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R4670/PointNICE/matlab_utils.py
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matlab_utils.py
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# -*- coding: utf-8 -*-
# @Author: Theo
# @Date: 2018-03-21 18:46:09
# @Last Modified by: Theo Lemaire
# @Last Modified time: 2018-03-29 18:57:42
''' Module of utilitary functions calling MATLAB routines internally. '''
import os
import logging
import pickle
import numpy as np
import matlab.engine
from .utils import InputError
# Get package logger
logger = logging.getLogger('PointNICE')
def findPeaksMATLAB(y, mpp, mpd, mph):
''' Find peaks in a signal by calling internally the matlab "finpeaks" function.
:param y: input signal
:param mpp: minimal peak prominence (signal units)
:param mpd: minimal distance between consecutive peaks (number of indexes)
:param mph: minimal peak height (signal units)
:return: 4-tuple with indexes, values, witdths and prominences of peaks
'''
# Start MATLAB matlab_engine if not existing
if 'matlab_eng' not in globals():
global matlab_eng
logger.info('starting matlab engine')
matlab_eng = matlab.engine.start_matlab()
logger.info('matlab engine started')
_, ipeaks, widths, proms = np.array(matlab_eng.findpeaks(matlab.double(y.tolist()),
'MinPeakProminence', mpp,
'MinPeakDistance', mpd,
'MinPeakHeight', mph,
nargout=4))
return (np.array(ipeaks[0], dtype=int) - 1, np.array(widths[0]), np.array(proms[0]))
def detectSpikesMATLAB(t, y, mph, mpp, mtd):
''' Detect spikes on a signal using the MATLAB findpeaks function,
and return their indexes, width and prominence.
:param t: regular time vector (s)
:param y: signal vector (signal units)
:param mph: minimal peak height (signal units)
:param mpp: minimal peak prominence (signal units)
:param mtd: minimal distance between consecutive peaks (time difference)
:return: 3-tuple with indexes, widths and prominences of spikes
'''
dt = t[1] - t[0]
ipeaks, widthpeaks, prompeaks = findPeaksMATLAB(y, mpp, int(np.ceil(mtd / dt)), mph)
return (ipeaks, widthpeaks * dt, prompeaks)
def detectSpikesInFile(filename, mph, mpp, mtd):
if not os.path.isfile(filename):
raise InputError('File does not exist')
with open(filename, 'rb') as fh:
frame = pickle.load(fh)
df = frame['data']
t = df['t'].values
Qm = df['Qm'].values
return detectSpikesMATLAB(t, Qm, mph, mpp, mtd)
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