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scatterplot: Make 2D scatterplot and linear regression of regressor predictions.

Docstring:

Usage: qiime sample-classifier scatterplot [OPTIONS]

  Make a 2D scatterplot and linear regression of predicted vs. true values for
  a set of samples predicted using a sample regressor.

Inputs:
  --i-predictions ARTIFACT SampleData[RegressorPredictions]
                         Predicted values to plot on y axis. Must be
                         predictions of numeric data produced by a sample
                         regressor.                                 [required]
Parameters:
  --m-truth-file METADATA
  --m-truth-column COLUMN  MetadataColumn[Numeric]
                         Metadata column (true values) to plot on x axis.
                                                                    [required]
  --p-missing-samples TEXT Choices('error', 'ignore')
                         How to handle missing samples in metadata. "error"
                         will fail if missing samples are detected. "ignore"
                         will cause the feature table and metadata to be
                         filtered, so that only samples found in both files
                         are retained.                      [default: 'error']
Outputs:
  --o-visualization VISUALIZATION
                                                                    [required]
Miscellaneous:
  --output-dir PATH      Output unspecified results to a directory
  --verbose / --quiet    Display verbose output to stdout and/or stderr
                         during execution of this action. Or silence output if
                         execution is successful (silence is golden).
  --example-data PATH    Write example data and exit.
  --citations            Show citations and exit.
  --use-cache DIRECTORY  Specify the cache to be used for the intermediate
                         work of this action. If not provided, the default
                         cache under $TMP/qiime2/ will be used.
                         IMPORTANT FOR HPC USERS: If you are on an HPC system
                         and are using parallel execution it is important to
                         set this to a location that is globally accessible to
                         all nodes in the cluster.
  --help                 Show this message and exit.

Import:

from qiime2.plugins.sample_classifier.visualizers import scatterplot

Docstring:

Make 2D scatterplot and linear regression of regressor predictions.

Make a 2D scatterplot and linear regression of predicted vs. true values
for a set of samples predicted using a sample regressor.

Parameters
----------
predictions : SampleData[RegressorPredictions]
    Predicted values to plot on y axis. Must be predictions of numeric data
    produced by a sample regressor.
truth : MetadataColumn[Numeric]
    Metadata column (true values) to plot on x axis.
missing_samples : Str % Choices('error', 'ignore'), optional
    How to handle missing samples in metadata. "error" will fail if missing
    samples are detected. "ignore" will cause the feature table and
    metadata to be filtered, so that only samples found in both files are
    retained.

Returns
-------
visualization : Visualization