def test_initial_state(self): model = load(join(dirname(__file__), "reprod_all.bnd"), join(dirname(__file__), "reprod_all.cfg")) i1 = model.get_initial_state() model = load(join(dirname(__file__), "reprod_all.bnd"), join(dirname(__file__), "reprod_joined_init.cfg")) i2 = model.get_initial_state() self.assertEqual(set(i1.keys()), set(i2.keys())) self.assertEqual(i2["p63"], 1) self.assertEqual(i2["p53"], 1) self.assertEqual(i2["GF"], [0,1])
def test_load_multiple_cfgs(self):
sim = load(join(dirname(__file__), "reprod_all.bnd"))
sim2 = load(join(dirname(__file__), "p53_Mdm2.bnd"),
join(dirname(__file__), "p53_Mdm2_runcfg.cfg"))
sim3 = load(join(dirname(__file__), "cellcycle.bnd"),
join(dirname(__file__), "cellcycle_runcfg.cfg"),
join(dirname(__file__), "cellcycle_runcfg-thread_1.cfg"))
def test_uppmaboss_write(self):
sim = load(
"https://raw.githubusercontent.com/sysbio-curie/UPMaBoSS-docker/master/CellFate/CellFateModel_uppmaboss.bnd",
"https://raw.githubusercontent.com/sysbio-curie/UPMaBoSS-docker/master/CellFate/CellFateModel_uppmaboss.cfg"
)
uppmaboss_model = UpdatePopulation(sim)
uppmaboss_model.setDivisionNode("Division")
uppmaboss_model.setDeathNode("Death")
uppmaboss_model.setExternalVariable(
"$TNF_induc", "$ProdTNF_NFkB*p[(NFkB,Death) = (1,0)]")
uppmaboss_model.setStepNumber(12)
uppmaboss_sim = uppmaboss_model.run('defined')
expected_pop_ratios = [
1.0, 0.9218339999999924, 0.8467423241939606, 0.8180987248510877,
0.7990468417467085, 0.7717098511967935, 0.7300537251389624,
0.677575273214723, 0.6208988119113313, 0.5665235984581267,
0.5183656934475426, 0.4771136331972621, 0.4430243412189205
]
pop_ratios = uppmaboss_sim.get_population_ratios('WT').values.tolist()
for i, pop_ratio in enumerate(pop_ratios):
self.assertAlmostEqual(pop_ratio, expected_pop_ratios[i])
def test_load_reserved_names(self):
with self.assertRaises(Exception) as context:
sim = load(join(dirname(__file__), "reserved_names.bnd"),
join(dirname(__file__), "reserved_names.cfg"))
print(context.exception)
self.assertTrue("Name NOT is reserved !" == str(context.exception))
def test_copy_p53_Mdm2(self):
sim = load(join(dirname(__file__), "p53_Mdm2.bnd"),
join(dirname(__file__), "p53_Mdm2_runcfg.cfg"))
sim_copy = sim.copy()
self.assertEqual(str(sim.network), str(sim_copy.network))
self.assertEqual(sim.str_cfg(), sim_copy.str_cfg())
def test_modifications_p53_Mdm2(self):
sim = load(join(dirname(__file__), "p53_Mdm2.bnd"),
join(dirname(__file__), "p53_Mdm2_runcfg.cfg"))
sim.update_parameters(sample_count=100)
sim.network.set_output(['Mdm2C', 'Mdm2N'])
sim.mutate("Dam", "ON")
res = sim.run()
probas = res.get_last_states_probtraj().values[0]
expected_probas = [0.442395, 0.018827, 0.157108, 0.381669]
for i, proba in enumerate(probas):
self.assertAlmostEqual(proba,
expected_probas[i],
delta=proba * 1e-6)
if exists("saved_sim"):
shutil.rmtree("saved_sim")
res.save("saved_sim")
self.assertTrue(exists("saved_sim"))
self.assertTrue(exists("saved_sim/saved_sim.bnd"))
self.assertTrue(exists("saved_sim/saved_sim.cfg"))
self.assertTrue(exists("saved_sim/res_probtraj.csv"))
