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alpha-passthrough: Alpha Passthrough (non-phylogenetic)ΒΆ

Docstring:

Usage: qiime diversity-lib alpha-passthrough [OPTIONS]

  Computes a vector of values (one value for each samples in a feature
  table) using the scikit-bio implementation of the selected alpha diversity
  metric.

Inputs:
  --i-table ARTIFACT FeatureTable[Frequency]
                       The feature table containing the samples for which a
                       selected metric should be computed.          [required]
Parameters:
  --p-metric TEXT Choices('strong', 'menhinick', 'robbins',
    'goods_coverage', 'margalef', 'heip_e', 'mcintosh_e', 'lladser_pe',
    'doubles', 'michaelis_menten_fit', 'esty_ci', 'simpson_e', 'chao1_ci',
    'singles', 'berger_parker_d', 'ace', 'gini_index', 'kempton_taylor_q',
    'mcintosh_d', 'dominance', 'fisher_alpha', 'osd', 'enspie', 'brillouin_d',
    'chao1', 'simpson')
                       The alpha diversity metric to be computed.   [required]
Outputs:
  --o-vector ARTIFACT SampleData[AlphaDiversity]
                       Vector containing per-sample values for the chosen
                       metric.                                      [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.
  --help               Show this message and exit.

Import:

from qiime2.plugins.diversity_lib.methods import alpha_passthrough

Docstring:

Alpha Passthrough (non-phylogenetic)

Computes a vector of values (one value for each samples in a feature table)
using the scikit-bio implementation of the selected alpha diversity metric.

Parameters
----------
table : FeatureTable[Frequency]
    The feature table containing the samples for which a selected metric
    should be computed.
metric : Str % Choices('fisher_alpha', 'chao1', 'goods_coverage', 'berger_parker_d', 'mcintosh_d', 'menhinick', 'mcintosh_e', 'kempton_taylor_q', 'margalef', 'chao1_ci', 'osd', 'doubles', 'heip_e', 'michaelis_menten_fit', 'strong', 'esty_ci', 'simpson_e', 'lladser_pe', 'brillouin_d', 'singles', 'robbins', 'enspie', 'gini_index', 'dominance', 'ace', 'simpson')
    The alpha diversity metric to be computed.

Returns
-------
vector : SampleData[AlphaDiversity]
    Vector containing per-sample values for the chosen metric.