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Commit 5ab9ee85 authored by HEMERY Mathieu's avatar HEMERY Mathieu
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Merge branch 'feature/Hybrid' into develop

parents 0104137f 6ab1ee95
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arithmetic_rules.pl
View file @ 5ab9ee85
......@@ -9,6 +9,9 @@
normalize_number/2
]).
% Insert here for separate compilation and linting
:- use_module(doc).
:- use_module(util).
:- dynamic(canonical/3).
......
events.pl
View file @ 5ab9ee85
......@@ -3,6 +3,7 @@
[
% Public API
add_event/2,
add_time_event/2,
list_events/0,
list_model_events/0
]
......@@ -51,10 +52,22 @@ add_event(Condition, ParameterValues) :-
add_item([kind: event, item: event(Condition, ParameterValues)]).
add_time_event(Condition, ParameterValues) :-
biocham_command(*),
type(Condition, condition),
Condition =.. [_Functor, 'Time', Threshold],
type(ParameterValues, '*'(parameter_name = arithmetic_expression)),
doc('Introduce a special kind of event when Time is the only variable, they may be used
for efficiency reason during numerical integration. The only allowed syntax is of the
form: Time > a or Time >= b.'),
add_item([kind: time_event, item: event('Time'>Threshold, ParameterValues)]).
list_events :-
biocham_command,
doc('lists all the declared events.'),
list_items([kind: event]).
list_items([kind: event]),
list_items([kind: time_event]).
:- devdoc('\\section{Private predicates}').
......@@ -65,6 +78,7 @@ list_model_events :-
lists all the events in a loadable syntax
(auxiliary predicate of list_model).
'),
% List the regular events
\+ (
item(
[no_inheritance, kind: event, item: event(Condition, ParameterValues)]
......@@ -78,4 +92,19 @@ list_model_events :-
),
write(').\n')
)
),
% List the time events
\+ (
item(
[no_inheritance, kind: time_event, item: event(Condition, ParameterValues)]
),
\+ (
format('add_time_event(~w, ', [Condition]),
write_successes(
member(Parameter = Value, ParameterValues),
write(', '),
format('~w = ~w', [Parameter, Value])
),
write(').\n')
)
).
hybrid.pl 0 → 100644
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This diff is collapsed.
hybrid.plt 0 → 100644
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:- use_module(hybrid).
example_reactions([[[1*gen],[1*tem],c1*'gen_stoch'],[[1*tem],[],c2*('tem_total'/(100*1))],[[1*tem],[1*tem,1*gen],c3*('tem_total'/(100*1))],[[1*gen,1*struc],[1*virus],c4*('gen_stoch'*('struc_total'/(100*1)))]]).
:- begin_tests(hybrid).
test(build_constraints_list) :-
hybrid:build_constraints_list([[a],[0],[b,c]], [lower_level1, '0', lower_level3]).
test(build_reaction_data) :-
Sorted_species = [gen,struc,tem,virus],
example_reactions(List),
hybrid:build_reaction_data(List, Sorted_species, Data),
Data = [[['-1','+0','+1','+0'],c1*'gen_stoch'],[['+0','+0','-1','+0'],c2*('tem_total'/(100*1))],[['+1','+0','+0','+0'],c3*('tem_total'/(100*1))],[['-1','-1','+0','+1'],c4*('gen_stoch'*('struc_total'/(100*1)))]].
test(compute_maximum_change) :-
example_reactions(List),
hybrid:compute_maximum_change(List,2).
:- end_tests(hybrid).
library/examples/hybrid/Goutsias_dynamic.bc 0 → 100644
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MA(c1) for a => a + b.
MA(c2) for b => _.
MA(c3) for c => a + c.
MA(c4) for a => _.
MA(c5) for d + e => c.
MA(c6) for c => d + e.
MA(c7) for c + e => f.
MA(c8) for f => c + e.
MA(c9) for b + b => e.