self.assertTrue(exists("saved_sim/res_fp.csv"))
self.assertTrue(exists("saved_sim/res_statdist.csv"))
def perform_MaBoSS_simulation(n_profile, fname, profile_name, list_drugs):
path_fname = path_model + "_" + str(n_profile)
for drug_id in list_drugs:
path_fname_drug = path_fname + "_drug" + str(drug_id)
#fname_drug=fname+"_drug"+str(drug_id)
os.system("chmod +x " + path_fname_drug + ".bnd")
os.system("chmod +x " + path_fname_drug + ".cfg")
os.chdir(os.path.dirname(path_model))
simulation = maboss.load(path_fname_drug + ".bnd",
path_fname_drug + ".cfg")
result = simulation.run()
nodes_traj = result.get_nodes_probtraj()[outputs]
final_results = nodes_traj.tail(1).to_csv(header=0, index=1,
sep=' ')[:-1]
# add the number of the simulation to the line finally saved
os.system("echo '" + str(n_profile) + " " + profile_name + " " +
str(drug_id) + " " + final_results + "' >> " + save_file)
#Remove temporary files
#os.system("rm "+path_fname_drug+"/*")
#os.system("rmdir "+path_fname_drug)
#os.system("rm "+path_fname_drug+".bnd")
#os.system("rm "+path_fname_drug+".cfg")
previous.append(n_profile)
def test_probtraj_cellcycle_cmaboss(self):
path = dirname(__file__)
sim = load(join(path, "cellcycle.bnd"),
join(path, "cellcycle_runcfg.cfg"),
join(path, "cellcycle_runcfg-thread_1.cfg"))
res = sim.run(cmaboss=True)
res_states_probtraj = pandas.read_csv(join(
path, "res", "cellcycle_states_probtraj.csv"),
index_col=0,
header=0)
res_last_states_probtraj = pandas.read_csv(join(
path, "res", "cellcycle_last_states_probtraj.csv"),
index_col=0,
header=0)
res_nodes_probtraj = pandas.read_csv(join(
path, "res", "cellcycle_nodes_probtraj.csv"),
index_col=0,
header=0)
self.assertTrue(
numpy.isclose(res.get_states_probtraj().sort_index(axis=1),
res_states_probtraj.sort_index(axis=1)).all())
self.assertTrue(
numpy.isclose(res.get_last_states_probtraj().sort_index(axis=1),
res_last_states_probtraj.sort_index(axis=1)).all())
self.assertTrue(
numpy.isclose(res.get_nodes_probtraj().sort_index(axis=1),
res_nodes_probtraj.sort_index(axis=1)).all())
def test_simulate_p53_Mdm2(self): sim = load(join(dirname(__file__), "p53_Mdm2.bnd"), join(dirname(__file__), "p53_Mdm2_runcfg.cfg")) res = sim.run() res.plot_fixpoint() res.plot_trajectory(error=True) res.plot_node_trajectory(error=True) res.plot_entropy_trajectory() res.plot_piechart()
def test_load_confusedparser(self): sim = load( join(dirname(__file__), "confused_parser.bnd"), join(dirname(__file__), "confused_parser.cfg") ) self.assertEqual( list(sim.network.keys()), ['A', 'NOTH', 'B'] )
def test_uppmaboss_remote(self):
sim = load(
"https://raw.githubusercontent.com/sysbio-curie/UPMaBoSS-docker/master/CellFate/CellFateModel_uppmaboss.bnd",
"https://raw.githubusercontent.com/sysbio-curie/UPMaBoSS-docker/master/CellFate/CellFateModel_uppmaboss.cfg"
)
uppmaboss_model = UpdatePopulation(
sim,
"https://github.com/sysbio-curie/UPMaBoSS-docker/blob/master/CellFate/CellFateModel_uppmaboss.upp"
)
uppmaboss_sim = uppmaboss_model.run('remote')
def test_type_istate(self):
sim = load(
join(dirname(__file__), "TregModel_InitPop.bnd"),
