MachineLearningGait/data_reader.py at main · ryan-w-c/MachineLearningGait · GitHub

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# Ryan Cavanagh
import os
import numpy as np
import pandas as pd
import glob

allTimestamps = []

def read_data():
    directory = os.path.join(os.path.join(os.path.join(os.path.join(os.getcwd(), '**'), '**'), '**'), '**')
    dataSetList = []
    for dir in glob.glob(directory):
        try:
            data = []
            x = dir.split(os.sep)
            data.append(x[-3] + " " + x[-2] + " " + x[-1])

            df = pd.read_csv(os.path.join(dir, "WL.CSV"), skiprows=1)
            x = np.transpose(df.iloc[:,2:4].to_numpy())
            # print(x)
            data.append(x)
            start = x[0][0]
            end = x[1][-1]
            # print(start, end)

            df = pd.read_csv(os.path.join(dir, "WR.CSV"), skiprows=1)
            x = np.transpose(df.iloc[:,2:4].to_numpy())
            # print(x)
            data.append(x)
            start = min(start, x[0][0])
            end = max(end, x[1][-1])
            # print(start, end)

            df = pd.read_csv(os.path.join(dir, "PS.CSV"), skiprows=1)
            x = np.transpose(df.iloc[:,2:14][start:end + 1].to_numpy())
            #print(np.transpose(df.iloc[:,1:2][start:end + 1].to_numpy()))
            allTimestamps.append(np.transpose(df.iloc[:,0:1][start:end + 1].to_numpy()))
            # print(x.shape)
            data.append(x)
            # print(data)
            # data.append(df.iloc[:,2:4])
            dataSetList.append(data)
        except:
            print(dir)

    print(len(dataSetList))
    # print dataset
    for e in dataSetList:
        print("\n\n" + e[0] + "\n\n")
        print("WL:\n", e[1], "\n\nWR:\n",e[2], "\n\nPS:\n", e[3])
        print(e[1].shape)
        print(e[2].shape)
        print(e[3].shape)
        print("\n\n\n")
        break

    return dataSetList

def get_timestamps(dataIndex):
    return allTimestamps[dataIndex]