MA(c10) for e => b + b.
parameter(c1 = 0.043).
parameter(c2 = 7e-4).
parameter(c3 = 71.5).
parameter(c4 = 3.9e-6).
parameter(c5 = 0.02).
parameter(c6 = 0.48).
parameter(c7 = 4e-4).
parameter(c8 = 9e-12).
parameter(c9 = 0.08).
parameter(c10 = 0.5).
present(a,0).
present(b,10).
present(c,0).
present(d,2).
present(e,10).
present(f,0).
library/examples/hybrid/Goutsias_input_ode.bc 0 → 100644
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MA(c9) for b + b => e.
MA(c10) for e => b + b.
parameter(c9 = 0.08).
parameter(c10 = 0.5).
present(b,10).
present(e,10).
library/examples/hybrid/Goutsias_input_stoch.bc 0 → 100644
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MA(c1) for a => a + b.
MA(c2) for b => _.
MA(c3) for c => a + c.
MA(c4) for a => _.
MA(c5) for d + e => c.
MA(c6) for c => d + e.
MA(c7) for c + e => f.
MA(c8) for f => c + e.
parameter(c1 = 0.043).
parameter(c2 = 7e-4).
parameter(c3 = 71.5).
parameter(c4 = 3.9e-6).
parameter(c5 = 0.02).
parameter(c6 = 0.48).
parameter(c7 = 4e-4).
parameter(c8 = 9e-12).
present(a,0).
present(b,10).
present(c,0).
present(d,2).
present(e,10).
present(f,0).
library/examples/hybrid/T7.bc 0 → 100644
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MA(c1) for gen => tem.
MA(c2) for tem => _.
MA(c3) for tem => tem + gen.
MA(c4) for gen + struc => virus.
MA(c5) for tem => tem + struc.
MA(c6) for struc => _.
parameter(c1 = 0.025).
parameter(c2 = 0.25).
parameter(c3 = 1).
parameter(c4 = 0.0000075).
parameter(c5 = 1000).
parameter(c6 = 1.99).
present(gen,0).
present(tem).
present(struc,0).
present(virus,0).
\ No newline at end of file
library/examples/hybrid/T7_hybrid.bc 0 → 100644
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parameter(gen_stoch = 0).
parameter(virus_stoch = 0).
parameter(alpha1 = 0).
parameter(alpha2 = 0).
parameter(alpha3 = 0).
parameter(alpha4 = 0).
parameter(alpha_sum = 0).
% Hybrid species
present(tem).
parameter(tem_stoch = 0).
function(tem_total =tem+tem_stoch).
parameter(tem_total =tem+tem_stoch).
function(virus = virus_stoch).
parameter(struc_stoch = 0).
function(struc_total = struc+struc_stoch).
parameter(struc_total = struc+struc_stoch).
tem_total * 1000 for tem => tem + struc.
struc_total * 1.99 for struc => _.
% stochastic
parameter(tau = 0).
parameter(ran = 0).
add_event(Time > tau,
alpha1 = gen_stoch * 0.025,
alpha2 = tem_total * 0.25,
alpha3 = tem_total,
alpha4 = gen_stoch * struc_total * 0.0000075,
alpha_sum = alpha1 + alpha2 + alpha3 + alpha4,
tau = (if alpha_sum <= 0 then inf else Time+(-1 / alpha_sum) * log(random_float)),
ran = random_float,
gen_stoch = (if alpha_sum*ran>0 and alpha_sum*ran<=alpha1 then gen_stoch-1
else if alpha_sum*ran>alpha1+alpha2 and alpha_sum*ran<=alpha1+alpha2+alpha3 then gen_stoch+1
else if alpha_sum*ran>alpha1+alpha2+alpha3 and alpha_sum*ran<=alpha1+alpha2+alpha3+alpha4 then gen_stoch-1
else gen_stoch),
tem_stoch = (if alpha_sum*ran>0 and alpha_sum*ran<=alpha1 then tem_stoch+1
else if alpha_sum*ran>alpha1 and alpha_sum*ran<=alpha1+alpha2 then tem_stoch-1
else tem_stoch),
struc_stoch = (if alpha_sum*ran>alpha1+alpha2+alpha3 and alpha_sum*ran<=alpha1+alpha2+alpha3+alpha4 then struc_stoch-1
else struc_stoch),
virus_stoch = (if alpha_sum*ran>alpha1+alpha2+alpha3 and alpha_sum*ran<=alpha1+alpha2+alpha3+alpha4 then virus_stoch+1
else virus_stoch)).
option(show: {struc_total,virus}).
