diff options
Diffstat (limited to 'numpy/lib/index_tricks.py')
| -rw-r--r-- | numpy/lib/index_tricks.py | 104 |
1 files changed, 69 insertions, 35 deletions
diff --git a/numpy/lib/index_tricks.py b/numpy/lib/index_tricks.py index d145477c3..b69226d48 100644 --- a/numpy/lib/index_tricks.py +++ b/numpy/lib/index_tricks.py @@ -1,11 +1,12 @@ import functools import sys import math +import warnings import numpy.core.numeric as _nx from numpy.core.numeric import ( asarray, ScalarType, array, alltrue, cumprod, arange, ndim - ) +) from numpy.core.numerictypes import find_common_type, issubdtype import numpy.matrixlib as matrixlib @@ -24,7 +25,7 @@ __all__ = [ 'ravel_multi_index', 'unravel_index', 'mgrid', 'ogrid', 'r_', 'c_', 's_', 'index_exp', 'ix_', 'ndenumerate', 'ndindex', 'fill_diagonal', 'diag_indices', 'diag_indices_from' - ] +] def _ix__dispatcher(*args): @@ -105,6 +106,7 @@ def ix_(*args): out.append(new) return tuple(out) + class nd_grid: """ Construct a multi-dimensional "meshgrid". @@ -147,39 +149,39 @@ class nd_grid: try: size = [] typ = int - for k in range(len(key)): - step = key[k].step - start = key[k].start + for kk in key: + step = kk.step + start = kk.start if start is None: start = 0 if step is None: step = 1 - if isinstance(step, complex): + if isinstance(step, (_nx.complexfloating, complex)): size.append(int(abs(step))) typ = float else: size.append( - int(math.ceil((key[k].stop - start)/(step*1.0)))) - if (isinstance(step, float) or - isinstance(start, float) or - isinstance(key[k].stop, float)): + int(math.ceil((kk.stop - start) / (step * 1.0)))) + if (isinstance(step, (_nx.floating, float)) or + isinstance(start, (_nx.floating, float)) or + isinstance(kk.stop, (_nx.floating, float))): typ = float if self.sparse: nn = [_nx.arange(_x, dtype=_t) - for _x, _t in zip(size, (typ,)*len(size))] + for _x, _t in zip(size, (typ,)*len(size))] else: nn = _nx.indices(size, typ) - for k in range(len(size)): - step = key[k].step - start = key[k].start + for k, kk in enumerate(key): + step = kk.step + start = kk.start if start is None: start = 0 if step is None: step = 1 - if isinstance(step, complex): + if isinstance(step, (_nx.complexfloating, complex)): step = int(abs(step)) if step != 1: - step = (key[k].stop - start)/float(step-1) + step = (kk.stop - start) / float(step - 1) nn[k] = (nn[k]*step+start) if self.sparse: slobj = [_nx.newaxis]*len(size) @@ -194,12 +196,11 @@ class nd_grid: start = key.start if start is None: start = 0 - if isinstance(step, complex): + if isinstance(step, (_nx.complexfloating, complex)): step = abs(step) length = int(step) if step != 1: step = (key.stop-start)/float(step-1) - stop = key.stop + step return _nx.arange(0, length, 1, float)*step + start else: return _nx.arange(start, stop, step) @@ -221,18 +222,18 @@ class MGridClass(nd_grid): 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 + 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] + >>> np.mgrid[0:5, 0:5] array([[[0, 0, 0, 0, 0], [1, 1, 1, 1, 1], [2, 2, 2, 2, 2], @@ -247,11 +248,14 @@ class MGridClass(nd_grid): array([-1. , -0.5, 0. , 0.5, 1. ]) """ + def __init__(self): - super(MGridClass, self).__init__(sparse=False) + super().__init__(sparse=False) + mgrid = MGridClass() + class OGridClass(nd_grid): """ `nd_grid` instance which returns an open multi-dimensional "meshgrid". @@ -291,8 +295,10 @@ class OGridClass(nd_grid): [4]]), array([[0, 1, 2, 3, 4]])] """ + def __init__(self): - super(OGridClass, self).__init__(sparse=True) + super().