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September 2014

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commit/galaxy-central: dannon: Merged in BjoernGruening/galaxy-central-5/BjoernGruening/add-install_dir-to-perl5lib-and-path-bef-1410949639333 (pull request #499)
by commits-noreply＠bitbucket.org 22 Sep '14

22 Sep '14

1 new commit in galaxy-central: https://bitbucket.org/galaxy/galaxy-central/commits/e3b16462112b/ Changeset: e3b16462112b User: dannon Date: 2014-09-22 15:09:07+00:00 Summary: Merged in BjoernGruening/galaxy-central-5/BjoernGruening/add-install_dir-to-perl5lib-and-path-bef-1410949639333 (pull request #499) Add $INSTALL_DIR to PERL5LIB and PATH before starting to install libraries. A few packages need this in order to recognise previous installed packages. Affected #: 1 file diff -r df92b55d194a4d67a1b863c85044eb91c138c74b -r e3b16462112b2ab8150564e183213048e7c027da lib/tool_shed/galaxy_install/tool_dependencies/recipe/step_handler.py --- a/lib/tool_shed/galaxy_install/tool_dependencies/recipe/step_handler.py +++ b/lib/tool_shed/galaxy_install/tool_dependencies/recipe/step_handler.py @@ -1105,6 +1105,8 @@ # If set to a true value then MakeMaker's prompt function will always # return the default without waiting for user input. cmd = '''PERL_MM_USE_DEFAULT=1; export PERL_MM_USE_DEFAULT; ''' + cmd += 'export PERL5LIB=$INSTALL_DIR/lib/perl5:$PERL5LIB;' + cmd += 'export PATH=$INSTALL_DIR/bin:$PATH;' if perl_package.find( '://' ) != -1: # We assume a URL to a gem file. url = perl_package Repository URL: https://bitbucket.org/galaxy/galaxy-central/ -- This is a commit notification from bitbucket.org. You are receiving this because you have the service enabled, addressing the recipient of this email.

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commit/galaxy-central: 2 new changesets
by commits-noreply＠bitbucket.org 22 Sep '14

22 Sep '14

2 new commits in galaxy-central: https://bitbucket.org/galaxy/galaxy-central/commits/4969f6502d42/ Changeset: 4969f6502d42 Branch: BjoernGruening/add-install_dir-to-perl5lib-and-path-bef-1410949639333 User: BjoernGruening Date: 2014-09-17 10:27:56+00:00 Summary: Add $INSTALL_DIR to PERL5LIB and PATH before starting to install libraries. A few packages need this in order to recognise previous installed packages. Affected #: 1 file diff -r 02738142b8cf5e0372ac5c2b46eeff5f0ab8e87a -r 4969f6502d423feb580946d6b4812a477cff77b4 lib/tool_shed/galaxy_install/tool_dependencies/recipe/step_handler.py --- a/lib/tool_shed/galaxy_install/tool_dependencies/recipe/step_handler.py +++ b/lib/tool_shed/galaxy_install/tool_dependencies/recipe/step_handler.py @@ -1105,6 +1105,8 @@ # If set to a true value then MakeMaker's prompt function will always # return the default without waiting for user input. cmd = '''PERL_MM_USE_DEFAULT=1; export PERL_MM_USE_DEFAULT; ''' + cmd += 'export PERL5LIB=$INSTALL_DIR/lib/perl5:$PERL5LIB;' + cmd += 'export PATH=$INSTALL_DIR/bin:$PATH;' if perl_package.find( '://' ) != -1: # We assume a URL to a gem file. url = perl_package https://bitbucket.org/galaxy/galaxy-central/commits/e3b16462112b/ Changeset: e3b16462112b User: dannon Date: 2014-09-22 15:09:07+00:00 Summary: Merged in BjoernGruening/galaxy-central-5/BjoernGruening/add-install_dir-to-perl5lib-and-path-bef-1410949639333 (pull request #499) Add $INSTALL_DIR to PERL5LIB and PATH before starting to install libraries. A few packages need this in order to recognise previous installed packages. Affected #: 1 file diff -r df92b55d194a4d67a1b863c85044eb91c138c74b -r e3b16462112b2ab8150564e183213048e7c027da lib/tool_shed/galaxy_install/tool_dependencies/recipe/step_handler.py --- a/lib/tool_shed/galaxy_install/tool_dependencies/recipe/step_handler.py +++ b/lib/tool_shed/galaxy_install/tool_dependencies/recipe/step_handler.py @@ -1105,6 +1105,8 @@ # If set to a true value then MakeMaker's prompt function will always # return the default without waiting for user input. cmd = '''PERL_MM_USE_DEFAULT=1; export PERL_MM_USE_DEFAULT; ''' + cmd += 'export PERL5LIB=$INSTALL_DIR/lib/perl5:$PERL5LIB;' + cmd += 'export PATH=$INSTALL_DIR/bin:$PATH;' if perl_package.find( '://' ) != -1: # We assume a URL to a gem file. url = perl_package Repository URL: https://bitbucket.org/galaxy/galaxy-central/ -- This is a commit notification from bitbucket.org. You are receiving this because you have the service enabled, addressing the recipient of this email.

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commit/galaxy-central: jmchilton: Merged in jmchilton/galaxy-central-fork-1 (pull request #496)
by commits-noreply＠bitbucket.org 22 Sep '14

22 Sep '14

1 new commit in galaxy-central: https://bitbucket.org/galaxy/galaxy-central/commits/df92b55d194a/ Changeset: df92b55d194a User: jmchilton Date: 2014-09-22 14:24:39+00:00 Summary: Merged in jmchilton/galaxy-central-fork-1 (pull request #496) More consistent tool API for map/reduce operations. Affected #: 4 files diff -r 42f677bab2e4880b62758614fcb2c7dc27013788 -r df92b55d194a4d67a1b863c85044eb91c138c74b lib/galaxy/tools/parameters/basic.py --- a/lib/galaxy/tools/parameters/basic.py +++ b/lib/galaxy/tools/parameters/basic.py @@ -1887,6 +1887,11 @@ elif isinstance( value, dict ) and 'src' in value and 'id' in value: if value['src'] == 'hda': rval = trans.sa_session.query( trans.app.model.HistoryDatasetAssociation ).get( trans.app.security.decode_id(value['id']) ) + elif value['src'] == 'hdca': + decoded_id = trans.app.security.decode_id( value[ 'id' ] ) + rval = trans.sa_session.query( trans.app.model.HistoryDatasetCollectionAssociation ).get( decoded_id ) + else: + raise ValueError("Unknown input source %s passed to job submission API." % value['src']) elif str( value ).startswith( "__collection_reduce__|" ): encoded_id = str( value )[ len( "__collection_reduce__|" ): ] decoded_id = trans.app.security.decode_id( encoded_id ) @@ -1903,6 +1908,10 @@ raise ValueError( "The previously selected dataset has been previously deleted" ) if hasattr( v, "dataset" ) and v.dataset.state in [ galaxy.model.Dataset.states.ERROR, galaxy.model.Dataset.states.DISCARDED ]: raise ValueError( "The previously selected dataset has entered an unusable state" ) + if not self.multiple: + if len( values ) > 1: + raise ValueError( "More than one dataset supplied to single input dataset parameter.") + rval = values[ 0 ] return rval def to_string( self, value, app ): diff -r 42f677bab2e4880b62758614fcb2c7dc27013788 -r df92b55d194a4d67a1b863c85044eb91c138c74b lib/galaxy/tools/parameters/meta.py --- a/lib/galaxy/tools/parameters/meta.py +++ b/lib/galaxy/tools/parameters/meta.py @@ -14,7 +14,33 @@ execution). """ + def classify_unmodified_parameter( input_key ): + value = incoming[ input_key ] + if isinstance( value, dict ) and 'values' in value: + # Explicit meta wrapper for inputs... + is_batch = value.get( 'batch', False ) + is_linked = value.get( 'linked', True ) + if is_batch and is_linked: + classification = permutations.input_classification.MATCHED + elif is_batch: + classification = permutations.input_classification.MULTIPLIED + else: + classification = permutations.input_classification.SINGLE + if __collection_multirun_parameter( value ): + collection_value = value[ 'values' ][ 0 ] + values = __expand_collection_parameter( trans, input_key, collection_value, collections_to_match ) + else: + values = value[ 'values' ] + else: + classification = permutations.input_classification.SINGLE + values = value + return classification, values + + from galaxy.dataset_collections import matching + collections_to_match = matching.CollectionsToMatch() + def classifier( input_key ): + collection_multirun_key = "%s|__collection_multirun__" % input_key multirun_key = "%s|__multirun__" % input_key if multirun_key in incoming: multi_value = util.listify( incoming[ multirun_key ] ) @@ -24,41 +50,12 @@ if len( multi_value ) == 0: multi_value = None return permutations.input_classification.SINGLE, multi_value[ 0 ] + elif collection_multirun_key in incoming: + incoming_val = incoming[ collection_multirun_key ] + values = __expand_collection_parameter( trans, input_key, incoming_val, collections_to_match ) + return permutations.input_classification.MATCHED, values else: - return permutations.input_classification.SINGLE, incoming[ input_key ] - - from galaxy.dataset_collections import matching - collections_to_match = matching.CollectionsToMatch() - - def collection_classifier( input_key ): - multirun_key = "%s|__collection_multirun__" % input_key - if multirun_key in incoming: - incoming_val = incoming[ multirun_key ] - # If subcollectin multirun of data_collection param - value will - # be "hdca_id|subcollection_type" else it will just be hdca_id - if "|" in incoming_val: - encoded_hdc_id, subcollection_type = incoming_val.split( "|", 1 ) - else: - try: - src = incoming_val[ "src" ] - if src != "hdca": - raise exceptions.ToolMetaParameterException( "Invalid dataset collection source type %s" % src ) - encoded_hdc_id = incoming_val[ "id" ] - except TypeError: - encoded_hdc_id = incoming_val - subcollection_type = None - hdc_id = trans.app.security.decode_id( encoded_hdc_id ) - hdc = trans.sa_session.query( model.HistoryDatasetCollectionAssociation ).get( hdc_id ) - collections_to_match.add( input_key, hdc, subcollection_type=subcollection_type ) - if subcollection_type is not None: - from galaxy.dataset_collections import subcollections - subcollection_elements = subcollections.split_dataset_collection_instance( hdc, subcollection_type ) - return permutations.input_classification.MATCHED, subcollection_elements - else: - hdas = hdc.collection.dataset_instances - return permutations.input_classification.MATCHED, hdas - else: - return permutations.input_classification.SINGLE, incoming[ input_key ] + return classify_unmodified_parameter( input_key ) # Stick an unexpanded version of multirun keys so they can be replaced, # by expand_mult_inputs. @@ -76,20 +73,59 @@ multirun_found = False collection_multirun_found = False for key, value in incoming.iteritems(): - multirun_found = try_replace_key( key, "|__multirun__" ) or multirun_found - collection_multirun_found = try_replace_key( key, "|__collection_multirun__" ) or collection_multirun_found + if isinstance( value, dict ) and 'values' in value: + batch = value.get( 'batch', False ) + if batch: + if __collection_multirun_parameter( value ): + collection_multirun_found = True + else: + multirun_found = True + else: + continue + else: + # Old-style batching (remove someday? - pretty hacky and didn't live in API long) + try_replace_key( key, "|__multirun__" ) or multirun_found + try_replace_key( key, "|__collection_multirun__" ) or collection_multirun_found - if sum( [ 1 if f else 0 for f in [ multirun_found, collection_multirun_found ] ] ) > 1: - # In theory doable, but to complicated for a first pass. - message = "Cannot specify parallel execution across both multiple datasets and dataset collections." - raise exceptions.ToolMetaParameterException( message ) + expanded_incomings = permutations.expand_multi_inputs( incoming_template, classifier ) + if collections_to_match.has_collections(): + collection_info = trans.app.dataset_collections_service.match_collections( collections_to_match ) + else: + collection_info = None + return expanded_incomings, collection_info - if multirun_found: - return permutations.expand_multi_inputs( incoming_template, classifier ), None + +def __expand_collection_parameter( trans, input_key, incoming_val, collections_to_match ): + # If subcollectin multirun of data_collection param - value will + # be "hdca_id|subcollection_type" else it will just be hdca_id + if "|" in incoming_val: + encoded_hdc_id, subcollection_type = incoming_val.split( "|", 1 ) else: - expanded_incomings = permutations.expand_multi_inputs( incoming_template, collection_classifier ) - if collections_to_match.has_collections(): - collection_info = trans.app.dataset_collections_service.match_collections( collections_to_match ) - else: - collection_info = None - return expanded_incomings, collection_info + try: + src = incoming_val[ "src" ] + if src != "hdca": + raise exceptions.ToolMetaParameterException( "Invalid dataset collection source type %s" % src ) + encoded_hdc_id = incoming_val[ "id" ] + subcollection_type = incoming_val.get( 'map_over_type', None ) + except TypeError: + encoded_hdc_id = incoming_val + subcollection_type = None + hdc_id = trans.app.security.decode_id( encoded_hdc_id ) + hdc = trans.sa_session.query( model.HistoryDatasetCollectionAssociation ).get( hdc_id ) + collections_to_match.add( input_key, hdc, subcollection_type=subcollection_type ) + if subcollection_type is not None: + from galaxy.dataset_collections import subcollections + subcollection_elements = subcollections.split_dataset_collection_instance( hdc, subcollection_type ) + return subcollection_elements + else: + hdas = hdc.collection.dataset_instances + return hdas + + +def __collection_multirun_parameter( value ): + batch_values = util.listify( value[ 'values' ] ) + if len( batch_values ) == 1: + batch_over = batch_values[ 0 ] + if isinstance( batch_over, dict ) and ('src' in batch_over) and (batch_over[ 'src' ] == 'hdca'): + return True + return False diff -r 42f677bab2e4880b62758614fcb2c7dc27013788 -r df92b55d194a4d67a1b863c85044eb91c138c74b test/api/test_tools.py --- a/test/api/test_tools.py +++ b/test/api/test_tools.py @@ -109,6 +109,35 @@ output1_content = self.dataset_populator.get_history_dataset_content( history_id, dataset=output1 ) self.assertEqual( output1_content.strip(), "Cat1Test" ) + @skip_without_tool( "cat1" ) + def test_run_cat1_listified_param( self ): + # Run simple non-upload tool with an input data parameter. + history_id = self.dataset_populator.new_history() + new_dataset = self.dataset_populator.new_dataset( history_id, content='Cat1Testlistified' ) + inputs = dict( + input1=[dataset_to_param( new_dataset )], + ) + outputs = self._cat1_outputs( history_id, inputs=inputs ) + self.assertEquals( len( outputs ), 1 ) + output1 = outputs[ 0 ] + output1_content = self.dataset_populator.get_history_dataset_content( history_id, dataset=output1 ) + self.assertEqual( output1_content.strip(), "Cat1Testlistified" ) + + @skip_without_tool( "cat1" ) + def test_run_cat1_single_meta_wrapper( self ): + # Wrap input in a no-op meta parameter wrapper like Sam is planning to + # use for all UI API submissions. + history_id = self.dataset_populator.new_history() + new_dataset = self.dataset_populator.new_dataset( history_id, content='123' ) + inputs = dict( + input1={ 'batch': False, 'values': [ dataset_to_param( new_dataset ) ] }, + ) + outputs = self._cat1_outputs( history_id, inputs=inputs ) + self.assertEquals( len( outputs ), 1 ) + output1 = outputs[ 0 ] + output1_content = self.dataset_populator.get_history_dataset_content( history_id, dataset=output1 ) + self.assertEqual( output1_content.strip(), "123" ) + @skip_without_tool( "validation_default" ) def test_validation( self ): history_id = self.dataset_populator.new_history() @@ -118,6 +147,20 @@ response = self._run( "validation_default", history_id, inputs ) self._assert_status_code_is( response, 400 ) + @skip_without_tool( "collection_paired_test" ) + def test_collection_parameter( self ): + history_id = self.dataset_populator.new_history() + hdca_id = self.__build_pair( history_id, [ "123", "456" ] ) + inputs = { + "f1": { "src": "hdca", "id": hdca_id }, + } + output = self._run( "collection_paired_test", history_id, inputs, assert_ok=True ) + assert len( output[ 'jobs' ] ) == 1 + assert len( output[ 'implicit_collections' ] ) == 0 + assert len( output[ 'outputs' ] ) == 1 + contents = self.dataset_populator.get_history_dataset_content( history_id, hid=4 ) + assert contents.strip() == "123\n456", contents + @skip_without_tool( "cat1" ) def test_run_cat1_with_two_inputs( self ): # Run tool with an multiple data parameter and grouping (repeat) @@ -135,16 +178,31 @@ self.assertEqual( output1_content.strip(), "Cat1Test\nCat2Test" ) @skip_without_tool( "cat1" ) + def test_multirun_cat1_legacy( self ): + history_id, datasets = self._prepare_cat1_multirun() + inputs = { + "input1|__multirun__": datasets, + } + self._check_cat1_multirun( history_id, inputs ) + + @skip_without_tool( "cat1" ) def test_multirun_cat1( self ): + history_id, datasets = self._prepare_cat1_multirun() + inputs = { + "input1": { + 'batch': True, + 'values': datasets, + }, + } + self._check_cat1_multirun( history_id, inputs ) + + def _prepare_cat1_multirun( self ): history_id = self.dataset_populator.new_history() new_dataset1 = self.dataset_populator.new_dataset( history_id, content='123' ) new_dataset2 = self.dataset_populator.new_dataset( history_id, content='456' ) - inputs = { - "input1|__multirun__": [ - dataset_to_param( new_dataset1 ), - dataset_to_param( new_dataset2 ), - ], - } + return history_id, [ dataset_to_param( new_dataset1 ), dataset_to_param( new_dataset2 ) ] + + def _check_cat1_multirun( self, history_id, inputs ): outputs = self._cat1_outputs( history_id, inputs=inputs ) self.assertEquals( len( outputs ), 2 ) output1 = outputs[ 0 ] @@ -154,6 +212,20 @@ self.assertEquals( output1_content.strip(), "123" ) self.assertEquals( output2_content.strip(), "456" ) + @skip_without_tool( "random_lines1" ) + def test_multirun_non_data_parameter( self ): + history_id = self.dataset_populator.new_history() + new_dataset1 = self.dataset_populator.new_dataset( history_id, content='123\n456\n789' ) + inputs = { + 'input': dataset_to_param( new_dataset1 ), + 'num_lines': { 'batch': True, 'values': [ 1, 2, 3 ] } + } + outputs = self._run_and_get_outputs( 'random_lines1', history_id, inputs ) + # Assert we have three outputs with 1, 2, and 3 lines respectively. + assert len( outputs ) == 3 + outputs_contents = [ self.dataset_populator.get_history_dataset_content( history_id, dataset=o ).strip() for o in outputs ] + assert sorted( map( lambda c: len( c.split( "\n" ) ), outputs_contents ) ) == [ 1, 2, 3 ] + @skip_without_tool( "cat1" ) def test_multirun_in_repeat( self ): history_id = self.dataset_populator.new_history() @@ -177,35 +249,60 @@ self.assertEquals( output2_content.strip(), "Common\n456" ) @skip_without_tool( "cat1" ) - def test_multirun_on_multiple_inputs( self ): - history_id = self.dataset_populator.new_history() - new_dataset1 = self.dataset_populator.new_dataset( history_id, content='123' ) - new_dataset2 = self.dataset_populator.new_dataset( history_id, content='456' ) - new_dataset3 = self.dataset_populator.new_dataset( history_id, content='789' ) - new_dataset4 = self.dataset_populator.new_dataset( history_id, content='0ab' ) + def test_multirun_on_multiple_inputs_legacy( self ): + history_id, first_two, second_two = self._setup_two_multiruns() inputs = { - "input1|__multirun__": [ - dataset_to_param( new_dataset1 ), - dataset_to_param( new_dataset2 ), - ], - 'queries_0|input2|__multirun__': [ - dataset_to_param( new_dataset3 ), - dataset_to_param( new_dataset4 ), - ], + "input1|__multirun__": first_two, + 'queries_0|input2|__multirun__': second_two, } outputs = self._cat1_outputs( history_id, inputs=inputs ) self.assertEquals( len( outputs ), 2 ) outputs_contents = [ self.dataset_populator.get_history_dataset_content( history_id, dataset=o ).strip() for o in outputs ] assert "123\n789" in outputs_contents assert "456\n0ab" in outputs_contents - # TODO: Once cross production (instead of linking inputs) is an option - # again redo test with these checks... - # self.assertEquals( len( outputs ), 4 ) - # assert "123\n0ab" in outputs_contents - # assert "456\n789" in outputs_contents @skip_without_tool( "cat1" ) - def test_map_over_collection( self ): + def test_multirun_on_multiple_inputs( self ): + history_id, first_two, second_two = self._setup_two_multiruns() + inputs = { + "input1": { 'batch': True, 'values': first_two }, + 'queries_0|input2': { 'batch': True, 'values': second_two }, + } + outputs = self._cat1_outputs( history_id, inputs=inputs ) + self.assertEquals( len( outputs ), 2 ) + outputs_contents = [ self.dataset_populator.get_history_dataset_content( history_id, dataset=o ).strip() for o in outputs ] + assert "123\n789" in outputs_contents + assert "456\n0ab" in outputs_contents + + @skip_without_tool( "cat1" ) + def test_multirun_on_multiple_inputs_unlinked( self ): + history_id, first_two, second_two = self._setup_two_multiruns() + inputs = { + "input1": { 'batch': True, 'linked': False, 'values': first_two }, + 'queries_0|input2': { 'batch': True, 'linked': False, 'values': second_two }, + } + outputs = self._cat1_outputs( history_id, inputs=inputs ) + outputs_contents = [ self.dataset_populator.get_history_dataset_content( history_id, dataset=o ).strip() for o in outputs ] + self.assertEquals( len( outputs ), 4 ) + assert "123\n789" in outputs_contents + assert "456\n0ab" in outputs_contents + assert "123\n0ab" in outputs_contents + assert "456\n789" in outputs_contents + + def _setup_two_multiruns( self ): + history_id = self.dataset_populator.new_history() + new_dataset1 = self.dataset_populator.new_dataset( history_id, content='123' ) + new_dataset2 = self.dataset_populator.new_dataset( history_id, content='456' ) + new_dataset3 = self.dataset_populator.new_dataset( history_id, content='789' ) + new_dataset4 = self.dataset_populator.new_dataset( history_id, content='0ab' ) + return ( + history_id, + [ dataset_to_param( new_dataset1 ), dataset_to_param( new_dataset2 ) ], + [ dataset_to_param( new_dataset3 ), dataset_to_param( new_dataset4 ) ] + ) + + @skip_without_tool( "cat1" ) + def test_map_over_collection_legacy( self ): history_id = self.dataset_populator.new_history() hdca_id = self.__build_pair( history_id, [ "123", "456" ] ) inputs = { @@ -214,6 +311,18 @@ # first, next test method tests other. "input1|__collection_multirun__": hdca_id, } + self._run_and_check_simple_collection_mapping( history_id, inputs ) + + @skip_without_tool( "cat1" ) + def test_map_over_collection( self ): + history_id = self.dataset_populator.new_history() + hdca_id = self.__build_pair( history_id, [ "123", "456" ] ) + inputs = { + "input1": { 'batch': True, 'values': [ { 'src': 'hdca', 'id': hdca_id } ] }, + } + self._run_and_check_simple_collection_mapping( history_id, inputs ) + + def _run_and_check_simple_collection_mapping( self, history_id, inputs ): create = self._run_cat1( history_id, inputs=inputs, assert_ok=True ) outputs = create[ 'outputs' ] jobs = create[ 'jobs' ] @@ -229,12 +338,24 @@ self.assertEquals( output2_content.strip(), "456" ) @skip_without_tool( "cat1" ) - def test_map_over_nested_collections( self ): + def test_map_over_nested_collections_legacy( self ): history_id = self.dataset_populator.new_history() hdca_id = self.__build_nested_list( history_id ) inputs = { "input1|__collection_multirun__": dict( src="hdca", id=hdca_id ), } + self._check_simple_cat1_over_nested_collections( history_id, inputs ) + + @skip_without_tool( "cat1" ) + def test_map_over_nested_collections( self ): + history_id = self.dataset_populator.new_history() + hdca_id = self.__build_nested_list( history_id ) + inputs = { + "input1": { 'batch': True, 'values': [ dict( src="hdca", id=hdca_id ) ] }, + } + self._check_simple_cat1_over_nested_collections( history_id, inputs ) + + def _check_simple_cat1_over_nested_collections( self, history_id, inputs ): create = self._run_cat1( history_id, inputs=inputs, assert_ok=True ) outputs = create[ 'outputs' ] jobs = create[ 'jobs' ] @@ -257,7 +378,7 @@ self.assertEquals( outputs[ 0 ][ "id" ], first_object_forward_element[ "object" ][ "id" ] ) @skip_without_tool( "cat1" ) - def test_map_over_two_collections( self ): + def test_map_over_two_collections_legacy( self ): history_id = self.dataset_populator.new_history() hdca1_id = self.__build_pair( history_id, [ "123", "456" ] ) hdca2_id = self.__build_pair( history_id, [ "789", "0ab" ] ) @@ -265,7 +386,24 @@ "input1|__collection_multirun__": hdca1_id, "queries_0|input2|__collection_multirun__": hdca2_id, } - outputs = self._cat1_outputs( history_id, inputs=inputs ) + self._check_map_cat1_over_two_collections( history_id, inputs ) + + @skip_without_tool( "cat1" ) + def test_map_over_two_collections( self ): + history_id = self.dataset_populator.new_history() + hdca1_id = self.__build_pair( history_id, [ "123", "456" ] ) + hdca2_id = self.__build_pair( history_id, [ "789", "0ab" ] ) + inputs = { + "input1": { 'batch': True, 'values': [ {'src': 'hdca', 'id': hdca1_id } ] }, + "queries_0|input2": { 'batch': True, 'values': [ { 'src': 'hdca', 'id': hdca2_id } ] }, + } + self._check_map_cat1_over_two_collections( history_id, inputs ) + + def _check_map_cat1_over_two_collections( self, history_id, inputs ): + response = self._run_cat1( history_id, inputs ) + self._assert_status_code_is( response, 200 ) + response_object = response.json() + outputs = response_object[ 'outputs' ] self.assertEquals( len( outputs ), 2 ) output1 = outputs[ 0 ] output2 = outputs[ 1 ] @@ -274,6 +412,49 @@ self.assertEquals( output1_content.strip(), "123\n789" ) self.assertEquals( output2_content.strip(), "456\n0ab" ) + self.assertEquals( len( response_object[ 'jobs' ] ), 2 ) + self.assertEquals( len( response_object[ 'implicit_collections' ] ), 1 ) + + @skip_without_tool( "cat1" ) + def test_map_over_two_collections_unlinked( self ): + history_id = self.dataset_populator.new_history() + hdca1_id = self.__build_pair( history_id, [ "123", "456" ] ) + hdca2_id = self.__build_pair( history_id, [ "789", "0ab" ] ) + inputs = { + "input1": { 'batch': True, 'linked': False, 'values': [ {'src': 'hdca', 'id': hdca1_id } ] }, + "queries_0|input2": { 'batch': True, 'linked': False, 'values': [ { 'src': 'hdca', 'id': hdca2_id } ] }, + } + response = self._run_cat1( history_id, inputs ) + self._assert_status_code_is( response, 200 ) + response_object = response.json() + outputs = response_object[ 'outputs' ] + self.assertEquals( len( outputs ), 4 ) + + self.assertEquals( len( response_object[ 'jobs' ] ), 4 ) + # Implicit collections not created with unlinked inputs yet - this may + # be problematic. + self.assertEquals( len( response_object[ 'implicit_collections' ] ), 0 ) + + @skip_without_tool( "cat1" ) + def test_map_over_collected_and_individual_datasets( self ): + history_id = self.dataset_populator.new_history() + hdca1_id = self.__build_pair( history_id, [ "123", "456" ] ) + new_dataset1 = self.dataset_populator.new_dataset( history_id, content='789' ) + new_dataset2 = self.dataset_populator.new_dataset( history_id, content='0ab' ) + + inputs = { + "input1": { 'batch': True, 'values': [ {'src': 'hdca', 'id': hdca1_id } ] }, + "queries_0|input2": { 'batch': True, 'values': [ dataset_to_param( new_dataset1 ), dataset_to_param( new_dataset2 ) ] }, + } + response = self._run_cat1( history_id, inputs ) + self._assert_status_code_is( response, 200 ) + response_object = response.json() + outputs = response_object[ 'outputs' ] + self.assertEquals( len( outputs ), 2 ) + + self.assertEquals( len( response_object[ 'jobs' ] ), 2 ) + self.assertEquals( len( response_object[ 'implicit_collections' ] ), 1 ) + @skip_without_tool( "cat1" ) def test_cannot_map_over_incompatible_collections( self ): history_id = self.dataset_populator.new_history() @@ -289,7 +470,7 @@ assert run_response.status_code >= 400 @skip_without_tool( "multi_data_param" ) - def test_reduce_collections( self ): + def test_reduce_collections_legacy( self ): history_id = self.dataset_populator.new_history() hdca1_id = self.__build_pair( history_id, [ "123", "456" ] ) hdca2_id = self.dataset_collection_populator.create_list_in_history( history_id ).json()[ "id" ] @@ -297,6 +478,20 @@ "f1": "__collection_reduce__|%s" % hdca1_id, "f2": "__collection_reduce__|%s" % hdca2_id, } + self._check_simple_reduce_job( history_id, inputs ) + + @skip_without_tool( "multi_data_param" ) + def test_reduce_collections( self ): + history_id = self.dataset_populator.new_history() + hdca1_id = self.__build_pair( history_id, [ "123", "456" ] ) + hdca2_id = self.dataset_collection_populator.create_list_in_history( history_id ).json()[ "id" ] + inputs = { + "f1": { 'src': 'hdca', 'id': hdca1_id }, + "f2": { 'src': 'hdca', 'id': hdca2_id }, + } + self._check_simple_reduce_job( history_id, inputs ) + + def _check_simple_reduce_job( self, history_id, inputs ): create = self._run( "multi_data_param", history_id, inputs, assert_ok=True ) outputs = create[ 'outputs' ] jobs = create[ 'jobs' ] @@ -310,12 +505,27 @@ assert len( output2_content.strip().split("\n") ) == 3, output2_content @skip_without_tool( "collection_paired_test" ) - def test_subcollection_mapping( self ): + def test_subcollection_mapping_legacy( self ): history_id = self.dataset_populator.new_history() hdca_list_id = self.__build_nested_list( history_id ) inputs = { "f1|__collection_multirun__": "%s|paired" % hdca_list_id } + self._check_simple_subcollection_mapping( history_id, inputs ) + + @skip_without_tool( "collection_paired_test" ) + def test_subcollection_mapping( self ): + history_id = self.dataset_populator.new_history() + hdca_list_id = self.__build_nested_list( history_id ) + inputs = { + "f1": { + 'batch': True, + 'values': [ { 'src': 'hdca', 'map_over_type': 'paired', 'id': hdca_list_id }], + } + } + self._check_simple_subcollection_mapping( history_id, inputs ) + + def _check_simple_subcollection_mapping( self, history_id, inputs ): # Following wait not really needed - just getting so many database # locked errors with sqlite. self.dataset_populator.wait_for_history( history_id, assert_ok=True ) @@ -329,7 +539,7 @@ assert output2_content.strip() == "789\n0ab", output2_content @skip_without_tool( "collection_mixed_param" ) - def test_combined_mapping_and_subcollection_mapping( self ): + def test_combined_mapping_and_subcollection_mapping_legacy( self ): history_id = self.dataset_populator.new_history() nested_list_id = self.__build_nested_list( history_id ) create_response = self.dataset_collection_populator.create_list_in_history( history_id, contents=["xxx", "yyy"] ) @@ -338,6 +548,27 @@ "f1|__collection_multirun__": "%s|paired" % nested_list_id, "f2|__collection_multirun__": list_id, } + self._check_combined_mapping_and_subcollection_mapping( history_id, inputs ) + + @skip_without_tool( "collection_mixed_param" ) + def test_combined_mapping_and_subcollection_mapping( self ): + history_id = self.dataset_populator.new_history() + nested_list_id = self.__build_nested_list( history_id ) + create_response = self.dataset_collection_populator.create_list_in_history( history_id, contents=["xxx", "yyy"] ) + list_id = create_response.json()[ "id" ] + inputs = { + "f1": { + 'batch': True, + 'values': [ { 'src': 'hdca', 'map_over_type': 'paired', 'id': nested_list_id }], + }, + "f2": { + 'batch': True, + 'values': [ { 'src': 'hdca', 'id': list_id }], + }, + } + self._check_combined_mapping_and_subcollection_mapping( history_id, inputs ) + + def _check_combined_mapping_and_subcollection_mapping( self, history_id, inputs ): self.dataset_populator.wait_for_history( history_id, assert_ok=True ) outputs = self._run_and_get_outputs( "collection_mixed_param", history_id, inputs ) assert len( outputs ), 2 diff -r 42f677bab2e4880b62758614fcb2c7dc27013788 -r df92b55d194a4d67a1b863c85044eb91c138c74b test/api/test_workflows.py --- a/test/api/test_workflows.py +++ b/test/api/test_workflows.py @@ -361,13 +361,13 @@ hdca = self.dataset_collection_populator.create_pair_in_history( history_id, contents=["1 2 3\n4 5 6", "7 8 9\n10 11 10"] ).json() hdca_id = hdca[ "id" ] inputs1 = { - "input|__collection_multirun__": hdca_id, + "input": { "batch": True, "values": [ { "src": "hdca", "id": hdca_id } ] }, "num_lines": 2 } implicit_hdca1, job_id1 = self._run_tool_get_collection_and_job_id( history_id, "random_lines1", inputs1 ) inputs2 = { - "f1": "__collection_reduce__|%s" % ( implicit_hdca1[ "id" ] ), - "f2": "__collection_reduce__|%s" % ( implicit_hdca1[ "id" ] ) + "f1": { "src": "hdca", "id": implicit_hdca1[ "id" ] }, + "f2": { "src": "hdca", "id": implicit_hdca1[ "id" ] }, } reduction_run_output = self.dataset_populator.run_tool( tool_id="multi_data_param", @@ -413,12 +413,12 @@ hdca = self.dataset_collection_populator.create_pair_in_history( history_id, contents=["1 2 3\n4 5 6", "7 8 9\n10 11 10"] ).json() hdca_id = hdca[ "id" ] inputs1 = { - "input|__collection_multirun__": hdca_id, + "input": { "batch": True, "values": [ { "src": "hdca", "id": hdca_id } ] }, "num_lines": 2 } implicit_hdca1, job_id1 = self._run_tool_get_collection_and_job_id( history_id, "random_lines1", inputs1 ) inputs2 = { - "input|__collection_multirun__": implicit_hdca1[ "id" ], + "input": { "batch": True, "values": [ { "src": "hdca", "id": implicit_hdca1[ "id" ] } ] }, "num_lines": 1 } _, job_id2 = self._run_tool_get_collection_and_job_id( history_id, "random_lines1", inputs2 ) Repository URL: https://bitbucket.org/galaxy/galaxy-central/ -- This is a commit notification from bitbucket.org. 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commit/galaxy-central: 10 new changesets
by commits-noreply＠bitbucket.org 22 Sep '14

