holoviews.element Package


element Package

Inheritance diagram of holoviews.element
class holoviews.element. Bars ( data , kdims=None , vdims=None , **kwargs ) [source]

Bases: holoviews.element.chart.Chart

Bars is an Element type, representing a number of stacked and grouped bars, depending the dimensionality of the key and value dimensions. Bars is useful for categorical data, which may be laid via groups, categories and stacks.

param String group ( allow_None=False, basestring=<class ‘str’>, constant=True, default=Bars, instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
A string describing the data wrapped by the object.
param String label ( allow_None=False, basestring=<class ‘str’>, constant=True, default=, instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
Optional label describing the data, typically reflecting where or how it was measured. The label should allow a specific measurement or dataset to be referenced for a given group.
param Dict cdims ( allow_None=False, constant=False, default=OrderedDict(), instantiate=True, is_instance=True, pickle_default_value=True, precedence=None, readonly=False )
The constant dimensions defined as a dictionary of Dimension:value pairs providing additional dimension information about the object. Aliased with constant_dimensions.
param List kdims ( allow_None=False, bounds=(1, 3), constant=False, default=[Dimension(‘x’)], instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
The key dimensions of the Chart, determining the number of indexable dimensions.
param List vdims ( allow_None=False, bounds=(1, None), constant=False, default=[Dimension(‘y’)], instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
The value dimensions of the Chart, usually corresponding to a number of dependent variables.
param Tuple extents ( allow_None=False, constant=False, default=(None, None, None, None), instantiate=False, length=4, pickle_default_value=True, precedence=None, readonly=False )
Allows overriding the extents of the Element in 2D space defined as four-tuple defining the (left, bottom, right and top) edges.
param List datatype ( allow_None=False, bounds=(0, None), constant=False, default=[‘dataframe’, ‘dataframe’, ‘dataframe’, ‘dictionary’, ‘grid’, ‘ndelement’, ‘array’, ‘cube’, ‘xarray’, ‘dask’], instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
A priority list of the data types to be used for storage on the .data attribute. If the input supplied to the element constructor cannot be put into the requested format, the next format listed will be used until a suitable format is found (or the data fails to be understood).
add_dimension ( dimension , dim_pos , dim_val , vdim=False , **kwargs )

Create a new object with an additional key dimensions. Requires the dimension name or object, the desired position in the key dimensions and a key value scalar or sequence of the same length as the existing keys.

aggregate ( dimensions=None , function=None , spreadfn=None , **kwargs )

Aggregates over the supplied key dimensions with the defined function.

clone ( data=None , shared_data=True , new_type=None , *args , **overrides )

Returns a clone of the object with matching parameter values containing the specified args and kwargs.

If shared_data is set to True and no data explicitly supplied, the clone will share data with the original. May also supply a new_type, which will inherit all shared parameters.

closest ( coords=[] , **kwargs )

Given a single coordinate or multiple coordinates as a tuple or list of tuples or keyword arguments matching the dimension closest will find the closest actual x/y coordinates. Different Element types should implement this appropriately depending on the space they represent, if the Element does not support snapping raise NotImplementedError.

collapse_data ( data , function=None , kdims=None , **kwargs )

Class method to collapse a list of data matching the data format of the Element type. By implementing this method HoloMap can collapse multiple Elements of the same type. The kwargs are passed to the collapse function. The collapse function must support the numpy style axis selection. Valid function include: np.mean, np.sum, np.product, np.std, scipy.stats.kurtosis etc. Some data backends also require the key dimensions to aggregate over.

ddims

The list of deep dimensions

debug ( msg , *args , **kw )

Print msg merged with args as a debugging statement.

See Python’s logging module for details of message formatting.

defaults ( )

Return {parameter_name:parameter.default} for all non-constant Parameters.

Note that a Parameter for which instantiate==True has its default instantiated.

dframe ( dimensions=None )

Returns the data in the form of a DataFrame. Supplying a list of dimensions filters the dataframe. If the data is already a DataFrame a copy is returned.

dimension_values ( dim , expanded=True , flat=True )

Returns the values along a particular dimension. If unique values are requested will return only unique values.

dimensions ( selection='all' , label=False )

Provides convenient access to Dimensions on nested Dimensioned objects. Dimensions can be selected by their type, i.e. ‘key’ or ‘value’ dimensions. By default ‘all’ dimensions are returned.

force_new_dynamic_value = functools.partial(<function Parameterized.force_new_dynamic_value>, <class 'holoviews.element.chart.Bars'>)
get_dimension ( dimension , default=None , strict=False )

Access a Dimension object by name or index. Returns the default value if the dimension is not found and strict is False. If strict is True, a KeyError is raised instead.

get_dimension_index ( dim )

Returns the index of the requested dimension.

get_dimension_type ( dim )

Returns the specified Dimension type if specified or if the dimension_values types are consistent otherwise None is returned.

get_param_values = functools.partial(<function Parameterized.get_param_values>, <class 'holoviews.element.chart.Bars'>)
get_value_generator = functools.partial(<function Parameterized.get_value_generator>, <class 'holoviews.element.chart.Bars'>)
groupby ( dimensions=[] , container_type=<class 'holoviews.core.spaces.HoloMap'> , group_type=None , dynamic=False , **kwargs )

Return the results of a groupby operation over the specified dimensions as an object of type container_type (expected to be dictionary-like).

Keys vary over the columns (dimensions) and the corresponding values are collections of group_type (e.g an Element, list, tuple) constructed with kwargs (if supplied).

If dynamic is requested container_type is automatically set to a DynamicMap, allowing dynamic exploration of large datasets. If the data does not represent a full cartesian grid of the requested dimensions some Elements will be empty.

hist ( dimension=None , num_bins=20 , bin_range=None , adjoin=True , individually=True , **kwargs )

The hist method generates a histogram to be adjoined to the Element in an AdjointLayout. By default the histogram is computed along the first value dimension of the Element, however any dimension may be selected. The number of bins and the bin_ranges and any kwargs to be passed to the histogram operation may also be supplied.

iloc

Returns an iloc object providing a convenient interface to slice and index into the Dataset using row and column indices. Allow selection by integer index, slice and list of integer indices and boolean arrays.

Examples:

  • Index the first row and column:

    dataset.iloc[0, 0]

  • Select rows 1 and 2 with a slice:

    dataset.iloc[1:3, :]

  • Select with a list of integer coordinates:

    dataset.iloc[[0, 2, 3]]

inspect_value = functools.partial(<function Parameterized.inspect_value>, <class 'holoviews.element.chart.Bars'>)
map ( map_fn , specs=None , clone=True )

Recursively replaces elements using a map function when the specification applies.

matches ( spec )

A specification may be a class, a tuple or a string. Equivalent to isinstance if a class is supplied, otherwise matching occurs on type, group and label. These may be supplied as a tuple of strings or as a single string of the form “{type}.{group}.{label}”. Matching may be done on {type} alone, {type}.{group}, or {type}.{group}.{label}. The strings for the type, group, and label will each be sanitized before the match, and so the sanitized versions of those values will need to be provided if the match is to succeed.

message ( msg , *args , **kw )

Print msg merged with args as a message.

See Python’s logging module for details of message formatting.

ndloc

Returns an ndloc object providing nd-array like indexing for gridded datasets. Follows NumPy array indexing conventions, allowing for indexing, slicing and selecting a list of indices on multi-dimensional arrays using integer indices. The order of array indices is inverted relative to the Dataset key dimensions, e.g. an Image with key dimensions ‘x’ and ‘y’ can be indexed with image.ndloc[iy, ix] , where iy and ix are integer indices along the y and x dimensions.

Examples:

  • Index value in 2D array:

    dataset.ndloc[3, 1]

  • Slice along y-axis of 2D array:

    dataset.ndloc[2:5, :]

  • Vectorized (non-orthogonal) indexing along x- and y-axes:

    dataset.ndloc[[1, 2, 3], [0, 2, 3]]

options ( options=None , backend=None , clone=True , **kwargs )

Applies options on an object or nested group of objects in a flat format returning a new object with the options applied. If the options are to be set directly on the object a simple format may be used, e.g.:

obj.options(cmap=’viridis’, show_title=False)

If the object is nested the options must be qualified using a type[.group][.label] specification, e.g.:

obj.options(‘Image’, cmap=’viridis’, show_title=False)

or using:

obj.options({‘Image’: dict(cmap=’viridis’, show_title=False)})

If no options are supplied all options on the object will be reset. Disabling clone will modify the object inplace.

opts ( options=None , backend=None , clone=True , **kwargs )

Applies options on an object or nested group of objects in a by options group returning a new object with the options applied. If the options are to be set directly on the object a simple format may be used, e.g.:

obj.opts(style={‘cmap’: ‘viridis’}, plot={‘show_title’: False})

If the object is nested the options must be qualified using a type[.group][.label] specification, e.g.:

obj.opts({‘Image’: {‘plot’: {‘show_title’: False},
‘style’: {‘cmap’: ‘viridis}}})

If no opts are supplied all options on the object will be reset. Disabling clone will modify the object inplace.

params ( parameter_name=None )

Return the Parameters of this class as the dictionary {name: parameter_object}

Includes Parameters from this class and its superclasses.

pprint ( imports=None , prefix=' ' , unknown_value='<?>' , qualify=False , separator='' )

(Experimental) Pretty printed representation that may be evaluated with eval. See pprint() function for more details.

print_param_defaults ( )

Print the default values of all cls’s Parameters.

print_param_values ( )

Print the values of all this object’s Parameters.

range ( dim , data_range=True )

Computes the range of values along a supplied dimension, taking into account the range and soft_range defined on the Dimension object.

reduce ( dimensions=[] , function=None , spreadfn=None , **reduce_map )

Allows reducing the values along one or more key dimension with the supplied function. The dimensions may be supplied as a list and a function to apply or a mapping between the dimensions and functions to apply along each dimension.

reindex ( kdims=None , vdims=None )

Create a new object with a re-ordered set of dimensions. Allows converting key dimensions to value dimensions and vice versa.

relabel ( label=None , group=None , depth=0 )

Assign a new label and/or group to an existing LabelledData object, creating a clone of the object with the new settings.

sample ( samples=[] , closest=True , **kwargs )

Allows sampling of Dataset as an iterator of coordinates matching the key dimensions, returning a new object containing just the selected samples. Alternatively may supply kwargs to sample a coordinate on an object. By default it will attempt to snap to the nearest coordinate if the Element supports it, snapping may be disabled with the closest argument.

script_repr ( imports=[] , prefix=' ' )

Variant of __repr__ designed for generating a runnable script.

select ( selection_specs=None , **selection )

Allows selecting data by the slices, sets and scalar values along a particular dimension. The indices should be supplied as keywords mapping between the selected dimension and value. Additionally selection_specs (taking the form of a list of type.group.label strings, types or functions) may be supplied, which will ensure the selection is only applied if the specs match the selected object.

set_default ( param_name , value )

Set the default value of param_name.

Equivalent to setting param_name on the class.

set_dynamic_time_fn = functools.partial(<function Parameterized.set_dynamic_time_fn>, <class 'holoviews.element.chart.Bars'>)
set_param = functools.partial(<function Parameterized.set_param>, <class 'holoviews.element.chart.Bars'>)
shape

Returns the shape of the data.

sort ( by=[] , reverse=False )

Sorts the data by the values along the supplied dimensions.

state_pop ( )

Restore the most recently saved state.

See state_push() for more details.

state_push ( )

Save this instance’s state.

For Parameterized instances, this includes the state of dynamically generated values.

Subclasses that maintain short-term state should additionally save and restore that state using state_push() and state_pop().

Generally, this method is used by operations that need to test something without permanently altering the objects’ state.

table ( datatype=None )

Converts the data Element to a Table, optionally may specify a supported data type. The default data types are ‘numpy’ (for homogeneous data), ‘dataframe’, and ‘dictionary’.

to

Property to create a conversion interface with methods to convert to other Element types.

traverse ( fn , specs=None , full_breadth=True )

Traverses any nested LabelledData object (i.e LabelledData objects containing LabelledData objects), applying the supplied function to each constituent element if the supplied specifications. The output of these function calls are collected and returned in the accumulator list.

If specs is None, all constituent elements are processed. Otherwise, specs must be a list of type.group.label specs, types, and functions.

verbose ( msg , *args , **kw )

Print msg merged with args as a verbose message.

See Python’s logging module for details of message formatting.

warning ( msg , *args , **kw )

Print msg merged with args as a warning, unless module variable warnings_as_exceptions is True, then raise an Exception containing the arguments.

See Python’s logging module for details of message formatting.

class holoviews.element. Spread ( data , kdims=None , vdims=None , **kwargs ) [source]

Bases: holoviews.element.chart.ErrorBars

Spread is a Chart Element type representing a spread of values as given by a mean and standard error or confidence intervals. Just like the ErrorBars Element type, mean and deviations from the mean should be supplied as either an Nx3 or Nx4 array representing the x-values, mean values and symmetric or asymmetric errors respective. Internally the data is always expanded to an Nx4 array.

param String group ( allow_None=False, basestring=<class ‘str’>, constant=True, default=Spread, instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
A string describing the quantity measured by the ErrorBars object.
param String label ( allow_None=False, basestring=<class ‘str’>, constant=True, default=, instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
Optional label describing the data, typically reflecting where or how it was measured. The label should allow a specific measurement or dataset to be referenced for a given group.
param Dict cdims ( allow_None=False, constant=False, default=OrderedDict(), instantiate=True, is_instance=True, pickle_default_value=True, precedence=None, readonly=False )
The constant dimensions defined as a dictionary of Dimension:value pairs providing additional dimension information about the object. Aliased with constant_dimensions.
param List kdims ( allow_None=False, bounds=(1, 2), constant=True, default=[Dimension(‘x’)], instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
The Dimensions corresponding to the x- and y-positions of the error bars.
param List vdims ( allow_None=False, bounds=(1, 3), constant=True, default=[Dimension(‘y’), Dimension(‘yerror’)], instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
The value dimensions of the Chart, usually corresponding to a number of dependent variables.
param Tuple extents ( allow_None=False, constant=False, default=(None, None, None, None), instantiate=False, length=4, pickle_default_value=True, precedence=None, readonly=False )
Allows overriding the extents of the Element in 2D space defined as four-tuple defining the (left, bottom, right and top) edges.
param List datatype ( allow_None=False, bounds=(0, None), constant=False, default=[‘dataframe’, ‘dataframe’, ‘dataframe’, ‘dictionary’, ‘grid’, ‘ndelement’, ‘array’, ‘cube’, ‘xarray’, ‘dask’], instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
A priority list of the data types to be used for storage on the .data attribute. If the input supplied to the element constructor cannot be put into the requested format, the next format listed will be used until a suitable format is found (or the data fails to be understood).
add_dimension ( dimension , dim_pos , dim_val , vdim=False , **kwargs )

Create a new object with an additional key dimensions. Requires the dimension name or object, the desired position in the key dimensions and a key value scalar or sequence of the same length as the existing keys.

aggregate ( dimensions=None , function=None , spreadfn=None , **kwargs )

Aggregates over the supplied key dimensions with the defined function.

clone ( data=None , shared_data=True , new_type=None , *args , **overrides )

Returns a clone of the object with matching parameter values containing the specified args and kwargs.

If shared_data is set to True and no data explicitly supplied, the clone will share data with the original. May also supply a new_type, which will inherit all shared parameters.

closest ( coords=[] , **kwargs )

Given a single coordinate or multiple coordinates as a tuple or list of tuples or keyword arguments matching the dimension closest will find the closest actual x/y coordinates. Different Element types should implement this appropriately depending on the space they represent, if the Element does not support snapping raise NotImplementedError.

collapse_data ( data , function=None , kdims=None , **kwargs )

Class method to collapse a list of data matching the data format of the Element type. By implementing this method HoloMap can collapse multiple Elements of the same type. The kwargs are passed to the collapse function. The collapse function must support the numpy style axis selection. Valid function include: np.mean, np.sum, np.product, np.std, scipy.stats.kurtosis etc. Some data backends also require the key dimensions to aggregate over.

ddims

The list of deep dimensions

debug ( msg , *args , **kw )

Print msg merged with args as a debugging statement.

See Python’s logging module for details of message formatting.

defaults ( )

Return {parameter_name:parameter.default} for all non-constant Parameters.

Note that a Parameter for which instantiate==True has its default instantiated.

dframe ( dimensions=None )

Returns the data in the form of a DataFrame. Supplying a list of dimensions filters the dataframe. If the data is already a DataFrame a copy is returned.

dimension_values ( dim , expanded=True , flat=True )

Returns the values along a particular dimension. If unique values are requested will return only unique values.

dimensions ( selection='all' , label=False )

Provides convenient access to Dimensions on nested Dimensioned objects. Dimensions can be selected by their type, i.e. ‘key’ or ‘value’ dimensions. By default ‘all’ dimensions are returned.

force_new_dynamic_value = functools.partial(<function Parameterized.force_new_dynamic_value>, <class 'holoviews.element.chart.Spread'>)
get_dimension ( dimension , default=None , strict=False )

Access a Dimension object by name or index. Returns the default value if the dimension is not found and strict is False. If strict is True, a KeyError is raised instead.

get_dimension_index ( dim )

Returns the index of the requested dimension.

get_dimension_type ( dim )

Returns the specified Dimension type if specified or if the dimension_values types are consistent otherwise None is returned.

get_param_values = functools.partial(<function Parameterized.get_param_values>, <class 'holoviews.element.chart.Spread'>)
get_value_generator = functools.partial(<function Parameterized.get_value_generator>, <class 'holoviews.element.chart.Spread'>)
groupby ( dimensions=[] , container_type=<class 'holoviews.core.spaces.HoloMap'> , group_type=None , dynamic=False , **kwargs )

Return the results of a groupby operation over the specified dimensions as an object of type container_type (expected to be dictionary-like).

Keys vary over the columns (dimensions) and the corresponding values are collections of group_type (e.g an Element, list, tuple) constructed with kwargs (if supplied).

If dynamic is requested container_type is automatically set to a DynamicMap, allowing dynamic exploration of large datasets. If the data does not represent a full cartesian grid of the requested dimensions some Elements will be empty.

hist ( dimension=None , num_bins=20 , bin_range=None , adjoin=True , individually=True , **kwargs )

The hist method generates a histogram to be adjoined to the Element in an AdjointLayout. By default the histogram is computed along the first value dimension of the Element, however any dimension may be selected. The number of bins and the bin_ranges and any kwargs to be passed to the histogram operation may also be supplied.

iloc

Returns an iloc object providing a convenient interface to slice and index into the Dataset using row and column indices. Allow selection by integer index, slice and list of integer indices and boolean arrays.

Examples:

  • Index the first row and column:

    dataset.iloc[0, 0]

  • Select rows 1 and 2 with a slice:

    dataset.iloc[1:3, :]

  • Select with a list of integer coordinates:

    dataset.iloc[[0, 2, 3]]

inspect_value = functools.partial(<function Parameterized.inspect_value>, <class 'holoviews.element.chart.Spread'>)
map ( map_fn , specs=None , clone=True )

Recursively replaces elements using a map function when the specification applies.

matches ( spec )

A specification may be a class, a tuple or a string. Equivalent to isinstance if a class is supplied, otherwise matching occurs on type, group and label. These may be supplied as a tuple of strings or as a single string of the form “{type}.{group}.{label}”. Matching may be done on {type} alone, {type}.{group}, or {type}.{group}.{label}. The strings for the type, group, and label will each be sanitized before the match, and so the sanitized versions of those values will need to be provided if the match is to succeed.

message ( msg , *args , **kw )

Print msg merged with args as a message.

See Python’s logging module for details of message formatting.

ndloc

Returns an ndloc object providing nd-array like indexing for gridded datasets. Follows NumPy array indexing conventions, allowing for indexing, slicing and selecting a list of indices on multi-dimensional arrays using integer indices. The order of array indices is inverted relative to the Dataset key dimensions, e.g. an Image with key dimensions ‘x’ and ‘y’ can be indexed with image.ndloc[iy, ix] , where iy and ix are integer indices along the y and x dimensions.

Examples:

  • Index value in 2D array:

    dataset.ndloc[3, 1]

  • Slice along y-axis of 2D array:

    dataset.ndloc[2:5, :]

  • Vectorized (non-orthogonal) indexing along x- and y-axes:

    dataset.ndloc[[1, 2, 3], [0, 2, 3]]

options ( options=None , backend=None , clone=True , **kwargs )

Applies options on an object or nested group of objects in a flat format returning a new object with the options applied. If the options are to be set directly on the object a simple format may be used, e.g.:

obj.options(cmap=’viridis’, show_title=False)

If the object is nested the options must be qualified using a type[.group][.label] specification, e.g.:

obj.options(‘Image’, cmap=’viridis’, show_title=False)

or using:

obj.options({‘Image’: dict(cmap=’viridis’, show_title=False)})

If no options are supplied all options on the object will be reset. Disabling clone will modify the object inplace.

opts ( options=None , backend=None , clone=True , **kwargs )

Applies options on an object or nested group of objects in a by options group returning a new object with the options applied. If the options are to be set directly on the object a simple format may be used, e.g.:

obj.opts(style={‘cmap’: ‘viridis’}, plot={‘show_title’: False})

If the object is nested the options must be qualified using a type[.group][.label] specification, e.g.:

obj.opts({‘Image’: {‘plot’: {‘show_title’: False},
‘style’: {‘cmap’: ‘viridis}}})

If no opts are supplied all options on the object will be reset. Disabling clone will modify the object inplace.

params ( parameter_name=None )

Return the Parameters of this class as the dictionary {name: parameter_object}

Includes Parameters from this class and its superclasses.

pprint ( imports=None , prefix=' ' , unknown_value='<?>' , qualify=False , separator='' )

(Experimental) Pretty printed representation that may be evaluated with eval. See pprint() function for more details.

print_param_defaults ( )

Print the default values of all cls’s Parameters.

print_param_values ( )

Print the values of all this object’s Parameters.

reduce ( dimensions=[] , function=None , spreadfn=None , **reduce_map )

Allows reducing the values along one or more key dimension with the supplied function. The dimensions may be supplied as a list and a function to apply or a mapping between the dimensions and functions to apply along each dimension.

reindex ( kdims=None , vdims=None )

Create a new object with a re-ordered set of dimensions. Allows converting key dimensions to value dimensions and vice versa.

relabel ( label=None , group=None , depth=0 )

Assign a new label and/or group to an existing LabelledData object, creating a clone of the object with the new settings.

sample ( samples=[] , closest=True , **kwargs )

Allows sampling of Dataset as an iterator of coordinates matching the key dimensions, returning a new object containing just the selected samples. Alternatively may supply kwargs to sample a coordinate on an object. By default it will attempt to snap to the nearest coordinate if the Element supports it, snapping may be disabled with the closest argument.

script_repr ( imports=[] , prefix=' ' )

Variant of __repr__ designed for generating a runnable script.

select ( selection_specs=None , **selection )

Allows selecting data by the slices, sets and scalar values along a particular dimension. The indices should be supplied as keywords mapping between the selected dimension and value. Additionally selection_specs (taking the form of a list of type.group.label strings, types or functions) may be supplied, which will ensure the selection is only applied if the specs match the selected object.

set_default ( param_name , value )

Set the default value of param_name.

Equivalent to setting param_name on the class.

set_dynamic_time_fn = functools.partial(<function Parameterized.set_dynamic_time_fn>, <class 'holoviews.element.chart.Spread'>)
set_param = functools.partial(<function Parameterized.set_param>, <class 'holoviews.element.chart.Spread'>)
shape

Returns the shape of the data.

sort ( by=[] , reverse=False )

Sorts the data by the values along the supplied dimensions.

state_pop ( )

Restore the most recently saved state.

See state_push() for more details.

state_push ( )

Save this instance’s state.

For Parameterized instances, this includes the state of dynamically generated values.

Subclasses that maintain short-term state should additionally save and restore that state using state_push() and state_pop().

Generally, this method is used by operations that need to test something without permanently altering the objects’ state.

table ( datatype=None )

Converts the data Element to a Table, optionally may specify a supported data type. The default data types are ‘numpy’ (for homogeneous data), ‘dataframe’, and ‘dictionary’.

to

Property to create a conversion interface with methods to convert to other Element types.

traverse ( fn , specs=None , full_breadth=True )

Traverses any nested LabelledData object (i.e LabelledData objects containing LabelledData objects), applying the supplied function to each constituent element if the supplied specifications. The output of these function calls are collected and returned in the accumulator list.

If specs is None, all constituent elements are processed. Otherwise, specs must be a list of type.group.label specs, types, and functions.

verbose ( msg , *args , **kw )

Print msg merged with args as a verbose message.

See Python’s logging module for details of message formatting.

warning ( msg , *args , **kw )

Print msg merged with args as a warning, unless module variable warnings_as_exceptions is True, then raise an Exception containing the arguments.

See Python’s logging module for details of message formatting.

class holoviews.element. Scatter3D ( data , kdims=None , vdims=None , **kwargs ) [source]

Bases: holoviews.core.element.Element3D , holoviews.element.chart.Scatter

Scatter3D object represents a number of coordinates in 3D-space. Additionally Scatter3D points may have any number of value dimensions. The data may therefore be supplied as NxD matrix where N represents the number of samples, and D the number of key and value dimensions.

param String group ( allow_None=False, basestring=<class ‘str’>, constant=True, default=Scatter3D, instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
A string describing the data wrapped by the object.
param String label ( allow_None=False, basestring=<class ‘str’>, constant=True, default=, instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
Optional label describing the data, typically reflecting where or how it was measured. The label should allow a specific measurement or dataset to be referenced for a given group.
param Dict cdims ( allow_None=False, constant=False, default=OrderedDict(), instantiate=True, is_instance=True, pickle_default_value=True, precedence=None, readonly=False )
The constant dimensions defined as a dictionary of Dimension:value pairs providing additional dimension information about the object. Aliased with constant_dimensions.
param List kdims ( allow_None=False, bounds=(0, None), constant=False, default=[Dimension(‘x’), Dimension(‘y’), Dimension(‘z’)], instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
The key dimensions of the Chart, determining the number of indexable dimensions.
param List vdims ( allow_None=False, bounds=(0, None), constant=False, default=[], instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
Scatter3D can have optional value dimensions, which may be mapped onto color and size.
param Tuple extents ( allow_None=False, constant=False, default=(None, None, None, None, None, None), instantiate=False, length=6, pickle_default_value=True, precedence=None, readonly=False )
Allows overriding the extents of the Element in 3D space defined as (xmin, ymin, zmin, xmax, ymax, zmax).
param List datatype ( allow_None=False, bounds=(0, None), constant=False, default=[‘dataframe’, ‘dataframe’, ‘dataframe’, ‘dictionary’, ‘grid’, ‘ndelement’, ‘array’, ‘cube’, ‘xarray’, ‘dask’], instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
A priority list of the data types to be used for storage on the .data attribute. If the input supplied to the element constructor cannot be put into the requested format, the next format listed will be used until a suitable format is found (or the data fails to be understood).
add_dimension ( dimension , dim_pos , dim_val , vdim=False , **kwargs )

Create a new object with an additional key dimensions. Requires the dimension name or object, the desired position in the key dimensions and a key value scalar or sequence of the same length as the existing keys.

aggregate ( dimensions=None , function=None , spreadfn=None , **kwargs )

Aggregates over the supplied key dimensions with the defined function.

clone ( data=None , shared_data=True , new_type=None , *args , **overrides )

Returns a clone of the object with matching parameter values containing the specified args and kwargs.

If shared_data is set to True and no data explicitly supplied, the clone will share data with the original. May also supply a new_type, which will inherit all shared parameters.

closest ( coords=[] , **kwargs )

Given a single coordinate or multiple coordinates as a tuple or list of tuples or keyword arguments matching the dimension closest will find the closest actual x/y coordinates. Different Element types should implement this appropriately depending on the space they represent, if the Element does not support snapping raise NotImplementedError.

collapse_data ( data , function=None , kdims=None , **kwargs )

Class method to collapse a list of data matching the data format of the Element type. By implementing this method HoloMap can collapse multiple Elements of the same type. The kwargs are passed to the collapse function. The collapse function must support the numpy style axis selection. Valid function include: np.mean, np.sum, np.product, np.std, scipy.stats.kurtosis etc. Some data backends also require the key dimensions to aggregate over.

ddims

The list of deep dimensions

debug ( msg , *args , **kw )

Print msg merged with args as a debugging statement.

See Python’s logging module for details of message formatting.

defaults ( )

Return {parameter_name:parameter.default} for all non-constant Parameters.

Note that a Parameter for which instantiate==True has its default instantiated.

dframe ( dimensions=None )

Returns the data in the form of a DataFrame. Supplying a list of dimensions filters the dataframe. If the data is already a DataFrame a copy is returned.

dimension_values ( dim , expanded=True , flat=True )

Returns the values along a particular dimension. If unique values are requested will return only unique values.

dimensions ( selection='all' , label=False )

Provides convenient access to Dimensions on nested Dimensioned objects. Dimensions can be selected by their type, i.e. ‘key’ or ‘value’ dimensions. By default ‘all’ dimensions are returned.

force_new_dynamic_value = functools.partial(<function Parameterized.force_new_dynamic_value>, <class 'holoviews.element.chart3d.Scatter3D'>)
get_dimension ( dimension , default=None , strict=False )

Access a Dimension object by name or index. Returns the default value if the dimension is not found and strict is False. If strict is True, a KeyError is raised instead.

get_dimension_index ( dim )

Returns the index of the requested dimension.

get_dimension_type ( dim )

Returns the specified Dimension type if specified or if the dimension_values types are consistent otherwise None is returned.

get_param_values = functools.partial(<function Parameterized.get_param_values>, <class 'holoviews.element.chart3d.Scatter3D'>)
get_value_generator = functools.partial(<function Parameterized.get_value_generator>, <class 'holoviews.element.chart3d.Scatter3D'>)
groupby ( dimensions=[] , container_type=<class 'holoviews.core.spaces.HoloMap'> , group_type=None , dynamic=False , **kwargs )

Return the results of a groupby operation over the specified dimensions as an object of type container_type (expected to be dictionary-like).

Keys vary over the columns (dimensions) and the corresponding values are collections of group_type (e.g an Element, list, tuple) constructed with kwargs (if supplied).

If dynamic is requested container_type is automatically set to a DynamicMap, allowing dynamic exploration of large datasets. If the data does not represent a full cartesian grid of the requested dimensions some Elements will be empty.

hist ( dimension=None , num_bins=20 , bin_range=None , adjoin=True , individually=True , **kwargs )

The hist method generates a histogram to be adjoined to the Element in an AdjointLayout. By default the histogram is computed along the first value dimension of the Element, however any dimension may be selected. The number of bins and the bin_ranges and any kwargs to be passed to the histogram operation may also be supplied.

iloc

Returns an iloc object providing a convenient interface to slice and index into the Dataset using row and column indices. Allow selection by integer index, slice and list of integer indices and boolean arrays.

Examples:

  • Index the first row and column:

    dataset.iloc[0, 0]

  • Select rows 1 and 2 with a slice:

    dataset.iloc[1:3, :]

  • Select with a list of integer coordinates:

    dataset.iloc[[0, 2, 3]]

inspect_value = functools.partial(<function Parameterized.inspect_value>, <class 'holoviews.element.chart3d.Scatter3D'>)
map ( map_fn , specs=None , clone=True )

Recursively replaces elements using a map function when the specification applies.

matches ( spec )

A specification may be a class, a tuple or a string. Equivalent to isinstance if a class is supplied, otherwise matching occurs on type, group and label. These may be supplied as a tuple of strings or as a single string of the form “{type}.{group}.{label}”. Matching may be done on {type} alone, {type}.{group}, or {type}.{group}.{label}. The strings for the type, group, and label will each be sanitized before the match, and so the sanitized versions of those values will need to be provided if the match is to succeed.

message ( msg , *args , **kw )

Print msg merged with args as a message.

