[galaxy-commits] commit/galaxy-central: carlfeberhard: data providers: add data to factory decorator to allow datasets api to parse query strings into provider settings; datasets API: allow new providers to be used in raw_data; clean up and pack scripts

24 Jun 2013

1 new commit in galaxy-central:
https://bitbucket.org/galaxy/galaxy-central/commits/72b02995c8b1/
Changeset:   72b02995c8b1
User:        carlfeberhard
Date:        2013-06-24 20:06:16
Summary:     data providers: add data to factory decorator to allow datasets api to parse query strings into provider settings; datasets API: allow new providers to be used in raw_data; clean up and pack scripts
Affected #:  20 files
diff -r 8ea772733c979a4d5578ba4c8c31dd3f47cc32ba -r 72b02995c8b188b8efe9b3ac4c5996e972e596f1 lib/galaxy/datatypes/binary.py

--- a/lib/galaxy/datatypes/binary.py
+++ b/lib/galaxy/datatypes/binary.py
@@ -267,25 +267,25 @@
     # bam does not use '#' to indicate comments/headers - we need to strip out those headers from the std. providers
     #TODO:?? seems like there should be an easier way to do/inherit this - metadata.comment_char?
     #TODO: incorporate samtools options to control output: regions first, then flags, etc.
-    @dataproviders.decorators.dataprovider_factory( 'line' )
+    @dataproviders.decorators.dataprovider_factory( 'line', dataproviders.line.FilteredLineDataProvider.settings )
     def line_dataprovider( self, dataset, **settings ):
         samtools_source = dataproviders.dataset.SamtoolsDataProvider( dataset )
         settings[ 'comment_char' ] = '@'
         return dataproviders.line.FilteredLineDataProvider( samtools_source, **settings )
-    @dataproviders.decorators.dataprovider_factory( 'regex-line' )
+    @dataproviders.decorators.dataprovider_factory( 'regex-line', dataproviders.line.RegexLineDataProvider.settings )
     def regex_line_dataprovider( self, dataset, **settings ):
         samtools_source = dataproviders.dataset.SamtoolsDataProvider( dataset )
         settings[ 'comment_char' ] = '@'
         return dataproviders.line.RegexLineDataProvider( samtools_source, **settings )
-    @dataproviders.decorators.dataprovider_factory( 'column' )
+    @dataproviders.decorators.dataprovider_factory( 'column', dataproviders.column.ColumnarDataProvider.settings )
     def column_dataprovider( self, dataset, **settings ):
         samtools_source = dataproviders.dataset.SamtoolsDataProvider( dataset )
         settings[ 'comment_char' ] = '@'
         return dataproviders.column.ColumnarDataProvider( samtools_source, **settings )
-    @dataproviders.decorators.dataprovider_factory( 'map' )
+    @dataproviders.decorators.dataprovider_factory( 'map', dataproviders.column.MapDataProvider.settings )
     def map_dataprovider( self, dataset, **settings ):
         samtools_source = dataproviders.dataset.SamtoolsDataProvider( dataset )
         settings[ 'comment_char' ] = '@'
@@ -293,30 +293,30 @@
# these can't be used directly - may need BamColumn, BamMap (Bam metadata -> column/map)
     # OR - see genomic_region_dataprovider
-    #@dataproviders.decorators.dataprovider_factory( 'dataset-column' )
+    #@dataproviders.decorators.dataprovider_factory( 'dataset-column', dataproviders.column.ColumnarDataProvider.settings )
     #def dataset_column_dataprovider( self, dataset, **settings ):
     #    settings[ 'comment_char' ] = '@'
     #    return super( Sam, self ).dataset_column_dataprovider( dataset, **settings )
-    #@dataproviders.decorators.dataprovider_factory( 'dataset-map' )
+    #@dataproviders.decorators.dataprovider_factory( 'dataset-map', dataproviders.column.MapDataProvider.settings )
     #def dataset_map_dataprovider( self, dataset, **settings ):
     #    settings[ 'comment_char' ] = '@'
     #    return super( Sam, self ).dataset_map_dataprovider( dataset, **settings )
-    @dataproviders.decorators.dataprovider_factory( 'header' )
+    @dataproviders.decorators.dataprovider_factory( 'header', dataproviders.line.RegexLineDataProvider.settings )
     def header_dataprovider( self, dataset, **settings ):
         # in this case we can use an option of samtools view to provide just what we need (w/o regex)
         samtools_source = dataproviders.dataset.SamtoolsDataProvider( dataset, '-H' )
         return dataproviders.line.RegexLineDataProvider( samtools_source, **settings )
-    @dataproviders.decorators.dataprovider_factory( 'id-seq-qual' )
+    @dataproviders.decorators.dataprovider_factory( 'id-seq-qual', dataproviders.column.MapDataProvider.settings )
     def id_seq_qual_dataprovider( self, dataset, **settings ):
         settings[ 'indeces' ] = [ 0, 9, 10 ]
         settings[ 'column_types' ] = [ 'str', 'str', 'str' ]
         settings[ 'column_names' ] = [ 'id', 'seq', 'qual' ]
         return self.map_dataprovider( dataset, **settings )
-    @dataproviders.decorators.dataprovider_factory( 'genomic-region' )
+    @dataproviders.decorators.dataprovider_factory( 'genomic-region', dataproviders.column.ColumnarDataProvider.settings )
     def genomic_region_dataprovider( self, dataset, **settings ):
         # GenomicRegionDataProvider currently requires a dataset as source - may not be necc.
         #TODO:?? consider (at least) the possible use of a kwarg: metadata_source (def. to source.dataset),
@@ -330,7 +330,7 @@
         settings[ 'column_types' ] = [ 'str', 'int', 'int' ]
         return self.column_dataprovider( dataset, **settings )
-    @dataproviders.decorators.dataprovider_factory( 'genomic-region-map' )
+    @dataproviders.decorators.dataprovider_factory( 'genomic-region-map', dataproviders.column.MapDataProvider.settings )
     def genomic_region_map_dataprovider( self, dataset, **settings ):
         settings[ 'indeces' ] = [ 2, 3, 3 ]
         settings[ 'column_types' ] = [ 'str', 'int', 'int' ]
diff -r 8ea772733c979a4d5578ba4c8c31dd3f47cc32ba -r 72b02995c8b188b8efe9b3ac4c5996e972e596f1 lib/galaxy/datatypes/data.py
--- a/lib/galaxy/datatypes/data.py
+++ b/lib/galaxy/datatypes/data.py
@@ -593,7 +593,6 @@
         Base dataprovider factory for all datatypes that returns the proper provider
         for the given `data_format` or raises a `NoProviderAvailable`.
         """
-        #TODO:?? is this handling super class providers?
         if self.has_dataprovider( data_format ):
             return self.dataproviders[ data_format ]( self, dataset, **settings )
         raise dataproviders.exceptions.NoProviderAvailable( self, data_format )
@@ -603,12 +602,12 @@
         dataset_source = dataproviders.dataset.DatasetDataProvider( dataset )
         return dataproviders.base.DataProvider( dataset_source, **settings )
-    @dataproviders.decorators.dataprovider_factory( 'chunk' )
+    @dataproviders.decorators.dataprovider_factory( 'chunk', dataproviders.chunk.ChunkDataProvider.settings )
     def chunk_dataprovider( self, dataset, **settings ):
         dataset_source = dataproviders.dataset.DatasetDataProvider( dataset )
         return dataproviders.chunk.ChunkDataProvider( dataset_source, **settings )
-    @dataproviders.decorators.dataprovider_factory( 'chunk64' )
+    @dataproviders.decorators.dataprovider_factory( 'chunk64', dataproviders.chunk.Base64ChunkDataProvider.settings )
     def chunk64_dataprovider( self, dataset, **settings ):
         dataset_source = dataproviders.dataset.DatasetDataProvider( dataset )
         return dataproviders.chunk.Base64ChunkDataProvider( dataset_source, **settings )
@@ -785,7 +784,7 @@
     split = classmethod(split)
# ------------- Dataproviders
-    @dataproviders.decorators.dataprovider_factory( 'line' )
+    @dataproviders.decorators.dataprovider_factory( 'line', dataproviders.line.FilteredLineDataProvider.settings )
     def line_dataprovider( self, dataset, **settings ):
         """
         Returns an iterator over the dataset's lines (that have been `strip`ed)
@@ -794,7 +793,7 @@
         dataset_source = dataproviders.dataset.DatasetDataProvider( dataset )
         return dataproviders.line.FilteredLineDataProvider( dataset_source, **settings )
-    @dataproviders.decorators.dataprovider_factory( 'regex-line' )
+    @dataproviders.decorators.dataprovider_factory( 'regex-line', dataproviders.line.RegexLineDataProvider.settings )
     def regex_line_dataprovider( self, dataset, **settings ):
         """
         Returns an iterator over the dataset's lines
diff -r 8ea772733c979a4d5578ba4c8c31dd3f47cc32ba -r 72b02995c8b188b8efe9b3ac4c5996e972e596f1 lib/galaxy/datatypes/dataproviders/base.py
--- a/lib/galaxy/datatypes/dataproviders/base.py
+++ b/lib/galaxy/datatypes/dataproviders/base.py
@@ -22,8 +22,13 @@
icorporate existing visualization/dataproviders
 some of the sources (esp. in datasets) don't need to be re-created
+YAGNI: InterleavingMultiSourceDataProvider, CombiningMultiSourceDataProvider
-YAGNI: InterleavingMultiSourceDataProvider, CombiningMultiSourceDataProvider
+datasets API entry point:
+    kwargs should be parsed from strings 2 layers up (in the DatasetsAPI) - that's the 'proper' place for that.
+    but how would it know how/what to parse if it doesn't have access to the classes used in the provider?
+        Building a giant list by sweeping all possible dprov classes doesn't make sense
+    For now - I'm burying them in the class __init__s - but I don't like that
 """
import logging
@@ -31,6 +36,31 @@
# ----------------------------------------------------------------------------- base classes
+class HasSettings( type ):
+    """
+    Metaclass for data providers that allows defining and inheriting
+    a dictionary named 'settings'.
+
+    Useful for allowing class level access to expected variable types
+    passed to class `__init__` functions so they can be parsed from a query string.
+    """
+    # yeah - this is all too acrobatic
+    def __new__( cls, name, base_classes, attributes ):
+        settings = {}
+        # get settings defined in base classes
+        for base_class in base_classes:
+            base_settings = getattr( base_class, 'settings', None )
+            if base_settings:
+                settings.update( base_settings )
+        # get settings defined in this class
+        new_settings = attributes.pop( 'settings', None )
+        if new_settings:
+            settings.update( new_settings )
+        attributes[ 'settings' ] = settings
+        return type.__new__( cls, name, base_classes, attributes )
+
+
+# ----------------------------------------------------------------------------- base classes
 class DataProvider( object ):
     """
     Base class for all data providers. Data providers:
@@ -39,6 +69,12 @@
         (c) do not allow write methods
             (but otherwise implement the other file object interface methods)
     """
+    # a definition of expected types for keyword arguments sent to __init__
+    #   useful for controlling how query string dictionaries can be parsed into correct types for __init__
+    #   empty in this base class
+    __metaclass__ = HasSettings
+    settings = {}
+
     def __init__( self, source, **kwargs ):
         """
         :param source: the source that this iterator will loop over.
@@ -130,13 +166,16 @@
         - `num_valid_data_read`: how many data have been returned from `filter`.
         - `num_data_returned`: how many data has this provider yielded.
     """
+    # not useful here - we don't want functions over the query string
+    #settings.update({ 'filter_fn': 'function' })
+
     def __init__( self, source, filter_fn=None, **kwargs ):
         """
         :param filter_fn: a lambda or function that will be passed a datum and
             return either the (optionally modified) datum or None.
         """
         super( FilteredDataProvider, self ).__init__( source, **kwargs )
-        self.filter_fn = filter_fn
+        self.filter_fn = filter_fn if hasattr( filter_fn, '__call__' ) else None
         # count how many data we got from the source
         self.num_data_read = 0
         # how many valid data have we gotten from the source
@@ -179,6 +218,12 @@
Useful for grabbing sections from a source (e.g. pagination).
     """
+    # define the expected types of these __init__ arguments so they can be parsed out from query strings
+    settings = {
+        'limit' : 'int',
+        'offset': 'int'
+    }
+
     #TODO: may want to squash this into DataProvider
     def __init__( self, source, offset=0, limit=None, **kwargs ):
         """
diff -r 8ea772733c979a4d5578ba4c8c31dd3f47cc32ba -r 72b02995c8b188b8efe9b3ac4c5996e972e596f1 lib/galaxy/datatypes/dataproviders/chunk.py
--- a/lib/galaxy/datatypes/dataproviders/chunk.py
+++ b/lib/galaxy/datatypes/dataproviders/chunk.py
@@ -26,6 +26,10 @@
     """
     MAX_CHUNK_SIZE = 2**16
     DEFAULT_CHUNK_SIZE = MAX_CHUNK_SIZE
+    settings = {
+        'chunk_index'   : 'int',
+        'chunk_size'    : 'int'
+    }
#TODO: subclass from LimitedOffsetDataProvider?
     # see web/framework/base.iterate_file, util/__init__.file_reader, and datatypes.tabular
@@ -38,8 +42,8 @@
             (gen. in bytes).
         """
         super( ChunkDataProvider, self ).__init__( source, **kwargs )
-        self.chunk_size = chunk_size
-        self.chunk_pos = chunk_index * self.chunk_size
+        self.chunk_size = int( chunk_size )
+        self.chunk_pos = int( chunk_index ) * self.chunk_size
def validate_source( self, source ):
         """
diff -r 8ea772733c979a4d5578ba4c8c31dd3f47cc32ba -r 72b02995c8b188b8efe9b3ac4c5996e972e596f1 lib/galaxy/datatypes/dataproviders/column.py
--- a/lib/galaxy/datatypes/dataproviders/column.py
+++ b/lib/galaxy/datatypes/dataproviders/column.py
@@ -29,6 +29,14 @@
     the same number of columns as the number of indeces asked for (even if they
     are filled with None).
     """
+    settings = {
+        'indeces'       : 'list:int',
+        'column_count'  : 'int',
+        'column_types'  : 'list:str',
+        'parse_columns' : 'bool',
+        'deliminator'   : 'str'
+    }
+
     def __init__( self, source, indeces=None,
             column_count=None, column_types=None, parsers=None, parse_columns=True,
             deliminator='\t', **kwargs ):
@@ -91,11 +99,11 @@
         # how/whether to parse each column value
         self.parsers = {}
         if parse_columns:
-            self.parsers = self._get_default_parsers()
+            self.parsers = self.get_default_parsers()
             # overwrite with user desired parsers
             self.parsers.update( parsers or {} )
-    def _get_default_parsers( self ):
+    def get_default_parsers( self ):
         """
         Return parser dictionary keyed for each columnar type
         (as defined in datatypes).
@@ -132,7 +140,7 @@
             #'gffstrand': # -, +, ?, or '.' for None, etc.
         }
-    def _parse_value( self, val, type ):
+    def parse_value( self, val, type ):
         """
         Attempt to parse and return the given value based on the given type.
@@ -153,7 +161,7 @@
             return None
         return val
-    def _get_column_type( self, index ):
+    def get_column_type( self, index ):
         """