22 Sep '14

10 new commits in galaxy-central: https://bitbucket.org/galaxy/galaxy-central/commits/d5218767204d/ Changeset: d5218767204d User: jmchilton Date: 2014-09-16 15:57:48+00:00 Summary: Allow sending singleton lists of datasets to single dataset parameters via API tool submission. Request from Sam. Affected #: 2 files diff -r 80d68ea889c01357b520ecefc56f86b0a44549fc -r d5218767204d12af6275b320409e507ae3dfe95b lib/galaxy/tools/parameters/basic.py --- a/lib/galaxy/tools/parameters/basic.py +++ b/lib/galaxy/tools/parameters/basic.py @@ -1903,6 +1903,10 @@ raise ValueError( "The previously selected dataset has been previously deleted" ) if hasattr( v, "dataset" ) and v.dataset.state in [ galaxy.model.Dataset.states.ERROR, galaxy.model.Dataset.states.DISCARDED ]: raise ValueError( "The previously selected dataset has entered an unusable state" ) + if not self.multiple: + if len( values ) > 1: + raise ValueError( "More than one dataset supplied to single input dataset parameter.") + rval = values[ 0 ] return rval def to_string( self, value, app ): diff -r 80d68ea889c01357b520ecefc56f86b0a44549fc -r d5218767204d12af6275b320409e507ae3dfe95b test/api/test_tools.py --- a/test/api/test_tools.py +++ b/test/api/test_tools.py @@ -109,6 +109,20 @@ output1_content = self.dataset_populator.get_history_dataset_content( history_id, dataset=output1 ) self.assertEqual( output1_content.strip(), "Cat1Test" ) + @skip_without_tool( "cat1" ) + def test_run_cat1_listified_param( self ): + # Run simple non-upload tool with an input data parameter. + history_id = self.dataset_populator.new_history() + new_dataset = self.dataset_populator.new_dataset( history_id, content='Cat1Testlistified' ) + inputs = dict( + input1=[dataset_to_param( new_dataset )], + ) + outputs = self._cat1_outputs( history_id, inputs=inputs ) + self.assertEquals( len( outputs ), 1 ) + output1 = outputs[ 0 ] + output1_content = self.dataset_populator.get_history_dataset_content( history_id, dataset=output1 ) + self.assertEqual( output1_content.strip(), "Cat1Testlistified" ) + @skip_without_tool( "validation_default" ) def test_validation( self ): history_id = self.dataset_populator.new_history() https://bitbucket.org/galaxy/galaxy-central/commits/d9c75786e6b4/ Changeset: d9c75786e6b4 User: jmchilton Date: 2014-09-16 15:57:48+00:00 Summary: Overhaul multi-run and collection multi-run tool API jobs. Adding consistency allowing each parameter to be wrapped in a object describing the meta-properties of the submitting value - this was requested by Sam to make the new tool form easier to manage, it makes multi-running properties work for non-data parameters, and allows linked/unlinked specification of parameters. Affected #: 2 files diff -r d5218767204d12af6275b320409e507ae3dfe95b -r d9c75786e6b43f18f9c1eaded635d5d6b236e2a7 lib/galaxy/tools/parameters/meta.py --- a/lib/galaxy/tools/parameters/meta.py +++ b/lib/galaxy/tools/parameters/meta.py @@ -14,6 +14,28 @@ execution). """ + def classifiy_unmodified_parameter( input_key ): + value = incoming[ input_key ] + if isinstance( value, dict ) and 'values' in value: + # Explicit meta wrapper for inputs... + is_batch = value.get( 'batch', False ) + is_linked = value.get( 'linked', True ) + if is_batch and is_linked: + classification = permutations.input_classification.MATCHED + elif is_batch: + classification = permutations.input_classification.MULTIPLIED + else: + classification = permutations.input_classification.SINGLE + if __collection_multirun_parameter( value ): + collection_value = value[ 'values' ][ 0 ] + values = __expand_collection_parameter( trans, input_key, collection_value, collections_to_match ) + else: + values = value[ 'values' ] + else: + classification = permutations.input_classification.SINGLE + values = value + return classification, values + def classifier( input_key ): multirun_key = "%s|__multirun__" % input_key if multirun_key in incoming: @@ -25,7 +47,7 @@ multi_value = None return permutations.input_classification.SINGLE, multi_value[ 0 ] else: - return permutations.input_classification.SINGLE, incoming[ input_key ] + return classifiy_unmodified_parameter( input_key ) from galaxy.dataset_collections import matching collections_to_match = matching.CollectionsToMatch() @@ -34,31 +56,10 @@ multirun_key = "%s|__collection_multirun__" % input_key if multirun_key in incoming: incoming_val = incoming[ multirun_key ] - # If subcollectin multirun of data_collection param - value will - # be "hdca_id|subcollection_type" else it will just be hdca_id - if "|" in incoming_val: - encoded_hdc_id, subcollection_type = incoming_val.split( "|", 1 ) - else: - try: - src = incoming_val[ "src" ] - if src != "hdca": - raise exceptions.ToolMetaParameterException( "Invalid dataset collection source type %s" % src ) - encoded_hdc_id = incoming_val[ "id" ] - except TypeError: - encoded_hdc_id = incoming_val - subcollection_type = None - hdc_id = trans.app.security.decode_id( encoded_hdc_id ) - hdc = trans.sa_session.query( model.HistoryDatasetCollectionAssociation ).get( hdc_id ) - collections_to_match.add( input_key, hdc, subcollection_type=subcollection_type ) - if subcollection_type is not None: - from galaxy.dataset_collections import subcollections - subcollection_elements = subcollections.split_dataset_collection_instance( hdc, subcollection_type ) - return permutations.input_classification.MATCHED, subcollection_elements - else: - hdas = hdc.collection.dataset_instances - return permutations.input_classification.MATCHED, hdas + values = __expand_collection_parameter( trans, input_key, incoming_val, collections_to_match ) + return permutations.input_classification.MATCHED, values else: - return permutations.input_classification.SINGLE, incoming[ input_key ] + return classifiy_unmodified_parameter( input_key ) # Stick an unexpanded version of multirun keys so they can be replaced, # by expand_mult_inputs. @@ -76,8 +77,19 @@ multirun_found = False collection_multirun_found = False for key, value in incoming.iteritems(): - multirun_found = try_replace_key( key, "|__multirun__" ) or multirun_found - collection_multirun_found = try_replace_key( key, "|__collection_multirun__" ) or collection_multirun_found + if isinstance( value, dict ) and 'values' in value: + batch = value.get( 'batch', False ) + if batch: + if __collection_multirun_parameter( value ): + collection_multirun_found = True + else: + multirun_found = True + else: + continue + else: + # Old-style batching (remove someday - didn't live in API long?) + multirun_found = try_replace_key( key, "|__multirun__" ) or multirun_found + collection_multirun_found = try_replace_key( key, "|__collection_multirun__" ) or collection_multirun_found if sum( [ 1 if f else 0 for f in [ multirun_found, collection_multirun_found ] ] ) > 1: # In theory doable, but to complicated for a first pass. @@ -93,3 +105,38 @@ else: collection_info = None return expanded_incomings, collection_info + + +def __expand_collection_parameter( trans, input_key, incoming_val, collections_to_match ): + # If subcollectin multirun of data_collection param - value will + # be "hdca_id|subcollection_type" else it will just be hdca_id + if "|" in incoming_val: + encoded_hdc_id, subcollection_type = incoming_val.split( "|", 1 ) + else: + try: + src = incoming_val[ "src" ] + if src != "hdca": + raise exceptions.ToolMetaParameterException( "Invalid dataset collection source type %s" % src ) + encoded_hdc_id = incoming_val[ "id" ] + except TypeError: + encoded_hdc_id = incoming_val + subcollection_type = None + hdc_id = trans.app.security.decode_id( encoded_hdc_id ) + hdc = trans.sa_session.query( model.HistoryDatasetCollectionAssociation ).get( hdc_id ) + collections_to_match.add( input_key, hdc, subcollection_type=subcollection_type ) + if subcollection_type is not None: + from galaxy.dataset_collections import subcollections + subcollection_elements = subcollections.split_dataset_collection_instance( hdc, subcollection_type ) + return subcollection_elements + else: + hdas = hdc.collection.dataset_instances + return hdas + + +def __collection_multirun_parameter( value ): + batch_values = util.listify( value[ 'values' ] ) + if len( batch_values ) == 1: + batch_over = batch_values[ 0 ] + if isinstance( batch_over, dict ) and ('src' in batch_over) and (batch_over[ 'src' ] == 'hdca'): + return True + return False diff -r d5218767204d12af6275b320409e507ae3dfe95b -r d9c75786e6b43f18f9c1eaded635d5d6b236e2a7 test/api/test_tools.py --- a/test/api/test_tools.py +++ b/test/api/test_tools.py @@ -123,6 +123,22 @@ output1_content = self.dataset_populator.get_history_dataset_content( history_id, dataset=output1 ) self.assertEqual( output1_content.strip(), "Cat1Testlistified" ) + @skip_without_tool( "cat1" ) + def test_run_cat1_single_meta_wrapper( self ): + # Wrap input in a no-op meta parameter wrapper like Sam is planning to + # use for all UI API submissions. + history_id = self.dataset_populator.new_history() + new_dataset = self.dataset_populator.new_dataset( history_id, content='123' ) + inputs = dict( + input1={ 'batch': False, 'values': [ dataset_to_param( new_dataset ) ] }, + ) + outputs = self._cat1_outputs( history_id, inputs=inputs ) + self.assertEquals( len( outputs ), 1 ) + output1 = outputs[ 0 ] + output1_content = self.dataset_populator.get_history_dataset_content( history_id, dataset=output1 ) + self.assertEqual( output1_content.strip(), "123" ) + + @skip_without_tool( "validation_default" ) def test_validation( self ): history_id = self.dataset_populator.new_history() @@ -149,16 +165,31 @@ self.assertEqual( output1_content.strip(), "Cat1Test\nCat2Test" ) @skip_without_tool( "cat1" ) + def test_multirun_cat1_legacy( self ): + history_id, datasets = self._prepare_cat1_multirun() + inputs = { + "input1|__multirun__": datasets, + } + self._check_cat1_multirun( history_id, inputs ) + + @skip_without_tool( "cat1" ) def test_multirun_cat1( self ): + history_id, datasets = self._prepare_cat1_multirun() + inputs = { + "input1": { + 'batch': True, + 'values': datasets, + }, + } + self._check_cat1_multirun( history_id, inputs ) + + def _prepare_cat1_multirun( self ): history_id = self.dataset_populator.new_history() new_dataset1 = self.dataset_populator.new_dataset( history_id, content='123' ) new_dataset2 = self.dataset_populator.new_dataset( history_id, content='456' ) - inputs = { - "input1|__multirun__": [ - dataset_to_param( new_dataset1 ), - dataset_to_param( new_dataset2 ), - ], - } + return history_id, [ dataset_to_param( new_dataset1 ), dataset_to_param( new_dataset2 ) ] + + def _check_cat1_multirun( self, history_id, inputs ): outputs = self._cat1_outputs( history_id, inputs=inputs ) self.assertEquals( len( outputs ), 2 ) output1 = outputs[ 0 ] @@ -168,6 +199,20 @@ self.assertEquals( output1_content.strip(), "123" ) self.assertEquals( output2_content.strip(), "456" ) + @skip_without_tool( "random_lines1" ) + def test_multirun_non_data_parameter( self ): + history_id = self.dataset_populator.new_history() + new_dataset1 = self.dataset_populator.new_dataset( history_id, content='123\n456\n789' ) + inputs = { + 'input': dataset_to_param( new_dataset1 ), + 'num_lines': { 'batch': True, 'values': [ 1, 2, 3 ] } + } + outputs = self._run_and_get_outputs( 'random_lines1', history_id, inputs ) + # Assert we have three outputs with 1, 2, and 3 lines respectively. + assert len( outputs ) == 3 + outputs_contents = [ self.dataset_populator.get_history_dataset_content( history_id, dataset=o ).strip() for o in outputs ] + assert sorted( map( lambda c: len( c.split( "\n" ) ), outputs_contents ) ) == [ 1, 2, 3 ] + @skip_without_tool( "cat1" ) def test_multirun_in_repeat( self ): history_id = self.dataset_populator.new_history() @@ -191,35 +236,60 @@ self.assertEquals( output2_content.strip(), "Common\n456" ) @skip_without_tool( "cat1" ) - def test_multirun_on_multiple_inputs( self ): - history_id = self.dataset_populator.new_history() - new_dataset1 = self.dataset_populator.new_dataset( history_id, content='123' ) - new_dataset2 = self.dataset_populator.new_dataset( history_id, content='456' ) - new_dataset3 = self.dataset_populator.new_dataset( history_id, content='789' ) - new_dataset4 = self.dataset_populator.new_dataset( history_id, content='0ab' ) + def test_multirun_on_multiple_inputs_legacy( self ): + history_id, first_two, second_two = self._setup_two_multiruns() inputs = { - "input1|__multirun__": [ - dataset_to_param( new_dataset1 ), - dataset_to_param( new_dataset2 ), - ], - 'queries_0|input2|__multirun__': [ - dataset_to_param( new_dataset3 ), - dataset_to_param( new_dataset4 ), - ], + "input1|__multirun__": first_two, + 'queries_0|input2|__multirun__': second_two, } outputs = self._cat1_outputs( history_id, inputs=inputs ) self.assertEquals( len( outputs ), 2 ) outputs_contents = [ self.dataset_populator.get_history_dataset_content( history_id, dataset=o ).strip() for o in outputs ] assert "123\n789" in outputs_contents assert "456\n0ab" in outputs_contents - # TODO: Once cross production (instead of linking inputs) is an option - # again redo test with these checks... - # self.assertEquals( len( outputs ), 4 ) - # assert "123\n0ab" in outputs_contents - # assert "456\n789" in outputs_contents @skip_without_tool( "cat1" ) - def test_map_over_collection( self ): + def test_multirun_on_multiple_inputs( self ): + history_id, first_two, second_two = self._setup_two_multiruns() + inputs = { + "input1": { 'batch': True, 'values': first_two }, + 'queries_0|input2': { 'batch': True, 'values': second_two }, + } + outputs = self._cat1_outputs( history_id, inputs=inputs ) + self.assertEquals( len( outputs ), 2 ) + outputs_contents = [ self.dataset_populator.get_history_dataset_content( history_id, dataset=o ).strip() for o in outputs ] + assert "123\n789" in outputs_contents + assert "456\n0ab" in outputs_contents + + @skip_without_tool( "cat1" ) + def test_multirun_on_multiple_inputs_unlinked( self ): + history_id, first_two, second_two = self._setup_two_multiruns() + inputs = { + "input1": { 'batch': True, 'linked': False, 'values': first_two }, + 'queries_0|input2': { 'batch': True, 'linked': False, 'values': second_two }, + } + outputs = self._cat1_outputs( history_id, inputs=inputs ) + outputs_contents = [ self.dataset_populator.get_history_dataset_content( history_id, dataset=o ).strip() for o in outputs ] + self.assertEquals( len( outputs ), 4 ) + assert "123\n789" in outputs_contents + assert "456\n0ab" in outputs_contents + assert "123\n0ab" in outputs_contents + assert "456\n789" in outputs_contents + + def _setup_two_multiruns( self ): + history_id = self.dataset_populator.new_history() + new_dataset1 = self.dataset_populator.new_dataset( history_id, content='123' ) + new_dataset2 = self.dataset_populator.new_dataset( history_id, content='456' ) + new_dataset3 = self.dataset_populator.new_dataset( history_id, content='789' ) + new_dataset4 = self.dataset_populator.new_dataset( history_id, content='0ab' ) + return ( + history_id, + [ dataset_to_param( new_dataset1 ), dataset_to_param( new_dataset2 ) ], + [ dataset_to_param( new_dataset3 ), dataset_to_param( new_dataset4 ) ] + ) + + @skip_without_tool( "cat1" ) + def test_map_over_collection_legacy( self ): history_id = self.dataset_populator.new_history() hdca_id = self.__build_pair( history_id, [ "123", "456" ] ) inputs = { @@ -228,6 +298,18 @@ # first, next test method tests other. "input1|__collection_multirun__": hdca_id, } + self._run_and_check_simple_collection_mapping( history_id, inputs ) + + @skip_without_tool( "cat1" ) + def test_map_over_collection( self ): + history_id = self.dataset_populator.new_history() + hdca_id = self.__build_pair( history_id, [ "123", "456" ] ) + inputs = { + "input1": { 'batch': True, 'values': [ { 'src': 'hdca', 'id': hdca_id } ] }, + } + self._run_and_check_simple_collection_mapping( history_id, inputs ) + + def _run_and_check_simple_collection_mapping( self, history_id, inputs ): create = self._run_cat1( history_id, inputs=inputs, assert_ok=True ) outputs = create[ 'outputs' ] jobs = create[ 'jobs' ] @@ -243,12 +325,24 @@ self.assertEquals( output2_content.strip(), "456" ) @skip_without_tool( "cat1" ) - def test_map_over_nested_collections( self ): + def test_map_over_nested_collections_legacy( self ): history_id = self.dataset_populator.new_history() hdca_id = self.__build_nested_list( history_id ) inputs = { "input1|__collection_multirun__": dict( src="hdca", id=hdca_id ), } + self._check_simple_cat1_over_nested_collections( history_id, inputs ) + + @skip_without_tool( "cat1" ) + def test_map_over_nested_collections( self ): + history_id = self.dataset_populator.new_history() + hdca_id = self.__build_nested_list( history_id ) + inputs = { + "input1": { 'batch': True, 'values': [ dict( src="hdca", id=hdca_id ) ] }, + } + self._check_simple_cat1_over_nested_collections( history_id, inputs ) + + def _check_simple_cat1_over_nested_collections( self, history_id, inputs ): create = self._run_cat1( history_id, inputs=inputs, assert_ok=True ) outputs = create[ 'outputs' ] jobs = create[ 'jobs' ] @@ -271,7 +365,7 @@ self.assertEquals( outputs[ 0 ][ "id" ], first_object_forward_element[ "object" ][ "id" ] ) @skip_without_tool( "cat1" ) - def test_map_over_two_collections( self ): + def test_map_over_two_collections_legacy( self ): history_id = self.dataset_populator.new_history() hdca1_id = self.__build_pair( history_id, [ "123", "456" ] ) hdca2_id = self.__build_pair( history_id, [ "789", "0ab" ] ) @@ -279,7 +373,24 @@ "input1|__collection_multirun__": hdca1_id, "queries_0|input2|__collection_multirun__": hdca2_id, } - outputs = self._cat1_outputs( history_id, inputs=inputs ) + self._check_map_cat1_over_two_collections( history_id, inputs ) + + @skip_without_tool( "cat1" ) + def test_map_over_two_collections( self ): + history_id = self.dataset_populator.new_history() + hdca1_id = self.__build_pair( history_id, [ "123", "456" ] ) + hdca2_id = self.__build_pair( history_id, [ "789", "0ab" ] ) + inputs = { + "input1": { 'batch': True, 'values': [ {'src': 'hdca', 'id': hdca1_id } ] }, + "queries_0|input2": { 'batch': True, 'values': [ { 'src': 'hdca', 'id': hdca2_id } ] }, + } + self._check_map_cat1_over_two_collections( history_id, inputs ) + + def _check_map_cat1_over_two_collections( self, history_id, inputs ): + response = self._run_cat1( history_id, inputs ) + self._assert_status_code_is( response, 200 ) + response_object = response.json() + outputs = response_object[ 'outputs' ] self.assertEquals( len( outputs ), 2 ) output1 = outputs[ 0 ] output2 = outputs[ 1 ] @@ -288,6 +399,29 @@ self.assertEquals( output1_content.strip(), "123\n789" ) self.assertEquals( output2_content.strip(), "456\n0ab" ) + self.assertEquals( len( response_object[ 'jobs' ] ), 2 ) + self.assertEquals( len( response_object[ 'implicit_collections' ] ), 1 ) + + @skip_without_tool( "cat1" ) + def test_map_over_two_collections_unlinked( self ): + history_id = self.dataset_populator.new_history() + hdca1_id = self.__build_pair( history_id, [ "123", "456" ] ) + hdca2_id = self.__build_pair( history_id, [ "789", "0ab" ] ) + inputs = { + "input1": { 'batch': True, 'linked': False, 'values': [ {'src': 'hdca', 'id': hdca1_id } ] }, + "queries_0|input2": { 'batch': True, 'linked': False, 'values': [ { 'src': 'hdca', 'id': hdca2_id } ] }, + } + response = self._run_cat1( history_id, inputs ) + self._assert_status_code_is( response, 200 ) + response_object = response.json() + outputs = response_object[ 'outputs' ] + self.assertEquals( len( outputs ), 4 ) + + self.assertEquals( len( response_object[ 'jobs' ] ), 4 ) + # Implicit collections not created with unlinked inputs yet - this may + # be problematic. + self.assertEquals( len( response_object[ 'implicit_collections' ] ), 0 ) + @skip_without_tool( "cat1" ) def test_cannot_map_over_incompatible_collections( self ): history_id = self.dataset_populator.new_history() https://bitbucket.org/galaxy/galaxy-central/commits/e5e67860cbde/ Changeset: e5e67860cbde User: jmchilton Date: 2014-09-16 15:57:48+00:00 Summary: Allow mixing batch multi-running of collections and individual datasets. I wouldn't really recommend doing this per se - but probably don't want to prevent it either. Affected #: 2 files diff -r d9c75786e6b43f18f9c1eaded635d5d6b236e2a7 -r e5e67860cbde0edb272e1dbd225f4195e8b4785f lib/galaxy/tools/parameters/meta.py --- a/lib/galaxy/tools/parameters/meta.py +++ b/lib/galaxy/tools/parameters/meta.py @@ -36,7 +36,11 @@ values = value return classification, values + from galaxy.dataset_collections import matching + collections_to_match = matching.CollectionsToMatch() + def classifier( input_key ): + collection_multirun_key = "%s|__collection_multirun__" % input_key multirun_key = "%s|__multirun__" % input_key if multirun_key in incoming: multi_value = util.listify( incoming[ multirun_key ] ) @@ -46,16 +50,8 @@ if len( multi_value ) == 0: multi_value = None return permutations.input_classification.SINGLE, multi_value[ 0 ] - else: - return classifiy_unmodified_parameter( input_key ) - - from galaxy.dataset_collections import matching - collections_to_match = matching.CollectionsToMatch() - - def collection_classifier( input_key ): - multirun_key = "%s|__collection_multirun__" % input_key - if multirun_key in incoming: - incoming_val = incoming[ multirun_key ] + elif collection_multirun_key in incoming: + incoming_val = incoming[ collection_multirun_key ] values = __expand_collection_parameter( trans, input_key, incoming_val, collections_to_match ) return permutations.input_classification.MATCHED, values else: @@ -87,24 +83,16 @@ else: continue else: - # Old-style batching (remove someday - didn't live in API long?) - multirun_found = try_replace_key( key, "|__multirun__" ) or multirun_found - collection_multirun_found = try_replace_key( key, "|__collection_multirun__" ) or collection_multirun_found + # Old-style batching (remove someday? - pretty hacky and didn't live in API long) + try_replace_key( key, "|__multirun__" ) or multirun_found + try_replace_key( key, "|__collection_multirun__" ) or collection_multirun_found - if sum( [ 1 if f else 0 for f in [ multirun_found, collection_multirun_found ] ] ) > 1: - # In theory doable, but to complicated for a first pass. - message = "Cannot specify parallel execution across both multiple datasets and dataset collections." - raise exceptions.ToolMetaParameterException( message ) - - if multirun_found: - return permutations.expand_multi_inputs( incoming_template, classifier ), None + expanded_incomings = permutations.expand_multi_inputs( incoming_template, classifier ) + if collections_to_match.has_collections(): + collection_info = trans.app.dataset_collections_service.match_collections( collections_to_match ) else: - expanded_incomings = permutations.expand_multi_inputs( incoming_template, collection_classifier ) - if collections_to_match.has_collections(): - collection_info = trans.app.dataset_collections_service.match_collections( collections_to_match ) - else: - collection_info = None - return expanded_incomings, collection_info + collection_info = None + return expanded_incomings, collection_info def __expand_collection_parameter( trans, input_key, incoming_val, collections_to_match ): diff -r d9c75786e6b43f18f9c1eaded635d5d6b236e2a7 -r e5e67860cbde0edb272e1dbd225f4195e8b4785f test/api/test_tools.py --- a/test/api/test_tools.py +++ b/test/api/test_tools.py @@ -423,6 +423,26 @@ self.assertEquals( len( response_object[ 'implicit_collections' ] ), 0 ) @skip_without_tool( "cat1" ) + def test_map_over_collected_and_individual_datasets( self ): + history_id = self.dataset_populator.new_history() + hdca1_id = self.__build_pair( history_id, [ "123", "456" ] ) + new_dataset1 = self.dataset_populator.new_dataset( history_id, content='789' ) + new_dataset2 = self.dataset_populator.new_dataset( history_id, content='0ab' ) + + inputs = { + "input1": { 'batch': True, 'values': [ {'src': 'hdca', 'id': hdca1_id } ] }, + "queries_0|input2": { 'batch': True, 'values': [ dataset_to_param( new_dataset1 ), dataset_to_param( new_dataset2 ) ] }, + } + response = self._run_cat1( history_id, inputs ) + self._assert_status_code_is( response, 200 ) + response_object = response.json() + outputs = response_object[ 'outputs' ] + self.assertEquals( len( outputs ), 2 ) + + self.assertEquals( len( response_object[ 'jobs' ] ), 2 ) + self.assertEquals( len( response_object[ 'implicit_collections' ] ), 1 ) + + @skip_without_tool( "cat1" ) def test_cannot_map_over_incompatible_collections( self ): history_id = self.dataset_populator.new_history() hdca1_id = self.__build_pair( history_id, [ "123", "456" ] ) https://bitbucket.org/galaxy/galaxy-central/commits/a7f6b4b1468c/ Changeset: a7f6b4b1468c User: jmchilton Date: 2014-09-16 15:57:48+00:00 Summary: Simplified dataset collection reductions via API. Old tool form needed to encode every value as a string so I had done "__collection_reduction__|<hdca_id>" to distinguish that value from an "<hda_id>" - since hdca and hdas can have the same encoded ids. The new tool form API is going to use the API which allows for richer object representations - so {"src": "hda", "id": "<hda_id>"} versus {"src": "hdca", "id": "<hdca_id>"} should be enough to distinguish between passing an HDA and an HDCA to a multiple input data parameter. Affected #: 2 files diff -r e5e67860cbde0edb272e1dbd225f4195e8b4785f -r a7f6b4b1468cc52237981a7e7c1645f4720f8b1e lib/galaxy/tools/parameters/basic.py --- a/lib/galaxy/tools/parameters/basic.py +++ b/lib/galaxy/tools/parameters/basic.py @@ -1887,6 +1887,11 @@ elif isinstance( value, dict ) and 'src' in value and 'id' in value: if value['src'] == 'hda': rval = trans.sa_session.query( trans.app.model.HistoryDatasetAssociation ).get( trans.app.security.decode_id(value['id']) ) + elif value['src'] == 'hdca': + decoded_id = trans.app.security.decode_id( value[ 'id' ] ) + rval = trans.sa_session.query( trans.app.model.HistoryDatasetCollectionAssociation ).get( decoded_id ) + else: + raise ValueError("Unknown input source %s passed to job submission API." % value['src']) elif str( value ).startswith( "__collection_reduce__|" ): encoded_id = str( value )[ len( "__collection_reduce__|" ): ] decoded_id = trans.app.security.decode_id( encoded_id ) diff -r e5e67860cbde0edb272e1dbd225f4195e8b4785f -r a7f6b4b1468cc52237981a7e7c1645f4720f8b1e test/api/test_tools.py --- a/test/api/test_tools.py +++ b/test/api/test_tools.py @@ -457,7 +457,7 @@ assert run_response.status_code >= 400 @skip_without_tool( "multi_data_param" ) - def test_reduce_collections( self ): + def test_reduce_collections_legacy( self ): history_id = self.dataset_populator.new_history() hdca1_id = self.__build_pair( history_id, [ "123", "456" ] ) hdca2_id = self.dataset_collection_populator.create_list_in_history( history_id ).json()[ "id" ] @@ -465,6 +465,20 @@ "f1": "__collection_reduce__|%s" % hdca1_id, "f2": "__collection_reduce__|%s" % hdca2_id, } + self._check_simple_reduce_job( history_id, inputs ) + + @skip_without_tool( "multi_data_param" ) + def test_reduce_collections( self ): + history_id = self.dataset_populator.new_history() + hdca1_id = self.__build_pair( history_id, [ "123", "456" ] ) + hdca2_id = self.dataset_collection_populator.create_list_in_history( history_id ).json()[ "id" ] + inputs = { + "f1": { 'src': 'hdca', 'id': hdca1_id }, + "f2": { 'src': 'hdca', 'id': hdca2_id }, + } + self._check_simple_reduce_job( history_id, inputs ) + + def _check_simple_reduce_job( self, history_id, inputs ): create = self._run( "multi_data_param", history_id, inputs, assert_ok=True ) outputs = create[ 'outputs' ] jobs = create[ 'jobs' ] https://bitbucket.org/galaxy/galaxy-central/commits/6185cea44918/ Changeset: 6185cea44918 User: jmchilton Date: 2014-09-16 15:57:48+00:00 Summary: Redo API for subcollection mapping steps in tools. Like the reductions - was previously constrained by sequeezing these values into simple strings - now the tool form will target the API I think this expanded version is a little more straight-forward (though verbose). Adds consistency with rest of the tool form API changes. Affected #: 2 files diff -r a7f6b4b1468cc52237981a7e7c1645f4720f8b1e -r 6185cea4491868aea6207879e88118402f4344d3 lib/galaxy/tools/parameters/meta.py --- a/lib/galaxy/tools/parameters/meta.py +++ b/lib/galaxy/tools/parameters/meta.py @@ -106,9 +106,10 @@ if src != "hdca": raise exceptions.ToolMetaParameterException( "Invalid dataset collection source type %s" % src ) encoded_hdc_id = incoming_val[ "id" ] + subcollection_type = incoming_val.get( 'map_over_type', None ) except TypeError: encoded_hdc_id = incoming_val - subcollection_type = None + subcollection_type = None hdc_id = trans.app.security.decode_id( encoded_hdc_id ) hdc = trans.sa_session.query( model.HistoryDatasetCollectionAssociation ).get( hdc_id ) collections_to_match.add( input_key, hdc, subcollection_type=subcollection_type ) diff -r a7f6b4b1468cc52237981a7e7c1645f4720f8b1e -r 6185cea4491868aea6207879e88118402f4344d3 test/api/test_tools.py --- a/test/api/test_tools.py +++ b/test/api/test_tools.py @@ -492,12 +492,27 @@ assert len( output2_content.strip().split("\n") ) == 3, output2_content @skip_without_tool( "collection_paired_test" ) - def test_subcollection_mapping( self ): + def test_subcollection_mapping_legacy( self ): history_id = self.dataset_populator.new_history() hdca_list_id = self.__build_nested_list( history_id ) inputs = { "f1|__collection_multirun__": "%s|paired" % hdca_list_id } + self._check_simple_subcollection_mapping( history_id, inputs ) + + @skip_without_tool( "collection_paired_test" ) + def test_subcollection_mapping( self ): + history_id = self.dataset_populator.new_history() + hdca_list_id = self.__build_nested_list( history_id ) + inputs = { + "f1": { + 'batch': True, + 'values': [ { 'src': 'hdca', 'map_over_type': 'paired', 'id': hdca_list_id }], + } + } + self._check_simple_subcollection_mapping( history_id, inputs ) + + def _check_simple_subcollection_mapping( self, history_id, inputs ): # Following wait not really needed - just getting so many database # locked errors with sqlite. self.dataset_populator.wait_for_history( history_id, assert_ok=True ) @@ -511,7 +526,7 @@ assert output2_content.strip() == "789\n0ab", output2_content @skip_without_tool( "collection_mixed_param" ) - def test_combined_mapping_and_subcollection_mapping( self ): + def test_combined_mapping_and_subcollection_mapping_legacy( self ): history_id = self.dataset_populator.new_history() nested_list_id = self.__build_nested_list( history_id ) create_response = self.dataset_collection_populator.create_list_in_history( history_id, contents=["xxx", "yyy"] ) @@ -520,6 +535,27 @@ "f1|__collection_multirun__": "%s|paired" % nested_list_id, "f2|__collection_multirun__": list_id, } + self._check_combined_mapping_and_subcollection_mapping( history_id, inputs ) + + @skip_without_tool( "collection_mixed_param" ) + def test_combined_mapping_and_subcollection_mapping( self ): + history_id = self.dataset_populator.new_history() + nested_list_id = self.__build_nested_list( history_id ) + create_response = self.dataset_collection_populator.create_list_in_history( history_id, contents=["xxx", "yyy"] ) + list_id = create_response.json()[ "id" ] + inputs = { + "f1": { + 'batch': True, + 'values': [ { 'src': 'hdca', 'map_over_type': 'paired', 'id': nested_list_id }], + }, + "f2": { + 'batch': True, + 'values': [ { 'src': 'hdca', 'id': list_id }], + }, + } + self._check_combined_mapping_and_subcollection_mapping( history_id, inputs ) + + def _check_combined_mapping_and_subcollection_mapping( self, history_id, inputs ): self.dataset_populator.wait_for_history( history_id, assert_ok=True ) outputs = self._run_and_get_outputs( "collection_mixed_param", history_id, inputs ) assert len( outputs ), 2 https://bitbucket.org/galaxy/galaxy-central/commits/b8bc9b8b9806/ Changeset: b8bc9b8b9806 User: jmchilton Date: 2014-09-16 15:57:48+00:00 Summary: Add tools test for data_collection input parameter specification. Affected #: 1 file diff -r 6185cea4491868aea6207879e88118402f4344d3 -r b8bc9b8b980689cbd32ad999675a31203574afb9 test/api/test_tools.py --- a/test/api/test_tools.py +++ b/test/api/test_tools.py @@ -148,6 +148,20 @@ response = self._run( "validation_default", history_id, inputs ) self._assert_status_code_is( response, 400 ) + @skip_without_tool( "collection_paired_test" ) + def test_collection_parameter( self ): + history_id = self.dataset_populator.new_history() + hdca_id = self.