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https://github.com/galaxyproject/galaxy.git
synced 2026-10-16 07:19:13 +08:00
Trackster: enable a tool to be run on complete dataset or a visible region.
This commit is contained in:
Jeremy Goecks
@@ -645,16 +645,17 @@ class TracksController( BaseController, UsesVisualization, UsesHistoryDatasetAss
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return self.tracks_grid( trans, **kwargs )
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@web.expose
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def run_tool( self, trans, dataset_id, chrom, low, high, tool_id, **kwargs ):
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def run_tool( self, trans, dataset_id, tool_id, chrom=None, low=None, high=None, **kwargs ):
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"""
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Run a tool on a subset of input data to produce a new output dataset that
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corresponds to a dataset that a user is currently viewing.
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"""
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# Parameter checks.
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if not chrom or not low or not high:
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return messages.NO_DATA
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low, high = int( low ), int( high )
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# Run tool on region if region is specificied.
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run_on_region = False
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if chrom and low and high:
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run_on_region = True
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low, high = int( low ), int( high )
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# Dataset check.
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original_dataset = self.get_dataset( trans, dataset_id, check_ownership=False, check_accessible=True )
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@@ -678,27 +679,23 @@ class TracksController( BaseController, UsesVisualization, UsesHistoryDatasetAss
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tool_params = tool.params_from_strings( tool_params, self.app )
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#
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# Convert input datasets so that region of dataset can be quickly
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# extracted.
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# TODO: Is it useful/necessary to create data subsets for all input
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# datasets or only the original dataset (aka the dataset that the user
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# is viewing)? Currently we create data subsets for all input datasets
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# because this provides the best performance as the tool runs on small
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# datasets.
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# If running tool on region, convert input datasets (create indices) so
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# that can regions of data can be quickly extracted.
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#
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messages_list = []
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for jida in original_job.input_datasets:
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input_dataset = jida.dataset
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# TODO: put together more robust way to determine if a dataset can be indexed.
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if hasattr( input_dataset, 'get_track_type' ):
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# Can index dataset.
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track_type, data_sources = input_dataset.datatype.get_track_type()
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# Convert to datasource that provides 'data' because we need to
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# extract the original data.
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data_source = data_sources[ 'data' ]
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msg = self._convert_dataset( trans, input_dataset, data_source )
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if msg is not None:
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messages_list.append( msg )
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if run_on_region:
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for jida in original_job.input_datasets:
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input_dataset = jida.dataset
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# TODO: put together more robust way to determine if a dataset can be indexed.
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if hasattr( input_dataset, 'get_track_type' ):
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# Can index dataset.
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track_type, data_sources = input_dataset.datatype.get_track_type()
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# Convert to datasource that provides 'data' because we need to
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# extract the original data.
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data_source = data_sources[ 'data' ]
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msg = self._convert_dataset( trans, input_dataset, data_source )
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if msg is not None:
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messages_list.append( msg )
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# Return any messages generated during conversions.
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return_message = _get_highest_priority_msg( messages_list )
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@@ -706,41 +703,40 @@ class TracksController( BaseController, UsesVisualization, UsesHistoryDatasetAss
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return return_message
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#
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# Set input datasets for tool. Input datasets are subsets of full
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# datasets and are based on chrom, low, high.
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# Set target history (the history that tool will use for inputs/outputs).
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# If user owns dataset, put new data in original dataset's history; if
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# user does not own dataset (and hence is accessing dataset via sharing),
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# put new data in user's current history.
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#
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# If user is rerunning own tool, put new data in original dataset's
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# history. If another user is running tool, put new data in current
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# history.
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if original_dataset.history.user == trans.user:
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working_history = original_dataset.history
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target_history = original_dataset.history
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else:
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working_history = trans.get_history( create=True )
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hda_permissions = trans.app.security_agent.history_get_default_permissions( working_history )
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messages_list = []
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target_history = trans.get_history( create=True )
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hda_permissions = trans.app.security_agent.history_get_default_permissions( target_history )
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#
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# Set input datasets for tool. If running on region, extract and use subset
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# when possible.
