diff --git a/lib/galaxy/config/sample/datatypes_conf.xml.sample b/lib/galaxy/config/sample/datatypes_conf.xml.sample
index 9671cbf2766c..10876393db4f 100644
--- a/lib/galaxy/config/sample/datatypes_conf.xml.sample
+++ b/lib/galaxy/config/sample/datatypes_conf.xml.sample
@@ -216,6 +216,9 @@
+
+
+
diff --git a/lib/galaxy/config/sample/tool_conf.xml.sample b/lib/galaxy/config/sample/tool_conf.xml.sample
index 31b0bb4e6ef5..57810365641a 100644
--- a/lib/galaxy/config/sample/tool_conf.xml.sample
+++ b/lib/galaxy/config/sample/tool_conf.xml.sample
@@ -79,6 +79,7 @@
+
diff --git a/lib/galaxy/tool_util/toolbox/views/static.py b/lib/galaxy/tool_util/toolbox/views/static.py
index 2eba8eef3f4b..7972cc84e835 100644
--- a/lib/galaxy/tool_util/toolbox/views/static.py
+++ b/lib/galaxy/tool_util/toolbox/views/static.py
@@ -105,7 +105,7 @@ def definition_with_items_to_panel(definition, allow_sections: bool = True, item
f"Failed to find matching section for (id, name) = ({section_def.id}, {section_def.name})"
)
continue
- section = closest_section.copy()
+ section = closest_section.copy(merge_tools=True)
if section_def.id is not None:
section.id = section_def.id
if section_def.name is not None:
diff --git a/lib/galaxy/workflow/modules.py b/lib/galaxy/workflow/modules.py
index 4b5f18bee32c..79aac7f72115 100644
--- a/lib/galaxy/workflow/modules.py
+++ b/lib/galaxy/workflow/modules.py
@@ -126,6 +126,8 @@ class ConditionalStepWhen(BooleanToolParameter):
def to_cwl(value, hda_references, step):
element_identifier = None
+ if isinstance(value, model.HistoryDatasetCollectionAssociation):
+ value = value.collection
if isinstance(value, model.DatasetCollectionElement) and value.hda:
element_identifier = value.element_identifier
value = value.hda
@@ -155,14 +157,13 @@ def to_cwl(value, hda_references, step):
properties, value.dataset.created_from_basename or element_identifier or value.name
)
return properties
- elif hasattr(value, "collection"):
- collection = value.collection
- if collection.collection_type == "list":
- return [to_cwl(dce, hda_references=hda_references, step=step) for dce in collection.dataset_elements]
+ elif isinstance(value, model.DatasetCollection):
+ if value.collection_type == "list":
+ return [to_cwl(dce, hda_references=hda_references, step=step) for dce in value.dataset_elements]
else:
# Could be record or nested lists
rval = {}
- for element in collection.elements:
+ for element in value.elements:
rval[element.element_identifier] = to_cwl(
element.element_object, hda_references=hda_references, step=step
)
diff --git a/test/unit/workflows/test_modules.py b/test/unit/workflows/test_modules.py
index 27955d3d4f96..8e0df5f81624 100644
--- a/test/unit/workflows/test_modules.py
+++ b/test/unit/workflows/test_modules.py
@@ -261,6 +261,19 @@ def test_to_cwl():
assert hda_references == hdas
+def test_to_cwl_nested_collection():
+ hda = model.HistoryDatasetAssociation(create_dataset=True, flush=False)
+ hda.dataset.state = model.Dataset.states.OK
+ dc_inner = model.DatasetCollection(collection_type="list")
+ model.DatasetCollectionElement(collection=dc_inner, element_identifier="inner", element=hda)
+ dc_outer = model.DatasetCollection(collection_type="list:list")
+ model.DatasetCollectionElement(collection=dc_outer, element_identifier="outer", element=dc_inner)
+ hdca = model.HistoryDatasetCollectionAssociation(name="the collection", collection=dc_outer)
+ result = modules.to_cwl(hdca, [], model.WorkflowStep())
+ assert result["outer"][0]["class"] == "File"
+ assert result["outer"][0]["basename"] == "inner"
+
+
class MapOverTestCase(NamedTuple):
data_input: str
step_input_def: Union[str, List[str]]
diff --git a/tools/stats/filtering_1_1_0.xml b/tools/stats/filtering_1_1_0.xml
new file mode 100644
index 000000000000..1a20cf40c947
--- /dev/null
+++ b/tools/stats/filtering_1_1_0.xml
@@ -0,0 +1,103 @@
+
+ data on any column using simple expressions
+
+ operation_0335
+
+
+ python '$__tool_directory__/filtering.py' '$input' '$out_file1' '$inputs' ${input.metadata.columns} "${input.metadata.column_types}" $header_lines
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+.. class:: warningmark
+
+Double equal signs, ==, must be used as *"equal to"* (e.g., **c1 == 'chr22'**)
+
+.. class:: infomark
+
+**TIP:** Attempting to apply a filtering condition may throw exceptions if the data type (e.g., string, integer) in every line of the columns being filtered is not appropriate for the condition (e.g., attempting certain numerical calculations on strings). If an exception is thrown when applying the condition to a line, that line is skipped as invalid for the filter condition. The number of invalid skipped lines is documented in the resulting history item as a "Condition/data issue".
+
+.. class:: infomark
+
+**TIP:** If your data is not TAB delimited, use *Text Manipulation->Convert*
+
+-----
+
+**Syntax**
+
+The filter tool allows you to restrict the dataset using simple conditional statements.
+
+- Columns are referenced with **c** and a **number**. For example, **c1** refers to the first column of a tab-delimited file
+- Make sure that multi-character operators contain no white space ( e.g., **<=** is valid while **< =** is not valid )
+- When using 'equal-to' operator **double equal sign '==' must be used** ( e.g., **c1=='chr1'** )
+- Non-numerical values must be included in single or double quotes ( e.g., **c6=='+'** )
+- Filtering condition can include logical operators, but **make sure operators are all lower case** ( e.g., **(c1!='chrX' and c1!='chrY') or not c6=='+'** )
+
+-----
+
+**Example**
+
+- **c1=='chr1'** selects lines in which the first column is chr1
+- **c3-c2<100*c4** selects lines where subtracting column 3 from column 2 is less than the value of column 4 times 100
+- **len(c2.split(',')) < 4** will select lines where the second column has less than four comma separated elements
+- **c2>=1** selects lines in which the value of column 2 is greater than or equal to 1
+- Numbers should not contain commas - **c2<=44,554,350** will not work, but **c2<=44554350** will
+- Some words in the data can be used, but must be single or double quoted ( e.g., **c3=='exon'** )
+
+
+
+