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
