plot from NWB files

.travis.yml

@@ -6,9 +6,9 @@ matrix:
        env: 
           - ENV_FILE=environment_py27.yml
           - ENV_NAME=img_pipe_py2
-     - python: "3.5"
+     - python: "3.6"
        env: 
-          - ENV_FILE=environment_py35.yml
+          - ENV_FILE=environment_py36.yml
           - ENV_NAME=img_pipe_py3
 before_script:
   - "export DISPLAY=:99.0"

environment_py27.yml

@@ -59,5 +59,5 @@ dependencies:
   - traits==4.6.0
   - traitsui==5.1.0
   - wcwidth==0.1.7
+  - nwbext_ecog==0.7.2
 prefix: ~/anaconda/envs/img_pipe_py2
-

environment_py35.yml

@@ -63,4 +63,3 @@ dependencies:
   - sympy==1.1.1
   - tqdm==4.15.0
 prefix: ~/anaconda/envs/img_pipe_py3
-

environment_py36.yml

@@ -0,0 +1,121 @@
+name: img_pipe_py36
+channels:
+  - defaults
+  - conda-forge
+  - statiskit
+dependencies:
+  #- appnope=0.1.0 #=py36hf537a9a_0
+  - apptools=4.4.0=py36_1
+  - backcall=0.1.0=py36_0
+  - backports=1.0=py36_1
+  - backports.os=0.1.1=py36_0
+  - blas=1.0=mkl
+  - bzip2=1.0.6 #=h1de35cc_5
+  - ca-certificates=2019.1.23=0
+  - certifi=2019.3.9=py36_0
+  - configobj=5.0.6=py36_1
+  - curl=7.64.1 #=ha441bb4_0
+  - cython=0.29.7 #=py36h0a44026_0
+  - dbus=1.13.6 #=h90a0687_0
+  - decorator=4.4.0=py36_1
+  - envisage=4.7.1=py_0
+  - expat=2.2.6 #=h0a44026_0
+  - freetype=2.9.1 #=hb4e5f40_0
+  - future=0.17.1=py36_0
+  - gettext=0.19.8.1 #=h15daf44_3
+  - glib=2.56.2 #=hd9629dc_0
+  - hdf4=4.2.13 #=h39711bb_2
+  - hdf5=1.10.4 #=hfa1e0ec_0
+  - icu=58.2 #=h4b95b61_1
+  - importlib_metadata=0.9=py36_0
+  - intel-openmp=2019.3=199
+  - ipython=7.5.0 #=py36h39e3cac_0
+  - ipython_genutils=0.2.0 #=py36h241746c_0
+  - jedi=0.13.3=py36_0
+  - jpeg=9b #=he5867d9_2
+  - jsoncpp=1.8.4 #=h04f5b5a_0
+  - krb5=1.16.1 #=hddcf347_7
+  - libcurl=7.64.1 #=h051b688_0
+  - libcxx #=4.0.1 #=hcfea43d_1
+  - libcxxabi #=4.0.1 #=hcfea43d_1
+  - libedit=3.1.20181209 #=hb402a30_0
+  - libffi=3.2.1 #=h475c297_4
+  - libgfortran #=3.0.1 #=h93005f0_2
+  - libiconv=1.15 #=hdd342a3_7
+  - libnetcdf=4.6.1 #=hd5207e6_2
+  - libogg=1.3.2 #=h1de35cc_0
