def test_wrap_consistent_names(): assert (sorted(ones(10, dtype='i4', chunks=(4,)).dask) == sorted(ones(10, dtype='i4', chunks=(4,)).dask)) assert (sorted(ones(10, dtype='i4', chunks=(4,)).dask) != sorted(ones(10, chunks=(4,)).dask)) assert (sorted(da.full((3, 3), 100, chunks=(2, 2), dtype='f8').dask) == sorted(da.full((3, 3), 100, chunks=(2, 2), dtype='f8').dask)) assert (sorted(da.full((3, 3), 100, chunks=(2, 2), dtype='i2').dask) != sorted(da.full((3, 3), 100, chunks=(2, 2)).dask))
def test_wrap_consistent_names(): assert sorted(ones(10, dtype='i4', chunks=(4,)).dask) ==\ sorted(ones(10, dtype='i4', chunks=(4,)).dask) assert sorted(ones(10, dtype='i4', chunks=(4,)).dask) !=\ sorted(ones(10, chunks=(4,)).dask) assert sorted(da.full((3, 3), 100, chunks=(2, 2), dtype='f8').dask) ==\ sorted(da.full((3, 3), 100, chunks=(2, 2), dtype='f8').dask) assert sorted(da.full((3, 3), 100, chunks=(2, 2), dtype='f8').dask) !=\ sorted(da.full((3, 3), 100, chunks=(2, 2)).dask)
def test_wrap_consistent_names(): assert sorted(ones(10, dtype="i4", chunks=(4, )).dask) == sorted( ones(10, dtype="i4", chunks=(4, )).dask) assert sorted(ones(10, dtype="i4", chunks=(4, )).dask) != sorted( ones(10, chunks=(4, )).dask) assert sorted(da.full( (3, 3), 100, chunks=(2, 2), dtype="f8").dask) == sorted( da.full((3, 3), 100, chunks=(2, 2), dtype="f8").dask) assert sorted(da.full( (3, 3), 100, chunks=(2, 2), dtype="i2").dask) != sorted( da.full((3, 3), 100, chunks=(2, 2)).dask)
def ones_like(a, dtype=None, order="C", chunks=None, name=None, shape=None): """ 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 result. order : {'C', 'F'}, optional Whether to store multidimensional data in C- or Fortran-contiguous (row- or column-wise) order in memory. chunks : sequence of ints The number of samples on each block. Note that the last block will have fewer samples if ``len(array) % chunks != 0``. name : str, optional An optional keyname for the array. Defaults to hashing the input keyword arguments. shape : int or sequence of ints, optional. Overrides the shape of the result. Returns ------- out : ndarray Array of ones with the same shape and type as `a`. See Also -------- zeros_like : Return an array of zeros with shape and type of input. empty_like : Return an empty array with shape and type of input. zeros : Return a new array setting values to zero. ones : Return a new array setting values to one. empty : Return a new uninitialized array. """ a = asarray(a, name=False) shape, chunks = _get_like_function_shapes_chunks(a, chunks, shape) return ones( shape, dtype=(dtype or a.dtype), order=order, chunks=chunks, name=name, meta=a._meta, )
def test_singleton_size(): a = ones(10, dtype='i4', chunks=(4,)) x = np.array(a) assert (x == np.ones(10, dtype='i4')).all()
def test_size_as_list(): a = ones([10, 10], dtype='i4', chunks=(4, 4)) x = np.array(a) assert (x == np.ones((10, 10), dtype='i4')).all()
def test_can_make_really_big_array_of_ones(): ones((1000000, 1000000), chunks=(100000, 100000)) ones(shape=(1000000, 1000000), chunks=(100000, 100000))
def test_kwargs(): a = ones(10, dtype="i4", chunks=(4, )) x = np.array(a) assert (x == np.ones(10, dtype="i4")).all()
def test_ones(): a = ones((10, 10), dtype="i4", chunks=(4, 4)) x = np.array(a) assert (x == np.ones((10, 10), "i4")).all() assert a.name.startswith("ones_like-")
def test_ones(): a = ones((10, 10), dtype='i4', blockshape=(4, 4)) x = np.array(a) assert (x == np.ones((10, 10), 'i4')).all()
def test_kwargs(): a = ones(10, dtype='i4', blockshape=(4,)) x = np.array(a) assert (x == np.ones(10, dtype='i4')).all()
def test_singleton_size(): a = ones(10, dtype='i4', blockshape=(4,)) x = np.array(a) assert (x == np.ones(10, dtype='i4')).all()
def test_size_as_list(): a = ones([10, 10], dtype='i4', blockshape=(4, 4)) x = np.array(a) assert (x == np.ones((10, 10), dtype='i4')).all()
def test_kwargs(): a = ones(10, dtype='i4', chunks=(4,)) x = np.array(a) assert (x == np.ones(10, dtype='i4')).all()
def test_size_as_list(): a = ones([10, 10], dtype="i4", chunks=(4, 4)) x = np.array(a) assert (x == np.ones((10, 10), dtype="i4")).all()
def test_singleton_size(): a = ones(10, dtype="i4", chunks=(4, )) x = np.array(a) assert (x == np.ones(10, dtype="i4")).all()
def test_ones(): a = ones((10, 10), dtype='i4', chunks=(4, 4)) x = np.array(a) assert (x == np.ones((10, 10), 'i4')).all()
def test_ones(): a = ones((10, 10), dtype='i4', chunks=(4, 4)) x = np.array(a) assert (x == np.ones((10, 10), 'i4')).all() assert a.name.startswith('ones-')