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#
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for jida in original_job.input_datasets:
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input_dataset = jida.dataset
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if hasattr( input_dataset.datatype, 'get_track_type' ):
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#
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# Dataset can be indexed and hence a subset can be extracted.
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#
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if run_on_region and hasattr( input_dataset.datatype, 'get_track_type' ):
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# Dataset is indexed and hence a subset can be extracted and used
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# as input.
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track_type, data_sources = input_dataset.datatype.get_track_type()
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data_source = data_sources[ 'data' ]
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converted_dataset = input_dataset.get_converted_dataset( trans, data_source )
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deps = input_dataset.get_converted_dataset_deps( trans, data_source )
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#
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# Create new HDA for input dataset's subset.
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#
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new_dataset = trans.app.model.HistoryDatasetAssociation( extension=input_dataset.ext, \
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dbkey=input_dataset.dbkey, \
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create_dataset=True, \
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sa_session=trans.sa_session,
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name="Subset [%s:%i-%i] of data %i" % \
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( chrom, low, high, input_dataset.hid ),
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visible=False )
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working_history.add_dataset( new_dataset )
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dbkey=input_dataset.dbkey, \
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create_dataset=True, \
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sa_session=trans.sa_session,
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name="Subset [%s:%i-%i] of data %i" % \
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( chrom, low, high, input_dataset.hid ),
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visible=False )
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target_history.add_dataset( new_dataset )
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trans.sa_session.add( new_dataset )
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trans.app.security_agent.set_all_dataset_permissions( new_dataset.dataset, hda_permissions )
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@@ -751,7 +747,7 @@ class TracksController( BaseController, UsesVisualization, UsesHistoryDatasetAss
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dependencies=deps )
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data_provider.write_data_to_file( chrom, low, high, new_dataset.file_name )
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# TODO: size not working.
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# TODO: (a) size not working; (b) need to set peek.
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new_dataset.set_size()
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new_dataset.info = "Data subset for trackster"
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new_dataset.set_dataset_state( trans.app.model.Dataset.states.OK )
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@@ -761,18 +757,21 @@ class TracksController( BaseController, UsesVisualization, UsesHistoryDatasetAss
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tool_params[ jida.name ] = new_dataset
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#
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# Start tool and handle outputs.
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# Execute tool and handle outputs.
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#
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try:
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subset_job, subset_job_outputs = tool.execute( trans, incoming=tool_params, history=working_history )
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subset_job, subset_job_outputs = tool.execute( trans, incoming=tool_params, history=target_history )
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except Exception, e:
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# Lots of things can go wrong when trying to execute tool.
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return to_json_string( { "error" : True, "message" : e.__class__.__name__ + ": " + str(e) } )
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for output in subset_job_outputs.values():
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output.visible = False
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trans.sa_session.flush()
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if run_on_region:
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for output in subset_job_outputs.values():
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output.visible = False
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trans.sa_session.flush()
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#
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# Return new track that corresponds to the original dataset.
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#
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output_name = None
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for joda in original_job.output_datasets:
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if joda.dataset == original_dataset:
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@@ -784,9 +783,9 @@ class TracksController( BaseController, UsesVisualization, UsesHistoryDatasetAss
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return self.add_track_async( trans, output_dataset.id )
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#
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# -----------------
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# Helper methods.
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#
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# -----------------
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def _check_dataset_state( self, trans, dataset ):
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"""
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File diff suppressed because one or more lines are too long
+62
-24
@@ -885,11 +885,15 @@ var Tool = function(track, tool_dict) {
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this.parent_div.find("input").click(function() { $(this).select() });
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// Add 'Go' button.