__build_pair( history_id, [ "123", "456" ] ) + inputs = { + "f1": { "src": "hdca", "id": hdca_id }, + } + output = self._run( "collection_paired_test", history_id, inputs, assert_ok=True ) + assert len( output[ 'jobs' ] ) == 1 + assert len( output[ 'implicit_collections' ] ) == 0 + assert len( output[ 'outputs' ] ) == 1 + contents = self.dataset_populator.get_history_dataset_content( history_id, hid=4 ) + assert contents.strip() == "123\n456", contents + @skip_without_tool( "cat1" ) def test_run_cat1_with_two_inputs( self ): # Run tool with an multiple data parameter and grouping (repeat) https://bitbucket.org/galaxy/galaxy-central/commits/f5ea6456c64e/ Changeset: f5ea6456c64e User: jmchilton Date: 2014-09-16 15:57:48+00:00 Summary: PEP-8 fix. Affected #: 1 file diff -r b8bc9b8b980689cbd32ad999675a31203574afb9 -r f5ea6456c64ece76db8528eee5c88eb839cbaa34 test/api/test_tools.py --- a/test/api/test_tools.py +++ b/test/api/test_tools.py @@ -138,7 +138,6 @@ output1_content = self.dataset_populator.get_history_dataset_content( history_id, dataset=output1 ) self.assertEqual( output1_content.strip(), "123" ) - @skip_without_tool( "validation_default" ) def test_validation( self ): history_id = self.dataset_populator.new_history() https://bitbucket.org/galaxy/galaxy-central/commits/e66166960524/ Changeset: e66166960524 User: jmchilton Date: 2014-09-16 15:57:48+00:00 Summary: Update map/reduce workflow tests for newer API constructs. Old ones still work - but I wanted to verify the new changes didn't cause any unintended consequences with workflows. Affected #: 1 file diff -r f5ea6456c64ece76db8528eee5c88eb839cbaa34 -r e6616696052491bf563b690865f307f2de96d57c test/api/test_workflows.py --- a/test/api/test_workflows.py +++ b/test/api/test_workflows.py @@ -350,13 +350,13 @@ hdca = self.dataset_collection_populator.create_pair_in_history( history_id, contents=["1 2 3\n4 5 6", "7 8 9\n10 11 10"] ).json() hdca_id = hdca[ "id" ] inputs1 = { - "input|__collection_multirun__": hdca_id, + "input": { "batch": True, "values": [ { "src": "hdca", "id": hdca_id } ] }, "num_lines": 2 } implicit_hdca1, job_id1 = self._run_tool_get_collection_and_job_id( history_id, "random_lines1", inputs1 ) inputs2 = { - "f1": "__collection_reduce__|%s" % ( implicit_hdca1[ "id" ] ), - "f2": "__collection_reduce__|%s" % ( implicit_hdca1[ "id" ] ) + "f1": { "src": "hdca", "id": implicit_hdca1[ "id" ] }, + "f2": { "src": "hdca", "id": implicit_hdca1[ "id" ] }, } reduction_run_output = self.dataset_populator.run_tool( tool_id="multi_data_param", @@ -402,12 +402,12 @@ hdca = self.dataset_collection_populator.create_pair_in_history( history_id, contents=["1 2 3\n4 5 6", "7 8 9\n10 11 10"] ).json() hdca_id = hdca[ "id" ] inputs1 = { - "input|__collection_multirun__": hdca_id, + "input": { "batch": True, "values": [ { "src": "hdca", "id": hdca_id } ] }, "num_lines": 2 } implicit_hdca1, job_id1 = self._run_tool_get_collection_and_job_id( history_id, "random_lines1", inputs1 ) inputs2 = { - "input|__collection_multirun__": implicit_hdca1[ "id" ], + "input": { "batch": True, "values": [ { "src": "hdca", "id": implicit_hdca1[ "id" ] } ] }, "num_lines": 1 } _, job_id2 = self._run_tool_get_collection_and_job_id( history_id, "random_lines1", inputs2 ) https://bitbucket.org/galaxy/galaxy-central/commits/708d988d3e7b/ Changeset: 708d988d3e7b User: jmchilton Date: 2014-09-16 18:51:31+00:00 Summary: Fix spelling error in method name (thanks Nicola!). Affected #: 1 file diff -r e6616696052491bf563b690865f307f2de96d57c -r 708d988d3e7bf0ea9c91e0c2b2cbdc53037d3544 lib/galaxy/tools/parameters/meta.py --- a/lib/galaxy/tools/parameters/meta.py +++ b/lib/galaxy/tools/parameters/meta.py @@ -14,7 +14,7 @@ execution). """ - def classifiy_unmodified_parameter( input_key ): + def classify_unmodified_parameter( input_key ): value = incoming[ input_key ] if isinstance( value, dict ) and 'values' in value: # Explicit meta wrapper for inputs... @@ -55,7 +55,7 @@ values = __expand_collection_parameter( trans, input_key, incoming_val, collections_to_match ) return permutations.input_classification.MATCHED, values else: - return classifiy_unmodified_parameter( input_key ) + return classify_unmodified_parameter( input_key ) # Stick an unexpanded version of multirun keys so they can be replaced, # by expand_mult_inputs. https://bitbucket.org/galaxy/galaxy-central/commits/df92b55d194a/ Changeset: df92b55d194a User: jmchilton Date: 2014-09-22 14:24:39+00:00 Summary: Merged in jmchilton/galaxy-central-fork-1 (pull request #496) More consistent tool API for map/reduce operations. Affected #: 4 files diff -r 42f677bab2e4880b62758614fcb2c7dc27013788 -r df92b55d194a4d67a1b863c85044eb91c138c74b lib/galaxy/tools/parameters/basic.py --- a/lib/galaxy/tools/parameters/basic.py +++ b/lib/galaxy/tools/parameters/basic.py @@ -1887,6 +1887,11 @@ elif isinstance( value, dict ) and 'src' in value and 'id' in value: if value['src'] == 'hda': rval = trans.sa_session.query( trans.app.model.HistoryDatasetAssociation ).get( trans.app.security.decode_id(value['id']) ) + elif value['src'] == 'hdca': + decoded_id = trans.app.security.decode_id( value[ 'id' ] ) + rval = trans.sa_session.query( trans.app.model.HistoryDatasetCollectionAssociation ).get( decoded_id ) + else: + raise ValueError("Unknown input source %s passed to job submission API." % value['src']) elif str( value ).startswith( "__collection_reduce__|" ): encoded_id = str( value )[ len( "__collection_reduce__|" ): ] decoded_id = trans.app.security.decode_id( encoded_id ) @@ -1903,6 +1908,10 @@ raise ValueError( "The previously selected dataset has been previously deleted" ) if hasattr( v, "dataset" ) and v.dataset.state in [ galaxy.model.Dataset.states.ERROR, galaxy.model.Dataset.states.DISCARDED ]: raise ValueError( "The previously selected dataset has entered an unusable state" ) + if not self.multiple: + if len( values ) > 1: + raise ValueError( "More than one dataset supplied to single input dataset parameter.") + rval = values[ 0 ] return rval def to_string( self, value, app ): diff -r 42f677bab2e4880b62758614fcb2c7dc27013788 -r df92b55d194a4d67a1b863c85044eb91c138c74b lib/galaxy/tools/parameters/meta.py --- a/lib/galaxy/tools/parameters/meta.py +++ b/lib/galaxy/tools/parameters/meta.py @@ -14,7 +14,33 @@ execution). """ + def classify_unmodified_parameter( input_key ): + value = incoming[ input_key ] + if isinstance( value, dict ) and 'values' in value: + # Explicit meta wrapper for inputs... + is_batch = value.get( 'batch', False ) + is_linked = value.get( 'linked', True ) + if is_batch and is_linked: + classification = permutations.input_classification.MATCHED + elif is_batch: + classification = permutations.input_classification.MULTIPLIED + else: + classification = permutations.input_classification.SINGLE + if __collection_multirun_parameter( value ): + collection_value = value[ 'values' ][ 0 ] + values = __expand_collection_parameter( trans, input_key, collection_value, collections_to_match ) + else: + values = value[ 'values' ] + else: + classification = permutations.input_classification.SINGLE + values = value + return classification, values + + from galaxy.dataset_collections import matching + collections_to_match = matching.CollectionsToMatch() + def classifier( input_key ): + collection_multirun_key = "%s|__collection_multirun__" % input_key multirun_key = "%s|__multirun__" % input_key if multirun_key in incoming: multi_value = util.listify( incoming[ multirun_key ] ) @@ -24,41 +50,12 @@ if len( multi_value ) == 0: multi_value = None return permutations.input_classification.SINGLE, multi_value[ 0 ] + elif collection_multirun_key in incoming: + incoming_val = incoming[ collection_multirun_key ] + values = __expand_collection_parameter( trans, input_key, incoming_val, collections_to_match ) + return permutations.input_classification.MATCHED, values else: - return permutations.input_classification.SINGLE, incoming[ input_key ] - - from galaxy.dataset_collections import matching - collections_to_match = matching.CollectionsToMatch() - - def collection_classifier( input_key ): - multirun_key = "%s|__collection_multirun__" % input_key - if multirun_key in incoming: - incoming_val = incoming[ multirun_key ] - # If subcollectin multirun of data_collection param - value will - # be "hdca_id|subcollection_type" else it will just be hdca_id - if "|" in incoming_val: - encoded_hdc_id, subcollection_type = incoming_val.split( "|", 1 ) - else: - try: - src = incoming_val[ "src" ] - if src != "hdca": - raise exceptions.ToolMetaParameterException( "Invalid dataset collection source type %s" % src ) - encoded_hdc_id = incoming_val[ "id" ] - except TypeError: - encoded_hdc_id = incoming_val - subcollection_type = None - hdc_id = trans.app.security.decode_id( encoded_hdc_id ) - hdc = trans.sa_session.query( model.HistoryDatasetCollectionAssociation ).get( hdc_id ) - collections_to_match.add( input_key, hdc, subcollection_type=subcollection_type ) - if subcollection_type is not None: - from galaxy.dataset_collections import subcollections - subcollection_elements = subcollections.split_dataset_collection_instance( hdc, subcollection_type ) - return permutations.input_classification.MATCHED, subcollection_elements - else: - hdas = hdc.collection.dataset_instances - return permutations.input_classification.MATCHED, hdas - else: - return permutations.input_classification.SINGLE, incoming[ input_key ] + return classify_unmodified_parameter( input_key ) # Stick an unexpanded version of multirun keys so they can be replaced, # by expand_mult_inputs. @@ -76,20 +73,59 @@ multirun_found = False collection_multirun_found = False for key, value in incoming.iteritems(): - multirun_found = try_replace_key( key, "|__multirun__" ) or multirun_found - collection_multirun_found = try_replace_key( key, "|__collection_multirun__" ) or collection_multirun_found + if isinstance( value, dict ) and 'values' in value: + batch = value.get( 'batch', False ) + if batch: + if __collection_multirun_parameter( value ): + collection_multirun_found = True + else: + multirun_found = True + else: + continue + else: + # Old-style batching (remove someday? - pretty hacky and didn't live in API long) + try_replace_key( key, "|__multirun__" ) or multirun_found + try_replace_key( key, "|__collection_multirun__" ) or collection_multirun_found - if sum( [ 1 if f else 0 for f in [ multirun_found, collection_multirun_found ] ] ) > 1: - # In theory doable, but to complicated for a first pass. - message = "Cannot specify parallel execution across both multiple datasets and dataset collections." - raise exceptions.ToolMetaParameterException( message ) + expanded_incomings = permutations.expand_multi_inputs( incoming_template, classifier ) + if collections_to_match.has_collections(): + collection_info = trans.app.dataset_collections_service.match_collections( collections_to_match ) + else: + collection_info = None + return expanded_incomings, collection_info - if multirun_found: - return permutations.expand_multi_inputs( incoming_template, classifier ), None + +def __expand_collection_parameter( trans, input_key, incoming_val, collections_to_match ): + # If subcollectin multirun of data_collection param - value will + # be "hdca_id|subcollection_type" else it will just be hdca_id + if "|" in incoming_val: + encoded_hdc_id, subcollection_type = incoming_val.split( "|", 1 ) else: - expanded_incomings = permutations.expand_multi_inputs( incoming_template, collection_classifier ) - if collections_to_match.has_collections(): - collection_info = trans.app.dataset_collections_service.match_collections( collections_to_match ) - else: - collection_info = None - return expanded_incomings, collection_info + try: + src = incoming_val[ "src" ] + if src != "hdca": + raise exceptions.ToolMetaParameterException( "Invalid dataset collection source type %s" % src ) + encoded_hdc_id = incoming_val[ "id" ] + subcollection_type = incoming_val.get( 'map_over_type', None ) + except TypeError: + encoded_hdc_id = incoming_val + subcollection_type = None + hdc_id = trans.app.security.decode_id( encoded_hdc_id ) + hdc = trans.sa_session.query( model.HistoryDatasetCollectionAssociation ).get( hdc_id ) + collections_to_match.add( input_key, hdc, subcollection_type=subcollection_type ) + if subcollection_type is not None: + from galaxy.dataset_collections import subcollections + subcollection_elements = subcollections.split_dataset_collection_instance( hdc, subcollection_type ) + return subcollection_elements + else: + hdas = hdc.collection.dataset_instances + return hdas + + +def __collection_multirun_parameter( value ): + batch_values = util.listify( value[ 'values' ] ) + if len( batch_values ) == 1: + batch_over = batch_values[ 0 ] + if isinstance( batch_over, dict ) and ('src' in batch_over) and (batch_over[ 'src' ] == 'hdca'): + return True + return False diff -r 42f677bab2e4880b62758614fcb2c7dc27013788 -r df92b55d194a4d67a1b863c85044eb91c138c74b test/api/test_tools.py --- a/test/api/test_tools.py +++ b/test/api/test_tools.py @@ -109,6 +109,35 @@ output1_content = self.dataset_populator.get_history_dataset_content( history_id, dataset=output1 ) self.assertEqual( output1_content.strip(), "Cat1Test" ) + @skip_without_tool( "cat1" ) + def test_run_cat1_listified_param( self ): + # Run simple non-upload tool with an input data parameter. + history_id = self.dataset_populator.new_history() + new_dataset = self.dataset_populator.new_dataset( history_id, content='Cat1Testlistified' ) + inputs = dict( + input1=[dataset_to_param( new_dataset )], + ) + outputs = self._cat1_outputs( history_id, inputs=inputs ) + self.assertEquals( len( outputs ), 1 ) + output1 = outputs[ 0 ] + output1_content = self.dataset_populator.get_history_dataset_content( history_id, dataset=output1 ) + self.assertEqual( output1_content.strip(), "Cat1Testlistified" ) + + @skip_without_tool( "cat1" ) + def test_run_cat1_single_meta_wrapper( self ): + # Wrap input in a no-op meta parameter wrapper like Sam is planning to + # use for all UI API submissions. + history_id = self.dataset_populator.new_history() + new_dataset = self.dataset_populator.new_dataset( history_id, content='123' ) + inputs = dict( + input1={ 'batch': False, 'values': [ dataset_to_param( new_dataset ) ] }, + ) + outputs = self._cat1_outputs( history_id, inputs=inputs ) + self.assertEquals( len( outputs ), 1 ) + output1 = outputs[ 0 ] + output1_content = self.dataset_populator.get_history_dataset_content( history_id, dataset=output1 ) + self.assertEqual( output1_content.strip(), "123" ) + @skip_without_tool( "validation_default" ) def test_validation( self ): history_id = self.dataset_populator.new_history() @@ -118,6 +147,20 @@ response = self._run( "validation_default", history_id, inputs ) self._assert_status_code_is( response, 400 ) + @skip_without_tool( "collection_paired_test" ) + def test_collection_parameter( self ): + history_id = self.dataset_populator.new_history() + hdca_id = self.__build_pair( history_id, [ "123", "456" ] ) + inputs = { + "f1": { "src": "hdca", "id": hdca_id }, + } + output = self._run( "collection_paired_test", history_id, inputs, assert_ok=True ) + assert len( output[ 'jobs' ] ) == 1 + assert len( output[ 'implicit_collections' ] ) == 0 + assert len( output[ 'outputs' ] ) == 1 + contents = self.dataset_populator.get_history_dataset_content( history_id, hid=4 ) + assert contents.strip() == "123\n456", contents + @skip_without_tool( "cat1" ) def test_run_cat1_with_two_inputs( self ): # Run tool with an multiple data parameter and grouping (repeat) @@ -135,16 +178,31 @@ self.assertEqual( output1_content.strip(), "Cat1Test\nCat2Test" ) @skip_without_tool( "cat1" ) + def test_multirun_cat1_legacy( self ): + history_id, datasets = self._prepare_cat1_multirun() + inputs = { + "input1|__multirun__": datasets, + } + self._check_cat1_multirun( history_id, inputs ) + + @skip_without_tool( "cat1" ) def test_multirun_cat1( self ): + history_id, datasets = self._prepare_cat1_multirun() + inputs = { + "input1": { + 'batch': True, + 'values': datasets, + }, + } + self._check_cat1_multirun( history_id, inputs ) + + def _prepare_cat1_multirun( self ): history_id = self.dataset_populator.new_history() new_dataset1 = self.dataset_populator.new_dataset( history_id, content='123' ) new_dataset2 = self.dataset_populator.new_dataset( history_id, content='456' ) - inputs = { - "input1|__multirun__": [ - dataset_to_param( new_dataset1 ), - dataset_to_param( new_dataset2 ), - ], - } + return history_id, [ dataset_to_param( new_dataset1 ), dataset_to_param( new_dataset2 ) ] + + def _check_cat1_multirun( self, history_id, inputs ): outputs = self._cat1_outputs( history_id, inputs=inputs ) self.assertEquals( len( outputs ), 2 ) output1 = outputs[ 0 ] @@ -154,6 +212,20 @@ self.assertEquals( output1_content.strip(), "123" ) self.assertEquals( output2_content.strip(), "456" ) + @skip_without_tool( "random_lines1" ) + def test_multirun_non_data_parameter( self ): + history_id = self.dataset_populator.new_history() + new_dataset1 = self.dataset_populator.new_dataset( history_id, content='123\n456\n789' ) + inputs = { + 'input': dataset_to_param( new_dataset1 ), + 'num_lines': { 'batch': True, 'values': [ 1, 2, 3 ] } + } + outputs = self._run_and_get_outputs( 'random_lines1', history_id, inputs ) + # Assert we have three outputs with 1, 2, and 3 lines respectively. + assert len( outputs ) == 3 + outputs_contents = [ self.dataset_populator.get_history_dataset_content( history_id, dataset=o ).strip() for o in outputs ] + assert sorted( map( lambda c: len( c.split( "\n" ) ), outputs_contents ) ) == [ 1, 2, 3 ] + @skip_without_tool( "cat1" ) def test_multirun_in_repeat( self ): history_id = self.dataset_populator.new_history() @@ -177,35 +249,60 @@ self.assertEquals( output2_content.strip(), "Common\n456" ) @skip_without_tool( "cat1" ) - def test_multirun_on_multiple_inputs( self ): - history_id = self.dataset_populator.new_history() - new_dataset1 = self.dataset_populator.new_dataset( history_id, content='123' ) - new_dataset2 = self.dataset_populator.new_dataset( history_id, content='456' ) - new_dataset3 = self.dataset_populator.new_dataset( history_id, content='789' ) - new_dataset4 = self.dataset_populator.new_dataset( history_id, content='0ab' ) + def test_multirun_on_multiple_inputs_legacy( self ): + history_id, first_two, second_two = self._setup_two_multiruns() inputs = { - "input1|__multirun__": [ - dataset_to_param( new_dataset1 ), - dataset_to_param( new_dataset2 ), - ], - 'queries_0|input2|__multirun__': [ - dataset_to_param( new_dataset3 ), - dataset_to_param( new_dataset4 ), - ], + "input1|__multirun__": first_two, + 'queries_0|input2|__multirun__': second_two, } outputs = self._cat1_outputs( history_id, inputs=inputs ) self.assertEquals( len( outputs ), 2 ) outputs_contents = [ self.dataset_populator.get_history_dataset_content( history_id, dataset=o ).strip() for o in outputs ] assert "123\n789" in outputs_contents assert "456\n0ab" in outputs_contents - # TODO: Once cross production (instead of linking inputs) is an option - # again redo test with these checks... - # self.assertEquals( len( outputs ), 4 ) - # assert "123\n0ab" in outputs_contents - # assert "456\n789" in outputs_contents @skip_without_tool( "cat1" ) - def test_map_over_collection( self ): + def test_multirun_on_multiple_inputs( self ): + history_id, first_two, second_two = self._setup_two_multiruns() + inputs = { + "input1": { 'batch': True, 'values': first_two }, + 'queries_0|input2': { 'batch': True, 'values': second_two }, + } + outputs = self._cat1_outputs( history_id, inputs=inputs ) + self.assertEquals( len( outputs ), 2 ) + outputs_contents = [ self.dataset_populator.get_history_dataset_content( history_id, dataset=o ).strip() for o in outputs ] + assert "123\n789" in outputs_contents + assert "456\n0ab" in outputs_contents + + @skip_without_tool( "cat1" ) + def test_multirun_on_multiple_inputs_unlinked( self ): + history_id, first_two, second_two = self._setup_two_multiruns() + inputs = { + "input1": { 'batch': True, 'linked': False, 'values': first_two }, + 'queries_0|input2': { 'batch': True, 'linked': False, 'values': second_two }, + } + outputs = self._cat1_outputs( history_id, inputs=inputs ) + outputs_contents = [ self.dataset_populator.get_history_dataset_content( history_id, dataset=o ).strip() for o in outputs ] + self.assertEquals( len( outputs ), 4 ) + assert "123\n789" in outputs_contents + assert "456\n0ab" in outputs_contents + assert "123\n0ab" in outputs_contents + assert "456\n789" in outputs_contents + + def _setup_two_multiruns( self ): + history_id = self.dataset_populator.new_history() + new_dataset1 = self.dataset_populator.new_dataset( history_id, content='123' ) + new_dataset2 = self.dataset_populator.new_dataset( history_id, content='456' ) + new_dataset3 = self.dataset_populator.new_dataset( history_id, content='789' ) + new_dataset4 = self.dataset_populator.new_dataset( history_id, content='0ab' ) + return ( + history_id, + [ dataset_to_param( new_dataset1 ), dataset_to_param( new_dataset2 ) ], + [ dataset_to_param( new_dataset3 ), dataset_to_param( new_dataset4 ) ] + ) + + @skip_without_tool( "cat1" ) + def test_map_over_collection_legacy( self ): history_id = self.dataset_populator.new_history() hdca_id = self.__build_pair( history_id, [ "123", "456" ] ) inputs = { @@ -214,6 +311,18 @@ # first, next test method tests other. "input1|__collection_multirun__": hdca_id, } + self._run_and_check_simple_collection_mapping( history_id, inputs ) + + @skip_without_tool( "cat1" ) + def test_map_over_collection( self ): + history_id = self.dataset_populator.new_history() + hdca_id = self.__build_pair( history_id, [ "123", "456" ] ) + inputs = { + "input1": { 'batch': True, 'values': [ { 'src': 'hdca', 'id': hdca_id } ] }, + } + self._run_and_check_simple_collection_mapping( history_id, inputs ) + + def _run_and_check_simple_collection_mapping( self, history_id, inputs ): create = self._run_cat1( history_id, inputs=inputs, assert_ok=True ) outputs = create[ 'outputs' ] jobs = create[ 'jobs' ] @@ -229,12 +338,24 @@ self.assertEquals( output2_content.strip(), "456" ) @skip_without_tool( "cat1" ) - def test_map_over_nested_collections( self ): + def test_map_over_nested_collections_legacy( self ): history_id = self.dataset_populator.new_history() hdca_id = self.__build_nested_list( history_id ) inputs = { "input1|__collection_multirun__": dict( src="hdca", id=hdca_id ), } + self._check_simple_cat1_over_nested_collections( history_id, inputs ) + + @skip_without_tool( "cat1" ) + def test_map_over_nested_collections( self ): + history_id = self.dataset_populator.new_history() + hdca_id = self.__build_nested_list( history_id ) + inputs = { + "input1": { 'batch': True, 'values': [ dict( src="hdca", id=hdca_id ) ] }, + } + self._check_simple_cat1_over_nested_collections( history_id, inputs ) + + def _check_simple_cat1_over_nested_collections( self, history_id, inputs ): create = self._run_cat1( history_id, inputs=inputs, assert_ok=True ) outputs = create[ 'outputs' ] jobs = create[ 'jobs' ] @@ -257,7 +378,7 @@ self.assertEquals( outputs[ 0 ][ "id" ], first_object_forward_element[ "object" ][ "id" ] ) @skip_without_tool( "cat1" ) - def test_map_over_two_collections( self ): + def test_map_over_two_collections_legacy( self ): history_id = self.dataset_populator.new_history() hdca1_id = self.__build_pair( history_id, [ "123", "456" ] ) hdca2_id = self.__build_pair( history_id, [ "789", "0ab" ] ) @@ -265,7 +386,24 @@ "input1|__collection_multirun__": hdca1_id, "queries_0|input2|__collection_multirun__": hdca2_id, } - outputs = self._cat1_outputs( history_id, inputs=inputs ) + self._check_map_cat1_over_two_collections( history_id, inputs ) + + @skip_without_tool( "cat1" ) + def test_map_over_two_collections( self ): + history_id = self.dataset_populator.new_history() + hdca1_id = self.__build_pair( history_id, [ "123", "456" ] ) + hdca2_id = self.__build_pair( history_id, [ "789", "0ab" ] ) + inputs = { + "input1": { 'batch': True, 'values': [ {'src': 'hdca', 'id': hdca1_id } ] }, + "queries_0|input2": { 'batch': True, 'values': [ { 'src': 'hdca', 'id': hdca2_id } ] }, + } + self._check_map_cat1_over_two_collections( history_id, inputs ) + + def _check_map_cat1_over_two_collections( self, history_id, inputs ): + response = self._run_cat1( history_id, inputs ) + self._assert_status_code_is( response, 200 ) + response_object = response.json() + outputs = response_object[ 'outputs' ] self.assertEquals( len( outputs ), 2 ) output1 = outputs[ 0 ] output2 = outputs[ 1 ] @@ -274,6 +412,49 @@ self.assertEquals( output1_content.strip(), "123\n789" ) self.assertEquals( output2_content.strip(), "456\n0ab" ) + self.assertEquals( len( response_object[ 'jobs' ] ), 2 ) + self.assertEquals( len( response_object[ 'implicit_collections' ] ), 1 ) + + @skip_without_tool( "cat1" ) + def test_map_over_two_collections_unlinked( self ): + history_id = self.dataset_populator.new_history() + hdca1_id = self.__build_pair( history_id, [ "123", "456" ] ) + hdca2_id = self.__build_pair( history_id, [ "789", "0ab" ] ) + inputs = { + "input1": { 'batch': True, 'linked': False, 'values': [ {'src': 'hdca', 'id': hdca1_id } ] }, + "queries_0|input2": { 'batch': True, 'linked': False, 'values': [ { 'src': 'hdca', 'id': hdca2_id } ] }, + } + response = self._run_cat1( history_id, inputs ) + self._assert_status_code_is( response, 200 ) + response_object = response.json() + outputs = response_object[ 'outputs' ] + self.assertEquals( len( outputs ), 4 ) + + self.assertEquals( len( response_object[ 'jobs' ] ), 4 ) + # Implicit collections not created with unlinked inputs yet - this may + # be problematic. + self.assertEquals( len( response_object[ 'implicit_collections' ] ), 0 ) + + @skip_without_tool( "cat1" ) + def test_map_over_collected_and_individual_datasets( self ): + history_id = self.dataset_populator.new_history() + hdca1_id = self.__build_pair( history_id, [ "123", "456" ] ) + new_dataset1 = self.dataset_populator.new_dataset( history_id, content='789' ) + new_dataset2 = self.dataset_populator.new_dataset( history_id, content='0ab' ) + + inputs = { + "input1": { 'batch': True, 'values': [ {'src': 'hdca', 'id': hdca1_id } ] }, + "queries_0|input2": { 'batch': True, 'values': [ dataset_to_param( new_dataset1 ), dataset_to_param( new_dataset2 ) ] }, + } + response = self._run_cat1( history_id, inputs ) + self._assert_status_code_is( response, 200 ) + response_object = response.json() + outputs = response_object[ 'outputs' ] + self.assertEquals( len( outputs ), 2 ) + + self.assertEquals( len( response_object[ 'jobs' ] ), 2 ) + self.assertEquals( len( response_object[ 'implicit_collections' ] ), 1 ) + @skip_without_tool( "cat1" ) def test_cannot_map_over_incompatible_collections( self ): history_id = self.dataset_populator.new_history() @@ -289,7 +470,7 @@ assert run_response.status_code >= 400 @skip_without_tool( "multi_data_param" ) - def test_reduce_collections( self ): + def test_reduce_collections_legacy( self ): history_id = self.dataset_populator.new_history() hdca1_id = self.__build_pair( history_id, [ "123", "456" ] ) hdca2_id = self.dataset_collection_populator.create_list_in_history( history_id ).json()[ "id" ] @@ -297,6 +478,20 @@ "f1": "__collection_reduce__|%s" % hdca1_id, "f2": "__collection_reduce__|%s" % hdca2_id, } + self._check_simple_reduce_job( history_id, inputs ) + + @skip_without_tool( "multi_data_param" ) + def test_reduce_collections( self ): + history_id = self.dataset_populator.new_history() + hdca1_id = self.__build_pair( history_id, [ "123", "456" ] ) + hdca2_id = self.dataset_collection_populator.create_list_in_history( history_id ).json()[ "id" ] + inputs = { + "f1": { 'src': 'hdca', 'id': hdca1_id }, + "f2": { 'src': 'hdca', 'id': hdca2_id }, + } + self._check_simple_reduce_job( history_id, inputs ) + + def _check_simple_reduce_job( self, history_id, inputs ): create = self._run( "multi_data_param", history_id, inputs, assert_ok=True ) outputs = create[ 'outputs' ] jobs = create[ 'jobs' ] @@ -310,12 +505,27 @@ assert len( output2_content.strip().split("\n") ) == 3, output2_content @skip_without_tool( "collection_paired_test" ) - def test_subcollection_mapping( self ): + def test_subcollection_mapping_legacy( self ): history_id = self.dataset_populator.new_history() hdca_list_id = self.__build_nested_list( history_id ) inputs = { "f1|__collection_multirun__": "%s|paired" % hdca_list_id } + self._check_simple_subcollection_mapping( history_id, inputs ) + + @skip_without_tool( "collection_paired_test" ) + def test_subcollection_mapping( self ): + history_id = self.dataset_populator.new_history() + hdca_list_id = self.__build_nested_list( history_id ) + inputs = { + "f1": { + 'batch': True, + 'values': [ { 'src': 'hdca', 'map_over_type': 'paired', 'id': hdca_list_id }], + } + } + self._check_simple_subcollection_mapping( history_id, inputs ) + + def _check_simple_subcollection_mapping( self, history_id, inputs ): # Following wait not really needed - just getting so many database # locked errors with sqlite. self.dataset_populator.wait_for_history( history_id, assert_ok=True ) @@ -329,7 +539,7 @@ assert output2_content.strip() == "789\n0ab", output2_content @skip_without_tool( "collection_mixed_param" ) - def test_combined_mapping_and_subcollection_mapping( self ): + def test_combined_mapping_and_subcollection_mapping_legacy( self ): history_id = self.dataset_populator.new_history() nested_list_id = self.__build_nested_list( history_id ) create_response = self.dataset_collection_populator.create_list_in_history( history_id, contents=["xxx", "yyy"] ) @@ -338,6 +548,27 @@ "f1|__collection_multirun__": "%s|paired" % nested_list_id, "f2|__collection_multirun__": list_id, } + self._check_combined_mapping_and_subcollection_mapping( history_id, inputs ) + + @skip_without_tool( "collection_mixed_param" ) + def test_combined_mapping_and_subcollection_mapping( self ): + history_id = self.dataset_populator.new_history() + nested_list_id = self.__build_nested_list( history_id ) + create_response = self.dataset_collection_populator.create_list_in_history( history_id, contents=["xxx", "yyy"] ) + list_id = create_response.json()[ "id" ] + inputs = { + "f1": { + 'batch': True, + 'values': [ { 'src': 'hdca', 'map_over_type': 'paired', 'id': nested_list_id }], + }, + "f2": { + 'batch': True, + 'values': [ { 'src': 'hdca', 'id': list_id }], + }, + } + self._check_combined_mapping_and_subcollection_mapping( history_id, inputs ) + + def _check_combined_mapping_and_subcollection_mapping( self, history_id, inputs ): self.dataset_populator.wait_for_history( history_id, assert_ok=True ) outputs = self._run_and_get_outputs( "collection_mixed_param", history_id, inputs ) assert len( outputs ), 2 diff -r 42f677bab2e4880b62758614fcb2c7dc27013788 -r df92b55d194a4d67a1b863c85044eb91c138c74b test/api/test_workflows.py --- a/test/api/test_workflows.py +++ b/test/api/test_workflows.py @@ -361,13 +361,13 @@ hdca = self.dataset_collection_populator.create_pair_in_history( history_id, contents=["1 2 3\n4 5 6", "7 8 9\n10 11 10"] ).json() hdca_id = hdca[ "id" ] inputs1 = { - "input|__collection_multirun__": hdca_id, + "input": { "batch": True, "values": [ { "src": "hdca", "id": hdca_id } ] }, "num_lines": 2 } implicit_hdca1, job_id1 = self._run_tool_get_collection_and_job_id( history_id, "random_lines1", inputs1 ) inputs2 = { - "f1": "__collection_reduce__|%s" % ( implicit_hdca1[ "id" ] ), - "f2": "__collection_reduce__|%s" % ( implicit_hdca1[ "id" ] ) + "f1": { "src": "hdca", "id": implicit_hdca1[ "id" ] }, + "f2": { "src": "hdca", "id": implicit_hdca1[ "id" ] }, } reduction_run_output = self.dataset_populator.run_tool( tool_id="multi_data_param", @@ -413,12 +413,12 @@ hdca = self.dataset_collection_populator.create_pair_in_history( history_id, contents=["1 2 3\n4 5 6", "7 8 9\n10 11 10"] ).json() hdca_id = hdca[ "id" ] inputs1 = { - "input|__collection_multirun__": hdca_id, + "input": { "batch": True, "values": [ { "src": "hdca", "id": hdca_id } ] }, "num_lines": 2 } implicit_hdca1, job_id1 = self._run_tool_get_collection_and_job_id( history_id, "random_lines1", inputs1 ) inputs2 = { - "input|__collection_multirun__": implicit_hdca1[ "id" ], + "input": { "batch": True, "values": [ { "src": "hdca", "id": implicit_hdca1[ "id" ] } ] }, "num_lines": 1 } _, job_id2 = self._run_tool_get_collection_and_job_id( history_id, "random_lines1", inputs2 ) Repository URL: https://bitbucket.org/galaxy/galaxy-central/ -- This is a commit notification from bitbucket.org. 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commit/galaxy-central: jmchilton: Allow configuration of Galaxy via environment variables.
by commits-noreply＠bitbucket.org 22 Sep '14