See Python’s logging module for details of message formatting.

ndloc

Returns an ndloc object providing nd-array like indexing for gridded datasets. Follows NumPy array indexing conventions, allowing for indexing, slicing and selecting a list of indices on multi-dimensional arrays using integer indices. The order of array indices is inverted relative to the Dataset key dimensions, e.g. an Image with key dimensions ‘x’ and ‘y’ can be indexed with image.ndloc[iy, ix] , where iy and ix are integer indices along the y and x dimensions.

Examples:

  • Index value in 2D array:

    dataset.ndloc[3, 1]

  • Slice along y-axis of 2D array:

    dataset.ndloc[2:5, :]

  • Vectorized (non-orthogonal) indexing along x- and y-axes:

    dataset.ndloc[[1, 2, 3], [0, 2, 3]]

options ( options=None , backend=None , clone=True , **kwargs )

Applies options on an object or nested group of objects in a flat format returning a new object with the options applied. If the options are to be set directly on the object a simple format may be used, e.g.:

obj.options(cmap=’viridis’, show_title=False)

If the object is nested the options must be qualified using a type[.group][.label] specification, e.g.:

obj.options(‘Image’, cmap=’viridis’, show_title=False)

or using:

obj.options({‘Image’: dict(cmap=’viridis’, show_title=False)})

If no options are supplied all options on the object will be reset. Disabling clone will modify the object inplace.

opts ( options=None , backend=None , clone=True , **kwargs )

Applies options on an object or nested group of objects in a by options group returning a new object with the options applied. If the options are to be set directly on the object a simple format may be used, e.g.:

obj.opts(style={‘cmap’: ‘viridis’}, plot={‘show_title’: False})

If the object is nested the options must be qualified using a type[.group][.label] specification, e.g.:

obj.opts({‘Image’: {‘plot’: {‘show_title’: False},
‘style’: {‘cmap’: ‘viridis}}})

If no opts are supplied all options on the object will be reset. Disabling clone will modify the object inplace.

params ( parameter_name=None )

Return the Parameters of this class as the dictionary {name: parameter_object}

Includes Parameters from this class and its superclasses.

pprint ( imports=None , prefix=' ' , unknown_value='<?>' , qualify=False , separator='' )

(Experimental) Pretty printed representation that may be evaluated with eval. See pprint() function for more details.

print_param_defaults ( )

Print the default values of all cls’s Parameters.

print_param_values ( )

Print the values of all this object’s Parameters.

range ( dim , data_range=True )

Computes the range of values along a supplied dimension, taking into account the range and soft_range defined on the Dimension object.

reduce ( dimensions=[] , function=None , spreadfn=None , **reduce_map )

Allows reducing the values along one or more key dimension with the supplied function. The dimensions may be supplied as a list and a function to apply or a mapping between the dimensions and functions to apply along each dimension.

reindex ( kdims=None , vdims=None )

Create a new object with a re-ordered set of dimensions. Allows converting key dimensions to value dimensions and vice versa.

relabel ( label=None , group=None , depth=0 )

Assign a new label and/or group to an existing LabelledData object, creating a clone of the object with the new settings.

sample ( samples=[] , closest=True , **kwargs )

Allows sampling of Dataset as an iterator of coordinates matching the key dimensions, returning a new object containing just the selected samples. Alternatively may supply kwargs to sample a coordinate on an object. By default it will attempt to snap to the nearest coordinate if the Element supports it, snapping may be disabled with the closest argument.

script_repr ( imports=[] , prefix=' ' )

Variant of __repr__ designed for generating a runnable script.

select ( selection_specs=None , **selection )

Allows selecting data by the slices, sets and scalar values along a particular dimension. The indices should be supplied as keywords mapping between the selected dimension and value. Additionally selection_specs (taking the form of a list of type.group.label strings, types or functions) may be supplied, which will ensure the selection is only applied if the specs match the selected object.

set_default ( param_name , value )

Set the default value of param_name.

Equivalent to setting param_name on the class.

set_dynamic_time_fn = functools.partial(<function Parameterized.set_dynamic_time_fn>, <class 'holoviews.element.chart3d.Scatter3D'>)
set_param = functools.partial(<function Parameterized.set_param>, <class 'holoviews.element.chart3d.Scatter3D'>)
shape

Returns the shape of the data.

sort ( by=[] , reverse=False )

Sorts the data by the values along the supplied dimensions.

state_pop ( )

Restore the most recently saved state.

See state_push() for more details.

state_push ( )

Save this instance’s state.

For Parameterized instances, this includes the state of dynamically generated values.

Subclasses that maintain short-term state should additionally save and restore that state using state_push() and state_pop().

Generally, this method is used by operations that need to test something without permanently altering the objects’ state.

table ( datatype=None )

Converts the data Element to a Table, optionally may specify a supported data type. The default data types are ‘numpy’ (for homogeneous data), ‘dataframe’, and ‘dictionary’.

to

Property to create a conversion interface with methods to convert to other Element types.

traverse ( fn , specs=None , full_breadth=True )

Traverses any nested LabelledData object (i.e LabelledData objects containing LabelledData objects), applying the supplied function to each constituent element if the supplied specifications. The output of these function calls are collected and returned in the accumulator list.

If specs is None, all constituent elements are processed. Otherwise, specs must be a list of type.group.label specs, types, and functions.

verbose ( msg , *args , **kw )

Print msg merged with args as a verbose message.

See Python’s logging module for details of message formatting.

warning ( msg , *args , **kw )

Print msg merged with args as a warning, unless module variable warnings_as_exceptions is True, then raise an Exception containing the arguments.

See Python’s logging module for details of message formatting.

class holoviews.element. Histogram ( data , edges=None , **params ) [source]

Bases: holoviews.element.chart.Chart

Histogram contains a number of bins, which are defined by the upper and lower bounds of their edges and the computed bin values.

param String group ( allow_None=False, basestring=<class ‘str’>, constant=True, default=Histogram, instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
A string describing the data wrapped by the object.
param String label ( allow_None=False, basestring=<class ‘str’>, constant=True, default=, instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
Optional label describing the data, typically reflecting where or how it was measured. The label should allow a specific measurement or dataset to be referenced for a given group.
param Dict cdims ( allow_None=False, constant=False, default=OrderedDict(), instantiate=True, is_instance=True, pickle_default_value=True, precedence=None, readonly=False )
The constant dimensions defined as a dictionary of Dimension:value pairs providing additional dimension information about the object. Aliased with constant_dimensions.
param List kdims ( allow_None=False, bounds=(1, 1), constant=False, default=[Dimension(‘x’)], instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
Dimensions on Element2Ds determine the number of indexable dimensions.
param List vdims ( allow_None=False, bounds=(1, 1), constant=False, default=[Dimension(‘Frequency’)], instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
The value dimensions of the Chart, usually corresponding to a number of dependent variables.
param Tuple extents ( allow_None=False, constant=False, default=(None, None, None, None), instantiate=False, length=4, pickle_default_value=True, precedence=None, readonly=False )
Allows overriding the extents of the Element in 2D space defined as four-tuple defining the (left, bottom, right and top) edges.
param List datatype ( allow_None=False, bounds=(0, None), constant=False, default=[‘grid’], instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
A priority list of the data types to be used for storage on the .data attribute. If the input supplied to the element constructor cannot be put into the requested format, the next format listed will be used until a suitable format is found (or the data fails to be understood).
add_dimension ( dimension , dim_pos , dim_val , vdim=False , **kwargs )

Create a new object with an additional key dimensions. Requires the dimension name or object, the desired position in the key dimensions and a key value scalar or sequence of the same length as the existing keys.

aggregate ( dimensions=None , function=None , spreadfn=None , **kwargs )

Aggregates over the supplied key dimensions with the defined function.

clone ( data=None , shared_data=True , new_type=None , *args , **overrides )

Returns a clone of the object with matching parameter values containing the specified args and kwargs.

If shared_data is set to True and no data explicitly supplied, the clone will share data with the original. May also supply a new_type, which will inherit all shared parameters.

closest ( coords=[] , **kwargs )

Given a single coordinate or multiple coordinates as a tuple or list of tuples or keyword arguments matching the dimension closest will find the closest actual x/y coordinates. Different Element types should implement this appropriately depending on the space they represent, if the Element does not support snapping raise NotImplementedError.

collapse_data ( data , function=None , kdims=None , **kwargs )

Class method to collapse a list of data matching the data format of the Element type. By implementing this method HoloMap can collapse multiple Elements of the same type. The kwargs are passed to the collapse function. The collapse function must support the numpy style axis selection. Valid function include: np.mean, np.sum, np.product, np.std, scipy.stats.kurtosis etc. Some data backends also require the key dimensions to aggregate over.

ddims

The list of deep dimensions

debug ( msg , *args , **kw )

Print msg merged with args as a debugging statement.

See Python’s logging module for details of message formatting.

defaults ( )

Return {parameter_name:parameter.default} for all non-constant Parameters.

Note that a Parameter for which instantiate==True has its default instantiated.

dframe ( dimensions=None )

Returns the data in the form of a DataFrame. Supplying a list of dimensions filters the dataframe. If the data is already a DataFrame a copy is returned.

dimension_values ( dim , expanded=True , flat=True )

Returns the values along a particular dimension. If unique values are requested will return only unique values.

dimensions ( selection='all' , label=False )

Provides convenient access to Dimensions on nested Dimensioned objects. Dimensions can be selected by their type, i.e. ‘key’ or ‘value’ dimensions. By default ‘all’ dimensions are returned.

edges

Property to access the Histogram edges provided for backward compatibility

force_new_dynamic_value = functools.partial(<function Parameterized.force_new_dynamic_value>, <class 'holoviews.element.chart.Histogram'>)
get_dimension ( dimension , default=None , strict=False )

Access a Dimension object by name or index. Returns the default value if the dimension is not found and strict is False. If strict is True, a KeyError is raised instead.

get_dimension_index ( dim )

Returns the index of the requested dimension.

get_dimension_type ( dim )

Returns the specified Dimension type if specified or if the dimension_values types are consistent otherwise None is returned.

get_param_values = functools.partial(<function Parameterized.get_param_values>, <class 'holoviews.element.chart.Histogram'>)
get_value_generator = functools.partial(<function Parameterized.get_value_generator>, <class 'holoviews.element.chart.Histogram'>)
groupby ( dimensions=[] , container_type=<class 'holoviews.core.spaces.HoloMap'> , group_type=None , dynamic=False , **kwargs )

Return the results of a groupby operation over the specified dimensions as an object of type container_type (expected to be dictionary-like).

Keys vary over the columns (dimensions) and the corresponding values are collections of group_type (e.g an Element, list, tuple) constructed with kwargs (if supplied).

If dynamic is requested container_type is automatically set to a DynamicMap, allowing dynamic exploration of large datasets. If the data does not represent a full cartesian grid of the requested dimensions some Elements will be empty.

hist ( dimension=None , num_bins=20 , bin_range=None , adjoin=True , individually=True , **kwargs )

The hist method generates a histogram to be adjoined to the Element in an AdjointLayout. By default the histogram is computed along the first value dimension of the Element, however any dimension may be selected. The number of bins and the bin_ranges and any kwargs to be passed to the histogram operation may also be supplied.

iloc

Returns an iloc object providing a convenient interface to slice and index into the Dataset using row and column indices. Allow selection by integer index, slice and list of integer indices and boolean arrays.

Examples:

  • Index the first row and column:

    dataset.iloc[0, 0]

  • Select rows 1 and 2 with a slice:

    dataset.iloc[1:3, :]

  • Select with a list of integer coordinates:

    dataset.iloc[[0, 2, 3]]

inspect_value = functools.partial(<function Parameterized.inspect_value>, <class 'holoviews.element.chart.Histogram'>)
map ( map_fn , specs=None , clone=True )

Recursively replaces elements using a map function when the specification applies.

matches ( spec )

A specification may be a class, a tuple or a string. Equivalent to isinstance if a class is supplied, otherwise matching occurs on type, group and label. These may be supplied as a tuple of strings or as a single string of the form “{type}.{group}.{label}”. Matching may be done on {type} alone, {type}.{group}, or {type}.{group}.{label}. The strings for the type, group, and label will each be sanitized before the match, and so the sanitized versions of those values will need to be provided if the match is to succeed.

message ( msg , *args , **kw )

Print msg merged with args as a message.

See Python’s logging module for details of message formatting.

ndloc

Returns an ndloc object providing nd-array like indexing for gridded datasets. Follows NumPy array indexing conventions, allowing for indexing, slicing and selecting a list of indices on multi-dimensional arrays using integer indices. The order of array indices is inverted relative to the Dataset key dimensions, e.g. an Image with key dimensions ‘x’ and ‘y’ can be indexed with image.ndloc[iy, ix] , where iy and ix are integer indices along the y and x dimensions.

Examples:

  • Index value in 2D array:

    dataset.ndloc[3, 1]

  • Slice along y-axis of 2D array:

    dataset.ndloc[2:5, :]

  • Vectorized (non-orthogonal) indexing along x- and y-axes:

    dataset.ndloc[[1, 2, 3], [0, 2, 3]]

options ( options=None , backend=None , clone=True , **kwargs )

Applies options on an object or nested group of objects in a flat format returning a new object with the options applied. If the options are to be set directly on the object a simple format may be used, e.g.:

obj.options(cmap=’viridis’, show_title=False)

If the object is nested the options must be qualified using a type[.group][.label] specification, e.g.:

obj.options(‘Image’, cmap=’viridis’, show_title=False)

or using:

obj.options({‘Image’: dict(cmap=’viridis’, show_title=False)})

If no options are supplied all options on the object will be reset. Disabling clone will modify the object inplace.

opts ( options=None , backend=None , clone=True , **kwargs )

Applies options on an object or nested group of objects in a by options group returning a new object with the options applied. If the options are to be set directly on the object a simple format may be used, e.g.:

obj.opts(style={‘cmap’: ‘viridis’}, plot={‘show_title’: False})

If the object is nested the options must be qualified using a type[.group][.label] specification, e.g.:

obj.opts({‘Image’: {‘plot’: {‘show_title’: False},
‘style’: {‘cmap’: ‘viridis}}})

If no opts are supplied all options on the object will be reset. Disabling clone will modify the object inplace.

params ( parameter_name=None )

Return the Parameters of this class as the dictionary {name: parameter_object}

Includes Parameters from this class and its superclasses.

pprint ( imports=None , prefix=' ' , unknown_value='<?>' , qualify=False , separator='' )

(Experimental) Pretty printed representation that may be evaluated with eval. See pprint() function for more details.

print_param_defaults ( )

Print the default values of all cls’s Parameters.

print_param_values ( )

Print the values of all this object’s Parameters.

range ( dim , data_range=True )

Computes the range of values along a supplied dimension, taking into account the range and soft_range defined on the Dimension object.

reduce ( dimensions=[] , function=None , spreadfn=None , **reduce_map )

Allows reducing the values along one or more key dimension with the supplied function. The dimensions may be supplied as a list and a function to apply or a mapping between the dimensions and functions to apply along each dimension.

reindex ( kdims=None , vdims=None )

Create a new object with a re-ordered set of dimensions. Allows converting key dimensions to value dimensions and vice versa.

relabel ( label=None , group=None , depth=0 )

Assign a new label and/or group to an existing LabelledData object, creating a clone of the object with the new settings.

sample ( samples=[] , closest=True , **kwargs )

Allows sampling of Dataset as an iterator of coordinates matching the key dimensions, returning a new object containing just the selected samples. Alternatively may supply kwargs to sample a coordinate on an object. By default it will attempt to snap to the nearest coordinate if the Element supports it, snapping may be disabled with the closest argument.

script_repr ( imports=[] , prefix=' ' )

Variant of __repr__ designed for generating a runnable script.

select ( selection_specs=None , **selection )

Allows selecting data by the slices, sets and scalar values along a particular dimension. The indices should be supplied as keywords mapping between the selected dimension and value. Additionally selection_specs (taking the form of a list of type.group.label strings, types or functions) may be supplied, which will ensure the selection is only applied if the specs match the selected object.

set_default ( param_name , value )

Set the default value of param_name.

Equivalent to setting param_name on the class.

set_dynamic_time_fn = functools.partial(<function Parameterized.set_dynamic_time_fn>, <class 'holoviews.element.chart.Histogram'>)
set_param = functools.partial(<function Parameterized.set_param>, <class 'holoviews.element.chart.Histogram'>)
shape

Returns the shape of the data.

sort ( by=[] , reverse=False )

Sorts the data by the values along the supplied dimensions.

state_pop ( )

Restore the most recently saved state.

See state_push() for more details.

state_push ( )

Save this instance’s state.

For Parameterized instances, this includes the state of dynamically generated values.

Subclasses that maintain short-term state should additionally save and restore that state using state_push() and state_pop().

Generally, this method is used by operations that need to test something without permanently altering the objects’ state.

table ( datatype=None )

Converts the data Element to a Table, optionally may specify a supported data type. The default data types are ‘numpy’ (for homogeneous data), ‘dataframe’, and ‘dictionary’.

to

Property to create a conversion interface with methods to convert to other Element types.

traverse ( fn , specs=None , full_breadth=True )

Traverses any nested LabelledData object (i.e LabelledData objects containing LabelledData objects), applying the supplied function to each constituent element if the supplied specifications. The output of these function calls are collected and returned in the accumulator list.

If specs is None, all constituent elements are processed. Otherwise, specs must be a list of type.group.label specs, types, and functions.

values

Property to access the Histogram values provided for backward compatibility

verbose ( msg , *args , **kw )

Print msg merged with args as a verbose message.

See Python’s logging module for details of message formatting.

warning ( msg , *args , **kw )

Print msg merged with args as a warning, unless module variable warnings_as_exceptions is True, then raise an Exception containing the arguments.

See Python’s logging module for details of message formatting.

class holoviews.element. Area ( data , kdims=None , vdims=None , **kwargs ) [source]

Bases: holoviews.element.chart.Curve

An Area Element represents the area under a Curve and is specified in the same format as a regular Curve, with the key dimension corresponding to a column of x-values and the value dimension corresponding to a column of y-values. Optionally a second value dimension may be supplied to shade the region between the curves.

param String group ( allow_None=False, basestring=<class ‘str’>, constant=True, default=Area, instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
A string describing the data wrapped by the object.
param String label ( allow_None=False, basestring=<class ‘str’>, constant=True, default=, instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
Optional label describing the data, typically reflecting where or how it was measured. The label should allow a specific measurement or dataset to be referenced for a given group.
param Dict cdims ( allow_None=False, constant=False, default=OrderedDict(), instantiate=True, is_instance=True, pickle_default_value=True, precedence=None, readonly=False )
The constant dimensions defined as a dictionary of Dimension:value pairs providing additional dimension information about the object. Aliased with constant_dimensions.
param List kdims ( allow_None=False, bounds=(1, 2), constant=False, default=[Dimension(‘x’)], instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
The key dimensions of the Chart, determining the number of indexable dimensions.
param List vdims ( allow_None=False, bounds=(1, None), constant=False, default=[Dimension(‘y’)], instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
The value dimensions of the Chart, usually corresponding to a number of dependent variables.
param Tuple extents ( allow_None=False, constant=False, default=(None, None, None, None), instantiate=False, length=4, pickle_default_value=True, precedence=None, readonly=False )
Allows overriding the extents of the Element in 2D space defined as four-tuple defining the (left, bottom, right and top) edges.
param List datatype ( allow_None=False, bounds=(0, None), constant=False, default=[‘dataframe’, ‘dataframe’, ‘dataframe’, ‘dictionary’, ‘grid’, ‘ndelement’, ‘array’, ‘cube’, ‘xarray’, ‘dask’], instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
A priority list of the data types to be used for storage on the .data attribute. If the input supplied to the element constructor cannot be put into the requested format, the next format listed will be used until a suitable format is found (or the data fails to be understood).
add_dimension ( dimension , dim_pos , dim_val , vdim=False , **kwargs )

Create a new object with an additional key dimensions. Requires the dimension name or object, the desired position in the key dimensions and a key value scalar or sequence of the same length as the existing keys.

aggregate ( dimensions=None , function=None , spreadfn=None , **kwargs )

Aggregates over the supplied key dimensions with the defined function.

clone ( data=None , shared_data=True , new_type=None , *args , **overrides )

Returns a clone of the object with matching parameter values containing the specified args and kwargs.

If shared_data is set to True and no data explicitly supplied, the clone will share data with the original. May also supply a new_type, which will inherit all shared parameters.

closest ( coords=[] , **kwargs )

Given a single coordinate or multiple coordinates as a tuple or list of tuples or keyword arguments matching the dimension closest will find the closest actual x/y coordinates. Different Element types should implement this appropriately depending on the space they represent, if the Element does not support snapping raise NotImplementedError.

collapse_data ( data , function=None , kdims=None , **kwargs )

Class method to collapse a list of data matching the data format of the Element type. By implementing this method HoloMap can collapse multiple Elements of the same type. The kwargs are passed to the collapse function. The collapse function must support the numpy style axis selection. Valid function include: np.mean, np.sum, np.product, np.std, scipy.stats.kurtosis etc. Some data backends also require the key dimensions to aggregate over.

ddims

The list of deep dimensions

debug ( msg , *args , **kw )

Print msg merged with args as a debugging statement.

See Python’s logging module for details of message formatting.

defaults ( )

Return {parameter_name:parameter.default} for all non-constant Parameters.

Note that a Parameter for which instantiate==True has its default instantiated.

dframe ( dimensions=None )

Returns the data in the form of a DataFrame. Supplying a list of dimensions filters the dataframe. If the data is already a DataFrame a copy is returned.

dimension_values ( dim , expanded=True , flat=True )

Returns the values along a particular dimension. If unique values are requested will return only unique values.

dimensions ( selection='all' , label=False )

Provides convenient access to Dimensions on nested Dimensioned objects. Dimensions can be selected by their type, i.e. ‘key’ or ‘value’ dimensions. By default ‘all’ dimensions are returned.

force_new_dynamic_value = functools.partial(<function Parameterized.force_new_dynamic_value>, <class 'holoviews.element.chart.Area'>)
get_dimension ( dimension , default=None , strict=False )

Access a Dimension object by name or index. Returns the default value if the dimension is not found and strict is False. If strict is True, a KeyError is raised instead.

get_dimension_index ( dim )

Returns the index of the requested dimension.

get_dimension_type ( dim )

Returns the specified Dimension type if specified or if the dimension_values types are consistent otherwise None is returned.

get_param_values = functools.partial(<function Parameterized.get_param_values>, <class 'holoviews.element.chart.Area'>)
get_value_generator = functools.partial(<function Parameterized.get_value_generator>, <class 'holoviews.element.chart.Area'>)
groupby ( dimensions=[] , container_type=<class 'holoviews.core.spaces.HoloMap'> , group_type=None , dynamic=False , **kwargs )

Return the results of a groupby operation over the specified dimensions as an object of type container_type (expected to be dictionary-like).

Keys vary over the columns (dimensions) and the corresponding values are collections of group_type (e.g an Element, list, tuple) constructed with kwargs (if supplied).

If dynamic is requested container_type is automatically set to a DynamicMap, allowing dynamic exploration of large datasets. If the data does not represent a full cartesian grid of the requested dimensions some Elements will be empty.

hist ( dimension=None , num_bins=20 , bin_range=None , adjoin=True , individually=True , **kwargs )

The hist method generates a histogram to be adjoined to the Element in an AdjointLayout. By default the histogram is computed along the first value dimension of the Element, however any dimension may be selected. The number of bins and the bin_ranges and any kwargs to be passed to the histogram operation may also be supplied.

iloc

Returns an iloc object providing a convenient interface to slice and index into the Dataset using row and column indices. Allow selection by integer index, slice and list of integer indices and boolean arrays.

Examples:

  • Index the first row and column:

    dataset.iloc[0, 0]

  • Select rows 1 and 2 with a slice:

    dataset.iloc[1:3, :]

  • Select with a list of integer coordinates:

    dataset.iloc[[0, 2, 3]]

inspect_value = functools.partial(<function Parameterized.inspect_value>, <class 'holoviews.element.chart.Area'>)
map ( map_fn , specs=None , clone=True )

Recursively replaces elements using a map function when the specification applies.

matches ( spec )

A specification may be a class, a tuple or a string. Equivalent to isinstance if a class is supplied, otherwise matching occurs on type, group and label. These may be supplied as a tuple of strings or as a single string of the form “{type}.{group}.{label}”. Matching may be done on {type} alone, {type}.{group}, or {type}.{group}.{label}. The strings for the type, group, and label will each be sanitized before the match, and so the sanitized versions of those values will need to be provided if the match is to succeed.

message ( msg , *args , **kw )

Print msg merged with args as a message.

See Python’s logging module for details of message formatting.

ndloc

Returns an ndloc object providing nd-array like indexing for gridded datasets. Follows NumPy array indexing conventions, allowing for indexing, slicing and selecting a list of indices on multi-dimensional arrays using integer indices. The order of array indices is inverted relative to the Dataset key dimensions, e.g. an Image with key dimensions ‘x’ and ‘y’ can be indexed with image.ndloc[iy, ix] , where iy and ix are integer indices along the y and x dimensions.

Examples:

  • Index value in 2D array:

    dataset.ndloc[3, 1]

  • Slice along y-axis of 2D array:

    dataset.ndloc[2:5, :]

  • Vectorized (non-orthogonal) indexing along x- and y-axes:

    dataset.ndloc[[1, 2, 3], [0, 2, 3]]

options ( options=None , backend=None , clone=True , **kwargs )

Applies options on an object or nested group of objects in a flat format returning a new object with the options applied. If the options are to be set directly on the object a simple format may be used, e.g.:

obj.options(cmap=’viridis’, show_title=False)

If the object is nested the options must be qualified using a type[.group][.label] specification, e.g.:

obj.options(‘Image’, cmap=’viridis’, show_title=False)

or using:

obj.options({‘Image’: dict(cmap=’viridis’, show_title=False)})

If no options are supplied all options on the object will be reset. Disabling clone will modify the object inplace.

opts ( options=None , backend=None , clone=True , **kwargs )

Applies options on an object or nested group of objects in a by options group returning a new object with the options applied. If the options are to be set directly on the object a simple format may be used, e.g.:

obj.opts(style={‘cmap’: ‘viridis’}, plot={‘show_title’: False})

If the object is nested the options must be qualified using a type[.group][.label] specification, e.g.:

obj.opts({‘Image’: {‘plot’: {‘show_title’: False},
‘style’: {‘cmap’: ‘viridis}}})

If no opts are supplied all options on the object will be reset. Disabling clone will modify the object inplace.

params ( parameter_name=None )

Return the Parameters of this class as the dictionary {name: parameter_object}

Includes Parameters from this class and its superclasses.

pprint ( imports=None , prefix=' ' , unknown_value='<?>' , qualify=False , separator='' )

(Experimental) Pretty printed representation that may be evaluated with eval. See pprint() function for more details.

print_param_defaults ( )

Print the default values of all cls’s Parameters.

print_param_values ( )

Print the values of all this object’s Parameters.

range ( dim , data_range=True )

Computes the range of values along a supplied dimension, taking into account the range and soft_range defined on the Dimension object.

reduce ( dimensions=[] , function=None , spreadfn=None , **reduce_map )

Allows reducing the values along one or more key dimension with the supplied function. The dimensions may be supplied as a list and a function to apply or a mapping between the dimensions and functions to apply along each dimension.

reindex ( kdims=None , vdims=None )

Create a new object with a re-ordered set of dimensions. Allows converting key dimensions to value dimensions and vice versa.

relabel ( label=None , group=None , depth=0 )

Assign a new label and/or group to an existing LabelledData object, creating a clone of the object with the new settings.

sample ( samples=[] , closest=True , **kwargs )

Allows sampling of Dataset as an iterator of coordinates matching the key dimensions, returning a new object containing just the selected samples. Alternatively may supply kwargs to sample a coordinate on an object. By default it will attempt to snap to the nearest coordinate if the Element supports it, snapping may be disabled with the closest argument.

script_repr ( imports=[] , prefix=' ' )

Variant of __repr__ designed for generating a runnable script.

select ( selection_specs=None , **selection )

Allows selecting data by the slices, sets and scalar values along a particular dimension. The indices should be supplied as keywords mapping between the selected dimension and value. Additionally selection_specs (taking the form of a list of type.group.label strings, types or functions) may be supplied, which will ensure the selection is only applied if the specs match the selected object.

set_default ( param_name , value )

Set the default value of param_name.

Equivalent to setting param_name on the class.

set_dynamic_time_fn = functools.partial(<function Parameterized.set_dynamic_time_fn>, <class 'holoviews.element.chart.Area'>)
set_param = functools.partial(<function Parameterized.set_param>, <class 'holoviews.element.chart.Area'>)
shape

Returns the shape of the data.

sort ( by=[] , reverse=False )

Sorts the data by the values along the supplied dimensions.

classmethod stack ( areas ) [source]

Stacks an (Nd)Overlay of Area or Curve Elements by offsetting their baselines. To stack a HoloMap or DynamicMap use the map method.

state_pop ( )

Restore the most recently saved state.

See state_push() for more details.

state_push ( )

Save this instance’s state.

For Parameterized instances, this includes the state of dynamically generated values.

Subclasses that maintain short-term state should additionally save and restore that state using state_push() and state_pop().

Generally, this method is used by operations that need to test something without permanently altering the objects’ state.

table ( datatype=None )

Converts the data Element to a Table, optionally may specify a supported data type. The default data types are ‘numpy’ (for homogeneous data), ‘dataframe’, and ‘dictionary’.

to

Property to create a conversion interface with methods to convert to other Element types.

traverse ( fn , specs=None , full_breadth=True )

Traverses any nested LabelledData object (i.e LabelledData objects containing LabelledData objects), applying the supplied function to each constituent element if the supplied specifications. The output of these function calls are collected and returned in the accumulator list.

If specs is None, all constituent elements are processed. Otherwise, specs must be a list of type.group.label specs, types, and functions.

verbose ( msg , *args , **kw )

Print msg merged with args as a verbose message.

See Python’s logging module for details of message formatting.

warning ( msg , *args , **kw )

Print msg merged with args as a warning, unless module variable warnings_as_exceptions is True, then raise an Exception containing the arguments.

See Python’s logging module for details of message formatting.

class holoviews.element. TriMesh ( data , kdims=None , vdims=None , **params ) [source]

Bases: holoviews.element.graphs.Graph

A TriMesh represents a mesh of triangles represented as the simplices and nodes. The simplices represent a indices into the nodes array. The mesh therefore follows a datastructure very similar to a graph, with the abstract connectivity between nodes stored on the TriMesh element itself, the node positions stored on a Nodes element and the concrete paths making up each triangle generated when required by accessing the edgepaths.

