[Doc] Fix ndarray-links for arguments

Author: oscargus

lib/matplotlib/category.py

@@ -43,7 +43,7 @@ def convert(value, unit, axis):
 
         Returns
         -------
-        float or ndarray[float]
+        float or `~numpy.ndarray` of float
         """
         if unit is None:
             raise ValueError(

lib/matplotlib/cm.py

@@ -437,12 +437,12 @@ def to_rgba(self, x, alpha=None, bytes=False, norm=True):
         Return a normalized rgba array corresponding to *x*.
 
         In the normal case, *x* is a 1D or 2D sequence of scalars, and
-        the corresponding ndarray of rgba values will be returned,
+        the corresponding `~numpy.ndarray` of rgba values will be returned,
         based on the norm and colormap set for this ScalarMappable.
 
         There is one special case, for handling images that are already
         rgb or rgba, such as might have been read from an image file.
-        If *x* is an ndarray with 3 dimensions,
+        If *x* is an `~numpy.ndarray` with 3 dimensions,
         and the last dimension is either 3 or 4, then it will be
         treated as an rgb or rgba array, and no mapping will be done.
         The array can be uint8, or it can be floating point with

lib/matplotlib/collections.py

@@ -953,7 +953,7 @@ def set_sizes(self, sizes, dpi=72.0):
 
         Parameters
         ----------
-        sizes : ndarray or None
+        sizes : `numpy.ndarray` or None
             The size to set for each element of the collection.  The
             value is the 'area' of the element.
         dpi : float, default: 72

lib/matplotlib/colors.py

@@ -403,8 +403,8 @@ def to_rgba_array(c, alpha=None):
     Parameters
     ----------
     c : Matplotlib color or array of colors
-        If *c* is a masked array, an ndarray is returned with a (0, 0, 0, 0)
-        row for each masked value or row in *c*.
+        If *c* is a masked array, an `~numpy.ndarray` is returned with a
+        (0, 0, 0, 0) row for each masked value or row in *c*.
 
     alpha : float or sequence of floats, optional
         If *alpha* is given, force the alpha value of the returned RGBA tuple
@@ -684,11 +684,11 @@ def __call__(self, X, alpha=None, bytes=False):
         """
         Parameters
         ----------
-        X : float or int, ndarray or scalar
+        X : float or int, `~numpy.ndarray` or scalar
             The data value(s) to convert to RGBA.
-            For floats, X should be in the interval ``[0.0, 1.0]`` to
+            For floats, *X* should be in the interval ``[0.0, 1.0]`` to
             return the RGBA values ``X*100`` percent along the Colormap line.
-            For integers, X should be in the interval ``[0, Colormap.N)`` to
+            For integers, *X* should be in the interval ``[0, Colormap.N)`` to
             return RGBA values *indexed* from the Colormap with index ``X``.
         alpha : float or array-like or None
             Alpha must be a scalar between 0 and 1, a sequence of such
@@ -2061,7 +2061,7 @@ def rgb_to_hsv(arr):
 
     Returns
     -------
-    (..., 3) ndarray
+    (..., 3) `~numpy.ndarray`
        Colors converted to HSV values in range [0, 1]
     """
     arr = np.asarray(arr)
@@ -2112,7 +2112,7 @@ def hsv_to_rgb(hsv):
 
     Returns
     -------
-    (..., 3) ndarray
+    (..., 3) `~numpy.ndarray`
        Colors converted to RGB values in range [0, 1]
     """
     hsv = np.asarray(hsv)
@@ -2279,7 +2279,7 @@ def hillshade(self, elevation, vert_exag=1, dx=1, dy=1, fraction=1.):
 
         Returns
         -------
-        ndarray
+        `~numpy.ndarray`
             A 2D array of illumination values between 0-1, where 0 is
             completely in shadow and 1 is completely illuminated.
         """
@@ -2322,7 +2322,7 @@ def shade_normals(self, normals, fraction=1.):
 
         Returns
         -------
-        ndarray
+        `~numpy.ndarray`
             A 2D array of illumination values between 0-1, where 0 is
             completely in shadow and 1 is completely illuminated.
         """
@@ -2404,7 +2404,7 @@ def shade(self, data, cmap, norm=None, blend_mode='overlay', vmin=None,
 