22 Sep '14

1 new commit in galaxy-central: https://bitbucket.org/galaxy/galaxy-central/commits/42f677bab2e4/ Changeset: 42f677bab2e4 User: jmchilton Date: 2014-09-22 02:02:09+00:00 Summary: Allow configuration of Galaxy via environment variables. Allow overriding config defaults (those not specified in the configuration file) with GALAXY_CONFIG_<config-name> and allow overriding actual configured values with GALAXY_CONFIG_OVERRIDE_<config-name>. Here config-name is the actual value in galaxy.ini but in upper case. Affected #: 1 file diff -r 5fac4d4b7d7d6b056056bf2a6094c7777dc28a71 -r 42f677bab2e4880b62758614fcb2c7dc27013788 lib/galaxy/config.py --- a/lib/galaxy/config.py +++ b/lib/galaxy/config.py @@ -20,6 +20,9 @@ log = logging.getLogger( __name__ ) +CONFIG_DEFAULT_PREFIX = "GALAXY_CONFIG_" +CONFIG_OVERRIDE_PREFIX = "GALAXY_CONFIG_OVERRIDE_" + def resolve_path( path, root ): """If 'path' is relative make absolute by prepending 'root'""" @@ -36,6 +39,15 @@ deprecated_options = ( 'database_file', ) def __init__( self, **kwargs ): + for key in os.environ: + if key.startswith( CONFIG_OVERRIDE_PREFIX ): + config_key = key[ len( CONFIG_OVERRIDE_PREFIX ): ].lower() + kwargs[ config_key ] = os.environ[ key ] + elif key.startswith( CONFIG_DEFAULT_PREFIX ): + config_key = key[ len( CONFIG_DEFAULT_PREFIX ): ].lower() + if config_key not in kwargs: + kwargs[ config_key ] = os.environ[ key ] + self.config_dict = kwargs self.root = kwargs.get( 'root_dir', '.' ) Repository URL: https://bitbucket.org/galaxy/galaxy-central/ -- This is a commit notification from bitbucket.org. You are receiving this because you have the service enabled, addressing the recipient of this email.