join(dirname(__file__), "TregModel_InitPop_ActTCR2_TGFB.cfg")
)
istate = sim.network.get_istate()
self.assertEqual([type(value) for value in istate["PTEN"].values()], [float, float])
self.assertEqual([type(value) for value in istate[("TCR_b1", "TCR_b2", "CD28")].values()], [str, str, str])
self.assertEqual([type(value) for value in istate[("PI3K_b1", "PI3K_b2")].values()], [float, float, float])
self.assertEqual([type(value) for value in istate["TGFB"].values()], [str, str])
def test_convert_reprod_all_minibn(self): model = load(join(dirname(__file__), "reprod_all.bnd"), join(dirname(__file__), "reprod_all.cfg")) minibn_model = to_minibn(model) self.assertEqual( sorted(list(minibn_model.keys())), sorted([ 'ECMicroenv', 'DNAdamage', 'Migration', 'Metastasis', 'VIM', 'AKT2', 'ERK', 'miR200', 'AKT1', 'EMT', 'Invasion', 'p63', 'SMAD', 'CDH2', 'CTNNB1', 'CDH1', 'p53', 'p73', 'miR34', 'ZEB2', 'Apoptosis', 'miR203', 'p21', 'CellCycleArrest', 'GF', 'NICD', 'TGFbeta', 'TWIST1', 'SNAI2', 'ZEB1', 'SNAI1', 'DKK1' ]) )
def test_run_p53_Mdm2(self):
sim = load(join(dirname(__file__), "p53_Mdm2.bnd"),
join(dirname(__file__), "p53_Mdm2_runcfg.cfg"))
mbcli = MaBoSSClient(host="localhost", port=7777)
res = mbcli.run(sim)
self.assertEqual(
res.getFP(), "Fixed Points (1)\n" +
"FP\tProba\tState\tMdm2N\tp53_h\tp53\tMdm2C\tDam\n" +
"#1\t0.90536\tMdm2N\t1\t0\t0\t0\t0\n")
res.get_states_probtraj()
res.get_statdist_clusters()
mbcli.close()
def test_uppmaboss_cmaboss(self):
sim = load(join(dirname(__file__), "CellFateModel.bnd"),
join(dirname(__file__), "CellFateModel_1h.cfg"))
uppmaboss_model = UpdatePopulation(
sim, join(dirname(__file__), "CellFate_1h.upp"))
uppmaboss_sim = uppmaboss_model.run('WT_cmaboss', cmaboss=True)
pop_ratios = uppmaboss_sim.get_population_ratios('WT').values.tolist()
expected_pop_ratios = [
1.0, 0.6907820416914479, 0.6341903631891185, 0.612996053462505,
0.5996083687781087, 0.5788914827739509, 0.5466795703259922,
0.5075723301828101, 0.46462393081796144, 0.4237712222056809,
0.388072085864841, 0.35730025864566073, 0.3320260202532354
]
for i, pop_ratio in enumerate(pop_ratios):
self.assertAlmostEqual(pop_ratio, expected_pop_ratios[i])
def test_uppmaboss_server(self):
sim = load(join(dirname(__file__), "CellFateModel.bnd"),
join(dirname(__file__), "CellFateModel_1h.cfg"))
uppmaboss_model = UpdatePopulation(
sim, join(dirname(__file__), "CellFate_1h.upp"))
uppmaboss_sim = uppmaboss_model.run(host='localhost', port=7777)
pop_ratios = uppmaboss_sim.get_population_ratios('WT').values.tolist()
expected_pop_ratios = [
1.0, 0.6907579999999945, 0.6341980442019741, 0.6126727283836865,
0.5992233366501704, 0.5788557354373725, 0.5473173595477481,
0.5081754112622799, 0.4654525962620004, 0.4247217704682538,
0.3886947462882363, 0.3581526679038661, 0.3328878624045683
]
for i, pop_ratio in enumerate(pop_ratios):
self.assertAlmostEqual(pop_ratio, expected_pop_ratios[i])
def test_statdist_p53_Mdm2(self):
path = dirname(__file__)
sim = load(join(path, "p53_Mdm2.bnd"), join(path,
"p53_Mdm2_runcfg.cfg"))
res = sim.run()
res_states_statdist = pandas.read_csv(join(
path, "res", "p53_Mdm2_states_statdist.csv"),
