diff --git a/modules/stochastic_tools/doc/content/source/reporters/StatisticsReporter.md b/modules/stochastic_tools/doc/content/source/reporters/StatisticsReporter.md new file mode 100644 index 000000000000..ae984376e7b1 --- /dev/null +++ b/modules/stochastic_tools/doc/content/source/reporters/StatisticsReporter.md @@ -0,0 +1,121 @@ +# StatisticsReporter + +!syntax description /Reporters/StatisticsReporter + +## Description + +The `StatisticsReporter` object computes statistical values for each vector of +`VectorPostprocessor` (VPP) objects or support values from Reporters. The results are output in +values with names based on the input data and the desired statistic calculation. Optionally +confidence level intervals can be computed. + +## Statistics + +The statistics to compute are indicated by the [!param](/Reporters/StatisticsReporter/compute) +parameter, which can contain multiple values as listed below. Note that multiple +statistical measures can be computed simultaneously by passing in more than one to the input +parameter. The current statistical measures the `StatisticsReporter` can compute are: + +- +minimum+ + + `compute = min`\\ + Computes the minimum value for the supplied vectors. + +- +maximum+ + + `compute = max`\\ + Computes the maximum value for the supplied vectors. + +- +sum+ + + `compute = sum`\\ + Computes the sum ($\Sigma$) of the supplied vectors $\vec{v}$, where $N$ is the length of the vector: + + !equation + \Sigma = \sum_{i=1}^N{v_i} + +- +mean+ + + `compute = average`\\ + Computes the average ($\bar{v}$) of the supplied vectors $\vec{v}$: + + !equation + \bar{v} = \frac{\sum_{i=1}^{N}{v_i}}{N} + +- +standard deviation+ + + `compute = stddev`\\ + Computes the standard deviation ($\sigma$) of the supplied vectors $\vec{v}$: + + !equation + \sigma = \sqrt{\frac{\sum_{i=1}^{N}{(v_i - \bar{v})^2}}{N-1}} + +- +L2-Norm+ + + `compute = norm2`\\ + Computes the L2-norm, $|v|_2$ of the supplied vectors $\vec{v}$, this is also known as the + Euclidean Norm or the "distance": + + !equation + |v|_2 = \sqrt{\sum_{i=1}^{N}{{v_i}^2}} + +- +standard error+ + + `compute = stderr`\\ + Computes the standard error ($\sigma_{\bar{v}}$) of the supplied vectors $\vec{v}$: + + !equation + \sigma_{\bar{v}} = \frac{\sigma}{\sqrt{N}} + +- +ratio+ + + `compute = ratio`\\ + Computes the ratio of the maximum to the minimu of the supplied data. + + + +## Confidence Levels + +Bootstrap confidence level intervals, as defined by [!cite](tibshirani1993introduction), are enabled +by specifying the desired levels using the +[!param](/Reporters/StatisticsReporter/ci_levels) parameter and setting +the method of calculation using the +[!param](/Reporters/StatisticsReporter/ci_method). +The levels listed should be in the range (0, 1). For example, the levels 0.05, 0.95 result in the +computation of the 0.05, 0.95 confidence level intervals. + +Enabling the confidence level intervals will compute the intervals for each level and each statistic +and the result will appear in the same output vector as the associated statistic calculation. + +The available methods include the following: + +- +percentile+: Percentile bootstrap method as defined in Ch. 13 of [!cite](tibshirani1993introduction). + +## Example 1: Statistics + +The following input file snippet demonstrates how to compute various statistics using the +`StatisticsReporter` object. + +!listing reporters/statistics/statistics.i block=Reporters + +This block results in the following JSON file output. + +!listing reporters/statistics/gold/statistics_out.json + + +## Example 2: Confidence Levels + +The following input file snippet demonstrates how to compute various statistics and +confidence levels using the `StatisticsReporter` object. + +!listing reporters/bootstrap_statistics/percentile/percentile.i block=Reporters + +This block results in the following JSON file. + +!listing reporters/bootstrap_statistics/percentile/gold/percentile_out.json + +!syntax parameters /Reporters/StatisticsReporter + +!syntax inputs /Reporters/StatisticsReporter + +!syntax children /Reporters/StatisticsReporter diff --git a/modules/stochastic_tools/doc/content/source/vectorpostprocessors/PolynomialChaosData.md b/modules/stochastic_tools/doc/content/source/vectorpostprocessors/PolynomialChaosData.md index 23f4380dabf7..7f6d1e037da3 100644 --- a/modules/stochastic_tools/doc/content/source/vectorpostprocessors/PolynomialChaosData.md +++ b/modules/stochastic_tools/doc/content/source/vectorpostprocessors/PolynomialChaosData.md @@ -1 +1,23 @@ -!template load file=stubs/moose_object.md.template name=PolynomialChaosData syntax=/VectorPostprocessors/PolynomialChaosData \ No newline at end of file +# PolynomialChaosData + +!alert construction title=Undocumented Class +The PolynomialChaosData has not been documented. The content listed below should be used as a starting point for +documenting the class, which includes the typical automatic documentation associated with a +MooseObject; however, what is contained is ultimately determined by what is necessary to make the +documentation clear for users. + +!syntax description /VectorPostprocessors/PolynomialChaosData + +## Overview + +!! Replace these lines with information regarding the PolynomialChaosData object. + +## Example Input File Syntax + +!! Describe and include an example of