         Get the column type for the parser from `self.column_types` or `None`
         if the type is unavailable.
@@ -165,18 +173,18 @@
         except IndexError, ind_err:
             return None
-    def _parse_column_at_index( self, columns, parser_index, index ):
+    def parse_column_at_index( self, columns, parser_index, index ):
         """
         Get the column type for the parser from `self.column_types` or `None`
         if the type is unavailable.
         """
         try:
-            return self._parse_value( columns[ index ], self._get_column_type( parser_index ) )
+            return self.parse_value( columns[ index ], self.get_column_type( parser_index ) )
         # if a selected index is not within columns, return None
         except IndexError, index_err:
             return None
-    def _parse_columns_from_line( self, line ):
+    def parse_columns_from_line( self, line ):
         """
         Returns a list of the desired, parsed columns.
         :param line: the line to parse
@@ -188,13 +196,13 @@
         selected_indeces = self.selected_column_indeces or list( xrange( len( all_columns ) ) )
         parsed_columns = []
         for parser_index, column_index in enumerate( selected_indeces ):
-            parsed_columns.append( self._parse_column_at_index( all_columns, parser_index, column_index ) )
+            parsed_columns.append( self.parse_column_at_index( all_columns, parser_index, column_index ) )
         return parsed_columns
def __iter__( self ):
         parent_gen = super( ColumnarDataProvider, self ).__iter__()
         for line in parent_gen:
-            columns = self._parse_columns_from_line( line )
+            columns = self.parse_columns_from_line( line )
             yield columns
#TODO: implement column filters here and not below - flatten hierarchy
@@ -223,6 +231,10 @@
     .. note: that the subclass constructors are passed kwargs - so they're
     params (limit, offset, etc.) are also applicable here.
     """
+    settings = {
+        'column_names'  : 'list:str',
+    }
+
     def __init__( self, source, column_names=None, **kwargs ):
         """
         :param column_names: an ordered list of strings that will be used as the keys
diff -r 8ea772733c979a4d5578ba4c8c31dd3f47cc32ba -r 72b02995c8b188b8efe9b3ac4c5996e972e596f1 lib/galaxy/datatypes/dataproviders/dataset.py
--- a/lib/galaxy/datatypes/dataproviders/dataset.py
+++ b/lib/galaxy/datatypes/dataproviders/dataset.py
@@ -141,7 +141,7 @@
         """
         # metadata columns are 1-based indeces
         column = getattr( self.dataset.metadata, name )
-        return ( column - 1 ) if isinstance( column, int ) else None
+        return ( column - 1 ) if ( isinstance( column, int ) and column > 0 ) else None
def get_genomic_region_indeces( self, check=False ):
         """
@@ -271,6 +271,12 @@
     """
     # dictionary keys when named_columns=True
     COLUMN_NAMES = [ 'chrom', 'start', 'end' ]
+    settings = {
+        'chrom_column'  : 'int',
+        'start_column'  : 'int',
+        'end_column'    : 'int',
+        'named_columns' : 'bool',
+    }
def __init__( self, dataset, chrom_column=None, start_column=None, end_column=None, named_columns=False, **kwargs ):
         """
@@ -333,6 +339,14 @@
     'chrom', 'start', 'end' (and 'strand' and 'name' if available).
     """
     COLUMN_NAMES = [ 'chrom', 'start', 'end', 'strand', 'name' ]
+    settings = {
+        'chrom_column'  : 'int',
+        'start_column'  : 'int',
+        'end_column'    : 'int',
+        'strand_column' : 'int',
+        'name_column'   : 'int',
+        'named_columns' : 'bool',
+    }
def __init__( self, dataset, chrom_column=None, start_column=None, end_column=None,
                   strand_column=None, name_column=None, named_columns=False, **kwargs ):
@@ -349,25 +363,40 @@
         dataset_source = DatasetDataProvider( dataset )
# get genomic indeces and add strand and name
+        self.column_names = []
+        indeces = []
+        #TODO: this is sort of involved and oogly
         if chrom_column == None:
             chrom_column = dataset_source.get_metadata_column_index_by_name( 'chromCol' )
+            if chrom_column != None:
+                self.column_names.append( 'chrom' )
+                indeces.append( chrom_column )
         if start_column == None:
             start_column = dataset_source.get_metadata_column_index_by_name( 'startCol' )
+            if start_column != None:
+                self.column_names.append( 'start' )
+                indeces.append( start_column )
         if end_column == None:
             end_column = dataset_source.get_metadata_column_index_by_name( 'endCol' )
+            if end_column != None:
+                self.column_names.append( 'end' )
+                indeces.append( end_column )
         if strand_column == None:
             strand_column = dataset_source.get_metadata_column_index_by_name( 'strandCol' )
+            if strand_column != None:
+                self.column_names.append( 'strand' )
+                indeces.append( strand_column )
         if name_column == None:
             name_column = dataset_source.get_metadata_column_index_by_name( 'nameCol' )
-        indeces = [ chrom_column, start_column, end_column, strand_column, name_column ]
+            if name_column != None:
+                self.column_names.append( 'name' )
+                indeces.append( name_column )
+
         kwargs.update({ 'indeces' : indeces })
-
         if not kwargs.get( 'column_types', None ):
             kwargs.update({ 'column_types' : dataset_source.get_metadata_column_types( indeces=indeces ) })
self.named_columns = named_columns
-        if self.named_columns:
-            self.column_names = self.COLUMN_NAMES
super( IntervalDataProvider, self ).__init__( dataset_source, **kwargs )
@@ -390,6 +419,10 @@
             sequence: <joined lines of nucleotide/amino data>
         }
     """
+    settings = {
+        'ids'  : 'list:str',
+    }
+
     def __init__( self, source, ids=None, **kwargs ):
         """
         :param ids: optionally return only ids (and sequences) that are in this list.
@@ -419,6 +452,10 @@
             sequence: <joined lines of nucleotide/amino data>
         }
     """
+    settings = {
+        'ids'  : 'list:str',
+    }
+
     def __init__( self, source, ids=None, **kwargs ):
         """
         :param ids: optionally return only ids (and sequences) that are in this list.
@@ -445,6 +482,10 @@
     Class that returns chrom, pos, data from a wiggle source.
     """
     COLUMN_NAMES = [ 'chrom', 'pos', 'value' ]
+    settings = {
+        'named_columns' : 'bool',
+        'column_names'  : 'list:str',
+    }
def __init__( self, source, named_columns=False, column_names=None, **kwargs ):
         """
@@ -483,6 +524,10 @@
     Class that returns chrom, pos, data from a wiggle source.
     """
     COLUMN_NAMES = [ 'chrom', 'pos', 'value' ]
+    settings = {
+        'named_columns' : 'bool',
+        'column_names'  : 'list:str',
+    }
def __init__( self, source, chrom, start, end, named_columns=False, column_names=None, **kwargs ):
         """
diff -r 8ea772733c979a4d5578ba4c8c31dd3f47cc32ba -r 72b02995c8b188b8efe9b3ac4c5996e972e596f1 lib/galaxy/datatypes/dataproviders/decorators.py
--- a/lib/galaxy/datatypes/dataproviders/decorators.py
+++ b/lib/galaxy/datatypes/dataproviders/decorators.py
@@ -87,17 +87,40 @@
     #    log.debug( '\t\t ', fn.__doc__ )
     return cls
-def dataprovider_factory( name ):
+def dataprovider_factory( name, settings=None ):
     """
-    Wraps a class method and marks it as a dataprovider factory.
+    Wraps a class method and marks it as a dataprovider factory and creates a
+    function to parse query strings to __init__ arguments as the
+    `parse_query_string_settings` attribute of the factory function.
+
+    An example use of the `parse_query_string_settings`:
+    ..example::
+    kwargs = dataset.datatype.dataproviders[ provider ].parse_query_string_settings( query_kwargs )
+    return list( dataset.datatype.dataprovider( dataset, provider, **kwargs ) )
:param name: what name/key to register the factory under in `cls.dataproviders`
-    :param type: any hashable var
+    :type name: any hashable var
+    :param settings: dictionary containing key/type pairs for parsing query strings
+    to __init__ arguments
+    :type settings: dictionary
     """
+    #TODO:?? use *args for settings allowing mulitple dictionaries
+    # make a function available through the name->provider dispatch to parse query strings
+    #   callable like:
+    # settings_dict = dataproviders[ provider_name ].parse_query_string_settings( query_kwargs )
+    #TODO: ugh - overly complicated but the best I could think of
+    def parse_query_string_settings( query_kwargs ):
+        return _parse_query_string_settings( query_kwargs, settings )
+
     #log.debug( 'dataprovider:', name )
     def named_dataprovider_factory( func ):
         #log.debug( 'named_dataprovider_factory:', name, '->', func.__name__ )
         setattr( func, _DATAPROVIDER_METHOD_NAME_KEY, name )
+
+        setattr( func, 'parse_query_string_settings', parse_query_string_settings )
+        setattr( func, 'settings', settings )
+        #TODO: I want a way to inherit settings from the previous provider( this_name ) instead of defining over and over
+
         #log.debug( '\t setting:', getattr( func, _DATAPROVIDER_METHOD_NAME_KEY ) )
         @wraps( func )
         def wrapped_dataprovider_factory( self, *args, **kwargs ):
@@ -105,3 +128,38 @@
             return func( self, *args, **kwargs )
         return wrapped_dataprovider_factory
     return named_dataprovider_factory
+
+def _parse_query_string_settings( query_kwargs, settings=None ):
+    """
+    Parse the values in `query_kwargs` from strings to the proper types
+    listed in the same key in `settings`.
+    """
+    def list_from_query_string( s ):
+        # assume csv
+        return s.split( ',' )
+
+    parsers = {
+        'int'   : int,
+        'float' : float,
+        'bool'  : bool,
+        'list:str'  : lambda s: list_from_query_string( s ),
+        'list:int'  : lambda s: [ int( i ) for i in list_from_query_string( s ) ],
+    }
+    settings = settings or {}
+    # yay! yet another set of query string parsers! <-- sarcasm
+    # work through the keys in settings finding matching keys in query_kwargs
+    #   if found in both, get the expected/needed type from settings and store the new parsed value
+    #   if we can't parse it (no parser, bad value), delete the key from query_kwargs so the provider will use the defaults
+    for key in settings:
+        if key in query_kwargs:
+            #TODO: this would be the place to sanitize any strings
+            query_value = query_kwargs[ key ]
+            needed_type = settings[ key ]
+            try:
+                query_kwargs[ key ] = parsers[ needed_type ]( query_value )
+            except ( KeyError, ValueError ):
+                del query_kwargs[ key ]
+
+        #TODO:?? do we want to remove query_kwarg entries NOT in settings?
+    return query_kwargs
+
diff -r 8ea772733c979a4d5578ba4c8c31dd3f47cc32ba -r 72b02995c8b188b8efe9b3ac4c5996e972e596f1 lib/galaxy/datatypes/dataproviders/line.py
--- a/lib/galaxy/datatypes/dataproviders/line.py
+++ b/lib/galaxy/datatypes/dataproviders/line.py
@@ -27,6 +27,12 @@
     to return.
     """
     DEFAULT_COMMENT_CHAR = '#'
+    settings = {
+        'string_lines'  : 'bool',
+        'provide_blank' : 'bool',
+        'comment_char'  : 'str',
+    }
+
     def __init__( self, source, strip_lines=True, provide_blank=False, comment_char=DEFAULT_COMMENT_CHAR, **kwargs ):
         """
         :param strip_lines: remove whitespace from the beginning an ending
@@ -78,6 +84,11 @@
     .. note:: the regex matches are effectively OR'd (if **any** regex matches
     the line it is considered valid and will be provided).
     """
+    settings = {
+        'regex_list'    : 'list:str',
+        'invert'        : 'bool',
+    }
+
     def __init__( self, source, regex_list=None, invert=False, **kwargs ):
         """
         :param regex_list: list of strings or regular expression strings that will
diff -r 8ea772733c979a4d5578ba4c8c31dd3f47cc32ba -r 72b02995c8b188b8efe9b3ac4c5996e972e596f1 lib/galaxy/datatypes/interval.py
--- a/lib/galaxy/datatypes/interval.py
+++ b/lib/galaxy/datatypes/interval.py
@@ -334,20 +334,24 @@
         return None
# ------------- Dataproviders
-    @dataproviders.decorators.dataprovider_factory( 'genomic-region' )
+    @dataproviders.decorators.dataprovider_factory( 'genomic-region',
+                                                    dataproviders.dataset.GenomicRegionDataProvider.settings )
     def genomic_region_dataprovider( self, dataset, **settings ):
         return dataproviders.dataset.GenomicRegionDataProvider( dataset, **settings )
-    @dataproviders.decorators.dataprovider_factory( 'genomic-region-map' )
+    @dataproviders.decorators.dataprovider_factory( 'genomic-region-map',
+                                                    dataproviders.dataset.GenomicRegionDataProvider.settings )
     def genomic_region_map_dataprovider( self, dataset, **settings ):
         settings[ 'named_columns' ] = True
         return self.genomic_region_dataprovider( dataset, **settings )
-    @dataproviders.decorators.dataprovider_factory( 'interval' )
+    @dataproviders.decorators.dataprovider_factory( 'interval',
+                                                    dataproviders.dataset.IntervalDataProvider.settings )
     def interval_dataprovider( self, dataset, **settings ):
         return dataproviders.dataset.IntervalDataProvider( dataset, **settings )
-    @dataproviders.decorators.dataprovider_factory( 'interval-map' )
+    @dataproviders.decorators.dataprovider_factory( 'interval-map',
+                                                    dataproviders.dataset.IntervalDataProvider.settings )
     def interval_map_dataprovider( self, dataset, **settings ):
         settings[ 'named_columns' ] = True
         return self.interval_dataprovider( dataset, **settings )
@@ -809,20 +813,24 @@
# ------------- Dataproviders
     # redefine bc super is Tabular
-    @dataproviders.decorators.dataprovider_factory( 'genomic-region' )
+    @dataproviders.decorators.dataprovider_factory( 'genomic-region',
+                                                    dataproviders.dataset.GenomicRegionDataProvider.settings )
     def genomic_region_dataprovider( self, dataset, **settings ):
         return dataproviders.dataset.GenomicRegionDataProvider( dataset, 0, 3, 4, **settings )
-    @dataproviders.decorators.dataprovider_factory( 'genomic-region-map' )
+    @dataproviders.decorators.dataprovider_factory( 'genomic-region-map',
+                                                    dataproviders.dataset.GenomicRegionDataProvider.settings )
     def genomic_region_map_dataprovider( self, dataset, **settings ):
         settings[ 'named_columns' ] = True
