diff --git a/latextable.py b/latextable.py
index 85bf292397b031227c0b496c545a0cd276cf5e9c..da011a80604baa5b30afd8995c5e0c4ab493b365 100644
--- a/latextable.py
+++ b/latextable.py
@@ -32,7 +32,10 @@ syn = {
"instructions" : "circuit size",
"homotopycontinuation": "HomotopyContinuation.jl",
"macaulay2": "Macaulay2",
- "sirocco": "SIROCCO"
+ "sirocco": "SIROCCO",
+ "pathjump": "jump",
+ "maxwmeanprec": "w. mean",
+ "maxprec": "max.",
}
def title(D, key):
diff --git a/packages/adaptive b/packages/adaptive
index 0a0ac5b099e0ba362bd1bcc260232f545aa514b2..521047c6e118081f9ea86f9ce154e9164bef8e56 160000
--- a/packages/adaptive
+++ b/packages/adaptive
@@ -1 +1 @@
-Subproject commit 0a0ac5b099e0ba362bd1bcc260232f545aa514b2
+Subproject commit 521047c6e118081f9ea86f9ce154e9164bef8e56
diff --git a/synthesize.sage b/synthesize.sage
index 272838425773adb71483cdf588e7f4776fab9161..3426e9c3697f204e8d36a94c5805bf6484624fa3 100644
--- a/synthesize.sage
+++ b/synthesize.sage
@@ -5,8 +5,9 @@ import argparse
import math
from pathlib import Path
-parser = argparse.ArgumentParser(description = "A python script to generate a table of results out of given entries.")
-parser.add_argument("entries", help = "A JSON file containing entries.")
+parser = argparse.ArgumentParser(
+ description="A python script to generate a table of results out of given entries.")
+parser.add_argument("entries", help="A JSON file containing entries.")
args = parser.parse_args()
@@ -39,7 +40,8 @@ def time_format(t):
return str(int(t/60)) + " min"
else:
return str(int(t/3600)) + " h"
-
+
+
def time_format_2(t):
t = float(t)
if t == 0:
@@ -54,7 +56,8 @@ def time_format_2(t):
return str(int(t/60)) + " min"
else:
return str(int(t/3600)) + " h"
-
+
+
def steps_format(N):
if N == 0:
return ""
@@ -63,6 +66,7 @@ def steps_format(N):
else:
return str(math.ceil(N/1_000.0)) + "\\,k"
+
def steps_format_2(N):
if N == 0:
return ""
@@ -74,7 +78,8 @@ def steps_format_2(N):
return "{0:.1f}".format(N/1_000.0)
else:
return str(math.ceil(N/1_000.0))
-
+
+
def bytes_format(N):
if N == 0:
return ""
@@ -106,7 +111,8 @@ def fusion(LT1, LT2):
for _ in range(m - n)
]
return [l1 + l2 for l1, l2 in zip(LT1, LT2)]
-
+
+
def _header(header_dict):
res = []
if header_dict["children"] != 0:
@@ -135,35 +141,50 @@ def get_leaves(D):
L += get_leaves(child)
return L
+
def degrees(data):
data_path = (Path("data") / Path(data)).with_suffix(".json")
if not data_path.exists():
return [-1]
-
+
data_file = open(data_path, "r")
try:
d = json.load(data_file)
except:
return [-1]
-
-
- A = PolynomialRing(CC, names = d["parameters"] + d["variables"])
+
+ A = PolynomialRing(CC, names=d["parameters"] + d["variables"])
t = A.gens()[0]
- return [A(f).subs(t = 0).degree() for f in d["system"]]
-
-def instructions(data, derivative = False):
+ return [A(f).subs(t=0).degree() for f in d["system"]]
+
+
+def instructions(data, derivative=False):
function = "f" if not derivative else "df"
for pkg in ["algpath", "adaptive"]:
- pkg_out = Path("benchmarks") / Path(data) / Path(pkg) / Path("out.json")
+ pkg_out = Path("benchmarks") / Path(data) / \
+ Path(pkg) / Path("out.json")
if pkg_out.exists():
return json.load(open(str(pkg_out), "r"))["instructions"][function]
return -1
-
-#. Formulas for the different statistics to computes
+
+def name(data):
+ data_names = data.split("/")
+ if data_names[0] in ["linear", "newton"]:
+ name = data_names[1]
+ else:
+ name = data_names[0]
+
+ name = name.split("-")[0]
+ name += " *"*("random" in data) + \
+ " \\textsuperscript{N}"*("newton" in data) + " \\textsuperscript{F}"*("factorized" in data)
+ return name
+
+
+# . Formulas for the different statistics to computes
data_stats = {
"raw name": lambda data: data.replace("/", "\_"),
- "name": lambda data: data.split("/")[1].split("-")[0] + " *"*(not "all" in data) + " \\textsuperscript{N}"*("newton" in data),
+ "name": name,
