add test for firerate model, move step size test

functionalityTests.py

@@ -1,29 +1,9 @@
 
-from models.LIFAC import LIFACModel
-from stimuli.StepStimulus import StepStimulus
 import numpy as np
 import matplotlib.pyplot as plt
 import functions as fu
 
 
-def test_lifac():
-    model = LIFACModel()
-    stimulus = StepStimulus(0.5, 1, 15)
-
-    for step_size in [0.001, 0.1]:
-        model.set_variable("step_size", step_size)
-
-        v, spiketimes = model(stimulus, 2)
-
-        plt.plot(np.arange(0, 2, step_size/1000), v, label="step_size:" + str(step_size))
-
-    plt.xlabel("time in seconds")
-    plt.ylabel("Voltage")
-    plt.title("Voltage in the LIFAC-Model with different step sizes")
-    plt.show()
-    plt.close()
-
-
 def test_plot_inverses(ficurve):
     var = ficurve.boltzmann_fit_vars
 
@@ -42,3 +22,7 @@ def test_plot_inverses(ficurve):
              '.', c="red", label='inverse')
     plt.legend()
     plt.show()
+
+
+
+

tests/ModelTests.py

@@ -0,0 +1,48 @@
+
+import matplotlib.pyplot as plt
+import numpy as np
+from models.FirerateModel import FirerateModel
+from models.LIFAC import LIFACModel
+from stimuli.StepStimulus import StepStimulus
+
+
+def main():
+    # test_firerate_model()
+    test_stepsize_influence()
+
+
+def test_stepsize_influence():
+    # model = LIFACModel()
+    model = FirerateModel()
+    stimulus = StepStimulus(0.5, 1, 15)
+
+    for step_size in [0.001, 0.1]:
+        model.set_variable("step_size", step_size)
+
+        model.simulate(stimulus, 2)
+
+        # y = model.get_voltage_trace()
+        y = model.get_frequency()
+
+        plt.plot(np.arange(0, 2, step_size/1000), y, label="step_size:" + str(step_size))
+
+    plt.xlabel("time in seconds")
+    plt.ylabel("Voltage")
+    plt.title("Voltage in the LIFAC-Model with different step sizes")
+    plt.legend()
+    plt.show()
+    plt.close()
+
+
+def test_firerate_model():
+    model = FirerateModel()
+    duration = 0.2
+    stimulus = StepStimulus(duration/2, duration, 10)
+
+    model.simulate(stimulus, duration*2)
+    plt.plot(np.arange(0, duration*2, model.get_sampling_interval()/1000), model.get_frequency())
+    plt.show()
+
+
+if __name__ == '__main__':
+    main()