         return self.genomic_region_dataprovider( dataset, **settings )
-    @dataproviders.decorators.dataprovider_factory( 'interval' )
+    @dataproviders.decorators.dataprovider_factory( 'interval',
+                                                    dataproviders.dataset.IntervalDataProvider.settings )
     def interval_dataprovider( self, dataset, **settings ):
         return dataproviders.dataset.IntervalDataProvider( dataset, 0, 3, 4, 6, 2, **settings )
-    @dataproviders.decorators.dataprovider_factory( 'interval-map' )
+    @dataproviders.decorators.dataprovider_factory( 'interval-map',
+                                                    dataproviders.dataset.IntervalDataProvider.settings )
     def interval_map_dataprovider( self, dataset, **settings ):
         settings[ 'named_columns' ] = True
         return self.interval_dataprovider( dataset, **settings )
@@ -1193,12 +1201,12 @@
         return resolution
# ------------- Dataproviders
-    @dataproviders.decorators.dataprovider_factory( 'wiggle' )
+    @dataproviders.decorators.dataprovider_factory( 'wiggle', dataproviders.dataset.WiggleDataProvider.settings )
     def wiggle_dataprovider( self, dataset, **settings ):
         dataset_source = dataproviders.dataset.DatasetDataProvider( dataset )
         return dataproviders.dataset.WiggleDataProvider( dataset_source, **settings )
-    @dataproviders.decorators.dataprovider_factory( 'wiggle-map' )
+    @dataproviders.decorators.dataprovider_factory( 'wiggle-map', dataproviders.dataset.WiggleDataProvider.settings )
     def wiggle_map_dataprovider( self, dataset, **settings ):
         dataset_source = dataproviders.dataset.DatasetDataProvider( dataset )
         settings[ 'named_columns' ] = True
diff -r 8ea772733c979a4d5578ba4c8c31dd3f47cc32ba -r 72b02995c8b188b8efe9b3ac4c5996e972e596f1 lib/galaxy/datatypes/sequence.py
--- a/lib/galaxy/datatypes/sequence.py
+++ b/lib/galaxy/datatypes/sequence.py
@@ -15,8 +15,6 @@
 from galaxy import util
 from sniff import *
-from galaxy.datatypes import dataproviders
-
 import pkg_resources
 pkg_resources.require("simplejson")
 import simplejson
@@ -399,15 +397,6 @@
         f.close()
     _count_split = classmethod(_count_split)
-    def provider( self, dataset, data_format, **settings ):
-        from galaxy.dataproviders import dataset as dataset_providers
-
-        if  data_format == 'id_seq':
-            source = dataset_providers.DatasetDataProvider( dataset )
-            return dataset_providers.FastaDataProvider( source, **settings )
-
-        return super( Fasta, self ).provider( dataset, data_format, **settings )
-
class csFasta( Sequence ):
     """ Class representing the SOLID Color-Space sequence ( csfasta ) """
diff -r 8ea772733c979a4d5578ba4c8c31dd3f47cc32ba -r 72b02995c8b188b8efe9b3ac4c5996e972e596f1 lib/galaxy/datatypes/tabular.py
--- a/lib/galaxy/datatypes/tabular.py
+++ b/lib/galaxy/datatypes/tabular.py
@@ -345,26 +345,25 @@
         return  vizs
# ------------- Dataproviders
-    @dataproviders.decorators.dataprovider_factory( 'column' )
+    @dataproviders.decorators.dataprovider_factory( 'column', dataproviders.column.ColumnarDataProvider.settings )
     def column_dataprovider( self, dataset, **settings ):
         """Uses column settings that are passed in"""
-        print 'Tabular.comment_char:', settings.get( 'comment_char', None )
-
         dataset_source = dataproviders.dataset.DatasetDataProvider( dataset )
         return dataproviders.column.ColumnarDataProvider( dataset_source, **settings )
-    @dataproviders.decorators.dataprovider_factory( 'dataset-column' )
+    @dataproviders.decorators.dataprovider_factory( 'dataset-column',
+                                                    dataproviders.column.ColumnarDataProvider.settings )
     def dataset_column_dataprovider( self, dataset, **settings ):
         """Attempts to get column settings from dataset.metadata"""
         return dataproviders.dataset.DatasetColumnarDataProvider( dataset, **settings )
-    @dataproviders.decorators.dataprovider_factory( 'map' )
+    @dataproviders.decorators.dataprovider_factory( 'map', dataproviders.column.MapDataProvider.settings )
     def map_dataprovider( self, dataset, **settings ):
         """Uses column settings that are passed in"""
         dataset_source = dataproviders.dataset.DatasetDataProvider( dataset )
         return dataproviders.column.MapDataProvider( dataset_source, **settings )
-    @dataproviders.decorators.dataprovider_factory( 'dataset-map' )
+    @dataproviders.decorators.dataprovider_factory( 'dataset-map', dataproviders.column.MapDataProvider.settings )
     def dataset_map_dataprovider( self, dataset, **settings ):
         """Attempts to get column settings from dataset.metadata"""
         return dataproviders.dataset.DatasetMapDataProvider( dataset, **settings )
@@ -502,55 +501,58 @@
     # ------------- Dataproviders
     # sam does not use '#' to indicate comments/headers - we need to strip out those headers from the std. providers
     #TODO:?? seems like there should be an easier way to do this - metadata.comment_char?
-    @dataproviders.decorators.dataprovider_factory( 'line' )
+    @dataproviders.decorators.dataprovider_factory( 'line', dataproviders.line.FilteredLineDataProvider.settings )
     def line_dataprovider( self, dataset, **settings ):
         settings[ 'comment_char' ] = '@'
         return super( Sam, self ).line_dataprovider( dataset, **settings )
-    @dataproviders.decorators.dataprovider_factory( 'regex-line' )
+    @dataproviders.decorators.dataprovider_factory( 'regex-line', dataproviders.line.RegexLineDataProvider.settings )
     def regex_line_dataprovider( self, dataset, **settings ):
         settings[ 'comment_char' ] = '@'
         return super( Sam, self ).regex_line_dataprovider( dataset, **settings )
-    @dataproviders.decorators.dataprovider_factory( 'column' )
+    @dataproviders.decorators.dataprovider_factory( 'column', dataproviders.column.ColumnarDataProvider.settings )
     def column_dataprovider( self, dataset, **settings ):
         settings[ 'comment_char' ] = '@'
         return super( Sam, self ).column_dataprovider( dataset, **settings )
-    @dataproviders.decorators.dataprovider_factory( 'dataset-column' )
+    @dataproviders.decorators.dataprovider_factory( 'dataset-column',
+                                                    dataproviders.column.ColumnarDataProvider.settings )
     def dataset_column_dataprovider( self, dataset, **settings ):
         settings[ 'comment_char' ] = '@'
         return super( Sam, self ).dataset_column_dataprovider( dataset, **settings )
-    @dataproviders.decorators.dataprovider_factory( 'map' )
+    @dataproviders.decorators.dataprovider_factory( 'map', dataproviders.column.MapDataProvider.settings )
     def map_dataprovider( self, dataset, **settings ):
         settings[ 'comment_char' ] = '@'
         return super( Sam, self ).map_dataprovider( dataset, **settings )
-    @dataproviders.decorators.dataprovider_factory( 'dataset-map' )
+    @dataproviders.decorators.dataprovider_factory( 'dataset-map', dataproviders.column.MapDataProvider.settings )
     def dataset_map_dataprovider( self, dataset, **settings ):
         settings[ 'comment_char' ] = '@'
         return super( Sam, self ).dataset_map_dataprovider( dataset, **settings )
-    @dataproviders.decorators.dataprovider_factory( 'header' )
+    @dataproviders.decorators.dataprovider_factory( 'header', dataproviders.line.RegexLineDataProvider.settings )
     def header_dataprovider( self, dataset, **settings ):
         dataset_source = dataproviders.dataset.DatasetDataProvider( dataset )
         headers_source = dataproviders.line.RegexLineDataProvider( dataset_source, regex_list=[ '^@' ] )
         return dataproviders.line.RegexLineDataProvider( headers_source, **settings )
-    @dataproviders.decorators.dataprovider_factory( 'id-seq-qual' )
+    @dataproviders.decorators.dataprovider_factory( 'id-seq-qual', map_dataprovider.settings )
     def id_seq_qual_dataprovider( self, dataset, **settings ):
         # provided as an example of a specified column map (w/o metadata)
         settings[ 'indeces' ] = [ 0, 9, 10 ]
         settings[ 'column_names' ] = [ 'id', 'seq', 'qual' ]
         return self.map_dataprovider( dataset, **settings )
-    @dataproviders.decorators.dataprovider_factory( 'genomic-region' )
+    @dataproviders.decorators.dataprovider_factory( 'genomic-region',
+                                                    dataproviders.dataset.GenomicRegionDataProvider.settings )
     def genomic_region_dataprovider( self, dataset, **settings ):
         settings[ 'comment_char' ] = '@'
         return dataproviders.dataset.GenomicRegionDataProvider( dataset, 2, 3, 3, **settings )
-    @dataproviders.decorators.dataprovider_factory( 'genomic-region-map' )
+    @dataproviders.decorators.dataprovider_factory( 'genomic-region-map',
+                                                    dataproviders.dataset.GenomicRegionDataProvider.settings )
     def genomic_region_map_dataprovider( self, dataset, **settings ):
         settings[ 'comment_char' ] = '@'
         return dataproviders.dataset.GenomicRegionDataProvider( dataset, 2, 3, 3, True, **settings )
@@ -621,11 +623,13 @@
             return False
# ------------- Dataproviders
-    @dataproviders.decorators.dataprovider_factory( 'genomic-region' )
+    @dataproviders.decorators.dataprovider_factory( 'genomic-region',
+                                                    dataproviders.dataset.GenomicRegionDataProvider.settings )
     def genomic_region_dataprovider( self, dataset, **settings ):
         return dataproviders.dataset.GenomicRegionDataProvider( dataset, **settings )
-    @dataproviders.decorators.dataprovider_factory( 'genomic-region-map' )
+    @dataproviders.decorators.dataprovider_factory( 'genomic-region-map',
+                                                    dataproviders.dataset.GenomicRegionDataProvider.settings )
     def genomic_region_map_dataprovider( self, dataset, **settings ):
         settings[ 'named_columns' ] = True
         return self.genomic_region_dataprovider( dataset, **settings )
@@ -668,11 +672,13 @@
             dataset.metadata.sample_names = line.split()[ 9: ]
# ------------- Dataproviders
-    @dataproviders.decorators.dataprovider_factory( 'genomic-region' )
+    @dataproviders.decorators.dataprovider_factory( 'genomic-region',
+                                                    dataproviders.dataset.GenomicRegionDataProvider.settings )
     def genomic_region_dataprovider( self, dataset, **settings ):
         return dataproviders.dataset.GenomicRegionDataProvider( dataset, 0, 1, 1, **settings )
-    @dataproviders.decorators.dataprovider_factory( 'genomic-region-map' )
+    @dataproviders.decorators.dataprovider_factory( 'genomic-region-map',
+                                                    dataproviders.dataset.GenomicRegionDataProvider.settings )
     def genomic_region_map_dataprovider( self, dataset, **settings ):
         settings[ 'named_columns' ] = True
         return self.genomic_region_dataprovider( dataset, **settings )
diff -r 8ea772733c979a4d5578ba4c8c31dd3f47cc32ba -r 72b02995c8b188b8efe9b3ac4c5996e972e596f1 lib/galaxy/visualization/data_providers/registry.py
--- a/lib/galaxy/visualization/data_providers/registry.py
+++ b/lib/galaxy/visualization/data_providers/registry.py
@@ -32,7 +32,7 @@
             "bigwig": genome.BigWigDataProvider,
             "bigbed": genome.BigBedDataProvider,
-            "column": ColumnDataProvider
+            "column_with_stats": ColumnDataProvider
         }
def get_data_provider( self, trans, name=None, source='data', raw=False, original_dataset=None ):
diff -r 8ea772733c979a4d5578ba4c8c31dd3f47cc32ba -r 72b02995c8b188b8efe9b3ac4c5996e972e596f1 lib/galaxy/visualization/registry.py
--- a/lib/galaxy/visualization/registry.py
+++ b/lib/galaxy/visualization/registry.py
@@ -15,22 +15,27 @@
 log = logging.getLogger( __name__ )
__TODO__ = """
-    BUGS:
-        anon users clicking a viz link gets 'must be' msg in galaxy_main (w/ masthead)
-            should not show visualizations (no icon)?
-        newick files aren't being sniffed prop? - datatype is txt
+BUGS:
+    anon users clicking a viz link gets 'must be' msg in galaxy_main (w/ masthead)
+        should not show visualizations (no icon)?
+    newick files aren't being sniffed prop? - datatype is txt
-    have parsers create objects instead of dicts
-    allow data_sources with no model_class but have tests (isAdmin, etc.)
-        maybe that's an instance of User model_class?
-    some confused vocabulary in docs, var names
-    tests:
-        anding, grouping, not
-    data_sources:
-        lists of
-    add description element to visualization.
+have parsers create objects instead of dicts
+allow data_sources with no model_class but have tests (isAdmin, etc.)
+    maybe that's an instance of User model_class?
+some confused vocabulary in docs, var names
+tests:
+    anding, grouping, not
+data_sources:
+    lists of
+add description element to visualization.
+
+TESTS to add:
+    has dataprovider
+    user is admin
 """
+# ------------------------------------------------------------------- the registry
 class VisualizationsRegistry( object ):
     """
     Main responsibilities are:
@@ -93,6 +98,12 @@
         """
         self.listings = VisualizationsConfigParser.parse( self.configuration_filepath )
+    #TODO: def get_visualization( self, trans, visualization_name, target_object ):
+    #    """
+    #    Is the visualization with the given `visualization_name` applicable
+    #    to the `target_object`?
+    #    """
+
     # -- building links to visualizations from objects --
     def get_visualizations( self, trans, target_object ):
         """
@@ -151,10 +162,11 @@
                     # convert datatypes to their actual classes (for use with isinstance)
                     test_result = trans.app.datatypes_registry.get_datatype_class_by_name( test_result )
                     if not test_result:
-                        # warn if can't find class, but continue
+                        # warn if can't find class, but continue (with other tests)
                         log.warn( 'visualizations_registry cannot find class (%s) for applicability test', test_result )
                         continue
+            #NOTE: tests are OR'd, if any test passes - the visualization can be applied
             if test_fn( target_object, test_result ):
                 #log.debug( 'test passed' )
                 return True
diff -r 8ea772733c979a4d5578ba4c8c31dd3f47cc32ba -r 72b02995c8b188b8efe9b3ac4c5996e972e596f1 lib/galaxy/webapps/galaxy/api/datasets.py
--- a/lib/galaxy/webapps/galaxy/api/datasets.py
+++ b/lib/galaxy/webapps/galaxy/api/datasets.py
@@ -6,6 +6,7 @@
 from galaxy.web.base.controller import BaseAPIController, UsesVisualizationMixin, UsesHistoryDatasetAssociationMixin
 from galaxy.web.base.controller import UsesHistoryMixin
 from galaxy.web.framework.helpers import is_true
