1.0,1.0,,0.0,6,1,16,,100,,,16,3.53098726272583
+17,1.0,1.0,,0.0,6,1,17,,100,,,16,3.5446603298187256
+18,1.0,1.0,,0.0,6,1,18,,100,,,16,3.6750056743621826
+19,1.0,1.0,,0.0,6,1,19,,100,,,16,3.571000337600708
+20,1.0,1.0,,0.0,6,1,20,,100,,,16,3.6359827518463135
+21,1.0,1.0,,0.0,6,1,21,,100,,,16,3.8520050048828125
+22,1.0,1.0,,0.0,6,1,22,,100,,,16,3.736022710800171
+23,1.0,1.0,,0.0,6,1,23,,100,,,16,3.588015079498291
+24,1.0,1.0,,0.0,6,1,24,,100,,,16,3.4979968070983887
+25,0.9921875,0.9921875,,0.0,7,1,0,,200,,,16,5.264633655548096
+26,0.9921875,0.9921875,,0.0,7,1,1,,200,,,16,5.221013069152832
+27,0.9765625,0.984375,,0.0,7,1,2,,200,,,16,5.185742616653442
+28,0.9921875,0.9921875,,0.0,7,1,3,,200,,,16,5.147996187210083
+29,0.9921875,0.9921875,,0.0,7,1,4,,200,,,16,5.168007135391235
+30,0.984375,0.984375,,0.0,7,1,5,,200,,,16,5.155004024505615
+31,1.0,1.0,,0.0,7,1,6,,200,,,16,5.236385822296143
+32,1.0,1.0,,0.0,7,1,7,,200,,,16,5.172990322113037
+33,0.9921875,0.9921875,,0.0,7,1,8,,200,,,16,5.142988681793213
+34,0.984375,0.984375,,0.0,7,1,9,,200,,,16,5.101004362106323
+35,1.0,1.0,,0.0,7,1,10,,200,,,16,5.189334154129028
+36,0.984375,0.984375,,0.0,7,1,11,,200,,,16,5.128244876861572
+37,0.9921875,0.9921875,,0.0,7,1,12,,200,,,16,5.310995578765869
+38,0.96875,0.96875,,0.0,7,1,13,,200,,,16,5.24201512336731
+39,0.9921875,0.9921875,,0.0,7,1,14,,200,,,16,5.182563543319702
+40,0.984375,0.984375,,0.0,7,1,15,,200,,,16,5.144992828369141
+41,0.984375,0.984375,,0.0,7,1,16,,200,,,16,5.312995672225952
+42,0.9765625,0.984375,,0.0,7,1,17,,200,,,16,5.1311354637146
+43,1.0,1.0,,0.0,7,1,18,,200,,,16,5.339013338088989
+44,0.9921875,0.9921875,,0.0,7,1,19,,200,,,16,5.221023797988892
+45,0.9765625,0.9765625,,0.0,7,1,20,,200,,,16,5.319993495941162
+46,0.984375,0.984375,,0.0,7,1,21,,200,,,16,5.334997653961182
+47,0.984375,0.984375,,0.0,7,1,22,,200,,,16,5.753476142883301
+48,0.984375,0.984375,,0.0,7,1,23,,200,,,16,5.286027193069458
+49,0.984375,0.984375,,0.0,7,1,24,,200,,,16,5.421004772186279
+50,0.94140625,0.94140625,,0.0,8,1,0,,400,,,16,10.563998937606812
+51,0.9375,0.9375,,0.0,8,1,1,,400,,,16,10.599129915237427
+52,0.9296875,0.9296875,,0.0,8,1,2,,400,,,16,10.513018369674683
+53,0.92578125,0.92578125,,0.0,8,1,3,,400,,,16,10.479025840759277
+54,0.91015625,0.91015625,,0.0,8,1,4,,400,,,16,10.540561437606812
+55,0.94140625,0.94140625,,0.0,8,1,5,,400,,,16,10.610530376434326
+56,0.92578125,0.92578125,,0.0,8,1,6,,400,,,16,10.48002314567566
+57,0.921875,0.921875,,0.0,8,1,7,,400,,,16,10.472128629684448
+58,0.9375,0.94140625,,0.0,8,1,8,,400,,,16,10.534027338027954
+59,0.9375,0.9375,,0.0,8,1,9,,400,,,16,10.515436172485352
+60,0.9296875,0.9296875,,0.0,8,1,10,,400,,,16,10.485190391540527
+61,0.94140625,0.94140625,,0.0,8,1,11,,400,,,16,10.584991216659546
+62,0.92578125,0.93359375,,0.0,8,1,12,,400,,,16,10.441001176834106
+63,0.9453125,0.9453125,,0.0,8,1,13,,400,,,16,10.592207908630371
+64,0.9375,0.9375,,0.0,8,1,14,,400,,,16,10.535990476608276
+65,0.9375,0.9375,,0.0,8,1,15,,400,,,16,10.715257406234741
+66,0.94140625,0.94140625,,0.0,8,1,16,,400,,,16,10.448989868164062
+67,0.93359375,0.93359375,,0.0,8,1,17,,400,,,16,10.536112546920776
+68,0.9453125,0.9453125,,0.0,8,1,18,,400,,,16,10.463780403137207
+69,0.9296875,0.9296875,,0.0,8,1,19,,400,,,16,10.518012285232544
+70,0.9375,0.9375,,0.0,8,1,20,,400,,,16,10.479022741317749
+71,0.93359375,0.93359375,,0.0,8,1,21,,400,,,16,10.53666877746582
+72,0.921875,0.921875,,0.0,8,1,22,,400,,,16,10.420018434524536
+73,0.9296875,0.9296875,,0.0,8,1,23,,400,,,16,10.532020330429077
+74,0.9296875,0.9296875,,0.0,8,1,24,,400,,,16,10.574517965316772
+75,0.875,0.875,,0.0,9,1,0,,800,,,16,29.394367456436157
+76,0.865234375,0.865234375,,0.0,9,1,1,,800,,,16,29.173154830932617
+77,0.869140625,0.869140625,,0.0,9,1,2,,800,,,16,29.44241738319397
+78,0.853515625,0.853515625,,0.0,9,1,3,,800,,,16,29.039673566818237
+79,0.86328125,0.86328125,,0.0,9,1,4,,800,,,16,29.264853954315186
+80,0.861328125,0.861328125,,0.0,9,1,5,,800,,,16,29.30986785888672
+81,0.87109375,0.87109375,,0.0,9,1,6,,800,,,16,29.28273844718933
+82,0.880859375,0.880859375,,0.0,9,1,7,,800,,,16,29.061137914657593
+83,0.859375,0.859375,,0.0,9,1,8,,800,,,16,29.228630781173706
+84,0.861328125,0.861328125,,0.0,9,1,9,,800,,,16,28.88874650001526
+85,0.87109375,0.87109375,,0.0,9,1,10,,800,,,16,29.063357830047607
+86,0.865234375,0.865234375,,0.0,9,1,11,,800,,,16,29.02619433403015
+87,0.8671875,0.8671875,,0.0,9,1,12,,800,,,16,29.176979064941406
+88,0.8671875,0.8671875,,0.0,9,1,13,,800,,,16,29.129068851470947
+89,0.873046875,0.875,,0.0,9,1,14,,800,,,16,29.299342393875122
+90,0.884765625,0.884765625,,0.0,9,1,15,,800,,,16,28.992002964019775
+91,0.875,0.875,,0.0,9,1,16,,800,,,16,29.446760177612305
+92,0.875,0.875,,0.0,9,1,17,,800,,,16,29.03170871734619
+93,0.8828125,0.8828125,,0.0,9,1,18,,800,,,16,29.08052396774292
+94,0.873046875,0.873046875,,0.0,9,1,19,,800,,,16,28.9830961227417
+95,0.84765625,0.84765625,,0.0,9,1,20,,800,,,16,30.133849143981934
+96,0.88671875,0.88671875,,0.0,9,1,21,,800,,,16,28.985820770263672
+97,0.8515625,0.8515625,,0.0,9,1,22,,800,,,16,29.25120973587036
+98,0.853515625,0.853515625,,0.0,9,1,23,,800,,,16,29.219417095184326
+99,0.861328125,0.86328125,,0.0,9,1,24,,800,,,16,29.013487339019775
+100,1.0,1.0,,0.01,6,1,0,,100,,,16,3.44399094581604
+101,0.984375,1.0,,0.01,6,1,1,,100,,,16,3.4339990615844727
+102,1.0,1.0,,0.01,6,1,2,,100,,,16,3.539984703063965
+103,1.0,1.0,,0.01,6,1,3,,100,,,16,3.457148790359497
+104,1.0,1.0,,0.01,6,1,4,,100,,,16,3.4369897842407227
+105,1.0,1.0,,0.01,6,1,5,,100,,,16,3.4730350971221924
+106,1.0,1.0,,0.01,6,1,6,,100,,,16,3.4719924926757812
+107,1.0,1.0,,0.01,6,1,7,,100,,,16,3.6589972972869873
+108,1.0,1.0,,0.01,6,1,8,,100,,,16,3.4600088596343994
+109,1.0,1.0,,0.01,6,1,9,,100,,,16,3.498011350631714
+110,1.0,1.0,,0.01,6,1,10,,100,,,16,3.502018451690674
+111,1.0,1.0,,0.01,6,1,11,,100,,,16,3.589592456817627
+112,1.0,1.0,,0.01,6,1,12,,100,,,16,3.45171856880188
+113,1.0,1.0,,0.01,6,1,13,,100,,,16,3.4860188961029053
+114,1.0,1.0,,0.01,6,1,14,,100,,,16,3.488011598587036
+115,1.0,1.0,,0.01,6,1,15,,100,,,16,3.6050164699554443
+116,0.984375,1.0,,0.01,6,1,16,,100,,,16,3.4789958000183105
+117,1.0,1.0,,0.01,6,1,17,,100,,,16,3.495023488998413
+118,1.0,1.0,,0.01,6,1,18,,100,,,16,3.461021900177002
+119,1.0,1.0,,0.01,6,1,19,,100,,,16,3.515993595123291
+120,1.0,1.0,,0.01,6,1,20,,100,,,16,3.578659772872925
+121,1.0,1.0,,0.01,6,1,21,,100,,,16,3.505013942718506
+122,1.0,1.0,,0.01,6,1,22,,100,,,16,3.4819910526275635
+123,1.0,1.0,,0.01,6,1,23,,100,,,16,3.4700186252593994
+124,1.0,1.0,,0.01,6,1,24,,100,,,16,3.525986671447754
+125,0.9296875,0.9296875,,0.01,7,1,0,,200,,,16,5.182991981506348
+126,0.9609375,0.96875,,0.01,7,1,1,,200,,,16,5.131999492645264
+127,0.9765625,0.9765625,,0.01,7,1,2,,200,,,16,5.101903915405273
+128,0.9453125,0.953125,,0.01,7,1,3,,200,,,16,5.111018896102905
+129,0.921875,0.9296875,,0.01,7,1,4,,200,,,16,5.119308233261108
+130,0.9609375,0.9609375,,0.01,7,1,5,,200,,,16,5.133042573928833
+131,0.9453125,0.9453125,,0.01,7,1,6,,200,,,16,5.112083911895752
+132,0.9765625,0.9765625,,0.01,7,1,7,,200,,,16,5.0989930629730225
+133,0.96875,0.9765625,,0.01,7,1,8,,200,,,16,5.152666091918945
+134,0.953125,0.9609375,,0.01,7,1,9,,200,,,16,5.128021001815796
+135,0.9375,0.953125,,0.01,7,1,10,,200,,,16,5.116467237472534
+136,0.9453125,0.953125,,0.01,7,1,11,,200,,,16,5.068989038467407
+137,0.9453125,0.953125,,0.01,7,1,12,,200,,,16,5.217989921569824
+138,0.9296875,0.9375,,0.01,7,1,13,,200,,,16,5.107642889022827
+139,0.9296875,0.9296875,,0.01,7,1,14,,200,,,16,5.128357410430908
+140,0.96875,0.96875,,0.01,7,1,15,,200,,,16,5.2000062465667725
+141,0.9453125,0.9453125,,0.01,7,1,16,,200,,,16,5.164013147354126
+142,0.953125,0.9609375,,0.01,7,1,17,,200,,,16,5.112022638320923
+143,0.9609375,0.9765625,,0.01,7,1,18,,200,,,16,5.254020929336548
+144,0.96875,0.9765625,,0.01,7,1,19,,200,,,16,5.098048210144043
+145,0.9453125,0.953125,,0.01,7,1,20,,200,,,16,5.143029451370239
+146,0.96875,0.9609375,,0.01,7,1,21,,200,,,16,5.232011079788208
+147,0.96875,0.96875,,0.01,7,1,22,,200,,,16,5.10802149772644
+148,0.984375,0.984375,,0.01,7,1,23,,200,,,16,5.116028785705566
+149,0.9375,0.9453125,,0.01,7,1,24,,200,,,16,5.270989894866943
+150,0.84765625,0.859375,,0.01,8,1,0,,400,,,16,10.474096298217773
+151,0.87109375,0.875,,0.01,8,1,1,,400,,,16,10.580392599105835
+152,0.84765625,0.86328125,,0.01,8,1,2,,400,,,16,10.37899923324585
+153,0.87109375,0.875,,0.01,8,1,3,,400,,,16,10.544758081436157
+154,0.88671875,0.890625,,0.01,8,1,4,,400,,,16,10.537380695343018
+155,0.8671875,0.8671875,,0.01,8,1,5,,400,,,16,10.461849212646484
+156,0.85546875,0.86328125,,0.01,8,1,6,,400,,,16,10.396737813949585
+157,0.86328125,0.8671875,,0.01,8,1,7,,400,,,16,10.638020038604736
+158,0.875,0.87890625,,0.01,8,1,8,,400,,,16,10.403590202331543
+159,0.875,0.875,,0.01,8,1,9,,400,,,16,10.470147371292114
+160,0.86328125,0.86328125,,0.01,8,1,10,,400,,,16,10.456992387771606
+161,0.84765625,0.85546875,,0.01,8,1,11,,400,,,16,10.46611213684082
+162,0.85546875,0.859375,,0.01,8,1,12,,400,,,16,10.446013450622559
+163,0.859375,0.875,,0.01,8,1,13,,400,,,16,10.522253036499023
+164,0.8515625,0.85546875,,0.01,8,1,14,,400,,,16,10.407543897628784
+165,0.8359375,0.84375,,0.01,8,1,15,,400,,,16,10.495137929916382
+166,0.87109375,0.875,,0.01,8,1,16,,400,,,16,10.459007978439331
+167,0.87109375,0.875,,0.01,8,1,17,,400,,,16,10.464965581893921
+168,0.83984375,0.84765625,,0.01,8,1,18,,400,,,16,10.42500114440918
+169,0.859375,0.875,,0.01,8,1,19,,400,,,16,10.542990684509277
+170,0.85546875,0.87109375,,0.01,8,1,20,,400,,,16,10.475743055343628
+171,0.84375,0.859375,,0.01,8,1,21,,400,,,16,10.425108194351196
+172,0.86328125,0.86328125,,0.01,8,1,22,,400,,,16,10.412006855010986
+173,0.89453125,0.90234375,,0.01,8,1,23,,400,,,16,10.458159923553467
+174,0.86328125,0.86328125,,0.01,8,1,24,,400,,,16,10.411003589630127
+175,0.783203125,0.783203125,,0.01,9,1,0,,800,,,16,29.123159408569336
+176,0.771484375,0.77734375,,0.01,9,1,1,,800,,,16,28.864702463150024
+177,0.767578125,0.7734375,,0.01,9,1,2,,800,,,16,29.083159923553467
+178,0.755859375,0.765625,,0.01,9,1,3,,800,,,16,28.73412799835205
+179,0.765625,0.7734375,,0.01,9,1,4,,800,,,16,29.13333010673523
+180,0.767578125,0.771484375,,0.01,9,1,5,,800,,,16,28.811002016067505
+181,0.759765625,0.763671875,,0.01,9,1,6,,800,,,16,28.964075565338135
+182,0.7578125,0.765625,,0.01,9,1,7,,800,,,16,28.717440128326416
+183,0.76171875,0.765625,,0.01,9,1,8,,800,,,16,28.89050555229187
+184,0.744140625,0.75390625,,0.01,9,1,9,,800,,,16,28.744742155075073
+185,0.748046875,0.755859375,,0.01,9,1,10,,800,,,16,28.916541576385498
+186,0.794921875,0.79296875,,0.01,9,1,11,,800,,,16,28.658581495285034
+187,0.7578125,0.76171875,,0.01,9,1,12,,800,,,16,28.876265287399292
+188,0.79296875,0.79296875,,0.01,9,1,13,,800,,,16,28.798943996429443
+189,0.7578125,0.7578125,,0.01,9,1,14,,800,,,16,28.852571964263916
+190,0.783203125,0.78125,,0.01,9,1,15,,800,,,16,28.80446195602417
+191,0.771484375,0.77734375,,0.01,9,1,16,,800,,,16,28.915541172027588
+192,0.771484375,0.771484375,,0.01,9,1,17,,800,,,16,28.686417818069458
+193,0.7578125,0.759765625,,0.01,9,1,18,,800,,,16,28.792275428771973
+194,0.771484375,0.7734375,,0.01,9,1,19,,800,,,16,28.768209218978882
+195,0.748046875,0.751953125,,0.01,9,1,20,,800,,,16,28.972150087356567
+196,0.755859375,0.7578125,,0.01,9,1,21,,800,,,16,28.61903190612793
+197,0.80078125,0.802734375,,0.01,9,1,22,,800,,,16,28.877201318740845
+198,0.77734375,0.78125,,0.01,9,1,23,,800,,,16,28.727038383483887
+199,0.767578125,0.76953125,,0.01,9,1,24,,800,,,16,28.858298301696777
+200,0.796875,0.828125,,0.1,6,1,0,,100,,,16,3.578157901763916
+201,0.828125,0.84375,,0.1,6,1,1,,100,,,16,3.439002752304077
+202,0.765625,0.828125,,0.1,6,1,2,,100,,,16,3.4276278018951416
+203,0.8125,0.796875,,0.1,6,1,3,,100,,,16,3.447909116744995
+204,0.78125,0.8125,,0.1,6,1,4,,100,,,16,3.4439916610717773
+205,0.8125,0.796875,,0.1,6,1,5,,100,,,16,3.5300230979919434
+206,0.796875,0.78125,,0.1,6,1,6,,100,,,16,3.4420077800750732
+207,0.75,0.796875,,0.1,6,1,7,,100,,,16,3.447021245956421
+208,0.796875,0.734375,,0.1,6,1,8,,100,,,16,3.426032543182373
+209,0.890625,0.890625,,0.1,6,1,9,,100,,,16,3.5850231647491455
+210,0.796875,0.8125,,0.1,6,1,10,,100,,,16,3.4854745864868164
+211,0.828125,0.84375,,0.1,6,1,11,,100,,,16,3.459583282470703
+212,0.734375,0.8125,,0.1,6,1,12,,100,,,16,3.444711446762085
+213,0.78125,0.84375,,0.1,6,1,13,,100,,,16,3.43803334236145
+214,0.8125,0.875,,0.1,6,1,14,,100,,,16,3.488010883331299
+215,0.890625,0.890625,,0.1,6,1,15,,100,,,16,3.4802324771881104
+216,0.765625,0.765625,,0.1,6,1,16,,100,,,16,3.464015483856201
+217,0.859375,0.828125,,0.1,6,1,17,,100,,,16,3.5240211486816406
+218,0.796875,0.78125,,0.1,6,1,18,,100,,,16,3.605025053024292
+219,0.703125,0.71875,,0.1,6,1,19,,100,,,16,3.4666454792022705
+220,0.828125,0.8125,,0.1,6,1,20,,100,,,16,3.4480156898498535
+221,0.875,0.875,,0.1,6,1,21,,100,,,16,3.4660050868988037
+222,0.859375,0.859375,,0.1,6,1,22,,100,,,16,3.4350008964538574
+223,0.703125,0.703125,,0.1,6,1,23,,100,,,16,3.524542808532715
+224,0.765625,0.796875,,0.1,6,1,24,,100,,,16,3.4760191440582275
+225,0.703125,0.7109375,,0.1,7,1,0,,200,,,16,5.120009183883667
+226,0.7421875,0.75,,0.1,7,1,1,,200,,,16,5.064577579498291
+227,0.7109375,0.6953125,,0.1,7,1,2,,200,,,16,5.069133281707764
+228,0.625,0.671875,,0.1,7,1,3,,200,,,16,5.045992612838745
+229,0.7421875,0.75,,0.1,7,1,4,,200,,,16,5.093989133834839
+230,0.7265625,0.6953125,,0.1,7,1,5,,200,,,16,5.081989765167236
+231,0.6953125,0.7109375,,0.1,7,1,6,,200,,,16,5.073967218399048
+232,0.671875,0.6484375,,0.1,7,1,7,,200,,,16,5.075058937072754
+233,0.7109375,0.7109375,,0.1,7,1,8,,200,,,16,5.087991714477539
+234,0.6875,0.7109375,,0.1,7,1,9,,200,,,16,5.062997341156006
+235,0.625,0.6328125,,0.1,7,1,10,,200,,,16,5.08828067779541
+236,0.6484375,0.671875,,0.1,7,1,11,,200,,,16,5.099009990692139
+237,0.6640625,0.6484375,,0.1,7,1,12,,200,,,16,5.106034755706787
+238,0.75,0.75,,0.1,7,1,13,,200,,,16,5.045626640319824
+239,0.6640625,0.703125,,0.1,7,1,14,,200,,,16,5.160175323486328
+240,0.734375,0.7265625,,0.1,7,1,15,,200,,,16,5.075995206832886
+241,0.7265625,0.7265625,,0.1,7,1,16,,200,,,16,5.092995643615723
+242,0.71875,0.71875,,0.1,7,1,17,,200,,,16,5.16599178314209
+243,0.7265625,0.71875,,0.1,7,1,18,,200,,,16,5.095984697341919
+244,0.7421875,0.734375,,0.1,7,1,19,,200,,,16,5.052172422409058
+245,0.6484375,0.671875,,0.1,7,1,20,,200,,,16,5.227008581161499
+246,0.75,0.734375,,0.1,7,1,21,,200,,,16,5.0830206871032715
+247,0.71875,0.7265625,,0.1,7,1,22,,200,,,16,5.065530776977539
+248,0.6875,0.6875,,0.1,7,1,23,,200,,,16,5.1840033531188965
+249,0.703125,0.71875,,0.1,7,1,24,,200,,,16,5.103999376296997
+250,0.62890625,0.62890625,,0.1,8,1,0,,400,,,16,10.370797395706177
+251,0.62109375,0.62109375,,0.1,8,1,1,,400,,,16,10.418274402618408
+252,0.62109375,0.62109375,,0.1,8,1,2,,400,,,16,10.411893844604492
+253,0.5859375,0.5859375,,0.1,8,1,3,,400,,,16,10.380018949508667
+254,0.55078125,0.5390625,,0.1,8,1,4,,400,,,16,10.300020217895508
+255,0.6484375,0.65234375,,0.1,8,1,5,,400,,,16,10.430625677108765
+256,0.61328125,0.59375,,0.1,8,1,6,,400,,,16,10.272989511489868
+257,0.6484375,0.62890625,,0.1,8,1,7,,400,,,16,10.366991758346558
+258,0.65625,0.65234375,,0.1,8,1,8,,400,,,16,10.392023801803589
+259,0.65625,0.65625,,0.1,8,1,9,,400,,,16,10.353360652923584
+260,0.63671875,0.640625,,0.1,8,1,10,,400,,,16,10.345020055770874
+261,0.671875,0.65625,,0.1,8,1,11,,400,,,16,10.359870433807373
+262,0.6328125,0.61328125,,0.1,8,1,12,,400,,,16,10.302993535995483
+263,0.60546875,0.6171875,,0.1,8,1,13,,400,,,16,10.389234066009521
+264,0.6640625,0.67578125,,0.1,8,1,14,,400,,,16,10.308775901794434
+265,0.640625,0.625,,0.1,8,1,15,,400,,,16,10.380001783370972
+266,0.60546875,0.6484375,,0.1,8,1,16,,400,,,16,10.421687126159668
+267,0.6171875,0.625,,0.1,8,1,17,,400,,,16,10.350981950759888
+268,0.640625,0.62109375,,0.1,8,1,18,,400,,,16,10.290995836257935
+269,0.59765625,0.62109375,,0.1,8,1,19,,400,,,16,10.674318075180054
+270,0.65625,0.6640625,,0.1,8,1,20,,400,,,16,10.394622564315796
+271,0.66796875,0.67578125,,0.1,8,1,21,,400,,,16,10.394285440444946
+272,0.5703125,0.56640625,,0.1,8,1,22,,400,,,16,10.43499207496643
+273,0.56640625,0.5859375,,0.1,8,1,23,,400,,,16,10.372746706008911
+274,0.61328125,0.609375,,0.1,8,1,24,,400,,,16,10.329009532928467
+275,0.5390625,0.55078125,,0.1,9,1,0,,800,,,16,29.086649417877197
+276,0.607421875,0.59375,,0.1,9,1,1,,800,,,16,28.584514379501343
+277,0.5625,0.552734375,,0.1,9,1,2,,800,,,16,28.766215801239014
+278,0.607421875,0.61328125,,0.1,9,1,3,,800,,,16,28.72340202331543
+279,0.564453125,0.5859375,,0.1,9,1,4,,800,,,16,28.81281876564026
+280,0.552734375,0.568359375,,0.1,9,1,5,,800,,,16,28.785064697265625
+281,0.568359375,0.58203125,,0.1,9,1,6,,800,,,16,28.843510150909424
+282,0.546875,0.54296875,,0.1,9,1,7,,800,,,16,28.544695615768433
+283,0.5625,0.583984375,,0.1,9,1,8,,800,,,16,28.709464073181152
+284,0.583984375,0.580078125,,0.1,9,1,9,,800,,,16,28.63861584663391
+285,0.541015625,0.55859375,,0.1,9,1,10,,800,,,16,28.79845643043518
+286,0.568359375,0.583984375,,0.1,9,1,11,,800,,,16,28.682183504104614
+287,0.587890625,0.583984375,,0.1,9,1,12,,800,,,16,28.776066780090332
+288,0.556640625,0.578125,,0.1,9,1,13,,800,,,16,28.52717137336731
+289,0.5546875,0.568359375,,0.1,9,1,14,,800,,,16,29.410460948944092
+290,0.576171875,0.5703125,,0.1,9,1,15,,800,,,16,28.643233060836792
+291,0.560546875,0.572265625,,0.1,9,1,16,,800,,,16,28.727856636047363
+292,0.572265625,0.580078125,,0.1,9,1,17,,800,,,16,28.514925718307495
+293,0.59375,0.6015625,,0.1,9,1,18,,800,,,16,28.673571825027466
+294,0.576171875,0.564453125,,0.1,9,1,19,,800,,,16,28.498872995376587
+295,0.541015625,0.546875,,0.1,9,1,20,,800,,,16,28.87548804283142
+296,0.578125,0.55859375,,0.1,9,1,21,,800,,,16,28.582998275756836
+297,0.564453125,0.564453125,,0.1,9,1,22,,800,,,16,28.7668879032135
+298,0.560546875,0.5625,,0.1,9,1,23,,800,,,16,28.600615739822388
+299,0.5703125,0.60546875,,0.1,9,1,24,,800,,,16,28.79895520210266
+300,0.625,0.703125,,0.2,6,1,0,,100,,,16,3.576777935028076
+301,0.6875,0.65625,,0.2,6,1,1,,100,,,16,3.5000150203704834
+302,0.703125,0.765625,,0.2,6,1,2,,100,,,16,3.42253041267395
+303,0.640625,0.6875,,0.2,6,1,3,,100,,,16,3.474729537963867
+304,0.6875,0.734375,,0.2,6,1,4,,100,,,16,3.477992057800293
+305,0.703125,0.6875,,0.2,6,1,5,,100,,,16,3.5170223712921143
+306,0.59375,0.6875,,0.2,6,1,6,,100,,,16,3.481020450592041
+307,0.609375,0.671875,,0.2,6,1,7,,100,,,16,3.4700262546539307
+308,0.75,0.71875,,0.2,6,1,8,,100,,,16,3.481590986251831
+309,0.640625,0.703125,,0.2,6,1,9,,100,,,16,3.6100106239318848
+310,0.640625,0.6875,,0.2,6,1,10,,100,,,16,3.477011203765869
+311,0.671875,0.71875,,0.2,6,1,11,,100,,,16,3.5023460388183594
+312,0.6875,0.6875,,0.2,6,1,12,,100,,,16,3.460371255874634
+313,0.765625,0.734375,,0.2,6,1,13,,100,,,16,3.520026206970215
+314,0.625,0.671875,,0.2,6,1,14,,100,,,16,3.479022979736328
+315,0.65625,0.734375,,0.2,6,1,15,,100,,,16,3.4991910457611084
+316,0.6875,0.703125,,0.2,6,1,16,,100,,,16,3.5000219345092773
+317,0.734375,0.765625,,0.2,6,1,17,,100,,,16,3.472012519836426
+318,0.6875,0.6875,,0.2,6,1,18,,100,,,16,3.6110174655914307
+319,0.625,0.734375,,0.2,6,1,19,,100,,,16,3.4961156845092773
+320,0.71875,0.703125,,0.2,6,1,20,,100,,,16,3.487999200820923
+321,0.671875,0.671875,,0.2,6,1,21,,100,,,16,3.5169901847839355
+322,0.59375,0.65625,,0.2,6,1,22,,100,,,16,3.536015033721924
+323,0.65625,0.65625,,0.2,6,1,23,,100,,,16,3.493021249771118
+324,0.578125,0.609375,,0.2,6,1,24,,100,,,16,3.479027509689331
+325,0.640625,0.640625,,0.2,7,1,0,,200,,,16,5.12703013420105
+326,0.6015625,0.59375,,0.2,7,1,1,,200,,,16,5.1239941120147705
+327,0.625,0.625,,0.2,7,1,2,,200,,,16,5.109241008758545
+328,0.6328125,0.59375,,0.2,7,1,3,,200,,,16,5.055020570755005
+329,0.625,0.6640625,,0.2,7,1,4,,200,,,16,5.118991374969482
+330,0.59375,0.59375,,0.2,7,1,5,,200,,,16,5.086024522781372
+331,0.59375,0.609375,,0.2,7,1,6,,200,,,16,5.078019380569458
+332,0.703125,0.71875,,0.2,7,1,7,,200,,,16,5.125013589859009
+333,0.6484375,0.6328125,,0.2,7,1,8,,200,,,16,5.119170188903809
+334,0.5625,0.6015625,,0.2,7,1,9,,200,,,16,5.113019704818726
+335,0.59375,0.59375,,0.2,7,1,10,,200,,,16,5.112203359603882
+336,0.578125,0.6015625,,0.2,7,1,11,,200,,,16,5.0889928340911865
+337,0.609375,0.6328125,,0.2,7,1,12,,200,,,16,5.121013402938843
+338,0.625,0.6640625,,0.2,7,1,13,,200,,,16,5.111868619918823
+339,0.5546875,0.546875,,0.2,7,1,14,,200,,,16,5.113992691040039
+340,0.703125,0.65625,,0.2,7,1,15,,200,,,16,5.060022830963135
+341,0.5859375,0.6015625,,0.2,7,1,16,,200,,,16,5.092007875442505
+342,0.6484375,0.640625,,0.2,7,1,17,,200,,,16,5.125019311904907
+343,0.53125,0.5625,,0.2,7,1,18,,200,,,16,5.1000001430511475
+344,0.6171875,0.640625,,0.2,7,1,19,,200,,,16,5.097203731536865
+345,0.625,0.6796875,,0.2,7,1,20,,200,,,16,5.226996421813965
+346,0.5703125,0.5703125,,0.2,7,1,21,,200,,,16,5.059009790420532
+347,0.609375,0.6171875,,0.2,7,1,22,,200,,,16,5.102227687835693
+348,0.6640625,0.671875,,0.2,7,1,23,,200,,,16,5.1720216274261475
+349,0.640625,0.625,,0.2,7,1,24,,200,,,16,5.146007061004639
+350,0.5625,0.5546875,,0.2,8,1,0,,400,,,16,10.346646070480347
+351,0.58984375,0.58203125,,0.2,8,1,1,,400,,,16,10.413209438323975
+352,0.56640625,0.55859375,,0.2,8,1,2,,400,,,16,10.426023483276367
+353,0.56640625,0.5703125,,0.2,8,1,3,,400,,,16,10.443725824356079
+354,0.58984375,0.5859375,,0.2,8,1,4,,400,,,16,10.331996202468872
+355,0.546875,0.546875,,0.2,8,1,5,,400,,,16,10.474819421768188
+356,0.59375,0.6015625,,0.2,8,1,6,,400,,,16,10.302989959716797
+357,0.59375,0.58984375,,0.2,8,1,7,,400,,,16,10.395000219345093
+358,0.59765625,0.609375,,0.2,8,1,8,,400,,,16,10.37308382987976
+359,0.5234375,0.52734375,,0.2,8,1,9,,400,,,16,10.434643268585205
+360,0.51171875,0.55078125,,0.2,8,1,10,,400,,,16,10.363025903701782
+361,0.5703125,0.55859375,,0.2,8,1,11,,400,,,16,10.441237449645996
+362,0.640625,0.6640625,,0.2,8,1,12,,400,,,16,10.356121301651001
+363,0.546875,0.53515625,,0.2,8,1,13,,400,,,16,10.355113744735718
+364,0.60546875,0.58984375,,0.2,8,1,14,,400,,,16,10.402772426605225
+365,0.56640625,0.5859375,,0.2,8,1,15,,400,,,16,10.416026830673218
+366,0.5625,0.5625,,0.2,8,1,16,,400,,,16,10.374992609024048
+367,0.62109375,0.6171875,,0.2,8,1,17,,400,,,16,10.403777122497559
+368,0.51953125,0.609375,,0.2,8,1,18,,400,,,16,10.396997213363647
+369,0.578125,0.62109375,,0.2,8,1,19,,400,,,16,10.523990154266357
+370,0.5703125,0.58984375,,0.2,8,1,20,,400,,,16,10.408026456832886
+371,0.5703125,0.57421875,,0.2,8,1,21,,400,,,16,10.406320095062256
+372,0.59375,0.578125,,0.2,8,1,22,,400,,,16,10.540990352630615
+373,0.53515625,0.5546875,,0.2,8,1,23,,400,,,16,10.45217227935791
+374,0.578125,0.5703125,,0.2,8,1,24,,400,,,16,10.328016996383667
+375,0.556640625,0.556640625,,0.2,9,1,0,,800,,,16,29.05496835708618
+376,0.51171875,0.517578125,,0.2,9,1,1,,800,,,16,28.740124464035034
+377,0.537109375,0.5546875,,0.2,9,1,2,,800,,,16,28.942466497421265
+378,0.517578125,0.5390625,,0.2,9,1,3,,800,,,16,28.71194291114807
+379,0.556640625,0.548828125,,0.2,9,1,4,,800,,,16,28.674171686172485
+380,0.576171875,0.5625,,0.2,9,1,5,,800,,,16,28.65387487411499
+381,0.576171875,0.576171875,,0.2,9,1,6,,800,,,16,28.70324397087097
+382,0.580078125,0.568359375,,0.2,9,1,7,,800,,,16,28.628174781799316
+383,0.541015625,0.541015625,,0.2,9,1,8,,800,,,16,28.80237913131714
+384,0.552734375,0.541015625,,0.2,9,1,9,,800,,,16,28.635788440704346
+385,0.525390625,0.53515625,,0.2,9,1,10,,800,,,16,28.93262481689453
+386,0.55078125,0.537109375,,0.2,9,1,11,,800,,,16,28.558943271636963
+387,0.6015625,0.578125,,0.2,9,1,12,,800,,,16,28.706650257110596
+388,0.533203125,0.525390625,,0.2,9,1,13,,800,,,16,28.56359577178955
+389,0.537109375,0.521484375,,0.2,9,1,14,,800,,,16,28.72932481765747
+390,0.52734375,0.51953125,,0.2,9,1,15,,800,,,16,28.429492950439453
+391,0.55859375,0.560546875,,0.2,9,1,16,,800,,,16,28.678462505340576
+392,0.513671875,0.55859375,,0.2,9,1,17,,800,,,16,28.559422731399536
+393,0.578125,0.5625,,0.2,9,1,18,,800,,,16,28.709693908691406
+394,0.5390625,0.552734375,,0.2,9,1,19,,800,,,16,28.517654418945312
+395,0.517578125,0.529296875,,0.2,9,1,20,,800,,,16,28.717972993850708
+396,0.548828125,0.5625,,0.2,9,1,21,,800,,,16,28.469651460647583
+397,0.5625,0.546875,,0.2,9,1,22,,800,,,16,28.714134216308594
+398,0.546875,0.525390625,,0.2,9,1,23,,800,,,16,28.475526809692383
+399,0.5703125,0.55859375,,0.2,9,1,24,,800,,,16,28.639175176620483
+400,1.0,1.0,,0.0,6,2,0,,100,,,16,3.5360372066497803
+401,1.0,1.0,,0.0,6,2,1,,100,,,16,3.449991226196289
+402,1.0,1.0,,0.0,6,2,2,,100,,,16,3.4539918899536133
+403,1.0,1.0,,0.0,6,2,3,,100,,,16,3.455183744430542
+404,1.0,1.0,,0.0,6,2,4,,100,,,16,3.5089938640594482
+405,1.0,1.0,,0.0,6,2,5,,100,,,16,3.539024591445923
+406,1.0,1.0,,0.0,6,2,6,,100,,,16,3.486997604370117
+407,1.0,1.0,,0.0,6,2,7,,100,,,16,3.5159943103790283
+408,1.0,1.0,,0.0,6,2,8,,100,,,16,3.5559921264648438
+409,1.0,1.0,,0.0,6,2,9,,100,,,16,3.626009941101074
+410,1.0,1.0,,0.0,6,2,10,,100,,,16,3.513982057571411
+411,1.0,1.0,,0.0,6,2,11,,100,,,16,3.4727208614349365
+412,1.0,1.0,,0.0,6,2,12,,100,,,16,3.4910223484039307
+413,1.0,1.0,,0.0,6,2,13,,100,,,16,3.5490286350250244
+414,1.0,1.0,,0.0,6,2,14,,100,,,16,3.5030176639556885
+415,1.0,1.0,,0.0,6,2,15,,100,,,16,3.4899606704711914
+416,1.0,1.0,,0.0,6,2,16,,100,,,16,3.480997323989868
+417,1.0,1.0,,0.0,6,2,17,,100,,,16,3.5170037746429443
+418,1.0,1.0,,0.0,6,2,18,,100,,,16,3.590693473815918
+419,1.0,1.0,,0.0,6,2,19,,100,,,16,3.5089926719665527
+420,1.0,1.0,,0.0,6,2,20,,100,,,16,3.496692419052124
+421,1.0,1.0,,0.0,6,2,21,,100,,,16,3.5280044078826904
+422,1.0,1.0,,0.0,6,2,22,,100,,,16,3.5370285511016846
+423,1.0,1.0,,0.0,6,2,23,,100,,,16,3.5496418476104736
+424,1.0,1.0,,0.0,6,2,24,,100,,,16,3.4889912605285645
+425,0.984375,0.984375,,0.0,7,2,0,,200,,,16,5.206026077270508
+426,0.984375,0.984375,,0.0,7,2,1,,200,,,16,5.181992053985596
+427,1.0,1.0,,0.0,7,2,2,,200,,,16,5.141499757766724
+428,0.9921875,0.9921875,,0.0,7,2,3,,200,,,16,5.085997104644775
+429,1.0,1.0,,0.0,7,2,4,,200,,,16,5.194021701812744
+430,0.9921875,0.9921875,,0.0,7,2,5,,200,,,16,5.1160242557525635
+431,0.9921875,0.9921875,,0.0,7,2,6,,200,,,16,5.118992805480957
+432,1.0,1.0,,0.0,7,2,7,,200,,,16,5.125993251800537
+433,0.9765625,0.9765625,,0.0,7,2,8,,200,,,16,5.149662017822266
+434,1.0,1.0,,0.0,7,2,9,,200,,,16,5.1220009326934814
+435,0.9921875,0.9921875,,0.0,7,2,10,,200,,,16,5.37582540512085
+436,0.9921875,0.9921875,,0.0,7,2,11,,200,,,16,5.133985757827759
+437,1.0,1.0,,0.0,7,2,12,,200,,,16,5.148994445800781
+438,0.984375,0.984375,,0.0,7,2,13,,200,,,16,5.121499061584473
+439,1.0,1.0,,0.0,7,2,14,,200,,,16,5.1342082023620605
+440,0.984375,0.984375,,0.0,7,2,15,,200,,,16,5.151994943618774
+441,0.9921875,0.9921875,,0.0,7,2,16,,200,,,16,5.170002698898315
+442,0.9921875,0.9921875,,0.0,7,2,17,,200,,,16,5.140002727508545
+443,0.984375,0.984375,,0.0,7,2,18,,200,,,16,5.1600446701049805
+444,0.9921875,0.9921875,,0.0,7,2,19,,200,,,16,5.100566625595093
+445,0.984375,0.984375,,0.0,7,2,20,,200,,,16,5.164997816085815
+446,1.0,1.0,,0.0,7,2,21,,200,,,16,5.1569952964782715
+447,0.984375,0.984375,,0.0,7,2,22,,200,,,16,5.134657859802246
+448,0.9921875,0.9921875,,0.0,7,2,23,,200,,,16,5.125024795532227
+449,0.9921875,0.9921875,,0.0,7,2,24,,200,,,16,5.150999069213867
+450,0.93359375,0.93359375,,0.0,8,2,0,,400,,,16,10.496111154556274
+451,0.92578125,0.92578125,,0.0,8,2,1,,400,,,16,10.53699803352356
+452,0.94921875,0.94921875,,0.0,8,2,2,,400,,,16,10.492022037506104
+453,0.92578125,0.92578125,,0.0,8,2,3,,400,,,16,10.498646259307861
+454,0.953125,0.953125,,0.0,8,2,4,,400,,,16,10.505020141601562
+455,0.91796875,0.921875,,0.0,8,2,5,,400,,,16,10.572557926177979
+456,0.93359375,0.93359375,,0.0,8,2,6,,400,,,16,10.461997509002686
+457,0.953125,0.953125,,0.0,8,2,7,,400,,,16,10.543989181518555
+458,0.96875,0.96875,,0.0,8,2,8,,400,,,16,10.631222009658813
+459,0.9375,0.9375,,0.0,8,2,9,,400,,,16,10.556918144226074
+460,0.9296875,0.9296875,,0.0,8,2,10,,400,,,16,10.416422843933105
+461,0.96484375,0.96484375,,0.0,8,2,11,,400,,,16,10.604813575744629
+462,0.9296875,0.9296875,,0.0,8,2,12,,400,,,16,10.42902684211731
+463,0.92578125,0.92578125,,0.0,8,2,13,,400,,,16,10.570764064788818
+464,0.92578125,0.92578125,,0.0,8,2,14,,400,,,16,10.567125082015991
+465,0.94140625,0.94140625,,0.0,8,2,15,,400,,,16,10.542994976043701
+466,0.93359375,0.93359375,,0.0,8,2,16,,400,,,16,10.431990146636963
+467,0.9453125,0.9453125,,0.0,8,2,17,,400,,,16,10.601248025894165
+468,0.9375,0.9375,,0.0,8,2,18,,400,,,16,10.487026453018188
+469,0.92578125,0.92578125,,0.0,8,2,19,,400,,,16,10.466026544570923
+470,0.953125,0.953125,,0.0,8,2,20,,400,,,16,10.575943231582642
+471,0.93359375,0.93359375,,0.0,8,2,21,,400,,,16,10.489856958389282
+472,0.9375,0.9375,,0.0,8,2,22,,400,,,16,10.48381757736206
+473,0.94921875,0.94921875,,0.0,8,2,23,,400,,,16,10.67398738861084
+474,0.93359375,0.93359375,,0.0,8,2,24,,400,,,16,10.436985492706299
+475,0.857421875,0.857421875,,0.0,9,2,0,,800,,,16,29.312406301498413
+476,0.865234375,0.865234375,,0.0,9,2,1,,800,,,16,29.068387985229492
+477,0.876953125,0.876953125,,0.0,9,2,2,,800,,,16,29.25738263130188
+478,0.87890625,0.87890625,,0.0,9,2,3,,800,,,16,29.052698135375977
+479,0.8515625,0.8515625,,0.0,9,2,4,,800,,,16,29.167085886001587
+480,0.86328125,0.86328125,,0.0,9,2,5,,800,,,16,28.966849088668823
+481,0.87890625,0.87890625,,0.0,9,2,6,,800,,,16,29.20008945465088
+482,0.857421875,0.859375,,0.0,9,2,7,,800,,,16,28.859803438186646
+483,0.859375,0.861328125,,0.0,9,2,8,,800,,,16,29.29753303527832
+484,0.865234375,0.865234375,,0.0,9,2,9,,800,,,16,28.932755947113037
+485,0.8515625,0.8515625,,0.0,9,2,10,,800,,,16,28.89515447616577
+486,0.8671875,0.8671875,,0.0,9,2,11,,800,,,16,28.872549533843994
+487,0.857421875,0.857421875,,0.0,9,2,12,,800,,,16,29.014426946640015
+488,0.869140625,0.869140625,,0.0,9,2,13,,800,,,16,29.043933153152466
+489,0.880859375,0.880859375,,0.0,9,2,14,,800,,,16,29.211193561553955
+490,0.87109375,0.87109375,,0.0,9,2,15,,800,,,16,28.93129873275757
+491,0.87109375,0.87109375,,0.0,9,2,16,,800,,,16,29.163185834884644
+492,0.869140625,0.869140625,,0.0,9,2,17,,800,,,16,28.81534767150879
+493,0.896484375,0.896484375,,0.0,9,2,18,,800,,,16,29.034233570098877
+494,0.873046875,0.873046875,,0.0,9,2,19,,800,,,16,28.893821954727173
+495,0.849609375,0.849609375,,0.0,9,2,20,,800,,,16,29.10957407951355
+496,0.87109375,0.87109375,,0.0,9,2,21,,800,,,16,28.85665249824524
+497,0.84765625,0.849609375,,0.0,9,2,22,,800,,,16,29.10981059074402
+498,0.865234375,0.865234375,,0.0,9,2,23,,800,,,16,28.864736318588257
+499,0.8828125,0.8828125,,0.0,9,2,24,,800,,,16,29.13645029067993
+500,1.0,1.0,,0.01,6,2,0,,100,,,16,3.4892115592956543
+501,1.0,1.0,,0.01,6,2,1,,100,,,16,3.5340054035186768
+502,1.0,1.0,,0.01,6,2,2,,100,,,16,3.477998733520508
+503,1.0,1.0,,0.01,6,2,3,,100,,,16,3.506072759628296
+504,1.0,1.0,,0.01,6,2,4,,100,,,16,3.4730193614959717
+505,1.0,1.0,,0.01,6,2,5,,100,,,16,3.5889971256256104
+506,1.0,1.0,,0.01,6,2,6,,100,,,16,3.522996187210083
+507,1.0,1.0,,0.01,6,2,7,,100,,,16,3.4759819507598877
+508,1.0,1.0,,0.01,6,2,8,,100,,,16,3.514223098754883
+509,1.0,1.0,,0.01,6,2,9,,100,,,16,3.502018451690674
+510,1.0,1.0,,0.01,6,2,10,,100,,,16,3.5310299396514893
+511,1.0,1.0,,0.01,6,2,11,,100,,,16,3.4900331497192383
+512,1.0,1.0,,0.01,6,2,12,,100,,,16,3.5095436573028564
+513,1.0,1.0,,0.01,6,2,13,,100,,,16,3.5819952487945557
+514,1.0,1.0,,0.01,6,2,14,,100,,,16,3.6169891357421875
+515,1.0,1.0,,0.01,6,2,15,,100,,,16,3.526280403137207
+516,1.0,1.0,,0.01,6,2,16,,100,,,16,3.4740381240844727
+517,1.0,1.0,,0.01,6,2,17,,100,,,16,3.5009918212890625
+518,1.0,1.0,,0.01,6,2,18,,100,,,16,3.5139997005462646
+519,1.0,1.0,,0.01,6,2,19,,100,,,16,3.5207860469818115
+520,1.0,1.0,,0.01,6,2,20,,100,,,16,3.522988796234131
+521,1.0,1.0,,0.01,6,2,21,,100,,,16,3.5180230140686035
+522,1.0,1.0,,0.01,6,2,22,,100,,,16,3.522986650466919
+523,1.0,1.0,,0.01,6,2,23,,100,,,16,3.609995126724243
+524,1.0,1.0,,0.01,6,2,24,,100,,,16,3.488741874694824
+525,0.96875,0.9765625,,0.01,7,2,0,,200,,,16,5.1512298583984375
+526,0.96875,0.96875,,0.01,7,2,1,,200,,,16,5.143007516860962
+527,0.96875,0.96875,,0.01,7,2,2,,200,,,16,5.147325754165649
+528,0.9765625,0.9765625,,0.01,7,2,3,,200,,,16,5.099989652633667
+529,0.9609375,0.96875,,0.01,7,2,4,,200,,,16,5.144985198974609
+530,0.9765625,0.9765625,,0.01,7,2,5,,200,,,16,5.1799163818359375
+531,0.9609375,0.96875,,0.01,7,2,6,,200,,,16,5.128316402435303
+532,0.9609375,0.96875,,0.01,7,2,7,,200,,,16,5.0979907512664795
+533,0.96875,0.9765625,,0.01,7,2,8,,200,,,16,5.200982332229614
+534,0.984375,0.984375,,0.01,7,2,9,,200,,,16,5.106989622116089
+535,0.96875,0.96875,,0.01,7,2,10,,200,,,16,5.1369946002960205
+536,0.9609375,0.9609375,,0.01,7,2,11,,200,,,16,5.206960678100586
+537,0.9765625,0.984375,,0.01,7,2,12,,200,,,16,5.198997974395752
+538,0.984375,0.984375,,0.01,7,2,13,,200,,,16,5.128991365432739
+539,0.9921875,1.0,,0.01,7,2,14,,200,,,16,5.258352756500244
+540,0.984375,0.9921875,,0.01,7,2,15,,200,,,16,5.130993127822876
+541,0.984375,0.984375,,0.01,7,2,16,,200,,,16,5.1709983348846436
+542,0.9609375,0.9609375,,0.01,7,2,17,,200,,,16,5.263540506362915
+543,0.96875,0.96875,,0.01,7,2,18,,200,,,16,5.17123007774353
+544,0.9921875,0.9921875,,0.01,7,2,19,,200,,,16,5.191029787063599
+545,0.96875,0.96875,,0.01,7,2,20,,200,,,16,5.287994146347046
+546,0.9765625,0.9765625,,0.01,7,2,21,,200,,,16,5.16901707649231
+547,0.984375,0.984375,,0.01,7,2,22,,200,,,16,5.17350959777832
+548,0.953125,0.9609375,,0.01,7,2,23,,200,,,16,5.261174440383911
+549,0.9609375,0.96875,,0.01,7,2,24,,200,,,16,5.184993743896484
+550,0.90234375,0.90234375,,0.01,8,2,0,,400,,,16,10.461993217468262
+551,0.890625,0.89453125,,0.01,8,2,1,,400,,,16,10.584819555282593
+552,0.890625,0.890625,,0.01,8,2,2,,400,,,16,10.568993330001831
+553,0.8984375,0.90234375,,0.01,8,2,3,,400,,,16,10.585578203201294
+554,0.875,0.87890625,,0.01,8,2,4,,400,,,16,10.5029616355896
+555,0.8828125,0.89453125,,0.01,8,2,5,,400,,,16,10.613683462142944
+556,0.87890625,0.890625,,0.01,8,2,6,,400,,,16,10.733999967575073
+557,0.88671875,0.890625,,0.01,8,2,7,,400,,,16,10.534568309783936
+558,0.8671875,0.87109375,,0.01,8,2,8,,400,,,16,10.654998064041138
+559,0.859375,0.87109375,,0.01,8,2,9,,400,,,16,10.515411853790283
+560,0.87890625,0.8828125,,0.01,8,2,10,,400,,,16,10.4383225440979
+561,0.8671875,0.875,,0.01,8,2,11,,400,,,16,10.700989484786987
+562,0.8828125,0.8828125,,0.01,8,2,12,,400,,,16,10.477486371994019
+563,0.875,0.875,,0.01,8,2,13,,400,,,16,10.49996042251587
+564,0.87109375,0.87890625,,0.01,8,2,14,,400,,,16,10.543138980865479
+565,0.91796875,0.921875,,0.01,8,2,15,,400,,,16,10.543022632598877
+566,0.8828125,0.88671875,,0.01,8,2,16,,400,,,16,10.406704902648926
+567,0.8828125,0.88671875,,0.01,8,2,17,,400,,,16,10.616116285324097
+568,0.8984375,0.8984375,,0.01,8,2,18,,400,,,16,10.438817262649536
+569,0.8828125,0.88671875,,0.01,8,2,19,,400,,,16,10.550013780593872
+570,0.88671875,0.890625,,0.01,8,2,20,,400,,,16,10.566826343536377
+571,0.87890625,0.88671875,,0.01,8,2,21,,400,,,16,10.50537657737732
+572,0.8828125,0.88671875,,0.01,8,2,22,,400,,,16,10.418991327285767
+573,0.8984375,0.90625,,0.01,8,2,23,,400,,,16,10.629990816116333
+574,0.87109375,0.875,,0.01,8,2,24,,400,,,16,10.455745458602905
+575,0.810546875,0.814453125,,0.01,9,2,0,,800,,,16,29.206498384475708
+576,0.779296875,0.791015625,,0.01,9,2,1,,800,,,16,28.989569902420044
+577,0.796875,0.810546875,,0.01,9,2,2,,800,,,16,29.143932819366455
+578,0.77734375,0.78515625,,0.01,9,2,3,,800,,,16,28.908509016036987
+579,0.791015625,0.79296875,,0.01,9,2,4,,800,,,16,28.962236881256104
+580,0.763671875,0.76953125,,0.01,9,2,5,,800,,,16,28.88282561302185
+581,0.744140625,0.751953125,,0.01,9,2,6,,800,,,16,28.9761700630188
+582,0.77734375,0.779296875,,0.01,9,2,7,,800,,,16,28.86475396156311
+583,0.796875,0.798828125,,0.01,9,2,8,,800,,,16,29.074400186538696
+584,0.802734375,0.80859375,,0.01,9,2,9,,800,,,16,28.944782257080078
+585,0.78515625,0.79296875,,0.01,9,2,10,,800,,,16,29.081369400024414
+586,0.791015625,0.80078125,,0.01,9,2,11,,800,,,16,28.799309015274048
+587,0.78515625,0.796875,,0.01,9,2,12,,800,,,16,29.08208131790161
+588,0.7734375,0.78125,,0.01,9,2,13,,800,,,16,28.826667308807373
+589,0.7890625,0.794921875,,0.01,9,2,14,,800,,,16,28.950032711029053
+590,0.806640625,0.806640625,,0.01,9,2,15,,800,,,16,28.666748762130737
+591,0.771484375,0.7734375,,0.01,9,2,16,,800,,,16,28.93527626991272
+592,0.78515625,0.791015625,,0.01,9,2,17,,800,,,16,28.67645287513733
+593,0.783203125,0.78515625,,0.01,9,2,18,,800,,,16,28.96159315109253
+594,0.779296875,0.783203125,,0.01,9,2,19,,800,,,16,28.77005410194397
+595,0.7734375,0.7734375,,0.01,9,2,20,,800,,,16,28.828235149383545
+596,0.78125,0.7890625,,0.01,9,2,21,,800,,,16,28.75797438621521
+597,0.794921875,0.796875,,0.01,9,2,22,,800,,,16,28.964792251586914
+598,0.796875,0.802734375,,0.01,9,2,23,,800,,,16,28.78521466255188
+599,0.810546875,0.8125,,0.01,9,2,24,,800,,,16,29.21740961074829
+600,0.84375,0.84375,,0.1,6,2,0,,100,,,16,3.4300284385681152
+601,0.875,0.875,,0.1,6,2,1,,100,,,16,3.4650025367736816
+602,0.828125,0.859375,,0.1,6,2,2,,100,,,16,3.572030544281006
+603,0.90625,0.90625,,0.1,6,2,3,,100,,,16,3.450997829437256
+604,0.875,0.890625,,0.1,6,2,4,,100,,,16,3.451465368270874
+605,0.96875,0.96875,,0.1,6,2,5,,100,,,16,3.496507167816162
+606,0.828125,0.828125,,0.1,6,2,6,,100,,,16,3.5059969425201416
+607,0.890625,0.9375,,0.1,6,2,7,,100,,,16,3.5126025676727295
+608,0.921875,0.90625,,0.1,6,2,8,,100,,,16,3.477013111114502
+609,0.890625,0.890625,,0.1,6,2,9,,100,,,16,3.486013174057007
+610,0.953125,0.96875,,0.1,6,2,10,,100,,,16,3.4780235290527344
+611,0.890625,0.90625,,0.1,6,2,11,,100,,,16,3.5660202503204346
+612,0.84375,0.84375,,0.1,6,2,12,,100,,,16,3.4889941215515137
+613,0.921875,0.9375,,0.1,6,2,13,,100,,,16,3.515005350112915
+614,0.90625,0.90625,,0.1,6,2,14,,100,,,16,4.074659585952759
+615,0.859375,0.859375,,0.1,6,2,15,,100,,,16,3.5620009899139404
+616,0.78125,0.84375,,0.1,6,2,16,,100,,,16,3.478545904159546
+617,0.90625,0.90625,,0.1,6,2,17,,100,,,16,3.502016067504883
+618,0.921875,0.9375,,0.1,6,2,18,,100,,,16,3.5449905395507812
+619,0.84375,0.859375,,0.1,6,2,19,,100,,,16,3.5119943618774414
+620,0.875,0.875,,0.1,6,2,20,,100,,,16,3.514991044998169
+621,0.828125,0.84375,,0.1,6,2,21,,100,,,16,3.5079963207244873
+622,0.875,0.859375,,0.1,6,2,22,,100,,,16,3.4736878871917725
+623,0.84375,0.84375,,0.1,6,2,23,,100,,,16,3.4853498935699463
+624,0.8125,0.8125,,0.1,6,2,24,,100,,,16,3.6400222778320312
+625,0.75,0.7265625,,0.1,7,2,0,,200,,,16,5.137032747268677
+626,0.71875,0.703125,,0.1,7,2,1,,200,,,16,5.0910022258758545
+627,0.7421875,0.75,,0.1,7,2,2,,200,,,16,5.087005376815796
+628,0.796875,0.796875,,0.1,7,2,3,,200,,,16,5.091017007827759
+629,0.71875,0.734375,,0.1,7,2,4,,200,,,16,5.13663911819458
+630,0.765625,0.7578125,,0.1,7,2,5,,200,,,16,5.061994314193726
+631,0.75,0.734375,,0.1,7,2,6,,200,,,16,5.1200268268585205
+632,0.78125,0.78125,,0.1,7,2,7,,200,,,16,5.094000577926636
+633,0.734375,0.7265625,,0.1,7,2,8,,200,,,16,5.109020709991455
+634,0.7578125,0.7578125,,0.1,7,2,9,,200,,,16,5.0870139598846436
+635,0.8046875,0.7890625,,0.1,7,2,10,,200,,,16,5.090639591217041
+636,0.7890625,0.7890625,,0.1,7,2,11,,200,,,16,5.08799409866333
+637,0.7421875,0.7265625,,0.1,7,2,12,,200,,,16,5.1560163497924805
+638,0.7734375,0.8125,,0.1,7,2,13,,200,,,16,5.100993633270264
+639,0.7578125,0.7421875,,0.1,7,2,14,,200,,,16,5.115888357162476
+640,0.703125,0.7109375,,0.1,7,2,15,,200,,,16,5.161764621734619
+641,0.734375,0.7265625,,0.1,7,2,16,,200,,,16,5.141991376876831
+642,0.703125,0.71875,,0.1,7,2,17,,200,,,16,5.07299542427063
+643,0.7109375,0.7578125,,0.1,7,2,18,,200,,,16,5.213016986846924
+644,0.7109375,0.765625,,0.1,7,2,19,,200,,,16,5.130986928939819
+645,0.765625,0.7734375,,0.1,7,2,20,,200,,,16,5.155025243759155
+646,0.703125,0.6953125,,0.1,7,2,21,,200,,,16,5.176590919494629
+647,0.75,0.765625,,0.1,7,2,22,,200,,,16,5.118186712265015
+648,0.7578125,0.796875,,0.1,7,2,23,,200,,,16,5.0819292068481445
+649,0.8046875,0.796875,,0.1,7,2,24,,200,,,16,5.22756028175354
+650,0.6015625,0.62890625,,0.1,8,2,0,,400,,,16,10.32300066947937
+651,0.640625,0.6484375,,0.1,8,2,1,,400,,,16,10.550228118896484
+652,0.6328125,0.66015625,,0.1,8,2,2,,400,,,16,10.567021131515503
+653,0.6171875,0.62109375,,0.1,8,2,3,,400,,,16,10.432991981506348
+654,0.61328125,0.62109375,,0.1,8,2,4,,400,,,16,10.399194717407227
+655,0.65234375,0.66796875,,0.1,8,2,5,,400,,,16,10.430615186691284
+656,0.58203125,0.59375,,0.1,8,2,6,,400,,,16,10.371778726577759
+657,0.640625,0.62890625,,0.1,8,2,7,,400,,,16,10.46800947189331
+658,0.6640625,0.66796875,,0.1,8,2,8,,400,,,16,10.349028587341309
+659,0.61328125,0.6328125,,0.1,8,2,9,,400,,,16,10.401467561721802
+660,0.6640625,0.6328125,,0.1,8,2,10,,400,,,16,10.35502314567566
+661,0.67578125,0.671875,,0.1,8,2,11,,400,,,16,10.39802098274231
+662,0.703125,0.703125,,0.1,8,2,12,,400,,,16,10.339687585830688
+663,0.609375,0.6171875,,0.1,8,2,13,,400,,,16,10.383140325546265
+664,0.63671875,0.66015625,,0.1,8,2,14,,400,,,16,10.354019403457642
+665,0.625,0.625,,0.1,8,2,15,,400,,,16,10.434643268585205
+666,0.625,0.62109375,,0.1,8,2,16,,400,,,16,10.323009490966797
+667,0.6328125,0.6640625,,0.1,8,2,17,,400,,,16,10.432658195495605
+668,0.57421875,0.5625,,0.1,8,2,18,,400,,,16,10.299089431762695
+669,0.6796875,0.67578125,,0.1,8,2,19,,400,,,16,10.37302303314209
+670,0.64453125,0.6484375,,0.1,8,2,20,,400,,,16,10.36799693107605
+671,0.59765625,0.6328125,,0.1,8,2,21,,400,,,16,10.44315505027771
+672,0.640625,0.6328125,,0.1,8,2,22,,400,,,16,10.33100152015686
+673,0.68359375,0.6796875,,0.1,8,2,23,,400,,,16,10.430996179580688
+674,0.5703125,0.62890625,,0.1,8,2,24,,400,,,16,10.45616888999939
+675,0.5703125,0.568359375,,0.1,9,2,0,,800,,,16,28.946051597595215
+676,0.568359375,0.583984375,,0.1,9,2,1,,800,,,16,28.765154600143433
+677,0.55859375,0.58203125,,0.1,9,2,2,,800,,,16,28.816184759140015
+678,0.587890625,0.599609375,,0.1,9,2,3,,800,,,16,28.65799641609192
+679,0.578125,0.595703125,,0.1,9,2,4,,800,,,16,29.008557558059692
+680,0.611328125,0.61328125,,0.1,9,2,5,,800,,,16,28.723405599594116
+681,0.59765625,0.623046875,,0.1,9,2,6,,800,,,16,28.86681818962097
+682,0.595703125,0.619140625,,0.1,9,2,7,,800,,,16,28.68911123275757
+683,0.583984375,0.580078125,,0.1,9,2,8,,800,,,16,28.82101798057556
+684,0.62109375,0.611328125,,0.1,9,2,9,,800,,,16,28.74523115158081
+685,0.587890625,0.580078125,,0.1,9,2,10,,800,,,16,28.633086442947388
+686,0.58203125,0.58984375,,0.1,9,2,11,,800,,,16,28.51705837249756
+687,0.58203125,0.619140625,,0.1,9,2,12,,800,,,16,28.750061511993408
+688,0.564453125,0.576171875,,0.1,9,2,13,,800,,,16,28.64319372177124
+689,0.607421875,0.61328125,,0.1,9,2,14,,800,,,16,28.94421148300171
+690,0.6015625,0.60546875,,0.1,9,2,15,,800,,,16,28.620171785354614
+691,0.533203125,0.560546875,,0.1,9,2,16,,800,,,16,28.665555000305176
+692,0.58984375,0.583984375,,0.1,9,2,17,,800,,,16,28.719539642333984
+693,0.591796875,0.615234375,,0.1,9,2,18,,800,,,16,28.65205478668213
+694,0.576171875,0.583984375,,0.1,9,2,19,,800,,,16,28.627787351608276
+695,0.599609375,0.611328125,,0.1,9,2,20,,800,,,16,28.752596378326416
+696,0.595703125,0.591796875,,0.1,9,2,21,,800,,,16,28.539286375045776
+697,0.5703125,0.5625,,0.1,9,2,22,,800,,,16,29.82935619354248
+698,0.591796875,0.583984375,,0.1,9,2,23,,800,,,16,28.47621726989746
+699,0.615234375,0.609375,,0.1,9,2,24,,800,,,16,28.821089267730713
+700,0.6875,0.734375,,0.2,6,2,0,,100,,,16,3.4310197830200195
+701,0.78125,0.796875,,0.2,6,2,1,,100,,,16,3.549025058746338
+702,0.796875,0.78125,,0.2,6,2,2,,100,,,16,3.40602445602417
+703,0.796875,0.859375,,0.2,6,2,3,,100,,,16,3.6114659309387207
+704,0.78125,0.75,,0.2,6,2,4,,100,,,16,3.4379920959472656
+705,0.796875,0.8125,,0.2,6,2,5,,100,,,16,3.4998223781585693
+706,0.734375,0.75,,0.2,6,2,6,,100,,,16,3.470986843109131
+707,0.71875,0.796875,,0.2,6,2,7,,100,,,16,3.445996046066284
+708,0.765625,0.796875,,0.2,6,2,8,,100,,,16,3.4419901371002197
+709,0.796875,0.765625,,0.2,6,2,9,,100,,,16,3.484988212585449
+710,0.71875,0.75,,0.2,6,2,10,,100,,,16,3.56198787689209
+711,0.734375,0.734375,,0.2,6,2,11,,100,,,16,3.4710030555725098
+712,0.625,0.671875,,0.2,6,2,12,,100,,,16,3.454987049102783
+713,0.78125,0.765625,,0.2,6,2,13,,100,,,16,3.4599902629852295
+714,0.75,0.765625,,0.2,6,2,14,,100,,,16,3.4751739501953125
+715,0.703125,0.8125,,0.2,6,2,15,,100,,,16,3.4999959468841553
+716,0.671875,0.703125,,0.2,6,2,16,,100,,,16,3.441998243331909
+717,0.703125,0.796875,,0.2,6,2,17,,100,,,16,3.466989755630493
+718,0.6875,0.734375,,0.2,6,2,18,,100,,,16,3.4699926376342773
+719,0.828125,0.828125,,0.2,6,2,19,,100,,,16,3.581984281539917
+720,0.6875,0.6875,,0.2,6,2,20,,100,,,16,3.48953914642334
+721,0.78125,0.8125,,0.2,6,2,21,,100,,,16,3.5089895725250244
+722,0.75,0.765625,,0.2,6,2,22,,100,,,16,3.468238115310669
+723,0.734375,0.734375,,0.2,6,2,23,,100,,,16,3.542998790740967
+724,0.71875,0.734375,,0.2,6,2,24,,100,,,16,3.471997022628784
+725,0.609375,0.6015625,,0.2,7,2,0,,200,,,16,5.161992073059082
+726,0.6015625,0.65625,,0.2,7,2,1,,200,,,16,5.029996871948242
+727,0.6875,0.65625,,0.2,7,2,2,,200,,,16,5.214987516403198
+728,0.578125,0.59375,,0.2,7,2,3,,200,,,16,5.077988862991333
+729,0.734375,0.71875,,0.2,7,2,4,,200,,,16,5.097668409347534
+730,0.671875,0.703125,,0.2,7,2,5,,200,,,16,5.136987209320068
+731,0.5703125,0.6171875,,0.2,7,2,6,,200,,,16,5.098982334136963
+732,0.6328125,0.6328125,,0.2,7,2,7,,200,,,16,5.034982204437256
+733,0.6640625,0.71875,,0.2,7,2,8,,200,,,16,5.174989938735962
+734,0.6015625,0.6171875,,0.2,7,2,9,,200,,,16,5.080155849456787
+735,0.6796875,0.6953125,,0.2,7,2,10,,200,,,16,5.103133201599121
+736,0.6640625,0.65625,,0.2,7,2,11,,200,,,16,5.122988224029541
+737,0.609375,0.71875,,0.2,7,2,12,,200,,,16,5.219021320343018
+738,0.6796875,0.6796875,,0.2,7,2,13,,200,,,16,5.07799220085144
+739,0.640625,0.625,,0.2,7,2,14,,200,,,16,5.1098034381866455
+740,0.6171875,0.6484375,,0.2,7,2,15,,200,,,16,5.067741870880127
+741,0.6953125,0.71875,,0.2,7,2,16,,200,,,16,5.122990846633911
+742,0.6328125,0.6484375,,0.2,7,2,17,,200,,,16,5.049994945526123
+743,0.6953125,0.6953125,,0.2,7,2,18,,200,,,16,5.114988088607788
+744,0.5625,0.6015625,,0.2,7,2,19,,200,,,16,5.05499005317688
+745,0.671875,0.65625,,0.2,7,2,20,,200,,,16,5.119995594024658
+746,0.640625,0.6484375,,0.2,7,2,21,,200,,,16,5.086766958236694
+747,0.640625,0.640625,,0.2,7,2,22,,200,,,16,5.109104633331299
+748,0.6484375,0.6796875,,0.2,7,2,23,,200,,,16,5.045991659164429
+749,0.640625,0.6171875,,0.2,7,2,24,,200,,,16,5.121007442474365
+750,0.55078125,0.58984375,,0.2,8,2,0,,400,,,16,10.305009841918945
+751,0.57421875,0.60546875,,0.2,8,2,1,,400,,,16,10.484156608581543
+752,0.6328125,0.6484375,,0.2,8,2,2,,400,,,16,10.33700180053711
+753,0.6015625,0.59375,,0.2,8,2,3,,400,,,16,10.393001317977905
+754,0.5625,0.55859375,,0.2,8,2,4,,400,,,16,10.480171918869019
+755,0.57421875,0.58203125,,0.2,8,2,5,,400,,,16,10.425869464874268
+756,0.6171875,0.61328125,,0.2,8,2,6,,400,,,16,10.319247722625732
+757,0.5078125,0.53515625,,0.2,8,2,7,,400,,,16,10.524016618728638
+758,0.609375,0.59375,,0.2,8,2,8,,400,,,16,10.31999683380127
+759,0.61328125,0.6015625,,0.2,8,2,9,,400,,,16,10.479547262191772
+760,0.578125,0.55859375,,0.2,8,2,10,,400,,,16,10.490012645721436
+761,0.59765625,0.6015625,,0.2,8,2,11,,400,,,16,10.389009714126587
+762,0.609375,0.578125,,0.2,8,2,12,,400,,,16,10.306158781051636
+763,0.6328125,0.609375,,0.2,8,2,13,,400,,,16,10.448585510253906
+764,0.609375,0.5703125,,0.2,8,2,14,,400,,,16,10.274986267089844
+765,0.6171875,0.61328125,,0.2,8,2,15,,400,,,16,10.336298704147339
+766,0.62109375,0.62109375,,0.2,8,2,16,,400,,,16,10.334988117218018
+767,0.5859375,0.60546875,,0.2,8,2,17,,400,,,16,10.3822500705719
+768,0.58984375,0.57421875,,0.2,8,2,18,,400,,,16,10.307729721069336
+769,0.6171875,0.59765625,,0.2,8,2,19,,400,,,16,10.398988246917725
+770,0.56640625,0.57421875,,0.2,8,2,20,,400,,,16,10.347422361373901
+771,0.5859375,0.59375,,0.2,8,2,21,,400,,,16,10.396484136581421
+772,0.53515625,0.55859375,,0.2,8,2,22,,400,,,16,10.25699496269226
+773,0.6015625,0.5859375,,0.2,8,2,23,,400,,,16,10.412011623382568
+774,0.609375,0.62109375,,0.2,8,2,24,,400,,,16,10.32075047492981
+775,0.56640625,0.546875,,0.2,9,2,0,,800,,,16,28.974182605743408
+776,0.56640625,0.58984375,,0.2,9,2,1,,800,,,16,28.650411128997803
+777,0.572265625,0.552734375,,0.2,9,2,2,,800,,,16,28.89219570159912
+778,0.51953125,0.5390625,,0.2,9,2,3,,800,,,16,28.65997076034546
+779,0.541015625,0.52734375,,0.2,9,2,4,,800,,,16,28.861171007156372
+780,0.544921875,0.541015625,,0.2,9,2,5,,800,,,16,28.56504487991333
+781,0.544921875,0.544921875,,0.2,9,2,6,,800,,,16,28.789698362350464
+782,0.556640625,0.55859375,,0.2,9,2,7,,800,,,16,28.54499316215515
+783,0.591796875,0.572265625,,0.2,9,2,8,,800,,,16,28.74299645423889
+784,0.595703125,0.59765625,,0.2,9,2,9,,800,,,16,28.678799390792847
+785,0.6171875,0.591796875,,0.2,9,2,10,,800,,,16,28.8198344707489
+786,0.57421875,0.5546875,,0.2,9,2,11,,800,,,16,28.664626598358154
+787,0.546875,0.572265625,,0.2,9,2,12,,800,,,16,28.702959299087524
+788,0.580078125,0.568359375,,0.2,9,2,13,,800,,,16,28.575956344604492
+789,0.576171875,0.572265625,,0.2,9,2,14,,800,,,16,28.848121404647827
+790,0.517578125,0.544921875,,0.2,9,2,15,,800,,,16,28.621817588806152
+791,0.544921875,0.544921875,,0.2,9,2,16,,800,,,16,28.711308240890503
+792,0.55078125,0.546875,,0.2,9,2,17,,800,,,16,28.474000453948975
+793,0.5703125,0.5859375,,0.2,9,2,18,,800,,,16,28.727770566940308
+794,0.576171875,0.587890625,,0.2,9,2,19,,800,,,16,28.689268350601196
+795,0.55859375,0.576171875,,0.2,9,2,20,,800,,,16,28.678404808044434
+796,0.533203125,0.533203125,,0.2,9,2,21,,800,,,16,28.52360486984253
+797,0.544921875,0.55859375,,0.2,9,2,22,,800,,,16,28.64936351776123
+798,0.552734375,0.568359375,,0.2,9,2,23,,800,,,16,28.55361008644104
+799,0.5625,0.548828125,,0.2,9,2,24,,800,,,16,28.770488023757935
+800,1.0,1.0,,0.0,6,5,0,,100,,,16,3.453009605407715
+801,1.0,1.0,,0.0,6,5,1,,100,,,16,3.606991767883301
+802,1.0,1.0,,0.0,6,5,2,,100,,,16,3.4229977130889893
+803,1.0,1.0,,0.0,6,5,3,,100,,,16,3.440640687942505
+804,1.0,1.0,,0.0,6,5,4,,100,,,16,3.4700257778167725
+805,1.0,1.0,,0.0,6,5,5,,100,,,16,3.459017515182495
+806,1.0,1.0,,0.0,6,5,6,,100,,,16,3.512620687484741
+807,1.0,1.0,,0.0,6,5,7,,100,,,16,3.4659945964813232
+808,1.0,1.0,,0.0,6,5,8,,100,,,16,3.4470245838165283
+809,1.0,1.0,,0.0,6,5,9,,100,,,16,3.498993158340454
+810,1.0,1.0,,0.0,6,5,10,,100,,,16,3.6050026416778564
+811,1.0,1.0,,0.0,6,5,11,,100,,,16,3.487020492553711
+812,1.0,1.0,,0.0,6,5,12,,100,,,16,3.4796884059906006
+813,1.0,1.0,,0.0,6,5,13,,100,,,16,3.4959983825683594
+814,1.0,1.0,,0.0,6,5,14,,100,,,16,3.4515178203582764
+815,1.0,1.0,,0.0,6,5,15,,100,,,16,3.513274908065796
+816,1.0,1.0,,0.0,6,5,16,,100,,,16,3.4650328159332275
+817,1.0,1.0,,0.0,6,5,17,,100,,,16,3.4949913024902344
+818,1.0,1.0,,0.0,6,5,18,,100,,,16,3.469991445541382