Unlike a Graph each simplex is represented as the node indices of the three corners of each triangle.

param String group ( allow_None=False, basestring=<class ‘str’>, constant=True, default=TriMesh, instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
A string describing the data wrapped by the object.
param String label ( allow_None=False, basestring=<class ‘str’>, constant=True, default=, instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
Optional label describing the data, typically reflecting where or how it was measured. The label should allow a specific measurement or dataset to be referenced for a given group.
param Dict cdims ( allow_None=False, constant=False, default=OrderedDict(), instantiate=True, is_instance=True, pickle_default_value=True, precedence=None, readonly=False )
The constant dimensions defined as a dictionary of Dimension:value pairs providing additional dimension information about the object. Aliased with constant_dimensions.
param List kdims ( allow_None=False, bounds=(3, 3), constant=False, default=[‘node1’, ‘node2’, ‘node3’], instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
Dimensions declaring the node indices of each triangle.
param List vdims ( allow_None=False, bounds=(0, None), constant=True, default=[], instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
The value dimensions defined as the list of dimensions used to describe the components of the data. If multiple value dimensions are supplied, a particular value dimension may be indexed by name after the key dimensions. Aliased with value_dimensions.
param Tuple extents ( allow_None=False, constant=False, default=(None, None, None, None), instantiate=False, length=4, pickle_default_value=True, precedence=None, readonly=False )
Allows overriding the extents of the Element in 2D space defined as four-tuple defining the (left, bottom, right and top) edges.
param List datatype ( allow_None=False, bounds=(0, None), constant=False, default=[‘dataframe’, ‘dataframe’, ‘dataframe’, ‘dictionary’, ‘grid’, ‘ndelement’, ‘array’, ‘cube’, ‘xarray’, ‘dask’], instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
A priority list of the data types to be used for storage on the .data attribute. If the input supplied to the element constructor cannot be put into the requested format, the next format listed will be used until a suitable format is found (or the data fails to be understood).
add_dimension ( dimension , dim_pos , dim_val , vdim=False , **kwargs )

Create a new object with an additional key dimensions. Requires the dimension name or object, the desired position in the key dimensions and a key value scalar or sequence of the same length as the existing keys.

aggregate ( dimensions=None , function=None , spreadfn=None , **kwargs )

Aggregates over the supplied key dimensions with the defined function.

closest ( coords=[] , **kwargs )

Given a single coordinate or multiple coordinates as a tuple or list of tuples or keyword arguments matching the dimension closest will find the closest actual x/y coordinates. Different Element types should implement this appropriately depending on the space they represent, if the Element does not support snapping raise NotImplementedError.

collapse_data ( data , function=None , kdims=None , **kwargs )

Class method to collapse a list of data matching the data format of the Element type. By implementing this method HoloMap can collapse multiple Elements of the same type. The kwargs are passed to the collapse function. The collapse function must support the numpy style axis selection. Valid function include: np.mean, np.sum, np.product, np.std, scipy.stats.kurtosis etc. Some data backends also require the key dimensions to aggregate over.

ddims

The list of deep dimensions

debug ( msg , *args , **kw )

Print msg merged with args as a debugging statement.

See Python’s logging module for details of message formatting.

defaults ( )

Return {parameter_name:parameter.default} for all non-constant Parameters.

Note that a Parameter for which instantiate==True has its default instantiated.

dframe ( dimensions=None )

Returns the data in the form of a DataFrame. Supplying a list of dimensions filters the dataframe. If the data is already a DataFrame a copy is returned.

dimension_values ( dim , expanded=True , flat=True )

Returns the values along a particular dimension. If unique values are requested will return only unique values.

edge_type

alias of EdgePaths

edgepaths

Returns the EdgePaths by generating a triangle for each simplex.

force_new_dynamic_value = functools.partial(<function Parameterized.force_new_dynamic_value>, <class 'holoviews.element.graphs.TriMesh'>)
from_networkx ( G , layout_function , nodes=None , **kwargs )

Generate a HoloViews Graph from a networkx.Graph object and networkx layout function. Any keyword arguments will be passed to the layout function. By default it will extract all node and edge attributes from the networkx.Graph but explicit node information may also be supplied.

classmethod from_vertices ( data ) [source]

Uses Delauney triangulation to compute triangle simplices for each point.

get_dimension ( dimension , default=None , strict=False )

Access a Dimension object by name or index. Returns the default value if the dimension is not found and strict is False. If strict is True, a KeyError is raised instead.

get_dimension_index ( dim )

Returns the index of the requested dimension.

get_dimension_type ( dim )

Returns the specified Dimension type if specified or if the dimension_values types are consistent otherwise None is returned.

get_param_values = functools.partial(<function Parameterized.get_param_values>, <class 'holoviews.element.graphs.TriMesh'>)
get_value_generator = functools.partial(<function Parameterized.get_value_generator>, <class 'holoviews.element.graphs.TriMesh'>)
groupby ( dimensions=[] , container_type=<class 'holoviews.core.spaces.HoloMap'> , group_type=None , dynamic=False , **kwargs )

Return the results of a groupby operation over the specified dimensions as an object of type container_type (expected to be dictionary-like).

Keys vary over the columns (dimensions) and the corresponding values are collections of group_type (e.g an Element, list, tuple) constructed with kwargs (if supplied).

If dynamic is requested container_type is automatically set to a DynamicMap, allowing dynamic exploration of large datasets. If the data does not represent a full cartesian grid of the requested dimensions some Elements will be empty.

hist ( dimension=None , num_bins=20 , bin_range=None , adjoin=True , individually=True , **kwargs )

The hist method generates a histogram to be adjoined to the Element in an AdjointLayout. By default the histogram is computed along the first value dimension of the Element, however any dimension may be selected. The number of bins and the bin_ranges and any kwargs to be passed to the histogram operation may also be supplied.

iloc

Returns an iloc object providing a convenient interface to slice and index into the Dataset using row and column indices. Allow selection by integer index, slice and list of integer indices and boolean arrays.

Examples:

  • Index the first row and column:

    dataset.iloc[0, 0]

  • Select rows 1 and 2 with a slice:

    dataset.iloc[1:3, :]

  • Select with a list of integer coordinates:

    dataset.iloc[[0, 2, 3]]

inspect_value = functools.partial(<function Parameterized.inspect_value>, <class 'holoviews.element.graphs.TriMesh'>)
map ( map_fn , specs=None , clone=True )

Recursively replaces elements using a map function when the specification applies.

matches ( spec )

A specification may be a class, a tuple or a string. Equivalent to isinstance if a class is supplied, otherwise matching occurs on type, group and label. These may be supplied as a tuple of strings or as a single string of the form “{type}.{group}.{label}”. Matching may be done on {type} alone, {type}.{group}, or {type}.{group}.{label}. The strings for the type, group, and label will each be sanitized before the match, and so the sanitized versions of those values will need to be provided if the match is to succeed.

message ( msg , *args , **kw )

Print msg merged with args as a message.

See Python’s logging module for details of message formatting.

ndloc

Returns an ndloc object providing nd-array like indexing for gridded datasets. Follows NumPy array indexing conventions, allowing for indexing, slicing and selecting a list of indices on multi-dimensional arrays using integer indices. The order of array indices is inverted relative to the Dataset key dimensions, e.g. an Image with key dimensions ‘x’ and ‘y’ can be indexed with image.ndloc[iy, ix] , where iy and ix are integer indices along the y and x dimensions.

Examples:

  • Index value in 2D array:

    dataset.ndloc[3, 1]

  • Slice along y-axis of 2D array:

    dataset.ndloc[2:5, :]

  • Vectorized (non-orthogonal) indexing along x- and y-axes:

    dataset.ndloc[[1, 2, 3], [0, 2, 3]]

node_type

alias of Nodes

nodes

Computes the node positions the first time they are requested if no explicit node information was supplied.

options ( options=None , backend=None , clone=True , **kwargs )

Applies options on an object or nested group of objects in a flat format returning a new object with the options applied. If the options are to be set directly on the object a simple format may be used, e.g.:

obj.options(cmap=’viridis’, show_title=False)

If the object is nested the options must be qualified using a type[.group][.label] specification, e.g.:

obj.options(‘Image’, cmap=’viridis’, show_title=False)

or using:

obj.options({‘Image’: dict(cmap=’viridis’, show_title=False)})

If no options are supplied all options on the object will be reset. Disabling clone will modify the object inplace.

opts ( options=None , backend=None , clone=True , **kwargs )

Applies options on an object or nested group of objects in a by options group returning a new object with the options applied. If the options are to be set directly on the object a simple format may be used, e.g.:

obj.opts(style={‘cmap’: ‘viridis’}, plot={‘show_title’: False})

If the object is nested the options must be qualified using a type[.group][.label] specification, e.g.:

obj.opts({‘Image’: {‘plot’: {‘show_title’: False},
‘style’: {‘cmap’: ‘viridis}}})

If no opts are supplied all options on the object will be reset. Disabling clone will modify the object inplace.

params ( parameter_name=None )

Return the Parameters of this class as the dictionary {name: parameter_object}

Includes Parameters from this class and its superclasses.

point_type

alias of holoviews.element.chart.Points

pprint ( imports=None , prefix=' ' , unknown_value='<?>' , qualify=False , separator='' )

(Experimental) Pretty printed representation that may be evaluated with eval. See pprint() function for more details.

print_param_defaults ( )

Print the default values of all cls’s Parameters.

print_param_values ( )

Print the values of all this object’s Parameters.

reduce ( dimensions=[] , function=None , spreadfn=None , **reduce_map )

Allows reducing the values along one or more key dimension with the supplied function. The dimensions may be supplied as a list and a function to apply or a mapping between the dimensions and functions to apply along each dimension.

reindex ( kdims=None , vdims=None )

Create a new object with a re-ordered set of dimensions. Allows converting key dimensions to value dimensions and vice versa.

relabel ( label=None , group=None , depth=0 )

Assign a new label and/or group to an existing LabelledData object, creating a clone of the object with the new settings.

sample ( samples=[] , closest=True , **kwargs )

Allows sampling of Dataset as an iterator of coordinates matching the key dimensions, returning a new object containing just the selected samples. Alternatively may supply kwargs to sample a coordinate on an object. By default it will attempt to snap to the nearest coordinate if the Element supports it, snapping may be disabled with the closest argument.

script_repr ( imports=[] , prefix=' ' )

Variant of __repr__ designed for generating a runnable script.

select ( selection_specs=None , **selection ) [source]

Allows selecting data by the slices, sets and scalar values along a particular dimension. The indices should be supplied as keywords mapping between the selected dimension and value. Additionally selection_specs (taking the form of a list of type.group.label strings, types or functions) may be supplied, which will ensure the selection is only applied if the specs match the selected object.

set_default ( param_name , value )

Set the default value of param_name.

Equivalent to setting param_name on the class.

set_dynamic_time_fn = functools.partial(<function Parameterized.set_dynamic_time_fn>, <class 'holoviews.element.graphs.TriMesh'>)
set_param = functools.partial(<function Parameterized.set_param>, <class 'holoviews.element.graphs.TriMesh'>)
shape

Returns the shape of the data.

sort ( by=[] , reverse=False )

Sorts the data by the values along the supplied dimensions.

state_pop ( )

Restore the most recently saved state.

See state_push() for more details.

state_push ( )

Save this instance’s state.

For Parameterized instances, this includes the state of dynamically generated values.

Subclasses that maintain short-term state should additionally save and restore that state using state_push() and state_pop().

Generally, this method is used by operations that need to test something without permanently altering the objects’ state.

table ( datatype=None )

Converts the data Element to a Table, optionally may specify a supported data type. The default data types are ‘numpy’ (for homogeneous data), ‘dataframe’, and ‘dictionary’.

to

Property to create a conversion interface with methods to convert to other Element types.

traverse ( fn , specs=None , full_breadth=True )

Traverses any nested LabelledData object (i.e LabelledData objects containing LabelledData objects), applying the supplied function to each constituent element if the supplied specifications. The output of these function calls are collected and returned in the accumulator list.

If specs is None, all constituent elements are processed. Otherwise, specs must be a list of type.group.label specs, types, and functions.

verbose ( msg , *args , **kw )

Print msg merged with args as a verbose message.

See Python’s logging module for details of message formatting.

warning ( msg , *args , **kw )

Print msg merged with args as a warning, unless module variable warnings_as_exceptions is True, then raise an Exception containing the arguments.

See Python’s logging module for details of message formatting.

class holoviews.element. Labels ( data , kdims=None , vdims=None , **kwargs ) [source]

Bases: holoviews.core.data.Dataset , holoviews.core.element.Element2D

Labels represents a collection of text labels associated with 2D coordinates. Unlike the Text annotation, Labels is a Dataset type which allows drawing vectorized labels from tabular or gridded data.

param String group ( allow_None=False, basestring=<class ‘str’>, constant=True, default=Labels, instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
A string describing the data wrapped by the object.
param String label ( allow_None=False, basestring=<class ‘str’>, constant=True, default=, instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
Optional label describing the data, typically reflecting where or how it was measured. The label should allow a specific measurement or dataset to be referenced for a given group.
param Dict cdims ( allow_None=False, constant=False, default=OrderedDict(), instantiate=True, is_instance=True, pickle_default_value=True, precedence=None, readonly=False )
The constant dimensions defined as a dictionary of Dimension:value pairs providing additional dimension information about the object. Aliased with constant_dimensions.
param List kdims ( allow_None=False, bounds=(2, 2), constant=True, default=[Dimension(‘x’), Dimension(‘y’)], instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
The label of the x- and y-dimension of the Labels element in form of a string or dimension object.
param List vdims ( allow_None=False, bounds=(1, None), constant=False, default=[Dimension(‘Label’)], instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
Defines the value dimension corresponding to the label text.
param Tuple extents ( allow_None=False, constant=False, default=(None, None, None, None), instantiate=False, length=4, pickle_default_value=True, precedence=None, readonly=False )
Allows overriding the extents of the Element in 2D space defined as four-tuple defining the (left, bottom, right and top) edges.
param List datatype ( allow_None=False, bounds=(0, None), constant=False, default=[‘dataframe’, ‘dataframe’, ‘dataframe’, ‘dictionary’, ‘grid’, ‘ndelement’, ‘array’, ‘cube’, ‘xarray’, ‘dask’], instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
A priority list of the data types to be used for storage on the .data attribute. If the input supplied to the element constructor cannot be put into the requested format, the next format listed will be used until a suitable format is found (or the data fails to be understood).
add_dimension ( dimension , dim_pos , dim_val , vdim=False , **kwargs )

Create a new object with an additional key dimensions. Requires the dimension name or object, the desired position in the key dimensions and a key value scalar or sequence of the same length as the existing keys.

aggregate ( dimensions=None , function=None , spreadfn=None , **kwargs )

Aggregates over the supplied key dimensions with the defined function.

clone ( data=None , shared_data=True , new_type=None , *args , **overrides )

Returns a clone of the object with matching parameter values containing the specified args and kwargs.

If shared_data is set to True and no data explicitly supplied, the clone will share data with the original. May also supply a new_type, which will inherit all shared parameters.

closest ( coords=[] , **kwargs )

Given a single coordinate or multiple coordinates as a tuple or list of tuples or keyword arguments matching the dimension closest will find the closest actual x/y coordinates. Different Element types should implement this appropriately depending on the space they represent, if the Element does not support snapping raise NotImplementedError.

collapse_data ( data , function=None , kdims=None , **kwargs )

Class method to collapse a list of data matching the data format of the Element type. By implementing this method HoloMap can collapse multiple Elements of the same type. The kwargs are passed to the collapse function. The collapse function must support the numpy style axis selection. Valid function include: np.mean, np.sum, np.product, np.std, scipy.stats.kurtosis etc. Some data backends also require the key dimensions to aggregate over.

ddims

The list of deep dimensions

debug ( msg , *args , **kw )

Print msg merged with args as a debugging statement.

See Python’s logging module for details of message formatting.

defaults ( )

Return {parameter_name:parameter.default} for all non-constant Parameters.

Note that a Parameter for which instantiate==True has its default instantiated.

dframe ( dimensions=None )

Returns the data in the form of a DataFrame. Supplying a list of dimensions filters the dataframe. If the data is already a DataFrame a copy is returned.

dimension_values ( dim , expanded=True , flat=True )

Returns the values along a particular dimension. If unique values are requested will return only unique values.

dimensions ( selection='all' , label=False )

Provides convenient access to Dimensions on nested Dimensioned objects. Dimensions can be selected by their type, i.e. ‘key’ or ‘value’ dimensions. By default ‘all’ dimensions are returned.

force_new_dynamic_value = functools.partial(<function Parameterized.force_new_dynamic_value>, <class 'holoviews.element.annotation.Labels'>)
get_dimension ( dimension , default=None , strict=False )

Access a Dimension object by name or index. Returns the default value if the dimension is not found and strict is False. If strict is True, a KeyError is raised instead.

get_dimension_index ( dim )

Returns the index of the requested dimension.

get_dimension_type ( dim )

Returns the specified Dimension type if specified or if the dimension_values types are consistent otherwise None is returned.

get_param_values = functools.partial(<function Parameterized.get_param_values>, <class 'holoviews.element.annotation.Labels'>)
get_value_generator = functools.partial(<function Parameterized.get_value_generator>, <class 'holoviews.element.annotation.Labels'>)
groupby ( dimensions=[] , container_type=<class 'holoviews.core.spaces.HoloMap'> , group_type=None , dynamic=False , **kwargs )

Return the results of a groupby operation over the specified dimensions as an object of type container_type (expected to be dictionary-like).

Keys vary over the columns (dimensions) and the corresponding values are collections of group_type (e.g an Element, list, tuple) constructed with kwargs (if supplied).

If dynamic is requested container_type is automatically set to a DynamicMap, allowing dynamic exploration of large datasets. If the data does not represent a full cartesian grid of the requested dimensions some Elements will be empty.

hist ( dimension=None , num_bins=20 , bin_range=None , adjoin=True , individually=True , **kwargs )

The hist method generates a histogram to be adjoined to the Element in an AdjointLayout. By default the histogram is computed along the first value dimension of the Element, however any dimension may be selected. The number of bins and the bin_ranges and any kwargs to be passed to the histogram operation may also be supplied.

iloc

Returns an iloc object providing a convenient interface to slice and index into the Dataset using row and column indices. Allow selection by integer index, slice and list of integer indices and boolean arrays.

Examples:

  • Index the first row and column:

    dataset.iloc[0, 0]

  • Select rows 1 and 2 with a slice:

    dataset.iloc[1:3, :]

  • Select with a list of integer coordinates:

    dataset.iloc[[0, 2, 3]]

inspect_value = functools.partial(<function Parameterized.inspect_value>, <class 'holoviews.element.annotation.Labels'>)
map ( map_fn , specs=None , clone=True )

Recursively replaces elements using a map function when the specification applies.

matches ( spec )

A specification may be a class, a tuple or a string. Equivalent to isinstance if a class is supplied, otherwise matching occurs on type, group and label. These may be supplied as a tuple of strings or as a single string of the form “{type}.{group}.{label}”. Matching may be done on {type} alone, {type}.{group}, or {type}.{group}.{label}. The strings for the type, group, and label will each be sanitized before the match, and so the sanitized versions of those values will need to be provided if the match is to succeed.

message ( msg , *args , **kw )

Print msg merged with args as a message.

See Python’s logging module for details of message formatting.

ndloc

Returns an ndloc object providing nd-array like indexing for gridded datasets. Follows NumPy array indexing conventions, allowing for indexing, slicing and selecting a list of indices on multi-dimensional arrays using integer indices. The order of array indices is inverted relative to the Dataset key dimensions, e.g. an Image with key dimensions ‘x’ and ‘y’ can be indexed with image.ndloc[iy, ix] , where iy and ix are integer indices along the y and x dimensions.

Examples:

  • Index value in 2D array:

    dataset.ndloc[3, 1]

  • Slice along y-axis of 2D array:

    dataset.ndloc[2:5, :]

  • Vectorized (non-orthogonal) indexing along x- and y-axes:

    dataset.ndloc[[1, 2, 3], [0, 2, 3]]

options ( options=None , backend=None , clone=True , **kwargs )

Applies options on an object or nested group of objects in a flat format returning a new object with the options applied. If the options are to be set directly on the object a simple format may be used, e.g.:

obj.options(cmap=’viridis’, show_title=False)

If the object is nested the options must be qualified using a type[.group][.label] specification, e.g.:

obj.options(‘Image’, cmap=’viridis’, show_title=False)

or using:

obj.options({‘Image’: dict(cmap=’viridis’, show_title=False)})

If no options are supplied all options on the object will be reset. Disabling clone will modify the object inplace.

opts ( options=None , backend=None , clone=True , **kwargs )

Applies options on an object or nested group of objects in a by options group returning a new object with the options applied. If the options are to be set directly on the object a simple format may be used, e.g.:

obj.opts(style={‘cmap’: ‘viridis’}, plot={‘show_title’: False})

If the object is nested the options must be qualified using a type[.group][.label] specification, e.g.:

obj.opts({‘Image’: {‘plot’: {‘show_title’: False},
‘style’: {‘cmap’: ‘viridis}}})

If no opts are supplied all options on the object will be reset. Disabling clone will modify the object inplace.

params ( parameter_name=None )

Return the Parameters of this class as the dictionary {name: parameter_object}

Includes Parameters from this class and its superclasses.

pprint ( imports=None , prefix=' ' , unknown_value='<?>' , qualify=False , separator='' )

(Experimental) Pretty printed representation that may be evaluated with eval. See pprint() function for more details.

print_param_defaults ( )

Print the default values of all cls’s Parameters.

print_param_values ( )

Print the values of all this object’s Parameters.

range ( dim , data_range=True )

Computes the range of values along a supplied dimension, taking into account the range and soft_range defined on the Dimension object.

reduce ( dimensions=[] , function=None , spreadfn=None , **reduce_map )

Allows reducing the values along one or more key dimension with the supplied function. The dimensions may be supplied as a list and a function to apply or a mapping between the dimensions and functions to apply along each dimension.

reindex ( kdims=None , vdims=None )

Create a new object with a re-ordered set of dimensions. Allows converting key dimensions to value dimensions and vice versa.

relabel ( label=None , group=None , depth=0 )

Assign a new label and/or group to an existing LabelledData object, creating a clone of the object with the new settings.

sample ( samples=[] , closest=True , **kwargs )

Allows sampling of Dataset as an iterator of coordinates matching the key dimensions, returning a new object containing just the selected samples. Alternatively may supply kwargs to sample a coordinate on an object. By default it will attempt to snap to the nearest coordinate if the Element supports it, snapping may be disabled with the closest argument.

script_repr ( imports=[] , prefix=' ' )

Variant of __repr__ designed for generating a runnable script.

select ( selection_specs=None , **selection )

Allows selecting data by the slices, sets and scalar values along a particular dimension. The indices should be supplied as keywords mapping between the selected dimension and value. Additionally selection_specs (taking the form of a list of type.group.label strings, types or functions) may be supplied, which will ensure the selection is only applied if the specs match the selected object.

set_default ( param_name , value )

Set the default value of param_name.

Equivalent to setting param_name on the class.

set_dynamic_time_fn = functools.partial(<function Parameterized.set_dynamic_time_fn>, <class 'holoviews.element.annotation.Labels'>)
set_param = functools.partial(<function Parameterized.set_param>, <class 'holoviews.element.annotation.Labels'>)
shape

Returns the shape of the data.

sort ( by=[] , reverse=False )

Sorts the data by the values along the supplied dimensions.

state_pop ( )

Restore the most recently saved state.

See state_push() for more details.

state_push ( )

Save this instance’s state.

For Parameterized instances, this includes the state of dynamically generated values.

Subclasses that maintain short-term state should additionally save and restore that state using state_push() and state_pop().

Generally, this method is used by operations that need to test something without permanently altering the objects’ state.

table ( datatype=None )

Converts the data Element to a Table, optionally may specify a supported data type. The default data types are ‘numpy’ (for homogeneous data), ‘dataframe’, and ‘dictionary’.

to

Property to create a conversion interface with methods to convert to other Element types.

traverse ( fn , specs=None , full_breadth=True )

Traverses any nested LabelledData object (i.e LabelledData objects containing LabelledData objects), applying the supplied function to each constituent element if the supplied specifications. The output of these function calls are collected and returned in the accumulator list.

If specs is None, all constituent elements are processed. Otherwise, specs must be a list of type.group.label specs, types, and functions.

verbose ( msg , *args , **kw )

Print msg merged with args as a verbose message.

See Python’s logging module for details of message formatting.

warning ( msg , *args , **kw )

Print msg merged with args as a warning, unless module variable warnings_as_exceptions is True, then raise an Exception containing the arguments.

See Python’s logging module for details of message formatting.

class holoviews.element. RGB ( data , kdims=None , vdims=None , **params ) [source]

Bases: holoviews.element.raster.Image

An RGB element is a Image containing channel data for the the red, green, blue and (optionally) the alpha channels. The values of each channel must be in the range 0.0 to 1.0.

In input array may have a shape of NxMx4 or NxMx3. In the latter case, the defined alpha dimension parameter is appended to the list of value dimensions.

param String group ( allow_None=False, basestring=<class ‘str’>, constant=True, default=RGB, instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
A string describing the data wrapped by the object.
param String label ( allow_None=False, basestring=<class ‘str’>, constant=True, default=, instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
Optional label describing the data, typically reflecting where or how it was measured. The label should allow a specific measurement or dataset to be referenced for a given group.
param Dict cdims ( allow_None=False, constant=False, default=OrderedDict(), instantiate=True, is_instance=True, pickle_default_value=True, precedence=None, readonly=False )
The constant dimensions defined as a dictionary of Dimension:value pairs providing additional dimension information about the object. Aliased with constant_dimensions.
param List kdims ( allow_None=False, bounds=(2, 2), constant=True, default=[Dimension(‘x’), Dimension(‘y’)], instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
The label of the x- and y-dimension of the Raster in the form of a string or dimension object.
param List vdims ( allow_None=False, bounds=(3, 4), constant=False, default=[Dimension(‘R’), Dimension(‘G’), Dimension(‘B’)], instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
The dimension description of the data held in the matrix. If an alpha channel is supplied, the defined alpha_dimension is automatically appended to this list.
param Tuple extents ( allow_None=False, constant=False, default=(None, None, None, None), instantiate=False, length=4, pickle_default_value=True, precedence=None, readonly=False )
Allows overriding the extents of the Element in 2D space defined as four-tuple defining the (left, bottom, right and top) edges.
param List datatype ( allow_None=False, bounds=(0, None), constant=False, default=[‘image’, ‘grid’, ‘xarray’, ‘cube’, ‘dataframe’, ‘dictionary’], instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
A priority list of the data types to be used for storage on the .data attribute. If the input supplied to the element constructor cannot be put into the requested format, the next format listed will be used until a suitable format is found (or the data fails to be understood).
param ClassSelector bounds ( allow_None=False, constant=False, default=BoundingBox(radius=0.5), instantiate=True, is_instance=True, pickle_default_value=True, precedence=None, readonly=False )
The bounding region in sheet coordinates containing the data.
param Number rtol ( allow_None=True, bounds=None, constant=False, default=None, inclusive_bounds=(True, True), instantiate=False, pickle_default_value=True, precedence=None, readonly=False, softbounds=None, time_dependent=False, time_fn=<Time Time00001> )
The tolerance used to enforce regular sampling for regular, gridded data where regular sampling is expected. Expressed as the maximal allowable sampling difference between sample locations.
param ClassSelector alpha_dimension ( allow_None=False, constant=False, default=A, instantiate=False, is_instance=True, pickle_default_value=True, precedence=None, readonly=False )
The alpha dimension definition to add the value dimensions if an alpha channel is supplied.
add_dimension ( dimension , dim_pos , dim_val , vdim=False , **kwargs )

Create a new object with an additional key dimensions. Requires the dimension name or object, the desired position in the key dimensions and a key value scalar or sequence of the same length as the existing keys.

clone ( data=None , shared_data=True , new_type=None , *args , **overrides )

Returns a clone of the object with matching parameter values containing the specified args and kwargs.

If shared_data is set to True and no data explicitly supplied, the clone will share data with the original. May also supply a new_type, which will inherit all shared parameters.

closest ( coords=[] , **kwargs )

Given a single coordinate or multiple coordinates as a tuple or list of tuples or keyword arguments matching the dimension closest will find the closest actual x/y coordinates.

closest_cell_center ( x , y )

Given arbitrary sheet coordinates, return the sheet coordinates of the center of the closest unit.

ddims

The list of deep dimensions

debug ( msg , *args , **kw )

Print msg merged with args as a debugging statement.

See Python’s logging module for details of message formatting.

defaults ( )

Return {parameter_name:parameter.default} for all non-constant Parameters.

Note that a Parameter for which instantiate==True has its default instantiated.

dframe ( dimensions=None )

Returns the data in the form of a DataFrame. Supplying a list of dimensions filters the dataframe. If the data is already a DataFrame a copy is returned.

dimension_values ( dim , expanded=True , flat=True )

Returns the values along a particular dimension. If unique values are requested will return only unique values.

dimensions ( selection='all' , label=False )

Provides convenient access to Dimensions on nested Dimensioned objects. Dimensions can be selected by their type, i.e. ‘key’ or ‘value’ dimensions. By default ‘all’ dimensions are returned.

force_new_dynamic_value = functools.partial(<function Parameterized.force_new_dynamic_value>, <class 'holoviews.element.raster.RGB'>)
get_dimension ( dimension , default=None , strict=False )

Access a Dimension object by name or index. Returns the default value if the dimension is not found and strict is False. If strict is True, a KeyError is raised instead.

get_dimension_index ( dim )

Returns the index of the requested dimension.

get_dimension_type ( dim )

Returns the specified Dimension type if specified or if the dimension_values types are consistent otherwise None is returned.

get_param_values = functools.partial(<function Parameterized.get_param_values>, <class 'holoviews.element.raster.RGB'>)
get_value_generator = functools.partial(<function Parameterized.get_value_generator>, <class 'holoviews.element.raster.RGB'>)
groupby ( dimensions=[] , container_type=<class 'holoviews.core.spaces.HoloMap'> , group_type=None , dynamic=False , **kwargs )

Return the results of a groupby operation over the specified dimensions as an object of type container_type (expected to be dictionary-like).

Keys vary over the columns (dimensions) and the corresponding values are collections of group_type (e.g an Element, list, tuple) constructed with kwargs (if supplied).

If dynamic is requested container_type is automatically set to a DynamicMap, allowing dynamic exploration of large datasets. If the data does not represent a full cartesian grid of the requested dimensions some Elements will be empty.

hist ( dimension=None , num_bins=20 , bin_range=None , adjoin=True , individually=True , **kwargs )

The hist method generates a histogram to be adjoined to the Element in an AdjointLayout. By default the histogram is computed along the first value dimension of the Element, however any dimension may be selected. The number of bins and the bin_ranges and any kwargs to be passed to the histogram operation may also be supplied.

iloc

Returns an iloc object providing a convenient interface to slice and index into the Dataset using row and column indices. Allow selection by integer index, slice and list of integer indices and boolean arrays.

Examples:

  • Index the first row and column:

    dataset.iloc[0, 0]

  • Select rows 1 and 2 with a slice:

    dataset.iloc[1:3, :]

  • Select with a list of integer coordinates:

    dataset.iloc[[0, 2, 3]]

inspect_value = functools.partial(<function Parameterized.inspect_value>, <class 'holoviews.element.raster.RGB'>)
classmethod load_image ( filename , height=1 , array=False , bounds=None , bare=False , **kwargs ) [source]

Returns an raster element or raw numpy array from a PNG image file, using matplotlib.

The specified height determines the bounds of the raster object in sheet coordinates: by default the height is 1 unit with the width scaled appropriately by the image aspect ratio.

Note that as PNG images are encoded as RGBA, the red component maps to the first channel, the green component maps to the second component etc. For RGB elements, this mapping is trivial but may be important for subclasses e.g. for HSV elements.

Setting bare=True will apply options disabling axis labels displaying just the bare image. Any additional keyword arguments will be passed to the Image object.

map ( map_fn , specs=None , clone=True )

Recursively replaces elements using a map function when the specification applies.

matches ( spec )

A specification may be a class, a tuple or a string. Equivalent to isinstance if a class is supplied, otherwise matching occurs on type, group and label. These may be supplied as a tuple of strings or as a single string of the form “{type}.{group}.{label}”. Matching may be done on {type} alone, {type}.{group}, or {type}.{group}.{label}. The strings for the type, group, and label will each be sanitized before the match, and so the sanitized versions of those values will need to be provided if the match is to succeed.

matrix2sheet ( float_row , float_col )

Convert a floating-point location (float_row,float_col) in matrix coordinates to its corresponding location (x,y) in sheet coordinates.

