44 lines
1.3 KiB
Python
44 lines
1.3 KiB
Python
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from models.LIFAC import LIFACModel
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from stimuli.StepStimulus import StepStimulus
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import numpy as np
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import matplotlib.pyplot as plt
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import functions as fu
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def test_lifac():
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model = LIFACModel()
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stimulus = StepStimulus(0.5, 1, 15)
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for step_size in [0.001, 0.1]:
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model.set_variable("step_size", step_size)
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v, spiketimes = model(stimulus, 2)
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plt.plot(np.arange(0, 2, step_size/1000), v, label="step_size:" + str(step_size))
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plt.xlabel("time in seconds")
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plt.ylabel("Voltage")
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plt.title("Voltage in the LIFAC-Model with different step sizes")
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plt.show()
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plt.close()
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def test_plot_inverses(ficurve):
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var = ficurve.boltzmann_fit_vars
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fig, ax1 = plt.subplots(1, 1, figsize=(4.5, 4.5), tight_layout=True)
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start = min(ficurve.stimulus_value)
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end = max(ficurve.stimulus_value)
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x_values = np.arange(start, end, (end-start)/5000)
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ax1.plot(x_values, [fu.full_boltzmann(x, var[0], var[1], var[2], var[3]) for x in x_values], label="fit")
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ax1.set_ylabel('freq')
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ax1.set_xlabel('stimulus')
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start = var[1]
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end = var[0]
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x_values = np.arange(start, end, (end - start) / 50)
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ax1.plot([fu.inverse_full_boltzmann(x, var[0], var[1], var[2], var[3]) for x in x_values], x_values,
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'.', c="red", label='inverse')
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plt.legend()
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plt.show() |