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functions.py
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Fri, May 17, 05:01

functions.py
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import scipy
from scipy import signal
import numpy as np
import itertools
def LowPass(data, ChimeraSettings, lowPass):
"""
Function used to filter data with a digital Bessel filter of the 4th order.
Specially useful for high bandwidth recordings.
Parameters
----------
data :
Data to be filtered.
samplerate : float
Sampling frequency of the data aquisition.
lowPass : float
Cutoff frequency of the filter.
Returns
-------
output: a list of the currents filtered
newsamplerate : float of new sampling frequency corresponding to 2*Cutoff frequency (Nyquist-Shannon sampling theorem).
"""
samplerate = ChimeraSettings.ADCSAMPLERATE
Wn = round(2 * lowPass / samplerate, 4) # [0,1] nyquist frequency
b, a = scipy.signal.bessel(4, Wn, btype='low', analog=False) # 4-th order digital filter
z, p, k = signal.tf2zpk(b, a)
eps = 1e-9
r = np.max(np.abs(p))
approx_impulse_len = int(np.ceil(np.log(eps) / np.log(r)))
Filt_sig = (signal.filtfilt(b, a, data, method='gust', irlen=approx_impulse_len))
ds_factor = np.ceil(samplerate / (2 * lowPass))
output = {}
output = scipy.signal.resample(Filt_sig, int(len(data) / ds_factor))
output = output[100:len(output)-100]
newsamplerate = samplerate / ds_factor
return output, newsamplerate
def LowPassFast(data, ChimeraSettings, displaysubsample, lowPass):
downsampled = signal.resample(data, int(1 / displaysubsample * len(data)))
effsamplerate = (ChimeraSettings.ADCSAMPLERATE / displaysubsample)
Wn = round(2 * lowPass / effsamplerate, 4)
b, a = scipy.signal.bessel(4, Wn, btype='low', analog=False)
z, p, k = signal.tf2zpk(b, a)
eps = 1e-9
r = np.max(np.abs(p))
approx_impulse_len = int(np.ceil(np.log(eps) / np.log(r)))
output = signal.filtfilt(b, a, downsampled, method='gust', irlen=approx_impulse_len)
output = output[100:len(output) - 100]
return output, effsamplerate
def EventDetection(inputtrace, Threshold=5, DwellTime=1):
meanvalue = np.mean(inputtrace)
stdeviation = np.std(inputtrace)
limitdown = meanvalue - Threshold * stdeviation
conditiondown = inputtrace < limitdown
alldrops = [sum(1 for _ in group) for key, group in itertools.groupby(conditiondown) if key]
downdrops = [item for item in alldrops if item>DwellTime]
ndown = len(downdrops)
if ndown == 0:
ndown = False
return ndown
def MakeAllVoltagesForIV(stepV, maxV):
NumberOfElements = int((2*maxV)/stepV+2)
AllVoltages = np.zeros(NumberOfElements)
Counter = 1
for i in range(1, int(NumberOfElements)-1):
if divmod(i, 2)[1]:
AllVoltages[i] = -stepV*Counter
else:
AllVoltages[i] = stepV*Counter
Counter += 1
print('IV Voltages: {}'.format(AllVoltages))
return AllVoltages

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