geoviews package#

Subpackages#

Submodules#

Module contents#

class geoviews.Contours(data=None, kdims=None, vdims=None, **kwargs)[source]#

Bases: _Element, Contours

Contours is a Path Element type that may contain any number of closed paths with an associated value and a coordinate reference system.

Methods

geom([union, projection])

Converts the Contours to a shapely geometry.

Parameter Definitions

Parameters inherited from:

group = String(constant=True, default='Contours', label='Group')

A string describing the data wrapped by the object.

geom(union=False, projection=None)[source]#

Converts the Contours to a shapely geometry.

Parameters:
unionbool, default=False

Whether to compute a union between the geometries

projectionEPSG python:str | Cartopy CRS | python:None

Whether to project the geometry to other coordinate system

Returns:
A shapely geometry
class geoviews.Cycle(cycle=None, **params)[source]#

Bases: Parameterized

A simple container class that specifies cyclic options. A typical example would be to cycle the curve colors in an Overlay composed of an arbitrary number of curves. The values may be supplied as an explicit list or a key to look up in the default cycles attribute.

Parameter Definitions

key = String(allow_None=True, default='default_colors', label='Key')

The key in the default_cycles dictionary used to specify the color cycle if values is not supplied.

values = List(bounds=(0, None), default=[], label='Values')

The values the cycle will iterate over.

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

Bases: _Element, Dataset

Coordinate system aware version of a HoloViews dataset.

Parameter Definitions

Parameters inherited from:

group = String(default='Dataset', label='Group')

A string describing the data wrapped by the object.

kdims = List(bounds=(0, None), constant=True, default=[Dimension('Longitude'), Dimension('Latitude')], label='Kdims')

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.

class geoviews.Dimension(spec, **params)[source]#

Bases: Parameterized

Dimension objects are used to specify some important general features that may be associated with a collection of values.

For instance, a Dimension may specify that a set of numeric values actually correspond to ‘Height’ (dimension name), in units of meters, with a descriptive label ‘Height of adult males’.

All dimensions object have a name that identifies them and a label containing a suitable description. If the label is not explicitly specified it matches the name.

These two parameters define the core identity of the dimension object and must match if two dimension objects are to be considered equivalent. All other parameters are considered optional metadata and are not used when testing for equality.

Unlike all the other parameters, these core parameters can be used to construct a Dimension object from a tuple. This format is sufficient to define an identical Dimension:

Dimension(‘a’, label=’Dimension A’) == Dimension((‘a’, ‘Dimension A’))

Everything else about a dimension is considered to reflect non-semantic preferences. Examples include the default value (which may be used in a visualization to set an initial slider position), how the value is to rendered as text (which may be used to specify the printed floating point precision) or a suitable range of values to consider for a particular analysis.

Attributes:
pprint_label

The pretty-printed label string for the Dimension

spec

“Returns the Dimensions tuple specification

type

Methods

clone([spec])

Clones the Dimension with new parameters

pprint_value(value[, print_unit])

Applies the applicable formatter to the value.

pprint_value_string(value)

Pretty print the dimension value and unit with title_format

pprint

Notes

Full unit support with automated conversions are on the HoloViews roadmap. Once rich unit objects are supported, the unit (or more specifically the type of unit) will be part of the core dimension specification used to establish equality.

Until this feature is implemented, there are two auxiliary parameters that hold some partial information about the unit: the name of the unit and whether or not it is cyclic. The name of the unit is used as part of the pretty-printed representation and knowing whether it is cyclic is important for certain operations.

Parameter Definitions

label = String(allow_None=True, label='Label')

Unrestricted label used to describe the dimension. A label should succinctly describe the dimension and may contain any characters, including Unicode and LaTeX expression.

cyclic = Boolean(default=False, label='Cyclic')

Whether the range of this feature is cyclic such that the maximum allowed value (defined by the range parameter) is continuous with the minimum allowed value.

default = Parameter(allow_None=True, label='Default')

Default value of the Dimension which may be useful for widget or other situations that require an initial or default value.

nodata = Integer(allow_None=True, inclusive_bounds=(True, True), label='Nodata')

Optional missing-data value for integer data. If non-None, data with this value will be replaced with NaN.