__init__(sparse=True) + ogrid = OGridClass() @@ -344,7 +350,7 @@ class AxisConcatenator: start = 0 if step is None: step = 1 - if isinstance(step, complex): + if isinstance(step, (_nx.complexfloating, complex)): size = int(abs(step)) newobj = linspace(start, stop, num=size) else: @@ -356,7 +362,7 @@ class AxisConcatenator: elif isinstance(item, str): if k != 0: raise ValueError("special directives must be the " - "first entry.") + "first entry.") if item in ('r', 'c'): matrix = True col = (item == 'c') @@ -375,8 +381,8 @@ class AxisConcatenator: try: axis = int(item) continue - except (ValueError, TypeError): - raise ValueError("unknown special directive") + except (ValueError, TypeError) as e: + raise ValueError("unknown special directive") from e elif type(item) in ScalarType: newobj = array(item, ndmin=ndmin) scalars.append(len(objs)) @@ -419,6 +425,7 @@ class AxisConcatenator: # etc. because otherwise we couldn't get the doc string to come out right # in help(r_) + class RClass(AxisConcatenator): """ Translates slice objects to concatenation along the first axis. @@ -517,8 +524,10 @@ class RClass(AxisConcatenator): def __init__(self): AxisConcatenator.__init__(self, 0) + r_ = RClass() + class CClass(AxisConcatenator): """ Translates slice objects to concatenation along the second axis. @@ -527,7 +536,7 @@ class CClass(AxisConcatenator): useful because of its common occurrence. In particular, arrays will be stacked along their last axis after being upgraded to at least 2-D with 1's post-pended to the shape (column vectors made out of 1-D arrays). - + See Also -------- column_stack : Stack 1-D arrays as columns into a 2-D array. @@ -611,8 +620,9 @@ class ndindex: Parameters ---------- - `*args` : ints - The size of each dimension of the array. + shape : ints, or a single tuple of ints + The size of each dimension of the array can be passed as + individual parameters or as the elements of a tuple. See Also -------- @@ -620,6 +630,8 @@ class ndindex: Examples -------- + Dimensions as individual arguments + >>> for index in np.ndindex(3, 2, 1): ... print(index) (0, 0, 0) @@ -629,6 +641,17 @@ class ndindex: (2, 0, 0) (2, 1, 0) + Same dimensions - but in a tuple ``(3, 2, 1)`` + + >>> for index in np.ndindex((3, 2, 1)): + ... print(index) + (0, 0, 0) + (0, 1, 0) + (1, 0, 0) + (1, 1, 0) + (2, 0, 0) + (2, 1, 0) + """ def __init__(self, *shape): @@ -647,7 +670,15 @@ class ndindex: Increment the multi-dimensional index by one. This method is for backward compatibility only: do not use. + + .. deprecated:: 1.20.0 + This method has been advised against since numpy 1.8.0, but only + started emitting DeprecationWarning as of this version. """ + # NumPy 1.20.0, 2020-09-08 + warnings.warn( + "`ndindex.ndincr()` is deprecated, use `next(ndindex)` instead", + DeprecationWarning, stacklevel=2) next(self) def __next__(self): @@ -730,6 +761,7 @@ class IndexExpression: else: return item + index_exp = IndexExpression(maketuple=True) s_ = IndexExpression(maketuple=False) @@ -757,9 +789,11 @@ def fill_diagonal(a, val, wrap=False): a : array, at least 2-D. Array whose diagonal is to be filled, it gets modified in-place. - val : scalar - Value to be written on the diagonal, its type must be compatible with - that of the array a. + val : scalar or array_like + Value(s) to write on the diagonal. If `val` is scalar, the value is + written along the diagonal. If array-like, the flattened `val` is + written along the diagonal, repeating if necessary to fill all + diagonal entries. wrap : bool For tall matrices in NumPy version up to 1.6.2, the @@ -862,7 +896,7 @@ def fill_diagonal(a, val, wrap=False): # Explicit, fast formula for the common case. For 2-d arrays, we # accept rectangular ones. step = a.shape[1] + 1 - #This is needed to don't have tall matrix have the diagonal wrap. + # This is needed to don't have tall matrix have the diagonal wrap. if not wrap: end = a.shape[1] * a.shape[1] else: @@ -896,7 +930,7 @@ def diag_indices(n, ndim=2): ndim : int, optional The number of dimensions. - See also + See Also -------- diag_indices_from |