Exemple #1
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    },
    parameter_descriptions={
        'metric': 'The alpha diversity metric to be computed.'
    },
    output_descriptions={
        'alpha_diversity': 'Vector containing per-sample alpha diversities.'
    },
    name='Alpha diversity (phylogenetic)',
    description=("Computes a user-specified phylogenetic alpha diversity "
                 "metric for all samples in a feature table."),
    citations=[citations['faith1992conservation']])

plugin.methods.register_function(
    function=q2_diversity.alpha,
    inputs={'table': FeatureTable[Frequency]},
    parameters={'metric': Str % Choices(alpha.non_phylogenetic_metrics())},
    outputs=[('alpha_diversity', SampleData[AlphaDiversity])],
    input_descriptions={
        'table': ('The feature table containing the samples for which alpha '
                  'diversity should be computed.')
    },
    parameter_descriptions={
        'metric': 'The alpha diversity metric to be computed.'
    },
    output_descriptions={
        'alpha_diversity': 'Vector containing per-sample alpha diversities.'
    },
    name='Alpha diversity',
    description=("Computes a user-specified alpha diversity metric for all "
                 "samples in a feature table."))
Exemple #2
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    },
    parameter_descriptions={
        'metric': 'The alpha diversity metric to be computed.'
    },
    output_descriptions={
        'alpha_diversity': 'Vector containing per-sample alpha diversities.'
    },
    name='Alpha diversity (phylogenetic)',
    description=("Computes a user-specified phylogenetic alpha diversity "
                 "metric for all samples in a feature table.")
)

plugin.methods.register_function(
    function=q2_diversity.alpha,
    inputs={'table': FeatureTable[Frequency] % Properties('uniform-sampling')},
    parameters={'metric': Str % Choices(alpha.non_phylogenetic_metrics())},
    outputs=[('alpha_diversity', SampleData[AlphaDiversity])],
    input_descriptions={
        'table': ('The feature table containing the samples for which alpha '
                  'diversity should be computed.')
    },
    parameter_descriptions={
        'metric': 'The alpha diversity metric to be computed.'
    },
    output_descriptions={
        'alpha_diversity': 'Vector containing per-sample alpha diversities.'
    },
    name='Alpha diversity',
    description=("Computes a user-specified alpha diversity metric for all "
                 "samples in a feature table.")
)