         Returns
         -------
-        ndarray
+        `~numpy.ndarray`
             An MxNx4 array of floats ranging between 0-1.
         """
         if vmin is None:
@@ -2465,7 +2465,7 @@ def shade_rgb(self, rgb, elevation, fraction=1., blend_mode='hsv',
 
         Returns
         -------
-        ndarray
+        `~numpy.ndarray`
             An (m, n, 3) array of floats ranging between 0-1.
         """
         # Calculate the "hillshade" intensity.
@@ -2512,9 +2512,9 @@ def blend_hsv(self, rgb, intensity, hsv_max_sat=None, hsv_max_val=None,
 
         Parameters
         ----------
-        rgb : ndarray
+        rgb : `~numpy.ndarray`
             An MxNx3 RGB array of floats ranging from 0 to 1 (color image).
-        intensity : ndarray
+        intensity : `~numpy.ndarray`
             An MxNx1 array of floats ranging from 0 to 1 (grayscale image).
         hsv_max_sat : number, default: 1
             The maximum saturation value that the *intensity* map can shift the
@@ -2531,7 +2531,7 @@ def blend_hsv(self, rgb, intensity, hsv_max_sat=None, hsv_max_val=None,
 
         Returns
         -------
-        ndarray
+        `~numpy.ndarray`
             An MxNx3 RGB array representing the combined images.
         """
         # Backward compatibility...
@@ -2574,14 +2574,14 @@ def blend_soft_light(self, rgb, intensity):
 
         Parameters
         ----------
-        rgb : ndarray
+        rgb : `~numpy.ndarray`
             An MxNx3 RGB array of floats ranging from 0 to 1 (color image).
-        intensity : ndarray
+        intensity : `~numpy.ndarray`
             An MxNx1 array of floats ranging from 0 to 1 (grayscale image).
 
         Returns
         -------
-        ndarray
+        `~numpy.ndarray`
             An MxNx3 RGB array representing the combined images.
         """
         return 2 * intensity * rgb + (1 - 2 * intensity) * rgb**2
@@ -2592,9 +2592,9 @@ def blend_overlay(self, rgb, intensity):
 
         Parameters
         ----------
-        rgb : ndarray
+        rgb : `~numpy.ndarray`
             An MxNx3 RGB array of floats ranging from 0 to 1 (color image).
-        intensity : ndarray
+        intensity : `~numpy.ndarray`
             An MxNx1 array of floats ranging from 0 to 1 (grayscale image).
 
         Returns

lib/matplotlib/dates.py

@@ -320,10 +320,10 @@ def get_epoch():
 
 def _dt64_to_ordinalf(d):
     """
-    Convert `numpy.datetime64` or an ndarray of those types to Gregorian
-    date as UTC float relative to the epoch (see `.get_epoch`).  Roundoff
-    is float64 precision.  Practically: microseconds for dates between
-    290301 BC, 294241 AD, milliseconds for larger dates
+    Convert `numpy.datetime64` or an `numpy.ndarray` of those types to
+    Gregorian date as UTC float relative to the epoch (see `.get_epoch`).
+    Roundoff is float64 precision.  Practically: microseconds for dates
+    between 290301 BC, 294241 AD, milliseconds for larger dates
     (see `numpy.datetime64`).
     """
 

lib/matplotlib/figure.py

@@ -1339,7 +1339,7 @@ def align_xlabels(self, axs=None):
         Parameters
         ----------
         axs : list of `~matplotlib.axes.Axes`
-            Optional list of (or ndarray) `~matplotlib.axes.Axes`
+            Optional list of (or `~numpy.ndarray`) `~matplotlib.axes.Axes`
             to align the xlabels.
             Default is to align all Axes on the figure.
 
@@ -1400,7 +1400,7 @@ def align_ylabels(self, axs=None):
         Parameters
         ----------
         axs : list of `~matplotlib.axes.Axes`
-            Optional list (or ndarray) of `~matplotlib.axes.Axes`
+            Optional list (or `~numpy.ndarray`) of `~matplotlib.axes.Axes`
             to align the ylabels.
             Default is to align all Axes on the figure.
 