+  - libpng=1.6.37 #=ha441bb4_0
+  - libssh2=1.8.2 #=ha12b0ac_0
+  - libtheora=1.1.1 #=hb4e5f40_1
+  - libtiff=4.0.10 #=hcb84e12_2
+  - libvorbis=1.3.6 #=h1de35cc_0
+  - libxml2=2.9.9 #=hab757c2_0
+  - lz4-c=1.8.1.2 #=h1de35cc_0
+  - mkl=2019.3=199
+  - mkl_fft=1.0.12 #=py36h5e564d8_0
+  - mkl_random=1.0.2 #=py36h27c97d8_0
+  - ncurses=6.1 #=h0a44026_1
+  - numpy=1.16.3 #=py36hacdab7b_0
+  - numpy-base=1.16.3 #=py36h6575580_0
+  - openssl=1.1.1b #=h1de35cc_1
+  - parso=0.4.0=py_0
+  - path.py=12.0.1=py_0
+  - pcre=8.43 #=h0a44026_0
+  - pexpect=4.7.0=py36_0
+  - pickleshare=0.7.5=py36_0
+  - pip=19.1.1=py36_0
+  - prompt_toolkit=2.0.9=py36_0
+  - ptyprocess=0.6.0=py36_0
+  - pyface=6.0.0=py36_0
+  - pygments=2.4.0=py_0
+  - pyqt=5.9.2 #=py36h655552a_2
+  - python=3.6.8 #=haf84260_0
+  - qt=5.9.7 #=h468cd18_1
+  - readline=7.0 #=h1de35cc_5
+  - scipy=1.2.1 #=py36h1410ff5_0
+  - setuptools=41.0.1=py36_0
+  - simplegeneric=0.8.1=py36_2
+  - sip=4.19.8 #=py36h0a44026_0
+  - six=1.12.0=py36_0
+  - sqlite=3.28.0 #=ha441bb4_0
+  - tbb=2019.4 #=h04f5b5a_0
+  - tk=8.6.8 #=ha441bb4_0
+  - traitlets=4.3.2 #=py36h65bd3ce_0
+  - traits=5.1.1 #=py36h1de35cc_0
+  - traitsui=6.0.0=py36_1
+  - vtk=8.2.0 #=py36h9bafd54_200
+  - wcwidth=0.1.7 #=py36h8c6ec74_0
+  - wheel=0.33.4=py36_0
+  - xz=5.2.4 #=h1de35cc_4
+  - zipp=0.3.3=py36_1
+  - zlib=1.2.11 #=h1de35cc_3
+  - zstd=1.3.7 #=h5bba6e5_0
+  - pip:
+    - chardet==3.0.4
+    - configparser==3.7.4
+    - cycler==0.10.0
+    - h5py==2.9.0
+    - hdmf==1.0.3
+    - idna==2.8
+    - img-pipe==2019.3.15.2
+    - kiwisolver==1.1.0
+    - matplotlib==3.0.3
+    - mayavi==4.6.2
+    - mne==0.17.2
+    - mpmath==1.1.0
+    - nibabel==2.4.0
+    - nipy==0.4.2
+    - nwbext-ecog==0.7.2
+    - pandas==0.24.2
+    - pymcubes==0.0.9
+    - pynwb==1.0.2
+    - pyparsing==2.4.0
+    - python-dateutil==2.8.0
+    - pytz==2019.1
+    - pyvtk==0.5.18
+    - requests==2.22.0
+    - ruamel-yaml==0.15.96
+    - sympy==1.4
+    - tqdm==4.32.1
+    - urllib3==1.25.2
+#prefix: /anaconda3/envs/img_pipe_py36

