Alexander/P-unit_model
2
0
Fork 0
Code Issues Pull Requests Releases Wiki Activity

add set a_zero to a baseline value before simulation

Browse Source
This commit is contained in:
a.ott 2020-07-06 14:12:11 +02:00
parent a52dc65626
commit 71115d83d0
2 changed files with 17 additions and 1 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

9
Baseline.py
View File

@ -326,6 +326,8 @@ class BaselineModel(Baseline):
super().__init__() super().__init__()
self.model = model self.model = model
self.eod_frequency = eod_frequency self.eod_frequency = eod_frequency
self.set_model_adaption_to_baseline()
self.stimulus = SinusoidalStepStimulus(eod_frequency, 0) self.stimulus = SinusoidalStepStimulus(eod_frequency, 0)
self.eod = self.stimulus.as_array(0, self.simulation_time, model.get_sampling_interval()) self.eod = self.stimulus.as_array(0, self.simulation_time, model.get_sampling_interval())
self.time = np.arange(0, self.simulation_time, model.get_sampling_interval()) self.time = np.arange(0, self.simulation_time, model.get_sampling_interval())
@ -337,6 +339,13 @@ class BaselineModel(Baseline):
self.v1_traces.append(v) self.v1_traces.append(v)
self.spiketimes.append(st) self.spiketimes.append(st)
def set_model_adaption_to_baseline(self):
stimulus = SinusoidalStepStimulus(self.eod_frequency, 0, 0, 0)
self.model.simulate_fast(stimulus, 1)
adaption = self.model.get_adaption_trace()
self.model.set_variable("a_zero", adaption[-1])
print("Baseline: model a_zero set to", adaption[-1])
def get_baseline_frequency(self): def get_baseline_frequency(self):
if self.baseline_frequency == -1: if self.baseline_frequency == -1:
self.baseline_frequency = self._get_baseline_frequency_given_data(self.spiketimes) self.baseline_frequency = self._get_baseline_frequency_given_data(self.spiketimes)

9
FiCurve.py
View File

@ -34,7 +34,6 @@ class FICurve:
self.initialize() self.initialize()
self.save_values(save_dir) self.save_values(save_dir)
def initialize(self): def initialize(self):
self.calculate_all_frequency_points() self.calculate_all_frequency_points()
self.f_inf_fit = hF.fit_clipped_line(self.stimulus_values, self.f_inf_frequencies) self.f_inf_fit = hF.fit_clipped_line(self.stimulus_values, self.f_inf_frequencies)
@ -395,8 +394,16 @@ class FICurveModel(FICurve):
self.spiketimes_array = np.zeros((len(stimulus_values), trials), dtype=list) self.spiketimes_array = np.zeros((len(stimulus_values), trials), dtype=list)
self.mean_frequency_traces = [] self.mean_frequency_traces = []
self.mean_time_traces = [] self.mean_time_traces = []
self.set_model_adaption_to_baseline()
super().__init__(stimulus_values) super().__init__(stimulus_values)
def set_model_adaption_to_baseline(self):
stimulus = SinusoidalStepStimulus(self.eod_frequency, 0, 0, 0)
self.model.simulate_fast(stimulus, 1)
adaption = self.model.get_adaption_trace()
self.model.set_variable("a_zero", adaption[-1])
print("FiCurve: model a_zero set to", adaption[-1])
def calculate_all_frequency_points(self): def calculate_all_frequency_points(self):
sampling_interval = self.model.get_sampling_interval() sampling_interval = self.model.get_sampling_interval()