+819,1.0,1.0,,0.0,6,5,19,,100,,,16,3.623985528945923
+820,1.0,1.0,,0.0,6,5,20,,100,,,16,3.492025375366211
+821,1.0,1.0,,0.0,6,5,21,,100,,,16,3.4749977588653564
+822,1.0,1.0,,0.0,6,5,22,,100,,,16,3.4860217571258545
+823,1.0,1.0,,0.0,6,5,23,,100,,,16,3.543081521987915
+824,1.0,1.0,,0.0,6,5,24,,100,,,16,3.5170185565948486
+825,0.984375,0.984375,,0.0,7,5,0,,200,,,16,5.1510329246521
+826,0.9921875,0.9921875,,0.0,7,5,1,,200,,,16,5.096007585525513
+827,0.984375,0.984375,,0.0,7,5,2,,200,,,16,5.241010904312134
+828,0.984375,0.984375,,0.0,7,5,3,,200,,,16,5.10599422454834
+829,1.0,1.0,,0.0,7,5,4,,200,,,16,5.146798849105835
+830,0.9921875,0.9921875,,0.0,7,5,5,,200,,,16,5.223026514053345
+831,0.984375,0.984375,,0.0,7,5,6,,200,,,16,5.105031251907349
+832,0.9765625,0.9765625,,0.0,7,5,7,,200,,,16,5.098022699356079
+833,0.984375,0.984375,,0.0,7,5,8,,200,,,16,5.202007293701172
+834,0.9765625,0.9765625,,0.0,7,5,9,,200,,,16,5.106022119522095
+835,0.9921875,0.9921875,,0.0,7,5,10,,200,,,16,5.385624647140503
+836,1.0,1.0,,0.0,7,5,11,,200,,,16,5.159000635147095
+837,0.984375,0.984375,,0.0,7,5,12,,200,,,16,5.12992000579834
+838,0.984375,0.984375,,0.0,7,5,13,,200,,,16,5.074986696243286
+839,1.0,1.0,,0.0,7,5,14,,200,,,16,5.166989326477051
+840,0.9921875,0.9921875,,0.0,7,5,15,,200,,,16,5.132998466491699
+841,0.9921875,0.9921875,,0.0,7,5,16,,200,,,16,5.129623889923096
+842,0.984375,0.984375,,0.0,7,5,17,,200,,,16,5.122988224029541
+843,0.9921875,0.9921875,,0.0,7,5,18,,200,,,16,5.143450736999512
+844,1.0,1.0,,0.0,7,5,19,,200,,,16,5.0899951457977295
+845,0.9921875,0.9921875,,0.0,7,5,20,,200,,,16,5.119024038314819
+846,0.9921875,0.9921875,,0.0,7,5,21,,200,,,16,5.128040313720703
+847,0.9765625,0.9765625,,0.0,7,5,22,,200,,,16,5.135540962219238
+848,1.0,1.0,,0.0,7,5,23,,200,,,16,5.091012716293335
+849,1.0,1.0,,0.0,7,5,24,,200,,,16,5.142017364501953
+850,0.93359375,0.93359375,,0.0,8,5,0,,400,,,16,10.499012231826782
+851,0.92578125,0.92578125,,0.0,8,5,1,,400,,,16,10.529584646224976
+852,0.94140625,0.94140625,,0.0,8,5,2,,400,,,16,10.441010475158691
+853,0.93359375,0.93359375,,0.0,8,5,3,,400,,,16,10.497997045516968
+854,0.92578125,0.92578125,,0.0,8,5,4,,400,,,16,10.499692440032959
+855,0.9375,0.9375,,0.0,8,5,5,,400,,,16,10.655568599700928
+856,0.93359375,0.93359375,,0.0,8,5,6,,400,,,16,10.452582836151123
+857,0.953125,0.953125,,0.0,8,5,7,,400,,,16,10.483989715576172
+858,0.9375,0.9375,,0.0,8,5,8,,400,,,16,10.453026533126831
+859,0.93359375,0.9375,,0.0,8,5,9,,400,,,16,10.480411291122437
+860,0.921875,0.921875,,0.0,8,5,10,,400,,,16,10.423033237457275
+861,0.90625,0.90625,,0.0,8,5,11,,400,,,16,10.468998193740845
+862,0.9140625,0.9140625,,0.0,8,5,12,,400,,,16,10.435163736343384
+863,0.9296875,0.9296875,,0.0,8,5,13,,400,,,16,10.556746482849121
+864,0.93359375,0.93359375,,0.0,8,5,14,,400,,,16,10.42498779296875
+865,0.9375,0.9375,,0.0,8,5,15,,400,,,16,10.476552486419678
+866,0.93359375,0.93359375,,0.0,8,5,16,,400,,,16,10.570025205612183
+867,0.9375,0.9375,,0.0,8,5,17,,400,,,16,10.536997318267822
+868,0.9296875,0.9296875,,0.0,8,5,18,,400,,,16,10.417565107345581
+869,0.9609375,0.9609375,,0.0,8,5,19,,400,,,16,10.596997499465942
+870,0.92578125,0.92578125,,0.0,8,5,20,,400,,,16,10.41201400756836
+871,0.92578125,0.92578125,,0.0,8,5,21,,400,,,16,10.459284782409668
+872,0.92578125,0.92578125,,0.0,8,5,22,,400,,,16,10.567001342773438
+873,0.9453125,0.9453125,,0.0,8,5,23,,400,,,16,10.525999307632446
+874,0.91015625,0.91015625,,0.0,8,5,24,,400,,,16,10.446213006973267
+875,0.859375,0.859375,,0.0,9,5,0,,800,,,16,29.46255874633789
+876,0.869140625,0.869140625,,0.0,9,5,1,,800,,,16,29.007813930511475
+877,0.884765625,0.884765625,,0.0,9,5,2,,800,,,16,29.106722354888916
+878,0.873046875,0.873046875,,0.0,9,5,3,,800,,,16,28.928203582763672
+879,0.896484375,0.896484375,,0.0,9,5,4,,800,,,16,29.290343523025513
+880,0.869140625,0.869140625,,0.0,9,5,5,,800,,,16,29.006873846054077
+881,0.8984375,0.8984375,,0.0,9,5,6,,800,,,16,29.28532886505127
+882,0.857421875,0.859375,,0.0,9,5,7,,800,,,16,29.078425645828247
+883,0.857421875,0.857421875,,0.0,9,5,8,,800,,,16,29.809881687164307
+884,0.876953125,0.876953125,,0.0,9,5,9,,800,,,16,29.67210578918457
+885,0.8515625,0.853515625,,0.0,9,5,10,,800,,,16,29.69359064102173
+886,0.873046875,0.873046875,,0.0,9,5,11,,800,,,16,29.47550868988037
+887,0.869140625,0.869140625,,0.0,9,5,12,,800,,,16,29.31025743484497
+888,0.873046875,0.873046875,,0.0,9,5,13,,800,,,16,29.134824514389038
+889,0.853515625,0.857421875,,0.0,9,5,14,,800,,,16,29.275604248046875
+890,0.869140625,0.869140625,,0.0,9,5,15,,800,,,16,28.933579206466675
+891,0.8828125,0.8828125,,0.0,9,5,16,,800,,,16,29.060291528701782
+892,0.8515625,0.85546875,,0.0,9,5,17,,800,,,16,28.94073724746704
+893,0.890625,0.890625,,0.0,9,5,18,,800,,,16,29.29896879196167
+894,0.849609375,0.849609375,,0.0,9,5,19,,800,,,16,28.962422609329224
+895,0.880859375,0.880859375,,0.0,9,5,20,,800,,,16,29.217981100082397
+896,0.857421875,0.857421875,,0.0,9,5,21,,800,,,16,28.987696886062622
+897,0.876953125,0.876953125,,0.0,9,5,22,,800,,,16,29.20370364189148
+898,0.875,0.875,,0.0,9,5,23,,800,,,16,28.955811500549316
+899,0.87890625,0.87890625,,0.0,9,5,24,,800,,,16,29.20948338508606
+900,1.0,1.0,,0.01,6,5,0,,100,,,16,3.4939920902252197
+901,1.0,1.0,,0.01,6,5,1,,100,,,16,3.556034564971924
+902,1.0,1.0,,0.01,6,5,2,,100,,,16,3.4328322410583496
+903,1.0,1.0,,0.01,6,5,3,,100,,,16,3.4454762935638428
+904,1.0,1.0,,0.01,6,5,4,,100,,,16,3.472991704940796
+905,1.0,1.0,,0.01,6,5,5,,100,,,16,3.5180089473724365
+906,1.0,1.0,,0.01,6,5,6,,100,,,16,3.5009918212890625
+907,1.0,1.0,,0.01,6,5,7,,100,,,16,3.4879887104034424
+908,1.0,1.0,,0.01,6,5,8,,100,,,16,3.448021173477173
+909,1.0,1.0,,0.01,6,5,9,,100,,,16,3.4779958724975586
+910,1.0,1.0,,0.01,6,5,10,,100,,,16,3.5982093811035156
+911,1.0,1.0,,0.01,6,5,11,,100,,,16,3.495187520980835
+912,1.0,1.0,,0.01,6,5,12,,100,,,16,3.466019630432129
+913,1.0,1.0,,0.01,6,5,13,,100,,,16,3.503988742828369
+914,1.0,1.0,,0.01,6,5,14,,100,,,16,3.516019582748413
+915,1.0,1.0,,0.01,6,5,15,,100,,,16,3.496994972229004
+916,1.0,1.0,,0.01,6,5,16,,100,,,16,3.4570186138153076
+917,1.0,1.0,,0.01,6,5,17,,100,,,16,3.4870052337646484
+918,1.0,1.0,,0.01,6,5,18,,100,,,16,3.4720096588134766
+919,1.0,1.0,,0.01,6,5,19,,100,,,16,3.6104366779327393
+920,1.0,1.0,,0.01,6,5,20,,100,,,16,3.4739859104156494
+921,1.0,1.0,,0.01,6,5,21,,100,,,16,3.546003580093384
+922,1.0,1.0,,0.01,6,5,22,,100,,,16,3.4710123538970947
+923,1.0,1.0,,0.01,6,5,23,,100,,,16,3.533005714416504
+924,1.0,1.0,,0.01,6,5,24,,100,,,16,3.476008176803589
+925,0.96875,0.96875,,0.01,7,5,0,,200,,,16,5.169995069503784
+926,0.9765625,0.9765625,,0.01,7,5,1,,200,,,16,5.149332523345947
+927,0.9765625,0.9765625,,0.01,7,5,2,,200,,,16,5.284024238586426
+928,0.96875,0.96875,,0.01,7,5,3,,200,,,16,5.121992349624634
+929,0.9609375,0.96875,,0.01,7,5,4,,200,,,16,5.174986362457275
+930,0.96875,0.9765625,,0.01,7,5,5,,200,,,16,5.257188081741333
+931,0.9609375,0.9609375,,0.01,7,5,6,,200,,,16,5.128007173538208
+932,0.984375,0.984375,,0.01,7,5,7,,200,,,16,5.126816987991333
+933,0.9921875,0.9921875,,0.01,7,5,8,,200,,,16,5.306016206741333
+934,0.96875,0.9765625,,0.01,7,5,9,,200,,,16,5.133007049560547
+935,0.9609375,0.96875,,0.01,7,5,10,,200,,,16,5.123411417007446
+936,0.984375,0.9921875,,0.01,7,5,11,,200,,,16,5.2121803760528564
+937,0.9765625,0.9765625,,0.01,7,5,12,,200,,,16,5.161005735397339
+938,0.984375,0.9921875,,0.01,7,5,13,,200,,,16,5.14164400100708
+939,0.9921875,0.9921875,,0.01,7,5,14,,200,,,16,5.2510151863098145
+940,0.984375,0.9921875,,0.01,7,5,15,,200,,,16,5.109003067016602
+941,0.9921875,0.9921875,,0.01,7,5,16,,200,,,16,5.181010484695435
+942,0.984375,0.984375,,0.01,7,5,17,,200,,,16,5.2215330600738525
+943,0.96875,0.96875,,0.01,7,5,18,,200,,,16,5.1766791343688965
+944,0.96875,0.96875,,0.01,7,5,19,,200,,,16,5.131018877029419
+945,0.9609375,0.96875,,0.01,7,5,20,,200,,,16,5.319007396697998
+946,0.984375,0.984375,,0.01,7,5,21,,200,,,16,5.154003381729126
+947,0.9609375,0.96875,,0.01,7,5,22,,200,,,16,5.178006887435913
+948,0.984375,0.984375,,0.01,7,5,23,,200,,,16,5.191014051437378
+949,1.0,1.0,,0.01,7,5,24,,200,,,16,5.174424886703491
+950,0.87890625,0.890625,,0.01,8,5,0,,400,,,16,10.495024681091309
+951,0.90234375,0.90234375,,0.01,8,5,1,,400,,,16,10.593720197677612
+952,0.875,0.87890625,,0.01,8,5,2,,400,,,16,10.511624813079834
+953,0.93359375,0.93359375,,0.01,8,5,3,,400,,,16,10.530990600585938
+954,0.9296875,0.9296875,,0.01,8,5,4,,400,,,16,10.518988132476807
+955,0.93359375,0.93359375,,0.01,8,5,5,,400,,,16,10.564791440963745
+956,0.91015625,0.91796875,,0.01,8,5,6,,400,,,16,10.498990058898926
+957,0.92578125,0.92578125,,0.01,8,5,7,,400,,,16,10.551996946334839
+958,0.91796875,0.921875,,0.01,8,5,8,,400,,,16,10.521017074584961
+959,0.87890625,0.8828125,,0.01,8,5,9,,400,,,16,10.573038339614868
+960,0.91015625,0.9140625,,0.01,8,5,10,,400,,,16,10.478999376296997
+961,0.890625,0.8984375,,0.01,8,5,11,,400,,,16,10.545480489730835
+962,0.9296875,0.93359375,,0.01,8,5,12,,400,,,16,10.526989221572876
+963,0.89453125,0.90234375,,0.01,8,5,13,,400,,,16,10.471617221832275
+964,0.875,0.87890625,,0.01,8,5,14,,400,,,16,10.494994401931763
+965,0.91796875,0.921875,,0.01,8,5,15,,400,,,16,10.527011394500732
+966,0.88671875,0.88671875,,0.01,8,5,16,,400,,,16,11.046267747879028
+967,0.87109375,0.87890625,,0.01,8,5,17,,400,,,16,10.598992109298706
+968,0.9140625,0.9140625,,0.01,8,5,18,,400,,,16,10.440991640090942
+969,0.8984375,0.90234375,,0.01,8,5,19,,400,,,16,10.512691020965576
+970,0.87890625,0.8828125,,0.01,8,5,20,,400,,,16,10.43298625946045
+971,0.90234375,0.91015625,,0.01,8,5,21,,400,,,16,10.516987562179565
+972,0.89453125,0.8984375,,0.01,8,5,22,,400,,,16,10.476348876953125
+973,0.8984375,0.8984375,,0.01,8,5,23,,400,,,16,10.547989845275879
+974,0.89453125,0.8984375,,0.01,8,5,24,,400,,,16,10.46799111366272
+975,0.80078125,0.8046875,,0.01,9,5,0,,800,,,16,29.272345781326294
+976,0.818359375,0.8203125,,0.01,9,5,1,,800,,,16,29.213220596313477
+977,0.79296875,0.80078125,,0.01,9,5,2,,800,,,16,29.132797479629517
+978,0.833984375,0.833984375,,0.01,9,5,3,,800,,,16,29.12754774093628
+979,0.7890625,0.7890625,,0.01,9,5,4,,800,,,16,29.140511751174927
+980,0.83203125,0.8359375,,0.01,9,5,5,,800,,,16,28.984861373901367
+981,0.822265625,0.82421875,,0.01,9,5,6,,800,,,16,29.105563640594482
+982,0.8125,0.8125,,0.01,9,5,7,,800,,,16,28.927231788635254
+983,0.787109375,0.794921875,,0.01,9,5,8,,800,,,16,29.116933822631836
+984,0.83984375,0.83984375,,0.01,9,5,9,,800,,,16,29.335166215896606
+985,0.80859375,0.80859375,,0.01,9,5,10,,800,,,16,29.61337947845459
+986,0.779296875,0.78125,,0.01,9,5,11,,800,,,16,28.90134334564209
+987,0.822265625,0.828125,,0.01,9,5,12,,800,,,16,29.253705739974976
+988,0.814453125,0.814453125,,0.01,9,5,13,,800,,,16,28.993779182434082
+989,0.79296875,0.794921875,,0.01,9,5,14,,800,,,16,28.966476440429688
+990,0.818359375,0.818359375,,0.01,9,5,15,,800,,,16,28.881546020507812
+991,0.822265625,0.82421875,,0.01,9,5,16,,800,,,16,29.244828462600708
+992,0.818359375,0.818359375,,0.01,9,5,17,,800,,,16,28.993690729141235
+993,0.822265625,0.822265625,,0.01,9,5,18,,800,,,16,29.19780945777893
+994,0.8046875,0.810546875,,0.01,9,5,19,,800,,,16,29.176836013793945
+995,0.8203125,0.82421875,,0.01,9,5,20,,800,,,16,29.144786596298218
+996,0.796875,0.80078125,,0.01,9,5,21,,800,,,16,29.190051317214966
+997,0.818359375,0.818359375,,0.01,9,5,22,,800,,,16,29.03595805168152
+998,0.8125,0.81640625,,0.01,9,5,23,,800,,,16,28.764297008514404
+999,0.79296875,0.794921875,,0.01,9,5,24,,800,,,16,29.20928955078125
+1000,0.890625,0.90625,,0.1,6,5,0,,100,,,16,3.4219915866851807
+1001,0.921875,0.921875,,0.1,6,5,1,,100,,,16,3.5839931964874268
+1002,0.953125,0.953125,,0.1,6,5,2,,100,,,16,3.4499075412750244
+1003,0.90625,0.90625,,0.1,6,5,3,,100,,,16,3.4369916915893555
+1004,0.90625,0.90625,,0.1,6,5,4,,100,,,16,3.4410109519958496
+1005,0.90625,0.921875,,0.1,6,5,5,,100,,,16,3.514024019241333
+1006,0.9375,0.953125,,0.1,6,5,6,,100,,,16,3.5040762424468994
+1007,0.921875,0.921875,,0.1,6,5,7,,100,,,16,3.4807896614074707
+1008,0.90625,0.90625,,0.1,6,5,8,,100,,,16,3.455017566680908
+1009,0.921875,0.921875,,0.1,6,5,9,,100,,,16,3.491007089614868
+1010,0.984375,0.984375,,0.1,6,5,10,,100,,,16,3.5741355419158936
+1011,0.96875,0.953125,,0.1,6,5,11,,100,,,16,3.4839744567871094
+1012,0.953125,0.96875,,0.1,6,5,12,,100,,,16,3.4841980934143066
+1013,0.890625,0.90625,,0.1,6,5,13,,100,,,16,3.5059921741485596
+1014,0.921875,0.953125,,0.1,6,5,14,,100,,,16,3.523991346359253
+1015,0.96875,0.984375,,0.1,6,5,15,,100,,,16,3.5010251998901367
+1016,0.96875,0.953125,,0.1,6,5,16,,100,,,16,3.483018398284912
+1017,0.921875,0.921875,,0.1,6,5,17,,100,,,16,3.493008852005005
+1018,0.9375,0.9375,,0.1,6,5,18,,100,,,16,3.5070016384124756
+1019,0.984375,0.984375,,0.1,6,5,19,,100,,,16,3.616575241088867
+1020,0.90625,0.921875,,0.1,6,5,20,,100,,,16,3.476992130279541
+1021,0.9375,0.9375,,0.1,6,5,21,,100,,,16,3.487016439437866
+1022,1.0,1.0,,0.1,6,5,22,,100,,,16,3.472018241882324
+1023,0.953125,0.9375,,0.1,6,5,23,,100,,,16,3.578359842300415
+1024,0.953125,0.96875,,0.1,6,5,24,,100,,,16,3.515993118286133
+1025,0.8125,0.8203125,,0.1,7,5,0,,200,,,16,5.17699933052063
+1026,0.8359375,0.8515625,,0.1,7,5,1,,200,,,16,5.097018241882324
+1027,0.8125,0.8125,,0.1,7,5,2,,200,,,16,5.2159528732299805
+1028,0.8203125,0.84375,,0.1,7,5,3,,200,,,16,5.0880303382873535
+1029,0.828125,0.8359375,,0.1,7,5,4,,200,,,16,5.1485631465911865
+1030,0.8046875,0.8125,,0.1,7,5,5,,200,,,16,5.212008953094482
+1031,0.8125,0.8046875,,0.1,7,5,6,,200,,,16,5.127736568450928
+1032,0.75,0.7734375,,0.1,7,5,7,,200,,,16,5.136999607086182
+1033,0.7734375,0.7890625,,0.1,7,5,8,,200,,,16,5.276987552642822
+1034,0.796875,0.8125,,0.1,7,5,9,,200,,,16,5.072996616363525
+1035,0.8515625,0.875,,0.1,7,5,10,,200,,,16,5.129194498062134
+1036,0.7890625,0.796875,,0.1,7,5,11,,200,,,16,5.212035179138184
+1037,0.8515625,0.84375,,0.1,7,5,12,,200,,,16,5.134022951126099
+1038,0.796875,0.8125,,0.1,7,5,13,,200,,,16,5.081996440887451
+1039,0.828125,0.8359375,,0.1,7,5,14,,200,,,16,5.192009925842285
+1040,0.828125,0.84375,,0.1,7,5,15,,200,,,16,5.088992595672607
+1041,0.828125,0.828125,,0.1,7,5,16,,200,,,16,5.129700422286987
+1042,0.796875,0.8046875,,0.1,7,5,17,,200,,,16,5.220031976699829
+1043,0.796875,0.8359375,,0.1,7,5,18,,200,,,16,5.11099648475647
+1044,0.8359375,0.84375,,0.1,7,5,19,,200,,,16,5.099012613296509
+1045,0.828125,0.828125,,0.1,7,5,20,,200,,,16,5.202999830245972
+1046,0.8359375,0.84375,,0.1,7,5,21,,200,,,16,5.104991912841797
+1047,0.84375,0.84375,,0.1,7,5,22,,200,,,16,5.103177547454834
+1048,0.734375,0.734375,,0.1,7,5,23,,200,,,16,5.0870232582092285
+1049,0.859375,0.859375,,0.1,7,5,24,,200,,,16,5.160994052886963
+1050,0.67578125,0.6953125,,0.1,8,5,0,,400,,,16,10.401010274887085
+1051,0.69140625,0.68359375,,0.1,8,5,1,,400,,,16,10.456748962402344
+1052,0.69140625,0.703125,,0.1,8,5,2,,400,,,16,10.364996671676636
+1053,0.69921875,0.703125,,0.1,8,5,3,,400,,,16,10.447014093399048
+1054,0.734375,0.765625,,0.1,8,5,4,,400,,,16,10.413749694824219
+1055,0.69140625,0.68359375,,0.1,8,5,5,,400,,,16,10.512811422348022
+1056,0.69140625,0.69140625,,0.1,8,5,6,,400,,,16,10.36499547958374
+1057,0.68359375,0.72265625,,0.1,8,5,7,,400,,,16,10.424655199050903
+1058,0.6953125,0.71484375,,0.1,8,5,8,,400,,,16,10.403014421463013
+1059,0.703125,0.7265625,,0.1,8,5,9,,400,,,16,10.490333795547485
+1060,0.6640625,0.67578125,,0.1,8,5,10,,400,,,16,10.404167890548706
+1061,0.71484375,0.703125,,0.1,8,5,11,,400,,,16,10.40199065208435
+1062,0.765625,0.7734375,,0.1,8,5,12,,400,,,16,10.36599850654602
+1063,0.73046875,0.73046875,,0.1,8,5,13,,400,,,16,10.518819808959961
+1064,0.734375,0.7265625,,0.1,8,5,14,,400,,,16,10.418994665145874
+1065,0.67578125,0.6640625,,0.1,8,5,15,,400,,,16,10.381176948547363
+1066,0.67578125,0.6796875,,0.1,8,5,16,,400,,,16,10.482006788253784
+1067,0.6875,0.6953125,,0.1,8,5,17,,400,,,16,10.476115465164185
+1068,0.609375,0.65234375,,0.1,8,5,18,,400,,,16,10.415660858154297
+1069,0.66015625,0.6953125,,0.1,8,5,19,,400,,,16,10.555989265441895
+1070,0.69921875,0.7109375,,0.1,8,5,20,,400,,,16,10.374988555908203
+1071,0.72265625,0.73046875,,0.1,8,5,21,,400,,,16,10.401241064071655
+1072,0.71484375,0.734375,,0.1,8,5,22,,400,,,16,10.484023571014404
+1073,0.65625,0.69140625,,0.1,8,5,23,,400,,,16,10.407008647918701
+1074,0.71875,0.734375,,0.1,8,5,24,,400,,,16,10.37588095664978
+1075,0.611328125,0.6328125,,0.1,9,5,0,,800,,,16,29.152113437652588
+1076,0.62890625,0.671875,,0.1,9,5,1,,800,,,16,28.734443187713623
+1077,0.650390625,0.662109375,,0.1,9,5,2,,800,,,16,29.013980388641357
+1078,0.619140625,0.62890625,,0.1,9,5,3,,800,,,16,28.8145694732666
+1079,0.625,0.619140625,,0.1,9,5,4,,800,,,16,28.938399076461792
+1080,0.619140625,0.625,,0.1,9,5,5,,800,,,16,28.778600692749023
+1081,0.6171875,0.619140625,,0.1,9,5,6,,800,,,16,28.97702169418335
+1082,0.669921875,0.65234375,,0.1,9,5,7,,800,,,16,28.722559213638306
+1083,0.62109375,0.615234375,,0.1,9,5,8,,800,,,16,28.784847736358643
+1084,0.6328125,0.640625,,0.1,9,5,9,,800,,,16,28.582732677459717
+1085,0.6328125,0.6328125,,0.1,9,5,10,,800,,,16,29.036587238311768
+1086,0.59765625,0.62890625,,0.1,9,5,11,,800,,,16,28.572702407836914
+1087,0.623046875,0.6171875,,0.1,9,5,12,,800,,,16,28.839388608932495
+1088,0.609375,0.607421875,,0.1,9,5,13,,800,,,16,28.68613624572754
+1089,0.609375,0.64453125,,0.1,9,5,14,,800,,,16,28.729718923568726
+1090,0.63671875,0.625,,0.1,9,5,15,,800,,,16,28.690807342529297
+1091,0.65234375,0.65625,,0.1,9,5,16,,800,,,16,28.80867290496826
+1092,0.603515625,0.615234375,,0.1,9,5,17,,800,,,16,28.61693286895752
+1093,0.609375,0.609375,,0.1,9,5,18,,800,,,16,28.82337975502014
+1094,0.63671875,0.65234375,,0.1,9,5,19,,800,,,16,28.6285297870636
+1095,0.587890625,0.599609375,,0.1,9,5,20,,800,,,16,28.879366636276245
+1096,0.6171875,0.611328125,,0.1,9,5,21,,800,,,16,28.622166633605957
+1097,0.603515625,0.625,,0.1,9,5,22,,800,,,16,28.88223624229431
+1098,0.626953125,0.625,,0.1,9,5,23,,800,,,16,28.637573957443237
+1099,0.65625,0.662109375,,0.1,9,5,24,,800,,,16,28.72325587272644
+1100,0.8125,0.84375,,0.2,6,5,0,,100,,,16,3.490992784500122
+1101,0.90625,0.890625,,0.2,6,5,1,,100,,,16,3.4490089416503906
+1102,0.765625,0.8125,,0.2,6,5,2,,100,,,16,3.398993730545044
+1103,0.828125,0.828125,,0.2,6,5,3,,100,,,16,3.5333924293518066
+1104,0.84375,0.828125,,0.2,6,5,4,,100,,,16,3.5945780277252197
+1105,0.828125,0.84375,,0.2,6,5,5,,100,,,16,3.507999897003174
+1106,0.6875,0.71875,,0.2,6,5,6,,100,,,16,3.4776906967163086
+1107,0.796875,0.84375,,0.2,6,5,7,,100,,,16,3.4547038078308105
+1108,0.78125,0.828125,,0.2,6,5,8,,100,,,16,3.4940237998962402
+1109,0.890625,0.875,,0.2,6,5,9,,100,,,16,3.5450122356414795
+1110,0.875,0.859375,,0.2,6,5,10,,100,,,16,3.489015579223633
+1111,0.796875,0.78125,,0.2,6,5,11,,100,,,16,3.476025342941284
+1112,0.828125,0.8125,,0.2,6,5,12,,100,,,16,3.448009729385376
+1113,0.8125,0.828125,,0.2,6,5,13,,100,,,16,3.6286070346832275
+1114,0.78125,0.8125,,0.2,6,5,14,,100,,,16,3.503953456878662
+1115,0.859375,0.859375,,0.2,6,5,15,,100,,,16,3.4749882221221924
+1116,0.78125,0.765625,,0.2,6,5,16,,100,,,16,3.4840216636657715
+1117,0.828125,0.859375,,0.2,6,5,17,,100,,,16,3.4849960803985596
+1118,0.859375,0.875,,0.2,6,5,18,,100,,,16,3.505021810531616
+1119,0.875,0.875,,0.2,6,5,19,,100,,,16,3.5073535442352295
+1120,0.734375,0.8125,,0.2,6,5,20,,100,,,16,3.517014741897583
+1121,0.875,0.859375,,0.2,6,5,21,,100,,,16,3.4889984130859375
+1122,0.8125,0.796875,,0.2,6,5,22,,100,,,16,3.6299867630004883
+1123,0.828125,0.859375,,0.2,6,5,23,,100,,,16,3.491992950439453
+1124,0.6875,0.734375,,0.2,6,5,24,,100,,,16,3.4645278453826904
+1125,0.703125,0.7421875,,0.2,7,5,0,,200,,,16,5.129019737243652
+1126,0.7421875,0.7734375,,0.2,7,5,1,,200,,,16,5.203016042709351
+1127,0.71875,0.7109375,,0.2,7,5,2,,200,,,16,5.1289873123168945
+1128,0.703125,0.6953125,,0.2,7,5,3,,200,,,16,5.06002402305603
+1129,0.7109375,0.6953125,,0.2,7,5,4,,200,,,16,5.219765663146973
+1130,0.7578125,0.75,,0.2,7,5,5,,200,,,16,5.092016935348511
+1131,0.71875,0.703125,,0.2,7,5,6,,200,,,16,5.147996664047241
+1132,0.71875,0.6875,,0.2,7,5,7,,200,,,16,5.141993522644043
+1133,0.734375,0.7578125,,0.2,7,5,8,,200,,,16,5.181993722915649
+1134,0.640625,0.703125,,0.2,7,5,9,,200,,,16,5.042993783950806
+1135,0.75,0.75,,0.2,7,5,10,,200,,,16,5.146208047866821
+1136,0.6640625,0.6328125,,0.2,7,5,11,,200,,,16,5.116005182266235
+1137,0.7109375,0.75,,0.2,7,5,12,,200,,,16,5.122016429901123
+1138,0.7109375,0.71875,,0.2,7,5,13,,200,,,16,5.088019847869873
+1139,0.6484375,0.7265625,,0.2,7,5,14,,200,,,16,5.077881574630737
+1140,0.734375,0.703125,,0.2,7,5,15,,200,,,16,5.070522308349609
+1141,0.6875,0.7265625,,0.2,7,5,16,,200,,,16,5.093997001647949
+1142,0.71875,0.703125,,0.2,7,5,17,,200,,,16,5.103023529052734
+1143,0.7109375,0.7265625,,0.2,7,5,18,,200,,,16,5.104022741317749
+1144,0.75,0.765625,,0.2,7,5,19,,200,,,16,5.086998224258423
+1145,0.6796875,0.671875,,0.2,7,5,20,,200,,,16,5.154989957809448
+1146,0.6796875,0.703125,,0.2,7,5,21,,200,,,16,5.067729711532593
+1147,0.71875,0.734375,,0.2,7,5,22,,200,,,16,5.100996971130371
+1148,0.75,0.7734375,,0.2,7,5,23,,200,,,16,5.116986513137817
+1149,0.703125,0.703125,,0.2,7,5,24,,200,,,16,5.112988710403442
+1150,0.609375,0.61328125,,0.2,8,5,0,,400,,,16,10.409672737121582
+1151,0.6640625,0.65234375,,0.2,8,5,1,,400,,,16,10.439101219177246
+1152,0.640625,0.6328125,,0.2,8,5,2,,400,,,16,10.564035177230835
+1153,0.5703125,0.56640625,,0.2,8,5,3,,400,,,16,10.475021839141846
+1154,0.6171875,0.6171875,,0.2,8,5,4,,400,,,16,10.387222051620483
+1155,0.59375,0.61328125,,0.2,8,5,5,,400,,,16,10.481853246688843
+1156,0.65625,0.66015625,,0.2,8,5,6,,400,,,16,10.354025602340698
+1157,0.66015625,0.64453125,,0.2,8,5,7,,400,,,16,10.427994012832642
+1158,0.65234375,0.66796875,,0.2,8,5,8,,400,,,16,10.472991228103638
+1159,0.58984375,0.59765625,,0.2,8,5,9,,400,,,16,10.390900135040283
+1160,0.625,0.61328125,,0.2,8,5,10,,400,,,16,10.321015357971191
+1161,0.64453125,0.65234375,,0.2,8,5,11,,400,,,16,10.446006774902344
+1162,0.6328125,0.62109375,,0.2,8,5,12,,400,,,16,10.382147312164307
+1163,0.60546875,0.60546875,,0.2,8,5,13,,400,,,16,10.389691829681396
+1164,0.61328125,0.65625,,0.2,8,5,14,,400,,,16,10.372020959854126
+1165,0.6640625,0.6640625,,0.2,8,5,15,,400,,,16,10.376002073287964
+1166,0.6328125,0.63671875,,0.2,8,5,16,,400,,,16,10.305006742477417
+1167,0.61328125,0.63671875,,0.2,8,5,17,,400,,,16,10.463254690170288
+1168,0.62109375,0.6171875,,0.2,8,5,18,,400,,,16,10.322692394256592
+1169,0.60546875,0.58984375,,0.2,8,5,19,,400,,,16,10.420023202896118
+1170,0.6171875,0.58984375,,0.2,8,5,20,,400,,,16,10.375995635986328
+1171,0.63671875,0.62890625,,0.2,8,5,21,,400,,,16,10.365663528442383
+1172,0.59765625,0.609375,,0.2,8,5,22,,400,,,16,10.329020261764526
+1173,0.61328125,0.62890625,,0.2,8,5,23,,400,,,16,10.417992115020752
+1174,0.6328125,0.6328125,,0.2,8,5,24,,400,,,16,10.330694437026978
+1175,0.546875,0.548828125,,0.2,9,5,0,,800,,,16,28.964691162109375
+1176,0.580078125,0.59375,,0.2,9,5,1,,800,,,16,28.798337697982788
+1177,0.56640625,0.55859375,,0.2,9,5,2,,800,,,16,28.982088327407837
+1178,0.564453125,0.55859375,,0.2,9,5,3,,800,,,16,28.74756145477295
+1179,0.55078125,0.55859375,,0.2,9,5,4,,800,,,16,28.809473752975464
+1180,0.564453125,0.576171875,,0.2,9,5,5,,800,,,16,28.591128826141357
+1181,0.56640625,0.56640625,,0.2,9,5,6,,800,,,16,29.062695741653442
+1182,0.564453125,0.56640625,,0.2,9,5,7,,800,,,16,28.617886543273926
+1183,0.5859375,0.611328125,,0.2,9,5,8,,800,,,16,28.858093738555908
+1184,0.546875,0.56640625,,0.2,9,5,9,,800,,,16,28.768563508987427
+1185,0.583984375,0.6015625,,0.2,9,5,10,,800,,,16,28.855273246765137
+1186,0.578125,0.568359375,,0.2,9,5,11,,800,,,16,28.743011713027954
+1187,0.572265625,0.576171875,,0.2,9,5,12,,800,,,16,28.725401639938354
+1188,0.5859375,0.58203125,,0.2,9,5,13,,800,,,16,28.57799506187439
+1189,0.55859375,0.576171875,,0.2,9,5,14,,800,,,16,28.707963466644287
+1190,0.587890625,0.58984375,,0.2,9,5,15,,800,,,16,28.542900323867798
+1191,0.5625,0.580078125,,0.2,9,5,16,,800,,,16,28.910313367843628
+1192,0.59375,0.59765625,,0.2,9,5,17,,800,,,16,28.648618698120117
+1193,0.529296875,0.560546875,,0.2,9,5,18,,800,,,16,28.825318336486816
+1194,0.5859375,0.568359375,,0.2,9,5,19,,800,,,16,28.6441593170166
+1195,0.583984375,0.580078125,,0.2,9,5,20,,800,,,16,28.709838390350342
+1196,0.53515625,0.583984375,,0.2,9,5,21,,800,,,16,28.56199073791504
+1197,0.5546875,0.552734375,,0.2,9,5,22,,800,,,16,28.655017614364624
+1198,0.57421875,0.572265625,,0.2,9,5,23,,800,,,16,28.53298044204712
+1199,0.55859375,0.56640625,,0.2,9,5,24,,800,,,16,28.87242865562439
+1200,1.0,1.0,,0.0,6,10,0,,100,,,16,3.4552524089813232
+1201,1.0,1.0,,0.0,6,10,1,,100,,,16,3.4339993000030518
+1202,1.0,1.0,,0.0,6,10,2,,100,,,16,3.438992500305176
+1203,1.0,1.0,,0.0,6,10,3,,100,,,16,3.437020778656006
+1204,1.0,1.0,,0.0,6,10,4,,100,,,16,3.5169970989227295
+1205,1.0,1.0,,0.0,6,10,5,,100,,,16,3.533000946044922
+1206,1.0,1.0,,0.0,6,10,6,,100,,,16,3.4746170043945312
+1207,1.0,1.0,,0.0,6,10,7,,100,,,16,3.492654800415039
+1208,1.0,1.0,,0.0,6,10,8,,100,,,16,3.5969910621643066
+1209,1.0,1.0,,0.0,6,10,9,,100,,,16,3.502991199493408
+1210,1.0,1.0,,0.0,6,10,10,,100,,,16,3.4659860134124756
+1211,1.0,1.0,,0.0,6,10,11,,100,,,16,3.453990936279297
+1212,1.0,1.0,,0.0,6,10,12,,100,,,16,3.478990316390991
+1213,1.0,1.0,,0.0,6,10,13,,100,,,16,3.5499942302703857
+1214,1.0,1.0,,0.0,6,10,14,,100,,,16,3.4607787132263184
+1215,1.0,1.0,,0.0,6,10,15,,100,,,16,3.4715347290039062
+1216,1.0,1.0,,0.0,6,10,16,,100,,,16,3.4980359077453613
+1217,1.0,1.0,,0.0,6,10,17,,100,,,16,3.618990421295166
+1218,1.0,1.0,,0.0,6,10,18,,100,,,16,3.4937686920166016
+1219,1.0,1.0,,0.0,6,10,19,,100,,,16,3.4944348335266113
+1220,1.0,1.0,,0.0,6,10,20,,100,,,16,3.4607644081115723
+1221,1.0,1.0,,0.0,6,10,21,,100,,,16,3.503995656967163
+1222,1.0,1.0,,0.0,6,10,22,,100,,,16,3.50400710105896
+1223,1.0,1.0,,0.0,6,10,23,,100,,,16,3.4765625
+1224,1.0,1.0,,0.0,6,10,24,,100,,,16,3.4790196418762207
+1225,0.9921875,0.9921875,,0.0,7,10,0,,200,,,16,5.180008888244629
+1226,0.9765625,0.984375,,0.0,7,10,1,,200,,,16,5.116009950637817
+1227,0.9921875,0.9921875,,0.0,7,10,2,,200,,,16,5.128864288330078
+1228,1.0,1.0,,0.0,7,10,3,,200,,,16,5.128991365432739
+1229,1.0,1.0,,0.0,7,10,4,,200,,,16,5.178563594818115
+1230,0.984375,0.984375,,0.0,7,10,5,,200,,,16,5.103995084762573
+1231,0.9921875,0.9921875,,0.0,7,10,6,,200,,,16,5.352992534637451
+1232,0.9921875,0.9921875,,0.0,7,10,7,,200,,,16,5.144988536834717
+1233,0.984375,0.984375,,0.0,7,10,8,,200,,,16,5.148993253707886
+1234,0.984375,0.984375,,0.0,7,10,9,,200,,,16,5.144989013671875
+1235,0.96875,0.96875,,0.0,7,10,10,,200,,,16,5.246232271194458
+1236,0.9921875,0.9921875,,0.0,7,10,11,,200,,,16,5.109001874923706
+1237,0.9921875,0.9921875,,0.0,7,10,12,,200,,,16,5.139007091522217
+1238,0.9921875,0.9921875,,0.0,7,10,13,,200,,,16,5.198998212814331
+1239,1.0,1.0,,0.0,7,10,14,,200,,,16,5.152765989303589
+1240,0.984375,0.9921875,,0.0,7,10,15,,200,,,16,5.126269578933716
+1241,0.9921875,0.9921875,,0.0,7,10,16,,200,,,16,5.274996042251587
+1242,0.984375,0.984375,,0.0,7,10,17,,200,,,16,5.138019800186157
+1243,0.96875,0.96875,,0.0,7,10,18,,200,,,16,5.131315231323242
+1244,0.9921875,0.9921875,,0.0,7,10,19,,200,,,16,5.234992980957031
+1245,0.9921875,0.9921875,,0.0,7,10,20,,200,,,16,5.1719958782196045
+1246,0.984375,0.984375,,0.0,7,10,21,,200,,,16,5.166120290756226
+1247,0.984375,1.0,,0.0,7,10,22,,200,,,16,5.266188144683838
+1248,1.0,1.0,,0.0,7,10,23,,200,,,16,5.110990524291992
+1249,0.9921875,0.9921875,,0.0,7,10,24,,200,,,16,5.170984268188477
+1250,0.921875,0.921875,,0.0,8,10,0,,400,,,16,10.624985694885254
+1251,0.93359375,0.93359375,,0.0,8,10,1,,400,,,16,10.51683783531189
+1252,0.94140625,0.94140625,,0.0,8,10,2,,400,,,16,10.465991258621216
+1253,0.94140625,0.94140625,,0.0,8,10,3,,400,,,16,10.590267181396484
+1254,0.9296875,0.9296875,,0.0,8,10,4,,400,,,16,10.452014446258545
+1255,0.93359375,0.9375,,0.0,8,10,5,,400,,,16,10.496606349945068
+1256,0.92578125,0.92578125,,0.0,8,10,6,,400,,,16,10.536128520965576
+1257,0.93359375,0.93359375,,0.0,8,10,7,,400,,,16,10.533016920089722
+1258,0.921875,0.921875,,0.0,8,10,8,,400,,,16,10.480011463165283
+1259,0.94140625,0.94140625,,0.0,8,10,9,,400,,,16,10.616207599639893
+1260,0.94140625,0.94140625,,0.0,8,10,10,,400,,,16,10.440994501113892
+1261,0.9296875,0.9296875,,0.0,8,10,11,,400,,,16,10.5020170211792
+1262,0.93359375,0.93359375,,0.0,8,10,12,,400,,,16,10.520108461380005
+1263,0.9453125,0.9453125,,0.0,8,10,13,,400,,,16,10.531322956085205
+1264,0.91796875,0.91796875,,0.0,8,10,14,,400,,,16,10.513023138046265
+1265,0.9296875,0.9296875,,0.0,8,10,15,,400,,,16,10.638848543167114
+1266,0.9296875,0.93359375,,0.0,8,10,16,,400,,,16,10.483002424240112
+1267,0.921875,0.921875,,0.0,8,10,17,,400,,,16,10.521065950393677
+1268,0.9296875,0.9296875,,0.0,8,10,18,,400,,,16,10.484614372253418
+1269,0.9453125,0.9453125,,0.0,8,10,19,,400,,,16,10.48602032661438
+1270,0.953125,0.953125,,0.0,8,10,20,,400,,,16,10.440558195114136
+1271,0.93359375,0.93359375,,0.0,8,10,21,,400,,,16,10.521523237228394
+1272,0.9453125,0.9453125,,0.0,8,10,22,,400,,,16,10.461989641189575
+1273,0.9375,0.9375,,0.0,8,10,23,,400,,,16,10.472689628601074
+1274,0.92578125,0.92578125,,0.0,8,10,24,,400,,,16,10.438990354537964
+1275,0.8828125,0.8828125,,0.0,9,10,0,,800,,,16,29.300535202026367
+1276,0.873046875,0.873046875,,0.0,9,10,1,,800,,,16,29.13441228866577
+1277,0.87890625,0.87890625,,0.0,9,10,2,,800,,,16,29.18769121170044
+1278,0.8828125,0.8828125,,0.0,9,10,3,,800,,,16,29.180747509002686
+1279,0.85546875,0.85546875,,0.0,9,10,4,,800,,,16,29.258854150772095
+1280,0.87890625,0.87890625,,0.0,9,10,5,,800,,,16,29.0176043510437
+1281,0.869140625,0.869140625,,0.0,9,10,6,,800,,,16,29.263768672943115
+1282,0.86328125,0.86328125,,0.0,9,10,7,,800,,,16,28.99706768989563
+1283,0.87890625,0.87890625,,0.0,9,10,8,,800,,,16,29.20806336402893
+1284,0.84765625,0.84765625,,0.0,9,10,9,,800,,,16,29.724751710891724
+1285,0.873046875,0.873046875,,0.0,9,10,10,,800,,,16,29.291422605514526
+1286,0.865234375,0.865234375,,0.0,9,10,11,,800,,,16,28.931843280792236
+1287,0.869140625,0.869140625,,0.0,9,10,12,,800,,,16,29.26750946044922
+1288,0.888671875,0.888671875,,0.0,9,10,13,,800,,,16,29.037100076675415
+1289,0.861328125,0.861328125,,0.0,9,10,14,,800,,,16,29.266470432281494
+1290,0.859375,0.859375,,0.0,9,10,15,,800,,,16,29.089407920837402
+1291,0.8671875,0.8671875,,0.0,9,10,16,,800,,,16,29.124629974365234
+1292,0.880859375,0.880859375,,0.0,9,10,17,,800,,,16,29.239683151245117
+1293,0.86328125,0.86328125,,0.0,9,10,18,,800,,,16,29.20217776298523
+1294,0.86328125,0.86328125,,0.0,9,10,19,,800,,,16,29.56899881362915
+1295,0.857421875,0.857421875,,0.0,9,10,20,,800,,,16,29.115322828292847
+1296,0.87890625,0.87890625,,0.0,9,10,21,,800,,,16,29.13876461982727
+1297,0.880859375,0.880859375,,0.0,9,10,22,,800,,,16,29.170190811157227
+1298,0.861328125,0.861328125,,0.0,9,10,23,,800,,,16,28.879034996032715
+1299,0.853515625,0.85546875,,0.0,9,10,24,,800,,,16,29.161651611328125
+1300,1.0,1.0,,0.01,6,10,0,,100,,,16,3.4589905738830566
+1301,1.0,1.0,,0.01,6,10,1,,100,,,16,3.4710004329681396
+1302,1.0,1.0,,0.01,6,10,2,,100,,,16,3.4921860694885254
+1303,1.0,1.0,,0.01,6,10,3,,100,,,16,3.529987335205078
+1304,1.0,1.0,,0.01,6,10,4,,100,,,16,3.509993314743042
+1305,1.0,1.0,,0.01,6,10,5,,100,,,16,3.5199947357177734
+1306,1.0,1.0,,0.01,6,10,6,,100,,,16,3.4929912090301514
+1307,1.0,1.0,,0.01,6,10,7,,100,,,16,3.5079946517944336
+1308,1.0,1.0,,0.01,6,10,8,,100,,,16,3.5669891834259033
+1309,1.0,1.0,,0.01,6,10,9,,100,,,16,3.5129904747009277
+1310,1.0,1.0,,0.01,6,10,10,,100,,,16,3.5087132453918457
+1311,1.0,1.0,,0.01,6,10,11,,100,,,16,3.493987560272217
+1312,1.0,1.0,,0.01,6,10,12,,100,,,16,3.5639872550964355
+1313,1.0,1.0,,0.01,6,10,13,,100,,,16,3.5404694080352783
+1314,1.0,1.0,,0.01,6,10,14,,100,,,16,3.4799997806549072
+1315,1.0,1.0,,0.01,6,10,15,,100,,,16,3.510288715362549
+1316,1.0,1.0,,0.01,6,10,16,,100,,,16,3.5020012855529785
+1317,1.0,1.0,,0.01,6,10,17,,100,,,16,3.5700230598449707
+1318,1.0,1.0,,0.01,6,10,18,,100,,,16,3.5040230751037598
+1319,1.0,1.0,,0.01,6,10,19,,100,,,16,3.545027017593384
+1320,1.0,1.0,,0.01,6,10,20,,100,,,16,3.4949934482574463
+1321,1.0,1.0,,0.01,6,10,21,,100,,,16,3.6270012855529785
+1322,1.0,1.0,,0.01,6,10,22,,100,,,16,3.530008554458618
+1323,1.0,1.0,,0.01,6,10,23,,100,,,16,3.5009942054748535
+1324,1.0,1.0,,0.01,6,10,24,,100,,,16,3.510237455368042
+1325,0.9921875,0.9921875,,0.01,7,10,0,,200,,,16,5.207025766372681
+1326,0.984375,0.984375,,0.01,7,10,1,,200,,,16,5.156098127365112
+1327,0.984375,0.984375,,0.01,7,10,2,,200,,,16,5.173706293106079
+1328,0.96875,0.9765625,,0.01,7,10,3,,200,,,16,5.156017303466797
+1329,0.9765625,0.984375,,0.01,7,10,4,,200,,,16,5.196019172668457
+1330,0.96875,0.96875,,0.01,7,10,5,,200,,,16,5.170023679733276
+1331,0.9765625,0.9765625,,0.01,7,10,6,,200,,,16,5.2069902420043945
+1332,0.9765625,0.984375,,0.01,7,10,7,,200,,,16,5.130626440048218
+1333,0.953125,0.9609375,,0.01,7,10,8,,200,,,16,5.200019121170044
+1334,0.96875,0.9765625,,0.01,7,10,9,,200,,,16,5.1510233879089355
+1335,0.9765625,0.9765625,,0.01,7,10,10,,200,,,16,5.175670862197876
+1336,0.984375,0.984375,,0.01,7,10,11,,200,,,16,5.1349992752075195
+1337,1.0,1.0,,0.01,7,10,12,,200,,,16,5.2081239223480225
+1338,0.9609375,0.96875,,0.01,7,10,13,,200,,,16,5.190005779266357
+1339,0.9921875,0.9921875,,0.01,7,10,14,,200,,,16,5.160999536514282
+1340,0.984375,0.984375,,0.01,7,10,15,,200,,,16,5.136034250259399
+1341,0.96875,0.9765625,,0.01,7,10,16,,200,,,16,5.212027549743652
+1342,0.9921875,1.0,,0.01,7,10,17,,200,,,16,5.180001258850098
+1343,0.984375,0.984375,,0.01,7,10,18,,200,,,16,5.195202589035034
+1344,0.9921875,0.9921875,,0.01,7,10,19,,200,,,16,5.177011728286743
+1345,0.984375,0.984375,,0.01,7,10,20,,200,,,16,5.193021059036255
+1346,0.96875,0.96875,,0.01,7,10,21,,200,,,16,5.184507369995117
+1347,0.9609375,0.9609375,,0.01,7,10,22,,200,,,16,5.227442264556885
+1348,0.984375,0.984375,,0.01,7,10,23,,200,,,16,5.165008544921875
+1349,0.9765625,0.9765625,,0.01,7,10,24,,200,,,16,5.168107509613037
+1350,0.9296875,0.93359375,,0.01,8,10,0,,400,,,16,10.552996397018433
+1351,0.9453125,0.9453125,,0.01,8,10,1,,400,,,16,10.612607479095459
+1352,0.91015625,0.91015625,,0.01,8,10,2,,400,,,16,10.570988655090332
+1353,0.90625,0.91015625,,0.01,8,10,3,,400,,,16,10.54098629951477
+1354,0.875,0.87890625,,0.01,8,10,4,,400,,,16,10.571017742156982
+1355,0.8984375,0.90234375,,0.01,8,10,5,,400,,,16,10.604748249053955
+1356,0.93359375,0.93359375,,0.01,8,10,6,,400,,,16,10.618990182876587
+1357,0.91796875,0.91796875,,0.01,8,10,7,,400,,,16,10.560016393661499
+1358,0.91015625,0.9140625,,0.01,8,10,8,,400,,,16,10.521153688430786
+1359,0.875,0.8828125,,0.01,8,10,9,,400,,,16,10.57976245880127
+1360,0.9296875,0.9296875,,0.01,8,10,10,,400,,,16,10.527153015136719
+1361,0.8984375,0.8984375,,0.01,8,10,11,,400,,,16,10.544018030166626
+1362,0.9140625,0.91796875,,0.01,8,10,12,,400,,,16,10.54308009147644
+1363,0.8984375,0.8984375,,0.01,8,10,13,,400,,,16,10.582268476486206
+1364,0.9140625,0.91796875,,0.01,8,10,14,,400,,,16,10.538018941879272
+1365,0.9296875,0.93359375,,0.01,8,10,15,,400,,,16,10.644014120101929
+1366,0.921875,0.921875,,0.01,8,10,16,,400,,,16,10.557133197784424
+1367,0.90234375,0.90625,,0.01,8,10,17,,400,,,16,10.551424026489258
+1368,0.921875,0.92578125,,0.01,8,10,18,,400,,,16,10.557026147842407
+1369,0.921875,0.921875,,0.01,8,10,19,,400,,,16,10.57275938987732
+1370,0.890625,0.89453125,,0.01,8,10,20,,400,,,16,10.578813552856445
+1371,0.93359375,0.93359375,,0.01,8,10,21,,400,,,16,10.630380868911743
+1372,0.921875,0.921875,,0.01,8,10,22,,400,,,16,10.485339164733887
+1373,0.90625,0.91015625,,0.01,8,10,23,,400,,,16,10.52299427986145
+1374,0.90625,0.91015625,,0.01,8,10,24,,400,,,16,10.553994178771973
+1375,0.84765625,0.849609375,,0.01,9,10,0,,800,,,16,29.41778564453125
+1376,0.826171875,0.830078125,,0.01,9,10,1,,800,,,16,29.162626028060913
+1377,0.833984375,0.837890625,,0.01,9,10,2,,800,,,16,29.428181886672974
+1378,0.806640625,0.810546875,,0.01,9,10,3,,800,,,16,29.150871515274048
+1379,0.8515625,0.85546875,,0.01,9,10,4,,800,,,16,29.429377794265747
+1380,0.8203125,0.82421875,,0.01,9,10,5,,800,,,16,29.17891001701355
+1381,0.84375,0.845703125,,0.01,9,10,6,,800,,,16,29.259002447128296
+1382,0.841796875,0.84375,,0.01,9,10,7,,800,,,16,29.062482118606567
+1383,0.80859375,0.8125,,0.01,9,10,8,,800,,,16,29.36108112335205
+1384,0.828125,0.830078125,,0.01,9,10,9,,800,,,16,28.984460830688477
+1385,0.8203125,0.82421875,,0.01,9,10,10,,800,,,16,29.35868549346924
+1386,0.814453125,0.814453125,,0.01,9,10,11,,800,,,16,28.935670614242554
+1387,0.82421875,0.82421875,,0.01,9,10,12,,800,,,16,29.067810535430908
+1388,0.8046875,0.8125,,0.01,9,10,13,,800,,,16,28.981929063796997
+1389,0.84765625,0.84765625,,0.01,9,10,14,,800,,,16,29.151221752166748
+1390,0.83984375,0.84375,,0.01,9,10,15,,800,,,16,28.919116258621216
+1391,0.802734375,0.80859375,,0.01,9,10,16,,800,,,16,29.26116633415222
+1392,0.814453125,0.8203125,,0.01,9,10,17,,800,,,16,28.961451768875122
+1393,0.8203125,0.82421875,,0.01,9,10,18,,800,,,16,29.25418996810913
+1394,0.8359375,0.837890625,,0.01,9,10,19,,800,,,16,28.991318464279175
+1395,0.826171875,0.826171875,,0.01,9,10,20,,800,,,16,29.079763650894165
+1396,0.83203125,0.83984375,,0.01,9,10,21,,800,,,16,28.943113803863525
+1397,0.8046875,0.810546875,,0.01,9,10,22,,800,,,16,29.1110737323761
+1398,0.826171875,0.826171875,,0.01,9,10,23,,800,,,16,28.970327854156494
+1399,0.828125,0.828125,,0.01,9,10,24,,800,,,16,29.29851460456848
+1400,1.0,1.0,,0.1,6,10,0,,100,,,16,3.517995834350586
+1401,1.0,1.0,,0.1,6,10,1,,100,,,16,3.4890148639678955
+1402,0.984375,0.984375,,0.1,6,10,2,,100,,,16,3.477989435195923
+1403,0.96875,0.96875,,0.1,6,10,3,,100,,,16,3.5089941024780273
+1404,0.984375,0.984375,,0.1,6,10,4,,100,,,16,3.4830100536346436
+1405,1.0,1.0,,0.1,6,10,5,,100,,,16,3.4973342418670654
+1406,1.0,1.0,,0.1,6,10,6,,100,,,16,3.4929938316345215
+1407,0.96875,0.96875,,0.1,6,10,7,,100,,,16,3.602785110473633
+1408,0.984375,0.96875,,0.1,6,10,8,,100,,,16,3.5360167026519775
+1409,1.0,1.0,,0.1,6,10,9,,100,,,16,3.5160200595855713
+1410,0.9375,0.953125,,0.1,6,10,10,,100,,,16,3.521996021270752
+1411,0.984375,0.984375,,0.1,6,10,11,,100,,,16,3.480987310409546
+1412,0.953125,0.953125,,0.1,6,10,12,,100,,,16,3.5400264263153076
+1413,0.96875,0.96875,,0.1,6,10,13,,100,,,16,3.534011125564575
+1414,0.984375,1.0,,0.1,6,10,14,,100,,,16,3.518611192703247
+1415,0.96875,0.984375,,0.1,6,10,15,,100,,,16,3.5119776725769043
+1416,0.96875,0.984375,,0.1,6,10,16,,100,,,16,3.6420328617095947
+1417,0.953125,0.984375,,0.1,6,10,17,,100,,,16,3.525005578994751
+1418,0.9375,0.953125,,0.1,6,10,18,,100,,,16,3.499985456466675
+1419,1.0,1.0,,0.1,6,10,19,,100,,,16,3.528005361557007
+1420,1.0,1.0,,0.1,6,10,20,,100,,,16,3.5210063457489014
+1421,1.0,1.0,,0.1,6,10,21,,100,,,16,3.5509965419769287
+1422,0.953125,0.96875,,0.1,6,10,22,,100,,,16,3.5110960006713867
+1423,0.984375,0.984375,,0.1,6,10,23,,100,,,16,3.5303564071655273
+1424,0.984375,1.0,,0.1,6,10,24,,100,,,16,3.481992483139038
+1425,0.8671875,0.8671875,,0.1,7,10,0,,200,,,16,5.26898717880249
+1426,0.859375,0.890625,,0.1,7,10,1,,200,,,16,5.126991510391235
+1427,0.8671875,0.8671875,,0.1,7,10,2,,200,,,16,5.125996351242065
+1428,0.828125,0.8203125,,0.1,7,10,3,,200,,,16,5.196983575820923
+1429,0.859375,0.8828125,,0.1,7,10,4,,200,,,16,5.1846489906311035
+1430,0.890625,0.8984375,,0.1,7,10,5,,200,,,16,5.1019933223724365
+1431,0.890625,0.90625,,0.1,7,10,6,,200,,,16,5.262991666793823
+1432,0.8671875,0.8671875,,0.1,7,10,7,,200,,,16,5.108987808227539
+1433,0.8828125,0.890625,,0.1,7,10,8,,200,,,16,5.183993101119995
+1434,0.8203125,0.84375,,0.1,7,10,9,,200,,,16,5.219767093658447
+1435,0.8125,0.828125,,0.1,7,10,10,,200,,,16,5.1259925365448
+1436,0.859375,0.84375,,0.1,7,10,11,,200,,,16,5.129990577697754
+1437,0.8125,0.828125,,0.1,7,10,12,,200,,,16,5.21999192237854
+1438,0.84375,0.84375,,0.1,7,10,13,,200,,,16,5.145994186401367
+1439,0.8359375,0.84375,,0.1,7,10,14,,200,,,16,5.122992277145386
+1440,0.875,0.875,,0.1,7,10,15,,200,,,16,5.20688533782959
+1441,0.890625,0.890625,,0.1,7,10,16,,200,,,16,5.155986070632935
+1442,0.890625,0.8828125,,0.1,7,10,17,,200,,,16,5.167980432510376
+1443,0.875,0.875,,0.1,7,10,18,,200,,,16,5.222192287445068
+1444,0.875,0.875,,0.1,7,10,19,,200,,,16,5.13900351524353
+1445,0.8359375,0.8359375,,0.1,7,10,20,,200,,,16,5.176020860671997
+1446,0.90625,0.8984375,,0.1,7,10,21,,200,,,16,5.28624701499939
+1447,0.8828125,0.8984375,,0.1,7,10,22,,200,,,16,5.1778340339660645
+1448,0.8125,0.828125,,0.1,7,10,23,,200,,,16,5.11199426651001
+1449,0.8828125,0.8828125,,0.1,7,10,24,,200,,,16,5.217018127441406
+1450,0.78515625,0.78515625,,0.1,8,10,0,,400,,,16,10.46199893951416
+1451,0.7578125,0.76953125,,0.1,8,10,1,,400,,,16,10.547094106674194
+1452,0.75,0.74609375,,0.1,8,10,2,,400,,,16,10.451990365982056
+1453,0.76171875,0.7578125,,0.1,8,10,3,,400,,,16,10.437586307525635
+1454,0.73046875,0.74609375,,0.1,8,10,4,,400,,,16,10.375020503997803
+1455,0.75,0.75,,0.1,8,10,5,,400,,,16,10.453241109848022
+1456,0.73828125,0.73828125,,0.1,8,10,6,,400,,,16,10.360662460327148
+1457,0.74609375,0.75,,0.1,8,10,7,,400,,,16,10.453991889953613
+1458,0.74609375,0.74609375,,0.1,8,10,8,,400,,,16,10.396994829177856
+1459,0.71484375,0.7109375,,0.1,8,10,9,,400,,,16,10.424038410186768
+1460,0.7734375,0.77734375,,0.1,8,10,10,,400,,,16,10.42301607131958
+1461,0.7734375,0.79296875,,0.1,8,10,11,,400,,,16,10.496996641159058
+1462,0.7734375,0.77734375,,0.1,8,10,12,,400,,,16,10.429577112197876
+1463,0.77734375,0.7734375,,0.1,8,10,13,,400,,,16,10.576004028320312
+1464,0.75,0.74609375,,0.1,8,10,14,,400,,,16,10.389993906021118
+1465,0.73828125,0.76171875,,0.1,8,10,15,,400,,,16,10.496122360229492
+1466,0.78125,0.78125,,0.1,8,10,16,,400,,,16,10.425025701522827
+1467,0.76171875,0.75390625,,0.1,8,10,17,,400,,,16,10.444011688232422
+1468,0.72265625,0.74609375,,0.1,8,10,18,,400,,,16,10.45559573173523
+1469,0.7734375,0.78515625,,0.1,8,10,19,,400,,,16,10.517386436462402
+1470,0.7734375,0.78515625,,0.1,8,10,20,,400,,,16,10.394590377807617
+1471,0.70703125,0.71875,,0.1,8,10,21,,400,,,16,10.519808053970337
+1472,0.77734375,0.78515625,,0.1,8,10,22,,400,,,16,10.402000665664673
+1473,0.73046875,0.7421875,,0.1,8,10,23,,400,,,16,10.45679521560669
+1474,0.6875,0.71484375,,0.1,8,10,24,,400,,,16,10.536997318267822
+1475,0.666015625,0.669921875,,0.1,9,10,0,,800,,,16,29.048943758010864
+1476,0.677734375,0.673828125,,0.1,9,10,1,,800,,,16,28.83858895301819
+1477,0.654296875,0.650390625,,0.1,9,10,2,,800,,,16,28.977953910827637
+1478,0.638671875,0.642578125,,0.1,9,10,3,,800,,,16,28.635481595993042
+1479,0.611328125,0.626953125,,0.1,9,10,4,,800,,,16,28.959526300430298
+1480,0.6640625,0.673828125,,0.1,9,10,5,,800,,,16,28.638118028640747
+1481,0.609375,0.638671875,,0.1,9,10,6,,800,,,16,28.945003032684326
+1482,0.654296875,0.669921875,,0.1,9,10,7,,800,,,16,28.935137033462524
+1483,0.6328125,0.646484375,,0.1,9,10,8,,800,,,16,28.828669786453247
+1484,0.63671875,0.642578125,,0.1,9,10,9,,800,,,16,28.691519498825073
+1485,0.64453125,0.638671875,,0.1,9,10,10,,800,,,16,28.891635417938232
+1486,0.669921875,0.6640625,,0.1,9,10,11,,800,,,16,28.61499261856079
+1487,0.677734375,0.6640625,,0.1,9,10,12,,800,,,16,28.814269065856934
+1488,0.658203125,0.66796875,,0.1,9,10,13,,800,,,16,28.701977491378784
+1489,0.673828125,0.666015625,,0.1,9,10,14,,800,,,16,29.061755657196045
+1490,0.64453125,0.640625,,0.1,9,10,15,,800,,,16,28.762423038482666
+1491,0.66796875,0.6484375,,0.1,9,10,16,,800,,,16,28.788388967514038
+1492,0.654296875,0.654296875,,0.1,9,10,17,,800,,,16,28.63111400604248
+1493,0.64453125,0.638671875,,0.1,9,10,18,,800,,,16,28.713891983032227
+1494,0.669921875,0.693359375,,0.1,9,10,19,,800,,,16,28.73477864265442
+1495,0.640625,0.650390625,,0.1,9,10,20,,800,,,16,28.815966606140137
+1496,0.658203125,0.662109375,,0.1,9,10,21,,800,,,16,28.649900674819946
+1497,0.658203125,0.65234375,,0.1,9,10,22,,800,,,16,28.938698530197144
+1498,0.69140625,0.68359375,,0.1,9,10,23,,800,,,16,28.668307542800903
+1499,0.64453125,0.64453125,,0.1,9,10,24,,800,,,16,29.021859645843506
+1500,0.828125,0.84375,,0.2,6,10,0,,100,,,16,3.524989604949951
+1501,0.8125,0.84375,,0.2,6,10,1,,100,,,16,3.4658167362213135
+1502,0.8125,0.84375,,0.2,6,10,2,,100,,,16,3.4450185298919678
+1503,0.90625,0.90625,,0.2,6,10,3,,100,,,16,3.468900442123413
+1504,0.875,0.890625,,0.2,6,10,4,,100,,,16,3.468203067779541
+1505,0.9375,0.953125,,0.2,6,10,5,,100,,,16,3.5900001525878906
+1506,0.859375,0.890625,,0.2,6,10,6,,100,,,16,3.485015869140625
+1507,0.921875,0.90625,,0.2,6,10,7,,100,,,16,3.499990701675415
+1508,0.9375,0.9375,,0.2,6,10,8,,100,,,16,3.475996732711792
+1509,0.9375,0.953125,,0.2,6,10,9,,100,,,16,3.5279903411865234
+1510,0.875,0.890625,,0.2,6,10,10,,100,,,16,3.5510032176971436
+1511,0.890625,0.90625,,0.2,6,10,11,,100,,,16,3.5150082111358643
+1512,0.84375,0.90625,,0.2,6,10,12,,100,,,16,3.506654739379883
+1513,0.9375,0.953125,,0.2,6,10,13,,100,,,16,3.500140428543091
+1514,0.875,0.890625,,0.2,6,10,14,,100,,,16,3.587019205093384
+1515,0.859375,0.859375,,0.2,6,10,15,,100,,,16,3.493086814880371
+1516,0.921875,0.921875,,0.2,6,10,16,,100,,,16,3.489020586013794
+1517,0.9375,0.9375,,0.2,6,10,17,,100,,,16,3.5850307941436768
+1518,0.859375,0.890625,,0.2,6,10,18,,100,,,16,3.5030176639556885
+1519,0.9375,0.9375,,0.2,6,10,19,,100,,,16,3.542032241821289
+1520,0.84375,0.84375,,0.2,6,10,20,,100,,,16,3.4920084476470947
+1521,0.875,0.875,,0.2,6,10,21,,100,,,16,3.542185068130493
+1522,0.90625,0.90625,,0.2,6,10,22,,100,,,16,3.4939944744110107
+1523,0.875,0.890625,,0.2,6,10,23,,100,,,16,3.6379880905151367
+1524,0.890625,0.90625,,0.2,6,10,24,,100,,,16,3.495032548904419
+1525,0.7421875,0.7109375,,0.2,7,10,0,,200,,,16,5.164016246795654
+1526,0.75,0.75,,0.2,7,10,1,,200,,,16,5.100987672805786
+1527,0.7890625,0.8125,,0.2,7,10,2,,200,,,16,5.152586221694946
+1528,0.75,0.7578125,,0.2,7,10,3,,200,,,16,5.094711065292358
+1529,0.734375,0.734375,,0.2,7,10,4,,200,,,16,5.133991003036499
+1530,0.7578125,0.7734375,,0.2,7,10,5,,200,,,16,5.171013593673706
+1531,0.7890625,0.796875,,0.2,7,10,6,,200,,,16,5.175729036331177
+1532,0.75,0.78125,,0.2,7,10,7,,200,,,16,5.120021104812622
+1533,0.7734375,0.8046875,,0.2,7,10,8,,200,,,16,5.23163104057312
+1534,0.6953125,0.703125,,0.2,7,10,9,,200,,,16,5.123007297515869
+1535,0.796875,0.8203125,,0.2,7,10,10,,200,,,16,5.154212236404419
+1536,0.734375,0.7421875,,0.2,7,10,11,,200,,,16,5.193027496337891
+1537,0.765625,0.7421875,,0.2,7,10,12,,200,,,16,5.175013780593872
+1538,0.7109375,0.71875,,0.2,7,10,13,,200,,,16,5.111025094985962
+1539,0.78125,0.8359375,,0.2,7,10,14,,200,,,16,5.256003379821777
+1540,0.7890625,0.8125,,0.2,7,10,15,,200,,,16,5.115031719207764
+1541,0.796875,0.7734375,,0.2,7,10,16,,200,,,16,5.141989707946777
+1542,0.8125,0.8203125,,0.2,7,10,17,,200,,,16,5.20898962020874
+1543,0.7578125,0.765625,,0.2,7,10,18,,200,,,16,5.1936750411987305
+1544,0.65625,0.640625,,0.2,7,10,19,,200,,,16,5.122998952865601
+1545,0.7109375,0.6953125,,0.2,7,10,20,,200,,,16,5.289676189422607
+1546,0.75,0.7421875,,0.2,7,10,21,,200,,,16,5.115022659301758
+1547,0.765625,0.7734375,,0.2,7,10,22,,200,,,16,5.156009197235107
+1548,0.796875,0.8125,,0.2,7,10,23,,200,,,16,5.2260167598724365
+1549,0.796875,0.8046875,,0.2,7,10,24,,200,,,16,5.146989345550537
+1550,0.66796875,0.65625,,0.2,8,10,0,,400,,,16,10.37001919746399
+1551,0.64453125,0.6953125,,0.2,8,10,1,,400,,,16,10.448593378067017
+1552,0.69140625,0.69140625,,0.2,8,10,2,,400,,,16,10.45626187324524
+1553,0.66015625,0.67578125,,0.2,8,10,3,,400,,,16,10.460066795349121
+1554,0.66015625,0.6796875,,0.2,8,10,4,,400,,,16,10.439283609390259
+1555,0.66796875,0.6796875,,0.2,8,10,5,,400,,,16,10.4909987449646
+1556,0.6875,0.6640625,,0.2,8,10,6,,400,,,16,10.400311708450317
+1557,0.55078125,0.59765625,,0.2,8,10,7,,400,,,16,10.445415258407593
+1558,0.65234375,0.64453125,,0.2,8,10,8,,400,,,16,10.4020094871521
+1559,0.6328125,0.66015625,,0.2,8,10,9,,400,,,16,10.4386305809021
+1560,0.6953125,0.69921875,,0.2,8,10,10,,400,,,16,10.402989625930786
+1561,0.6640625,0.67578125,,0.2,8,10,11,,400,,,16,10.458006858825684
+1562,0.6171875,0.640625,,0.2,8,10,12,,400,,,16,10.418451309204102
+1563,0.6171875,0.63671875,,0.2,8,10,13,,400,,,16,10.37453317642212
+1564,0.625,0.6484375,,0.2,8,10,14,,400,,,16,10.346825361251831
+1565,0.66015625,0.65625,,0.2,8,10,15,,400,,,16,10.365990400314331
+1566,0.6640625,0.671875,,0.2,8,10,16,,400,,,16,10.327989339828491
+1567,0.7109375,0.69140625,,0.2,8,10,17,,400,,,16,10.425837755203247
+1568,0.66015625,0.65625,,0.2,8,10,18,,400,,,16,10.38701057434082
+1569,0.65625,0.6484375,,0.2,8,10,19,,400,,,16,10.512038230895996
+1570,0.6328125,0.62109375,,0.2,8,10,20,,400,,,16,10.39143419265747
+1571,0.73046875,0.7578125,,0.2,8,10,21,,400,,,16,10.433286428451538
+1572,0.69921875,0.6875,,0.2,8,10,22,,400,,,16,10.414003610610962
+1573,0.64453125,0.68359375,,0.2,8,10,23,,400,,,16,10.472042322158813
+1574,0.66015625,0.66015625,,0.2,8,10,24,,400,,,16,10.352022886276245
+1575,0.634765625,0.634765625,,0.2,9,10,0,,800,,,16,29.172884941101074
+1576,0.57421875,0.568359375,,0.2,9,10,1,,800,,,16,28.93595242500305
+1577,0.595703125,0.59765625,,0.2,9,10,2,,800,,,16,29.034496545791626
+1578,0.6328125,0.625,,0.2,9,10,3,,800,,,16,28.827284812927246
+1579,0.615234375,0.61328125,,0.2,9,10,4,,800,,,16,28.881384134292603
+1580,0.58203125,0.58203125,,0.2,9,10,5,,800,,,16,28.677003622055054
+1581,0.61328125,0.611328125,,0.2,9,10,6,,800,,,16,28.830049753189087
+1582,0.60546875,0.599609375,,0.2,9,10,7,,800,,,16,28.62890338897705
+1583,0.587890625,0.591796875,,0.2,9,10,8,,800,,,16,28.899487495422363
+1584,0.638671875,0.6328125,,0.2,9,10,9,,800,,,16,28.73349952697754
+1585,0.59375,0.591796875,,0.2,9,10,10,,800,,,16,28.941746950149536
+1586,0.5703125,0.583984375,,0.2,9,10,11,,800,,,16,28.70046639442444
+1587,0.595703125,0.59765625,,0.2,9,10,12,,800,,,16,28.853862047195435
+1588,0.607421875,0.603515625,,0.2,9,10,13,,800,,,16,28.67550778388977
+1589,0.62890625,0.62109375,,0.2,9,10,14,,800,,,16,28.684023141860962
+1590,0.599609375,0.595703125,,0.2,9,10,15,,800,,,16,28.498563051223755
+1591,0.587890625,0.60546875,,0.2,9,10,16,,800,,,16,28.843620538711548
+1592,0.59765625,0.587890625,,0.2,9,10,17,,800,,,16,28.60623526573181
+1593,0.5859375,0.59765625,,0.2,9,10,18,,800,,,16,28.800645351409912
+1594,0.59765625,0.59765625,,0.2,9,10,19,,800,,,16,28.674240827560425
+1595,0.576171875,0.591796875,,0.2,9,10,20,,800,,,16,28.746101140975952
+1596,0.630859375,0.6328125,,0.2,9,10,21,,800,,,16,29.327795028686523
+1597,0.59765625,0.591796875,,0.2,9,10,22,,800,,,16,28.716732263565063
+1598,0.619140625,0.6328125,,0.2,9,10,23,,800,,,16,28.562032461166382
+1599,0.5859375,0.578125,,0.2,9,10,24,,800,,,16,28.808595657348633
diff --git a/experiments/bench/oneMax/data/easimple-pop=100.csv b/experiments/bench/oneMax/data/easimple-pop=100.csv
