import cupy from cupy import _core def column_stack(tup): """Stacks 1-D and 2-D arrays as columns into a 2-D array. A 1-D array is first converted to a 2-D column array. Then, the 2-D arrays are concatenated along the second axis. Args: tup (sequence of arrays): 1-D or 2-D arrays to be stacked. Returns: cupy.ndarray: A new 2-D array of stacked columns. .. seealso:: :func:`numpy.column_stack` """ if any(not isinstance(a, cupy.ndarray) for a in tup): raise TypeError('Only cupy arrays can be column stacked') lst = list(tup) for i, a in enumerate(lst): if a.ndim == 1: a = a[:, cupy.newaxis] lst[i] = a elif a.ndim != 2: raise ValueError( 'Only 1 or 2 dimensional arrays can be column stacked') return concatenate(lst, axis=1) def concatenate(tup, axis=0, out=None, *, dtype=None, casting='same_kind'): """Joins arrays along an axis. Args: tup (sequence of arrays): Arrays to be joined. All of these should have same dimensionalities except the specified axis. axis (int or None): The axis to join arrays along. If axis is None, arrays are flattened before use. Default is 0. out (cupy.ndarray): Output array. dtype (str or dtype): If provided, the destination array will have this dtype. Cannot be provided together with ``out``. casting ({‘no’, ‘equiv’, ‘safe’, ‘same_kind’, ‘unsafe’}, optional): Controls what kind of data casting may occur. Defaults to ``'same_kind'``. Returns: cupy.ndarray: Joined array. .. seealso:: :func:`numpy.concatenate` """ if axis is None: tup = [m.ravel() for m in tup] axis = 0 return _core.concatenate_method(tup, axis, out, dtype, casting) def dstack(tup): """Stacks arrays along the third axis. Args: tup (sequence of arrays): Arrays to be stacked. Each array is converted by :func:`cupy.atleast_3d` before stacking. Returns: cupy.ndarray: Stacked array. .. seealso:: :func:`numpy.dstack` """ return concatenate([cupy.atleast_3d(m) for m in tup], 2) def hstack(tup, *, dtype=None, casting='same_kind'): """Stacks arrays horizontally. If an input array has one dimension, then the array is treated as a horizontal vector and stacked along the first axis. Otherwise, the array is stacked along the second axis. Args: tup (sequence of arrays): Arrays to be stacked. dtype (str or dtype): If provided, the destination array will have this dtype. casting ({‘no’, ‘equiv’, ‘safe’, ‘same_kind’, ‘unsafe’}, optional): Controls what kind of data casting may occur. Defaults to ``'same_kind'``. Returns: cupy.ndarray: Stacked array. .. seealso:: :func:`numpy.hstack` """ arrs = [cupy.atleast_1d(a) for a in tup] axis = 1 if arrs[0].ndim == 1: axis = 0 return concatenate(arrs, axis, dtype=dtype, casting=casting) def vstack(tup, *, dtype=None, casting='same_kind'): """Stacks arrays vertically. If an input array has one dimension, then the array is treated as a horizontal vector and stacked along the additional axis at the head. Otherwise, the array is stacked along the first axis. Args: tup (sequence of arrays): Arrays to be stacked. Each array is converted by :func:`cupy.atleast_2d` before stacking. dtype (str or dtype): If provided, the destination array will have this dtype. casting ({‘no’, ‘equiv’, ‘safe’, ‘same_kind’, ‘unsafe’}, optional): Controls what kind of data casting may occur. Defaults to ``'same_kind'``. Returns: cupy.ndarray: Stacked array. .. seealso:: :func:`numpy.dstack` """ return concatenate([cupy.atleast_2d(m) for m in tup], 0, dtype=dtype, casting=casting) def stack(tup, axis=0, out=None, *, dtype=None, casting='same_kind'): """Stacks arrays along a new axis. Args: tup (sequence of arrays): Arrays to be stacked. axis (int): Axis along which the arrays are stacked. out (cupy.ndarray): Output array. dtype (str or dtype): If provided, the destination array will have this dtype. Cannot be provided together with ``out``. casting ({‘no’, ‘equiv’, ‘safe’, ‘same_kind’, ‘unsafe’}, optional): Controls what kind of data casting may occur. Defaults to ``'same_kind'``. Returns: cupy.ndarray: Stacked array. .. seealso:: :func:`numpy.stack` """ return concatenate([cupy.expand_dims(x, axis) for x in tup], axis, out, dtype=dtype, casting=casting)