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import numpy as np
import matplotlib.pyplot as plt
from scipy.signal import medfilt
import math
import gitInformation
from neo.io import NeuralynxIO
import sklearn
from scipy.interpolate import Rbf
import fastdtw
import time
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gitInformation.printInformation()
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# Session folder with all needed neuralynx files
sessionfolder = 'C:\\Users\\Dominik\\Documents\\GitRep\\kt-2015-DSPHandsOn\\MedianFilter\\Python\\08. Tests'
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NIO = NeuralynxIO(sessiondir = sessionfolder, cachedir = sessionfolder)
block = NIO.read_block()
seg = block.segments[0]
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analogsignals = {}
# Save all recorded datas in a analogsignals dictionary.
for i in range(len(seg.analogsignalarrays)):
analogsignals["analogsignal{0}".format(i)] = seg.analogsignalarrays[i]
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csc = {}
count = -1
# Extract the magnitude of each data.
for i in analogsignals:
csc["csc{0}".format(i[-1])] = analogsignals[i].magnitude
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