new file mode 100644
index 0000000000000000000000000000000000000000..16282ea0e5301c2445accee94091f73de1bdd70f
--- /dev/null
+++ b/experiments/bench/oneMax/data/easimple-pop=100.csv
@@ -0,0 +1,401 @@
+,best_pop,best_hof,best_arm,std,dim,n_eval,run_number,UCB_sigma,ngen,mu,lambda,n_thread,time
+0,1.0,1.0,,0.0,6,1,0,,100,,,16,3.5225002765655518
+1,1.0,1.0,,0.0,6,1,1,,100,,,16,3.521007537841797
+2,1.0,1.0,,0.0,6,1,2,,100,,,16,3.4270076751708984
+3,1.0,1.0,,0.0,6,1,3,,100,,,16,3.4740054607391357
+4,1.0,1.0,,0.0,6,1,4,,100,,,16,3.5750057697296143
+5,1.0,1.0,,0.0,6,1,5,,100,,,16,3.5659914016723633
+6,1.0,1.0,,0.0,6,1,6,,100,,,16,3.495009183883667
+7,1.0,1.0,,0.0,6,1,7,,100,,,16,3.5169920921325684
+8,1.0,1.0,,0.0,6,1,8,,100,,,16,4.1200056076049805
+9,1.0,1.0,,0.0,6,1,9,,100,,,16,3.570002317428589
+10,1.0,1.0,,0.0,6,1,10,,100,,,16,3.536003351211548
+11,1.0,1.0,,0.0,6,1,11,,100,,,16,3.4630050659179688
+12,1.0,1.0,,0.0,6,1,12,,100,,,16,3.4370105266571045
+13,1.0,1.0,,0.0,6,1,13,,100,,,16,3.570007562637329
+14,1.0,1.0,,0.0,6,1,14,,100,,,16,3.447009563446045
+15,1.0,1.0,,0.0,6,1,15,,100,,,16,3.4361369609832764
+16,1.0,1.0,,0.0,6,1,16,,100,,,16,3.4259958267211914
+17,1.0,1.0,,0.0,6,1,17,,100,,,16,3.4489853382110596
+18,1.0,1.0,,0.0,6,1,18,,100,,,16,3.4649972915649414
+19,1.0,1.0,,0.0,6,1,19,,100,,,16,3.447993040084839
+20,1.0,1.0,,0.0,6,1,20,,100,,,16,3.4550180435180664
+21,1.0,1.0,,0.0,6,1,21,,100,,,16,3.4539971351623535
+22,1.0,1.0,,0.0,6,1,22,,100,,,16,3.5863139629364014
+23,1.0,1.0,,0.0,6,1,23,,100,,,16,3.4709839820861816
+24,1.0,1.0,,0.0,6,1,24,,100,,,16,3.441988706588745
+25,1.0,1.0,,0.0,7,1,0,,200,,,16,5.130982160568237
+26,1.0,1.0,,0.0,7,1,1,,200,,,16,5.2329912185668945
+27,0.9921875,0.9921875,,0.0,7,1,2,,200,,,16,5.0972630977630615
+28,0.9765625,0.9765625,,0.0,7,1,3,,200,,,16,5.066988945007324
+29,0.9921875,0.9921875,,0.0,7,1,4,,200,,,16,5.18001127243042
+30,1.0,1.0,,0.0,7,1,5,,200,,,16,5.0689966678619385
+31,1.0,1.0,,0.0,7,1,6,,200,,,16,5.066021919250488
+32,1.0,1.0,,0.0,7,1,7,,200,,,16,5.1080005168914795
+33,0.984375,0.984375,,0.0,7,1,8,,200,,,16,5.096992492675781
+34,0.9765625,0.9765625,,0.0,7,1,9,,200,,,16,5.079006910324097
+35,0.9921875,0.9921875,,0.0,7,1,10,,200,,,16,5.088011264801025
+36,0.984375,0.984375,,0.0,7,1,11,,200,,,16,5.039995193481445
+37,1.0,1.0,,0.0,7,1,12,,200,,,16,5.092015027999878
+38,0.9765625,0.9765625,,0.0,7,1,13,,200,,,16,5.05699610710144
+39,0.9921875,0.9921875,,0.0,7,1,14,,200,,,16,5.094995737075806
+40,0.9765625,0.9765625,,0.0,7,1,15,,200,,,16,5.043993949890137
+41,0.96875,0.9765625,,0.0,7,1,16,,200,,,16,5.066009521484375
+42,0.984375,0.984375,,0.0,7,1,17,,200,,,16,5.071012496948242
+43,0.9765625,0.9765625,,0.0,7,1,18,,200,,,16,5.107004165649414
+44,0.9921875,0.9921875,,0.0,7,1,19,,200,,,16,5.065985679626465
+45,0.9921875,0.9921875,,0.0,7,1,20,,200,,,16,5.1510162353515625
+46,0.984375,0.9921875,,0.0,7,1,21,,200,,,16,5.085017919540405
+47,0.984375,0.9921875,,0.0,7,1,22,,200,,,16,5.078677654266357
+48,0.96875,0.96875,,0.0,7,1,23,,200,,,16,5.110006332397461
+49,0.9921875,0.9921875,,0.0,7,1,24,,200,,,16,5.126008749008179
+50,0.921875,0.921875,,0.0,8,1,0,,400,,,16,10.498008012771606
+51,0.9453125,0.9453125,,0.0,8,1,1,,400,,,16,10.375243902206421
+52,0.9609375,0.9609375,,0.0,8,1,2,,400,,,16,10.460008144378662
+53,0.9375,0.9375,,0.0,8,1,3,,400,,,16,10.52800989151001
+54,0.94921875,0.94921875,,0.0,8,1,4,,400,,,16,10.372008562088013
+55,0.94140625,0.94140625,,0.0,8,1,5,,400,,,16,10.554711103439331
+56,0.9609375,0.9609375,,0.0,8,1,6,,400,,,16,10.437982559204102
+57,0.91015625,0.91015625,,0.0,8,1,7,,400,,,16,10.49198865890503
+58,0.9453125,0.9453125,,0.0,8,1,8,,400,,,16,10.59199571609497
+59,0.94140625,0.94140625,,0.0,8,1,9,,400,,,16,10.41936731338501
+60,0.93359375,0.93359375,,0.0,8,1,10,,400,,,16,10.351017951965332
+61,0.93359375,0.93359375,,0.0,8,1,11,,400,,,16,10.56501293182373
+62,0.92578125,0.92578125,,0.0,8,1,12,,400,,,16,10.421261072158813
+63,0.9296875,0.9296875,,0.0,8,1,13,,400,,,16,10.43929147720337
+64,0.93359375,0.93359375,,0.0,8,1,14,,400,,,16,10.631023406982422
+65,0.9375,0.9375,,0.0,8,1,15,,400,,,16,10.496336698532104
+66,0.93359375,0.93359375,,0.0,8,1,16,,400,,,16,10.392006874084473
+67,0.9609375,0.9609375,,0.0,8,1,17,,400,,,16,10.484108209609985
+68,0.94921875,0.94921875,,0.0,8,1,18,,400,,,16,10.344013452529907
+69,0.921875,0.921875,,0.0,8,1,19,,400,,,16,10.436991930007935
+70,0.94921875,0.94921875,,0.0,8,1,20,,400,,,16,10.436023712158203
+71,0.9375,0.9375,,0.0,8,1,21,,400,,,16,10.412323236465454
+72,0.9375,0.9375,,0.0,8,1,22,,400,,,16,10.325130939483643
+73,0.90625,0.9140625,,0.0,8,1,23,,400,,,16,10.547173976898193
+74,0.92578125,0.92578125,,0.0,8,1,24,,400,,,16,10.37741994857788
+75,0.896484375,0.896484375,,0.0,9,1,0,,800,,,16,29.69838523864746
+76,0.869140625,0.869140625,,0.0,9,1,1,,800,,,16,29.21294617652893
+77,0.876953125,0.876953125,,0.0,9,1,2,,800,,,16,29.184057474136353
+78,0.861328125,0.861328125,,0.0,9,1,3,,800,,,16,28.927010536193848
+79,0.87109375,0.87109375,,0.0,9,1,4,,800,,,16,29.123291969299316
+80,0.880859375,0.880859375,,0.0,9,1,5,,800,,,16,28.829989910125732
+81,0.87109375,0.87109375,,0.0,9,1,6,,800,,,16,29.25247049331665
+82,0.87109375,0.873046875,,0.0,9,1,7,,800,,,16,29.110393285751343
+83,0.87109375,0.87109375,,0.0,9,1,8,,800,,,16,29.07777762413025
+84,0.869140625,0.87109375,,0.0,9,1,9,,800,,,16,28.875005960464478
+85,0.876953125,0.876953125,,0.0,9,1,10,,800,,,16,28.938528537750244
+86,0.845703125,0.845703125,,0.0,9,1,11,,800,,,16,28.825993299484253
+87,0.876953125,0.876953125,,0.0,9,1,12,,800,,,16,29.203014850616455
+88,0.859375,0.861328125,,0.0,9,1,13,,800,,,16,28.948869466781616
+89,0.861328125,0.861328125,,0.0,9,1,14,,800,,,16,29.158101558685303
+90,0.876953125,0.876953125,,0.0,9,1,15,,800,,,16,28.90901207923889
+91,0.875,0.875,,0.0,9,1,16,,800,,,16,28.99173641204834
+92,0.880859375,0.880859375,,0.0,9,1,17,,800,,,16,28.87599205970764
+93,0.869140625,0.869140625,,0.0,9,1,18,,800,,,16,29.078078269958496
+94,0.859375,0.859375,,0.0,9,1,19,,800,,,16,28.770277738571167
+95,0.880859375,0.880859375,,0.0,9,1,20,,800,,,16,29.028451442718506
+96,0.87890625,0.87890625,,0.0,9,1,21,,800,,,16,28.97899293899536
+97,0.865234375,0.865234375,,0.0,9,1,22,,800,,,16,29.083005666732788
+98,0.849609375,0.849609375,,0.0,9,1,23,,800,,,16,28.900007247924805
+99,0.85546875,0.85546875,,0.0,9,1,24,,800,,,16,29.050899267196655
+100,1.0,1.0,,0.01,6,1,0,,100,,,16,3.4423587322235107
+101,1.0,1.0,,0.01,6,1,1,,100,,,16,3.6570069789886475
+102,1.0,1.0,,0.01,6,1,2,,100,,,16,3.7389941215515137
+103,1.0,1.0,,0.01,6,1,3,,100,,,16,3.6143007278442383
+104,1.0,1.0,,0.01,6,1,4,,100,,,16,3.659000873565674
+105,1.0,1.0,,0.01,6,1,5,,100,,,16,3.5320141315460205
+106,1.0,1.0,,0.01,6,1,6,,100,,,16,3.485997200012207
+107,1.0,1.0,,0.01,6,1,7,,100,,,16,3.450007200241089
+108,1.0,1.0,,0.01,6,1,8,,100,,,16,3.4309940338134766
+109,1.0,1.0,,0.01,6,1,9,,100,,,16,3.469224214553833
+110,1.0,1.0,,0.01,6,1,10,,100,,,16,3.5510220527648926
+111,1.0,1.0,,0.01,6,1,11,,100,,,16,3.465837240219116
+112,1.0,1.0,,0.01,6,1,12,,100,,,16,3.450995922088623
+113,1.0,1.0,,0.01,6,1,13,,100,,,16,3.456021547317505
+114,1.0,1.0,,0.01,6,1,14,,100,,,16,3.4509921073913574
+115,1.0,1.0,,0.01,6,1,15,,100,,,16,3.4980080127716064
+116,1.0,1.0,,0.01,6,1,16,,100,,,16,3.4479849338531494
+117,0.984375,0.984375,,0.01,6,1,17,,100,,,16,3.471996784210205
+118,1.0,1.0,,0.01,6,1,18,,100,,,16,3.462993860244751
+119,1.0,1.0,,0.01,6,1,19,,100,,,16,3.553985595703125
+120,1.0,1.0,,0.01,6,1,20,,100,,,16,3.5269010066986084
+121,1.0,1.0,,0.01,6,1,21,,100,,,16,3.4689865112304688
+122,1.0,1.0,,0.01,6,1,22,,100,,,16,3.460014820098877
+123,1.0,1.0,,0.01,6,1,23,,100,,,16,3.472012996673584
+124,1.0,1.0,,0.01,6,1,24,,100,,,16,3.5390045642852783
+125,0.9375,0.9375,,0.01,7,1,0,,200,,,16,5.1260085105896
+126,0.9765625,0.9765625,,0.01,7,1,1,,200,,,16,5.055012941360474
+127,0.9609375,0.9765625,,0.01,7,1,2,,200,,,16,5.230483293533325
+128,0.921875,0.921875,,0.01,7,1,3,,200,,,16,5.056009531021118
+129,0.953125,0.953125,,0.01,7,1,4,,200,,,16,5.109992504119873
+130,0.96875,0.96875,,0.01,7,1,5,,200,,,16,5.136998414993286
+131,0.96875,0.96875,,0.01,7,1,6,,200,,,16,5.080497980117798
+132,0.9609375,0.96875,,0.01,7,1,7,,200,,,16,5.061008453369141
+133,0.9453125,0.9453125,,0.01,7,1,8,,200,,,16,5.082032680511475
+134,0.9921875,0.9921875,,0.01,7,1,9,,200,,,16,5.076990365982056
+135,0.96875,0.96875,,0.01,7,1,10,,200,,,16,5.092769622802734
+136,0.9609375,0.9609375,,0.01,7,1,11,,200,,,16,5.069992542266846
+137,0.9375,0.953125,,0.01,7,1,12,,200,,,16,5.1349873542785645
+138,0.9453125,0.953125,,0.01,7,1,13,,200,,,16,5.102367639541626
+139,0.9765625,0.9765625,,0.01,7,1,14,,200,,,16,5.1039817333221436
+140,0.90625,0.921875,,0.01,7,1,15,,200,,,16,5.098991394042969
+141,0.953125,0.953125,,0.01,7,1,16,,200,,,16,5.128994941711426
+142,0.9453125,0.9453125,,0.01,7,1,17,,200,,,16,5.042388916015625
+143,0.9609375,0.96875,,0.01,7,1,18,,200,,,16,5.133241176605225
+144,0.9765625,0.984375,,0.01,7,1,19,,200,,,16,5.068989038467407
+145,0.9375,0.953125,,0.01,7,1,20,,200,,,16,5.165015935897827
+146,0.9765625,0.984375,,0.01,7,1,21,,200,,,16,5.160987854003906
+147,0.9453125,0.9453125,,0.01,7,1,22,,200,,,16,5.095009088516235
+148,0.953125,0.953125,,0.01,7,1,23,,200,,,16,5.087011814117432
+149,0.9765625,0.984375,,0.01,7,1,24,,200,,,16,5.242021322250366
+150,0.87890625,0.88671875,,0.01,8,1,0,,400,,,16,10.498998641967773
+151,0.87109375,0.87890625,,0.01,8,1,1,,400,,,16,10.594366550445557
+152,0.8359375,0.83984375,,0.01,8,1,2,,400,,,16,10.390004634857178
+153,0.859375,0.875,,0.01,8,1,3,,400,,,16,10.480017900466919
+154,0.83984375,0.85546875,,0.01,8,1,4,,400,,,16,10.479344367980957
+155,0.8828125,0.890625,,0.01,8,1,5,,400,,,16,10.45937705039978
+156,0.8671875,0.875,,0.01,8,1,6,,400,,,16,10.346532821655273
+157,0.8671875,0.87890625,,0.01,8,1,7,,400,,,16,10.57599949836731
+158,0.875,0.87890625,,0.01,8,1,8,,400,,,16,10.359987497329712
+159,0.8671875,0.87109375,,0.01,8,1,9,,400,,,16,10.437799453735352
+160,0.9140625,0.9296875,,0.01,8,1,10,,400,,,16,10.482987403869629
+161,0.9140625,0.9140625,,0.01,8,1,11,,400,,,16,10.476015090942383
+162,0.85546875,0.87109375,,0.01,8,1,12,,400,,,16,10.361020803451538
+163,0.87890625,0.87890625,,0.01,8,1,13,,400,,,16,10.511443853378296
+164,0.86328125,0.8671875,,0.01,8,1,14,,400,,,16,10.333019495010376
+165,0.86328125,0.87109375,,0.01,8,1,15,,400,,,16,10.448004007339478
+166,0.8671875,0.87109375,,0.01,8,1,16,,400,,,16,10.362003803253174
+167,0.87109375,0.875,,0.01,8,1,17,,400,,,16,10.490233421325684
+168,0.87890625,0.87890625,,0.01,8,1,18,,400,,,16,10.348990678787231
+169,0.859375,0.859375,,0.01,8,1,19,,400,,,16,10.407986164093018
+170,0.83984375,0.83984375,,0.01,8,1,20,,400,,,16,10.31798768043518
+171,0.828125,0.83984375,,0.01,8,1,21,,400,,,16,10.433493614196777
+172,0.859375,0.859375,,0.01,8,1,22,,400,,,16,10.358011245727539
+173,0.87890625,0.8828125,,0.01,8,1,23,,400,,,16,10.52700161933899
+174,0.87109375,0.875,,0.01,8,1,24,,400,,,16,10.350010871887207
+175,0.7734375,0.783203125,,0.01,9,1,0,,800,,,16,29.13000512123108
+176,0.779296875,0.78125,,0.01,9,1,1,,800,,,16,28.851338148117065
+177,0.734375,0.744140625,,0.01,9,1,2,,800,,,16,29.018425464630127
+178,0.763671875,0.771484375,,0.01,9,1,3,,800,,,16,28.7741756439209
+179,0.771484375,0.771484375,,0.01,9,1,4,,800,,,16,28.8899929523468
+180,0.779296875,0.78125,,0.01,9,1,5,,800,,,16,28.728666305541992
+181,0.76171875,0.76953125,,0.01,9,1,6,,800,,,16,28.96578550338745
+182,0.75390625,0.759765625,,0.01,9,1,7,,800,,,16,28.65698528289795
+183,0.779296875,0.783203125,,0.01,9,1,8,,800,,,16,28.915172576904297
+184,0.767578125,0.767578125,,0.01,9,1,9,,800,,,16,28.760705947875977
+185,0.767578125,0.763671875,,0.01,9,1,10,,800,,,16,29.046656847000122
+186,0.751953125,0.75,,0.01,9,1,11,,800,,,16,28.714956283569336
+187,0.7890625,0.796875,,0.01,9,1,12,,800,,,16,28.920907497406006
+188,0.775390625,0.783203125,,0.01,9,1,13,,800,,,16,28.68890118598938
+189,0.771484375,0.7734375,,0.01,9,1,14,,800,,,16,28.98079013824463
+190,0.7578125,0.767578125,,0.01,9,1,15,,800,,,16,28.87597894668579
+191,0.7890625,0.7890625,,0.01,9,1,16,,800,,,16,28.929336071014404
+192,0.7421875,0.755859375,,0.01,9,1,17,,800,,,16,28.62600803375244
+193,0.767578125,0.7734375,,0.01,9,1,18,,800,,,16,28.94744873046875
+194,0.759765625,0.763671875,,0.01,9,1,19,,800,,,16,28.642345905303955
+195,0.76953125,0.771484375,,0.01,9,1,20,,800,,,16,28.99617314338684
+196,0.771484375,0.767578125,,0.01,9,1,21,,800,,,16,28.64525866508484
+197,0.7734375,0.76953125,,0.01,9,1,22,,800,,,16,28.764776468276978
+198,0.767578125,0.779296875,,0.01,9,1,23,,800,,,16,28.628981351852417
+199,0.771484375,0.771484375,,0.01,9,1,24,,800,,,16,29.041065216064453
+200,0.84375,0.84375,,0.1,6,1,0,,100,,,16,3.5130088329315186
+201,0.90625,0.90625,,0.1,6,1,1,,100,,,16,3.3929996490478516
+202,0.875,0.875,,0.1,6,1,2,,100,,,16,3.40701961517334
+203,0.796875,0.78125,,0.1,6,1,3,,100,,,16,3.4370081424713135
+204,0.734375,0.703125,,0.1,6,1,4,,100,,,16,3.436990737915039
+205,0.71875,0.765625,,0.1,6,1,5,,100,,,16,3.5000123977661133
+206,0.84375,0.828125,,0.1,6,1,6,,100,,,16,3.399005174636841
+207,0.921875,0.921875,,0.1,6,1,7,,100,,,16,3.4430789947509766
+208,0.734375,0.765625,,0.1,6,1,8,,100,,,16,3.4200057983398438
+209,0.828125,0.84375,,0.1,6,1,9,,100,,,16,3.5609865188598633
+210,0.8125,0.796875,,0.1,6,1,10,,100,,,16,3.4500017166137695
+211,0.734375,0.765625,,0.1,6,1,11,,100,,,16,3.437014579772949
+212,0.765625,0.734375,,0.1,6,1,12,,100,,,16,3.4414560794830322
+213,0.84375,0.84375,,0.1,6,1,13,,100,,,16,3.436011552810669
+214,0.75,0.8125,,0.1,6,1,14,,100,,,16,3.491020679473877
+215,0.78125,0.828125,,0.1,6,1,15,,100,,,16,3.4265365600585938
+216,0.71875,0.75,,0.1,6,1,16,,100,,,16,3.4478838443756104
+217,0.828125,0.859375,,0.1,6,1,17,,100,,,16,3.4440219402313232
+218,0.828125,0.84375,,0.1,6,1,18,,100,,,16,3.5562119483947754
+219,0.75,0.75,,0.1,6,1,19,,100,,,16,3.4620354175567627
+220,0.84375,0.84375,,0.1,6,1,20,,100,,,16,3.412013053894043
+221,0.78125,0.796875,,0.1,6,1,21,,100,,,16,3.4440131187438965
+222,0.828125,0.859375,,0.1,6,1,22,,100,,,16,3.4450228214263916
+223,0.8125,0.84375,,0.1,6,1,23,,100,,,16,3.5010108947753906
+224,0.78125,0.796875,,0.1,6,1,24,,100,,,16,3.43200421333313
+225,0.7421875,0.7265625,,0.1,7,1,0,,200,,,16,5.096013307571411
+226,0.6640625,0.6640625,,0.1,7,1,1,,200,,,16,5.018006086349487
+227,0.703125,0.6953125,,0.1,7,1,2,,200,,,16,5.034989833831787
+228,0.71875,0.71875,,0.1,7,1,3,,200,,,16,5.014998435974121
+229,0.7421875,0.7734375,,0.1,7,1,4,,200,,,16,5.065016031265259
+230,0.71875,0.6953125,,0.1,7,1,5,,200,,,16,5.0640177726745605
+231,0.6796875,0.6640625,,0.1,7,1,6,,200,,,16,5.095216751098633
+232,0.6328125,0.671875,,0.1,7,1,7,,200,,,16,5.053992509841919
+233,0.7734375,0.8046875,,0.1,7,1,8,,200,,,16,5.156010389328003
+234,0.6953125,0.6953125,,0.1,7,1,9,,200,,,16,5.0330095291137695
+235,0.71875,0.734375,,0.1,7,1,10,,200,,,16,5.094991445541382
+236,0.6640625,0.6953125,,0.1,7,1,11,,200,,,16,5.107010841369629
+237,0.7109375,0.734375,,0.1,7,1,12,,200,,,16,5.039011716842651
+238,0.625,0.625,,0.1,7,1,13,,200,,,16,5.056008577346802
+239,0.6953125,0.6875,,0.1,7,1,14,,200,,,16,5.194042205810547
+240,0.609375,0.6171875,,0.1,7,1,15,,200,,,16,5.019018650054932
+241,0.671875,0.671875,,0.1,7,1,16,,200,,,16,5.070004940032959
+242,0.7109375,0.7265625,,0.1,7,1,17,,200,,,16,5.1580116748809814
+243,0.71875,0.6953125,,0.1,7,1,18,,200,,,16,5.052359580993652
+244,0.7421875,0.75,,0.1,7,1,19,,200,,,16,5.052003383636475
+245,0.671875,0.7265625,,0.1,7,1,20,,200,,,16,5.156012296676636
+246,0.6953125,0.6796875,,0.1,7,1,21,,200,,,16,5.064010858535767
+247,0.6875,0.6875,,0.1,7,1,22,,200,,,16,5.0610997676849365
+248,0.71875,0.7265625,,0.1,7,1,23,,200,,,16,5.088009357452393
+249,0.625,0.6640625,,0.1,7,1,24,,200,,,16,5.085987567901611
+250,0.6328125,0.6328125,,0.1,8,1,0,,400,,,16,10.327996492385864
+251,0.6328125,0.64453125,,0.1,8,1,1,,400,,,16,10.354998588562012
+252,0.62109375,0.609375,,0.1,8,1,2,,400,,,16,10.349018573760986
+253,0.64453125,0.66015625,,0.1,8,1,3,,400,,,16,10.327049732208252
+254,0.59765625,0.6171875,,0.1,8,1,4,,400,,,16,10.281022310256958
+255,0.6015625,0.60546875,,0.1,8,1,5,,400,,,16,10.384015321731567
+256,0.5546875,0.55859375,,0.1,8,1,6,,400,,,16,10.297021389007568
+257,0.58203125,0.625,,0.1,8,1,7,,400,,,16,10.52901005744934
+258,0.58984375,0.625,,0.1,8,1,8,,400,,,16,10.265013456344604
+259,0.66015625,0.66015625,,0.1,8,1,9,,400,,,16,10.331030130386353
+260,0.59765625,0.5703125,,0.1,8,1,10,,400,,,16,10.295989036560059
+261,0.5390625,0.57421875,,0.1,8,1,11,,400,,,16,10.422873497009277
+262,0.64453125,0.63671875,,0.1,8,1,12,,400,,,16,10.27898645401001
+263,0.58203125,0.59765625,,0.1,8,1,13,,400,,,16,10.447029113769531
+264,0.58203125,0.6015625,,0.1,8,1,14,,400,,,16,10.261008024215698
+265,0.59765625,0.62109375,,0.1,8,1,15,,400,,,16,10.33171558380127
+266,0.578125,0.58203125,,0.1,8,1,16,,400,,,16,10.39899206161499
+267,0.58203125,0.58203125,,0.1,8,1,17,,400,,,16,10.304355144500732
+268,0.58203125,0.61328125,,0.1,8,1,18,,400,,,16,10.29801321029663
+269,0.65234375,0.65625,,0.1,8,1,19,,400,,,16,10.439020156860352
+270,0.5703125,0.5859375,,0.1,8,1,20,,400,,,16,10.239061832427979
+271,0.671875,0.65234375,,0.1,8,1,21,,400,,,16,10.371310234069824
+272,0.58984375,0.58203125,,0.1,8,1,22,,400,,,16,10.258010387420654
+273,0.59375,0.609375,,0.1,8,1,23,,400,,,16,10.368011713027954
+274,0.59765625,0.625,,0.1,8,1,24,,400,,,16,10.27602219581604
+275,0.587890625,0.59765625,,0.1,9,1,0,,800,,,16,28.874988079071045
+276,0.546875,0.55078125,,0.1,9,1,1,,800,,,16,28.622418642044067
+277,0.599609375,0.607421875,,0.1,9,1,2,,800,,,16,43.27905082702637
+278,0.59765625,0.591796875,,0.1,9,1,3,,800,,,16,79.47013258934021
+279,0.591796875,0.583984375,,0.1,9,1,4,,800,,,16,79.05806255340576
+280,0.5703125,0.583984375,,0.1,9,1,5,,800,,,16,79.79075789451599
+281,0.58984375,0.5625,,0.1,9,1,6,,800,,,16,79.0019199848175
+282,0.599609375,0.6015625,,0.1,9,1,7,,800,,,16,79.82742762565613
+283,0.5546875,0.55078125,,0.1,9,1,8,,800,,,16,79.74400091171265
+284,0.54296875,0.525390625,,0.1,9,1,9,,800,,,16,79.61744284629822
+285,0.556640625,0.564453125,,0.1,9,1,10,,800,,,16,79.45785355567932
+286,0.537109375,0.537109375,,0.1,9,1,11,,800,,,16,79.1419894695282
+287,0.5625,0.552734375,,0.1,9,1,12,,800,,,16,79.46596717834473
+288,0.564453125,0.548828125,,0.1,9,1,13,,800,,,16,79.34769558906555
+289,0.564453125,0.5703125,,0.1,9,1,14,,800,,,16,79.38695549964905
+290,0.529296875,0.529296875,,0.1,9,1,15,,800,,,16,79.53227233886719
+291,0.580078125,0.5703125,,0.1,9,1,16,,800,,,16,79.47738599777222
+292,0.59375,0.58984375,,0.1,9,1,17,,800,,,16,79.4590539932251
+293,0.57421875,0.58203125,,0.1,9,1,18,,800,,,16,78.6256799697876
+294,0.5859375,0.580078125,,0.1,9,1,19,,800,,,16,78.69906616210938
+295,0.619140625,0.619140625,,0.1,9,1,20,,800,,,16,78.99776673316956
+296,0.595703125,0.578125,,0.1,9,1,21,,800,,,16,76.01518630981445
+297,0.568359375,0.568359375,,0.1,9,1,22,,800,,,16,75.1906430721283
+298,0.576171875,0.580078125,,0.1,9,1,23,,800,,,16,75.57501244544983
+299,0.619140625,0.60546875,,0.1,9,1,24,,800,,,16,75.4232485294342
+300,0.703125,0.65625,,0.2,6,1,0,,100,,,16,7.088556528091431
+301,0.75,0.75,,0.2,6,1,1,,100,,,16,7.289182186126709
+302,0.59375,0.625,,0.2,6,1,2,,100,,,16,7.096833944320679
+303,0.640625,0.625,,0.2,6,1,3,,100,,,16,7.32688045501709
+304,0.75,0.765625,,0.2,6,1,4,,100,,,16,7.1079254150390625
+305,0.734375,0.71875,,0.2,6,1,5,,100,,,16,7.189478635787964
+306,0.65625,0.65625,,0.2,6,1,6,,100,,,16,7.193982362747192
+307,0.6875,0.671875,,0.2,6,1,7,,100,,,16,7.122666835784912
+308,0.703125,0.71875,,0.2,6,1,8,,100,,,16,7.059499502182007
+309,0.625,0.59375,,0.2,6,1,9,,100,,,16,6.998458623886108
+310,0.640625,0.703125,,0.2,6,1,10,,100,,,16,7.047248363494873
+311,0.59375,0.65625,,0.2,6,1,11,,100,,,16,7.210296392440796
+312,0.6875,0.671875,,0.2,6,1,12,,100,,,16,7.3901286125183105
+313,0.71875,0.765625,,0.2,6,1,13,,100,,,16,7.163694381713867
+314,0.703125,0.6875,,0.2,6,1,14,,100,,,16,7.4183361530303955
+315,0.734375,0.71875,,0.2,6,1,15,,100,,,16,7.132516622543335
+316,0.671875,0.65625,,0.2,6,1,16,,100,,,16,7.218353033065796
+317,0.71875,0.734375,,0.2,6,1,17,,100,,,16,7.256520986557007
+318,0.640625,0.671875,,0.2,6,1,18,,100,,,16,6.99045205116272
+319,0.6875,0.65625,,0.2,6,1,19,,100,,,16,7.130892515182495
+320,0.78125,0.734375,,0.2,6,1,20,,100,,,16,6.936325550079346
+321,0.78125,0.75,,0.2,6,1,21,,100,,,16,7.216282606124878
+322,0.75,0.71875,,0.2,6,1,22,,100,,,16,7.2068517208099365
+323,0.78125,0.78125,,0.2,6,1,23,,100,,,16,7.328383207321167
+324,0.703125,0.703125,,0.2,6,1,24,,100,,,16,7.147797346115112
+325,0.671875,0.671875,,0.2,7,1,0,,200,,,16,11.947970628738403
+326,0.6015625,0.609375,,0.2,7,1,1,,200,,,16,11.589144706726074
+327,0.5625,0.578125,,0.2,7,1,2,,200,,,16,11.469240188598633
+328,0.578125,0.609375,,0.2,7,1,3,,200,,,16,11.589090585708618
+329,0.609375,0.609375,,0.2,7,1,4,,200,,,16,11.84244418144226
+330,0.625,0.6015625,,0.2,7,1,5,,200,,,16,11.467111825942993
+331,0.6484375,0.6171875,,0.2,7,1,6,,200,,,16,11.607553005218506
+332,0.609375,0.6328125,,0.2,7,1,7,,200,,,16,12.018526077270508
+333,0.5703125,0.640625,,0.2,7,1,8,,200,,,16,11.907921075820923
+334,0.6015625,0.6171875,,0.2,7,1,9,,200,,,16,11.461730003356934
+335,0.6484375,0.6484375,,0.2,7,1,10,,200,,,16,11.696197509765625
+336,0.59375,0.6328125,,0.2,7,1,11,,200,,,16,11.952533960342407
+337,0.5859375,0.546875,,0.2,7,1,12,,200,,,16,11.964995861053467
+338,0.5625,0.5546875,,0.2,7,1,13,,200,,,16,11.360517740249634
+339,0.5625,0.5703125,,0.2,7,1,14,,200,,,16,11.637140274047852
+340,0.6796875,0.65625,,0.2,7,1,15,,200,,,16,11.8042893409729
+341,0.578125,0.546875,,0.2,7,1,16,,200,,,16,11.883296966552734
+342,0.6171875,0.6171875,,0.2,7,1,17,,200,,,16,11.372945308685303
+343,0.53125,0.625,,0.2,7,1,18,,200,,,16,11.40497612953186
+344,0.6171875,0.6328125,,0.2,7,1,19,,200,,,16,11.965016603469849
+345,0.609375,0.6015625,,0.2,7,1,20,,200,,,16,11.481650590896606
+346,0.6484375,0.6484375,,0.2,7,1,21,,200,,,16,11.19699501991272
+347,0.6328125,0.6328125,,0.2,7,1,22,,200,,,16,11.75974988937378
+348,0.5859375,0.59375,,0.2,7,1,23,,200,,,16,11.920303106307983
+349,0.609375,0.6171875,,0.2,7,1,24,,200,,,16,11.621772527694702
+350,0.57421875,0.62109375,,0.2,8,1,0,,400,,,16,25.782994508743286
+351,0.57421875,0.57421875,,0.2,8,1,1,,400,,,16,25.988471746444702
+352,0.59375,0.6171875,,0.2,8,1,2,,400,,,16,25.699668407440186
+353,0.58984375,0.5703125,,0.2,8,1,3,,400,,,16,25.512256383895874
+354,0.6015625,0.578125,,0.2,8,1,4,,400,,,16,25.89079213142395
+355,0.57421875,0.5625,,0.2,8,1,5,,400,,,16,25.9947726726532
+356,0.57421875,0.5859375,,0.2,8,1,6,,400,,,16,25.80664849281311
+357,0.58203125,0.5859375,,0.2,8,1,7,,400,,,16,25.812772035598755
+358,0.56640625,0.56640625,,0.2,8,1,8,,400,,,16,25.509360551834106
+359,0.5625,0.59375,,0.2,8,1,9,,400,,,16,25.51815414428711
+360,0.5625,0.58203125,,0.2,8,1,10,,400,,,16,25.614379167556763
+361,0.54296875,0.56640625,,0.2,8,1,11,,400,,,16,25.543198585510254
+362,0.5859375,0.58203125,,0.2,8,1,12,,400,,,16,25.91432237625122
+363,0.55859375,0.5625,,0.2,8,1,13,,400,,,16,25.53929567337036
+364,0.5859375,0.58203125,,0.2,8,1,14,,400,,,16,25.56706738471985
+365,0.5625,0.55859375,,0.2,8,1,15,,400,,,16,25.712387084960938
+366,0.5859375,0.6015625,,0.2,8,1,16,,400,,,16,25.796109437942505
+367,0.5859375,0.60546875,,0.2,8,1,17,,400,,,16,26.487733125686646
+368,0.6171875,0.61328125,,0.2,8,1,18,,400,,,16,27.09585952758789
+369,0.5703125,0.57421875,,0.2,8,1,19,,400,,,16,26.60591459274292
+370,0.62109375,0.6015625,,0.2,8,1,20,,400,,,16,18.552346229553223
+371,0.5859375,0.6015625,,0.2,8,1,21,,400,,,16,10.417118072509766
+372,0.58203125,0.5703125,,0.2,8,1,22,,400,,,16,10.41304349899292
+373,0.55078125,0.5703125,,0.2,8,1,23,,400,,,16,10.517022848129272
+374,0.57421875,0.5703125,,0.2,8,1,24,,400,,,16,10.371999740600586
+375,0.55078125,0.541015625,,0.2,9,1,0,,800,,,16,28.84241271018982
+376,0.52734375,0.529296875,,0.2,9,1,1,,800,,,16,28.699305057525635
+377,0.513671875,0.548828125,,0.2,9,1,2,,800,,,16,28.83052635192871
+378,0.533203125,0.525390625,,0.2,9,1,3,,800,,,16,28.61614203453064
+379,0.5546875,0.56640625,,0.2,9,1,4,,800,,,16,28.8135187625885
+380,0.509765625,0.53515625,,0.2,9,1,5,,800,,,16,28.59300684928894
+381,0.552734375,0.541015625,,0.2,9,1,6,,800,,,16,28.722005128860474
+382,0.53125,0.533203125,,0.2,9,1,7,,800,,,16,28.722684860229492
+383,0.53515625,0.556640625,,0.2,9,1,8,,800,,,16,28.90349793434143
+384,0.552734375,0.55078125,,0.2,9,1,9,,800,,,16,29.022993564605713
+385,0.5390625,0.53515625,,0.2,9,1,10,,800,,,16,28.837945699691772
+386,0.54296875,0.556640625,,0.2,9,1,11,,800,,,16,28.638678073883057
+387,0.501953125,0.51171875,,0.2,9,1,12,,800,,,16,28.751835823059082
+388,0.529296875,0.51953125,,0.2,9,1,13,,800,,,16,28.88070249557495
+389,0.541015625,0.55859375,,0.2,9,1,14,,800,,,16,28.99802017211914
+390,0.55078125,0.544921875,,0.2,9,1,15,,800,,,16,28.732925176620483
+391,0.53125,0.5234375,,0.2,9,1,16,,800,,,16,28.739745140075684
+392,0.57421875,0.5703125,,0.2,9,1,17,,800,,,16,28.63746213912964
+393,0.5390625,0.541015625,,0.2,9,1,18,,800,,,16,29.099549531936646
+394,0.501953125,0.544921875,,0.2,9,1,19,,800,,,16,28.730146884918213
+395,0.53515625,0.52734375,,0.2,9,1,20,,800,,,16,28.993767738342285
+396,0.54296875,0.56640625,,0.2,9,1,21,,800,,,16,28.66638469696045
+397,0.572265625,0.55859375,,0.2,9,1,22,,800,,,16,28.919008255004883
+398,0.513671875,0.52734375,,0.2,9,1,23,,800,,,16,28.6738338470459
+399,0.53125,0.560546875,,0.2,9,1,24,,800,,,16,28.829394817352295
diff --git a/experiments/bench/oneMax/data/easimple-pop=1000.csv b/experiments/bench/oneMax/data/easimple-pop=1000.csv
new file mode 100644
index 0000000000000000000000000000000000000000..bea9ec39f65c65e39f9c4d0279c9cc3521a13a8a
--- /dev/null
+++ b/experiments/bench/oneMax/data/easimple-pop=1000.csv
@@ -0,0 +1,401 @@
+,best_pop,best_hof,best_arm,std,dim,n_eval,run_number,UCB_sigma,ngen,mu,lambda,n_thread,time
+0,1.0,1.0,,0.0,6,1,0,,100,,,16,8.658551931381226
+1,1.0,1.0,,0.0,6,1,1,,100,,,16,8.589167833328247
+2,1.0,1.0,,0.0,6,1,2,,100,,,16,8.863619565963745
+3,1.0,1.0,,0.0,6,1,3,,100,,,16,8.866016626358032
+4,1.0,1.0,,0.0,6,1,4,,100,,,16,8.742724895477295
+5,1.0,1.0,,0.0,6,1,5,,100,,,16,8.758261442184448
+6,1.0,1.0,,0.0,6,1,6,,100,,,16,8.719042539596558
+7,1.0,1.0,,0.0,6,1,7,,100,,,16,8.929068326950073
+8,1.0,1.0,,0.0,6,1,8,,100,,,16,8.695988893508911
+9,1.0,1.0,,0.0,6,1,9,,100,,,16,8.800977230072021
+10,1.0,1.0,,0.0,6,1,10,,100,,,16,9.02398943901062
+11,1.0,1.0,,0.0,6,1,11,,100,,,16,9.58165168762207
+12,1.0,1.0,,0.0,6,1,12,,100,,,16,13.03299880027771
+13,1.0,1.0,,0.0,6,1,13,,100,,,16,14.209120750427246
+14,1.0,1.0,,0.0,6,1,14,,100,,,16,14.762995958328247
+15,1.0,1.0,,0.0,6,1,15,,100,,,16,14.642704963684082
+16,1.0,1.0,,0.0,6,1,16,,100,,,16,14.846545934677124
+17,1.0,1.0,,0.0,6,1,17,,100,,,16,14.77661657333374
+18,1.0,1.0,,0.0,6,1,18,,100,,,16,14.720995664596558
+19,1.0,1.0,,0.0,6,1,19,,100,,,16,14.759589910507202
+20,1.0,1.0,,0.0,6,1,20,,100,,,16,14.240996360778809
+21,1.0,1.0,,0.0,6,1,21,,100,,,16,12.172183990478516
+22,1.0,1.0,,0.0,6,1,22,,100,,,16,13.67898964881897
+23,1.0,1.0,,0.0,6,1,23,,100,,,16,13.400997400283813
+24,1.0,1.0,,0.0,6,1,24,,100,,,16,13.504753351211548
+25,1.0,1.0,,0.0,7,1,0,,200,,,16,31.073124885559082
+26,1.0,1.0,,0.0,7,1,1,,200,,,16,30.74764060974121
+27,1.0,1.0,,0.0,7,1,2,,200,,,16,29.750239372253418
+28,1.0,1.0,,0.0,7,1,3,,200,,,16,27.513737678527832
+29,1.0,1.0,,0.0,7,1,4,,200,,,16,25.962236166000366
+30,1.0,1.0,,0.0,7,1,5,,200,,,16,26.22708797454834
+31,1.0,1.0,,0.0,7,1,6,,200,,,16,25.685993194580078
+32,1.0,1.0,,0.0,7,1,7,,200,,,16,27.380411624908447
+33,1.0,1.0,,0.0,7,1,8,,200,,,16,26.277541160583496
+34,1.0,1.0,,0.0,7,1,9,,200,,,16,25.486239671707153
+35,1.0,1.0,,0.0,7,1,10,,200,,,16,25.492244482040405
+36,1.0,1.0,,0.0,7,1,11,,200,,,16,25.446127891540527
+37,1.0,1.0,,0.0,7,1,12,,200,,,16,25.415498733520508
+38,1.0,1.0,,0.0,7,1,13,,200,,,16,26.226104497909546
+39,1.0,1.0,,0.0,7,1,14,,200,,,16,27.05217409133911
+40,1.0,1.0,,0.0,7,1,15,,200,,,16,22.680264949798584
+41,1.0,1.0,,0.0,7,1,16,,200,,,16,23.89915442466736
+42,1.0,1.0,,0.0,7,1,17,,200,,,16,23.91988444328308
+43,1.0,1.0,,0.0,7,1,18,,200,,,16,22.416691064834595
+44,1.0,1.0,,0.0,7,1,19,,200,,,16,24.621994495391846
+45,1.0,1.0,,0.0,7,1,20,,200,,,16,23.8881516456604
+46,1.0,1.0,,0.0,7,1,21,,200,,,16,23.82668662071228
+47,1.0,1.0,,0.0,7,1,22,,200,,,16,22.471529245376587
+48,1.0,1.0,,0.0,7,1,23,,200,,,16,24.809544324874878
+49,1.0,1.0,,0.0,7,1,24,,200,,,16,23.712992191314697
+50,0.9921875,0.9921875,,0.0,8,1,0,,400,,,16,72.35450577735901
+51,1.0,1.0,,0.0,8,1,1,,400,,,16,73.31023693084717
+52,1.0,1.0,,0.0,8,1,2,,400,,,16,72.1270866394043
+53,1.0,1.0,,0.0,8,1,3,,400,,,16,72.02160882949829
+54,1.0,1.0,,0.0,8,1,4,,400,,,16,73.42812728881836
+55,1.0,1.0,,0.0,8,1,5,,400,,,16,72.05073308944702
+56,0.9921875,0.99609375,,0.0,8,1,6,,400,,,16,73.02230930328369
+57,1.0,1.0,,0.0,8,1,7,,400,,,16,88.17005038261414
+58,1.0,1.0,,0.0,8,1,8,,400,,,16,96.14842057228088
+59,1.0,1.0,,0.0,8,1,9,,400,,,16,90.82969903945923
+60,1.0,1.0,,0.0,8,1,10,,400,,,16,81.78883981704712
+61,1.0,1.0,,0.0,8,1,11,,400,,,16,79.13903617858887
+62,1.0,1.0,,0.0,8,1,12,,400,,,16,79.18589758872986
+63,0.99609375,1.0,,0.0,8,1,13,,400,,,16,76.72475528717041
+64,1.0,1.0,,0.0,8,1,14,,400,,,16,73.71565580368042
+65,1.0,1.0,,0.0,8,1,15,,400,,,16,72.30092930793762
+66,1.0,1.0,,0.0,8,1,16,,400,,,16,72.4833116531372
+67,1.0,1.0,,0.0,8,1,17,,400,,,16,73.09994173049927
+68,1.0,1.0,,0.0,8,1,18,,400,,,16,72.071861743927
+69,1.0,1.0,,0.0,8,1,19,,400,,,16,73.21182560920715
+70,0.9921875,0.99609375,,0.0,8,1,20,,400,,,16,72.11425924301147
+71,0.99609375,0.99609375,,0.0,8,1,21,,400,,,16,72.06727695465088
+72,1.0,1.0,,0.0,8,1,22,,400,,,16,73.08577275276184
+73,1.0,1.0,,0.0,8,1,23,,400,,,16,72.01918411254883
+74,1.0,1.0,,0.0,8,1,24,,400,,,16,96.89290380477905
+75,0.978515625,0.978515625,,0.0,9,1,0,,800,,,16,305.58592796325684
+76,0.974609375,0.9765625,,0.0,9,1,1,,800,,,16,270.61480593681335
+77,0.98046875,0.98046875,,0.0,9,1,2,,800,,,16,256.91538667678833
+78,0.98046875,0.98046875,,0.0,9,1,3,,800,,,16,256.39720606803894
+79,0.978515625,0.978515625,,0.0,9,1,4,,800,,,16,307.99484300613403
+80,0.96875,0.96875,,0.0,9,1,5,,800,,,16,287.3972463607788
+81,0.97265625,0.97265625,,0.0,9,1,6,,800,,,16,260.96209025382996
+82,0.97265625,0.974609375,,0.0,9,1,7,,800,,,16,257.63217306137085
+83,0.9765625,0.9765625,,0.0,9,1,8,,800,,,16,258.8093376159668
+84,0.978515625,0.978515625,,0.0,9,1,9,,800,,,16,323.2753577232361
+85,0.98828125,0.98828125,,0.0,9,1,10,,800,,,16,273.843875169754
+86,0.984375,0.984375,,0.0,9,1,11,,800,,,16,256.7925155162811
+87,0.9765625,0.9765625,,0.0,9,1,12,,800,,,16,258.39758038520813
+88,0.982421875,0.982421875,,0.0,9,1,13,,800,,,16,290.17931032180786
+89,0.978515625,0.978515625,,0.0,9,1,14,,800,,,16,296.0412006378174
+90,0.97265625,0.97265625,,0.0,9,1,15,,800,,,16,266.6681568622589
+91,0.982421875,0.982421875,,0.0,9,1,16,,800,,,16,256.8743169307709
+92,0.982421875,0.982421875,,0.0,9,1,17,,800,,,16,256.94142627716064
+93,0.982421875,0.982421875,,0.0,9,1,18,,800,,,16,312.72450709342957
+94,0.978515625,0.978515625,,0.0,9,1,19,,800,,,16,282.8326213359833
+95,0.9609375,0.9609375,,0.0,9,1,20,,800,,,16,259.20402669906616
+96,0.98046875,0.98046875,,0.0,9,1,21,,800,,,16,257.75157499313354
+97,0.97265625,0.97265625,,0.0,9,1,22,,800,,,16,266.56203293800354
+98,0.974609375,0.974609375,,0.0,9,1,23,,800,,,16,316.0810966491699
+99,0.966796875,0.966796875,,0.0,9,1,24,,800,,,16,272.56105041503906
+100,1.0,1.0,,0.01,6,1,0,,100,,,16,9.215989351272583
+101,1.0,1.0,,0.01,6,1,1,,100,,,16,9.274524211883545
+102,1.0,1.0,,0.01,6,1,2,,100,,,16,10.517987489700317
+103,1.0,1.0,,0.01,6,1,3,,100,,,16,9.33899474143982
+104,1.0,1.0,,0.01,6,1,4,,100,,,16,9.278651475906372
+105,1.0,1.0,,0.01,6,1,5,,100,,,16,9.30199146270752
+106,1.0,1.0,,0.01,6,1,6,,100,,,16,11.559013366699219
+107,1.0,1.0,,0.01,6,1,7,,100,,,16,9.140548467636108
+108,1.0,1.0,,0.01,6,1,8,,100,,,16,9.335005521774292
+109,1.0,1.0,,0.01,6,1,9,,100,,,16,10.521993398666382
+110,1.0,1.0,,0.01,6,1,10,,100,,,16,9.241124153137207
+111,1.0,1.0,,0.01,6,1,11,,100,,,16,9.27799391746521
+112,1.0,1.0,,0.01,6,1,12,,100,,,16,9.30998420715332
+113,1.0,1.0,,0.01,6,1,13,,100,,,16,11.684556245803833
+114,1.0,1.0,,0.01,6,1,14,,100,,,16,9.310986995697021
+115,1.0,1.0,,0.01,6,1,15,,100,,,16,9.202986717224121
+116,1.0,1.0,,0.01,6,1,16,,100,,,16,10.678130149841309
+117,1.0,1.0,,0.01,6,1,17,,100,,,16,9.22098708152771
+118,1.0,1.0,,0.01,6,1,18,,100,,,16,9.285988807678223
+119,1.0,1.0,,0.01,6,1,19,,100,,,16,9.305264711380005
+120,1.0,1.0,,0.01,6,1,20,,100,,,16,11.47999095916748
+121,1.0,1.0,,0.01,6,1,21,,100,,,16,9.351989984512329
+122,1.0,1.0,,0.01,6,1,22,,100,,,16,9.286646366119385
+123,1.0,1.0,,0.01,6,1,23,,100,,,16,10.636996030807495
+124,1.0,1.0,,0.01,6,1,24,,100,,,16,9.401986837387085
+125,1.0,1.0,,0.01,7,1,0,,200,,,16,23.829083681106567
+126,1.0,1.0,,0.01,7,1,1,,200,,,16,22.617223262786865
+127,1.0,1.0,,0.01,7,1,2,,200,,,16,23.752129554748535
+128,1.0,1.0,,0.01,7,1,3,,200,,,16,23.821120262145996
+129,1.0,1.0,,0.01,7,1,4,,200,,,16,23.925584077835083
+130,1.0,1.0,,0.01,7,1,5,,200,,,16,22.67663335800171
+131,1.0,1.0,,0.01,7,1,6,,200,,,16,23.583207607269287
+132,1.0,1.0,,0.01,7,1,7,,200,,,16,23.74353837966919
+133,1.0,1.0,,0.01,7,1,8,,200,,,16,23.705979824066162
+134,1.0,1.0,,0.01,7,1,9,,200,,,16,22.470069408416748
+135,1.0,1.0,,0.01,7,1,10,,200,,,16,23.786155939102173
+136,1.0,1.0,,0.01,7,1,11,,200,,,16,23.904861450195312
+137,1.0,1.0,,0.01,7,1,12,,200,,,16,23.6889967918396
+138,1.0,1.0,,0.01,7,1,13,,200,,,16,22.576746463775635
+139,1.0,1.0,,0.01,7,1,14,,200,,,16,23.628039598464966
+140,1.0,1.0,,0.01,7,1,15,,200,,,16,23.713616371154785
+141,1.0,1.0,,0.01,7,1,16,,200,,,16,23.72052001953125
+142,1.0,1.0,,0.01,7,1,17,,200,,,16,22.497989177703857
+143,1.0,1.0,,0.01,7,1,18,,200,,,16,23.770681381225586
+144,1.0,1.0,,0.01,7,1,19,,200,,,16,27.117577075958252
+145,1.0,1.0,,0.01,7,1,20,,200,,,16,32.616048097610474
+146,1.0,1.0,,0.01,7,1,21,,200,,,16,34.396647453308105
+147,1.0,1.0,,0.01,7,1,22,,200,,,16,33.24363374710083
+148,1.0,1.0,,0.01,7,1,23,,200,,,16,29.736634254455566
+149,1.0,1.0,,0.01,7,1,24,,200,,,16,28.733754634857178
+150,0.97265625,0.97265625,,0.01,8,1,0,,400,,,16,93.20167469978333
+151,0.984375,0.98828125,,0.01,8,1,1,,400,,,16,79.6258487701416
+152,0.98046875,0.98046875,,0.01,8,1,2,,400,,,16,78.80089282989502
+153,0.98828125,0.98828125,,0.01,8,1,3,,400,,,16,78.74081563949585
+154,0.99609375,0.99609375,,0.01,8,1,4,,400,,,16,76.91936826705933
+155,0.97265625,0.97265625,,0.01,8,1,5,,400,,,16,72.79108119010925
+156,0.96484375,0.96875,,0.01,8,1,6,,400,,,16,72.23954105377197
+157,0.98046875,0.9765625,,0.01,8,1,7,,400,,,16,73.45432877540588
+158,0.9921875,0.9921875,,0.01,8,1,8,,400,,,16,72.13410830497742
+159,0.953125,0.95703125,,0.01,8,1,9,,400,,,16,72.0783839225769
+160,0.98828125,0.9921875,,0.01,8,1,10,,400,,,16,73.08140349388123
+161,0.96875,0.9765625,,0.01,8,1,11,,400,,,16,71.98898887634277
+162,0.984375,0.98828125,,0.01,8,1,12,,400,,,16,72.0156934261322
+163,0.9765625,0.98046875,,0.01,8,1,13,,400,,,16,73.36383032798767
+164,0.9609375,0.96875,,0.01,8,1,14,,400,,,16,71.73453569412231
+165,0.9765625,0.98046875,,0.01,8,1,15,,400,,,16,96.41294026374817
+166,0.97265625,0.9765625,,0.01,8,1,16,,400,,,16,92.92839503288269
+167,0.98828125,0.9921875,,0.01,8,1,17,,400,,,16,89.9843533039093
+168,0.97265625,0.97265625,,0.01,8,1,18,,400,,,16,79.0311336517334
+169,0.98046875,0.984375,,0.01,8,1,19,,400,,,16,79.25383925437927
+170,0.96875,0.97265625,,0.01,8,1,20,,400,,,16,78.87917232513428
+171,0.9765625,0.98046875,,0.01,8,1,21,,400,,,16,75.56508183479309
+172,0.9921875,0.99609375,,0.01,8,1,22,,400,,,16,72.28684377670288
+173,0.97265625,0.9765625,,0.01,8,1,23,,400,,,16,73.53729748725891
+174,0.98828125,0.9921875,,0.01,8,1,24,,400,,,16,72.14394640922546
+175,0.896484375,0.900390625,,0.01,9,1,0,,800,,,16,257.79822182655334
+176,0.8671875,0.869140625,,0.01,9,1,1,,800,,,16,263.2531147003174
+177,0.869140625,0.865234375,,0.01,9,1,2,,800,,,16,317.12439799308777
+178,0.8515625,0.859375,,0.01,9,1,3,,800,,,16,271.69107818603516
+179,0.859375,0.861328125,,0.01,9,1,4,,800,,,16,256.7715554237366
+180,0.83984375,0.849609375,,0.01,9,1,5,,800,,,16,256.6079902648926
+181,0.861328125,0.8671875,,0.01,9,1,6,,800,,,16,295.20734190940857
+182,0.849609375,0.853515625,,0.01,9,1,7,,800,,,16,293.7382621765137
+183,0.84765625,0.8515625,,0.01,9,1,8,,800,,,16,264.0548949241638
+184,0.890625,0.892578125,,0.01,9,1,9,,800,,,16,255.97117471694946
+185,0.888671875,0.892578125,,0.01,9,1,10,,800,,,16,257.4189007282257
+186,0.869140625,0.875,,0.01,9,1,11,,800,,,16,317.7225089073181
+187,0.861328125,0.869140625,,0.01,9,1,12,,800,,,16,276.2368302345276
+188,0.900390625,0.90625,,0.01,9,1,13,,800,,,16,258.1038637161255
+189,0.896484375,0.90234375,,0.01,9,1,14,,800,,,16,255.67489433288574
+190,0.85546875,0.865234375,,0.01,9,1,15,,800,,,16,271.9613480567932
+191,0.8671875,0.87109375,,0.01,9,1,16,,800,,,16,310.34279441833496
+192,0.87109375,0.875,,0.01,9,1,17,,800,,,16,270.1286175251007
+193,0.873046875,0.876953125,,0.01,9,1,18,,800,,,16,257.2579309940338
+194,0.83984375,0.84375,,0.01,9,1,19,,800,,,16,254.64955282211304
+195,0.869140625,0.875,,0.01,9,1,20,,800,,,16,296.22491574287415
+196,0.884765625,0.888671875,,0.01,9,1,21,,800,,,16,291.98523020744324
+197,0.84765625,0.85546875,,0.01,9,1,22,,800,,,16,262.42993569374084
+198,0.880859375,0.884765625,,0.01,9,1,23,,800,,,16,255.95724868774414
+199,0.875,0.8828125,,0.01,9,1,24,,800,,,16,258.60947012901306
+200,0.9375,0.9375,,0.1,6,1,0,,100,,,16,9.186992406845093
+201,0.984375,0.984375,,0.1,6,1,1,,100,,,16,10.40519642829895
+202,0.921875,0.9375,,0.1,6,1,2,,100,,,16,9.2479887008667
+203,0.90625,0.921875,,0.1,6,1,3,,100,,,16,9.066989421844482
+204,0.96875,0.96875,,0.1,6,1,4,,100,,,16,9.970532655715942
+205,0.953125,0.96875,,0.1,6,1,5,,100,,,16,12.772019147872925
+206,0.90625,0.90625,,0.1,6,1,6,,100,,,16,14.426992654800415
+207,0.90625,0.890625,,0.1,6,1,7,,100,,,16,14.44610595703125
+208,0.9375,0.9375,,0.1,6,1,8,,100,,,16,14.525991201400757
+209,0.96875,0.9375,,0.1,6,1,9,,100,,,16,14.449540615081787
+210,0.9375,0.90625,,0.1,6,1,10,,100,,,16,14.568012475967407
+211,0.90625,0.953125,,0.1,6,1,11,,100,,,16,14.696073532104492
+212,0.9375,0.9375,,0.1,6,1,12,,100,,,16,15.020989656448364
+213,0.96875,0.953125,,0.1,6,1,13,,100,,,16,14.376235961914062
+214,0.96875,0.96875,,0.1,6,1,14,,100,,,16,12.18100094795227
+215,0.984375,0.96875,,0.1,6,1,15,,100,,,16,13.539005041122437
+216,0.984375,0.984375,,0.1,6,1,16,,100,,,16,13.341986894607544
+217,0.96875,0.953125,,0.1,6,1,17,,100,,,16,13.500665426254272
+218,0.84375,0.9375,,0.1,6,1,18,,100,,,16,13.363996982574463
+219,0.90625,0.9375,,0.1,6,1,19,,100,,,16,13.63153886795044
+220,0.984375,0.984375,,0.1,6,1,20,,100,,,16,13.64098572731018
+221,0.9375,0.984375,,0.1,6,1,21,,100,,,16,13.422027826309204
+222,0.9375,0.9375,,0.1,6,1,22,,100,,,16,13.542954921722412
+223,0.984375,0.984375,,0.1,6,1,23,,100,,,16,13.440002679824829
+224,0.921875,0.90625,,0.1,6,1,24,,100,,,16,13.533641576766968
+225,0.734375,0.8046875,,0.1,7,1,0,,200,,,16,29.24511981010437
+226,0.8203125,0.8359375,,0.1,7,1,1,,200,,,16,25.37653160095215
+227,0.8671875,0.8515625,,0.1,7,1,2,,200,,,16,25.09498620033264
+228,0.828125,0.84375,,0.1,7,1,3,,200,,,16,25.094584465026855
+229,0.734375,0.765625,,0.1,7,1,4,,200,,,16,25.28505802154541
+230,0.7578125,0.7421875,,0.1,7,1,5,,200,,,16,27.251065254211426
+231,0.796875,0.7890625,,0.1,7,1,6,,200,,,16,25.787378311157227
+232,0.78125,0.7890625,,0.1,7,1,7,,200,,,16,25.20868158340454
+233,0.734375,0.7265625,,0.1,7,1,8,,200,,,16,25.202595472335815
+234,0.8125,0.796875,,0.1,7,1,9,,200,,,16,25.191988706588745
+235,0.75,0.7734375,,0.1,7,1,10,,200,,,16,25.084625482559204
+236,0.78125,0.7734375,,0.1,7,1,11,,200,,,16,26.799620389938354
+237,0.7265625,0.84375,,0.1,7,1,12,,200,,,16,23.276159286499023
+238,0.828125,0.8203125,,0.1,7,1,13,,200,,,16,23.663782835006714
+239,0.8203125,0.8203125,,0.1,7,1,14,,200,,,16,23.73060965538025
+240,0.7578125,0.7421875,,0.1,7,1,15,,200,,,16,22.318994998931885
+241,0.7890625,0.765625,,0.1,7,1,16,,200,,,16,24.632859230041504
+242,0.734375,0.734375,,0.1,7,1,17,,200,,,16,24.320923328399658
+243,0.796875,0.796875,,0.1,7,1,18,,200,,,16,23.6411349773407
+244,0.6875,0.75,,0.1,7,1,19,,200,,,16,22.365991830825806
+245,0.7734375,0.78125,,0.1,7,1,20,,200,,,16,24.64873719215393
+246,0.7890625,0.78125,,0.1,7,1,21,,200,,,16,23.694257497787476
+247,0.71875,0.75,,0.1,7,1,22,,200,,,16,23.597310304641724
+248,0.796875,0.8046875,,0.1,7,1,23,,200,,,16,22.480270624160767
+249,0.7734375,0.7890625,,0.1,7,1,24,,200,,,16,24.357985496520996
+250,0.6328125,0.6484375,,0.1,8,1,0,,400,,,16,73.28313398361206
+251,0.6875,0.69140625,,0.1,8,1,1,,400,,,16,71.52731013298035
+252,0.68359375,0.671875,,0.1,8,1,2,,400,,,16,71.66506266593933
+253,0.64453125,0.640625,,0.1,8,1,3,,400,,,16,72.93872570991516
+254,0.6640625,0.671875,,0.1,8,1,4,,400,,,16,71.76369524002075
+255,0.640625,0.64453125,,0.1,8,1,5,,400,,,16,72.81657218933105
+256,0.67578125,0.65625,,0.1,8,1,6,,400,,,16,68.70021772384644
+257,0.6015625,0.59765625,,0.1,8,1,7,,400,,,16,66.65284776687622
+258,0.6484375,0.625,,0.1,8,1,8,,400,,,16,66.32572054862976
+259,0.62109375,0.609375,,0.1,8,1,9,,400,,,16,65.81182599067688
+260,0.6171875,0.6015625,,0.1,8,1,10,,400,,,16,66.1966245174408
+261,0.6328125,0.64453125,,0.1,8,1,11,,400,,,16,65.88473773002625
+262,0.63671875,0.640625,,0.1,8,1,12,,400,,,16,65.93336224555969
+263,0.62890625,0.65625,,0.1,8,1,13,,400,,,16,65.92475128173828
+264,0.65625,0.64453125,,0.1,8,1,14,,400,,,16,65.66771817207336
+265,0.5703125,0.578125,,0.1,8,1,15,,400,,,16,66.02658247947693
+266,0.60546875,0.5859375,,0.1,8,1,16,,400,,,16,66.03510212898254
+267,0.62109375,0.625,,0.1,8,1,17,,400,,,16,65.48440837860107
+268,0.66015625,0.6328125,,0.1,8,1,18,,400,,,16,65.76400136947632
+269,0.66015625,0.65625,,0.1,8,1,19,,400,,,16,65.59495210647583
+270,0.6875,0.70703125,,0.1,8,1,20,,400,,,16,65.87519073486328
+271,0.63671875,0.65625,,0.1,8,1,21,,400,,,16,65.93250703811646
+272,0.671875,0.671875,,0.1,8,1,22,,400,,,16,65.67358136177063
+273,0.6328125,0.62109375,,0.1,8,1,23,,400,,,16,65.77689003944397
+274,0.65625,0.64453125,,0.1,8,1,24,,400,,,16,65.68172144889832
+275,0.583984375,0.578125,,0.1,9,1,0,,800,,,16,237.00707936286926
+276,0.578125,0.576171875,,0.1,9,1,1,,800,,,16,236.38524293899536
+277,0.55078125,0.55859375,,0.1,9,1,2,,800,,,16,236.57492089271545
+278,0.58984375,0.580078125,,0.1,9,1,3,,800,,,16,236.18124866485596
+279,0.556640625,0.5859375,,0.1,9,1,4,,800,,,16,236.42050957679749
+280,0.603515625,0.603515625,,0.1,9,1,5,,800,,,16,236.32935070991516
+281,0.587890625,0.58203125,,0.1,9,1,6,,800,,,16,236.87866950035095
+282,0.564453125,0.5703125,,0.1,9,1,7,,800,,,16,236.17107224464417
+283,0.564453125,0.591796875,,0.1,9,1,8,,800,,,16,237.37579989433289
+284,0.572265625,0.560546875,,0.1,9,1,9,,800,,,16,236.05196905136108
+285,0.548828125,0.515625,,0.1,9,1,10,,800,,,16,236.1306619644165
+286,0.576171875,0.57421875,,0.1,9,1,11,,800,,,16,235.9100067615509
+287,0.625,0.611328125,,0.1,9,1,12,,800,,,16,236.37693548202515
+288,0.60546875,0.607421875,,0.1,9,1,13,,800,,,16,235.72664141654968
+289,0.578125,0.564453125,,0.1,9,1,14,,800,,,16,236.03150463104248
+290,0.5703125,0.58984375,,0.1,9,1,15,,800,,,16,236.33945059776306
+291,0.58203125,0.5859375,,0.1,9,1,16,,800,,,16,236.73955249786377
+292,0.59765625,0.5859375,,0.1,9,1,17,,800,,,16,236.08498907089233
+293,0.544921875,0.560546875,,0.1,9,1,18,,800,,,16,235.93656396865845
+294,0.583984375,0.572265625,,0.1,9,1,19,,800,,,16,236.04071950912476
+295,0.6015625,0.583984375,,0.1,9,1,20,,800,,,16,236.98011708259583
+296,0.56640625,0.55078125,,0.1,9,1,21,,800,,,16,236.48257184028625
+297,0.595703125,0.58203125,,0.1,9,1,22,,800,,,16,236.32059597969055
+298,0.5625,0.583984375,,0.1,9,1,23,,800,,,16,236.14423298835754
+299,0.564453125,0.578125,,0.1,9,1,24,,800,,,16,236.94558835029602
+300,0.828125,0.796875,,0.2,6,1,0,,100,,,16,8.362991571426392
+301,0.8125,0.796875,,0.2,6,1,1,,100,,,16,8.302511930465698
+302,0.796875,0.765625,,0.2,6,1,2,,100,,,16,8.321798086166382
+303,0.71875,0.71875,,0.2,6,1,3,,100,,,16,8.311986207962036
+304,0.71875,0.75,,0.2,6,1,4,,100,,,16,8.335987091064453
+305,0.84375,0.84375,,0.2,6,1,5,,100,,,16,8.399168729782104
+306,0.8125,0.859375,,0.2,6,1,6,,100,,,16,8.325016498565674
+307,0.8125,0.796875,,0.2,6,1,7,,100,,,16,8.259990215301514
+308,0.75,0.8125,,0.2,6,1,8,,100,,,16,8.3112051486969
+309,0.734375,0.71875,,0.2,6,1,9,,100,,,16,8.92718243598938
+310,0.84375,0.84375,,0.2,6,1,10,,100,,,16,8.344019651412964
+311,0.734375,0.78125,,0.2,6,1,11,,100,,,16,8.326612949371338
+312,0.78125,0.796875,,0.2,6,1,12,,100,,,16,8.326690912246704
+313,0.734375,0.734375,,0.2,6,1,13,,100,,,16,8.4080228805542
+314,0.84375,0.796875,,0.2,6,1,14,,100,,,16,8.358001947402954
+315,0.671875,0.703125,,0.2,6,1,15,,100,,,16,8.332995414733887
+316,0.734375,0.8125,,0.2,6,1,16,,100,,,16,8.328332901000977
+317,0.765625,0.765625,,0.2,6,1,17,,100,,,16,8.390296936035156
+318,0.734375,0.75,,0.2,6,1,18,,100,,,16,8.374001026153564
+319,0.734375,0.78125,,0.2,6,1,19,,100,,,16,8.307998895645142
+320,0.6875,0.796875,,0.2,6,1,20,,100,,,16,8.366004943847656
+321,0.765625,0.734375,,0.2,6,1,21,,100,,,16,8.331610202789307
+322,0.734375,0.71875,,0.2,6,1,22,,100,,,16,8.38798999786377
+323,0.859375,0.84375,,0.2,6,1,23,,100,,,16,8.229892015457153
+324,0.734375,0.796875,,0.2,6,1,24,,100,,,16,8.361994981765747
+325,0.71875,0.6875,,0.2,7,1,0,,200,,,16,20.985686540603638
+326,0.609375,0.6484375,,0.2,7,1,1,,200,,,16,21.04100251197815
+327,0.6640625,0.640625,,0.2,7,1,2,,200,,,16,21.067052602767944
+328,0.578125,0.625,,0.2,7,1,3,,200,,,16,20.878392219543457
+329,0.671875,0.6484375,,0.2,7,1,4,,200,,,16,20.987014055252075
+330,0.640625,0.6171875,,0.2,7,1,5,,200,,,16,21.052321434020996
+331,0.6015625,0.671875,,0.2,7,1,6,,200,,,16,20.69839882850647
+332,0.671875,0.6171875,,0.2,7,1,7,,200,,,16,20.982534408569336
+333,0.640625,0.6171875,,0.2,7,1,8,,200,,,16,20.872255325317383
+334,0.6875,0.6640625,,0.2,7,1,9,,200,,,16,20.859368562698364
+335,0.609375,0.640625,,0.2,7,1,10,,200,,,16,20.918815851211548
+336,0.703125,0.671875,,0.2,7,1,11,,200,,,16,20.88842272758484
+337,0.6328125,0.6328125,,0.2,7,1,12,,200,,,16,21.02548575401306
+338,0.65625,0.6484375,,0.2,7,1,13,,200,,,16,20.88823390007019
+339,0.65625,0.640625,,0.2,7,1,14,,200,,,16,20.803990125656128
+340,0.6875,0.6640625,,0.2,7,1,15,,200,,,16,20.89032745361328
+341,0.609375,0.6484375,,0.2,7,1,16,,200,,,16,20.848385334014893
+342,0.7265625,0.703125,,0.2,7,1,17,,200,,,16,20.94611430168152
+343,0.671875,0.6484375,,0.2,7,1,18,,200,,,16,20.962299346923828
+344,0.6640625,0.6640625,,0.2,7,1,19,,200,,,16,20.869149446487427
+345,0.6640625,0.65625,,0.2,7,1,20,,200,,,16,20.890717267990112
+346,0.6328125,0.6640625,,0.2,7,1,21,,200,,,16,20.989556074142456
+347,0.65625,0.6328125,,0.2,7,1,22,,200,,,16,20.752980709075928
+348,0.6328125,0.6328125,,0.2,7,1,23,,200,,,16,20.91626262664795
+349,0.65625,0.6328125,,0.2,7,1,24,,200,,,16,20.951284885406494
+350,0.61328125,0.59375,,0.2,8,1,0,,400,,,16,65.91119360923767
+351,0.578125,0.59375,,0.2,8,1,1,,400,,,16,65.70312213897705
+352,0.56640625,0.5625,,0.2,8,1,2,,400,,,16,65.69584679603577
+353,0.578125,0.5703125,,0.2,8,1,3,,400,,,16,65.98069763183594
+354,0.609375,0.5859375,,0.2,8,1,4,,400,,,16,65.7504460811615
+355,0.60546875,0.5859375,,0.2,8,1,5,,400,,,16,65.20052027702332
+356,0.58203125,0.59765625,,0.2,8,1,6,,400,,,16,65.98973393440247
+357,0.5859375,0.58203125,,0.2,8,1,7,,400,,,16,65.58167314529419
+358,0.62109375,0.60546875,,0.2,8,1,8,,400,,,16,65.63985276222229
+359,0.6484375,0.62109375,,0.2,8,1,9,,400,,,16,65.52052760124207
+360,0.6328125,0.61328125,,0.2,8,1,10,,400,,,16,65.80396938323975
+361,0.55078125,0.58203125,,0.2,8,1,11,,400,,,16,65.76201605796814
+362,0.578125,0.58984375,,0.2,8,1,12,,400,,,16,65.65511536598206
+363,0.59765625,0.5859375,,0.2,8,1,13,,400,,,16,65.34500670433044
+364,0.62890625,0.60546875,,0.2,8,1,14,,400,,,16,65.55599021911621
+365,0.58203125,0.61328125,,0.2,8,1,15,,400,,,16,65.91927480697632
+366,0.57421875,0.57421875,,0.2,8,1,16,,400,,,16,65.70129942893982
+367,0.55078125,0.54296875,,0.2,8,1,17,,400,,,16,65.42034840583801
+368,0.6015625,0.5859375,,0.2,8,1,18,,400,,,16,65.75007390975952
+369,0.6484375,0.625,,0.2,8,1,19,,400,,,16,65.78350448608398
+370,0.59765625,0.56640625,,0.2,8,1,20,,400,,,16,65.97322416305542
+371,0.59375,0.58984375,,0.2,8,1,21,,400,,,16,65.3145215511322
+372,0.6015625,0.59765625,,0.2,8,1,22,,400,,,16,65.56131339073181
+373,0.60546875,0.60546875,,0.2,8,1,23,,400,,,16,65.65050673484802
+374,0.56640625,0.5859375,,0.2,8,1,24,,400,,,16,65.82900643348694
+375,0.55859375,0.55078125,,0.2,9,1,0,,800,,,16,237.373939037323
+376,0.5390625,0.544921875,,0.2,9,1,1,,800,,,16,235.89510536193848
+377,0.580078125,0.572265625,,0.2,9,1,2,,800,,,16,236.8866093158722
+378,0.529296875,0.529296875,,0.2,9,1,3,,800,,,16,236.20176911354065
+379,0.587890625,0.572265625,,0.2,9,1,4,,800,,,16,236.72814559936523
+380,0.578125,0.564453125,,0.2,9,1,5,,800,,,16,236.24928641319275
+381,0.5625,0.564453125,,0.2,9,1,6,,800,,,16,236.35016465187073
+382,0.564453125,0.560546875,,0.2,9,1,7,,800,,,16,237.08912444114685
+383,0.560546875,0.541015625,,0.2,9,1,8,,800,,,16,237.1502923965454
+384,0.556640625,0.5390625,,0.2,9,1,9,,800,,,16,235.68748140335083
+385,0.537109375,0.54296875,,0.2,9,1,10,,800,,,16,236.93508315086365
+386,0.546875,0.529296875,,0.2,9,1,11,,800,,,16,236.81636667251587
+387,0.5234375,0.505859375,,0.2,9,1,12,,800,,,16,237.1837830543518
+388,0.55859375,0.54296875,,0.2,9,1,13,,800,,,16,235.9561858177185
+389,0.568359375,0.544921875,,0.2,9,1,14,,800,,,16,236.71410083770752
+390,0.5390625,0.548828125,,0.2,9,1,15,,800,,,16,235.98287296295166
+391,0.509765625,0.525390625,,0.2,9,1,16,,800,,,16,236.65497422218323
+392,0.546875,0.533203125,,0.2,9,1,17,,800,,,16,236.58176517486572
+393,0.5390625,0.521484375,,0.2,9,1,18,,800,,,16,238.10152196884155
+394,0.54296875,0.533203125,,0.2,9,1,19,,800,,,16,238.9151895046234
+395,0.55859375,0.54296875,,0.2,9,1,20,,800,,,16,238.62138867378235
+396,0.57421875,0.58203125,,0.2,9,1,21,,800,,,16,236.11227416992188
+397,0.55859375,0.544921875,,0.2,9,1,22,,800,,,16,237.50217413902283
+398,0.5859375,0.560546875,,0.2,9,1,23,,800,,,16,239.01814556121826
+399,0.55859375,0.53515625,,0.2,9,1,24,,800,,,16,239.4321219921112
diff --git a/experiments/bench/oneMax/data/mu+lambda-pop=100.csv b/experiments/bench/oneMax/data/mu+lambda-pop=100.csv
new file mode 100644
index 0000000000000000000000000000000000000000..61b4c67c9341424e6b06457a79ebdcedb45af4ad
--- /dev/null
