0.2.0

examples/showcase_image.py

@@ -232,7 +232,7 @@
                   nodecmap='Dark2',
                   nodecolor='yeo7networks',
                   nodealpha = 0.8,
-                  subtitle = 'Highlight a community',
+                  subtitles = 'Highlight a community',
                   highlightnodes={'yeo7networks': 'Cont'},
                   highlightlevel=0.95,
                   fig=fig, ax=ax,

netplotbrain/__version.py

@@ -1 +1 @@
-__version__ = "0.2.0-alpha7"
+__version__ = "0.2.0"

netplotbrain/plot.py

@@ -190,7 +190,7 @@ def plot(nodes=None, fig: Optional[plt.Figure] = None, ax=None, view: str = 'L',
                                         hemisphere=hemi_frame,
                                         azim=azim[fi], elev=elev[fi],
                                         **profile)
-                
+
             # Template voxels will have origin at 0,0,0
             # It is easier to scale the nodes from the image affine
             # Then to rescale the ax.voxels function

netplotbrain/plotting/plot_parcels.py

@@ -59,9 +59,9 @@ def _get_nodes_from_nii(img, nodes=None, voxsize=None, template=None):
     z_coord = []
     for r in rois:
         allcoords = np.where(imgdata == r)
-        x_coord.append(np.median(allcoords[0]))
-        y_coord.append(np.median(allcoords[1]))
-        z_coord.append(np.median(allcoords[2]))
+        x_coord.append(np.mean(allcoords[0]))
+        y_coord.append(np.mean(allcoords[1]))
+        z_coord.append(np.mean(allcoords[2]))
 
     # If nodes is None, define the dataframe
     if nodes is None:

netplotbrain/utils/coloring.py

@@ -37,7 +37,7 @@ def _highlight_nodes(nodes, nodecolor, highlightnodes, **kwargs):
     elif isinstance(highlightnodes, str):
         if highlightnodes not in nodes:
             raise ValueError('If highlightnodes is a str it must be a column in nodes')
-        highlightnodes = nodes[highlightnodes].values()
+        highlight_idx = nodes[highlightnodes].values
     else:
         highlight_idx = np.zeros(len(nodes))
         highlight_idx[highlightnodes] = 1
@@ -127,6 +127,7 @@ def _get_colorby_colors(df, colorby, datatype='node', **kwargs):
     # Get relevant kwargs
     cmap = kwargs.get(datatype + 'cmap')
     color_vminvmax = kwargs.get(datatype + 'colorvminvmax')
+    #TODO: Add flag if colours are in column
     colortype = _detect_coloring_type(df, colorby)
     cmap = cm.get_cmap(cmap)
     if colortype == 'discrete':