index_col=0,
header=0)
self.assertTrue(
numpy.isclose(
res.get_states_statdist().sort_index(axis=1).dropna(),
res_states_statdist.sort_index(axis=1).dropna()).all())
res_statdist_cluster0 = pandas.read_csv(join(
path, "res", "p53_Mdm2_statdist_cluster0.csv"),
index_col=0,
header=0)
self.assertTrue(
numpy.isclose(res.get_statdist_clusters()[0].sort_index(axis=1),
res_statdist_cluster0.sort_index(axis=1)).all())
res_statdist_clusters_summary = pandas.read_csv(join(
path, "res", "p53_Mdm2_statdist_clusters_summary.csv"),
index_col=0,
header=0)
self.assertTrue(
numpy.isclose(
res.get_statdist_clusters_summary().sort_index(axis=1),
res_statdist_clusters_summary.sort_index(axis=1)).all())
res_statdist_clusters_summary_error = pandas.read_csv(join(
path, "res", "p53_Mdm2_statdist_clusters_summary_error.csv"),
index_col=0,
header=0)
self.assertTrue(
numpy.isclose(
res.get_statdist_clusters_summary_error().sort_index(axis=1),
res_statdist_clusters_summary_error.sort_index(axis=1)).all())
def test_toyexample_cmaboss(self):
path = dirname(__file__)
sim = load(join(path, "Four_cycle.bnd"),
join(path, "Four_cycle_FEscape.cfg"))
set_nodes_istate(sim, ["A", "B", "C"], [1, 0])
res = sim.run()
self.assertEqual(list(res.get_nodes_probtraj().columns.values),
['A', 'B', 'C'])
sim.network.set_output(['A', 'B'])
res = sim.run(cmaboss=True)
self.assertEqual(list(res.get_nodes_probtraj().columns.values),
['A', 'B'])
with self.assertRaises(AssertionError,
msg="Node(s) 'D' not defined !"):
sim.network.set_output(['A', 'B', 'C', 'E'])
def test_uppmaboss_cmaboss_only_final_state(self):
sim = load(join(dirname(__file__), "CellFateModel.bnd"),
join(dirname(__file__), "CellFateModel_1h.cfg"))
uppmaboss_model = UpdatePopulation(
sim, join(dirname(__file__), "CellFate_1h.upp"))
uppmaboss_sim = uppmaboss_model.run('WT_cmaboss_final',
cmaboss=True,
only_final_state=True)
pop_ratios = uppmaboss_sim.get_population_ratios('WT').values.tolist()
expected_pop_ratios = [
1.0, 0.6778600000000088, 0.6279830611999899, 0.6097213137802712,
0.594362433886137, 0.5680084035675778, 0.5307981730498335,
0.4871453312981917, 0.4427225485370628, 0.4022798437281834,
0.367703891159712, 0.3393539211512898, 0.31562968852360135
]
for i, pop_ratio in enumerate(pop_ratios):
self.assertAlmostEqual(pop_ratio, expected_pop_ratios[i])
def getBioLQMModel(self):
if self.model.format == LogicalModel.MABOSS:
maboss_sim = maboss.load(
join(settings.MEDIA_ROOT, self.model.bnd_file.path),
join(settings.MEDIA_ROOT, self.model.cfg_file.path))
biolqm_model = maboss.to_biolqm(maboss_sim)
return biolqm_model
elif self.model.format == LogicalModel.ZGINML:
ginsim_model = ginsim.load(
join(settings.MEDIA_ROOT, self.model.file.path))
return ginsim.to_biolqm(ginsim_model)
elif self.model.format == LogicalModel.SBML:
biolqm_model = biolqm.load(
join(settings.MEDIA_ROOT, self.model.file.path))
return biolqm_model
else:
raise MethodNotAllowed()
def test_uppmaboss_overwrite(self):
# Now again, but with a modified max_time, and with overwrite
# Results should be different if overwriting indeed works
sim = load(join(dirname(__file__), "CellFateModel.bnd"),
