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volatility: Generate interactive volatility plotΒΆ

Docstring:

Usage: qiime longitudinal volatility [OPTIONS]

  Generate an interactive control chart depicting the longitudinal
  volatility of sample metadata and/or feature frequencies across time (as
  set using the "state_column" parameter). Any numeric metadata column (and
  metadata-transformable artifacts, e.g., alpha diversity results) can be
  plotted on the y-axis, and are selectable using the "metric_column"
  selector. Metric values are averaged to compare across any categorical
  metadata column using the "group_column" selector. Longitudinal volatility
  for individual subjects sampled over time is co-plotted as "spaghetti"
  plots if the "individual_id_column" parameter is used. state_column will
  typically be a measure of time, but any numeric metadata column can be
  used.

Inputs:
  --i-table ARTIFACT FeatureTable[RelativeFrequency]
                         Feature table containing metrics.          [optional]
Parameters:
  --m-metadata-file METADATA...
    (multiple            Sample metadata file containing
     arguments will be   individual-id-column.
     merged)                                                        [required]
  --p-state-column TEXT  Metadata column containing state (time) variable
                         information.                               [required]
  --p-individual-id-column TEXT
                         Metadata column containing IDs for individual
                         subjects.                                  [optional]
  --p-default-group-column TEXT
                         The default metadata column on which to separate
                         groups for comparison (all categorical metadata
                         columns will be available in the visualization).
                                                                    [optional]
  --p-default-metric TEXT
                         Numeric metadata or artifact column to test by
                         default (all numeric metadata columns will be
                         available in the visualization).           [optional]
  --p-yscale TEXT Choices('linear', 'pow', 'sqrt', 'log')
                         y-axis scaling strategy to apply. [default: 'linear']
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.longitudinal.visualizers import volatility

Docstring:

Generate interactive volatility plot

Generate an interactive control chart depicting the longitudinal volatility
of sample metadata and/or feature frequencies across time (as set using the
"state_column" parameter). Any numeric metadata column (and metadata-
transformable artifacts, e.g., alpha diversity results) can be plotted on
the y-axis, and are selectable using the "metric_column" selector. Metric
values are averaged to compare across any categorical metadata column using
the "group_column" selector. Longitudinal volatility for individual
subjects sampled over time is co-plotted as "spaghetti" plots if the
"individual_id_column" parameter is used. state_column will typically be a
measure of time, but any numeric metadata column can be used.

Parameters
----------
metadata : Metadata
    Sample metadata file containing individual_id_column.
state_column : Str
    Metadata column containing state (time) variable information.
individual_id_column : Str, optional
    Metadata column containing IDs for individual subjects.
default_group_column : Str, optional
    The default metadata column on which to separate groups for comparison
    (all categorical metadata columns will be available in the
    visualization).
default_metric : Str, optional
    Numeric metadata or artifact column to test by default (all numeric
    metadata columns will be available in the visualization).
table : FeatureTable[RelativeFrequency], optional
    Feature table containing metrics.
yscale : Str % Choices('linear', 'pow', 'sqrt', 'log'), optional
    y-axis scaling strategy to apply.

Returns
-------
visualization : Visualization