\ No newline at end of file
library/examples/hybrid/T7_input_ode.bc 0 → 100644
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MA(c5) for tem => tem + struc.
MA(c6) for struc => _.
parameter(c5 = 1000).
parameter(c6 = 1.99).
present(tem, 1).
present(struc, 0).
\ No newline at end of file
library/examples/hybrid/T7_input_stoch.bc 0 → 100644
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MA(c1) for gen => tem.
MA(c2) for tem => _.
MA(c3) for tem => tem + gen.
MA(c4) for gen + struc => virus.
parameter(c1 = 0.025).
parameter(c2 = 0.25).
parameter(c3 = 1).
parameter(c4 = 0.0000075).
present(gen, 0).
present(tem, 1).
present(struc, 0).
present(virus, 0).
\ No newline at end of file
library/examples/hybrid/Test_dynamic.bc 0 → 100644
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MA(k1) for A + 2*B => C.
MA(k2) for C => 2*A.
parameter(k1 = 1).
parameter(k2 = 1).
present(A,1).
present(B,1).
present(C,0).
\ No newline at end of file
library/examples/hybrid/Test_dynamic_out.bc 0 → 100644
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parameter(tau = 0).
parameter(ran = 0).
parameter(delta_t = 0).
parameter(k1_diff = 0).
parameter(k2_diff = 0).
function(kk1 = k1_diff).
function(kk2 = k2_diff).
function(A_total = floor(100*1*A + A_stoch)).
parameter(A_stoch = 0).
function(AA = A_stoch).
function(B_total = floor(100*1*B + B_stoch)).
parameter(B_stoch = 0).
function(BB = B_stoch).
function(C_total = floor(100*1*C + C_stoch)).
parameter(C_stoch = 0).
function(CC = C_stoch).
k1_diff*(k1*((A_total/(100*1))*(B_total/(100*1))^2))for A+2*B=>C.
k2_diff*(k2*(C_total/(100*1)))for C=>2*A.
present(A,1).
present(B,1).
present(C,0).
parameter(
k1 = 1,
k2 = 1
).
parameter(alpha1 = 0).
parameter(alpha2 = 0).
parameter(alpha_sum = 0).
parameter(lower_level1 = 0).
parameter(lower_level2 = 0).
parameter(lower_level3 = 0).
add_event(Time > tau,
k1_diff = (if k1*(A_total*B_total^2) >= 1/(step_size * 20) and A_total >= 10 and B_total >= 10 then 1 else 0),
k2_diff = (if k2*C_total >= 1/(step_size * 20) and C_total >= 20 then 1 else 0),
alpha1 = (1-k1_diff)*(k1/2*A_total/100*B_total/100*(B_total+ -1)/100),
alpha2 = (1-k2_diff)*(k2*C_total/100),
alpha_sum = alpha1 + alpha2,
delta_t = (if alpha_sum <= 0 then step_size else (-1 / alpha_sum) * log(random_float)),
tau = Time+delta_t/100,
ran = random_float,
lower_level1 = (if A_total >= 1 then 1 else 0),
lower_level2 = (if B_total >= 2 then 1 else 0),
lower_level3 = (if C_total >= 1 then 1 else 0),
A_stoch = (if alpha_sum*ran>0 and alpha_sum*ran<=alpha1 and lower_level1>0 then A_stoch-1
else if alpha_sum*ran>alpha1 and alpha_sum*ran<=alpha1 + alpha2 and lower_level2>0 then A_stoch+2
else A_stoch),
B_stoch = (if alpha_sum*ran>0 and alpha_sum*ran<=alpha1 and lower_level1>0 then B_stoch-2
else B_stoch),
C_stoch = (if alpha_sum*ran>0 and alpha_sum*ran<=alpha1 and lower_level1>0 then C_stoch+1
else if alpha_sum*ran>alpha1 and alpha_sum*ran<=alpha1 + alpha2 and lower_level2>0 then C_stoch-1
else C_stoch)
).