join(dirname(__file__), "CellFateModel_1h.cfg"))
sim.param["max_time"] = 2
expected_pop_ratios = [
1.0, 0.6323979999999877, 0.5972195964539613, 0.5413299949589563,
0.4570216375540166, 0.3810664694790497, 0.3280296382569338,
0.29096852169701004, 0.26290169809410047, 0.23962359303974,
0.2201920366329486, 0.2039266710788974, 0.19007637943255015
]
uppmaboss_model = UpdatePopulation(
sim, join(dirname(__file__), "CellFate_1h.upp"))
uppmaboss_sim = uppmaboss_model.run('WT', overwrite=True)
pop_ratios = uppmaboss_sim.get_population_ratios('WT').values.tolist()
for i, pop_ratio in enumerate(pop_ratios):
self.assertAlmostEqual(pop_ratio, expected_pop_ratios[i])
def test_probtraj_p53_Mdm2_cmaboss_v2(self):
path = dirname(__file__)
sim = load(join(path, "p53_Mdm2.bnd"),
join(path, "p53_Mdm2_runcfg.cfg"),
cmaboss=True)
res = sim.run()
res_states_probtraj = pandas.read_csv(join(
path, "res", "p53_Mdm2_states_probtraj.csv"),
index_col=0,
header=0)
res_last_states_probtraj = pandas.read_csv(join(
path, "res", "p53_Mdm2_last_states_probtraj.csv"),
index_col=0,
header=0)
res_nodes_probtraj = pandas.read_csv(join(
path, "res", "p53_Mdm2_nodes_probtraj.csv"),
index_col=0,
header=0)
self.assertTrue(
numpy.isclose(
res.get_states_probtraj().sort_index(axis=1),
res_states_probtraj.sort_index(axis=1),
).all())
self.assertTrue(
numpy.isclose(
res.get_last_states_probtraj().sort_index(axis=1),
res_last_states_probtraj.sort_index(axis=1),
).all())
self.assertTrue(
numpy.isclose(
res.get_nodes_probtraj().sort_index(axis=1),
res_nodes_probtraj.sort_index(axis=1),
).all())
def main(argv):
if len(argv) < 3 or len(argv) > 6:
print(
("Bad arguments, MBSS_FormatTable.py <file.bnd> <file.cfg> "
"<(optional)threshold> <(optional)-mb MaBoSS executable name>"),
file=sys.stderr
)
exit()
bndFile = argv[1]
cfgFile = argv[2]
mabossCommand = None
probCutoff = None
if len(argv) > 3:
index = 3
while index < len(argv):
if argv[index].startswith("-mb"):
mabossCommand = argv[index+1]
index += 2
else:
probCutoff = float(argv[index])
index += 1
simulationName = os.path.splitext(os.path.basename(argv[2]))[0]
simulation = maboss.load(bndFile, cfgFile, command=mabossCommand)
result = simulation.run(command=mabossCommand, prefix=simulationName)
result.save(simulationName)
table = result.get_states_probtraj_full()
table.to_csv(os.path.join(simulationName, ("%s_probtraj_table.csv" % simulationName)), sep="\t")
result.write_statdist_table(
os.path.join(simulationName, "%s_statdist_table.csv" % simulationName),
probCutoff
)
def getMaBoSSModel(self):
if self.model.format == LogicalModel.MABOSS:
return maboss.load(
join(settings.MEDIA_ROOT, self.model.bnd_file.path),
join(settings.MEDIA_ROOT, self.model.cfg_file.path))
elif self.model.format == LogicalModel.ZGINML:
ginsim_model = ginsim.load(self.model.file.path)
return ginsim.to_maboss(ginsim_model)
elif self.model.format == LogicalModel.SBML:
t0 = time()
biolqm_model = biolqm.load(self.model.file.path)
t1 = time()
print("Loaded sbml with biolqm : %.2gs" % (t1 - t0))
maboss_model = biolqm.to_maboss(biolqm_model)