+++ b/experiments/bench/oneMax/data/mu+lambda-pop=100.csv
@@ -0,0 +1,1601 @@
+,best_pop,best_hof,best_arm,std,dim,n_eval,run_number,UCB_sigma,ngen,mu,lambda,n_thread,time
+0,1.0,1.0,,0.0,6,1,0,,100,100,,16,3.9129936695098877
+1,1.0,1.0,,0.0,6,1,1,,100,100,,16,4.008453369140625
+2,1.0,1.0,,0.0,6,1,2,,100,100,,16,4.628479957580566
+3,1.0,1.0,,0.0,6,1,3,,100,100,,16,4.663094997406006
+4,1.0,1.0,,0.0,6,1,4,,100,100,,16,4.065397024154663
+5,1.0,1.0,,0.0,6,1,5,,100,100,,16,3.955989360809326
+6,1.0,1.0,,0.0,6,1,6,,100,100,,16,3.8449912071228027
+7,1.0,1.0,,0.0,6,1,7,,100,100,,16,3.8923277854919434
+8,1.0,1.0,,0.0,6,1,8,,100,100,,16,3.8890185356140137
+9,1.0,1.0,,0.0,6,1,9,,100,100,,16,3.816009998321533
+10,1.0,1.0,,0.0,6,1,10,,100,100,,16,3.8151814937591553
+11,1.0,1.0,,0.0,6,1,11,,100,100,,16,3.900458335876465
+12,1.0,1.0,,0.0,6,1,12,,100,100,,16,3.8359949588775635
+13,1.0,1.0,,0.0,6,1,13,,100,100,,16,3.8030083179473877
+14,1.0,1.0,,0.0,6,1,14,,100,100,,16,3.800990581512451
+15,1.0,1.0,,0.0,6,1,15,,100,100,,16,3.926093101501465
+16,1.0,1.0,,0.0,6,1,16,,100,100,,16,3.7900145053863525
+17,1.0,1.0,,0.0,6,1,17,,100,100,,16,3.821129560470581
+18,1.0,1.0,,0.0,6,1,18,,100,100,,16,3.8120367527008057
+19,1.0,1.0,,0.0,6,1,19,,100,100,,16,4.040014982223511
+20,1.0,1.0,,0.0,6,1,20,,100,100,,16,3.7959954738616943
+21,1.0,1.0,,0.0,6,1,21,,100,100,,16,3.870999574661255
+22,1.0,1.0,,0.0,6,1,22,,100,100,,16,3.7900032997131348
+23,1.0,1.0,,0.0,6,1,23,,100,100,,16,3.9330227375030518
+24,1.0,1.0,,0.0,6,1,24,,100,100,,16,3.8070335388183594
+25,0.984375,0.984375,,0.0,7,1,0,,200,100,,16,6.28781270980835
+26,0.984375,0.984375,,0.0,7,1,1,,200,100,,16,6.290000677108765
+27,1.0,1.0,,0.0,7,1,2,,200,100,,16,6.277897834777832
+28,0.984375,0.984375,,0.0,7,1,3,,200,100,,16,6.289996385574341
+29,0.9921875,0.9921875,,0.0,7,1,4,,200,100,,16,6.371114253997803
+30,0.9921875,0.9921875,,0.0,7,1,5,,200,100,,16,6.246021270751953
+31,0.9921875,0.9921875,,0.0,7,1,6,,200,100,,16,6.306366920471191
+32,1.0,1.0,,0.0,7,1,7,,200,100,,16,6.222016334533691
+33,0.984375,0.9921875,,0.0,7,1,8,,200,100,,16,6.292001724243164
+34,0.984375,0.984375,,0.0,7,1,9,,200,100,,16,6.331112384796143
+35,1.0,1.0,,0.0,7,1,10,,200,100,,16,6.229084014892578
+36,0.9921875,0.9921875,,0.0,7,1,11,,200,100,,16,6.429994106292725
+37,1.0,1.0,,0.0,7,1,12,,200,100,,16,6.2669901847839355
+38,0.9921875,0.9921875,,0.0,7,1,13,,200,100,,16,6.279999494552612
+39,1.0,1.0,,0.0,7,1,14,,200,100,,16,6.532820224761963
+40,0.9765625,0.984375,,0.0,7,1,15,,200,100,,16,6.236408233642578
+41,1.0,1.0,,0.0,7,1,16,,200,100,,16,6.2759926319122314
+42,1.0,1.0,,0.0,7,1,17,,200,100,,16,6.252023220062256
+43,1.0,1.0,,0.0,7,1,18,,200,100,,16,6.284257650375366
+44,0.9921875,0.9921875,,0.0,7,1,19,,200,100,,16,6.404647588729858
+45,0.984375,0.984375,,0.0,7,1,20,,200,100,,16,6.286026954650879
+46,0.9765625,0.984375,,0.0,7,1,21,,200,100,,16,6.247997283935547
+47,0.984375,0.984375,,0.0,7,1,22,,200,100,,16,6.319917678833008
+48,0.9921875,0.9921875,,0.0,7,1,23,,200,100,,16,6.2565836906433105
+49,0.9765625,0.9765625,,0.0,7,1,24,,200,100,,16,6.405007362365723
+50,0.9296875,0.93359375,,0.0,8,1,0,,400,100,,16,14.560350179672241
+51,0.91796875,0.91796875,,0.0,8,1,1,,400,100,,16,14.63364553451538
+52,0.9453125,0.9453125,,0.0,8,1,2,,400,100,,16,14.52816367149353
+53,0.9296875,0.93359375,,0.0,8,1,3,,400,100,,16,14.604202270507812
+54,0.921875,0.921875,,0.0,8,1,4,,400,100,,16,14.496005296707153
+55,0.9296875,0.9296875,,0.0,8,1,5,,400,100,,16,14.681779623031616
+56,0.9375,0.94140625,,0.0,8,1,6,,400,100,,16,14.650343179702759
+57,0.9375,0.9375,,0.0,8,1,7,,400,100,,16,14.598716497421265
+58,0.9453125,0.9453125,,0.0,8,1,8,,400,100,,16,14.539385318756104
+59,0.9453125,0.9453125,,0.0,8,1,9,,400,100,,16,14.59545087814331
+60,0.921875,0.921875,,0.0,8,1,10,,400,100,,16,14.495851755142212
+61,0.95703125,0.95703125,,0.0,8,1,11,,400,100,,16,14.545175313949585
+62,0.91796875,0.91796875,,0.0,8,1,12,,400,100,,16,14.49099087715149
+63,0.9453125,0.9453125,,0.0,8,1,13,,400,100,,16,14.630367040634155
+64,0.96484375,0.96484375,,0.0,8,1,14,,400,100,,16,14.475945949554443
+65,0.92578125,0.92578125,,0.0,8,1,15,,400,100,,16,14.547165155410767
+66,0.9609375,0.9609375,,0.0,8,1,16,,400,100,,16,14.489875555038452
+67,0.9296875,0.9296875,,0.0,8,1,17,,400,100,,16,14.682514667510986
+68,0.9375,0.94140625,,0.0,8,1,18,,400,100,,16,14.50999903678894
+69,0.90234375,0.90625,,0.0,8,1,19,,400,100,,16,14.513511657714844
+70,0.93359375,0.93359375,,0.0,8,1,20,,400,100,,16,14.443987369537354
+71,0.91796875,0.91796875,,0.0,8,1,21,,400,100,,16,14.56960940361023
+72,0.9375,0.94140625,,0.0,8,1,22,,400,100,,16,14.52106237411499
+73,0.94921875,0.94921875,,0.0,8,1,23,,400,100,,16,14.598000288009644
+74,0.9296875,0.9296875,,0.0,8,1,24,,400,100,,16,14.45608901977539
+75,0.87890625,0.87890625,,0.0,9,1,0,,800,100,,16,44.68483352661133
+76,0.845703125,0.845703125,,0.0,9,1,1,,800,100,,16,44.49042320251465
+77,0.85546875,0.85546875,,0.0,9,1,2,,800,100,,16,44.61711573600769
+78,0.857421875,0.857421875,,0.0,9,1,3,,800,100,,16,44.38662838935852
+79,0.861328125,0.861328125,,0.0,9,1,4,,800,100,,16,44.58679795265198
+80,0.853515625,0.85546875,,0.0,9,1,5,,800,100,,16,44.322158098220825
+81,0.857421875,0.857421875,,0.0,9,1,6,,800,100,,16,44.68658208847046
+82,0.873046875,0.873046875,,0.0,9,1,7,,800,100,,16,44.37596249580383
+83,0.884765625,0.884765625,,0.0,9,1,8,,800,100,,16,44.51291561126709
+84,0.865234375,0.865234375,,0.0,9,1,9,,800,100,,16,44.19843792915344
+85,0.875,0.875,,0.0,9,1,10,,800,100,,16,44.540735960006714
+86,0.86328125,0.865234375,,0.0,9,1,11,,800,100,,16,44.219650983810425
+87,0.849609375,0.849609375,,0.0,9,1,12,,800,100,,16,44.5736403465271
+88,0.861328125,0.861328125,,0.0,9,1,13,,800,100,,16,44.218228340148926
+89,0.849609375,0.857421875,,0.0,9,1,14,,800,100,,16,44.59189701080322
+90,0.876953125,0.876953125,,0.0,9,1,15,,800,100,,16,44.31062054634094
+91,0.837890625,0.837890625,,0.0,9,1,16,,800,100,,16,44.4210319519043
+92,0.8671875,0.8671875,,0.0,9,1,17,,800,100,,16,44.28978991508484
+93,0.873046875,0.873046875,,0.0,9,1,18,,800,100,,16,44.513373136520386
+94,0.875,0.876953125,,0.0,9,1,19,,800,100,,16,44.297175884246826
+95,0.861328125,0.861328125,,0.0,9,1,20,,800,100,,16,44.50450420379639
+96,0.869140625,0.869140625,,0.0,9,1,21,,800,100,,16,44.31076788902283
+97,0.876953125,0.87890625,,0.0,9,1,22,,800,100,,16,44.669357776641846
+98,0.857421875,0.857421875,,0.0,9,1,23,,800,100,,16,44.21803021430969
+99,0.861328125,0.861328125,,0.0,9,1,24,,800,100,,16,44.35468649864197
+100,1.0,1.0,,0.01,6,1,0,,100,100,,16,3.7750132083892822
+101,1.0,1.0,,0.01,6,1,1,,100,100,,16,3.836333751678467
+102,1.0,1.0,,0.01,6,1,2,,100,100,,16,3.788003444671631
+103,1.0,1.0,,0.01,6,1,3,,100,100,,16,3.7660343647003174
+104,0.984375,0.984375,,0.01,6,1,4,,100,100,,16,3.8230159282684326
+105,1.0,1.0,,0.01,6,1,5,,100,100,,16,3.8662338256835938
+106,1.0,1.0,,0.01,6,1,6,,100,100,,16,3.806025505065918
+107,1.0,1.0,,0.01,6,1,7,,100,100,,16,3.8440029621124268
+108,0.984375,1.0,,0.01,6,1,8,,100,100,,16,3.7989935874938965
+109,1.0,1.0,,0.01,6,1,9,,100,100,,16,3.9000141620635986
+110,0.984375,0.984375,,0.01,6,1,10,,100,100,,16,3.806997060775757
+111,1.0,1.0,,0.01,6,1,11,,100,100,,16,3.8135313987731934
+112,1.0,1.0,,0.01,6,1,12,,100,100,,16,3.792999505996704
+113,1.0,1.0,,0.01,6,1,13,,100,100,,16,3.964019536972046
+114,0.984375,1.0,,0.01,6,1,14,,100,100,,16,3.830989122390747
+115,0.96875,0.984375,,0.01,6,1,15,,100,100,,16,3.842031240463257
+116,0.984375,1.0,,0.01,6,1,16,,100,100,,16,3.805023193359375
+117,1.0,1.0,,0.01,6,1,17,,100,100,,16,3.9410226345062256
+118,1.0,1.0,,0.01,6,1,18,,100,100,,16,3.825019598007202
+119,0.984375,1.0,,0.01,6,1,19,,100,100,,16,3.8707668781280518
+120,1.0,1.0,,0.01,6,1,20,,100,100,,16,3.802002429962158
+121,0.984375,1.0,,0.01,6,1,21,,100,100,,16,3.9810004234313965
+122,1.0,1.0,,0.01,6,1,22,,100,100,,16,3.852400302886963
+123,1.0,1.0,,0.01,6,1,23,,100,100,,16,3.8750033378601074
+124,0.953125,0.984375,,0.01,6,1,24,,100,100,,16,3.8420026302337646
+125,0.9375,0.9453125,,0.01,7,1,0,,200,100,,16,6.4290077686309814
+126,0.8984375,0.9140625,,0.01,7,1,1,,200,100,,16,6.282623767852783
+127,0.9296875,0.9453125,,0.01,7,1,2,,200,100,,16,6.2920238971710205
+128,0.8828125,0.90625,,0.01,7,1,3,,200,100,,16,6.217023134231567
+129,0.9453125,0.953125,,0.01,7,1,4,,200,100,,16,6.3260228633880615
+130,0.9140625,0.9375,,0.01,7,1,5,,200,100,,16,6.408308029174805
+131,0.9296875,0.9453125,,0.01,7,1,6,,200,100,,16,6.342965126037598
+132,0.875,0.8984375,,0.01,7,1,7,,200,100,,16,6.373021364212036
+133,0.9296875,0.9453125,,0.01,7,1,8,,200,100,,16,6.270997524261475
+134,0.921875,0.9375,,0.01,7,1,9,,200,100,,16,6.268020868301392
+135,0.9375,0.9453125,,0.01,7,1,10,,200,100,,16,6.465104818344116
+136,0.921875,0.9375,,0.01,7,1,11,,200,100,,16,6.268997430801392
+137,0.953125,0.96875,,0.01,7,1,12,,200,100,,16,6.3291778564453125
+138,0.9140625,0.9375,,0.01,7,1,13,,200,100,,16,6.2520222663879395
+139,0.90625,0.921875,,0.01,7,1,14,,200,100,,16,6.299033880233765
+140,0.8984375,0.9140625,,0.01,7,1,15,,200,100,,16,6.434699535369873
+141,0.9140625,0.921875,,0.01,7,1,16,,200,100,,16,6.30403208732605
+142,0.9609375,0.96875,,0.01,7,1,17,,200,100,,16,6.284996747970581
+143,0.921875,0.9375,,0.01,7,1,18,,200,100,,16,6.28327751159668
+144,0.9140625,0.9375,,0.01,7,1,19,,200,100,,16,6.262034177780151
+145,0.90625,0.9296875,,0.01,7,1,20,,200,100,,16,6.439645528793335
+146,0.8984375,0.9140625,,0.01,7,1,21,,200,100,,16,6.495023250579834
+147,0.9453125,0.9453125,,0.01,7,1,22,,200,100,,16,6.314993143081665
+148,0.8828125,0.90625,,0.01,7,1,23,,200,100,,16,6.315017938613892
+149,0.921875,0.9296875,,0.01,7,1,24,,200,100,,16,6.283843040466309
+150,0.80859375,0.82421875,,0.01,8,1,0,,400,100,,16,14.820480108261108
+151,0.8125,0.80859375,,0.01,8,1,1,,400,100,,16,14.889018058776855
+152,0.80078125,0.81640625,,0.01,8,1,2,,400,100,,16,14.61100959777832
+153,0.83203125,0.8359375,,0.01,8,1,3,,400,100,,16,14.746051549911499
+154,0.84375,0.8515625,,0.01,8,1,4,,400,100,,16,14.654011964797974
+155,0.7890625,0.80859375,,0.01,8,1,5,,400,100,,16,14.722839832305908
+156,0.79296875,0.8046875,,0.01,8,1,6,,400,100,,16,14.635365009307861
+157,0.8203125,0.84375,,0.01,8,1,7,,400,100,,16,14.669610023498535
+158,0.82421875,0.83203125,,0.01,8,1,8,,400,100,,16,14.580265283584595
+159,0.82421875,0.828125,,0.01,8,1,9,,400,100,,16,14.695924997329712
+160,0.79296875,0.80859375,,0.01,8,1,10,,400,100,,16,14.547267198562622
+161,0.796875,0.8125,,0.01,8,1,11,,400,100,,16,14.653374671936035
+162,0.765625,0.78515625,,0.01,8,1,12,,400,100,,16,14.608066082000732
+163,0.78515625,0.80078125,,0.01,8,1,13,,400,100,,16,14.795071840286255
+164,0.8125,0.82421875,,0.01,8,1,14,,400,100,,16,14.668247699737549
+165,0.765625,0.7890625,,0.01,8,1,15,,400,100,,16,14.641963481903076
+166,0.78125,0.80078125,,0.01,8,1,16,,400,100,,16,14.553835391998291
+167,0.82421875,0.83984375,,0.01,8,1,17,,400,100,,16,14.77118444442749
+168,0.76953125,0.78515625,,0.01,8,1,18,,400,100,,16,14.5831618309021
+169,0.80078125,0.8203125,,0.01,8,1,19,,400,100,,16,14.662021398544312
+170,0.77734375,0.7890625,,0.01,8,1,20,,400,100,,16,14.614983320236206
+171,0.8125,0.82421875,,0.01,8,1,21,,400,100,,16,14.661258697509766
+172,0.8125,0.82421875,,0.01,8,1,22,,400,100,,16,14.612496376037598
+173,0.81640625,0.828125,,0.01,8,1,23,,400,100,,16,14.68599247932434
+174,0.8359375,0.8515625,,0.01,8,1,24,,400,100,,16,14.380352973937988
+175,0.681640625,0.6953125,,0.01,9,1,0,,800,100,,16,44.61797642707825
+176,0.693359375,0.6953125,,0.01,9,1,1,,800,100,,16,44.01527285575867
+177,0.71484375,0.724609375,,0.01,9,1,2,,800,100,,16,44.509512424468994
+178,0.697265625,0.70703125,,0.01,9,1,3,,800,100,,16,44.30484318733215
+179,0.69921875,0.716796875,,0.01,9,1,4,,800,100,,16,44.20665693283081
+180,0.68359375,0.69921875,,0.01,9,1,5,,800,100,,16,44.152600049972534
+181,0.70703125,0.716796875,,0.01,9,1,6,,800,100,,16,44.365922689437866
+182,0.712890625,0.728515625,,0.01,9,1,7,,800,100,,16,43.92216730117798
+183,0.677734375,0.67578125,,0.01,9,1,8,,800,100,,16,44.22818207740784
+184,0.71875,0.732421875,,0.01,9,1,9,,800,100,,16,44.02559304237366
+185,0.720703125,0.7265625,,0.01,9,1,10,,800,100,,16,44.35171318054199
+186,0.705078125,0.7109375,,0.01,9,1,11,,800,100,,16,43.94589352607727
+187,0.6640625,0.681640625,,0.01,9,1,12,,800,100,,16,44.185471534729004
+188,0.7265625,0.736328125,,0.01,9,1,13,,800,100,,16,44.07432556152344
+189,0.68359375,0.708984375,,0.01,9,1,14,,800,100,,16,44.277716398239136
+190,0.701171875,0.708984375,,0.01,9,1,15,,800,100,,16,44.07411503791809
+191,0.708984375,0.724609375,,0.01,9,1,16,,800,100,,16,44.05744004249573
+192,0.66796875,0.685546875,,0.01,9,1,17,,800,100,,16,44.03176403045654
+193,0.666015625,0.68359375,,0.01,9,1,18,,800,100,,16,44.36163663864136
+194,0.69140625,0.70703125,,0.01,9,1,19,,800,100,,16,43.96682381629944
+195,0.666015625,0.6796875,,0.01,9,1,20,,800,100,,16,44.00735807418823
+196,0.68359375,0.701171875,,0.01,9,1,21,,800,100,,16,43.82914590835571
+197,0.685546875,0.701171875,,0.01,9,1,22,,800,100,,16,44.733893394470215
+198,0.69140625,0.69921875,,0.01,9,1,23,,800,100,,16,43.88948631286621
+199,0.697265625,0.720703125,,0.01,9,1,24,,800,100,,16,44.15677762031555
+200,0.765625,0.765625,,0.1,6,1,0,,100,100,,16,3.7709906101226807
+201,0.75,0.828125,,0.1,6,1,1,,100,100,,16,3.7779970169067383
+202,0.78125,0.796875,,0.1,6,1,2,,100,100,,16,3.781337261199951
+203,0.734375,0.75,,0.1,6,1,3,,100,100,,16,3.8330435752868652
+204,0.6875,0.765625,,0.1,6,1,4,,100,100,,16,3.8039941787719727
+205,0.671875,0.765625,,0.1,6,1,5,,100,100,,16,3.7990221977233887
+206,0.859375,0.84375,,0.1,6,1,6,,100,100,,16,3.8495290279388428
+207,0.6875,0.765625,,0.1,6,1,7,,100,100,,16,3.79298996925354
+208,0.734375,0.78125,,0.1,6,1,8,,100,100,,16,3.8380072116851807
+209,0.75,0.78125,,0.1,6,1,9,,100,100,,16,3.7950000762939453
+210,0.78125,0.796875,,0.1,6,1,10,,100,100,,16,3.800001859664917
+211,0.703125,0.6875,,0.1,6,1,11,,100,100,,16,3.7990269660949707
+212,0.796875,0.84375,,0.1,6,1,12,,100,100,,16,3.820012331008911
+213,0.703125,0.703125,,0.1,6,1,13,,100,100,,16,3.8330237865448
+214,0.703125,0.734375,,0.1,6,1,14,,100,100,,16,3.794715642929077
+215,0.8125,0.828125,,0.1,6,1,15,,100,100,,16,3.831655740737915
+216,0.703125,0.734375,,0.1,6,1,16,,100,100,,16,3.858999490737915
+217,0.734375,0.796875,,0.1,6,1,17,,100,100,,16,3.8579859733581543
+218,0.671875,0.765625,,0.1,6,1,18,,100,100,,16,3.809992790222168
+219,0.75,0.78125,,0.1,6,1,19,,100,100,,16,3.816983461380005
+220,0.625,0.6875,,0.1,6,1,20,,100,100,,16,3.902989149093628
+221,0.84375,0.828125,,0.1,6,1,21,,100,100,,16,3.8509838581085205
+222,0.609375,0.71875,,0.1,6,1,22,,100,100,,16,3.8135149478912354
+223,0.6875,0.75,,0.1,6,1,23,,100,100,,16,3.839984893798828
+224,0.703125,0.75,,0.1,6,1,24,,100,100,,16,3.913991928100586
+225,0.6328125,0.6484375,,0.1,7,1,0,,200,100,,16,6.274980306625366
+226,0.578125,0.640625,,0.1,7,1,1,,200,100,,16,6.203986883163452
+227,0.6484375,0.671875,,0.1,7,1,2,,200,100,,16,6.297854423522949
+228,0.6328125,0.6796875,,0.1,7,1,3,,200,100,,16,6.227991819381714
+229,0.7109375,0.671875,,0.1,7,1,4,,200,100,,16,6.298379421234131
+230,0.6953125,0.6875,,0.1,7,1,5,,200,100,,16,6.209001302719116
+231,0.625,0.6484375,,0.1,7,1,6,,200,100,,16,6.220552206039429
+232,0.546875,0.5703125,,0.1,7,1,7,,200,100,,16,6.297585964202881
+233,0.65625,0.6328125,,0.1,7,1,8,,200,100,,16,6.245004177093506
+234,0.6796875,0.7109375,,0.1,7,1,9,,200,100,,16,6.248990058898926
+235,0.6953125,0.6953125,,0.1,7,1,10,,200,100,,16,6.273634195327759
+236,0.6953125,0.6875,,0.1,7,1,11,,200,100,,16,6.27898907661438
+237,0.6484375,0.6640625,,0.1,7,1,12,,200,100,,16,6.396073818206787
+238,0.53125,0.578125,,0.1,7,1,13,,200,100,,16,6.188988924026489
+239,0.6484375,0.6796875,,0.1,7,1,14,,200,100,,16,6.286140203475952
+240,0.5703125,0.609375,,0.1,7,1,15,,200,100,,16,6.178006172180176
+241,0.6328125,0.6484375,,0.1,7,1,16,,200,100,,16,6.256018161773682
+242,0.65625,0.65625,,0.1,7,1,17,,200,100,,16,6.368697881698608
+243,0.6171875,0.65625,,0.1,7,1,18,,200,100,,16,6.236835241317749
+244,0.6015625,0.640625,,0.1,7,1,19,,200,100,,16,6.208987712860107
+245,0.65625,0.6484375,,0.1,7,1,20,,200,100,,16,6.250988245010376
+246,0.6484375,0.65625,,0.1,7,1,21,,200,100,,16,6.221705198287964
+247,0.578125,0.65625,,0.1,7,1,22,,200,100,,16,6.360987186431885
+248,0.703125,0.71875,,0.1,7,1,23,,200,100,,16,6.212990760803223
+249,0.6171875,0.65625,,0.1,7,1,24,,200,100,,16,6.272989511489868
+250,0.59765625,0.60546875,,0.1,8,1,0,,400,100,,16,14.379489183425903
+251,0.515625,0.57421875,,0.1,8,1,1,,400,100,,16,14.567835092544556
+252,0.5859375,0.59375,,0.1,8,1,2,,400,100,,16,14.605791091918945
+253,0.59765625,0.58984375,,0.1,8,1,3,,400,100,,16,14.611203908920288
+254,0.59765625,0.6015625,,0.1,8,1,4,,400,100,,16,14.4362154006958
+255,0.55859375,0.6171875,,0.1,8,1,5,,400,100,,16,14.47007441520691
+256,0.5703125,0.58203125,,0.1,8,1,6,,400,100,,16,14.451815843582153
+257,0.61328125,0.62109375,,0.1,8,1,7,,400,100,,16,14.439971923828125
+258,0.58203125,0.578125,,0.1,8,1,8,,400,100,,16,14.367189645767212
+259,0.6171875,0.6171875,,0.1,8,1,9,,400,100,,16,14.51597285270691
+260,0.54296875,0.53515625,,0.1,8,1,10,,400,100,,16,14.387982845306396
+261,0.578125,0.58984375,,0.1,8,1,11,,400,100,,16,14.448167562484741
+262,0.6171875,0.640625,,0.1,8,1,12,,400,100,,16,14.358737707138062
+263,0.56640625,0.5546875,,0.1,8,1,13,,400,100,,16,14.621918439865112
+264,0.61328125,0.6171875,,0.1,8,1,14,,400,100,,16,14.398389101028442
+265,0.5859375,0.62890625,,0.1,8,1,15,,400,100,,16,14.471427917480469
+266,0.58203125,0.6171875,,0.1,8,1,16,,400,100,,16,14.349922180175781
+267,0.58984375,0.58984375,,0.1,8,1,17,,400,100,,16,14.402319192886353
+268,0.56640625,0.57421875,,0.1,8,1,18,,400,100,,16,14.323347806930542
+269,0.609375,0.609375,,0.1,8,1,19,,400,100,,16,14.432743787765503
+270,0.55859375,0.58203125,,0.1,8,1,20,,400,100,,16,14.305994510650635
+271,0.5859375,0.59765625,,0.1,8,1,21,,400,100,,16,14.460441589355469
+272,0.59375,0.57421875,,0.1,8,1,22,,400,100,,16,14.357495307922363
+273,0.58203125,0.5703125,,0.1,8,1,23,,400,100,,16,14.56322431564331
+274,0.5703125,0.59765625,,0.1,8,1,24,,400,100,,16,14.402883052825928
+275,0.53515625,0.55078125,,0.1,9,1,0,,800,100,,16,44.421621799468994
+276,0.55078125,0.552734375,,0.1,9,1,1,,800,100,,16,43.945300817489624
+277,0.556640625,0.568359375,,0.1,9,1,2,,800,100,,16,44.24582648277283
+278,0.525390625,0.56640625,,0.1,9,1,3,,800,100,,16,43.9807665348053
+279,0.501953125,0.50390625,,0.1,9,1,4,,800,100,,16,44.24028158187866
+280,0.5390625,0.529296875,,0.1,9,1,5,,800,100,,16,43.858635902404785
+281,0.576171875,0.5859375,,0.1,9,1,6,,800,100,,16,44.20660138130188
+282,0.55859375,0.556640625,,0.1,9,1,7,,800,100,,16,43.77288508415222
+283,0.5546875,0.556640625,,0.1,9,1,8,,800,100,,16,44.1192147731781
+284,0.537109375,0.54296875,,0.1,9,1,9,,800,100,,16,43.83630347251892
+285,0.541015625,0.54296875,,0.1,9,1,10,,800,100,,16,44.23440670967102
+286,0.525390625,0.52734375,,0.1,9,1,11,,800,100,,16,43.71450734138489
+287,0.564453125,0.560546875,,0.1,9,1,12,,800,100,,16,44.27558922767639
+288,0.541015625,0.552734375,,0.1,9,1,13,,800,100,,16,43.89778184890747
+289,0.576171875,0.55859375,,0.1,9,1,14,,800,100,,16,44.06175875663757
+290,0.501953125,0.521484375,,0.1,9,1,15,,800,100,,16,43.8115553855896
+291,0.5078125,0.515625,,0.1,9,1,16,,800,100,,16,44.07054901123047
+292,0.541015625,0.53515625,,0.1,9,1,17,,800,100,,16,43.82111167907715
+293,0.54296875,0.537109375,,0.1,9,1,18,,800,100,,16,44.064990758895874
+294,0.53515625,0.53515625,,0.1,9,1,19,,800,100,,16,43.83300447463989
+295,0.580078125,0.572265625,,0.1,9,1,20,,800,100,,16,44.050885915756226
+296,0.4921875,0.50390625,,0.1,9,1,21,,800,100,,16,43.820700883865356
+297,0.564453125,0.5625,,0.1,9,1,22,,800,100,,16,44.258169174194336
+298,0.54296875,0.55078125,,0.1,9,1,23,,800,100,,16,43.90075445175171
+299,0.564453125,0.564453125,,0.1,9,1,24,,800,100,,16,44.045682191848755
+300,0.671875,0.6875,,0.2,6,1,0,,100,100,,16,3.7720043659210205
+301,0.671875,0.703125,,0.2,6,1,1,,100,100,,16,3.8900153636932373
+302,0.625,0.65625,,0.2,6,1,2,,100,100,,16,3.7680091857910156
+303,0.609375,0.609375,,0.2,6,1,3,,100,100,,16,3.777484178543091
+304,0.640625,0.65625,,0.2,6,1,4,,100,100,,16,3.7721922397613525
+305,0.671875,0.6875,,0.2,6,1,5,,100,100,,16,3.9040207862854004
+306,0.671875,0.6875,,0.2,6,1,6,,100,100,,16,3.7830121517181396
+307,0.546875,0.578125,,0.2,6,1,7,,100,100,,16,3.778012990951538
+308,0.609375,0.640625,,0.2,6,1,8,,100,100,,16,3.7790074348449707
+309,0.578125,0.609375,,0.2,6,1,9,,100,100,,16,3.9380156993865967
+310,0.671875,0.65625,,0.2,6,1,10,,100,100,,16,3.788987159729004
+311,0.640625,0.640625,,0.2,6,1,11,,100,100,,16,3.80183482170105
+312,0.59375,0.640625,,0.2,6,1,12,,100,100,,16,3.8027243614196777
+313,0.640625,0.671875,,0.2,6,1,13,,100,100,,16,3.894982099533081
+314,0.640625,0.640625,,0.2,6,1,14,,100,100,,16,3.8489928245544434
+315,0.734375,0.703125,,0.2,6,1,15,,100,100,,16,3.8139841556549072
+316,0.703125,0.71875,,0.2,6,1,16,,100,100,,16,3.8045265674591064
+317,0.671875,0.703125,,0.2,6,1,17,,100,100,,16,3.9090328216552734
+318,0.640625,0.765625,,0.2,6,1,18,,100,100,,16,3.811995267868042
+319,0.671875,0.671875,,0.2,6,1,19,,100,100,,16,3.821626663208008
+320,0.578125,0.625,,0.2,6,1,20,,100,100,,16,3.788994312286377
+321,0.609375,0.6875,,0.2,6,1,21,,100,100,,16,3.929985284805298
+322,0.65625,0.703125,,0.2,6,1,22,,100,100,,16,3.841996431350708
+323,0.703125,0.75,,0.2,6,1,23,,100,100,,16,3.806105375289917
+324,0.71875,0.734375,,0.2,6,1,24,,100,100,,16,3.8089845180511475
+325,0.5859375,0.609375,,0.2,7,1,0,,200,100,,16,6.284990310668945
+326,0.6328125,0.6328125,,0.2,7,1,1,,200,100,,16,6.205718994140625
+327,0.609375,0.6328125,,0.2,7,1,2,,200,100,,16,6.232213258743286
+328,0.640625,0.65625,,0.2,7,1,3,,200,100,,16,6.271988868713379
+329,0.5703125,0.625,,0.2,7,1,4,,200,100,,16,6.268024444580078
+330,0.609375,0.640625,,0.2,7,1,5,,200,100,,16,6.2200071811676025
+331,0.5703125,0.5625,,0.2,7,1,6,,200,100,,16,6.2442357540130615
+332,0.59375,0.6015625,,0.2,7,1,7,,200,100,,16,6.207998991012573
+333,0.5546875,0.6015625,,0.2,7,1,8,,200,100,,16,6.320030212402344
+334,0.5625,0.578125,,0.2,7,1,9,,200,100,,16,6.207454204559326
+335,0.5234375,0.578125,,0.2,7,1,10,,200,100,,16,6.263293266296387
+336,0.5625,0.609375,,0.2,7,1,11,,200,100,,16,6.2296178340911865
+337,0.578125,0.625,,0.2,7,1,12,,200,100,,16,6.239985227584839
+338,0.609375,0.625,,0.2,7,1,13,,200,100,,16,6.329996585845947
+339,0.53125,0.578125,,0.2,7,1,14,,200,100,,16,6.269057512283325
+340,0.5859375,0.6328125,,0.2,7,1,15,,200,100,,16,6.211990594863892
+341,0.6015625,0.6015625,,0.2,7,1,16,,200,100,,16,6.245013475418091
+342,0.59375,0.640625,,0.2,7,1,17,,200,100,,16,6.211002588272095
+343,0.53125,0.5546875,,0.2,7,1,18,,200,100,,16,6.327354669570923
+344,0.5859375,0.609375,,0.2,7,1,19,,200,100,,16,6.2400007247924805
+345,0.609375,0.625,,0.2,7,1,20,,200,100,,16,6.266218423843384
+346,0.5546875,0.5703125,,0.2,7,1,21,,200,100,,16,6.238992691040039
+347,0.5078125,0.6015625,,0.2,7,1,22,,200,100,,16,6.274027109146118
+348,0.609375,0.625,,0.2,7,1,23,,200,100,,16,6.323238372802734
+349,0.625,0.625,,0.2,7,1,24,,200,100,,16,6.255025863647461
+350,0.52734375,0.56640625,,0.2,8,1,0,,400,100,,16,14.467580080032349
+351,0.48828125,0.49609375,,0.2,8,1,1,,400,100,,16,14.519110679626465
+352,0.515625,0.515625,,0.2,8,1,2,,400,100,,16,14.444714069366455
+353,0.58984375,0.59765625,,0.2,8,1,3,,400,100,,16,14.53735899925232
+354,0.54296875,0.54296875,,0.2,8,1,4,,400,100,,16,14.352695941925049
+355,0.57421875,0.59375,,0.2,8,1,5,,400,100,,16,14.4305260181427
+356,0.53515625,0.56640625,,0.2,8,1,6,,400,100,,16,14.339993476867676
+357,0.55078125,0.55859375,,0.2,8,1,7,,400,100,,16,14.41398549079895
+358,0.54296875,0.55078125,,0.2,8,1,8,,400,100,,16,14.453673124313354
+359,0.5625,0.57421875,,0.2,8,1,9,,400,100,,16,14.611904859542847
+360,0.578125,0.59765625,,0.2,8,1,10,,400,100,,16,14.371805906295776
+361,0.5625,0.57421875,,0.2,8,1,11,,400,100,,16,14.477521419525146
+362,0.51953125,0.53125,,0.2,8,1,12,,400,100,,16,14.417253494262695
+363,0.609375,0.59375,,0.2,8,1,13,,400,100,,16,14.495185613632202
+364,0.56640625,0.5625,,0.2,8,1,14,,400,100,,16,14.373080253601074
+365,0.53515625,0.55078125,,0.2,8,1,15,,400,100,,16,14.413397789001465
+366,0.515625,0.5234375,,0.2,8,1,16,,400,100,,16,14.378227710723877
+367,0.578125,0.5859375,,0.2,8,1,17,,400,100,,16,14.457906007766724
+368,0.48828125,0.5625,,0.2,8,1,18,,400,100,,16,14.358240604400635
+369,0.57421875,0.5703125,,0.2,8,1,19,,400,100,,16,14.53198790550232
+370,0.51171875,0.53125,,0.2,8,1,20,,400,100,,16,14.406689405441284
+371,0.49609375,0.53515625,,0.2,8,1,21,,400,100,,16,14.411774158477783
+372,0.49609375,0.53125,,0.2,8,1,22,,400,100,,16,14.28022050857544
+373,0.515625,0.53515625,,0.2,8,1,23,,400,100,,16,14.409989595413208
+374,0.51953125,0.59375,,0.2,8,1,24,,400,100,,16,14.294563055038452
+375,0.513671875,0.51953125,,0.2,9,1,0,,800,100,,16,44.17455005645752
+376,0.482421875,0.490234375,,0.2,9,1,1,,800,100,,16,44.05387544631958
+377,0.4765625,0.486328125,,0.2,9,1,2,,800,100,,16,44.45615077018738
+378,0.537109375,0.560546875,,0.2,9,1,3,,800,100,,16,44.08325505256653
+379,0.5234375,0.5078125,,0.2,9,1,4,,800,100,,16,44.1523015499115
+380,0.533203125,0.53515625,,0.2,9,1,5,,800,100,,16,44.00796341896057
+381,0.548828125,0.560546875,,0.2,9,1,6,,800,100,,16,44.04999256134033
+382,0.55859375,0.546875,,0.2,9,1,7,,800,100,,16,43.788671016693115
+383,0.54296875,0.56640625,,0.2,9,1,8,,800,100,,16,43.95444321632385
+384,0.517578125,0.517578125,,0.2,9,1,9,,800,100,,16,43.960251569747925
+385,0.537109375,0.54296875,,0.2,9,1,10,,800,100,,16,44.168148040771484
+386,0.515625,0.51953125,,0.2,9,1,11,,800,100,,16,43.9941349029541
+387,0.498046875,0.5,,0.2,9,1,12,,800,100,,16,43.987372159957886
+388,0.560546875,0.55859375,,0.2,9,1,13,,800,100,,16,43.85255670547485
+389,0.544921875,0.55078125,,0.2,9,1,14,,800,100,,16,44.12353038787842
+390,0.529296875,0.5234375,,0.2,9,1,15,,800,100,,16,43.80184578895569
+391,0.501953125,0.498046875,,0.2,9,1,16,,800,100,,16,44.164520263671875
+392,0.546875,0.548828125,,0.2,9,1,17,,800,100,,16,43.925227880477905
+393,0.53125,0.53515625,,0.2,9,1,18,,800,100,,16,44.052574157714844
+394,0.54296875,0.541015625,,0.2,9,1,19,,800,100,,16,43.621429443359375
+395,0.498046875,0.52734375,,0.2,9,1,20,,800,100,,16,44.06024765968323
+396,0.51953125,0.529296875,,0.2,9,1,21,,800,100,,16,43.77345371246338
+397,0.4921875,0.546875,,0.2,9,1,22,,800,100,,16,44.15169048309326
+398,0.525390625,0.5390625,,0.2,9,1,23,,800,100,,16,43.6316294670105
+399,0.51953125,0.537109375,,0.2,9,1,24,,800,100,,16,44.0680034160614
+400,1.0,1.0,,0.0,6,2,0,,100,100,,16,3.7430214881896973
+401,1.0,1.0,,0.0,6,2,1,,100,100,,16,3.7990224361419678
+402,1.0,1.0,,0.0,6,2,2,,100,100,,16,3.7696704864501953
+403,1.0,1.0,,0.0,6,2,3,,100,100,,16,3.8424417972564697
+404,1.0,1.0,,0.0,6,2,4,,100,100,,16,3.779984474182129
+405,1.0,1.0,,0.0,6,2,5,,100,100,,16,3.816985607147217
+406,1.0,1.0,,0.0,6,2,6,,100,100,,16,3.795992136001587
+407,1.0,1.0,,0.0,6,2,7,,100,100,,16,3.9397664070129395
+408,1.0,1.0,,0.0,6,2,8,,100,100,,16,3.8040237426757812
+409,1.0,1.0,,0.0,6,2,9,,100,100,,16,3.8000073432922363
+410,1.0,1.0,,0.0,6,2,10,,100,100,,16,3.813638925552368
+411,1.0,1.0,,0.0,6,2,11,,100,100,,16,3.9199936389923096
+412,1.0,1.0,,0.0,6,2,12,,100,100,,16,3.8130245208740234
+413,1.0,1.0,,0.0,6,2,13,,100,100,,16,3.82698392868042
+414,1.0,1.0,,0.0,6,2,14,,100,100,,16,3.8120205402374268
+415,1.0,1.0,,0.0,6,2,15,,100,100,,16,3.9415855407714844
+416,1.0,1.0,,0.0,6,2,16,,100,100,,16,3.807013988494873
+417,1.0,1.0,,0.0,6,2,17,,100,100,,16,3.8362064361572266
+418,1.0,1.0,,0.0,6,2,18,,100,100,,16,3.809018611907959
+419,1.0,1.0,,0.0,6,2,19,,100,100,,16,3.9618515968322754
+420,1.0,1.0,,0.0,6,2,20,,100,100,,16,3.8080062866210938
+421,1.0,1.0,,0.0,6,2,21,,100,100,,16,3.8259928226470947
+422,1.0,1.0,,0.0,6,2,22,,100,100,,16,3.8119864463806152
+423,1.0,1.0,,0.0,6,2,23,,100,100,,16,3.9424376487731934
+424,1.0,1.0,,0.0,6,2,24,,100,100,,16,3.8160037994384766
+425,0.984375,0.9921875,,0.0,7,2,0,,200,100,,16,6.308626890182495
+426,0.984375,0.984375,,0.0,7,2,1,,200,100,,16,6.297022342681885
+427,0.984375,0.984375,,0.0,7,2,2,,200,100,,16,6.25995945930481
+428,0.984375,0.984375,,0.0,7,2,3,,200,100,,16,6.251021862030029
+429,0.984375,0.984375,,0.0,7,2,4,,200,100,,16,6.3961021900177
+430,0.9921875,0.9921875,,0.0,7,2,5,,200,100,,16,6.250024318695068
+431,0.9921875,0.9921875,,0.0,7,2,6,,200,100,,16,6.266011714935303
+432,1.0,1.0,,0.0,7,2,7,,200,100,,16,6.243024110794067
+433,0.9765625,0.9765625,,0.0,7,2,8,,200,100,,16,6.330994606018066
+434,1.0,1.0,,0.0,7,2,9,,200,100,,16,6.3884663581848145
+435,0.984375,0.984375,,0.0,7,2,10,,200,100,,16,6.284003496170044
+436,1.0,1.0,,0.0,7,2,11,,200,100,,16,6.222019195556641
+437,0.9921875,0.9921875,,0.0,7,2,12,,200,100,,16,6.29701566696167
+438,0.9921875,0.9921875,,0.0,7,2,13,,200,100,,16,6.2330145835876465
+439,0.9921875,0.9921875,,0.0,7,2,14,,200,100,,16,6.414269685745239
+440,1.0,1.0,,0.0,7,2,15,,200,100,,16,6.262020111083984
+441,0.984375,0.984375,,0.0,7,2,16,,200,100,,16,6.2969958782196045
+442,0.984375,0.984375,,0.0,7,2,17,,200,100,,16,6.271986722946167
+443,0.96875,0.9765625,,0.0,7,2,18,,200,100,,16,6.255704164505005
+444,1.0,1.0,,0.0,7,2,19,,200,100,,16,6.371106386184692
+445,1.0,1.0,,0.0,7,2,20,,200,100,,16,6.301337718963623
+446,0.984375,0.984375,,0.0,7,2,21,,200,100,,16,6.241991281509399
+447,1.0,1.0,,0.0,7,2,22,,200,100,,16,6.319306373596191
+448,0.984375,0.984375,,0.0,7,2,23,,200,100,,16,6.299056768417358
+449,0.9921875,0.9921875,,0.0,7,2,24,,200,100,,16,6.423987150192261
+450,0.9296875,0.9296875,,0.0,8,2,0,,400,100,,16,14.658995866775513
+451,0.91015625,0.9140625,,0.0,8,2,1,,400,100,,16,14.634245157241821
+452,0.94140625,0.94140625,,0.0,8,2,2,,400,100,,16,14.508724927902222
+453,0.93359375,0.9375,,0.0,8,2,3,,400,100,,16,14.587697982788086
+454,0.9375,0.9375,,0.0,8,2,4,,400,100,,16,14.546550750732422
+455,0.9296875,0.9296875,,0.0,8,2,5,,400,100,,16,14.697357416152954
+456,0.9296875,0.9296875,,0.0,8,2,6,,400,100,,16,14.505018472671509
+457,0.9453125,0.94921875,,0.0,8,2,7,,400,100,,16,14.605323791503906
+458,0.953125,0.953125,,0.0,8,2,8,,400,100,,16,14.444989681243896
+459,0.92578125,0.92578125,,0.0,8,2,9,,400,100,,16,15.272562503814697
+460,0.9375,0.9375,,0.0,8,2,10,,400,100,,16,14.522481918334961
+461,0.921875,0.921875,,0.0,8,2,11,,400,100,,16,14.56795597076416
+462,0.9375,0.9375,,0.0,8,2,12,,400,100,,16,14.477025747299194
+463,0.92578125,0.92578125,,0.0,8,2,13,,400,100,,16,14.820953607559204
+464,0.91796875,0.91796875,,0.0,8,2,14,,400,100,,16,14.598754167556763
+465,0.9375,0.9375,,0.0,8,2,15,,400,100,,16,14.677329540252686
+466,0.94140625,0.94140625,,0.0,8,2,16,,400,100,,16,14.506300210952759
+467,0.921875,0.921875,,0.0,8,2,17,,400,100,,16,14.677440166473389
+468,0.9609375,0.9609375,,0.0,8,2,18,,400,100,,16,14.544984579086304
+469,0.95703125,0.9609375,,0.0,8,2,19,,400,100,,16,14.697523355484009
+470,0.93359375,0.94140625,,0.0,8,2,20,,400,100,,16,14.533084630966187
+471,0.92578125,0.92578125,,0.0,8,2,21,,400,100,,16,14.65770697593689
+472,0.9375,0.94140625,,0.0,8,2,22,,400,100,,16,14.574612617492676
+473,0.92578125,0.92578125,,0.0,8,2,23,,400,100,,16,14.600989818572998
+474,0.953125,0.953125,,0.0,8,2,24,,400,100,,16,14.543453216552734
+475,0.86328125,0.86328125,,0.0,9,2,0,,800,100,,16,44.766945123672485
+476,0.85546875,0.85546875,,0.0,9,2,1,,800,100,,16,44.54328227043152
+477,0.86328125,0.86328125,,0.0,9,2,2,,800,100,,16,44.84570622444153
+478,0.8671875,0.8671875,,0.0,9,2,3,,800,100,,16,44.37884473800659
+479,0.861328125,0.861328125,,0.0,9,2,4,,800,100,,16,44.77371287345886
+480,0.85546875,0.85546875,,0.0,9,2,5,,800,100,,16,44.47178292274475
+481,0.869140625,0.869140625,,0.0,9,2,6,,800,100,,16,44.82945275306702
+482,0.880859375,0.880859375,,0.0,9,2,7,,800,100,,16,44.5315043926239
+483,0.86328125,0.86328125,,0.0,9,2,8,,800,100,,16,44.56874394416809
+484,0.837890625,0.837890625,,0.0,9,2,9,,800,100,,16,44.436906814575195
+485,0.857421875,0.857421875,,0.0,9,2,10,,800,100,,16,44.65070986747742
+486,0.865234375,0.865234375,,0.0,9,2,11,,800,100,,16,44.230122804641724
+487,0.86328125,0.86328125,,0.0,9,2,12,,800,100,,16,44.60206341743469
+488,0.859375,0.859375,,0.0,9,2,13,,800,100,,16,44.387486934661865
+489,0.8671875,0.869140625,,0.0,9,2,14,,800,100,,16,44.60698747634888
+490,0.857421875,0.859375,,0.0,9,2,15,,800,100,,16,44.267282247543335
+491,0.853515625,0.853515625,,0.0,9,2,16,,800,100,,16,44.64175367355347
+492,0.849609375,0.8515625,,0.0,9,2,17,,800,100,,16,44.26336741447449
+493,0.849609375,0.849609375,,0.0,9,2,18,,800,100,,16,44.435543060302734
+494,0.87890625,0.87890625,,0.0,9,2,19,,800,100,,16,44.234522342681885
+495,0.873046875,0.875,,0.0,9,2,20,,800,100,,16,44.57845997810364
+496,0.8671875,0.8671875,,0.0,9,2,21,,800,100,,16,44.47524166107178
+497,0.85546875,0.857421875,,0.0,9,2,22,,800,100,,16,44.67589259147644
+498,0.875,0.875,,0.0,9,2,23,,800,100,,16,44.377880811691284
+499,0.8671875,0.869140625,,0.0,9,2,24,,800,100,,16,44.60809946060181
+500,1.0,1.0,,0.01,6,2,0,,100,100,,16,3.8720319271087646
+501,1.0,1.0,,0.01,6,2,1,,100,100,,16,3.829009771347046
+502,1.0,1.0,,0.01,6,2,2,,100,100,,16,3.815011978149414
+503,1.0,1.0,,0.01,6,2,3,,100,100,,16,3.8246819972991943
+504,1.0,1.0,,0.01,6,2,4,,100,100,,16,3.9039831161499023
+505,1.0,1.0,,0.01,6,2,5,,100,100,,16,3.8779923915863037
+506,1.0,1.0,,0.01,6,2,6,,100,100,,16,3.8440113067626953
+507,1.0,1.0,,0.01,6,2,7,,100,100,,16,3.8379828929901123
+508,1.0,1.0,,0.01,6,2,8,,100,100,,16,3.8980278968811035
+509,1.0,1.0,,0.01,6,2,9,,100,100,,16,3.8620078563690186
+510,1.0,1.0,,0.01,6,2,10,,100,100,,16,3.891799211502075
+511,1.0,1.0,,0.01,6,2,11,,100,100,,16,3.878999710083008
+512,1.0,1.0,,0.01,6,2,12,,100,100,,16,3.9379963874816895
+513,1.0,1.0,,0.01,6,2,13,,100,100,,16,3.874990463256836
+514,1.0,1.0,,0.01,6,2,14,,100,100,,16,3.8550126552581787
+515,1.0,1.0,,0.01,6,2,15,,100,100,,16,3.8790063858032227
+516,1.0,1.0,,0.01,6,2,16,,100,100,,16,3.9699926376342773
+517,1.0,1.0,,0.01,6,2,17,,100,100,,16,3.8970143795013428
+518,1.0,1.0,,0.01,6,2,18,,100,100,,16,3.8846380710601807
+519,0.984375,1.0,,0.01,6,2,19,,100,100,,16,3.8560216426849365
+520,1.0,1.0,,0.01,6,2,20,,100,100,,16,3.966153860092163
+521,1.0,1.0,,0.01,6,2,21,,100,100,,16,3.8940160274505615
+522,1.0,1.0,,0.01,6,2,22,,100,100,,16,3.8610305786132812
+523,1.0,1.0,,0.01,6,2,23,,100,100,,16,3.865964889526367
+524,1.0,1.0,,0.01,6,2,24,,100,100,,16,3.9960336685180664
+525,0.9609375,0.96875,,0.01,7,2,0,,200,100,,16,6.395208835601807
+526,0.9453125,0.953125,,0.01,7,2,1,,200,100,,16,6.29601526260376
+527,0.9453125,0.953125,,0.01,7,2,2,,200,100,,16,6.370142936706543
+528,0.9296875,0.953125,,0.01,7,2,3,,200,100,,16,6.282008409500122
+529,0.9609375,0.96875,,0.01,7,2,4,,200,100,,16,6.3580169677734375
+530,0.921875,0.9375,,0.01,7,2,5,,200,100,,16,6.320203542709351
+531,0.953125,0.96875,,0.01,7,2,6,,200,100,,16,6.299007415771484
+532,0.96875,0.984375,,0.01,7,2,7,,200,100,,16,6.377002000808716
+533,0.9296875,0.9453125,,0.01,7,2,8,,200,100,,16,6.3210203647613525
+534,0.8984375,0.9296875,,0.01,7,2,9,,200,100,,16,6.3111865520477295
+535,0.9609375,0.9609375,,0.01,7,2,10,,200,100,,16,6.327052116394043
+536,0.9609375,0.96875,,0.01,7,2,11,,200,100,,16,6.342380523681641
+537,0.9375,0.96875,,0.01,7,2,12,,200,100,,16,6.385031461715698
+538,0.9296875,0.9453125,,0.01,7,2,13,,200,100,,16,6.296993732452393
+539,0.9375,0.9453125,,0.01,7,2,14,,200,100,,16,6.355015754699707
+540,0.90625,0.9296875,,0.01,7,2,15,,200,100,,16,6.309995174407959
+541,0.953125,0.9609375,,0.01,7,2,16,,200,100,,16,6.390411376953125
+542,0.9609375,0.96875,,0.01,7,2,17,,200,100,,16,6.35300350189209
+543,0.90625,0.921875,,0.01,7,2,18,,200,100,,16,6.333299160003662
+544,0.9765625,0.984375,,0.01,7,2,19,,200,100,,16,6.367534160614014
+545,0.9609375,0.9609375,,0.01,7,2,20,,200,100,,16,6.366007089614868
+546,0.953125,0.9609375,,0.01,7,2,21,,200,100,,16,6.32399320602417
+547,0.9375,0.9453125,,0.01,7,2,22,,200,100,,16,6.358780145645142
+548,0.9296875,0.9375,,0.01,7,2,23,,200,100,,16,6.266987323760986
+549,0.9375,0.9453125,,0.01,7,2,24,,200,100,,16,6.331622838973999
+550,0.83984375,0.83984375,,0.01,8,2,0,,400,100,,16,14.496980905532837
+551,0.80859375,0.828125,,0.01,8,2,1,,400,100,,16,14.571182250976562
+552,0.890625,0.8984375,,0.01,8,2,2,,400,100,,16,14.61913776397705
+553,0.828125,0.84375,,0.01,8,2,3,,400,100,,16,14.751970291137695
+554,0.83984375,0.8515625,,0.01,8,2,4,,400,100,,16,14.623525857925415
+555,0.8203125,0.8359375,,0.01,8,2,5,,400,100,,16,14.705204248428345
+556,0.8125,0.82421875,,0.01,8,2,6,,400,100,,16,14.489434480667114
+557,0.83203125,0.84765625,,0.01,8,2,7,,400,100,,16,14.568687438964844
+558,0.8359375,0.84765625,,0.01,8,2,8,,400,100,,16,14.43801236152649
+559,0.8515625,0.86328125,,0.01,8,2,9,,400,100,,16,14.653838872909546
+560,0.828125,0.84375,,0.01,8,2,10,,400,100,,16,14.559392213821411
+561,0.83984375,0.84765625,,0.01,8,2,11,,400,100,,16,14.591638088226318
+562,0.84765625,0.86328125,,0.01,8,2,12,,400,100,,16,14.537438869476318
+563,0.828125,0.84375,,0.01,8,2,13,,400,100,,16,14.641525983810425
+564,0.8125,0.82421875,,0.01,8,2,14,,400,100,,16,14.505990743637085
+565,0.796875,0.8203125,,0.01,8,2,15,,400,100,,16,14.668687105178833
+566,0.8203125,0.83203125,,0.01,8,2,16,,400,100,,16,14.580018043518066
+567,0.828125,0.83984375,,0.01,8,2,17,,400,100,,16,14.601460695266724
+568,0.83203125,0.8515625,,0.01,8,2,18,,400,100,,16,14.542721271514893
+569,0.82421875,0.8359375,,0.01,8,2,19,,400,100,,16,14.594989776611328
+570,0.80859375,0.8203125,,0.01,8,2,20,,400,100,,16,14.452652215957642
+571,0.796875,0.8125,,0.01,8,2,21,,400,100,,16,14.560978174209595
+572,0.8203125,0.8359375,,0.01,8,2,22,,400,100,,16,14.489721059799194
+573,0.8359375,0.84375,,0.01,8,2,23,,400,100,,16,14.609424114227295
+574,0.828125,0.83203125,,0.01,8,2,24,,400,100,,16,14.49917984008789
+575,0.720703125,0.732421875,,0.01,9,2,0,,800,100,,16,44.56099724769592
+576,0.712890625,0.73046875,,0.01,9,2,1,,800,100,,16,44.36147499084473
+577,0.6953125,0.712890625,,0.01,9,2,2,,800,100,,16,44.639424562454224
+578,0.732421875,0.74609375,,0.01,9,2,3,,800,100,,16,44.18275284767151
+579,0.70703125,0.71484375,,0.01,9,2,4,,800,100,,16,44.34233522415161
+580,0.732421875,0.74609375,,0.01,9,2,5,,800,100,,16,44.26452851295471
+581,0.732421875,0.732421875,,0.01,9,2,6,,800,100,,16,44.58424520492554
+582,0.701171875,0.71484375,,0.01,9,2,7,,800,100,,16,44.16157793998718
+583,0.732421875,0.740234375,,0.01,9,2,8,,800,100,,16,44.34217596054077
+584,0.712890625,0.732421875,,0.01,9,2,9,,800,100,,16,44.19418120384216
+585,0.70703125,0.712890625,,0.01,9,2,10,,800,100,,16,44.67667269706726
+586,0.748046875,0.759765625,,0.01,9,2,11,,800,100,,16,44.262083292007446
+587,0.73046875,0.740234375,,0.01,9,2,12,,800,100,,16,44.484267234802246
+588,0.73828125,0.7421875,,0.01,9,2,13,,800,100,,16,44.186360120773315
+589,0.7578125,0.765625,,0.01,9,2,14,,800,100,,16,44.27262592315674
+590,0.720703125,0.736328125,,0.01,9,2,15,,800,100,,16,44.06158185005188
+591,0.755859375,0.76953125,,0.01,9,2,16,,800,100,,16,44.251933574676514
+592,0.71484375,0.72265625,,0.01,9,2,17,,800,100,,16,44.084906816482544
+593,0.748046875,0.759765625,,0.01,9,2,18,,800,100,,16,44.49787402153015
+594,0.728515625,0.74609375,,0.01,9,2,19,,800,100,,16,44.176618337631226
+595,0.748046875,0.7578125,,0.01,9,2,20,,800,100,,16,44.109020709991455
+596,0.708984375,0.724609375,,0.01,9,2,21,,800,100,,16,44.14593291282654
+597,0.728515625,0.740234375,,0.01,9,2,22,,800,100,,16,44.45158004760742
+598,0.7421875,0.76171875,,0.01,9,2,23,,800,100,,16,44.275917291641235
+599,0.6953125,0.7109375,,0.01,9,2,24,,800,100,,16,44.43396186828613
+600,0.859375,0.875,,0.1,6,2,0,,100,100,,16,3.8150198459625244
+601,0.828125,0.84375,,0.1,6,2,1,,100,100,,16,3.8299918174743652
+602,0.875,0.890625,,0.1,6,2,2,,100,100,,16,3.859992742538452
+603,0.8125,0.828125,,0.1,6,2,3,,100,100,,16,3.8371365070343018
+604,0.78125,0.796875,,0.1,6,2,4,,100,100,,16,3.8150341510772705
+605,0.765625,0.8125,,0.1,6,2,5,,100,100,,16,3.8259942531585693
+606,0.8125,0.78125,,0.1,6,2,6,,100,100,,16,3.9294300079345703
+607,0.796875,0.859375,,0.1,6,2,7,,100,100,,16,3.8281495571136475
+608,0.8125,0.8125,,0.1,6,2,8,,100,100,,16,3.8169851303100586
+609,0.78125,0.84375,,0.1,6,2,9,,100,100,,16,3.857020139694214
+610,0.8125,0.8125,,0.1,6,2,10,,100,100,,16,3.9430017471313477
+611,0.75,0.8125,,0.1,6,2,11,,100,100,,16,3.830998659133911
+612,0.78125,0.8125,,0.1,6,2,12,,100,100,,16,3.870746374130249
+613,0.828125,0.859375,,0.1,6,2,13,,100,100,,16,3.878018856048584
+614,0.765625,0.796875,,0.1,6,2,14,,100,100,,16,3.9710044860839844
+615,0.796875,0.828125,,0.1,6,2,15,,100,100,,16,3.8590056896209717
+616,0.8125,0.8125,,0.1,6,2,16,,100,100,,16,3.876993179321289
+617,0.796875,0.796875,,0.1,6,2,17,,100,100,,16,3.8640217781066895
+618,0.8125,0.84375,,0.1,6,2,18,,100,100,,16,3.989008903503418
+619,0.734375,0.765625,,0.1,6,2,19,,100,100,,16,3.9030206203460693
+620,0.671875,0.71875,,0.1,6,2,20,,100,100,,16,3.854670763015747
+621,0.84375,0.859375,,0.1,6,2,21,,100,100,,16,3.8620049953460693
+622,0.84375,0.875,,0.1,6,2,22,,100,100,,16,3.991006374359131
+623,0.765625,0.78125,,0.1,6,2,23,,100,100,,16,3.855048418045044
+624,0.796875,0.8125,,0.1,6,2,24,,100,100,,16,3.8389992713928223
+625,0.59375,0.6640625,,0.1,7,2,0,,200,100,,16,6.5220091342926025
+626,0.6015625,0.6640625,,0.1,7,2,1,,200,100,,16,6.236683368682861
+627,0.6484375,0.703125,,0.1,7,2,2,,200,100,,16,6.2833945751190186
+628,0.625,0.6484375,,0.1,7,2,3,,200,100,,16,6.4099955558776855
+629,0.5859375,0.6484375,,0.1,7,2,4,,200,100,,16,6.277990341186523
+630,0.6640625,0.671875,,0.1,7,2,5,,200,100,,16,6.228017807006836
+631,0.6875,0.6953125,,0.1,7,2,6,,200,100,,16,6.274628162384033
+632,0.6796875,0.703125,,0.1,7,2,7,,200,100,,16,6.25499415397644
+633,0.6484375,0.6796875,,0.1,7,2,8,,200,100,,16,6.403993844985962
+634,0.71875,0.71875,,0.1,7,2,9,,200,100,,16,6.2530198097229
+635,0.71875,0.703125,,0.1,7,2,10,,200,100,,16,6.2900214195251465
+636,0.6484375,0.6328125,,0.1,7,2,11,,200,100,,16,6.247876167297363
+637,0.6328125,0.65625,,0.1,7,2,12,,200,100,,16,6.2627294063568115
+638,0.65625,0.6875,,0.1,7,2,13,,200,100,,16,6.329012393951416
+639,0.6875,0.6875,,0.1,7,2,14,,200,100,,16,6.277495384216309
+640,0.6171875,0.65625,,0.1,7,2,15,,200,100,,16,6.257116794586182
+641,0.65625,0.6875,,0.1,7,2,16,,200,100,,16,6.3109962940216064
+642,0.609375,0.6640625,,0.1,7,2,17,,200,100,,16,6.230995416641235
+643,0.671875,0.703125,,0.1,7,2,18,,200,100,,16,6.350866794586182
+644,0.671875,0.703125,,0.1,7,2,19,,200,100,,16,6.234344482421875
+645,0.671875,0.6875,,0.1,7,2,20,,200,100,,16,6.312246084213257
+646,0.6875,0.6796875,,0.1,7,2,21,,200,100,,16,6.298058986663818
+647,0.640625,0.6484375,,0.1,7,2,22,,200,100,,16,6.3252198696136475
+648,0.6328125,0.6640625,,0.1,7,2,23,,200,100,,16,6.274015188217163
+649,0.6484375,0.640625,,0.1,7,2,24,,200,100,,16,6.346984386444092
+650,0.62109375,0.60546875,,0.1,8,2,0,,400,100,,16,14.508515357971191
+651,0.55859375,0.5859375,,0.1,8,2,1,,400,100,,16,14.535204410552979
+652,0.59765625,0.59375,,0.1,8,2,2,,400,100,,16,14.42739725112915
+653,0.54296875,0.6015625,,0.1,8,2,3,,400,100,,16,14.507023811340332
+654,0.58203125,0.6015625,,0.1,8,2,4,,400,100,,16,14.447137832641602
+655,0.5703125,0.5859375,,0.1,8,2,5,,400,100,,16,14.521013975143433
+656,0.52734375,0.51953125,,0.1,8,2,6,,400,100,,16,14.449050664901733
+657,0.5703125,0.59765625,,0.1,8,2,7,,400,100,,16,14.527989625930786
+658,0.5859375,0.59765625,,0.1,8,2,8,,400,100,,16,14.60231900215149
+659,0.62890625,0.65625,,0.1,8,2,9,,400,100,,16,14.532920360565186
+660,0.66015625,0.67578125,,0.1,8,2,10,,400,100,,16,14.450204372406006
+661,0.6484375,0.64453125,,0.1,8,2,11,,400,100,,16,14.594343423843384
+662,0.57421875,0.5859375,,0.1,8,2,12,,400,100,,16,14.477160692214966
+663,0.6015625,0.609375,,0.1,8,2,13,,400,100,,16,14.560792922973633
+664,0.55859375,0.5546875,,0.1,8,2,14,,400,100,,16,14.499001741409302
+665,0.5625,0.58203125,,0.1,8,2,15,,400,100,,16,14.552217483520508
+666,0.6328125,0.640625,,0.1,8,2,16,,400,100,,16,14.358989477157593
+667,0.6328125,0.6328125,,0.1,8,2,17,,400,100,,16,14.515904664993286
+668,0.5078125,0.5859375,,0.1,8,2,18,,400,100,,16,14.383125305175781
+669,0.6015625,0.62890625,,0.1,8,2,19,,400,100,,16,14.583372831344604
+670,0.578125,0.57421875,,0.1,8,2,20,,400,100,,16,14.530843734741211
+671,0.546875,0.59375,,0.1,8,2,21,,400,100,,16,14.534005403518677
+672,0.60546875,0.64453125,,0.1,8,2,22,,400,100,,16,14.572360515594482
+673,0.55859375,0.58984375,,0.1,8,2,23,,400,100,,16,14.518568515777588
+674,0.59375,0.6015625,,0.1,8,2,24,,400,100,,16,14.39522409439087
+675,0.564453125,0.578125,,0.1,9,2,0,,800,100,,16,44.41280150413513
+676,0.5703125,0.56640625,,0.1,9,2,1,,800,100,,16,43.99477171897888
+677,0.568359375,0.57421875,,0.1,9,2,2,,800,100,,16,44.59539246559143
+678,0.5546875,0.5625,,0.1,9,2,3,,800,100,,16,44.06127691268921
+679,0.5625,0.56640625,,0.1,9,2,4,,800,100,,16,44.271387815475464
+680,0.52734375,0.537109375,,0.1,9,2,5,,800,100,,16,44.102869749069214
+681,0.572265625,0.5859375,,0.1,9,2,6,,800,100,,16,45.08278441429138
+682,0.568359375,0.57421875,,0.1,9,2,7,,800,100,,16,44.06184148788452
+683,0.505859375,0.5390625,,0.1,9,2,8,,800,100,,16,44.03152251243591
+684,0.55859375,0.5625,,0.1,9,2,9,,800,100,,16,43.92149090766907
+685,0.546875,0.564453125,,0.1,9,2,10,,800,100,,16,44.267632246017456
+686,0.5546875,0.55859375,,0.1,9,2,11,,800,100,,16,44.0746283531189
+687,0.57421875,0.580078125,,0.1,9,2,12,,800,100,,16,44.305808305740356
+688,0.5390625,0.57421875,,0.1,9,2,13,,800,100,,16,43.964868783950806
+689,0.564453125,0.556640625,,0.1,9,2,14,,800,100,,16,44.338072776794434
+690,0.521484375,0.56640625,,0.1,9,2,15,,800,100,,16,44.161217212677
+691,0.537109375,0.572265625,,0.1,9,2,16,,800,100,,16,44.167930126190186
+692,0.546875,0.556640625,,0.1,9,2,17,,800,100,,16,44.166571855545044
+693,0.5546875,0.564453125,,0.1,9,2,18,,800,100,,16,44.04958653450012
+694,0.5546875,0.560546875,,0.1,9,2,19,,800,100,,16,44.01554203033447
+695,0.568359375,0.564453125,,0.1,9,2,20,,800,100,,16,44.26926565170288
+696,0.552734375,0.560546875,,0.1,9,2,21,,800,100,,16,43.90253186225891
+697,0.568359375,0.572265625,,0.1,9,2,22,,800,100,,16,44.39518666267395
+698,0.515625,0.55078125,,0.1,9,2,23,,800,100,,16,44.18519902229309
+699,0.568359375,0.56640625,,0.1,9,2,24,,800,100,,16,44.20054221153259
+700,0.6875,0.703125,,0.2,6,2,0,,100,100,,16,3.8395674228668213
+701,0.65625,0.6875,,0.2,6,2,1,,100,100,,16,3.9199841022491455
+702,0.625,0.625,,0.2,6,2,2,,100,100,,16,3.824993848800659
+703,0.6875,0.75,,0.2,6,2,3,,100,100,,16,3.7907912731170654
+704,0.796875,0.765625,,0.2,6,2,4,,100,100,,16,3.8359930515289307
+705,0.671875,0.765625,,0.2,6,2,5,,100,100,,16,3.9430229663848877
+706,0.703125,0.734375,,0.2,6,2,6,,100,100,,16,3.8180179595947266
+707,0.671875,0.71875,,0.2,6,2,7,,100,100,,16,3.861024856567383
+708,0.625,0.65625,,0.2,6,2,8,,100,100,,16,3.81917142868042
+709,0.671875,0.6875,,0.2,6,2,9,,100,100,,16,3.9140145778656006
+710,0.78125,0.8125,,0.2,6,2,10,,100,100,,16,3.8840231895446777
+711,0.671875,0.703125,,0.2,6,2,11,,100,100,,16,3.8659887313842773
+712,0.6875,0.734375,,0.2,6,2,12,,100,100,,16,3.8229939937591553
+713,0.59375,0.671875,,0.2,6,2,13,,100,100,,16,3.901987075805664
+714,0.65625,0.71875,,0.2,6,2,14,,100,100,,16,3.8390066623687744
+715,0.71875,0.78125,,0.2,6,2,15,,100,100,,16,3.869783401489258
+716,0.65625,0.703125,,0.2,6,2,16,,100,100,,16,3.8439865112304688
+717,0.6875,0.703125,,0.2,6,2,17,,100,100,,16,3.879002809524536
+718,0.5625,0.65625,,0.2,6,2,18,,100,100,,16,3.8470120429992676
+719,0.6875,0.703125,,0.2,6,2,19,,100,100,,16,3.853017807006836
+720,0.71875,0.71875,,0.2,6,2,20,,100,100,,16,3.89402437210083
+721,0.6875,0.671875,,0.2,6,2,21,,100,100,,16,4.028990983963013
+722,0.625,0.640625,,0.2,6,2,22,,100,100,,16,3.8949849605560303
+723,0.609375,0.65625,,0.2,6,2,23,,100,100,,16,4.661566734313965
+724,0.671875,0.671875,,0.2,6,2,24,,100,100,,16,3.777029275894165
+725,0.5859375,0.6015625,,0.2,7,2,0,,200,100,,16,6.3140034675598145
+726,0.5546875,0.5859375,,0.2,7,2,1,,200,100,,16,6.229987144470215
+727,0.5859375,0.6015625,,0.2,7,2,2,,200,100,,16,6.239985942840576
+728,0.6015625,0.625,,0.2,7,2,3,,200,100,,16,6.230192422866821
+729,0.5546875,0.6484375,,0.2,7,2,4,,200,100,,16,6.242025375366211
+730,0.625,0.671875,,0.2,7,2,5,,200,100,,16,6.224990129470825
+731,0.6171875,0.6328125,,0.2,7,2,6,,200,100,,16,6.265967130661011
+732,0.625,0.625,,0.2,7,2,7,,200,100,,16,6.211985349655151
+733,0.625,0.640625,,0.2,7,2,8,,200,100,,16,6.3249828815460205
+734,0.6796875,0.703125,,0.2,7,2,9,,200,100,,16,6.205993175506592
+735,0.578125,0.6171875,,0.2,7,2,10,,200,100,,16,6.244798898696899
+736,0.5859375,0.6640625,,0.2,7,2,11,,200,100,,16,6.21100378036499
+737,0.5546875,0.5703125,,0.2,7,2,12,,200,100,,16,6.248998641967773
+738,0.6484375,0.6640625,,0.2,7,2,13,,200,100,,16,6.331698179244995
+739,0.5546875,0.6015625,,0.2,7,2,14,,200,100,,16,6.243671894073486
+740,0.6171875,0.6015625,,0.2,7,2,15,,200,100,,16,6.233023166656494
+741,0.546875,0.6484375,,0.2,7,2,16,,200,100,,16,6.2890238761901855
+742,0.609375,0.6015625,,0.2,7,2,17,,200,100,,16,6.191995620727539
+743,0.546875,0.6328125,,0.2,7,2,18,,200,100,,16,6.317328453063965
+744,0.59375,0.609375,,0.2,7,2,19,,200,100,,16,6.2685089111328125
+745,0.5390625,0.59375,,0.2,7,2,20,,200,100,,16,6.281007289886475
+746,0.546875,0.578125,,0.2,7,2,21,,200,100,,16,6.229022741317749
+747,0.625,0.6484375,,0.2,7,2,22,,200,100,,16,6.273326873779297
+748,0.546875,0.5859375,,0.2,7,2,23,,200,100,,16,6.376023769378662
+749,0.6171875,0.6328125,,0.2,7,2,24,,200,100,,16,6.298989772796631
+750,0.5703125,0.578125,,0.2,8,2,0,,400,100,,16,14.448146104812622
+751,0.55078125,0.5546875,,0.2,8,2,1,,400,100,,16,14.512645959854126
+752,0.5390625,0.59765625,,0.2,8,2,2,,400,100,,16,14.430007696151733
+753,0.53515625,0.5625,,0.2,8,2,3,,400,100,,16,14.512283563613892
+754,0.6015625,0.6015625,,0.2,8,2,4,,400,100,,16,14.381987571716309
+755,0.484375,0.51953125,,0.2,8,2,5,,400,100,,16,14.517955541610718
+756,0.5390625,0.5625,,0.2,8,2,6,,400,100,,16,14.384761810302734
+757,0.61328125,0.609375,,0.2,8,2,7,,400,100,,16,14.493270635604858
+758,0.546875,0.57421875,,0.2,8,2,8,,400,100,,16,14.387989521026611
+759,0.58203125,0.57421875,,0.2,8,2,9,,400,100,,16,14.589779376983643
+760,0.5234375,0.53515625,,0.2,8,2,10,,400,100,,16,14.382001876831055
+761,0.52734375,0.57421875,,0.2,8,2,11,,400,100,,16,14.482814073562622
+762,0.52734375,0.546875,,0.2,8,2,12,,400,100,,16,14.393264770507812
+763,0.578125,0.57421875,,0.2,8,2,13,,400,100,,16,14.374256134033203
+764,0.5390625,0.5703125,,0.2,8,2,14,,400,100,,16,14.355032682418823
