Automated_classification_of_stroke_deficit/scripts/analyse_GW_3D.py

import pandas as pd
import matplotlib.pyplot as plt
from scipy import signal
import numpy as np
import math
from mpl_toolkits import mplot3d
import easygui
from master_funcs import *
import dataframe_image as dfi
import dill
%matplotlib qt


patients=['PB_T2_3_1', 'PB_T2_3_2', 'PB_T2_3_3', 'PB_T2_4_2', 'PB_T2_5_1', 'PB_T2_6_1', 'PB_T2_6_2', 'PB_T3_23_1', 'PB_T3_23_3', 'PB_T3_24_1', 'PB_T3_24_2', 'PB_T3_24_3']

for z in patients:
    print(z)
    GW_3D='/home/user/owncloud/3D_videos/GW_3D/'+z+'_P3_GW_DLC_3D.csv'
    data = pd.read_csv(GW_3D, delimiter=",", skiprows=0, header=[1,2])
    coln=data.columns
    zero='grid_top_left'
    x='grid_top_right'
    y='grid_bottom_left'
    data=transform(data, zero, x, y)
    vel, acc=vel_acc(data, '3D')
    fault_reset=0
    max_s, last_s=max_step(data)
    ff=[max_s]
    for i in range(0, last_s):
        if (fault_reset==0) and ((data['forepaw_right', 'z'][i]-data[zero, 'z'][i])<0):
            print('foot fault at', i)
            ff.append(i)
            fault_reset=1
        if (fault_reset==1) and ((data['forepaw_right', 'z'][i]-data[zero, 'z'][i])>0):
            fault_reset=0
    if z=='PB_T2_3_1':
        footfault_3d=pd.DataFrame([ff], index=[z])
    else:
        footfault_3d_temp=pd.DataFrame([ff], index=[z])
        footfault_3d=footfault_3d.append(footfault_3d_temp)
        
footfault_3d.columns=['Non Foot Fault']+['Frame #']*(footfault_3d.shape[1]-1)
dfi.export(footfault_3d, '/home/user/owncloud/thesis_figures/DLC_GW_3d.png')                                                                                                                            
    


patients=['PB_T2_3_1', 'PB_T2_3_2', 'PB_T2_3_3', 'PB_T2_4_2', 'PB_T2_5_1', 'PB_T2_6_1', 'PB_T2_6_2', 'PB_T3_23_1', 'PB_T3_23_3', 'PB_T3_24_1', 'PB_T3_24_2', 'PB_T3_24_3']

for z in patients:  
    print(z)
    dill.load_session('/home/user/Documents/Master/GW_'+z+'_data.pkl') 
    pred_rfc = best_model.predict(X_test)
    det=np.where(pred_rfc)
    if z=='PB_T2_3_1':
        footfault_FI_3d=pd.DataFrame(det, index=[z])
    else:
        footfault_FI_3d_temp=pd.DataFrame(det, index=[z])
        footfault_FI_3d=footfault_FI_3d.append(footfault_FI_3d_temp)