PhotometryAnalysis/PreprocessingFunctions.py at main · hagikent/PhotometryAnalysis · GitHub

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# -*- coding: utf-8 -*-
"""
Created on Wed Apr 19 11:21:31 2023

@author: kenta.hagihara
"""
import os
import csv
import numpy as  np
import pylab as plt
from scipy.signal import medfilt, butter, filtfilt
from scipy.stats import linregress
from scipy.optimize import curve_fit, minimize
import glob

#Preprocessing functions

def tc_crop(tc, nFrame2cut):
    tc_cropped = tc[nFrame2cut:]
    return tc_cropped

def tc_medfilt(tc, kernelSize):
    tc_filtered = medfilt(tc, kernel_size=kernelSize)
    return tc_filtered

def tc_lowcut(tc, sampling_rate):
    b,a = butter(2, 9, btype='low', fs=sampling_rate)
    tc_filtered = filtfilt(b,a, tc)
    return tc_filtered

def tc_polyfit(tc, sampling_rate, degree):
    time_seconds = np.arange(len(tc)) /sampling_rate
    coefs = np.polyfit(time_seconds, tc, deg=degree)
    tc_poly = np.polyval(coefs, time_seconds)
    return tc_poly

def tc_slidingbase(tc, sampling_rate):
    b,a = butter(2, 0.0001, btype='low', fs=sampling_rate)
    tc_base = filtfilt(b,a, tc, padtype='even')
    return tc_base

def tc_dFF(tc, tc_base, b_percentile):
    tc_dFoF = tc/tc_base
    sort = np.sort(tc_dFoF)
    b_median = np.median(sort[0:round(len(sort) * b_percentile)])
    tc_dFoF = tc_dFoF - b_median
    return tc_dFoF

def tc_filling(tc, nFrame2cut):
    tc_filled = np.append(np.ones([nFrame2cut,1])*tc[0], tc)
    return tc_filled


#Preprocessing total function

def tc_preprocess(tc, nFrame2cut, kernelSize, sampling_rate, degree, b_percentile):
    tc_cropped = tc_crop(tc, nFrame2cut)
    tc_filtered = medfilt(tc_cropped, kernel_size=kernelSize)
    tc_filtered = tc_lowcut(tc_filtered, sampling_rate)
    tc_poly = tc_polyfit(tc_filtered, sampling_rate, degree)
    tc_estim = tc_filtered - tc_poly
    tc_base = tc_slidingbase(tc_filtered, sampling_rate)
    tc_dFoF = tc_dFF(tc_filtered, tc_base, b_percentile)
    tc_dFoF = tc_filling(tc_dFoF, nFrame2cut)
    return tc_dFoF