BBBW Road Test Data Analysis

RoadTestAnalysis.py

# -*- coding: utf-8 -*-
"""
Spyder Editor

"""

import matplotlib.pyplot as plt
import csv
import numpy as np
from scipy import stats

def fftSmooth(data):
    a = np.fft.rfft(data)
    a[20:] = 0
    b = np.fft.irfft(a)
    return b

def deriv(data):
    der = []
    for i in range(len(data) -3):
        der.append(float(data[i+3]) - float(data[i]))
    return der

def diff(data1, data2):
    dif = []
    for i in range(len(data1)):
        dif.append(float(data1[i]) - float(data2[i]))
    return dif

def reg(data):
    x = []
    for i in range(len(data)):
        x.append(i * 5)
    ret = []
    for i in range(len(data) - 10):
        slope, intercept, r_value, p_value, std_err = stats.linregress(x[i:i+10],data[i:i+10])
        ret.append(slope)
    return ret
        
def crunch(path):
    f = open(path)
    reader = csv.reader(f)
    
    inTemp = []
    outTemp = []
    inRelH = []
    outRelH = []
    inAbsH = []
    outAbsH = []
    
    for i in reader:
        inTemp.append(float(i[2]))
        outTemp.append(float(i[3]))
        inRelH.append(float(i[4]))
        outRelH.append(float(i[5]))
        inAbsH.append(float(i[6]))
        outAbsH.append(float(i[7]))
        
    a = fftSmooth(inTemp)
    b = fftSmooth(outTemp)
    c = fftSmooth(inRelH)
    d = fftSmooth(outRelH)
    e = fftSmooth(inAbsH)
    f = fftSmooth(outAbsH)
    
    plt.plot(inTemp)
    plt.plot(outTemp)
    plt.show()
    plt.plot(inRelH)
    plt.plot(outRelH)
    plt.show()
    plt.plot(inAbsH)
    plt.plot(outAbsH)
    plt.show()
    
    smoothIn = inTemp
    smoothOut = outTemp
    der = deriv(smoothIn)
    dif = diff(smoothIn, smoothOut)
   
    x = []
    y = []
    for i in range(len(der)):
        if dif[i] > 0:
            x.append(dif[i])
            y.append(der[i])
    
    slope, intercept, r_value, p_value, std_err = stats.linregress(x, y)
    x1 = []
    y1 = []
    for i in range(len(x)):
        x1.append(x[i])
        y1.append(x[i] * slope + intercept)
    '''
    plt.plot(x, y)
    #plt.plot(x1, y1)
    #print(slope, r_value)
    plt.show()
    '''
    #print(slope, r_value)
    '''
    plt.plot(a)
    plt.plot(b)
    #slopeT, interceptT, r_valueT, p_valueT, std_errT = stats.linregress(a, b)
    plt.show()
    plt.plot(c)
    plt.plot(d)
    #slopeRH, interceptRH, r_valueRH, p_valueRH, std_errRH = stats.linregress(c, d)
    plt.show()
    
    plt.plot(e)
    plt.plot(f)
    #slopeAH, interceptAH, r_valueAH, p_valueAH, std_errAH = stats.linregress(e, f)
    plt.show()
    #print(slopeT, slopeRH, slopeAH)
    '''
    efDiff = diff(e, f)
    avDiff = np.average(efDiff)
    print(avDiff)
    
print('Window closed')
print('Slope', 'R squared')
crunch('c:/Users/rcrei/Desktop/data_15.csv')
crunch('c:/Users/rcrei/Desktop/data_09.csv')
crunch('c:/Users/rcrei/Desktop/data_08.csv')
print()
print('Window open')
print('Slope', 'R squared')
crunch('c:/Users/rcrei/Desktop/data_20.csv')
crunch('c:/Users/rcrei/Desktop/data_19.csv')
crunch('c:/Users/rcrei/Desktop/data_17.csv')