Valid for scalar or array float_row and float_col.

Inverse of sheet2matrix().

matrixidx2sheet ( row , col )

Return (x,y) where x and y are the floating point coordinates of the center of the given matrix cell (row,col). If the matrix cell represents a 0.2 by 0.2 region, then the center location returned would be 0.1,0.1.

NOTE: This is NOT the strict mathematical inverse of sheet2matrixidx(), because sheet2matrixidx() discards all but the integer portion of the continuous matrix coordinate.

Valid only for scalar or array row and col.

message ( msg , *args , **kw )

Print msg merged with args as a message.

See Python’s logging module for details of message formatting.

ndloc

Returns an ndloc object providing nd-array like indexing for gridded datasets. Follows NumPy array indexing conventions, allowing for indexing, slicing and selecting a list of indices on multi-dimensional arrays using integer indices. The order of array indices is inverted relative to the Dataset key dimensions, e.g. an Image with key dimensions ‘x’ and ‘y’ can be indexed with image.ndloc[iy, ix] , where iy and ix are integer indices along the y and x dimensions.

Examples:

  • Index value in 2D array:

    dataset.ndloc[3, 1]

  • Slice along y-axis of 2D array:

    dataset.ndloc[2:5, :]

  • Vectorized (non-orthogonal) indexing along x- and y-axes:

    dataset.ndloc[[1, 2, 3], [0, 2, 3]]

options ( options=None , backend=None , clone=True , **kwargs )

Applies options on an object or nested group of objects in a flat format returning a new object with the options applied. If the options are to be set directly on the object a simple format may be used, e.g.:

obj.options(cmap=’viridis’, show_title=False)

If the object is nested the options must be qualified using a type[.group][.label] specification, e.g.:

obj.options(‘Image’, cmap=’viridis’, show_title=False)

or using:

obj.options({‘Image’: dict(cmap=’viridis’, show_title=False)})

If no options are supplied all options on the object will be reset. Disabling clone will modify the object inplace.

opts ( options=None , backend=None , clone=True , **kwargs )

Applies options on an object or nested group of objects in a by options group returning a new object with the options applied. If the options are to be set directly on the object a simple format may be used, e.g.:

obj.opts(style={‘cmap’: ‘viridis’}, plot={‘show_title’: False})

If the object is nested the options must be qualified using a type[.group][.label] specification, e.g.:

obj.opts({‘Image’: {‘plot’: {‘show_title’: False},
‘style’: {‘cmap’: ‘viridis}}})

If no opts are supplied all options on the object will be reset. Disabling clone will modify the object inplace.

params ( parameter_name=None )

Return the Parameters of this class as the dictionary {name: parameter_object}

Includes Parameters from this class and its superclasses.

pprint ( imports=None , prefix=' ' , unknown_value='<?>' , qualify=False , separator='' )

(Experimental) Pretty printed representation that may be evaluated with eval. See pprint() function for more details.

print_param_defaults ( )

Print the default values of all cls’s Parameters.

print_param_values ( )

Print the values of all this object’s Parameters.

reduce ( dimensions=[] , function=None , spreadfn=None , **reduce_map )

Allows reducing the values along one or more key dimension with the supplied function. The dimensions may be supplied as a list and a function to apply or a mapping between the dimensions and functions to apply along each dimension.

reindex ( kdims=None , vdims=None )

Create a new object with a re-ordered set of dimensions. Allows converting key dimensions to value dimensions and vice versa.

relabel ( label=None , group=None , depth=0 )

Assign a new label and/or group to an existing LabelledData object, creating a clone of the object with the new settings.

rgb

Returns the corresponding RGB element.

Other than the updating parameter definitions, this is the only change needed to implemented an arbitrary colorspace as a subclass of RGB.

sample ( samples=[] , **kwargs )

Allows sampling of an Image as an iterator of coordinates matching the key dimensions, returning a new object containing just the selected samples. Alternatively may supply kwargs to sample a coordinate on an object. On an Image the coordinates are continuously indexed and will always snap to the nearest coordinate.

script_repr ( imports=[] , prefix=' ' )

Variant of __repr__ designed for generating a runnable script.

select ( selection_specs=None , **selection )

Allows selecting data by the slices, sets and scalar values along a particular dimension. The indices should be supplied as keywords mapping between the selected dimension and value. Additionally selection_specs (taking the form of a list of type.group.label strings, types or functions) may be supplied, which will ensure the selection is only applied if the specs match the selected object.

set_default ( param_name , value )

Set the default value of param_name.

Equivalent to setting param_name on the class.

set_dynamic_time_fn = functools.partial(<function Parameterized.set_dynamic_time_fn>, <class 'holoviews.element.raster.RGB'>)
set_param = functools.partial(<function Parameterized.set_param>, <class 'holoviews.element.raster.RGB'>)
shape

Returns the shape of the data.

sheet2matrix ( x , y )

Convert a point (x,y) in Sheet coordinates to continuous matrix coordinates.

Returns (float_row,float_col), where float_row corresponds to y, and float_col to x.

Valid for scalar or array x and y.

Note about Bounds For a Sheet with BoundingBox(points=((-0.5,-0.5),(0.5,0.5))) and density=3, x=-0.5 corresponds to float_col=0.0 and x=0.5 corresponds to float_col=3.0. float_col=3.0 is not inside the matrix representing this Sheet, which has the three columns (0,1,2). That is, x=-0.5 is inside the BoundingBox but x=0.5 is outside. Similarly, y=0.5 is inside (at row 0) but y=-0.5 is outside (at row 3) (it’s the other way round for y because the matrix row index increases as y decreases).

sheet2matrixidx ( x , y )

Convert a point (x,y) in sheet coordinates to the integer row and column index of the matrix cell in which that point falls, given a bounds and density. Returns (row,column).

Note that if coordinates along the right or bottom boundary are passed into this function, the returned matrix coordinate of the boundary will be just outside the matrix, because the right and bottom boundaries are exclusive.

Valid for scalar or array x and y.

sheetcoordinates_of_matrixidx ( )

Return x,y where x is a vector of sheet coordinates representing the x-center of each matrix cell, and y represents the corresponding y-center of the cell.

sort ( by=[] , reverse=False )

Sorts the data by the values along the supplied dimensions.

state_pop ( )

Restore the most recently saved state.

See state_push() for more details.

state_push ( )

Save this instance’s state.

For Parameterized instances, this includes the state of dynamically generated values.

Subclasses that maintain short-term state should additionally save and restore that state using state_push() and state_pop().

Generally, this method is used by operations that need to test something without permanently altering the objects’ state.

table ( datatype=None )

Converts the data Element to a Table, optionally may specify a supported data type. The default data types are ‘numpy’ (for homogeneous data), ‘dataframe’, and ‘dictionary’.

to

Property to create a conversion interface with methods to convert to other Element types.

traverse ( fn , specs=None , full_breadth=True )

Traverses any nested LabelledData object (i.e LabelledData objects containing LabelledData objects), applying the supplied function to each constituent element if the supplied specifications. The output of these function calls are collected and returned in the accumulator list.

If specs is None, all constituent elements are processed. Otherwise, specs must be a list of type.group.label specs, types, and functions.

verbose ( msg , *args , **kw )

Print msg merged with args as a verbose message.

See Python’s logging module for details of message formatting.

warning ( msg , *args , **kw )

Print msg merged with args as a warning, unless module variable warnings_as_exceptions is True, then raise an Exception containing the arguments.

See Python’s logging module for details of message formatting.

xdensity

The spacing between elements in an underlying matrix representation, in the x direction.

ydensity

The spacing between elements in an underlying matrix representation, in the y direction.

class holoviews.element. Text ( x , y , text , fontsize=12 , halign='center' , valign='center' , rotation=0 , **params ) [source]

Bases: holoviews.element.annotation.Annotation

Draw a text annotation at the specified position with custom fontsize, alignment and rotation.

param String group ( allow_None=False, basestring=<class ‘str’>, constant=True, default=Text, instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
A string describing the data wrapped by the object.
param String label ( allow_None=False, basestring=<class ‘str’>, constant=True, default=, instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
Optional label describing the data, typically reflecting where or how it was measured. The label should allow a specific measurement or dataset to be referenced for a given group.
param Dict cdims ( allow_None=False, constant=False, default=OrderedDict(), instantiate=True, is_instance=True, pickle_default_value=True, precedence=None, readonly=False )
The constant dimensions defined as a dictionary of Dimension:value pairs providing additional dimension information about the object. Aliased with constant_dimensions.
param List kdims ( allow_None=False, bounds=(2, 2), constant=False, default=[Dimension(‘x’), Dimension(‘y’)], instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
The key dimensions defined as list of dimensions that may be used in indexing (and potential slicing) semantics. The order of the dimensions listed here determines the semantics of each component of a multi-dimensional indexing operation. Aliased with key_dimensions.
param List vdims ( allow_None=False, bounds=(0, None), constant=True, default=[], instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
The value dimensions defined as the list of dimensions used to describe the components of the data. If multiple value dimensions are supplied, a particular value dimension may be indexed by name after the key dimensions. Aliased with value_dimensions.
param Tuple extents ( allow_None=False, constant=False, default=(None, None, None, None), instantiate=False, length=4, pickle_default_value=True, precedence=None, readonly=False )
Allows overriding the extents of the Element in 2D space defined as four-tuple defining the (left, bottom, right and top) edges.
param ClassSelector x ( allow_None=False, constant=False, default=0, instantiate=True, is_instance=True, pickle_default_value=True, precedence=None, readonly=False )
The x-position of the arrow which make be numeric or a timestamp.
param ClassSelector y ( allow_None=False, constant=False, default=0, instantiate=True, is_instance=True, pickle_default_value=True, precedence=None, readonly=False )
The y-position of the arrow which make be numeric or a timestamp.
param String text ( allow_None=False, basestring=<class ‘str’>, constant=False, default=, instantiate=False, pickle_default_value=True, precedence=None, readonly=False )
The text to be displayed.
param Number fontsize ( allow_None=False, bounds=None, constant=False, default=12, inclusive_bounds=(True, True), instantiate=False, pickle_default_value=True, precedence=None, readonly=False, softbounds=None, time_dependent=False, time_fn=<Time Time00001> )
Font size of the text.
param Number rotation ( allow_None=False, bounds=None, constant=False, default=0, inclusive_bounds=(True, True), instantiate=False, pickle_default_value=True, precedence=None, readonly=False, softbounds=None, time_dependent=False, time_fn=<Time Time00001> )
Text rotation angle in degrees.
param ObjectSelector halign ( allow_None=None, check_on_set=True, compute_default_fn=None, constant=False, default=center, instantiate=False, objects=[‘left’, ‘right’, ‘center’], pickle_default_value=True, precedence=None, readonly=False )
The horizontal alignment position of the displayed text. Allowed values are ‘left’, ‘right’ and ‘center’.
param ObjectSelector valign ( allow_None=None, check_on_set=True, compute_default_fn=None, constant=False, default=center, instantiate=False, objects=[‘top’, ‘bottom’, ‘center’], pickle_default_value=True, precedence=None, readonly=False )
The vertical alignment position of the displayed text. Allowed values are ‘center’, ‘top’ and ‘bottom’.
closest ( coords )

Class method that returns the exact keys for a given list of coordinates. The supplied bounds defines the extent within which the samples are drawn and the optional shape argument is the shape of the numpy array (typically the shape of the .data attribute) when applicable.

collapse_data ( data , function=None , kdims=None , **kwargs )

Class method to collapse a list of data matching the data format of the Element type. By implementing this method HoloMap can collapse multiple Elements of the same type. The kwargs are passed to the collapse function. The collapse function must support the numpy style axis selection. Valid function include: np.mean, np.sum, np.product, np.std, scipy.stats.kurtosis etc. Some data backends also require the key dimensions to aggregate over.

ddims

The list of deep dimensions

debug ( msg , *args , **kw )

Print msg merged with args as a debugging statement.

See Python’s logging module for details of message formatting.

defaults ( )

Return {parameter_name:parameter.default} for all non-constant Parameters.

Note that a Parameter for which instantiate==True has its default instantiated.

dimensions ( selection='all' , label=False )

Provides convenient access to Dimensions on nested Dimensioned objects. Dimensions can be selected by their type, i.e. ‘key’ or ‘value’ dimensions. By default ‘all’ dimensions are returned.

force_new_dynamic_value = functools.partial(<function Parameterized.force_new_dynamic_value>, <class 'holoviews.element.annotation.Text'>)
get_dimension ( dimension , default=None , strict=False )

Access a Dimension object by name or index. Returns the default value if the dimension is not found and strict is False. If strict is True, a KeyError is raised instead.

get_dimension_index ( dim )

Returns the index of the requested dimension.

get_dimension_type ( dim )

Returns the specified Dimension type if specified or if the dimension_values types are consistent otherwise None is returned.

get_param_values = functools.partial(<function Parameterized.get_param_values>, <class 'holoviews.element.annotation.Text'>)
get_value_generator = functools.partial(<function Parameterized.get_value_generator>, <class 'holoviews.element.annotation.Text'>)
hist ( dimension=None , num_bins=20 , bin_range=None , adjoin=True , individually=True , **kwargs )

The hist method generates a histogram to be adjoined to the Element in an AdjointLayout. By default the histogram is computed along the first value dimension of the Element, however any dimension may be selected. The number of bins and the bin_ranges and any kwargs to be passed to the histogram operation may also be supplied.

inspect_value = functools.partial(<function Parameterized.inspect_value>, <class 'holoviews.element.annotation.Text'>)
map ( map_fn , specs=None , clone=True )

Recursively replaces elements using a map function when the specification applies.

matches ( spec )

A specification may be a class, a tuple or a string. Equivalent to isinstance if a class is supplied, otherwise matching occurs on type, group and label. These may be supplied as a tuple of strings or as a single string of the form “{type}.{group}.{label}”. Matching may be done on {type} alone, {type}.{group}, or {type}.{group}.{label}. The strings for the type, group, and label will each be sanitized before the match, and so the sanitized versions of those values will need to be provided if the match is to succeed.

message ( msg , *args , **kw )

Print msg merged with args as a message.

See Python’s logging module for details of message formatting.

options ( options=None , backend=None , clone=True , **kwargs )

Applies options on an object or nested group of objects in a flat format returning a new object with the options applied. If the options are to be set directly on the object a simple format may be used, e.g.:

obj.options(cmap=’viridis’, show_title=False)

If the object is nested the options must be qualified using a type[.group][.label] specification, e.g.:

obj.options(‘Image’, cmap=’viridis’, show_title=False)

or using:

obj.options({‘Image’: dict(cmap=’viridis’, show_title=False)})

If no options are supplied all options on the object will be reset. Disabling clone will modify the object inplace.

opts ( options=None , backend=None , clone=True , **kwargs )

Applies options on an object or nested group of objects in a by options group returning a new object with the options applied. If the options are to be set directly on the object a simple format may be used, e.g.:

obj.opts(style={‘cmap’: ‘viridis’}, plot={‘show_title’: False})

If the object is nested the options must be qualified using a type[.group][.label] specification, e.g.:

obj.opts({‘Image’: {‘plot’: {‘show_title’: False},
‘style’: {‘cmap’: ‘viridis}}})

If no opts are supplied all options on the object will be reset. Disabling clone will modify the object inplace.

params ( parameter_name=None )

Return the Parameters of this class as the dictionary {name: parameter_object}

Includes Parameters from this class and its superclasses.

pprint ( imports=None , prefix=' ' , unknown_value='<?>' , qualify=False , separator='' )

(Experimental) Pretty printed representation that may be evaluated with eval. See pprint() function for more details.

print_param_defaults ( )

Print the default values of all cls’s Parameters.

print_param_values ( )

Print the values of all this object’s Parameters.

range ( dimension , data_range=True )

Returns the range of values along the specified dimension.

If data_range is True, the data may be used to try and infer the appropriate range. Otherwise, (None,None) is returned to indicate that no range is defined.

reduce ( dimensions=[] , function=None , **reduce_map )

Base class signature to demonstrate API for reducing Elements, using some reduce function, e.g. np.mean, which is applied along a particular Dimension. The dimensions and reduce functions should be passed as keyword arguments or as a list of dimensions and a single function.

relabel ( label=None , group=None , depth=0 )

Assign a new label and/or group to an existing LabelledData object, creating a clone of the object with the new settings.

sample ( samples=[] , **sample_values )

Base class signature to demonstrate API for sampling Elements. To sample an Element supply either a list of samples or keyword arguments, where the key should match an existing key dimension on the Element.

script_repr ( imports=[] , prefix=' ' )

Variant of __repr__ designed for generating a runnable script.

select ( selection_specs=None , **kwargs )

Allows slicing or indexing into the Dimensioned object by supplying the dimension and index/slice as key value pairs. Select descends recursively through the data structure applying the key dimension selection. The ‘value’ keyword allows selecting the value dimensions on objects which have any declared.

The selection may also be selectively applied to specific objects by supplying the selection_specs as an iterable of type.group.label specs, types or functions.

set_default ( param_name , value )

Set the default value of param_name.

Equivalent to setting param_name on the class.

set_dynamic_time_fn = functools.partial(<function Parameterized.set_dynamic_time_fn>, <class 'holoviews.element.annotation.Text'>)
set_param = functools.partial(<function Parameterized.set_param>, <class 'holoviews.element.annotation.Text'>)
state_pop ( )

Restore the most recently saved state.

See state_push() for more details.

state_push ( )

Save this instance’s state.

For Parameterized instances, this includes the state of dynamically generated values.

Subclasses that maintain short-term state should additionally save and restore that state using state_push() and state_pop().

Generally, this method is used by operations that need to test something without permanently altering the objects’ state.

table ( datatype=None )

Converts the data Element to a Table, optionally may specify a supported data type. The default data types are ‘numpy’ (for homogeneous data), ‘dataframe’, and ‘dictionary’.

traverse ( fn , specs=None , full_breadth=True )

Traverses any nested LabelledData object (i.e LabelledData objects containing LabelledData objects), applying the supplied function to each constituent element if the supplied specifications. The output of these function calls are collected and returned in the accumulator list.

If specs is None, all constituent elements are processed. Otherwise, specs must be a list of type.group.label specs, types, and functions.

verbose ( msg , *args , **kw )

Print msg merged with args as a verbose message.

See Python’s logging module for details of message formatting.

warning ( msg , *args , **kw )

Print msg merged with args as a warning, unless module variable warnings_as_exceptions is True, then raise an Exception containing the arguments.

See Python’s logging module for details of message formatting.

class holoviews.element. Dataset ( data , kdims=None , vdims=None , **kwargs ) [source]

Bases: holoviews.core.element.Element

Dataset provides a general baseclass for Element types that contain structured data and supports a range of data formats.

The Dataset class supports various methods offering a consistent way of working with the stored data regardless of the storage format used. These operations include indexing, selection and various ways of aggregating or collapsing the data with a supplied function.

param String group ( allow_None=False, basestring=<class ‘str’>, constant=True, default=Dataset, instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
A string describing the data wrapped by the object.
param String label ( allow_None=False, basestring=<class ‘str’>, constant=True, default=, instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
Optional label describing the data, typically reflecting where or how it was measured. The label should allow a specific measurement or dataset to be referenced for a given group.
param Dict cdims ( allow_None=False, constant=False, default=OrderedDict(), instantiate=True, is_instance=True, pickle_default_value=True, precedence=None, readonly=False )
The constant dimensions defined as a dictionary of Dimension:value pairs providing additional dimension information about the object. Aliased with constant_dimensions.
param List kdims ( allow_None=False, bounds=(0, None), constant=True, default=[], instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
The key dimensions defined as list of dimensions that may be used in indexing (and potential slicing) semantics. The order of the dimensions listed here determines the semantics of each component of a multi-dimensional indexing operation. Aliased with key_dimensions.
param List vdims ( allow_None=False, bounds=(0, None), constant=True, default=[], instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
The value dimensions defined as the list of dimensions used to describe the components of the data. If multiple value dimensions are supplied, a particular value dimension may be indexed by name after the key dimensions. Aliased with value_dimensions.
param List datatype ( allow_None=False, bounds=(0, None), constant=False, default=[‘dataframe’, ‘dataframe’, ‘dataframe’, ‘dictionary’, ‘grid’, ‘ndelement’, ‘array’, ‘cube’, ‘xarray’, ‘dask’], instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
A priority list of the data types to be used for storage on the .data attribute. If the input supplied to the element constructor cannot be put into the requested format, the next format listed will be used until a suitable format is found (or the data fails to be understood).
add_dimension ( dimension , dim_pos , dim_val , vdim=False , **kwargs ) [source]

Create a new object with an additional key dimensions. Requires the dimension name or object, the desired position in the key dimensions and a key value scalar or sequence of the same length as the existing keys.

aggregate ( dimensions=None , function=None , spreadfn=None , **kwargs ) [source]

Aggregates over the supplied key dimensions with the defined function.

clone ( data=None , shared_data=True , new_type=None , *args , **overrides ) [source]

Returns a clone of the object with matching parameter values containing the specified args and kwargs.

If shared_data is set to True and no data explicitly supplied, the clone will share data with the original. May also supply a new_type, which will inherit all shared parameters.

closest ( coords=[] , **kwargs ) [source]

Given a single coordinate or multiple coordinates as a tuple or list of tuples or keyword arguments matching the dimension closest will find the closest actual x/y coordinates. Different Element types should implement this appropriately depending on the space they represent, if the Element does not support snapping raise NotImplementedError.

collapse_data ( data , function=None , kdims=None , **kwargs )

Class method to collapse a list of data matching the data format of the Element type. By implementing this method HoloMap can collapse multiple Elements of the same type. The kwargs are passed to the collapse function. The collapse function must support the numpy style axis selection. Valid function include: np.mean, np.sum, np.product, np.std, scipy.stats.kurtosis etc. Some data backends also require the key dimensions to aggregate over.

ddims

The list of deep dimensions

debug ( msg , *args , **kw )

Print msg merged with args as a debugging statement.

See Python’s logging module for details of message formatting.

defaults ( )

Return {parameter_name:parameter.default} for all non-constant Parameters.

Note that a Parameter for which instantiate==True has its default instantiated.

dframe ( dimensions=None ) [source]

Returns the data in the form of a DataFrame. Supplying a list of dimensions filters the dataframe. If the data is already a DataFrame a copy is returned.

dimension_values ( dim , expanded=True , flat=True ) [source]

Returns the values along a particular dimension. If unique values are requested will return only unique values.

dimensions ( selection='all' , label=False )

Provides convenient access to Dimensions on nested Dimensioned objects. Dimensions can be selected by their type, i.e. ‘key’ or ‘value’ dimensions. By default ‘all’ dimensions are returned.

force_new_dynamic_value = functools.partial(<function Parameterized.force_new_dynamic_value>, <class 'holoviews.core.data.Dataset'>)
get_dimension ( dimension , default=None , strict=False )

Access a Dimension object by name or index. Returns the default value if the dimension is not found and strict is False. If strict is True, a KeyError is raised instead.

get_dimension_index ( dim )

Returns the index of the requested dimension.

get_dimension_type ( dim ) [source]

Returns the specified Dimension type if specified or if the dimension_values types are consistent otherwise None is returned.

get_param_values = functools.partial(<function Parameterized.get_param_values>, <class 'holoviews.core.data.Dataset'>)
get_value_generator = functools.partial(<function Parameterized.get_value_generator>, <class 'holoviews.core.data.Dataset'>)
groupby ( dimensions=[] , container_type=<class 'holoviews.core.spaces.HoloMap'> , group_type=None , dynamic=False , **kwargs ) [source]

Return the results of a groupby operation over the specified dimensions as an object of type container_type (expected to be dictionary-like).

Keys vary over the columns (dimensions) and the corresponding values are collections of group_type (e.g an Element, list, tuple) constructed with kwargs (if supplied).

If dynamic is requested container_type is automatically set to a DynamicMap, allowing dynamic exploration of large datasets. If the data does not represent a full cartesian grid of the requested dimensions some Elements will be empty.

hist ( dimension=None , num_bins=20 , bin_range=None , adjoin=True , individually=True , **kwargs )

The hist method generates a histogram to be adjoined to the Element in an AdjointLayout. By default the histogram is computed along the first value dimension of the Element, however any dimension may be selected. The number of bins and the bin_ranges and any kwargs to be passed to the histogram operation may also be supplied.

iloc

Returns an iloc object providing a convenient interface to slice and index into the Dataset using row and column indices. Allow selection by integer index, slice and list of integer indices and boolean arrays.

Examples:

  • Index the first row and column:

    dataset.iloc[0, 0]

  • Select rows 1 and 2 with a slice:

    dataset.iloc[1:3, :]

  • Select with a list of integer coordinates:

    dataset.iloc[[0, 2, 3]]

inspect_value = functools.partial(<function Parameterized.inspect_value>, <class 'holoviews.core.data.Dataset'>)
map ( map_fn , specs=None , clone=True )

Recursively replaces elements using a map function when the specification applies.

matches ( spec )

A specification may be a class, a tuple or a string. Equivalent to isinstance if a class is supplied, otherwise matching occurs on type, group and label. These may be supplied as a tuple of strings or as a single string of the form “{type}.{group}.{label}”. Matching may be done on {type} alone, {type}.{group}, or {type}.{group}.{label}. The strings for the type, group, and label will each be sanitized before the match, and so the sanitized versions of those values will need to be provided if the match is to succeed.

message ( msg , *args , **kw )

Print msg merged with args as a message.

See Python’s logging module for details of message formatting.

ndloc

Returns an ndloc object providing nd-array like indexing for gridded datasets. Follows NumPy array indexing conventions, allowing for indexing, slicing and selecting a list of indices on multi-dimensional arrays using integer indices. The order of array indices is inverted relative to the Dataset key dimensions, e.g. an Image with key dimensions ‘x’ and ‘y’ can be indexed with image.ndloc[iy, ix] , where iy and ix are integer indices along the y and x dimensions.

Examples:

  • Index value in 2D array:

    dataset.ndloc[3, 1]

  • Slice along y-axis of 2D array:

    dataset.ndloc[2:5, :]

  • Vectorized (non-orthogonal) indexing along x- and y-axes:

    dataset.ndloc[[1, 2, 3], [0, 2, 3]]

options ( options=None , backend=None , clone=True , **kwargs )

Applies options on an object or nested group of objects in a flat format returning a new object with the options applied. If the options are to be set directly on the object a simple format may be used, e.g.:

obj.options(cmap=’viridis’, show_title=False)

If the object is nested the options must be qualified using a type[.group][.label] specification, e.g.:

obj.options(‘Image’, cmap=’viridis’, show_title=False)

or using:

obj.options({‘Image’: dict(cmap=’viridis’, show_title=False)})

If no options are supplied all options on the object will be reset. Disabling clone will modify the object inplace.

opts ( options=None , backend=None , clone=True , **kwargs )

Applies options on an object or nested group of objects in a by options group returning a new object with the options applied. If the options are to be set directly on the object a simple format may be used, e.g.:

obj.opts(style={‘cmap’: ‘viridis’}, plot={‘show_title’: False})

If the object is nested the options must be qualified using a type[.group][.label] specification, e.g.:

obj.opts({‘Image’: {‘plot’: {‘show_title’: False},
‘style’: {‘cmap’: ‘viridis}}})

If no opts are supplied all options on the object will be reset. Disabling clone will modify the object inplace.

params ( parameter_name=None )

Return the Parameters of this class as the dictionary {name: parameter_object}

Includes Parameters from this class and its superclasses.

pprint ( imports=None , prefix=' ' , unknown_value='<?>' , qualify=False , separator='' )

(Experimental) Pretty printed representation that may be evaluated with eval. See pprint() function for more details.

print_param_defaults ( )

Print the default values of all cls’s Parameters.

print_param_values ( )

Print the values of all this object’s Parameters.

range ( dim , data_range=True ) [source]

Computes the range of values along a supplied dimension, taking into account the range and soft_range defined on the Dimension object.

reduce ( dimensions=[] , function=None , spreadfn=None , **reduce_map ) [source]

Allows reducing the values along one or more key dimension with the supplied function. The dimensions may be supplied as a list and a function to apply or a mapping between the dimensions and functions to apply along each dimension.

reindex ( kdims=None , vdims=None ) [source]

Create a new object with a re-ordered set of dimensions. Allows converting key dimensions to value dimensions and vice versa.

relabel ( label=None , group=None , depth=0 )

Assign a new label and/or group to an existing LabelledData object, creating a clone of the object with the new settings.

sample ( samples=[] , closest=True , **kwargs ) [source]

Allows sampling of Dataset as an iterator of coordinates matching the key dimensions, returning a new object containing just the selected samples. Alternatively may supply kwargs to sample a coordinate on an object. By default it will attempt to snap to the nearest coordinate if the Element supports it, snapping may be disabled with the closest argument.

script_repr ( imports=[] , prefix=' ' )

Variant of __repr__ designed for generating a runnable script.

select ( selection_specs=None , **selection ) [source]

Allows selecting data by the slices, sets and scalar values along a particular dimension. The indices should be supplied as keywords mapping between the selected dimension and value. Additionally selection_specs (taking the form of a list of type.group.label strings, types or functions) may be supplied, which will ensure the selection is only applied if the specs match the selected object.

set_default ( param_name , value )

Set the default value of param_name.

Equivalent to setting param_name on the class.

set_dynamic_time_fn = functools.partial(<function Parameterized.set_dynamic_time_fn>, <class 'holoviews.core.data.Dataset'>)
set_param = functools.partial(<function Parameterized.set_param>, <class 'holoviews.core.data.Dataset'>)
shape

Returns the shape of the data.

sort ( by=[] , reverse=False ) [source]

Sorts the data by the values along the supplied dimensions.

state_pop ( )

Restore the most recently saved state.

See state_push() for more details.

state_push ( )

Save this instance’s state.

For Parameterized instances, this includes the state of dynamically generated values.

Subclasses that maintain short-term state should additionally save and restore that state using state_push() and state_pop().

Generally, this method is used by operations that need to test something without permanently altering the objects’ state.

table ( datatype=None )

Converts the data Element to a Table, optionally may specify a supported data type. The default data types are ‘numpy’ (for homogeneous data), ‘dataframe’, and ‘dictionary’.

to

Property to create a conversion interface with methods to convert to other Element types.

traverse ( fn , specs=None , full_breadth=True )

Traverses any nested LabelledData object (i.e LabelledData objects containing LabelledData objects), applying the supplied function to each constituent element if the supplied specifications. The output of these function calls are collected and returned in the accumulator list.

If specs is None, all constituent elements are processed. Otherwise, specs must be a list of type.group.label specs, types, and functions.

verbose ( msg , *args , **kw )

Print msg merged with args as a verbose message.

See Python’s logging module for details of message formatting.

warning ( msg , *args , **kw )

Print msg merged with args as a warning, unless module variable warnings_as_exceptions is True, then raise an Exception containing the arguments.