print("Converted to MaBoSS : %.2gs" % (time() - t1))
return maboss_model
else:
raise MethodNotAllowed()
def get(self, request, project_id, simulation_id):
HasMaBoSSSimulation.load(self, request, project_id, simulation_id)
model = maboss.load(self.getBNDFilePath(), self.getCFGFilePath())
if self.simulation.states_probtraj is not None:
states_probtraj = loads(self.simulation.states_probtraj)
states_lastprob = {}
for state, values in states_probtraj.items():
list_values = list(values.values())
states_lastprob.update(
{state: list_values[len(list_values) - 1]})
nodes = [
name for name, node in model.network.items()
if not node.is_internal
]
nb_nodes = len(nodes)
nb_fp = len(states_lastprob.keys())
states = []
res = np.zeros((nb_nodes, 0))
for index, proba in states_lastprob.items():
if proba > 0.01:
states.append(index)
if index == "<nil>":
res = np.append(res, np.zeros((nb_nodes, 1)), axis=1)
else:
t_res = np.zeros((nb_nodes, 1))
for node in [
t_node.strip() for t_node in index.split("--")
]:
# print(node)
t_res[nodes.index(node)] = 1
res = np.append(res, t_res, axis=1)
columns = ["FP%d" % i for i in range(res.shape[1])]
mat = np.transpose(res)
pca = PCA()
pca_res = pca.fit(mat)
x_new = pca.transform(mat)
res = {}
for i, state in enumerate(states):
res.update({state: list(x_new[i, 0:2])})
raw_arrows = np.transpose(pca_res.components_[0:2, :])
# Adjusting arrow length to fit in the graph
max_x_arrows = max(raw_arrows[:, 0])
min_x_arrows = min(raw_arrows[:, 0])
max_x_values = max(x_new[:, 0])
min_x_values = min(x_new[:, 0])
min_x_ratio = abs(min_x_values / min_x_arrows)
max_x_ratio = abs(max_x_values / max_x_arrows)
x_ratio = min(min_x_ratio, max_x_ratio)
max_y_arrows = max(raw_arrows[:, 1])
min_y_arrows = min(raw_arrows[:, 1])
max_y_values = max(x_new[:, 1])
min_y_values = min(x_new[:, 1])
min_y_ratio = abs(min_y_values / min_y_arrows)
max_y_ratio = abs(max_y_values / max_y_arrows)
y_ratio = min(min_y_ratio, max_y_ratio)
from math import log10, floor
def round_sig(x, sig=2):
if x == 0.0:
return x
return round(x, sig - int(floor(log10(abs(x)))) - 1)
values = []
names = []
for i, arrow_raw in enumerate(raw_arrows):
as_list = [round(val, 2) for val in list(arrow_raw)]
if as_list not in values:
values.append(as_list)
names.append([nodes[i]])
else:
names[values.index(as_list)].append(nodes[i])
values = [[value[0] * x_ratio, value[1] * y_ratio]
for value in values]
return Response({
'status':
'Finished',
'data':
json.dumps(res),
'arrows':
values,
'arrowlabels':
names,
'explainedVariance': [
round_sig(value * 100, 4)
for value in list(pca.explained_variance_ratio_[0:2])
]
})
else:
return Response({'status': 'Busy'})
def test_load_p53_Mdm2(self):
sim = load(join(dirname(__file__), "p53_Mdm2.bnd"),
join(dirname(__file__), "p53_Mdm2_runcfg.cfg"))
self.assertEqual(sim.network['Mdm2C'].logExp, "$case_a ? p53_h : p53")
from maboss import load, UpdatePopulation
from os.path import exists, splitext
if __name__ == "__main__":
if len(argv) < 4:
print("Usage:\n")
print("UpMaBoSS.py <file.bnd> <file.cfg> <file.upp>")
exit(1)
bnd_file = argv[1]
cfg_file = argv[2]