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commit/galaxy-central: 2 new changesets
by commits-noreply＠bitbucket.org 21 Sep '14

21 Sep '14

2 new commits in galaxy-central: https://bitbucket.org/galaxy/galaxy-central/commits/87f7abe35390/ Changeset: 87f7abe35390 User: jmchilton Date: 2014-09-22 01:48:58+00:00 Summary: Reduce code duplication between job metrics and dependency resolution plugins. Same code reused again downstream in workflow schedulers plugin framework. Affected #: 3 files diff -r 6fe929724b066bd8b61ee0149479aba1e4e42f56 -r 87f7abe35390d8822f04e3e03dcc0598b5bf076c lib/galaxy/jobs/metrics/__init__.py --- a/lib/galaxy/jobs/metrics/__init__.py +++ b/lib/galaxy/jobs/metrics/__init__.py @@ -3,7 +3,7 @@ from xml.etree import ElementTree -from galaxy.util.submodules import submodules +from galaxy.util import plugin_config from galaxy import util from ..metrics import formatting @@ -49,17 +49,8 @@ return self.job_instrumenters[ destination_id ].collect_properties( job_id, job_directory ) def __plugins_dict( self ): - plugin_dict = {} - for plugin_module in self.__plugin_modules(): - for clazz in plugin_module.__all__: - plugin_type = getattr( clazz, 'plugin_type', None ) - if plugin_type: - plugin_dict[ plugin_type ] = clazz - return plugin_dict - - def __plugin_modules( self ): import galaxy.jobs.metrics.instrumenters - return submodules( galaxy.jobs.metrics.instrumenters ) + return plugin_config.plugins_dict( galaxy.jobs.metrics.instrumenters, 'plugin_type' ) class NullJobInstrumenter( object ): @@ -117,14 +108,7 @@ return per_plugin_properites def __plugins_for_element( self, plugins_element ): - plugins = [] - for plugin_element in plugins_element.getchildren(): - plugin_type = plugin_element.tag - plugin_kwds = dict( plugin_element.items() ) - plugin_kwds.update( self.extra_kwargs ) - plugin = self.plugin_classes[ plugin_type ]( **plugin_kwds ) - plugins.append( plugin ) - return plugins + return plugin_config.load_plugins_from_element(self.plugin_classes, plugins_element, self.extra_kwargs) @staticmethod def from_file( plugin_classes, conf_file, **kwargs ): diff -r 6fe929724b066bd8b61ee0149479aba1e4e42f56 -r 87f7abe35390d8822f04e3e03dcc0598b5bf076c lib/galaxy/tools/deps/__init__.py --- a/lib/galaxy/tools/deps/__init__.py +++ b/lib/galaxy/tools/deps/__init__.py @@ -12,7 +12,7 @@ from .resolvers import INDETERMINATE_DEPENDENCY from .resolvers.galaxy_packages import GalaxyPackageDependencyResolver from .resolvers.tool_shed_packages import ToolShedPackageDependencyResolver -from galaxy.util.submodules import submodules +from galaxy.util import plugin_config def build_dependency_manager( config ): @@ -110,24 +110,9 @@ :param root: Object representing the root ``<dependency_resolvers>`` object in the file. :type root: ``xml.etree.ElementTree.Element`` """ - resolvers = [] - resolvers_element = root - for resolver_element in resolvers_element.getchildren(): - resolver_type = resolver_element.tag - resolver_kwds = dict(resolver_element.items()) - resolver = self.resolver_classes[resolver_type](self, **resolver_kwds) - resolvers.append(resolver) - return resolvers + extra_kwds = dict( dependency_manager=self ) + return plugin_config.load_plugins_from_element( self.resolver_classes, root, extra_kwds ) def __resolvers_dict( self ): - resolver_dict = {} - for resolver_module in self.__resolver_modules(): - for clazz in resolver_module.__all__: - resolver_type = getattr(clazz, 'resolver_type', None) - if resolver_type: - resolver_dict[resolver_type] = clazz - return resolver_dict - - def __resolver_modules( self ): import galaxy.tools.deps.resolvers - return submodules( galaxy.tools.deps.resolvers ) + return plugin_config.plugins_dict( galaxy.tools.deps.resolvers, 'resolver_type' ) diff -r 6fe929724b066bd8b61ee0149479aba1e4e42f56 -r 87f7abe35390d8822f04e3e03dcc0598b5bf076c lib/galaxy/util/plugin_config.py --- /dev/null +++ b/lib/galaxy/util/plugin_config.py @@ -0,0 +1,32 @@ +from galaxy.util.submodules import submodules + + +def plugins_dict(module, plugin_type_identifier): + """ Walk through all classes in submodules of module and find ones labelled + with specified plugin_type_identifier and throw in a dictionary to allow + constructions from plugins by these types later on. + """ + plugin_dict = {} + + for plugin_module in submodules( module ): + # FIXME: this is not how one is suppose to use __all__ why did you do + # this past John? + for clazz in plugin_module.__all__: + plugin_type = getattr( clazz, plugin_type_identifier, None ) + if plugin_type: + plugin_dict[ plugin_type ] = clazz + + return plugin_dict + + +def load_plugins_from_element(plugins_dict, plugins_element, extra_kwds={}): + plugins = [] + + for plugin_element in plugins_element.getchildren(): + plugin_type = plugin_element.tag + plugin_kwds = dict( plugin_element.items() ) + plugin_kwds.update( extra_kwds ) + plugin = plugins_dict[ plugin_type ]( **plugin_kwds ) + plugins.append( plugin ) + + return plugins https://bitbucket.org/galaxy/galaxy-central/commits/5fac4d4b7d7d/ Changeset: 5fac4d4b7d7d User: jmchilton Date: 2014-09-22 01:48:58+00:00 Summary: Allow loading dependency resolvers and job metrics from YAML instead of XML. Mostly for downstream Pulsar configuration improvements - but I don't see a reason not to allow this in Galaxy as well. Besides simply being more pleasant to write - having everything configurable by Python dictionary should enable easier automation and programatic configuration of these job running systems. Affected #: 3 files diff -r 87f7abe35390d8822f04e3e03dcc0598b5bf076c -r 5fac4d4b7d7d6b056056bf2a6094c7777dc28a71 lib/galaxy/jobs/metrics/__init__.py --- a/lib/galaxy/jobs/metrics/__init__.py +++ b/lib/galaxy/jobs/metrics/__init__.py @@ -1,8 +1,6 @@ import collections import os -from xml.etree import ElementTree - from galaxy.util import plugin_config from galaxy import util @@ -37,7 +35,7 @@ self.set_destination_instrumenter( destination_id, instrumenter ) def set_destination_conf_element( self, destination_id, element ): - instrumenter = JobInstrumenter( self.plugin_classes, element ) + instrumenter = JobInstrumenter( self.plugin_classes, ('xml', element) ) self.set_destination_instrumenter( destination_id, instrumenter ) def set_destination_instrumenter( self, destination_id, job_instrumenter=None ): @@ -69,10 +67,10 @@ class JobInstrumenter( object ): - def __init__( self, plugin_classes, metrics_element, **kwargs ): + def __init__( self, plugin_classes, plugins_source, **kwargs ): self.extra_kwargs = kwargs self.plugin_classes = plugin_classes - self.plugins = self.__plugins_for_element( metrics_element ) + self.plugins = self.__plugins_from_source( plugins_source ) def pre_execute_commands( self, job_directory ): commands = [] @@ -107,12 +105,12 @@ log.exception( "Failed to collect job properties for plugin %s" % plugin ) return per_plugin_properites - def __plugins_for_element( self, plugins_element ): - return plugin_config.load_plugins_from_element(self.plugin_classes, plugins_element, self.extra_kwargs) + def __plugins_from_source( self, plugins_source ): + return plugin_config.load_plugins(self.plugin_classes, plugins_source, self.extra_kwargs) @staticmethod def from_file( plugin_classes, conf_file, **kwargs ): if not conf_file or not os.path.exists( conf_file ): return NULL_JOB_INSTRUMENTER - plugins_element = ElementTree.parse( conf_file ).getroot() - return JobInstrumenter( plugin_classes, plugins_element, **kwargs ) + plugins_source = plugin_config.plugin_source_from_path( conf_file ) + return JobInstrumenter( plugin_classes, plugins_source, **kwargs ) diff -r 87f7abe35390d8822f04e3e03dcc0598b5bf076c -r 5fac4d4b7d7d6b056056bf2a6094c7777dc28a71 lib/galaxy/tools/deps/__init__.py --- a/lib/galaxy/tools/deps/__init__.py +++ b/lib/galaxy/tools/deps/__init__.py @@ -7,8 +7,6 @@ import logging log = logging.getLogger( __name__ ) -from xml.etree import ElementTree - from .resolvers import INDETERMINATE_DEPENDENCY from .resolvers.galaxy_packages import GalaxyPackageDependencyResolver from .resolvers.tool_shed_packages import ToolShedPackageDependencyResolver @@ -94,8 +92,8 @@ def __build_dependency_resolvers( self, conf_file ): if not conf_file or not os.path.exists( conf_file ): return self.__default_dependency_resolvers() - root = ElementTree.parse( conf_file ).getroot() - return self.__parse_resolver_conf_xml( root ) + plugin_source = plugin_config.plugin_source_from_path( conf_file ) + return self.__parse_resolver_conf_xml( plugin_source ) def __default_dependency_resolvers( self ): return [ @@ -104,14 +102,11 @@ GalaxyPackageDependencyResolver(self, versionless=True), ] - def __parse_resolver_conf_xml(self, root): + def __parse_resolver_conf_xml(self, plugin_source): """ - - :param root: Object representing the root ``<dependency_resolvers>`` object in the file. - :type root: ``xml.etree.ElementTree.Element`` """ extra_kwds = dict( dependency_manager=self ) - return plugin_config.load_plugins_from_element( self.resolver_classes, root, extra_kwds ) + return plugin_config.load_plugins( self.resolver_classes, plugin_source, extra_kwds ) def __resolvers_dict( self ): import galaxy.tools.deps.resolvers diff -r 87f7abe35390d8822f04e3e03dcc0598b5bf076c -r 5fac4d4b7d7d6b056056bf2a6094c7777dc28a71 lib/galaxy/util/plugin_config.py --- a/lib/galaxy/util/plugin_config.py +++ b/lib/galaxy/util/plugin_config.py @@ -1,3 +1,16 @@ +from xml.etree import ElementTree + +try: + from galaxy import eggs + eggs.require('PyYAML') +except Exception: + # If not in Galaxy, ignore this. + pass +try: + import yaml +except ImportError: + yaml = None + from galaxy.util.submodules import submodules @@ -19,7 +32,15 @@ return plugin_dict -def load_plugins_from_element(plugins_dict, plugins_element, extra_kwds={}): +def load_plugins(plugins_dict, plugin_source, extra_kwds={}): + source_type, source = plugin_source + if source_type == "xml": + return __load_plugins_from_element(plugins_dict, source, extra_kwds) + else: + return __load_plugins_from_dicts(plugins_dict, source, extra_kwds) + + +def __load_plugins_from_element(plugins_dict, plugins_element, extra_kwds): plugins = [] for plugin_element in plugins_element.getchildren(): @@ -30,3 +51,31 @@ plugins.append( plugin ) return plugins + + +def __load_plugins_from_dicts(plugins_dict, configs, extra_kwds): + plugins = [] + + for config in configs: + plugin_type = config[ "type" ] + plugin_kwds = config + plugin_kwds.update( extra_kwds ) + plugin = plugins_dict[ plugin_type ]( **plugin_kwds ) + plugins.append( plugin ) + + return plugins + + +def plugin_source_from_path(path): + if path.endswith(".yaml") or path.endswith(".yml"): + return ('dict', __read_yaml(path)) + else: + return ('xml', ElementTree.parse( path ).getroot()) + + +def __read_yaml(path): + if yaml is None: + raise ImportError("Attempting to read YAML configuration file - but PyYAML dependency unavailable.") + + with open(path, "rb") as f: + return yaml.load(f) Repository URL: https://bitbucket.org/galaxy/galaxy-central/ -- This is a commit notification from bitbucket.org. 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[galaxyproject/usegalaxy-playbook] d2e65c: Remove downtime message from Test and Main
by GitHub 20 Sep '14

20 Sep '14

Branch: refs/heads/master Home: https://github.com/galaxyproject/usegalaxy-playbook Commit: d2e65c460baf48e0cc9e690541c8a5d8cfbf99c2 https://github.com/galaxyproject/usegalaxy-playbook/commit/d2e65c460baf48e0… Author: Nate Coraor <nate(a)bx.psu.edu> Date: 2014-09-20 (Sat, 20 Sep 2014) Changed paths: M production/group_vars/galaxyservers.yml M stage/group_vars/galaxyservers.yml Log Message: ----------- Remove downtime message from Test and Main

1 0

[galaxyproject/usegalaxy-playbook] 8d30db: Update Test/Main Pulsar and set new retry options ...
by GitHub 19 Sep '14

19 Sep '14

Branch: refs/heads/master Home: https://github.com/galaxyproject/usegalaxy-playbook Commit: 8d30dbcb984e82bb4f1fc3d4f60f2e5bf1ed0363 https://github.com/galaxyproject/usegalaxy-playbook/commit/8d30dbcb984e82bb… Author: Nate Coraor <nate(a)bx.psu.edu> Date: 2014-09-19 (Fri, 19 Sep 2014) Changed paths: M production/group_vars/pulsarservers.yml M production/host_vars/login5.stampede.tacc.utexas.edu.yml M stage/group_vars/all.yml M stage/host_vars/login5.stampede.tacc.utexas.edu.yml Log Message: ----------- Update Test/Main Pulsar and set new retry options for transfers. Thanks @jmchilton.

1 0

[galaxyproject/usegalaxy-playbook] 23f869: Update Test (did this earlier, forgot to commit/pu...
by GitHub 19 Sep '14

19 Sep '14

Branch: refs/heads/master Home: https://github.com/galaxyproject/usegalaxy-playbook Commit: 23f869e97e75e93a1a8805f903688790391a1e14 https://github.com/galaxyproject/usegalaxy-playbook/commit/23f869e97e75e93a… Author: Nate Coraor <nate(a)bx.psu.edu> Date: 2014-09-19 (Fri, 19 Sep 2014) Changed paths: M stage/group_vars/all.yml Log Message: ----------- Update Test (did this earlier, forgot to commit/push). Commit: 53a0f63a3576fc40f630d1dc390d6d72eb52b722 https://github.com/galaxyproject/usegalaxy-playbook/commit/53a0f63a3576fc40… Author: Nate Coraor <nate(a)bx.psu.edu> Date: 2014-09-19 (Fri, 19 Sep 2014) Changed paths: M production/group_vars/pulsarservers.yml M stage/group_vars/pulsarservers.yml Log Message: ----------- Update Test/Main Pulsar (ditto). Compare: https://github.com/galaxyproject/usegalaxy-playbook/compare/7b729c1a8fac...…

1 0

commit/galaxy-central: guerler: Charts: Fix selection grid
by commits-noreply＠bitbucket.org 19 Sep '14

