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90+ < h1 > Source code for dpnp.dpnp_iface_counting</ h1 > < div class ="highlight "> < pre >
91+ < span > </ span > < span class ="c1 "> # -*- coding: utf-8 -*-</ span >
92+ < span class ="c1 "> # *****************************************************************************</ span >
93+ < span class ="c1 "> # Copyright (c) 2016-2024, Intel Corporation</ span >
94+ < span class ="c1 "> # All rights reserved.</ span >
95+ < span class ="c1 "> #</ span >
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99+ < span class ="c1 "> # this list of conditions and the following disclaimer.</ span >
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102+ < span class ="c1 "> # and/or other materials provided with the distribution.</ span >
103+ < span class ="c1 "> #</ span >
104+ < span class ="c1 "> # THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"</ span >
105+ < span class ="c1 "> # AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE</ span >
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116+
117+ < span class ="sd "> """</ span >
118+ < span class ="sd "> Interface of the counting function of the dpnp</ span >
119+
120+ < span class ="sd "> Notes</ span >
121+ < span class ="sd "> -----</ span >
122+ < span class ="sd "> This module is a face or public interface file for the library</ span >
123+ < span class ="sd "> it contains:</ span >
124+ < span class ="sd "> - Interface functions</ span >
125+ < span class ="sd "> - documentation for the functions</ span >
126+ < span class ="sd "> - The functions parameters check</ span >
127+
128+ < span class ="sd "> """</ span >
129+
130+ < span class ="kn "> import</ span > < span class ="nn "> dpnp</ span >
131+
132+ < span class ="n "> __all__</ span > < span class ="o "> =</ span > < span class ="p "> [</ span > < span class ="s2 "> "count_nonzero"</ span > < span class ="p "> ]</ span >
133+
134+
135+ < div class ="viewcode-block " id ="count_nonzero ">
136+ < a class ="viewcode-back " href ="../../reference/generated/dpnp.count_nonzero.html#dpnp.count_nonzero "> [docs]</ a >
137+ < span class ="k "> def</ span > < span class ="nf "> count_nonzero</ span > < span class ="p "> (</ span > < span class ="n "> a</ span > < span class ="p "> ,</ span > < span class ="n "> axis</ span > < span class ="o "> =</ span > < span class ="kc "> None</ span > < span class ="p "> ,</ span > < span class ="o "> *</ span > < span class ="p "> ,</ span > < span class ="n "> keepdims</ span > < span class ="o "> =</ span > < span class ="kc "> False</ span > < span class ="p "> ):</ span >
138+ < span class ="w "> </ span > < span class ="sd "> """</ span >
139+ < span class ="sd "> Counts the number of non-zero values in the array `a`.</ span >
140+
141+ < span class ="sd "> For full documentation refer to :obj:`numpy.count_nonzero`.</ span >
142+
143+ < span class ="sd "> Returns</ span >
144+ < span class ="sd "> -------</ span >
145+ < span class ="sd "> out : dpnp.ndarray</ span >
146+ < span class ="sd "> Number of non-zero values in the array along a given axis.</ span >
147+ < span class ="sd "> Otherwise, a zero-dimensional array with the total number of</ span >
148+ < span class ="sd "> non-zero values in the array is returned.</ span >
149+
150+ < span class ="sd "> Limitations</ span >
151+ < span class ="sd "> -----------</ span >
152+ < span class ="sd "> Parameters `a` is supported as either :class:`dpnp.ndarray`</ span >
153+ < span class ="sd "> or :class:`dpctl.tensor.usm_ndarray`.</ span >
154+ < span class ="sd "> Otherwise ``TypeError`` exception will be raised.</ span >
155+ < span class ="sd "> Input array data types are limited by supported DPNP :ref:`Data types`.</ span >
156+
157+ < span class ="sd "> See Also</ span >
158+ < span class ="sd "> --------</ span >
159+ < span class ="sd "> :obj:`dpnp.nonzero` : Return the coordinates of all the non-zero values.</ span >
160+
161+ < span class ="sd "> Examples</ span >
162+ < span class ="sd "> --------</ span >
163+ < span class ="sd "> >>> import dpnp as np</ span >
164+ < span class ="sd "> >>> np.count_nonzero(np.eye(4))</ span >
165+ < span class ="sd "> array(4)</ span >
166+ < span class ="sd "> >>> a = np.array([[0, 1, 7, 0],</ span >
167+ < span class ="sd "> [3, 0, 2, 19]])</ span >
168+ < span class ="sd "> >>> np.count_nonzero(a)</ span >
169+ < span class ="sd "> array(5)</ span >
170+ < span class ="sd "> >>> np.count_nonzero(a, axis=0)</ span >
171+ < span class ="sd "> array([1, 1, 2, 1])</ span >
172+ < span class ="sd "> >>> np.count_nonzero(a, axis=1)</ span >
173+ < span class ="sd "> array([2, 3])</ span >
174+ < span class ="sd "> >>> np.count_nonzero(a, axis=1, keepdims=True)</ span >
175+ < span class ="sd "> array([[2],</ span >
176+ < span class ="sd "> [3]])</ span >
177+
178+ < span class ="sd "> """</ span >
179+
180+ < span class ="c1 "> # TODO: might be improved by implementing an extension</ span >
181+ < span class ="c1 "> # with `count_nonzero` kernel</ span >
182+ < span class ="n "> a</ span > < span class ="o "> =</ span > < span class ="n "> dpnp</ span > < span class ="o "> .</ span > < span class ="n "> astype</ span > < span class ="p "> (</ span > < span class ="n "> a</ span > < span class ="p "> ,</ span > < span class ="n "> dpnp</ span > < span class ="o "> .</ span > < span class ="n "> bool</ span > < span class ="p "> ,</ span > < span class ="n "> copy</ span > < span class ="o "> =</ span > < span class ="kc "> False</ span > < span class ="p "> )</ span >
183+ < span class ="k "> return</ span > < span class ="n "> a</ span > < span class ="o "> .</ span > < span class ="n "> sum</ span > < span class ="p "> (</ span > < span class ="n "> axis</ span > < span class ="o "> =</ span > < span class ="n "> axis</ span > < span class ="p "> ,</ span > < span class ="n "> dtype</ span > < span class ="o "> =</ span > < span class ="n "> dpnp</ span > < span class ="o "> .</ span > < span class ="n "> intp</ span > < span class ="p "> ,</ span > < span class ="n "> keepdims</ span > < span class ="o "> =</ span > < span class ="n "> keepdims</ span > < span class ="p "> )</ span > </ div >
184+
185+ </ pre > </ div >
186+
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