"dimension": lambda data: len(json.load(open(f"data/{data}.json", "r"))["system"]),
"max deg": lambda data: int(max(degrees(data))),
"paths": lambda data: len(json.load(open(f"data/{data}.json", "r"))["fiber"]),
@@ -194,11 +215,13 @@ result_stats = {
"maxmeanprec": lambda res: steps_format(max([int(p) for p in res["meanpreclist"]])),
"wmeanprec": lambda res: steps_format(numpy.mean([int(p) for p in res["weightedmeanpreclist"]])),
"maxwmeanprec": lambda res: steps_format(max([int(p) for p in res["weightedmeanpreclist"]])),
+ "pathjump": lambda res: "" + ("ncertified" in res and "failures" in res and int(res["ncertified"]) != len(res["steplist"]) - int(res["failures"]))*"X"
}
+
def _table(data, branch, node):
key = node["val"]
-
+
# Data stats
if key in data_stats:
try:
@@ -208,44 +231,51 @@ def _table(data, branch, node):
# Local stats
if key in result_stats:
- pkg_name = branch[0]
- results = json.load(open(f"benchmarks/{data}/{pkg_name}/out.json", "r"))
+ pkg_name = branch[1]
try:
+ results = json.load(
+ open(f"benchmarks/{data}/{pkg_name}/out.json", "r"))
return [{"str": str(result_stats[key](results)), "w": int(1)}]
except:
- return [{"str": "", "w": int(1)}]
-
+ return [{"str": "err", "w": int(1)}]
+
# Packages handling
if key in ["homotopycontinuation", "algpath", "macaulay2", "sirocco", "adaptive"]:
dir = f"benchmarks/{data}/{key}/"
if not (Path(dir) / "info.json").exists():
return [{"str": "not benchmarked", "w": len(get_leaves(node))}]
-
- info_dict = json.load(open(f"{dir}info.json"))
+
+ try:
+ info_dict = json.load(open(f"{dir}info.json"))
+ except:
+ return [{"str": "err", "w": len(get_leaves(node))}]
+
if info_dict["timeout error"]:
timeout = info_dict["timeout"]
return [{"str": f"$>$ {time_format(timeout)}", "w": len(get_leaves(node))}]
-
+
if info_dict["memory error"]:
memory = info_dict["memory"]
return [{"str": f"$>$ {bytes_format(memory)}", "w": len(get_leaves(node))}]
if info_dict["script error"]:
return [{"str": "script error", "w": len(get_leaves(node))}]
-
+
if info_dict["killed manually"]:
return [{"str": "killed", "w": len(get_leaves(node))}]
# By default, compute recursively the table
# This is the case for the following node values: "instructions"
- return sum([_table(data, [key] + branch, child) for child in node["children"]], [])
-
+ return sum([_table(data, branch + [key], child) for child in node["children"]], [])
+
+
def table(data, dict):
return _table(data, [], dict)
# Computing the table and writing it in a .json file
-table_dict = {"header": header(header_dict), "table": [table(data, header_dict) for data in data_list]}
+table_dict = {"header": header(header_dict), "table": [
+ table(data, header_dict) for data in data_list]}
table_file = open(f"{os.path.dirname(args.entries)}/table.json", "w")
-json.dump(table_dict, table_file, indent = 2)
-table_file.close()
\ No newline at end of file
+json.dump(table_dict, table_file, indent=2)
+table_file.close()
diff --git a/tables/issac_2025/entries.json b/tables/issac_2025/entries.json
index 786d88d775ba48daafd919cb6e1bc3d7d2b733d9..668b880725e7b4ec05ad23fce2c05b2ae1417cd4 100644
--- a/tables/issac_2025/entries.json
+++ b/tables/issac_2025/entries.json
@@ -49,8 +49,21 @@
"children": []
},
{
- "val": "maxsteps",
+ "val": "pathjump",
"children": []
+ },
+ {
+ "val": "steps",
+ "children": [
+ {
+ "val": "medsteps",
+ "children": []
+ },
+ {
+ "val": "maxsteps",
+ "children": []
+ }
+ ]
}
]
},
@@ -62,15 +75,33 @@
"children": []
},
{
- "val": "maxprec",
- "children": []
+ "val": "prec",
+ "children": [
+ {
+ "val": "maxprec",
+ "children": []
+ },
+ {
+ "val": "maxwmeanprec",
+ "children": []
+ }
+ ]
},
{
- "val": "maxsteps",
- "children": []
+ "val": "steps",
+ "children": [
+ {
+ "val": "medsteps",
+ "children": []
+ },
+ {
+ "val": "maxsteps",
+ "children": []
+ }
+ ]
}
]
}
]
}
-}
+}
\ No newline at end of file