def simulate():
print "running"
#if modelscales_select.value == "No_Models":
#print modelscales_select.value
#else:
#print modelscales_select.value
print pwd
sys.path.append(pwd) # uncomment only when using executiveViz
ec = ExecutiveControl()
modelscale = models_select.value.split()[0]
modelname = models_select.value.split()[1]
chosenmodel = ec.choose_model(modelscale=modelscale,
modelname=modelname)
parameters = ast.literal_eval(runtime_input.value)
print parameters
print stimulation.value
if stimulation.value == "yes":
stimparameters = ast.literal_eval(stim_type_input.value)
stimparameters.update(
{"stimlist": ast.literal_eval(stim_list_input.value)})
ec.launch_model(parameters=parameters,
onmodel=chosenmodel,
stimparameters=stimparameters,
stimloc=stim_loc_input.value)
#with Profiler() as prof, ResourceProfiler() as rprof:
# ec.launch_model ( parameters=parameters, onmodel=chosenmodel,
# stimparameters=stimparameters, stimloc=stim_loc_input.value )
else:
ec.launch_model(parameters=parameters, onmodel=chosenmodel)
#with Profiler() as prof, ResourceProfiler() as rprof:
# ec.launch_model( parameters=parameters, onmodel=chosenmodel )
#myplot = visualize([prof, rprof])
ec.save_response()
print "done running"
def update_global_model(attr, old, new):
menu_list = new.split()
modelscale = menu_list[0] # update global modelscale
modelname = menu_list[1] # update glocal modelname
#print modelscale, modelname
sys.path.append(pwd) # uncomment only when using executiveViz
chosenmodel = ExecutiveControl.choose_model(modelscale=str(modelscale),
modelname=str(modelname))
modeltitle.text = chosenmodel.name
modeldescr.text = chosenmodel.description
modelregions.text = "Potential stimulation sites: " + str(
chosenmodel.regions)
runmodel.disabled = False
def __init__(self, model, validation_test, alpha=0.05, epsilon=5):
"""
This constructor method initializes the dictionary ``.model``,
validation test ``.validation_test``, level of significance ``.alpha``
and error limit (Epsilon) ``.epsilon``.
Default value for ``.alpha`` is set to 0.05 while value of ``.epsilon`` is set to 5.
"""
self.level_of_significance = alpha
self.epsilon = epsilon
self.modelscale = model["modelscale"]
self.modelname = model["modelname"]
self.validation_test = validation_test
from executive import ExecutiveControl as ec
self.exc = ec()
self.desired_model = ec.choose_model(modelscale=self.modelscale,
modelname=self.modelname)
class ExecutiveControlTest(unittest.TestCase):
def setUp(self):
self.ec = ExecutiveControl(
) #instance for non: static & class methods.
self.pwd = os.getcwd()
#@unittest.skip("reason for skipping")
def test_1_list_modelscales(self):
x = len(self.ec.list_modelscales()) != 0
self.assertEqual(x, True)
#@unittest.skip("reason for skipping")
def test_2_list_models(self):
dummyscale_path = self.pwd + os.sep + "models" + os.sep + "dummyscale"
for i in range(3): # create three dummymodels
os.makedirs(dummyscale_path + os.sep + "dummymodel" + str(i + 1))
self.assertEqual(len(self.ec.list_models(modelscale="dummyscale")), 3)
shutil.rmtree(dummyscale_path)
#@unittest.skip("reason for skipping")
def test_3_choose_model(self):
# NOTE: this only works if the 'minimal' script
# ~/models/cells/model2015Masoli.py exists
# 'minimal' => a class with __init__ method with
# self.modelname = "PC2015Masoli.py"
x = self.ec.choose_model(modelscale="cells",
modelname="PC2015Masoli") #"DummyTest"
self.assertEqual(x.modelname, "PC2015Masoli")
#@unittest.skip("reason for skipping")
def test_4_launch_model_NEURON_nostimulus_with_capability(self):
pickedmodel = self.ec.choose_model(modelscale="cells",
modelname="DummyTest")
parameters = {"dt": 0.01, "celsius": 30, "tstop": 100, "v_init": 65}
self.assertEqual(
self.ec.launch_model(parameters=parameters,
onmodel=pickedmodel,
capabilities={
'model': None,
'vtest': None
}), pickedmodel)
@unittest.skip("reason for skipping")
def test_5_launch_model_NEURON_nostimulus_raw(self):
pickedmodel = self.ec.choose_model(modelscale="cells",
modelname="PC2015Masoli")
parameters = {"dt": 0.1, "celsius": 30, "tstop": 10, "v_init": 65}
self.assertEqual(
self.ec.launch_model(parameters=parameters, onmodel=pickedmodel),
pickedmodel)
@unittest.skip("reason for skipping")
def test_6_save_response(self):
pickedmodel = self.ec.choose_model(modelscale="cells",
modelname="PC2015Masoli")
parameters = {"dt": 0.1, "celsius": 30, "tstop": 10, "v_init": 65}
stimparameters = {
"type": ["current", "IClamp"],
"stimlist": [{
"amp": 0.5,
"dur": 5.0,
"delay": 1.0
}, {
"amp": 1.0,
"dur": 5.0,
"delay": 0.0 + 5.0
}],
"tstop":
parameters["tstop"]
}
model = self.ec.launch_model(parameters=parameters,
onmodel=pickedmodel,
stimparameters=stimparameters,
stimloc="soma")
fullfilename = self.ec.save_response()
#
sesstime = str(self.ec.tm.nwbfile.session_start_time).replace(
" ", "_")[0:-6]
filename_shouldbe = self.ec.tm.nwbfile.session_id + "_" + sesstime.replace(
":", "-") + ".h5"
#
path = os.getcwd(
) + os.sep + "responses" + os.sep + model.modelscale + os.sep + model.modelname
shutil.rmtree(path)
#
fullname_shouldbe = path + os.sep + filename_shouldbe
#
self.assertEqual(fullfilename, fullname_shouldbe)
