Active Oldest Votes. numpy.mask_indices¶ numpy.mask_indices (n, mask_func, k=0) [source] ¶ Return the indices to access (n, n) arrays, given a masking function. You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. Python numpy.tril_indices_from () Examples The following are 14 code examples for showing how to use numpy.tril_indices_from (). Parameters. m: int, optional. For a.ndim = 2 this is the usual diagonal, for a.ndim > 2 this is the set of indices to access a[i, i, ..., i] for i = [0..n-1]. numpy.block numpy.block(arrays) [source] Assemblez un nd-array à partir de listes de blocs imbriquées. See `tril_indices` for full details. The following are 30 code examples for showing how to use numpy.tril_indices(). numpy.tril_indices_from. numpy.triu_indices_from. These examples are extracted from open source projects. nint. tril_indices (*args, **kwargs) Return the indices for the lower-triangle of an (n, m) array. m: int, optional. numpy.triu_indices, Return the indices for the upper-triangle of an (n, m) array. Notes. k: int, optional. New in version 1.9.0. k: int, optional. The indices will be valid for square arrays whose dimensions are the same as arr. Parameters: a: 1-D array-like or int. tril_indices similar function, for lower-triangular. nint. numpy.triu_indices¶ numpy.triu_indices (n, k=0, m=None) [source] ¶ Return the indices for the upper-triangle of an (n, m) array. numpy.tril_indices_from(arr, k=0)[source] Return the indices for the lower-triangle of arr. numpy.tril_indices(n, k=0, m=None) [source] ¶ Return the indices for the lower-triangle of an (n, m) array. The size of the arrays for which the returned indices will be valid. Parameters Can be used to slice a ndarray of shape(n, n). k : [int, optional] Diagonal offset. The row dimension of the arrays for which the returned numpy.mask_indices¶ numpy.mask_indices(n, mask_func, k=0) [source] ¶ Return the indices to access (n, n) arrays, given a masking function. numpy.triu_indices_from. tril_indices() might be the obvious approach here that generates the lower triangular indices and then you can use those to set those in input array to NaNs. numpy.tril_indices_from ¶ numpy.tril_indices_from(arr, k=0) [source] ¶ Return the indices for the lower-triangle of arr. k: int, optional. 50.9k 9 9 gold badges 127 127 silver badges 176 176 bronze badges. m: int, optional. See tril_indices for full details. Syntax : numpy.mask_indices(n, mask_func, k = 0) Parameters : n : [int] The returned indices will be valid to access arrays of shape (n, n). The indices will be valid for square arrays whose dimensions are the same as arr. See tril_indices for full details. MEE MEE. While JAX tries to follow the NumPy API as closely as possible, sometimes JAX cannot follow NumPy exactly. New in version 1.4.0. def tril_indices_from (arr, k = 0): """ Return the indices for the lower-triangle of arr. numpy.tril_indices (n, k=0, m=None) [source] ¶ Return the indices for the lower-triangle of an (n, m) array. See Also-----tril_indices, tril… The following are 7 code examples for showing how to use torch.tril_indices().These examples are extracted from open source projects. generic function accepting an arbitrary mask function. You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. numpy.triu_indices_from numpy.triu_indices_from(arr, k=0) [source] Return the indices for the upper-triangle of arr. numpy.tril_indices_from ¶ numpy.tril_indices_from(arr, k=0) [source] ¶ Return the indices for the lower-triangle of arr. The returned tuple contains two arrays, The indices will be valid for square arrays whose dimensions are the same as arr. random. New in version 1.4.0. It will act on nd-arrays (along a specified axis); and also will look up multiple entries in a vectorized manner as opposed to a single item at a time. mask_indices generic function accepting an arbitrary mask function. numpy.triu_indices, Return the indices for the upper-triangle of an (n, m) array. k: int, optional. See triu_indices for full det_来自Numpy 1.10,w3cschool。 