# 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.nanstd.rst:2
msgid "mars.tensor.nanstd"
msgstr ""

#: mars.tensor.nanstd:1 of
msgid ""
"Compute the standard deviation along the specified axis, while ignoring "
"NaNs."
msgstr ""

#: mars.tensor.nanstd:4 of
msgid ""
"Returns the standard deviation, a measure of the spread of a "
"distribution, of the non-NaN tensor elements. The standard deviation is "
"computed for the flattened tensor by default, otherwise over the "
"specified axis."
msgstr ""

#: mars.tensor.nanstd:9 of
msgid ""
"For all-NaN slices or slices with zero degrees of freedom, NaN is "
"returned and a `RuntimeWarning` is raised."
msgstr ""

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

#: mars.tensor.nanstd:12 of
msgid "Calculate the standard deviation of the non-NaN values."
msgstr ""

#: mars.tensor.nanstd:14 of
msgid ""
"Axis along which the standard deviation is computed. The default is to "
"compute the standard deviation of the flattened tensor."
msgstr ""

#: mars.tensor.nanstd:17 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 tensor type."
msgstr ""

#: mars.tensor.nanstd:21 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.nanstd:25 of
msgid ""
"Means Delta Degrees of Freedom.  The divisor used in calculations is ``N "
"- ddof``, where ``N`` represents the number of non-NaN elements.  By "
"default `ddof` is zero."
msgstr ""

#: mars.tensor.nanstd:29 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 original `a`.  If this value is anything but the "
"default it is passed through as-is to the relevant functions of the sub-"
"classes.  If these functions do not have a `keepdims` kwarg, a "
"RuntimeError will be raised."
msgstr ""

#: mars.tensor.nanstd:29 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 original `a`."
msgstr ""

#: mars.tensor.nanstd:33 of
msgid ""
"If this value is anything but the default it is passed through as-is to "
"the relevant functions of the sub-classes.  If these functions do not "
"have a `keepdims` kwarg, a RuntimeError will be raised."
msgstr ""

#: mars.tensor.nanstd:38 of
msgid "The number of chunks to combine."
msgstr ""

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

#: mars.tensor.nanstd:41 of
msgid ""
"**standard_deviation** -- If `out` is None, return a new array containing"
" the standard deviation, otherwise return a reference to the output "
"tensor. If ddof is >= the number of non-NaN elements in a slice or the "
"slice contains only NaNs, then the result for that slice is NaN."
msgstr ""

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

#: mars.tensor.nanstd:47 of
msgid ":func:`var`, :func:`mean`, :func:`std`, :func:`nanvar`, :func:`nanmean`"
msgstr ""

#: mars.tensor.nanstd:50 of
msgid "Notes"
msgstr ""

#: mars.tensor.nanstd:51 of
msgid ""
"The standard deviation is the square root of the average of the squared "
"deviations from the mean: ``std = sqrt(mean(abs(x - x.mean())**2))``."
msgstr ""

#: mars.tensor.nanstd:54 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.nanstd:64 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.nanstd:67 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.nanstd:74 of
msgid "Examples"
msgstr ""

