| /dports/science/py-scikit-fuzzy/scikit-fuzzy-0.4.2/skfuzzy/image/ |
| H A D | shape.py | 93 arr_shape = np.array(arr_in.shape)
94 if (arr_shape % block_shape).sum() != 0:
100 new_shape = tuple(arr_shape // block_shape) + tuple(block_shape)
221 arr_shape = np.array(arr_in.shape)
222 window_shape = np.array(window_shape, dtype=arr_shape.dtype)
224 if ((arr_shape - window_shape) < 0).any():
233 new_shape = tuple(arr_shape - window_shape + 1) + tuple(window_shape)
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| /dports/science/py-gpaw/gpaw-21.6.0/gpaw/nlopt/ |
| H A D | basic.py | 48 arr_shape = []
51 arr_shape.append(ar_shape)
58 arr_shape = None
61 arr_shape = broadcast(arr_shape, root=0)
82 for ii, cshape in enumerate(arr_shape):
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| /dports/graphics/py-scikit-image/scikit-image-0.19.0/skimage/util/ |
| H A D | shape.py | 84 arr_shape = np.array(arr_in.shape)
85 if (arr_shape % block_shape).sum() != 0:
89 new_shape = tuple(arr_shape // block_shape) + tuple(block_shape)
225 arr_shape = np.array(arr_in.shape)
226 window_shape = np.array(window_shape, dtype=arr_shape.dtype)
228 if ((arr_shape - window_shape) < 0).any():
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| /dports/math/py-numpy/numpy-1.20.3/numpy/lib/ |
| H A D | shape_base.py | 29 def _make_along_axis_idx(arr_shape, indices, axis): argument
33 if len(arr_shape) != indices.ndim:
42 for dim, n in zip(dest_dims, arr_shape):
163 arr_shape = (len(arr),) # flatiter has no .shape
167 arr_shape = arr.shape
170 return arr[_make_along_axis_idx(arr_shape, indices, axis)]
254 arr_shape = (len(arr),) # flatiter has no .shape
257 arr_shape = arr.shape
260 arr[_make_along_axis_idx(arr_shape, indices, axis)] = values
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| /dports/devel/py-pythran/pythran-0.11.0/pythran/pythonic/numpy/ |
| H A D | frexp.hpp | 51 auto arr_shape = sutils::getshape(arr); in frexp() local
53 arr_shape, builtins::None); in frexp()
54 types::ndarray<int, typename E::shape_t> exps(arr_shape, builtins::None); in frexp()
|
| /dports/math/py-pymc3/pymc-3.11.4/pymc3/ |
| H A D | theanof.py | 478 def _make_along_axis_idx(arr_shape, indices, axis):
488 for dim, n in zip(dest_dims, arr_shape):
513 arr_shape = (len(arr),) # flatiter has no .shape
525 arr_shape = arr.shape
530 return arr[_make_along_axis_idx(arr_shape, indices, _axis)]
|
| /dports/math/py-PyWavelets/pywt-1.2.0/pywt/ |
| H A D | _multilevel.py | 613 arr_shape = np.asarray(coeffs[0].shape)
618 arr_shape[axes] += np.asarray(d['d'*ndim_transform].shape)[axes]
621 arr_shape = tuple(arr_shape.tolist())
624 is_tight_packing = (np.prod(arr_shape) == ncoeffs)
625 return arr_shape, is_tight_packing
757 arr_shape, is_tight_packing = _determine_coeff_array_shape(coeffs, axes)
763 coeff_arr = np.empty(arr_shape, dtype=a_coeffs.dtype)
765 coeff_arr = np.full(arr_shape, padding, dtype=a_coeffs.dtype)
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| /dports/science/py-h5py/h5py-3.6.0/h5py/ |
| H A D | _selector.pyx | 268 tuple shape, start, count, step, scalar, arr_shape
283 arr_shape = tuple(
286 return FancySelection(shape, space, count, arr_shape)
322 cdef npy_intp* arr_shape
324 arr_shape = <npy_intp*>emalloc(sizeof(npy_intp) * self.selector.rank)
329 arr_shape[arr_rank] = mshape[i]
332 arr = PyArray_SimpleNew(arr_rank, arr_shape, self.np_typenum)
336 efree(arr_shape)
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| /dports/math/py-pandas/pandas-1.2.5/pandas/tests/ |
| H A D | test_nanops.py | 35 arr_shape = (11, 7)
37 self.arr_float = np.random.randn(*arr_shape)
38 self.arr_float1 = np.random.randn(*arr_shape)
40 self.arr_int = np.random.randint(-10, 10, arr_shape)
41 self.arr_bool = np.random.randint(0, 2, arr_shape) == 0
44 self.arr_date = np.random.randint(0, 20000, arr_shape).astype("M8[ns]")