% Plot part
option(show: {A_total, B_total, C_total}). % Choose here the species to plot
numerical_simulation(method:rsbk, time: 20).
plot.
option(show: {}).
\ No newline at end of file
library/examples/hybrid/biomodel9_input_ode.bc 0 → 100644
View file @ 5ab9ee85
MA(r2a__a2) for P_KKK+E2=>E2_P_KKK.
MA(r2a__d2) for E2_P_KKK=>P_KKK+E2.
MA(r2b__k2) for E2_P_KKK=>E2+KKK.
MA(r3a__a3) for KK+P_KKK=>P_KKK_KK.
MA(r3a__d3) for P_KKK_KK=>KK+P_KKK.
MA(r3b__k3) for P_KKK_KK=>P_KK+P_KKK.
MA(r4a__a4) for P_KK+KKPase=>KKPase_P_KK.
MA(r4a__d4) for KKPase_P_KK=>P_KK+KKPase.
MA(r4b__k4) for KKPase_P_KK=>KK+KKPase.
MA(r5a__a5) for P_KK+P_KKK=>P_KKK_P_KK.
MA(r5a__d5) for P_KKK_P_KK=>P_KK+P_KKK.
MA(r5b__k5) for P_KKK_P_KK=>PP_KK+P_KKK.
MA(r6a__a6) for PP_KK+KKPase=>KKPase_PP_KK.
MA(r6a__d6) for KKPase_PP_KK=>PP_KK+KKPase.
MA(r6b__k6) for KKPase_PP_KK=>P_KK+KKPase.
MA(r7a__a7) for K+PP_KK=>PP_KK_K.
MA(r7a__d7) for PP_KK_K=>K+PP_KK.
MA(r7b__k7) for PP_KK_K=>P_K+PP_KK.
MA(r8a__a8) for P_K+KPase=>KPase_P_K.
MA(r8a__d8) for KPase_P_K=>P_K+KPase.
MA(r8b__k8) for KPase_P_K=>K+KPase.
MA(r9a__a9) for P_K+PP_KK=>PP_KK_P_K.
MA(r9a__d9) for PP_KK_P_K=>P_K+PP_KK.
MA(r9b__k9) for PP_KK_P_K=>PP_KK+PP_K.
MA(r10a__a10) for PP_K+KPase=>KPase_PP_K.
MA(r10a__d10) for KPase_PP_K=>PP_K+KPase.
MA(r10b__k10) for KPase_PP_K=>P_K+KPase.
present(E2,0.0003).
present(KKK,0.003).
present(P_KKK,0.0).
present(KK,1.2).
present(P_KK,0.0).
present(PP_KK,0.0).
present(K,1.2).
present(P_K,0.0).
present(PP_K,0.0).
present(KPase,0.12).
present(KKPase,0.0003).
present(E2_P_KKK,0.0).
present(P_KKK_KK,0.0).
present(P_KKK_P_KK,0.0).
present(PP_KK_K,0.0).
present(PP_KK_P_K,0.0).
present(KKPase_PP_KK,0.0).
present(KKPase_P_KK,0.0).
present(KPase_PP_K,0.0).
present(KPase_P_K,0.0).