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var run_tool_row = $("<div>").addClass("slider-row").appendTo(this.parent_div);
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var run_tool_button = $("<input type='submit'>").attr("value", "Run").appendTo(run_tool_row);
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var run_tool_row = $("<div>").addClass("param-row").appendTo(this.parent_div);
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var run_on_dataset_button = $("<input type='submit'>").attr("value", "Run on complete dataset").appendTo(run_tool_row);
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var run_on_region_button = $("<input type='submit'>").attr("value", "Run on visible region").css("margin-left", "3em").appendTo(run_tool_row);
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var tool = this;
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run_tool_button.click( function() {
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tool.run();
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run_on_region_button.click( function() {
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tool.run_on_region();
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});
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run_on_dataset_button.click( function() {
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tool.run_on_dataset();
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});
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};
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extend(Tool.prototype, {
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@@ -920,51 +924,87 @@ extend(Tool.prototype, {
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return param_values;
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},
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/**
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* Run tool. This creates a new child track, runs tool, and places tool's output in the new track.
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* Run tool on dataset. Output is placed in dataset's history and no changes to viz are made.
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*/
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run: function() {
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// Put together params for running tool.
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var url_params = {
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dataset_id: this.track.original_dataset_id,
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chrom: this.track.view.chrom,
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low: this.track.view.low,
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high: this.track.view.high,
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tool_id: this.name
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};
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$.extend(url_params, this.get_param_values_dict());
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run_on_dataset: function() {
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var tool = this;
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tool.run(
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// URL params.
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{
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dataset_id: this.track.original_dataset_id,
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tool_id: tool.name
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},
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// Success callback.
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function(track_data) {
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show_modal(tool.name + " is Running",
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tool.name + " is running on the complete dataset. Tool outputs are in dataset's history.",
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{ "Close" : hide_modal } );
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}
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);
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},
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/**
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* Run dataset on visible region. This creates a new track and sets the track's contents
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* to the tool's output.
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*/
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run_on_region: function() {
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//
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// Create track for tool's output immediately to provide user feedback.
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//
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var
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url_params =
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{
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dataset_id: this.track.original_dataset_id,
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chrom: this.track.view.chrom,
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low: this.track.view.low,
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high: this.track.view.high,
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tool_id: this.name
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},
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current_track = this.track,
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// Set name of track to include tool name, parameters, and region used.
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track_name = url_params.tool_id +
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current_track.tool_region_and_parameters_str(url_params.chrom, url_params.low, url_params.high),
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new_track;
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// Create and add track.
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// TODO: add support for other kinds of tool data tracks.
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if (current_track.track_type === 'FeatureTrack') {
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new_track = new ToolDataFeatureTrack(track_name, view, current_track.hda_ldda, undefined, {}, {}, current_track);
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}
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this.track.add_track(new_track);
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new_track.content_div.text("Starting job.");
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// Run tool.
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this.run(url_params,
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// Success callback.
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function(track_data) {
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new_track.dataset_id = track_data.dataset_id;
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new_track.content_div.text("Running job.");
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new_track.init();
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}
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);
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},
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/**
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* Run tool using a set of URL params and a success callback.
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*/
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run: function(url_params, success_callback) {
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// Add tool params to URL params.
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$.extend(url_params, this.get_param_values_dict());
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// Run tool.
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var json_run_tool = function() {
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$.getJSON(run_tool_url, url_params, function(track_data) {
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if (track_data === "no converter") {
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$.getJSON(run_tool_url, url_params, function(response) {
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if (response === "no converter") {
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// No converter available for input datasets, so cannot run tool.
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new_track.container_div.addClass("error");
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new_track.content_div.text(DATA_NOCONVERTER);
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}
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else if (track_data.error) {
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else if (response.error) {
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// General error.
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new_track.container_div.addClass("error");
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new_track.content_div.text(DATA_CANNOT_RUN_TOOL + track_data.message);
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new_track.content_div.text(DATA_CANNOT_RUN_TOOL + response.message);
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}
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else if (track_data === "pending") {
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else if (response === "pending") {
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// Converting/indexing input datasets; show message and try again.
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new_track.container_div.addClass("pending");
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new_track.content_div.text("Converting input data so that it can be easily reused.");
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@@ -972,9 +1012,7 @@ extend(Tool.prototype, {
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}
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else {
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// Job submitted and running.
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new_track.dataset_id = track_data.dataset_id;
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new_track.content_div.text("Running job.");
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new_track.init();
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success_callback(response);
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}
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});
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};
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