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

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).
  --citations          Show citations and exit.
  --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