bugfix pattern_tools: size of vector with changed neurons was not cor…

…rect

neurodynex/hopfield_network/demo.py

@@ -123,7 +123,7 @@ def run_demo():
 
     """
     # Demo2: more neurons, more patterns, more noise
-    run_hf_demo(pattern_size=6, nr_random_patterns=5, initially_flipped_pixels=11, nr_iterations=5)
+    # run_hf_demo(pattern_size=6, nr_random_patterns=5, initially_flipped_pixels=11, nr_iterations=5)
 
     # Demo3: more parameters
     # run_hf_demo(pattern_size=4, nr_random_patterns=5,
@@ -180,5 +180,5 @@ def upd_random(state_s0, weights):
 
 
 if __name__ == '__main__':
-    # run_demo()
-    run_user_function_demo()
+    run_demo()
+    # run_user_function_demo()

neurodynex/hopfield_network/pattern_tools.py

@@ -232,7 +232,7 @@ def get_noisy_copy(template, noise_level):
     n = np.prod(template.shape)
     nr_mutations = int(round(n * noise_level))
     idx_reassignment = np.random.choice(n, nr_mutations, replace=False)
-    rand_values = np.random.binomial(1, 0.5, n)
+    rand_values = np.random.binomial(1, 0.5, nr_mutations)
     rand_values = rand_values * 2 - 1  # map {0,1} to {-1, +1}
     linear_template[idx_reassignment] = rand_values
     return linear_template.reshape(template.shape)

neurodynex/tools/spike_tools.py

@@ -31,9 +31,9 @@
 
 def get_spike_time(voltage_monitor, spike_threshold):
     """
-    Detects the spike times in the voltage. The spike time is the value in voltage_monitor.t for
-    which voltage_monitor.v[idx] is above threshold AND voltage_monitor.v[idx-1] is below threshold
-    (crossing from below).
+    Detects the spike times in the voltage. Here, the spike time is DEFINED as the value in
+    voltage_monitor.t for which voltage_monitor.v[idx] is above threshold AND
+    voltage_monitor.v[idx-1] is below threshold (crossing from below).
     Note: currently only the spike times of the first column in voltage_monitor are detected. Matrix-like
     monitors are not supported.
     Args:
@@ -57,6 +57,9 @@ def get_spike_time(voltage_monitor, spike_threshold):
 def get_spike_stats(voltage_monitor, spike_threshold):
     """
     Detects spike times and computes ISI, mean ISI and firing frequency.
+    Here, the spike time is DEFINED as the value in
+    voltage_monitor.t for which voltage_monitor.v[idx] is above threshold AND
+    voltage_monitor.v[idx-1] is below threshold (crossing from below).
     Note: meanISI and firing frequency are set to numpy.nan if less than two spikes are detected
     Note: currently only the spike times of the first column in voltage_monitor are detected. Matrix-like
     monitors are not supported.