#-----------------------------------------------------------------------------# Copyright (c) Anaconda, Inc., and Bokeh Contributors.# All rights reserved.## The full license is in the file LICENSE.txt, distributed with this software.#-----------------------------------------------------------------------------#-----------------------------------------------------------------------------# Boilerplate#-----------------------------------------------------------------------------from__future__importannotationsimportlogging# isort:skiplog=logging.getLogger(__name__)#-----------------------------------------------------------------------------# Imports#-----------------------------------------------------------------------------# Bokeh importsfrom..core.has_propsimportabstractfrom..core.propertiesimport(AnyRef,Bool,Instance,Int,NonEmpty,Nullable,Required,RestrictedDict,Seq,String,)from..modelimportModel#-----------------------------------------------------------------------------# Globals and constants#-----------------------------------------------------------------------------__all__=("AllIndices","BooleanFilter","CustomJSFilter","DifferenceFilter","Filter","GroupFilter","IndexFilter","IntersectionFilter","InversionFilter","SymmetricDifferenceFilter","UnionFilter",)#-----------------------------------------------------------------------------# General API#-----------------------------------------------------------------------------
[docs]@abstractclassFilter(Model):''' A Filter model represents a filtering operation that returns a row-wise subset of data when applied to a ``ColumnDataSource``. '''# explicit __init__ to support Init signaturesdef__init__(self,*args,**kwargs)->None:super().__init__(*args,**kwargs)def__invert__(self)->Filter:returnInversionFilter(operand=self)def__and__(self,other:Filter)->Filter:returnIntersectionFilter(operands=[self,other])def__or__(self,other:Filter)->Filter:returnUnionFilter(operands=[self,other])def__sub__(self,other:Filter)->Filter:returnDifferenceFilter(operands=[self,other])def__xor__(self,other:Filter)->Filter:returnSymmetricDifferenceFilter(operands=[self,other])
[docs]classAllIndices(Filter):""" Trivial filter that includes all indices in a dataset. """# explicit __init__ to support Init signaturesdef__init__(self,*args,**kwargs)->None:super().__init__(*args,**kwargs)
[docs]classInversionFilter(Filter):""" Inverts indices resulting from another filter. """# explicit __init__ to support Init signaturesdef__init__(self,*args,**kwargs)->None:super().__init__(*args,**kwargs)operand=Required(Instance(Filter),help=""" Indices produced by this filter will be inverted. """)
@abstractclassCompositeFilter(Filter):""" Base class for composite filters. """# explicit __init__ to support Init signaturesdef__init__(self,*args,**kwargs)->None:super().__init__(*args,**kwargs)operands=Required(NonEmpty(Seq(Instance(Filter))),help=""" A collection of filters to perform an operation on. """)
[docs]classIntersectionFilter(CompositeFilter):""" Computes intersection of indices resulting from other filters. """# explicit __init__ to support Init signaturesdef__init__(self,*args,**kwargs)->None:super().__init__(*args,**kwargs)
[docs]classUnionFilter(CompositeFilter):""" Computes union of indices resulting from other filters. """# explicit __init__ to support Init signaturesdef__init__(self,*args,**kwargs)->None:super().__init__(*args,**kwargs)
[docs]classDifferenceFilter(CompositeFilter):""" Computes difference of indices resulting from other filters. """# explicit __init__ to support Init signaturesdef__init__(self,*args,**kwargs)->None:super().__init__(*args,**kwargs)
[docs]classSymmetricDifferenceFilter(CompositeFilter):""" Computes symmetric difference of indices resulting from other filters. """# explicit __init__ to support Init signaturesdef__init__(self,*args,**kwargs)->None:super().__init__(*args,**kwargs)
[docs]classIndexFilter(Filter):''' An ``IndexFilter`` filters data by returning the subset of data at a given set of indices. '''indices=Nullable(Seq(Int),help=""" A list of integer indices representing the subset of data to select. """)def__init__(self,*args,**kwargs)->None:iflen(args)==1and"indices"notinkwargs:kwargs["indices"]=args[0]super().__init__(**kwargs)
[docs]classBooleanFilter(Filter):''' A ``BooleanFilter`` filters data by returning the subset of data corresponding to indices where the values of the booleans array is True. '''booleans=Nullable(Seq(Bool),help=""" A list of booleans indicating which rows of data to select. """)def__init__(self,*args,**kwargs)->None:iflen(args)==1and"booleans"notinkwargs:kwargs["booleans"]=args[0]super().__init__(**kwargs)
[docs]classGroupFilter(Filter):''' A ``GroupFilter`` represents the rows of a ``ColumnDataSource`` where the values of the categorical column column_name match the group variable. '''column_name=Required(String,help=""" The name of the column to perform the group filtering operation on. """)group=Required(String,help=""" The value of the column indicating the rows of data to keep. """)def__init__(self,*args,**kwargs)->None:iflen(args)==2and"column_name"notinkwargsand"group"notinkwargs:kwargs["column_name"]=args[0]kwargs["group"]=args[1]super().__init__(**kwargs)
[docs]classCustomJSFilter(Filter):''' Filter data sources with a custom defined JavaScript function. .. warning:: The explicit purpose of this Bokeh Model is to embed *raw JavaScript code* for a browser to execute. If any part of the code is derived from untrusted user inputs, then you must take appropriate care to sanitize the user input prior to passing to Bokeh. '''# explicit __init__ to support Init signaturesdef__init__(self,*args,**kwargs)->None:super().__init__(*args,**kwargs)args=RestrictedDict(String,AnyRef,disallow=("source",),help=""" A mapping of names to Python objects. In particular those can be bokeh's models. These objects are made available to the callback's code snippet as the values of named parameters to the callback. """)code=String(default="",help=""" A snippet of JavaScript code to filter data contained in a columnar data source. The code is made into the body of a function, and all of of the named objects in ``args`` are available as parameters that the code can use. The variable ``source`` will contain the data source that is associated with the ``CDSView`` this filter is added to. The code should either return the indices of the subset or an array of booleans to use to subset data source rows. Example: .. code-block:: code = ''' const indices = [] for (let i = 0; i <= source.data['some_column'].length; i++) { if (source.data['some_column'][i] == 'some_value') { indices.push(i) } } return indices ''' """)
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