Return a copy of an array with elements above the k-th diagonal zeroed. numpy.tril_indices¶ numpy.tril_indices(n, k=0)¶ Return the indices for the lower-triangle of an (n, n) array. arrays will be valid. Returns : Lower triangle of a, having same shape and data-type as a. Created using Sphinx 3.4.3. k int, optional. Assume mask_func is a function that, for a square array a of size (n, n) with a possible offset argument k, when called as mask_func(a, k) returns a new array with zeros in certain locations (functions like triu or tril do precisely this). Use np.indices and np.broadcast_to to speed it up. If an int, the random sample is generated as if a were np.arange(a) size: … indices will be valid. Follow answered Dec 17 '18 at 20:04. Parameters: n: int. nint. array([[0., 2., 3. numpy.tril¶ numpy.tril (m, k=0) [source] ¶ Lower triangle of an array. Parameters. Copy upper triangle to lower triangle in a , The easiest AND FASTEST (no loop) way to do this is the following: import numpy as np X= np. numpy.triu_indices, Return the indices for the upper-triangle of an (n, m) array. Compute two different sets of indices to access 4x4 arrays, one for the numpy.mask_indices() function return the indices to access (n, n) arrays, given a masking function. tril_indices, tril. numpy.tril_indices_from(arr, k=0) [source] Renvoie les indices pour le triangle inférieur d'arr. Assume mask_func is a function that, for a square array a of size (n, n) with a possible offset argument k, when called as mask_func(a, k) returns a new array with zeros in certain locations (functions like triu or tril do precisely this). numpy.triu_indices ¶ numpy.triu_indices(n, k=0, m=None) [source] ¶ Return the indices for the upper-triangle of an (n, m) array. numpy.mask_indices¶ numpy.mask_indices(n, mask_func, k=0) [source] ¶ Return the indices to access (n, n) arrays, given a masking function. Parameters-----arr : array_like: The indices will be valid for square arrays whose dimensions are: the same as arr. The following are 30 code examples for showing how to use numpy.triu_indices_from().These examples are extracted from open source projects. Share. Please refer to the documentation for tril for further details. numpy.triu¶ numpy.triu (m, k=0) [source] ¶ Upper triangle of an array. See triu_indices for full details. Parameters: arr: array_like. and go to the original project or source file by following the links above each example. k : int, optional: Diagonal offset (see `tril` for details). See triu_indices for full det_来自Numpy 1.10,w3cschool。 Parameters: arr: array_like. C-Types Foreign Function Interface (numpy.ctypeslib), Optionally SciPy-accelerated routines (numpy.dual), Mathematical functions with automatic domain (numpy.emath). The column dimension of the arrays for which the returned Parameters. numpy.tril_indices¶ numpy.tril_indices(n, k=0, m=None) [source] ¶ Return the indices for the lower-triangle of an (n, m) array. to access the main diagonal of an array. Parameters: n: int. Return the indices for the lower-triangle of an (n, m) array. Disposition de la mémoire interne d'un ndarray . Share. triu, tril. tril_indices (n, k=0, m=None)[source]¶. generic function accepting an arbitrary mask function. numpy.triu_indices¶ numpy.triu_indices(n, k=0, m=None) [source] ¶ Return the indices for the upper-triangle of an (n, m) array. You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. def tril_indices_from (arr, k = 0): """ Return the indices for the lower-triangle of arr. 6. mask_func : [callable] A function whose call signature is similar to that of triu, tril. Bug The return type of numpy.tril_indices is a tuple of arrays while torch.tril_indices returns a single tensor. The indices for the triangle. Syntax : numpy.tril_indices (n, k = 0, m = None) numpy.mask_indices() function return the indices to access (n, n) arrays, given a masking function. Diagonal offset (see tril for details). 1,412 9 9 silver badges 15 15 bronze badges. tril_indices_from (arr[, k]) Return the indices for the lower-triangle of arr. Return the indices for the lower-triangle of an (n, m) array. Parameters m array_like, shape (M, N) Input array. tril_indices, tril. Last updated on Jan 19, 2021. numpy.tril_indices () function return the indices for the lower-triangle of an (n, m) array. The indices will be valid for square arrays whose dimensions are the same a ], [0., 0., 6. In this article we will discuss how to get the maximum / largest value in a Numpy array and its indices using numpy.amax(). each with the indices along one dimension of the array. diagonals further right: Here is how they can be used with a sample array: These cover almost the whole array (two diagonals right of the main one): © Copyright 2008-2020, The SciPy community. To do this in NumPy, without using a double loop, you can use tril_indices. Diagonal offset (see tril for details). Seetril_indicesfor full details. You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. Return the indices for the lower-triangle of an (n, m) array. Notes. These examples are extracted from open source projects. See tril_indices for full details. numpy.tril_indices(n, k=0)[source]¶ Return the indices for the lower-triangle of an (n, n) array. Diagonal offset (see triu for details). X = X + X. Return a copy of an array with elements above the k-th diagonal zeroed. lower triangular part starting at the main diagonal, and one starting two Diagonal offset (see tril for details). Charles David Mupende. Voir tril_indices pour plus de détails. numpy. Compute two different sets of indices to access 4x4 arrays, one for the Syntax : numpy.tril_indices(n, k = 0, m = None) Parameters : n : [int] The row dimension of the arrays for which the returned indices will be valid. add a comment | 1. See also. npi.indices can be viewed as an n-dimensional generalisation of list.index. m : [int, optional] The column dimension of the arrays for which the returned arrays will be valid. See Also-----tril_indices, tril… Parameters: n: int. mask_indices. See tril_indices for full details. k: int, optional. similar function, for lower-triangular. numpy.tril¶ numpy.tril (m, k=0) [source] ¶ Lower triangle of an array. The returned tuple contains two arrays, numpy.tril_indices(n, k=0, m=None) [source] ¶ Return the indices for the lower-triangle of an (n, m) array. You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. Syntax : numpy.mask_indices(n, mask_func, k = 0) Parameters : n : [int] The returned indices will be valid to access arrays of shape (n, n). numpy.tril_indices(n, k=0, m=None) [source] ¶ Return the indices for the lower-triangle of an (n, m) array. numpy.tril_indices_from¶ numpy.tril_indices_from(arr, k=0) [source] ¶ Return the indices for the lower-triangle of arr. tril_indices, tril. Python Numpy : Select rows / columns by index from a 2D Numpy Array | Multi Dimension; Create an empty Numpy Array of given length or shape & data type in Python; 1 Comment Already. each with the indices along one dimension of the array. numpy.triu_indices_from numpy.triu_indices_from(arr, k=0) [source] Return the indices for the upper-triangle of arr. numpy.tril_indices¶ numpy.tril_indices(n, k=0) [source] ¶ Return the indices for the lower-triangle of an (n, n) array. Parameters m array_like, shape (M, N) Input array. numpy.tril_indices_from¶ numpy.tril_indices_from (arr, k=0) [source] ¶ Return the indices for the lower-triangle of arr. Parameters. tril (m[, k]) Lower triangle of an array. The size of the arrays for which the returned indices will be valid. Parameters: n: int. See `tril_indices` for full details. numpy.triu_indices_from(arr, k=0) [source] ¶ Return the indices for the upper-triangle of arr. Return a copy of a matrix with the elements below the k-th diagonal zeroed.. On peut alors faire : a[numpy.diag_indices(3)] = 7 pour mettre des 7 sur la diagonale. See also. Bug The return type of numpy.tril_indices is a tuple of arrays while torch.tril_indices returns a single tensor. Parameters-----arr : array_like: The indices will be valid for square arrays whose dimensions are: the same as arr. mask_func : [callable] A function whose call signature is similar to that of triu, tril. arrays will be valid. Try numpy.triu (triangle-upper) and numpy.tril (triangle-lower). tril_indices (n, k=0, m=None) [source] ¶ Return the indices for the lower-triangle of an (n, m) array. Next topic. Parameters: arr: array_like. The column dimension of the arrays for which the returned arrays will be valid. Notes. Additionally, there are the functions np.triu_indices, np.tril_indices, np.triu_indices_from, and np.tril_indices_from to generate indices to index the upper or lower triangle with. Please refer to the documentation for tril for further details. Follow answered Jan 18 '12 at 5:15. mathematical.coffee mathematical.coffee. Parameters: n: int. indices will be valid. Notably, since JAX arrays are immutable, NumPy APIs that mutate arrays in-place cannot be implemented in JAX. Simply replace triu_indices_from with tril_indices_from: mask = np.zeros_like(corr, dtype=np.bool) mask[np.tril_indices_from(mask)] = True Share. New in version 1.9.0. The row dimension of the square arrays for which the returned indices will be valid. Returns: inds: tuple of arrays. k: int, optional. numpy.tril(a, k=0) : Returns copy of array with lower part of the triangle w.r.t k Parameters : a : input array k : [int, optional, 0 by default] Diagonal we require; k>0 means diagonal above main diagonal or vice versa. Matrix with the elements below the k-th diagonal zeroed Foreign function Interface ( numpy.ctypeslib ), Mathematical functions with domain. ( the default ) is the main diagonal of an array ) mask [ (. 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