upp_file = argv[3]
if not exists(bnd_file):
print("Cannot find .bnd file")
exit(1)
if not exists(cfg_file):
print("Cannot find .cfg file")
exit(1)
if not exists(upp_file):
print("Cannot find .upp file")
exit(1)
workdir = splitext(cfg_file)[0]
maboss_model = load(bnd_file, cfg_file)
simulation = UpdatePopulation(maboss_model, upp_file, verbose=True)
result = simulation.run(workdir=workdir)
result.save(workdir)
def test_check_p53_Mdm2(self):
sim = load(join(dirname(__file__), "p53_Mdm2.bnd"),
join(dirname(__file__), "p53_Mdm2_runcfg.cfg"))
errors = sim.check()
self.assertEqual(len(errors), 0)
def post(self, request, project_id, model_id):
# print("Entering post function")
t0 = time()
HasModel.load(self, request, project_id, model_id)
t1 = time()
# print("Model properties loaded (%.2gs)" % (t1-t0))
if self.model.format == LogicalModel.ZGINML:
path = join(settings.MEDIA_ROOT, self.model.file.path)
ginsim_model = ginsim.load(path)
maboss_model = ginsim.to_maboss(ginsim_model)
tmp_bnd_path = join(settings.TMP_ROOT, splitext(basename(self.model.file.path))[0] + ".bnd")
bnd_file = open(tmp_bnd_path, 'w')
maboss_model.print_bnd(out=bnd_file)
bnd_file.close()
tmp_cfg_path = join(settings.TMP_ROOT, splitext(basename(self.model.file.path))[0] + ".cfg")
cfg_file = open(tmp_cfg_path, 'w')
maboss_model.print_cfg(out=cfg_file)
cfg_file.close()
maboss_simulation = MaBoSSSimulation(
project=self.project,
model=self.model,
name=request.POST['name'],
bnd_file=File(open(tmp_bnd_path, 'rb'), name=basename(tmp_bnd_path)),
cfg_file=File(open(tmp_cfg_path, 'rb'), name=basename(tmp_cfg_path)),
status=MaBoSSSimulation.BUSY
)
maboss_simulation.save()
remove(tmp_bnd_path)
remove(tmp_cfg_path)
elif self.model.format == LogicalModel.MABOSS:
bnd_path = join(settings.MEDIA_ROOT, self.model.bnd_file.path)
cfg_path = join(settings.MEDIA_ROOT, self.model.cfg_file.path)
maboss_simulation = MaBoSSSimulation(
project=self.project,
model=self.model,
name=request.POST['name'],
bnd_file=File(open(bnd_path, 'rb'), name=basename(bnd_path)),
cfg_file=File(open(cfg_path, 'rb'), name=basename(cfg_path)),
status=MaBoSSSimulation.BUSY
)
maboss_simulation.save()
maboss_model = maboss.load(bnd_path, cfg_path)
elif self.model.format == LogicalModel.SBML:
maboss_model = self.getMaBoSSModel()
tmp_bnd_path = join(settings.TMP_ROOT, splitext(basename(self.model.file.path))[0] + ".bnd")
bnd_file = open(tmp_bnd_path, 'w')
maboss_model.print_bnd(out=bnd_file)
bnd_file.close()
tmp_cfg_path = join(settings.TMP_ROOT, splitext(basename(self.model.file.path))[0] + ".cfg")
cfg_file = open(tmp_cfg_path, 'w')
maboss_model.print_cfg(out=cfg_file)
cfg_file.close()
maboss_simulation = MaBoSSSimulation(
project=self.project,
model=self.model,
name=request.POST['name'],
bnd_file=File(open(tmp_bnd_path, 'rb'), name=basename(tmp_bnd_path)),
cfg_file=File(open(tmp_cfg_path, 'rb'), name=basename(tmp_cfg_path)),
status=MaBoSSSimulation.BUSY
)
maboss_simulation.save()
remove(tmp_bnd_path)
remove(tmp_cfg_path)
else:
return HttpResponse(status=500)
# t2 = time()
# print("Model loaded (%.2gs)" % (t2-t1))
cfg_settings = loads(request.POST['settings'])