19 Sep '14

1 new commit in galaxy-central: https://bitbucket.org/galaxy/galaxy-central/commits/6fe929724b06/ Changeset: 6fe929724b06 User: guerler Date: 2014-09-19 17:11:06+00:00 Summary: Charts: Fix selection grid Affected #: 2 files diff -r afdd7586c0e66d84c2da3401b1b1c1fc79a48cc7 -r 6fe929724b066bd8b61ee0149479aba1e4e42f56 config/plugins/visualizations/charts/static/build-app.js --- a/config/plugins/visualizations/charts/static/build-app.js +++ b/config/plugins/visualizations/charts/static/build-app.js @@ -3,4 +3,4 @@ // (c) 2009-2013 Jeremy Ashkenas, DocumentCloud Inc. // Underscore may be freely distributed under the MIT license. -define("mvc/ui/ui-modal",[],function(){var 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n=this;this.$el.on("input",function(){n.options.onchange&&n.options.onchange(n.$el.val())})},value:function(e){return e!==undefined&&this.$el.val(e),this.$el.val()},_template:function(e){return e.area?'<textarea id="'+e.id+'" class="ui-textarea '+e.cls+'"></textarea>':'<input id="'+e.id+'" type="'+e.type+'" value="'+e.value+'" placeholder="'+e.placeholder+'" class="ui-input '+e.cls+'">'}}),v=Backbone.View.extend({optionsDefault:{value:""},initialize:function(t){this.options=e.merge(t,this.optionsDefault),this.setElement(this._template(this.options))},value:function(e){return e!==undefined&&this.$el.val(e),this.$el.val()},_template:function(e){return'<hidden id="'+e.id+'" value="'+e.value+'"/>'}});return{Anchor:c,Button:f,ButtonIcon:l,ButtonMenu:i,Icon:a,Image:o,Input:d,Label:u,Message:h,Modal:s,RadioButton:r.RadioButton,Checkbox:r.Checkbox,Radio:r.Radio,Searchbox:p,Select:t,Hidden:v,Slider:n}}),define("plugin/library/jobs",["utils/utils"],function(e){return Backbone.Model.extend({initialize:function(t,n){this.app=t,this.options=e.merge(n,this.optionsDefault)},request:function(e,t,n,r,i){var s=this;e.state("wait","Requesting job results...");var o=e.get("dataset_id_job");o!=""?s._wait(e,r,i):s._submit(e,t,n,r,i)},cleanup:function(t){var n=this,r=t.get("dataset_id_job");r!=""&&(e.request("PUT",config.root+"api/histories/none/contents/"+r,{deleted:!0},function(){n._refreshHdas()}),t.set("dataset_id_job",""))},_submit:function(t,n,r,i,s){var o=this,u=t.id,a=t.get("type"),f=t.definition;data={tool_id:"charts",inputs:{input:{id:t.get("dataset_id"),src:"hda"},module:f.execute,columns:r,settings:n}},t.state("wait","Sending job request..."),e.request("POST",config.root+"api/tools",data,function(e){if(!e.outputs||e.outputs.length==0)t.state("failed","Job submission failed. No response."),s&&s();else{o._refreshHdas();var n=e.outputs[0];t.state("wait","Your job has been queued. You may close the browser window. The job will run in the background."),t.set("dataset_id_job",n.id),this.app.storage.save(),o._wait(t,i,s)}},function(e){var n="";e&&e.message&&e.message.data&&e.message.data.input&&(n=e.message.data.input+"."),t.state("failed","This visualization requires the 'charts' tool. Please make sure it is installed. "+n),s&&s()})},_wait:function(t,n,r){var i=this;e.request("GET",config.root+"api/datasets/"+t.get("dataset_id_job"),{},function(e){var s=!1;switch(e.state){case"ok":t.state("wait","Job completed successfully..."),n&&n(e),s=!0;break;case"error":t.state("failed","Job has failed. Please check the history for details."),r&&r(e),s=!0;break;case"running":t.state("wait","Your job is running. You may close the browser window. The job will continue in the background.")}s||setTimeout(function(){i._wait(t,n,r)},i.app.config.get("query_timeout"))})},_refreshHdas:function(){Galaxy&&Galaxy.currHistoryPanel&&Galaxy.currHistoryPanel.refreshContents()}})}),define("plugin/library/datasets",["utils/utils"],function(e){return Backbone.Collection.extend({list:{},cache:{},initialize:function(t,n){this.app=t,this.options=e.merge(n,this.optionsDefault)},request:function(e){e.groups?this._get_blocks(e):this._get_dataset(e.id,e.success,e.error)},_get_blocks:function(e){function h(i){c._get(i,function(){var s=!1;for(var o in e.groups){destination_group=e.groups[o],source_group=i.groups[o],destination_group.values||(destination_group.values=[]),destination_group.values=destination_group.values.concat(source_group.values);if(source_group.values.length==0){s=!0;break}}if(++l<a&&!s){n&&n(parseInt(l/a*100));var u=i.start+r;i=$.extend(!0,f,{start:u}),h(i)}else t()})}var t=e.success,n=e.progress,r=this.app.config.get("query_limit"),i=this.app.config.get("query_timeout"),s=e.start||0,o=s+e.query_limit||s+this.app.config.get("query_limit"),u=Math.abs(o-s);if(u<=0){console.debug("FAILED - Datasets::request() - Invalid query range.");return}var a=Math.ceil(u/r)||1,f=$.extend(!0,{},e),l=0,c=this,p=$.extend(!0,f,{start:s});this._get_dataset(e.id,function(){h(p)})},_get_dataset:function(t,n,r){var i=this.list[t];if(i){n(i);return}var s=this;e.request("GET",config.root+"api/datasets/"+t,{},function(e){switch(e.state){case"error":r&&r(e);break;default:s.list[t]=e,n(e)}})},_block_id:function(e,t){return e.id+"_"+e.start+"_"+e.start+this.app.config.get("query_limit")+"_"+t},_get:function(e,t){e.start=e.start||0;var n=[],r={},i=0;for(var s in e.groups){var o=e.groups[s];for(var u in o.columns){var a=o.columns[u].index,f=this._block_id(e,a);if(this.cache[f]||a==="auto"||a==="zero")continue;!r[a]&&a!==undefined&&(r[a]=i,n.push(a),i++)}}if(n.length==0){this._fill_from_cache(e),t(e);return}var l={dataset_id:e.id,start:e.start,columns:n},c=this;this._fetch(l,function(r){for(var i in r){var s=n[i],o=c._block_id(e,s);c.cache[o]=r[i]}c._fill_from_cache(e),t(e)})},_fill_from_cache:function(e){var t=e.start;console.debug("Datasets::_fill_from_cache() - Filling request from cache at "+t+".");var n=0;for(var r in e.groups){var i=e.groups[r];for(var s in i.columns){var o=i.columns[s],u=this._block_id(e,o.index),a=this.cache[u];a&&(n=Math.max(n,a.length))}}n==0&&console.debug("Datasets::_fill_from_cache() - Reached data range limit.");for(var r in e.groups){var i=e.groups[r];i.values=[];for(var f=0;f<n;f++)i.values[f]={x:parseInt(f)+t}}for(var r in e.groups){var i=e.groups[r];for(var s in i.columns){var o=i.columns[s];switch(o.index){case"auto":for(var f=0;f<n;f++){var l=i.values[f];l[s]=parseInt(f)+t}break;case"zero":for(var f=0;f<n;f++){var l=i.values[f];l[s]=0}break;default:var u=this._block_id(e,o.index),a=this.cache[u];for(var f=0;f<n;f++){var l=i.values[f],c=a[f];isNaN(c)&&!o.is_label&&(c=0),l[s]=c}}}}},_fetch:function(t,n){var r=t.start?t.start:0,i=this.app.config.get("query_limit"),s=0;t.columns&&(s=t.columns.length,console.debug("Datasets::_fetch() - Fetching "+s+" column(s) at "+r+".")),s==0&&console.debug("Datasets::_fetch() - No columns requested");var o="";for(var u in t.columns)o+=t.columns[u]+",";o=o.substring(0,o.length-1);var a=this;e.request("GET",config.root+"api/datasets/"+t.dataset_id,{data_type:"raw_data",provider:"dataset-column",limit:i,offset:r,indeces:o},function(e){var t=new Array(s);for(var r=0;r<s;r++)t[r]=[];for(var r in e.data){var i=e.data[r];for(var o in i){var u=i[o];u!==undefined&&u!=2147483647&&t[o].push(u)}}console.debug("Datasets::_fetch() - Fetching complete."),n(t)})}})}),define("plugin/models/group",[],function(){return Backbone.Model.extend({defaults:{key:"Data label",date:""},reset:function(){this.clear({silent:!0}).set(this.defaults),this.trigger("reset",this)}})}),define("plugin/models/groups",["plugin/models/group"],function(e){return Backbone.Collection.extend({model:e})}),define("plugin/models/chart",["plugin/models/groups"],function(e){return Backbone.Model.extend({defaults:{id:null,title:"",type:"",date:null,state:"",state_info:"",modified:!1,dataset_id:"",dataset_id_job:""},initialize:function(t){this.groups=new e,this.settings=new Backbone.Model},reset:function(){this.clear({silent:!0}).set(this.defaults),this.groups.reset(),this.settings.clear(),this.trigger("reset",this)},copy:function(e){var t=this;t.clear({silent:!0}).set(this.defaults),t.set(e.attributes),t.settings=e.settings.clone(),t.groups.reset(),e.groups.each(function(e){t.groups.add(e.clone())}),t.trigger("change",t)},state:function(e,t){this.set("state",e),this.set("state_info",t),this.trigger("set:state"),console.debug("Chart:state() - "+t+" ("+e+")")}})});var Visualization=Backbone.Model.extend({defaults:{config:{}},urlRoot:function(){var e="/api/visualizations";return window.galaxy_config&&galaxy_config.root?galaxy_config.root+e:e},initialize:function(e){_.isObject(e.config)&&_.isObject(this.defaults.config)&&_.defaults(e.config,this.defaults.config),this._setUpListeners()},_setUpListeners:function(){},set:function(e,t){if(e==="config"){var n=this.get("config");_.isObject(n)&&(t=_.extend(_.clone(n),t))}return Backbone.Model.prototype.set.call(this,e,t),this},toString:function(){var e=this.get("id")||"";return this.get("title")&&(e+=":"+this.get("title")),"Visualization("+e+")"}}),VisualizationCollection=Backbone.Collection.extend({model:Visualization,url:function(){return galaxy_config.root+"api/visualizations"},initialize:function(e,t){t=t||{}},set:function(e,t){var n=this;e=_.map(e,function(e){var t=n.get(e.id);if(!t)return e;var r=t.toJSON();return _.extend(r,e),r}),Backbone.Collection.prototype.set.call(this,e,t)},toString:function(){return["VisualizationCollection(",[this.historyId,this.length].join(),")"].join("")}});define("mvc/visualization/visualization-model",function(){}),define("plugin/library/storage",["utils/utils","plugin/models/chart","plugin/models/group","mvc/visualization/visualization-model"],function(e,t,n){return Backbone.Model.extend({vis:null,initialize:function(e){this.app=e,this.chart=this.app.chart,this.options=this.app.options,this.id=this.options.id,this.vis=new Visualization({type:"charts",config:{dataset_id:this.options.config.dataset_id,chart_dict:{}}}),this.id&&(this.vis.id=this.id);var t=this.options.config.chart_dict;t&&(this.vis.get("config").chart_dict=t)},save:function(){var e=this.app.chart;this.vis.get("config").chart_dict={};var t=e.get("title");t!=""&&this.vis.set("title",t);var n={attributes:e.attributes,settings:e.settings.attributes,groups:[]};e.groups.each(function(e){n.groups.push(e.attributes)}),this.vis.get("config").chart_dict=n;var r=this;this.vis.save().fail(function(e,t,n){console.error(e,t,n)}).then(function(e){e&&e.id&&(r.id=e.id)})},load:function(){var e=this.vis.get("config").chart_dict;if(!e.attributes)return!1;var t=e.attributes.type;if(!t)return console.debug("Storage::load() - Chart type not provided. Invalid format."),!1;var r=this.app.types.get(t);if(!r)return console.debug("Storage::load() - Chart type not supported. Please re-configure the chart. Resetting chart."),!1;console.debug("Storage::load() - Loading chart type "+t+"."),this.chart.definition=r,this.chart.set(e.attributes),this.chart.state("ok","Loading saved visualization..."),this.chart.settings.set(e.settings);for(var i in e.groups)this.chart.groups.add(new n(e.groups[i]));return this.chart.set("modified",!1),!0}})}),define("plugin/library/deferred",["utils/utils"],function(e){return Backbone.Model.extend({queue:[],process:{},counter:0,initialize:function(){this.on("refresh",function(){for(var e in this.queue)if(this.counter==0){var t=this.queue[e];this.queue.splice(e,1),t()}})},execute:function(e){this.queue.push(e),this.trigger("refresh")},register:function(){var t=e.uuid();return this.process[t]=!0,this.counter++,console.debug("Deferred:register() - Registering "+t),t},done:function(e){this.process[e]&&(delete this.process[e],this.counter--,console.debug("Deferred:done() - Unregistering "+e),this.trigger("refresh"))},ready:function(){return this.counter==0}})}),define("plugin/views/viewport",["mvc/ui/ui-portlet","mvc/ui/ui-misc","utils/utils"],function(e,t,n){return Backbone.View.extend({container_list:[],canvas_list:[],initialize:function(e,t){this.app=e,this.chart=this.app.chart,this.options=n.merge(t,this.optionsDefault),this.setElement($(this._template())),this._fullscreen(this.$el,100),this._createContainer("div");var r=this;this.chart.on("redraw",function(){r._draw(r.chart)}),this.chart.on("set:state",function(){var e=r.$el.find("#info"),t=r.$el.find(".charts-viewport-container"),n=e.find("#icon");n.removeClass(),e.show(),e.find("#text").html(r.chart.get("state_info"));var i=r.chart.get("state");switch(i){case"ok":e.hide(),t.show();break;case"failed":n.addClass("icon fa fa-warning"),t.hide();break;default:n.addClass("icon fa fa-spinner fa-spin"),t.show()}})},show:function(){this.$el.show()},hide:function(){this.$el.hide()},_fullscreen:function(e,t){e.css("height",$(window).height()-t),$(window).resize(function(){e.css("height",$(window).height()-t)})},_createContainer:function(e,t){t=t||1;for(var n in this.container_list)this.container_list[n].remove();this.container_list=[],this.canvas_list=[];for(var n=0;n<t;n++){var r=$(this._templateContainer(e,parseInt(100/t)));this.$el.append(r),this.container_list[n]=r,this.canvas_list[n]=r.find(".charts-viewport-canvas").attr("id")}},_draw:function(e){var t=this,n=this.app.deferred.register(),r=e.get("type");this.chart_definition=e.definition;var i=1;e.settings.get("use_panels")==="true"&&(i=e.groups.length),this._createContainer(this.chart_definition.tag,i),e.state("wait","Please wait...");if(!this.chart_definition.execute||this.chart_definition.execute&&e.get("modified"))this.app.jobs.cleanup(e),e.set("modified",!1);var t=this;require(["plugin/charts/"+this.app.chartPath(r)+"/wrapper"],function(r){if(t.chart_definition.execute)t.app.jobs.request(e,t._defaultSettingsString(e),t._defaultRequestString(e),function(){var i=new r(t.app,{process_id:n,chart:e,request_dictionary:t._defaultRequestDictionary(e),canvas_list:t.canvas_list})},function(){this.app.deferred.done(n)});else var i=new r(t.app,{process_id:n,chart:e,request_dictionary:t._defaultRequestDictionary(e),canvas_list:t.canvas_list})})},_defaultRequestString:function(e){var t="",n=0,r=this;return e.groups.each(function(e){n++;for(var i in r.chart_definition.columns)t+=i+"_"+n+":"+(parseInt(e.get(i))+1)+", "}),t.substring(0,t.length-2)},_defaultSettingsString:function(e){var t="";for(key in e.settings.attributes)t+=key+":"+e.settings.get(key)+", ";return t.substring(0,t.length-2)},_defaultRequestDictionary:function(e){var t={groups:[]};this.chart_definition.execute?t.id=e.get("dataset_id_job"):t.id=e.get("dataset_id");var r=0,i=this;return e.groups.each(function(e){var s={};for(var o in i.chart_definition.columns){var u=i.chart_definition.columns[o];s[o]=n.merge({index:e.get(o)},u)}t.groups.push({key:++r+":"+e.get("key"),columns:s})}),t},_template:function(){return'<div class="charts-viewport"><div id="info" class="info"><span id="icon" class="icon"/><span id="text" class="text" /></div></div>'},_templateContainer:function(e,t){return'<div class="charts-viewport-container" style="width:'+t+'%;">'+'<div id="menu"/>'+"<"+e+' id="'+n.uuid()+'" class="charts-viewport-canvas">'+"</div>"}})}),define("plugin/library/screenshot",["libs/underscore"],function(e){function t(e){e.$el.find("svg").length>0?r(e):n(e)}function n(e){try{var t=e.$el.find(".jqplot-target"),n=t.jqplotToImageStr({});n&&(window.location.href=n.replace("image/png","image/octet-stream"))}catch(r){console.debug("FAILED - Screenshot::_fromCanvas() - "+r),e.error&&e.error("Please reduce your chart to a single panel and try again.")}}function r(e){var t=e.$el,n=e.url,r=e.name,s=new XMLSerializer,o=document.createElement("canvas"),u=$(o),a=t.find("svg").length,f=t.find("svg").first(),l=parseInt(f.css("height")),c=parseInt(f.css("width"));u.attr("width",c*a),u.attr("height",l),(!o.getContext||!o.getContext("2d"))&&alert("Your browser doesn't support this feature, please use a modern browser");var h=o.getContext("2d"),p=0;t.find("svg").each(function(){var e=$(this);e.attr({version:"1.1",xmlns:"http://www.w3.org/2000/svg",width:c,height:l});var t=s.serializeToString(this);h.drawSvg(t,p,0,c,l),p+=c}),window.location.href=i(o,o.getContext("2d"),"white").replace("image/png","image/octet-stream")}function i(e,t,n){var r=e.width,i=e.height,s;if(n){s=t.getImageData(0,0,r,i);var o=t.globalCompositeOperation;t.globalCompositeOperation="destination-over",t.fillStyle=n,t.fillRect(0,0,r,i)}var u=e.toDataURL("image/png");return n&&(t.clearRect(0,0,r,i),t.putImageData(s,0,0),t.globalCompositeOperation=o),u}function s(e){window.location.href="data:none/none;base64,"+btoa(a(e).string)}function o(e){for(var t in document.styleSheets){var n=document.styleSheets[t],r=n.cssRules;if(r)for(var i=0,s=r.length;i<s;i++)try{e.find(r[i].selectorText).each(function(e,t){t.style.cssText+=r[i].style.cssText})}catch(o){}}}function u(e){var t=a(e),n={filename:name||"chart",type:"application/pdf",height:t.height,width:t.width,scale:2,svg:t.string},r=$("body"),i=r.find("#viewport-form");i.length===0&&(i=$("<form>",{id:"viewport-form",method:"post",action:"http://export.highcharts.com/",display:"none"}),r.append(i)),i.empty();for(name in n){var s=$("<input/>",{type:"hidden",name:name,value:n[name]});i.append(s)}try{i.submit()}catch(o){console.log(o)}}function a(e){if(e.$el.find("svg").length==0&&e.error){e.error("No SVG found. This chart type does not support SVG/PDF export.");return}var t=e.$el,n=t.find("svg").length,r=parseInt(t.find("svg").first().css("height")),i=parseInt(t.find("svg").first().css("width")),s=new XMLSerializer,u=$("<svg/>");u.attr({version:"1.1",xmlns:"http://www.w3.org/2000/svg",width:i*n,height:r});var a="",f=0;return t.find("svg").each(function(){var e=$(this).clone();o(e);var t=$('<g transform="translate('+f+', 0)">');t.append(e.find("g").first()),u.append(t),f+=i}),{string:s.serializeToString(u[0]),height:r,width:i}}return{createPNG:t,createSVG:s,createPDF:u}}),define("plugin/views/viewer",["utils/utils","mvc/ui/ui-misc","mvc/ui/ui-portlet","plugin/views/viewport","plugin/library/screenshot"],function(e,t,n,r,i){return Backbone.View.extend({initialize:function(e,s){this.app=e,this.chart=this.app.chart,this.viewport_view=new r(e);var o=this;this.message=new t.Message;var u=new t.ButtonMenu({icon:"fa-camera",title:"Screenshot",tooltip:"Download as PNG, SVG or PDF file"});u.addMenu({id:"button-png",title:"Save as PNG",icon:"fa-file",onclick:function(){o._wait(o.chart,function(){i.createPNG({$el:o.viewport_view.$el,title:o.chart.get("title"),error:function(e){o.message.update({message:e,status:"danger"})}})})}}),u.addMenu({id:"button-svg",title:"Save as SVG",icon:"fa-file-text-o",onclick:function(){o._wait(o.chart,function(){i.createSVG({$el:o.viewport_view.$el,title:o.chart.get("title"),error:function(e){o.message.update({message:e,status:"danger"})}})})}}),u.addMenu({id:"button-png",title:"Save as PDF",icon:"fa-file-o",onclick:function(){o.app.modal.show({title:"Send chart data for PDF creation",body:"Galaxy does not provide integrated PDF export scripts. You may click 'Continue' to create the PDF by using a 3rd party service (https://export.highcharts.com)",buttons:{Cancel:function(){o.app.modal.hide()},Continue:function(){o.app.modal.hide(),o._wait(o.chart,function(){i.createPDF({$el:o.viewport_view.$el,title:o.chart.get("title"),error:function(e){o.message.update({message:e,status:"danger"})}})})}}})}}),this.portlet=new n.View({icon:"fa-bar-chart-o",title:"Viewport",scrollable:!1,operations:{edit_button:new t.ButtonIcon({icon:"fa-edit",tooltip:"Customize this chart",title:"Editor",onclick:function(){o._wait(o.chart,function(){o.app.go("editor")})}}),picture_button_menu:u}}),this.portlet.append(this.message.$el),this.portlet.append(this.viewport_view.$el),this.setElement(this.portlet.$el);var o=this;this.chart.on("change:title",function(){o._refreshTitle()})},show:function(){this.$el.show(),$(window).trigger("resize")},hide:function(){this.$el.hide()},_refreshTitle:function(){var e=this.chart.get("title");this.portlet.title(e)},_wait:function(e,t){this.app.deferred.ready()?t():this.message.update({message:"Your chart is currently being processed. Please wait and try again."})}})}),define("mvc/ui/ui-tabs",["utils/utils"],function(e){var t=Backbone.View.extend({optionsDefault:{title_new:"",operations:null,onnew:null,max:null,onchange:null},initialize:function(t){this.visible=!1,this.$nav=null,this.$content=null,this.first_tab=null,this.current_id=null,this.options=e.merge(t,this.optionsDefault);var n=$(this._template(this.options));this.$nav=n.find(".tab-navigation"),this.$content=n.find(".tab-content"),this.setElement(n),this.list={};var r=this;this.options.operations&&$.each(this.options.operations,function(e,t){t.$el.prop("id",e),r.$nav.find(".operations").append(t.$el)});if(this.options.onnew){var i=$(this._template_tab_new(this.options));this.$nav.append(i),i.tooltip({title:"Add a new tab",placement:"bottom",container:r.$el}),i.on("click",function(e){i.tooltip("hide"),r.options.onnew()})}},size:function(){return _.size(this.list)},current:function(){return this.$el.find(".tab-pane.active").attr("id")},add:function(e){var t=this,n=e.id,r=$(this._template_tab(e)),i=$(this._template_tab_content(e));this.list[n]=e.ondel?!0:!1,this.options.onnew?this.$nav.find("#new-tab").before(r):this.$nav.append(r),i.append(e.$el),this.$content.append(i),this.size()==1&&(r.addClass("active"),i.addClass("active"),this.first_tab=n),this.options.max&&this.size()>=this.options.max&&this.$el.find("#new-tab").hide();if(e.ondel){var s=r.find("#delete");s.tooltip({title:"Delete this tab",placement:"bottom",container:t.$el}),s.on("click",function(){return s.tooltip("destroy"),t.$el.find(".tooltip").remove(),e.ondel(),!1})}r.on("click",function(r){r.preventDefault(),e.onclick?e.onclick():t.show(n)}),this.current_id||(this.current_id=n)},del:function(e){this.$el.find("#tab-"+e).remove(),this.$el.find("#"+e).remove(),this.first_tab==e&&(this.first_tab=null),this.first_tab!=null&&this.show(this.first_tab),this.list[e]&&delete this.list[e],this.size()<this.options.max&&this.$el.find("#new-tab").show()},delRemovable:function(){for(var e in this.list)this.del(e)},show:function(e){this.$el.fadeIn("fast"),this.visible=!0,e&&(this.$el.find("#tab-"+this.current_id).removeClass("active"),this.$el.find("#"+this.current_id).removeClass("active"),this.$el.find("#tab-"+e).addClass("active"),this.$el.find("#"+e).addClass("active"),this.current_id=e),this.options.onchange&&this.options.onchange(e)},hide:function(){this.$el.fadeOut("fast"),this.visible=!1},hideOperation:function(e){this.$nav.find("#"+e).hide()},showOperation:function(e){this.$nav.find("#"+e).show()},setOperation:function(e,t){var n=this.$nav.find("#"+e);n.off("click"),n.on("click",t)},title:function(e,t){var n=this.$el.find("#tab-title-text-"+e);return t&&n.html(t),n.html()},retitle:function(e){var t=0;for(var n in this.list)this.title(n,++t+": "+e)},_template:function(e){return'<div class="ui-tabs tabbable tabs-left"><ul id="tab-navigation" class="tab-navigation nav nav-tabs"><div class="operations" style="float: right; margin-bottom: 4px;"></div></ul><div id="tab-content" class="tab-content"/></div>'},_template_tab_new:function(e){return'<li id="new-tab"><a href="javascript:void(0);"><i class="ui-tabs-add fa fa-plus-circle"/>'+e.title_new+"</a>"+"</li>"},_template_tab:function(e){var t='<li id="tab-'+e.id+'" class="tab-element">'+'<a id="tab-title-link-'+e.id+'" title="" href="#'+e.id+'" data-original-title="">'+'<span id="tab-title-text-'+e.id+'" class="tab-title-text">'+e.title+"</span>";return e.ondel&&(t+='<i id="delete" class="ui-tabs-delete fa fa-minus-circle"/>'),t+="</a></li>",t},_template_tab_content:function(e){return'<div id="'+e.id+'" class="tab-pane"/>'}});return{View:t}}),define("mvc/ui/ui-table",["utils/utils"],function(e){var t=Backbone.View.extend({row:null,row_count:0,optionsDefault:{content:"No content available.",onchange:null,ondblclick:null,onconfirm:null,cls:"ui-table",cls_tr:""},events:{click:"_onclick",dblclick:"_ondblclick"},initialize:function(t){this.options=e.merge(t,this.optionsDefault);var n=$(this._template(this.options));this.$thead=n.find("thead"),this.$tbody=n.find("tbody"),this.$tmessage=n.find("tmessage"),this.setElement(n),this.row=this._row()},addHeader:function(e){var t=$("<th></th>");t.append(e),this.row.append(t)},appendHeader:function(){this.$thead.append(this.row),this.row=$("<tr></tr>")},add:function(e,t,n){var r=$("<td></td>");t&&r.css("width",t),n&&r.css("text-align",n),r.append(e),this.row.append(r)},append:function(e,t){this._commit(e,t,!1)},prepend:function(e,t){this._commit(e,t,!0)},get:function(e){return this.$el.find("#"+e)},del:function(e){var t=this.$tbody.find("#"+e);t.length>0&&(t.remove(),this.row_count--,this._refresh())},delAll:function(){this.$tbody.empty(),this.row_count=0,this._refresh()},value:function(e){this.before=this.$tbody.find(".current").attr("id"),e!==undefined&&(this.$tbody.find("tr").removeClass("current"),e&&this.$tbody.find("#"+e).addClass("current"));var t=this.$tbody.find(".current").attr("id");return t===undefined?null:(t!=this.before&&this.options.onchange&&this.options.onchange(e),t)},size:function(){return this.$tbody.find("tr").length},_commit:function(e,t,n){this.del(e),this.row.attr("id",e),n?this.$tbody.prepend(this.row):this.$tbody.append(this.row),t&&(this.row.hide(),this.row.fadeIn()),this.row=this._row(),this.row_count++,this._refresh()},_row:function(){return $('<tr class="'+this.options.cls_tr+'"></tr>')},_onclick:function(e){var t=this.value(),n=$(e.target).closest("tr").attr("id");n!=""&&n&&t!=n&&(this.options.onconfirm?this.options.onconfirm(n):this.value(n))},_ondblclick:function(e){var t=this.value();t&&this.options.ondblclick&&this.options.ondblclick(t)},_refresh:function(){this.row_count==0?this.$tmessage.show():this.$tmessage.hide()},_template:function(e){return'<div><table class="'+e.cls+'">'+"<thead></thead>"+"<tbody></tbody>"+"</table>"+"<tmessage>"+e.content+"</tmessage>"+"<div>"}});return{View:t}}),define("plugin/views/group",["mvc/ui/ui-table","mvc/ui/ui-misc","utils/utils"],function(e,t,n){return Backbone.View.extend({initialize:function(r,i){this.app=r;var s=this;this.chart=this.app.chart,this.group=i.group,this.group_key=new t.Input({placeholder:"Data label",onchange:function(e){s.group.set("key",e)}}),this.table=new e.View({content:"No data column."});var o=$("<div/>");o.append(n.wrap((new t.Label({title:"Provide a label:"})).$el)),o.append(n.wrap(this.group_key.$el)),o.append(n.wrap((new t.Label({title:"Select columns:"})).$el)),o.append(n.wrap(this.table.$el)),this.setElement(o);var s=this;this.chart.on("change:dataset_id",function(){s._refreshTable()}),this.chart.on("change:type",function(){s._refreshTable()}),this.group.on("change:key",function(){s._refreshGroupKey()}),this.group.on("change",function(){s._refreshGroup()}),this._refreshTable(),this._refreshGroupKey(),this._refreshGroup()},_refreshTable:function(){var e=this.chart.get("dataset_id"),n=this.chart.get("type");if(!e||!n)return;var r=this,i=this.chart.definition;this.table.delAll();var s={};for(var o in i.columns){var u=i.columns[o];if(!u){console.debug("Group::_refreshTable() - Skipping column definition.");continue}var a=new t.Select.View({id:"select_"+o,wait:!0}),f=u.title;u.is_unique&&(f+=" (all data labels)"),this.table.add(f,"25%"),this.table.add(a.$el),this.table.append(o),s[o]=a}this.chart.state("wait","Loading metadata...");var l=this.app.deferred.register(),c={id:e,success:function(e){for(var t in s)r._addRow(t,e,s,i.columns[t]);r.chart.state("ok","Metadata initialized..."),r.app.deferred.done(l)}};this.app.datasets.request(c)},_addRow:function(e,t,n,r){var i=this,s=r.is_label,o=r.is_auto,u=r.is_numeric,a=r.is_unique,f=r.is_zero,l=[],c=n[e];o&&l.push({label:"Column: Row Number",value:"auto"}),f&&l.push({label:"Column: None",value:"zero"});var h=t.metadata_column_types;for(var p in h){var d=!1;h[p]=="int"||h[p]=="float"?d=u:d=s,d&&l.push({label:"Column: "+(parseInt(p)+1)+" ["+h[p]+"]",value:p})}c.update(l),a&&this.chart.groups.first()&&this.group.set(e,this.chart.groups.first().get(e));if(!c.exists(this.group.get(e))){var v=c.first();console.debug('Group()::_addRow() - Switching model value from "'+this.group.get(e)+'" to "'+v+'".'),this.group.set(e,v)}c.value(this.group.get(e)),this.group.off("change:"+e),this.group.on("change:"+e,function(){c.value(i.group.get(e))}),c.setOnChange(function(t){a?i.chart.groups.each(function(n){n.set(e,t)}):i.group.set(e,t),i.chart.set("modified",!0)}),c.show()},_refreshGroup:function(){this.group.set("date",n.time())},_refreshGroupKey:function(){var e=this.group.get("key");e===undefined&&(e=""),this.group_key.value(e)}})}),define("plugin/library/ui-table-form",["mvc/ui/ui-table","mvc/ui/ui-misc","utils/utils"],function(e,t,n){var r=Backbone.View.extend({optionsDefault:{title:"",content:"",mode:""},list:[],initialize:function(r,i){this.app=r,this.options=n.merge(i,this.optionsDefault),this.table_title=new t.Label({title:this.options.title}),this.table=new e.View({content:this.options.content});var s=$('<div class="ui-table-form"/>');this.options.title&&s.append(n.wrap(this.table_title.