+765,0.58984375,0.59765625,,0.2,8,2,15,,400,100,,16,14.442118406295776
+766,0.546875,0.55859375,,0.2,8,2,16,,400,100,,16,14.366000890731812
+767,0.5625,0.5703125,,0.2,8,2,17,,400,100,,16,14.474656343460083
+768,0.609375,0.6015625,,0.2,8,2,18,,400,100,,16,14.343986749649048
+769,0.5234375,0.5390625,,0.2,8,2,19,,400,100,,16,14.54587435722351
+770,0.52734375,0.52734375,,0.2,8,2,20,,400,100,,16,14.438976049423218
+771,0.578125,0.58984375,,0.2,8,2,21,,400,100,,16,14.54979133605957
+772,0.60546875,0.61328125,,0.2,8,2,22,,400,100,,16,14.39299988746643
+773,0.59765625,0.6171875,,0.2,8,2,23,,400,100,,16,14.443698167800903
+774,0.5234375,0.55859375,,0.2,8,2,24,,400,100,,16,14.361044883728027
+775,0.5546875,0.552734375,,0.2,9,2,0,,800,100,,16,44.333080768585205
+776,0.5625,0.5625,,0.2,9,2,1,,800,100,,16,44.10083889961243
+777,0.5078125,0.515625,,0.2,9,2,2,,800,100,,16,44.43175959587097
+778,0.53515625,0.544921875,,0.2,9,2,3,,800,100,,16,44.09408926963806
+779,0.5390625,0.53515625,,0.2,9,2,4,,800,100,,16,44.05863332748413
+780,0.533203125,0.53125,,0.2,9,2,5,,800,100,,16,43.88783359527588
+781,0.5234375,0.541015625,,0.2,9,2,6,,800,100,,16,44.24381875991821
+782,0.5390625,0.541015625,,0.2,9,2,7,,800,100,,16,43.64183712005615
+783,0.552734375,0.546875,,0.2,9,2,8,,800,100,,16,43.953054666519165
+784,0.5703125,0.572265625,,0.2,9,2,9,,800,100,,16,43.985490798950195
+785,0.541015625,0.5390625,,0.2,9,2,10,,800,100,,16,44.23357605934143
+786,0.515625,0.521484375,,0.2,9,2,11,,800,100,,16,43.99697828292847
+787,0.5234375,0.552734375,,0.2,9,2,12,,800,100,,16,44.07939291000366
+788,0.52734375,0.52734375,,0.2,9,2,13,,800,100,,16,43.98955750465393
+789,0.556640625,0.55859375,,0.2,9,2,14,,800,100,,16,44.03802156448364
+790,0.560546875,0.546875,,0.2,9,2,15,,800,100,,16,43.95863628387451
+791,0.5625,0.5703125,,0.2,9,2,16,,800,100,,16,44.11037349700928
+792,0.54296875,0.5390625,,0.2,9,2,17,,800,100,,16,44.05990719795227
+793,0.498046875,0.501953125,,0.2,9,2,18,,800,100,,16,44.130207538604736
+794,0.529296875,0.52734375,,0.2,9,2,19,,800,100,,16,44.121161699295044
+795,0.5234375,0.525390625,,0.2,9,2,20,,800,100,,16,44.09450054168701
+796,0.525390625,0.533203125,,0.2,9,2,21,,800,100,,16,43.877084255218506
+797,0.53125,0.52734375,,0.2,9,2,22,,800,100,,16,43.944350719451904
+798,0.537109375,0.564453125,,0.2,9,2,23,,800,100,,16,43.94460415840149
+799,0.498046875,0.501953125,,0.2,9,2,24,,800,100,,16,44.06094145774841
+800,1.0,1.0,,0.0,6,5,0,,100,100,,16,3.789987325668335
+801,1.0,1.0,,0.0,6,5,1,,100,100,,16,3.7919914722442627
+802,1.0,1.0,,0.0,6,5,2,,100,100,,16,3.8939850330352783
+803,1.0,1.0,,0.0,6,5,3,,100,100,,16,3.8252718448638916
+804,1.0,1.0,,0.0,6,5,4,,100,100,,16,3.776149272918701
+805,1.0,1.0,,0.0,6,5,5,,100,100,,16,3.799199104309082
+806,1.0,1.0,,0.0,6,5,6,,100,100,,16,3.8709876537323
+807,1.0,1.0,,0.0,6,5,7,,100,100,,16,3.8139896392822266
+808,1.0,1.0,,0.0,6,5,8,,100,100,,16,3.7819838523864746
+809,1.0,1.0,,0.0,6,5,9,,100,100,,16,3.8089919090270996
+810,1.0,1.0,,0.0,6,5,10,,100,100,,16,3.852987766265869
+811,1.0,1.0,,0.0,6,5,11,,100,100,,16,3.835988759994507
+812,1.0,1.0,,0.0,6,5,12,,100,100,,16,3.8909852504730225
+813,1.0,1.0,,0.0,6,5,13,,100,100,,16,3.8381667137145996
+814,1.0,1.0,,0.0,6,5,14,,100,100,,16,3.806983232498169
+815,1.0,1.0,,0.0,6,5,15,,100,100,,16,3.8329837322235107
+816,1.0,1.0,,0.0,6,5,16,,100,100,,16,3.8089864253997803
+817,1.0,1.0,,0.0,6,5,17,,100,100,,16,3.8146414756774902
+818,1.0,1.0,,0.0,6,5,18,,100,100,,16,3.8079874515533447
+819,1.0,1.0,,0.0,6,5,19,,100,100,,16,3.862455368041992
+820,1.0,1.0,,0.0,6,5,20,,100,100,,16,3.806871175765991
+821,1.0,1.0,,0.0,6,5,21,,100,100,,16,3.8320202827453613
+822,1.0,1.0,,0.0,6,5,22,,100,100,,16,3.8339884281158447
+823,1.0,1.0,,0.0,6,5,23,,100,100,,16,3.8920304775238037
+824,1.0,1.0,,0.0,6,5,24,,100,100,,16,3.8079981803894043
+825,0.9921875,0.9921875,,0.0,7,5,0,,200,100,,16,6.280022621154785
+826,0.9921875,0.9921875,,0.0,7,5,1,,200,100,,16,6.411023855209351
+827,1.0,1.0,,0.0,7,5,2,,200,100,,16,6.2755444049835205
+828,0.984375,0.984375,,0.0,7,5,3,,200,100,,16,6.259009599685669
+829,0.9921875,0.9921875,,0.0,7,5,4,,200,100,,16,6.278010606765747
+830,0.9921875,0.9921875,,0.0,7,5,5,,200,100,,16,6.260984659194946
+831,0.9765625,0.984375,,0.0,7,5,6,,200,100,,16,6.350430727005005
+832,0.984375,0.984375,,0.0,7,5,7,,200,100,,16,6.236035346984863
+833,0.9765625,0.9765625,,0.0,7,5,8,,200,100,,16,6.3340163230896
+834,0.9921875,1.0,,0.0,7,5,9,,200,100,,16,6.2990217208862305
+835,1.0,1.0,,0.0,7,5,10,,200,100,,16,6.276995897293091
+836,0.9921875,0.9921875,,0.0,7,5,11,,200,100,,16,6.432694911956787
+837,0.9921875,0.9921875,,0.0,7,5,12,,200,100,,16,6.318977117538452
+838,0.9921875,0.9921875,,0.0,7,5,13,,200,100,,16,6.251004219055176
+839,0.9765625,0.9765625,,0.0,7,5,14,,200,100,,16,6.2900331020355225
+840,0.9921875,0.9921875,,0.0,7,5,15,,200,100,,16,6.246014595031738
+841,0.984375,0.9921875,,0.0,7,5,16,,200,100,,16,6.382859468460083
+842,1.0,1.0,,0.0,7,5,17,,200,100,,16,6.266013860702515
+843,0.984375,0.984375,,0.0,7,5,18,,200,100,,16,6.325846910476685
+844,0.9921875,0.9921875,,0.0,7,5,19,,200,100,,16,6.302018404006958
+845,0.984375,0.9921875,,0.0,7,5,20,,200,100,,16,6.341989517211914
+846,1.0,1.0,,0.0,7,5,21,,200,100,,16,6.34002423286438
+847,0.984375,0.984375,,0.0,7,5,22,,200,100,,16,6.289998292922974
+848,1.0,1.0,,0.0,7,5,23,,200,100,,16,6.26602578163147
+849,0.9921875,0.9921875,,0.0,7,5,24,,200,100,,16,6.32699728012085
+850,0.9140625,0.9140625,,0.0,8,5,0,,400,100,,16,14.617721319198608
+851,0.9453125,0.9453125,,0.0,8,5,1,,400,100,,16,14.592174291610718
+852,0.94140625,0.94140625,,0.0,8,5,2,,400,100,,16,14.564698696136475
+853,0.9609375,0.9609375,,0.0,8,5,3,,400,100,,16,14.614036798477173
+854,0.9375,0.9375,,0.0,8,5,4,,400,100,,16,14.54711103439331
+855,0.93359375,0.93359375,,0.0,8,5,5,,400,100,,16,14.597832918167114
+856,0.921875,0.92578125,,0.0,8,5,6,,400,100,,16,14.58928370475769
+857,0.9296875,0.93359375,,0.0,8,5,7,,400,100,,16,14.678661823272705
+858,0.921875,0.921875,,0.0,8,5,8,,400,100,,16,14.472352981567383
+859,0.921875,0.921875,,0.0,8,5,9,,400,100,,16,14.577255487442017
+860,0.92578125,0.9296875,,0.0,8,5,10,,400,100,,16,14.542091131210327
+861,0.953125,0.953125,,0.0,8,5,11,,400,100,,16,14.549030542373657
+862,0.9296875,0.93359375,,0.0,8,5,12,,400,100,,16,14.462903261184692
+863,0.9296875,0.93359375,,0.0,8,5,13,,400,100,,16,14.556849241256714
+864,0.94140625,0.94140625,,0.0,8,5,14,,400,100,,16,14.52259612083435
+865,0.93359375,0.9375,,0.0,8,5,15,,400,100,,16,14.59022569656372
+866,0.953125,0.95703125,,0.0,8,5,16,,400,100,,16,14.472075462341309
+867,0.94140625,0.94140625,,0.0,8,5,17,,400,100,,16,14.595473766326904
+868,0.92578125,0.92578125,,0.0,8,5,18,,400,100,,16,14.601065158843994
+869,0.9375,0.9375,,0.0,8,5,19,,400,100,,16,14.651004791259766
+870,0.93359375,0.93359375,,0.0,8,5,20,,400,100,,16,14.457161664962769
+871,0.93359375,0.93359375,,0.0,8,5,21,,400,100,,16,14.599626779556274
+872,0.921875,0.921875,,0.0,8,5,22,,400,100,,16,14.504337072372437
+873,0.9375,0.9375,,0.0,8,5,23,,400,100,,16,14.601042985916138
+874,0.9296875,0.9296875,,0.0,8,5,24,,400,100,,16,14.4298255443573
+875,0.8671875,0.869140625,,0.0,9,5,0,,800,100,,16,44.68339991569519
+876,0.875,0.875,,0.0,9,5,1,,800,100,,16,44.45999884605408
+877,0.869140625,0.869140625,,0.0,9,5,2,,800,100,,16,44.80538558959961
+878,0.861328125,0.861328125,,0.0,9,5,3,,800,100,,16,44.23840641975403
+879,0.869140625,0.869140625,,0.0,9,5,4,,800,100,,16,44.52592325210571
+880,0.853515625,0.853515625,,0.0,9,5,5,,800,100,,16,44.25752067565918
+881,0.859375,0.859375,,0.0,9,5,6,,800,100,,16,44.650304317474365
+882,0.861328125,0.861328125,,0.0,9,5,7,,800,100,,16,44.388622999191284
+883,0.8828125,0.8828125,,0.0,9,5,8,,800,100,,16,44.37554883956909
+884,0.865234375,0.865234375,,0.0,9,5,9,,800,100,,16,44.22521424293518
+885,0.857421875,0.857421875,,0.0,9,5,10,,800,100,,16,44.48507785797119
+886,0.875,0.875,,0.0,9,5,11,,800,100,,16,44.28190755844116
+887,0.865234375,0.8671875,,0.0,9,5,12,,800,100,,16,44.44366788864136
+888,0.859375,0.859375,,0.0,9,5,13,,800,100,,16,44.13088536262512
+889,0.87109375,0.873046875,,0.0,9,5,14,,800,100,,16,45.199907541275024
+890,0.87890625,0.87890625,,0.0,9,5,15,,800,100,,16,44.19539403915405
+891,0.859375,0.859375,,0.0,9,5,16,,800,100,,16,44.444387435913086
+892,0.853515625,0.853515625,,0.0,9,5,17,,800,100,,16,44.17811846733093
+893,0.849609375,0.849609375,,0.0,9,5,18,,800,100,,16,44.43070149421692
+894,0.884765625,0.884765625,,0.0,9,5,19,,800,100,,16,44.155701875686646
+895,0.875,0.876953125,,0.0,9,5,20,,800,100,,16,44.38663172721863
+896,0.859375,0.859375,,0.0,9,5,21,,800,100,,16,44.17919921875
+897,0.876953125,0.876953125,,0.0,9,5,22,,800,100,,16,44.575475215911865
+898,0.8984375,0.8984375,,0.0,9,5,23,,800,100,,16,44.24245882034302
+899,0.87890625,0.880859375,,0.0,9,5,24,,800,100,,16,44.18614625930786
+900,1.0,1.0,,0.01,6,5,0,,100,100,,16,3.8529844284057617
+901,1.0,1.0,,0.01,6,5,1,,100,100,,16,3.8352043628692627
+902,1.0,1.0,,0.01,6,5,2,,100,100,,16,3.804008960723877
+903,1.0,1.0,,0.01,6,5,3,,100,100,,16,3.8126182556152344
+904,1.0,1.0,,0.01,6,5,4,,100,100,,16,3.8530311584472656
+905,1.0,1.0,,0.01,6,5,5,,100,100,,16,3.8590023517608643
+906,1.0,1.0,,0.01,6,5,6,,100,100,,16,3.7960081100463867
+907,1.0,1.0,,0.01,6,5,7,,100,100,,16,3.8191909790039062
+908,1.0,1.0,,0.01,6,5,8,,100,100,,16,3.844987154006958
+909,1.0,1.0,,0.01,6,5,9,,100,100,,16,3.8430330753326416
+910,1.0,1.0,,0.01,6,5,10,,100,100,,16,3.821990966796875
+911,1.0,1.0,,0.01,6,5,11,,100,100,,16,3.847184896469116
+912,1.0,1.0,,0.01,6,5,12,,100,100,,16,3.8360071182250977
+913,1.0,1.0,,0.01,6,5,13,,100,100,,16,3.8980209827423096
+914,1.0,1.0,,0.01,6,5,14,,100,100,,16,3.9034807682037354
+915,1.0,1.0,,0.01,6,5,15,,100,100,,16,3.8172109127044678
+916,1.0,1.0,,0.01,6,5,16,,100,100,,16,3.906031370162964
+917,1.0,1.0,,0.01,6,5,17,,100,100,,16,3.8440210819244385
+918,1.0,1.0,,0.01,6,5,18,,100,100,,16,3.8059957027435303
+919,1.0,1.0,,0.01,6,5,19,,100,100,,16,3.820016622543335
+920,1.0,1.0,,0.01,6,5,20,,100,100,,16,3.8670246601104736
+921,1.0,1.0,,0.01,6,5,21,,100,100,,16,3.880023956298828
+922,1.0,1.0,,0.01,6,5,22,,100,100,,16,3.8289148807525635
+923,1.0,1.0,,0.01,6,5,23,,100,100,,16,3.8179965019226074
+924,1.0,1.0,,0.01,6,5,24,,100,100,,16,3.8499867916107178
+925,0.9921875,0.9921875,,0.01,7,5,0,,200,100,,16,6.4030210971832275
+926,0.953125,0.9609375,,0.01,7,5,1,,200,100,,16,6.262004852294922
+927,0.9453125,0.9609375,,0.01,7,5,2,,200,100,,16,6.299831867218018
+928,0.953125,0.9609375,,0.01,7,5,3,,200,100,,16,6.264816045761108
+929,0.9453125,0.953125,,0.01,7,5,4,,200,100,,16,6.357999801635742
+930,0.953125,0.96875,,0.01,7,5,5,,200,100,,16,6.350200414657593
+931,0.9609375,0.96875,,0.01,7,5,6,,200,100,,16,6.2731099128723145
+932,0.9609375,0.96875,,0.01,7,5,7,,200,100,,16,6.266021251678467
+933,1.0,1.0,,0.01,7,5,8,,200,100,,16,6.3296191692352295
+934,0.9765625,0.984375,,0.01,7,5,9,,200,100,,16,6.30699610710144
+935,0.953125,0.9609375,,0.01,7,5,10,,200,100,,16,6.35699987411499
+936,0.96875,0.9765625,,0.01,7,5,11,,200,100,,16,6.248998641967773
+937,0.96875,0.984375,,0.01,7,5,12,,200,100,,16,6.359630346298218
+938,0.9765625,0.984375,,0.01,7,5,13,,200,100,,16,6.284985065460205
+939,0.9609375,0.9609375,,0.01,7,5,14,,200,100,,16,6.3059868812561035
+940,0.9765625,0.984375,,0.01,7,5,15,,200,100,,16,6.364013433456421
+941,0.953125,0.9609375,,0.01,7,5,16,,200,100,,16,6.3240203857421875
+942,0.953125,0.9609375,,0.01,7,5,17,,200,100,,16,6.278294563293457
+943,0.9609375,0.9609375,,0.01,7,5,18,,200,100,,16,6.314749479293823
+944,0.9609375,0.9765625,,0.01,7,5,19,,200,100,,16,6.248019456863403
+945,0.96875,0.9765625,,0.01,7,5,20,,200,100,,16,6.421018362045288
+946,0.953125,0.96875,,0.01,7,5,21,,200,100,,16,6.317000150680542
+947,0.953125,0.9609375,,0.01,7,5,22,,200,100,,16,6.338559150695801
+948,0.953125,0.953125,,0.01,7,5,23,,200,100,,16,6.31201958656311
+949,0.96875,0.9765625,,0.01,7,5,24,,200,100,,16,6.30802059173584
+950,0.85546875,0.8671875,,0.01,8,5,0,,400,100,,16,14.658541917800903
+951,0.87109375,0.8828125,,0.01,8,5,1,,400,100,,16,14.772740840911865
+952,0.86328125,0.875,,0.01,8,5,2,,400,100,,16,14.493250370025635
+953,0.875,0.875,,0.01,8,5,3,,400,100,,16,14.641407251358032
+954,0.890625,0.890625,,0.01,8,5,4,,400,100,,16,14.500553369522095
+955,0.84375,0.85546875,,0.01,8,5,5,,400,100,,16,14.56726861000061
+956,0.859375,0.87890625,,0.01,8,5,6,,400,100,,16,14.510990381240845
+957,0.890625,0.89453125,,0.01,8,5,7,,400,100,,16,14.662296533584595
+958,0.85546875,0.8671875,,0.01,8,5,8,,400,100,,16,14.534826040267944
+959,0.90234375,0.90625,,0.01,8,5,9,,400,100,,16,14.583536863327026
+960,0.86328125,0.87109375,,0.01,8,5,10,,400,100,,16,14.533594131469727
+961,0.8671875,0.875,,0.01,8,5,11,,400,100,,16,14.642128229141235
+962,0.8828125,0.890625,,0.01,8,5,12,,400,100,,16,14.552406072616577
+963,0.875,0.88671875,,0.01,8,5,13,,400,100,,16,14.683947324752808
+964,0.87109375,0.8828125,,0.01,8,5,14,,400,100,,16,14.477021932601929
+965,0.87109375,0.87890625,,0.01,8,5,15,,400,100,,16,14.556147336959839
+966,0.8515625,0.859375,,0.01,8,5,16,,400,100,,16,14.394019603729248
+967,0.859375,0.87109375,,0.01,8,5,17,,400,100,,16,14.544320821762085
+968,0.84765625,0.859375,,0.01,8,5,18,,400,100,,16,14.449026107788086
+969,0.89453125,0.90625,,0.01,8,5,19,,400,100,,16,14.596232175827026
+970,0.890625,0.890625,,0.01,8,5,20,,400,100,,16,14.523020505905151
+971,0.890625,0.8984375,,0.01,8,5,21,,400,100,,16,14.561481952667236
+972,0.84765625,0.85546875,,0.01,8,5,22,,400,100,,16,14.401012897491455
+973,0.87890625,0.88671875,,0.01,8,5,23,,400,100,,16,14.564609050750732
+974,0.8671875,0.87890625,,0.01,8,5,24,,400,100,,16,14.521994352340698
+975,0.763671875,0.771484375,,0.01,9,5,0,,800,100,,16,44.55252003669739
+976,0.77734375,0.787109375,,0.01,9,5,1,,800,100,,16,44.3550705909729
+977,0.77734375,0.7890625,,0.01,9,5,2,,800,100,,16,44.4915189743042
+978,0.783203125,0.791015625,,0.01,9,5,3,,800,100,,16,44.03886437416077
+979,0.759765625,0.77734375,,0.01,9,5,4,,800,100,,16,44.410083055496216
+980,0.765625,0.7734375,,0.01,9,5,5,,800,100,,16,44.05298185348511
+981,0.76953125,0.77734375,,0.01,9,5,6,,800,100,,16,44.470505237579346
+982,0.77734375,0.787109375,,0.01,9,5,7,,800,100,,16,44.15282082557678
+983,0.751953125,0.765625,,0.01,9,5,8,,800,100,,16,44.15975642204285
+984,0.765625,0.771484375,,0.01,9,5,9,,800,100,,16,43.95405459403992
+985,0.77734375,0.78515625,,0.01,9,5,10,,800,100,,16,44.52341151237488
+986,0.76171875,0.76953125,,0.01,9,5,11,,800,100,,16,44.08833026885986
+987,0.73828125,0.751953125,,0.01,9,5,12,,800,100,,16,44.00705003738403
+988,0.755859375,0.765625,,0.01,9,5,13,,800,100,,16,44.15873432159424
+989,0.744140625,0.75,,0.01,9,5,14,,800,100,,16,44.317052125930786
+990,0.783203125,0.79296875,,0.01,9,5,15,,800,100,,16,44.16995096206665
+991,0.76953125,0.779296875,,0.01,9,5,16,,800,100,,16,44.40223240852356
+992,0.765625,0.775390625,,0.01,9,5,17,,800,100,,16,44.18921685218811
+993,0.765625,0.7734375,,0.01,9,5,18,,800,100,,16,44.52621817588806
+994,0.763671875,0.7734375,,0.01,9,5,19,,800,100,,16,44.16518259048462
+995,0.7734375,0.78515625,,0.01,9,5,20,,800,100,,16,44.30681777000427
+996,0.76953125,0.7734375,,0.01,9,5,21,,800,100,,16,44.13783502578735
+997,0.763671875,0.7734375,,0.01,9,5,22,,800,100,,16,44.28433585166931
+998,0.78125,0.787109375,,0.01,9,5,23,,800,100,,16,43.953712701797485
+999,0.755859375,0.765625,,0.01,9,5,24,,800,100,,16,44.20329737663269
+1000,0.84375,0.859375,,0.1,6,5,0,,100,100,,16,3.763000249862671
+1001,0.71875,0.796875,,0.1,6,5,1,,100,100,,16,3.754009962081909
+1002,0.875,0.890625,,0.1,6,5,2,,100,100,,16,3.7915823459625244
+1003,0.890625,0.890625,,0.1,6,5,3,,100,100,,16,3.834996223449707
+1004,0.796875,0.84375,,0.1,6,5,4,,100,100,,16,3.8010218143463135
+1005,0.8125,0.84375,,0.1,6,5,5,,100,100,,16,3.825871229171753
+1006,0.828125,0.875,,0.1,6,5,6,,100,100,,16,3.8740146160125732
+1007,0.921875,0.9375,,0.1,6,5,7,,100,100,,16,3.8419811725616455
+1008,0.90625,0.9375,,0.1,6,5,8,,100,100,,16,3.8140125274658203
+1009,0.796875,0.890625,,0.1,6,5,9,,100,100,,16,3.8130221366882324
+1010,0.890625,0.890625,,0.1,6,5,10,,100,100,,16,3.788193702697754
+1011,0.90625,0.953125,,0.1,6,5,11,,100,100,,16,3.8049914836883545
+1012,0.921875,0.9375,,0.1,6,5,12,,100,100,,16,3.8240268230438232
+1013,0.84375,0.875,,0.1,6,5,13,,100,100,,16,3.8190131187438965
+1014,0.859375,0.890625,,0.1,6,5,14,,100,100,,16,3.8009984493255615
+1015,0.90625,0.90625,,0.1,6,5,15,,100,100,,16,3.8440115451812744
+1016,0.859375,0.90625,,0.1,6,5,16,,100,100,,16,3.877004384994507
+1017,0.9375,0.9375,,0.1,6,5,17,,100,100,,16,3.8428001403808594
+1018,0.859375,0.90625,,0.1,6,5,18,,100,100,,16,3.821014404296875
+1019,0.90625,0.921875,,0.1,6,5,19,,100,100,,16,3.8349924087524414
+1020,0.796875,0.8125,,0.1,6,5,20,,100,100,,16,3.910033702850342
+1021,0.8125,0.84375,,0.1,6,5,21,,100,100,,16,3.819000482559204
+1022,0.9375,0.96875,,0.1,6,5,22,,100,100,,16,3.862992525100708
+1023,0.78125,0.84375,,0.1,6,5,23,,100,100,,16,3.8150010108947754
+1024,0.890625,0.921875,,0.1,6,5,24,,100,100,,16,3.9290049076080322
+1025,0.7578125,0.7734375,,0.1,7,5,0,,200,100,,16,6.295386791229248
+1026,0.6796875,0.71875,,0.1,7,5,1,,200,100,,16,6.184998273849487
+1027,0.703125,0.7265625,,0.1,7,5,2,,200,100,,16,6.284837007522583
+1028,0.78125,0.8046875,,0.1,7,5,3,,200,100,,16,6.214033365249634
+1029,0.734375,0.7890625,,0.1,7,5,4,,200,100,,16,6.255016088485718
+1030,0.7578125,0.796875,,0.1,7,5,5,,200,100,,16,6.2202088832855225
+1031,0.7578125,0.78125,,0.1,7,5,6,,200,100,,16,6.256824016571045
+1032,0.7734375,0.765625,,0.1,7,5,7,,200,100,,16,6.340025186538696
+1033,0.71875,0.7578125,,0.1,7,5,8,,200,100,,16,6.251997470855713
+1034,0.6796875,0.703125,,0.1,7,5,9,,200,100,,16,6.234722137451172
+1035,0.6953125,0.6875,,0.1,7,5,10,,200,100,,16,6.226470232009888
+1036,0.6953125,0.734375,,0.1,7,5,11,,200,100,,16,6.197990417480469
+1037,0.6796875,0.71875,,0.1,7,5,12,,200,100,,16,6.345021963119507
+1038,0.6875,0.7109375,,0.1,7,5,13,,200,100,,16,6.225987672805786
+1039,0.75,0.75,,0.1,7,5,14,,200,100,,16,6.2917492389678955
+1040,0.6953125,0.734375,,0.1,7,5,15,,200,100,,16,6.237006425857544
+1041,0.703125,0.734375,,0.1,7,5,16,,200,100,,16,6.273021936416626
+1042,0.6953125,0.703125,,0.1,7,5,17,,200,100,,16,6.327019929885864
+1043,0.765625,0.7734375,,0.1,7,5,18,,200,100,,16,6.22699236869812
+1044,0.7109375,0.7734375,,0.1,7,5,19,,200,100,,16,6.211730003356934
+1045,0.7265625,0.75,,0.1,7,5,20,,200,100,,16,6.258015394210815
+1046,0.671875,0.6953125,,0.1,7,5,21,,200,100,,16,6.227997064590454
+1047,0.6953125,0.7265625,,0.1,7,5,22,,200,100,,16,6.400011301040649
+1048,0.7265625,0.7421875,,0.1,7,5,23,,200,100,,16,6.2110207080841064
+1049,0.6796875,0.703125,,0.1,7,5,24,,200,100,,16,6.356062412261963
+1050,0.58984375,0.609375,,0.1,8,5,0,,400,100,,16,14.433605194091797
+1051,0.62109375,0.640625,,0.1,8,5,1,,400,100,,16,14.563206672668457
+1052,0.61328125,0.62109375,,0.1,8,5,2,,400,100,,16,14.480992078781128
+1053,0.6875,0.703125,,0.1,8,5,3,,400,100,,16,14.546164751052856
+1054,0.609375,0.625,,0.1,8,5,4,,400,100,,16,14.376001358032227
+1055,0.60546875,0.6328125,,0.1,8,5,5,,400,100,,16,14.543479919433594
+1056,0.6640625,0.6875,,0.1,8,5,6,,400,100,,16,14.386020421981812
+1057,0.62109375,0.64453125,,0.1,8,5,7,,400,100,,16,14.457691431045532
+1058,0.625,0.62890625,,0.1,8,5,8,,400,100,,16,14.414120197296143
+1059,0.59375,0.60546875,,0.1,8,5,9,,400,100,,16,14.539076328277588
+1060,0.64453125,0.66796875,,0.1,8,5,10,,400,100,,16,14.424856662750244
+1061,0.625,0.625,,0.1,8,5,11,,400,100,,16,14.442557573318481
+1062,0.64453125,0.67578125,,0.1,8,5,12,,400,100,,16,14.3710196018219
+1063,0.68359375,0.6953125,,0.1,8,5,13,,400,100,,16,14.56452989578247
+1064,0.59765625,0.6171875,,0.1,8,5,14,,400,100,,16,14.421571016311646
+1065,0.68359375,0.69921875,,0.1,8,5,15,,400,100,,16,14.436941385269165
+1066,0.65234375,0.6640625,,0.1,8,5,16,,400,100,,16,14.342663764953613
+1067,0.6796875,0.68359375,,0.1,8,5,17,,400,100,,16,14.386596441268921
+1068,0.6328125,0.640625,,0.1,8,5,18,,400,100,,16,14.304699897766113
+1069,0.65234375,0.6640625,,0.1,8,5,19,,400,100,,16,14.416999340057373
+1070,0.60546875,0.609375,,0.1,8,5,20,,400,100,,16,14.342690467834473
+1071,0.59375,0.609375,,0.1,8,5,21,,400,100,,16,14.41474723815918
+1072,0.625,0.62890625,,0.1,8,5,22,,400,100,,16,14.376125812530518
+1073,0.5625,0.59765625,,0.1,8,5,23,,400,100,,16,14.540270328521729
+1074,0.640625,0.65234375,,0.1,8,5,24,,400,100,,16,14.444059133529663
+1075,0.59375,0.611328125,,0.1,9,5,0,,800,100,,16,44.23557257652283
+1076,0.5703125,0.5859375,,0.1,9,5,1,,800,100,,16,44.01528525352478
+1077,0.576171875,0.595703125,,0.1,9,5,2,,800,100,,16,44.0730082988739
+1078,0.611328125,0.625,,0.1,9,5,3,,800,100,,16,43.64253520965576
+1079,0.57421875,0.5859375,,0.1,9,5,4,,800,100,,16,44.12713861465454
+1080,0.5625,0.572265625,,0.1,9,5,5,,800,100,,16,44.08005976676941
+1081,0.5859375,0.609375,,0.1,9,5,6,,800,100,,16,44.138230085372925
+1082,0.5703125,0.55859375,,0.1,9,5,7,,800,100,,16,43.99911308288574
+1083,0.599609375,0.611328125,,0.1,9,5,8,,800,100,,16,44.22360181808472
+1084,0.5703125,0.58203125,,0.1,9,5,9,,800,100,,16,43.75979542732239
+1085,0.552734375,0.587890625,,0.1,9,5,10,,800,100,,16,44.141148805618286
+1086,0.572265625,0.580078125,,0.1,9,5,11,,800,100,,16,43.71725249290466
+1087,0.591796875,0.587890625,,0.1,9,5,12,,800,100,,16,44.1769232749939
+1088,0.564453125,0.578125,,0.1,9,5,13,,800,100,,16,43.89895749092102
+1089,0.572265625,0.572265625,,0.1,9,5,14,,800,100,,16,44.2015917301178
+1090,0.546875,0.556640625,,0.1,9,5,15,,800,100,,16,43.81664156913757
+1091,0.5390625,0.5546875,,0.1,9,5,16,,800,100,,16,44.168803691864014
+1092,0.587890625,0.591796875,,0.1,9,5,17,,800,100,,16,43.78395915031433
+1093,0.552734375,0.556640625,,0.1,9,5,18,,800,100,,16,43.90673041343689
+1094,0.580078125,0.578125,,0.1,9,5,19,,800,100,,16,43.6360023021698
+1095,0.52734375,0.529296875,,0.1,9,5,20,,800,100,,16,44.13234090805054
+1096,0.560546875,0.5546875,,0.1,9,5,21,,800,100,,16,43.845083475112915
+1097,0.6015625,0.603515625,,0.1,9,5,22,,800,100,,16,44.10506272315979
+1098,0.56640625,0.58203125,,0.1,9,5,23,,800,100,,16,43.74241852760315
+1099,0.578125,0.583984375,,0.1,9,5,24,,800,100,,16,44.13155961036682
+1100,0.71875,0.78125,,0.2,6,5,0,,100,100,,16,3.78716778755188
+1101,0.765625,0.78125,,0.2,6,5,1,,100,100,,16,3.912994623184204
+1102,0.734375,0.78125,,0.2,6,5,2,,100,100,,16,3.7730181217193604
+1103,0.75,0.8125,,0.2,6,5,3,,100,100,,16,3.785515785217285
+1104,0.75,0.765625,,0.2,6,5,4,,100,100,,16,3.767017364501953
+1105,0.796875,0.796875,,0.2,6,5,5,,100,100,,16,3.9060113430023193
+1106,0.71875,0.75,,0.2,6,5,6,,100,100,,16,3.7940127849578857
+1107,0.734375,0.796875,,0.2,6,5,7,,100,100,,16,3.804002046585083
+1108,0.734375,0.78125,,0.2,6,5,8,,100,100,,16,4.384484052658081
+1109,0.765625,0.828125,,0.2,6,5,9,,100,100,,16,3.9239847660064697
+1110,0.765625,0.765625,,0.2,6,5,10,,100,100,,16,3.7929978370666504
+1111,0.75,0.796875,,0.2,6,5,11,,100,100,,16,3.791262626647949
+1112,0.8125,0.859375,,0.2,6,5,12,,100,100,,16,3.814990282058716
+1113,0.71875,0.734375,,0.2,6,5,13,,100,100,,16,3.89198899269104
+1114,0.90625,0.890625,,0.2,6,5,14,,100,100,,16,3.9011616706848145
+1115,0.8125,0.828125,,0.2,6,5,15,,100,100,,16,3.7969789505004883
+1116,0.671875,0.734375,,0.2,6,5,16,,100,100,,16,3.806180477142334
+1117,0.6875,0.734375,,0.2,6,5,17,,100,100,,16,3.8919920921325684
+1118,0.78125,0.796875,,0.2,6,5,18,,100,100,,16,3.8329880237579346
+1119,0.8125,0.84375,,0.2,6,5,19,,100,100,,16,3.8559861183166504
+1120,0.765625,0.765625,,0.2,6,5,20,,100,100,,16,3.804988384246826
+1121,0.6875,0.734375,,0.2,6,5,21,,100,100,,16,3.8369812965393066
+1122,0.75,0.8125,,0.2,6,5,22,,100,100,,16,3.8570539951324463
+1123,0.84375,0.875,,0.2,6,5,23,,100,100,,16,3.8104212284088135
+1124,0.75,0.796875,,0.2,6,5,24,,100,100,,16,3.7909975051879883
+1125,0.6484375,0.6796875,,0.2,7,5,0,,200,100,,16,6.2609992027282715
+1126,0.6484375,0.671875,,0.2,7,5,1,,200,100,,16,6.1869916915893555
+1127,0.609375,0.671875,,0.2,7,5,2,,200,100,,16,6.248013257980347
+1128,0.5625,0.6171875,,0.2,7,5,3,,200,100,,16,6.270663738250732
+1129,0.6171875,0.671875,,0.2,7,5,4,,200,100,,16,6.220988035202026
+1130,0.6171875,0.6640625,,0.2,7,5,5,,200,100,,16,6.184993505477905
+1131,0.6875,0.6953125,,0.2,7,5,6,,200,100,,16,6.2169928550720215
+1132,0.6171875,0.65625,,0.2,7,5,7,,200,100,,16,6.227988004684448
+1133,0.6328125,0.640625,,0.2,7,5,8,,200,100,,16,6.382381916046143
+1134,0.7109375,0.7265625,,0.2,7,5,9,,200,100,,16,6.187982082366943
+1135,0.625,0.6171875,,0.2,7,5,10,,200,100,,16,6.242426872253418
+1136,0.6328125,0.640625,,0.2,7,5,11,,200,100,,16,6.205005407333374
+1137,0.703125,0.71875,,0.2,7,5,12,,200,100,,16,6.284029960632324
+1138,0.609375,0.625,,0.2,7,5,13,,200,100,,16,6.341282367706299
+1139,0.6875,0.71875,,0.2,7,5,14,,200,100,,16,6.217035531997681
+1140,0.5859375,0.6015625,,0.2,7,5,15,,200,100,,16,6.193021774291992
+1141,0.625,0.6484375,,0.2,7,5,16,,200,100,,16,6.253010272979736
+1142,0.65625,0.6640625,,0.2,7,5,17,,200,100,,16,6.318996429443359
+1143,0.6796875,0.6875,,0.2,7,5,18,,200,100,,16,6.375717639923096
+1144,0.59375,0.640625,,0.2,7,5,19,,200,100,,16,6.227004289627075
+1145,0.640625,0.6796875,,0.2,7,5,20,,200,100,,16,6.236990213394165
+1146,0.6015625,0.6171875,,0.2,7,5,21,,200,100,,16,6.216010808944702
+1147,0.6875,0.6875,,0.2,7,5,22,,200,100,,16,6.303351640701294
+1148,0.6953125,0.6875,,0.2,7,5,23,,200,100,,16,6.334994792938232
+1149,0.6953125,0.6953125,,0.2,7,5,24,,200,100,,16,6.243007183074951
+1150,0.56640625,0.5703125,,0.2,8,5,0,,400,100,,16,14.451982975006104
+1151,0.5546875,0.56640625,,0.2,8,5,1,,400,100,,16,14.493289709091187
+1152,0.57421875,0.58203125,,0.2,8,5,2,,400,100,,16,14.40435242652893
+1153,0.5859375,0.58984375,,0.2,8,5,3,,400,100,,16,14.455973148345947
+1154,0.6015625,0.578125,,0.2,8,5,4,,400,100,,16,14.44904613494873
+1155,0.5703125,0.5859375,,0.2,8,5,5,,400,100,,16,14.43348479270935
+1156,0.53125,0.56640625,,0.2,8,5,6,,400,100,,16,14.383997440338135
+1157,0.62890625,0.64453125,,0.2,8,5,7,,400,100,,16,14.394721984863281
+1158,0.546875,0.57421875,,0.2,8,5,8,,400,100,,16,14.35301399230957
+1159,0.578125,0.58984375,,0.2,8,5,9,,400,100,,16,14.564071655273438
+1160,0.58203125,0.58203125,,0.2,8,5,10,,400,100,,16,14.345016241073608
+1161,0.578125,0.59375,,0.2,8,5,11,,400,100,,16,14.497248649597168
+1162,0.58984375,0.61328125,,0.2,8,5,12,,400,100,,16,14.363262176513672
+1163,0.61328125,0.6328125,,0.2,8,5,13,,400,100,,16,14.349644660949707
+1164,0.5625,0.58203125,,0.2,8,5,14,,400,100,,16,14.298010349273682
+1165,0.54296875,0.6171875,,0.2,8,5,15,,400,100,,16,14.385737895965576
+1166,0.58984375,0.59375,,0.2,8,5,16,,400,100,,16,14.315995693206787
+1167,0.6015625,0.59765625,,0.2,8,5,17,,400,100,,16,14.405732870101929
+1168,0.6015625,0.61328125,,0.2,8,5,18,,400,100,,16,14.38167953491211
+1169,0.5859375,0.5859375,,0.2,8,5,19,,400,100,,16,14.578851461410522
+1170,0.58203125,0.6171875,,0.2,8,5,20,,400,100,,16,14.320427656173706
+1171,0.578125,0.59765625,,0.2,8,5,21,,400,100,,16,14.408906698226929
+1172,0.62109375,0.62890625,,0.2,8,5,22,,400,100,,16,14.323650121688843
+1173,0.609375,0.62109375,,0.2,8,5,23,,400,100,,16,14.433086395263672
+1174,0.5546875,0.5625,,0.2,8,5,24,,400,100,,16,14.315990924835205
+1175,0.564453125,0.572265625,,0.2,9,5,0,,800,100,,16,44.30867075920105
+1176,0.55859375,0.572265625,,0.2,9,5,1,,800,100,,16,43.824588775634766
+1177,0.54296875,0.55078125,,0.2,9,5,2,,800,100,,16,44.35557150840759
+1178,0.560546875,0.5703125,,0.2,9,5,3,,800,100,,16,43.99215745925903
+1179,0.490234375,0.5625,,0.2,9,5,4,,800,100,,16,43.99802803993225
+1180,0.52734375,0.54296875,,0.2,9,5,5,,800,100,,16,43.75412964820862
+1181,0.521484375,0.537109375,,0.2,9,5,6,,800,100,,16,44.182425022125244
+1182,0.52734375,0.53515625,,0.2,9,5,7,,800,100,,16,43.90331435203552
+1183,0.51171875,0.52734375,,0.2,9,5,8,,800,100,,16,44.0692663192749
+1184,0.5625,0.572265625,,0.2,9,5,9,,800,100,,16,43.66517210006714
+1185,0.552734375,0.5703125,,0.2,9,5,10,,800,100,,16,44.1685836315155
+1186,0.51171875,0.505859375,,0.2,9,5,11,,800,100,,16,43.961971282958984
+1187,0.55859375,0.572265625,,0.2,9,5,12,,800,100,,16,43.79748034477234
+1188,0.533203125,0.546875,,0.2,9,5,13,,800,100,,16,43.673375606536865
+1189,0.5703125,0.578125,,0.2,9,5,14,,800,100,,16,44.10062527656555
+1190,0.544921875,0.544921875,,0.2,9,5,15,,800,100,,16,43.79202389717102
+1191,0.53515625,0.544921875,,0.2,9,5,16,,800,100,,16,44.10643935203552
+1192,0.525390625,0.56640625,,0.2,9,5,17,,800,100,,16,43.69362545013428
+1193,0.568359375,0.58203125,,0.2,9,5,18,,800,100,,16,44.28891324996948
+1194,0.568359375,0.583984375,,0.2,9,5,19,,800,100,,16,43.827210664749146
+1195,0.533203125,0.546875,,0.2,9,5,20,,800,100,,16,44.08602595329285
+1196,0.51171875,0.53515625,,0.2,9,5,21,,800,100,,16,43.745967388153076
+1197,0.556640625,0.556640625,,0.2,9,5,22,,800,100,,16,44.084744691848755
+1198,0.521484375,0.544921875,,0.2,9,5,23,,800,100,,16,43.667075872421265
+1199,0.5546875,0.5625,,0.2,9,5,24,,800,100,,16,43.97508192062378
+1200,1.0,1.0,,0.0,6,10,0,,100,100,,16,3.7630202770233154
+1201,1.0,1.0,,0.0,6,10,1,,100,100,,16,3.8020071983337402
+1202,1.0,1.0,,0.0,6,10,2,,100,100,,16,3.7749927043914795
+1203,1.0,1.0,,0.0,6,10,3,,100,100,,16,3.8860106468200684
+1204,1.0,1.0,,0.0,6,10,4,,100,100,,16,3.789017915725708
+1205,1.0,1.0,,0.0,6,10,5,,100,100,,16,3.8270232677459717
+1206,1.0,1.0,,0.0,6,10,6,,100,100,,16,3.815779685974121
+1207,1.0,1.0,,0.0,6,10,7,,100,100,,16,3.9043612480163574
+1208,1.0,1.0,,0.0,6,10,8,,100,100,,16,3.86602520942688
+1209,1.0,1.0,,0.0,6,10,9,,100,100,,16,3.8342032432556152
+1210,1.0,1.0,,0.0,6,10,10,,100,100,,16,3.8310179710388184
+1211,1.0,1.0,,0.0,6,10,11,,100,100,,16,3.8750216960906982
+1212,1.0,1.0,,0.0,6,10,12,,100,100,,16,3.808992385864258
+1213,1.0,1.0,,0.0,6,10,13,,100,100,,16,3.8109922409057617
+1214,1.0,1.0,,0.0,6,10,14,,100,100,,16,3.8326683044433594
+1215,1.0,1.0,,0.0,6,10,15,,100,100,,16,3.8670196533203125
+1216,1.0,1.0,,0.0,6,10,16,,100,100,,16,3.8260130882263184
+1217,1.0,1.0,,0.0,6,10,17,,100,100,,16,3.8620078563690186
+1218,1.0,1.0,,0.0,6,10,18,,100,100,,16,3.8539891242980957
+1219,1.0,1.0,,0.0,6,10,19,,100,100,,16,3.837987184524536
+1220,1.0,1.0,,0.0,6,10,20,,100,100,,16,3.8330211639404297
+1221,1.0,1.0,,0.0,6,10,21,,100,100,,16,3.8660943508148193
+1222,1.0,1.0,,0.0,6,10,22,,100,100,,16,3.8339948654174805
+1223,1.0,1.0,,0.0,6,10,23,,100,100,,16,3.882005453109741
+1224,1.0,1.0,,0.0,6,10,24,,100,100,,16,3.872995376586914
+1225,1.0,1.0,,0.0,7,10,0,,200,100,,16,6.2910192012786865
+1226,0.984375,0.984375,,0.0,7,10,1,,200,100,,16,6.228988885879517
+1227,0.984375,0.984375,,0.0,7,10,2,,200,100,,16,6.282730579376221
+1228,0.9921875,0.9921875,,0.0,7,10,3,,200,100,,16,6.237989187240601
+1229,0.9921875,0.9921875,,0.0,7,10,4,,200,100,,16,6.341994285583496
+1230,0.984375,0.984375,,0.0,7,10,5,,200,100,,16,6.237999677658081
+1231,0.96875,0.9765625,,0.0,7,10,6,,200,100,,16,6.287992238998413
+1232,0.9921875,0.9921875,,0.0,7,10,7,,200,100,,16,6.295786380767822
+1233,0.9765625,0.9765625,,0.0,7,10,8,,200,100,,16,6.3190014362335205
+1234,0.9921875,0.9921875,,0.0,7,10,9,,200,100,,16,6.291008949279785
+1235,0.9921875,0.9921875,,0.0,7,10,10,,200,100,,16,6.26900839805603
+1236,0.984375,0.984375,,0.0,7,10,11,,200,100,,16,6.227004528045654
+1237,1.0,1.0,,0.0,7,10,12,,200,100,,16,6.305633783340454
+1238,0.984375,0.984375,,0.0,7,10,13,,200,100,,16,6.24802303314209
+1239,0.984375,0.984375,,0.0,7,10,14,,200,100,,16,6.354017496109009
+1240,0.96875,0.96875,,0.0,7,10,15,,200,100,,16,6.284022569656372
+1241,0.9921875,1.0,,0.0,7,10,16,,200,100,,16,6.3798418045043945
+1242,0.9921875,0.9921875,,0.0,7,10,17,,200,100,,16,6.485018253326416
+1243,0.96875,0.96875,,0.0,7,10,18,,200,100,,16,6.2791008949279785
+1244,0.984375,0.984375,,0.0,7,10,19,,200,100,,16,6.306986331939697
+1245,0.9921875,1.0,,0.0,7,10,20,,200,100,,16,6.302991151809692
+1246,1.0,1.0,,0.0,7,10,21,,200,100,,16,6.269193410873413
+1247,1.0,1.0,,0.0,7,10,22,,200,100,,16,6.303991317749023
+1248,1.0,1.0,,0.0,7,10,23,,200,100,,16,6.253997802734375
+1249,0.9921875,0.9921875,,0.0,7,10,24,,200,100,,16,6.330991268157959
+1250,0.9296875,0.9296875,,0.0,8,10,0,,400,100,,16,14.562236547470093
+1251,0.94140625,0.94140625,,0.0,8,10,1,,400,100,,16,14.636992931365967
+1252,0.92578125,0.92578125,,0.0,8,10,2,,400,100,,16,14.5088369846344
+1253,0.921875,0.921875,,0.0,8,10,3,,400,100,,16,14.666990995407104
+1254,0.9140625,0.9140625,,0.0,8,10,4,,400,100,,16,14.584985971450806
+1255,0.9296875,0.9296875,,0.0,8,10,5,,400,100,,16,14.770755529403687
+1256,0.93359375,0.93359375,,0.0,8,10,6,,400,100,,16,14.491994142532349
+1257,0.9296875,0.9296875,,0.0,8,10,7,,400,100,,16,14.604988098144531
+1258,0.8984375,0.90234375,,0.0,8,10,8,,400,100,,16,14.474151134490967
+1259,0.9453125,0.9453125,,0.0,8,10,9,,400,100,,16,14.5881507396698
+1260,0.94921875,0.94921875,,0.0,8,10,10,,400,100,,16,14.464236736297607
+1261,0.94140625,0.9453125,,0.0,8,10,11,,400,100,,16,14.59399700164795
+1262,0.94140625,0.94140625,,0.0,8,10,12,,400,100,,16,14.536003828048706
+1263,0.91796875,0.91796875,,0.0,8,10,13,,400,100,,16,14.584923505783081
+1264,0.91796875,0.91796875,,0.0,8,10,14,,400,100,,16,14.489204406738281
+1265,0.94140625,0.9453125,,0.0,8,10,15,,400,100,,16,14.661481142044067
+1266,0.9453125,0.9453125,,0.0,8,10,16,,400,100,,16,14.600627422332764
+1267,0.91015625,0.91796875,,0.0,8,10,17,,400,100,,16,14.535165548324585
+1268,0.92578125,0.92578125,,0.0,8,10,18,,400,100,,16,14.45901870727539
+1269,0.9375,0.9375,,0.0,8,10,19,,400,100,,16,14.604186296463013
+1270,0.93359375,0.93359375,,0.0,8,10,20,,400,100,,16,14.442018985748291
+1271,0.9296875,0.9296875,,0.0,8,10,21,,400,100,,16,14.54565691947937
+1272,0.92578125,0.9296875,,0.0,8,10,22,,400,100,,16,14.414534568786621
+1273,0.92578125,0.92578125,,0.0,8,10,23,,400,100,,16,14.525376796722412
+1274,0.94140625,0.94140625,,0.0,8,10,24,,400,100,,16,14.49102258682251
+1275,0.8515625,0.8515625,,0.0,9,10,0,,800,100,,16,44.56715703010559
+1276,0.8671875,0.8671875,,0.0,9,10,1,,800,100,,16,44.41112923622131
+1277,0.845703125,0.845703125,,0.0,9,10,2,,800,100,,16,44.53636145591736
+1278,0.857421875,0.857421875,,0.0,9,10,3,,800,100,,16,44.324357748031616
+1279,0.861328125,0.861328125,,0.0,9,10,4,,800,100,,16,44.50866222381592
+1280,0.8515625,0.8515625,,0.0,9,10,5,,800,100,,16,44.251044273376465
+1281,0.8671875,0.8671875,,0.0,9,10,6,,800,100,,16,44.562358379364014
+1282,0.849609375,0.849609375,,0.0,9,10,7,,800,100,,16,44.386803150177
+1283,0.8671875,0.8671875,,0.0,9,10,8,,800,100,,16,44.52668285369873
+1284,0.861328125,0.861328125,,0.0,9,10,9,,800,100,,16,44.29712176322937
+1285,0.876953125,0.876953125,,0.0,9,10,10,,800,100,,16,44.66125822067261
+1286,0.859375,0.859375,,0.0,9,10,11,,800,100,,16,44.07258200645447
+1287,0.86328125,0.86328125,,0.0,9,10,12,,800,100,,16,44.595794677734375
+1288,0.873046875,0.873046875,,0.0,9,10,13,,800,100,,16,44.11559510231018
+1289,0.876953125,0.876953125,,0.0,9,10,14,,800,100,,16,44.55713868141174
+1290,0.85546875,0.85546875,,0.0,9,10,15,,800,100,,16,44.3010458946228
+1291,0.875,0.875,,0.0,9,10,16,,800,100,,16,44.29214096069336
+1292,0.8671875,0.8671875,,0.0,9,10,17,,800,100,,16,44.30598473548889
+1293,0.859375,0.859375,,0.0,9,10,18,,800,100,,16,44.48204183578491
+1294,0.86328125,0.86328125,,0.0,9,10,19,,800,100,,16,44.14624238014221
+1295,0.875,0.876953125,,0.0,9,10,20,,800,100,,16,44.382662296295166
+1296,0.861328125,0.861328125,,0.0,9,10,21,,800,100,,16,44.192298412323
+1297,0.865234375,0.8671875,,0.0,9,10,22,,800,100,,16,44.50978183746338
+1298,0.86328125,0.86328125,,0.0,9,10,23,,800,100,,16,44.07561111450195
+1299,0.888671875,0.888671875,,0.0,9,10,24,,800,100,,16,44.375073194503784
+1300,1.0,1.0,,0.01,6,10,0,,100,100,,16,3.800318479537964
+1301,1.0,1.0,,0.01,6,10,1,,100,100,,16,3.809002637863159
+1302,1.0,1.0,,0.01,6,10,2,,100,100,,16,3.817013740539551
+1303,1.0,1.0,,0.01,6,10,3,,100,100,,16,3.809995412826538
+1304,1.0,1.0,,0.01,6,10,4,,100,100,,16,3.8100030422210693
+1305,1.0,1.0,,0.01,6,10,5,,100,100,,16,3.797987937927246
+1306,1.0,1.0,,0.01,6,10,6,,100,100,,16,3.8619894981384277
+1307,1.0,1.0,,0.01,6,10,7,,100,100,,16,3.808002233505249
+1308,1.0,1.0,,0.01,6,10,8,,100,100,,16,3.807690382003784
+1309,1.0,1.0,,0.01,6,10,9,,100,100,,16,3.843994140625
+1310,1.0,1.0,,0.01,6,10,10,,100,100,,16,3.8859970569610596
+1311,1.0,1.0,,0.01,6,10,11,,100,100,,16,3.8160033226013184
+1312,1.0,1.0,,0.01,6,10,12,,100,100,,16,3.857992172241211
+1313,1.0,1.0,,0.01,6,10,13,,100,100,,16,3.8500189781188965
+1314,1.0,1.0,,0.01,6,10,14,,100,100,,16,3.8870127201080322
+1315,1.0,1.0,,0.01,6,10,15,,100,100,,16,3.7955963611602783
+1316,1.0,1.0,,0.01,6,10,16,,100,100,,16,3.8381218910217285
+1317,1.0,1.0,,0.01,6,10,17,,100,100,,16,3.841022253036499
+1318,1.0,1.0,,0.01,6,10,18,,100,100,,16,3.9089930057525635
+1319,1.0,1.0,,0.01,6,10,19,,100,100,,16,3.852018356323242
+1320,1.0,1.0,,0.01,6,10,20,,100,100,,16,3.80802059173584
+1321,1.0,1.0,,0.01,6,10,21,,100,100,,16,3.826019525527954
+1322,1.0,1.0,,0.01,6,10,22,,100,100,,16,3.9514989852905273
+1323,1.0,1.0,,0.01,6,10,23,,100,100,,16,3.8532514572143555
+1324,1.0,1.0,,0.01,6,10,24,,100,100,,16,3.798997163772583
+1325,0.984375,0.984375,,0.01,7,10,0,,200,100,,16,6.326195240020752
+1326,0.96875,0.9765625,,0.01,7,10,1,,200,100,,16,6.265997886657715
+1327,0.953125,0.9609375,,0.01,7,10,2,,200,100,,16,6.264346122741699
+1328,0.9609375,0.9609375,,0.01,7,10,3,,200,100,,16,6.345001220703125
+1329,0.984375,0.984375,,0.01,7,10,4,,200,100,,16,6.349016427993774
+1330,0.9765625,0.9765625,,0.01,7,10,5,,200,100,,16,6.263018369674683
+1331,0.96875,0.96875,,0.01,7,10,6,,200,100,,16,6.320785760879517
+1332,0.9765625,0.9765625,,0.01,7,10,7,,200,100,,16,6.251983642578125
+1333,0.96875,0.984375,,0.01,7,10,8,,200,100,,16,6.393602609634399
+1334,0.9921875,1.0,,0.01,7,10,9,,200,100,,16,6.258988618850708
+1335,0.9765625,0.9765625,,0.01,7,10,10,,200,100,,16,6.291982412338257
+1336,0.96875,0.9765625,,0.01,7,10,11,,200,100,,16,6.277987241744995
+1337,0.9921875,0.9921875,,0.01,7,10,12,,200,100,,16,6.318709373474121
+1338,0.96875,0.9765625,,0.01,7,10,13,,200,100,,16,6.411553144454956
+1339,0.96875,0.96875,,0.01,7,10,14,,200,100,,16,6.294538974761963
+1340,0.9609375,0.96875,,0.01,7,10,15,,200,100,,16,6.2780187129974365
+1341,0.9609375,0.96875,,0.01,7,10,16,,200,100,,16,6.336998224258423
+1342,0.9609375,0.9609375,,0.01,7,10,17,,200,100,,16,6.254019260406494
+1343,0.96875,0.9765625,,0.01,7,10,18,,200,100,,16,6.366881847381592
+1344,0.96875,0.9765625,,0.01,7,10,19,,200,100,,16,6.25599479675293
+1345,0.96875,0.9765625,,0.01,7,10,20,,200,100,,16,6.313999891281128
+1346,0.984375,0.984375,,0.01,7,10,21,,200,100,,16,6.300022840499878
+1347,0.984375,0.984375,,0.01,7,10,22,,200,100,,16,6.304507493972778
+1348,0.984375,0.984375,,0.01,7,10,23,,200,100,,16,6.3760316371917725
+1349,0.984375,0.984375,,0.01,7,10,24,,200,100,,16,6.319030284881592
+1350,0.88671875,0.90234375,,0.01,8,10,0,,400,100,,16,14.564136981964111
+1351,0.8671875,0.87890625,,0.01,8,10,1,,400,100,,16,14.693748474121094
+1352,0.8828125,0.88671875,,0.01,8,10,2,,400,100,,16,14.480985879898071
+1353,0.91015625,0.9140625,,0.01,8,10,3,,400,100,,16,14.6137216091156
+1354,0.89453125,0.8984375,,0.01,8,10,4,,400,100,,16,14.513046026229858
+1355,0.9140625,0.91796875,,0.01,8,10,5,,400,100,,16,14.663359642028809
+1356,0.8671875,0.87890625,,0.01,8,10,6,,400,100,,16,14.499014377593994
+1357,0.91015625,0.9140625,,0.01,8,10,7,,400,100,,16,14.611068487167358
+1358,0.88671875,0.89453125,,0.01,8,10,8,,400,100,,16,14.55802035331726
+1359,0.90625,0.9140625,,0.01,8,10,9,,400,100,,16,14.706343173980713
+1360,0.8828125,0.890625,,0.01,8,10,10,,400,100,,16,14.582001447677612
+1361,0.8671875,0.87890625,,0.01,8,10,11,,400,100,,16,15.199872255325317
+1362,0.90234375,0.90625,,0.01,8,10,12,,400,100,,16,14.557384490966797
+1363,0.8828125,0.890625,,0.01,8,10,13,,400,100,,16,14.588038921356201
+1364,0.890625,0.8984375,,0.01,8,10,14,,400,100,,16,14.522017240524292
+1365,0.90234375,0.91015625,,0.01,8,10,15,,400,100,,16,14.623703956604004
+1366,0.87109375,0.87890625,,0.01,8,10,16,,400,100,,16,14.514991283416748
+1367,0.88671875,0.890625,,0.01,8,10,17,,400,100,,16,14.636829614639282
+1368,0.8671875,0.87109375,,0.01,8,10,18,,400,100,,16,14.464989423751831
+1369,0.87890625,0.88671875,,0.01,8,10,19,,400,100,,16,14.563626050949097
+1370,0.88671875,0.88671875,,0.01,8,10,20,,400,100,,16,14.50902247428894
+1371,0.875,0.88671875,,0.01,8,10,21,,400,100,,16,14.698225736618042
+1372,0.9296875,0.93359375,,0.01,8,10,22,,400,100,,16,14.562914609909058
+1373,0.89453125,0.89453125,,0.01,8,10,23,,400,100,,16,14.541823625564575
+1374,0.84375,0.85546875,,0.01,8,10,24,,400,100,,16,14.480490922927856
+1375,0.802734375,0.8125,,0.01,9,10,0,,800,100,,16,44.53096342086792
+1376,0.8203125,0.826171875,,0.01,9,10,1,,800,100,,16,44.35498356819153
+1377,0.763671875,0.767578125,,0.01,9,10,2,,800,100,,16,44.55807185173035
+1378,0.78515625,0.79296875,,0.01,9,10,3,,800,100,,16,44.359490633010864
+1379,0.787109375,0.79296875,,0.01,9,10,4,,800,100,,16,44.32682275772095
+1380,0.802734375,0.8046875,,0.01,9,10,5,,800,100,,16,44.30001664161682
+1381,0.76171875,0.76953125,,0.01,9,10,6,,800,100,,16,44.43307280540466
+1382,0.7734375,0.77734375,,0.01,9,10,7,,800,100,,16,44.05543398857117
+1383,0.8046875,0.8125,,0.01,9,10,8,,800,100,,16,44.31524872779846
+1384,0.767578125,0.77734375,,0.01,9,10,9,,800,100,,16,43.959123611450195
+1385,0.814453125,0.814453125,,0.01,9,10,10,,800,100,,16,44.476478099823
+1386,0.796875,0.80859375,,0.01,9,10,11,,800,100,,16,44.111027240753174
+1387,0.759765625,0.76953125,,0.01,9,10,12,,800,100,,16,44.39329218864441
+1388,0.80078125,0.80859375,,0.01,9,10,13,,800,100,,16,44.17123246192932
+1389,0.81640625,0.822265625,,0.01,9,10,14,,800,100,,16,44.44554805755615
+1390,0.771484375,0.78125,,0.01,9,10,15,,800,100,,16,44.02779817581177
+1391,0.802734375,0.80859375,,0.01,9,10,16,,800,100,,16,44.39881730079651
+1392,0.79296875,0.798828125,,0.01,9,10,17,,800,100,,16,44.08395576477051
+1393,0.787109375,0.79296875,,0.01,9,10,18,,800,100,,16,44.545893907547
+1394,0.779296875,0.787109375,,0.01,9,10,19,,800,100,,16,44.23042392730713
+1395,0.802734375,0.810546875,,0.01,9,10,20,,800,100,,16,44.35557842254639
+1396,0.771484375,0.78125,,0.01,9,10,21,,800,100,,16,44.13212823867798
+1397,0.787109375,0.794921875,,0.01,9,10,22,,800,100,,16,44.43531107902527
+1398,0.765625,0.78125,,0.01,9,10,23,,800,100,,16,44.02405667304993
+1399,0.802734375,0.810546875,,0.01,9,10,24,,800,100,,16,44.32807660102844
+1400,0.921875,0.953125,,0.1,6,10,0,,100,100,,16,3.8860058784484863
+1401,0.875,0.90625,,0.1,6,10,1,,100,100,,16,3.7790114879608154
+1402,0.90625,0.9375,,0.1,6,10,2,,100,100,,16,3.788987636566162
+1403,0.9375,0.96875,,0.1,6,10,3,,100,100,,16,3.7931389808654785
+1404,0.890625,0.921875,,0.1,6,10,4,,100,100,,16,3.894007682800293
+1405,0.953125,0.96875,,0.1,6,10,5,,100,100,,16,3.8110082149505615
+1406,0.859375,0.890625,,0.1,6,10,6,,100,100,,16,3.809987783432007
+1407,0.921875,0.9375,,0.1,6,10,7,,100,100,,16,3.8303585052490234
+1408,0.953125,0.953125,,0.1,6,10,8,,100,100,,16,3.9310123920440674
+1409,0.9375,0.953125,,0.1,6,10,9,,100,100,,16,3.8200175762176514
+1410,0.828125,0.859375,,0.1,6,10,10,,100,100,,16,3.836515426635742
+1411,0.921875,0.953125,,0.1,6,10,11,,100,100,,16,3.829618453979492
+1412,0.859375,0.90625,,0.1,6,10,12,,100,100,,16,3.9109952449798584
+1413,0.90625,0.90625,,0.1,6,10,13,,100,100,,16,3.8130128383636475
+1414,0.859375,0.90625,,0.1,6,10,14,,100,100,,16,3.8220202922821045
+1415,0.90625,0.921875,,0.1,6,10,15,,100,100,,16,3.8398947715759277
+1416,0.9375,0.953125,,0.1,6,10,16,,100,100,,16,3.9020230770111084
+1417,0.953125,0.953125,,0.1,6,10,17,,100,100,,16,3.833986282348633
+1418,0.859375,0.890625,,0.1,6,10,18,,100,100,,16,3.8253581523895264
+1419,0.796875,0.84375,,0.1,6,10,19,,100,100,,16,3.8129870891571045
+1420,0.875,0.921875,,0.1,6,10,20,,100,100,,16,3.8720128536224365
+1421,1.0,1.0,,0.1,6,10,21,,100,100,,16,3.864022970199585
+1422,0.9375,0.96875,,0.1,6,10,22,,100,100,,16,3.8170230388641357
+1423,0.953125,0.96875,,0.1,6,10,23,,100,100,,16,3.8540284633636475
+1424,0.9375,0.953125,,0.1,6,10,24,,100,100,,16,3.8469974994659424
+1425,0.7578125,0.7734375,,0.1,7,10,0,,200,100,,16,6.255589008331299
+1426,0.828125,0.8359375,,0.1,7,10,1,,200,100,,16,6.221022367477417
+1427,0.78125,0.8046875,,0.1,7,10,2,,200,100,,16,6.32755184173584
+1428,0.7734375,0.7890625,,0.1,7,10,3,,200,100,,16,6.201019763946533
+1429,0.75,0.78125,,0.1,7,10,4,,200,100,,16,6.256998300552368
+1430,0.71875,0.7578125,,0.1,7,10,5,,200,100,,16,6.207019567489624
+1431,0.8046875,0.828125,,0.1,7,10,6,,200,100,,16,6.29179310798645
+1432,0.75,0.8046875,,0.1,7,10,7,,200,100,,16,6.304027557373047
+1433,0.8515625,0.859375,,0.1,7,10,8,,200,100,,16,6.271346807479858
+1434,0.7734375,0.8046875,,0.1,7,10,9,,200,100,,16,6.224017858505249
+1435,0.7890625,0.8125,,0.1,7,10,10,,200,100,,16,6.283098459243774
+1436,0.765625,0.78125,,0.1,7,10,11,,200,100,,16,6.193023681640625
+1437,0.7734375,0.796875,,0.1,7,10,12,,200,100,,16,6.260002613067627
+1438,0.78125,0.8046875,,0.1,7,10,13,,200,100,,16,6.240019798278809
+1439,0.7734375,0.8125,,0.1,7,10,14,,200,100,,16,6.345156669616699
+1440,0.78125,0.78125,,0.1,7,10,15,,200,100,,16,6.285996198654175
+1441,0.765625,0.7890625,,0.1,7,10,16,,200,100,,16,6.239022493362427
+1442,0.8203125,0.8359375,,0.1,7,10,17,,200,100,,16,6.246986150741577
+1443,0.7734375,0.7734375,,0.1,7,10,18,,200,100,,16,6.221438407897949
+1444,0.734375,0.765625,,0.1,7,10,19,,200,100,,16,6.171649217605591
+1445,0.75,0.765625,,0.1,7,10,20,,200,100,,16,6.301997184753418
+1446,0.796875,0.8125,,0.1,7,10,21,,200,100,,16,6.236016035079956
+1447,0.75,0.78125,,0.1,7,10,22,,200,100,,16,6.295007944107056
+1448,0.8125,0.8359375,,0.1,7,10,23,,200,100,,16,6.254001617431641
+1449,0.7109375,0.7734375,,0.1,7,10,24,,200,100,,16,6.287940263748169
+1450,0.6875,0.6875,,0.1,8,10,0,,400,100,,16,14.599380493164062
+1451,0.6484375,0.65234375,,0.1,8,10,1,,400,100,,16,14.624665975570679
+1452,0.68359375,0.6953125,,0.1,8,10,2,,400,100,,16,14.47702407836914
+1453,0.625,0.66015625,,0.1,8,10,3,,400,100,,16,14.47910475730896
+1454,0.61328125,0.6171875,,0.1,8,10,4,,400,100,,16,14.375009536743164
+1455,0.734375,0.72265625,,0.1,8,10,5,,400,100,,16,14.579461336135864
+1456,0.6484375,0.671875,,0.1,8,10,6,,400,100,,16,14.45000410079956
+1457,0.65625,0.65625,,0.1,8,10,7,,400,100,,16,14.500012874603271
+1458,0.609375,0.640625,,0.1,8,10,8,,400,100,,16,14.40648102760315
+1459,0.61328125,0.62890625,,0.1,8,10,9,,400,100,,16,14.52016806602478
+1460,0.65234375,0.67578125,,0.1,8,10,10,,400,100,,16,14.387635469436646
+1461,0.64453125,0.66015625,,0.1,8,10,11,,400,100,,16,14.523988008499146
+1462,0.69921875,0.7109375,,0.1,8,10,12,,400,100,,16,14.499102592468262
+1463,0.65234375,0.6875,,0.1,8,10,13,,400,100,,16,14.488799095153809
+1464,0.703125,0.6953125,,0.1,8,10,14,,400,100,,16,14.404354572296143
+1465,0.6640625,0.6796875,,0.1,8,10,15,,400,100,,16,14.485280990600586
+1466,0.63671875,0.65234375,,0.1,8,10,16,,400,100,,16,14.390599489212036
+1467,0.6796875,0.703125,,0.1,8,10,17,,400,100,,16,14.449635982513428
+1468,0.69921875,0.71484375,,0.1,8,10,18,,400,100,,16,14.297101736068726
+1469,0.68359375,0.69921875,,0.1,8,10,19,,400,100,,16,14.409023523330688
+1470,0.68359375,0.69140625,,0.1,8,10,20,,400,100,,16,14.365158557891846
+1471,0.6796875,0.671875,,0.1,8,10,21,,400,100,,16,14.443681716918945
+1472,0.73046875,0.7421875,,0.1,8,10,22,,400,100,,16,14.477703332901001
+1473,0.6640625,0.68359375,,0.1,8,10,23,,400,100,,16,14.529467105865479
+1474,0.6484375,0.671875,,0.1,8,10,24,,400,100,,16,14.369236469268799
+1475,0.619140625,0.626953125,,0.1,9,10,0,,800,100,,16,44.41040539741516
+1476,0.5625,0.578125,,0.1,9,10,1,,800,100,,16,44.066667795181274
+1477,0.55078125,0.55859375,,0.1,9,10,2,,800,100,,16,44.258904457092285
+1478,0.630859375,0.65234375,,0.1,9,10,3,,800,100,,16,43.83064103126526
+1479,0.57421875,0.58984375,,0.1,9,10,4,,800,100,,16,44.27174615859985
+1480,0.58984375,0.595703125,,0.1,9,10,5,,800,100,,16,43.94964146614075
+1481,0.638671875,0.646484375,,0.1,9,10,6,,800,100,,16,44.32074856758118
+1482,0.630859375,0.6328125,,0.1,9,10,7,,800,100,,16,43.97145342826843
+1483,0.55859375,0.568359375,,0.1,9,10,8,,800,100,,16,44.113288164138794
+1484,0.5625,0.572265625,,0.1,9,10,9,,800,100,,16,43.78162932395935
+1485,0.595703125,0.609375,,0.1,9,10,10,,800,100,,16,43.909536838531494
+1486,0.560546875,0.587890625,,0.1,9,10,11,,800,100,,16,43.829368352890015
+1487,0.576171875,0.58203125,,0.1,9,10,12,,800,100,,16,44.1992723941803
+1488,0.5859375,0.599609375,,0.1,9,10,13,,800,100,,16,43.91659212112427
+1489,0.6015625,0.607421875,,0.1,9,10,14,,800,100,,16,44.24908447265625
+1490,0.59375,0.615234375,,0.1,9,10,15,,800,100,,16,43.8193473815918
+1491,0.58984375,0.607421875,,0.1,9,10,16,,800,100,,16,44.122448444366455
+1492,0.58984375,0.611328125,,0.1,9,10,17,,800,100,,16,43.66205167770386
+1493,0.607421875,0.625,,0.1,9,10,18,,800,100,,16,44.014267683029175
+1494,0.59375,0.60546875,,0.1,9,10,19,,800,100,,16,43.7904736995697
+1495,0.6015625,0.609375,,0.1,9,10,20,,800,100,,16,44.000494718551636
+1496,0.591796875,0.587890625,,0.1,9,10,21,,800,100,,16,43.95460081100464
+1497,0.578125,0.580078125,,0.1,9,10,22,,800,100,,16,44.23811316490173
+1498,0.5859375,0.59765625,,0.1,9,10,23,,800,100,,16,43.79144477844238
+1499,0.59375,0.607421875,,0.1,9,10,24,,800,100,,16,44.156020164489746
+1500,0.796875,0.8125,,0.2,6,10,0,,100,100,,16,3.796199321746826
+1501,0.765625,0.78125,,0.2,6,10,1,,100,100,,16,3.8480019569396973
+1502,0.796875,0.84375,,0.2,6,10,2,,100,100,,16,3.7740206718444824
+1503,0.78125,0.8125,,0.2,6,10,3,,100,100,,16,3.7895655632019043
+1504,0.75,0.765625,,0.2,6,10,4,,100,100,,16,3.784034490585327
+1505,0.796875,0.828125,,0.2,6,10,5,,100,100,,16,3.8540022373199463
+1506,0.71875,0.796875,,0.2,6,10,6,,100,100,,16,3.8390402793884277
+1507,0.875,0.859375,,0.2,6,10,7,,100,100,,16,3.8184001445770264
+1508,0.75,0.75,,0.2,6,10,8,,100,100,,16,3.7811214923858643
+1509,0.859375,0.875,,0.2,6,10,9,,100,100,,16,3.8860135078430176
+1510,0.828125,0.859375,,0.2,6,10,10,,100,100,,16,3.7889926433563232
+1511,0.703125,0.734375,,0.2,6,10,11,,100,100,,16,3.8043837547302246
+1512,0.734375,0.796875,,0.2,6,10,12,,100,100,,16,3.813021659851074
+1513,0.75,0.78125,,0.2,6,10,13,,100,100,,16,3.8250207901000977
+1514,0.859375,0.875,,0.2,6,10,14,,100,100,,16,3.875002384185791
+1515,0.765625,0.796875,,0.2,6,10,15,,100,100,,16,3.801992177963257
+1516,0.859375,0.875,,0.2,6,10,16,,100,100,,16,3.8256242275238037
+1517,0.859375,0.84375,,0.2,6,10,17,,100,100,,16,3.839998722076416
+1518,0.90625,0.96875,,0.2,6,10,18,,100,100,,16,3.878020763397217
+1519,0.8125,0.875,,0.2,6,10,19,,100,100,,16,3.818995714187622
