# SOME DESCRIPTIVE TITLE.
# Copyright (C) 1999-2020, The Alibaba Group Holding Ltd.
# This file is distributed under the same license as the mars package.
# FIRST AUTHOR <EMAIL@ADDRESS>, 2020.
#
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"Project-Id-Version: mars 0.5.0a2\n"
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#: ../../source/reference/tensor/generated/mars.tensor.meshgrid.rst:2
msgid "mars.tensor.meshgrid"
msgstr ""

#: mars.tensor.meshgrid:1 of
msgid "Return coordinate matrices from coordinate vectors."
msgstr ""

#: mars.tensor.meshgrid:3 of
msgid ""
"Make N-D coordinate arrays for vectorized evaluations of N-D "
"scalar/vector fields over N-D grids, given one-dimensional coordinate "
"tensors x1, x2,..., xn."
msgstr ""

#: mars.tensor.meshgrid of
msgid "Parameters"
msgstr ""

#: mars.tensor.meshgrid:7 of
msgid "1-D arrays representing the coordinates of a grid."
msgstr ""

#: mars.tensor.meshgrid:9 of
msgid ""
"Cartesian ('xy', default) or matrix ('ij') indexing of output. See Notes "
"for more details."
msgstr ""

#: mars.tensor.meshgrid:12 of
msgid ""
"If True a sparse grid is returned in order to conserve memory. Default is"
" False."
msgstr ""

#: mars.tensor.meshgrid of
msgid "Returns"
msgstr ""

#: mars.tensor.meshgrid:16 of
msgid ""
"**X1, X2,..., XN** -- For vectors `x1`, `x2`,..., 'xn' with lengths "
"``Ni=len(xi)`` , return ``(N1, N2, N3,...Nn)`` shaped tensors if "
"indexing='ij' or ``(N2, N1, N3,...Nn)`` shaped tensors if indexing='xy' "
"with the elements of `xi` repeated to fill the matrix along the first "
"dimension for `x1`, the second for `x2` and so on."
msgstr ""

#: mars.tensor.meshgrid of
msgid "Return type"
msgstr ""

#: mars.tensor.meshgrid:24 of
msgid "Notes"
msgstr ""

#: mars.tensor.meshgrid:25 of
msgid ""
"This function supports both indexing conventions through the indexing "
"keyword argument.  Giving the string 'ij' returns a meshgrid with matrix "
"indexing, while 'xy' returns a meshgrid with Cartesian indexing. In the "
"2-D case with inputs of length M and N, the outputs are of shape (N, M) "
"for 'xy' indexing and (M, N) for 'ij' indexing.  In the 3-D case with "
"inputs of length M, N and P, outputs are of shape (N, M, P) for 'xy' "
"indexing and (M, N, P) for 'ij' indexing.  The difference is illustrated "
"by the following code snippet::"
msgstr ""

#: mars.tensor.meshgrid:44 of
msgid "In the 1-D and 0-D case, the indexing and sparse keywords have no effect."
msgstr ""

#: mars.tensor.meshgrid:47 of
msgid "Examples"
msgstr ""

#: mars.tensor.meshgrid:67 of
msgid "`meshgrid` is very useful to evaluate functions on a grid."
msgstr ""

