diff options
Diffstat (limited to 'numpy/lib/index_tricks.py')
| -rw-r--r-- | numpy/lib/index_tricks.py | 51 |
1 files changed, 40 insertions, 11 deletions
diff --git a/numpy/lib/index_tricks.py b/numpy/lib/index_tricks.py index 3daacaff6..1da73dee5 100644 --- a/numpy/lib/index_tricks.py +++ b/numpy/lib/index_tricks.py @@ -3,16 +3,15 @@ import sys import math import warnings +import numpy as np +from .._utils import set_module import numpy.core.numeric as _nx -from numpy.core.numeric import ( - asarray, ScalarType, array, alltrue, cumprod, arange, ndim -) +from numpy.core.numeric import ScalarType, array from numpy.core.numerictypes import issubdtype 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 @@ -94,7 +93,7 @@ def ix_(*args): nd = len(args) for k, new in enumerate(args): if not isinstance(new, _nx.ndarray): - new = asarray(new) + new = np.asarray(new) if new.size == 0: # Explicitly type empty arrays to avoid float default new = new.astype(_nx.intp) @@ -232,7 +231,9 @@ class MGridClass(nd_grid): -------- lib.index_tricks.nd_grid : class of `ogrid` and `mgrid` objects ogrid : like mgrid but returns open (not fleshed out) mesh grids + meshgrid: return coordinate matrices from coordinate vectors r_ : array concatenator + :ref:`how-to-partition` Examples -------- @@ -283,7 +284,9 @@ class OGridClass(nd_grid): -------- np.lib.index_tricks.nd_grid : class of `ogrid` and `mgrid` objects mgrid : like `ogrid` but returns dense (or fleshed out) mesh grids + meshgrid: return coordinate matrices from coordinate vectors r_ : array concatenator + :ref:`how-to-partition` Examples -------- @@ -389,7 +392,7 @@ class AxisConcatenator: scalar = True newobj = item else: - item_ndim = ndim(item) + item_ndim = np.ndim(item) newobj = array(item, copy=False, subok=True, ndmin=ndmin) if trans1d != -1 and item_ndim < ndmin: k2 = ndmin - item_ndim @@ -594,7 +597,7 @@ class ndenumerate: """ def __init__(self, arr): - self.iter = asarray(arr).flat + self.iter = np.asarray(arr).flat def __next__(self): """ @@ -907,9 +910,9 @@ def fill_diagonal(a, val, wrap=False): else: # For more than d=2, the strided formula is only valid for arrays with # all dimensions equal, so we check first. - if not alltrue(diff(a.shape) == 0): + if not np.all(diff(a.shape) == 0): raise ValueError("All dimensions of input must be of equal length") - step = 1 + (cumprod(a.shape[:-1])).sum() + step = 1 + (np.cumprod(a.shape[:-1])).sum() # Write the value out into the diagonal. a.flat[:end:step] = val @@ -980,7 +983,7 @@ def diag_indices(n, ndim=2): [0, 1]]]) """ - idx = arange(n) + idx = np.arange(n) return (idx,) * ndim @@ -1007,13 +1010,39 @@ def diag_indices_from(arr): ----- .. versionadded:: 1.4.0 + Examples + -------- + + Create a 4 by 4 array. + + >>> a = np.arange(16).reshape(4, 4) + >>> a + array([[ 0, 1, 2, 3], + [ 4, 5, 6, 7], + [ 8, 9, 10, 11], + [12, 13, 14, 15]]) + + Get the indices of the diagonal elements. + + >>> di = np.diag_indices_from(a) + >>> di + (array([0, 1, 2, 3]), array([0, 1, 2, 3])) + + >>> a[di] + array([ 0, 5, 10, 15]) + + This is simply syntactic sugar for diag_indices. + + >>> np.diag_indices(a.shape[0]) + (array([0, 1, 2, 3]), array([0, 1, 2, 3])) + """ if not arr.ndim >= 2: raise ValueError("input array must be at least 2-d") # For more than d=2, the strided formula is only valid for arrays with # all dimensions equal, so we check first. - if not alltrue(diff(arr.shape) == 0): + if not np.all(diff(arr.shape) == 0): raise ValueError("All dimensions of input must be of equal length") return diag_indices(arr.shape[0], arr.ndim) |