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 neuroglia.datasets import make_calcium_traces

data = make_calcium_traces(duration=10.0,oscillation=False)

traces = data['traces']
spikes = data['spikes']

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)

neuron_ids = traces.columns

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))

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