diff options
Diffstat (limited to 'numpy/lib/index_tricks.py')
| -rw-r--r-- | numpy/lib/index_tricks.py | 155 |
1 files changed, 120 insertions, 35 deletions
diff --git a/numpy/lib/index_tricks.py b/numpy/lib/index_tricks.py index d2139338e..56abe293a 100644 --- a/numpy/lib/index_tricks.py +++ b/numpy/lib/index_tricks.py @@ -1,5 +1,6 @@ from __future__ import division, absolute_import, print_function +import functools import sys import math @@ -9,13 +10,18 @@ from numpy.core.numeric import ( ) from numpy.core.numerictypes import find_common_type, issubdtype -from . import function_base import numpy.matrixlib as matrixlib from .function_base import diff from numpy.core.multiarray import ravel_multi_index, unravel_index +from numpy.core.overrides import set_module +from numpy.core import overrides, linspace from numpy.lib.stride_tricks import as_strided +array_function_dispatch = functools.partial( + overrides.array_function_dispatch, module='numpy') + + __all__ = [ 'ravel_multi_index', 'unravel_index', 'mgrid', 'ogrid', 'r_', 'c_', 's_', 'index_exp', 'ix_', 'ndenumerate', 'ndindex', 'fill_diagonal', @@ -23,6 +29,11 @@ __all__ = [ ] +def _ix__dispatcher(*args): + return args + + +@array_function_dispatch(_ix__dispatcher) def ix_(*args): """ Construct an open mesh from multiple sequences. @@ -121,39 +132,13 @@ class nd_grid(object): Notes ----- Two instances of `nd_grid` are made available in the NumPy namespace, - `mgrid` and `ogrid`:: + `mgrid` and `ogrid`, approximately defined as:: mgrid = nd_grid(sparse=False) ogrid = nd_grid(sparse=True) Users should use these pre-defined instances instead of using `nd_grid` directly. - - Examples - -------- - >>> mgrid = np.lib.index_tricks.nd_grid() - >>> mgrid[0:5,0:5] - array([[[0, 0, 0, 0, 0], - [1, 1, 1, 1, 1], - [2, 2, 2, 2, 2], - [3, 3, 3, 3, 3], - [4, 4, 4, 4, 4]], - [[0, 1, 2, 3, 4], - [0, 1, 2, 3, 4], - [0, 1, 2, 3, 4], - [0, 1, 2, 3, 4], - [0, 1, 2, 3, 4]]]) - >>> mgrid[-1:1:5j] - array([-1. , -0.5, 0. , 0.5, 1. ]) - - >>> ogrid = np.lib.index_tricks.nd_grid(sparse=True) - >>> ogrid[0:5,0:5] - [array([[0], - [1], - [2], - [3], - [4]]), array([[0, 1, 2, 3, 4]])] - """ def __init__(self, sparse=False): @@ -220,13 +205,97 @@ class nd_grid(object): else: return _nx.arange(start, stop, step) - def __len__(self): - return 0 -mgrid = nd_grid(sparse=False) -ogrid = nd_grid(sparse=True) -mgrid.__doc__ = None # set in numpy.add_newdocs -ogrid.__doc__ = None # set in numpy.add_newdocs +class MGridClass(nd_grid): + """ + `nd_grid` instance which returns a dense multi-dimensional "meshgrid". + + An instance of `numpy.lib.index_tricks.nd_grid` which returns an dense + (or fleshed out) mesh-grid when indexed, so that each returned argument + has the same shape. The dimensions and number of the output arrays are + equal to the number of indexing dimensions. If the step length is not a + complex number, then the stop is not inclusive. + + However, if the step length is a **complex number** (e.g. 5j), then + the integer part of its magnitude is interpreted as specifying the + number of points to create between the start and stop values, where + the stop value **is inclusive**. + + Returns + ---------- + mesh-grid `ndarrays` all of the same dimensions + + See Also + -------- + numpy.lib.index_tricks.nd_grid : class of `ogrid` and `mgrid` objects + ogrid : like mgrid but returns open (not fleshed out) mesh grids + r_ : array concatenator + + Examples + -------- + >>> np.mgrid[0:5,0:5] + array([[[0, 0, 0, 0, 0], + [1, 1, 1, 1, 1], + [2, 2, 2, 2, 2], + [3, 3, 3, 3, 3], + [4, 4, 4, 4, 4]], + [[0, 1, 2, 3, 4], + [0, 1, 2, 3, 4], + [0, 1, 2, 3, 4], + [0, 1, 2, 3, 4], + [0, 1, 2, 3, 4]]]) + >>> np.mgrid[-1:1:5j] + array([-1. , -0.5, 0. , 0.5, 1. ]) + + """ + def __init__(self): + super(MGridClass, self).