def run(self):
"""
"""
logger.info("Starting %i simulations for %s parameters (%s total simulations)"\
% (self.nsimu, self.nparam, self.total_simu))
param_name = self.parameter_to_explore['name']
for param_value in self.parameter_to_explore['vector']:
name = "%s_%.2f" % (param_name, param_value)
fullpath = os.path.join(self.results_path, name)
paramtree_tmp = copy.deepcopy(self.paramtree)
paramtree_tmp.change_dic(param_name, param_value)
l = Launcher(self.results_path,
self.nsimu,
name=name,
ncore=self.ncore,
paramtree=paramtree_tmp,
measuretree=self.measuretree,
name_without_date=True)
l.run()
del paramtree_tmp
del l
gc.collect()
if self.pool_eval:
p = Process(results_path=fullpath)
p.evaluate(debug=True, run_all=True, verbose=False)
del p
gc.collect()
self.create_log()
def run(self, simu_path, pool_folder, eval_results_path):
"""
"""
nparams = len(pool_folder)
plog = self.get_param_from_log(simu_path)
nsimu = int(plog['nsimu'])
param_name = plog["parameter to explore name"]
param = self.get_param(pool_folder)
kt_plate = []
logger.info("Running processes on each pool")
for i, simudir in enumerate(sorted(pool_folder)):
logger.info(color("Running processes on pool called: %s" % os.path.split(simudir)[-1], 'BOLD'))
p = Process(results_path=simudir)
resu = p.evaluate(name="Mitotic Plate", draw=False, verbose=False)
kt_plate.append(resu)
# Configure and plot the graph
logger.info("Plotting results")
timelapse = np.arange(0, plog['duration'], plog['dt'])
plot_data = {}
plot_data['title'] = "Mitotic plate formation with %s variable" % param_name
plot_data['xaxis'] = {'data': timelapse, 'label': 'Time (second)'}
plot_data['yaxis'] = {'label': 'Dispersion measure (relative to the spindle length)', 'axis': []}
plot_data['error'] = False
plot_data['legend'] = True
# plot_data['limit_y_min'] = 0
# Draw parameters box
plot_data["params_box"] = [{'name': "Name", 'data': plog["name"]},
{'name': "Simulations number", 'data': nsimu},
]
# User matplotlib to get color gradient
cm = plt.get_cmap('gist_rainbow')
for i, resu in enumerate(kt_plate):
plot_color = cm(1. * i / nparams)
plot_data['yaxis']['axis'].append({'data': resu['dispersion'],
'color': plot_color,
'legend': "%s" % resu['params'][param_name]
})
dic_plot(plot_data, os.path.join(eval_results_path, "Mitotic_Plate_Formation.svg"))
# Now we gonna plote plate formation according to parameter explored
plot_data['yaxis'] = {'label': 'Dispersion measure (relative to the spindle length)', 'axis': []}
plot_data['xaxis'] = {'data': [], 'label': param_name}
plot_data['legend'] = False
plot_data["params_box"].append({'name': 'Infos', 'data': 'Dispersion measure is the mean to the last 30 sec before anaphase trigger'})
yaxisparam = []
xaxisparam = []
for i, resu in enumerate(kt_plate):
plot_color = cm(1. * i / nparams)
# Compute mean plate rate see on last 30 second before anaphase
start = (param['t_A'] - 30) / param['dt']
stop = (param['t_A']) / param['dt']
# Remove nan value
disp = resu['dispersion'][start:stop]
disp = disp[~np.isnan(disp)]
yaxisparam.append(disp.mean())
xaxisparam.append(resu['params'][param_name])
plot_data['xaxis']['data'] = np.array(xaxisparam)
plot_data['yaxis']['axis'].append({'data': np.array(yaxisparam),
'color': 'blue',
})
dic_plot(plot_data, os.path.join(eval_results_path, "Mitotic_Plate_Formation2.svg"))
return kt_plate
PARAMFILE = params_file
MEASUREFILE = measures_file
result_path = args.results
number_simu = args.nsimu
name = args.name
pool_eval = args.eval
only_eval = args.only_eval
ncore = 4
if name == "":
name = "%s_n%i" % (config.simu_name, number_simu)
if only_eval:
p = Process(results_path=only_eval)
resu = p.evaluate(run_all=True, debug=True)
else:
l = Launcher(result_path,
number_simu,
name=name,
ncore=ncore,
paramfile=PARAMFILE,
measurefile=MEASUREFILE)
l.run()
if pool_eval:
p = Process(results_path=l.results_path)
resu = p.evaluate(groups=evaluations, debug=True)