+from galaxy.datatypes import dataproviders
import logging
 log = logging.getLogger( __name__ )
@@ -217,10 +218,24 @@
             return msg
registry = trans.app.data_provider_registry
+
         # allow the caller to specifiy which provider is used
-        if provider and provider in registry.dataset_type_name_to_data_provider:
-            data_provider = registry.dataset_type_name_to_data_provider[ provider ]( dataset )
-        # or have it look up by datatype
+        #   pulling from the original providers if possible, then the new providers
+        if provider:
+            if provider in registry.dataset_type_name_to_data_provider:
+                data_provider = registry.dataset_type_name_to_data_provider[ provider ]( dataset )
+
+            elif dataset.datatype.has_dataprovider( provider ):
+                kwargs = dataset.datatype.dataproviders[ provider ].parse_query_string_settings( kwargs )
+                # use dictionary to allow more than the data itself to be returned (data totals, other meta, etc.)
+                return {
+                    'data': list( dataset.datatype.dataprovider( dataset, provider, **kwargs ) )
+                }
+
+            else:
+                raise dataproviders.exceptions.NoProviderAvailable( dataset.datatype, provider )
+
+        # no provider name: look up by datatype
         else:
             data_provider = registry.get_data_provider( trans, raw=True, original_dataset=dataset )
diff -r 8ea772733c979a4d5578ba4c8c31dd3f47cc32ba -r 72b02995c8b188b8efe9b3ac4c5996e972e596f1 static/scripts/mvc/visualizations/scatterplotControlForm.js
--- a/static/scripts/mvc/visualizations/scatterplotControlForm.js
+++ b/static/scripts/mvc/visualizations/scatterplotControlForm.js
@@ -562,7 +562,7 @@
var params = {
             data_type   : 'raw_data',
-            provider    : 'column',
+            provider    : 'column_with_stats',
             columns     : '[' + columns + ']'
         };
         this.log( '\t data settings (url params):', params );
diff -r 8ea772733c979a4d5578ba4c8c31dd3f47cc32ba -r 72b02995c8b188b8efe9b3ac4c5996e972e596f1 static/scripts/packed/mvc/data.js
--- a/static/scripts/packed/mvc/data.js
+++ b/static/scripts/packed/mvc/data.js
@@ -1,1 +1,1 @@
-define(["libs/backbone/backbone-relational"],function(){var d=Backbone.RelationalModel.extend({});var e=Backbone.RelationalModel.extend({defaults:{id:"",type:"",name:"",hda_ldda:"hda",metadata:null},initialize:function(){this._set_metadata();this.on("change",this._set_metadata,this)},_set_metadata:function(){var i=new d();_.each(_.keys(this.attributes),function(j){if(j.indexOf("metadata_")===0){var l=j.split("metadata_")[1];i.set(l,this.attributes[j]);delete this.attributes[j]}},this);this.set("metadata",i,{silent:true})},get_metadata:function(i){return this.attributes.metadata.get(i)},urlRoot:galaxy_paths.get("datasets_url")});var c=e.extend({defaults:_.extend({},e.prototype.defaults,{chunk_url:null,first_data_chunk:null,chunk_index:-1,at_eof:false}),initialize:function(i){e.prototype.initialize.call(this);this.attributes.chunk_index=(this.attributes.first_data_chunk?1:0)},get_next_chunk:function(){if(this.attributes.at_eof){return null}var i=this,j=$.Deferred();$.getJSON(this.attributes.chunk_url,{chunk:i.attributes.chunk_index++}).success(function(k){var l;if(k.ck_data!==""){l=k}else{i.attributes.at_eof=true;l=null}j.resolve(l)});return j}});var g=Backbone.Collection.extend({model:e});var f=Backbone.View.extend({initialize:function(i){(new b(i)).render()},render:function(){var m=$("<table/>").attr({id:"content_table",cellpadding:0});this.$el.append(m);var i=this.model.get_metadata("column_names");if(i){m.append("<tr><th>"+i.join("</th><th>")+"</th></tr>")}var k=this.model.get("first_data_chunk");if(k){this._renderChunk(k)}var j=this,n=_.find(this.$el.parents(),function(o){return $(o).css("overflow")==="auto"}),l=false;if(!n){n=window}n=$(n);n.scroll(function(){if(!l&&(j.$el.height()-n.scrollTop()-n.height()<=0)){l=true;$.when(j.model.get_next_chunk()).then(function(o){if(o){j._renderChunk(o);l=false}})}});$("#loading_indicator").ajaxStart(function(){$(this).show()}).ajaxStop(function(){$(this).hide()})},_renderCell:function(k,i,l){var j=this.model.get_metadata("column_types");if(l!==undefined){return $("<td>").attr("colspan",l).addClass("stringalign").text(k)}else{if(j[i]==="str"||j==="list"){return $("<td>").addClass("stringalign").text(k)}else{return $("<td>").text(k)}}},_renderRow:function(i){var j=i.split("\t"),l=$("<tr>"),k=this.model.get_metadata("columns");if(j.length===k){_.each(j,function(n,m){l.append(this._renderCell(n,m))},this)}else{if(j.length>k){_.each(j.slice(0,k-1),function(n,m){l.append(this._renderCell(n,m))},this);l.append(this._renderCell(j.slice(k-1).join("\t"),k-1))}else{if(k>5&&j.length===k-1){_.each(j,function(n,m){l.append(this._renderCell(n,m))},this);l.append($("<td>"))}else{l.append(this._renderCell(i,0,k))}}}return l},_renderChunk:function(i){var j=this.$el.find("table");_.each(i.ck_data.split("\n"),function(k,l){j.append(this._renderRow(k))},this)}});var b=Backbone.View.extend({col:{chrom:null,start:null,end:null},url_viz:null,dataset_id:null,genome_build:null,initialize:function(i){var j=i.model.attributes.metadata.attributes;if(typeof j.chromCol==="undefined"||typeof j.startCol==="undefined"||typeof j.endCol==="undefined"){console.log("TabularButtonTrackster : Metadata for column identification is missing.")}else{this.col.chrom=j.chromCol-1;this.col.start=j.startCol-1;this.col.end=j.endCol-1}if(this.col.chrom===null){return}if(typeof i.model.attributes.id==="undefined"){console.log("TabularButtonTrackster : Dataset identification is missing.")}else{this.dataset_id=i.model.attributes.id}if(typeof i.model.attributes.url_viz==="undefined"){console.log("TabularButtonTrackster : Url for visualization controller is missing.")}else{this.url_viz=i.model.attributes.url_viz}if(typeof i.model.attributes.genome_build!=="undefined"){this.genome_build=i.model.attributes.genome_build}},events:{"mouseover tr":"btn_viz_show",mouseleave:"btn_viz_hide"},btn_viz_show:function(m){if(this.col.chrom===null){return}var q=$(m.target).parent();var n=q.children().eq(this.col.chrom).html();var i=q.children().eq(this.col.start).html();var k=q.children().eq(this.col.end).html();if(n!==""&&i!==""&&k!==""){var p={dataset_id:this.dataset_id,gene_region:n+":"+i+"-"+k};var l=q.offset();var j=l.left-10;var o=l.top;$("#btn_viz").css({position:"fixed",top:o+"px",left:j+"px"});$("#btn_viz").off("click");$("#btn_viz").click(this.create_trackster_action(this.url_viz,p,this.genome_build));$("#btn_viz").show()}},btn_viz_hide:function(){$("#btn_viz").hide()},create_trackster_action:function(i,k,j){return function(){var l={};if(j){l["f-dbkey"]=j}$.ajax({url:i+"/list_tracks?"+$.param(l),dataType:"html",error:function(){alert(("Could not add this dataset to browser")+".")},success:function(m){var n=window.parent;n.show_modal(("View Data in a New or Saved Visualization"),"",{Cancel:function(){n.hide_modal()},"View in saved visualization":function(){n.show_modal(("Add Data to Saved Visualization"),m,{Cancel:function(){n.hide_modal()},"Add to visualization":function(){$(n.document).find("input[name=id]:checked").each(function(){var o=$(this).val();k.id=o;n.location=i+"/trackster?"+$.param(k)})}})},"View in new visualization":function(){n.location=i+"/trackster?"+$.param(k)}})}});return false}},render:function(){var i=new IconButtonView({model:new IconButton({title:"Visualize",icon_class:"chart_curve",id:"btn_viz"})});this.$el.append(i.render().$el);$("#btn_viz").hide()}});var a=function(l,j,m,i){var k=new j({model:new l(m)});k.render();if(i){i.append(k.$el)}return k};var h=function(k,i){var j=$("<div/>").appendTo(i);return new f({el:j,model:new c(k)}).render()};return{Dataset:e,TabularDataset:c,DatasetCollection:g,TabularDatasetChunkedView:f,createTabularDatasetChunkedView:h}});
\ No newline at end of file
+define(["libs/backbone/backbone-relational"],function(){var d=Backbone.RelationalModel.extend({});var e=Backbone.RelationalModel.extend({defaults:{id:"",type:"",name:"",hda_ldda:"hda",metadata:null},initialize:function(){this._set_metadata();this.on("change",this._set_metadata,this)},_set_metadata:function(){var i=new d();_.each(_.keys(this.attributes),function(j){if(j.indexOf("metadata_")===0){var l=j.split("metadata_")[1];i.set(l,this.attributes[j]);delete this.attributes[j]}},this);this.set("metadata",i,{silent:true})},get_metadata:function(i){return this.attributes.metadata.get(i)},urlRoot:galaxy_paths.get("datasets_url")});var c=e.extend({defaults:_.extend({},e.prototype.defaults,{chunk_url:null,first_data_chunk:null,chunk_index:-1,at_eof:false}),initialize:function(i){e.prototype.initialize.call(this);this.attributes.chunk_index=(this.attributes.first_data_chunk?1:0)},get_next_chunk:function(){if(this.attributes.at_eof){return null}var i=this,j=$.Deferred();$.getJSON(this.attributes.chunk_url,{chunk:i.attributes.chunk_index++}).success(function(k){var l;if(k.ck_data!==""){l=k}else{i.attributes.at_eof=true;l=null}j.resolve(l)});return j}});var g=Backbone.Collection.extend({model:e});var f=Backbone.View.extend({initialize:function(i){(new b(i)).render()},render:function(){var m=$("<table/>").attr({id:"content_table",cellpadding:0});this.$el.append(m);var i=this.model.get_metadata("column_names");if(i){m.append("<tr><th>"+i.join("</th><th>")+"</th></tr>")}var k=this.model.get("first_data_chunk");if(k){this._renderChunk(k)}var j=this,n=_.find(this.$el.parents(),function(o){return $(o).css("overflow")==="auto"}),l=false;if(!n){n=window}n=$(n);n.scroll(function(){if(!l&&(j.$el.height()-n.scrollTop()-n.height()<=0)){l=true;$.when(j.model.get_next_chunk()).then(function(o){if(o){j._renderChunk(o);l=false}})}});$("#loading_indicator").ajaxStart(function(){$(this).show()}).ajaxStop(function(){$(this).hide()})},_renderCell:function(k,i,l){var j=this.model.get_metadata("column_types");if(l!==undefined){return $("<td>").attr("colspan",l).addClass("stringalign").text(k)}else{if(j[i]==="str"||j==="list"){return $("<td>").addClass("stringalign").text(k)}else{return $("<td>").text(k)}}},_renderRow:function(i){var j=i.split("\t"),l=$("<tr>"),k=this.model.get_metadata("columns");if(j.length===k){_.each(j,function(n,m){l.append(this._renderCell(n,m))},this)}else{if(j.length>k){_.each(j.slice(0,k-1),function(n,m){l.append(this._renderCell(n,m))},this);l.append(this._renderCell(j.slice(k-1).join("\t"),k-1))}else{if(k>5&&j.length===k-1){_.each(j,function(n,m){l.append(this._renderCell(n,m))},this);l.append($("<td>"))}else{l.append(this._renderCell(i,0,k))}}}return l},_renderChunk:function(i){var j=this.$el.find("table");_.each(i.ck_data.split("\n"),function(k,l){j.append(this._renderRow(k))},this)}});var b=Backbone.View.extend({col:{chrom:null,start:null,end:null},url_viz:null,dataset_id:null,genome_build:null,initialize:function(i){var j=i.model.attributes.metadata.attributes;if(typeof j.chromCol==="undefined"||typeof j.startCol==="undefined"||typeof j.endCol==="undefined"){console.log("TabularButtonTrackster : Metadata for column identification is missing.")}else{this.col.chrom=j.chromCol-1;this.col.start=j.startCol-1;this.col.end=j.endCol-1}if(this.col.chrom===null){return}if(typeof i.model.attributes.id==="undefined"){console.log("TabularButtonTrackster : Dataset identification is missing.")}else{this.dataset_id=i.model.attributes.id}if(typeof i.model.attributes.url_viz==="undefined"){console.log("TabularButtonTrackster : Url for visualization controller is missing.")}else{this.url_viz=i.model.attributes.url_viz}if(typeof i.model.attributes.genome_build!=="undefined"){this.genome_build=i.model.attributes.genome_build}},events:{"mouseover tr":"btn_viz_show",mouseleave:"btn_viz_hide"},btn_viz_show:function(m){if(this.col.chrom===null){return}var q=$(m.target).parent();var n=q.children().eq(this.col.chrom).html();var i=q.children().eq(this.col.start).html();var k=q.children().eq(this.col.end).html();if(n!==""&&i!==""&&k!==""){var p={dataset_id:this.dataset_id,gene_region:n+":"+i+"-"+k};var l=q.offset();var j=l.left-10;var o=l.top;$("#btn_viz").css({position:"fixed",top:o+"px",left:j+"px"});$("#btn_viz").off("click");$("#btn_viz").click(this.create_trackster_action(this.url_viz,p,this.genome_build));$("#btn_viz").show()}},btn_viz_hide:function(){$("#btn_viz").hide()},create_trackster_action:function(i,k,j){return function(){var l={};if(j){l["f-dbkey"]=j}$.ajax({url:i+"/list_tracks?"+$.param(l),dataType:"html",error:function(){alert(("Could not add this dataset to browser")+".")},success:function(m){var n=window.parent;n.show_modal(("View Data in a New or Saved Visualization"),"",{Cancel:function(){n.hide_modal()},"View in saved visualization":function(){n.show_modal(("Add Data to Saved Visualization"),m,{Cancel:function(){n.hide_modal()},"Add to visualization":function(){$(n.document).find("input[name=id]:checked").each(function(){var o=$(this).val();k.id=o;n.frame_manager.frame_new({title:"Trackster",type:"url",content:i+"/trackster?"+$.param(k)});n.hide_modal()})}})},"View in new visualization":function(){var o=i+"/trackster?"+$.param(k);n.frame_manager.frame_new({title:"Trackster",type:"url",content:o});n.hide_modal()}})}});return false}},render:function(){var i=new IconButtonView({model:new IconButton({title:"Visualize",icon_class:"chart_curve",id:"btn_viz"})});this.$el.append(i.render().$el);$("#btn_viz").hide()}});var a=function(l,j,m,i){var k=new j({model:new l(m)});k.render();if(i){i.append(k.$el)}return k};var h=function(k,i){var j=$("<div/>").appendTo(i);return new f({el:j,model:new c(k)}).render()};return{Dataset:e,TabularDataset:c,DatasetCollection:g,TabularDatasetChunkedView:f,createTabularDatasetChunkedView:h}});
\ No newline at end of file
diff -r 8ea772733c979a4d5578ba4c8c31dd3f47cc32ba -r 72b02995c8b188b8efe9b3ac4c5996e972e596f1 static/scripts/packed/mvc/dataset/hda-base.js
--- a/static/scripts/packed/mvc/dataset/hda-base.js
+++ b/static/scripts/packed/mvc/dataset/hda-base.js
@@ -1,1 +1,1 @@