img_pipe/plotting/__init__.py

@@ -1,3 +1,5 @@
 from .ctmr_brain_plot import *
 from .plot_brain import * 
-#from mlab_3D_to_2D import *
+#from mlab_3D_to_2D import *
+
+from .plot_from_nwb import *

img_pipe/plotting/plot_from_nwb.py

@@ -0,0 +1,196 @@
+# plot_from_nwb.py
+# author: Luiz Tauffer
+# date: 20.04.2019
+
+import matplotlib.pyplot as plt
+import mayavi
+import scipy.io
+from .ctmr_brain_plot import ctmr_gauss_plot, el_add
+from img_pipe.SupplementalFiles import FS_colorLUT as FS_colorLUT
+import numpy as np
+import os
+
+import pynwb
+import nwbext_ecog
+
+
+def plot_from_nwb(subj_file,  
+                  hem='stereo',
+                  opacity=1.0,
+                  roi = [],
+                  electrodes=False,
+                  elec_roi=[],
+                  elec_space='original',
+                  fpath_atlas=''):
+    '''
+    This function will plot the mesh structures and electrode positions 
+    contained in a NWB file.
+
+    Parameters
+    ----------
+    subj_file : str
+        subject file path
+    hem : str, optional
+        hemisphere: 'lh', 'rh' or 'stereo'. Default='stereo'
+    opacity : float, optional
+        opacity of the mesh, between 0.0 and 1.0. Default=1.0
+    roi : list, optional
+        list of ROI (dictionaries) to be highlighted. Default=[]
+    electrodes : boolean, optional
+        if True plots electrodes. Default=False
+    elec_roi : list, optional
+        list of ROI of electrodes to plot. Default=[]
+    elec_space : str, optional
+        'original' or 'warped'. Default='original'
+    fpath_atlas : string, necessary if elec_space=='warped'
+        path to atlas model file
+
+
+    Returns
+    -------
+    mesh : mayavi brain mesh
+    mlab : mayavi mlab scene
+    None : if an error occurred
+    '''
+
+    # Check for file path
+    exists = os.path.isfile(subj_file)
+    if exists:
+        io = pynwb.NWBHDF5IO(subj_file,'r')
+        nwb = io.read()
+    else:
+        print('ERROR: File or path does not exist!')
+        print('Given path to file: ', subj_file)
+        print('The standard path is given by your local Freesurfer installation',
+              '$SUBJECTS_DIR variable. If this is a wrong path, put the correct',
+              'path as an argument, e.g.:')
+        return None
+
+    # Check for Brain Atlas
+    if elec_space=='warped':
+        # Check for file path
+        exists = os.path.isfile(fpath_atlas)
+        if exists:
+            io_atlas = pynwb.NWBHDF5IO(fpath_atlas,'r')
+            nwb_atlas = io_atlas.read()
+        else:
+            print('ERROR: Could not find Brain Atlas!')
+            print('Searched path: ', fpath_atlas)
+            print('The standard path is given by your local Freesurfer installation',
+                  '$SUBJECTS_DIR variable. Please save the Atlas file in this folder')
+            return None
+
+    # Subject ID
+    subject_id = nwb.subject.subject_id
+
+    # Get mesh and plot the pial surfaces
+    if (hem=='lh') or (hem=='rh'):
+        if elec_space=='original':
+            pial_mesh = nwb.subject.cortical_surfaces.surfaces[hem+'_pial']
+        elif elec_space=='warped':
+            pial_mesh = nwb_atlas.subject.cortical_surfaces.surfaces[hem+'_pial']
+        else:
+            print('ERROR: Invalid elec_space name.')
+            return None
+        mesh, mlab = ctmr_gauss_plot(pial_mesh.faces[()], 
+                                     pial_mesh.vertices[()],
+                                     opacity=opacity,
+                                     color=(0.8, 0.8, 0.8))
+
+    elif hem=='stereo':
+        if elec_space=='original': #subject's brain mesh
+            pial_mesh_l = nwb.subject.cortical_surfaces['lh_pial']
+            pial_mesh_r = nwb.subject.cortical_surfaces['rh_pial']
+        elif elec_space=='warped': #atlas' brain mesh
+            pial_mesh_l = nwb_atlas.subject.cortical_surfaces.surfaces['lh_pial']
+            pial_mesh_r = nwb_atlas.subject.cortical_surfaces.surfaces['rh_pial']
+        else:
+            print('ERROR: Invalid elec_space name.')
+            return None
+