__init__(sparse=False) + +mgrid = MGridClass() + +class OGridClass(nd_grid): + """ + `nd_grid` instance which returns an open multi-dimensional "meshgrid". + + An instance of `numpy.lib.index_tricks.nd_grid` which returns an open + (i.e. not fleshed out) mesh-grid when indexed, so that only one dimension + of each returned array is greater than 1. The dimension and number of the + output arrays are equal to the number of indexing dimensions. If the step + length is not a complex number, then the stop is not inclusive. + + However, if the step length is a **complex number** (e.g. 5j), then + the integer part of its magnitude is interpreted as specifying the + number of points to create between the start and stop values, where + the stop value **is inclusive**. + + Returns + ---------- + mesh-grid `ndarrays` with only one dimension :math:`\\neq 1` + + See Also + -------- + np.lib.index_tricks.nd_grid : class of `ogrid` and `mgrid` objects + mgrid : like `ogrid` but returns dense (or fleshed out) mesh grids + r_ : array concatenator + + Examples + -------- + >>> from numpy import ogrid + >>> ogrid[-1:1:5j] + array([-1. , -0.5, 0. , 0.5, 1. ]) + >>> ogrid[0:5,0:5] + [array([[0], + [1], + [2], + [3], + [4]]), array([[0, 1, 2, 3, 4]])] + + """ + def __init__(self): + super(OGridClass, self).__init__(sparse=True) + +ogrid = OGridClass() + class AxisConcatenator(object): """ @@ -277,7 +346,7 @@ class AxisConcatenator(object): step = 1 if isinstance(step, complex): size = int(abs(step)) - newobj = function_base.linspace(start, stop, num=size) + newobj = linspace(start, stop, num=size) else: newobj = _nx.arange(start, stop, step) if ndmin > 1: @@ -476,8 +545,11 @@ class CClass(AxisConcatenator): def __init__(self): AxisConcatenator.__init__(self, -1, ndmin=2, trans1d=0) + c_ = CClass() + +@set_module('numpy') class ndenumerate(object): """ Multidimensional index iterator. @@ -528,6 +600,7 @@ class ndenumerate(object): next = __next__ +@set_module('numpy') class ndindex(object): """ An N-dimensional iterator object to index arrays. @@ -668,6 +741,12 @@ s_ = IndexExpression(maketuple=False) # The following functions complement those in twodim_base, but are # applicable to N-dimensions. + +def _fill_diagonal_dispatcher(a, val, wrap=None): + return (a,) + + +@array_function_dispatch(_fill_diagonal_dispatcher) def fill_diagonal(a, val, wrap=False): """Fill the main diagonal of the given array of any dimensionality. @@ -782,6 +861,7 @@ def fill_diagonal(a, val, wrap=False): a.flat[:end:step] = val +@set_module('numpy') def diag_indices(n, ndim=2): """ Return the indices to access the main diagonal of an array. @@ -850,6 +930,11 @@ def diag_indices(n, ndim=2): return (idx,) * ndim +def _diag_indices_from(arr): + return (arr,) + + +@array_function_dispatch(_diag_indices_from) def diag_indices_from(arr): """ Return the indices to access the main diagonal of an n-dimensional array. |