-var HDABaseView=Backbone.View.extend(LoggableMixin).extend({tagName:"div",className:"historyItemContainer",initialize:function(a){if(a.logger){this.logger=this.model.logger=a.logger}this.log(this+".initialize:",a);this.defaultPrimaryActionButtonRenderers=[this._render_showParamsButton];if(!a.urlTemplates){throw ("HDAView needs urlTemplates on initialize")}this.urlTemplates=a.urlTemplates;this.expanded=a.expanded||false;this.model.bind("change",function(c,d){var b=_.without(_.keys(d.changes),"display_apps","display_types");if(b.length){this.render()}else{if(this.expanded){this._render_displayApps()}}},this)},render:function(){var b=this,e=this.model.get("id"),c=this.model.get("state"),a=$("<div/>").attr("id","historyItem-"+e),d=(this.$el.children().size()===0);this.$el.attr("id","historyItemContainer-"+e);this.urls=this._renderUrls(this.urlTemplates,this.model.toJSON());a.addClass("historyItemWrapper").addClass("historyItem").addClass("historyItem-"+c);a.append(this._render_warnings());a.append(this._render_titleBar());this._setUpBehaviors(a);this.body=$(this._render_body());a.append(this.body);this.$el.fadeOut("fast",function(){b.$el.children().remove();b.$el.append(a).fadeIn("fast",function(){b.log(b+" rendered:",b.$el);var f="rendered";if(d){f+=":initial"}else{if(b.model.inReadyState()){f+=":ready"}}b.trigger(f)})});return this},_renderUrls:function(d,a){var b=this,c={};_.each(d,function(e,f){if(_.isObject(e)){c[f]=b._renderUrls(e,a)}else{if(f==="meta_download"){c[f]=b._renderMetaDownloadUrls(e,a)}else{try{c[f]=_.template(e,a)}catch(g){throw (b+"._renderUrls error: "+g+"\n rendering:"+e+"\n with "+JSON.stringify(a))}}}});return c},_renderMetaDownloadUrls:function(b,a){return _.map(a.meta_files,function(c){return{url:_.template(b,{id:a.id,file_type:c.file_type}),file_type:c.file_type}})},_setUpBehaviors:function(a){a=a||this.$el;make_popup_menus(a);a.find(".tooltip").tooltip({placement:"bottom"})},_render_warnings:function(){return $(jQuery.trim(HDABaseView.templates.messages(this.model.toJSON())))},_render_titleBar:function(){var a=$('<div class="historyItemTitleBar" style="overflow: hidden"></div>');a.append(this._render_titleButtons());a.append('<span class="state-icon"></span>');a.append(this._render_titleLink());return a},_render_titleButtons:function(){var a=$('<div class="historyItemButtons"></div>');a.append(this._render_displayButton());return a},_render_displayButton:function(){if((this.model.get("state")===HistoryDatasetAssociation.STATES.NOT_VIEWABLE)||(this.model.get("state")===HistoryDatasetAssociation.STATES.NEW)||(!this.model.get("accessible"))){this.displayButton=null;return null}var a={icon_class:"display",target:"galaxy_main"};if(this.model.get("purged")){a.enabled=false;a.title=_l("Cannot display datasets removed from disk")}else{a.title=_l("View data");a.href=this.urls.display}this.displayButton=new IconButtonView({model:new IconButton(a)});return this.displayButton.render().$el},_render_titleLink:function(){return $(jQuery.trim(HDABaseView.templates.titleLink(_.extend(this.model.toJSON(),{urls:this.urls}))))},_render_hdaSummary:function(){var a=_.extend(this.model.toJSON(),{urls:this.urls});return HDABaseView.templates.hdaSummary(a)},_render_primaryActionButtons:function(c){var a=this,b=$("<div/>").attr("id","primary-actions-"+this.model.get("id"));_.each(c,function(d){b.append(d.call(a))});return b},_render_downloadButton:function(){if(this.model.get("purged")||!this.model.hasData()){return null}var a=HDABaseView.templates.downloadLinks(_.extend(this.model.toJSON(),{urls:this.urls}));return $(a.trim())},_render_showParamsButton:function(){this.showParamsButton=new IconButtonView({model:new IconButton({title:_l("View details"),href:this.urls.show_params,target:"galaxy_main",icon_class:"information"})});return this.showParamsButton.render().$el},_render_displayAppArea:function(){return $("<div/>").addClass("display-apps")},_render_displayApps:function(c){c=c||this.$el;var d=c.find("div.display-apps"),a=this.model.get("display_types"),b=this.model.get("display_apps");if((!this.model.hasData())||(!c||!c.length)||(!d.length)){return}d.html(null);if(!_.isEmpty(a)){d.append(HDABaseView.templates.displayApps({displayApps:a}))}if(!_.isEmpty(b)){d.append(HDABaseView.templates.displayApps({displayApps:b}))}},_render_peek:function(){var a=this.model.get("peek");if(!a){return null}return $("<div/>").append($("<pre/>").attr("id","peek"+this.model.get("id")).addClass("peek").append(a))},_render_body:function(){var a=$("<div/>").attr("id","info-"+this.model.get("id")).addClass("historyItemBody").attr("style","display: none");if(this.expanded){this._render_body_html(a);a.css("display","block")}return a},_render_body_html:function(a){a.html("");switch(this.model.get("state")){case HistoryDatasetAssociation.STATES.NEW:this._render_body_new(a);break;case HistoryDatasetAssociation.STATES.NOT_VIEWABLE:this._render_body_not_viewable(a);break;case HistoryDatasetAssociation.STATES.UPLOAD:this._render_body_uploading(a);break;case HistoryDatasetAssociation.STATES.PAUSED:this._render_body_paused(a);break;case HistoryDatasetAssociation.STATES.QUEUED:this._render_body_queued(a);break;case HistoryDatasetAssociation.STATES.RUNNING:this._render_body_running(a);break;case HistoryDatasetAssociation.STATES.ERROR:this._render_body_error(a);break;case HistoryDatasetAssociation.STATES.DISCARDED:this._render_body_discarded(a);break;case HistoryDatasetAssociation.STATES.SETTING_METADATA:this._render_body_setting_metadata(a);break;case HistoryDatasetAssociation.STATES.EMPTY:this._render_body_empty(a);break;case HistoryDatasetAssociation.STATES.FAILED_METADATA:this._render_body_failed_metadata(a);break;case HistoryDatasetAssociation.STATES.OK:this._render_body_ok(a);break;default:a.append($('<div>Error: unknown dataset state "'+this.model.get("state")+'".</div>'))}a.append('<div style="clear: both"></div>');this._setUpBehaviors(a)},_render_body_new:function(b){var a=_l("This is a new dataset and not all of its data are available yet");b.append($("<div>"+_l(a)+"</div>"))},_render_body_not_viewable:function(a){a.append($("<div>"+_l("You do not have permission to view dataset")+"</div>"))},_render_body_uploading:function(a){a.append($("<div>"+_l("Dataset is uploading")+"</div>"))},_render_body_queued:function(a){a.append($("<div>"+_l("Job is waiting to run")+"</div>"));a.append(this._render_primaryActionButtons(this.defaultPrimaryActionButtonRenderers))},_render_body_paused:function(a){a.append($("<div>"+_l("Job is paused.  Use the history menu to resume")+"</div>"));a.append(this._render_primaryActionButtons(this.defaultPrimaryActionButtonRenderers))},_render_body_running:function(a){a.append("<div>"+_l("Job is currently running")+"</div>");a.append(this._render_primaryActionButtons(this.defaultPrimaryActionButtonRenderers))},_render_body_error:function(a){if(!this.model.get("purged")){a.append($("<div>"+this.model.get("misc_blurb")+"</div>"))}a.append((_l("An error occurred with this dataset")+": <i>"+$.trim(this.model.get("misc_info"))+"</i>"));a.append(this._render_primaryActionButtons(this.defaultPrimaryActionButtonRenderers.concat([this._render_downloadButton])))},_render_body_discarded:function(a){a.append("<div>"+_l("The job creating this dataset was cancelled before completion")+".</div>");a.append(this._render_primaryActionButtons(this.defaultPrimaryActionButtonRenderers))},_render_body_setting_metadata:function(a){a.append($("<div>"+_l("Metadata is being auto-detected")+".</div>"))},_render_body_empty:function(a){a.append($("<div>"+_l("No data")+": <i>"+this.model.get("misc_blurb")+"</i></div>"));a.append(this._render_primaryActionButtons(this.defaultPrimaryActionButtonRenderers))},_render_body_failed_metadata:function(a){a.append($(HDABaseView.templates.failedMetadata(_.extend(this.model.toJSON(),{urls:this.urls}))));this._render_body_ok(a)},_render_body_ok:function(a){a.append(this._render_hdaSummary());if(this.model.isDeletedOrPurged()){a.append(this._render_primaryActionButtons([this._render_downloadButton,this._render_showParamsButton]));return}a.append(this._render_primaryActionButtons([this._render_downloadButton,this._render_showParamsButton]));a.append('<div class="clear"/>');a.append(this._render_displayAppArea());this._render_displayApps(a);a.append(this._render_peek())},events:{"click .historyItemTitle":"toggleBodyVisibility"},toggleBodyVisibility:function(c,a){var b=this;this.expanded=(a===undefined)?(!this.body.is(":visible")):(a);if(this.expanded){b._render_body_html(b.body);this.body.slideDown("fast",function(){b.trigger("body-expanded",b.model.get("id"))})}else{this.body.slideUp("fast",function(){b.trigger("body-collapsed",b.model.get("id"))})}},remove:function(b){var a=this;this.$el.fadeOut("fast",function(){a.$el.remove();a.off();if(b){b()}})},toString:function(){var a=(this.model)?(this.model+""):("(no model)");return"HDABaseView("+a+")"}});HDABaseView.templates={warningMsg:Handlebars.templates["template-warningmessagesmall"],messages:Handlebars.templates["template-hda-warning-messages"],titleLink:Handlebars.templates["template-hda-titleLink"],hdaSummary:Handlebars.templates["template-hda-hdaSummary"],downloadLinks:Handlebars.templates["template-hda-downloadLinks"],failedMetadata:Handlebars.templates["template-hda-failedMetadata"],displayApps:Handlebars.templates["template-hda-displayApps"]};
\ No newline at end of file
+var HDABaseView=Backbone.View.extend(LoggableMixin).extend({tagName:"div",className:"historyItemContainer",initialize:function(a){if(a.logger){this.logger=this.model.logger=a.logger}this.log(this+".initialize:",a);this.defaultPrimaryActionButtonRenderers=[this._render_showParamsButton];if(!a.urlTemplates){throw ("HDAView needs urlTemplates on initialize")}this.urlTemplates=a.urlTemplates;this.expanded=a.expanded||false;this.model.bind("change",function(c,d){var b=_.without(_.keys(d.changes),"display_apps","display_types");if(b.length){this.render()}else{if(this.expanded){this._render_displayApps()}}},this)},render:function(){var b=this,e=this.model.get("id"),c=this.model.get("state"),a=$("<div/>").attr("id","historyItem-"+e),d=(this.$el.children().size()===0);this.$el.attr("id","historyItemContainer-"+e);this.urls=this._renderUrls(this.urlTemplates,this.model.toJSON());a.addClass("historyItemWrapper").addClass("historyItem").addClass("historyItem-"+c);a.append(this._render_warnings());a.append(this._render_titleBar());this._setUpBehaviors(a);this.body=$(this._render_body());a.append(this.body);this.$el.fadeOut("fast",function(){b.$el.children().remove();b.$el.append(a).fadeIn("fast",function(){b.log(b+" rendered:",b.$el);var f="rendered";if(d){f+=":initial"}else{if(b.model.inReadyState()){f+=":ready"}}b.trigger(f)})});return this},_renderUrls:function(d,a){var b=this,c={};_.each(d,function(e,f){if(_.isObject(e)){c[f]=b._renderUrls(e,a)}else{if(f==="meta_download"){c[f]=b._renderMetaDownloadUrls(e,a)}else{try{c[f]=_.template(e,a)}catch(g){throw (b+"._renderUrls error: "+g+"\n rendering:"+e+"\n with "+JSON.stringify(a))}}}});return c},_renderMetaDownloadUrls:function(b,a){return _.map(a.meta_files,function(c){return{url:_.template(b,{id:a.id,file_type:c.file_type}),file_type:c.file_type}})},_setUpBehaviors:function(a){a=a||this.$el;make_popup_menus(a);a.find(".tooltip").tooltip({placement:"bottom"})},_render_warnings:function(){return $(jQuery.trim(HDABaseView.templates.messages(this.model.toJSON())))},_render_titleBar:function(){var a=$('<div class="historyItemTitleBar" style="overflow: hidden"></div>');a.append(this._render_titleButtons());a.append('<span class="state-icon"></span>');a.append(this._render_titleLink());return a},_render_titleButtons:function(){var a=$('<div class="historyItemButtons"></div>');a.append(this._render_displayButton());return a},_render_displayButton:function(){if((this.model.get("state")===HistoryDatasetAssociation.STATES.NOT_VIEWABLE)||(this.model.get("state")===HistoryDatasetAssociation.STATES.NEW)||(!this.model.get("accessible"))){this.displayButton=null;return null}var a={icon_class:"display",target:"galaxy_main"};if(this.model.get("purged")){a.enabled=false;a.title=_l("Cannot display datasets removed from disk")}else{a.title=_l("View data");a.href="javascript:parent.frame_manager.frame_new({title: 'Data Viewer', type: 'url', center: true, content: '"+this.urls.display+"'});"}this.displayButton=new IconButtonView({model:new IconButton(a)});return this.displayButton.render().$el},_render_titleLink:function(){return $(jQuery.trim(HDABaseView.templates.titleLink(_.extend(this.model.toJSON(),{urls:this.urls}))))},_render_hdaSummary:function(){var a=_.extend(this.model.toJSON(),{urls:this.urls});return HDABaseView.templates.hdaSummary(a)},_render_primaryActionButtons:function(c){var a=this,b=$("<div/>").attr("id","primary-actions-"+this.model.get("id"));_.each(c,function(d){b.append(d.call(a))});return b},_render_downloadButton:function(){if(this.model.get("purged")||!this.model.hasData()){return null}var a=HDABaseView.templates.downloadLinks(_.extend(this.model.toJSON(),{urls:this.urls}));return $(a.trim())},_render_showParamsButton:function(){this.showParamsButton=new IconButtonView({model:new IconButton({title:_l("View details"),href:this.urls.show_params,target:"galaxy_main",icon_class:"information"})});return this.showParamsButton.render().$el},_render_displayAppArea:function(){return $("<div/>").addClass("display-apps")},_render_displayApps:function(c){c=c||this.$el;var d=c.find("div.display-apps"),a=this.model.get("display_types"),b=this.model.get("display_apps");if((!this.model.hasData())||(!c||!c.length)||(!d.length)){return}d.html(null);if(!_.isEmpty(a)){d.append(HDABaseView.templates.displayApps({displayApps:a}))}if(!_.isEmpty(b)){d.append(HDABaseView.templates.displayApps({displayApps:b}))}},_render_peek:function(){var a=this.model.get("peek");if(!a){return null}return $("<div/>").append($("<pre/>").attr("id","peek"+this.model.get("id")).addClass("peek").append(a))},_render_body:function(){var a=$("<div/>").attr("id","info-"+this.model.get("id")).addClass("historyItemBody").attr("style","display: none");if(this.expanded){this._render_body_html(a);a.css("display","block")}return a},_render_body_html:function(a){a.html("");switch(this.model.get("state")){case HistoryDatasetAssociation.STATES.NEW:this._render_body_new(a);break;case HistoryDatasetAssociation.STATES.NOT_VIEWABLE:this._render_body_not_viewable(a);break;case HistoryDatasetAssociation.STATES.UPLOAD:this._render_body_uploading(a);break;case HistoryDatasetAssociation.STATES.PAUSED:this._render_body_paused(a);break;case HistoryDatasetAssociation.STATES.QUEUED:this._render_body_queued(a);break;case HistoryDatasetAssociation.STATES.RUNNING:this._render_body_running(a);break;case HistoryDatasetAssociation.STATES.ERROR:this._render_body_error(a);break;case HistoryDatasetAssociation.STATES.DISCARDED:this._render_body_discarded(a);break;case HistoryDatasetAssociation.STATES.SETTING_METADATA:this._render_body_setting_metadata(a);break;case HistoryDatasetAssociation.STATES.EMPTY:this._render_body_empty(a);break;case HistoryDatasetAssociation.STATES.FAILED_METADATA:this._render_body_failed_metadata(a);break;case HistoryDatasetAssociation.STATES.OK:this._render_body_ok(a);break;default:a.append($('<div>Error: unknown dataset state "'+this.model.get("state")+'".</div>'))}a.append('<div style="clear: both"></div>');this._setUpBehaviors(a)},_render_body_new:function(b){var a=_l("This is a new dataset and not all of its data are available yet");b.append($("<div>"+_l(a)+"</div>"))},_render_body_not_viewable:function(a){a.append($("<div>"+_l("You do not have permission to view dataset")+"</div>"))},_render_body_uploading:function(a){a.append($("<div>"+_l("Dataset is uploading")+"</div>"))},_render_body_queued:function(a){a.append($("<div>"+_l("Job is waiting to run")+"</div>"));a.append(this._render_primaryActionButtons(this.defaultPrimaryActionButtonRenderers))},_render_body_paused:function(a){a.append($("<div>"+_l("Job is paused.  