这个是我做设计的老师给我的代码，我们的课题是对心电图进行分析，老师给了三个代码，但是第一个代码的输入有点问题，本人又是个新手小白不知道怎么改，求求大神帮我看看！
import cmath
from abc import ABC, abstractmethod
import numpy as np
import scipy.integrate as integrate
import scipy.interpolate as interpolate
import scipy.signal as signal
class Analysis(ABC):
def __init__(self, type, leads):
self.type = type
self.leads = leads
@abstractmethod
def analyse(self):
pass
# Auto-Correlation Cross-Correlation Integral Squared
class ACIS(Analysis):
def analyse(self):
matrix = []
for i in range(0, len(self.leads)):
for j in range(0, len(self.leads)):
if list(np.zeros(len(self.leads[i])))==self.leads[i] or list(np.zeros(len(self.leads[j])))==self.leads[j]:
matrix.append(0)
continue
correlation = correlationFunction(self.leads[i], self.leads[j])
square = np.square(correlation)
integral = integrate.simps(square)
division = np.divide(integral, 1000000)
if (np.math.isnan(division)):
matrix.append(0)
else:
matrix.append(division)
return matrix
def correlationFunction(list1, list2):
x = list1[:]
y = list2[:]
# correlation(x,y)/sqrt(x^2 * y^2)
correlation = np.correlate(x, y, mode='full')[len(x)-1:]
return np.divide(correlation, np.sqrt(np.multiply(np.var(x), np.var(y))))
class CorrelationFourierTransform(Analysis):
def analyse(self):
matrixfttReal = []
matrixftReal = []
matrixfttImm = []
matrixftImm = []
matrixAmplitude = []
matrixAmplitudePeaks = []
for i in range(0, len(self.leads)):
# print(str(i+1) + "/"+str(len(self.leads)))
for j in range(0, len(self.leads)):
if list(np.zeros(len(self.leads[i])))==self.leads[i] or list(np.zeros(len(self.leads[j])))==self.leads[j]:
matrixfttReal.append(0)
matrixftReal.append(0)
matrixfttImm.append(0)
matrixftImm.append(0)
matrixAmplitude.append(0)
matrixAmplitudePeaks.append(0)
continue
correlation = correlationFunction(self.leads[i], self.leads[j])
x = np.linspace(1/500, 10, len(correlation))
newX, newY = FT.splineFunctionDescaling(x, correlation)
frequency = np.logspace(-2, 2, 100)
g1, g2 = FT.doFourier(newX, newY, frequency)
amplitude = np.sqrt(np.add(np.square(np.real(g1)), np.square(np.imag(g1))))
integralfttReal = integrate.simps(x=frequency, y=np.abs(np.real(g2)))
integralfttImmaginary = integrate.simps(x=frequency, y=np.abs(np.imag(g2)))
integralftReal = integrate.simps(x=frequency, y=np.abs(np.real(g1)))
integralftImmaginary = integrate.simps(x=frequency, y=np.abs(np.imag(g1)))
integralAmplitude = integrate.simps(x=frequency, y=amplitude)
peakSum = 0
for index in signal.find_peaks(amplitude, threshold=0.05)[0]:
peakSum += np.multiply(amplitude[index], frequency[index])
matrixfttReal.append(integralfttReal)
matrixfttImm.append(integralfttImmaginary)
matrixftReal.append(integralftReal)
matrixftImm.append(integralftImmaginary)
matrixAmplitude.append(integralAmplitude)
matrixAmplitudePeaks.append(peakSum)
return (matrixfttReal, matrixfttImm, matrixftReal, matrixftImm, matrixAmplitude,matrixAmplitudePeaks)
class FT:
j = complex(0, 1)
i = complex(1, 1)
@staticmethod
def ftt(g, g_infinte, w, t, N):
result = 0
result = FT.ft(g, g_infinte, w, t, N)*FT.j*w
return result
@staticmethod
def ft(g, g_infinte,w,t,N):
result = 0
temp = FT.j * w * g[0] + (1 - cmath.exp(-FT.j * w * t[1]))\
* ((g[1] - g[0]) / t[1]) + g_infinte * cmath.exp(-FT.j * w * t[N - 1])
for k in range(2, N):
result = result + ((g[k] - g[k - 1]) / (t[k] - t[k - 1])) * \
(cmath.exp(-FT.j * w * t[k - 1]) - cmath.exp(-FT.j * w * t[k]))
result = (result + temp) / (-(w) * (w))
return result
@staticmethod
def splineFunctionDescaling(x, y):
spline = interpolate.CubicSpline(x, y)
splineX = np.logspace(np.log10(x[1]), np.log10(x[-1]), int(len(x) / 4))
newY = []
for x in splineX:
newY.append(spline(x))
return (splineX, newY)
@staticmethod
def doFourier(x, y, frequency):
timePoints = len(x)
timeSpace = x
g_infinite = 0
g1 = np.zeros(len(frequency)) * FT.i
g2 = np.zeros(len(frequency)) * FT.i
for a in range(len(frequency)):
g1[a] = FT.ft(y, g_infinite, frequency[a], timeSpace, timePoints)
g2[a] = FT.ftt(y, g_infinite, frequency[a], timeSpace, timePoints)
return g1, g2过程结果不重要 主要是输入这边的代码，我下载的数据无法输入我也不知道他的输入是什么意思，求大佬指点啊！！！
老师给了一些数据，格式是asc的
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