@@ -1455,7 +1455,7 @@ def align_labels(self, axs=None):
         Parameters
         ----------
         axs : list of `~matplotlib.axes.Axes`
-            Optional list (or ndarray) of `~matplotlib.axes.Axes`
+            Optional list (or `~numpy.ndarray`) of `~matplotlib.axes.Axes`
             to align the labels.
             Default is to align all Axes on the figure.
 

lib/matplotlib/image.py

@@ -1143,8 +1143,8 @@ def set_data(self, x, y, A):
             Monotonic arrays of shapes (N,) and (M,), respectively, specifying
             pixel centers.
         A : array-like
-            (M, N) ndarray or masked array of values to be colormapped, or
-            (M, N, 3) RGB array, or (M, N, 4) RGBA array.
+            (M, N) `~numpy.ndarray` or masked array of values to be
+            colormapped, or (M, N, 3) RGB array, or (M, N, 4) RGBA array.
         """
         x = np.array(x, np.float32)
         y = np.array(y, np.float32)
@@ -1232,7 +1232,7 @@ def __init__(self, ax,
             The data to be color-coded. The interpretation depends on the
             shape:
 
-            - (M, N) ndarray or masked array: values to be colormapped
+            - (M, N) `~numpy.ndarray` or masked array: values to be colormapped
             - (M, N, 3): RGB array
             - (M, N, 4): RGBA array
 
@@ -1298,7 +1298,7 @@ def set_data(self, x, y, A):
             The data to be color-coded. The interpretation depends on the
             shape:
 
-            - (M, N) ndarray or masked array: values to be colormapped
+            - (M, N) `~numpy.ndarray` or masked array: values to be colormapped
             - (M, N, 3): RGB array
             - (M, N, 4): RGBA array
         """

lib/matplotlib/quiver.py

@@ -946,7 +946,7 @@ def _find_tails(self, mag, rounding=True, half=5, full=10, flag=50):
 
         Parameters
         ----------
-        mag : array
+        mag : `~numpy.ndarray`
             Vector magnitudes; must be non-negative (and an actual ndarray).
         rounding : bool, default: True
             Whether to round or to truncate to the nearest half-barb.

lib/matplotlib/transforms.py

@@ -755,7 +755,7 @@ def __init__(self, points, **kwargs):
         """
         Parameters
         ----------
-        points : ndarray
+        points : `~numpy.ndarray`
             A 2x2 numpy array of the form ``[[x0, y0], [x1, y1]]``.
         """
         super().__init__(**kwargs)
@@ -897,7 +897,7 @@ def update_from_data_x(self, x, ignore=None):
 
         Parameters
         ----------
-        x : ndarray
+        x : `~numpy.ndarray`
             Array of x-values.
 
         ignore : bool, optional
@@ -917,7 +917,7 @@ def update_from_data_y(self, y, ignore=None):
 
         Parameters
         ----------
-        y : ndarray
+        y : `~numpy.ndarray`
             Array of y-values.
 
         ignore : bool, optional
@@ -937,7 +937,7 @@ def update_from_data_xy(self, xy, ignore=None, updatex=True, updatey=True):
 
         Parameters
         ----------
-        xy : ndarray
+        xy : `~numpy.ndarray`
             A numpy array of 2D points.
 
         ignore : bool, optional

lib/mpl_toolkits/mplot3d/axes3d.py

@@ -2698,10 +2698,10 @@ def voxels(self, *args, facecolors=None, edgecolors=None, shade=True,
               can be either a string, or a 1D rgb/rgba array
             - ``None``, the default, to use a single color for the faces, and
               the style default for the edges.
-            - A 3D ndarray of color names, with each item the color for the
-              corresponding voxel. The size must match the voxels.
-            - A 4D ndarray of rgb/rgba data, with the components along the
-              last axis.
+            - A 3D `~numpy.ndarray` of color names, with each item the color
+              for the corresponding voxel. The size must match the voxels.
+            - A 4D `~numpy.ndarray` of rgb/rgba data, with the components
+              along the last axis.
 
         shade : bool, default: True
             Whether to shade the facecolors.