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

# This notebook is used to interactively choose the best parameters for identifying the gait landmarks in each trial.

# In[1]:


from IPython.html.widgets import interactive
from IPython.display import display
from IPython.core.pylabtools import figsize
import matplotlib.pyplot as plt
from gaitanalysis.gait import plot_gait_cycles


# In[2]:


import sys
sys.path.append('../src')


# In[3]:


import utils


# In[4]:


get_ipython().run_line_magic('matplotlib', 'inline')


# In[5]:


trial_number = '016'
event = 'Longitudinal Perturbation'


# In[6]:


trial = utils.Trial(trial_number)
# trial.remove_precomputed_data()
trial._write_event_data_frame_to_disk(event)
trial._write_inverse_dynamics_to_disk(event)


# In[7]:


gait_data = trial.gait_data_objs[event]


# In[8]:


window = 1000
last_index = len(gait_data.data) - window


# In[9]:


from gait_landmark_settings import settings
p = settings[trial_number]
p


# In[10]:


def plot_landmarks(filter_frequency=p[0], threshold=p[1], index=0):
    gait_data.grf_landmarks('FP2.ForY', 'FP1.ForY',
                               filter_frequency=filter_frequency, threshold=threshold)
    axes = gait_data.plot_landmarks(['FP2.ForY'], 'right', index=index, window=window)


# In[11]:


figsize(14, 6)


# In[12]:


w = interactive(plot_landmarks, filter_frequency=(0.0, 50.0, 1.0),
                threshold=(0.0, 70.0, 1.0), index=(0, last_index, window))
w.msg_throttle = 0
display(w)


# In[13]:


w.kwargs


# In[14]:


_ = gait_data.grf_landmarks('FP2.ForY', 'FP1.ForY',
                        filter_frequency=w.kwargs['filter_frequency'],
                        threshold=w.kwargs['threshold'])


# In[15]:


_ = gait_data.split_at('right', num_samples=20, belt_speed_column='RightBeltSpeed')


# In[16]:


cols = ['FP2.ForY',
        'FP2.MomZ',
        'Right.Ankle.PlantarFlexion.Angle',
        'Right.Ankle.PlantarFlexion.Rate',
        'Right.Ankle.PlantarFlexion.Moment']


# In[17]:


figsize(14, len(cols) * 3)


# In[18]:


axes = gait_data.plot_gait_cycles(*cols)


# In[19]:


figsize(14, 6)
axes = gait_data.gait_cycle_stats['Number of Samples'].hist(bins=50)


# In[20]:


culled_gait_cycles, culled_gait_cycle_stats = trial._remove_bad_gait_cycles(event)


# In[21]:


figsize(14, 6)
axes = culled_gait_cycle_stats['Number of Samples'].hist(bins=50)


# In[22]:


figsize(14, len(cols) * 3)


# In[23]:


axes = plot_gait_cycles(culled_gait_cycles, *cols)


# # Footer

# In[24]:


get_ipython().system('git rev-parse HEAD')


# In[25]:


get_ipython().system('git --git-dir=/home/moorepants/src/GaitAnalysisToolKit/.git --work-tree=/home/moorepants/src/GaitAnalysisToolKit rev-parse HEAD')


# In[26]:


get_ipython().run_line_magic('install_ext', 'http://raw.github.com/jrjohansson/version_information/master/version_information.py')


# In[27]:


get_ipython().run_line_magic('load_ext', 'version_information')


# In[28]:


get_ipython().run_line_magic('version_information', 'numpy, scipy, pandas, matplotlib, tables, oct2py, dtk, gaitanalysis')