Use the history menu to resume")+"</div>"));a.append(this._render_primaryActionButtons(this.defaultPrimaryActionButtonRenderers))},_render_body_running:function(a){a.append("<div>"+_l("Job is currently running")+"</div>");a.append(this._render_primaryActionButtons(this.defaultPrimaryActionButtonRenderers))},_render_body_error:function(a){if(!this.model.get("purged")){a.append($("<div>"+this.model.get("misc_blurb")+"</div>"))}a.append((_l("An error occurred with this dataset")+": <i>"+$.trim(this.model.get("misc_info"))+"</i>"));a.append(this._render_primaryActionButtons(this.defaultPrimaryActionButtonRenderers.concat([this._render_downloadButton])))},_render_body_discarded:function(a){a.append("<div>"+_l("The job creating this dataset was cancelled before completion")+".</div>");a.append(this._render_primaryActionButtons(this.defaultPrimaryActionButtonRenderers))},_render_body_setting_metadata:function(a){a.append($("<div>"+_l("Metadata is being auto-detected")+".</div>"))},_render_body_empty:function(a){a.append($("<div>"+_l("No data")+": <i>"+this.model.get("misc_blurb")+"</i></div>"));a.append(this._render_primaryActionButtons(this.defaultPrimaryActionButtonRenderers))},_render_body_failed_metadata:function(a){a.append($(HDABaseView.templates.failedMetadata(_.extend(this.model.toJSON(),{urls:this.urls}))));this._render_body_ok(a)},_render_body_ok:function(a){a.append(this._render_hdaSummary());if(this.model.isDeletedOrPurged()){a.append(this._render_primaryActionButtons([this._render_downloadButton,this._render_showParamsButton]));return}a.append(this._render_primaryActionButtons([this._render_downloadButton,this._render_showParamsButton]));a.append('<div class="clear"/>');a.append(this._render_displayAppArea());this._render_displayApps(a);a.append(this._render_peek())},events:{"click .historyItemTitle":"toggleBodyVisibility"},toggleBodyVisibility:function(c,a){var b=this;this.expanded=(a===undefined)?(!this.body.is(":visible")):(a);if(this.expanded){b._render_body_html(b.body);this.body.slideDown("fast",function(){b.trigger("body-expanded",b.model.get("id"))})}else{this.body.slideUp("fast",function(){b.trigger("body-collapsed",b.model.get("id"))})}},remove:function(b){var a=this;this.$el.fadeOut("fast",function(){a.$el.remove();a.off();if(b){b()}})},toString:function(){var a=(this.model)?(this.model+""):("(no model)");return"HDABaseView("+a+")"}});HDABaseView.templates={warningMsg:Handlebars.templates["template-warningmessagesmall"],messages:Handlebars.templates["template-hda-warning-messages"],titleLink:Handlebars.templates["template-hda-titleLink"],hdaSummary:Handlebars.templates["template-hda-hdaSummary"],downloadLinks:Handlebars.templates["template-hda-downloadLinks"],failedMetadata:Handlebars.templates["template-hda-failedMetadata"],displayApps:Handlebars.templates["template-hda-displayApps"]};
\ No newline at end of file
diff -r 8ea772733c979a4d5578ba4c8c31dd3f47cc32ba -r 72b02995c8b188b8efe9b3ac4c5996e972e596f1 static/scripts/packed/mvc/dataset/hda-edit.js
--- a/static/scripts/packed/mvc/dataset/hda-edit.js
+++ b/static/scripts/packed/mvc/dataset/hda-edit.js
@@ -1,1 +1,1 @@
-var HDAEditView=HDABaseView.extend(LoggableMixin).extend({initialize:function(a){HDABaseView.prototype.initialize.call(this,a);this.defaultPrimaryActionButtonRenderers=[this._render_showParamsButton,this._render_rerunButton]},_setUpBehaviors:function(c){HDABaseView.prototype._setUpBehaviors.call(this,c);var a=this,b=this.urls.purge,d=c.find("#historyItemPurger-"+this.model.get("id"));if(d){d.attr("href",["javascript","void(0)"].join(":"));d.click(function(e){var f=jQuery.ajax(b);f.success(function(i,g,h){a.model.set("purged",true);a.trigger("purged",a)});f.error(function(h,g,i){a.trigger("error",_l("Unable to purge this dataset"),h,g,i)})})}},_render_warnings:function(){return $(jQuery.trim(HDABaseView.templates.messages(_.extend(this.model.toJSON(),{urls:this.urls}))))},_render_titleButtons:function(){var a=$('<div class="historyItemButtons"></div>');a.append(this._render_displayButton());a.append(this._render_editButton());a.append(this._render_deleteButton());return a},_render_editButton:function(){if((this.model.get("state")===HistoryDatasetAssociation.STATES.NEW)||(this.model.get("state")===HistoryDatasetAssociation.STATES.UPLOAD)||(this.model.get("state")===HistoryDatasetAssociation.STATES.NOT_VIEWABLE)||(!this.model.get("accessible"))){this.editButton=null;return null}var c=this.model.get("purged"),a=this.model.get("deleted"),b={title:_l("Edit Attributes"),href:this.urls.edit,target:"galaxy_main",icon_class:"edit"};if(a||c){b.enabled=false;if(c){b.title=_l("Cannot edit attributes of datasets removed from disk")}else{if(a){b.title=_l("Undelete dataset to edit attributes")}}}this.editButton=new IconButtonView({model:new IconButton(b)});return this.editButton.render().$el},_render_deleteButton:function(){if((this.model.get("state")===HistoryDatasetAssociation.STATES.NEW)||(this.model.get("state")===HistoryDatasetAssociation.STATES.NOT_VIEWABLE)||(!this.model.get("accessible"))){this.deleteButton=null;return null}var a=this,b=a.urls["delete"],c={title:_l("Delete"),href:b,id:"historyItemDeleter-"+this.model.get("id"),icon_class:"delete",on_click:function(){$.ajax({url:b,type:"POST",error:function(){a.$el.show()},success:function(){a.model.set({deleted:true})}})}};if(this.model.get("deleted")||this.model.get("purged")){c={title:_l("Dataset is already deleted"),icon_class:"delete",enabled:false}}this.deleteButton=new IconButtonView({model:new IconButton(c)});return this.deleteButton.render().$el},_render_hdaSummary:function(){var a=_.extend(this.model.toJSON(),{urls:this.urls});if(this.model.get("metadata_dbkey")==="?"&&!this.model.isDeletedOrPurged()){_.extend(a,{dbkey_unknown_and_editable:true})}return HDABaseView.templates.hdaSummary(a)},_render_errButton:function(){if(this.model.get("state")!==HistoryDatasetAssociation.STATES.ERROR){this.errButton=null;return null}this.errButton=new IconButtonView({model:new IconButton({title:_l("View or report this error"),href:this.urls.report_error,target:"galaxy_main",icon_class:"bug"})});return this.errButton.render().$el},_render_rerunButton:function(){this.rerunButton=new IconButtonView({model:new IconButton({title:_l("Run this job again"),href:this.urls.rerun,target:"galaxy_main",icon_class:"arrow-circle"})});return this.rerunButton.render().$el},_render_visualizationsButton:function(){var a=this.model.get("visualizations");if((!this.model.hasData())||(_.isEmpty(a))){this.visualizationsButton=null;return null}if(_.isObject(a[0])){return this._render_visualizationsFrameworkButton(a)}if(!this.urls.visualization){this.visualizationsButton=null;return null}var c=this.model.get("dbkey"),f=this.urls.visualization,d={},g={dataset_id:this.model.get("id"),hda_ldda:"hda"};if(c){g.dbkey=c}this.visualizationsButton=new IconButtonView({model:new IconButton({title:_l("Visualize"),href:this.urls.visualization,icon_class:"chart_curve"})});var b=this.visualizationsButton.render().$el;b.addClass("visualize-icon");function e(h){switch(h){case"trackster":return create_trackster_action_fn(f,g,c);case"scatterplot":return create_scatterplot_action_fn(f,g);default:return function(){window.parent.location=f+"/"+h+"?"+$.param(g)}}}if(a.length===1){b.attr("title",a[0]);b.click(e(a[0]))}else{_.each(a,function(i){var h=i.charAt(0).toUpperCase()+i.slice(1);d[_l(h)]=e(i)});make_popupmenu(b,d)}return b},_render_visualizationsFrameworkButton:function(a){if(!(this.model.hasData())||!(a&&!_.isEmpty(a))){this.visualizationsButton=null;return null}this.visualizationsButton=new IconButtonView({model:new IconButton({title:_l("Visualize"),icon_class:"chart_curve"})});var c=this.visualizationsButton.render().$el;c.addClass("visualize-icon");if(_.keys(a).length===1){c.attr("title",_.keys(a)[0]);c.attr("href",_.values(a)[0])}else{var d=[];_.each(a,function(e){d.push(e)});var b=new PopupMenu(c,d)}return c},_render_secondaryActionButtons:function(b){var c=$("<div/>"),a=this;c.attr("style","float: right;").attr("id","secondary-actions-"+this.model.get("id"));_.each(b,function(d){c.append(d.call(a))});return c},_render_tagButton:function(){if(!(this.model.hasData())||(!this.urls.tags.get)){this.tagButton=null;return null}this.tagButton=new IconButtonView({model:new IconButton({title:_l("Edit dataset tags"),target:"galaxy_main",href:this.urls.tags.get,icon_class:"tags"})});return this.tagButton.render().$el},_render_annotateButton:function(){if(!(this.model.hasData())||(!this.urls.annotation.get)){this.annotateButton=null;return null}this.annotateButton=new IconButtonView({model:new IconButton({title:_l("Edit dataset annotation"),target:"galaxy_main",icon_class:"annotate"})});return this.annotateButton.render().$el},_render_tagArea:function(){if(!this.urls.tags.set){return null}return $(HDAEditView.templates.tagArea(_.extend(this.model.toJSON(),{urls:this.urls})).trim())},_render_annotationArea:function(){if(!this.urls.annotation.get){return null}return $(HDAEditView.templates.annotationArea(_.extend(this.model.toJSON(),{urls:this.urls})).trim())},_render_body_error:function(a){HDABaseView.prototype._render_body_error.call(this,a);var b=a.find("#primary-actions-"+this.model.get("id"));b.prepend(this._render_errButton())},_render_body_ok:function(a){a.append(this._render_hdaSummary());if(this.model.isDeletedOrPurged()){a.append(this._render_primaryActionButtons([this._render_downloadButton,this._render_showParamsButton,this._render_rerunButton]));return}a.append(this._render_primaryActionButtons([this._render_downloadButton,this._render_showParamsButton,this._render_rerunButton,this._render_visualizationsButton]));a.append(this._render_secondaryActionButtons([this._render_tagButton,this._render_annotateButton]));a.append('<div class="clear"/>');a.append(this._render_tagArea());a.append(this._render_annotationArea());a.append(this._render_displayAppArea());this._render_displayApps(a);a.append(this._render_peek())},events:{"click .historyItemTitle":"toggleBodyVisibility","click a.icon-button.tags":"loadAndDisplayTags","click a.icon-button.annotate":"loadAndDisplayAnnotation"},loadAndDisplayTags:function(c){this.log(this+".loadAndDisplayTags",c);var a=this,d=this.$el.find(".tag-area"),b=d.find(".tag-elt");if(d.is(":hidden")){if(!jQuery.trim(b.html())){$.ajax({url:this.urls.tags.get,error:function(g,e,f){a.log("Tagging failed",g,e,f);a.trigger("error",_l("Tagging failed"),g,e,f)},success:function(e){b.html(e);b.find(".tooltip").tooltip();d.slideDown("fast")}})}else{d.slideDown("fast")}}else{d.slideUp("fast")}return false},loadAndDisplayAnnotation:function(b){this.log(this+".loadAndDisplayAnnotation",b);var d=this.$el.find(".annotation-area"),c=d.find(".annotation-elt"),a=this.urls.annotation.set;if(d.is(":hidden")){if(!jQuery.trim(c.html())){$.ajax({url:this.urls.annotation.get,error:function(){view.log("Annotation failed",xhr,status,error);view.trigger("error",_l("Annotation failed"),xhr,status,error)},success:function(e){if(e===""){e="<em>"+_l("Describe or add notes to dataset")+"</em>"}c.html(e);d.find(".tooltip").tooltip();async_save_text(c.attr("id"),c.attr("id"),a,"new_annotation",18,true,4);d.slideDown("fast")}})}else{d.slideDown("fast")}}else{d.slideUp("fast")}return false},toString:function(){var a=(this.model)?(this.model+""):("(no model)");return"HDAView("+a+")"}});HDAEditView.templates={tagArea:Handlebars.templates["template-hda-tagArea"],annotationArea:Handlebars.templates["template-hda-annotationArea"]};function create_scatterplot_action_fn(a,b){action=function(){var d=$(window.parent.document).find("iframe#galaxy_main"),c=a+"/scatterplot?"+$.param(b);d.attr("src",c);$("div.popmenu-wrapper").remove();return false};return action}function create_trackster_action_fn(a,c,b){return function(){var d={};if(b){d["f-dbkey"]=b}$.ajax({url:a+"/list_tracks?"+$.param(d),dataType:"html",error:function(){alert(_l("Could not add this dataset to browser")+".")},success:function(e){var f=window.parent;f.show_modal(_l("View Data in a New or Saved Visualization"),"",{Cancel:function(){f.hide_modal()},"View in saved visualization":function(){f.show_modal(_l("Add Data to Saved Visualization"),e,{Cancel:function(){f.hide_modal()},"Add to visualization":function(){$(f.document).find("input[name=id]:checked").each(function(){var g=$(this).val();c.id=g;f.location=a+"/trackster?"+$.param(c)})}})},"View in new visualization":function(){f.location=a+"/trackster?"+$.param(c)}})}});return false}};
\ No newline at end of file
+var HDAEditView=HDABaseView.extend(LoggableMixin).extend({initialize:function(a){HDABaseView.prototype.initialize.call(this,a);this.defaultPrimaryActionButtonRenderers=[this._render_showParamsButton,this._render_rerunButton]},_setUpBehaviors:function(c){HDABaseView.prototype._setUpBehaviors.call(this,c);var a=this,b=this.urls.purge,d=c.find("#historyItemPurger-"+this.model.get("id"));if(d){d.attr("href",["javascript","void(0)"].join(":"));d.click(function(e){var f=jQuery.ajax(b);f.success(function(i,g,h){a.model.set("purged",true);a.trigger("purged",a)});f.error(function(h,g,i){a.trigger("error",_l("Unable to purge this dataset"),h,g,i)})})}},_render_warnings:function(){return $(jQuery.trim(HDABaseView.templates.messages(_.extend(this.model.toJSON(),{urls:this.urls}))))},_render_titleButtons:function(){var a=$('<div class="historyItemButtons"></div>');a.append(this._render_displayButton());a.append(this._render_editButton());a.append(this._render_deleteButton());return a},_render_editButton:function(){if((this.model.get("state")===HistoryDatasetAssociation.STATES.NEW)||(this.model.get("state")===HistoryDatasetAssociation.STATES.UPLOAD)||(this.model.get("state")===HistoryDatasetAssociation.STATES.NOT_VIEWABLE)||(!this.model.get("accessible"))){this.editButton=null;return null}var c=this.model.get("purged"),a=this.model.get("deleted"),b={title:_l("Edit Attributes"),href:this.urls.edit,target:"galaxy_main",icon_class:"edit"};if(a||c){b.enabled=false;if(c){b.title=_l("Cannot edit attributes of datasets removed from disk")}else{if(a){b.title=_l("Undelete dataset to edit attributes")}}}this.editButton=new IconButtonView({model:new IconButton(b)});return this.editButton.render().$el},_render_deleteButton:function(){if((this.model.get("state")===HistoryDatasetAssociation.STATES.NEW)||(this.model.get("state")===HistoryDatasetAssociation.STATES.NOT_VIEWABLE)||(!this.model.get("accessible"))){this.deleteButton=null;return null}var a=this,b=a.urls["delete"],c={title:_l("Delete"),href:b,id:"historyItemDeleter-"+this.model.get("id"),icon_class:"delete",on_click:function(){$.ajax({url:b,type:"POST",error:function(){a.$el.show()},success:function(){a.model.set({deleted:true})}})}};if(this.model.get("deleted")||this.model.get("purged")){c={title:_l("Dataset is already deleted"),icon_class:"delete",enabled:false}}this.deleteButton=new IconButtonView({model:new IconButton(c)});return this.deleteButton.render().$el},_render_hdaSummary:function(){var a=_.extend(this.model.toJSON(),{urls:this.urls});if(this.model.get("metadata_dbkey")==="?"&&!this.model.isDeletedOrPurged()){_.extend(a,{dbkey_unknown_and_editable:true})}return HDABaseView.templates.hdaSummary(a)},_render_errButton:function(){if(this.model.get("state")!