how to use the PolynomialChaosData object. + +!syntax parameters /VectorPostprocessors/PolynomialChaosData + +!syntax inputs /VectorPostprocessors/PolynomialChaosData + +!syntax children /VectorPostprocessors/PolynomialChaosData diff --git a/modules/stochastic_tools/doc/content/source/vectorpostprocessors/Statistics.md b/modules/stochastic_tools/doc/content/source/vectorpostprocessors/Statistics.md index 8555ea7ce354..e22f4ac28bd7 100644 --- a/modules/stochastic_tools/doc/content/source/vectorpostprocessors/Statistics.md +++ b/modules/stochastic_tools/doc/content/source/vectorpostprocessors/Statistics.md @@ -1,129 +1,4 @@ # Statistics -!syntax description /VectorPostprocessors/Statistics - -## Description - -The `Statistics` object computes statistical values for each vector of other -`VectorPostprocessor` (VPP) objects. The results are output in vectors that are assigned names -based on the VPP and vector name (object-vector) and each entry in the vector corresponding -the the desired statistics and optionally confidence level intervals. - -The first column, named `stat_type` and contains an unique integer identifier for the type of -statistical measure computed and the confidence levels, if computed. - -## Statistics - -The statistics to compute are indicated by the -[!param](/VectorPostprocessors/Statistics/compute) parameter, which can contain -multiple values as listed below. This list also includes the associated numeric identifier -that is included in the `stat_type` vector output the VPP object. - -measures are chosen using the `stats` input parameter. Note that multiple -statistical measures can be computed simultaneously by passing in more than one to the `stats` input -parameter. The current statistical measures (and their `stat_type` identifier) the -`StatisticsPostprocessor` can compute are: - -- +minimum (0)+ - - `compute = min`\\ - Computes the minimum value for the supplied vectors. - -- +maximum (1)+ - - `compute = max`\\ - Computes the maximum value for the supplied vectors. - -- +sum (2)+ - - `compute = sum`\\ - Computes the sum ($\Sigma$) of the supplied vectors $\vec{v}$, where $N$ is the length of the vector: - - !equation - \Sigma = \sum_{i=1}^N{v_i} - -- +mean (3)+ - - `compute = average`\\ - Computes the average ($\bar{v}$) of the supplied vectors $\vec{v}$: - - !equation - \bar{v} = \frac{\sum_{i=1}^{N}{v_i}}{N} - -- +standard deviation (4)+ - - `compute = stddev`\\ - Computes the standard deviation ($\sigma$) of the supplied vectors $\vec{v}$: - - !equation - \sigma = \sqrt{\frac{\sum_{i=1}^{N}{(v_i - \bar{v})^2}}{N-1}} - -- +2-Norm (5)+ - - `compute = norm2`\\ - Computes the 2-norm, $|v|_2$ of the supplied vectors $\vec{v}$, this is also known as the - Euclidean Norm or the "distance": - - !equation - |v|_2 = \sqrt{\sum_{i=1}^{N}{{v_i}^2}} - -- +standard error (6)+ - - `compute = stderr`\\ - Computes the standard error ($\sigma_{\bar{v}}$) of the supplied vectors $\vec{v}$: - - !equation - \sigma_{\bar{v}} = \frac{\sigma}{\sqrt{N}} - - -## Confidence Levels - -Bootstrap confidence level intervals, as defined by [!cite](tibshirani1993introduction), are enabled -by specifying the desired levels using the -[!param](/VectorPostprocessors/Statistics/ci_levels) parameter and setting -the method of calculation using the -[!param](/VectorPostprocessors/Statistics/ci_method). -The levels listed should be in the range (0, 0.5]. For example, the levels 0.05, 0.1, and 0.5 provided -result in the computation of the 0.05, 0.1, 0.5, 0.9, and 0.95 confidence level intervals. - -Enabling the confidence level intervals will compute the intervals for each level and each statistic -and the result will appear in the same output vector as the associated statistic calculation. The -`stat_type` vector will include decimal values where the ones place indicates the statistic -computed and the decimal corresponds with the confidence level. - -The available methods include the following: - -- +percentile+: Percentile bootstrap method as defined in Ch. 13 of [!cite](tibshirani1993introduction). - -## Example 1: Statistics - -The following input file snippet demonstrates how to compute various statistics using the -`Statistics` object. - -!listing statistics.i block=VectorPostprocessors - -This block results in the following CSV file for the "stats" block of the input file. Notice -the first column corresponds with the numeric identifier for the statistics being computed. - -!listing statistics/gold/statistics_out_stats_0001.csv - - -## Example 2: Confidence Levels - -The following input file snippet demonstrates how to compute various statistics and -confidence levels using the `Statistics` object - -!listing bootstrap_statistics/percentile/percentile.i block=VectorPostprocessors - -This block results in the following CSV file for the "stats" block of the input file. Notice -the first column corresponds with the numeric identifier for the statistics being computed. - -!listing bootstrap_statistics/percentile/gold/percentile_out_stats_0001.csv - -!syntax parameters /VectorPostprocessors/Statistics - -!syntax inputs /VectorPostprocessors/Statistics - -!syntax children /VectorPostprocessors/Statistics - -!bibtex bibliography +!alert warning title=Deprecated Object +The `Statistics` objects has been replaced by [reporters/StatisticsReporter.md].