Alexander/P-unit_model
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better figures

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This commit is contained in:
a.ott 2020-08-19 17:16:57 +02:00
parent a8ce30d92b
commit 68e7b75768
2 changed files with 34 additions and 41 deletions
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25
Figures_Model.py
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@ -7,10 +7,11 @@ import matplotlib.pyplot as plt
import numpy as np import numpy as np
import models.smallModels as sM import models.smallModels as sM
def main(): def main():
# stimulus_development() # stimulus_development()
# model_adaption_example() model_adaption_example()
model_comparison() # model_comparison()
pass pass
@ -81,18 +82,19 @@ def model_comparison():
def stimulus_development(): def stimulus_development():
time_start = 0 time_start = -0.020
time_duration = 0.025 time_duration = 0.080
stimulus = SinusoidalStepStimulus(745, 0.2, 0.1, 0.1) stimulus = SinusoidalStepStimulus(745, 0.2, 0.1, 0.1)
step_size = 0.00005 step_size = 0.000005
stim_array = stimulus.as_array(time_start, time_duration, step_size) stim_array = stimulus.as_array(time_start, time_duration, step_size)
rectified = hF.rectify_stimulus_array(stim_array) rectified = hF.rectify_stimulus_array(stim_array)
filtered = dendritic_lowpass(rectified, 0.0014, step_size) filtered = dendritic_lowpass(rectified, 0.001, step_size)
fig, axes = plt.subplots(3, 1, figsize=(6, 6), sharex="col") fig, axes = plt.subplots(3, 1, figsize=(6, 6), sharex="col")
time = np.arange(time_start, time_duration, step_size) time = np.arange(time_start, time_start+time_duration, step_size)
axes[0].plot(time, stim_array) axes[0].plot(time, stim_array)
axes[0].set_title("stimulus") axes[0].set_title("stimulus")
@ -102,13 +104,14 @@ def stimulus_development():
axes[2].plot(time, filtered) axes[2].plot(time, filtered)
axes[2].set_title("rectified with dendritic filter") axes[2].set_title("rectified with dendritic filter")
axes[0].set_ylim((-1.05, 1.05)) axes[0].set_ylim((-1.15, 1.15))
axes[1].set_ylim((-1.05, 1.05)) axes[1].set_ylim((-1.15, 1.15))
axes[2].set_ylim((-1.15, 1.15))
for ax in axes: for ax in axes:
ax.set_ylabel("Amplitude [mV]") ax.set_ylabel("Amplitude [mV]")
axes[2].set_xlabel("Time [s]") axes[2].set_xlabel("Time [s]")
axes[0].set_xlim((time_start-0.0005, time_duration)) axes[0].set_xlim((0, 0.05))
# axes[2].set_ylim((0, 1.05)) # axes[2].set_ylim((0, 1.05))
plt.tight_layout() plt.tight_layout()
@ -162,7 +165,7 @@ def model_adaption_example():
axes[0].plot(time_part, v1[start_idx:end_idx]) axes[0].plot(time_part, v1[start_idx:end_idx])
axes[0].set_ylabel("Membrane voltage [mV]") axes[0].set_ylabel("Membrane voltage [mV]")
# axes[1].plot(time[start_idx:end_idx], adaption[start_idx:end_idx]) # axes[1].plot(time[start_idx:end_idx], adaption[start_idx:end_idx])
axes[1].plot(time_part, adaption[start_idx:end_idx]) axes[1].plot(time_part, -1*np.array(adaption[start_idx:end_idx]))
axes[1].set_ylabel("Adaption current [mV]") axes[1].set_ylabel("Adaption current [mV]")
axes[1].set_xlabel("Time [ms]") axes[1].set_xlabel("Time [ms]")
axes[1].set_xlim((start, end)) axes[1].set_xlim((start, end))

50
Figures_Stimuli.py
View File

@ -6,12 +6,14 @@ import matplotlib.pyplot as plt
def main(): def main():
plot_step_stimulus() stimuli_protocol_examples()
plot_sam_stimulus()
pass pass
def plot_step_stimulus(): def stimuli_protocol_examples():
fig, axes = plt.subplots(2, 1)
start = 0 start = 0
end = 1 end = 1
@ -19,47 +21,35 @@ def plot_step_stimulus():
time_end = 1.2 time_end = 1.2
step_size = 0.00005 step_size = 0.00005
frequency = 20 frequency = 55
contrast = 0.5 contrast = 0.5
# Sinusoidal STEP stimulus
# frequency, contrast, start_time=0, duration=np.inf, amplitude=1 # frequency, contrast, start_time=0, duration=np.inf, amplitude=1
step_stim= SinusoidalStepStimulus(frequency, contrast, start, end-start) step_stim = SinusoidalStepStimulus(frequency, contrast, start, end - start)
values = step_stim.as_array(time_start, time_end-time_start, step_size) values = step_stim.as_array(time_start, time_end - time_start, step_size)
time = np.arange(time_start, time_end, step_size) time = np.arange(time_start, time_end, step_size)
plt.plot(time, values) axes[0].plot(time, values)
plt.xlabel("Time [s]") axes[0].set_ylabel("Voltage [mV]")
plt.ylabel("Voltage [mV]")
plt.savefig("thesis/figures/sin_step_stim_example.pdf")
plt.close()
def plot_sam_stimulus():
start = 0
end = 1
time_start = -0.2
time_end = 1.2
step_size = 0.00005
contrast = 0.5 # SAM Stimulus:
mod_freq = 10 mod_freq = 10
carrier_freq = 53 step_stim = SinusAmplitudeModulationStimulus(frequency, contrast, mod_freq, start, end - start)
# carrier_frequency, contrast, modulation_frequency, start_time=0, duration=np.inf, amplitude=1
step_stim = SinusAmplitudeModulationStimulus(carrier_freq, contrast, mod_freq, start, end - start)
values = step_stim.as_array(time_start, time_end - time_start, step_size) values = step_stim.as_array(time_start, time_end - time_start, step_size)
time = np.arange(time_start, time_end, step_size) time = np.arange(time_start, time_end, step_size)
plt.plot(time, values) plt.plot(time, values)
beat_time = np.arange(start, end, step_size) beat_time = np.arange(start, end, step_size)
beat_values = np.sin(beat_time*2*np.pi*mod_freq) * contrast + 1 beat_values = np.sin(beat_time * 2 * np.pi * mod_freq) * contrast + 1
plt.plot(beat_time, beat_values) axes[1].plot(beat_time, beat_values)
axes[1].set_xlabel("Time [s]")
axes[1].set_ylabel("Voltage [mV]")
plt.xlabel("Time [s]") plt.savefig("thesis/figures/stimuliExamples.pdf")
plt.ylabel("Voltage [mV]")
# plt.show()
plt.savefig("thesis/figures/sam_stim_example.pdf")
plt.close() plt.close()