Source code for bmtk.analyzer.firing_rates
# Copyright 2017. Allen Institute. All rights reserved
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import pandas as pd
import numpy as np
[docs]def convert_rates(rates_file):
rates_df = pd.read_csv(rates_file, sep=' ', names=['gid', 'time', 'rate'])
rates_sorted_df = rates_df.sort_values(['gid', 'time'])
rates_dict = {}
for gid, rates in rates_sorted_df.groupby('gid'):
start = rates['time'].iloc[0]
#start = rates['rate'][0]
end = rates['time'].iloc[-1]
dt = float(end - start)/len(rates)
rates_dict[gid] = {'start': start, 'end': end, 'dt': dt, 'rates': np.array(rates['rate'])}
return rates_dict
[docs]def firing_rates_equal(rates_file1, rates_file2, err=0.0001):
trial_1 = convert_rates(rates_file1)
trial_2 = convert_rates(rates_file2)
if set(trial_1.keys()) != set(trial_2.keys()):
return False
for gid, rates_data1 in trial_1.items():
rates_data2 = trial_2[gid]
if rates_data1['dt'] != rates_data2['dt'] or rates_data1['start'] != rates_data2['start'] or rates_data1['end'] != rates_data2['end']:
return False
for r1, r2 in zip(rates_data1['rates'], rates_data2['rates']):
if abs(r1 - r2) > err:
return False
return True