+1520,0.78125,0.796875,,0.2,6,10,20,,100,100,,16,3.800990343093872
+1521,0.765625,0.796875,,0.2,6,10,21,,100,100,,16,3.870988607406616
+1522,0.859375,0.890625,,0.2,6,10,22,,100,100,,16,3.909022569656372
+1523,0.703125,0.796875,,0.2,6,10,23,,100,100,,16,3.834791421890259
+1524,0.828125,0.84375,,0.2,6,10,24,,100,100,,16,3.8010246753692627
+1525,0.6875,0.6953125,,0.2,7,10,0,,200,100,,16,6.291996240615845
+1526,0.65625,0.671875,,0.2,7,10,1,,200,100,,16,6.23800802230835
+1527,0.71875,0.75,,0.2,7,10,2,,200,100,,16,6.238224506378174
+1528,0.6484375,0.7109375,,0.2,7,10,3,,200,100,,16,6.316177606582642
+1529,0.7578125,0.78125,,0.2,7,10,4,,200,100,,16,6.283012628555298
+1530,0.6640625,0.6796875,,0.2,7,10,5,,200,100,,16,6.224021911621094
+1531,0.65625,0.6484375,,0.2,7,10,6,,200,100,,16,6.249374151229858
+1532,0.6953125,0.703125,,0.2,7,10,7,,200,100,,16,6.209987163543701
+1533,0.671875,0.6796875,,0.2,7,10,8,,200,100,,16,6.345209121704102
+1534,0.6171875,0.625,,0.2,7,10,9,,200,100,,16,6.244987726211548
+1535,0.640625,0.703125,,0.2,7,10,10,,200,100,,16,6.265343427658081
+1536,0.640625,0.6796875,,0.2,7,10,11,,200,100,,16,6.215015411376953
+1537,0.671875,0.6875,,0.2,7,10,12,,200,100,,16,6.2460033893585205
+1538,0.6953125,0.6953125,,0.2,7,10,13,,200,100,,16,6.31522798538208
+1539,0.703125,0.71875,,0.2,7,10,14,,200,100,,16,6.273688077926636
+1540,0.6640625,0.6953125,,0.2,7,10,15,,200,100,,16,6.243029832839966
+1541,0.6171875,0.6640625,,0.2,7,10,16,,200,100,,16,6.243995189666748
+1542,0.7109375,0.734375,,0.2,7,10,17,,200,100,,16,6.226997375488281
+1543,0.6328125,0.6640625,,0.2,7,10,18,,200,100,,16,6.287674427032471
+1544,0.671875,0.6875,,0.2,7,10,19,,200,100,,16,6.289021015167236
+1545,0.6484375,0.671875,,0.2,7,10,20,,200,100,,16,6.2399914264678955
+1546,0.703125,0.71875,,0.2,7,10,21,,200,100,,16,6.268988609313965
+1547,0.6875,0.71875,,0.2,7,10,22,,200,100,,16,6.256103038787842
+1548,0.6875,0.71875,,0.2,7,10,23,,200,100,,16,6.235989332199097
+1549,0.65625,0.671875,,0.2,7,10,24,,200,100,,16,6.272987604141235
+1550,0.59765625,0.60546875,,0.2,8,10,0,,400,100,,16,14.474455833435059
+1551,0.59375,0.59375,,0.2,8,10,1,,400,100,,16,14.53762435913086
+1552,0.6328125,0.64453125,,0.2,8,10,2,,400,100,,16,14.434020280838013
+1553,0.5546875,0.57421875,,0.2,8,10,3,,400,100,,16,14.491475820541382
+1554,0.60546875,0.64453125,,0.2,8,10,4,,400,100,,16,14.361429452896118
+1555,0.55859375,0.5859375,,0.2,8,10,5,,400,100,,16,14.44128131866455
+1556,0.56640625,0.5546875,,0.2,8,10,6,,400,100,,16,14.381020545959473
+1557,0.59765625,0.6171875,,0.2,8,10,7,,400,100,,16,14.563472032546997
+1558,0.57421875,0.58203125,,0.2,8,10,8,,400,100,,16,14.397029876708984
+1559,0.67578125,0.67578125,,0.2,8,10,9,,400,100,,16,14.509320259094238
+1560,0.58984375,0.58203125,,0.2,8,10,10,,400,100,,16,14.314023971557617
+1561,0.58203125,0.59375,,0.2,8,10,11,,400,100,,16,14.464481592178345
+1562,0.53515625,0.60546875,,0.2,8,10,12,,400,100,,16,14.313401937484741
+1563,0.58203125,0.59375,,0.2,8,10,13,,400,100,,16,14.448457717895508
+1564,0.640625,0.640625,,0.2,8,10,14,,400,100,,16,14.400634765625
+1565,0.59765625,0.6015625,,0.2,8,10,15,,400,100,,16,14.417220115661621
+1566,0.609375,0.62890625,,0.2,8,10,16,,400,100,,16,14.320985794067383
+1567,0.6015625,0.61328125,,0.2,8,10,17,,400,100,,16,14.524627923965454
+1568,0.6171875,0.625,,0.2,8,10,18,,400,100,,16,14.578006505966187
+1569,0.58203125,0.61328125,,0.2,8,10,19,,400,100,,16,14.515365362167358
+1570,0.61328125,0.62890625,,0.2,8,10,20,,400,100,,16,14.36251711845398
+1571,0.625,0.63671875,,0.2,8,10,21,,400,100,,16,14.453907489776611
+1572,0.6328125,0.64453125,,0.2,8,10,22,,400,100,,16,14.307387590408325
+1573,0.625,0.64453125,,0.2,8,10,23,,400,100,,16,14.42363715171814
+1574,0.60546875,0.609375,,0.2,8,10,24,,400,100,,16,14.373066186904907
+1575,0.552734375,0.552734375,,0.2,9,10,0,,800,100,,16,44.44088935852051
+1576,0.5234375,0.52734375,,0.2,9,10,1,,800,100,,16,43.93399500846863
+1577,0.533203125,0.56640625,,0.2,9,10,2,,800,100,,16,44.677250623703
+1578,0.5546875,0.55859375,,0.2,9,10,3,,800,100,,16,44.60948848724365
+1579,0.5390625,0.548828125,,0.2,9,10,4,,800,100,,16,48.8896267414093
+1580,0.55859375,0.548828125,,0.2,9,10,5,,800,100,,16,50.198251247406006
+1581,0.576171875,0.583984375,,0.2,9,10,6,,800,100,,16,50.978373765945435
+1582,0.56640625,0.580078125,,0.2,9,10,7,,800,100,,16,49.47441005706787
+1583,0.5546875,0.564453125,,0.2,9,10,8,,800,100,,16,51.95449948310852
+1584,0.544921875,0.552734375,,0.2,9,10,9,,800,100,,16,50.67292141914368
+1585,0.59765625,0.607421875,,0.2,9,10,10,,800,100,,16,50.896559953689575
+1586,0.546875,0.5703125,,0.2,9,10,11,,800,100,,16,46.65531611442566
+1587,0.525390625,0.546875,,0.2,9,10,12,,800,100,,16,46.740480184555054
+1588,0.544921875,0.55078125,,0.2,9,10,13,,800,100,,16,47.993003606796265
+1589,0.55078125,0.568359375,,0.2,9,10,14,,800,100,,16,46.98220133781433
+1590,0.529296875,0.55859375,,0.2,9,10,15,,800,100,,16,46.48979997634888
+1591,0.603515625,0.61328125,,0.2,9,10,16,,800,100,,16,48.054638624191284
+1592,0.611328125,0.61328125,,0.2,9,10,17,,800,100,,16,46.470842599868774
+1593,0.595703125,0.61328125,,0.2,9,10,18,,800,100,,16,46.7482590675354
+1594,0.51171875,0.546875,,0.2,9,10,19,,800,100,,16,47.99225211143494
+1595,0.51953125,0.529296875,,0.2,9,10,20,,800,100,,16,46.82289719581604
+1596,0.54296875,0.55078125,,0.2,9,10,21,,800,100,,16,46.72078824043274
+1597,0.5859375,0.578125,,0.2,9,10,22,,800,100,,16,48.24712038040161
+1598,0.57421875,0.587890625,,0.2,9,10,23,,800,100,,16,46.65318465232849
+1599,0.541015625,0.548828125,,0.2,9,10,24,,800,100,,16,46.989219188690186
diff --git a/experiments/bench/oneMax/data/mu+lambda-pop=1000.csv b/experiments/bench/oneMax/data/mu+lambda-pop=1000.csv
new file mode 100644
index 0000000000000000000000000000000000000000..6f963076863de609d01b5f5eba6e122afe2762e6
--- /dev/null
+++ b/experiments/bench/oneMax/data/mu+lambda-pop=1000.csv
@@ -0,0 +1,401 @@
+,best_pop,best_hof,best_arm,std,dim,n_eval,run_number,UCB_sigma,ngen,mu,lambda,n_thread,time
+0,1.0,1.0,,0.0,6,1,0,,100,1000,,16,13.141543865203857
+1,1.0,1.0,,0.0,6,1,1,,100,1000,,16,12.955002546310425
+2,1.0,1.0,,0.0,6,1,2,,100,1000,,16,14.070065975189209
+3,1.0,1.0,,0.0,6,1,3,,100,1000,,16,12.811997175216675
+4,1.0,1.0,,0.0,6,1,4,,100,1000,,16,12.809285640716553
+5,1.0,1.0,,0.0,6,1,5,,100,1000,,16,12.850998401641846
+6,1.0,1.0,,0.0,6,1,6,,100,1000,,16,13.973590612411499
+7,1.0,1.0,,0.0,6,1,7,,100,1000,,16,12.745024681091309
+8,1.0,1.0,,0.0,6,1,8,,100,1000,,16,12.908993244171143
+9,1.0,1.0,,0.0,6,1,9,,100,1000,,16,13.447794198989868
+10,1.0,1.0,,0.0,6,1,10,,100,1000,,16,14.828165054321289
+11,1.0,1.0,,0.0,6,1,11,,100,1000,,16,12.813992261886597
+12,1.0,1.0,,0.0,6,1,12,,100,1000,,16,12.818995714187622
+13,1.0,1.0,,0.0,6,1,13,,100,1000,,16,13.487255334854126
+14,1.0,1.0,,0.0,6,1,14,,100,1000,,16,13.714987993240356
+15,1.0,1.0,,0.0,6,1,15,,100,1000,,16,12.801503419876099
+16,1.0,1.0,,0.0,6,1,16,,100,1000,,16,12.846996068954468
+17,1.0,1.0,,0.0,6,1,17,,100,1000,,16,14.12099313735962
+18,1.0,1.0,,0.0,6,1,18,,100,1000,,16,12.831235885620117
+19,1.0,1.0,,0.0,6,1,19,,100,1000,,16,12.710985898971558
+20,1.0,1.0,,0.0,6,1,20,,100,1000,,16,12.879738807678223
+21,1.0,1.0,,0.0,6,1,21,,100,1000,,16,14.063007593154907
+22,1.0,1.0,,0.0,6,1,22,,100,1000,,16,12.943544626235962
+23,1.0,1.0,,0.0,6,1,23,,100,1000,,16,12.79799747467041
+24,1.0,1.0,,0.0,6,1,24,,100,1000,,16,12.852991819381714
+25,1.0,1.0,,0.0,7,1,0,,200,1000,,16,35.75133204460144
+26,1.0,1.0,,0.0,7,1,1,,200,1000,,16,35.77596592903137
+27,1.0,1.0,,0.0,7,1,2,,200,1000,,16,35.57852649688721
+28,1.0,1.0,,0.0,7,1,3,,200,1000,,16,34.31400942802429
+29,1.0,1.0,,0.0,7,1,4,,200,1000,,16,35.76261305809021
+30,1.0,1.0,,0.0,7,1,5,,200,1000,,16,35.46574091911316
+31,1.0,1.0,,0.0,7,1,6,,200,1000,,16,35.55162024497986
+32,1.0,1.0,,0.0,7,1,7,,200,1000,,16,34.33861184120178
+33,1.0,1.0,,0.0,7,1,8,,200,1000,,16,35.676581382751465
+34,1.0,1.0,,0.0,7,1,9,,200,1000,,16,35.55725622177124
+35,1.0,1.0,,0.0,7,1,10,,200,1000,,16,35.452250719070435
+36,1.0,1.0,,0.0,7,1,11,,200,1000,,16,34.503225326538086
+37,1.0,1.0,,0.0,7,1,12,,200,1000,,16,35.59889268875122
+38,1.0,1.0,,0.0,7,1,13,,200,1000,,16,35.72613263130188
+39,1.0,1.0,,0.0,7,1,14,,200,1000,,16,35.4976487159729
+40,1.0,1.0,,0.0,7,1,15,,200,1000,,16,34.2741322517395
+41,1.0,1.0,,0.0,7,1,16,,200,1000,,16,35.74898147583008
+42,1.0,1.0,,0.0,7,1,17,,200,1000,,16,35.56364583969116
+43,1.0,1.0,,0.0,7,1,18,,200,1000,,16,34.11655354499817
+44,1.0,1.0,,0.0,7,1,19,,200,1000,,16,32.96876335144043
+45,1.0,1.0,,0.0,7,1,20,,200,1000,,16,32.871750354766846
+46,1.0,1.0,,0.0,7,1,21,,200,1000,,16,32.77799034118652
+47,1.0,1.0,,0.0,7,1,22,,200,1000,,16,32.71415042877197
+48,1.0,1.0,,0.0,7,1,23,,200,1000,,16,32.774253129959106
+49,1.0,1.0,,0.0,7,1,24,,200,1000,,16,32.81650114059448
+50,1.0,1.0,,0.0,8,1,0,,400,1000,,16,108.23618865013123
+51,1.0,1.0,,0.0,8,1,1,,400,1000,,16,108.41151809692383
+52,0.99609375,0.99609375,,0.0,8,1,2,,400,1000,,16,108.14181184768677
+53,1.0,1.0,,0.0,8,1,3,,400,1000,,16,107.94203734397888
+54,0.99609375,0.99609375,,0.0,8,1,4,,400,1000,,16,107.7881932258606
+55,0.99609375,0.99609375,,0.0,8,1,5,,400,1000,,16,107.96946930885315
+56,0.9921875,0.9921875,,0.0,8,1,6,,400,1000,,16,107.89672136306763
+57,0.99609375,0.99609375,,0.0,8,1,7,,400,1000,,16,107.77035856246948
+58,0.98828125,0.98828125,,0.0,8,1,8,,400,1000,,16,107.83615708351135
+59,0.99609375,0.99609375,,0.0,8,1,9,,400,1000,,16,107.84840726852417
+60,1.0,1.0,,0.0,8,1,10,,400,1000,,16,107.86388897895813
+61,0.9921875,0.9921875,,0.0,8,1,11,,400,1000,,16,107.8292133808136
+62,1.0,1.0,,0.0,8,1,12,,400,1000,,16,107.62529230117798
+63,0.99609375,0.99609375,,0.0,8,1,13,,400,1000,,16,107.99907803535461
+64,0.98828125,0.9921875,,0.0,8,1,14,,400,1000,,16,107.83375287055969
+65,1.0,1.0,,0.0,8,1,15,,400,1000,,16,107.9557113647461
+66,0.99609375,0.99609375,,0.0,8,1,16,,400,1000,,16,107.61099600791931
+67,0.99609375,0.99609375,,0.0,8,1,17,,400,1000,,16,107.66991901397705
+68,1.0,1.0,,0.0,8,1,18,,400,1000,,16,107.49476289749146
+69,0.99609375,1.0,,0.0,8,1,19,,400,1000,,16,107.55078721046448
+70,0.98828125,0.98828125,,0.0,8,1,20,,400,1000,,16,107.79274725914001
+71,1.0,1.0,,0.0,8,1,21,,400,1000,,16,107.6319510936737
+72,0.9921875,0.9921875,,0.0,8,1,22,,400,1000,,16,107.47671604156494
+73,0.99609375,1.0,,0.0,8,1,23,,400,1000,,16,107.68823289871216
+74,0.98828125,0.98828125,,0.0,8,1,24,,400,1000,,16,107.7297580242157
+75,0.98046875,0.98046875,,0.0,9,1,0,,800,1000,,16,390.92485785484314
+76,0.958984375,0.958984375,,0.0,9,1,1,,800,1000,,16,389.49429631233215
+77,0.970703125,0.97265625,,0.0,9,1,2,,800,1000,,16,389.79029083251953
+78,0.98046875,0.98046875,,0.0,9,1,3,,800,1000,,16,389.43884897232056
+79,0.951171875,0.953125,,0.0,9,1,4,,800,1000,,16,390.3404173851013
+80,0.966796875,0.966796875,,0.0,9,1,5,,800,1000,,16,389.4277653694153
+81,0.96484375,0.96484375,,0.0,9,1,6,,800,1000,,16,390.0247640609741
+82,0.9609375,0.962890625,,0.0,9,1,7,,800,1000,,16,389.92755126953125
+83,0.97265625,0.974609375,,0.0,9,1,8,,800,1000,,16,389.83030700683594
+84,0.962890625,0.96484375,,0.0,9,1,9,,800,1000,,16,389.49288868904114
+85,0.970703125,0.97265625,,0.0,9,1,10,,800,1000,,16,390.3582525253296
+86,0.96484375,0.96484375,,0.0,9,1,11,,800,1000,,16,389.787814617157
+87,0.96875,0.970703125,,0.0,9,1,12,,800,1000,,16,389.64947056770325
+88,0.970703125,0.970703125,,0.0,9,1,13,,800,1000,,16,389.37326765060425
+89,0.96875,0.96875,,0.0,9,1,14,,800,1000,,16,390.0918788909912
+90,0.958984375,0.958984375,,0.0,9,1,15,,800,1000,,16,390.0012671947479
+91,0.95703125,0.958984375,,0.0,9,1,16,,800,1000,,16,389.5962197780609
+92,0.962890625,0.962890625,,0.0,9,1,17,,800,1000,,16,389.5372688770294
+93,0.958984375,0.958984375,,0.0,9,1,18,,800,1000,,16,389.8753478527069
+94,0.97265625,0.97265625,,0.0,9,1,19,,800,1000,,16,389.25567078590393
+95,0.94921875,0.951171875,,0.0,9,1,20,,800,1000,,16,390.65052938461304
+96,0.96875,0.96875,,0.0,9,1,21,,800,1000,,16,389.14415645599365
+97,0.958984375,0.958984375,,0.0,9,1,22,,800,1000,,16,389.95477867126465
+98,0.962890625,0.962890625,,0.0,9,1,23,,800,1000,,16,389.9654402732849
+99,0.95703125,0.95703125,,0.0,9,1,24,,800,1000,,16,389.83215045928955
+100,1.0,1.0,,0.01,6,1,0,,100,1000,,16,11.776980876922607
+101,1.0,1.0,,0.01,6,1,1,,100,1000,,16,11.768988132476807
+102,1.0,1.0,,0.01,6,1,2,,100,1000,,16,11.800522327423096
+103,1.0,1.0,,0.01,6,1,3,,100,1000,,16,11.778608560562134
+104,1.0,1.0,,0.01,6,1,4,,100,1000,,16,11.804924249649048
+105,1.0,1.0,,0.01,6,1,5,,100,1000,,16,11.87699270248413
+106,1.0,1.0,,0.01,6,1,6,,100,1000,,16,11.813494205474854
+107,1.0,1.0,,0.01,6,1,7,,100,1000,,16,11.817170143127441
+108,1.0,1.0,,0.01,6,1,8,,100,1000,,16,11.733030080795288
+109,1.0,1.0,,0.01,6,1,9,,100,1000,,16,11.899771451950073
+110,1.0,1.0,,0.01,6,1,10,,100,1000,,16,11.782000303268433
+111,1.0,1.0,,0.01,6,1,11,,100,1000,,16,11.78898286819458
+112,1.0,1.0,,0.01,6,1,12,,100,1000,,16,11.822817325592041
+113,1.0,1.0,,0.01,6,1,13,,100,1000,,16,11.885993480682373
+114,1.0,1.0,,0.01,6,1,14,,100,1000,,16,11.815990447998047
+115,1.0,1.0,,0.01,6,1,15,,100,1000,,16,11.757014274597168
+116,1.0,1.0,,0.01,6,1,16,,100,1000,,16,11.763991594314575
+117,1.0,1.0,,0.01,6,1,17,,100,1000,,16,11.885558605194092
+118,1.0,1.0,,0.01,6,1,18,,100,1000,,16,11.774724245071411
+119,1.0,1.0,,0.01,6,1,19,,100,1000,,16,11.808991193771362
+120,1.0,1.0,,0.01,6,1,20,,100,1000,,16,11.860454082489014
+121,1.0,1.0,,0.01,6,1,21,,100,1000,,16,11.932001829147339
+122,1.0,1.0,,0.01,6,1,22,,100,1000,,16,11.986681938171387
+123,1.0,1.0,,0.01,6,1,23,,100,1000,,16,11.76001262664795
+124,1.0,1.0,,0.01,6,1,24,,100,1000,,16,11.825994968414307
+125,1.0,1.0,,0.01,7,1,0,,200,1000,,16,32.325329303741455
+126,0.9921875,1.0,,0.01,7,1,1,,200,1000,,16,32.25080418586731
+127,1.0,1.0,,0.01,7,1,2,,200,1000,,16,32.216949701309204
+128,1.0,1.0,,0.01,7,1,3,,200,1000,,16,32.26881265640259
+129,1.0,1.0,,0.01,7,1,4,,200,1000,,16,32.3819625377655
+130,1.0,1.0,,0.01,7,1,5,,200,1000,,16,32.398481369018555
+131,0.9921875,0.9921875,,0.01,7,1,6,,200,1000,,16,32.00610089302063
+132,1.0,1.0,,0.01,7,1,7,,200,1000,,16,32.26021695137024
+133,1.0,1.0,,0.01,7,1,8,,200,1000,,16,32.149068117141724
+134,1.0,1.0,,0.01,7,1,9,,200,1000,,16,32.23104214668274
+135,1.0,1.0,,0.01,7,1,10,,200,1000,,16,32.13652586936951
+136,0.9921875,1.0,,0.01,7,1,11,,200,1000,,16,32.14418029785156
+137,1.0,1.0,,0.01,7,1,12,,200,1000,,16,32.309666872024536
+138,0.9921875,1.0,,0.01,7,1,13,,200,1000,,16,32.187228202819824
+139,1.0,1.0,,0.01,7,1,14,,200,1000,,16,32.02753138542175
+140,1.0,1.0,,0.01,7,1,15,,200,1000,,16,32.24002408981323
+141,1.0,1.0,,0.01,7,1,16,,200,1000,,16,32.20332407951355
+142,1.0,1.0,,0.01,7,1,17,,200,1000,,16,32.17385721206665
+143,1.0,1.0,,0.01,7,1,18,,200,1000,,16,32.21952176094055
+144,1.0,1.0,,0.01,7,1,19,,200,1000,,16,32.18654775619507
+145,1.0,1.0,,0.01,7,1,20,,200,1000,,16,32.34015154838562
+146,1.0,1.0,,0.01,7,1,21,,200,1000,,16,32.22195601463318
+147,0.9921875,0.9921875,,0.01,7,1,22,,200,1000,,16,32.02109122276306
+148,1.0,1.0,,0.01,7,1,23,,200,1000,,16,32.2052481174469
+149,1.0,1.0,,0.01,7,1,24,,200,1000,,16,32.07593560218811
+150,0.9296875,0.9375,,0.01,8,1,0,,400,1000,,16,108.2103431224823
+151,0.9453125,0.953125,,0.01,8,1,1,,400,1000,,16,108.48109817504883
+152,0.94140625,0.94921875,,0.01,8,1,2,,400,1000,,16,108.0911328792572
+153,0.96484375,0.96875,,0.01,8,1,3,,400,1000,,16,108.28572750091553
+154,0.9375,0.94140625,,0.01,8,1,4,,400,1000,,16,108.06026554107666
+155,0.8984375,0.91015625,,0.01,8,1,5,,400,1000,,16,108.1576714515686
+156,0.9453125,0.94921875,,0.01,8,1,6,,400,1000,,16,108.08791399002075
+157,0.93359375,0.94921875,,0.01,8,1,7,,400,1000,,16,108.20874524116516
+158,0.921875,0.9296875,,0.01,8,1,8,,400,1000,,16,108.22286558151245
+159,0.94140625,0.9453125,,0.01,8,1,9,,400,1000,,16,108.20701932907104
+160,0.9765625,0.98046875,,0.01,8,1,10,,400,1000,,16,108.35809469223022
+161,0.91796875,0.921875,,0.01,8,1,11,,400,1000,,16,109.03073644638062
+162,0.9453125,0.94921875,,0.01,8,1,12,,400,1000,,16,108.27721619606018
+163,0.8984375,0.90625,,0.01,8,1,13,,400,1000,,16,108.17321991920471
+164,0.95703125,0.96484375,,0.01,8,1,14,,400,1000,,16,107.9281313419342
+165,0.9453125,0.94921875,,0.01,8,1,15,,400,1000,,16,108.15115356445312
+166,0.953125,0.9609375,,0.01,8,1,16,,400,1000,,16,108.01336693763733
+167,0.953125,0.9609375,,0.01,8,1,17,,400,1000,,16,108.35269522666931
+168,0.93359375,0.9453125,,0.01,8,1,18,,400,1000,,16,107.96164345741272
+169,0.98046875,0.984375,,0.01,8,1,19,,400,1000,,16,108.61579155921936
+170,0.953125,0.953125,,0.01,8,1,20,,400,1000,,16,108.04269075393677
+171,0.95703125,0.97265625,,0.01,8,1,21,,400,1000,,16,108.06843042373657
+172,0.94140625,0.953125,,0.01,8,1,22,,400,1000,,16,107.78897953033447
+173,0.93359375,0.9375,,0.01,8,1,23,,400,1000,,16,108.54243612289429
+174,0.9296875,0.9375,,0.01,8,1,24,,400,1000,,16,106.38762283325195
+175,0.822265625,0.828125,,0.01,9,1,0,,800,1000,,16,388.03406715393066
+176,0.8046875,0.80859375,,0.01,9,1,1,,800,1000,,16,387.1279261112213
+177,0.818359375,0.826171875,,0.01,9,1,2,,800,1000,,16,387.6450369358063
+178,0.796875,0.80859375,,0.01,9,1,3,,800,1000,,16,387.32711124420166
+179,0.837890625,0.841796875,,0.01,9,1,4,,800,1000,,16,387.52873945236206
+180,0.82421875,0.830078125,,0.01,9,1,5,,800,1000,,16,386.7089297771454
+181,0.81640625,0.818359375,,0.01,9,1,6,,800,1000,,16,387.5373866558075
+182,0.837890625,0.841796875,,0.01,9,1,7,,800,1000,,16,387.1973569393158
+183,0.810546875,0.81640625,,0.01,9,1,8,,800,1000,,16,387.4927132129669
+184,0.8203125,0.830078125,,0.01,9,1,9,,800,1000,,16,386.43453335762024
+185,0.83984375,0.84765625,,0.01,9,1,10,,800,1000,,16,387.63319635391235
+186,0.822265625,0.828125,,0.01,9,1,11,,800,1000,,16,386.7897996902466
+187,0.80859375,0.810546875,,0.01,9,1,12,,800,1000,,16,388.43552589416504
+188,0.8125,0.8203125,,0.01,9,1,13,,800,1000,,16,387.35343742370605
+189,0.8046875,0.8125,,0.01,9,1,14,,800,1000,,16,387.41548132896423
+190,0.83984375,0.84765625,,0.01,9,1,15,,800,1000,,16,386.68456745147705
+191,0.798828125,0.8046875,,0.01,9,1,16,,800,1000,,16,388.2384867668152
+192,0.83984375,0.845703125,,0.01,9,1,17,,800,1000,,16,386.7705292701721
+193,0.810546875,0.810546875,,0.01,9,1,18,,800,1000,,16,387.268443107605
+194,0.796875,0.80859375,,0.01,9,1,19,,800,1000,,16,386.64208221435547
+195,0.822265625,0.8203125,,0.01,9,1,20,,800,1000,,16,387.201767206192
+196,0.8203125,0.830078125,,0.01,9,1,21,,800,1000,,16,386.3406262397766
+197,0.818359375,0.822265625,,0.01,9,1,22,,800,1000,,16,386.93768334388733
+198,0.806640625,0.814453125,,0.01,9,1,23,,800,1000,,16,386.9306528568268
+199,0.794921875,0.80859375,,0.01,9,1,24,,800,1000,,16,388.20694375038147
+200,0.828125,0.828125,,0.1,6,1,0,,100,1000,,16,11.74900221824646
+201,0.828125,0.84375,,0.1,6,1,1,,100,1000,,16,11.817988872528076
+202,0.8125,0.796875,,0.1,6,1,2,,100,1000,,16,11.745636940002441
+203,0.8125,0.828125,,0.1,6,1,3,,100,1000,,16,11.69184684753418
+204,0.921875,0.921875,,0.1,6,1,4,,100,1000,,16,11.758424997329712
+205,0.84375,0.828125,,0.1,6,1,5,,100,1000,,16,11.669024229049683
+206,0.84375,0.890625,,0.1,6,1,6,,100,1000,,16,11.746997117996216
+207,0.78125,0.8125,,0.1,6,1,7,,100,1000,,16,11.809061765670776
+208,0.890625,0.875,,0.1,6,1,8,,100,1000,,16,11.741992473602295
+209,0.9375,0.921875,,0.1,6,1,9,,100,1000,,16,11.834017038345337
+210,0.734375,0.78125,,0.1,6,1,10,,100,1000,,16,11.808699607849121
+211,0.828125,0.8125,,0.1,6,1,11,,100,1000,,16,11.708991765975952
+212,0.78125,0.859375,,0.1,6,1,12,,100,1000,,16,11.783540964126587
+213,0.796875,0.796875,,0.1,6,1,13,,100,1000,,16,11.714462518692017
+214,0.84375,0.828125,,0.1,6,1,14,,100,1000,,16,11.835661172866821
+215,0.890625,0.90625,,0.1,6,1,15,,100,1000,,16,11.737992286682129
+216,0.875,0.90625,,0.1,6,1,16,,100,1000,,16,11.779268980026245
+217,0.8125,0.8125,,0.1,6,1,17,,100,1000,,16,11.795350790023804
+218,0.828125,0.859375,,0.1,6,1,18,,100,1000,,16,11.873086929321289
+219,0.828125,0.828125,,0.1,6,1,19,,100,1000,,16,11.679044246673584
+220,0.828125,0.875,,0.1,6,1,20,,100,1000,,16,11.761982917785645
+221,0.75,0.796875,,0.1,6,1,21,,100,1000,,16,11.715840578079224
+222,0.796875,0.859375,,0.1,6,1,22,,100,1000,,16,11.883473873138428
+223,0.8125,0.796875,,0.1,6,1,23,,100,1000,,16,11.895991325378418
+224,0.84375,0.875,,0.1,6,1,24,,100,1000,,16,11.803987503051758
+225,0.6875,0.671875,,0.1,7,1,0,,200,1000,,16,32.38796925544739
+226,0.6796875,0.6796875,,0.1,7,1,1,,200,1000,,16,32.27352857589722
+227,0.59375,0.65625,,0.1,7,1,2,,200,1000,,16,32.153940200805664
+228,0.7109375,0.703125,,0.1,7,1,3,,200,1000,,16,32.17020297050476
+229,0.6953125,0.6953125,,0.1,7,1,4,,200,1000,,16,32.15050554275513
+230,0.671875,0.6640625,,0.1,7,1,5,,200,1000,,16,32.18639945983887
+231,0.7109375,0.703125,,0.1,7,1,6,,200,1000,,16,32.17115354537964
+232,0.640625,0.65625,,0.1,7,1,7,,200,1000,,16,32.16943550109863
+233,0.6875,0.734375,,0.1,7,1,8,,200,1000,,16,32.31579256057739
+234,0.625,0.6953125,,0.1,7,1,9,,200,1000,,16,32.13526916503906
+235,0.6484375,0.6640625,,0.1,7,1,10,,200,1000,,16,32.11432600021362
+236,0.6640625,0.65625,,0.1,7,1,11,,200,1000,,16,32.287309408187866
+237,0.7109375,0.7109375,,0.1,7,1,12,,200,1000,,16,32.06744170188904
+238,0.6875,0.7109375,,0.1,7,1,13,,200,1000,,16,32.7177255153656
+239,0.65625,0.6640625,,0.1,7,1,14,,200,1000,,16,32.04427647590637
+240,0.7109375,0.703125,,0.1,7,1,15,,200,1000,,16,32.21569490432739
+241,0.6796875,0.671875,,0.1,7,1,16,,200,1000,,16,32.210917711257935
+242,0.65625,0.7109375,,0.1,7,1,17,,200,1000,,16,32.13530993461609
+243,0.703125,0.6953125,,0.1,7,1,18,,200,1000,,16,32.03787565231323
+244,0.6875,0.6953125,,0.1,7,1,19,,200,1000,,16,32.1207218170166
+245,0.6796875,0.7109375,,0.1,7,1,20,,200,1000,,16,32.15052127838135
+246,0.71875,0.7109375,,0.1,7,1,21,,200,1000,,16,32.191874265670776
+247,0.6796875,0.6953125,,0.1,7,1,22,,200,1000,,16,32.12848162651062
+248,0.71875,0.7265625,,0.1,7,1,23,,200,1000,,16,32.13089084625244
+249,0.6484375,0.6640625,,0.1,7,1,24,,200,1000,,16,32.358235120773315
+250,0.63671875,0.6328125,,0.1,8,1,0,,400,1000,,16,106.99269962310791
+251,0.58984375,0.61328125,,0.1,8,1,1,,400,1000,,16,107.02747535705566
+252,0.6328125,0.6171875,,0.1,8,1,2,,400,1000,,16,106.7957067489624
+253,0.625,0.62109375,,0.1,8,1,3,,400,1000,,16,106.7676191329956
+254,0.58203125,0.58203125,,0.1,8,1,4,,400,1000,,16,106.51975417137146
+255,0.61328125,0.6171875,,0.1,8,1,5,,400,1000,,16,106.88106632232666
+256,0.546875,0.61328125,,0.1,8,1,6,,400,1000,,16,106.25228571891785
+257,0.55859375,0.578125,,0.1,8,1,7,,400,1000,,16,106.6866569519043
+258,0.58984375,0.59375,,0.1,8,1,8,,400,1000,,16,106.61668157577515
+259,0.58984375,0.59375,,0.1,8,1,9,,400,1000,,16,106.90352988243103
+260,0.61328125,0.609375,,0.1,8,1,10,,400,1000,,16,106.54071736335754
+261,0.61328125,0.59765625,,0.1,8,1,11,,400,1000,,16,106.58031868934631
+262,0.6171875,0.60546875,,0.1,8,1,12,,400,1000,,16,106.581547498703
+263,0.6171875,0.6171875,,0.1,8,1,13,,400,1000,,16,106.93896579742432
+264,0.60546875,0.58984375,,0.1,8,1,14,,400,1000,,16,106.74179720878601
+265,0.671875,0.6640625,,0.1,8,1,15,,400,1000,,16,106.48212313652039
+266,0.62109375,0.62890625,,0.1,8,1,16,,400,1000,,16,106.8958854675293
+267,0.5859375,0.59765625,,0.1,8,1,17,,400,1000,,16,106.85733127593994
+268,0.56640625,0.57421875,,0.1,8,1,18,,400,1000,,16,106.38740134239197
+269,0.62109375,0.62890625,,0.1,8,1,19,,400,1000,,16,106.7304835319519
+270,0.57421875,0.58984375,,0.1,8,1,20,,400,1000,,16,106.79648518562317
+271,0.64453125,0.63671875,,0.1,8,1,21,,400,1000,,16,106.86593008041382
+272,0.62109375,0.62109375,,0.1,8,1,22,,400,1000,,16,106.66032099723816
+273,0.60546875,0.59765625,,0.1,8,1,23,,400,1000,,16,106.59079217910767
+274,0.59765625,0.58203125,,0.1,8,1,24,,400,1000,,16,106.71046710014343
+275,0.53515625,0.5625,,0.1,9,1,0,,800,1000,,16,384.7092580795288
+276,0.5625,0.568359375,,0.1,9,1,1,,800,1000,,16,384.2785243988037
+277,0.564453125,0.56640625,,0.1,9,1,2,,800,1000,,16,386.5039572715759
+278,0.5859375,0.58203125,,0.1,9,1,3,,800,1000,,16,384.27775478363037
+279,0.533203125,0.55859375,,0.1,9,1,4,,800,1000,,16,384.40743589401245
+280,0.552734375,0.5390625,,0.1,9,1,5,,800,1000,,16,384.51814556121826
+281,0.5859375,0.587890625,,0.1,9,1,6,,800,1000,,16,384.76656794548035
+282,0.591796875,0.58984375,,0.1,9,1,7,,800,1000,,16,384.8561408519745
+283,0.55078125,0.548828125,,0.1,9,1,8,,800,1000,,16,385.4239501953125
+284,0.564453125,0.5625,,0.1,9,1,9,,800,1000,,16,384.5137963294983
+285,0.5390625,0.533203125,,0.1,9,1,10,,800,1000,,16,384.50409173965454
+286,0.572265625,0.56640625,,0.1,9,1,11,,800,1000,,16,385.74767422676086
+287,0.53515625,0.53125,,0.1,9,1,12,,800,1000,,16,386.38335824012756
+288,0.58203125,0.56640625,,0.1,9,1,13,,800,1000,,16,384.60641860961914
+289,0.556640625,0.5546875,,0.1,9,1,14,,800,1000,,16,385.56277418136597
+290,0.57421875,0.568359375,,0.1,9,1,15,,800,1000,,16,388.25177574157715
+291,0.556640625,0.5625,,0.1,9,1,16,,800,1000,,16,386.9070234298706
+292,0.564453125,0.544921875,,0.1,9,1,17,,800,1000,,16,385.8026509284973
+293,0.56640625,0.580078125,,0.1,9,1,18,,800,1000,,16,384.9355719089508
+294,0.541015625,0.537109375,,0.1,9,1,19,,800,1000,,16,384.9541754722595
+295,0.521484375,0.53125,,0.1,9,1,20,,800,1000,,16,386.2977328300476
+296,0.533203125,0.564453125,,0.1,9,1,21,,800,1000,,16,384.3903720378876
+297,0.58984375,0.576171875,,0.1,9,1,22,,800,1000,,16,385.84518003463745
+298,0.541015625,0.5625,,0.1,9,1,23,,800,1000,,16,385.06016206741333
+299,0.54296875,0.548828125,,0.1,9,1,24,,800,1000,,16,385.20746088027954
+300,0.6875,0.734375,,0.2,6,1,0,,100,1000,,16,11.701416254043579
+301,0.734375,0.734375,,0.2,6,1,1,,100,1000,,16,11.66155457496643
+302,0.59375,0.703125,,0.2,6,1,2,,100,1000,,16,11.72099232673645
+303,0.765625,0.734375,,0.2,6,1,3,,100,1000,,16,11.768991708755493
+304,0.609375,0.703125,,0.2,6,1,4,,100,1000,,16,11.717772245407104
+305,0.734375,0.734375,,0.2,6,1,5,,100,1000,,16,11.817022323608398
+306,0.640625,0.703125,,0.2,6,1,6,,100,1000,,16,11.740135192871094
+307,0.6875,0.671875,,0.2,6,1,7,,100,1000,,16,11.670768976211548
+308,0.703125,0.734375,,0.2,6,1,8,,100,1000,,16,11.819988012313843
+309,0.640625,0.71875,,0.2,6,1,9,,100,1000,,16,11.71218490600586
+310,0.734375,0.6875,,0.2,6,1,10,,100,1000,,16,11.780304193496704
+311,0.6875,0.6875,,0.2,6,1,11,,100,1000,,16,11.778146028518677
+312,0.71875,0.734375,,0.2,6,1,12,,100,1000,,16,11.749991655349731
+313,0.671875,0.671875,,0.2,6,1,13,,100,1000,,16,11.834990501403809
+314,0.671875,0.640625,,0.2,6,1,14,,100,1000,,16,11.815843343734741
+315,0.6875,0.703125,,0.2,6,1,15,,100,1000,,16,11.702751398086548
+316,0.65625,0.640625,,0.2,6,1,16,,100,1000,,16,11.761118650436401
+317,0.734375,0.71875,,0.2,6,1,17,,100,1000,,16,11.75031852722168
+318,0.546875,0.703125,,0.2,6,1,18,,100,1000,,16,11.905989646911621
+319,0.734375,0.71875,,0.2,6,1,19,,100,1000,,16,11.815394639968872
+320,0.671875,0.6875,,0.2,6,1,20,,100,1000,,16,11.75999116897583
+321,0.71875,0.75,,0.2,6,1,21,,100,1000,,16,11.830982208251953
+322,0.703125,0.6875,,0.2,6,1,22,,100,1000,,16,11.903095483779907
+323,0.6875,0.765625,,0.2,6,1,23,,100,1000,,16,11.756868362426758
+324,0.640625,0.609375,,0.2,6,1,24,,100,1000,,16,11.808886528015137
+325,0.625,0.6171875,,0.2,7,1,0,,200,1000,,16,32.2998480796814
+326,0.6015625,0.6328125,,0.2,7,1,1,,200,1000,,16,32.21591663360596
+327,0.6640625,0.6640625,,0.2,7,1,2,,200,1000,,16,32.292810678482056
+328,0.6015625,0.6328125,,0.2,7,1,3,,200,1000,,16,32.210548400878906
+329,0.6796875,0.6640625,,0.2,7,1,4,,200,1000,,16,32.34899711608887
+330,0.6328125,0.59375,,0.2,7,1,5,,200,1000,,16,32.249956369400024
+331,0.59375,0.640625,,0.2,7,1,6,,200,1000,,16,32.010857820510864
+332,0.65625,0.640625,,0.2,7,1,7,,200,1000,,16,32.266817808151245
+333,0.5859375,0.609375,,0.2,7,1,8,,200,1000,,16,32.204946756362915
+334,0.609375,0.578125,,0.2,7,1,9,,200,1000,,16,32.13727283477783
+335,0.640625,0.65625,,0.2,7,1,10,,200,1000,,16,32.14590930938721
+336,0.5390625,0.609375,,0.2,7,1,11,,200,1000,,16,32.249958992004395
+337,0.6171875,0.6171875,,0.2,7,1,12,,200,1000,,16,32.47429418563843
+338,0.5546875,0.59375,,0.2,7,1,13,,200,1000,,16,32.32082533836365
+339,0.6171875,0.6171875,,0.2,7,1,14,,200,1000,,16,32.045756340026855
+340,0.5546875,0.5625,,0.2,7,1,15,,200,1000,,16,32.328510999679565
+341,0.5625,0.609375,,0.2,7,1,16,,200,1000,,16,32.218994140625
+342,0.609375,0.609375,,0.2,7,1,17,,200,1000,,16,32.25464153289795
+343,0.6171875,0.59375,,0.2,7,1,18,,200,1000,,16,32.24036383628845
+344,0.5703125,0.59375,,0.2,7,1,19,,200,1000,,16,32.23615312576294
+345,0.6953125,0.65625,,0.2,7,1,20,,200,1000,,16,32.35885190963745
+346,0.6640625,0.6484375,,0.2,7,1,21,,200,1000,,16,32.21221041679382
+347,0.59375,0.5859375,,0.2,7,1,22,,200,1000,,16,32.23531746864319
+348,0.5625,0.609375,,0.2,7,1,23,,200,1000,,16,32.313210010528564
+349,0.625,0.6328125,,0.2,7,1,24,,200,1000,,16,32.24318480491638
+350,0.5703125,0.58203125,,0.2,8,1,0,,400,1000,,16,107.28806209564209
+351,0.54296875,0.56640625,,0.2,8,1,1,,400,1000,,16,107.38576412200928
+352,0.5703125,0.5859375,,0.2,8,1,2,,400,1000,,16,107.79581212997437
+353,0.54296875,0.55078125,,0.2,8,1,3,,400,1000,,16,108.65942645072937
+354,0.5703125,0.55078125,,0.2,8,1,4,,400,1000,,16,108.61456561088562
+355,0.53515625,0.53515625,,0.2,8,1,5,,400,1000,,16,108.61366009712219
+356,0.578125,0.546875,,0.2,8,1,6,,400,1000,,16,108.25452470779419
+357,0.640625,0.640625,,0.2,8,1,7,,400,1000,,16,108.33169627189636
+358,0.546875,0.5546875,,0.2,8,1,8,,400,1000,,16,107.68780088424683
+359,0.54296875,0.55078125,,0.2,8,1,9,,400,1000,,16,108.41348934173584
+360,0.578125,0.57421875,,0.2,8,1,10,,400,1000,,16,108.14707493782043
+361,0.59375,0.578125,,0.2,8,1,11,,400,1000,,16,108.11785626411438
+362,0.5625,0.5546875,,0.2,8,1,12,,400,1000,,16,108.2481300830841
+363,0.5703125,0.55859375,,0.2,8,1,13,,400,1000,,16,107.91888427734375
+364,0.56640625,0.59375,,0.2,8,1,14,,400,1000,,16,108.15670943260193
+365,0.4921875,0.61328125,,0.2,8,1,15,,400,1000,,16,108.45635175704956
+366,0.5859375,0.56640625,,0.2,8,1,16,,400,1000,,16,108.44004821777344
+367,0.5234375,0.52734375,,0.2,8,1,17,,400,1000,,16,352.06099104881287
+368,0.5390625,0.58203125,,0.2,8,1,18,,400,1000,,16,109.71851873397827
+369,0.5234375,0.5546875,,0.2,8,1,19,,400,1000,,16,108.64684748649597
+370,0.5546875,0.56640625,,0.2,8,1,20,,400,1000,,16,107.61448860168457
+371,0.5546875,0.53125,,0.2,8,1,21,,400,1000,,16,107.85792946815491
+372,0.55859375,0.58203125,,0.2,8,1,22,,400,1000,,16,107.12293410301208
+373,0.57421875,0.5703125,,0.2,8,1,23,,400,1000,,16,107.20619893074036
+374,0.5390625,0.53125,,0.2,8,1,24,,400,1000,,16,107.44035863876343
+375,0.5390625,0.5390625,,0.2,9,1,0,,800,1000,,16,390.31168723106384
+376,0.5234375,0.521484375,,0.2,9,1,1,,800,1000,,16,389.7224202156067
+377,0.55859375,0.548828125,,0.2,9,1,2,,800,1000,,16,389.4500229358673
+378,0.5625,0.5390625,,0.2,9,1,3,,800,1000,,16,388.94454193115234
+379,0.56640625,0.564453125,,0.2,9,1,4,,800,1000,,16,388.32307839393616
+380,0.529296875,0.513671875,,0.2,9,1,5,,800,1000,,16,388.217209815979
+381,0.51171875,0.517578125,,0.2,9,1,6,,800,1000,,16,388.2096018791199
+382,0.53125,0.529296875,,0.2,9,1,7,,800,1000,,16,389.69890832901
+383,0.5,0.515625,,0.2,9,1,8,,800,1000,,16,389.9812219142914
+384,0.52734375,0.53125,,0.2,9,1,9,,800,1000,,16,388.92282152175903
+385,0.53515625,0.51953125,,0.2,9,1,10,,800,1000,,16,387.8685460090637
+386,0.54296875,0.537109375,,0.2,9,1,11,,800,1000,,16,388.4364893436432
+387,0.537109375,0.55078125,,0.2,9,1,12,,800,1000,,16,389.07747411727905
+388,0.55078125,0.552734375,,0.2,9,1,13,,800,1000,,16,389.38850474357605
+389,0.521484375,0.5625,,0.2,9,1,14,,800,1000,,16,388.79180240631104
+390,0.58203125,0.583984375,,0.2,9,1,15,,800,1000,,16,388.0411651134491
+391,0.552734375,0.556640625,,0.2,9,1,16,,800,1000,,16,389.47057366371155
+392,0.51953125,0.5078125,,0.2,9,1,17,,800,1000,,16,388.78166127204895
+393,0.5859375,0.578125,,0.2,9,1,18,,800,1000,,16,388.2980463504791
+394,0.52734375,0.5234375,,0.2,9,1,19,,800,1000,,16,390.4278588294983
+395,0.5546875,0.546875,,0.2,9,1,20,,800,1000,,16,388.9239709377289
+396,0.515625,0.509765625,,0.2,9,1,21,,800,1000,,16,388.58339262008667
+397,0.5390625,0.533203125,,0.2,9,1,22,,800,1000,,16,388.06998682022095
+398,0.51171875,0.51171875,,0.2,9,1,23,,800,1000,,16,389.3240246772766
+399,0.517578125,0.515625,,0.2,9,1,24,,800,1000,,16,391.7366578578949
diff --git a/experiments/bench/oneMax/data/mu+lambdaUCB-pop=100-budget=0.csv b/experiments/bench/oneMax/data/mu+lambdaUCB-pop=100-budget=0.csv
new file mode 100644
index 0000000000000000000000000000000000000000..164f2faa24ad8ce330af0c23e5ba74f4029291f8
--- /dev/null
+++ b/experiments/bench/oneMax/data/mu+lambdaUCB-pop=100-budget=0.csv
@@ -0,0 +1,301 @@
+,best_pop,best_hof,best_arm,std,dim,n_eval,run_number,UCB_sigma,ngen,mu,lambda,n_thread,time
+0,1.0,1.0,1.0,0.01,6,1,0,,100,100,,16,4.980448246002197
+1,1.0,1.0,1.0,0.01,6,1,1,,100,100,,16,4.759990453720093
+2,0.984375,0.984375,0.984375,0.01,6,1,2,,100,100,,16,5.5615739822387695
+3,1.0,1.0,1.0,0.01,6,1,3,,100,100,,16,4.742998838424683
+4,1.0,1.0,0.96875,0.01,6,1,4,,100,100,,16,4.729988098144531
+5,0.984375,1.0,0.984375,0.01,6,1,5,,100,100,,16,4.782660484313965
+6,0.984375,1.0,0.984375,0.01,6,1,6,,100,100,,16,4.856022357940674
+7,0.96875,0.984375,0.96875,0.01,6,1,7,,100,100,,16,4.741023063659668
+8,0.984375,1.0,0.96875,0.01,6,1,8,,100,100,,16,4.744164943695068
+9,0.984375,1.0,0.984375,0.01,6,1,9,,100,100,,16,4.846987247467041
+10,1.0,1.0,1.0,0.01,6,1,10,,100,100,,16,4.756989479064941
+11,1.0,1.0,1.0,0.01,6,1,11,,100,100,,16,4.743991851806641
+12,1.0,1.0,0.9375,0.01,6,1,12,,100,100,,16,4.72600245475769
+13,0.96875,0.984375,0.96875,0.01,6,1,13,,100,100,,16,4.767002582550049
+14,1.0,1.0,0.984375,0.01,6,1,14,,100,100,,16,4.734147548675537
+15,0.984375,1.0,0.984375,0.01,6,1,15,,100,100,,16,4.740192651748657
+16,1.0,1.0,1.0,0.01,6,1,16,,100,100,,16,4.851998329162598
+17,1.0,1.0,1.0,0.01,6,1,17,,100,100,,16,4.724990606307983
+18,0.96875,1.0,0.96875,0.01,6,1,18,,100,100,,16,4.743017673492432
+19,1.0,1.0,1.0,0.01,6,1,19,,100,100,,16,4.815401554107666
+20,1.0,1.0,1.0,0.01,6,1,20,,100,100,,16,4.732693672180176
+21,1.0,1.0,1.0,0.01,6,1,21,,100,100,,16,4.7564568519592285
+22,1.0,1.0,1.0,0.01,6,1,22,,100,100,,16,4.769992828369141
+23,1.0,1.0,0.953125,0.01,6,1,23,,100,100,,16,4.787449598312378
+24,0.984375,1.0,0.953125,0.01,6,1,24,,100,100,,16,4.764990329742432
+25,0.9375,0.9453125,0.9296875,0.01,7,1,0,,200,100,,16,9.205997228622437
+26,0.9296875,0.9375,0.8515625,0.01,7,1,1,,200,100,,16,9.190989971160889
+27,0.8984375,0.921875,0.8984375,0.01,7,1,2,,200,100,,16,9.271998167037964
+28,0.921875,0.9296875,0.921875,0.01,7,1,3,,200,100,,16,9.191993236541748
+29,0.9453125,0.953125,0.9296875,0.01,7,1,4,,200,100,,16,9.188127994537354
+30,0.9375,0.953125,0.8984375,0.01,7,1,5,,200,100,,16,9.153006315231323
+31,0.9140625,0.9296875,0.9140625,0.01,7,1,6,,200,100,,16,9.18513798713684
+32,0.9296875,0.9375,0.9296875,0.01,7,1,7,,200,100,,16,9.046038627624512
+33,0.9296875,0.953125,0.890625,0.01,7,1,8,,200,100,,16,9.199012041091919
+34,0.9375,0.953125,0.9375,0.01,7,1,9,,200,100,,16,9.263791561126709
+35,0.90625,0.9296875,0.84375,0.01,7,1,10,,200,100,,16,9.18723726272583
+36,0.9296875,0.9375,0.9296875,0.01,7,1,11,,200,100,,16,9.06900691986084
+37,0.8828125,0.90625,0.8828125,0.01,7,1,12,,200,100,,16,9.161990880966187
+38,0.9375,0.953125,0.9375,0.01,7,1,13,,200,100,,16,9.110997438430786
+39,0.953125,0.9609375,0.953125,0.01,7,1,14,,200,100,,16,9.172149658203125
+40,0.9296875,0.953125,0.9296875,0.01,7,1,15,,200,100,,16,9.134430885314941
+41,0.9375,0.953125,0.8515625,0.01,7,1,16,,200,100,,16,9.331418991088867
+42,0.921875,0.9375,0.921875,0.01,7,1,17,,200,100,,16,9.136552810668945
+43,0.90625,0.921875,0.90625,0.01,7,1,18,,200,100,,16,9.193666219711304
+44,0.921875,0.9375,0.921875,0.01,7,1,19,,200,100,,16,9.170022010803223
+45,0.90625,0.9296875,0.90625,0.01,7,1,20,,200,100,,16,9.16012716293335
+46,0.9375,0.953125,0.8984375,0.01,7,1,21,,200,100,,16,9.139999628067017
+47,0.890625,0.8984375,0.875,0.01,7,1,22,,200,100,,16,9.079585552215576
+48,0.921875,0.9296875,0.921875,0.01,7,1,23,,200,100,,16,9.150581359863281
+49,0.9296875,0.9296875,0.9140625,0.01,7,1,24,,200,100,,16,9.159009456634521
+50,0.8125,0.828125,0.80078125,0.01,8,1,0,,400,100,,16,23.852522373199463
+51,0.80078125,0.80859375,0.796875,0.01,8,1,1,,400,100,,16,23.779499769210815
+52,0.83203125,0.84375,0.83203125,0.01,8,1,2,,400,100,,16,24.753897666931152
+53,0.8125,0.828125,0.8125,0.01,8,1,3,,400,100,,16,24.567751169204712
+54,0.796875,0.80859375,0.79296875,0.01,8,1,4,,400,100,,16,24.18292236328125
+55,0.81640625,0.828125,0.79296875,0.01,8,1,5,,400,100,,16,24.25236988067627
+56,0.78125,0.80859375,0.75,0.01,8,1,6,,400,100,,16,23.954268217086792
+57,0.7578125,0.77734375,0.7578125,0.01,8,1,7,,400,100,,16,23.710009336471558
+58,0.81640625,0.828125,0.75390625,0.01,8,1,8,,400,100,,16,23.71167254447937
+59,0.8203125,0.82421875,0.80859375,0.01,8,1,9,,400,100,,16,24.027971982955933
+60,0.78125,0.7890625,0.73828125,0.01,8,1,10,,400,100,,16,23.579237461090088
+61,0.828125,0.83203125,0.8203125,0.01,8,1,11,,400,100,,16,24.02550172805786
+62,0.7734375,0.7890625,0.7578125,0.01,8,1,12,,400,100,,16,23.631338119506836
+63,0.80859375,0.8125,0.77734375,0.01,8,1,13,,400,100,,16,24.005136251449585
+64,0.8203125,0.8359375,0.8203125,0.01,8,1,14,,400,100,,16,24.009179830551147
+65,0.8203125,0.83984375,0.7890625,0.01,8,1,15,,400,100,,16,24.0573308467865
+66,0.80078125,0.81640625,0.77734375,0.01,8,1,16,,400,100,,16,23.86429452896118
+67,0.80859375,0.828125,0.80859375,0.01,8,1,17,,400,100,,16,24.37394094467163
+68,0.765625,0.7890625,0.73046875,0.01,8,1,18,,400,100,,16,23.78065061569214
+69,0.8203125,0.8359375,0.8203125,0.01,8,1,19,,400,100,,16,24.01465153694153
+70,0.7734375,0.8046875,0.7578125,0.01,8,1,20,,400,100,,16,23.757123947143555
+71,0.83203125,0.84765625,0.83203125,0.01,8,1,21,,400,100,,16,24.038951635360718
+72,0.78125,0.8046875,0.73828125,0.01,8,1,22,,400,100,,16,23.829625844955444
+73,0.79296875,0.80859375,0.78515625,0.01,8,1,23,,400,100,,16,23.75740671157837
+74,0.828125,0.84375,0.828125,0.01,8,1,24,,400,100,,16,24.432183980941772
+75,0.6875,0.701171875,0.6875,0.01,9,1,0,,800,100,,16,77.01383996009827
+76,0.705078125,0.71875,0.705078125,0.01,9,1,1,,800,100,,16,77.43781471252441
+77,0.728515625,0.744140625,0.728515625,0.01,9,1,2,,800,100,,16,78.48984146118164
+78,0.69140625,0.701171875,0.6875,0.01,9,1,3,,800,100,,16,76.56613445281982
+79,0.689453125,0.701171875,0.689453125,0.01,9,1,4,,800,100,,16,76.21025085449219
+80,0.73828125,0.755859375,0.73828125,0.01,9,1,5,,800,100,,16,78.6970751285553
+81,0.69921875,0.70703125,0.69140625,0.01,9,1,6,,800,100,,16,76.9853892326355
+82,0.703125,0.720703125,0.6796875,0.01,9,1,7,,800,100,,16,77.40980648994446
+83,0.701171875,0.71484375,0.669921875,0.01,9,1,8,,800,100,,16,77.3012068271637
+84,0.685546875,0.697265625,0.685546875,0.01,9,1,9,,800,100,,16,75.76248025894165
+85,0.689453125,0.69921875,0.662109375,0.01,9,1,10,,800,100,,16,76.41937017440796
+86,0.638671875,0.66015625,0.6328125,0.01,9,1,11,,800,100,,16,69.45286536216736
+87,0.701171875,0.716796875,0.701171875,0.01,9,1,12,,800,100,,16,77.21794891357422
+88,0.681640625,0.6953125,0.681640625,0.01,9,1,13,,800,100,,16,74.76160049438477
+89,0.708984375,0.720703125,0.708984375,0.01,9,1,14,,800,100,,16,77.4929473400116
+90,0.708984375,0.72265625,0.70703125,0.01,9,1,15,,800,100,,16,76.43168926239014
+91,0.677734375,0.69140625,0.677734375,0.01,9,1,16,,800,100,,16,75.18170523643494
+92,0.69140625,0.71484375,0.671875,0.01,9,1,17,,800,100,,16,75.61455607414246
+93,0.7109375,0.720703125,0.7109375,0.01,9,1,18,,800,100,,16,76.87898397445679
+94,0.6796875,0.69140625,0.658203125,0.01,9,1,19,,800,100,,16,73.97235441207886
+95,0.693359375,0.7109375,0.658203125,0.01,9,1,20,,800,100,,16,76.82054662704468
+96,0.697265625,0.708984375,0.693359375,0.01,9,1,21,,800,100,,16,75.99994730949402
+97,0.701171875,0.705078125,0.677734375,0.01,9,1,22,,800,100,,16,76.04358863830566
+98,0.71484375,0.724609375,0.693359375,0.01,9,1,23,,800,100,,16,77.8931667804718
+99,0.728515625,0.73046875,0.720703125,0.01,9,1,24,,800,100,,16,77.45727872848511
+100,0.75,0.78125,0.734375,0.1,6,1,0,,100,100,,16,4.563004732131958
+101,0.75,0.78125,0.703125,0.1,6,1,1,,100,100,,16,4.572994947433472
+102,0.765625,0.78125,0.734375,0.1,6,1,2,,100,100,,16,4.648991346359253
+103,0.78125,0.84375,0.6875,0.1,6,1,3,,100,100,,16,4.613989591598511
+104,0.71875,0.84375,0.65625,0.1,6,1,4,,100,100,,16,4.572988271713257
+105,0.734375,0.765625,0.703125,0.1,6,1,5,,100,100,,16,4.632523775100708
+106,0.734375,0.765625,0.65625,0.1,6,1,6,,100,100,,16,4.608011722564697
+107,0.6875,0.71875,0.671875,0.1,6,1,7,,100,100,,16,4.632985591888428
+108,0.703125,0.734375,0.65625,0.1,6,1,8,,100,100,,16,4.595003128051758
+109,0.71875,0.75,0.6875,0.1,6,1,9,,100,100,,16,4.674993991851807
+110,0.78125,0.828125,0.71875,0.1,6,1,10,,100,100,,16,4.64998197555542
+111,0.734375,0.78125,0.71875,0.1,6,1,11,,100,100,,16,4.5969836711883545
+112,0.65625,0.6875,0.578125,0.1,6,1,12,,100,100,,16,4.572172403335571
+113,0.6875,0.734375,0.640625,0.1,6,1,13,,100,100,,16,4.597990274429321
+114,0.765625,0.75,0.75,0.1,6,1,14,,100,100,,16,4.6209940910339355
+115,0.71875,0.765625,0.6875,0.1,6,1,15,,100,100,,16,4.629119396209717
+116,0.59375,0.71875,0.546875,0.1,6,1,16,,100,100,,16,4.637003183364868
+117,0.671875,0.71875,0.546875,0.1,6,1,17,,100,100,,16,4.609003305435181
+118,0.8125,0.84375,0.8125,0.1,6,1,18,,100,100,,16,4.649075269699097
+119,0.796875,0.8125,0.796875,0.1,6,1,19,,100,100,,16,4.658528089523315
+120,0.671875,0.671875,0.65625,0.1,6,1,20,,100,100,,16,4.607994079589844
+121,0.703125,0.75,0.6875,0.1,6,1,21,,100,100,,16,4.637006044387817
+122,0.78125,0.828125,0.765625,0.1,6,1,22,,100,100,,16,4.636988162994385
+123,0.703125,0.796875,0.6875,0.1,6,1,23,,100,100,,16,4.620990753173828
+124,0.796875,0.828125,0.765625,0.1,6,1,24,,100,100,,16,4.6280012130737305
+125,0.6796875,0.7109375,0.640625,0.1,7,1,0,,200,100,,16,8.664182424545288
+126,0.59375,0.625,0.5546875,0.1,7,1,1,,200,100,,16,8.383000135421753
+127,0.578125,0.6484375,0.5078125,0.1,7,1,2,,200,100,,16,8.533820867538452
+128,0.5234375,0.59375,0.484375,0.1,7,1,3,,200,100,,16,8.37065839767456
+129,0.734375,0.734375,0.703125,0.1,7,1,4,,200,100,,16,8.578346014022827
+130,0.6484375,0.6640625,0.625,0.1,7,1,5,,200,100,,16,8.57085919380188
+131,0.609375,0.6328125,0.6015625,0.1,7,1,6,,200,100,,16,8.514684915542603
+132,0.609375,0.625,0.546875,0.1,7,1,7,,200,100,,16,8.439126253128052
+133,0.6015625,0.640625,0.5625,0.1,7,1,8,,200,100,,16,8.637381792068481
+134,0.5546875,0.6171875,0.5390625,0.1,7,1,9,,200,100,,16,8.40501594543457
+135,0.6328125,0.640625,0.6328125,0.1,7,1,10,,200,100,,16,8.664458274841309
+136,0.640625,0.6875,0.625,0.1,7,1,11,,200,100,,16,8.454986810684204
+137,0.6328125,0.6328125,0.609375,0.1,7,1,12,,200,100,,16,8.595999956130981
+138,0.640625,0.65625,0.609375,0.1,7,1,13,,200,100,,16,8.522995710372925
+139,0.609375,0.609375,0.5859375,0.1,7,1,14,,200,100,,16,8.537482500076294
+140,0.640625,0.6875,0.625,0.1,7,1,15,,200,100,,16,8.563023090362549
+141,0.5703125,0.640625,0.5625,0.1,7,1,16,,200,100,,16,8.520997762680054
+142,0.625,0.6875,0.5625,0.1,7,1,17,,200,100,,16,8.547710180282593
+143,0.6171875,0.640625,0.6015625,0.1,7,1,18,,200,100,,16,8.624759435653687
+144,0.6171875,0.640625,0.6015625,0.1,7,1,19,,200,100,,16,8.477989435195923
+145,0.625,0.6953125,0.625,0.1,7,1,20,,200,100,,16,8.499011516571045
+146,0.625,0.640625,0.6171875,0.1,7,1,21,,200,100,,16,8.573191404342651
+147,0.625,0.671875,0.609375,0.1,7,1,22,,200,100,,16,8.5618736743927
+148,0.5390625,0.609375,0.5234375,0.1,7,1,23,,200,100,,16,8.628991842269897
+149,0.6328125,0.65625,0.640625,0.1,7,1,24,,200,100,,16,8.604495763778687
+150,0.5625,0.55859375,0.5390625,0.1,8,1,0,,400,100,,16,21.633991956710815
+151,0.52734375,0.5390625,0.51171875,0.1,8,1,1,,400,100,,16,21.52886939048767
+152,0.61328125,0.625,0.62109375,0.1,8,1,2,,400,100,,16,21.962021350860596
+153,0.59765625,0.640625,0.5859375,0.1,8,1,3,,400,100,,16,21.79739212989807
+154,0.5703125,0.59765625,0.578125,0.1,8,1,4,,400,100,,16,21.61724042892456
+155,0.59765625,0.60546875,0.5859375,0.1,8,1,5,,400,100,,16,21.87463641166687
+156,0.57421875,0.57421875,0.56640625,0.1,8,1,6,,400,100,,16,21.595513343811035
+157,0.5859375,0.6015625,0.56640625,0.1,8,1,7,,400,100,,16,21.57936692237854
+158,0.53125,0.5625,0.5078125,0.1,8,1,8,,400,100,,16,21.46367073059082
+159,0.56640625,0.59375,0.56640625,0.1,8,1,9,,400,100,,16,21.664541244506836
+160,0.61328125,0.609375,0.59765625,0.1,8,1,10,,400,100,,16,21.670549392700195
+161,0.57421875,0.5859375,0.55859375,0.1,8,1,11,,400,100,,16,21.8076229095459
+162,0.55078125,0.5546875,0.53515625,0.1,8,1,12,,400,100,,16,21.52197504043579
+163,0.578125,0.578125,0.5625,0.1,8,1,13,,400,100,,16,21.65594482421875
+164,0.609375,0.62890625,0.58203125,0.1,8,1,14,,400,100,,16,21.49161958694458
+165,0.54296875,0.54296875,0.51953125,0.1,8,1,15,,400,100,,16,21.42186737060547
+166,0.5,0.50390625,0.46875,0.1,8,1,16,,400,100,,16,21.42844820022583
+167,0.57421875,0.58203125,0.55859375,0.1,8,1,17,,400,100,,16,21.610957145690918
+168,0.61328125,0.61328125,0.58984375,0.1,8,1,18,,400,100,,16,21.595658540725708
+169,0.5859375,0.6015625,0.57421875,0.1,8,1,19,,400,100,,16,21.649583339691162
+170,0.6015625,0.60546875,0.58203125,0.1,8,1,20,,400,100,,16,21.38869309425354
+171,0.58984375,0.58984375,0.53515625,0.1,8,1,21,,400,100,,16,21.612898588180542
+172,0.5703125,0.58984375,0.5546875,0.1,8,1,22,,400,100,,16,21.478989839553833
+173,0.51171875,0.55859375,0.5078125,0.1,8,1,23,,400,100,,16,21.404143810272217
+174,0.515625,0.59375,0.515625,0.1,8,1,24,,400,100,,16,21.305704593658447
+175,0.515625,0.529296875,0.51953125,0.1,9,1,0,,800,100,,16,68.81816148757935
+176,0.5390625,0.5546875,0.529296875,0.1,9,1,1,,800,100,,16,68.70973563194275
+177,0.537109375,0.556640625,0.521484375,0.1,9,1,2,,800,100,,16,68.56006169319153
+178,0.548828125,0.544921875,0.517578125,0.1,9,1,3,,800,100,,16,68.6442186832428
+179,0.564453125,0.583984375,0.546875,0.1,9,1,4,,800,100,,16,68.89895343780518
+180,0.552734375,0.5546875,0.552734375,0.1,9,1,5,,800,100,,16,68.60347056388855
+181,0.55078125,0.55078125,0.517578125,0.1,9,1,6,,800,100,,16,69.0507881641388
+182,0.55859375,0.564453125,0.54296875,0.1,9,1,7,,800,100,,16,68.72424507141113
+183,0.55859375,0.5625,0.544921875,0.1,9,1,8,,800,100,,16,68.51149725914001
+184,0.5234375,0.529296875,0.5078125,0.1,9,1,9,,800,100,,16,68.01511359214783
+185,0.572265625,0.580078125,0.5625,0.1,9,1,10,,800,100,,16,68.79526853561401
+186,0.513671875,0.541015625,0.50390625,0.1,9,1,11,,800,100,,16,68.00836420059204
+187,0.544921875,0.556640625,0.533203125,0.1,9,1,12,,800,100,,16,68.32961225509644
+188,0.56640625,0.58203125,0.56640625,0.1,9,1,13,,800,100,,16,68.79878187179565
+189,0.548828125,0.55859375,0.5234375,0.1,9,1,14,,800,100,,16,68.48036980628967
+190,0.552734375,0.5546875,0.52734375,0.1,9,1,15,,800,100,,16,68.0496551990509
+191,0.537109375,0.578125,0.529296875,0.1,9,1,16,,800,100,,16,67.91076350212097
+192,0.541015625,0.548828125,0.517578125,0.1,9,1,17,,800,100,,16,68.49403190612793
+193,0.537109375,0.556640625,0.5234375,0.1,9,1,18,,800,100,,16,68.3828558921814
+194,0.54296875,0.5546875,0.541015625,0.1,9,1,19,,800,100,,16,68.47456097602844
+195,0.52734375,0.533203125,0.513671875,0.1,9,1,20,,800,100,,16,68.25948023796082
+196,0.529296875,0.529296875,0.515625,0.1,9,1,21,,800,100,,16,68.55234456062317
+197,0.54296875,0.556640625,0.51953125,0.1,9,1,22,,800,100,,16,68.61861181259155
+198,0.53515625,0.548828125,0.517578125,0.1,9,1,23,,800,100,,16,68.47465062141418
+199,0.533203125,0.5390625,0.5234375,0.1,9,1,24,,800,100,,16,68.43874669075012
+200,0.578125,0.609375,0.546875,0.2,6,1,0,,100,100,,16,4.539994239807129
+201,0.640625,0.6875,0.640625,0.2,6,1,1,,100,100,,16,4.57499361038208
+202,0.625,0.6875,0.625,0.2,6,1,2,,100,100,,16,4.56500768661499
+203,0.578125,0.609375,0.484375,0.2,6,1,3,,100,100,,16,4.690549373626709
+204,0.640625,0.625,0.59375,0.2,6,1,4,,100,100,,16,4.577438116073608
+205,0.609375,0.6875,0.5625,0.2,6,1,5,,100,100,,16,4.591012477874756
+206,0.671875,0.703125,0.640625,0.2,6,1,6,,100,100,,16,4.5940001010894775
+207,0.734375,0.734375,0.703125,0.2,6,1,7,,100,100,,16,4.604281187057495
+208,0.71875,0.6875,0.640625,0.2,6,1,8,,100,100,,16,4.587002515792847
+209,0.625,0.671875,0.578125,0.2,6,1,9,,100,100,,16,4.589001655578613
+210,0.65625,0.6875,0.609375,0.2,6,1,10,,100,100,,16,4.6370017528533936
+211,0.609375,0.6875,0.609375,0.2,6,1,11,,100,100,,16,4.571130752563477
+212,0.59375,0.65625,0.578125,0.2,6,1,12,,100,100,,16,4.621990203857422
+213,0.609375,0.625,0.546875,0.2,6,1,13,,100,100,,16,4.680999517440796
+214,0.625,0.6875,0.578125,0.2,6,1,14,,100,100,,16,4.593001842498779
+215,0.546875,0.65625,0.484375,0.2,6,1,15,,100,100,,16,4.584329128265381
+216,0.65625,0.6875,0.609375,0.2,6,1,16,,100,100,,16,4.5789971351623535
+217,0.546875,0.65625,0.515625,0.2,6,1,17,,100,100,,16,4.613228797912598
+218,0.609375,0.609375,0.5625,0.2,6,1,18,,100,100,,16,4.585999488830566
+219,0.640625,0.671875,0.609375,0.2,6,1,19,,100,100,,16,4.614007234573364
+220,0.609375,0.65625,0.609375,0.2,6,1,20,,100,100,,16,4.673997402191162
+221,0.65625,0.6875,0.625,0.2,6,1,21,,100,100,,16,4.616999626159668
+222,0.640625,0.671875,0.59375,0.2,6,1,22,,100,100,,16,4.589999675750732
+223,0.578125,0.625,0.53125,0.2,6,1,23,,100,100,,16,4.584807872772217
+224,0.65625,0.671875,0.625,0.2,6,1,24,,100,100,,16,4.590996503829956
+225,0.59375,0.6484375,0.578125,0.2,7,1,0,,200,100,,16,8.552433729171753
+226,0.5703125,0.5546875,0.5234375,0.2,7,1,1,,200,100,,16,8.556010961532593
+227,0.53125,0.5625,0.4921875,0.2,7,1,2,,200,100,,16,8.505558490753174
+228,0.59375,0.59375,0.5859375,0.2,7,1,3,,200,100,,16,8.547420263290405
+229,0.5,0.5390625,0.46875,0.2,7,1,4,,200,100,,16,8.480254888534546
+230,0.5546875,0.59375,0.5078125,0.2,7,1,5,,200,100,,16,8.479989528656006
+231,0.5859375,0.5859375,0.546875,0.2,7,1,6,,200,100,,16,8.522372722625732
+232,0.609375,0.625,0.59375,0.2,7,1,7,,200,100,,16,8.468993186950684
+233,0.6328125,0.625,0.5859375,0.2,7,1,8,,200,100,,16,8.518668174743652
+234,0.65625,0.640625,0.5625,0.2,7,1,9,,200,100,,16,8.529557228088379
+235,0.6171875,0.625,0.5859375,0.2,7,1,10,,200,100,,16,8.52673602104187
+236,0.515625,0.6328125,0.4609375,0.2,7,1,11,,200,100,,16,8.384892463684082
+237,0.671875,0.6640625,0.6484375,0.2,7,1,12,,200,100,,16,8.493431806564331
+238,0.5546875,0.65625,0.5546875,0.2,7,1,13,,200,100,,16,8.392533779144287
+239,0.625,0.609375,0.578125,0.2,7,1,14,,200,100,,16,8.61808729171753
+240,0.640625,0.6484375,0.609375,0.2,7,1,15,,200,100,,16,8.560014009475708
+241,0.5546875,0.578125,0.515625,0.2,7,1,16,,200,100,,16,8.6225106716156
