#!/usr/bin/env python
# coding: utf-8

# # Read Cortex Motion Analysis Corporation .trc and .forces files (example)
# 
# > [Laboratory of Biomechanics and Motor Control](http://pesquisa.ufabc.edu.br/bmclab)  
# > Federal University of ABC, Brazil

# In[1]:


import numpy as np
import pandas as pd
get_ipython().run_line_magic('matplotlib', 'inline')
import matplotlib as mpl
import matplotlib.pyplot as plt
import seaborn as sns
sns.set_style('whitegrid')
sns.set_context('notebook', font_scale=1.2, rc={"lines.linewidth": 2})
from scipy import signal
import sys, os
import pyversions  # https://pypi.org/project/pyversions/
sys.path.insert(1, r'./../functions')
import io_cortexmac as io  # from https://github.com/BMClab/BMC/tree/master/functions


# In[2]:


pyversions.versions();


# ## Use function `io_cortexmac.py` from BMClab's repo

# In[3]:


path2 = r'/mnt/B/Dropbox/BMClab/stuff/Biomecanica/2020/'


# In[4]:


fname = os.path.join(path2, 'walk_diurno.trc')
h_trc, trc = io.read_trc(fname, fname2='', units='m', dropna=False, na=0.0, df_multi=False)
trc.set_index('Time', drop=True, inplace=True)
trc.drop('Frame#', axis=1, inplace=True)


# In[5]:


fname = os.path.join(path2, 'walk_diurno.forces')
h_grf, grf = io.read_forces(fname, time=True, forcepla=[], mm2m=True, show_msg=True)


# In[6]:


trc


# In[7]:


grf


# ### trc and forces data have different sampling rates

# In[8]:


freq_trc = 1/np.mean(np.diff(trc.index))
freq_trc


# In[9]:


freq_grf = 1/np.mean(np.diff(grf.index))
freq_grf


# #### Resample trc to the force sampling rate (150 Hz to 450 Hz)

# In[10]:


# allocate variable
nrows = int(trc.shape[0]*np.round(freq_grf/freq_trc))
ncols = trc.shape[1]
data = np.nan*np.zeros((nrows, 1+ncols), dtype='float64')
# time column
data[:, 0] = np.linspace(start=0, stop=nrows/freq_grf, num=nrows, endpoint=False)
# resample data
for i in range(ncols):
     data[:, i+1] = signal.resample_poly(trc.iloc[:, i], np.round(freq_grf),
                                         np.round(freq_trc), window='blackman')
# create datafrane with new data
trc = pd.DataFrame(data=data[:, 1:], index=data[:, 0], columns=trc.columns)
trc.index.name = trc.index.name


# In[11]:


trc


# ## Plot of some data

# In[12]:


trc.columns


# In[13]:


grf.columns


# In[14]:


fig, axs = plt.subplots(2, 1, sharex = True, squeeze=True, figsize=(10, 5))
trc.plot(y=['R.Heely', 'L.Heely'], ax=axs[0], title='Data diurno')
grf.plot(y=['FY5', 'FY6'], ax=axs[1], colormap='viridis')
axs[0].set_ylabel('Position [m]')
axs[1].set_ylabel('Force [N]')
plt.show()


# This means that the subject stepped on force plate **#6** with her/his **left** foot and then stepped on force plate **#5** with her/his **right** foot.

# ## For data noturno

# In[15]:


fname = os.path.join(path2, 'walk_noturno.trc')
h_trc, trc = io.read_trc(fname, fname2='', units='m', dropna=False, na=0.0, df_multi=False)
trc.set_index('Time', drop=True, inplace=True)
trc.drop('Frame#', axis=1, inplace=True)
fname = os.path.join(path2, 'walk_noturno.forces')
h_grf, grf = io.read_forces(fname, time=True, forcepla=[], mm2m=True, show_msg=True)

freq_trc = 1/np.mean(np.diff(trc.index))
freq_grf = 1/np.mean(np.diff(grf.index))

# allocate variable
nrows = int(trc.shape[0]*np.round(freq_grf/freq_trc))
ncols = trc.shape[1]
data = np.nan*np.zeros((nrows, 1+ncols), dtype='float64')
# time column
data[:, 0] = np.linspace(start=0, stop=nrows/freq_grf, num=nrows, endpoint=False)
# resample data
for i in range(ncols):
     data[:, i+1] = signal.resample_poly(trc.iloc[:, i], np.round(freq_grf),
                                         np.round(freq_trc), window='blackman')
# create datafrane with new data
trc = pd.DataFrame(data=data[:, 1:], index=data[:, 0], columns=trc.columns)
trc.index.name = trc.index.name

fig, axs = plt.subplots(2, 1, sharex = True, squeeze=True, figsize=(10, 5))
trc.plot(y=['R.Heely', 'L.Heely'], ax=axs[0], title='Data noturno')
grf.plot(y=['FY5', 'FY6'], ax=axs[1], colormap='viridis')
axs[0].set_ylabel('Position [m]')
axs[1].set_ylabel('Force [N]')
plt.show()


# This means that the subject stepped on force plate **#6** with her/his **right** foot and then stepped on force plate **#5** with her/his **left** foot.