See Python’s logging module for details of message formatting.

class holoviews.element. VLine ( x , **params ) [source]

Bases: holoviews.element.annotation.Annotation

Vertical line annotation at the given position.

param String group ( allow_None=False, basestring=<class ‘str’>, constant=True, default=VLine, instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
A string describing the data wrapped by the object.
param String label ( allow_None=False, basestring=<class ‘str’>, constant=True, default=, instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
Optional label describing the data, typically reflecting where or how it was measured. The label should allow a specific measurement or dataset to be referenced for a given group.
param Dict cdims ( allow_None=False, constant=False, default=OrderedDict(), instantiate=True, is_instance=True, pickle_default_value=True, precedence=None, readonly=False )
The constant dimensions defined as a dictionary of Dimension:value pairs providing additional dimension information about the object. Aliased with constant_dimensions.
param List kdims ( allow_None=False, bounds=(2, 2), constant=False, default=[Dimension(‘x’), Dimension(‘y’)], instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
The key dimensions defined as list of dimensions that may be used in indexing (and potential slicing) semantics. The order of the dimensions listed here determines the semantics of each component of a multi-dimensional indexing operation. Aliased with key_dimensions.
param List vdims ( allow_None=False, bounds=(0, None), constant=True, default=[], instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
The value dimensions defined as the list of dimensions used to describe the components of the data. If multiple value dimensions are supplied, a particular value dimension may be indexed by name after the key dimensions. Aliased with value_dimensions.
param Tuple extents ( allow_None=False, constant=False, default=(None, None, None, None), instantiate=False, length=4, pickle_default_value=True, precedence=None, readonly=False )
Allows overriding the extents of the Element in 2D space defined as four-tuple defining the (left, bottom, right and top) edges.
param ClassSelector x ( allow_None=False, constant=False, default=0, instantiate=True, is_instance=True, pickle_default_value=True, precedence=None, readonly=False )
The x-position of the VLine which make be numeric or a timestamp.
closest ( coords )

Class method that returns the exact keys for a given list of coordinates. The supplied bounds defines the extent within which the samples are drawn and the optional shape argument is the shape of the numpy array (typically the shape of the .data attribute) when applicable.

collapse_data ( data , function=None , kdims=None , **kwargs )

Class method to collapse a list of data matching the data format of the Element type. By implementing this method HoloMap can collapse multiple Elements of the same type. The kwargs are passed to the collapse function. The collapse function must support the numpy style axis selection. Valid function include: np.mean, np.sum, np.product, np.std, scipy.stats.kurtosis etc. Some data backends also require the key dimensions to aggregate over.

ddims

The list of deep dimensions

debug ( msg , *args , **kw )

Print msg merged with args as a debugging statement.

See Python’s logging module for details of message formatting.

defaults ( )

Return {parameter_name:parameter.default} for all non-constant Parameters.

Note that a Parameter for which instantiate==True has its default instantiated.

dimensions ( selection='all' , label=False )

Provides convenient access to Dimensions on nested Dimensioned objects. Dimensions can be selected by their type, i.e. ‘key’ or ‘value’ dimensions. By default ‘all’ dimensions are returned.

force_new_dynamic_value = functools.partial(<function Parameterized.force_new_dynamic_value>, <class 'holoviews.element.annotation.VLine'>)
get_dimension ( dimension , default=None , strict=False )

Access a Dimension object by name or index. Returns the default value if the dimension is not found and strict is False. If strict is True, a KeyError is raised instead.

get_dimension_index ( dim )

Returns the index of the requested dimension.

get_dimension_type ( dim )

Returns the specified Dimension type if specified or if the dimension_values types are consistent otherwise None is returned.

get_param_values = functools.partial(<function Parameterized.get_param_values>, <class 'holoviews.element.annotation.VLine'>)
get_value_generator = functools.partial(<function Parameterized.get_value_generator>, <class 'holoviews.element.annotation.VLine'>)
hist ( dimension=None , num_bins=20 , bin_range=None , adjoin=True , individually=True , **kwargs )

The hist method generates a histogram to be adjoined to the Element in an AdjointLayout. By default the histogram is computed along the first value dimension of the Element, however any dimension may be selected. The number of bins and the bin_ranges and any kwargs to be passed to the histogram operation may also be supplied.

inspect_value = functools.partial(<function Parameterized.inspect_value>, <class 'holoviews.element.annotation.VLine'>)
map ( map_fn , specs=None , clone=True )

Recursively replaces elements using a map function when the specification applies.

matches ( spec )

A specification may be a class, a tuple or a string. Equivalent to isinstance if a class is supplied, otherwise matching occurs on type, group and label. These may be supplied as a tuple of strings or as a single string of the form “{type}.{group}.{label}”. Matching may be done on {type} alone, {type}.{group}, or {type}.{group}.{label}. The strings for the type, group, and label will each be sanitized before the match, and so the sanitized versions of those values will need to be provided if the match is to succeed.

message ( msg , *args , **kw )

Print msg merged with args as a message.

See Python’s logging module for details of message formatting.

options ( options=None , backend=None , clone=True , **kwargs )

Applies options on an object or nested group of objects in a flat format returning a new object with the options applied. If the options are to be set directly on the object a simple format may be used, e.g.:

obj.options(cmap=’viridis’, show_title=False)

If the object is nested the options must be qualified using a type[.group][.label] specification, e.g.:

obj.options(‘Image’, cmap=’viridis’, show_title=False)

or using:

obj.options({‘Image’: dict(cmap=’viridis’, show_title=False)})

If no options are supplied all options on the object will be reset. Disabling clone will modify the object inplace.

opts ( options=None , backend=None , clone=True , **kwargs )

Applies options on an object or nested group of objects in a by options group returning a new object with the options applied. If the options are to be set directly on the object a simple format may be used, e.g.:

obj.opts(style={‘cmap’: ‘viridis’}, plot={‘show_title’: False})

If the object is nested the options must be qualified using a type[.group][.label] specification, e.g.:

obj.opts({‘Image’: {‘plot’: {‘show_title’: False},
‘style’: {‘cmap’: ‘viridis}}})

If no opts are supplied all options on the object will be reset. Disabling clone will modify the object inplace.

params ( parameter_name=None )

Return the Parameters of this class as the dictionary {name: parameter_object}

Includes Parameters from this class and its superclasses.

pprint ( imports=None , prefix=' ' , unknown_value='<?>' , qualify=False , separator='' )

(Experimental) Pretty printed representation that may be evaluated with eval. See pprint() function for more details.

print_param_defaults ( )

Print the default values of all cls’s Parameters.

print_param_values ( )

Print the values of all this object’s Parameters.

range ( dimension , data_range=True )

Returns the range of values along the specified dimension.

If data_range is True, the data may be used to try and infer the appropriate range. Otherwise, (None,None) is returned to indicate that no range is defined.

reduce ( dimensions=[] , function=None , **reduce_map )

Base class signature to demonstrate API for reducing Elements, using some reduce function, e.g. np.mean, which is applied along a particular Dimension. The dimensions and reduce functions should be passed as keyword arguments or as a list of dimensions and a single function.

relabel ( label=None , group=None , depth=0 )

Assign a new label and/or group to an existing LabelledData object, creating a clone of the object with the new settings.

sample ( samples=[] , **sample_values )

Base class signature to demonstrate API for sampling Elements. To sample an Element supply either a list of samples or keyword arguments, where the key should match an existing key dimension on the Element.

script_repr ( imports=[] , prefix=' ' )

Variant of __repr__ designed for generating a runnable script.

select ( selection_specs=None , **kwargs )

Allows slicing or indexing into the Dimensioned object by supplying the dimension and index/slice as key value pairs. Select descends recursively through the data structure applying the key dimension selection. The ‘value’ keyword allows selecting the value dimensions on objects which have any declared.

The selection may also be selectively applied to specific objects by supplying the selection_specs as an iterable of type.group.label specs, types or functions.

set_default ( param_name , value )

Set the default value of param_name.

Equivalent to setting param_name on the class.

set_dynamic_time_fn = functools.partial(<function Parameterized.set_dynamic_time_fn>, <class 'holoviews.element.annotation.VLine'>)
set_param = functools.partial(<function Parameterized.set_param>, <class 'holoviews.element.annotation.VLine'>)
state_pop ( )

Restore the most recently saved state.

See state_push() for more details.

state_push ( )

Save this instance’s state.

For Parameterized instances, this includes the state of dynamically generated values.

Subclasses that maintain short-term state should additionally save and restore that state using state_push() and state_pop().

Generally, this method is used by operations that need to test something without permanently altering the objects’ state.

table ( datatype=None )

Converts the data Element to a Table, optionally may specify a supported data type. The default data types are ‘numpy’ (for homogeneous data), ‘dataframe’, and ‘dictionary’.

traverse ( fn , specs=None , full_breadth=True )

Traverses any nested LabelledData object (i.e LabelledData objects containing LabelledData objects), applying the supplied function to each constituent element if the supplied specifications. The output of these function calls are collected and returned in the accumulator list.

If specs is None, all constituent elements are processed. Otherwise, specs must be a list of type.group.label specs, types, and functions.

verbose ( msg , *args , **kw )

Print msg merged with args as a verbose message.

See Python’s logging module for details of message formatting.

warning ( msg , *args , **kw )

Print msg merged with args as a warning, unless module variable warnings_as_exceptions is True, then raise an Exception containing the arguments.

See Python’s logging module for details of message formatting.

class holoviews.element. Spline ( spline_points , **params ) [source]

Bases: holoviews.element.annotation.Annotation

Draw a spline using the given handle coordinates and handle codes. The constructor accepts a tuple in format (coords, codes).

Follows format of matplotlib spline definitions as used in matplotlib.path.Path with the following codes:

Path.STOP : 0 Path.MOVETO : 1 Path.LINETO : 2 Path.CURVE3 : 3 Path.CURVE4 : 4 Path.CLOSEPLOY: 79

param String group ( allow_None=False, basestring=<class ‘str’>, constant=True, default=Spline, instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
A string describing the data wrapped by the object.
param String label ( allow_None=False, basestring=<class ‘str’>, constant=True, default=, instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
Optional label describing the data, typically reflecting where or how it was measured. The label should allow a specific measurement or dataset to be referenced for a given group.
param Dict cdims ( allow_None=False, constant=False, default=OrderedDict(), instantiate=True, is_instance=True, pickle_default_value=True, precedence=None, readonly=False )
The constant dimensions defined as a dictionary of Dimension:value pairs providing additional dimension information about the object. Aliased with constant_dimensions.
param List kdims ( allow_None=False, bounds=(2, 2), constant=False, default=[Dimension(‘x’), Dimension(‘y’)], instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
The key dimensions defined as list of dimensions that may be used in indexing (and potential slicing) semantics. The order of the dimensions listed here determines the semantics of each component of a multi-dimensional indexing operation. Aliased with key_dimensions.
param List vdims ( allow_None=False, bounds=(0, None), constant=True, default=[], instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
The value dimensions defined as the list of dimensions used to describe the components of the data. If multiple value dimensions are supplied, a particular value dimension may be indexed by name after the key dimensions. Aliased with value_dimensions.
param Tuple extents ( allow_None=False, constant=False, default=(None, None, None, None), instantiate=False, length=4, pickle_default_value=True, precedence=None, readonly=False )
Allows overriding the extents of the Element in 2D space defined as four-tuple defining the (left, bottom, right and top) edges.
closest ( coords )

Class method that returns the exact keys for a given list of coordinates. The supplied bounds defines the extent within which the samples are drawn and the optional shape argument is the shape of the numpy array (typically the shape of the .data attribute) when applicable.

collapse_data ( data , function=None , kdims=None , **kwargs )

Class method to collapse a list of data matching the data format of the Element type. By implementing this method HoloMap can collapse multiple Elements of the same type. The kwargs are passed to the collapse function. The collapse function must support the numpy style axis selection. Valid function include: np.mean, np.sum, np.product, np.std, scipy.stats.kurtosis etc. Some data backends also require the key dimensions to aggregate over.

ddims

The list of deep dimensions

debug ( msg , *args , **kw )

Print msg merged with args as a debugging statement.

See Python’s logging module for details of message formatting.

defaults ( )

Return {parameter_name:parameter.default} for all non-constant Parameters.

Note that a Parameter for which instantiate==True has its default instantiated.

dimensions ( selection='all' , label=False )

Provides convenient access to Dimensions on nested Dimensioned objects. Dimensions can be selected by their type, i.e. ‘key’ or ‘value’ dimensions. By default ‘all’ dimensions are returned.

force_new_dynamic_value = functools.partial(<function Parameterized.force_new_dynamic_value>, <class 'holoviews.element.annotation.Spline'>)
get_dimension ( dimension , default=None , strict=False )

Access a Dimension object by name or index. Returns the default value if the dimension is not found and strict is False. If strict is True, a KeyError is raised instead.

get_dimension_index ( dim )

Returns the index of the requested dimension.

get_dimension_type ( dim )

Returns the specified Dimension type if specified or if the dimension_values types are consistent otherwise None is returned.

get_param_values = functools.partial(<function Parameterized.get_param_values>, <class 'holoviews.element.annotation.Spline'>)
get_value_generator = functools.partial(<function Parameterized.get_value_generator>, <class 'holoviews.element.annotation.Spline'>)
hist ( dimension=None , num_bins=20 , bin_range=None , adjoin=True , individually=True , **kwargs )

The hist method generates a histogram to be adjoined to the Element in an AdjointLayout. By default the histogram is computed along the first value dimension of the Element, however any dimension may be selected. The number of bins and the bin_ranges and any kwargs to be passed to the histogram operation may also be supplied.

inspect_value = functools.partial(<function Parameterized.inspect_value>, <class 'holoviews.element.annotation.Spline'>)
map ( map_fn , specs=None , clone=True )

Recursively replaces elements using a map function when the specification applies.

matches ( spec )

A specification may be a class, a tuple or a string. Equivalent to isinstance if a class is supplied, otherwise matching occurs on type, group and label. These may be supplied as a tuple of strings or as a single string of the form “{type}.{group}.{label}”. Matching may be done on {type} alone, {type}.{group}, or {type}.{group}.{label}. The strings for the type, group, and label will each be sanitized before the match, and so the sanitized versions of those values will need to be provided if the match is to succeed.

message ( msg , *args , **kw )

Print msg merged with args as a message.

See Python’s logging module for details of message formatting.

options ( options=None , backend=None , clone=True , **kwargs )

Applies options on an object or nested group of objects in a flat format returning a new object with the options applied. If the options are to be set directly on the object a simple format may be used, e.g.:

obj.options(cmap=’viridis’, show_title=False)

If the object is nested the options must be qualified using a type[.group][.label] specification, e.g.:

obj.options(‘Image’, cmap=’viridis’, show_title=False)

or using:

obj.options({‘Image’: dict(cmap=’viridis’, show_title=False)})

If no options are supplied all options on the object will be reset. Disabling clone will modify the object inplace.

opts ( options=None , backend=None , clone=True , **kwargs )

Applies options on an object or nested group of objects in a by options group returning a new object with the options applied. If the options are to be set directly on the object a simple format may be used, e.g.:

obj.opts(style={‘cmap’: ‘viridis’}, plot={‘show_title’: False})

If the object is nested the options must be qualified using a type[.group][.label] specification, e.g.:

obj.opts({‘Image’: {‘plot’: {‘show_title’: False},
‘style’: {‘cmap’: ‘viridis}}})

If no opts are supplied all options on the object will be reset. Disabling clone will modify the object inplace.

params ( parameter_name=None )

Return the Parameters of this class as the dictionary {name: parameter_object}

Includes Parameters from this class and its superclasses.

pprint ( imports=None , prefix=' ' , unknown_value='<?>' , qualify=False , separator='' )

(Experimental) Pretty printed representation that may be evaluated with eval. See pprint() function for more details.

print_param_defaults ( )

Print the default values of all cls’s Parameters.

print_param_values ( )

Print the values of all this object’s Parameters.

range ( dimension , data_range=True )

Returns the range of values along the specified dimension.

If data_range is True, the data may be used to try and infer the appropriate range. Otherwise, (None,None) is returned to indicate that no range is defined.

reduce ( dimensions=[] , function=None , **reduce_map )

Base class signature to demonstrate API for reducing Elements, using some reduce function, e.g. np.mean, which is applied along a particular Dimension. The dimensions and reduce functions should be passed as keyword arguments or as a list of dimensions and a single function.

relabel ( label=None , group=None , depth=0 )

Assign a new label and/or group to an existing LabelledData object, creating a clone of the object with the new settings.

sample ( samples=[] , **sample_values )

Base class signature to demonstrate API for sampling Elements. To sample an Element supply either a list of samples or keyword arguments, where the key should match an existing key dimension on the Element.

script_repr ( imports=[] , prefix=' ' )

Variant of __repr__ designed for generating a runnable script.

select ( selection_specs=None , **kwargs )

Allows slicing or indexing into the Dimensioned object by supplying the dimension and index/slice as key value pairs. Select descends recursively through the data structure applying the key dimension selection. The ‘value’ keyword allows selecting the value dimensions on objects which have any declared.

The selection may also be selectively applied to specific objects by supplying the selection_specs as an iterable of type.group.label specs, types or functions.

set_default ( param_name , value )

Set the default value of param_name.

Equivalent to setting param_name on the class.

set_dynamic_time_fn = functools.partial(<function Parameterized.set_dynamic_time_fn>, <class 'holoviews.element.annotation.Spline'>)
set_param = functools.partial(<function Parameterized.set_param>, <class 'holoviews.element.annotation.Spline'>)
state_pop ( )

Restore the most recently saved state.

See state_push() for more details.

state_push ( )

Save this instance’s state.

For Parameterized instances, this includes the state of dynamically generated values.

Subclasses that maintain short-term state should additionally save and restore that state using state_push() and state_pop().

Generally, this method is used by operations that need to test something without permanently altering the objects’ state.

table ( datatype=None )

Converts the data Element to a Table, optionally may specify a supported data type. The default data types are ‘numpy’ (for homogeneous data), ‘dataframe’, and ‘dictionary’.

traverse ( fn , specs=None , full_breadth=True )

Traverses any nested LabelledData object (i.e LabelledData objects containing LabelledData objects), applying the supplied function to each constituent element if the supplied specifications. The output of these function calls are collected and returned in the accumulator list.

If specs is None, all constituent elements are processed. Otherwise, specs must be a list of type.group.label specs, types, and functions.

verbose ( msg , *args , **kw )

Print msg merged with args as a verbose message.

See Python’s logging module for details of message formatting.

warning ( msg , *args , **kw )

Print msg merged with args as a warning, unless module variable warnings_as_exceptions is True, then raise an Exception containing the arguments.

See Python’s logging module for details of message formatting.

class holoviews.element. Div ( data , **params ) [source]

Bases: holoviews.core.element.Element

The Div element represents a div DOM node in an HTML document defined as a string containing valid HTML.

param String group ( allow_None=False, basestring=<class ‘str’>, constant=True, default=Div, instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
A string describing the data wrapped by the object.
param String label ( allow_None=False, basestring=<class ‘str’>, constant=True, default=, instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
Optional label describing the data, typically reflecting where or how it was measured. The label should allow a specific measurement or dataset to be referenced for a given group.
param Dict cdims ( allow_None=False, constant=False, default=OrderedDict(), instantiate=True, is_instance=True, pickle_default_value=True, precedence=None, readonly=False )
The constant dimensions defined as a dictionary of Dimension:value pairs providing additional dimension information about the object. Aliased with constant_dimensions.
param List kdims ( allow_None=False, bounds=(0, None), constant=True, default=[], instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
The key dimensions defined as list of dimensions that may be used in indexing (and potential slicing) semantics. The order of the dimensions listed here determines the semantics of each component of a multi-dimensional indexing operation. Aliased with key_dimensions.
param List vdims ( allow_None=False, bounds=(0, None), constant=True, default=[], instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
The value dimensions defined as the list of dimensions used to describe the components of the data. If multiple value dimensions are supplied, a particular value dimension may be indexed by name after the key dimensions. Aliased with value_dimensions.
clone ( data=None , shared_data=True , new_type=None , *args , **overrides )

Returns a clone of the object with matching parameter values containing the specified args and kwargs.

If shared_data is set to True and no data explicitly supplied, the clone will share data with the original. May also supply a new_type, which will inherit all shared parameters.

closest ( coords )

Class method that returns the exact keys for a given list of coordinates. The supplied bounds defines the extent within which the samples are drawn and the optional shape argument is the shape of the numpy array (typically the shape of the .data attribute) when applicable.

collapse_data ( data , function=None , kdims=None , **kwargs )

Class method to collapse a list of data matching the data format of the Element type. By implementing this method HoloMap can collapse multiple Elements of the same type. The kwargs are passed to the collapse function. The collapse function must support the numpy style axis selection. Valid function include: np.mean, np.sum, np.product, np.std, scipy.stats.kurtosis etc. Some data backends also require the key dimensions to aggregate over.

ddims

The list of deep dimensions

debug ( msg , *args , **kw )

Print msg merged with args as a debugging statement.

See Python’s logging module for details of message formatting.

defaults ( )

Return {parameter_name:parameter.default} for all non-constant Parameters.

Note that a Parameter for which instantiate==True has its default instantiated.

dimension_values ( dimension , expanded=True , flat=True )

Returns the values along the specified dimension. This method must be implemented for all Dimensioned type.

dimensions ( selection='all' , label=False )

Provides convenient access to Dimensions on nested Dimensioned objects. Dimensions can be selected by their type, i.e. ‘key’ or ‘value’ dimensions. By default ‘all’ dimensions are returned.

force_new_dynamic_value = functools.partial(<function Parameterized.force_new_dynamic_value>, <class 'holoviews.element.annotation.Div'>)
get_dimension ( dimension , default=None , strict=False )

Access a Dimension object by name or index. Returns the default value if the dimension is not found and strict is False. If strict is True, a KeyError is raised instead.

get_dimension_index ( dim )

Returns the index of the requested dimension.

get_dimension_type ( dim )

Returns the specified Dimension type if specified or if the dimension_values types are consistent otherwise None is returned.

get_param_values = functools.partial(<function Parameterized.get_param_values>, <class 'holoviews.element.annotation.Div'>)
get_value_generator = functools.partial(<function Parameterized.get_value_generator>, <class 'holoviews.element.annotation.Div'>)
hist ( dimension=None , num_bins=20 , bin_range=None , adjoin=True , individually=True , **kwargs )

The hist method generates a histogram to be adjoined to the Element in an AdjointLayout. By default the histogram is computed along the first value dimension of the Element, however any dimension may be selected. The number of bins and the bin_ranges and any kwargs to be passed to the histogram operation may also be supplied.

inspect_value = functools.partial(<function Parameterized.inspect_value>, <class 'holoviews.element.annotation.Div'>)
map ( map_fn , specs=None , clone=True )

Recursively replaces elements using a map function when the specification applies.

matches ( spec )

A specification may be a class, a tuple or a string. Equivalent to isinstance if a class is supplied, otherwise matching occurs on type, group and label. These may be supplied as a tuple of strings or as a single string of the form “{type}.{group}.{label}”. Matching may be done on {type} alone, {type}.{group}, or {type}.{group}.{label}. The strings for the type, group, and label will each be sanitized before the match, and so the sanitized versions of those values will need to be provided if the match is to succeed.

message ( msg , *args , **kw )

Print msg merged with args as a message.

See Python’s logging module for details of message formatting.

options ( options=None , backend=None , clone=True , **kwargs )

Applies options on an object or nested group of objects in a flat format returning a new object with the options applied. If the options are to be set directly on the object a simple format may be used, e.g.:

obj.options(cmap=’viridis’, show_title=False)

If the object is nested the options must be qualified using a type[.group][.label] specification, e.g.:

obj.options(‘Image’, cmap=’viridis’, show_title=False)

or using:

obj.options({‘Image’: dict(cmap=’viridis’, show_title=False)})

If no options are supplied all options on the object will be reset. Disabling clone will modify the object inplace.

opts ( options=None , backend=None , clone=True , **kwargs )

Applies options on an object or nested group of objects in a by options group returning a new object with the options applied. If the options are to be set directly on the object a simple format may be used, e.g.:

obj.opts(style={‘cmap’: ‘viridis’}, plot={‘show_title’: False})

If the object is nested the options must be qualified using a type[.group][.label] specification, e.g.:

obj.opts({‘Image’: {‘plot’: {‘show_title’: False},
‘style’: {‘cmap’: ‘viridis}}})

If no opts are supplied all options on the object will be reset. Disabling clone will modify the object inplace.

params ( parameter_name=None )

Return the Parameters of this class as the dictionary {name: parameter_object}

Includes Parameters from this class and its superclasses.

pprint ( imports=None , prefix=' ' , unknown_value='<?>' , qualify=False , separator='' )

(Experimental) Pretty printed representation that may be evaluated with eval. See pprint() function for more details.

print_param_defaults ( )

Print the default values of all cls’s Parameters.

print_param_values ( )

Print the values of all this object’s Parameters.

range ( dimension , data_range=True )

Returns the range of values along the specified dimension.

If data_range is True, the data may be used to try and infer the appropriate range. Otherwise, (None,None) is returned to indicate that no range is defined.

reduce ( dimensions=[] , function=None , **reduce_map )

Base class signature to demonstrate API for reducing Elements, using some reduce function, e.g. np.mean, which is applied along a particular Dimension. The dimensions and reduce functions should be passed as keyword arguments or as a list of dimensions and a single function.

relabel ( label=None , group=None , depth=0 )

Assign a new label and/or group to an existing LabelledData object, creating a clone of the object with the new settings.

sample ( samples=[] , **sample_values )

Base class signature to demonstrate API for sampling Elements. To sample an Element supply either a list of samples or keyword arguments, where the key should match an existing key dimension on the Element.

script_repr ( imports=[] , prefix=' ' )

Variant of __repr__ designed for generating a runnable script.

select ( selection_specs=None , **kwargs )

Allows slicing or indexing into the Dimensioned object by supplying the dimension and index/slice as key value pairs. Select descends recursively through the data structure applying the key dimension selection. The ‘value’ keyword allows selecting the value dimensions on objects which have any declared.

The selection may also be selectively applied to specific objects by supplying the selection_specs as an iterable of type.group.label specs, types or functions.

set_default ( param_name , value )

Set the default value of param_name.

Equivalent to setting param_name on the class.

set_dynamic_time_fn = functools.partial(<function Parameterized.set_dynamic_time_fn>, <class 'holoviews.element.annotation.Div'>)
set_param = functools.partial(<function Parameterized.set_param>, <class 'holoviews.element.annotation.Div'>)
state_pop ( )

Restore the most recently saved state.

See state_push() for more details.

state_push ( )

Save this instance’s state.

For Parameterized instances, this includes the state of dynamically generated values.

Subclasses that maintain short-term state should additionally save and restore that state using state_push() and state_pop().

Generally, this method is used by operations that need to test something without permanently altering the objects’ state.

table ( datatype=None )

Converts the data Element to a Table, optionally may specify a supported data type. The default data types are ‘numpy’ (for homogeneous data), ‘dataframe’, and ‘dictionary’.

traverse ( fn , specs=None , full_breadth=True )

Traverses any nested LabelledData object (i.e LabelledData objects containing LabelledData objects), applying the supplied function to each constituent element if the supplied specifications. The output of these function calls are collected and returned in the accumulator list.

If specs is None, all constituent elements are processed. Otherwise, specs must be a list of type.group.label specs, types, and functions.

verbose ( msg , *args , **kw )

Print msg merged with args as a verbose message.

See Python’s logging module for details of message formatting.

warning ( msg , *args , **kw )

Print msg merged with args as a warning, unless module variable warnings_as_exceptions is True, then raise an Exception containing the arguments.

See Python’s logging module for details of message formatting.

class holoviews.element. HLine ( y , **params ) [source]

Bases: holoviews.element.annotation.Annotation

Horizontal line annotation at the given position.

param String group ( allow_None=False, basestring=<class ‘str’>, constant=True, default=HLine, instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
A string describing the data wrapped by the object.
param String label ( allow_None=False, basestring=<class ‘str’>, constant=True, default=, instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
Optional label describing the data, typically reflecting where or how it was measured. The label should allow a specific measurement or dataset to be referenced for a given group.
param Dict cdims ( allow_None=False, constant=False, default=OrderedDict(), instantiate=True, is_instance=True, pickle_default_value=True, precedence=None, readonly=False )
The constant dimensions defined as a dictionary of Dimension:value pairs providing additional dimension information about the object. Aliased with constant_dimensions.
param List kdims ( allow_None=False, bounds=(2, 2), constant=False, default=[Dimension(‘x’), Dimension(‘y’)], instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
The key dimensions defined as list of dimensions that may be used in indexing (and potential slicing) semantics. The order of the dimensions listed here determines the semantics of each component of a multi-dimensional indexing operation. Aliased with key_dimensions.
param List vdims ( allow_None=False, bounds=(0, None), constant=True, default=[], instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
The value dimensions defined as the list of dimensions used to describe the components of the data. If multiple value dimensions are supplied, a particular value dimension may be indexed by name after the key dimensions. Aliased with value_dimensions.
param Tuple extents ( allow_None=False, constant=False, default=(None, None, None, None), instantiate=False, length=4, pickle_default_value=True, precedence=None, readonly=False )
Allows overriding the extents of the Element in 2D space defined as four-tuple defining the (left, bottom, right and top) edges.
param ClassSelector y ( allow_None=False, constant=False, default=0, instantiate=True, is_instance=True, pickle_default_value=True, precedence=None, readonly=False )
The y-position of the VLine which make be numeric or a timestamp.
closest ( coords )

Class method that returns the exact keys for a given list of coordinates. The supplied bounds defines the extent within which the samples are drawn and the optional shape argument is the shape of the numpy array (typically the shape of the .data attribute) when applicable.

collapse_data ( data , function=None , kdims=None , **kwargs )

Class method to collapse a list of data matching the data format of the Element type. By implementing this method HoloMap can collapse multiple Elements of the same type. The kwargs are passed to the collapse function. The collapse function must support the numpy style axis selection. Valid function include: np.mean, np.sum, np.product, np.std, scipy.stats.kurtosis etc. Some data backends also require the key dimensions to aggregate over.

ddims

The list of deep dimensions

debug ( msg , *args , **kw )

Print msg merged with args as a debugging statement.

See Python’s logging module for details of message formatting.

defaults ( )

Return {parameter_name:parameter.default} for all non-constant Parameters.

Note that a Parameter for which instantiate==True has its default instantiated.

dimensions ( selection='all' , label=False )

Provides convenient access to Dimensions on nested Dimensioned objects. Dimensions can be selected by their type, i.e. ‘key’ or ‘value’ dimensions. By default ‘all’ dimensions are returned.

force_new_dynamic_value = functools.partial(<function Parameterized.force_new_dynamic_value>, <class 'holoviews.element.annotation.HLine'>)
get_dimension ( dimension , default=None , strict=False )

Access a Dimension object by name or index. Returns the default value if the dimension is not found and strict is False. If strict is True, a KeyError is raised instead.

get_dimension_index ( dim )

Returns the index of the requested dimension.

get_dimension_type ( dim )

Returns the specified Dimension type if specified or if the dimension_values types are consistent otherwise None is returned.

get_param_values = functools.partial(<function Parameterized.get_param_values>, <class 'holoviews.element.annotation.HLine'>)
get_value_generator = functools.partial(<function Parameterized.get_value_generator>, <class 'holoviews.element.annotation.HLine'>)
hist ( dimension=None , num_bins=20 , bin_range=None , adjoin=True , individually=True , **kwargs )

The hist method generates a histogram to be adjoined to the Element in an AdjointLayout. By default the histogram is computed along the first value dimension of the Element, however any dimension may be selected. The number of bins and the bin_ranges and any kwargs to be passed to the histogram operation may also be supplied.

inspect_value = functools.partial(<function Parameterized.inspect_value>, <class 'holoviews.element.annotation.HLine'>)
map ( map_fn , specs=None , clone=True )

Recursively replaces elements using a map function when the specification applies.

matches ( spec )

A specification may be a class, a tuple or a string. Equivalent to isinstance if a class is supplied, otherwise matching occurs on type, group and label. These may be supplied as a tuple of strings or as a single string of the form “{type}.{group}.{label}”. Matching may be done on {type} alone, {type}.{group}, or {type}.{group}.{label}. The strings for the type, group, and label will each be sanitized before the match, and so the sanitized versions of those values will need to be provided if the match is to succeed.

message ( msg , *args , **kw )

Print msg merged with args as a message.