parameter(
compartment = 4.0e-12,
K_PP_norm_max = 0.900049,
r2a__a2 = 1000.0,
r2a__d2 = 150.0,
r2b__k2 = 150.0,
r3a__a3 = 1000.0,
r3a__d3 = 150.0,
r3b__k3 = 150.0,
r4a__a4 = 1000.0,
r4a__d4 = 150.0,
r4b__k4 = 150.0,
r5a__a5 = 1000.0,
r5a__d5 = 150.0,
r5b__k5 = 150.0,
r6a__a6 = 1000.0,
r6a__d6 = 150.0,
r6b__k6 = 150.0,
r7a__a7 = 1000.0,
r7a__d7 = 150.0,
r7b__k7 = 150.0,
r8a__a8 = 1000.0,
r8a__d8 = 150.0,
r8b__k8 = 150.0,
r9a__a9 = 1000.0,
r9a__d9 = 150.0,
r9b__k9 = 150.0,
r10a__a10 = 1000.0,
r10a__d10 = 150.0,
r10b__k10 = 150.0
).
function(
K_PP_norm = (PP_K+KPase_PP_K)/(PP_K+P_K+K+PP_KK_K+PP_KK_P_K+KPase_PP_K+KPase_P_K),
rel_K_PP_max = K_PP_norm/K_PP_norm_max,
KK_PP_norm = (PP_KK+PP_KK_K+PP_KK_P_K+KKPase_PP_KK)/(PP_KK+P_KK+KK+PP_KK_K+PP_KK_P_K+P_KKK_KK+P_KKK_P_KK+KKPase_PP_KK+KKPase_P_KK),
KKK_P_norm = (P_KKK+P_KKK_KK+P_KKK_P_KK)/(KKK+P_KKK+P_KKK_KK+P_KKK_P_KK)
).
\ No newline at end of file
library/examples/hybrid/biomodel9_input_stoch.bc 0 → 100644
View file @ 5ab9ee85
MA(r1a__a1) for KKK+E1=>E1_KKK.
MA(r1a__d1) for E1_KKK=>KKK+E1.
MA(r1b__k2) for E1_KKK=>E1+P_KKK.
present(E1,3.0e-5).
present(KKK,0.003).
present(E1_KKK,0.0).
present(P_KKK,0.0).
parameter(
r1a__a1 = 1000.0,
r1a__d1 = 150.0,
r1b__k2 = 150.0).
\ No newline at end of file
library/examples/hybrid/cell_input_ode.bc 0 → 100644
View file @ 5ab9ee85
MA(k3) for a => b.
MA(k4) for b + 2* c => 3*c.
MA(k8) for h => d.
MA(k9) for d => h.
present(h = 1).
%function(YT = g + f + [b] + [c]).
% function(CT = b + c + d + h).
parameter(k3 = 200). % k3*CT = 200
parameter(k4 = 180). % 10 < k4/CT^2 < 1000
parameter(k8 = 10000). % k8 >> k9
parameter(k9 = 100). % k9 >> k6
\ No newline at end of file
library/examples/hybrid/cell_input_stoch.bc 0 → 100644
View file @ 5ab9ee85
MA(k1) for _=>g.
MA(k2) for g=>_.
MA(k4p) for b => c.
MA(k5) for c => b.
MA(k6) for c => e.
MA(k7) for f =>_.
parameter(k1 = 0.1). % k1*CT = 0.015
parameter(k2 = 0).
parameter(k5 = 0).
parameter(k6 = 1). % 0.1 < k6 < 10
parameter(k7 = 0.6).
parameter(k4p = 0.018).
library/initial.bc
View file @ 5ab9ee85
......@@ -7,6 +7,7 @@ option(
error_epsilon_relative: 1e-6,
initial_step_size: 1e-6,
maximum_step_size: 1e-2,
minimum_step_size: 1e-5,
precision: 6, %5
nusmv_initial_states: all,
nusmv_counter_example: no,
......
markov.pl
View file @ 5ab9ee85
......@@ -26,8 +26,12 @@ stochastic_simulation(Until, Propensities, Time, Boolean) :-
retractall(last_time(_)),
assertz(last_time(0.0)),
get_option(stochastic_thresholding, Threshold),
%statistics(runtime,_),
markov_run(InitState, Conditions, Actions, Until, Propensities, Time,
Threshold),
%statistics(runtime,[_,T]),
%TT is T/1000,
%format("Simulation time: ~ps~n",[TT]),
make_state_table,
restore_parameters.