==HistoryDatasetAssociation.STATES.ERROR){this.errButton=null;return null}this.errButton=new IconButtonView({model:new IconButton({title:_l("View or report this error"),href:this.urls.report_error,target:"galaxy_main",icon_class:"bug"})});return this.errButton.render().$el},_render_rerunButton:function(){this.rerunButton=new IconButtonView({model:new IconButton({title:_l("Run this job again"),href:this.urls.rerun,target:"galaxy_main",icon_class:"arrow-circle"})});return this.rerunButton.render().$el},_render_visualizationsButton:function(){var a=this.model.get("visualizations");if((!this.model.hasData())||(_.isEmpty(a))){this.visualizationsButton=null;return null}if(_.isObject(a[0])){return this._render_visualizationsFrameworkButton(a)}if(!this.urls.visualization){this.visualizationsButton=null;return null}var c=this.model.get("dbkey"),f=this.urls.visualization,d={},g={dataset_id:this.model.get("id"),hda_ldda:"hda"};if(c){g.dbkey=c}this.visualizationsButton=new IconButtonView({model:new IconButton({title:_l("Visualize"),href:this.urls.visualization,icon_class:"chart_curve"})});var b=this.visualizationsButton.render().$el;b.addClass("visualize-icon");function e(h){switch(h){case"trackster":return create_trackster_action_fn(f,g,c);case"scatterplot":return create_scatterplot_action_fn(f,g);default:return function(){parent.frame_manager.frame_new({title:"Visualization",type:"url",content:f+"/"+h+"?"+$.param(g)})}}}if(a.length===1){b.attr("title",a[0]);b.click(e(a[0]))}else{_.each(a,function(i){var h=i.charAt(0).toUpperCase()+i.slice(1);d[_l(h)]=e(i)});make_popupmenu(b,d)}return b},_render_visualizationsFrameworkButton:function(a){if(!(this.model.hasData())||!(a&&!_.isEmpty(a))){this.visualizationsButton=null;return null}this.visualizationsButton=new IconButtonView({model:new IconButton({title:_l("Visualize"),icon_class:"chart_curve"})});var c=this.visualizationsButton.render().$el;c.addClass("visualize-icon");if(_.keys(a).length===1){c.attr("title",_.keys(a)[0]);c.attr("href",_.values(a)[0])}else{var d=[];_.each(a,function(e){d.push(e)});var b=new PopupMenu(c,d)}return c},_render_secondaryActionButtons:function(b){var c=$("<div/>"),a=this;c.attr("style","float: right;").attr("id","secondary-actions-"+this.model.get("id"));_.each(b,function(d){c.append(d.call(a))});return c},_render_tagButton:function(){if(!(this.model.hasData())||(!this.urls.tags.get)){this.tagButton=null;return null}this.tagButton=new IconButtonView({model:new IconButton({title:_l("Edit dataset tags"),target:"galaxy_main",href:this.urls.tags.get,icon_class:"tags"})});return this.tagButton.render().$el},_render_annotateButton:function(){if(!(this.model.hasData())||(!this.urls.annotation.get)){this.annotateButton=null;return null}this.annotateButton=new IconButtonView({model:new IconButton({title:_l("Edit dataset annotation"),target:"galaxy_main",icon_class:"annotate"})});return this.annotateButton.render().$el},_render_tagArea:function(){if(!this.urls.tags.set){return null}return $(HDAEditView.templates.tagArea(_.extend(this.model.toJSON(),{urls:this.urls})).trim())},_render_annotationArea:function(){if(!this.urls.annotation.get){return null}return $(HDAEditView.templates.annotationArea(_.extend(this.model.toJSON(),{urls:this.urls})).trim())},_render_body_error:function(a){HDABaseView.prototype._render_body_error.call(this,a);var b=a.find("#primary-actions-"+this.model.get("id"));b.prepend(this._render_errButton())},_render_body_ok:function(a){a.append(this._render_hdaSummary());if(this.model.isDeletedOrPurged()){a.append(this._render_primaryActionButtons([this._render_downloadButton,this._render_showParamsButton,this._render_rerunButton]));return}a.append(this._render_primaryActionButtons([this._render_downloadButton,this._render_showParamsButton,this._render_rerunButton,this._render_visualizationsButton]));a.append(this._render_secondaryActionButtons([this._render_tagButton,this._render_annotateButton]));a.append('<div class="clear"/>');a.append(this._render_tagArea());a.append(this._render_annotationArea());a.append(this._render_displayAppArea());this._render_displayApps(a);a.append(this._render_peek())},events:{"click .historyItemTitle":"toggleBodyVisibility","click a.icon-button.tags":"loadAndDisplayTags","click a.icon-button.annotate":"loadAndDisplayAnnotation"},loadAndDisplayTags:function(c){this.log(this+".loadAndDisplayTags",c);var a=this,d=this.$el.find(".tag-area"),b=d.find(".tag-elt");if(d.is(":hidden")){if(!jQuery.trim(b.html())){$.ajax({url:this.urls.tags.get,error:function(g,e,f){a.log("Tagging failed",g,e,f);a.trigger("error",_l("Tagging failed"),g,e,f)},success:function(e){b.html(e);b.find(".tooltip").tooltip();d.slideDown("fast")}})}else{d.slideDown("fast")}}else{d.slideUp("fast")}return false},loadAndDisplayAnnotation:function(b){this.log(this+".loadAndDisplayAnnotation",b);var d=this.$el.find(".annotation-area"),c=d.find(".annotation-elt"),a=this.urls.annotation.set;if(d.is(":hidden")){if(!jQuery.trim(c.html())){$.ajax({url:this.urls.annotation.get,error:function(){view.log("Annotation failed",xhr,status,error);view.trigger("error",_l("Annotation failed"),xhr,status,error)},success:function(e){if(e===""){e="<em>"+_l("Describe or add notes to dataset")+"</em>"}c.html(e);d.find(".tooltip").tooltip();async_save_text(c.attr("id"),c.attr("id"),a,"new_annotation",18,true,4);d.slideDown("fast")}})}else{d.slideDown("fast")}}else{d.slideUp("fast")}return false},toString:function(){var a=(this.model)?(this.model+""):("(no model)");return"HDAView("+a+")"}});HDAEditView.templates={tagArea:Handlebars.templates["template-hda-tagArea"],annotationArea:Handlebars.templates["template-hda-annotationArea"]};function create_scatterplot_action_fn(a,b){action=function(){parent.frame_manager.frame_new({title:"Scatterplot",type:"url",content:a+"/scatterplot?"+$.param(b),center:true});$("div.popmenu-wrapper").remove();return false};return action}function create_trackster_action_fn(a,c,b){return function(){var d={};if(b){d["f-dbkey"]=b}$.ajax({url:a+"/list_tracks?"+$.param(d),dataType:"html",error:function(){alert(_l("Could not add this dataset to browser")+".")},success:function(e){var f=window.parent;f.show_modal(_l("View Data in a New or Saved Visualization"),"",{Cancel:function(){f.hide_modal()},"View in saved visualization":function(){f.show_modal(_l("Add Data to Saved Visualization"),e,{Cancel:function(){f.hide_modal()},"Add to visualization":function(){$(f.document).find("input[name=id]:checked").each(function(){var g=$(this).val();c.id=g;f.hide_modal();f.frame_manager.frame_new({title:"Trackster",type:"url",content:a+"/trackster?"+$.param(c)})})}})},"View in new visualization":function(){f.hide_modal();f.frame_manager.frame_new({title:"Trackster",type:"url",content:a+"/trackster?"+$.param(c)})}})}});return false}};
\ No newline at end of file
diff -r 8ea772733c979a4d5578ba4c8c31dd3f47cc32ba -r 72b02995c8b188b8efe9b3ac4c5996e972e596f1 static/scripts/packed/mvc/visualizations/scatterplotControlForm.js
--- a/static/scripts/packed/mvc/visualizations/scatterplotControlForm.js
+++ b/static/scripts/packed/mvc/visualizations/scatterplotControlForm.js
@@ -1,1 +1,1 @@
-var ScatterplotControlForm=BaseView.extend(LoggableMixin).extend({className:"scatterplot-control-form",dataLoadDelay:4000,dataLoadSize:5000,loadingIndicatorImage:"loading_small_white_bg.gif",fetchMsg:"Fetching data...",renderMsg:"Rendering...",initialize:function(a){this.log(this+".initialize, attributes:",a);this.dataset=null;this.chartConfig=null;this.chart=null;this.loader=null;this.$dataControl=null;this.$chartControl=null;this.$statsDisplay=null;this.$chartDisplay=null;this.dataFetch=null;this.initializeFromAttributes(a);this.initializeChart(a);this.initializeDataLoader(a)},initializeFromAttributes:function(a){if(!a||!a.dataset){throw ("ScatterplotView requires a dataset")}else{this.dataset=a.dataset}if(jQuery.type(this.dataset.metadata_column_types)==="string"){this.dataset.metadata_column_types=this.dataset.metadata_column_types.split(", ")}this.log("\t dataset:",this.dataset);if(this.dataset.comment_lines&&this.dataset.comment_lines.length){var b=this.dataset.comment_lines[0],c=b.split("\t");if(c.length===this.dataset.metadata_column_types.length){this.possibleHeaders=c}}if(!a.apiDatasetsURL){throw ("ScatterplotView requires a apiDatasetsURL")}else{this.dataURL=a.apiDatasetsURL+"/"+this.dataset.id+"?"}this.log("\t dataURL:",this.dataURL)},initializeChart:function(a){this.chartConfig=a.chartConfig||{};this.log("\t initial chartConfig:",this.chartConfig);this.chart=new TwoVarScatterplot(this.chartConfig);this.chartConfig=this.chart.config},initializeDataLoader:function(b){var a=this;this.loader=new LazyDataLoader({url:null,start:b.start||0,total:b.total||this.dataset.metadata_data_lines,delay:this.dataLoadDelay,size:this.dataLoadSize,buildUrl:function(d,c){return this.url+"&"+jQuery.param({start_val:d,max_vals:c})}});$(this.loader).bind("error",function(e,c,d){a.log("ERROR:",c,d);alert("ERROR fetching data:\n"+c+"\n"+d);a.hideLoadingIndicator()})},render:function(){this.log(this+".render");this.$el.append(ScatterplotControlForm.templates.mainLayout({loadingIndicatorImagePath:galaxy_paths.get("image_path")+"/"+this.loadingIndicatorImage,message:""}));this.$dataControl=this._render_dataControl();this.$chartControl=this._render_chartControl();this.$statsDisplay=this.$el.find(".tab-pane#stats-display");this.$chartDisplay=this._render_chartDisplay();if(this.chartConfig.xColumn&&this.chartConfig.yColumn){this.renderChart()}this.$el.find(".tooltip").tooltip();return this},_render_dataControl:function(){var b=this,a=[],e=[],c=(this.possibleHeaders&&this.$dataControl)?(this.$dataControl.find("#first-line-header-checkbox").is(":checked")):(false);_.each(this.dataset.metadata_column_types,function(i,g){var h=g+1,f="column "+h;if(b.dataset.metadata_column_names){f=b.dataset.metadata_column_names[g]}else{if(c){f=b.possibleHeaders[g]}}a.push({index:h,name:f});if(i==="int"||i==="float"){e.push({index:h,name:f})}});var d=this.$el.find(".tab-pane#data-control");d.html(ScatterplotControlForm.templates.dataControl({allColumns:a,numericColumns:e,possibleHeaders:(this.possibleHeaders)?(this.possibleHeaders.join(", ")):(""),usePossibleHeaders:c}));if(!this.dataset.metadata_column_names&&this.possibleHeaders){d.find("#first-line-header").show()}d.find("#X-select").val(this.chartConfig.xColumn);d.find("#Y-select").val(this.chartConfig.yColumn);if(this.chartConfig.idColumn!==undefined){d.find("#include-id-checkbox").attr("checked",true).trigger("change");d.find("#ID-select").val(this.chartConfig.idColumn)}return d},_render_chartControl:function(){var a=this,b=this.$el.find(".tab-pane#chart-control"),c={datapointSize:{min:2,max:10,step:1},width:{min:200,max:800,step:20},height:{min:200,max:800,step:20}};b.append(ScatterplotControlForm.templates.chartControl(this.chartConfig));b.find(".numeric-slider-input").each(function(){var f=$(this),e=f.find(".slider-output"),g=f.find(".slider"),h=f.attr("id");function d(){var j=$(this),i=j.slider("value");e.text(i)}g.slider(_.extend(c[h],{value:a.chartConfig[h],change:d,slide:d}))});return b},_render_chartDisplay:function(){var a=this.$el.find(".tab-pane#chart-display");a.append(ScatterplotControlForm.templates.chartDisplay(this.chartConfig));return a},events:{"change #include-id-checkbox":"toggleThirdColumnSelector","change #first-line-header-checkbox":"rerenderDataControl","click #data-control #render-button":"renderChart","click #chart-control #render-button":"changeChartSettings"},toggleThirdColumnSelector:function(){this.$el.find('select[name="ID"]').parent().toggle()},rerenderDataControl:function(){this.$dataControl=this._render_dataControl()},showLoadingIndicator:function(b,c){b=b||"";var a=this.$el.find("div#loading-indicator");messageBox=a.find(".loading-message");if(a.is(":visible")){if(b){messageBox.fadeOut("fast",function(){messageBox.text(b);messageBox.fadeIn("fast",c)})}else{c()}}else{if(b){messageBox.text(b)}a.fadeIn("fast",c)}},hideLoadingIndicator:function(a){this.$el.find("div#loading-indicator").fadeOut("fast",a)},renderChart:function(){this.log(this+".renderChart");this.data=null;this.meta=null;_.extend(this.chartConfig,this.getChartSettings());this.log("\t chartConfig:",this.chartConfig);this.chart.updateConfig(this.chartConfig,false);this.loader.url=this.dataURL+"&"+jQuery.param(this.getDataSettings());this.log("\t loader: total lines:",this.loader.total," url:",this.loader.url);var a=this;$(this.loader).bind("loaded.new",function(c,b){a.log(a+" loaded.new",b);a.postProcessDataFetchResponse(b);a.log("\t postprocessed data:",a.data);a.log("\t postprocessed meta:",a.meta);a.showLoadingIndicator(a.renderMsg,function(){a.chart.render(a.data,a.meta);a.renderStats(a.data,a.meta);a.hideLoadingIndicator()})});$(this.loader).bind("complete",function(b,c){a.log(a+" complete",c);$(a.loader).unbind()});a.showLoadingIndicator(a.fetchMsg,function(){a.$el.find("ul.nav").find('a[href="#chart-display"]').tab("show");a.loader.load()})},renderStats:function(){this.log(this+".renderStats");this.$statsDisplay.html(ScatterplotControlForm.templates.statsDisplay({stats:[{name:"Count",xval:this.meta[0].count,yval:this.meta[1].count},{name:"Min",xval:this.meta[0].min,yval:this.meta[1].min},{name:"Max",xval:this.meta[0].max,yval:this.meta[1].max},{name:"Sum",xval:this.meta[0].sum,yval:this.meta[1].sum},{name:"Mean",xval:this.meta[0].mean,yval:this.meta[1].mean},{name:"Median",xval:this.meta[0].median,yval:this.meta[1].median}]}))},changeChartSettings:function(){var a=this;newChartSettings=this.getChartSettings();_.extend(this.chartConfig,newChartSettings);this.log("this.chartConfig:",this.chartConfig);this.chart.updateConfig(this.chartConfig,false);if(a.data&&a.meta){a.showLoadingIndicator(a.renderMsg,function(){a.$el.find("ul.nav").find('a[href="#chart-display"]').tab("show");a.chart.render(a.data,a.meta);a.hideLoadingIndicator()})}else{this.renderChart()}},postProcessDataFetchResponse:function(a){this.postProcessData(a.data);this.postProcessMeta(a.meta)},postProcessData:function(b){var a=this;if(a.data){_.each(b,function(d,c){a.data[c]=a.data[c].concat(d)})}else{a.data=b}},postProcessMeta:function(c){var a=this,b=this.dataset.metadata_column_types;if(a.meta){_.each(c,function(e,d){var i=a.meta[d],g=b[d];i.count+=(e.count)?(e.count):(0);if((g==="int")||(g==="float")){i.min=Math.min(e.min,i.min);i.max=Math.max(e.max,i.max);i.sum=e.sum+i.sum;i.mean=(i.count)?(i.sum/i.count):(null);var f=a.data[d].slice().sort(),h=Math.floor(f.length/2);if(f.length%2===0){i.median=((f[h]+f[(h+1)])/2)}else{i.median=f[h]}}})}else{a.meta=c}},getDataSettings:function(){var b=this.getColumnSelections(),a=[];this.log("\t columnSelections:",b);a=[b.X.colIndex-1,b.Y.colIndex-1];if(this.$dataControl.find("#include-id-checkbox").attr("checked")){a.push(b.ID.colIndex-1)}var c={data_type:"raw_data",provider:"column",columns:"["+a+"]"};this.log("\t data settings (url params):",c);return c},getColumnSelections:function(){var a={};this.$dataControl.find("div.column-select select").each(function(){var b=$(this),c=b.val();a[b.attr("name")]={colIndex:c,colName:b.children('[value="'+c+'"]').text()}});return a},getChartSettings:function(){var c={},d=this.getColumnSelections();c.datapointSize=this.$chartControl.find("#datapointSize.numeric-slider-input").find(".slider").slider("value");c.width=this.$chartControl.find("#width.numeric-slider-input").find(".slider").slider("value");c.height=this.$chartControl.find("#height.numeric-slider-input").find(".slider").slider("value");var b=this.$chartControl.find("input#X-axis-label").val(),a=this.$chartControl.find("input#Y-axis-label").val();c.xLabel=(b==="X")?(d.X.colName):(b);c.yLabel=(a==="Y")?(d.Y.colName):(a);c.animDuration=(this.$chartControl.find("#animate-chart").is(":checked"))?(this.chart.defaults.animDuration):(0);this.log("\t chartSettings:",c);return c},toString:function(){return"ScatterplotControlForm("+((this.dataset)?(this.dataset.id):(""))+")"}});ScatterplotControlForm.templates={mainLayout:Handlebars.templates["template-visualization-scatterplotControlForm"],dataControl:Handlebars.templates["template-visualization-dataControl"],chartControl:Handlebars.templates["template-visualization-chartControl"],statsDisplay:Handlebars.templates["template-visualization-statsDisplay"],chartDisplay:Handlebars.templates["template-visualization-chartDisplay"]};