See Python’s logging module for details of message formatting.

options ( options=None , backend=None , clone=True , **kwargs )

Applies options on an object or nested group of objects in a flat format returning a new object with the options applied. If the options are to be set directly on the object a simple format may be used, e.g.:

obj.options(cmap=’viridis’, show_title=False)

If the object is nested the options must be qualified using a type[.group][.label] specification, e.g.:

obj.options(‘Image’, cmap=’viridis’, show_title=False)

or using:

obj.options({‘Image’: dict(cmap=’viridis’, show_title=False)})

If no options are supplied all options on the object will be reset. Disabling clone will modify the object inplace.

opts ( options=None , backend=None , clone=True , **kwargs )

Applies options on an object or nested group of objects in a by options group returning a new object with the options applied. If the options are to be set directly on the object a simple format may be used, e.g.:

obj.opts(style={‘cmap’: ‘viridis’}, plot={‘show_title’: False})

If the object is nested the options must be qualified using a type[.group][.label] specification, e.g.:

obj.opts({‘Image’: {‘plot’: {‘show_title’: False},
‘style’: {‘cmap’: ‘viridis}}})

If no opts are supplied all options on the object will be reset. Disabling clone will modify the object inplace.

params ( parameter_name=None )

Return the Parameters of this class as the dictionary {name: parameter_object}

Includes Parameters from this class and its superclasses.

pprint ( imports=None , prefix=' ' , unknown_value='<?>' , qualify=False , separator='' )

(Experimental) Pretty printed representation that may be evaluated with eval. See pprint() function for more details.

print_param_defaults ( )

Print the default values of all cls’s Parameters.

print_param_values ( )

Print the values of all this object’s Parameters.

range ( dimension , data_range=True )

Returns the range of values along the specified dimension.

If data_range is True, the data may be used to try and infer the appropriate range. Otherwise, (None,None) is returned to indicate that no range is defined.

reduce ( dimensions=[] , function=None , **reduce_map )

Base class signature to demonstrate API for reducing Elements, using some reduce function, e.g. np.mean, which is applied along a particular Dimension. The dimensions and reduce functions should be passed as keyword arguments or as a list of dimensions and a single function.

relabel ( label=None , group=None , depth=0 )

Assign a new label and/or group to an existing LabelledData object, creating a clone of the object with the new settings.

sample ( samples=[] , **sample_values )

Base class signature to demonstrate API for sampling Elements. To sample an Element supply either a list of samples or keyword arguments, where the key should match an existing key dimension on the Element.

script_repr ( imports=[] , prefix=' ' )

Variant of __repr__ designed for generating a runnable script.

select ( selection_specs=None , **kwargs )

Allows slicing or indexing into the Dimensioned object by supplying the dimension and index/slice as key value pairs. Select descends recursively through the data structure applying the key dimension selection. The ‘value’ keyword allows selecting the value dimensions on objects which have any declared.

The selection may also be selectively applied to specific objects by supplying the selection_specs as an iterable of type.group.label specs, types or functions.

set_default ( param_name , value )

Set the default value of param_name.

Equivalent to setting param_name on the class.

set_dynamic_time_fn = functools.partial(<function Parameterized.set_dynamic_time_fn>, <class 'holoviews.element.annotation.HLine'>)
set_param = functools.partial(<function Parameterized.set_param>, <class 'holoviews.element.annotation.HLine'>)
state_pop ( )

Restore the most recently saved state.

See state_push() for more details.

state_push ( )

Save this instance’s state.

For Parameterized instances, this includes the state of dynamically generated values.

Subclasses that maintain short-term state should additionally save and restore that state using state_push() and state_pop().

Generally, this method is used by operations that need to test something without permanently altering the objects’ state.

table ( datatype=None )

Converts the data Element to a Table, optionally may specify a supported data type. The default data types are ‘numpy’ (for homogeneous data), ‘dataframe’, and ‘dictionary’.

traverse ( fn , specs=None , full_breadth=True )

Traverses any nested LabelledData object (i.e LabelledData objects containing LabelledData objects), applying the supplied function to each constituent element if the supplied specifications. The output of these function calls are collected and returned in the accumulator list.

If specs is None, all constituent elements are processed. Otherwise, specs must be a list of type.group.label specs, types, and functions.

verbose ( msg , *args , **kw )

Print msg merged with args as a verbose message.

See Python’s logging module for details of message formatting.

warning ( msg , *args , **kw )

Print msg merged with args as a warning, unless module variable warnings_as_exceptions is True, then raise an Exception containing the arguments.

See Python’s logging module for details of message formatting.

class holoviews.element. Nodes ( data , kdims=None , vdims=None , **kwargs ) [source]

Bases: holoviews.element.chart.Points

Nodes is a simple Element representing Graph nodes as a set of Points. Unlike regular Points, Nodes must define a third key dimension corresponding to the node index.

param String group ( allow_None=False, basestring=<class ‘str’>, constant=True, default=Nodes, instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
A string describing the data wrapped by the object.
param String label ( allow_None=False, basestring=<class ‘str’>, constant=True, default=, instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
Optional label describing the data, typically reflecting where or how it was measured. The label should allow a specific measurement or dataset to be referenced for a given group.
param Dict cdims ( allow_None=False, constant=False, default=OrderedDict(), instantiate=True, is_instance=True, pickle_default_value=True, precedence=None, readonly=False )
The constant dimensions defined as a dictionary of Dimension:value pairs providing additional dimension information about the object. Aliased with constant_dimensions.
param List kdims ( allow_None=False, bounds=(3, 3), constant=False, default=[Dimension(‘x’), Dimension(‘y’), Dimension(‘index’)], instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
The label of the x- and y-dimension of the Points in form of a string or dimension object.
param List vdims ( allow_None=False, bounds=(0, None), constant=False, default=[], instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
The value dimensions of the Chart, usually corresponding to a number of dependent variables.
param Tuple extents ( allow_None=False, constant=False, default=(None, None, None, None), instantiate=False, length=4, pickle_default_value=True, precedence=None, readonly=False )
Allows overriding the extents of the Element in 2D space defined as four-tuple defining the (left, bottom, right and top) edges.
param List datatype ( allow_None=False, bounds=(0, None), constant=False, default=[‘dataframe’, ‘dataframe’, ‘dataframe’, ‘dictionary’, ‘grid’, ‘ndelement’, ‘array’, ‘cube’, ‘xarray’, ‘dask’], instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
A priority list of the data types to be used for storage on the .data attribute. If the input supplied to the element constructor cannot be put into the requested format, the next format listed will be used until a suitable format is found (or the data fails to be understood).
add_dimension ( dimension , dim_pos , dim_val , vdim=False , **kwargs )

Create a new object with an additional key dimensions. Requires the dimension name or object, the desired position in the key dimensions and a key value scalar or sequence of the same length as the existing keys.

aggregate ( dimensions=None , function=None , spreadfn=None , **kwargs )

Aggregates over the supplied key dimensions with the defined function.

clone ( data=None , shared_data=True , new_type=None , *args , **overrides )

Returns a clone of the object with matching parameter values containing the specified args and kwargs.

If shared_data is set to True and no data explicitly supplied, the clone will share data with the original. May also supply a new_type, which will inherit all shared parameters.

closest ( coords=[] , **kwargs )

Given a single coordinate or multiple coordinates as a tuple or list of tuples or keyword arguments matching the dimension closest will find the closest actual x/y coordinates. Different Element types should implement this appropriately depending on the space they represent, if the Element does not support snapping raise NotImplementedError.

collapse_data ( data , function=None , kdims=None , **kwargs )

Class method to collapse a list of data matching the data format of the Element type. By implementing this method HoloMap can collapse multiple Elements of the same type. The kwargs are passed to the collapse function. The collapse function must support the numpy style axis selection. Valid function include: np.mean, np.sum, np.product, np.std, scipy.stats.kurtosis etc. Some data backends also require the key dimensions to aggregate over.

ddims

The list of deep dimensions

debug ( msg , *args , **kw )

Print msg merged with args as a debugging statement.

See Python’s logging module for details of message formatting.

defaults ( )

Return {parameter_name:parameter.default} for all non-constant Parameters.

Note that a Parameter for which instantiate==True has its default instantiated.

dframe ( dimensions=None )

Returns the data in the form of a DataFrame. Supplying a list of dimensions filters the dataframe. If the data is already a DataFrame a copy is returned.

dimension_values ( dim , expanded=True , flat=True )

Returns the values along a particular dimension. If unique values are requested will return only unique values.

dimensions ( selection='all' , label=False )

Provides convenient access to Dimensions on nested Dimensioned objects. Dimensions can be selected by their type, i.e. ‘key’ or ‘value’ dimensions. By default ‘all’ dimensions are returned.

force_new_dynamic_value = functools.partial(<function Parameterized.force_new_dynamic_value>, <class 'holoviews.element.graphs.Nodes'>)
get_dimension ( dimension , default=None , strict=False )

Access a Dimension object by name or index. Returns the default value if the dimension is not found and strict is False. If strict is True, a KeyError is raised instead.

get_dimension_index ( dim )

Returns the index of the requested dimension.

get_dimension_type ( dim )

Returns the specified Dimension type if specified or if the dimension_values types are consistent otherwise None is returned.

get_param_values = functools.partial(<function Parameterized.get_param_values>, <class 'holoviews.element.graphs.Nodes'>)
get_value_generator = functools.partial(<function Parameterized.get_value_generator>, <class 'holoviews.element.graphs.Nodes'>)
groupby ( dimensions=[] , container_type=<class 'holoviews.core.spaces.HoloMap'> , group_type=None , dynamic=False , **kwargs )

Return the results of a groupby operation over the specified dimensions as an object of type container_type (expected to be dictionary-like).

Keys vary over the columns (dimensions) and the corresponding values are collections of group_type (e.g an Element, list, tuple) constructed with kwargs (if supplied).

If dynamic is requested container_type is automatically set to a DynamicMap, allowing dynamic exploration of large datasets. If the data does not represent a full cartesian grid of the requested dimensions some Elements will be empty.

hist ( dimension=None , num_bins=20 , bin_range=None , adjoin=True , individually=True , **kwargs )

The hist method generates a histogram to be adjoined to the Element in an AdjointLayout. By default the histogram is computed along the first value dimension of the Element, however any dimension may be selected. The number of bins and the bin_ranges and any kwargs to be passed to the histogram operation may also be supplied.

iloc

Returns an iloc object providing a convenient interface to slice and index into the Dataset using row and column indices. Allow selection by integer index, slice and list of integer indices and boolean arrays.

Examples:

  • Index the first row and column:

    dataset.iloc[0, 0]

  • Select rows 1 and 2 with a slice:

    dataset.iloc[1:3, :]

  • Select with a list of integer coordinates:

    dataset.iloc[[0, 2, 3]]

inspect_value = functools.partial(<function Parameterized.inspect_value>, <class 'holoviews.element.graphs.Nodes'>)
map ( map_fn , specs=None , clone=True )

Recursively replaces elements using a map function when the specification applies.

matches ( spec )

A specification may be a class, a tuple or a string. Equivalent to isinstance if a class is supplied, otherwise matching occurs on type, group and label. These may be supplied as a tuple of strings or as a single string of the form “{type}.{group}.{label}”. Matching may be done on {type} alone, {type}.{group}, or {type}.{group}.{label}. The strings for the type, group, and label will each be sanitized before the match, and so the sanitized versions of those values will need to be provided if the match is to succeed.

message ( msg , *args , **kw )

Print msg merged with args as a message.

See Python’s logging module for details of message formatting.

ndloc

Returns an ndloc object providing nd-array like indexing for gridded datasets. Follows NumPy array indexing conventions, allowing for indexing, slicing and selecting a list of indices on multi-dimensional arrays using integer indices. The order of array indices is inverted relative to the Dataset key dimensions, e.g. an Image with key dimensions ‘x’ and ‘y’ can be indexed with image.ndloc[iy, ix] , where iy and ix are integer indices along the y and x dimensions.

Examples:

  • Index value in 2D array:

    dataset.ndloc[3, 1]

  • Slice along y-axis of 2D array:

    dataset.ndloc[2:5, :]

  • Vectorized (non-orthogonal) indexing along x- and y-axes:

    dataset.ndloc[[1, 2, 3], [0, 2, 3]]

options ( options=None , backend=None , clone=True , **kwargs )

Applies options on an object or nested group of objects in a flat format returning a new object with the options applied. If the options are to be set directly on the object a simple format may be used, e.g.:

obj.options(cmap=’viridis’, show_title=False)

If the object is nested the options must be qualified using a type[.group][.label] specification, e.g.:

obj.options(‘Image’, cmap=’viridis’, show_title=False)

or using:

obj.options({‘Image’: dict(cmap=’viridis’, show_title=False)})

If no options are supplied all options on the object will be reset. Disabling clone will modify the object inplace.

opts ( options=None , backend=None , clone=True , **kwargs )

Applies options on an object or nested group of objects in a by options group returning a new object with the options applied. If the options are to be set directly on the object a simple format may be used, e.g.:

obj.opts(style={‘cmap’: ‘viridis’}, plot={‘show_title’: False})

If the object is nested the options must be qualified using a type[.group][.label] specification, e.g.:

obj.opts({‘Image’: {‘plot’: {‘show_title’: False},
‘style’: {‘cmap’: ‘viridis}}})

If no opts are supplied all options on the object will be reset. Disabling clone will modify the object inplace.

params ( parameter_name=None )

Return the Parameters of this class as the dictionary {name: parameter_object}

Includes Parameters from this class and its superclasses.

pprint ( imports=None , prefix=' ' , unknown_value='<?>' , qualify=False , separator='' )

(Experimental) Pretty printed representation that may be evaluated with eval. See pprint() function for more details.

print_param_defaults ( )

Print the default values of all cls’s Parameters.

print_param_values ( )

Print the values of all this object’s Parameters.

range ( dim , data_range=True )

Computes the range of values along a supplied dimension, taking into account the range and soft_range defined on the Dimension object.

reduce ( dimensions=[] , function=None , spreadfn=None , **reduce_map )

Allows reducing the values along one or more key dimension with the supplied function. The dimensions may be supplied as a list and a function to apply or a mapping between the dimensions and functions to apply along each dimension.

reindex ( kdims=None , vdims=None )

Create a new object with a re-ordered set of dimensions. Allows converting key dimensions to value dimensions and vice versa.

relabel ( label=None , group=None , depth=0 )

Assign a new label and/or group to an existing LabelledData object, creating a clone of the object with the new settings.

sample ( samples=[] , closest=True , **kwargs )

Allows sampling of Dataset as an iterator of coordinates matching the key dimensions, returning a new object containing just the selected samples. Alternatively may supply kwargs to sample a coordinate on an object. By default it will attempt to snap to the nearest coordinate if the Element supports it, snapping may be disabled with the closest argument.

script_repr ( imports=[] , prefix=' ' )

Variant of __repr__ designed for generating a runnable script.

select ( selection_specs=None , **selection )

Allows selecting data by the slices, sets and scalar values along a particular dimension. The indices should be supplied as keywords mapping between the selected dimension and value. Additionally selection_specs (taking the form of a list of type.group.label strings, types or functions) may be supplied, which will ensure the selection is only applied if the specs match the selected object.

set_default ( param_name , value )

Set the default value of param_name.

Equivalent to setting param_name on the class.

set_dynamic_time_fn = functools.partial(<function Parameterized.set_dynamic_time_fn>, <class 'holoviews.element.graphs.Nodes'>)
set_param = functools.partial(<function Parameterized.set_param>, <class 'holoviews.element.graphs.Nodes'>)
shape

Returns the shape of the data.

sort ( by=[] , reverse=False )

Sorts the data by the values along the supplied dimensions.

state_pop ( )

Restore the most recently saved state.

See state_push() for more details.

state_push ( )

Save this instance’s state.

For Parameterized instances, this includes the state of dynamically generated values.

Subclasses that maintain short-term state should additionally save and restore that state using state_push() and state_pop().

Generally, this method is used by operations that need to test something without permanently altering the objects’ state.

table ( datatype=None )

Converts the data Element to a Table, optionally may specify a supported data type. The default data types are ‘numpy’ (for homogeneous data), ‘dataframe’, and ‘dictionary’.

to

Property to create a conversion interface with methods to convert to other Element types.

traverse ( fn , specs=None , full_breadth=True )

Traverses any nested LabelledData object (i.e LabelledData objects containing LabelledData objects), applying the supplied function to each constituent element if the supplied specifications. The output of these function calls are collected and returned in the accumulator list.

If specs is None, all constituent elements are processed. Otherwise, specs must be a list of type.group.label specs, types, and functions.

verbose ( msg , *args , **kw )

Print msg merged with args as a verbose message.

See Python’s logging module for details of message formatting.

warning ( msg , *args , **kw )

Print msg merged with args as a warning, unless module variable warnings_as_exceptions is True, then raise an Exception containing the arguments.

See Python’s logging module for details of message formatting.

class holoviews.element. Contours ( data , kdims=None , vdims=None , **params ) [source]

Bases: holoviews.element.path.Path

Contours is a type of Path that is also associated with a value (the contour level).

param String group ( allow_None=False, basestring=<class ‘str’>, constant=True, default=Contours, instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
A string describing the data wrapped by the object.
param String label ( allow_None=False, basestring=<class ‘str’>, constant=True, default=, instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
Optional label describing the data, typically reflecting where or how it was measured. The label should allow a specific measurement or dataset to be referenced for a given group.
param Dict cdims ( allow_None=False, constant=False, default=OrderedDict(), instantiate=True, is_instance=True, pickle_default_value=True, precedence=None, readonly=False )
The constant dimensions defined as a dictionary of Dimension:value pairs providing additional dimension information about the object. Aliased with constant_dimensions.
param List kdims ( allow_None=False, bounds=(2, 2), constant=True, default=[Dimension(‘x’), Dimension(‘y’)], instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
The label of the x- and y-dimension of the Image in form of a string or dimension object.
param List vdims ( allow_None=False, bounds=(0, None), constant=True, default=[], instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
Contours optionally accept a value dimension, corresponding to the supplied values.
param Tuple extents ( allow_None=False, constant=False, default=(None, None, None, None), instantiate=False, length=4, pickle_default_value=True, precedence=None, readonly=False )
Allows overriding the extents of the Element in 2D space defined as four-tuple defining the (left, bottom, right and top) edges.
param ObjectSelector datatype ( allow_None=False, check_on_set=False, compute_default_fn=None, constant=False, default=[‘multitabular’], instantiate=True, objects=[], pickle_default_value=True, precedence=None, readonly=False )
A priority list of the data types to be used for storage on the .data attribute. If the input supplied to the element constructor cannot be put into the requested format, the next format listed will be used until a suitable format is found (or the data fails to be understood).
param Number level ( allow_None=True, bounds=None, constant=False, default=None, inclusive_bounds=(True, True), instantiate=False, pickle_default_value=True, precedence=None, readonly=False, softbounds=None, time_dependent=False, time_fn=<Time Time00001> )
Optional level associated with the set of Contours.
add_dimension ( dimension , dim_pos , dim_val , vdim=False , **kwargs )

Create a new object with an additional key dimensions. Requires the dimension name or object, the desired position in the key dimensions and a key value scalar or sequence of the same length as the existing keys.

aggregate ( dimensions=None , function=None , spreadfn=None , **kwargs )

Aggregates over the supplied key dimensions with the defined function.

clone ( data=None , shared_data=True , new_type=None , *args , **overrides )

Returns a clone of the object with matching parameter values containing the specified args and kwargs.

If shared_data is set to True and no data explicitly supplied, the clone will share data with the original. May also supply a new_type, which will inherit all shared parameters.

closest ( coords=[] , **kwargs )

Given a single coordinate or multiple coordinates as a tuple or list of tuples or keyword arguments matching the dimension closest will find the closest actual x/y coordinates. Different Element types should implement this appropriately depending on the space they represent, if the Element does not support snapping raise NotImplementedError.

ddims

The list of deep dimensions

debug ( msg , *args , **kw )

Print msg merged with args as a debugging statement.

See Python’s logging module for details of message formatting.

defaults ( )

Return {parameter_name:parameter.default} for all non-constant Parameters.

Note that a Parameter for which instantiate==True has its default instantiated.

dframe ( dimensions=None )

Returns the data in the form of a DataFrame. Supplying a list of dimensions filters the dataframe. If the data is already a DataFrame a copy is returned.

dimensions ( selection='all' , label=False )

Provides convenient access to Dimensions on nested Dimensioned objects. Dimensions can be selected by their type, i.e. ‘key’ or ‘value’ dimensions. By default ‘all’ dimensions are returned.

force_new_dynamic_value = functools.partial(<function Parameterized.force_new_dynamic_value>, <class 'holoviews.element.path.Contours'>)
get_dimension ( dimension , default=None , strict=False )

Access a Dimension object by name or index. Returns the default value if the dimension is not found and strict is False. If strict is True, a KeyError is raised instead.

get_dimension_index ( dim )

Returns the index of the requested dimension.

get_dimension_type ( dim )

Returns the specified Dimension type if specified or if the dimension_values types are consistent otherwise None is returned.

get_param_values = functools.partial(<function Parameterized.get_param_values>, <class 'holoviews.element.path.Contours'>)
get_value_generator = functools.partial(<function Parameterized.get_value_generator>, <class 'holoviews.element.path.Contours'>)
groupby ( dimensions=[] , container_type=<class 'holoviews.core.spaces.HoloMap'> , group_type=None , dynamic=False , **kwargs )

Return the results of a groupby operation over the specified dimensions as an object of type container_type (expected to be dictionary-like).

Keys vary over the columns (dimensions) and the corresponding values are collections of group_type (e.g an Element, list, tuple) constructed with kwargs (if supplied).

If dynamic is requested container_type is automatically set to a DynamicMap, allowing dynamic exploration of large datasets. If the data does not represent a full cartesian grid of the requested dimensions some Elements will be empty.

hist ( dimension=None , num_bins=20 , bin_range=None , adjoin=True , individually=True , **kwargs )

The hist method generates a histogram to be adjoined to the Element in an AdjointLayout. By default the histogram is computed along the first value dimension of the Element, however any dimension may be selected. The number of bins and the bin_ranges and any kwargs to be passed to the histogram operation may also be supplied.

iloc

Returns an iloc object providing a convenient interface to slice and index into the Dataset using row and column indices. Allow selection by integer index, slice and list of integer indices and boolean arrays.

Examples:

  • Index the first row and column:

    dataset.iloc[0, 0]

  • Select rows 1 and 2 with a slice:

    dataset.iloc[1:3, :]

  • Select with a list of integer coordinates:

    dataset.iloc[[0, 2, 3]]

inspect_value = functools.partial(<function Parameterized.inspect_value>, <class 'holoviews.element.path.Contours'>)
map ( map_fn , specs=None , clone=True )

Recursively replaces elements using a map function when the specification applies.

matches ( spec )

A specification may be a class, a tuple or a string. Equivalent to isinstance if a class is supplied, otherwise matching occurs on type, group and label. These may be supplied as a tuple of strings or as a single string of the form “{type}.{group}.{label}”. Matching may be done on {type} alone, {type}.{group}, or {type}.{group}.{label}. The strings for the type, group, and label will each be sanitized before the match, and so the sanitized versions of those values will need to be provided if the match is to succeed.

message ( msg , *args , **kw )

Print msg merged with args as a message.

See Python’s logging module for details of message formatting.

ndloc

Returns an ndloc object providing nd-array like indexing for gridded datasets. Follows NumPy array indexing conventions, allowing for indexing, slicing and selecting a list of indices on multi-dimensional arrays using integer indices. The order of array indices is inverted relative to the Dataset key dimensions, e.g. an Image with key dimensions ‘x’ and ‘y’ can be indexed with image.ndloc[iy, ix] , where iy and ix are integer indices along the y and x dimensions.

Examples:

  • Index value in 2D array:

    dataset.ndloc[3, 1]

  • Slice along y-axis of 2D array:

    dataset.ndloc[2:5, :]

  • Vectorized (non-orthogonal) indexing along x- and y-axes:

    dataset.ndloc[[1, 2, 3], [0, 2, 3]]

options ( options=None , backend=None , clone=True , **kwargs )

Applies options on an object or nested group of objects in a flat format returning a new object with the options applied. If the options are to be set directly on the object a simple format may be used, e.g.:

obj.options(cmap=’viridis’, show_title=False)

If the object is nested the options must be qualified using a type[.group][.label] specification, e.g.:

obj.options(‘Image’, cmap=’viridis’, show_title=False)

or using:

obj.options({‘Image’: dict(cmap=’viridis’, show_title=False)})

If no options are supplied all options on the object will be reset. Disabling clone will modify the object inplace.

opts ( options=None , backend=None , clone=True , **kwargs )

Applies options on an object or nested group of objects in a by options group returning a new object with the options applied. If the options are to be set directly on the object a simple format may be used, e.g.:

obj.opts(style={‘cmap’: ‘viridis’}, plot={‘show_title’: False})

If the object is nested the options must be qualified using a type[.group][.label] specification, e.g.:

obj.opts({‘Image’: {‘plot’: {‘show_title’: False},
‘style’: {‘cmap’: ‘viridis}}})

If no opts are supplied all options on the object will be reset. Disabling clone will modify the object inplace.

params ( parameter_name=None )

Return the Parameters of this class as the dictionary {name: parameter_object}

Includes Parameters from this class and its superclasses.

pprint ( imports=None , prefix=' ' , unknown_value='<?>' , qualify=False , separator='' )

(Experimental) Pretty printed representation that may be evaluated with eval. See pprint() function for more details.

print_param_defaults ( )

Print the default values of all cls’s Parameters.

print_param_values ( )

Print the values of all this object’s Parameters.

range ( dim , data_range=True )

Computes the range of values along a supplied dimension, taking into account the range and soft_range defined on the Dimension object.

reduce ( dimensions=[] , function=None , spreadfn=None , **reduce_map )

Allows reducing the values along one or more key dimension with the supplied function. The dimensions may be supplied as a list and a function to apply or a mapping between the dimensions and functions to apply along each dimension.

reindex ( kdims=None , vdims=None )

Create a new object with a re-ordered set of dimensions. Allows converting key dimensions to value dimensions and vice versa.

relabel ( label=None , group=None , depth=0 )

Assign a new label and/or group to an existing LabelledData object, creating a clone of the object with the new settings.

sample ( samples=[] , closest=True , **kwargs )

Allows sampling of Dataset as an iterator of coordinates matching the key dimensions, returning a new object containing just the selected samples. Alternatively may supply kwargs to sample a coordinate on an object. By default it will attempt to snap to the nearest coordinate if the Element supports it, snapping may be disabled with the closest argument.

script_repr ( imports=[] , prefix=' ' )

Variant of __repr__ designed for generating a runnable script.

select ( selection_specs=None , **kwargs )

Bypasses selection on data and sets extents based on selection.

set_default ( param_name , value )

Set the default value of param_name.

Equivalent to setting param_name on the class.

set_dynamic_time_fn = functools.partial(<function Parameterized.set_dynamic_time_fn>, <class 'holoviews.element.path.Contours'>)
set_param = functools.partial(<function Parameterized.set_param>, <class 'holoviews.element.path.Contours'>)
shape

Returns the shape of the data.

sort ( by=[] , reverse=False )

Sorts the data by the values along the supplied dimensions.

split ( start=None , end=None , datatype=None , **kwargs )

The split method allows splitting a Path type into a list of subpaths of the same type. A start and/or end may be supplied to select a subset of paths.

state_pop ( )

Restore the most recently saved state.

See state_push() for more details.

state_push ( )

Save this instance’s state.

For Parameterized instances, this includes the state of dynamically generated values.

Subclasses that maintain short-term state should additionally save and restore that state using state_push() and state_pop().

Generally, this method is used by operations that need to test something without permanently altering the objects’ state.

table ( datatype=None )

Converts the data Element to a Table, optionally may specify a supported data type. The default data types are ‘numpy’ (for homogeneous data), ‘dataframe’, and ‘dictionary’.

to

Property to create a conversion interface with methods to convert to other Element types.

traverse ( fn , specs=None , full_breadth=True )

Traverses any nested LabelledData object (i.e LabelledData objects containing LabelledData objects), applying the supplied function to each constituent element if the supplied specifications. The output of these function calls are collected and returned in the accumulator list.

If specs is None, all constituent elements are processed. Otherwise, specs must be a list of type.group.label specs, types, and functions.

verbose ( msg , *args , **kw )

Print msg merged with args as a verbose message.

See Python’s logging module for details of message formatting.

warning ( msg , *args , **kw )

Print msg merged with args as a warning, unless module variable warnings_as_exceptions is True, then raise an Exception containing the arguments.

See Python’s logging module for details of message formatting.

class holoviews.element. HSV ( data , kdims=None , vdims=None , **params ) [source]

Bases: holoviews.element.raster.RGB

Example of a commonly used color space subclassed from RGB used for working in a HSV (hue, saturation and value) color space.

param String group ( allow_None=False, basestring=<class ‘str’>, constant=True, default=HSV, instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
A string describing the data wrapped by the object.
param String label ( allow_None=False, basestring=<class ‘str’>, constant=True, default=, instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
Optional label describing the data, typically reflecting where or how it was measured. The label should allow a specific measurement or dataset to be referenced for a given group.
param Dict cdims ( allow_None=False, constant=False, default=OrderedDict(), instantiate=True, is_instance=True, pickle_default_value=True, precedence=None, readonly=False )
The constant dimensions defined as a dictionary of Dimension:value pairs providing additional dimension information about the object. Aliased with constant_dimensions.
param List kdims ( allow_None=False, bounds=(2, 2), constant=True, default=[Dimension(‘x’), Dimension(‘y’)], instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
The label of the x- and y-dimension of the Raster in the form of a string or dimension object.
param List vdims ( allow_None=False, bounds=(3, 4), constant=False, default=[Dimension(‘H’), Dimension(‘S’), Dimension(‘V’)], instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
The dimension description of the data held in the array. If an alpha channel is supplied, the defined alpha_dimension is automatically appended to this list.
param Tuple extents ( allow_None=False, constant=False, default=(None, None, None, None), instantiate=False, length=4, pickle_default_value=True, precedence=None, readonly=False )
Allows overriding the extents of the Element in 2D space defined as four-tuple defining the (left, bottom, right and top) edges.
param List datatype ( allow_None=False, bounds=(0, None), constant=False, default=[‘image’, ‘grid’, ‘xarray’, ‘cube’, ‘dataframe’, ‘dictionary’], instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
A priority list of the data types to be used for storage on the .data attribute. If the input supplied to the element constructor cannot be put into the requested format, the next format listed will be used until a suitable format is found (or the data fails to be understood).
param ClassSelector bounds ( allow_None=False, constant=False, default=BoundingBox(radius=0.5), instantiate=True, is_instance=True, pickle_default_value=True, precedence=None, readonly=False )
The bounding region in sheet coordinates containing the data.
param Number rtol ( allow_None=True, bounds=None, constant=False, default=None, inclusive_bounds=(True, True), instantiate=False, pickle_default_value=True, precedence=None, readonly=False, softbounds=None, time_dependent=False, time_fn=<Time Time00001> )
The tolerance used to enforce regular sampling for regular, gridded data where regular sampling is expected. Expressed as the maximal allowable sampling difference between sample locations.
param ClassSelector alpha_dimension ( allow_None=False, constant=False, default=A, instantiate=False, is_instance=True, pickle_default_value=True, precedence=None, readonly=False )
The alpha dimension definition to add the value dimensions if an alpha channel is supplied.
add_dimension ( dimension , dim_pos , dim_val , vdim=False , **kwargs )

Create a new object with an additional key dimensions. Requires the dimension name or object, the desired position in the key dimensions and a key value scalar or sequence of the same length as the existing keys.

clone ( data=None , shared_data=True , new_type=None , *args , **overrides )

Returns a clone of the object with matching parameter values containing the specified args and kwargs.

