analyze_patient_data.py

import numpy as np
import matplotlib.pyplot as plt
import glob

input_path, output_path, extension = 'data/', 'output/', 'png'

files = glob.glob(input_path+'inflammation-*.csv')
files.sort()

#checks for sussy data
def detect_problems(patient_data):
    """Perform problem detection for one file for patient data"""
    if np.amax(data, axis=0) [0] == 0 and np.amax(data, axis=0) [20] == 20:
        print('sussy max')
    elif np.sum(np.amin(data, axis = 0)) == 0:
        print('sussy min')
    else:
        print('passed')

#plot mean, max, and min
def plot_graphs(filename, patient_data):
    """Plot line graph of patient inflammation data for one file"""
    #set up figs
    fig = plt.figure(figsize=(10.0, 3.0))

    #set up plots
    axes1 = fig.add_subplot(1,3,1)
    axes2 = fig.add_subplot(1,3,2)
    axes3 = fig.add_subplot(1,3,3)

    #plot the mean
    axes1.set_ylabel('average')
    axes1.plot(np.mean(patient_data, axis=0))

    #plot the max
    axes2.set_ylabel('max')
    axes2.plot(np.amax(patient_data, axis=0))

    #plot the min
    axes3.set_ylabel('min')
    axes3.plot(np.amin(patient_data, axis=0))

    fig.tight_layout()

    plt.savefig(output_path + filename [5:-3] + extension)
    plt.show()
    

for file in inflammation_files:

    #get the data
    print(file)
    data = np.loadtxt(fname=file, delimiter=',')
    
    #detect problems and create graphs
    detect_problems(data)
    plot_graphs(file, data)