Traitement_tdms.py

# -*- coding: utf-8 -*-

"""
Created on Mon Oct 11 13:42:45 2021

@author: Mathis Briatte
"""

from nptdms import TdmsFile
import numpy as np
import matplotlib.pyplot as plt
import os
from scipy.signal import butter
from scipy import signal
from pathlib import Path

directory = r'C:\Users\mbriatte\Desktop\test'
directory2 = 'C:\\Users\mbriatte\Desktop\\test\\'

for fich in os.listdir(directory):
    # if os.path.isfile(directory2 + str(fich)) and fich.endswith(".tdms"):
        tdms_file = TdmsFile(directory2 + str(fich))
        group = tdms_file.groups()[0]
        data = tdms_file.as_dataframe()
        print(data.columns)
        data.columns = ['Fn', 'Ft', 'Vitesse', 'Couple', 'CapaA', 'CapaB',
                        'Top', 'TriggCamera', 'Acc']
        Comparaison = ['Fn', 'Ft', 'Vitesse', 'Couple', 'CapaA', 'CapaB',
                       'Top', 'TriggCamera', 'Acc']
        facteur = [500, 500, 413, -50, 0.1, 0.3, 1, 1, 1]

        print(data)
        # Fréquence d'acquisition
        FREQ = 25000  # A modifier
        Inc = 1 / FREQ
        
        # Select lines

        pas = 1
        
        for column in data.columns:
            i = list(data.columns).index(column)
            data[column] = data[column]*facteur[i]

        # Create time table

        TIME = np.arange(0, len(data['Fn'])) / FREQ
        
        # Plot channels

        # Create lowpass filter to calculate the continuous value for each
        # TABL column

        nyquist = FREQ / 2
        order = 3
        cutoff = 5
        b, a = butter(order, cutoff/nyquist, 'lowpass')

        for column in data.columns:
    
            # Calculate continue and variable values for each TABL column
        
            val = data[column]
            val_cont = signal.filtfilt(b, a, val)
            val_var = val - val_cont

            # Plot TABL column data
        
            plt.figure()
        
            plt.plot(TIME, data[column], label=column)
            # plt.plot(TIME, val_var, color='steelblue', label=f'{i}_var',
            #          linewidth=0.5)
            # plt.plot(TIME, val_cont,color='orangered', label=f'{i}_cont',
            #          linewidth=0.5)

            plt.title('Diagramme de ' + f'{column}', fontsize=10)            
            plt.xticks(fontsize=7.5)
            plt.yticks(fontsize=7.5)
            plt.xlabel('Temps (s)', fontsize=7.5)
            plt.ylabel(column, fontsize=7.5)
            plt.grid(color='lightgrey')
            plt.legend(loc='upper left', bbox_to_anchor=(0, 1), fontsize=7.5)
            plt.clf()
            plt.show()