[DOC] Fix rendering of plots in some examples where titles or images are cut off

doc/changes/latest.rst

@@ -25,7 +25,6 @@ Fixes
 
 - Relax the :func:`~nilearn.interfaces.fmriprep.load_confounds` confounds selection on `cosine` as not all confound files contained the variables (:gh:`3816` by `Hao-Ting Wang`_).
 
-
 Enhancements
 ------------
 
@@ -42,3 +41,4 @@ Changes
 - :bdg-danger:`Deprecation` Empty region signals resulting from applying `mask_img` in :class:`~maskers.NiftiLabelsMasker` will no longer be kept in release 0.15. Meanwhile, use `keep_masked_labels` parameter when initializing the :class:`~maskers.NiftiLabelsMasker` object to enable/disable this behavior. (:gh:`3722` by `Mohammad Torabi`_).
 - :bdg-danger:`Deprecation` Empty region signals resulting from applying `mask_img` in :class:`~maskers.NiftiMapsMasker` will no longer be kept in release 0.15. Meanwhile, use `keep_masked_maps` parameter when initializing the :class:`~maskers.NiftiMapsMasker` object to enable/disable this behavior. (:gh:`3732` by `Mohammad Torabi`_).
 - Removed mention of license in "header" (:gh:`3838` by `Czarina Sy`_).
+- Configure plots in example gallery for better rendering  (:gh:`3753` by `Yasmin Mzayek`_)

examples/01_plotting/plot_demo_glass_brain_extensive.py

@@ -227,15 +227,15 @@
 
 display = plot_glass_brain(None, display_mode="lr")
 display.add_contours(stat_img, levels=[3.0], colors="r")
-display.title('"stat_img" on glass brain only "l" "r" hemispheres')
+display.title('"stat_img" on glass brain only\n"l" "r" hemispheres')
 
 
 ##############################################################################
 # Filled contours in both hemispheric plotting, by adding ``filled=True``.
 
 display = plot_glass_brain(None, display_mode="lr")
 display.add_contours(stat_img, filled=True, levels=[3.0], colors="r")
-display.title('Filled contours on glass brain only "l" "r" hemispheres')
+display.title('Filled contours on glass brain only\n"l" "r" hemispheres')
 
 
 ##############################################################################

examples/01_plotting/plot_demo_more_plotting.py

@@ -114,9 +114,11 @@
 # :class:`~nilearn.plotting.displays.YSlicer` object.
 # ``cut_coords`` is provided as an integer (1), and the coordinates are,
 # again, selected automatically.
+import matplotlib.pyplot as plt
 
 plotting.plot_stat_map(stat_img, display_mode='y', cut_coords=1,
-                       title="display_mode='y', cut_coords=1")
+                       title="display_mode='y', cut_coords=1",
+                       figure=plt.figure(figsize=(5, 4)))
 
 ###############################################################################
 # Visualizing without a colorbar on the right side
@@ -127,7 +129,8 @@
 
 plotting.plot_stat_map(stat_img, display_mode='z',
                        cut_coords=1, colorbar=False,
-                       title="display_mode='z', cut_coords=1, colorbar=False")
+                       title="display_mode='z', cut_coords=1,\ncolorbar=False",
+                       figure=plt.figure(figsize=(5, 7)))
 
 ###############################################################################
 # Visualize in - two views 'sagittal' and 'axial' with given coordinates

examples/01_plotting/plot_haxby_masks.py

@@ -64,7 +64,7 @@
 p_v = Rectangle((0, 0), 1, 1, fc="red")
 p_h = Rectangle((0, 0), 1, 1, fc="blue")
 p_f = Rectangle((0, 0), 1, 1, fc="limegreen")
-plt.legend([p_v, p_h, p_f], ["vt", "house", "face"])
+plt.legend([p_v, p_h, p_f], ["vt", "house", "face"], loc="lower right")
 
 show()
 

examples/02_decoding/plot_haxby_different_estimators.py

@@ -116,7 +116,7 @@
 # Then we make a rudimentary diagram
 import matplotlib.pyplot as plt
 
-plt.figure(figsize=(6, 6))
+plt.figure(figsize=(8, 6))
 
 all_categories = np.sort(np.hstack([categories, "AVERAGE"]))
 tick_position = np.arange(len(all_categories))
@@ -141,7 +141,7 @@
 plt.xlabel("Classification accuracy (AUC score)")
 plt.ylabel("Visual stimuli category")
 plt.xlim(xmin=0.5)
-plt.legend(loc="lower left", ncol=1)
+plt.legend(ncol=1, bbox_to_anchor=(1.3, 0.2))
 plt.title(
     "Category-specific classification accuracy for different classifiers"
 )
@@ -198,6 +198,7 @@
         cut_coords=[-15],
         threshold=threshold,
         title=f"{classifier_name.replace('_', ' ')}: face vs house",
+        figure=plt.figure(figsize=(3, 4)),
     )
 
 show()

examples/02_decoding/plot_oasis_vbm.py

@@ -219,7 +219,7 @@
 title = (
     "Negative $\\log_{10}$ p-values" "\n(Non-parametric + max-type correction)"
 )
-display.title(title, y=1.2)
+display.title(title)
 
 n_detections = (get_data(signed_neg_log_pvals_unmasked) > threshold).sum()
 print(f"\n{int(n_detections)} detections")

examples/02_decoding/plot_simulated_data.py

@@ -116,7 +116,7 @@ def plot_slices(data, title=None):
         hspace=0.05, wspace=0.05, left=0.03, right=0.97, top=0.9
     )
     if title is not None:
-        plt.suptitle(title, y=0.95)
+        plt.suptitle(title)
 
 
 ###############################################################################

examples/05_glm_second_level/plot_second_level_one_sample_test.py

@@ -107,6 +107,7 @@
     display_mode="z",
     plot_abs=False,
     title="group left-right button press (unc p<0.001)",
+    figure=plt.figure(figsize=(5, 5)),
 )
 plotting.show()
 

examples/06_manipulating_images/plot_extract_rois_statistical_maps.py

@@ -79,7 +79,7 @@
 for image, strategy in zip(images, ["percentile", "image intensity"]):
     title = (
         f"ROIs using {strategy} thresholding. "
-        "\n Each ROI in same color is an extracted region"
+        "Each ROI in same color is an extracted region"
     )
     plotting.plot_prob_atlas(
         image,

examples/07_advanced/plot_bids_analysis.py

@@ -159,5 +159,6 @@
     title="Group language network (unc p<0.001)",
     plot_abs=False,
     display_mode="x",
+    figure=plt.figure(figsize=(5, 4)),
 )
 plotting.show()

examples/07_advanced/plot_haxby_mass_univariate.py

@@ -176,7 +176,7 @@
     f"\n{n_detections} detections"
 )
 
-display.title(title, y=1.1)
+display.title(title, size=10)
 
 # Plot permutation p-values map
 display = plot_stat_map(
@@ -197,7 +197,7 @@
     f"\n{n_detections} detections"
 )
 
-display.title(title, y=1.1)
+display.title(title, size=10)
 
 show()
 

examples/07_advanced/plot_localizer_simple_analysis.py

@@ -85,6 +85,6 @@
     f"\n{(~masked_pvals.mask).sum()} detections"
 )
 
-display.title(title, y=1.1, alpha=0.8)
+display.title(title, y=1, alpha=0.8)
 
 show()