Fixed spelling issues and added 15 new words to known list

Author: antonwolfy

doc/known_words.txt

@@ -30,3 +30,18 @@ th
 prepend
 eps
 whitespace
+Mersenne
+Zipf
+Weibull
+Mises
+Von
+Lomax
+multinomial
+Hypergeometric
+Polyutils
+Unary
+docstring
+Extrema
+Penrose
+Decompositions
+broadcastable

dpnp/dparray.pyx

@@ -1064,7 +1064,7 @@ cdef class dparray:
         Limitations
         -----------
         Input array is supported as :obj:`dpnp.ndarray`.
-        Input kth is supported as :obj:`int`.
+        Input `kth` is supported as :obj:`int`.
         Parameters `axis`, `kind` and `order` are supported only with default values.
 
         """

dpnp/dpnp_array.py

@@ -979,12 +979,13 @@ def partition(self, kth, axis=-1, kind="introselect", order=None):
         """
         Return a partitioned copy of an array.
 
-        Rearranges the elements in the array in such a way that the value of the
-        element in kth position is in the position it would be in a sorted array.
+        Rearranges the elements in the array in such a way that the value of
+        the element in `kth` position is in the position it would be in
+        a sorted array.
 
-        All elements smaller than the kth element are moved before this element and
-        all equal or greater are moved behind it. The ordering of the elements in
-        the two partitions is undefined.
+        All elements smaller than the `kth` element are moved before this
+        element and all equal or greater are moved behind it. The ordering
+        of the elements in the two partitions is undefined.
 
         Refer to `dpnp.partition` for full documentation.
 

dpnp/dpnp_iface_arraycreation.py

@@ -3385,7 +3385,7 @@ def vander(
         tuples of lists, and ndarrays.
     N : int, optional
         Number of columns in the output. If `N` is not specified, a square
-        array is returned (N = len(x)).
+        array is returned ``(N = len(x))``.
     increasing : bool, optional
         Order of the powers of the columns. If ``True,`` the powers increase
         from left to right, if ``False`` (the default) they are reversed.

dpnp/dpnp_iface_indexing.py

@@ -930,7 +930,8 @@ def take_along_axis(a, indices, axis):
     >>> import dpnp as np
     >>> a = np.array([[10, 30, 20], [60, 40, 50]])
 
-    We can sort either by using sort directly, or argsort and this function
+    We can sort either by using :obj:`dpnp.sort` directly, or
+    :obj:`dpnp.argsort` and this function:
 
     >>> np.sort(a, axis=1)
     array([[10, 20, 30],
@@ -958,7 +959,7 @@ def take_along_axis(a, indices, axis):
            [60]])
 
     If we want to get the max and min at the same time, we can stack the
-    indices first
+    indices first:
 
     >>> ai_min = np.argmin(a, axis=1, keepdims=True)
     >>> ai_max = np.argmax(a, axis=1, keepdims=True)

dpnp/dpnp_iface_linearalgebra.py

@@ -305,7 +305,10 @@ def inner(a, b):
 
 def kron(a, b):
     """
-    Returns the kronecker product of two arrays.
+    Kronecker product of two arrays.
+
+    Computes the Kronecker product, a composite array made of blocks of the
+    second array scaled by the first.
 
     For full documentation refer to :obj:`numpy.kron`.
 
@@ -597,7 +600,7 @@ def tensordot(a, b, axes=2):
     Returns
     -------
     out : dpnp.ndarray
-        Returns the tensordot product of `a` and `b`.
+        Returns the tensor dot product of `a` and `b`.
 
     See Also
     --------

dpnp/dpnp_iface_sorting.py

@@ -162,7 +162,7 @@ def partition(x1, kth, axis=-1, kind="introselect", order=None):
     Limitations
     -----------
     Input array is supported as :obj:`dpnp.ndarray`.
-    Input kth is supported as :obj:`int`.
+    Input `kth` is supported as :obj:`int`.
     Parameters `axis`, `kind` and `order` are supported only with default
     values.
 

dpnp/random/dpnp_iface_random.py

@@ -1626,7 +1626,7 @@ def standard_normal(size=None, device=None, usm_type="device", sycl_queue=None):
 def standard_t(df, size=None):
     """
     Draw samples from a standard Student’s t distribution with
-    df degrees of freedom.
+    `df` degrees of freedom.
 
     For full documentation refer to :obj:`numpy.random.standard_t`.