+242,0.59375,0.5859375,0.53125,0.2,7,1,17,,200,100,,16,8.466983079910278
+243,0.546875,0.609375,0.5234375,0.2,7,1,18,,200,100,,16,8.54148530960083
+244,0.6015625,0.6015625,0.5703125,0.2,7,1,19,,200,100,,16,8.493003368377686
+245,0.4921875,0.5859375,0.4609375,0.2,7,1,20,,200,100,,16,8.40574049949646
+246,0.5546875,0.5859375,0.5390625,0.2,7,1,21,,200,100,,16,8.546997785568237
+247,0.5390625,0.59375,0.53125,0.2,7,1,22,,200,100,,16,8.426892042160034
+248,0.5703125,0.59375,0.5625,0.2,7,1,23,,200,100,,16,8.534531116485596
+249,0.515625,0.6015625,0.5078125,0.2,7,1,24,,200,100,,16,8.485002994537354
+250,0.56640625,0.55078125,0.53125,0.2,8,1,0,,400,100,,16,21.661521196365356
+251,0.5625,0.5859375,0.5546875,0.2,8,1,1,,400,100,,16,21.64159059524536
+252,0.53515625,0.54296875,0.48828125,0.2,8,1,2,,400,100,,16,21.66751265525818
+253,0.578125,0.5703125,0.55078125,0.2,8,1,3,,400,100,,16,21.72870922088623
+254,0.57421875,0.59765625,0.53125,0.2,8,1,4,,400,100,,16,21.58298659324646
+255,0.53125,0.54296875,0.50390625,0.2,8,1,5,,400,100,,16,21.66246247291565
+256,0.57421875,0.60546875,0.5234375,0.2,8,1,6,,400,100,,16,21.671775579452515
+257,0.54296875,0.5546875,0.53125,0.2,8,1,7,,400,100,,16,21.715075254440308
+258,0.53125,0.5625,0.51171875,0.2,8,1,8,,400,100,,16,21.486245155334473
+259,0.51953125,0.5625,0.46484375,0.2,8,1,9,,400,100,,16,21.473143100738525
+260,0.55078125,0.56640625,0.546875,0.2,8,1,10,,400,100,,16,21.513612031936646
+261,0.51171875,0.53125,0.50390625,0.2,8,1,11,,400,100,,16,21.53299331665039
+262,0.55078125,0.5625,0.51953125,0.2,8,1,12,,400,100,,16,21.388710021972656
+263,0.5625,0.5546875,0.515625,0.2,8,1,13,,400,100,,16,21.520968914031982
+264,0.51953125,0.53515625,0.51953125,0.2,8,1,14,,400,100,,16,21.39451313018799
+265,0.5546875,0.55859375,0.5234375,0.2,8,1,15,,400,100,,16,21.624860048294067
+266,0.5625,0.5703125,0.55078125,0.2,8,1,16,,400,100,,16,21.57380175590515
+267,0.5546875,0.5859375,0.53515625,0.2,8,1,17,,400,100,,16,21.476141929626465
+268,0.55078125,0.55078125,0.5234375,0.2,8,1,18,,400,100,,16,21.455005168914795
+269,0.515625,0.53515625,0.5,0.2,8,1,19,,400,100,,16,21.51510190963745
+270,0.51171875,0.53125,0.48046875,0.2,8,1,20,,400,100,,16,21.27868676185608
+271,0.58203125,0.57421875,0.54296875,0.2,8,1,21,,400,100,,16,21.359771728515625
+272,0.5625,0.55859375,0.53515625,0.2,8,1,22,,400,100,,16,21.33924174308777
+273,0.5703125,0.5625,0.55078125,0.2,8,1,23,,400,100,,16,21.568665742874146
+274,0.56640625,0.5859375,0.5546875,0.2,8,1,24,,400,100,,16,21.456631898880005
+275,0.521484375,0.53125,0.53515625,0.2,9,1,0,,800,100,,16,68.74340081214905
+276,0.53125,0.53515625,0.517578125,0.2,9,1,1,,800,100,,16,68.58837223052979
+277,0.55078125,0.564453125,0.54296875,0.2,9,1,2,,800,100,,16,68.66253638267517
+278,0.51171875,0.5078125,0.509765625,0.2,9,1,3,,800,100,,16,68.40132665634155
+279,0.53125,0.521484375,0.513671875,0.2,9,1,4,,800,100,,16,68.2510814666748
+280,0.51171875,0.51953125,0.49609375,0.2,9,1,5,,800,100,,16,68.16955184936523
+281,0.51953125,0.546875,0.51171875,0.2,9,1,6,,800,100,,16,68.50119876861572
+282,0.533203125,0.541015625,0.5234375,0.2,9,1,7,,800,100,,16,68.24303221702576
+283,0.5,0.533203125,0.49609375,0.2,9,1,8,,800,100,,16,68.28972935676575
+284,0.568359375,0.564453125,0.55078125,0.2,9,1,9,,800,100,,16,68.2095901966095
+285,0.5234375,0.525390625,0.505859375,0.2,9,1,10,,800,100,,16,68.31288599967957
+286,0.537109375,0.54296875,0.51171875,0.2,9,1,11,,800,100,,16,68.35973238945007
+287,0.552734375,0.54296875,0.52734375,0.2,9,1,12,,800,100,,16,68.78276777267456
+288,0.5625,0.572265625,0.546875,0.2,9,1,13,,800,100,,16,68.68293905258179
+289,0.501953125,0.50390625,0.470703125,0.2,9,1,14,,800,100,,16,68.3417558670044
+290,0.529296875,0.56640625,0.515625,0.2,9,1,15,,800,100,,16,68.29726767539978
+291,0.5390625,0.541015625,0.52734375,0.2,9,1,16,,800,100,,16,68.2119197845459
+292,0.529296875,0.51953125,0.509765625,0.2,9,1,17,,800,100,,16,68.11052203178406
+293,0.560546875,0.568359375,0.55859375,0.2,9,1,18,,800,100,,16,68.78559517860413
+294,0.521484375,0.517578125,0.50390625,0.2,9,1,19,,800,100,,16,68.19279527664185
+295,0.533203125,0.54296875,0.529296875,0.2,9,1,20,,800,100,,16,68.12688994407654
+296,0.5390625,0.54296875,0.5078125,0.2,9,1,21,,800,100,,16,68.1328992843628
+297,0.5546875,0.55078125,0.52734375,0.2,9,1,22,,800,100,,16,68.54535961151123
+298,0.5234375,0.541015625,0.515625,0.2,9,1,23,,800,100,,16,68.36077451705933
+299,0.54296875,0.55078125,0.521484375,0.2,9,1,24,,800,100,,16,68.59470415115356
diff --git a/experiments/bench/oneMax/data/mu+lambdaUCB-pop=100-n_evals.csv b/experiments/bench/oneMax/data/mu+lambdaUCB-pop=100-n_evals.csv
new file mode 100644
index 0000000000000000000000000000000000000000..22a3f13a3b4b181d3b554c422258fa49231d8fbc
--- /dev/null
+++ b/experiments/bench/oneMax/data/mu+lambdaUCB-pop=100-n_evals.csv
@@ -0,0 +1,901 @@
+,best_pop,best_hof,best_arm,std,dim,n_eval,run_number,UCB_sigma,ngen,mu,lambda,n_thread,time
+0,1.0,1.0,1.0,0.01,6,7,0,,100,100,,16,6.092102289199829
+1,1.0,1.0,1.0,0.01,6,7,1,,100,100,,16,6.132989406585693
+2,1.0,1.0,1.0,0.01,6,7,2,,100,100,,16,6.154202461242676
+3,1.0,1.0,1.0,0.01,6,7,3,,100,100,,16,6.096986770629883
+4,1.0,1.0,0.96875,0.01,6,7,4,,100,100,,16,6.042018413543701
+5,1.0,1.0,1.0,0.01,6,7,5,,100,100,,16,6.049992799758911
+6,1.0,1.0,1.0,0.01,6,7,6,,100,100,,16,6.057997226715088
+7,1.0,1.0,1.0,0.01,6,7,7,,100,100,,16,6.210469484329224
+8,1.0,1.0,0.984375,0.01,6,7,8,,100,100,,16,6.049999713897705
+9,1.0,1.0,1.0,0.01,6,7,9,,100,100,,16,6.122000694274902
+10,1.0,1.0,1.0,0.01,6,7,10,,100,100,,16,6.120000600814819
+11,1.0,1.0,1.0,0.01,6,7,11,,100,100,,16,6.059566020965576
+12,1.0,1.0,0.9375,0.01,6,7,12,,100,100,,16,6.196988105773926
+13,1.0,1.0,1.0,0.01,6,7,13,,100,100,,16,6.062658786773682
+14,1.0,1.0,0.96875,0.01,6,7,14,,100,100,,16,6.044993162155151
+15,1.0,1.0,1.0,0.01,6,7,15,,100,100,,16,6.1155149936676025
+16,1.0,1.0,1.0,0.01,6,7,16,,100,100,,16,6.064626216888428
+17,1.0,1.0,1.0,0.01,6,7,17,,100,100,,16,6.107993125915527
+18,1.0,1.0,1.0,0.01,6,7,18,,100,100,,16,6.087987184524536
+19,1.0,1.0,1.0,0.01,6,7,19,,100,100,,16,6.110989809036255
+20,1.0,1.0,1.0,0.01,6,7,20,,100,100,,16,6.219366073608398
+21,1.0,1.0,0.984375,0.01,6,7,21,,100,100,,16,6.068666458129883
+22,1.0,1.0,1.0,0.01,6,7,22,,100,100,,16,6.081459045410156
+23,1.0,1.0,0.953125,0.01,6,7,23,,100,100,,16,6.138855695724487
+24,1.0,1.0,0.9375,0.01,6,7,24,,100,100,,16,6.1324989795684814
+25,1.0,1.0,1.0,0.01,6,25,0,,100,100,,16,9.614202737808228
+26,1.0,1.0,1.0,0.01,6,25,1,,100,100,,16,9.420439720153809
+27,1.0,1.0,1.0,0.01,6,25,2,,100,100,,16,9.372044563293457
+28,1.0,1.0,0.984375,0.01,6,25,3,,100,100,,16,9.381992816925049
+29,1.0,1.0,1.0,0.01,6,25,4,,100,100,,16,9.305230140686035
+30,1.0,1.0,1.0,0.01,6,25,5,,100,100,,16,9.396003007888794
+31,1.0,1.0,0.96875,0.01,6,25,6,,100,100,,16,9.473680973052979
+32,1.0,1.0,1.0,0.01,6,25,7,,100,100,,16,9.40258240699768
+33,1.0,1.0,0.984375,0.01,6,25,8,,100,100,,16,9.40520167350769
+34,1.0,1.0,1.0,0.01,6,25,9,,100,100,,16,9.464779615402222
+35,1.0,1.0,1.0,0.01,6,25,10,,100,100,,16,9.536437273025513
+36,1.0,1.0,1.0,0.01,6,25,11,,100,100,,16,9.453989505767822
+37,1.0,1.0,1.0,0.01,6,25,12,,100,100,,16,9.240982055664062
+38,1.0,1.0,0.953125,0.01,6,25,13,,100,100,,16,9.36073899269104
+39,1.0,1.0,1.0,0.01,6,25,14,,100,100,,16,9.388288497924805
+40,1.0,1.0,1.0,0.01,6,25,15,,100,100,,16,9.354997634887695
+41,1.0,1.0,1.0,0.01,6,25,16,,100,100,,16,9.487738609313965
+42,1.0,1.0,1.0,0.01,6,25,17,,100,100,,16,9.556991338729858
+43,1.0,1.0,0.90625,0.01,6,25,18,,100,100,,16,9.358995199203491
+44,1.0,1.0,1.0,0.01,6,25,19,,100,100,,16,9.36969780921936
+45,1.0,1.0,1.0,0.01,6,25,20,,100,100,,16,9.323990821838379
+46,1.0,1.0,0.90625,0.01,6,25,21,,100,100,,16,9.322991847991943
+47,1.0,1.0,1.0,0.01,6,25,22,,100,100,,16,9.595850229263306
+48,1.0,1.0,0.96875,0.01,6,25,23,,100,100,,16,9.417617082595825
+49,1.0,1.0,1.0,0.01,6,25,24,,100,100,,16,9.384001016616821
+50,1.0,1.0,1.0,0.01,6,57,0,,100,100,,16,15.755402088165283
+51,1.0,1.0,0.921875,0.01,6,57,1,,100,100,,16,15.502999305725098
+52,1.0,1.0,1.0,0.01,6,57,2,,100,100,,16,15.589537620544434
+53,1.0,1.0,0.96875,0.01,6,57,3,,100,100,,16,15.402002573013306
+54,1.0,1.0,1.0,0.01,6,57,4,,100,100,,16,15.632002592086792
+55,1.0,1.0,1.0,0.01,6,57,5,,100,100,,16,15.770899534225464
+56,1.0,1.0,1.0,0.01,6,57,6,,100,100,,16,15.486394882202148
+57,1.0,1.0,1.0,0.01,6,57,7,,100,100,,16,15.757988452911377
+58,1.0,1.0,1.0,0.01,6,57,8,,100,100,,16,15.974487066268921
+59,1.0,1.0,0.921875,0.01,6,57,9,,100,100,,16,15.466228008270264
+60,1.0,1.0,1.0,0.01,6,57,10,,100,100,,16,15.587616682052612
+61,1.0,1.0,1.0,0.01,6,57,11,,100,100,,16,15.521720886230469
+62,1.0,1.0,1.0,0.01,6,57,12,,100,100,,16,15.7661292552948
+63,1.0,1.0,1.0,0.01,6,57,13,,100,100,,16,15.837349653244019
+64,1.0,1.0,1.0,0.01,6,57,14,,100,100,,16,15.688859462738037
+65,1.0,1.0,0.9375,0.01,6,57,15,,100,100,,16,15.648989200592041
+66,1.0,1.0,0.984375,0.01,6,57,16,,100,100,,16,15.784308195114136
+67,1.0,1.0,1.0,0.01,6,57,17,,100,100,,16,15.59933590888977
+68,1.0,1.0,1.0,0.01,6,57,18,,100,100,,16,15.618986129760742
+69,1.0,1.0,1.0,0.01,6,57,19,,100,100,,16,15.4139986038208
+70,1.0,1.0,0.90625,0.01,6,57,20,,100,100,,16,15.77599835395813
+71,1.0,1.0,0.96875,0.01,6,57,21,,100,100,,16,15.757240772247314
+72,1.0,1.0,1.0,0.01,6,57,22,,100,100,,16,15.43400502204895
+73,1.0,1.0,1.0,0.01,6,57,23,,100,100,,16,15.511993169784546
+74,1.0,1.0,1.0,0.01,6,57,24,,100,100,,16,15.797011375427246
+75,1.0,1.0,1.0,0.01,7,7,0,,200,100,,16,11.947282314300537
+76,1.0,1.0,0.96875,0.01,7,7,1,,200,100,,16,11.911014318466187
+77,0.9765625,0.984375,0.8984375,0.01,7,7,2,,200,100,,16,11.850351810455322
+78,1.0,1.0,1.0,0.01,7,7,3,,200,100,,16,11.777647733688354
+79,0.9921875,0.9921875,0.9140625,0.01,7,7,4,,200,100,,16,11.999787330627441
+80,0.984375,0.984375,0.984375,0.01,7,7,5,,200,100,,16,11.868733406066895
+81,0.984375,0.984375,0.9140625,0.01,7,7,6,,200,100,,16,11.913009405136108
+82,0.984375,0.984375,0.9375,0.01,7,7,7,,200,100,,16,11.823010206222534
+83,0.9921875,0.9921875,0.9921875,0.01,7,7,8,,200,100,,16,11.930108547210693
+84,0.96875,0.96875,0.9609375,0.01,7,7,9,,200,100,,16,11.885996103286743
+85,0.984375,0.984375,0.921875,0.01,7,7,10,,200,100,,16,11.850553750991821
+86,0.9921875,0.9921875,0.984375,0.01,7,7,11,,200,100,,16,11.835989236831665
+87,1.0,1.0,1.0,0.01,7,7,12,,200,100,,16,11.96470832824707
+88,0.9921875,1.0,0.9921875,0.01,7,7,13,,200,100,,16,11.854013681411743
+89,0.9921875,0.9921875,0.953125,0.01,7,7,14,,200,100,,16,11.87699556350708
+90,0.984375,0.984375,0.984375,0.01,7,7,15,,200,100,,16,11.918923139572144
+91,0.9765625,0.9765625,0.8671875,0.01,7,7,16,,200,100,,16,11.92929744720459
+92,0.9765625,0.984375,0.9765625,0.01,7,7,17,,200,100,,16,11.913996696472168
+93,0.9765625,0.9765625,0.9765625,0.01,7,7,18,,200,100,,16,11.888794898986816
+94,0.96875,0.9765625,0.96875,0.01,7,7,19,,200,100,,16,11.864994525909424
+95,0.9921875,1.0,0.9921875,0.01,7,7,20,,200,100,,16,11.978339672088623
+96,1.0,1.0,0.953125,0.01,7,7,21,,200,100,,16,11.933987617492676
+97,0.9921875,0.9921875,0.96875,0.01,7,7,22,,200,100,,16,11.892002582550049
+98,0.9765625,0.984375,0.9765625,0.01,7,7,23,,200,100,,16,11.854210615158081
+99,0.9921875,0.9921875,0.9921875,0.01,7,7,24,,200,100,,16,11.940583944320679
+100,1.0,1.0,1.0,0.01,7,25,0,,200,100,,16,18.589431762695312
+101,0.9921875,1.0,0.9921875,0.01,7,25,1,,200,100,,16,18.22602081298828
+102,0.984375,0.984375,0.984375,0.01,7,25,2,,200,100,,16,18.440179109573364
+103,1.0,1.0,1.0,0.01,7,25,3,,200,100,,16,18.589268445968628
+104,1.0,1.0,0.9921875,0.01,7,25,4,,200,100,,16,18.50899386405945
+105,1.0,1.0,1.0,0.01,7,25,5,,200,100,,16,18.447104930877686
+106,1.0,1.0,0.953125,0.01,7,25,6,,200,100,,16,18.67504906654358
+107,1.0,1.0,1.0,0.01,7,25,7,,200,100,,16,18.46715545654297
+108,0.9921875,0.9921875,0.9921875,0.01,7,25,8,,200,100,,16,18.455360651016235
+109,0.9921875,0.9921875,0.984375,0.01,7,25,9,,200,100,,16,18.245574951171875
+110,0.9921875,0.9921875,0.9921875,0.01,7,25,10,,200,100,,16,18.499677658081055
+111,0.9921875,0.9921875,0.9921875,0.01,7,25,11,,200,100,,16,18.725157260894775
+112,0.9921875,0.9921875,0.96875,0.01,7,25,12,,200,100,,16,18.61500072479248
+113,1.0,1.0,1.0,0.01,7,25,13,,200,100,,16,18.458106756210327
+114,1.0,1.0,1.0,0.01,7,25,14,,200,100,,16,18.584259510040283
+115,0.9921875,0.9921875,0.9921875,0.01,7,25,15,,200,100,,16,18.507988214492798
+116,1.0,1.0,1.0,0.01,7,25,16,,200,100,,16,18.51126790046692
+117,1.0,1.0,1.0,0.01,7,25,17,,200,100,,16,18.263434410095215
+118,0.9921875,0.9921875,0.9921875,0.01,7,25,18,,200,100,,16,18.514153718948364
+119,0.9921875,1.0,0.9921875,0.01,7,25,19,,200,100,,16,18.7093985080719
+120,1.0,1.0,0.9921875,0.01,7,25,20,,200,100,,16,18.498093366622925
+121,0.9921875,0.9921875,0.9921875,0.01,7,25,21,,200,100,,16,18.475518941879272
+122,1.0,1.0,0.9921875,0.01,7,25,22,,200,100,,16,18.604721307754517
+123,1.0,1.0,1.0,0.01,7,25,23,,200,100,,16,18.578863859176636
+124,0.9921875,0.9921875,0.9921875,0.01,7,25,24,,200,100,,16,18.629990339279175
+125,1.0,1.0,1.0,0.01,7,57,0,,200,100,,16,30.34855628013611
+126,1.0,1.0,1.0,0.01,7,57,1,,200,100,,16,31.239570140838623
+127,0.984375,0.9921875,0.984375,0.01,7,57,2,,200,100,,16,31.44869899749756
+128,1.0,1.0,1.0,0.01,7,57,3,,200,100,,16,31.063003301620483
+129,0.984375,0.984375,0.9140625,0.01,7,57,4,,200,100,,16,30.977994203567505
+130,1.0,1.0,0.953125,0.01,7,57,5,,200,100,,16,31.343952417373657
+131,1.0,1.0,0.9375,0.01,7,57,6,,200,100,,16,31.021122932434082
+132,0.9921875,1.0,0.984375,0.01,7,57,7,,200,100,,16,30.734166622161865
+133,1.0,1.0,1.0,0.01,7,57,8,,200,100,,16,30.346599102020264
+134,1.0,1.0,1.0,0.01,7,57,9,,200,100,,16,30.895087957382202
+135,1.0,1.0,0.9765625,0.01,7,57,10,,200,100,,16,31.245837211608887
+136,1.0,1.0,1.0,0.01,7,57,11,,200,100,,16,30.915587902069092
+137,1.0,1.0,0.9375,0.01,7,57,12,,200,100,,16,31.090105295181274
+138,0.9921875,0.9921875,0.953125,0.01,7,57,13,,200,100,,16,31.508567571640015
+139,0.9921875,0.9921875,0.9921875,0.01,7,57,14,,200,100,,16,31.03871488571167
+140,1.0,1.0,0.9296875,0.01,7,57,15,,200,100,,16,30.888540267944336
+141,1.0,1.0,0.984375,0.01,7,57,16,,200,100,,16,30.482491493225098
+142,1.0,1.0,1.0,0.01,7,57,17,,200,100,,16,30.639997720718384
+143,1.0,1.0,1.0,0.01,7,57,18,,200,100,,16,31.332937955856323
+144,1.0,1.0,0.9296875,0.01,7,57,19,,200,100,,16,31.003861665725708
+145,0.9921875,0.9921875,0.9453125,0.01,7,57,20,,200,100,,16,30.987611770629883
+146,0.984375,0.984375,0.9453125,0.01,7,57,21,,200,100,,16,31.495979070663452
+147,1.0,1.0,1.0,0.01,7,57,22,,200,100,,16,30.795201063156128
+148,1.0,1.0,1.0,0.01,7,57,23,,200,100,,16,31.000951528549194
+149,0.9921875,0.9921875,0.9921875,0.01,7,57,24,,200,100,,16,30.456673622131348
+150,0.91796875,0.921875,0.91796875,0.01,8,7,0,,400,100,,16,29.83985137939453
+151,0.92578125,0.92578125,0.9140625,0.01,8,7,1,,400,100,,16,30.134544610977173
+152,0.93359375,0.93359375,0.8828125,0.01,8,7,2,,400,100,,16,29.845092058181763
+153,0.93359375,0.93359375,0.93359375,0.01,8,7,3,,400,100,,16,30.10256791114807
+154,0.91796875,0.921875,0.87109375,0.01,8,7,4,,400,100,,16,29.59415364265442
+155,0.953125,0.953125,0.953125,0.01,8,7,5,,400,100,,16,30.099651098251343
+156,0.9140625,0.9140625,0.91015625,0.01,8,7,6,,400,100,,16,29.904390811920166
+157,0.921875,0.91796875,0.91796875,0.01,8,7,7,,400,100,,16,29.91660976409912
+158,0.9296875,0.9296875,0.9296875,0.01,8,7,8,,400,100,,16,29.592825412750244
+159,0.9375,0.94140625,0.9375,0.01,8,7,9,,400,100,,16,29.946072101593018
+160,0.91015625,0.9140625,0.859375,0.01,8,7,10,,400,100,,16,29.746731281280518
+161,0.8984375,0.90625,0.859375,0.01,8,7,11,,400,100,,16,30.065141201019287
+162,0.921875,0.921875,0.91796875,0.01,8,7,12,,400,100,,16,29.993029832839966
+163,0.92578125,0.92578125,0.875,0.01,8,7,13,,400,100,,16,30.082579374313354
+164,0.94140625,0.94140625,0.9375,0.01,8,7,14,,400,100,,16,30.01869487762451
+165,0.93359375,0.9375,0.89453125,0.01,8,7,15,,400,100,,16,29.747470140457153
+166,0.9375,0.94140625,0.89453125,0.01,8,7,16,,400,100,,16,29.63799810409546
+167,0.92578125,0.92578125,0.92578125,0.01,8,7,17,,400,100,,16,29.952158451080322
+168,0.94140625,0.9453125,0.94140625,0.01,8,7,18,,400,100,,16,29.907467365264893
+169,0.93359375,0.93359375,0.93359375,0.01,8,7,19,,400,100,,16,30.149658918380737
+170,0.93359375,0.93359375,0.91015625,0.01,8,7,20,,400,100,,16,29.89411950111389
+171,0.9140625,0.9140625,0.9140625,0.01,8,7,21,,400,100,,16,29.958499908447266
+172,0.8984375,0.90625,0.8984375,0.01,8,7,22,,400,100,,16,29.878238201141357
+173,0.9296875,0.93359375,0.9296875,0.01,8,7,23,,400,100,,16,29.82211971282959
+174,0.91796875,0.91796875,0.91796875,0.01,8,7,24,,400,100,,16,29.519466161727905
+175,0.9453125,0.9453125,0.94140625,0.01,8,25,0,,400,100,,16,43.06149435043335
+176,0.921875,0.921875,0.921875,0.01,8,25,1,,400,100,,16,42.69301462173462
+177,0.9453125,0.94921875,0.90234375,0.01,8,25,2,,400,100,,16,42.82991409301758
+178,0.9296875,0.9296875,0.9296875,0.01,8,25,3,,400,100,,16,42.910908699035645
+179,0.93359375,0.93359375,0.92578125,0.01,8,25,4,,400,100,,16,42.80174660682678
+180,0.953125,0.953125,0.953125,0.01,8,25,5,,400,100,,16,42.58665060997009
+181,0.953125,0.953125,0.94921875,0.01,8,25,6,,400,100,,16,42.451969146728516
+182,0.94140625,0.94140625,0.94140625,0.01,8,25,7,,400,100,,16,42.689716815948486
+183,0.9453125,0.9453125,0.9453125,0.01,8,25,8,,400,100,,16,43.039368629455566
+184,0.94140625,0.94140625,0.890625,0.01,8,25,9,,400,100,,16,42.78179955482483
+185,0.94140625,0.94921875,0.94140625,0.01,8,25,10,,400,100,,16,42.78510761260986
+186,0.93359375,0.9375,0.89453125,0.01,8,25,11,,400,100,,16,43.056169271469116
+187,0.94921875,0.94921875,0.94921875,0.01,8,25,12,,400,100,,16,42.67069172859192
+188,0.93359375,0.93359375,0.8984375,0.01,8,25,13,,400,100,,16,42.8445258140564
+189,0.94140625,0.94140625,0.8515625,0.01,8,25,14,,400,100,,16,42.676313400268555
+190,0.921875,0.9296875,0.89453125,0.01,8,25,15,,400,100,,16,42.776495695114136
+191,0.95703125,0.9609375,0.95703125,0.01,8,25,16,,400,100,,16,43.246875047683716
+192,0.9375,0.9375,0.9375,0.01,8,25,17,,400,100,,16,42.86768937110901
+193,0.94921875,0.953125,0.94921875,0.01,8,25,18,,400,100,,16,42.83473753929138
+194,0.94921875,0.94921875,0.8828125,0.01,8,25,19,,400,100,,16,42.89422297477722
+195,0.94921875,0.94921875,0.921875,0.01,8,25,20,,400,100,,16,42.82529258728027
+196,0.96484375,0.96484375,0.9609375,0.01,8,25,21,,400,100,,16,42.72086310386658
+197,0.9453125,0.9453125,0.9453125,0.01,8,25,22,,400,100,,16,42.42886257171631
+198,0.9375,0.9375,0.890625,0.01,8,25,23,,400,100,,16,42.66504383087158
+199,0.9453125,0.94921875,0.9453125,0.01,8,25,24,,400,100,,16,43.181159019470215
+200,0.95703125,0.95703125,0.95703125,0.01,8,57,0,,400,100,,16,66.75072622299194
+201,0.9609375,0.9609375,0.890625,0.01,8,57,1,,400,100,,16,67.0864007472992
+202,0.92578125,0.9296875,0.8515625,0.01,8,57,2,,400,100,,16,67.42097640037537
+203,0.94140625,0.94140625,0.890625,0.01,8,57,3,,400,100,,16,66.78347682952881
+204,0.93359375,0.93359375,0.93359375,0.01,8,57,4,,400,100,,16,66.56072473526001
+205,0.97265625,0.97265625,0.9375,0.01,8,57,5,,400,100,,16,65.93913674354553
+206,0.94140625,0.94140625,0.94140625,0.01,8,57,6,,400,100,,16,66.71356892585754
+207,0.9453125,0.94921875,0.9453125,0.01,8,57,7,,400,100,,16,67.27605247497559
+208,0.93359375,0.9375,0.8984375,0.01,8,57,8,,400,100,,16,66.79568433761597
+209,0.98046875,0.98046875,0.94140625,0.01,8,57,9,,400,100,,16,67.68655276298523
+210,0.95703125,0.95703125,0.90625,0.01,8,57,10,,400,100,,16,67.58019924163818
+211,0.93359375,0.9375,0.89453125,0.01,8,57,11,,400,100,,16,66.41345572471619
+212,0.95703125,0.95703125,0.95703125,0.01,8,57,12,,400,100,,16,66.53670978546143
+213,0.9609375,0.9609375,0.90234375,0.01,8,57,13,,400,100,,16,66.08362865447998
+214,0.93359375,0.93359375,0.92578125,0.01,8,57,14,,400,100,,16,66.96890068054199
+215,0.9453125,0.94921875,0.9140625,0.01,8,57,15,,400,100,,16,67.42441129684448
+216,0.95703125,0.95703125,0.95703125,0.01,8,57,16,,400,100,,16,66.63642835617065
+217,0.94140625,0.9453125,0.94140625,0.01,8,57,17,,400,100,,16,67.45345377922058
+218,0.9765625,0.9765625,0.93359375,0.01,8,57,18,,400,100,,16,67.49056196212769
+219,0.9453125,0.94921875,0.9453125,0.01,8,57,19,,400,100,,16,67.25909519195557
+220,0.95703125,0.95703125,0.9375,0.01,8,57,20,,400,100,,16,66.47112321853638
+221,0.9453125,0.94921875,0.89453125,0.01,8,57,21,,400,100,,16,66.06466460227966
+222,0.94140625,0.94921875,0.94140625,0.01,8,57,22,,400,100,,16,67.23120141029358
+223,0.953125,0.953125,0.9453125,0.01,8,57,23,,400,100,,16,67.56143426895142
+224,0.953125,0.953125,0.953125,0.01,8,57,24,,400,100,,16,67.08083963394165
+225,0.84375,0.84765625,0.83984375,0.01,9,7,0,,800,100,,16,89.35258412361145
+226,0.859375,0.859375,0.853515625,0.01,9,7,1,,800,100,,16,88.99746227264404
+227,0.85546875,0.857421875,0.85546875,0.01,9,7,2,,800,100,,16,89.49646949768066
+228,0.84765625,0.849609375,0.78515625,0.01,9,7,3,,800,100,,16,88.22070693969727
+229,0.84375,0.853515625,0.84375,0.01,9,7,4,,800,100,,16,89.6513831615448
+230,0.86328125,0.865234375,0.861328125,0.01,9,7,5,,800,100,,16,88.46592497825623
+231,0.85546875,0.859375,0.80859375,0.01,9,7,6,,800,100,,16,89.69336342811584
+232,0.841796875,0.845703125,0.83984375,0.01,9,7,7,,800,100,,16,89.03736591339111
+233,0.849609375,0.8515625,0.84765625,0.01,9,7,8,,800,100,,16,88.57469725608826
+234,0.83984375,0.83984375,0.837890625,0.01,9,7,9,,800,100,,16,88.74702787399292
+235,0.83984375,0.83984375,0.8359375,0.01,9,7,10,,800,100,,16,89.37587070465088
+236,0.861328125,0.861328125,0.81640625,0.01,9,7,11,,800,100,,16,88.89996099472046
+237,0.84765625,0.8515625,0.84765625,0.01,9,7,12,,800,100,,16,87.81291651725769
+238,0.861328125,0.86328125,0.859375,0.01,9,7,13,,800,100,,16,89.32346844673157
+239,0.859375,0.859375,0.82421875,0.01,9,7,14,,800,100,,16,89.0165946483612
+240,0.873046875,0.876953125,0.841796875,0.01,9,7,15,,800,100,,16,88.98417806625366
+241,0.859375,0.859375,0.85546875,0.01,9,7,16,,800,100,,16,88.69683313369751
+242,0.8515625,0.853515625,0.8515625,0.01,9,7,17,,800,100,,16,88.14396810531616
+243,0.86328125,0.8671875,0.86328125,0.01,9,7,18,,800,100,,16,88.55014371871948
+244,0.85546875,0.859375,0.85546875,0.01,9,7,19,,800,100,,16,88.32270574569702
+245,0.849609375,0.8515625,0.80859375,0.01,9,7,20,,800,100,,16,89.01156282424927
+246,0.83203125,0.837890625,0.83203125,0.01,9,7,21,,800,100,,16,88.61248564720154
+247,0.865234375,0.865234375,0.86328125,0.01,9,7,22,,800,100,,16,88.99453282356262
+248,0.837890625,0.83984375,0.8359375,0.01,9,7,23,,800,100,,16,88.42712712287903
+249,0.8515625,0.853515625,0.8515625,0.01,9,7,24,,800,100,,16,89.22194719314575
+250,0.87109375,0.87109375,0.865234375,0.01,9,25,0,,800,100,,16,117.89583992958069
+251,0.880859375,0.880859375,0.87890625,0.01,9,25,1,,800,100,,16,117.36684918403625
+252,0.880859375,0.880859375,0.87890625,0.01,9,25,2,,800,100,,16,117.2848334312439
+253,0.8828125,0.884765625,0.8828125,0.01,9,25,3,,800,100,,16,116.88520240783691
+254,0.88671875,0.890625,0.88671875,0.01,9,25,4,,800,100,,16,117.06639504432678
+255,0.8828125,0.8828125,0.880859375,0.01,9,25,5,,800,100,,16,117.63173007965088
+256,0.859375,0.859375,0.84375,0.01,9,25,6,,800,100,,16,117.13684725761414
+257,0.888671875,0.888671875,0.888671875,0.01,9,25,7,,800,100,,16,118.01717162132263
+258,0.880859375,0.880859375,0.880859375,0.01,9,25,8,,800,100,,16,117.75875329971313
+259,0.908203125,0.908203125,0.90625,0.01,9,25,9,,800,100,,16,117.44448971748352
+260,0.88671875,0.88671875,0.88671875,0.01,9,25,10,,800,100,,16,116.98593282699585
+261,0.888671875,0.890625,0.8515625,0.01,9,25,11,,800,100,,16,116.94371700286865
+262,0.875,0.876953125,0.875,0.01,9,25,12,,800,100,,16,117.77123999595642
+263,0.86328125,0.865234375,0.822265625,0.01,9,25,13,,800,100,,16,118.00383996963501
+264,0.865234375,0.87109375,0.865234375,0.01,9,25,14,,800,100,,16,117.37371516227722
+265,0.8984375,0.8984375,0.85546875,0.01,9,25,15,,800,100,,16,117.88578391075134
+266,0.888671875,0.890625,0.888671875,0.01,9,25,16,,800,100,,16,118.00324487686157
+267,0.8828125,0.8828125,0.880859375,0.01,9,25,17,,800,100,,16,117.49057149887085
+268,0.88671875,0.888671875,0.884765625,0.01,9,25,18,,800,100,,16,116.80888843536377
+269,0.890625,0.89453125,0.888671875,0.01,9,25,19,,800,100,,16,117.08965039253235
+270,0.890625,0.890625,0.890625,0.01,9,25,20,,800,100,,16,116.63112425804138
+271,0.87890625,0.8828125,0.87890625,0.01,9,25,21,,800,100,,16,117.81882405281067
+272,0.88671875,0.88671875,0.8828125,0.01,9,25,22,,800,100,,16,117.16252994537354
+273,0.876953125,0.880859375,0.876953125,0.01,9,25,23,,800,100,,16,117.73638558387756
+274,0.87109375,0.873046875,0.81640625,0.01,9,25,24,,800,100,,16,117.81981492042542
+275,0.892578125,0.892578125,0.83984375,0.01,9,57,0,,800,100,,16,167.30182886123657
+276,0.904296875,0.90625,0.873046875,0.01,9,57,1,,800,100,,16,166.94810605049133
+277,0.896484375,0.896484375,0.89453125,0.01,9,57,2,,800,100,,16,165.77797675132751
+278,0.8828125,0.8828125,0.8359375,0.01,9,57,3,,800,100,,16,168.83498644828796
+279,0.8671875,0.873046875,0.8671875,0.01,9,57,4,,800,100,,16,168.004714012146
+280,0.884765625,0.884765625,0.880859375,0.01,9,57,5,,800,100,,16,166.52105164527893
+281,0.892578125,0.892578125,0.859375,0.01,9,57,6,,800,100,,16,168.05312156677246
+282,0.900390625,0.900390625,0.900390625,0.01,9,57,7,,800,100,,16,169.8128480911255
+283,0.87890625,0.87890625,0.87890625,0.01,9,57,8,,800,100,,16,167.34218668937683
+284,0.880859375,0.880859375,0.87890625,0.01,9,57,9,,800,100,,16,167.55345726013184
+285,0.888671875,0.890625,0.8359375,0.01,9,57,10,,800,100,,16,165.30565881729126
+286,0.880859375,0.884765625,0.880859375,0.01,9,57,11,,800,100,,16,168.63609743118286
+287,0.91015625,0.91015625,0.908203125,0.01,9,57,12,,800,100,,16,168.2279999256134
+288,0.87890625,0.880859375,0.87890625,0.01,9,57,13,,800,100,,16,167.12668180465698
+289,0.873046875,0.873046875,0.87109375,0.01,9,57,14,,800,100,,16,168.31427550315857
+290,0.892578125,0.89453125,0.892578125,0.01,9,57,15,,800,100,,16,169.47984147071838
+291,0.88671875,0.884765625,0.880859375,0.01,9,57,16,,800,100,,16,167.27479529380798
+292,0.87109375,0.87109375,0.87109375,0.01,9,57,17,,800,100,,16,167.1934609413147
+293,0.880859375,0.8828125,0.880859375,0.01,9,57,18,,800,100,,16,165.85292291641235
+294,0.87890625,0.87890625,0.87890625,0.01,9,57,19,,800,100,,16,167.72286748886108
+295,0.892578125,0.896484375,0.892578125,0.01,9,57,20,,800,100,,16,168.42450833320618
+296,0.890625,0.890625,0.853515625,0.01,9,57,21,,800,100,,16,167.08142280578613
+297,0.890625,0.890625,0.890625,0.01,9,57,22,,800,100,,16,168.5804479122162
+298,0.875,0.876953125,0.830078125,0.01,9,57,23,,800,100,,16,169.64361310005188
+299,0.888671875,0.888671875,0.86328125,0.01,9,57,24,,800,100,,16,167.2578935623169
+300,0.96875,0.96875,0.921875,0.1,6,7,0,,100,100,,16,6.107085943222046
+301,0.921875,0.921875,0.828125,0.1,6,7,1,,100,100,,16,5.8640007972717285
+302,0.953125,0.9375,0.875,0.1,6,7,2,,100,100,,16,5.873037338256836
+303,0.9375,0.9375,0.8125,0.1,6,7,3,,100,100,,16,5.929062128067017
+304,0.90625,0.921875,0.828125,0.1,6,7,4,,100,100,,16,5.918983459472656
+305,0.9375,0.953125,0.875,0.1,6,7,5,,100,100,,16,5.915577173233032
+306,0.9375,0.921875,0.9375,0.1,6,7,6,,100,100,,16,5.883164405822754
+307,0.890625,0.875,0.796875,0.1,6,7,7,,100,100,,16,5.939273118972778
+308,0.90625,0.953125,0.875,0.1,6,7,8,,100,100,,16,6.052568674087524
+309,0.953125,0.953125,0.890625,0.1,6,7,9,,100,100,,16,5.911010503768921
+310,0.984375,0.984375,0.953125,0.1,6,7,10,,100,100,,16,5.927100419998169
+311,0.921875,0.921875,0.84375,0.1,6,7,11,,100,100,,16,5.971562147140503
+312,0.953125,0.9375,0.84375,0.1,6,7,12,,100,100,,16,5.942998886108398
+313,0.921875,0.921875,0.875,0.1,6,7,13,,100,100,,16,5.916010856628418
+314,0.921875,0.921875,0.890625,0.1,6,7,14,,100,100,,16,5.860004186630249
+315,0.890625,0.875,0.828125,0.1,6,7,15,,100,100,,16,5.940462827682495
+316,0.859375,0.90625,0.765625,0.1,6,7,16,,100,100,,16,6.039988040924072
+317,0.90625,0.90625,0.796875,0.1,6,7,17,,100,100,,16,5.893986463546753
+318,0.9375,0.9375,0.859375,0.1,6,7,18,,100,100,,16,5.906987905502319
+319,0.953125,0.953125,0.890625,0.1,6,7,19,,100,100,,16,5.97833776473999
+320,0.9375,0.9375,0.875,0.1,6,7,20,,100,100,,16,5.8757829666137695
+321,0.875,0.9375,0.828125,0.1,6,7,21,,100,100,,16,5.969990015029907
+322,0.9375,0.921875,0.859375,0.1,6,7,22,,100,100,,16,5.942993879318237
+323,0.890625,0.9375,0.859375,0.1,6,7,23,,100,100,,16,5.918006658554077
+324,0.984375,0.984375,0.953125,0.1,6,7,24,,100,100,,16,6.121990442276001
+325,1.0,0.984375,0.875,0.1,6,25,0,,100,100,,16,9.040645837783813
+326,1.0,1.0,0.921875,0.1,6,25,1,,100,100,,16,9.2099928855896
+327,0.984375,0.96875,0.9375,0.1,6,25,2,,100,100,,16,9.18405818939209
+328,1.0,0.984375,0.90625,0.1,6,25,3,,100,100,,16,9.187338829040527
+329,0.984375,0.96875,0.875,0.1,6,25,4,,100,100,,16,9.131983041763306
+330,0.984375,0.984375,0.96875,0.1,6,25,5,,100,100,,16,9.20299220085144
+331,1.0,0.984375,0.96875,0.1,6,25,6,,100,100,,16,9.170738935470581
+332,1.0,0.984375,0.890625,0.1,6,25,7,,100,100,,16,9.145017385482788
+333,1.0,0.984375,0.953125,0.1,6,25,8,,100,100,,16,9.087989568710327
+334,0.984375,0.96875,0.96875,0.1,6,25,9,,100,100,,16,9.046989440917969
+335,1.0,1.0,0.984375,0.1,6,25,10,,100,100,,16,9.171873807907104
+336,0.984375,0.984375,0.875,0.1,6,25,11,,100,100,,16,9.251009464263916
+337,1.0,0.984375,0.9375,0.1,6,25,12,,100,100,,16,9.119990825653076
+338,1.0,0.984375,0.984375,0.1,6,25,13,,100,100,,16,9.198283910751343
+339,0.984375,0.96875,0.875,0.1,6,25,14,,100,100,,16,9.109168767929077
+340,0.984375,0.984375,0.984375,0.1,6,25,15,,100,100,,16,9.262019872665405
+341,0.984375,0.984375,0.921875,0.1,6,25,16,,100,100,,16,9.075000524520874
+342,0.9375,0.9375,0.875,0.1,6,25,17,,100,100,,16,9.042989015579224
+343,1.0,0.984375,0.90625,0.1,6,25,18,,100,100,,16,9.196931838989258
+344,0.984375,1.0,0.875,0.1,6,25,19,,100,100,,16,9.215076446533203
+345,1.0,0.984375,1.0,0.1,6,25,20,,100,100,,16,9.195987701416016
+346,0.984375,0.984375,0.875,0.1,6,25,21,,100,100,,16,9.197140455245972
+347,1.0,1.0,0.96875,0.1,6,25,22,,100,100,,16,9.218862771987915
+348,0.96875,0.96875,0.953125,0.1,6,25,23,,100,100,,16,9.16657829284668
+349,1.0,0.984375,0.890625,0.1,6,25,24,,100,100,,16,9.03443193435669
+350,1.0,1.0,1.0,0.1,6,57,0,,100,100,,16,15.278610706329346
+351,1.0,1.0,0.90625,0.1,6,57,1,,100,100,,16,15.225254774093628
+352,1.0,1.0,1.0,0.1,6,57,2,,100,100,,16,15.07260537147522
+353,1.0,1.0,0.890625,0.1,6,57,3,,100,100,,16,15.144993543624878
+354,0.984375,0.984375,0.875,0.1,6,57,4,,100,100,,16,15.441376447677612
+355,1.0,0.984375,0.90625,0.1,6,57,5,,100,100,,16,15.114177942276001
+356,1.0,0.984375,0.984375,0.1,6,57,6,,100,100,,16,15.054266452789307
+357,1.0,1.0,1.0,0.1,6,57,7,,100,100,,16,14.88401198387146
+358,1.0,1.0,0.953125,0.1,6,57,8,,100,100,,16,14.956014633178711
+359,1.0,0.984375,1.0,0.1,6,57,9,,100,100,,16,15.231792449951172
+360,1.0,0.984375,0.9375,0.1,6,57,10,,100,100,,16,15.087622165679932
+361,1.0,1.0,1.0,0.1,6,57,11,,100,100,,16,15.137017965316772
+362,1.0,1.0,0.953125,0.1,6,57,12,,100,100,,16,15.299314022064209
+363,1.0,0.984375,0.984375,0.1,6,57,13,,100,100,,16,14.985993385314941
+364,0.984375,0.984375,0.953125,0.1,6,57,14,,100,100,,16,15.013597011566162
+365,1.0,0.984375,0.96875,0.1,6,57,15,,100,100,,16,14.928013563156128
+366,1.0,0.984375,0.96875,0.1,6,57,16,,100,100,,16,15.209126710891724
+367,1.0,1.0,1.0,0.1,6,57,17,,100,100,,16,15.295621871948242
+368,1.0,0.984375,0.953125,0.1,6,57,18,,100,100,,16,15.15113878250122
+369,0.984375,1.0,0.9375,0.1,6,57,19,,100,100,,16,15.176008462905884
+370,1.0,1.0,1.0,0.1,6,57,20,,100,100,,16,15.368449211120605
+371,1.0,1.0,1.0,0.1,6,57,21,,100,100,,16,15.032992124557495
+372,1.0,1.0,1.0,0.1,6,57,22,,100,100,,16,14.98998761177063
+373,0.96875,0.984375,0.90625,0.1,6,57,23,,100,100,,16,14.824984312057495
+374,1.0,0.984375,0.984375,0.1,6,57,24,,100,100,,16,15.154984712600708
+375,0.7421875,0.765625,0.734375,0.1,7,7,0,,200,100,,16,11.23356819152832
+376,0.8359375,0.8359375,0.6640625,0.1,7,7,1,,200,100,,16,11.07500171661377
+377,0.8203125,0.8046875,0.7578125,0.1,7,7,2,,200,100,,16,11.208363771438599
+378,0.7890625,0.8046875,0.71875,0.1,7,7,3,,200,100,,16,11.069658041000366
+379,0.78125,0.7734375,0.671875,0.1,7,7,4,,200,100,,16,11.147104501724243
+380,0.796875,0.7890625,0.7421875,0.1,7,7,5,,200,100,,16,11.164990186691284
+381,0.7734375,0.7890625,0.7109375,0.1,7,7,6,,200,100,,16,11.115990400314331
+382,0.7734375,0.7890625,0.734375,0.1,7,7,7,,200,100,,16,10.996524333953857
+383,0.78125,0.78125,0.6796875,0.1,7,7,8,,200,100,,16,11.208631992340088
+384,0.8125,0.8046875,0.7890625,0.1,7,7,9,,200,100,,16,11.075006008148193
+385,0.8359375,0.8203125,0.78125,0.1,7,7,10,,200,100,,16,11.109583616256714
+386,0.7421875,0.7734375,0.6875,0.1,7,7,11,,200,100,,16,11.011986494064331
+387,0.8125,0.8203125,0.78125,0.1,7,7,12,,200,100,,16,11.234111309051514
+388,0.8046875,0.796875,0.7734375,0.1,7,7,13,,200,100,,16,11.070984840393066
+389,0.8203125,0.828125,0.7578125,0.1,7,7,14,,200,100,,16,11.094844341278076
+390,0.734375,0.7890625,0.6953125,0.1,7,7,15,,200,100,,16,11.103575706481934
+391,0.796875,0.8203125,0.796875,0.1,7,7,16,,200,100,,16,11.225693225860596
+392,0.796875,0.796875,0.6875,0.1,7,7,17,,200,100,,16,11.084005355834961
+393,0.8671875,0.8515625,0.8203125,0.1,7,7,18,,200,100,,16,11.146182775497437
+394,0.8125,0.8125,0.7734375,0.1,7,7,19,,200,100,,16,11.016990423202515
+395,0.765625,0.78125,0.7265625,0.1,7,7,20,,200,100,,16,11.131356716156006
+396,0.8046875,0.796875,0.75,0.1,7,7,21,,200,100,,16,11.073986291885376
+397,0.7890625,0.796875,0.71875,0.1,7,7,22,,200,100,,16,11.135993003845215
+398,0.765625,0.7578125,0.6640625,0.1,7,7,23,,200,100,,16,10.944071531295776
+399,0.78125,0.78125,0.7734375,0.1,7,7,24,,200,100,,16,11.196065902709961
+400,0.890625,0.8984375,0.859375,0.1,7,25,0,,200,100,,16,17.662168264389038
+401,0.9453125,0.9453125,0.8828125,0.1,7,25,1,,200,100,,16,17.558995246887207
+402,0.953125,0.9375,0.8125,0.1,7,25,2,,200,100,,16,17.660374402999878
+403,0.90625,0.921875,0.84375,0.1,7,25,3,,200,100,,16,17.598427772521973
+404,0.9375,0.9375,0.9296875,0.1,7,25,4,,200,100,,16,17.575136184692383
+405,0.953125,0.9453125,0.890625,0.1,7,25,5,,200,100,,16,17.30844473838806
+406,0.921875,0.9296875,0.90625,0.1,7,25,6,,200,100,,16,17.503999948501587
+407,0.9609375,0.9609375,0.8828125,0.1,7,25,7,,200,100,,16,17.779785633087158
+408,0.9140625,0.921875,0.875,0.1,7,25,8,,200,100,,16,17.615013360977173
+409,0.9296875,0.953125,0.890625,0.1,7,25,9,,200,100,,16,17.625157356262207
+410,0.8671875,0.890625,0.8828125,0.1,7,25,10,,200,100,,16,17.706477403640747
+411,0.8828125,0.9140625,0.828125,0.1,7,25,11,,200,100,,16,17.53357982635498
+412,0.9296875,0.9296875,0.8671875,0.1,7,25,12,,200,100,,16,17.597564697265625
+413,0.9140625,0.921875,0.8828125,0.1,7,25,13,,200,100,,16,17.418501138687134
+414,0.8984375,0.8984375,0.7578125,0.1,7,25,14,,200,100,,16,17.420319318771362
+415,0.9140625,0.9296875,0.90625,0.1,7,25,15,,200,100,,16,17.74039578437805
+416,0.8984375,0.9140625,0.8046875,0.1,7,25,16,,200,100,,16,17.412676334381104
+417,0.9296875,0.9296875,0.890625,0.1,7,25,17,,200,100,,16,17.62021255493164
+418,0.9140625,0.8984375,0.8671875,0.1,7,25,18,,200,100,,16,17.58700942993164
+419,0.9140625,0.90625,0.890625,0.1,7,25,19,,200,100,,16,17.610206842422485
+420,0.9140625,0.921875,0.890625,0.1,7,25,20,,200,100,,16,17.60498833656311
+421,0.90625,0.890625,0.8203125,0.1,7,25,21,,200,100,,16,17.27957320213318
+422,0.953125,0.9453125,0.8984375,0.1,7,25,22,,200,100,,16,17.473994255065918
+423,0.9140625,0.90625,0.84375,0.1,7,25,23,,200,100,,16,17.666244745254517
+424,0.9140625,0.9140625,0.8359375,0.1,7,25,24,,200,100,,16,17.62306046485901
+425,0.984375,0.9765625,0.9140625,0.1,7,57,0,,200,100,,16,29.60013461112976
+426,0.984375,0.984375,0.9296875,0.1,7,57,1,,200,100,,16,29.877092599868774
+427,0.96875,0.96875,0.9375,0.1,7,57,2,,200,100,,16,29.424773693084717
+428,0.953125,0.96875,0.796875,0.1,7,57,3,,200,100,,16,29.27516484260559
+429,0.9765625,0.9765625,0.9453125,0.1,7,57,4,,200,100,,16,29.070707082748413
+430,0.9921875,0.984375,0.84375,0.1,7,57,5,,200,100,,16,29.58013129234314
+431,0.953125,0.953125,0.8828125,0.1,7,57,6,,200,100,,16,29.723634719848633
+432,0.9765625,0.96875,0.953125,0.1,7,57,7,,200,100,,16,29.726585865020752
+433,0.96875,0.9765625,0.9453125,0.1,7,57,8,,200,100,,16,29.617133617401123
+434,0.9765625,0.9765625,0.9609375,0.1,7,57,9,,200,100,,16,29.807085514068604
+435,0.9375,0.953125,0.890625,0.1,7,57,10,,200,100,,16,29.23213505744934
+436,0.984375,0.984375,0.921875,0.1,7,57,11,,200,100,,16,29.37598729133606
+437,0.96875,0.953125,0.8828125,0.1,7,57,12,,200,100,,16,29.02141761779785
+438,0.9609375,0.9453125,0.875,0.1,7,57,13,,200,100,,16,29.617659330368042
+439,0.9765625,0.9765625,0.9296875,0.1,7,57,14,,200,100,,16,29.76816964149475
+440,0.953125,0.9609375,0.875,0.1,7,57,15,,200,100,,16,29.41464066505432
+441,0.9453125,0.9453125,0.9140625,0.1,7,57,16,,200,100,,16,29.427026748657227
+442,0.9765625,0.9765625,0.9140625,0.1,7,57,17,,200,100,,16,29.772083044052124
+443,0.96875,0.9609375,0.9609375,0.1,7,57,18,,200,100,,16,29.24649143218994
+444,0.9921875,0.984375,0.9296875,0.1,7,57,19,,200,100,,16,29.387990951538086
+445,0.9921875,0.9921875,0.875,0.1,7,57,20,,200,100,,16,29.142889976501465
+446,0.984375,0.9609375,0.9453125,0.1,7,57,21,,200,100,,16,29.269009590148926
+447,0.953125,0.953125,0.84375,0.1,7,57,22,,200,100,,16,29.646749258041382
+448,0.96875,0.9765625,0.9609375,0.1,7,57,23,,200,100,,16,29.367650985717773
+449,0.9765625,0.96875,0.96875,0.1,7,57,24,,200,100,,16,29.395566701889038
+450,0.6796875,0.68359375,0.625,0.1,8,7,0,,400,100,,16,26.738548040390015
+451,0.671875,0.71484375,0.609375,0.1,8,7,1,,400,100,,16,26.828211545944214
+452,0.7109375,0.6953125,0.671875,0.1,8,7,2,,400,100,,16,26.685184955596924
+453,0.69921875,0.69140625,0.65625,0.1,8,7,3,,400,100,,16,26.64614748954773
+454,0.66796875,0.67578125,0.60546875,0.1,8,7,4,,400,100,,16,26.48786234855652
+455,0.68359375,0.6875,0.6484375,0.1,8,7,5,,400,100,,16,26.90431547164917
+456,0.671875,0.6875,0.640625,0.1,8,7,6,,400,100,,16,26.648452281951904
+457,0.6796875,0.6875,0.63671875,0.1,8,7,7,,400,100,,16,26.72761631011963
+458,0.671875,0.69140625,0.609375,0.1,8,7,8,,400,100,,16,26.527153491973877
+459,0.6328125,0.65625,0.59765625,0.1,8,7,9,,400,100,,16,26.674432516098022
+460,0.640625,0.66015625,0.58203125,0.1,8,7,10,,400,100,,16,26.65029788017273
+461,0.67578125,0.68359375,0.66015625,0.1,8,7,11,,400,100,,16,26.529667139053345
+462,0.6796875,0.6796875,0.59765625,0.1,8,7,12,,400,100,,16,26.41219401359558
+463,0.75390625,0.76171875,0.6953125,0.1,8,7,13,,400,100,,16,26.86212158203125
+464,0.66796875,0.66796875,0.60546875,0.1,8,7,14,,400,100,,16,26.580434560775757
+465,0.66015625,0.68359375,0.5859375,0.1,8,7,15,,400,100,,16,26.714037895202637
+466,0.67578125,0.71484375,0.6171875,0.1,8,7,16,,400,100,,16,26.51564860343933
+467,0.6328125,0.64453125,0.62890625,0.1,8,7,17,,400,100,,16,26.71179485321045
+468,0.66796875,0.68359375,0.59765625,0.1,8,7,18,,400,100,,16,26.5764217376709
+469,0.65234375,0.6875,0.59765625,0.1,8,7,19,,400,100,,16,26.536621570587158
+470,0.6875,0.703125,0.6015625,0.1,8,7,20,,400,100,,16,26.426705360412598
+471,0.65625,0.65625,0.6015625,0.1,8,7,21,,400,100,,16,26.83888339996338
+472,0.69921875,0.703125,0.6484375,0.1,8,7,22,,400,100,,16,26.569628953933716
+473,0.6484375,0.6875,0.58984375,0.1,8,7,23,,400,100,,16,26.66654396057129
+474,0.6796875,0.67578125,0.64453125,0.1,8,7,24,,400,100,,16,26.494081258773804
+475,0.77734375,0.78125,0.76953125,0.1,8,25,0,,400,100,,16,39.592689514160156
+476,0.82421875,0.81640625,0.78515625,0.1,8,25,1,,400,100,,16,39.62098574638367
+477,0.82421875,0.83203125,0.7578125,0.1,8,25,2,,400,100,,16,39.2376503944397
+478,0.78125,0.7734375,0.6796875,0.1,8,25,3,,400,100,,16,39.47959280014038
+479,0.796875,0.8046875,0.76953125,0.1,8,25,4,,400,100,,16,39.952696800231934
+480,0.765625,0.78515625,0.69140625,0.1,8,25,5,,400,100,,16,39.547807693481445
+481,0.77734375,0.76171875,0.734375,0.1,8,25,6,,400,100,,16,39.680240869522095
+482,0.76171875,0.79296875,0.76953125,0.1,8,25,7,,400,100,,16,39.89182925224304
+483,0.75,0.796875,0.73828125,0.1,8,25,8,,400,100,,16,39.56863307952881
+484,0.77734375,0.796875,0.76171875,0.1,8,25,9,,400,100,,16,39.60968255996704
+485,0.76953125,0.734375,0.72265625,0.1,8,25,10,,400,100,,16,39.19947028160095
+486,0.8125,0.82421875,0.80859375,0.1,8,25,11,,400,100,,16,39.615253925323486
+487,0.76953125,0.80078125,0.69921875,0.1,8,25,12,,400,100,,16,39.91619420051575
+488,0.78515625,0.79296875,0.734375,0.1,8,25,13,,400,100,,16,39.52684760093689
+489,0.80078125,0.80078125,0.72265625,0.1,8,25,14,,400,100,,16,39.64299154281616
+490,0.78515625,0.7890625,0.7265625,0.1,8,25,15,,400,100,,16,39.84526324272156
+491,0.7421875,0.75,0.6640625,0.1,8,25,16,,400,100,,16,39.661689043045044
+492,0.7421875,0.76953125,0.71875,0.1,8,25,17,,400,100,,16,39.4986777305603
+493,0.7890625,0.79296875,0.74609375,0.1,8,25,18,,400,100,,16,39.35331654548645
+494,0.77734375,0.78125,0.75,0.1,8,25,19,,400,100,,16,39.42121911048889
+495,0.796875,0.80078125,0.734375,0.1,8,25,20,,400,100,,16,39.9761438369751
+496,0.77734375,0.76953125,0.73828125,0.1,8,25,21,,400,100,,16,39.590503215789795
+497,0.8203125,0.82421875,0.7109375,0.1,8,25,22,,400,100,,16,39.91190266609192
+498,0.79296875,0.7890625,0.78125,0.1,8,25,23,,400,100,,16,39.896321296691895
+499,0.8203125,0.8203125,0.765625,0.1,8,25,24,,400,100,,16,39.7105438709259
+500,0.88671875,0.875,0.87109375,0.1,8,57,0,,400,100,,16,62.93982195854187
+501,0.8828125,0.87890625,0.83203125,0.1,8,57,1,,400,100,,16,62.03135657310486
+502,0.8828125,0.890625,0.85546875,0.1,8,57,2,,400,100,,16,63.08994150161743
+503,0.87890625,0.8671875,0.84765625,0.1,8,57,3,,400,100,,16,63.47326159477234
+504,0.85546875,0.859375,0.796875,0.1,8,57,4,,400,100,,16,62.87795829772949
+505,0.87890625,0.87890625,0.78515625,0.1,8,57,5,,400,100,,16,63.0032913684845
+506,0.8671875,0.86328125,0.86328125,0.1,8,57,6,,400,100,,16,63.74262762069702
+507,0.8984375,0.88671875,0.86328125,0.1,8,57,7,,400,100,,16,62.95278453826904
+508,0.8984375,0.890625,0.8203125,0.1,8,57,8,,400,100,,16,62.97239303588867
+509,0.9140625,0.9140625,0.8671875,0.1,8,57,9,,400,100,,16,62.026073694229126
+510,0.88671875,0.89453125,0.87109375,0.1,8,57,10,,400,100,,16,63.398465156555176
+511,0.8984375,0.8984375,0.87109375,0.1,8,57,11,,400,100,,16,64.4301266670227
+512,0.90625,0.88671875,0.875,0.1,8,57,12,,400,100,,16,63.04602003097534
+513,0.859375,0.8515625,0.8203125,0.1,8,57,13,,400,100,,16,63.05620098114014
+514,0.84375,0.84765625,0.80078125,0.1,8,57,14,,400,100,,16,63.65686392784119
+515,0.8671875,0.8671875,0.81640625,0.1,8,57,15,,400,100,,16,62.931920766830444
+516,0.87109375,0.86328125,0.8125,0.1,8,57,16,,400,100,,16,63.06161832809448
+517,0.890625,0.8828125,0.83984375,0.1,8,57,17,,400,100,,16,62.27687478065491
+518,0.90625,0.90625,0.87109375,0.1,8,57,18,,400,100,,16,63.14973258972168
+519,0.87109375,0.87109375,0.859375,0.1,8,57,19,,400,100,,16,63.31533980369568
+520,0.87890625,0.8828125,0.8515625,0.1,8,57,20,,400,100,,16,63.01797556877136
+521,0.87109375,0.875,0.83203125,0.1,8,57,21,,400,100,,16,63.514989376068115
+522,0.8828125,0.890625,0.78515625,0.1,8,57,22,,400,100,,16,63.92073845863342
+523,0.86328125,0.875,0.84765625,0.1,8,57,23,,400,100,,16,62.87836670875549
+524,0.859375,0.8671875,0.828125,0.1,8,57,24,,400,100,,16,62.89714574813843
+525,0.580078125,0.6015625,0.560546875,0.1,9,7,0,,800,100,,16,79.1671495437622
+526,0.583984375,0.60546875,0.537109375,0.1,9,7,1,,800,100,,16,78.87187719345093
+527,0.61328125,0.619140625,0.576171875,0.1,9,7,2,,800,100,,16,79.17107796669006
+528,0.6171875,0.611328125,0.576171875,0.1,9,7,3,,800,100,,16,78.75194191932678
+529,0.576171875,0.615234375,0.560546875,0.1,9,7,4,,800,100,,16,79.21482372283936
+530,0.59375,0.595703125,0.552734375,0.1,9,7,5,,800,100,,16,78.75323128700256
+531,0.603515625,0.603515625,0.59765625,0.1,9,7,6,,800,100,,16,78.99745202064514
+532,0.6015625,0.61328125,0.58984375,0.1,9,7,7,,800,100,,16,78.51195478439331
+533,0.587890625,0.6171875,0.560546875,0.1,9,7,8,,800,100,,16,78.75120949745178
+534,0.611328125,0.611328125,0.572265625,0.1,9,7,9,,800,100,,16,78.22176790237427
+535,0.587890625,0.611328125,0.576171875,0.1,9,7,10,,800,100,,16,79.03581094741821
+536,0.595703125,0.58984375,0.572265625,0.1,9,7,11,,800,100,,16,78.65696287155151
+537,0.58984375,0.60546875,0.529296875,0.1,9,7,12,,800,100,,16,79.16632223129272
+538,0.58984375,0.59765625,0.544921875,0.1,9,7,13,,800,100,,16,78.64985370635986
+539,0.580078125,0.61328125,0.55078125,0.1,9,7,14,,800,100,,16,78.82675814628601
+540,0.59765625,0.603515625,0.58203125,0.1,9,7,15,,800,100,,16,78.59513211250305
+541,0.623046875,0.626953125,0.587890625,0.1,9,7,16,,800,100,,16,78.52578496932983
+542,0.572265625,0.62109375,0.55859375,0.1,9,7,17,,800,100,,16,78.2648503780365
+543,0.58984375,0.607421875,0.5390625,0.1,9,7,18,,800,100,,16,79.22042298316956
+544,0.58203125,0.599609375,0.546875,0.1,9,7,19,,800,100,,16,78.63611054420471
+545,0.603515625,0.62109375,0.578125,0.1,9,7,20,,800,100,,16,79.07991003990173
+546,0.58984375,0.625,0.560546875,0.1,9,7,21,,800,100,,16,78.55008840560913
+547,0.595703125,0.61328125,0.5703125,0.1,9,7,22,,800,100,,16,78.75604510307312
+548,0.572265625,0.591796875,0.537109375,0.1,9,7,23,,800,100,,16,78.52245378494263
+549,0.572265625,0.595703125,0.564453125,0.1,9,7,24,,800,100,,16,78.57396340370178
+550,0.685546875,0.6796875,0.658203125,0.1,9,25,0,,800,100,,16,105.27009320259094
+551,0.62890625,0.658203125,0.59765625,0.1,9,25,1,,800,100,,16,106.24179196357727
+552,0.650390625,0.6484375,0.619140625,0.1,9,25,2,,800,100,,16,105.53585076332092
+553,0.646484375,0.64453125,0.61328125,0.1,9,25,3,,800,100,,16,106.37769722938538
+554,0.65625,0.669921875,0.625,0.1,9,25,4,,800,100,,16,106.31206488609314
+555,0.6484375,0.650390625,0.615234375,0.1,9,25,5,,800,100,,16,105.8237636089325
+556,0.67578125,0.658203125,0.64453125,0.1,9,25,6,,800,100,,16,105.51622653007507
+557,0.646484375,0.673828125,0.595703125,0.1,9,25,7,,800,100,,16,105.27367806434631
+558,0.689453125,0.69140625,0.642578125,0.1,9,25,8,,800,100,,16,105.73417258262634
+559,0.6484375,0.666015625,0.580078125,0.1,9,25,9,,800,100,,16,106.39395213127136
+560,0.66015625,0.669921875,0.587890625,0.1,9,25,10,,800,100,,16,105.47979927062988
+561,0.646484375,0.65234375,0.568359375,0.1,9,25,11,,800,100,,16,106.29671692848206
+562,0.671875,0.65625,0.6328125,0.1,9,25,12,,800,100,,16,106.57616209983826
+563,0.669921875,0.677734375,0.66015625,0.1,9,25,13,,800,100,,16,105.82686305046082
+564,0.658203125,0.66796875,0.63671875,0.1,9,25,14,,800,100,,16,105.8486557006836
+565,0.6796875,0.66796875,0.666015625,0.1,9,25,15,,800,100,,16,105.47785472869873
+566,0.634765625,0.66796875,0.619140625,0.1,9,25,16,,800,100,,16,105.72207570075989
+567,0.67578125,0.669921875,0.599609375,0.1,9,25,17,,800,100,,16,106.03552293777466
+568,0.64453125,0.6640625,0.638671875,0.1,9,25,18,,800,100,,16,105.62203526496887
+569,0.681640625,0.650390625,0.630859375,0.1,9,25,19,,800,100,,16,106.21441125869751
+570,0.646484375,0.646484375,0.609375,0.1,9,25,20,,800,100,,16,106.62009572982788
+571,0.68359375,0.666015625,0.625,0.1,9,25,21,,800,100,,16,105.80094003677368
+572,0.6484375,0.662109375,0.58984375,0.1,9,25,22,,800,100,,16,105.45069098472595
+573,0.642578125,0.662109375,0.619140625,0.1,9,25,23,,800,100,,16,105.3966281414032
+574,0.70703125,0.66796875,0.63671875,0.1,9,25,24,,800,100,,16,105.84110116958618
+575,0.70703125,0.732421875,0.654296875,0.1,9,57,0,,800,100,,16,154.76607966423035
+576,0.77734375,0.76953125,0.70703125,0.1,9,57,1,,800,100,,16,153.6509885787964
+577,0.7421875,0.740234375,0.71484375,0.1,9,57,2,,800,100,,16,155.8952944278717
+578,0.755859375,0.75,0.72265625,0.1,9,57,3,,800,100,,16,156.52683663368225
+579,0.70703125,0.708984375,0.60546875,0.1,9,57,4,,800,100,,16,154.15549182891846
+580,0.71875,0.7265625,0.669921875,0.1,9,57,5,,800,100,,16,153.94719576835632
+581,0.701171875,0.73046875,0.662109375,0.1,9,57,6,,800,100,,16,152.5177047252655
+582,0.783203125,0.759765625,0.716796875,0.1,9,57,7,,800,100,,16,155.7990756034851
+583,0.755859375,0.7578125,0.7265625,0.1,9,57,8,,800,100,,16,155.36183381080627
+584,0.720703125,0.732421875,0.67578125,0.1,9,57,9,,800,100,,16,153.87495803833008
+585,0.75,0.7421875,0.740234375,0.1,9,57,10,,800,100,,16,156.0883367061615
+586,0.732421875,0.73828125,0.703125,0.1,9,57,11,,800,100,,16,156.99501776695251
+587,0.7578125,0.767578125,0.6796875,0.1,9,57,12,,800,100,,16,153.65851640701294
+588,0.716796875,0.728515625,0.6796875,0.1,9,57,13,,800,100,,16,155.0822937488556
+589,0.74609375,0.76171875,0.689453125,0.1,9,57,14,,800,100,,16,153.65474438667297
+590,0.720703125,0.72265625,0.69140625,0.1,9,57,15,,800,100,,16,155.9614658355713
+591,0.74609375,0.734375,0.708984375,0.1,9,57,16,,800,100,,16,155.26390624046326
+592,0.703125,0.7265625,0.681640625,0.1,9,57,17,,800,100,,16,153.97386026382446
+593,0.763671875,0.76171875,0.705078125,0.1,9,57,18,,800,100,,16,155.94668197631836
+594,0.734375,0.740234375,0.708984375,0.1,9,57,19,,800,100,,16,156.29123210906982
+595,0.720703125,0.73046875,0.673828125,0.1,9,57,20,,800,100,,16,153.78992986679077
+596,0.71484375,0.71875,0.697265625,0.1,9,57,21,,800,100,,16,153.7270679473877
+597,0.720703125,0.724609375,0.705078125,0.1,9,57,22,,800,100,,16,153.55351662635803
+598,0.73046875,0.728515625,0.6953125,0.1,9,57,23,,800,100,,16,155.169575214386
+599,0.767578125,0.75,0.740234375,0.1,9,57,24,,800,100,,16,155.5815508365631
+600,0.765625,0.8125,0.75,0.2,6,7,0,,100,100,,16,5.963991403579712
+601,0.765625,0.828125,0.6875,0.2,6,7,1,,100,100,,16,5.877989292144775
+602,0.828125,0.859375,0.734375,0.2,6,7,2,,100,100,,16,5.918730735778809
+603,0.78125,0.765625,0.734375,0.2,6,7,3,,100,100,,16,5.913114547729492
+604,0.796875,0.828125,0.6875,0.2,6,7,4,,100,100,,16,5.876013994216919
+605,0.765625,0.78125,0.640625,0.2,6,7,5,,100,100,,16,5.902435302734375
+606,0.78125,0.828125,0.75,0.2,6,7,6,,100,100,,16,5.823002576828003
+607,0.765625,0.796875,0.75,0.2,6,7,7,,100,100,,16,5.92183256149292
+608,0.75,0.765625,0.703125,0.2,6,7,8,,100,100,,16,5.851727485656738
+609,0.796875,0.8125,0.65625,0.2,6,7,9,,100,100,,16,5.888010263442993
+610,0.8125,0.796875,0.765625,0.2,6,7,10,,100,100,,16,5.933988094329834
+611,0.640625,0.640625,0.59375,0.2,6,7,11,,100,100,,16,5.856449365615845
+612,0.828125,0.8125,0.75,0.2,6,7,12,,100,100,,16,5.9375975131988525
+613,0.84375,0.828125,0.8125,0.2,6,7,13,,100,100,,16,5.945014476776123
+614,0.734375,0.765625,0.625,0.2,6,7,14,,100,100,,16,5.826022386550903
+615,0.765625,0.796875,0.65625,0.2,6,7,15,,100,100,,16,5.923413276672363
+616,0.8125,0.78125,0.6875,0.2,6,7,16,,100,100,,16,5.876988410949707