+        mesh, mlab = ctmr_gauss_plot(pial_mesh_l.faces[()], 
+                                     pial_mesh_l.vertices[()],  
+                                     opacity=opacity,
+                                     color=(0.8, 0.8, 0.8))
+
+        mesh, mlab = ctmr_gauss_plot(pial_mesh_r.faces[()], 
+                                     pial_mesh_r.vertices[()],  
+                                     opacity=opacity,
+                                     color=(0.8, 0.8, 0.8),
+                                     new_fig=False)
+
+    # all anatomic regions
+    anatomic_regions = list(nwb.subject.cortical_surfaces.surfaces.keys())
+
+    # Paint chosen ROI in distinguished colors
+    for ind, rg in enumerate(roi):
+        full_name = rg['name']+'_pial'
+        if full_name in anatomic_regions:
+            rg_color = rg['color']
+            rg_mesh = nwb.subject.cortical_surfaces.surfaces[full_name]
+
+            mesh, mlab = ctmr_gauss_plot(rg_mesh.faces[()], 
+                                         rg_mesh.vertices[()],  
+                                         new_fig=False,
+                                         color=rg_color)
+        else:
+            print(full_name,' not present in the provided data file!')
+            print('Check list of available parcellated areas with:')
+            print('  list(nwb.subject.cortical_surfaces.surfaces.keys())')
+
+
+
+    # Plot electrodes
+    if electrodes:
+        # Electrodes positions
+        if elec_space=='original':
+            x_pos = nwb.electrodes['x'][:]
+            y_pos = nwb.electrodes['y'][:]
+            z_pos = nwb.electrodes['z'][:]
+            elec_pos = np.zeros((x_pos.shape[0],3)) 
+            elec_pos[:,0] = x_pos
+            elec_pos[:,1] = y_pos
+            elec_pos[:,2] = z_pos
+        elif elec_space=='warped':
+            x_pos = nwb.electrodes['x_warped'][:]
+            y_pos = nwb.electrodes['y_warped'][:]
+            z_pos = nwb.electrodes['z_warped'][:]
+            elec_pos = np.zeros((x_pos.shape[0],3)) 
+            elec_pos[:,0] = x_pos
+            elec_pos[:,1] = y_pos
+            elec_pos[:,2] = z_pos
+
+        region = nwb.electrodes.columns[4][:]
+
+        # Import freesurfer color lookup table as a dictionary
+        cmap = FS_colorLUT.get_lut()
+
+        # Make a list of electrode numbers
+        elec_numbers = np.arange(x_pos.shape[0])+1
+
+        # Find all the unique brain areas in this subject
+        region = nwb.electrodes.columns[4][:]
+        all_regions = list(set(region))
+
+        # If no ROIs were chosen for electrodes
+        if len(elec_roi)==0:
+            elec_roi = all_regions
+
+        # Loop through electrodes and plot them in each brain area
+        for ind, pos in enumerate(elec_pos):
+            b = region[ind]
+            if b[0:3]!='ctx' and b[0:4] != 'Left' and b[0:5] != 'Right' and b[0:5] != 'Brain' and b != 'Unknown':
+                if x_pos[ind]<0: #left side
+                    this_label = 'ctx-lh-%s'%(b)
+                else:           #right side
+                    this_label = 'ctx-rh-%s'%(b)
+
+            if (this_label != '') and (b in elec_roi):
+                try:    #check if 'this_label' exists within cmap
+                    el_color = np.array(cmap[this_label])/255.
+                    el_add(np.atleast_2d(pos), color=tuple(el_color))
+                except:
+                    el_add(np.atleast_2d(pos))
+
+    mlab.show()
+    return mesh, mlab

setup.py

@@ -17,7 +17,7 @@ def run(self):
 	  packages = find_packages(),
 	  include_package_data = True,
 	  setup_requires=['cython','numpy','scipy'],
-	  install_requires=['numpy','scipy','pyvtk','mayavi','pymcubes','mne','nibabel','nipy','matplotlib<2.0.0','configparser','tqdm'],
+	  install_requires=['numpy','scipy','pyvtk','mayavi','pymcubes','mne','nibabel','nipy','matplotlib','configparser','tqdm'],
 	  dependency_links=['http://www.vtk.org/files/release/6.3/VTK-6.3.0.tar.gz','https://downloads.sourceforge.net/project/pyqt/PyQt4/PyQt-4.12/PyQt4_gpl_mac-4.12.tar.gz?r=&ts=1487961590&use_mirror=superb-sea2'],
 	  cmdclass={'install':MyInstall},
 	  classifiers = [