\ No newline at end of file
+var ScatterplotControlForm=BaseView.extend(LoggableMixin).extend({className:"scatterplot-control-form",dataLoadDelay:4000,dataLoadSize:5000,loadingIndicatorImage:"loading_small_white_bg.gif",fetchMsg:"Fetching data...",renderMsg:"Rendering...",initialize:function(a){this.log(this+".initialize, attributes:",a);this.dataset=null;this.chartConfig=null;this.chart=null;this.loader=null;this.$dataControl=null;this.$chartControl=null;this.$statsDisplay=null;this.$chartDisplay=null;this.dataFetch=null;this.initializeFromAttributes(a);this.initializeChart(a);this.initializeDataLoader(a)},initializeFromAttributes:function(a){if(!a||!a.dataset){throw ("ScatterplotView requires a dataset")}else{this.dataset=a.dataset}if(jQuery.type(this.dataset.metadata_column_types)==="string"){this.dataset.metadata_column_types=this.dataset.metadata_column_types.split(", ")}this.log("\t dataset:",this.dataset);if(this.dataset.comment_lines&&this.dataset.comment_lines.length){var b=this.dataset.comment_lines[0],c=b.split("\t");if(c.length===this.dataset.metadata_column_types.length){this.possibleHeaders=c}}if(!a.apiDatasetsURL){throw ("ScatterplotView requires a apiDatasetsURL")}else{this.dataURL=a.apiDatasetsURL+"/"+this.dataset.id+"?"}this.log("\t dataURL:",this.dataURL)},initializeChart:function(a){this.chartConfig=a.chartConfig||{};this.log("\t initial chartConfig:",this.chartConfig);this.chart=new TwoVarScatterplot(this.chartConfig);this.chartConfig=this.chart.config},initializeDataLoader:function(b){var a=this;this.loader=new LazyDataLoader({url:null,start:b.start||0,total:b.total||this.dataset.metadata_data_lines,delay:this.dataLoadDelay,size:this.dataLoadSize,buildUrl:function(d,c){return this.url+"&"+jQuery.param({start_val:d,max_vals:c})}});$(this.loader).bind("error",function(e,c,d){a.log("ERROR:",c,d);alert("ERROR fetching data:\n"+c+"\n"+d);a.hideLoadingIndicator()})},render:function(){this.log(this+".render");this.$el.append(ScatterplotControlForm.templates.mainLayout({loadingIndicatorImagePath:galaxy_paths.get("image_path")+"/"+this.loadingIndicatorImage,message:""}));this.$dataControl=this._render_dataControl();this.$chartControl=this._render_chartControl();this.$statsDisplay=this.$el.find(".tab-pane#stats-display");this.$chartDisplay=this._render_chartDisplay();if(this.chartConfig.xColumn&&this.chartConfig.yColumn){this.renderChart()}this.$el.find(".tooltip").tooltip();return this},_render_dataControl:function(){var b=this,a=[],e=[],c=(this.possibleHeaders&&this.$dataControl)?(this.$dataControl.find("#first-line-header-checkbox").is(":checked")):(false);_.each(this.dataset.metadata_column_types,function(i,g){var h=g+1,f="column "+h;if(b.dataset.metadata_column_names){f=b.dataset.metadata_column_names[g]}else{if(c){f=b.possibleHeaders[g]}}a.push({index:h,name:f});if(i==="int"||i==="float"){e.push({index:h,name:f})}});var d=this.$el.find(".tab-pane#data-control");d.html(ScatterplotControlForm.templates.dataControl({allColumns:a,numericColumns:e,possibleHeaders:(this.possibleHeaders)?(this.possibleHeaders.join(", ")):(""),usePossibleHeaders:c}));if(!this.dataset.metadata_column_names&&this.possibleHeaders){d.find("#first-line-header").show()}d.find("#X-select").val(this.chartConfig.xColumn);d.find("#Y-select").val(this.chartConfig.yColumn);if(this.chartConfig.idColumn!==undefined){d.find("#include-id-checkbox").attr("checked",true).trigger("change");d.find("#ID-select").val(this.chartConfig.idColumn)}return d},_render_chartControl:function(){var a=this,b=this.$el.find(".tab-pane#chart-control"),c={datapointSize:{min:2,max:10,step:1},width:{min:200,max:800,step:20},height:{min:200,max:800,step:20}};b.append(ScatterplotControlForm.templates.chartControl(this.chartConfig));b.find(".numeric-slider-input").each(function(){var f=$(this),e=f.find(".slider-output"),g=f.find(".slider"),h=f.attr("id");function d(){var j=$(this),i=j.slider("value");e.text(i)}g.slider(_.extend(c[h],{value:a.chartConfig[h],change:d,slide:d}))});return b},_render_chartDisplay:function(){var a=this.$el.find(".tab-pane#chart-display");a.append(ScatterplotControlForm.templates.chartDisplay(this.chartConfig));return a},events:{"change #include-id-checkbox":"toggleThirdColumnSelector","change #first-line-header-checkbox":"rerenderDataControl","click #data-control #render-button":"renderChart","click #chart-control #render-button":"changeChartSettings"},toggleThirdColumnSelector:function(){this.$el.find('select[name="ID"]').parent().toggle()},rerenderDataControl:function(){this.$dataControl=this._render_dataControl()},showLoadingIndicator:function(b,c){b=b||"";var a=this.$el.find("div#loading-indicator");messageBox=a.find(".loading-message");if(a.is(":visible")){if(b){messageBox.fadeOut("fast",function(){messageBox.text(b);messageBox.fadeIn("fast",c)})}else{c()}}else{if(b){messageBox.text(b)}a.fadeIn("fast",c)}},hideLoadingIndicator:function(a){this.$el.find("div#loading-indicator").fadeOut("fast",a)},renderChart:function(){this.log(this+".renderChart");this.data=null;this.meta=null;_.extend(this.chartConfig,this.getChartSettings());this.log("\t chartConfig:",this.chartConfig);this.chart.updateConfig(this.chartConfig,false);this.loader.url=this.dataURL+"&"+jQuery.param(this.getDataSettings());this.log("\t loader: total lines:",this.loader.total," url:",this.loader.url);var a=this;$(this.loader).bind("loaded.new",function(c,b){a.log(a+" loaded.new",b);a.postProcessDataFetchResponse(b);a.log("\t postprocessed data:",a.data);a.log("\t postprocessed meta:",a.meta);a.showLoadingIndicator(a.renderMsg,function(){a.chart.render(a.data,a.meta);a.renderStats(a.data,a.meta);a.hideLoadingIndicator()})});$(this.loader).bind("complete",function(b,c){a.log(a+" complete",c);$(a.loader).unbind()});a.showLoadingIndicator(a.fetchMsg,function(){a.$el.find("ul.nav").find('a[href="#chart-display"]').tab("show");a.loader.load()})},renderStats:function(){this.log(this+".renderStats");this.$statsDisplay.html(ScatterplotControlForm.templates.statsDisplay({stats:[{name:"Count",xval:this.meta[0].count,yval:this.meta[1].count},{name:"Min",xval:this.meta[0].min,yval:this.meta[1].min},{name:"Max",xval:this.meta[0].max,yval:this.meta[1].max},{name:"Sum",xval:this.meta[0].sum,yval:this.meta[1].sum},{name:"Mean",xval:this.meta[0].mean,yval:this.meta[1].mean},{name:"Median",xval:this.meta[0].median,yval:this.meta[1].median}]}))},changeChartSettings:function(){var a=this;newChartSettings=this.getChartSettings();_.extend(this.chartConfig,newChartSettings);this.log("this.chartConfig:",this.chartConfig);this.chart.updateConfig(this.chartConfig,false);if(a.data&&a.meta){a.showLoadingIndicator(a.renderMsg,function(){a.$el.find("ul.nav").find('a[href="#chart-display"]').tab("show");a.chart.render(a.data,a.meta);a.hideLoadingIndicator()})}else{this.renderChart()}},postProcessDataFetchResponse:function(a){this.postProcessData(a.data);this.postProcessMeta(a.meta)},postProcessData:function(b){var a=this;if(a.data){_.each(b,function(d,c){a.data[c]=a.data[c].concat(d)})}else{a.data=b}},postProcessMeta:function(c){var a=this,b=this.dataset.metadata_column_types;if(a.meta){_.each(c,function(e,d){var i=a.meta[d],g=b[d];i.count+=(e.count)?(e.count):(0);if((g==="int")||(g==="float")){i.min=Math.min(e.min,i.min);i.max=Math.max(e.max,i.max);i.sum=e.sum+i.sum;i.mean=(i.count)?(i.sum/i.count):(null);var f=a.data[d].slice().sort(),h=Math.floor(f.length/2);if(f.length%2===0){i.median=((f[h]+f[(h+1)])/2)}else{i.median=f[h]}}})}else{a.meta=c}},getDataSettings:function(){var b=this.getColumnSelections(),a=[];this.log("\t columnSelections:",b);a=[b.X.colIndex-1,b.Y.colIndex-1];if(this.$dataControl.find("#include-id-checkbox").attr("checked")){a.push(b.ID.colIndex-1)}var c={data_type:"raw_data",provider:"column_with_stats",columns:"["+a+"]"};this.log("\t data settings (url params):",c);return c},getColumnSelections:function(){var a={};this.$dataControl.find("div.column-select select").each(function(){var b=$(this),c=b.val();a[b.attr("name")]={colIndex:c,colName:b.children('[value="'+c+'"]').text()}});return a},getChartSettings:function(){var c={},d=this.getColumnSelections();c.datapointSize=this.$chartControl.find("#datapointSize.numeric-slider-input").find(".slider").slider("value");c.width=this.$chartControl.find("#width.numeric-slider-input").find(".slider").slider("value");c.height=this.$chartControl.find("#height.numeric-slider-input").find(".slider").slider("value");var b=this.$chartControl.find("input#X-axis-label").val(),a=this.$chartControl.find("input#Y-axis-label").val();c.xLabel=(b==="X")?(d.X.colName):(b);c.yLabel=(a==="Y")?(d.Y.colName):(a);c.animDuration=(this.$chartControl.find("#animate-chart").is(":checked"))?(this.chart.defaults.animDuration):(0);this.log("\t chartSettings:",c);return c},toString:function(){return"ScatterplotControlForm("+((this.dataset)?(this.dataset.id):(""))+")"}});ScatterplotControlForm.templates={mainLayout:Handlebars.templates["template-visualization-scatterplotControlForm"],dataControl:Handlebars.templates["template-visualization-dataControl"],chartControl:Handlebars.templates["template-visualization-chartControl"],statsDisplay:Handlebars.templates["template-visualization-statsDisplay"],chartDisplay:Handlebars.templates["template-visualization-chartDisplay"]};
\ No newline at end of file
diff -r 8ea772733c979a4d5578ba4c8c31dd3f47cc32ba -r 72b02995c8b188b8efe9b3ac4c5996e972e596f1 visualizations_conf.xml.sample
--- a/visualizations_conf.xml.sample
+++ b/visualizations_conf.xml.sample
@@ -84,30 +84,30 @@
         (e.g. hda_ldda can be 'hda' or 'ldda' and modifies/informs dataset_id to fetch an HDA or LDDA)
   --><!ELEMENT param (#PCDATA)>
-      <!-- param tells the registry how to parse the query string param back into a resource/data_source.
-            For example, if a query string has "dataset_id=NNN" and the type is 'dataset', the registry
-            will attempt to fetch the hda with id of NNN from the database and pass it to the template.
-          (text): the query string param key this source will be parsed from (e.g. dataset_id)
-                  REQUIRED
-          type: the type of the resource.
-                  Can be: str (DEFAULT), bool, int, float, json, visualization, dbkey, dataset, or hda_ldda.
-          default: if a param is not passed on the query string (and is not required) OR the given param
-                  fails to parse, this value is used instead.
-                  DEFAULT: None
-          required: set this to true if the param is required for the template. Rendering will with an error
-                  if the param hasn't been sent.
-                  DEFAULT: false
-          csv: set this to true if the param is a comma separated list. The registry will attempt to
-                  parse each value as the given type and send the result as a list to the template.
-                  DEFAULT: false
-          constrain_to: (currently unused) constain a param to a set of values, error if not valid.
-                  DEFAULT: don't constrain
-          var_name_in_template: a new name for the resource/variable to use in the template. E.g. an initial
-                  query string param key might be 'dataset_id' in the URL, the registry parses it into an HDA,
-                  and if var_name_in_template is set to 'hda', the template will be able to access the HDA
-                  with the variable name 'hda' (as in hda.title).
-                  DEFAULT: keep the original query string name
-      -->
+    <!-- param tells the registry how to parse the query string param back into a resource/data_source.
+          For example, if a query string has "dataset_id=NNN" and the type is 'dataset', the registry
+          will attempt to fetch the hda with id of NNN from the database and pass it to the template.
+        (text): the query string param key this source will be parsed from (e.g. dataset_id)
+                REQUIRED
+        type: the type of the resource.
+                Can be: str (DEFAULT), bool, int, float, json, visualization, dbkey, dataset, or hda_ldda.
+        default: if a param is not passed on the query string (and is not required) OR the given param
+                fails to parse, this value is used instead.
+                DEFAULT: None
+        required: set this to true if the param is required for the template. Rendering will with an error
+                if the param hasn't been sent.
+                DEFAULT: false
+        csv: set this to true if the param is a comma separated list. The registry will attempt to
+                parse each value as the given type and send the result as a list to the template.
+                DEFAULT: false
+        constrain_to: (currently unused) constain a param to a set of values, error if not valid.
+                DEFAULT: don't constrain
+        var_name_in_template: a new name for the resource/variable to use in the template. E.g. an initial
+                query string param key might be 'dataset_id' in the URL, the registry parses it into an HDA,
+                and if var_name_in_template is set to 'hda', the template will be able to access the HDA
+                with the variable name 'hda' (as in hda.title).
+                DEFAULT: keep the original query string name
+    --><!ATTLIST param
         type        CDATA #IMPLIED
         default     CDATA #IMPLIED
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.

    

2024

2023

2022

2021

2020

2019

2018

2017

2016

2015

2014

2013

2012

2011

2010

[galaxy-commits] commit/galaxy-central: carlfeberhard: data providers: add data to factory decorator to allow datasets api to parse query strings into provider settings; datasets API: allow new providers to be used in raw_data; clean up and pack scripts