......
matrix.pl 0 → 100644
View file @ 5ab9ee85
:- module(matrix,
[
constant_list/3,
constant_matrix/4,
replace/4,
get_element/3,
replace_element/3,
init_matrix/1,
write_matrix/1,
ludcmp_matrix/2,
ludcmp_matrix/0,
matrix_sum/4,
matrix_prod/3,
scalar_prod/3,
matrix_apply/3,
matrix_sum/3,
create_diag_matrix/3,
sub_matrix/1,
transpose_matrix/2,
lusubst/2,
solve_linear_problem/3
]
).
:- use_module(util).
/* Module Matrix
*
* Several operations are done on a "global variable" of SWI-prolog (using nb_set/getval)
* but this is due to historical version of an efficient implementation in GNU-prolog and
* may not be necessary nor useful now.
*/
%! constant_list(+Length, +Element, -List)
%
% create a list with every element set up to Element
constant_list(0,_,[]) :-
!.
constant_list(N1,X,[X|L]) :-
N1 > 0, N is N1 - 1,
constant_list(N,X,L).
%! constant_matrix(+N_row, +N_column, +Element, -List)
%
% create a matrix with every element set up to Element
constant_matrix(RowSize,ColumnSize,Value,Matrix) :-
constant_list(ColumnSize,Value,Row), % The row size is the number of column
constant_list(RowSize,Row,Matrix).
%! replace(+List, +Index, +NewElement, -NewList)
%
% Allows to replace the i-th element of the list, where the 1st element is index by 1
replace([_|Tail], 1, NewElement, [NewElement|Tail]) :-
!.
replace([Element|Tail], I, NewElement, [Element|Tail2]):-
I > 1, I1 is I-1,
replace(Tail, I1, NewElement, Tail2).
%! init_matrix(+Matrix)
%
% Creates the global variable which will stores the matrix on which we are doing operations
init_matrix([Head|Tail]):-
length([Head|Tail],RowSize),
length(Head,ColumnSize),
nb_setval(stored_matrix,[Head|Tail]),
nb_setval(formal_m,RowSize),
nb_setval(formal_n,ColumnSize).
%! get_element(+RowIndex, +ColumnIndex, -Value)
%
% get the (i,j)-th element of the stored_matrix
get_element(RowIndex,ColumnIndex,Value) :-
nb_getval(stored_matrix,Matrix),
nth1(RowIndex,Matrix,Row),
nth1(ColumnIndex,Row,Value).
%! replace_element(+RowIndex, +ColumnIndex, +Value) :-
%
% set the (i,j)-th element of the stored matrix to Value
replace_element(RowIndex,ColumnIndex,Value) :-
nb_getval(stored_matrix,Matrix),
nth1(RowIndex,Matrix,Row),
replace(Row,ColumnIndex,Value,NewRow),
replace(Matrix,RowIndex,NewRow,NewMatrix),
nb_setval(stored_matrix,NewMatrix).
/* Some tools to write matrix in a pretty way, for debugging for examples*/
%! write_matrix(+Matrix)
write_matrix([]).
write_matrix([H|T]):-
write_tab(H),
write_matrix(T).
%! write_tab(+List)
write_tab([]) :-
nl.
write_tab([H|T]):-
write(H),write('\t'),
write_tab(T).
%! ludcmp_matrix(+Matrix, -TransformedMatrix)
%
% Perform an LU decomposition, that is find two matrices L and U such that Matrix = L.U,
% L and U begin respectively lower and upper diagonal.
% By convention, L has only 1 on its diagonal so that we gather them in a single matrix M
% such that M[i,j] = L[i,j] if i<j and M[i,j] = U[i,j] if i>=j. M is the transformed
% matrix and is stored in the global variable at the end of the call.
ludcmp_matrix(A,B):-
init_matrix(A),
ludcmp_matrix,
nb_getval(stored_matrix,B).
ludcmp_matrix :-
% Value if pivot element is zero (singular)
TINY=1.0E-100,
nb_getval(formal_m,M),