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Function ones_like

numpy/core/numeric.py:204–267  ·  view source on GitHub ↗

Return an array of ones with the same shape and type as a given array. Parameters ---------- a : array_like The shape and data-type of `a` define these same attributes of the returned array. dtype : data-type, optional Overrides the data type of the resu

(a, dtype=None, order='K', subok=True, shape=None)

Source from the content-addressed store, hash-verified

202
203@array_function_dispatch(_ones_like_dispatcher)
204def ones_like(a, dtype=None, order='K', subok=True, shape=None):
205 """
206 Return an array of ones with the same shape and type as a given array.
207
208 Parameters
209 ----------
210 a : array_like
211 The shape and data-type of `a` define these same attributes of
212 the returned array.
213 dtype : data-type, optional
214 Overrides the data type of the result.
215
216 .. versionadded:: 1.6.0
217 order : {'C', 'F', 'A', or 'K'}, optional
218 Overrides the memory layout of the result. 'C' means C-order,
219 'F' means F-order, 'A' means 'F' if `a` is Fortran contiguous,
220 'C' otherwise. 'K' means match the layout of `a` as closely
221 as possible.
222
223 .. versionadded:: 1.6.0
224 subok : bool, optional.
225 If True, then the newly created array will use the sub-class
226 type of `a`, otherwise it will be a base-class array. Defaults
227 to True.
228 shape : int or sequence of ints, optional.
229 Overrides the shape of the result. If order='K' and the number of
230 dimensions is unchanged, will try to keep order, otherwise,
231 order='C' is implied.
232
233 .. versionadded:: 1.17.0
234
235 Returns
236 -------
237 out : ndarray
238 Array of ones with the same shape and type as `a`.
239
240 See Also
241 --------
242 empty_like : Return an empty array with shape and type of input.
243 zeros_like : Return an array of zeros with shape and type of input.
244 full_like : Return a new array with shape of input filled with value.
245 ones : Return a new array setting values to one.
246
247 Examples
248 --------
249 >>> x = np.arange(6)
250 >>> x = x.reshape((2, 3))
251 >>> x
252 array([[0, 1, 2],
253 [3, 4, 5]])
254 >>> np.ones_like(x)
255 array([[1, 1, 1],
256 [1, 1, 1]])
257
258 >>> y = np.arange(3, dtype=float)
259 >>> y
260 array([0., 1., 2.])
261 >>> np.ones_like(y)

Callers 2

test_onesMethod · 0.90
iscloseFunction · 0.70

Calls 1

empty_likeFunction · 0.70

Tested by 1

test_onesMethod · 0.72