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

# In[1]:


get_ipython().run_line_magic('matplotlib', 'widget')
from tvb.simulator.plot.head_plotter_3d import HeadPlotter3D


# # Display ROIs & M/EEG sensor positions
# 
# *Candidate for new tutorial on visualizing all elements of the data set*
# 
# To be sure of the accuracy of forward solution for M/EEG, it is important to verify the geometry of the sources and sensors, as well as the boundaries. Here, we plot these elements of the forward solution for TVB's default dataset.
# 
# First, we load the data

# In[2]:


hp = HeadPlotter3D()


# then, plot the different elements

# In[3]:


hp.display_source_sensor_geometry()


# _More visualizations to come:_
# 
# * volume data -> MRI acquisition -> Registration -> Coordinates transform to MNI space 
#  |
#   \-- voxel-based gray matter parcellation (obtain parcellation mask) -> AAL/anatomical template
#  
# * surfaces data (cortical, skull, skin surfaces extraction) -> FSL/BET 
# 
# * connectivity data (white matter weights, tract-lengths)   -> Diffusion Toolkit + TrackVis
# 
# * region mapping between parcellation and number of vertices in the cortical surface.
# 
# + lead-field matrices (ie, projection matrices) mapping nodes onto EEG/MEG space