calcium refactoring

examples/plot_calcium_deconvolve.py

@@ -0,0 +1,61 @@
+#!/usr/bin/env python
+"""
+Deconvolve synthetic calcium traces
+==============================
+
+This is an example of how to infer spike events
+
+"""
+
+#######################################################
+# First, we'll generate some fake data
+
+import numpy as np
+import pandas as pd
+from oasis.functions import gen_data
+
+neuron_ids = ['a', 'b', 'c']
+sampling_rate = 30.0
+
+traces, _, spikes = map(np.squeeze, gen_data(N=3, b=2, seed=0))
+
+time = np.arange(0, traces.shape[1]/sampling_rate, 1/sampling_rate)
+
+traces = pd.DataFrame(traces.T, index=time, columns=neuron_ids)
+spikes = pd.DataFrame(spikes.T, index=time, columns=neuron_ids)
+
+########################################################
+# let's plot the data
+
+import matplotlib.pyplot as plt
+traces.plot()
+plt.show()
+
+##########################################################
+# Now, we'll deconvolve the data
+
+from neuroglia.calcium import CalciumDeconvolver
+
+deconvolver = CalciumDeconvolver()
+detected_events = deconvolver.transform(traces)
+
+for neuron in neuron_ids:
+ y_true = spikes[neuron]
+ y_pred = detected_events[neuron]
+ corr = np.corrcoef(y_pred,y_true)[0,1]
+ print("{}: {:0.2f}".format(neuron,corr))
+
+detected_events.plot()
+plt.show()
+
+##########################################################
+# Now, we'll predict spikes
+
+spikes_pred = deconvolver.predict(traces)
+spikes_true = (spikes>0).astype(int)
+
+for neuron in neuron_ids:
+ y_true = spikes_true[neuron]
+ y_pred = spikes_pred[neuron]
+ corr = np.corrcoef(y_pred,y_true)[0,1]
+ print("{}: {:0.2f}".format(neuron,corr))