If shared_data is set to True and no data explicitly supplied, the clone will share data with the original. May also supply a new_type, which will inherit all shared parameters.

closest ( coords=[] , **kwargs )

Given a single coordinate or multiple coordinates as a tuple or list of tuples or keyword arguments matching the dimension closest will find the closest actual x/y coordinates.

closest_cell_center ( x , y )

Given arbitrary sheet coordinates, return the sheet coordinates of the center of the closest unit.

ddims

The list of deep dimensions

debug ( msg , *args , **kw )

Print msg merged with args as a debugging statement.

See Python’s logging module for details of message formatting.

defaults ( )

Return {parameter_name:parameter.default} for all non-constant Parameters.

Note that a Parameter for which instantiate==True has its default instantiated.

dframe ( dimensions=None )

Returns the data in the form of a DataFrame. Supplying a list of dimensions filters the dataframe. If the data is already a DataFrame a copy is returned.

dimension_values ( dim , expanded=True , flat=True )

Returns the values along a particular dimension. If unique values are requested will return only unique values.

dimensions ( selection='all' , label=False )

Provides convenient access to Dimensions on nested Dimensioned objects. Dimensions can be selected by their type, i.e. ‘key’ or ‘value’ dimensions. By default ‘all’ dimensions are returned.

force_new_dynamic_value = functools.partial(<function Parameterized.force_new_dynamic_value>, <class 'holoviews.element.raster.HSV'>)
get_dimension ( dimension , default=None , strict=False )

Access a Dimension object by name or index. Returns the default value if the dimension is not found and strict is False. If strict is True, a KeyError is raised instead.

get_dimension_index ( dim )

Returns the index of the requested dimension.

get_dimension_type ( dim )

Returns the specified Dimension type if specified or if the dimension_values types are consistent otherwise None is returned.

get_param_values = functools.partial(<function Parameterized.get_param_values>, <class 'holoviews.element.raster.HSV'>)
get_value_generator = functools.partial(<function Parameterized.get_value_generator>, <class 'holoviews.element.raster.HSV'>)
groupby ( dimensions=[] , container_type=<class 'holoviews.core.spaces.HoloMap'> , group_type=None , dynamic=False , **kwargs )

Return the results of a groupby operation over the specified dimensions as an object of type container_type (expected to be dictionary-like).

Keys vary over the columns (dimensions) and the corresponding values are collections of group_type (e.g an Element, list, tuple) constructed with kwargs (if supplied).

If dynamic is requested container_type is automatically set to a DynamicMap, allowing dynamic exploration of large datasets. If the data does not represent a full cartesian grid of the requested dimensions some Elements will be empty.

hist ( dimension=None , num_bins=20 , bin_range=None , adjoin=True , individually=True , **kwargs )

The hist method generates a histogram to be adjoined to the Element in an AdjointLayout. By default the histogram is computed along the first value dimension of the Element, however any dimension may be selected. The number of bins and the bin_ranges and any kwargs to be passed to the histogram operation may also be supplied.

iloc

Returns an iloc object providing a convenient interface to slice and index into the Dataset using row and column indices. Allow selection by integer index, slice and list of integer indices and boolean arrays.

Examples:

  • Index the first row and column:

    dataset.iloc[0, 0]

  • Select rows 1 and 2 with a slice:

    dataset.iloc[1:3, :]

  • Select with a list of integer coordinates:

    dataset.iloc[[0, 2, 3]]

inspect_value = functools.partial(<function Parameterized.inspect_value>, <class 'holoviews.element.raster.HSV'>)
load_image ( filename , height=1 , array=False , bounds=None , bare=False , **kwargs )

Returns an raster element or raw numpy array from a PNG image file, using matplotlib.

The specified height determines the bounds of the raster object in sheet coordinates: by default the height is 1 unit with the width scaled appropriately by the image aspect ratio.

Note that as PNG images are encoded as RGBA, the red component maps to the first channel, the green component maps to the second component etc. For RGB elements, this mapping is trivial but may be important for subclasses e.g. for HSV elements.

Setting bare=True will apply options disabling axis labels displaying just the bare image. Any additional keyword arguments will be passed to the Image object.

map ( map_fn , specs=None , clone=True )

Recursively replaces elements using a map function when the specification applies.

matches ( spec )

A specification may be a class, a tuple or a string. Equivalent to isinstance if a class is supplied, otherwise matching occurs on type, group and label. These may be supplied as a tuple of strings or as a single string of the form “{type}.{group}.{label}”. Matching may be done on {type} alone, {type}.{group}, or {type}.{group}.{label}. The strings for the type, group, and label will each be sanitized before the match, and so the sanitized versions of those values will need to be provided if the match is to succeed.

matrix2sheet ( float_row , float_col )

Convert a floating-point location (float_row,float_col) in matrix coordinates to its corresponding location (x,y) in sheet coordinates.

Valid for scalar or array float_row and float_col.

Inverse of sheet2matrix().

matrixidx2sheet ( row , col )

Return (x,y) where x and y are the floating point coordinates of the center of the given matrix cell (row,col). If the matrix cell represents a 0.2 by 0.2 region, then the center location returned would be 0.1,0.1.

NOTE: This is NOT the strict mathematical inverse of sheet2matrixidx(), because sheet2matrixidx() discards all but the integer portion of the continuous matrix coordinate.

Valid only for scalar or array row and col.

message ( msg , *args , **kw )

Print msg merged with args as a message.

See Python’s logging module for details of message formatting.

ndloc

Returns an ndloc object providing nd-array like indexing for gridded datasets. Follows NumPy array indexing conventions, allowing for indexing, slicing and selecting a list of indices on multi-dimensional arrays using integer indices. The order of array indices is inverted relative to the Dataset key dimensions, e.g. an Image with key dimensions ‘x’ and ‘y’ can be indexed with image.ndloc[iy, ix] , where iy and ix are integer indices along the y and x dimensions.

Examples:

  • Index value in 2D array:

    dataset.ndloc[3, 1]

  • Slice along y-axis of 2D array:

    dataset.ndloc[2:5, :]

  • Vectorized (non-orthogonal) indexing along x- and y-axes:

    dataset.ndloc[[1, 2, 3], [0, 2, 3]]

options ( options=None , backend=None , clone=True , **kwargs )

Applies options on an object or nested group of objects in a flat format returning a new object with the options applied. If the options are to be set directly on the object a simple format may be used, e.g.:

obj.options(cmap=’viridis’, show_title=False)

If the object is nested the options must be qualified using a type[.group][.label] specification, e.g.:

obj.options(‘Image’, cmap=’viridis’, show_title=False)

or using:

obj.options({‘Image’: dict(cmap=’viridis’, show_title=False)})

If no options are supplied all options on the object will be reset. Disabling clone will modify the object inplace.

opts ( options=None , backend=None , clone=True , **kwargs )

Applies options on an object or nested group of objects in a by options group returning a new object with the options applied. If the options are to be set directly on the object a simple format may be used, e.g.:

obj.opts(style={‘cmap’: ‘viridis’}, plot={‘show_title’: False})

If the object is nested the options must be qualified using a type[.group][.label] specification, e.g.:

obj.opts({‘Image’: {‘plot’: {‘show_title’: False},
‘style’: {‘cmap’: ‘viridis}}})

If no opts are supplied all options on the object will be reset. Disabling clone will modify the object inplace.

params ( parameter_name=None )

Return the Parameters of this class as the dictionary {name: parameter_object}

Includes Parameters from this class and its superclasses.

pprint ( imports=None , prefix=' ' , unknown_value='<?>' , qualify=False , separator='' )

(Experimental) Pretty printed representation that may be evaluated with eval. See pprint() function for more details.

print_param_defaults ( )

Print the default values of all cls’s Parameters.

print_param_values ( )

Print the values of all this object’s Parameters.

reduce ( dimensions=[] , function=None , spreadfn=None , **reduce_map )

Allows reducing the values along one or more key dimension with the supplied function. The dimensions may be supplied as a list and a function to apply or a mapping between the dimensions and functions to apply along each dimension.

reindex ( kdims=None , vdims=None )

Create a new object with a re-ordered set of dimensions. Allows converting key dimensions to value dimensions and vice versa.

relabel ( label=None , group=None , depth=0 )

Assign a new label and/or group to an existing LabelledData object, creating a clone of the object with the new settings.

rgb

Conversion from HSV to RGB.

sample ( samples=[] , **kwargs )

Allows sampling of an Image as an iterator of coordinates matching the key dimensions, returning a new object containing just the selected samples. Alternatively may supply kwargs to sample a coordinate on an object. On an Image the coordinates are continuously indexed and will always snap to the nearest coordinate.

script_repr ( imports=[] , prefix=' ' )

Variant of __repr__ designed for generating a runnable script.

select ( selection_specs=None , **selection )

Allows selecting data by the slices, sets and scalar values along a particular dimension. The indices should be supplied as keywords mapping between the selected dimension and value. Additionally selection_specs (taking the form of a list of type.group.label strings, types or functions) may be supplied, which will ensure the selection is only applied if the specs match the selected object.

set_default ( param_name , value )

Set the default value of param_name.

Equivalent to setting param_name on the class.

set_dynamic_time_fn = functools.partial(<function Parameterized.set_dynamic_time_fn>, <class 'holoviews.element.raster.HSV'>)
set_param = functools.partial(<function Parameterized.set_param>, <class 'holoviews.element.raster.HSV'>)
shape

Returns the shape of the data.

sheet2matrix ( x , y )

Convert a point (x,y) in Sheet coordinates to continuous matrix coordinates.

Returns (float_row,float_col), where float_row corresponds to y, and float_col to x.

Valid for scalar or array x and y.

Note about Bounds For a Sheet with BoundingBox(points=((-0.5,-0.5),(0.5,0.5))) and density=3, x=-0.5 corresponds to float_col=0.0 and x=0.5 corresponds to float_col=3.0. float_col=3.0 is not inside the matrix representing this Sheet, which has the three columns (0,1,2). That is, x=-0.5 is inside the BoundingBox but x=0.5 is outside. Similarly, y=0.5 is inside (at row 0) but y=-0.5 is outside (at row 3) (it’s the other way round for y because the matrix row index increases as y decreases).

sheet2matrixidx ( x , y )

Convert a point (x,y) in sheet coordinates to the integer row and column index of the matrix cell in which that point falls, given a bounds and density. Returns (row,column).

Note that if coordinates along the right or bottom boundary are passed into this function, the returned matrix coordinate of the boundary will be just outside the matrix, because the right and bottom boundaries are exclusive.

Valid for scalar or array x and y.

sheetcoordinates_of_matrixidx ( )

Return x,y where x is a vector of sheet coordinates representing the x-center of each matrix cell, and y represents the corresponding y-center of the cell.

sort ( by=[] , reverse=False )

Sorts the data by the values along the supplied dimensions.

state_pop ( )

Restore the most recently saved state.

See state_push() for more details.

state_push ( )

Save this instance’s state.

For Parameterized instances, this includes the state of dynamically generated values.

Subclasses that maintain short-term state should additionally save and restore that state using state_push() and state_pop().

Generally, this method is used by operations that need to test something without permanently altering the objects’ state.

table ( datatype=None )

Converts the data Element to a Table, optionally may specify a supported data type. The default data types are ‘numpy’ (for homogeneous data), ‘dataframe’, and ‘dictionary’.

to

Property to create a conversion interface with methods to convert to other Element types.

traverse ( fn , specs=None , full_breadth=True )

Traverses any nested LabelledData object (i.e LabelledData objects containing LabelledData objects), applying the supplied function to each constituent element if the supplied specifications. The output of these function calls are collected and returned in the accumulator list.

If specs is None, all constituent elements are processed. Otherwise, specs must be a list of type.group.label specs, types, and functions.

verbose ( msg , *args , **kw )

Print msg merged with args as a verbose message.

See Python’s logging module for details of message formatting.

warning ( msg , *args , **kw )

Print msg merged with args as a warning, unless module variable warnings_as_exceptions is True, then raise an Exception containing the arguments.

See Python’s logging module for details of message formatting.

xdensity

The spacing between elements in an underlying matrix representation, in the x direction.

ydensity

The spacing between elements in an underlying matrix representation, in the y direction.

class holoviews.element. QuadMesh ( data , kdims=None , vdims=None , **params ) [source]

Bases: holoviews.core.data.Dataset , holoviews.core.element.Element2D

QuadMesh is a Raster type to hold x- and y- bin values with associated values. The x- and y-values of the QuadMesh may be supplied either as the edges of each bin allowing uneven sampling or as the bin centers, which will be converted to evenly sampled edges.

As a secondary but less supported mode QuadMesh can contain a mesh of quadrilateral coordinates that is not laid out in a grid. The data should then be supplied as three separate 2D arrays for the x-/y-coordinates and grid values.

param String group ( allow_None=False, basestring=<class ‘str’>, constant=True, default=QuadMesh, instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
A string describing the data wrapped by the object.
param String label ( allow_None=False, basestring=<class ‘str’>, constant=True, default=, instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
Optional label describing the data, typically reflecting where or how it was measured. The label should allow a specific measurement or dataset to be referenced for a given group.
param Dict cdims ( allow_None=False, constant=False, default=OrderedDict(), instantiate=True, is_instance=True, pickle_default_value=True, precedence=None, readonly=False )
The constant dimensions defined as a dictionary of Dimension:value pairs providing additional dimension information about the object. Aliased with constant_dimensions.
param List kdims ( allow_None=False, bounds=(2, 2), constant=True, default=[Dimension(‘x’), Dimension(‘y’)], instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
The key dimensions defined as list of dimensions that may be used in indexing (and potential slicing) semantics. The order of the dimensions listed here determines the semantics of each component of a multi-dimensional indexing operation. Aliased with key_dimensions.
param List vdims ( allow_None=False, bounds=(1, None), constant=False, default=[Dimension(‘z’)], instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
The value dimensions defined as the list of dimensions used to describe the components of the data. If multiple value dimensions are supplied, a particular value dimension may be indexed by name after the key dimensions. Aliased with value_dimensions.
param Tuple extents ( allow_None=False, constant=False, default=(None, None, None, None), instantiate=False, length=4, pickle_default_value=True, precedence=None, readonly=False )
Allows overriding the extents of the Element in 2D space defined as four-tuple defining the (left, bottom, right and top) edges.
param List datatype ( allow_None=False, bounds=(0, None), constant=False, default=[‘dataframe’, ‘dataframe’, ‘dataframe’, ‘dictionary’, ‘grid’, ‘ndelement’, ‘array’, ‘cube’, ‘xarray’, ‘dask’], instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
A priority list of the data types to be used for storage on the .data attribute. If the input supplied to the element constructor cannot be put into the requested format, the next format listed will be used until a suitable format is found (or the data fails to be understood).
add_dimension ( dimension , dim_pos , dim_val , vdim=False , **kwargs )

Create a new object with an additional key dimensions. Requires the dimension name or object, the desired position in the key dimensions and a key value scalar or sequence of the same length as the existing keys.

aggregate ( dimensions=None , function=None , spreadfn=None , **kwargs )

Aggregates over the supplied key dimensions with the defined function.

clone ( data=None , shared_data=True , new_type=None , *args , **overrides )

Returns a clone of the object with matching parameter values containing the specified args and kwargs.

If shared_data is set to True and no data explicitly supplied, the clone will share data with the original. May also supply a new_type, which will inherit all shared parameters.

closest ( coords=[] , **kwargs )

Given a single coordinate or multiple coordinates as a tuple or list of tuples or keyword arguments matching the dimension closest will find the closest actual x/y coordinates. Different Element types should implement this appropriately depending on the space they represent, if the Element does not support snapping raise NotImplementedError.

collapse_data ( data , function=None , kdims=None , **kwargs )

Class method to collapse a list of data matching the data format of the Element type. By implementing this method HoloMap can collapse multiple Elements of the same type. The kwargs are passed to the collapse function. The collapse function must support the numpy style axis selection. Valid function include: np.mean, np.sum, np.product, np.std, scipy.stats.kurtosis etc. Some data backends also require the key dimensions to aggregate over.

ddims

The list of deep dimensions

debug ( msg , *args , **kw )

Print msg merged with args as a debugging statement.

See Python’s logging module for details of message formatting.

defaults ( )

Return {parameter_name:parameter.default} for all non-constant Parameters.

Note that a Parameter for which instantiate==True has its default instantiated.

dframe ( dimensions=None )

Returns the data in the form of a DataFrame. Supplying a list of dimensions filters the dataframe. If the data is already a DataFrame a copy is returned.

dimension_values ( dim , expanded=True , flat=True )

Returns the values along a particular dimension. If unique values are requested will return only unique values.

dimensions ( selection='all' , label=False )

Provides convenient access to Dimensions on nested Dimensioned objects. Dimensions can be selected by their type, i.e. ‘key’ or ‘value’ dimensions. By default ‘all’ dimensions are returned.

force_new_dynamic_value = functools.partial(<function Parameterized.force_new_dynamic_value>, <class 'holoviews.element.raster.QuadMesh'>)
get_dimension ( dimension , default=None , strict=False )

Access a Dimension object by name or index. Returns the default value if the dimension is not found and strict is False. If strict is True, a KeyError is raised instead.

get_dimension_index ( dim )

Returns the index of the requested dimension.

get_dimension_type ( dim )

Returns the specified Dimension type if specified or if the dimension_values types are consistent otherwise None is returned.

get_param_values = functools.partial(<function Parameterized.get_param_values>, <class 'holoviews.element.raster.QuadMesh'>)
get_value_generator = functools.partial(<function Parameterized.get_value_generator>, <class 'holoviews.element.raster.QuadMesh'>)
groupby ( dimensions=[] , container_type=<class 'holoviews.core.spaces.HoloMap'> , group_type=None , dynamic=False , **kwargs )

Return the results of a groupby operation over the specified dimensions as an object of type container_type (expected to be dictionary-like).

Keys vary over the columns (dimensions) and the corresponding values are collections of group_type (e.g an Element, list, tuple) constructed with kwargs (if supplied).

If dynamic is requested container_type is automatically set to a DynamicMap, allowing dynamic exploration of large datasets. If the data does not represent a full cartesian grid of the requested dimensions some Elements will be empty.

hist ( dimension=None , num_bins=20 , bin_range=None , adjoin=True , individually=True , **kwargs )

The hist method generates a histogram to be adjoined to the Element in an AdjointLayout. By default the histogram is computed along the first value dimension of the Element, however any dimension may be selected. The number of bins and the bin_ranges and any kwargs to be passed to the histogram operation may also be supplied.

iloc

Returns an iloc object providing a convenient interface to slice and index into the Dataset using row and column indices. Allow selection by integer index, slice and list of integer indices and boolean arrays.

Examples:

  • Index the first row and column:

    dataset.iloc[0, 0]

  • Select rows 1 and 2 with a slice:

    dataset.iloc[1:3, :]

  • Select with a list of integer coordinates:

    dataset.iloc[[0, 2, 3]]

inspect_value = functools.partial(<function Parameterized.inspect_value>, <class 'holoviews.element.raster.QuadMesh'>)
map ( map_fn , specs=None , clone=True )

Recursively replaces elements using a map function when the specification applies.

matches ( spec )

A specification may be a class, a tuple or a string. Equivalent to isinstance if a class is supplied, otherwise matching occurs on type, group and label. These may be supplied as a tuple of strings or as a single string of the form “{type}.{group}.{label}”. Matching may be done on {type} alone, {type}.{group}, or {type}.{group}.{label}. The strings for the type, group, and label will each be sanitized before the match, and so the sanitized versions of those values will need to be provided if the match is to succeed.

message ( msg , *args , **kw )

Print msg merged with args as a message.

See Python’s logging module for details of message formatting.

ndloc

Returns an ndloc object providing nd-array like indexing for gridded datasets. Follows NumPy array indexing conventions, allowing for indexing, slicing and selecting a list of indices on multi-dimensional arrays using integer indices. The order of array indices is inverted relative to the Dataset key dimensions, e.g. an Image with key dimensions ‘x’ and ‘y’ can be indexed with image.ndloc[iy, ix] , where iy and ix are integer indices along the y and x dimensions.

Examples:

  • Index value in 2D array:

    dataset.ndloc[3, 1]

  • Slice along y-axis of 2D array:

    dataset.ndloc[2:5, :]

  • Vectorized (non-orthogonal) indexing along x- and y-axes:

    dataset.ndloc[[1, 2, 3], [0, 2, 3]]

options ( options=None , backend=None , clone=True , **kwargs )

Applies options on an object or nested group of objects in a flat format returning a new object with the options applied. If the options are to be set directly on the object a simple format may be used, e.g.:

obj.options(cmap=’viridis’, show_title=False)

If the object is nested the options must be qualified using a type[.group][.label] specification, e.g.:

obj.options(‘Image’, cmap=’viridis’, show_title=False)

or using:

obj.options({‘Image’: dict(cmap=’viridis’, show_title=False)})

If no options are supplied all options on the object will be reset. Disabling clone will modify the object inplace.

opts ( options=None , backend=None , clone=True , **kwargs )

Applies options on an object or nested group of objects in a by options group returning a new object with the options applied. If the options are to be set directly on the object a simple format may be used, e.g.:

obj.opts(style={‘cmap’: ‘viridis’}, plot={‘show_title’: False})

If the object is nested the options must be qualified using a type[.group][.label] specification, e.g.:

obj.opts({‘Image’: {‘plot’: {‘show_title’: False},
‘style’: {‘cmap’: ‘viridis}}})

If no opts are supplied all options on the object will be reset. Disabling clone will modify the object inplace.

params ( parameter_name=None )

Return the Parameters of this class as the dictionary {name: parameter_object}

Includes Parameters from this class and its superclasses.

pprint ( imports=None , prefix=' ' , unknown_value='<?>' , qualify=False , separator='' )

(Experimental) Pretty printed representation that may be evaluated with eval. See pprint() function for more details.

print_param_defaults ( )

Print the default values of all cls’s Parameters.

print_param_values ( )

Print the values of all this object’s Parameters.

range ( dim , data_range=True )

Computes the range of values along a supplied dimension, taking into account the range and soft_range defined on the Dimension object.

reduce ( dimensions=[] , function=None , spreadfn=None , **reduce_map )

Allows reducing the values along one or more key dimension with the supplied function. The dimensions may be supplied as a list and a function to apply or a mapping between the dimensions and functions to apply along each dimension.

reindex ( kdims=None , vdims=None )

Create a new object with a re-ordered set of dimensions. Allows converting key dimensions to value dimensions and vice versa.

relabel ( label=None , group=None , depth=0 )

Assign a new label and/or group to an existing LabelledData object, creating a clone of the object with the new settings.

sample ( samples=[] , closest=True , **kwargs )

Allows sampling of Dataset as an iterator of coordinates matching the key dimensions, returning a new object containing just the selected samples. Alternatively may supply kwargs to sample a coordinate on an object. By default it will attempt to snap to the nearest coordinate if the Element supports it, snapping may be disabled with the closest argument.

script_repr ( imports=[] , prefix=' ' )

Variant of __repr__ designed for generating a runnable script.

select ( selection_specs=None , **selection )

Allows selecting data by the slices, sets and scalar values along a particular dimension. The indices should be supplied as keywords mapping between the selected dimension and value. Additionally selection_specs (taking the form of a list of type.group.label strings, types or functions) may be supplied, which will ensure the selection is only applied if the specs match the selected object.

set_default ( param_name , value )

Set the default value of param_name.

Equivalent to setting param_name on the class.

set_dynamic_time_fn = functools.partial(<function Parameterized.set_dynamic_time_fn>, <class 'holoviews.element.raster.QuadMesh'>)
set_param = functools.partial(<function Parameterized.set_param>, <class 'holoviews.element.raster.QuadMesh'>)
shape

Returns the shape of the data.

sort ( by=[] , reverse=False )

Sorts the data by the values along the supplied dimensions.

state_pop ( )

Restore the most recently saved state.

See state_push() for more details.

state_push ( )

Save this instance’s state.

For Parameterized instances, this includes the state of dynamically generated values.

Subclasses that maintain short-term state should additionally save and restore that state using state_push() and state_pop().

Generally, this method is used by operations that need to test something without permanently altering the objects’ state.

table ( datatype=None )

Converts the data Element to a Table, optionally may specify a supported data type. The default data types are ‘numpy’ (for homogeneous data), ‘dataframe’, and ‘dictionary’.

to

Property to create a conversion interface with methods to convert to other Element types.

traverse ( fn , specs=None , full_breadth=True )

Traverses any nested LabelledData object (i.e LabelledData objects containing LabelledData objects), applying the supplied function to each constituent element if the supplied specifications. The output of these function calls are collected and returned in the accumulator list.

If specs is None, all constituent elements are processed. Otherwise, specs must be a list of type.group.label specs, types, and functions.

trimesh ( ) [source]

Converts a QuadMesh into a TriMesh.

verbose ( msg , *args , **kw )

Print msg merged with args as a verbose message.

See Python’s logging module for details of message formatting.

warning ( msg , *args , **kw )

Print msg merged with args as a warning, unless module variable warnings_as_exceptions is True, then raise an Exception containing the arguments.

See Python’s logging module for details of message formatting.

class holoviews.element. Image ( data , kdims=None , vdims=None , bounds=None , extents=None , xdensity=None , ydensity=None , rtol=None , **params ) [source]

Bases: holoviews.core.data.Dataset , holoviews.element.raster.Raster , holoviews.core.sheetcoords.SheetCoordinateSystem

Image is the atomic unit as which 2D data is stored, along with its bounds object. The input data may be a numpy.matrix object or a two-dimensional numpy array.

Allows slicing operations of the data in sheet coordinates or direct access to the data, via the .data attribute.

param String group ( allow_None=False, basestring=<class ‘str’>, constant=True, default=Image, instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
A string describing the data wrapped by the object.
param String label ( allow_None=False, basestring=<class ‘str’>, constant=True, default=, instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
Optional label describing the data, typically reflecting where or how it was measured. The label should allow a specific measurement or dataset to be referenced for a given group.
param Dict cdims ( allow_None=False, constant=False, default=OrderedDict(), instantiate=True, is_instance=True, pickle_default_value=True, precedence=None, readonly=False )
The constant dimensions defined as a dictionary of Dimension:value pairs providing additional dimension information about the object. Aliased with constant_dimensions.
param List kdims ( allow_None=False, bounds=(2, 2), constant=True, default=[Dimension(‘x’), Dimension(‘y’)], instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
The label of the x- and y-dimension of the Raster in the form of a string or dimension object.
param List vdims ( allow_None=False, bounds=(1, 1), constant=False, default=[Dimension(‘z’)], instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
The dimension description of the data held in the matrix.
param Tuple extents ( allow_None=False, constant=False, default=(None, None, None, None), instantiate=False, length=4, pickle_default_value=True, precedence=None, readonly=False )
Allows overriding the extents of the Element in 2D space defined as four-tuple defining the (left, bottom, right and top) edges.
param List datatype ( allow_None=False, bounds=(0, None), constant=False, default=[‘image’, ‘grid’, ‘xarray’, ‘cube’, ‘dataframe’, ‘dictionary’], instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
A priority list of the data types to be used for storage on the .data attribute. If the input supplied to the element constructor cannot be put into the requested format, the next format listed will be used until a suitable format is found (or the data fails to be understood).
param ClassSelector bounds ( allow_None=False, constant=False, default=BoundingBox(radius=0.5), instantiate=True, is_instance=True, pickle_default_value=True, precedence=None, readonly=False )
The bounding region in sheet coordinates containing the data.
param Number rtol ( allow_None=True, bounds=None, constant=False, default=None, inclusive_bounds=(True, True), instantiate=False, pickle_default_value=True, precedence=None, readonly=False, softbounds=None, time_dependent=False, time_fn=<Time Time00001> )
The tolerance used to enforce regular sampling for regular, gridded data where regular sampling is expected. Expressed as the maximal allowable sampling difference between sample locations.
add_dimension ( dimension , dim_pos , dim_val , vdim=False , **kwargs )

Create a new object with an additional key dimensions. Requires the dimension name or object, the desired position in the key dimensions and a key value scalar or sequence of the same length as the existing keys.

clone ( data=None , shared_data=True , new_type=None , *args , **overrides )

Returns a clone of the object with matching parameter values containing the specified args and kwargs.

If shared_data is set to True and no data explicitly supplied, the clone will share data with the original. May also supply a new_type, which will inherit all shared parameters.

closest ( coords=[] , **kwargs ) [source]

Given a single coordinate or multiple coordinates as a tuple or list of tuples or keyword arguments matching the dimension closest will find the closest actual x/y coordinates.

closest_cell_center ( x , y )

Given arbitrary sheet coordinates, return the sheet coordinates of the center of the closest unit.

ddims

The list of deep dimensions

debug ( msg , *args , **kw )

Print msg merged with args as a debugging statement.

See Python’s logging module for details of message formatting.

defaults ( )

Return {parameter_name:parameter.default} for all non-constant Parameters.

Note that a Parameter for which instantiate==True has its default instantiated.

dframe ( dimensions=None )

Returns the data in the form of a DataFrame. Supplying a list of dimensions filters the dataframe. If the data is already a DataFrame a copy is returned.

dimension_values ( dim , expanded=True , flat=True )

Returns the values along a particular dimension. If unique values are requested will return only unique values.

dimensions ( selection='all' , label=False )

Provides convenient access to Dimensions on nested Dimensioned objects. Dimensions can be selected by their type, i.e. ‘key’ or ‘value’ dimensions. By default ‘all’ dimensions are returned.

force_new_dynamic_value = functools.partial(<function Parameterized.force_new_dynamic_value>, <class 'holoviews.element.raster.Image'>)
get_dimension ( dimension , default=None , strict=False )

Access a Dimension object by name or index. Returns the default value if the dimension is not found and strict is False. If strict is True, a KeyError is raised instead.

get_dimension_index ( dim )

Returns the index of the requested dimension.

get_dimension_type ( dim )

Returns the specified Dimension type if specified or if the dimension_values types are consistent otherwise None is returned.

get_param_values = functools.partial(<function Parameterized.get_param_values>, <class 'holoviews.element.raster.Image'>)
get_value_generator = functools.partial(<function Parameterized.get_value_generator>, <class 'holoviews.element.raster.Image'>)
groupby ( dimensions=[] , container_type=<class 'holoviews.core.spaces.HoloMap'> , group_type=None , dynamic=False , **kwargs )

Return the results of a groupby operation over the specified dimensions as an object of type container_type (expected to be dictionary-like).

Keys vary over the columns (dimensions) and the corresponding values are collections of group_type (e.g an Element, list, tuple) constructed with kwargs (if supplied).

If dynamic is requested container_type is automatically set to a DynamicMap, allowing dynamic exploration of large datasets. If the data does not represent a full cartesian grid of the requested dimensions some Elements will be empty.

hist ( dimension=None , num_bins=20 , bin_range=None , adjoin=True , individually=True , **kwargs )

The hist method generates a histogram to be adjoined to the Element in an AdjointLayout. By default the histogram is computed along the first value dimension of the Element, however any dimension may be selected. The number of bins and the bin_ranges and any kwargs to be passed to the histogram operation may also be supplied.

iloc

Returns an iloc object providing a convenient interface to slice and index into the Dataset using row and column indices. Allow selection by integer index, slice and list of integer indices and boolean arrays.

Examples:

  • Index the first row and column:

    dataset.iloc[0, 0]

  • Select rows 1 and 2 with a slice:

    dataset.iloc[1:3, :]

  • Select with a list of integer coordinates:

    dataset.iloc[[0, 2, 3]]

inspect_value = functools.partial(<function Parameterized.inspect_value>, <class 'holoviews.element.raster.Image'>)
map ( map_fn , specs=None , clone=True )

Recursively replaces elements using a map function when the specification applies.

matches ( spec )

A specification may be a class, a tuple or a string. Equivalent to isinstance if a class is supplied, otherwise matching occurs on type, group and label. These may be supplied as a tuple of strings or as a single string of the form “{type}.{group}.{label}”. Matching may be done on {type} alone, {type}.{group}, or {type}.{group}.{label}. The strings for the type, group, and label will each be sanitized before the match, and so the sanitized versions of those values will need to be provided if the match is to succeed.

matrix2sheet ( float_row , float_col )

Convert a floating-point location (float_row,float_col) in matrix coordinates to its corresponding location (x,y) in sheet coordinates.