+617,0.78125,0.8125,0.71875,0.2,6,7,17,,100,100,,16,5.887010097503662
+618,0.8125,0.796875,0.71875,0.2,6,7,18,,100,100,,16,5.906991481781006
+619,0.796875,0.796875,0.609375,0.2,6,7,19,,100,100,,16,5.93899130821228
+620,0.75,0.78125,0.6875,0.2,6,7,20,,100,100,,16,5.878004550933838
+621,0.703125,0.75,0.6875,0.2,6,7,21,,100,100,,16,5.977996349334717
+622,0.78125,0.75,0.765625,0.2,6,7,22,,100,100,,16,5.826996564865112
+623,0.734375,0.75,0.671875,0.2,6,7,23,,100,100,,16,5.920478582382202
+624,0.8125,0.8125,0.75,0.2,6,7,24,,100,100,,16,5.882012367248535
+625,0.921875,0.921875,0.859375,0.2,6,25,0,,100,100,,16,9.08601975440979
+626,0.890625,0.921875,0.71875,0.2,6,25,1,,100,100,,16,9.103726148605347
+627,0.875,0.875,0.78125,0.2,6,25,2,,100,100,,16,9.08199167251587
+628,0.84375,0.8125,0.765625,0.2,6,25,3,,100,100,,16,9.015995264053345
+629,0.921875,0.921875,0.890625,0.2,6,25,4,,100,100,,16,8.948002099990845
+630,0.890625,0.875,0.84375,0.2,6,25,5,,100,100,,16,9.007238149642944
+631,0.921875,0.921875,0.765625,0.2,6,25,6,,100,100,,16,9.18163013458252
+632,0.90625,0.921875,0.828125,0.2,6,25,7,,100,100,,16,9.002012491226196
+633,0.9375,0.9375,0.9375,0.2,6,25,8,,100,100,,16,9.065993309020996
+634,0.859375,0.90625,0.8125,0.2,6,25,9,,100,100,,16,9.03200912475586
+635,0.9375,0.90625,0.859375,0.2,6,25,10,,100,100,,16,9.044004201889038
+636,0.90625,0.921875,0.84375,0.2,6,25,11,,100,100,,16,9.026014804840088
+637,0.875,0.875,0.78125,0.2,6,25,12,,100,100,,16,8.945000171661377
+638,0.859375,0.875,0.8125,0.2,6,25,13,,100,100,,16,9.09501028060913
+639,0.953125,0.96875,0.828125,0.2,6,25,14,,100,100,,16,9.161740064620972
+640,0.921875,0.90625,0.78125,0.2,6,25,15,,100,100,,16,9.108736753463745
+641,0.984375,0.96875,0.921875,0.2,6,25,16,,100,100,,16,9.048998355865479
+642,0.9375,0.953125,0.859375,0.2,6,25,17,,100,100,,16,9.077940702438354
+643,0.796875,0.78125,0.71875,0.2,6,25,18,,100,100,,16,9.04453706741333
+644,0.9375,0.90625,0.828125,0.2,6,25,19,,100,100,,16,9.024991273880005
+645,0.8125,0.84375,0.75,0.2,6,25,20,,100,100,,16,9.015135049819946
+646,0.890625,0.921875,0.796875,0.2,6,25,21,,100,100,,16,8.963989496231079
+647,0.890625,0.921875,0.890625,0.2,6,25,22,,100,100,,16,9.162144184112549
+648,0.890625,0.890625,0.875,0.2,6,25,23,,100,100,,16,9.054988622665405
+649,0.921875,0.90625,0.90625,0.2,6,25,24,,100,100,,16,9.043584823608398
+650,0.90625,0.921875,0.8125,0.2,6,57,0,,100,100,,16,15.08565092086792
+651,0.90625,0.90625,0.8125,0.2,6,57,1,,100,100,,16,14.82758641242981
+652,0.9375,0.9375,0.828125,0.2,6,57,2,,100,100,,16,14.851988315582275
+653,0.984375,0.984375,0.953125,0.2,6,57,3,,100,100,,16,14.803093910217285
+654,0.984375,0.96875,0.9375,0.2,6,57,4,,100,100,,16,14.921996593475342
+655,0.953125,0.953125,0.78125,0.2,6,57,5,,100,100,,16,15.08324146270752
+656,0.9375,0.921875,0.78125,0.2,6,57,6,,100,100,,16,14.857017040252686
+657,0.96875,0.984375,0.921875,0.2,6,57,7,,100,100,,16,14.91012954711914
+658,1.0,0.96875,0.84375,0.2,6,57,8,,100,100,,16,15.157186508178711
+659,0.984375,0.96875,0.984375,0.2,6,57,9,,100,100,,16,14.808578729629517
+660,0.953125,0.953125,0.796875,0.2,6,57,10,,100,100,,16,14.858022928237915
+661,0.953125,0.96875,0.890625,0.2,6,57,11,,100,100,,16,14.593986511230469
+662,0.9375,0.953125,0.875,0.2,6,57,12,,100,100,,16,14.800262928009033
+663,0.96875,0.9375,0.921875,0.2,6,57,13,,100,100,,16,15.070328712463379
+664,0.953125,0.9375,0.84375,0.2,6,57,14,,100,100,,16,14.853543758392334
+665,0.953125,0.9375,0.875,0.2,6,57,15,,100,100,,16,14.942013263702393
+666,0.9375,0.90625,0.859375,0.2,6,57,16,,100,100,,16,15.011208534240723
+667,0.96875,0.953125,0.953125,0.2,6,57,17,,100,100,,16,14.84800672531128
+668,0.96875,0.984375,0.90625,0.2,6,57,18,,100,100,,16,14.84610652923584
+669,0.953125,0.96875,0.84375,0.2,6,57,19,,100,100,,16,14.607944011688232
+670,0.953125,0.96875,0.875,0.2,6,57,20,,100,100,,16,14.83065152168274
+671,0.953125,0.9375,0.90625,0.2,6,57,21,,100,100,,16,15.078267335891724
+672,0.984375,0.984375,0.953125,0.2,6,57,22,,100,100,,16,14.857173681259155
+673,0.96875,0.96875,0.875,0.2,6,57,23,,100,100,,16,14.895993709564209
+674,0.96875,0.96875,0.859375,0.2,6,57,24,,100,100,,16,14.99717903137207
+675,0.71875,0.703125,0.6484375,0.2,7,7,0,,200,100,,16,11.163334846496582
+676,0.640625,0.6640625,0.6171875,0.2,7,7,1,,200,100,,16,11.031567096710205
+677,0.65625,0.6875,0.6015625,0.2,7,7,2,,200,100,,16,11.01101016998291
+678,0.6640625,0.7109375,0.625,0.2,7,7,3,,200,100,,16,10.975711822509766
+679,0.6484375,0.6484375,0.5703125,0.2,7,7,4,,200,100,,16,11.238090991973877
+680,0.6953125,0.71875,0.640625,0.2,7,7,5,,200,100,,16,11.093446254730225
+681,0.6796875,0.6796875,0.5859375,0.2,7,7,6,,200,100,,16,11.093549966812134
+682,0.6875,0.7109375,0.6484375,0.2,7,7,7,,200,100,,16,11.086006879806519
+683,0.6640625,0.6640625,0.6484375,0.2,7,7,8,,200,100,,16,11.02674651145935
+684,0.6796875,0.6796875,0.59375,0.2,7,7,9,,200,100,,16,11.039825916290283
+685,0.6640625,0.6796875,0.578125,0.2,7,7,10,,200,100,,16,11.033375024795532
+686,0.6953125,0.65625,0.6171875,0.2,7,7,11,,200,100,,16,10.983396291732788
+687,0.65625,0.6640625,0.65625,0.2,7,7,12,,200,100,,16,11.179810047149658
+688,0.65625,0.65625,0.6171875,0.2,7,7,13,,200,100,,16,11.054646015167236
+689,0.6796875,0.6875,0.640625,0.2,7,7,14,,200,100,,16,11.141597747802734
+690,0.75,0.6953125,0.6953125,0.2,7,7,15,,200,100,,16,11.054009199142456
+691,0.6484375,0.6640625,0.625,0.2,7,7,16,,200,100,,16,11.087157011032104
+692,0.7109375,0.7265625,0.6640625,0.2,7,7,17,,200,100,,16,11.204577922821045
+693,0.6796875,0.6875,0.6484375,0.2,7,7,18,,200,100,,16,11.03101134300232
+694,0.6875,0.671875,0.5703125,0.2,7,7,19,,200,100,,16,10.883023023605347
+695,0.65625,0.65625,0.5546875,0.2,7,7,20,,200,100,,16,11.17310643196106
+696,0.65625,0.6796875,0.625,0.2,7,7,21,,200,100,,16,11.106985569000244
+697,0.6484375,0.625,0.5390625,0.2,7,7,22,,200,100,,16,11.01250433921814
+698,0.6796875,0.6796875,0.6328125,0.2,7,7,23,,200,100,,16,10.966019868850708
+699,0.734375,0.7109375,0.6953125,0.2,7,7,24,,200,100,,16,11.116465091705322
+700,0.7421875,0.7421875,0.6796875,0.2,7,25,0,,200,100,,16,17.445565938949585
+701,0.8046875,0.796875,0.8125,0.2,7,25,1,,200,100,,16,17.283523321151733
+702,0.8203125,0.765625,0.6328125,0.2,7,25,2,,200,100,,16,17.3889799118042
+703,0.8125,0.796875,0.7578125,0.2,7,25,3,,200,100,,16,17.539457082748413
+704,0.8203125,0.796875,0.734375,0.2,7,25,4,,200,100,,16,17.407537698745728
+705,0.71875,0.75,0.6796875,0.2,7,25,5,,200,100,,16,17.51200580596924
+706,0.7890625,0.7734375,0.7421875,0.2,7,25,6,,200,100,,16,17.496985912322998
+707,0.734375,0.7734375,0.7109375,0.2,7,25,7,,200,100,,16,17.4553542137146
+708,0.796875,0.8203125,0.7421875,0.2,7,25,8,,200,100,,16,17.522010803222656
+709,0.71875,0.75,0.625,0.2,7,25,9,,200,100,,16,17.218070030212402
+710,0.7734375,0.7578125,0.59375,0.2,7,25,10,,200,100,,16,17.30504322052002
+711,0.8203125,0.7890625,0.7578125,0.2,7,25,11,,200,100,,16,17.682722568511963
+712,0.765625,0.765625,0.640625,0.2,7,25,12,,200,100,,16,17.483609437942505
+713,0.7421875,0.71875,0.6796875,0.2,7,25,13,,200,100,,16,17.43802547454834
+714,0.734375,0.71875,0.7265625,0.2,7,25,14,,200,100,,16,17.581013441085815
+715,0.78125,0.7890625,0.6953125,0.2,7,25,15,,200,100,,16,17.582453727722168
+716,0.8125,0.796875,0.75,0.2,7,25,16,,200,100,,16,17.461991548538208
+717,0.7578125,0.8046875,0.671875,0.2,7,25,17,,200,100,,16,17.200794458389282
+718,0.796875,0.78125,0.703125,0.2,7,25,18,,200,100,,16,17.405112981796265
+719,0.7109375,0.71875,0.65625,0.2,7,25,19,,200,100,,16,17.57348084449768
+720,0.796875,0.796875,0.7265625,0.2,7,25,20,,200,100,,16,17.495996475219727
+721,0.765625,0.78125,0.6875,0.2,7,25,21,,200,100,,16,17.47364902496338
+722,0.734375,0.7578125,0.671875,0.2,7,25,22,,200,100,,16,17.504013776779175
+723,0.8125,0.7890625,0.703125,0.2,7,25,23,,200,100,,16,17.47382354736328
+724,0.796875,0.796875,0.734375,0.2,7,25,24,,200,100,,16,17.41799259185791
+725,0.90625,0.90625,0.875,0.2,7,57,0,,200,100,,16,28.676185369491577
+726,0.8671875,0.84375,0.8046875,0.2,7,57,1,,200,100,,16,29.06569194793701
+727,0.8203125,0.8515625,0.75,0.2,7,57,2,,200,100,,16,29.20975971221924
+728,0.828125,0.8359375,0.765625,0.2,7,57,3,,200,100,,16,29.031054258346558
+729,0.8984375,0.890625,0.84375,0.2,7,57,4,,200,100,,16,29.18296718597412
+730,0.8671875,0.828125,0.75,0.2,7,57,5,,200,100,,16,29.41517663002014
+731,0.8828125,0.8828125,0.8046875,0.2,7,57,6,,200,100,,16,28.94330883026123
+732,0.90625,0.921875,0.828125,0.2,7,57,7,,200,100,,16,29.11839723587036
+733,0.8671875,0.84375,0.7578125,0.2,7,57,8,,200,100,,16,28.535170793533325
+734,0.90625,0.90625,0.828125,0.2,7,57,9,,200,100,,16,28.980674505233765
+735,0.8203125,0.84375,0.7421875,0.2,7,57,10,,200,100,,16,29.288350582122803
+736,0.84375,0.8203125,0.7421875,0.2,7,57,11,,200,100,,16,29.094629526138306
+737,0.859375,0.875,0.7734375,0.2,7,57,12,,200,100,,16,29.04108476638794
+738,0.8515625,0.859375,0.7578125,0.2,7,57,13,,200,100,,16,29.249117136001587
+739,0.8515625,0.8515625,0.78125,0.2,7,57,14,,200,100,,16,28.875886917114258
+740,0.8828125,0.8515625,0.8125,0.2,7,57,15,,200,100,,16,28.836891412734985
+741,0.8984375,0.8671875,0.765625,0.2,7,57,16,,200,100,,16,28.485169649124146
+742,0.8359375,0.8359375,0.7109375,0.2,7,57,17,,200,100,,16,28.699658155441284
+743,0.875,0.890625,0.7890625,0.2,7,57,18,,200,100,,16,29.29448103904724
+744,0.859375,0.8984375,0.828125,0.2,7,57,19,,200,100,,16,29.026054859161377
+745,0.84375,0.84375,0.765625,0.2,7,57,20,,200,100,,16,29.06356143951416
+746,0.8671875,0.859375,0.8125,0.2,7,57,21,,200,100,,16,29.298376321792603
+747,0.8359375,0.84375,0.8359375,0.2,7,57,22,,200,100,,16,29.064067840576172
+748,0.8359375,0.8359375,0.78125,0.2,7,57,23,,200,100,,16,29.2247896194458
+749,0.875,0.8515625,0.78125,0.2,7,57,24,,200,100,,16,28.706737995147705
+750,0.55859375,0.60546875,0.52734375,0.2,8,7,0,,400,100,,16,26.420573949813843
+751,0.59765625,0.63671875,0.54296875,0.2,8,7,1,,400,100,,16,26.860235691070557
+752,0.69140625,0.65625,0.60546875,0.2,8,7,2,,400,100,,16,26.60097098350525
+753,0.59375,0.6328125,0.53125,0.2,8,7,3,,400,100,,16,26.68199396133423
+754,0.59375,0.6015625,0.48046875,0.2,8,7,4,,400,100,,16,26.538097620010376
+755,0.58984375,0.58984375,0.52734375,0.2,8,7,5,,400,100,,16,26.671566247940063
+756,0.6015625,0.60546875,0.55078125,0.2,8,7,6,,400,100,,16,26.59502673149109
+757,0.58984375,0.6328125,0.54296875,0.2,8,7,7,,400,100,,16,26.556010961532593
+758,0.5859375,0.578125,0.53515625,0.2,8,7,8,,400,100,,16,26.335707426071167
+759,0.56640625,0.58984375,0.5078125,0.2,8,7,9,,400,100,,16,26.90636944770813
+760,0.57421875,0.57421875,0.55078125,0.2,8,7,10,,400,100,,16,26.655652284622192
+761,0.578125,0.63671875,0.55859375,0.2,8,7,11,,400,100,,16,26.692012071609497
+762,0.55859375,0.60546875,0.53125,0.2,8,7,12,,400,100,,16,26.437670707702637
+763,0.5859375,0.61328125,0.5390625,0.2,8,7,13,,400,100,,16,26.626633167266846
+764,0.546875,0.56640625,0.48828125,0.2,8,7,14,,400,100,,16,26.5722713470459
+765,0.578125,0.55859375,0.53125,0.2,8,7,15,,400,100,,16,26.50643825531006
+766,0.6171875,0.6015625,0.6015625,0.2,8,7,16,,400,100,,16,26.429214477539062
+767,0.6328125,0.62109375,0.5625,0.2,8,7,17,,400,100,,16,26.731773376464844
+768,0.58203125,0.625,0.5234375,0.2,8,7,18,,400,100,,16,26.58332371711731
+769,0.57421875,0.578125,0.5546875,0.2,8,7,19,,400,100,,16,26.70590567588806
+770,0.55859375,0.6015625,0.53125,0.2,8,7,20,,400,100,,16,26.468363046646118
+771,0.58203125,0.6328125,0.55859375,0.2,8,7,21,,400,100,,16,26.653011798858643
+772,0.60546875,0.62109375,0.59765625,0.2,8,7,22,,400,100,,16,26.577969551086426
+773,0.6328125,0.59765625,0.5625,0.2,8,7,23,,400,100,,16,26.481730222702026
+774,0.60546875,0.60546875,0.51171875,0.2,8,7,24,,400,100,,16,26.31199312210083
+775,0.6015625,0.64453125,0.546875,0.2,8,25,0,,400,100,,16,39.876314640045166
+776,0.6484375,0.67578125,0.6015625,0.2,8,25,1,,400,100,,16,39.54773926734924
+777,0.6328125,0.640625,0.62109375,0.2,8,25,2,,400,100,,16,39.79860711097717
+778,0.65234375,0.6015625,0.58203125,0.2,8,25,3,,400,100,,16,39.706008195877075
+779,0.64453125,0.7265625,0.62109375,0.2,8,25,4,,400,100,,16,39.787275314331055
+780,0.625,0.66796875,0.578125,0.2,8,25,5,,400,100,,16,39.468268394470215
+781,0.68359375,0.6796875,0.64453125,0.2,8,25,6,,400,100,,16,39.39379954338074
+782,0.63671875,0.64453125,0.58203125,0.2,8,25,7,,400,100,,16,39.4095196723938
+783,0.6484375,0.6484375,0.6171875,0.2,8,25,8,,400,100,,16,40.00562524795532
+784,0.6328125,0.6328125,0.6015625,0.2,8,25,9,,400,100,,16,39.47054433822632
+785,0.6640625,0.65625,0.6484375,0.2,8,25,10,,400,100,,16,39.64454174041748
+786,0.6171875,0.640625,0.5703125,0.2,8,25,11,,400,100,,16,39.78866124153137
+787,0.6875,0.67578125,0.640625,0.2,8,25,12,,400,100,,16,39.55102801322937
+788,0.69921875,0.68359375,0.63671875,0.2,8,25,13,,400,100,,16,39.345863342285156
+789,0.64453125,0.625,0.578125,0.2,8,25,14,,400,100,,16,39.17391324043274
+790,0.640625,0.65234375,0.62109375,0.2,8,25,15,,400,100,,16,39.482487201690674
+791,0.65625,0.63671875,0.6171875,0.2,8,25,16,,400,100,,16,39.79836630821228
+792,0.63671875,0.65625,0.609375,0.2,8,25,17,,400,100,,16,39.47719407081604
+793,0.65625,0.63671875,0.64453125,0.2,8,25,18,,400,100,,16,39.5304970741272
+794,0.6484375,0.69140625,0.58203125,0.2,8,25,19,,400,100,,16,39.64306712150574
+795,0.65625,0.6796875,0.6015625,0.2,8,25,20,,400,100,,16,39.57410740852356
+796,0.66796875,0.671875,0.63671875,0.2,8,25,21,,400,100,,16,39.54800629615784
+797,0.64453125,0.68359375,0.5859375,0.2,8,25,22,,400,100,,16,39.1894097328186
+798,0.66796875,0.671875,0.6484375,0.2,8,25,23,,400,100,,16,39.444368839263916
+799,0.66015625,0.69140625,0.60546875,0.2,8,25,24,,400,100,,16,39.792489528656006
+800,0.734375,0.73828125,0.69921875,0.2,8,57,0,,400,100,,16,63.03297734260559
+801,0.73046875,0.73828125,0.69140625,0.2,8,57,1,,400,100,,16,62.82802891731262
+802,0.703125,0.75,0.66796875,0.2,8,57,2,,400,100,,16,63.59988284111023
+803,0.71875,0.71484375,0.6875,0.2,8,57,3,,400,100,,16,62.546332120895386
+804,0.76953125,0.72265625,0.75,0.2,8,57,4,,400,100,,16,62.95150399208069
+805,0.71484375,0.68359375,0.69921875,0.2,8,57,5,,400,100,,16,61.88507652282715
+806,0.6796875,0.72265625,0.625,0.2,8,57,6,,400,100,,16,62.815024852752686
+807,0.734375,0.7578125,0.66015625,0.2,8,57,7,,400,100,,16,62.61427593231201
+808,0.69921875,0.70703125,0.66015625,0.2,8,57,8,,400,100,,16,62.401984453201294
+809,0.6875,0.71875,0.64453125,0.2,8,57,9,,400,100,,16,62.68899464607239
+810,0.734375,0.69921875,0.65234375,0.2,8,57,10,,400,100,,16,63.42784786224365
+811,0.7421875,0.73046875,0.69140625,0.2,8,57,11,,400,100,,16,62.51943612098694
+812,0.703125,0.734375,0.6640625,0.2,8,57,12,,400,100,,16,62.40397334098816
+813,0.7265625,0.71875,0.640625,0.2,8,57,13,,400,100,,16,61.71758031845093
+814,0.74609375,0.734375,0.66015625,0.2,8,57,14,,400,100,,16,62.920838832855225
+815,0.7265625,0.6875,0.62109375,0.2,8,57,15,,400,100,,16,63.41124081611633
+816,0.72265625,0.68359375,0.66796875,0.2,8,57,16,,400,100,,16,62.649603843688965
+817,0.7109375,0.70703125,0.60546875,0.2,8,57,17,,400,100,,16,62.95081090927124
+818,0.73046875,0.734375,0.671875,0.2,8,57,18,,400,100,,16,63.46947741508484
+819,0.78515625,0.76171875,0.71875,0.2,8,57,19,,400,100,,16,62.43563795089722
+820,0.734375,0.7578125,0.64453125,0.2,8,57,20,,400,100,,16,62.47174906730652
+821,0.71484375,0.7109375,0.6328125,0.2,8,57,21,,400,100,,16,61.57260847091675
+822,0.72265625,0.68359375,0.64453125,0.2,8,57,22,,400,100,,16,62.59169793128967
+823,0.74609375,0.73046875,0.71875,0.2,8,57,23,,400,100,,16,63.214601278305054
+824,0.76953125,0.76171875,0.7421875,0.2,8,57,24,,400,100,,16,62.60198736190796
+825,0.572265625,0.57421875,0.537109375,0.2,9,7,0,,800,100,,16,79.34851789474487
+826,0.5234375,0.568359375,0.513671875,0.2,9,7,1,,800,100,,16,78.79284739494324
+827,0.599609375,0.59765625,0.58203125,0.2,9,7,2,,800,100,,16,78.99208498001099
+828,0.556640625,0.564453125,0.52734375,0.2,9,7,3,,800,100,,16,78.84305906295776
+829,0.58203125,0.583984375,0.5625,0.2,9,7,4,,800,100,,16,78.84396839141846
+830,0.5390625,0.544921875,0.515625,0.2,9,7,5,,800,100,,16,78.11602520942688
+831,0.546875,0.5390625,0.525390625,0.2,9,7,6,,800,100,,16,78.98060345649719
+832,0.5703125,0.576171875,0.552734375,0.2,9,7,7,,800,100,,16,78.40642595291138
+833,0.58203125,0.5703125,0.5625,0.2,9,7,8,,800,100,,16,78.94102764129639
+834,0.560546875,0.5859375,0.4921875,0.2,9,7,9,,800,100,,16,78.43573689460754
+835,0.55078125,0.56640625,0.54296875,0.2,9,7,10,,800,100,,16,78.736398935318
+836,0.560546875,0.568359375,0.5546875,0.2,9,7,11,,800,100,,16,78.37219166755676
+837,0.556640625,0.576171875,0.52734375,0.2,9,7,12,,800,100,,16,78.52889132499695
+838,0.55078125,0.56640625,0.5390625,0.2,9,7,13,,800,100,,16,78.19596266746521
+839,0.5390625,0.56640625,0.537109375,0.2,9,7,14,,800,100,,16,78.85283350944519
+840,0.560546875,0.58984375,0.54296875,0.2,9,7,15,,800,100,,16,78.48840928077698
+841,0.55859375,0.55078125,0.546875,0.2,9,7,16,,800,100,,16,78.82580304145813
+842,0.55078125,0.56640625,0.509765625,0.2,9,7,17,,800,100,,16,78.3722755908966
+843,0.533203125,0.58203125,0.515625,0.2,9,7,18,,800,100,,16,78.58390355110168
+844,0.572265625,0.572265625,0.541015625,0.2,9,7,19,,800,100,,16,78.33907747268677
+845,0.58203125,0.58984375,0.5546875,0.2,9,7,20,,800,100,,16,78.4434142112732
+846,0.5703125,0.580078125,0.5234375,0.2,9,7,21,,800,100,,16,78.30260038375854
+847,0.525390625,0.572265625,0.494140625,0.2,9,7,22,,800,100,,16,78.75501894950867
+848,0.5703125,0.587890625,0.5390625,0.2,9,7,23,,800,100,,16,78.4683690071106
+849,0.552734375,0.5625,0.54296875,0.2,9,7,24,,800,100,,16,78.78117609024048
+850,0.587890625,0.5859375,0.583984375,0.2,9,25,0,,800,100,,16,106.19518995285034
+851,0.603515625,0.59375,0.58203125,0.2,9,25,1,,800,100,,16,105.4019455909729
+852,0.591796875,0.578125,0.572265625,0.2,9,25,2,,800,100,,16,105.16931343078613
+853,0.58984375,0.5859375,0.53515625,0.2,9,25,3,,800,100,,16,104.99832272529602
+854,0.595703125,0.591796875,0.546875,0.2,9,25,4,,800,100,,16,105.55810475349426
+855,0.57421875,0.587890625,0.521484375,0.2,9,25,5,,800,100,,16,106.05953407287598
+856,0.57421875,0.599609375,0.5546875,0.2,9,25,6,,800,100,,16,105.33877301216125
+857,0.572265625,0.6484375,0.52734375,0.2,9,25,7,,800,100,,16,106.08913898468018
+858,0.57421875,0.61328125,0.537109375,0.2,9,25,8,,800,100,,16,106.40415859222412
+859,0.5859375,0.57421875,0.5625,0.2,9,25,9,,800,100,,16,105.56644749641418
+860,0.568359375,0.57421875,0.5390625,0.2,9,25,10,,800,100,,16,105.2296884059906
+861,0.58984375,0.6015625,0.5625,0.2,9,25,11,,800,100,,16,105.21250772476196
+862,0.572265625,0.6015625,0.537109375,0.2,9,25,12,,800,100,,16,105.77387714385986
+863,0.5859375,0.607421875,0.5703125,0.2,9,25,13,,800,100,,16,105.9854953289032
+864,0.591796875,0.609375,0.544921875,0.2,9,25,14,,800,100,,16,105.25557899475098
+865,0.595703125,0.61328125,0.552734375,0.2,9,25,15,,800,100,,16,106.24169445037842
+866,0.595703125,0.6015625,0.5859375,0.2,9,25,16,,800,100,,16,106.2500581741333
+867,0.59765625,0.607421875,0.564453125,0.2,9,25,17,,800,100,,16,105.58812999725342
+868,0.603515625,0.578125,0.556640625,0.2,9,25,18,,800,100,,16,105.71098065376282
+869,0.576171875,0.62109375,0.54296875,0.2,9,25,19,,800,100,,16,104.91821503639221
+870,0.5859375,0.58984375,0.587890625,0.2,9,25,20,,800,100,,16,105.64013242721558
+871,0.580078125,0.576171875,0.533203125,0.2,9,25,21,,800,100,,16,106.39169001579285
+872,0.595703125,0.59765625,0.552734375,0.2,9,25,22,,800,100,,16,105.52587699890137
+873,0.591796875,0.6015625,0.560546875,0.2,9,25,23,,800,100,,16,106.30500102043152
+874,0.578125,0.6015625,0.54296875,0.2,9,25,24,,800,100,,16,106.43637156486511
+875,0.61328125,0.626953125,0.54296875,0.2,9,57,0,,800,100,,16,153.50189876556396
+876,0.630859375,0.599609375,0.578125,0.2,9,57,1,,800,100,,16,153.82139587402344
+877,0.62109375,0.642578125,0.5703125,0.2,9,57,2,,800,100,,16,152.63563203811646
+878,0.66015625,0.62109375,0.57421875,0.2,9,57,3,,800,100,,16,155.20042252540588
+879,0.6328125,0.62890625,0.587890625,0.2,9,57,4,,800,100,,16,155.2862424850464
+880,0.62109375,0.638671875,0.55859375,0.2,9,57,5,,800,100,,16,153.65730690956116
+881,0.61328125,0.615234375,0.603515625,0.2,9,57,6,,800,100,,16,155.53187680244446
+882,0.640625,0.654296875,0.595703125,0.2,9,57,7,,800,100,,16,156.22191548347473
+883,0.611328125,0.642578125,0.59375,0.2,9,57,8,,800,100,,16,153.5591745376587
+884,0.6328125,0.6328125,0.611328125,0.2,9,57,9,,800,100,,16,153.8430473804474
+885,0.634765625,0.63671875,0.58984375,0.2,9,57,10,,800,100,,16,153.38100624084473
+886,0.646484375,0.640625,0.6015625,0.2,9,57,11,,800,100,,16,155.448175907135
+887,0.623046875,0.630859375,0.5546875,0.2,9,57,12,,800,100,,16,155.07015442848206
+888,0.611328125,0.64453125,0.560546875,0.2,9,57,13,,800,100,,16,153.80399584770203
+889,0.6328125,0.625,0.564453125,0.2,9,57,14,,800,100,,16,156.1650471687317
+890,0.650390625,0.640625,0.609375,0.2,9,57,15,,800,100,,16,156.74522924423218
+891,0.646484375,0.615234375,0.568359375,0.2,9,57,16,,800,100,,16,153.78001523017883
+892,0.625,0.66015625,0.58203125,0.2,9,57,17,,800,100,,16,154.19456124305725
+893,0.615234375,0.615234375,0.568359375,0.2,9,57,18,,800,100,,16,152.9702606201172
+894,0.6171875,0.6328125,0.611328125,0.2,9,57,19,,800,100,,16,155.4539008140564
+895,0.623046875,0.65625,0.5859375,0.2,9,57,20,,800,100,,16,156.79778671264648
+896,0.60546875,0.640625,0.591796875,0.2,9,57,21,,800,100,,16,153.81468653678894
+897,0.6328125,0.623046875,0.6015625,0.2,9,57,22,,800,100,,16,155.61179971694946
+898,0.61328125,0.66015625,0.587890625,0.2,9,57,23,,800,100,,16,156.66607785224915
+899,0.615234375,0.6015625,0.56640625,0.2,9,57,24,,800,100,,16,153.550630569458
diff --git a/experiments/gp.py b/experiments/gp.py
new file mode 100644
index 0000000000000000000000000000000000000000..2950b637c8f8d740636669ae45d08c257c51aa13
--- /dev/null
+++ b/experiments/gp.py
@@ -0,0 +1,186 @@
+import warnings
+import gym
+try:
+ import pybullet_envs
+except ImportError:
+ warnings.warn("PyBullet environment not found")
+
+import numpy as np
+import random
+import operator
+
+from functools import partial
+import pandas as pd
+
+from deap import base, creator, tools, gp
+
+from GPRL.genetic_programming import team
+from GPRL.utils import gp_utils
+from GPRL.utils.utils import convert_logbook_to_dataframe
+from GPRL.factory import EvolveFactory
+
+from GPRL.UCB import UCBFitness
+
+def MC_fitness(individual, n_steps, num_episodes, gamma):
+ global ENV, toolbox
+ if ENV.action_space.shape:
+ agent = toolbox.compile(individual)
+ else:
+ func = toolbox.compile(individual)
+ agent = lambda *s: int(func(*s)[0])
+ s = 0
+ steps = 0
+ for _ in range(num_episodes):
+ state = ENV.reset()
+ for k in range(n_steps):
+ state, reward, done, _ = ENV.step(agent(*state))
+ s+= gamma*reward
+ steps += 1
+ if done:
+ break
+ return s, team.team_complexity(individual, gp_utils.complexity)
+
+
+class Factory(EvolveFactory):
+
+ def init_global_var(self):
+ global ENV, toolbox, creator
+
+ ENV = gym.make(self.conf["env"])
+ toolbox, creator = self.make_toolbox()
+
+ def make_toolbox(self):
+ core_function = [ (np.add, [float]*2, float), (np.subtract, [float]*2, float), (np.multiply, [float]*2, float), (gp_utils.div, [float]*2, float)]
+ exp_function = [ (gp_utils.exp, [float], float), (gp_utils.log, [float], float)]
+ trig_function = [(np.sin, [float], float)]
+ if_function = [ (gp_utils.if_then_else, [bool, float, float], float), (operator.gt, [float, float], bool), (operator.and_, [bool, bool], bool), (operator.or_, [bool, bool], bool) ]
+ classification_func = [(gp_utils.classification, [float, float, float], int)] #(gp_utils.intervales, [float], int)
+
+
+ if self.conf['function_set'] == "small":
+ function_set = core_function + if_function
+ elif self.conf["function_set"] == "extended":
+ function_set = core_function + exp_function + trig_function
+
+ INPUT = ENV.observation_space.shape[0]
+ if bool(ENV.action_space.shape):
+ ret = float
+ OUTPUT = ENV.action_space.shape[0]
+ else:
+ ret = int
+ OUTPUT = 1
+
+
+ pset = gp.PrimitiveSetTyped("MAIN", [float]*INPUT, ret)
+ for primitive in function_set:
+ pset.addPrimitive(*primitive)
+ pset.addTerminal(0.1, float)
+
+ for k in range(INPUT//2):
+ pset.addEphemeralConstant("const_"+str(k), lambda: np.random.uniform(-20.0, 20.0), float)
+ pset.addTerminal(True, bool)
+ pset.addTerminal(1, int)
+
+ creator.create("FitnessMax", UCBFitness, weights=(1.0, -1.0), c=self.conf["c"], sigma=1)
+ creator.create("Individual", list, fitness=creator.FitnessMax)
+
+ toolbox = base.Toolbox()
+ toolbox.register("expr", gp.genHalfAndHalf, pset=pset, min_=1, max_=4)
+ toolbox.register("team_grow", team.init_team, size=OUTPUT, unit_init=lambda: gp.PrimitiveTree(toolbox.expr()))
+ toolbox.register("individual", tools.initIterate, creator.Individual, toolbox.team_grow)
+
+ toolbox.register("population", tools.initRepeat, list, toolbox.individual)
+ toolbox.register("compile_gp", gp.compile, pset=pset)
+ toolbox.register("compile", team.team_compile, unit_compile=toolbox.compile_gp)
+
+ toolbox.register("evaluate", MC_fitness, n_steps=self.conf["n_steps"], num_episodes=self.conf["n_episodes"], gamma=self.conf["gamma"])
+
+ if self.conf.get("selection", False):
+ toolbox.register("select", eval(self.conf["selection"]["name"]), **self["selection"]["args"])
+ else:
+ toolbox.register("select", tools.selNSGA2)
+
+ def cx(x1, x2):
+ tmp1, tmp2 = gp.cxOnePoint(x1, x2)
+ return gp.PrimitiveTree(tmp1), gp.PrimitiveTree(tmp2)
+
+ toolbox.register("mate", team.fixed_mate, unit_cx=cx)
+ toolbox.register("expr_mut", gp.genFull, min_=0, max_=2)
+
+ toolbox.register("mutate_gp", gp_utils.mutate, expr=toolbox.expr_mut, pset=pset, mode="all", mu=0, std=1)
+ toolbox.register("mutate", team.mutate, unit_mut=lambda x: gp.PrimitiveTree(toolbox.mutate_gp(x)[0]))
+
+ toolbox.decorate("mate", gp.staticLimit(key=lambda x: team.height(x, operator.attrgetter("height")), max_value=self.conf.get("tree_max_depth",17)))
+ toolbox.decorate("mutate", gp.staticLimit(key=lambda x: team.height(x, operator.attrgetter("height")), max_value=self.conf.get("tree_max_depth",17)))
+
+ return toolbox, creator
+
+ def get_stats(self):
+ stats_fit = tools.Statistics(lambda ind: ind.fitness.values[0])
+ stats_complexity = tools.Statistics(lambda ind: team.team_complexity(ind, gp_utils.complexity))
+ stats_size = tools.Statistics(len)
+ #stats_bandit = tools.Statistics(lambda ind: len(ind.fitness.rewards))
+
+ mstats = tools.MultiStatistics(fitness=stats_fit, size=stats_size, complexity=stats_complexity)#, bandit=stats_bandit)
+ mstats.register("avg", lambda x: np.mean(x))
+ mstats.register("std", lambda x: np.std(x))
+ mstats.register("min", lambda x: np.min(x))
+ mstats.register("max", lambda x: np.max(x))
+
+ return mstats
+
+ def close(self):
+ global ENV
+ ENV.close()
+
+if __name__== "__main__":
+ import multiprocessing
+ import argparse
+ from deap import algorithms
+ from GPRL import algorithms as algo
+
+ parser = argparse.ArgumentParser()
+ parser.add_argument("--env", required=True, help="environment ID", type=str)
+ parser.add_argument("--n-episodes", help="Number of episodes", default=1, type=int)
+ parser.add_argument("--n-steps", help="Number of step per episode", default=2000, type=int)
+ parser.add_argument("--gamma", help="discount factor", default=1.0, type=float)
+ parser.add_argument("--algorithm", help="algorithm (mu+lambda), (mu, lambda) or UCB", default="UCB", type=str)
+ parser.add_argument("--cxpb", help="crossover probability", default=0.0, type=float)
+ parser.add_argument("--mutpb", help="mutation probability", default=1.0, type=float)
+ parser.add_argument("--lambda_", help="number of offspring", default=100, type=int)
+ parser.add_argument("--mu", help="number of parents", default=100, type=int)
+ parser.add_argument("--n-gen", help="number of generation", default=100, type=int)
+ parser.add_argument("--function-set", help="function set", default="small", type=str)
+ parser.add_argument("--simulation-budget", help="number of simulation allowed for UCB", default=1, type=int)
+ parser.add_argument("--c", help="constante d'exploration", default=1.0, type=float)
+ parser.add_argument("--n-thread", help="number of thread to use", default=1, type=int)
+ parser.add_argument("--path", help="path to save the results", default="", type=str)
+
+ args = parser.parse_args()
+
+ factory = Factory(vars(args))
+ factory.init_global_var()
+
+ mstats = factory.get_stats()
+
+ pool = multiprocessing.Pool(args.n_thread, initializer=factory.init_global_var)
+ toolbox.register("map", pool.map)
+
+ pop = toolbox.population(n=args.mu)
+ hof = tools.ParetoFront()
+
+ if args.algorithm == "UCB":
+ algo = partial(algo.eaMuPlusLambdaUCB, simulation_budget=args.simulation_budget, parallel_update=args.n_thread)
+ elif args.algorithm == "(mu, lambda)":
+ algo = algorithms.eaMuCommaLambda
+ elif args.algorithm == "(mu + lambda)":
+ algo = algorithms.eaMuPlusLambda
+
+ pop, log = algo(population=pop, toolbox=toolbox, cxpb=args.cxpb, mutpb=args.mutpb, mu=args.mu, lambda_=args.lambda_, ngen=args.n_gen, stats=mstats, halloffame=hof, verbose=True)
+
+ name = str(hash(vars(args).values()))
+ convert_logbook_to_dataframe(log).to_csv(args.path+"log_gp"+ name + ".csv", index=False)
+ print("Experiment is saved at : ", args.path + "log_gp"+name)
+
+ pool.close()
+ factory.close()
\ No newline at end of file
diff --git a/experiments/linGP.py b/experiments/linGP.py
new file mode 100644
index 0000000000000000000000000000000000000000..6bc501a99c91d04d2cf5c8210457f5f8a0c3baac
--- /dev/null
+++ b/experiments/linGP.py
@@ -0,0 +1,187 @@
+from functools import partial
+import warnings
+import random
+
+import numpy as np
+import gym
+try:
+ import pybullet_envs
+except ImportError:
+ warnings.warn("PyBullet environment not found")
+
+from deap import creator, tools, base
+from GPRL.genetic_programming import linearGP as linGP
+from GPRL.UCB import UCBFitness
+
+from GPRL.factory import EvolveFactory
+from GPRL.utils.utils import convert_logbook_to_dataframe
+
+def MC_fitness(individual, n_steps, num_episodes, gamma):
+ eff, _, _ = individual.to_effective(list(range(OUTPUT)))
+ if len(eff)==0:
+ return -2000.0, 999
+ if ENV.action_space.shape:
+ def agent(inputs):
+ register = eff.init_register()
+ return eff.execute(eff, inputs, register, list(range(OUTPUT)))
+ else:
+ if OUTPUT==1:
+ def agent(inputs):
+ register = eff.init_register()
+ return int(eff.execute(eff, inputs, register, list(range(OUTPUT)))>0)
+ else:
+ def agent(inputs):
+ register = eff.init_register()
+ return np.argmax(eff.execute(eff, inputs, register, list(range(OUTPUT))))
+ s = 0
+ steps = 0
+ for e in range(num_episodes):
+ state = ENV.reset()
+ for k in range(n_steps):
+ state, reward, done, _ = ENV.step(agent(state))
+ s+= gamma*reward
+ steps += 1
+ if done:
+ break
+ return s/num_episodes, sum(map(lambda x: linGP.opcode_complexity[x.opcode], eff))
+
+def mutate(individual, pIns, pDel, pSwap, pMut, pConst, pBranch):
+ if random.random() < pDel:
+ linGP.mutDelete(individual, effective=None)
+ if random.random() < pIns:
+ linGP.mutInsert(individual, pConst, pBranch, effective=list(range(OUTPUT)))
+ if random.random() < pSwap:
+ _, _, idxs = individual.to_effective(list(range(OUTPUT)))
+ linGP.mutSwap(individual, effective=idxs)
+ if random.random() < pMut:
+ linGP.Program.mutInstr(individual, 0.3, 0.3, 0.4, pBranch, effective=list(range(OUTPUT)))
+ return individual,
+
+class Factory(EvolveFactory):
+ def init_global_var(self):
+ global ENV, toolbox, creator
+ global INPUT, OUTPUT
+
+ ENV = gym.make(self.conf["env"])
+ INPUT = ENV.observation_space.shape[0]
+ if ENV.action_space.shape:
+ OUTPUT = ENV.action_space.shape[0]
+ else:
+ OUTPUT = ENV.action_space.n
+
+ toolbox, creator = self.make_toolbox()
+
+ def make_toolbox(self):
+ creator.create("FitnessMin", UCBFitness, weights=(1.0, -1.0))
+ creator.create("Individual", linGP.Program, fitness=creator.FitnessMin)
+
+ if self.conf['function_set']=="small":
+ ops = np.array([True]*3 + [False, True] + [False]*5 + [True]*2)
+ elif self.conf['function_set']=="extended":
+ ops = np.array([True]*3 + [False, True, False] + [True]*3+ [False] + [True]*2)
+ elif self.conf['function_set']=="all":
+ ops = np.ones(12, dtype=bool)
+
+ toolbox = base.Toolbox()
+ toolbox.register("Program", linGP.initProgam, creator.Individual, regCalcSize=self.conf['regCalcSize'], regInputSize=INPUT, regConstSize=self.conf['regConstSize'], pConst=self.conf['pConst'], pBranch=self.conf["pBranch"],
+ min_=self.conf['init_size_min'], max_=self.conf['init_size_max'], ops=ops)
+ toolbox.register("population", tools.initRepeat, list, toolbox.Program)
+
+ toolbox.register("evaluate", MC_fitness, n_steps=self.conf["n_steps"], num_episodes=self.conf["n_episodes"], gamma=self.conf["gamma"])
+
+ if self.conf.get("selection", False):
+ toolbox.register("select", eval(self.conf["selection"]["name"]), **self["selection"]["args"])
+ else:
+ toolbox.register("select", tools.selTournament, tournsize=5)
+
+ toolbox.register("mate", linGP.cxLinear, l_min=1, l_max=3, l_smax=8, dc_max=4, ds_max=8)
+ toolbox.register("mutate", mutate, pIns=self.conf["pIns"], pDel=self.conf["pDel"], pSwap=self.conf.get("pSwap", 0.0), pMut=self.conf["pMut"], pConst=self.conf["pConst"], pBranch=self.conf["pBranch"])
+
+ return toolbox, creator
+
+ def get_stats(self):
+ stats_fit = tools.Statistics(lambda ind: ind.fitness.values[0])
+ stats_complexity = tools.Statistics(lambda ind: sum(map(lambda x: linGP.opcode_complexity[x.opcode], ind.to_effective(list(range(OUTPUT)))[0])))
+ stats_eff = tools.Statistics(lambda ind: len(ind.to_effective(list(range(OUTPUT)))[0]))
+ stats_size = tools.Statistics(len)
+ #stats_bandit = tools.Statistics(lambda ind: len(ind.fitness.rewards))
+
+ mstats = tools.MultiStatistics(fitness=stats_fit, complexity=stats_complexity, size=stats_size, effective=stats_eff)#, bandit=stats_bandit)
+ mstats.register("avg", lambda x: np.mean(x))
+ mstats.register("std", lambda x: np.std(x))
+ mstats.register("min", lambda x: np.min(x))
+ mstats.register("max", lambda x: np.max(x))
+
+ return mstats
+
+ def close(self):
+ global ENV
+ ENV.close()
+
+if __name__ == '__main__':
+ import multiprocessing
+
+ import multiprocessing
+ import argparse
+ from deap import algorithms
+ import GPRL.algorithms as my_algorithms
+ import pandas as pd
+
+ parser = argparse.ArgumentParser()
+ parser.add_argument("--env", required=True, help="environment ID", type=str)
+ parser.add_argument("--n-episodes", help="Number of episodes", default=1, type=int)
+ parser.add_argument("--n-steps", help="Number of step per episode", default=2000, type=int)
+ parser.add_argument("--gamma", help="discount factor", default=1.0, type=float)
+
+ parser.add_argument("--regCalcSize", help="Size of calculation register of the program", default=8, type=int)
+ parser.add_argument("--regConstSize", help="Size of the constante register of the program", default=10, type=int)
+ parser.add_argument("--init-size-min", help="Minimal program size at initialization", default=2, type=int)
+ parser.add_argument("--init-size-max", help="Maximum program size at initialization", default=8, type=int)
+ parser.add_argument("--pConst", help="Probability of choosing the constante as input", default=1.0, type=float)
+ parser.add_argument("--pBranch", help="Probability of choosing a branch operation", default=1.0, type=float)
+
+ parser.add_argument("--pIns", help="macro-mutation probability of insertion", default=0.3, type=float)
+ parser.add_argument("--pDel", help="macro-mutation probability of deletion", default=0.6, type=float)
+ parser.add_argument("--pSwap", help="macro-mutation probability of swaping instruction", default=0.1, type=float)
+ parser.add_argument("--pMut", help="micro-mutation probability of mutating an existing instruction", default=0.5, type=float)
+
+ parser.add_argument("--algorithm", help="algorithm (mu+lambda), (mu, lambda) or UCB", default="UCB", type=str)
+ parser.add_argument("--cxpb", help="crossover probability", default=0.0, type=float)
+ parser.add_argument("--mutpb", help="mutation probability", default=1.0, type=float)
+ parser.add_argument("--lambda_", help="number of offspring", default=100, type=int)
+ parser.add_argument("--mu", help="number of parents", default=100, type=int)
+ parser.add_argument("--n-gen", help="number of generation", default=100, type=int)
+ parser.add_argument("--function-set", help="function set", default="small", type=str)
+ parser.add_argument("--simulation-budget", help="number of simulation allowed for UCB", default=1, type=int)
+ parser.add_argument("--c", help="constante d'exploration", default=1.0, type=float)
+ parser.add_argument("--n-thread", help="number of thread to use", default=1, type=int)
+ parser.add_argument("--path", help="path to save the results", default="", type=str)
+
+ args = parser.parse_args()
+
+ factory = Factory(vars(args))
+ factory.init_global_var()
+
+ mstats = factory.get_stats()
+
+ pool = multiprocessing.Pool(args.n_thread, initializer=factory.init_global_var)
+ toolbox.register("map", pool.map)
+
+ pop = toolbox.population(n=args.mu)
+ hof = tools.ParetoFront()
+
+ if args.algorithm == "UCB":
+ algo = partial(my_algorithms.eaMuPlusLambdaUCB, simulation_budget=args.simulation_budget, parallel_update=args.n_thread)
+ elif args.algorithm == "(mu, lambda)":
+ algo = algorithms.eaMuCommaLambda
+ elif args.algorithm == "(mu + lambda)":
+ algo = algorithms.eaMuPlusLambda
+
+ pop, log = algo(population=pop, toolbox=toolbox, cxpb=args.cxpb, mutpb=args.mutpb, mu=args.mu, lambda_=args.lambda_, ngen=args.n_gen, stats=mstats, halloffame=hof, verbose=True)
+
+ name = str(hash(vars(args).values()))
+ convert_logbook_to_dataframe(log).to_csv(args.path+"log_lingp"+ name + ".csv", index=False)
+ print("Experiment is saved at : ", args.path + "log_lingp-"+name)
+
+ pool.close()
+ factory.close()
\ No newline at end of file
diff --git a/experiments/qdgp.py b/experiments/qdgp.py
new file mode 100644
index 0000000000000000000000000000000000000000..f68d387800faca551f051f6485da2853eb11f9c4
--- /dev/null
+++ b/experiments/qdgp.py
@@ -0,0 +1,129 @@
+import operator
+import numpy as np
+import pandas as pd
+import gym
+from deap import gp
+from qdpy.containers import Grid
+
+from GPRL.utils import gp_utils
+from GPRL.utils.utils import convert_logbook_to_dataframe
+from GPRL.genetic_programming import team
+import gp as gp_script
+
+def MC_fitness(individual, n_steps, num_episodes, gamma, features_kept):
+ agent = gp_script.toolbox.compile(individual)
+
+ total_features = (0,) * (len(features_kept)-2)
+ total_avg_features = (0,) * (len(features_kept)-2)
+ s = 0
+ for e in range(num_episodes):
+ state = gp_script.ENV.reset()
+ for t in range(n_steps):
+ state, reward, done, _ = gp_script.ENV.step(agent(*state))
+ if gp_script.ENV.unwrapped.spec.id == "HopperBulletEnv-v0":
+ features = [abs(state[-8]), abs(state[-5]), abs(state[-3]), state[-1]]
+ elif gp_script.ENV.unwrapped.spec.id == "BipedalWalker-v3":
+ features = [abs(state[4]), abs(state[6]), abs(state[9]), abs(state[11]), state[8], state[13]]
+
+ s+= gamma*reward
+ total_features = tuple(x + y for x, y in zip(total_features, features))
+ if done:
+ break
+ total_avg_features = tuple(x/(t+1) + y for x, y in zip(total_features, total_avg_features))
+ total_features = (0,) * (len(features_kept)-2)
+
+ total_avg_features = [x/num_episodes for x in total_avg_features]
+
+ nb_weights = 0
+ for ind in individual:
+ for node in ind:
+ if isinstance(node, gp.Ephemeral):
+ nb_weights+=1
+ if nb_weights>20:
+ nb_weights = 20
+ total_avg_features.insert(0, nb_weights)
+
+ cpl = team.team_complexity(individual, gp_utils.complexity)
+ if cpl >= 100:
+ cpl = 100
+ total_avg_features.insert(0, cpl)
+
+
+ total_avg_features = np.array(total_avg_features)
+
+ if s/num_episodes < -200_000.0:
+ return -200_000.0, *total_avg_features[features_kept]
+ return s/num_episodes, *total_avg_features[features_kept]
+
+if '__main__' == __name__:
+ import multiprocessing
+ import argparse
+ from deap import algorithms
+ from .. import algorithms as algo
+
+ parser = argparse.ArgumentParser()
+ parser.add_argument("--env", required=True, help="environment ID", type=str)
+ parser.add_argument("--n-episodes", help="Number of episodes", default=1, type=int)
+ parser.add_argument("--n-steps", help="Number of step per episode", default=500, type=int)
+ parser.add_argument("--gamma", help="discount factor", default=1.0, type=float)
+
+ parser.add_argument("--cxpb", help="crossover probability", default=0.0, type=float)
+ parser.add_argument("--mutpb", help="mutation probability", default=1.0, type=float)
+ parser.add_argument("--batch-size", help="same thing as population size", default=500, type=int)
+ parser.add_argument("--lambda_", help="number of offspring", default=500, type=int)
+ parser.add_argument("--n-gen", help="number of generation", default=100, type=int)
+ parser.add_argument("--function-set", help="function set", default="small", type=str)
+ parser.add_argument("--simulation-budget", help="number of simulation allowed for UCB", default=1, type=int)
+ parser.add_argument("--c", help="constante d'exploration", default=1.0, type=float)
+ parser.add_argument("--n-thread", help="number of thread to use", default=1, type=int)
+ parser.add_argument("--path", help="path to save the results", default="", type=str)
+
+ args = parser.parse_args()
+
+
+ if args.env == "BipedalWalker-v3":
+ features_kept = np.zeros(8, dtype=bool)
+ features_kept[3] = True
+ features_kept[5] = True
+
+ nbBins = [10, 10] # The number of bins of the grid of elites. Here, we consider only $nbFeatures$ features with $maxTotalBins^(1/nbFeatures)$ bins each
+ features_domain = np.array([(0, 100), (0., 2.0), (0., 2.5), (0., 2.5), (0., 2.5), (0., 2.5), (0., 1.0), (0., 1.0)]) # The domain (min/max values) of the features
+ fitness_domain = ((-200.0, 350.0),) # The domain (min/max values) of the fitness
+ max_items_per_bin = 10 # The number of items in each bin of the grid
+ elif args.env != "HopperBulletEnv-v3":
+ features_kept = np.zeros(6, dtype=bool)
+ features_kept[3] = True
+ features_kept[4] = True
+ features_kept[5] = True
+
+ nbBins = [10, 10, 10]
+ features_domain = np.array([(0, 100), (0., 20.), (0.0, 1.2), (0.0, 1.2), (0.0, 1.2), (0.0, 1.0)])
+ fitness_domain = ((-200_000.0, 1100.0),)
+ max_items_per_bin = 5
+ else:
+ raise ValueError("Environment not supported ! Please use env-id : BipedalWalkerFeatures-v3 or HopperBulletEnvFeatures-v3")
+
+ args.features_kept = features_kept
+ conf = vars(args)
+ factory = gp_script.Factory(conf)
+ factory.init_global_var()
+
+ mstats = factory.get_stats()
+
+ pool = multiprocessing.Pool(args.n_thread, initializer=factory.init_global_var)
+ gp_script.toolbox.register("map", pool.map)
+ gp_script.toolbox.register('evaluate', MC_fitness, n_steps=conf["n_steps"], num_episodes=conf["n_episodes"], gamma=conf["gamma"], features_kept=conf["features_kept"])
+
+ pop = gp_script.toolbox.population(n=args.batch_size*10)
+
+ grid = Grid(shape=nbBins, max_items_per_bin=max_items_per_bin, fitness_domain=fitness_domain, features_domain=features_domain[features_kept], storage_type=list)
+
+ pop, log = algo.qdLambda(pop, gp_script.toolbox, grid, args.batch_size, cxpb=args.cxpb, mutpb=args.mutpb, lambda_=args.lambda_, ngen=args.n_gen, stats=mstats, verbose=True)
+
+ name = str(hash(vars(args).values()))
+ convert_logbook_to_dataframe(log).to_csv("log_gp-"+ name + ".csv", index=False)
+
+ print("Experiment is saved at : ", name)
+
+ pool.close()
+ factory.close()
diff --git a/experiments/qdlinGP.py b/experiments/qdlinGP.py
new file mode 100644
index 0000000000000000000000000000000000000000..5a27b094ebea9c7caf62b3e5fff145eb8c874c22
--- /dev/null
+++ b/experiments/qdlinGP.py
@@ -0,0 +1,139 @@
+import numpy as np
+from qdpy.containers import Grid
+
+from GPRL.utils.utils import convert_logbook_to_dataframe
+from . import linGP as linGP_script
+from GPRL.genetic_programming import linearGP as linGP
+
+def MC_fitness(individual, n_steps, num_episodes, gamma, features_kept):
+ eff, _, _ = individual.to_effective(list(range(linGP_script.OUTPUT)))
+
+ if len(eff)==0:
+ vals = (0,) * np.count_nonzero(features_kept)
+ return -200_000.0, *vals
+
+ def agent(inputs):
+ register = eff.init_register()
+ return eff.execute(eff, inputs, register, list(range(linGP_script.OUTPUT)))
+
+ total_features = (0,) * (len(features_kept)-2)
+ total_avg_features = (0,) * (len(features_kept)-2)
+ s = 0
+ for e in range(num_episodes):
+ state = linGP_script.ENV.reset()
+ for t in range(n_steps):
+ state, reward, done, _ = linGP_script.ENV.step(agent(state))
+
+ #Handcrafted Features
+ if linGP_script.ENV.unwrapped.spec.id == "HopperBulletEnv-v0":
+ features = [abs(state[-8]), abs(state[-5]), abs(state[-3]), state[-1]]
+ elif linGP_script.ENV.unwrapped.spec.id == "BipedalWalker-v3":
+ features = [abs(state[4]), abs(state[6]), abs(state[9]), abs(state[11]), state[8], state[13]]
+ s+= gamma*reward
+ total_features = tuple(x + y for x, y in zip(total_features, features))
+ if done:
+ break
+ total_avg_features = tuple(x/(t+1) + y for x, y in zip(total_features, total_avg_features))
+ total_features = (0,) * (len(features_kept)-2)
+
+ total_avg_features = [x/num_episodes for x in total_avg_features]
+
+ nb_weights = len(eff.get_used_regConstIdxs())
+ total_avg_features.insert(0, nb_weights if nb_weights<=10 else 10)
+
+ cpl = sum(map(lambda x: linGP.opcode_complexity[x.opcode], eff))
+ if cpl >= 100:
+ cpl =100
+ total_avg_features.insert(0, cpl)
+
+ total_avg_features = np.array(total_avg_features)
+
+ if s/num_episodes < -200_000.0:
+ return -200_000.0, *total_avg_features[features_kept]
+ return s/num_episodes, *total_avg_features[features_kept]
+
+if '__main__' == __name__:
+ import multiprocessing
+ import argparse
+ from deap import algorithms
+ from GPRL import algorithms as algo
+
+ parser = argparse.ArgumentParser()
+ parser.add_argument("--env", required=True, help="environment ID", type=str)
+ parser.add_argument("--n-episodes", help="Number of episodes", default=1, type=int)
+ parser.add_argument("--n-steps", help="Number of step per episode", default=2000, type=int)
+ parser.add_argument("--gamma", help="discount factor", default=1.0, type=float)
+
+ parser.add_argument("--regCalcSize", help="Size of calculation register of the program", default=8, type=int)
+ parser.add_argument("--regConstSize", help="Size of the constante register of the program", default=10, type=int)
+ parser.add_argument("--init-size-min", help="Minimal program size at initialization", default=2, type=int)
+ parser.add_argument("--init-size-max", help="Maximum program size at initialization", default=8, type=int)
+ parser.add_argument("--pConst", help="Probability of choosing the constante as input", default=1.0, type=float)
+ parser.add_argument("--pBranch", help="Probability of choosing a branch operation", default=1.0, type=float)
+
+ parser.add_argument("--pIns", help="macro-mutation probability of insertion", default=0.3, type=float)
+ parser.add_argument("--pDel", help="macro-mutation probability of deletion", default=0.6, type=float)
+ parser.add_argument("--pSwap", help="macro-mutation probability of swaping instruction", default=0.1, type=float)
+ parser.add_argument("--pMut", help="micro-mutation probability of mutating an existing instruction", default=0.5, type=float)
+
+ parser.add_argument("--algorithm", help="algorithm (mu+lambda), (mu, lambda) or UCB", default="UCB", type=str)
+ parser.add_argument("--cxpb", help="crossover probability", default=0.0, type=float)
+ parser.add_argument("--mutpb", help="mutation probability", default=1.0, type=float)
+ parser.add_argument("--lambda_", help="number of offspring", default=100, type=int)
+ parser.add_argument("--batch-size", help="same thing as population size", default=500, type=int)
+ parser.add_argument("--n-gen", help="number of generation", default=100, type=int)
+ parser.add_argument("--function-set", help="function set", default="small", type=str)
+ parser.add_argument("--simulation-budget", help="number of simulation allowed for UCB", default=1, type=int)
+ parser.add_argument("--c", help="constante d'exploration", default=1.0, type=float)
+ parser.add_argument("--n-thread", help="number of thread to use", default=1, type=int)
+ parser.add_argument("--path", help="path to save the results", default="", type=str)
+
+ args = parser.parse_args()
+
+
+ if args.env == "BipedalWalker-v3":
+ features_kept = np.zeros(8, dtype=bool)
+ features_kept[3] = True
+ features_kept[5] = True
+
+ nbBins = [10, 10] # The number of bins of the grid of elites. Here, we consider only $nbFeatures$ features with $maxTotalBins^(1/nbFeatures)$ bins each
+ features_domain = np.array([(0, 100), (0., 10.0), (0., 2.5), (0., 2.5), (0., 2.5), (0., 2.5), (0., 1.0), (0., 1.0)]) # The domain (min/max values) of the features
+ fitness_domain = ((-200.0, 350.0),) # The domain (min/max values) of the fitness
+ max_items_per_bin = 10 # The number of items in each bin of the grid
+ elif args.env != "HopperBulletEnv-v3":
+ features_kept = np.zeros(6, dtype=bool)
+ features_kept[3] = True
+ features_kept[4] = True
+ features_kept[5] = True
+
+ nbBins = [10, 10, 10]
+ features_domain = np.array([(0, 100), (0., 10.), (0.0, 1.2), (0.0, 1.2), (0.0, 1.2), (0.0, 1.0)])
+ fitness_domain = ((-200_000.0, 1100.0),)
+ max_items_per_bin = 5
+ else:
+ raise ValueError("Environment not supported ! Please use env-id : BipedalWalker-v3 or HopperBulletEnv-v3")
+
+ args.features_kept = features_kept
+ conf = vars(args)
+ factory = linGP_script.Factory(conf)
+ factory.init_global_var()
+
+ mstats = factory.get_stats()
+
+ pool = multiprocessing.Pool(args.n_thread, initializer=factory.init_global_var)
+ linGP_script.toolbox.register("map", pool.map)
+ linGP_script.toolbox.register('evaluate', MC_fitness, n_steps=conf["n_steps"], num_episodes=conf["n_episodes"], gamma=conf["gamma"], features_kept=conf["features_kept"])
+
+ pop = linGP_script.toolbox.population(n=args.batch_size*10)
+
+ grid = Grid(shape=nbBins, max_items_per_bin=max_items_per_bin, fitness_domain=fitness_domain, features_domain=features_domain[features_kept], storage_type=list)
+
+ pop, log = algo.qdLambda(pop, linGP_script.toolbox, grid, args.batch_size, cxpb=args.cxpb, mutpb=args.mutpb, lambda_=args.lambda_, ngen=args.n_gen, stats=mstats, verbose=True)
+
+ name = str(hash(vars(args).values()))
+ convert_logbook_to_dataframe(log).to_csv("log_lingp"+ name + ".csv", index=False)
+
+ print("Experiment is saved at : ", name)
+
+ pool.close()
+ factory.close()