[DOC] remove single occurence from docs.py (#3834)

* bg_on_data

* rm single occurence from docs.py

nilearn/_utils/docs.py

@@ -69,7 +69,7 @@ def custom_function(vertices):
 
 # bg_on_data
 docdict['bg_on_data'] = r"""
-bg_on_data : :obj:`bool`, optional
+bg_on_data : :obj:`bool`, default=False
     If `True` and a `bg_map` is specified,
     the `surf_data` data is multiplied by the background image,
     so that e.g. sulcal depth is jointly visible with `surf_data`.
@@ -84,18 +84,6 @@ def custom_function(vertices):
 
 """
 
-# bg_vmax
-docdict['bg_vmax'] = """
-bg_vmin : :obj:`float`, optional
-    vmax for `bg_img`.
-"""
-
-# bg_vmin
-docdict['bg_vmin'] = """
-bg_vmin : :obj:`float`, optional
-    vmin for `bg_img`.
-"""
-
 # black_bg
 docdict['black_bg'] = """
 black_bg : :obj:`bool`, or "auto", optional
@@ -290,13 +278,6 @@ def custom_function(vertices):
     to indicate the cut position.
 """
 
-# ensure_finite
-docdict['ensure_finite'] = """
-ensure_finite : :obj:`bool`, optional
-    If `True`, the non-finite values (NANs and infs) found in the data
-    will be replaced by zeros.
-"""
-
 # extractor / extract_type
 docdict['extractor'] = """
 extractor : {"local_regions", "connected_components"}, default="local_regions"
@@ -368,12 +349,6 @@ def custom_function(vertices):
     Hemisphere to display.
 """
 
-# hemispheres
-docdict['hemispheres'] = """
-hemispheres : :obj:`list` of :obj:`str`, default=["left", "right"]
-    Hemispheres to display.
-"""
-
 # high_pass
 docdict['high_pass'] = """
 high_pass : :obj:`float`, default=None
@@ -471,12 +446,6 @@ def custom_function(vertices):
     Lower fraction of the histogram to be discarded.
 """
 
-# mask_img
-docdict['mask_img'] = """
-mask_img : Niimg-like object
-    Object used for masking the data.
-"""
-
 # mask_strategy
 docdict["mask_strategy"] = """
 mask_strategy : {"background", "epi", "whole-brain-template",\
@@ -594,12 +563,6 @@ def custom_function(vertices):
 docdict['n_jobs'] = n_jobs.format("1")
 docdict['n_jobs_all'] = n_jobs.format("-1")
 
-# n_parcels
-docdict['n_parcels'] = """
-n_parcels : :obj:`int`, default=50
-    Number of parcels to divide the data into.
-"""
-
 # opening
 docdict['opening'] = """
 opening : :obj:`bool` or :obj:`int`, optional

nilearn/plotting/html_surface.py

@@ -240,7 +240,6 @@ def view_img_on_surf(stat_map_img, surf_mesh='fsaverage5',
         white background. Default=False.
 
     %(bg_on_data)s
-        Default=False.
 
     %(darkness)s
         Default=1.
@@ -346,7 +345,6 @@ def view_surf(surf_mesh, surf_map=None, bg_map=None, threshold=None,
         Default=None.
 
     %(bg_on_data)s
-        Default=False.
 
     %(darkness)s
         Default=1.

nilearn/plotting/img_plotting.py

@@ -134,8 +134,13 @@ def _plot_img_with_bg(img, bg_img=None, cut_coords=None,
     ----------
     %(img)s
         Image to plot.
-    %(bg_vmin)s
-    %(bg_vmax)s
+
+    bg_vmin : :obj:`float`, optional
+        vmin for `bg_img`.
+
+    bg_vmax : :obj:`float`, optional
+        vmax for `bg_img`.
+
     interpolation : string, optional
         Passed to the add_overlay calls.
         Default='nearest'.

nilearn/plotting/surf_plotting.py

@@ -711,7 +711,6 @@ def plot_surf(surf_mesh, surf_map=None, bg_map=None,
             ``matplotlib`` engine.
 
     %(bg_on_data)s
-        Default=False.
 
     %(darkness)s
         Default=1.
@@ -1065,7 +1064,6 @@ def plot_surf_stat_map(surf_mesh, stat_map, bg_map=None,
     %(symmetric_cbar)s
         Default='auto'.
     %(bg_on_data)s
-        Default=False.
 
     %(darkness)s
         Default=1.
@@ -1291,9 +1289,9 @@ def plot_img_on_surf(stat_map, surf_mesh='fsaverage5', mask_img=None,
         If ``None``, don't apply any mask.
 
     %(bg_on_data)s
-        Default=False.
 
-    %(hemispheres)s
+    hemispheres : :obj:`list` of :obj:`str`, default=["left", "right"]
+        Hemispheres to display.
 
     inflate : bool, optional
         If True, display images in inflated brain.
@@ -1506,7 +1504,6 @@ def plot_surf_roi(surf_mesh, roi_map, bg_map=None,
             ``matplotlib`` engine.
 
     %(bg_on_data)s
-        Default=False.
 
     %(darkness)s
         Default=1.

nilearn/regions/parcellations.py

@@ -141,7 +141,10 @@ class Parcellations(_MultiPCA):
         ward and rena are the best options. Ward will give higher quality
         parcels, but with increased computation time. ReNA is most useful as a
         fast data-reduction step, typically dividing the signal size by ten.
-    %(n_parcels)s
+
+    n_parcels : :obj:`int`, default=50
+        Number of parcels to divide the data into.
+
     %(random_state)s
         Default=0.
 

nilearn/regions/rena_clustering.py

@@ -443,7 +443,9 @@ class ReNA(BaseEstimator, ClusterMixin, TransformerMixin):
 
     Parameters
     ----------
-    %(mask_img)s
+    mask_img : Niimg-like object
+        Object used for masking the data.
+
     n_clusters : :obj:`int`, optional
         The number of clusters to find. Default=2.
 

nilearn/signal.py

@@ -663,8 +663,10 @@ def clean(
 
         Default="zscore".
     %(standardize_confounds)s
-    %(ensure_finite)s
-        Default=False.
+
+    ensure_finite : :obj:`bool`, default=False
+        If `True`, the non-finite values (NANs and infs) found in the data
+        will be replaced by zeros.
 
     kwargs : dict
         Keyword arguments to be passed to functions called within ``clean``.