$el)),s.append(n.wrap(this.table.$el)),this.setElement(s)},title:function(e){this.table_title.title(e)},update:function(e,t){this.table.delAll(),this.list=[];for(var n in e)this._add(e[n].id||n,e[n],t);for(var n in this.list)this.list[n].trigger("change")},_add:function(e,n,r){var i=this,s=null,o=n.type;switch(o){case"text":s=new t.Input({id:"field-"+e,placeholder:n.placeholder,value:r.get(e),onchange:function(t){r.set(e,t)}});break;case"radiobutton":s=new t.RadioButton.View({id:"field-"+e,data:n.data,value:r.get(e),onchange:function(t){r.set(e,t);var s=_.findWhere(n.data,{value:t});if(s&&s.operations){var o=s.operations;for(var u in o.show){var a=o.show[u];i.table.get(a).show()}for(var u in o.hide){var a=o.hide[u];i.table.get(a).hide()}}}});break;case"select":s=new t.Select.View({id:"field-"+e,data:n.data,value:r.get(e),onchange:function(t){r.set(e,t);var s=_.findWhere(n.data,{value:t});if(s&&s.operations){var o=s.operations;for(var u in o.show){var a=o.show[u];i.table.get(a).show()}for(var u in o.hide){var a=o.hide[u];i.table.get(a).hide()}}}});break;case"dataset":s=new t.Select.View({id:"field-"+e,onchange:function(t){r.set(e,t)}}),i.app.datasets.on("all",function(){var t=[];i.app.datasets.each(function(e){e.get("datatype_id")==n.data&&t.push({value:e.get("id"),label:e.get("name")})}),s.update(t),r.get(e)||r.set(e,s.first()),s.value(r.get(e))}),i.app.datasets.trigger("all.datasets");break;case"textarea":s=new t.Textarea({id:"field-"+e,onchange:function(){r.set(e,s.value())}});break;case"separator":s=$("<div/>");break;default:s=new t.Input({id:"field-"+e,placeholder:n.placeholder,type:n.type,onchange:function(){r.set(e,s.value())}})}if(o!="separator"){r.get(e)||r.set(e,n.init),s.value(r.get(e)),this.list[e]=s;var u=$("<div/>");u.append(s.$el),n.info&&u.append('<div class="ui-table-form-info">'+n.info+"</div>"),this.options.style=="bold"?(this.table.add((new t.Label({title:n.title,cls:"form-label"})).$el),this.table.add(u)):(this.table.add('<span class="ui-table-form-title">'+n.title+"</span>","25%"),this.table.add(u))}else this.table.add('<div class="ui-table-form-separator">'+n.title+":<div/>"),this.table.add($("<div/>"));this.table.append(e),n.hide&&this.table.get(e).hide()}});return{View:r}}),define("plugin/views/settings",["mvc/ui/ui-misc","plugin/library/ui-table-form","utils/utils"],function(e,t,n){return Backbone.View.extend({initialize:function(e,n){this.app=e;var r=this;this.chart=this.app.chart,this.form=new t.View(e,{title:"Configuration",content:"This chart type does not provide any options."}),this.setElement(this.form.$el);var r=this;this.chart.on("change",function(){r._refresh()})},_refresh:function(){var e=this.chart.definition;if(!e)return;this.form.title(e.category+" - "+e.title+":"),this.form.update(e.settings,this.chart.settings)}})}),define("plugin/views/types",["utils/utils","mvc/ui/ui-misc"],function(e,t){return Backbone.View.extend({optionsDefault:{onchange:null,ondblclick:null},events:{click:"_onclick",dblclick:"_ondblclick"},initialize:function(n,r){var i=this;this.app=n,this.options=e.merge(r,this.optionsDefault);var s=$('<div class="charts-grid"/>');s.append(e.wrap((new t.Label({title:"How many data points would you like to analyze?"})).$el)),this.library=new t.RadioButton.View({data:[{label:"Few (<500)",value:"small"},{label:"Some (<10k)",value:"medium"},{label:"Many (>10k)",value:"large"}],onchange:function(e){i._filter(e)}}),s.append(e.wrap(this.library.$el)),this.setElement(s),this._render(),this.library.value("small")},value:function(e){var t=this.$el.find(".current").attr("id");e!==undefined&&(this.$el.find(".current").removeClass("current"),this.$el.find("#"+e).addClass("current"));var n=this.$el.find(".current").attr("id");return n===undefined?null:(n!=t&&this.options.onchange&&this.options.onchange(e),n)},_filter:function(e){this.$el.find(".header").hide();var t=this.app.types.attributes;for(var n in t){var r=t[n],i=this.$el.find("#"+n),s=this.$el.find("#types-header-"+this.categories_index[r.category]),o=r.keywords||"";o.indexOf(e)>=0?(i.show(),s.show()):i.hide()}},_render:function(){this.categories={},this.categories_index={};var e=0,t=this.app.types.attributes;for(var n in t){var r=t[n],i=r.category;this.categories[i]||(this.categories[i]={},this.categories_index[i]=e++),this.categories[i][n]=r}for(var i in this.categories){var s=$('<div style="clear: both;"/>');s.append(this._template_header({id:"types-header-"+this.categories_index[i],title:i}));for(var n in this.categories[i]){var r=this.categories[i][n],o=r.title+" ("+r.library+")";r.zoomable&&(o='<span class="fa fa-search-plus"/>'+o),s.append(this._template_item({id:n,title:o,url:config.app_root+"charts/"+this.app.chartPath(n)+"/logo.png"}))}this.$el.append(s)}},_onclick:function(e){var t=this.value(),n=$(e.target).closest(".item").attr("id");n!=""&&n&&t!=n&&this.value(n)},_ondblclick:function(e){var t=this.value();t&&this.options.ondblclick&&this.options.ondblclick(t)},_template_header:function(e){return'<div id="'+e.id+'" class="header">'+"• "+e.title+"<div>"},_template_item:function(e){return'<div id="'+e.id+'" class="item">'+'<img class="image" src="'+e.url+'">'+'<div class="title">'+e.title+"</div>"+"<div>"}})}),define("plugin/views/editor",["mvc/ui/ui-tabs","mvc/ui/ui-misc","mvc/ui/ui-portlet","utils/utils","plugin/models/chart","plugin/models/group","plugin/views/group","plugin/views/settings","plugin/views/types"],function(e,t,n,r,i,s,o,u,a){return Backbone.View.extend({initialize:function(i,s){var o=this;this.app=i,this.chart=this.app.chart,this.message=new t.Message,this.portlet=new n.View({icon:"fa-bar-chart-o",title:"Editor",operations:{save:new t.ButtonIcon({icon:"fa-save",tooltip:"Draw Chart",title:"Draw",onclick:function(){o._saveChart()}}),back:new t.ButtonIcon({icon:"fa-caret-left",tooltip:"Return to Viewer",title:"Cancel",onclick:function(){o.app.go("viewer"),o.app.storage.load()}})}}),this.types=new a(i,{onchange:function(e){var t=o.app.types.get(e);t||console.debug("FAILED - Editor::onchange() - Chart type not supported."),o.chart.definition=t,o.chart.settings.clear(),o.chart.set({type:e}),o.chart.set("modified",!0),console.debug("Editor::onchange() - Switched chart type.")},ondblclick:function(e){o._saveChart()}}),this.tabs=new e.View({title_new:"Add Data",onnew:function(){var e=o._addGroupModel();o.tabs.show(e.id)}}),this.title=new t.Input({placeholder:"Chart title",onchange:function(){o.chart.set("title",o.title.value())}});var f=$("<div/>");f.append(r.wrap((new t.Label({title:"Provide a chart title:"})).$el)),f.append(r.wrap(this.title.$el)),f.append(r.wrap(this.types.$el)),this.tabs.add({id:"main",title:"Start",$el:f}),this.settings=new u(this.app),this.tabs.add({id:"settings",title:"Configuration",$el:this.settings.$el}),this.portlet.append(this.message.$el),this.portlet.append(this.tabs.$el),this.setElement(this.portlet.$el),this.tabs.hideOperation("back");var o=this;this.chart.on("change:title",function(e){o._refreshTitle()}),this.chart.on("change:type",function(e){o.types.value(e.get("type"))}),this.chart.on("reset",function(e){o._resetChart()}),this.app.chart.on("redraw",function(e){o.portlet.showOperation("back")}),this.app.chart.groups.on("add",function(e){o._addGroup(e)}),this.app.chart.groups.on("remove",function(e){o._removeGroup(e)}),this.app.chart.groups.on("reset",function(e){o._removeAllGroups()}),this.app.chart.groups.on("change:key",function(e){o._refreshGroupKey()}),this._resetChart()},show:function(){this.$el.show()},hide:function(){this.$el.hide()},_refreshTitle:function(){var e=this.chart.get("title");this.portlet.title(e),this.title.value(e)},_refreshGroupKey:function(){var e=this,t=0;this.chart.groups.each(function(n){var r=n.get("key","");r==""&&(r="Data label"),e.tabs.title(n.id,++t+": "+r)})},_addGroupModel:function(){var e=new s({id:r.uuid()});return this.chart.groups.add(e),e},_addGroup:function(e){var t=this,n=new o(this.app,{group:e});this.tabs.add({id:e.id,$el:n.$el,ondel:function(){t.chart.groups.remove(e.id)}}),this._refreshGroupKey(),this.chart.set("modified",!0)},_removeGroup:function(e){this.tabs.del(e.id),this._refreshGroupKey(),this.chart.set("modified",!0)},_removeAllGroups:function(e){this.tabs.delRemovable()},_resetChart:function(){this.chart.set("id",r.uuid()),this.chart.set("type","nvd3_bar"),this.chart.set("dataset_id",this.app.options.config.dataset_id),this.chart.set("title","New Chart"),this.portlet.hideOperation("back")},_saveChart:function(){this.chart.set({type:this.types.value(),title:this.title.value(),date:r.time()});if(this.chart.groups.length==0){this.message.update({message:"Please select data columns before drawing the chart."});var e=this._addGroupModel();this.tabs.show(e.id);return}var t=this,n=!0,i=this.chart.definition;this.chart.groups.each(function(e){if(!n)return;for(var r in i.columns)if(e.attributes[r]=="null"){t.message.update({status:"danger",message:"This chart type requires column types not found in your tabular file."}),t.tabs.show(e.id),n=!1;return}});if(!n)return;this.app.go("viewer");var t=this;this.app.deferred.execute(function(){t.app.storage.save(),t.chart.trigger("redraw")})}})}),define("plugin/models/config",[],function(){return Backbone.Model.extend({defaults:{query_limit:500,query_timeout:100}})}),define("plugin/charts/forms/default",[],function(){return{title:"",category:"",library:"",tag:"",keywords:"",query_limit:0,settings:{separator_x:{title:"X axis",type:"separator"},x_axis_label:{title:"Axis label",info:"Provide a label for the axis.",type:"text",init:"X-axis",placeholder:"Axis label"},x_axis_type:{title:"Axis value type",info:"Select the value type of the axis.",type:"select",init:"auto",data:[{label:"-- Do not show values --",value:"hide",operations:{hide:["x_axis_precision"]}},{label:"Auto",value:"auto",operations:{hide:["x_axis_precision"]}},{label:"Float",value:"f",operations:{show:["x_axis_precision"]}},{label:"Exponent",value:"e",operations:{show:["x_axis_precision"]}},{label:"Integer",value:"d",operations:{hide:["x_axis_precision"]}},{label:"Percentage",value:"p",operations:{show:["x_axis_precision"]}},{label:"SI-prefix",value:"s",operations:{hide:["x_axis_precision"]}}]},x_axis_precision:{title:"Axis tick format",info:"Select the tick format for the axis.",type:"select",init:"1",data:[{label:"0.00001",value:"5"},{label:"0.0001",value:"4"},{label:"0.001",value:"3"},{label:"0.01",value:"2"},{label:"0.1",value:"1"},{label:"1",value:"0"}]},separator_y:{title:"Y axis",type:"separator"},y_axis_label:{title:"Axis label",info:"Provide a label for the axis.",type:"text",init:"Y-axis",placeholder:"Axis label"},y_axis_type:{title:"Axis value type",info:"Select the value type of the 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arguments.length?(v=e,E):v},E.yRange=function(e){return arguments.length?(m=e,E):m},E.forceY=function(e){return arguments.length?(f=e,E):f},E.color=function(t){return arguments.length?(l=e.utils.getColor(t),E):l},E.id=function(e){return arguments.length?(i=e,E):i},E.showValues=function(e){return arguments.length?(c=e,E):c},E.valueFormat=function(e){return arguments.length?(h=e,E):h},E.rectClass=function(e){return arguments.length?(y=e,E):y},E},e.models.discreteBarChart=function(){function w(e){return e.each(function(e){var u=d3.select(this),p=this,y=(s||parseInt(u.style("width"))||960)-i.left-i.right,E=(o||parseInt(u.style("height"))||400)-i.top-i.bottom;w.update=function(){g.beforeUpdate(),u.call(w)},w.container=this;if(!e||!e.length||!e.filter(function(e){return e.values.length}).length){var S=u.selectAll(".nv-noData").data([m]);return S.enter().append("text").attr("class","nvd3 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arguments.length?(o=e,t.x(e),m):o},m.y=function(e){return arguments.length?(u=e,t.y(e),m):u},m.clipEdge=function(e){return arguments.length?(l=e,m):l},m.color=function(n){return arguments.length?(s=e.utils.getColor(n),t.color(s),m):s},m.interpolate=function(e){return arguments.length?(p=e,m):p},m.defined=function(e){return arguments.length?(a=e,m):a},m.isArea=function(e){return arguments.length?(f=d3.functor(e),m):f},m},e.models.lineChart=function(){function N(m){return m.each(function(m){var x=d3.select(this),C=this,k=(a||parseInt(x.style("width"))||960)-o.left-o.right,L=(f||parseInt(x.style("height"))||400)-o.top-o.bottom;N.update=function(){x.call(N)},N.container=this,b.disabled=m.map(function(e){return!!e.disabled});if(!w){var A;w={};for(A in b)b[A]instanceof Array?w[A]=b[A].slice(0):w[A]=b[A]}if(!m||!m.length||!m.filter(function(e){return e.values.length}).length){var O=x.selectAll(".nv-noData").data([E]);return O.enter().append("text").attr("class","nvd3 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t=e.models.line(),n=e.models.line(),r=e.models.axis(),i=e.models.axis(),s=e.models.axis(),o=e.models.axis(),u=e.models.legend(),a=d3.svg.brush(),f={top:30,right:30,bottom:30,left:60},l={top:0,right:30,bottom:20,left:60},c=e.utils.defaultColor(),h=null,p=null,d=100,v,m,g,y,b=!0,w=null,E=!0,S=function(e,t,n,r,i){return"<h3>"+e+"</h3>"+"<p>"+n+" at "+t+"</p>"},x="No Data Available.",T=d3.dispatch("tooltipShow","tooltipHide","brush"),N=0;t.clipEdge(!0),n.interactive(!1),r.orient("bottom").tickPadding(5),i.orient("left"),s.orient("bottom").tickPadding(5),o.orient("left");var C=function(n,s){var o=n.pos[0]+(s.offsetLeft||0),u=n.pos[1]+(s.offsetTop||0),a=r.tickFormat()(t.x()(n.point,n.pointIndex)),f=i.tickFormat()(t.y()(n.point,n.pointIndex)),l=S(n.series.key,a,f,n,k);e.tooltip.show([o,u],l,null,null,s)};return t.dispatch.on("elementMouseover.tooltip",function(e){e.pos=[e.pos[0]+f.left,e.pos[1]+f.top],T.tooltipShow(e)}),t.dispatch.on("elementMouseout.tooltip",function(e){T.tooltipHide(e)}),T.on("tooltipHide",function(){E&&e.tooltip.cleanup()}),k.dispatch=T,k.legend=u,k.lines=t,k.lines2=n,k.xAxis=r,k.yAxis=i,k.x2Axis=s,k.y2Axis=o,d3.rebind(k,t,"defined","isArea","size","xDomain","yDomain","xRange","yRange","forceX","forceY","interactive","clipEdge","clipVoronoi","id"),k.options=e.utils.optionsFunc.bind(k),k.x=function(e){return arguments.length?(t.x(e),n.x(e),k):t.x},k.y=function(e){return arguments.length?(t.y(e),n.y(e),k):t.y},k.margin=function(e){return arguments.length?(f.top=typeof e.top!="undefined"?e.top:f.top,f.right=typeof e.right!="undefined"?e.right:f.right,f.bottom=typeof e.bottom!="undefined"?e.bottom:f.bottom,f.left=typeof e.left!="undefined"?e.left:f.left,k):f},k.margin2=function(e){return arguments.length?(l=e,k):l},k.width=function(e){return 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t.dispatch.on("elementMouseover.tooltip",function(e){e.pos=[e.pos[0]+o.left,e.pos[1]+o.top],S.tooltipShow(e)}),t.dispatch.on("elementMouseout.tooltip",function(e){S.tooltipHide(e)}),S.on("tooltipHide",function(){v&&e.tooltip.cleanup()}),C.dispatch=S,C.multibar=t,C.legend=i,C.xAxis=n,C.yAxis=r,d3.rebind(C,t,"x","y","xDomain","yDomain","xRange","yRange","forceX","forceY","clipEdge","id","delay","showValues","showBarLabels","valueFormat","stacked","barColor"),C.options=e.utils.optionsFunc.bind(C),C.margin=function(e){return arguments.length?(o.top=typeof e.top!="undefined"?e.top:o.top,o.right=typeof e.right!="undefined"?e.right:o.right,o.bottom=typeof e.bottom!="undefined"?e.bottom:o.bottom,o.left=typeof e.left!="undefined"?e.left:o.left,C):o},C.width=function(e){return arguments.length?(u=e,C):u},C.height=function(e){return arguments.length?(a=e,C):a},C.color=function(t){return arguments.length?(f=e.utils.getColor(t),i.color(f),C):f},C.showControls=function(e){return arguments.length?(l=e,C):l},C.showLegend=function(e){return arguments.length?(c=e,C):c},C.showXAxis=function(e){return arguments.length?(h=e,C):h},C.showYAxis=function(e){return arguments.length?(p=e,C):p},C.tooltip=function(e){return arguments.length?(m=e,C):m},C.tooltips=function(e){return arguments.length?(v=e,C):v},C.tooltipContent=function(e){return arguments.length?(m=e,C):m},C.state=function(e){return arguments.length?(b=e,C):b},C.defaultState=function(e){return arguments.length?(w=e,C):w},C.noData=function(e){return arguments.length?(E=e,C):E},C.transitionDuration=function(e){return arguments.length?(T=e,C):T},C},e.models.multiChart=function(){function C(e){return e.each(function(e){var u=d3.select(this),f=this;C.update=function(){u.call(C)},C.container=this;var 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o=i.pos[0]+(s.offsetLeft||0),u=i.pos[1]+(s.offsetTop||0),f=i.pos[0]+(s.offsetLeft||0),l=p.range()[0]+a.top+(s.offsetTop||0),c=h.range()[0]+a.left+(s.offsetLeft||0),d=i.pos[1]+(s.offsetTop||0),v=n.tickFormat()(t.x()(i.point,i.pointIndex)),m=r.tickFormat()(t.y()(i.point,i.pointIndex));T!=null&&e.tooltip.show([f,l],T(i.series.key,v,m,i,B),"n",1,s,"x-nvtooltip"),N!=null&&e.tooltip.show([c,d],N(i.series.key,v,m,i,B),"e",1,s,"y-nvtooltip"),C!=null&&e.tooltip.show([o,u],C(i.series.key,v,m,i.point.tooltip,i,B),i.value<0?"n":"s",null,s)},H=[{key:"Magnify",disabled:!0}];return t.dispatch.on("elementMouseout.tooltip",function(e){A.tooltipHide(e),d3.select(".nv-chart-"+t.id()+" .nv-series-"+e.seriesIndex+" .nv-distx-"+e.pointIndex).attr("y1",0),d3.select(".nv-chart-"+t.id()+" .nv-series-"+e.seriesIndex+" 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value="'+e.value+'">'+e.label+"</label>",t},_template:function(){return'<div class="btn-group ui-radiobutton" data-toggle="buttons"/>'}}),{Radio:n,RadioButton:i,Checkbox:r}}),define("mvc/ui/ui-button-menu",["utils/utils"],function(e){return Backbone.View.extend({optionsDefault:{id:"",title:"",floating:"right",icon:null,onclick:null,cls:"icon-btn",tooltip:"",target:"",href:"",onunload:null,visible:!0,tag:""},$menu:null,initialize:function(t){this.options=e.merge(t,this.optionsDefault),this.setElement($(this._template(this.options)));var n=$(this.el).find(".root"),r=this;n.on("click",function(e){$(".tooltip").hide(),e.preventDefault(),r.options.onclick&&r.options.onclick()}),this.options.visible||this.hide(),n.tooltip({title:t.tooltip,placement:"bottom"})},show:function(){$(this.el).show()},hide:function(){$(this.el).hide()},addMenu:function(t){var n={title:"",target:"",href:"",onclick:null,divider:!1,icon:null,cls:"button-menu 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'+e.icon+'"/>',n+="</div>",n}})}),define("mvc/ui/ui-misc",["utils/utils","mvc/ui/ui-select-default","mvc/ui/ui-slider","mvc/ui/ui-options","mvc/ui/ui-button-menu","mvc/ui/ui-modal"],function(e,t,n,r,i,s){var o=Backbone.View.extend({optionsDefault:{url:"",cls:""},initialize:function(t){this.options=e.merge(t,this.optionsDefault),this.setElement(this._template(this.options))},_template:function(e){return'<img class="ui-image '+e.cls+'" src="'+e.url+'"/>'}}),u=Backbone.View.extend({optionsDefault:{title:"",cls:""},initialize:function(t){this.options=e.merge(t,this.optionsDefault),this.setElement(this._template(this.options))},title:function(e){this.$el.html(e)},_template:function(e){return'<label class="ui-label '+e.cls+'">'+e.title+"</label>"},value:function(){return options.title}}),a=Backbone.View.extend({optionsDefault:{floating:"right",icon:"",tooltip:"",placement:"bottom",title:"",cls:""},initialize:function(t){this.options=e.merge(t,this.optionsDefault),this.setElement(this._template(this.options)),$(this.el).tooltip({title:t.tooltip,placement:"bottom"})},_template:function(e){return'<div><span class="fa '+e.icon+'" class="ui-icon"/> '+e.title+"</div>"}}),f=Backbone.View.extend({optionsDefault:{id:null,title:"",floating:"right",cls:"btn btn-default",icon:""},initialize:function(t){this.options=e.merge(t,this.optionsDefault),this.setElement(this._template(this.options)),$(this.el).on("click",function(){$(".tooltip").hide(),t.onclick&&t.onclick()}),$(this.el).tooltip({title:t.tooltip,placement:"bottom"})},_template:function(e){var t='<button id="'+e.id+'" type="submit" style="float: '+e.floating+';" type="button" class="ui-button '+e.cls+'">';return e.icon&&(t+='<i class="icon fa '+e.icon+'"></i> '),t+=e.title+"</button>",t}}),l=Backbone.View.extend({optionsDefault:{id:null,title:"",floating:"right",cls:"ui-button-icon",icon:"",tooltip:"",onclick:null},initialize:function(t){this.options=e.merge(t,this.optionsDefault),this.setElement(this._template(this.options)),this.$button=this.$el.find(".button");var n=this;$(this.el).on("click",function(){$(".tooltip").hide(),t.onclick&&!n.disabled&&t.onclick()}),$(this.el).tooltip({title:t.tooltip,placement:"bottom"})},disable:function(){this.$button.addClass("disabled"),this.disabled=!0},enable:function(){this.$button.removeClass("disabled"),this.disabled=!1},_template:function(e){var t="";e.title&&(t="width: auto;");var n='<div id="'+e.id+'" style="float: '+e.floating+"; "+t+'" class="'+e.cls+'">';return e.title?n+='<div class="button"><i class="icon fa '+e.icon+'"/> '+'<span class="title">'+e.title+"</span>"+"</div>":n+='<i class="icon fa '+e.icon+'"/>',n+="</div>",n}}),c=Backbone.View.extend({optionsDefault:{title:"",cls:""},initialize:function(t){this.options=e.merge(t,this.optionsDefault),this.setElement(this._template(this.options)),$(this.el).on("click",t.onclick)},_template:function(e){return'<div><a href="javascript:void(0)" class="ui-anchor '+e.cls+'">'+e.title+"</a></div>"}}),h=Backbone.View.extend({optionsDefault:{message:"",status:"info",persistent:!1},initialize:function(t){this.options=e.merge(t,this.optionsDefault),this.setElement("<div></div>")},update:function(t){this.options=e.merge(t,this.optionsDefault);if(t.message!=""){this.$el.html(this._template(this.options)),this.$el.find(".alert").append(t.message),this.$el.fadeIn();if(!t.persistent){var n=this;window.setTimeout(function(){n.$el.is(":visible")?n.$el.fadeOut():n.$el.hide()},3e3)}}else this.$el.fadeOut()},_template:function(e){return'<div class="ui-message alert alert-'+e.status+'"/>'}}),p=Backbone.View.extend({optionsDefault:{onclick:null,searchword:""},initialize:function(t){this.options=e.merge(t,this.optionsDefault),this.setElement(this._template(this.options));var n=this;this.options.onclick&&this.$el.on("submit",function(e){var t=n.$el.find("#search");n.options.onclick(t.val())})},_template:function(e){return'<div class="ui-search"><form onsubmit="return false;"><input id="search" class="form-control input-sm" type="text" name="search" placeholder="Search..." value="'+e.searchword+'">'+'<button type="submit" class="btn search-btn">'+'<i class="fa fa-search"></i>'+"</button>"+"</form>"+"</div>"}}),d=Backbone.View.extend({optionsDefault:{value:"",type:"text",placeholder:"",disabled:!1,visible:!0,cls:"",area:!1},initialize:function(t){this.options=e.merge(t,this.optionsDefault),this.setElement(this._template(this.options)),this.options.disabled&&this.$el.prop("disabled",!0),this.options.visible||this.$el.hide();var n=this;this.$el.on("input",function(){n.options.onchange&&n.options.onchange(n.$el.val())})},value:function(e){return e!==undefined&&this.$el.val(e),this.$el.val()},_template:function(e){return e.area?'<textarea id="'+e.id+'" class="ui-textarea '+e.cls+'"></textarea>':'<input id="'+e.id+'" type="'+e.type+'" value="'+e.value+'" placeholder="'+e.placeholder+'" class="ui-input '+e.cls+'">'}}),v=Backbone.View.extend({optionsDefault:{value:""},initialize:function(t){this.options=e.merge(t,this.optionsDefault),this.setElement(this._template(this.options))},value:function(e){return e!==undefined&&this.$el.val(e),this.$el.val()},_template:function(e){return'<hidden id="'+e.id+'" value="'+e.value+'"/>'}});return{Anchor:c,Button:f,ButtonIcon:l,ButtonMenu:i,Icon:a,Image:o,Input:d,Label:u,Message:h,Modal:s,RadioButton:r.RadioButton,Checkbox:r.Checkbox,Radio:r.Radio,Searchbox:p,Select:t,Hidden:v,Slider:n}}),define("plugin/library/jobs",["utils/utils"],function(e){return Backbone.Model.extend({initialize:function(t,n){this.app=t,this.options=e.merge(n,this.optionsDefault)},request:function(e,t,n,r,i){var s=this;e.state("wait","Requesting job results...");var o=e.get("dataset_id_job");o!=""?s._wait(e,r,i):s._submit(e,t,n,r,i)},cleanup:function(t){var n=this,r=t.get("dataset_id_job");r!=""&&(e.request("PUT",config.root+"api/histories/none/contents/"+r,{deleted:!0},function(){n._refreshHdas()}),t.set("dataset_id_job",""))},_submit:function(t,n,r,i,s){var o=this,u=t.id,a=t.get("type"),f=t.definition;data={tool_id:"charts",inputs:{input:{id:t.get("dataset_id"),src:"hda"},module:f.execute,columns:r,settings:n}},t.state("wait","Sending job request..."),e.request("POST",config.root+"api/tools",data,function(e){if(!e.outputs||e.outputs.length==0)t.state("failed","Job submission failed. No response."),s&&s();else{o._refreshHdas();var n=e.outputs[0];t.state("wait","Your job has been queued. You may close the browser window. The job will run in the background."),t.set("dataset_id_job",n.id),this.app.storage.save(),o._wait(t,i,s)}},function(e){var n="";e&&e.message&&e.message.data&&e.message.data.input&&(n=e.message.data.input+"."),t.state("failed","This visualization requires the 'charts' tool. Please make sure it is installed. "+n),s&&s()})},_wait:function(t,n,r){var i=this;e.request("GET",config.root+"api/datasets/"+t.get("dataset_id_job"),{},function(e){var s=!1;switch(e.state){case"ok":t.state("wait","Job completed successfully..."),n&&n(e),s=!0;break;case"error":t.state("failed","Job has failed. Please check the history for details."),r&&r(e),s=!0;break;case"running":t.state("wait","Your job is running. You may close the browser window. The job will continue in the background.")}s||setTimeout(function(){i._wait(t,n,r)},i.app.config.get("query_timeout"))})},_refreshHdas:function(){Galaxy&&Galaxy.currHistoryPanel&&Galaxy.currHistoryPanel.refreshContents()}})}),define("plugin/library/datasets",["utils/utils"],function(e){return Backbone.Collection.extend({list:{},cache:{},initialize:function(t,n){this.app=t,this.options=e.merge(n,this.optionsDefault)},request:function(e){e.groups?this._get_blocks(e):this._get_dataset(e.id,e.success,e.error)},_get_blocks:function(e){function h(i){c._get(i,function(){var s=!1;for(var o in e.groups){destination_group=e.groups[o],source_group=i.groups[o],destination_group.values||(destination_group.values=[]),destination_group.values=destination_group.values.concat(source_group.values);if(source_group.values.length==0){s=!0;break}}if(++l<a&&!s){n&&n(parseInt(l/a*100));var u=i.start+r;i=$.extend(!0,f,{start:u}),h(i)}else t()})}var t=e.success,n=e.progress,r=this.app.config.get("query_limit"),i=this.app.config.get("query_timeout"),s=e.start||0,o=s+e.query_limit||s+this.app.config.get("query_limit"),u=Math.abs(o-s);if(u<=0){console.debug("FAILED - Datasets::request() - Invalid query range.");return}var a=Math.ceil(u/r)||1,f=$.extend(!0,{},e),l=0,c=this,p=$.extend(!0,f,{start:s});this._get_dataset(e.id,function(){h(p)})},_get_dataset:function(t,n,r){var i=this.list[t];if(i){n(i);return}var s=this;e.request("GET",config.root+"api/datasets/"+t,{},function(e){switch(e.state){case"error":r&&r(e);break;default:s.list[t]=e,n(e)}})},_block_id:function(e,t){return e.id+"_"+e.start+"_"+e.start+this.app.config.get("query_limit")+"_"+t},_get:function(e,t){e.start=e.start||0;var n=[],r={},i=0;for(var s in e.groups){var o=e.groups[s];for(var u in o.columns){var a=o.columns[u].index,f=this._block_id(e,a);if(this.cache[f]||a==="auto"||a==="zero")continue;!r[a]&&a!