Valid for scalar or array float_row and float_col.

Inverse of sheet2matrix().

matrixidx2sheet ( row , col )

Return (x,y) where x and y are the floating point coordinates of the center of the given matrix cell (row,col). If the matrix cell represents a 0.2 by 0.2 region, then the center location returned would be 0.1,0.1.

NOTE: This is NOT the strict mathematical inverse of sheet2matrixidx(), because sheet2matrixidx() discards all but the integer portion of the continuous matrix coordinate.

Valid only for scalar or array row and col.

message ( msg , *args , **kw )

Print msg merged with args as a message.

See Python’s logging module for details of message formatting.

ndloc

Returns an ndloc object providing nd-array like indexing for gridded datasets. Follows NumPy array indexing conventions, allowing for indexing, slicing and selecting a list of indices on multi-dimensional arrays using integer indices. The order of array indices is inverted relative to the Dataset key dimensions, e.g. an Image with key dimensions ‘x’ and ‘y’ can be indexed with image.ndloc[iy, ix] , where iy and ix are integer indices along the y and x dimensions.

Examples:

  • Index value in 2D array:

    dataset.ndloc[3, 1]

  • Slice along y-axis of 2D array:

    dataset.ndloc[2:5, :]

  • Vectorized (non-orthogonal) indexing along x- and y-axes:

    dataset.ndloc[[1, 2, 3], [0, 2, 3]]

options ( options=None , backend=None , clone=True , **kwargs )

Applies options on an object or nested group of objects in a flat format returning a new object with the options applied. If the options are to be set directly on the object a simple format may be used, e.g.:

obj.options(cmap=’viridis’, show_title=False)

If the object is nested the options must be qualified using a type[.group][.label] specification, e.g.:

obj.options(‘Image’, cmap=’viridis’, show_title=False)

or using:

obj.options({‘Image’: dict(cmap=’viridis’, show_title=False)})

If no options are supplied all options on the object will be reset. Disabling clone will modify the object inplace.

opts ( options=None , backend=None , clone=True , **kwargs )

Applies options on an object or nested group of objects in a by options group returning a new object with the options applied. If the options are to be set directly on the object a simple format may be used, e.g.:

obj.opts(style={‘cmap’: ‘viridis’}, plot={‘show_title’: False})

If the object is nested the options must be qualified using a type[.group][.label] specification, e.g.:

obj.opts({‘Image’: {‘plot’: {‘show_title’: False},
‘style’: {‘cmap’: ‘viridis}}})

If no opts are supplied all options on the object will be reset. Disabling clone will modify the object inplace.

params ( parameter_name=None )

Return the Parameters of this class as the dictionary {name: parameter_object}

Includes Parameters from this class and its superclasses.

pprint ( imports=None , prefix=' ' , unknown_value='<?>' , qualify=False , separator='' )

(Experimental) Pretty printed representation that may be evaluated with eval. See pprint() function for more details.

print_param_defaults ( )

Print the default values of all cls’s Parameters.

print_param_values ( )

Print the values of all this object’s Parameters.

reduce ( dimensions=[] , function=None , spreadfn=None , **reduce_map )

Allows reducing the values along one or more key dimension with the supplied function. The dimensions may be supplied as a list and a function to apply or a mapping between the dimensions and functions to apply along each dimension.

reindex ( kdims=None , vdims=None )

Create a new object with a re-ordered set of dimensions. Allows converting key dimensions to value dimensions and vice versa.

relabel ( label=None , group=None , depth=0 )

Assign a new label and/or group to an existing LabelledData object, creating a clone of the object with the new settings.

sample ( samples=[] , **kwargs ) [source]

Allows sampling of an Image as an iterator of coordinates matching the key dimensions, returning a new object containing just the selected samples. Alternatively may supply kwargs to sample a coordinate on an object. On an Image the coordinates are continuously indexed and will always snap to the nearest coordinate.

script_repr ( imports=[] , prefix=' ' )

Variant of __repr__ designed for generating a runnable script.

select ( selection_specs=None , **selection ) [source]

Allows selecting data by the slices, sets and scalar values along a particular dimension. The indices should be supplied as keywords mapping between the selected dimension and value. Additionally selection_specs (taking the form of a list of type.group.label strings, types or functions) may be supplied, which will ensure the selection is only applied if the specs match the selected object.

set_default ( param_name , value )

Set the default value of param_name.

Equivalent to setting param_name on the class.

set_dynamic_time_fn = functools.partial(<function Parameterized.set_dynamic_time_fn>, <class 'holoviews.element.raster.Image'>)
set_param = functools.partial(<function Parameterized.set_param>, <class 'holoviews.element.raster.Image'>)
shape

Returns the shape of the data.

sheet2matrix ( x , y )

Convert a point (x,y) in Sheet coordinates to continuous matrix coordinates.

Returns (float_row,float_col), where float_row corresponds to y, and float_col to x.

Valid for scalar or array x and y.

Note about Bounds For a Sheet with BoundingBox(points=((-0.5,-0.5),(0.5,0.5))) and density=3, x=-0.5 corresponds to float_col=0.0 and x=0.5 corresponds to float_col=3.0. float_col=3.0 is not inside the matrix representing this Sheet, which has the three columns (0,1,2). That is, x=-0.5 is inside the BoundingBox but x=0.5 is outside. Similarly, y=0.5 is inside (at row 0) but y=-0.5 is outside (at row 3) (it’s the other way round for y because the matrix row index increases as y decreases).

sheet2matrixidx ( x , y )

Convert a point (x,y) in sheet coordinates to the integer row and column index of the matrix cell in which that point falls, given a bounds and density. Returns (row,column).

Note that if coordinates along the right or bottom boundary are passed into this function, the returned matrix coordinate of the boundary will be just outside the matrix, because the right and bottom boundaries are exclusive.

Valid for scalar or array x and y.

sheetcoordinates_of_matrixidx ( )

Return x,y where x is a vector of sheet coordinates representing the x-center of each matrix cell, and y represents the corresponding y-center of the cell.

sort ( by=[] , reverse=False )

Sorts the data by the values along the supplied dimensions.

state_pop ( )

Restore the most recently saved state.

See state_push() for more details.

state_push ( )

Save this instance’s state.

For Parameterized instances, this includes the state of dynamically generated values.

Subclasses that maintain short-term state should additionally save and restore that state using state_push() and state_pop().

Generally, this method is used by operations that need to test something without permanently altering the objects’ state.

table ( datatype=None ) [source]

Converts the data Element to a Table, optionally may specify a supported data type. The default data types are ‘numpy’ (for homogeneous data), ‘dataframe’, and ‘dictionary’.

to

Property to create a conversion interface with methods to convert to other Element types.

traverse ( fn , specs=None , full_breadth=True )

Traverses any nested LabelledData object (i.e LabelledData objects containing LabelledData objects), applying the supplied function to each constituent element if the supplied specifications. The output of these function calls are collected and returned in the accumulator list.

If specs is None, all constituent elements are processed. Otherwise, specs must be a list of type.group.label specs, types, and functions.

verbose ( msg , *args , **kw )

Print msg merged with args as a verbose message.

See Python’s logging module for details of message formatting.

warning ( msg , *args , **kw )

Print msg merged with args as a warning, unless module variable warnings_as_exceptions is True, then raise an Exception containing the arguments.

See Python’s logging module for details of message formatting.

xdensity

The spacing between elements in an underlying matrix representation, in the x direction.

ydensity

The spacing between elements in an underlying matrix representation, in the y direction.

class holoviews.element. HexTiles ( data , kdims=None , vdims=None , **kwargs ) [source]

Bases: holoviews.core.data.Dataset , holoviews.core.element.Element2D

HexTiles is a statistical element with a visual representation that renders a density map of the data values as a hexagonal grid.

Before display the data is aggregated either by counting the values in each hexagonal bin or by computing aggregates.

param String group ( allow_None=False, basestring=<class ‘str’>, constant=True, default=HexTiles, instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
A string describing the data wrapped by the object.
param String label ( allow_None=False, basestring=<class ‘str’>, constant=True, default=, instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
Optional label describing the data, typically reflecting where or how it was measured. The label should allow a specific measurement or dataset to be referenced for a given group.
param Dict cdims ( allow_None=False, constant=False, default=OrderedDict(), instantiate=True, is_instance=True, pickle_default_value=True, precedence=None, readonly=False )
The constant dimensions defined as a dictionary of Dimension:value pairs providing additional dimension information about the object. Aliased with constant_dimensions.
param List kdims ( allow_None=False, bounds=(2, 2), constant=False, default=[Dimension(‘x’), Dimension(‘y’)], instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
The key dimensions defined as list of dimensions that may be used in indexing (and potential slicing) semantics. The order of the dimensions listed here determines the semantics of each component of a multi-dimensional indexing operation. Aliased with key_dimensions.
param List vdims ( allow_None=False, bounds=(0, None), constant=True, default=[], instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
The value dimensions defined as the list of dimensions used to describe the components of the data. If multiple value dimensions are supplied, a particular value dimension may be indexed by name after the key dimensions. Aliased with value_dimensions.
param Tuple extents ( allow_None=False, constant=False, default=(None, None, None, None), instantiate=False, length=4, pickle_default_value=True, precedence=None, readonly=False )
Allows overriding the extents of the Element in 2D space defined as four-tuple defining the (left, bottom, right and top) edges.
param List datatype ( allow_None=False, bounds=(0, None), constant=False, default=[‘dataframe’, ‘dataframe’, ‘dataframe’, ‘dictionary’, ‘grid’, ‘ndelement’, ‘array’, ‘cube’, ‘xarray’, ‘dask’], instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
A priority list of the data types to be used for storage on the .data attribute. If the input supplied to the element constructor cannot be put into the requested format, the next format listed will be used until a suitable format is found (or the data fails to be understood).
add_dimension ( dimension , dim_pos , dim_val , vdim=False , **kwargs )

Create a new object with an additional key dimensions. Requires the dimension name or object, the desired position in the key dimensions and a key value scalar or sequence of the same length as the existing keys.

aggregate ( dimensions=None , function=None , spreadfn=None , **kwargs )

Aggregates over the supplied key dimensions with the defined function.

clone ( data=None , shared_data=True , new_type=None , *args , **overrides )

Returns a clone of the object with matching parameter values containing the specified args and kwargs.

If shared_data is set to True and no data explicitly supplied, the clone will share data with the original. May also supply a new_type, which will inherit all shared parameters.

closest ( coords=[] , **kwargs )

Given a single coordinate or multiple coordinates as a tuple or list of tuples or keyword arguments matching the dimension closest will find the closest actual x/y coordinates. Different Element types should implement this appropriately depending on the space they represent, if the Element does not support snapping raise NotImplementedError.

collapse_data ( data , function=None , kdims=None , **kwargs )

Class method to collapse a list of data matching the data format of the Element type. By implementing this method HoloMap can collapse multiple Elements of the same type. The kwargs are passed to the collapse function. The collapse function must support the numpy style axis selection. Valid function include: np.mean, np.sum, np.product, np.std, scipy.stats.kurtosis etc. Some data backends also require the key dimensions to aggregate over.

ddims

The list of deep dimensions

debug ( msg , *args , **kw )

Print msg merged with args as a debugging statement.

See Python’s logging module for details of message formatting.

defaults ( )

Return {parameter_name:parameter.default} for all non-constant Parameters.

Note that a Parameter for which instantiate==True has its default instantiated.

dframe ( dimensions=None )

Returns the data in the form of a DataFrame. Supplying a list of dimensions filters the dataframe. If the data is already a DataFrame a copy is returned.

dimension_values ( dim , expanded=True , flat=True )

Returns the values along a particular dimension. If unique values are requested will return only unique values.

dimensions ( selection='all' , label=False )

Provides convenient access to Dimensions on nested Dimensioned objects. Dimensions can be selected by their type, i.e. ‘key’ or ‘value’ dimensions. By default ‘all’ dimensions are returned.

force_new_dynamic_value = functools.partial(<function Parameterized.force_new_dynamic_value>, <class 'holoviews.element.stats.HexTiles'>)
get_dimension ( dimension , default=None , strict=False )

Access a Dimension object by name or index. Returns the default value if the dimension is not found and strict is False. If strict is True, a KeyError is raised instead.

get_dimension_index ( dim )

Returns the index of the requested dimension.

get_dimension_type ( dim )

Returns the specified Dimension type if specified or if the dimension_values types are consistent otherwise None is returned.

get_param_values = functools.partial(<function Parameterized.get_param_values>, <class 'holoviews.element.stats.HexTiles'>)
get_value_generator = functools.partial(<function Parameterized.get_value_generator>, <class 'holoviews.element.stats.HexTiles'>)
groupby ( dimensions=[] , container_type=<class 'holoviews.core.spaces.HoloMap'> , group_type=None , dynamic=False , **kwargs )

Return the results of a groupby operation over the specified dimensions as an object of type container_type (expected to be dictionary-like).

Keys vary over the columns (dimensions) and the corresponding values are collections of group_type (e.g an Element, list, tuple) constructed with kwargs (if supplied).

If dynamic is requested container_type is automatically set to a DynamicMap, allowing dynamic exploration of large datasets. If the data does not represent a full cartesian grid of the requested dimensions some Elements will be empty.

hist ( dimension=None , num_bins=20 , bin_range=None , adjoin=True , individually=True , **kwargs )

The hist method generates a histogram to be adjoined to the Element in an AdjointLayout. By default the histogram is computed along the first value dimension of the Element, however any dimension may be selected. The number of bins and the bin_ranges and any kwargs to be passed to the histogram operation may also be supplied.

iloc

Returns an iloc object providing a convenient interface to slice and index into the Dataset using row and column indices. Allow selection by integer index, slice and list of integer indices and boolean arrays.

Examples:

  • Index the first row and column:

    dataset.iloc[0, 0]

  • Select rows 1 and 2 with a slice:

    dataset.iloc[1:3, :]

  • Select with a list of integer coordinates:

    dataset.iloc[[0, 2, 3]]

inspect_value = functools.partial(<function Parameterized.inspect_value>, <class 'holoviews.element.stats.HexTiles'>)
map ( map_fn , specs=None , clone=True )

Recursively replaces elements using a map function when the specification applies.

matches ( spec )

A specification may be a class, a tuple or a string. Equivalent to isinstance if a class is supplied, otherwise matching occurs on type, group and label. These may be supplied as a tuple of strings or as a single string of the form “{type}.{group}.{label}”. Matching may be done on {type} alone, {type}.{group}, or {type}.{group}.{label}. The strings for the type, group, and label will each be sanitized before the match, and so the sanitized versions of those values will need to be provided if the match is to succeed.

message ( msg , *args , **kw )

Print msg merged with args as a message.

See Python’s logging module for details of message formatting.

ndloc

Returns an ndloc object providing nd-array like indexing for gridded datasets. Follows NumPy array indexing conventions, allowing for indexing, slicing and selecting a list of indices on multi-dimensional arrays using integer indices. The order of array indices is inverted relative to the Dataset key dimensions, e.g. an Image with key dimensions ‘x’ and ‘y’ can be indexed with image.ndloc[iy, ix] , where iy and ix are integer indices along the y and x dimensions.

Examples:

  • Index value in 2D array:

    dataset.ndloc[3, 1]

  • Slice along y-axis of 2D array:

    dataset.ndloc[2:5, :]

  • Vectorized (non-orthogonal) indexing along x- and y-axes:

    dataset.ndloc[[1, 2, 3], [0, 2, 3]]

options ( options=None , backend=None , clone=True , **kwargs )

Applies options on an object or nested group of objects in a flat format returning a new object with the options applied. If the options are to be set directly on the object a simple format may be used, e.g.:

obj.options(cmap=’viridis’, show_title=False)

If the object is nested the options must be qualified using a type[.group][.label] specification, e.g.:

obj.options(‘Image’, cmap=’viridis’, show_title=False)

or using:

obj.options({‘Image’: dict(cmap=’viridis’, show_title=False)})

If no options are supplied all options on the object will be reset. Disabling clone will modify the object inplace.

opts ( options=None , backend=None , clone=True , **kwargs )

Applies options on an object or nested group of objects in a by options group returning a new object with the options applied. If the options are to be set directly on the object a simple format may be used, e.g.:

obj.opts(style={‘cmap’: ‘viridis’}, plot={‘show_title’: False})

If the object is nested the options must be qualified using a type[.group][.label] specification, e.g.:

obj.opts({‘Image’: {‘plot’: {‘show_title’: False},
‘style’: {‘cmap’: ‘viridis}}})

If no opts are supplied all options on the object will be reset. Disabling clone will modify the object inplace.

params ( parameter_name=None )

Return the Parameters of this class as the dictionary {name: parameter_object}

Includes Parameters from this class and its superclasses.

pprint ( imports=None , prefix=' ' , unknown_value='<?>' , qualify=False , separator='' )

(Experimental) Pretty printed representation that may be evaluated with eval. See pprint() function for more details.

print_param_defaults ( )

Print the default values of all cls’s Parameters.

print_param_values ( )

Print the values of all this object’s Parameters.

range ( dim , data_range=True )

Computes the range of values along a supplied dimension, taking into account the range and soft_range defined on the Dimension object.

reduce ( dimensions=[] , function=None , spreadfn=None , **reduce_map )

Allows reducing the values along one or more key dimension with the supplied function. The dimensions may be supplied as a list and a function to apply or a mapping between the dimensions and functions to apply along each dimension.

reindex ( kdims=None , vdims=None )

Create a new object with a re-ordered set of dimensions. Allows converting key dimensions to value dimensions and vice versa.

relabel ( label=None , group=None , depth=0 )

Assign a new label and/or group to an existing LabelledData object, creating a clone of the object with the new settings.

sample ( samples=[] , closest=True , **kwargs )

Allows sampling of Dataset as an iterator of coordinates matching the key dimensions, returning a new object containing just the selected samples. Alternatively may supply kwargs to sample a coordinate on an object. By default it will attempt to snap to the nearest coordinate if the Element supports it, snapping may be disabled with the closest argument.

script_repr ( imports=[] , prefix=' ' )

Variant of __repr__ designed for generating a runnable script.

select ( selection_specs=None , **selection )

Allows selecting data by the slices, sets and scalar values along a particular dimension. The indices should be supplied as keywords mapping between the selected dimension and value. Additionally selection_specs (taking the form of a list of type.group.label strings, types or functions) may be supplied, which will ensure the selection is only applied if the specs match the selected object.

set_default ( param_name , value )

Set the default value of param_name.

Equivalent to setting param_name on the class.

set_dynamic_time_fn = functools.partial(<function Parameterized.set_dynamic_time_fn>, <class 'holoviews.element.stats.HexTiles'>)
set_param = functools.partial(<function Parameterized.set_param>, <class 'holoviews.element.stats.HexTiles'>)
shape

Returns the shape of the data.

sort ( by=[] , reverse=False )

Sorts the data by the values along the supplied dimensions.

state_pop ( )

Restore the most recently saved state.

See state_push() for more details.

state_push ( )

Save this instance’s state.

For Parameterized instances, this includes the state of dynamically generated values.

Subclasses that maintain short-term state should additionally save and restore that state using state_push() and state_pop().

Generally, this method is used by operations that need to test something without permanently altering the objects’ state.

table ( datatype=None )

Converts the data Element to a Table, optionally may specify a supported data type. The default data types are ‘numpy’ (for homogeneous data), ‘dataframe’, and ‘dictionary’.

to

Property to create a conversion interface with methods to convert to other Element types.

traverse ( fn , specs=None , full_breadth=True )

Traverses any nested LabelledData object (i.e LabelledData objects containing LabelledData objects), applying the supplied function to each constituent element if the supplied specifications. The output of these function calls are collected and returned in the accumulator list.

If specs is None, all constituent elements are processed. Otherwise, specs must be a list of type.group.label specs, types, and functions.

verbose ( msg , *args , **kw )

Print msg merged with args as a verbose message.

See Python’s logging module for details of message formatting.

warning ( msg , *args , **kw )

Print msg merged with args as a warning, unless module variable warnings_as_exceptions is True, then raise an Exception containing the arguments.

See Python’s logging module for details of message formatting.

class holoviews.element. Chord ( data , kdims=None , vdims=None , compute=True , **params ) [source]

Bases: holoviews.element.graphs.Graph

Chord is a special type of Graph which computes the locations of each node on a circle and the chords connecting them. The amount of radial angle devoted to each node and the number of chords are scaled by a weight supplied as a value dimension.

If the values are integers then the number of chords is directly scaled by the value, if the values are floats then the number of chords are apportioned such that the lowest value edge is given one chord and all other nodes are given nodes proportional to their weight.

param String group ( allow_None=False, basestring=<class ‘str’>, constant=True, default=Chord, instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
A string describing the data wrapped by the object.
param String label ( allow_None=False, basestring=<class ‘str’>, constant=True, default=, instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
Optional label describing the data, typically reflecting where or how it was measured. The label should allow a specific measurement or dataset to be referenced for a given group.
param Dict cdims ( allow_None=False, constant=False, default=OrderedDict(), instantiate=True, is_instance=True, pickle_default_value=True, precedence=None, readonly=False )
The constant dimensions defined as a dictionary of Dimension:value pairs providing additional dimension information about the object. Aliased with constant_dimensions.
param List kdims ( allow_None=False, bounds=(2, 2), constant=False, default=[Dimension(‘start’), Dimension(‘end’)], instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
The key dimensions defined as list of dimensions that may be used in indexing (and potential slicing) semantics. The order of the dimensions listed here determines the semantics of each component of a multi-dimensional indexing operation. Aliased with key_dimensions.
param List vdims ( allow_None=False, bounds=(0, None), constant=True, default=[], instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
The value dimensions defined as the list of dimensions used to describe the components of the data. If multiple value dimensions are supplied, a particular value dimension may be indexed by name after the key dimensions. Aliased with value_dimensions.
param Tuple extents ( allow_None=False, constant=False, default=(None, None, None, None), instantiate=False, length=4, pickle_default_value=True, precedence=None, readonly=False )
Allows overriding the extents of the Element in 2D space defined as four-tuple defining the (left, bottom, right and top) edges.
param List datatype ( allow_None=False, bounds=(0, None), constant=False, default=[‘dataframe’, ‘dataframe’, ‘dataframe’, ‘dictionary’, ‘grid’, ‘ndelement’, ‘array’, ‘cube’, ‘xarray’, ‘dask’], instantiate=True, pickle_default_value=True, precedence=None, readonly=False )
A priority list of the data types to be used for storage on the .data attribute. If the input supplied to the element constructor cannot be put into the requested format, the next format listed will be used until a suitable format is found (or the data fails to be understood).
add_dimension ( dimension , dim_pos , dim_val , vdim=False , **kwargs )

Create a new object with an additional key dimensions. Requires the dimension name or object, the desired position in the key dimensions and a key value scalar or sequence of the same length as the existing keys.

aggregate ( dimensions=None , function=None , spreadfn=None , **kwargs )

Aggregates over the supplied key dimensions with the defined function.

closest ( coords=[] , **kwargs )

Given a single coordinate or multiple coordinates as a tuple or list of tuples or keyword arguments matching the dimension closest will find the closest actual x/y coordinates. Different Element types should implement this appropriately depending on the space they represent, if the Element does not support snapping raise NotImplementedError.

collapse_data ( data , function=None , kdims=None , **kwargs )

Class method to collapse a list of data matching the data format of the Element type. By implementing this method HoloMap can collapse multiple Elements of the same type. The kwargs are passed to the collapse function. The collapse function must support the numpy style axis selection. Valid function include: np.mean, np.sum, np.product, np.std, scipy.stats.kurtosis etc. Some data backends also require the key dimensions to aggregate over.

ddims

The list of deep dimensions

debug ( msg , *args , **kw )

Print msg merged with args as a debugging statement.

See Python’s logging module for details of message formatting.

defaults ( )

Return {parameter_name:parameter.default} for all non-constant Parameters.

Note that a Parameter for which instantiate==True has its default instantiated.

dframe ( dimensions=None )

Returns the data in the form of a DataFrame. Supplying a list of dimensions filters the dataframe. If the data is already a DataFrame a copy is returned.

dimension_values ( dim , expanded=True , flat=True )

Returns the values along a particular dimension. If unique values are requested will return only unique values.

edge_type

alias of EdgePaths

force_new_dynamic_value = functools.partial(<function Parameterized.force_new_dynamic_value>, <class 'holoviews.element.graphs.Chord'>)
from_networkx ( G , layout_function , nodes=None , **kwargs )

Generate a HoloViews Graph from a networkx.Graph object and networkx layout function. Any keyword arguments will be passed to the layout function. By default it will extract all node and edge attributes from the networkx.Graph but explicit node information may also be supplied.

get_dimension ( dimension , default=None , strict=False )

Access a Dimension object by name or index. Returns the default value if the dimension is not found and strict is False. If strict is True, a KeyError is raised instead.

get_dimension_index ( dim )

Returns the index of the requested dimension.

get_dimension_type ( dim )

Returns the specified Dimension type if specified or if the dimension_values types are consistent otherwise None is returned.

get_param_values = functools.partial(<function Parameterized.get_param_values>, <class 'holoviews.element.graphs.Chord'>)
get_value_generator = functools.partial(<function Parameterized.get_value_generator>, <class 'holoviews.element.graphs.Chord'>)
groupby ( dimensions=[] , container_type=<class 'holoviews.core.spaces.HoloMap'> , group_type=None , dynamic=False , **kwargs )

Return the results of a groupby operation over the specified dimensions as an object of type container_type (expected to be dictionary-like).

Keys vary over the columns (dimensions) and the corresponding values are collections of group_type (e.g an Element, list, tuple) constructed with kwargs (if supplied).

If dynamic is requested container_type is automatically set to a DynamicMap, allowing dynamic exploration of large datasets. If the data does not represent a full cartesian grid of the requested dimensions some Elements will be empty.

hist ( dimension=None , num_bins=20 , bin_range=None , adjoin=True , individually=True , **kwargs )

The hist method generates a histogram to be adjoined to the Element in an AdjointLayout. By default the histogram is computed along the first value dimension of the Element, however any dimension may be selected. The number of bins and the bin_ranges and any kwargs to be passed to the histogram operation may also be supplied.

iloc

Returns an iloc object providing a convenient interface to slice and index into the Dataset using row and column indices. Allow selection by integer index, slice and list of integer indices and boolean arrays.

Examples:

  • Index the first row and column:

    dataset.iloc[0, 0]

  • Select rows 1 and 2 with a slice:

    dataset.iloc[1:3, :]

  • Select with a list of integer coordinates:

    dataset.iloc[[0, 2, 3]]

inspect_value = functools.partial(<function Parameterized.inspect_value>, <class 'holoviews.element.graphs.Chord'>)
map ( map_fn , specs=None , clone=True )

Recursively replaces elements using a map function when the specification applies.

matches ( spec )

A specification may be a class, a tuple or a string. Equivalent to isinstance if a class is supplied, otherwise matching occurs on type, group and label. These may be supplied as a tuple of strings or as a single string of the form “{type}.{group}.{label}”. Matching may be done on {type} alone, {type}.{group}, or {type}.{group}.{label}. The strings for the type, group, and label will each be sanitized before the match, and so the sanitized versions of those values will need to be provided if the match is to succeed.

message ( msg , *args , **kw )

Print msg merged with args as a message.

See Python’s logging module for details of message formatting.

ndloc

Returns an ndloc object providing nd-array like indexing for gridded datasets. Follows NumPy array indexing conventions, allowing for indexing, slicing and selecting a list of indices on multi-dimensional arrays using integer indices. The order of array indices is inverted relative to the Dataset key dimensions, e.g. an Image with key dimensions ‘x’ and ‘y’ can be indexed with image.ndloc[iy, ix] , where iy and ix are integer indices along the y and x dimensions.

Examples:

  • Index value in 2D array:

    dataset.ndloc[3, 1]

  • Slice along y-axis of 2D array:

    dataset.ndloc[2:5, :]

  • Vectorized (non-orthogonal) indexing along x- and y-axes:

    dataset.ndloc[[1, 2, 3], [0, 2, 3]]

node_type

alias of Nodes

options ( options=None , backend=None , clone=True , **kwargs )

Applies options on an object or nested group of objects in a flat format returning a new object with the options applied. If the options are to be set directly on the object a simple format may be used, e.g.:

obj.options(cmap=’viridis’, show_title=False)

If the object is nested the options must be qualified using a type[.group][.label] specification, e.g.:

obj.options(‘Image’, cmap=’viridis’, show_title=False)

or using:

obj.options({‘Image’: dict(cmap=’viridis’, show_title=False)})

If no options are supplied all options on the object will be reset. Disabling clone will modify the object inplace.

opts ( options=None , backend=None , clone=True , **kwargs )

Applies options on an object or nested group of objects in a by options group returning a new object with the options applied. If the options are to be set directly on the object a simple format may be used, e.g.:

obj.opts(style={‘cmap’: ‘viridis’}, plot={‘show_title’: False})

If the object is nested the options must be qualified using a type[.group][.label] specification, e.g.:

obj.opts({‘Image’: {‘plot’: {‘show_title’: False},
‘style’: {‘cmap’: ‘viridis}}})

If no opts are supplied all options on the object will be reset. Disabling clone will modify the object inplace.

params ( parameter_name=None )

Return the Parameters of this class as the dictionary {name: parameter_object}

Includes Parameters from this class and its superclasses.

pprint ( imports=None , prefix=' ' , unknown_value='<?>' , qualify=False , separator='' )

(Experimental) Pretty printed representation that may be evaluated with eval. See pprint() function for more details.

print_param_defaults ( )

Print the default values of all cls’s Parameters.

print_param_values ( )

Print the values of all this object’s Parameters.

reduce ( dimensions=[] , function=None , spreadfn=None , **reduce_map )

Allows reducing the values along one or more key dimension with the supplied function. The dimensions may be supplied as a list and a function to apply or a mapping between the dimensions and functions to apply along each dimension.

reindex ( kdims=None , vdims=None )

Create a new object with a re-ordered set of dimensions. Allows converting key dimensions to value dimensions and vice versa.

relabel ( label=None , group=None , depth=0 )

Assign a new label and/or group to an existing LabelledData object, creating a clone of the object with the new settings.

sample ( samples=[] , closest=True , **kwargs )

Allows sampling of Dataset as an iterator of coordinates matching the key dimensions, returning a new object containing just the selected samples. Alternatively may supply kwargs to sample a coordinate on an object. By default it will attempt to snap to the nearest coordinate if the Element supports it, snapping may be disabled with the closest argument.

script_repr ( imports=[] , prefix=' ' )

Variant of __repr__ designed for generating a runnable script.

select ( selection_specs=None , selection_mode='edges' , **selection )

Allows selecting data by the slices, sets and scalar values along a particular dimension. The indices should be supplied as keywords mapping between the selected dimension and value. Additionally selection_specs (taking the form of a list of type.group.label strings, types or functions) may be supplied, which will ensure the selection is only applied if the specs match the selected object.

Selecting by a node dimensions selects all edges and nodes that are connected to the selected nodes. To select only edges between the selected nodes set the selection_mode to ‘nodes’.

set_default ( param_name , value )

Set the default value of param_name.

Equivalent to setting param_name on the class.

set_dynamic_time_fn = functools.partial(<function Parameterized.set_dynamic_time_fn>, <class 'holoviews.element.graphs.Chord'>)
set_param = functools.partial(<function Parameterized.set_param>, <class 'holoviews.element.graphs.Chord'>)
shape

Returns the shape of the data.

sort (