fix calculation of burstiness

Baseline.py

@@ -27,58 +27,15 @@ class Baseline:
     def get_coefficient_of_variation(self):
         raise NotImplementedError("NOT YET OVERRIDDEN FROM ABSTRACT CLASS")
 
-    def get_burstiness(self, test_plot=False):
-        isis = np.array(self.get_interspike_intervals()) * 1000  # change unit to ms
-
-        if len(isis) <= 10:
-            return 0
-
-        step = 0.1
-        bins = np.arange(0, max(isis), step)
-        num_spikes_per_bin = np.zeros(bins.shape)
-
-        for i, bin in enumerate(bins):
-            num_of_spikes = len((isis[(isis >= bin) & (isis < bin + step)]))
-            num_spikes_per_bin[i] = num_of_spikes
-
-        max_found = -1
-        end_of_peak = -1
-
-        if max(num_spikes_per_bin) < 10:
-            return 0
-
-        for i, num in enumerate(num_spikes_per_bin):
-            if i + 1 >= len(num_spikes_per_bin):
-                return 0
-            if max_found == -1:
-                if num_spikes_per_bin[i+1] > num:
-                    continue
-                elif num > 10:
-                    max_found = i
-            else:
-
-                if num_spikes_per_bin[i + 1] > num:
-                    end_of_peak = i + 1
-                    break
-
-        burstiness = sum(num_spikes_per_bin[:end_of_peak]) / len(isis)
-
-        if test_plot:
-            print("burst peak:", sum(num_spikes_per_bin[:end_of_peak]))
-            print("sum num per bin:", sum(num_spikes_per_bin))
-            print("len isis:", len(isis))
-            bins = np.arange(0, max(isis) * 1.01, 0.1)
+    def get_burstiness(self):
+        raise NotImplementedError("NOT YET OVERRIDDEN FROM ABSTRACT CLASS")
 
-            plt.title('Baseline ISIs - burstiness {:.2f}'.format(burstiness))
-            plt.xlabel('ISI in ms')
-            plt.ylabel('Count')
-            plt.hist(isis, bins=bins)
+    def __get_burstiness__(self, eod_freq):
+        isis = np.array(self.get_interspike_intervals())
 
-            plt.plot([step*(i+0.5) for i in range(len(num_spikes_per_bin))], num_spikes_per_bin, 'o', alpha=0.5)
-            plt.plot((0.5 * step, bins[end_of_peak - 1] + 0.5 * step,), (0, 0), 'o')
-            plt.show()
+        bursts = isis[isis < 1.5 * (1.0/eod_freq)]
 
-        return burstiness
+        return len(bursts) / float(len(isis))
 
     def get_interspike_intervals(self):
         raise NotImplementedError("NOT YET OVERRIDDEN FROM ABSTRACT CLASS")
@@ -274,6 +231,9 @@ class BaselineCellData(Baseline):
 
         return phase_list
 
+    def get_burstiness(self):
+        return self.__get_burstiness__(self.data.get_eod_frequency())
+
     def plot_baseline(self, save_path=None, position=0.5, time_length=0.2):
         # eod, v1, spiketimes, frequency
 
@@ -332,6 +292,9 @@ class BaselineModel(Baseline):
     def get_interspike_intervals(self):
         return self._get_interspike_intervals_given_data(self.spiketimes)
 
+    def get_burstiness(self):
+        return self.__get_burstiness__(self.eod_frequency)
+
     def get_spiketime_phases(self):
         sampling_interval = self.model.get_sampling_interval()