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Fix implicitly converted datasets unused when mapping over
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@@ -188,7 +188,8 @@ class ToolEvaluator(object):
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dataset_paths=input_dataset_paths,
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datatypes_registry=self.app.datatypes_registry,
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tool=self.tool,
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name=input.name)
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name=input.name,
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formats=input.formats)
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elif isinstance(input, DataToolParameter):
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# FIXME: We're populating param_dict with conversions when
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@@ -109,7 +109,7 @@ class DatasetMatcher(object):
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self.filter_values = filter_values
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def valid_hda_match(self, hda, check_implicit_conversions=True):
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""" Return False of this parameter can not be matched to the supplied
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""" Return False if this parameter can not be matched to the supplied
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HDA, otherwise return a description of the match (either a
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HdaDirectMatch describing a direct match or a HdaImplicitMatch
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describing an implicit conversion.)
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@@ -76,12 +76,14 @@ class WrappedParameters(object):
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dataset_instances,
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datatypes_registry=trans.app.datatypes_registry,
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tool=tool,
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name=input.name)
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name=input.name,
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formats=input.formats)
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elif isinstance(input, DataToolParameter):
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wrapper_kwds = dict(
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datatypes_registry=trans.app.datatypes_registry,
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tool=tool,
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name=input.name
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name=input.name,
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formats=input.formats
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)
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element_identifier = element_identifier_mapper.identifier(value, input_values)
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if element_identifier:
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@@ -234,7 +234,7 @@ class DatasetFilenameWrapper(ToolParameterValueWrapper):
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def items(self):
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return iter((k, self.get(k)) for k, v in self.metadata.items())
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def __init__(self, dataset, datatypes_registry=None, tool=None, name=None, dataset_path=None, identifier=None):
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def __init__(self, dataset, datatypes_registry=None, tool=None, name=None, dataset_path=None, identifier=None, formats=None):
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if not dataset:
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try:
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# TODO: allow this to work when working with grouping
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@@ -246,6 +246,10 @@ class DatasetFilenameWrapper(ToolParameterValueWrapper):
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# Tool wrappers should not normally be accessing .dataset directly,
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# so we will wrap it and keep the original around for file paths
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# Should we name this .value to maintain consistency with most other ToolParameterValueWrapper?
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if formats:
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target_ext, converted_dataset = dataset.find_conversion_destination(formats)
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if target_ext and converted_dataset:
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dataset = converted_dataset
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self.unsanitized = dataset
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self.dataset = wrap_with_safe_string(dataset, no_wrap_classes=ToolParameterValueWrapper)
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self.metadata = self.MetadataWrapper(dataset.metadata)
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