45 self.arr_tdelta = np.random.randint(0, 20000, arr_shape).astype("m8[ns]")
47 self.arr_nan = np.tile(np.nan, arr_shape)
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| /dports/math/py-pymc3/pymc-3.11.4/pymc3/tests/ |
| H A D | test_theanof.py | 61 def _make_along_axis_idx(arr_shape, indices, axis): argument
71 for dim, n in zip(dest_dims, arr_shape):
|
| /dports/science/py-scipy/scipy-1.7.1/scipy/spatial/src/ |
| H A D | distance_pybind.cpp | 221 const auto arr_shape = arr.shape(); in get_descriptor() local
222 desc.shape.assign(arr_shape, arr_shape + ndim); in get_descriptor()
|
| /dports/science/py-phonopy/phonopy-2.11.0/phonopy/phonon/ |
| H A D | dos.py | 198 arr_shape = frequencies.shape + (len(frequency_points), _coef.shape[1])
199 dos = np.zeros(arr_shape, dtype='double')
|
| /dports/science/phonopy/phonopy-2.11.0/phonopy/phonon/ |
| H A D | dos.py | 198 arr_shape = frequencies.shape + (len(frequency_points), _coef.shape[1])
199 dos = np.zeros(arr_shape, dtype='double')
|
| /dports/math/py-pystan/pystan-2.19.0.0/pystan/ |
| H A D | stanfit4model.pyx | 610 arr_shape = [n, chains, len(self.sim['fnames_oi'])]
611 arr = np.empty(arr_shape, order='F')
631 arr_shape = [sum(n_kept)] + shape
632 arr = np.empty(arr_shape, dtype=dtype, order='F')
643 arr_shape = [n, chains] + shape
644 arr = np.empty(arr_shape, dtype=dtype, order='F')
|
| /dports/misc/py-xgboost/xgboost-1.5.1/python-package/xgboost/ |
| H A D | core.py | 311 arr_shape: np.ndarray = ctypes2numpy(shape, dims.value, np.uint64)
312 length = int(np.prod(arr_shape))
317 arr_predict = arr_predict.reshape(arr_shape)
|
| /dports/misc/xgboost/xgboost-1.5.1/python-package/xgboost/ |
| H A D | core.py | 311 arr_shape: np.ndarray = ctypes2numpy(shape, dims.value, np.uint64)
312 length = int(np.prod(arr_shape))
317 arr_predict = arr_predict.reshape(arr_shape)
|
| /dports/math/py-numpy/numpy-1.20.3/numpy/core/src/multiarray/ |
| H A D | multiarraymodule.c | 400 npy_intp *arr_shape; in PyArray_ConcatenateArrays() local
411 arr_shape = PyArray_SHAPE(arrays[iarrays]); in PyArray_ConcatenateArrays()
416 shape[idim] += arr_shape[idim]; in PyArray_ConcatenateArrays()
419 else if (shape[idim] != arr_shape[idim]) { in PyArray_ConcatenateArrays()
425 idim, 0, shape[idim], iarrays, arr_shape[idim]); in PyArray_ConcatenateArrays()
|
| /dports/math/py-jax/jax-0.2.9/jax/_src/numpy/ |
| H A D | lax_numpy.py | 1664 arr_shape = _shape(arr)
1665 if arr_shape == shape:
1668 nlead = len(shape) - len(arr_shape)
1669 compatible = np.equal(arr_shape, shape[nlead:]) | np.equal(arr_shape, 1)
1672 raise ValueError(msg.format(arr_shape, shape))
1673 diff, = np.where(np.not_equal(shape[nlead:], arr_shape))
4118 arr_shape = replace(arr.shape, 1)
4120 out_shape = lax.broadcast_shapes(idx_shape, arr_shape)
4153 slice_sizes.append(arr_shape[i])
|
| /dports/math/libpgmath/flang-d07daf3/tools/flang1/flang1exe/ |
| H A D | ast.c | 1782 int arr_shape = A_SHAPEG(arr); /* shape of array */ in mk_subscr_copy() local
1798 if (upb == 0 && arr_shape) in mk_subscr_copy()
1799 upb = SHD_UPB(arr_shape, i); in mk_subscr_copy()
|
| /dports/misc/py-mxnet/incubator-mxnet-1.9.0/tests/python/unittest/ |
| H A D | test_numpy_op.py | 2965 for arr_shape, obj, val_shape, axis in config:
2978 a = mx.nd.random.uniform(-10.0, 10.0, shape=arr_shape).as_np_ndarray().astype(atype)
3620 for arr_shape, obj, axis in config:
3633 a = mx.nd.random.uniform(-1.0, 1.0, shape=arr_shape).as_np_ndarray()
|
| /dports/misc/mxnet/incubator-mxnet-1.9.0/tests/python/unittest/ |
| H A D | test_numpy_op.py | 2965 for arr_shape, obj, val_shape, axis in config:
2978 a = mx.nd.random.uniform(-10.0, 10.0, shape=arr_shape).as_np_ndarray().astype(atype)
3620 for arr_shape, obj, axis in config:
3633 a = mx.nd.random.uniform(-1.0, 1.0, shape=arr_shape).as_np_ndarray()
|