# 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.
#
#, fuzzy
msgid ""
msgstr ""
"Project-Id-Version: mars 0.5.0a2\n"
"Report-Msgid-Bugs-To: \n"
"POT-Creation-Date: 2020-06-16 16:57+0800\n"
"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n"
"Last-Translator: FULL NAME <EMAIL@ADDRESS>\n"
"Language-Team: LANGUAGE <LL@li.org>\n"
"MIME-Version: 1.0\n"
"Content-Type: text/plain; charset=utf-8\n"
"Content-Transfer-Encoding: 8bit\n"
"Generated-By: Babel 2.7.0\n"

#: ../../source/reference/tensor/generated/mars.tensor.std.rst:2
msgid "mars.tensor.std"
msgstr ""

#: mars.tensor.std:1 of
msgid "Compute the standard deviation along the specified axis."
msgstr ""

#: mars.tensor.std:3 of
msgid ""
"Returns the standard deviation, a measure of the spread of a "
"distribution, of the tensor elements. The standard deviation is computed "
"for the flattened tensor by default, otherwise over the specified axis."
msgstr ""

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

#: mars.tensor.std:7 of
msgid "Calculate the standard deviation of these values."
msgstr ""

#: mars.tensor.std:9 of
msgid ""
"Axis or axes along which the standard deviation is computed. The default "
"is to compute the standard deviation of the flattened tensor.  If this is"
" a tuple of ints, a standard deviation is performed over multiple axes, "
"instead of a single axis or all the axes as before."
msgstr ""

#: mars.tensor.std:9 of
msgid ""
"Axis or axes along which the standard deviation is computed. The default "
"is to compute the standard deviation of the flattened tensor."
msgstr ""

#: mars.tensor.std:12 of
msgid ""
"If this is a tuple of ints, a standard deviation is performed over "
"multiple axes, instead of a single axis or all the axes as before."
msgstr ""

#: mars.tensor.std:15 of
msgid ""
"Type to use in computing the standard deviation. For tensors of integer "
"type the default is float64, for tensors of float types it is the same as"
" the array type."
msgstr ""

#: mars.tensor.std:19 of
msgid ""
"Alternative output tensor in which to place the result. It must have the "
"same shape as the expected output but the type (of the calculated values)"
" will be cast if necessary."
msgstr ""

#: mars.tensor.std:23 of
msgid ""
"Means Delta Degrees of Freedom.  The divisor used in calculations is ``N "
"- ddof``, where ``N`` represents the number of elements. By default "
"`ddof` is zero."
msgstr ""

#: mars.tensor.std:27 of
msgid ""
"If this is set to True, the axes which are reduced are left in the result"
" as dimensions with size one. With this option, the result will broadcast"
" correctly against the input tensor.  If the default value is passed, "
"then `keepdims` will not be passed through to the `std` method of sub-"
"classes of `Tensor`, however any non-default value will be.  If the sub-"
"classes `sum` method does not implement `keepdims` any exceptions will be"
" raised."
msgstr ""

#: mars.tensor.std:27 of
msgid ""
"If this is set to True, the axes which are reduced are left in the result"
" as dimensions with size one. With this option, the result will broadcast"
" correctly against the input tensor."
msgstr ""

#: mars.tensor.std:31 of
msgid ""
"If the default value is passed, then `keepdims` will not be passed "
"through to the `std` method of sub-classes of `Tensor`, however any non-"
"default value will be.  If the sub-classes `sum` method does not "
"implement `keepdims` any exceptions will be raised."
msgstr ""

#: mars.tensor.std:37 of
msgid "The number of chunks to combine."
msgstr ""

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

#: mars.tensor.std:40 of
msgid ""
"**standard_deviation** -- If `out` is None, return a new tensor "
"containing the standard deviation, otherwise return a reference to the "
"output array."
msgstr ""

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

#: mars.tensor.std:44 of
msgid ":func:`var`, :func:`mean`, :func:`nanmean`, :func:`nanstd`, :func:`nanvar`"
msgstr ""

#: mars.tensor.std:47 of
msgid "Notes"
msgstr ""

#: mars.tensor.std:48 of
msgid ""
"The standard deviation is the square root of the average of the squared "
"deviations from the mean, i.e., ``std = sqrt(mean(abs(x - "
"x.mean())**2))``."
msgstr ""

#: mars.tensor.std:51 of
msgid ""
"The average squared deviation is normally calculated as ``x.sum() / N``, "
"where ``N = len(x)``.  If, however, `ddof` is specified, the divisor ``N "
"- ddof`` is used instead. In standard statistical practice, ``ddof=1`` "
"provides an unbiased estimator of the variance of the infinite "
"population. ``ddof=0`` provides a maximum likelihood estimate of the "
"variance for normally distributed variables. The standard deviation "
"computed in this function is the square root of the estimated variance, "
"so even with ``ddof=1``, it will not be an unbiased estimate of the "
"standard deviation per se."
msgstr ""

#: mars.tensor.std:61 of
msgid ""
"Note that, for complex numbers, `std` takes the absolute value before "
"squaring, so that the result is always real and nonnegative."
msgstr ""

#: mars.tensor.std:64 of
msgid ""
"For floating-point input, the *std* is computed using the same precision "
"the input has. Depending on the input data, this can cause the results to"
" be inaccurate, especially for float32 (see example below). Specifying a "
"higher-accuracy accumulator using the `dtype` keyword can alleviate this "
"issue."
msgstr ""

#: mars.tensor.std:71 of
msgid "Examples"
msgstr ""

#: mars.tensor.std:82 of
msgid "In single precision, std() can be inaccurate:"
msgstr ""

#: mars.tensor.std:90 of
msgid "Computing the standard deviation in float64 is more accurate:"
msgstr ""

