},
output_descriptions={
'grouped_table':
'A table that has been grouped along the given '
'`axis`. IDs on that axis are replaced by values in '
'the `metadata` column.'
},
name="Group samples or features by a metadata column",
description="Group samples or features in a feature table using metadata "
"to define the mapping of IDs to a group.")
plugin.methods.register_function(
function=q2_feature_table.merge,
inputs={'tables': List[FeatureTable[Frequency]]},
parameters={
'overlap_method': Str % Choices(q2_feature_table.overlap_methods()),
},
outputs=[('merged_table', FeatureTable[Frequency])],
input_descriptions={
'tables': 'The collection of feature tables to be merged.',
},
parameter_descriptions={
'overlap_method': 'Method for handling overlapping ids.',
},
output_descriptions={
'merged_table': ('The resulting merged feature table.'),
},
name="Combine multiple tables",
description="Combines feature tables using the `overlap_method` provided.")
plugin.methods.register_function(
'Along which axis to group. Each ID in the given axis must '
'exist in `metadata`.'
},
output_descriptions={
'grouped_table':
'A table that has been grouped along the given '
'`axis`. IDs on that axis are replaced by values in '
'the `metadata` column.'
},
name="Group samples or features by a metadata column",
description="Group samples or features in a feature table using metadata "
"to define the mapping of IDs to a group.")
i_table, p_overlap_method, o_table = TypeMap({
(FeatureTable[Frequency], Str % Choices(
sorted(q2_feature_table.overlap_methods()))):
FeatureTable[Frequency],
(
FeatureTable[RelativeFrequency],
# We don't want to allow summing of RelativeFrequency tables, so remove
# that option from the overlap methods
Str % Choices(sorted(q2_feature_table.overlap_methods() - {'sum'}))):
FeatureTable[RelativeFrequency]
})
plugin.methods.register_function(
function=q2_feature_table.merge,
inputs={'tables': List[i_table]},
parameters={'overlap_method': p_overlap_method},
outputs=[('merged_table', o_table)],
input_descriptions={
},
output_descriptions={
'grouped_table': 'A table that has been grouped along the given '
'`axis`. IDs on that axis are replaced by values in '
'the `metadata` column.'
},
name="Group samples or features by a metadata column",
description="Group samples or features in a feature table using metadata "
"to define the mapping of IDs to a group."
)
plugin.methods.register_function(
function=q2_feature_table.merge,
inputs={'tables': List[FeatureTable[Frequency]]},
parameters={
'overlap_method': Str % Choices(q2_feature_table.overlap_methods()),
},
outputs=[
('merged_table', FeatureTable[Frequency])],
input_descriptions={
'tables': 'The collection of feature tables to be merged.',
},
parameter_descriptions={
'overlap_method': 'Method for handling overlapping ids.',
},
output_descriptions={
'merged_table': ('The resulting merged feature table.'),
},
name="Combine multiple tables",
description="Combines feature tables using the `overlap_method` provided."
)