==undefined&&(r[a]=i,n.push(a),i++)}}if(n.length==0){this._fill_from_cache(e),t(e);return}var l={dataset_id:e.id,start:e.start,columns:n},c=this;this._fetch(l,function(r){for(var i in r){var s=n[i],o=c._block_id(e,s);c.cache[o]=r[i]}c._fill_from_cache(e),t(e)})},_fill_from_cache:function(e){var t=e.start;console.debug("Datasets::_fill_from_cache() - Filling request from cache at "+t+".");var n=0;for(var r in e.groups){var i=e.groups[r];for(var s in i.columns){var o=i.columns[s],u=this._block_id(e,o.index),a=this.cache[u];a&&(n=Math.max(n,a.length))}}n==0&&console.debug("Datasets::_fill_from_cache() - Reached data range limit.");for(var r in e.groups){var i=e.groups[r];i.values=[];for(var f=0;f<n;f++)i.values[f]={x:parseInt(f)+t}}for(var r in e.groups){var i=e.groups[r];for(var s in i.columns){var o=i.columns[s];switch(o.index){case"auto":for(var f=0;f<n;f++){var l=i.values[f];l[s]=parseInt(f)+t}break;case"zero":for(var f=0;f<n;f++){var l=i.values[f];l[s]=0}break;default:var u=this._block_id(e,o.index),a=this.cache[u];for(var f=0;f<n;f++){var l=i.values[f],c=a[f];isNaN(c)&&!o.is_label&&(c=0),l[s]=c}}}}},_fetch:function(t,n){var r=t.start?t.start:0,i=this.app.config.get("query_limit"),s=0;t.columns&&(s=t.columns.length,console.debug("Datasets::_fetch() - Fetching "+s+" column(s) at "+r+".")),s==0&&console.debug("Datasets::_fetch() - No columns requested");var o="";for(var u in t.columns)o+=t.columns[u]+",";o=o.substring(0,o.length-1);var a=this;e.request("GET",config.root+"api/datasets/"+t.dataset_id,{data_type:"raw_data",provider:"dataset-column",limit:i,offset:r,indeces:o},function(e){var t=new Array(s);for(var r=0;r<s;r++)t[r]=[];for(var r in e.data){var i=e.data[r];for(var o in i){var u=i[o];u!==undefined&&u!=2147483647&&t[o].push(u)}}console.debug("Datasets::_fetch() - Fetching complete."),n(t)})}})}),define("plugin/models/group",[],function(){return Backbone.Model.extend({defaults:{key:"Data label",date:""},reset:function(){this.clear({silent:!0}).set(this.defaults),this.trigger("reset",this)}})}),define("plugin/models/groups",["plugin/models/group"],function(e){return Backbone.Collection.extend({model:e})}),define("plugin/models/chart",["plugin/models/groups"],function(e){return Backbone.Model.extend({defaults:{id:null,title:"",type:"",date:null,state:"",state_info:"",modified:!1,dataset_id:"",dataset_id_job:""},initialize:function(t){this.groups=new e,this.settings=new Backbone.Model},reset:function(){this.clear({silent:!0}).set(this.defaults),this.groups.reset(),this.settings.clear(),this.trigger("reset",this)},copy:function(e){var t=this;t.clear({silent:!0}).set(this.defaults),t.set(e.attributes),t.settings=e.settings.clone(),t.groups.reset(),e.groups.each(function(e){t.groups.add(e.clone())}),t.trigger("change",t)},state:function(e,t){this.set("state",e),this.set("state_info",t),this.trigger("set:state"),console.debug("Chart:state() - "+t+" ("+e+")")}})});var Visualization=Backbone.Model.extend({defaults:{config:{}},urlRoot:function(){var e="/api/visualizations";return window.galaxy_config&&galaxy_config.root?galaxy_config.root+e:e},initialize:function(e){_.isObject(e.config)&&_.isObject(this.defaults.config)&&_.defaults(e.config,this.defaults.config),this._setUpListeners()},_setUpListeners:function(){},set:function(e,t){if(e==="config"){var n=this.get("config");_.isObject(n)&&(t=_.extend(_.clone(n),t))}return Backbone.Model.prototype.set.call(this,e,t),this},toString:function(){var e=this.get("id")||"";return this.get("title")&&(e+=":"+this.get("title")),"Visualization("+e+")"}}),VisualizationCollection=Backbone.Collection.extend({model:Visualization,url:function(){return galaxy_config.root+"api/visualizations"},initialize:function(e,t){t=t||{}},set:function(e,t){var n=this;e=_.map(e,function(e){var t=n.get(e.id);if(!t)return e;var r=t.toJSON();return _.extend(r,e),r}),Backbone.Collection.prototype.set.call(this,e,t)},toString:function(){return["VisualizationCollection(",[this.historyId,this.length].join(),")"].join("")}});define("mvc/visualization/visualization-model",function(){}),define("plugin/library/storage",["utils/utils","plugin/models/chart","plugin/models/group","mvc/visualization/visualization-model"],function(e,t,n){return Backbone.Model.extend({vis:null,initialize:function(e){this.app=e,this.chart=this.app.chart,this.options=this.app.options,this.id=this.options.id,this.vis=new Visualization({type:"charts",config:{dataset_id:this.options.config.dataset_id,chart_dict:{}}}),this.id&&(this.vis.id=this.id);var t=this.options.config.chart_dict;t&&(this.vis.get("config").chart_dict=t)},save:function(){var e=this.app.chart;this.vis.get("config").chart_dict={};var t=e.get("title");t!=""&&this.vis.set("title",t);var n={attributes:e.attributes,settings:e.settings.attributes,groups:[]};e.groups.each(function(e){n.groups.push(e.attributes)}),this.vis.get("config").chart_dict=n;var r=this;this.vis.save().fail(function(e,t,n){console.error(e,t,n)}).then(function(e){e&&e.id&&(r.id=e.id)})},load:function(){var e=this.vis.get("config").chart_dict;if(!e.attributes)return!1;var t=e.attributes.type;if(!t)return console.debug("Storage::load() - Chart type not provided. Invalid format."),!1;var r=this.app.types.get(t);if(!r)return console.debug("Storage::load() - Chart type not supported. Please re-configure the chart. Resetting chart."),!1;console.debug("Storage::load() - Loading chart type "+t+"."),this.chart.definition=r,this.chart.set(e.attributes),this.chart.state("ok","Loading saved visualization..."),this.chart.settings.set(e.settings);for(var i in e.groups)this.chart.groups.add(new n(e.groups[i]));return this.chart.set("modified",!1),!0}})}),define("plugin/library/deferred",["utils/utils"],function(e){return Backbone.Model.extend({queue:[],process:{},counter:0,initialize:function(){this.on("refresh",function(){for(var e in this.queue)if(this.counter==0){var t=this.queue[e];this.queue.splice(e,1),t()}})},execute:function(e){this.queue.push(e),this.trigger("refresh")},register:function(){var t=e.uuid();return this.process[t]=!0,this.counter++,console.debug("Deferred:register() - Registering "+t),t},done:function(e){this.process[e]&&(delete this.process[e],this.counter--,console.debug("Deferred:done() - Unregistering "+e),this.trigger("refresh"))},ready:function(){return this.counter==0}})}),define("plugin/views/viewport",["mvc/ui/ui-portlet","mvc/ui/ui-misc","utils/utils"],function(e,t,n){return Backbone.View.extend({container_list:[],canvas_list:[],initialize:function(e,t){this.app=e,this.chart=this.app.chart,this.options=n.merge(t,this.optionsDefault),this.setElement($(this._template())),this._fullscreen(this.$el,100),this._createContainer("div");var r=this;this.chart.on("redraw",function(){r._draw(r.chart)}),this.chart.on("set:state",function(){var e=r.$el.find("#info"),t=r.$el.find(".charts-viewport-container"),n=e.find("#icon");n.removeClass(),e.show(),e.find("#text").html(r.chart.get("state_info"));var i=r.chart.get("state");switch(i){case"ok":e.hide(),t.show();break;case"failed":n.addClass("icon fa fa-warning"),t.hide();break;default:n.addClass("icon fa fa-spinner fa-spin"),t.show()}})},show:function(){this.$el.show()},hide:function(){this.$el.hide()},_fullscreen:function(e,t){e.css("height",$(window).height()-t),$(window).resize(function(){e.css("height",$(window).height()-t)})},_createContainer:function(e,t){t=t||1;for(var n in this.container_list)this.container_list[n].remove();this.container_list=[],this.canvas_list=[];for(var n=0;n<t;n++){var r=$(this._templateContainer(e,parseInt(100/t)));this.$el.append(r),this.container_list[n]=r,this.canvas_list[n]=r.find(".charts-viewport-canvas").attr("id")}},_draw:function(e){var t=this,n=this.app.deferred.register(),r=e.get("type");this.chart_definition=e.definition;var i=1;e.settings.get("use_panels")==="true"&&(i=e.groups.length),this._createContainer(this.chart_definition.tag,i),e.state("wait","Please wait...");if(!this.chart_definition.execute||this.chart_definition.execute&&e.get("modified"))this.app.jobs.cleanup(e),e.set("modified",!1);var t=this;require(["plugin/charts/"+this.app.chartPath(r)+"/wrapper"],function(r){if(t.chart_definition.execute)t.app.jobs.request(e,t._defaultSettingsString(e),t._defaultRequestString(e),function(){var i=new r(t.app,{process_id:n,chart:e,request_dictionary:t._defaultRequestDictionary(e),canvas_list:t.canvas_list})},function(){this.app.deferred.done(n)});else var i=new r(t.app,{process_id:n,chart:e,request_dictionary:t._defaultRequestDictionary(e),canvas_list:t.canvas_list})})},_defaultRequestString:function(e){var t="",n=0,r=this;return e.groups.each(function(e){n++;for(var i in r.chart_definition.columns)t+=i+"_"+n+":"+(parseInt(e.get(i))+1)+", "}),t.substring(0,t.length-2)},_defaultSettingsString:function(e){var t="";for(key in e.settings.attributes)t+=key+":"+e.settings.get(key)+", ";return t.substring(0,t.length-2)},_defaultRequestDictionary:function(e){var t={groups:[]};this.chart_definition.execute?t.id=e.get("dataset_id_job"):t.id=e.get("dataset_id");var r=0,i=this;return e.groups.each(function(e){var s={};for(var o in i.chart_definition.columns){var u=i.chart_definition.columns[o];s[o]=n.merge({index:e.get(o)},u)}t.groups.push({key:++r+":"+e.get("key"),columns:s})}),t},_template:function(){return'<div class="charts-viewport"><div id="info" class="info"><span id="icon" class="icon"/><span id="text" class="text" /></div></div>'},_templateContainer:function(e,t){return'<div class="charts-viewport-container" style="width:'+t+'%;">'+'<div id="menu"/>'+"<"+e+' id="'+n.uuid()+'" class="charts-viewport-canvas">'+"</div>"}})}),define("plugin/library/screenshot",["libs/underscore"],function(e){function t(e){e.$el.find("svg").length>0?r(e):n(e)}function n(e){try{var t=e.$el.find(".jqplot-target"),n=t.jqplotToImageStr({});n&&(window.location.href=n.replace("image/png","image/octet-stream"))}catch(r){console.debug("FAILED - Screenshot::_fromCanvas() - "+r),e.error&&e.error("Please reduce your chart to a single panel and try again.")}}function r(e){var t=e.$el,n=e.url,r=e.name,s=new XMLSerializer,o=document.createElement("canvas"),u=$(o),a=t.find("svg").length,f=t.find("svg").first(),l=parseInt(f.css("height")),c=parseInt(f.css("width"));u.attr("width",c*a),u.attr("height",l),(!o.getContext||!o.getContext("2d"))&&alert("Your browser doesn't support this feature, please use a modern browser");var h=o.getContext("2d"),p=0;t.find("svg").each(function(){var e=$(this);e.attr({version:"1.1",xmlns:"http://www.w3.org/2000/svg",width:c,height:l});var t=s.serializeToString(this);h.drawSvg(t,p,0,c,l),p+=c}),window.location.href=i(o,o.getContext("2d"),"white").replace("image/png","image/octet-stream")}function i(e,t,n){var r=e.width,i=e.height,s;if(n){s=t.getImageData(0,0,r,i);var o=t.globalCompositeOperation;t.globalCompositeOperation="destination-over",t.fillStyle=n,t.fillRect(0,0,r,i)}var u=e.toDataURL("image/png");return n&&(t.clearRect(0,0,r,i),t.putImageData(s,0,0),t.globalCompositeOperation=o),u}function s(e){window.location.href="data:none/none;base64,"+btoa(a(e).string)}function o(e){for(var t in document.styleSheets){var n=document.styleSheets[t],r=n.cssRules;if(r)for(var i=0,s=r.length;i<s;i++)try{e.find(r[i].selectorText).each(function(e,t){t.style.cssText+=r[i].style.cssText})}catch(o){}}}function u(e){var t=a(e),n={filename:name||"chart",type:"application/pdf",height:t.height,width:t.width,scale:2,svg:t.string},r=$("body"),i=r.find("#viewport-form");i.length===0&&(i=$("<form>",{id:"viewport-form",method:"post",action:"http://export.highcharts.com/",display:"none"}),r.append(i)),i.empty();for(name in n){var s=$("<input/>",{type:"hidden",name:name,value:n[name]});i.append(s)}try{i.submit()}catch(o){console.log(o)}}function a(e){if(e.$el.find("svg").length==0&&e.error){e.error("No SVG found. This chart type does not support SVG/PDF export.");return}var t=e.$el,n=t.find("svg").length,r=parseInt(t.find("svg").first().css("height")),i=parseInt(t.find("svg").first().css("width")),s=new XMLSerializer,u=$("<svg/>");u.attr({version:"1.1",xmlns:"http://www.w3.org/2000/svg",width:i*n,height:r});var a="",f=0;return t.find("svg").each(function(){var e=$(this).clone();o(e);var t=$('<g transform="translate('+f+', 0)">');t.append(e.find("g").first()),u.append(t),f+=i}),{string:s.serializeToString(u[0]),height:r,width:i}}return{createPNG:t,createSVG:s,createPDF:u}}),define("plugin/views/viewer",["utils/utils","mvc/ui/ui-misc","mvc/ui/ui-portlet","plugin/views/viewport","plugin/library/screenshot"],function(e,t,n,r,i){return Backbone.View.extend({initialize:function(e,s){this.app=e,this.chart=this.app.chart,this.viewport_view=new r(e);var o=this;this.message=new t.Message;var u=new t.ButtonMenu({icon:"fa-camera",title:"Screenshot",tooltip:"Download as PNG, SVG or PDF file"});u.addMenu({id:"button-png",title:"Save as PNG",icon:"fa-file",onclick:function(){o._wait(o.chart,function(){i.createPNG({$el:o.viewport_view.$el,title:o.chart.get("title"),error:function(e){o.message.update({message:e,status:"danger"})}})})}}),u.addMenu({id:"button-svg",title:"Save as SVG",icon:"fa-file-text-o",onclick:function(){o._wait(o.chart,function(){i.createSVG({$el:o.viewport_view.$el,title:o.chart.get("title"),error:function(e){o.message.update({message:e,status:"danger"})}})})}}),u.addMenu({id:"button-png",title:"Save as PDF",icon:"fa-file-o",onclick:function(){o.app.modal.show({title:"Send chart data for PDF creation",body:"Galaxy does not provide integrated PDF export scripts. You may click 'Continue' to create the PDF by using a 3rd party service (https://export.highcharts.com)",buttons:{Cancel:function(){o.app.modal.hide()},Continue:function(){o.app.modal.hide(),o._wait(o.chart,function(){i.createPDF({$el:o.viewport_view.$el,title:o.chart.get("title"),error:function(e){o.message.update({message:e,status:"danger"})}})})}}})}}),this.portlet=new n.View({icon:"fa-bar-chart-o",title:"Viewport",scrollable:!1,operations:{edit_button:new t.ButtonIcon({icon:"fa-edit",tooltip:"Customize this chart",title:"Editor",onclick:function(){o._wait(o.chart,function(){o.app.go("editor")})}}),picture_button_menu:u}}),this.portlet.append(this.message.$el),this.portlet.append(this.viewport_view.$el),this.setElement(this.portlet.$el);var o=this;this.chart.on("change:title",function(){o._refreshTitle()})},show:function(){this.$el.show(),$(window).trigger("resize")},hide:function(){this.$el.hide()},_refreshTitle:function(){var e=this.chart.get("title");this.portlet.title(e)},_wait:function(e,t){this.app.deferred.ready()?t():this.message.update({message:"Your chart is currently being processed. Please wait and try again."})}})}),define("mvc/ui/ui-tabs",["utils/utils"],function(e){var t=Backbone.View.extend({optionsDefault:{title_new:"",operations:null,onnew:null,max:null,onchange:null},initialize:function(t){this.visible=!1,this.$nav=null,this.$content=null,this.first_tab=null,this.current_id=null,this.options=e.merge(t,this.optionsDefault);var n=$(this._template(this.options));this.$nav=n.find(".tab-navigation"),this.$content=n.find(".tab-content"),this.setElement(n),this.list={};var r=this;this.options.operations&&$.each(this.options.operations,function(e,t){t.$el.prop("id",e),r.$nav.find(".operations").append(t.$el)});if(this.options.onnew){var i=$(this._template_tab_new(this.options));this.$nav.append(i),i.tooltip({title:"Add a new tab",placement:"bottom",container:r.$el}),i.on("click",function(e){i.tooltip("hide"),r.options.onnew()})}},size:function(){return _.size(this.list)},current:function(){return this.$el.find(".tab-pane.active").attr("id")},add:function(e){var t=this,n=e.id,r=$(this._template_tab(e)),i=$(this._template_tab_content(e));this.list[n]=e.ondel?!0:!1,this.options.onnew?this.$nav.find("#new-tab").before(r):this.$nav.append(r),i.append(e.$el),this.$content.append(i),this.size()==1&&(r.addClass("active"),i.addClass("active"),this.first_tab=n),this.options.max&&this.size()>=this.options.max&&this.$el.find("#new-tab").hide();if(e.ondel){var s=r.find("#delete");s.tooltip({title:"Delete this tab",placement:"bottom",container:t.$el}),s.on("click",function(){return s.tooltip("destroy"),t.$el.find(".tooltip").remove(),e.ondel(),!1})}r.on("click",function(r){r.preventDefault(),e.onclick?e.onclick():t.show(n)}),this.current_id||(this.current_id=n)},del:function(e){this.$el.find("#tab-"+e).remove(),this.$el.find("#"+e).remove(),this.first_tab==e&&(this.first_tab=null),this.first_tab!=null&&this.show(this.first_tab),this.list[e]&&delete this.list[e],this.size()<this.options.max&&this.$el.find("#new-tab").show()},delRemovable:function(){for(var e in this.list)this.del(e)},show:function(e){this.$el.fadeIn("fast"),this.visible=!0,e&&(this.$el.find("#tab-"+this.current_id).removeClass("active"),this.$el.find("#"+this.current_id).removeClass("active"),this.$el.find("#tab-"+e).addClass("active"),this.$el.find("#"+e).addClass("active"),this.current_id=e),this.options.onchange&&this.options.onchange(e)},hide:function(){this.$el.fadeOut("fast"),this.visible=!1},hideOperation:function(e){this.$nav.find("#"+e).hide()},showOperation:function(e){this.$nav.find("#"+e).show()},setOperation:function(e,t){var n=this.$nav.find("#"+e);n.off("click"),n.on("click",t)},title:function(e,t){var n=this.$el.find("#tab-title-text-"+e);return t&&n.html(t),n.html()},retitle:function(e){var t=0;for(var n in this.list)this.title(n,++t+": "+e)},_template:function(e){return'<div class="ui-tabs tabbable tabs-left"><ul id="tab-navigation" class="tab-navigation nav nav-tabs"><div class="operations" style="float: right; margin-bottom: 4px;"></div></ul><div id="tab-content" class="tab-content"/></div>'},_template_tab_new:function(e){return'<li id="new-tab"><a href="javascript:void(0);"><i class="ui-tabs-add fa fa-plus-circle"/>'+e.title_new+"</a>"+"</li>"},_template_tab:function(e){var t='<li id="tab-'+e.id+'" class="tab-element">'+'<a id="tab-title-link-'+e.id+'" title="" href="#'+e.id+'" data-original-title="">'+'<span id="tab-title-text-'+e.id+'" class="tab-title-text">'+e.title+"</span>";return e.ondel&&(t+='<i id="delete" class="ui-tabs-delete fa fa-minus-circle"/>'),t+="</a></li>",t},_template_tab_content:function(e){return'<div id="'+e.id+'" class="tab-pane"/>'}});return{View:t}}),define("mvc/ui/ui-table",["utils/utils"],function(e){var t=Backbone.View.extend({row:null,row_count:0,optionsDefault:{content:"No content available.",onchange:null,ondblclick:null,onconfirm:null,cls:"ui-table",cls_tr:""},events:{click:"_onclick",dblclick:"_ondblclick"},initialize:function(t){this.options=e.merge(t,this.optionsDefault);var n=$(this._template(this.options));this.$thead=n.find("thead"),this.$tbody=n.find("tbody"),this.$tmessage=n.find("tmessage"),this.setElement(n),this.row=this._row()},addHeader:function(e){var t=$("<th></th>");t.append(e),this.row.append(t)},appendHeader:function(){this.$thead.append(this.row),this.row=$("<tr></tr>")},add:function(e,t,n){var r=$("<td></td>");t&&r.css("width",t),n&&r.css("text-align",n),r.append(e),this.row.append(r)},append:function(e,t){this._commit(e,t,!1)},prepend:function(e,t){this._commit(e,t,!0)},get:function(e){return this.$el.find("#"+e)},del:function(e){var t=this.$tbody.find("#"+e);t.length>0&&(t.remove(),this.row_count--,this._refresh())},delAll:function(){this.$tbody.empty(),this.row_count=0,this._refresh()},value:function(e){this.before=this.$tbody.find(".current").attr("id"),e!==undefined&&(this.$tbody.find("tr").removeClass("current"),e&&this.$tbody.find("#"+e).addClass("current"));var t=this.$tbody.find(".current").attr("id");return t===undefined?null:(t!=this.before&&this.options.onchange&&this.options.onchange(e),t)},size:function(){return this.$tbody.find("tr").length},_commit:function(e,t,n){this.del(e),this.row.attr("id",e),n?this.$tbody.prepend(this.row):this.$tbody.append(this.row),t&&(this.row.hide(),this.row.fadeIn()),this.row=this._row(),this.row_count++,this._refresh()},_row:function(){return $('<tr class="'+this.options.cls_tr+'"></tr>')},_onclick:function(e){var t=this.value(),n=$(e.target).closest("tr").attr("id");n!=""&&n&&t!=n&&(this.options.onconfirm?this.options.onconfirm(n):this.value(n))},_ondblclick:function(e){var t=this.value();t&&this.options.ondblclick&&this.options.ondblclick(t)},_refresh:function(){this.row_count==0?this.$tmessage.show():this.$tmessage.hide()},_template:function(e){return'<div><table class="'+e.cls+'">'+"<thead></thead>"+"<tbody></tbody>"+"</table>"+"<tmessage>"+e.content+"</tmessage>"+"<div>"}});return{View:t}}),define("plugin/views/group",["mvc/ui/ui-table","mvc/ui/ui-misc","utils/utils"],function(e,t,n){return Backbone.View.extend({initialize:function(r,i){this.app=r;var s=this;this.chart=this.app.chart,this.group=i.group,this.group_key=new t.Input({placeholder:"Data label",onchange:function(e){s.group.set("key",e)}}),this.table=new e.View({content:"No data column."});var o=$("<div/>");o.append(n.wrap((new t.Label({title:"Provide a label:"})).$el)),o.append(n.wrap(this.group_key.$el)),o.append(n.wrap((new t.Label({title:"Select columns:"})).$el)),o.append(n.wrap(this.table.$el)),this.setElement(o);var s=this;this.chart.on("change:dataset_id",function(){s._refreshTable()}),this.chart.on("change:type",function(){s._refreshTable()}),this.group.on("change:key",function(){s._refreshGroupKey()}),this.group.on("change",function(){s._refreshGroup()}),this._refreshTable(),this._refreshGroupKey(),this._refreshGroup()},_refreshTable:function(){var e=this.chart.get("dataset_id"),n=this.chart.get("type");if(!e||!n)return;var r=this,i=this.chart.definition;this.table.delAll();var s={};for(var o in i.columns){var u=i.columns[o];if(!u){console.debug("Group::_refreshTable() - Skipping column definition.");continue}var a=new t.Select.View({id:"select_"+o,wait:!0}),f=u.title;u.is_unique&&(f+=" (all data labels)"),this.table.add(f,"25%"),this.table.add(a.$el),this.table.append(o),s[o]=a}this.chart.state("wait","Loading metadata...");var l=this.app.deferred.register(),c={id:e,success:function(e){for(var t in s)r._addRow(t,e,s,i.columns[t]);r.chart.state("ok","Metadata initialized..."),r.app.deferred.done(l)}};this.app.datasets.request(c)},_addRow:function(e,t,n,r){var i=this,s=r.is_label,o=r.is_auto,u=r.is_numeric,a=r.is_unique,f=r.is_zero,l=[],c=n[e];o&&l.push({label:"Column: Row Number",value:"auto"}),f&&l.push({label:"Column: None",value:"zero"});var h=t.metadata_column_types;for(var p in h){var d=!1;h[p]=="int"||h[p]=="float"?d=u:d=s,d&&l.push({label:"Column: "+(parseInt(p)+1)+" ["+h[p]+"]",value:p})}c.update(l),a&&this.chart.groups.first()&&this.group.set(e,this.chart.groups.first().get(e));if(!c.exists(this.group.get(e))){var v=c.first();console.debug('Group()::_addRow() - Switching model value from "'+this.group.get(e)+'" to "'+v+'".'),this.group.set(e,v)}c.value(this.group.get(e)),this.group.off("change:"+e),this.group.on("change:"+e,function(){c.value(i.group.get(e))}),c.setOnChange(function(t){a?i.chart.groups.each(function(n){n.set(e,t)}):i.group.set(e,t),i.chart.set("modified",!0)}),c.show()},_refreshGroup:function(){this.group.set("date",n.time())},_refreshGroupKey:function(){var e=this.group.get("key");e===undefined&&(e=""),this.group_key.value(e)}})}),define("plugin/library/ui-table-form",["mvc/ui/ui-table","mvc/ui/ui-misc","utils/utils"],function(e,t,n){var r=Backbone.View.extend({optionsDefault:{title:"",content:"",mode:""},list:[],initialize:function(r,i){this.app=r,this.options=n.merge(i,this.optionsDefault),this.table_title=new t.Label({title:this.options.title}),this.table=new e.View({content:this.options.content});var s=$('<div class="ui-table-form"/>');this.options.title&&s.append(n.wrap(this.table_title.$el)),s.append(n.wrap(this.table.$el)),this.setElement(s)},title:function(e){this.table_title.title(e)},update:function(e,t){this.table.delAll(),this.list=[];for(var n in e)this._add(e[n].id||n,e[n],t);for(var n in this.list)this.list[n].trigger("change")},_add:function(e,n,r){var i=this,s=null,o=n.type;switch(o){case"text":s=new t.Input({id:"field-"+e,placeholder:n.placeholder,value:r.get(e),onchange:function(t){r.set(e,t)}});break;case"radiobutton":s=new t.RadioButton.View({id:"field-"+e,data:n.data,value:r.get(e),onchange:function(t){r.set(e,t);var s=_.findWhere(n.data,{value:t});if(s&&s.operations){var o=s.operations;for(var u in o.show){var a=o.show[u];i.table.get(a).show()}for(var u in o.hide){var a=o.hide[u];i.table.get(a).hide()}}}});break;case"select":s=new t.Select.View({id:"field-"+e,data:n.data,value:r.get(e),onchange:function(t){r.set(e,t);var s=_.findWhere(n.data,{value:t});if(s&&s.operations){var o=s.operations;for(var u in o.show){var a=o.show[u];i.table.get(a).show()}for(var u in o.hide){var a=o.hide[u];i.table.get(a).hide()}}}});break;case"dataset":s=new t.Select.View({id:"field-"+e,onchange:function(t){r.set(e,t)}}),i.app.datasets.on("all",function(){var t=[];i.app.datasets.each(function(e){e.get("datatype_id")==n.data&&t.push({value:e.get("id"),label:e.get("name")})}),s.update(t),r.get(e)||r.set(e,s.first()),s.value(r.get(e))}),i.app.datasets.trigger("all.datasets");break;case"textarea":s=new t.Textarea({id:"field-"+e,onchange:function(){r.set(e,s.value())}});break;case"separator":s=$("<div/>");break;default:s=new t.Input({id:"field-"+e,placeholder:n.placeholder,type:n.type,onchange:function(){r.set(e,s.value())}})}if(o!="separator"){r.get(e)||r.set(e,n.init),s.value(r.get(e)),this.list[e]=s;var u=$("<div/>");u.append(s.$el),n.info&&u.append('<div 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o=i.pos[0]+(s.offsetLeft||0),u=i.pos[1]+(s.offsetTop||0),f=i.pos[0]+(s.offsetLeft||0),l=p.range()[0]+a.top+(s.offsetTop||0),c=h.range()[0]+a.left+(s.offsetLeft||0),d=i.pos[1]+(s.offsetTop||0),v=n.tickFormat()(t.x()(i.point,i.pointIndex)),m=r.tickFormat()(t.y()(i.point,i.pointIndex));T!=null&&e.tooltip.show([f,l],T(i.series.key,v,m,i,B),"n",1,s,"x-nvtooltip"),N!=null&&e.tooltip.show([c,d],N(i.series.key,v,m,i,B),"e",1,s,"y-nvtooltip"),C!=null&&e.tooltip.show([o,u],C(i.series.key,v,m,i.point.tooltip,i,B),i.value<0?"n":"s",null,s)},H=[{key:"Magnify",disabled:!0}];return t.dispatch.on("elementMouseout.tooltip",function(e){A.tooltipHide(e),d3.select(".nv-chart-"+t.id()+" .nv-series-"+e.seriesIndex+" .nv-distx-"+e.pointIndex).attr("y1",0),d3.select(".nv-chart-"+t.id()+" .nv-series-"+e.seriesIndex+" 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v.size(2.2).sizeDomain([2.2,2.2]),v.dispatch.on("elementClick.area",function(e){m.areaClick(e)}),v.dispatch.on("elementMouseover.tooltip",function(e){e.pos=[e.pos[0]+t.left,e.pos[1]+t.top],m.tooltipShow(e)}),v.dispatch.on("elementMouseout.tooltip",function(e){m.tooltipHide(e)}),g.dispatch=m,g.scatter=v,d3.rebind(g,v,"interactive","size","xScale","yScale","zScale","xDomain","yDomain","xRange","yRange","sizeDomain","forceX","forceY","forceSize","clipVoronoi","useVoronoi","clipRadius","highlightPoint","clearHighlights"),g.options=e.utils.optionsFunc.bind(g),g.x=function(e){return arguments.length?(o=d3.functor(e),g):o},g.y=function(e){return arguments.length?(u=d3.functor(e),g):u},g.margin=function(e){return arguments.length?(t.top=typeof e.top!="undefined"?e.top:t.top,t.right=typeof e.right!="undefined"?e.right:t.right,t.bottom=typeof e.bottom!="undefined"?e.bottom:t.bottom,t.left=typeof e.left!="undefined"?e.left:t.left,g):t},g.width=function(e){return 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$.extend(!0,{},e,{title:"Scatter plot",category:"Others",zoomable:!0,columns:{x:{title:"Values for x-axis",is_numeric:!0},y:{title:"Values for y-axis",is_numeric:!0}}})}),define("plugin/charts/nvd3/stackedarea/config",["plugin/charts/nvd3/common/config"],function(e){return $.extend(!0,{},e,{title:"Regular",zoomable:!0,category:"Area charts",keywords:"default small",columns:{x:{title:"Values for x-axis",is_label:!0,is_auto:!0,is_unique:!0},y:{title:"Values for y-axis",is_numeric:!0}}})}),define("plugin/charts/jqplot/common/config",["plugin/charts/forms/default"],function(e){return $.extend(!0,{},e,{title:"",category:"",library:"jqPlot",tag:"div",zoomable:!0,keywords:"medium",query_limit:1e4,settings:{separator_grid:{title:"Grids",type:"separator"},x_axis_grid:{title:"Axis grid",info:"Would you like to show grid lines for the X axis?",type:"radiobutton",init:"false",data:[{label:"On",value:"true"},{label:"Off",value:"false"}]},y_axis_grid:{title:"Axis grid",info:"Would you like to show 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You are receiving this because you have the service enabled, addressing the recipient of this email.

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