[ENH 🔧 fixed surface vis bugs, updated cross-disorder and rtd]

docs/pages/02.whatsnew/index.rst

@@ -5,6 +5,16 @@
 What's new?
 ======================================
 
+v1.0.1 (January 11, 2021)
+------------------------------------------
+Bug fixes and improvement
+
+::
+
+    ↪ [ENH 🔧] Enhance cross-disorder module                 |  @saratheriver
+    ↪ [ENH 🔧] Fix bug in surface visualization              |  @saratheriver
+
+
 v1.0.0 (December 22, 2020)
 ------------------------------------------
 Initial release 😱

docs/pages/04.crossdisorder/index.rst

@@ -21,36 +21,81 @@ resulting in shared latent components that can be used for further analysis.
    .. code-tab:: py **Python** | meta
 
         >>> from enigmatoolbox.cross_disorder import cross_disorder_effect
+        >>> from enigmatoolbox.plotting import plot_cortical, plot_subcortical
+        >>> from enigmatoolbox.utils import parcel_to_surface
         >>> import matplotlib.pyplot as plt
 
-        >>> # Extract and visualize shared disorder effects
+        >>> # Extract shared disorder effects
         >>> components, variance, names = cross_disorder_effect()
 
-        >>> # Visualize eigenvalues in a scree plot
-        >>> fig, ax = plt.subplots(1, figsize=(7, 6))
-        >>> ax.plot(variance, lw=2, color='#A8221C', zorder=1)
-        >>> ax.scatter(range(variance.size), variance, s=78, color='#A8221C',
-        >>>            linewidth=1.5, edgecolor='w', zorder=3)
-        >>> ax.set_xlabel('Components')
-        >>> ax.set_ylabel('Eigenvalues')
-        >>> ax.spines['top'].set_visible(False)
-        >>> ax.spines['right'].set_visible(False)
+        >>> # Visualize cortical and subcortical eigenvalues in scree plots
+        >>> fig, ax = plt.subplots(1, 2, figsize=(14, 6))
+        >>> for ii, jj in enumerate(components):
+        >>>    ax[ii].plot(variance[jj], lw=2, color='#A8221C', zorder=1)
+        >>>    ax[ii].scatter(range(variance[jj].size), variance[jj], s=78, color='#A8221C',
+        >>>                   linewidth=1.5, edgecolor='w', zorder=3)
+        >>>    ax[ii].set_xlabel('Components')
 
+        >>>    if ii == 0:
+        >>>         ax[ii].set_ylabel('Cortical eigenvalues')
+        >>>    else:
+        >>>         ax[ii].set_ylabel('Subcortical eigenvalues')
+
+        >>>    ax[ii].spines['top'].set_visible(False)
+        >>>    ax[ii].spines['right'].set_visible(False)
+
+        >>> fig.tight_layout()
         >>> plt.show()
 
+        >>> # Visualize the first cortical and subcortical components on the surface brains
+        >>> plot_cortical(parcel_to_surface(components['cortex'][:, 0], 'aparc_fsa5'), color_range=(-0.5, 0.5),
+        ...               cmap='RdBu_r', color_bar=True, size=(800, 400))
+
+        >>> plot_subcortical(components['subcortex'][:, 0], color_range=(-0.5, 0.5),
+        ...                  cmap='RdBu_r', color_bar=True, size=(800, 400))
+
    .. code-tab:: matlab **Matlab** | meta
 
-        % Extract and visualize shared disorder effects
+        % Extract shared disorder effects
         [components, variance, ~, names] = cross_disorder_effect();
 
+        % Visualize cortical and subcortical eigenvalues in scree plots
+        fns  = fieldnames(components);
+
+        f = figure,
+        set(gcf,'color','w');
+        set(gcf,'units','normalized','position',[0 0 .75 0.3])
+
+        for ii = 1:numel(fieldnames(components))
+             axs = subplot(1, 2, ii); hold on
+             s = scatter(1:size(components.(fns{ii}), 2), variance.(fns{ii}), 128, [0.66 0.13 0.11], 'filled');
+             s.LineWidth = 1.5; s.MarkerEdgeColor = 'w';
+
+             plot(1:size(components.(fns{ii}), 2), variance.(fns{ii}), 'linewidth', 2, 'color', [0.66 0.13 0.11])
+             xlabel('Components')
+
+             if ii == 1
+                  ylabel('Cortical eigenvalues')
+             else
+                  ylabel('Subcortical eigenvalues')
+             end
+        end
+
+        % Visualize the first cortical and subcortical components on the surface brains
+        f = figure,
+            plot_cortical(parcel_to_surface(components.cortex(:, 1)), 'color_range', [-0.5 0.5], 'cmap', 'RdBu_r')
+
+        f = figure,
+            plot_subcortical(components.subcortex(:, 1), 'color_range', [-0.5 0.5], 'cmap', 'RdBu_r')
+
 .. image:: ./examples/example_figs/pca.png
     :align: center
 
 
 |
 
 
-Cross-correlation matrix
+Cross-correlation
 ------------------------------------------------------
 We can also explore shared and disease-specific morphometric signatures by 
 systematically cross-correlating patterns of brain structural abnormalities 
@@ -62,15 +107,42 @@ resulting in a correlation matrix
    .. code-tab:: py **Python** | meta
 
         >>> from enigmatoolbox.cross_disorder import cross_disorder_effect
+        >>> from nilearn import plotting
 
-        >>> # Extract and visualize shared disorder effects
+        >>> # Extract shared disorder effects
         >>> correlation_matrix, names = cross_disorder_effect(method='correlation')
 
+        >>> # Plot correlation matrices
+        >>> plotting.plot_matrix(correlation_matrix['cortex'], figure=(12, 8), labels=names['cortex'], vmax=1,
+        ...                      vmin=-1, cmap='RdBu_r', auto_fit=False)
+
+        >>> plotting.plot_matrix(correlation_matrix['subcortex'], figure=(12, 8), labels=names['subcortex'], vmax=1,
+        ...                      vmin=-1, cmap='RdBu_r', auto_fit=False)
+
    .. code-tab:: matlab **Matlab** | meta
 
-        % Extract and visualize shared disorder effects
+        % Extract shared disorder effects
         [~, ~, correlation_matrix, names] = cross_disorder_effect('method', 'correlation');
 
+        % Plot correlation matrices
+        f = figure('units','normalized','outerposition',[0 0 .65 1]),
+            imagesc(correlation_matrix.cortex, [-1 1])
+            axis square;
+            colormap(RdBu_r);
+            colorbar;
+            set(gca, 'YTick', 1:1:size(correlation_matrix.cortex, 1), ...
+                'YTickLabel', strrep(names.cortex, '_', ' '), 'XTick', 1:1:size(correlation_matrix.cortex, 1), ...
+                'XTickLabel', strrep(names.cortex, '_', ' '), 'XTickLabelRotation', 45)
+
+        f = figure('units','normalized','outerposition',[0 0 .65 1]),
+            imagesc(correlation_matrix.subcortex, [-1 1])
+            axis square;
+            colormap(RdBu_r);
+            colorbar;
+            set(gca, 'YTick', 1:1:size(correlation_matrix.subcortex, 1), ...
+                'YTickLabel', strrep(names.subcortex, '_', ' '), 'XTick', 1:1:size(correlation_matrix.subcortex, 1), ...
+                'XTickLabel', strrep(names.subcortex, '_', ' '), 'XTickLabelRotation', 45)  
+
 .. image:: ./examples/example_figs/ccmatrix.png
     :align: center