maboss_model.param.update(cfg_settings)
maboss_model.param['thread_count'] = 6
maboss_model.param['time_tick'] = float(maboss_model.param['max_time'])/100
mutations = loads(request.POST['mutations'])
for var, mutation in mutations.items():
maboss_model.mutate(var, mutation)
maboss_model.network.set_output(
[key for key, value in loads(request.POST['outputVariables']).items() if value]
)
for var, istate in parseIstates(request.POST['initialStates']).items():
maboss_model.network.set_istate(var, istate)
maboss_simulation.update_model(maboss_model)
server_host = request.POST.get('serverHost')
server_port = request.POST.get('serverPort')
thread = Thread(target=run_simulation, args=(maboss_model, maboss_simulation.id, server_host, server_port))
# t3 = time()
# print("Thread built (%.2gs)" % (t3-t2))
thread.start()
return Response({'simulation_id': maboss_simulation.id}, status=status.HTTP_200_OK)
def get(self, request, project_id, simulation_id):
HasMaBoSSSimulation.load(self, request, project_id, simulation_id)
model = maboss.load(self.getBNDFilePath(), self.getCFGFilePath())
if self.simulation.fixpoints is not None:
fixed_points = loads(self.simulation.fixpoints)
output_vars = [
label for label, node in model.network.items()
if not node.is_internal
]
nb_nodes = len(output_vars)
res = np.zeros((nb_nodes, 0))
for i, proba in enumerate(fixed_points["Proba"]):
t_res = np.zeros((nb_nodes, 1))
for node in output_vars:
t_res[output_vars.index(node)] = fixed_points[node][str(i)]
res = np.append(res, t_res, axis=1)
mat = np.transpose(res)
pca = PCA()
pca_res = pca.fit(mat)
x_new = pca.transform(mat)
res = {}
for i, state in enumerate(fixed_points["State"]):
res.update({fixed_points["State"][state]: list(x_new[i, 0:2])})
raw_arrows = np.transpose(pca_res.components_[0:2, :])
# Adjusting arrow length to fit in the graph
max_x_arrows = max(raw_arrows[:, 0])
min_x_arrows = min(raw_arrows[:, 0])
max_x_values = max(x_new[:, 0])
min_x_values = min(x_new[:, 0])
min_x_ratio = min_x_values / min_x_arrows
max_x_ratio = max_x_values / max_x_arrows
x_ratio = min(min_x_ratio, max_x_ratio)
max_y_arrows = max(raw_arrows[:, 1])
min_y_arrows = min(raw_arrows[:, 1])
max_y_values = max(x_new[:, 1])
min_y_values = min(x_new[:, 1])
min_y_ratio = min_y_values / min_y_arrows
max_y_ratio = max_y_values / max_y_arrows
y_ratio = min(min_y_ratio, max_y_ratio)
from math import log10, floor
def round_sig(x, sig=2):
if x == 0.0:
return x
return round(x, sig - int(floor(log10(abs(x)))) - 1)
values = []
names = []
for i, arrow_raw in enumerate(raw_arrows):
as_list = [round(val, 2) for val in list(arrow_raw)]
if as_list not in values:
values.append(as_list)
names.append([output_vars[i]])
else:
names[values.index(as_list)].append(output_vars[i])
values = [[value[0] * x_ratio, value[1] * y_ratio]
for value in values]
return Response({
'status':
'Finished',
'data':
json.dumps(res),
'arrows':
values,
'arrowlabels':
names,
'explainedVariance': [
round_sig(value * 100, 4)
for value in list(pca.explained_variance_ratio_[0:2])
]
})
else:
return Response({'status': 'Busy'})