range = Tuple(default=(None, None), label='Range', length=2)

Specifies the minimum and maximum allowed values for a Dimension. None is used to represent an unlimited bound.

soft_range = Tuple(default=(None, None), label='Soft range', length=2)

Specifies a minimum and maximum reference value, which may be overridden by the data.

step = Number(allow_None=True, inclusive_bounds=(True, True), label='Step')

Optional floating point step specifying how frequently the underlying space should be sampled. May be used to define a discrete sampling over the range.

type = Parameter(allow_None=True, label='Type')

Optional type associated with the Dimension values. The type may be an inbuilt constructor (such as int, str, float) or a custom class object.

unit = String(allow_None=True, label='Unit')

Optional unit string associated with the Dimension. For instance, the string ‘m’ may be used represent units of meters and ‘s’ to represent units of seconds.

value_format = Callable(allow_None=True, label='Value format')

Formatting function applied to each value before display.

values = List(bounds=(0, None), default=[], label='Values')

Optional specification of the allowed value set for the dimension that may also be used to retain a categorical ordering.

clone(spec=None, **overrides)[source]#

Clones the Dimension with new parameters

Derive a new Dimension that inherits existing parameters except for the supplied, explicit overrides

Parameters:
specpython:tuple, optional

Dimension tuple specification

**overrides: Dimension parameter overrides
Returns:
Cloned Dimension object
property pprint_label#

The pretty-printed label string for the Dimension

pprint_value(value, print_unit=False)[source]#

Applies the applicable formatter to the value.

Parameters:
value

Dimension value to format

Returns:
Formatted dimension value
pprint_value_string(value)[source]#

Pretty print the dimension value and unit with title_format

Parameters:
value

Dimension value to format

Returns:
Formatted dimension value python:str with unit
property spec#

“Returns the Dimensions tuple specification

Returns:
tupleDimension python:tuple specification
class geoviews.DynamicMap(callback, initial_items=None, streams=None, **params)[source]#

Bases: HoloMap

A DynamicMap is a type of HoloMap where the elements are dynamically generated by a callable. The callable is invoked with values associated with the key dimensions or with values supplied by stream parameters.

Attributes:
current_key

Returns the current key value.

opts
redim
unbounded

Returns a list of key dimensions that are unbounded, excluding stream parameters.

Methods

add_dimension(dimension, dim_pos, dim_val[, ...])

Adds a dimension and its values to the object

clone([data, shared_data, new_type, link])

Clones the object, overriding data and parameters.

collate()

Unpacks DynamicMap into container of DynamicMaps

decollate()

Packs DynamicMap of nested DynamicMaps into a single DynamicMap that returns a non-dynamic element

drop_dimension(dimensions)

Drops dimension(s) from keys

event(**kwargs)

Updates attached streams and triggers events

grid([dimensions])

Groups data by supplied dimension(s) laying the groups along the dimension(s) out in a GridSpace.

groupby([dimensions, container_type, group_type])

Groups DynamicMap by one or more dimensions

hist([dimension, num_bins, bin_range, adjoin])

Computes and adjoins histogram along specified dimension(s).

layout([dimensions])

Groups data by supplied dimension(s) laying the groups along the dimension(s) out in a NdLayout.

map(map_fn[, specs, clone, link_inputs])

Map a function to all objects matching the specs

options(*args, **kwargs)

Applies simplified option definition returning a new object.

overlay([dimensions])

Group by supplied dimension(s) and overlay each group

reindex([kdims, force])

Reorders key dimensions on DynamicMap

relabel([label, group, depth])

Clone object and apply new group and/or label.

reset()

Clear the DynamicMap cache

select([selection_specs])

Applies selection by dimension name

Parameter Definitions

Parameters inherited from:

kdims = List(bounds=(0, None), constant=True, default=[], label='Kdims')

The key dimensions of a DynamicMap map to the arguments of the callback. This mapping can be by position or by name.

callback = ClassSelector(allow_None=True, class_=<class 'holoviews.core.spaces.Callable'>, constant=True, label='Callback')

The callable used to generate the elements. The arguments to the callable includes any number of declared key dimensions as well as any number of stream parameters defined on the input streams. If the callable is an instance of Callable it will be used directly, otherwise it will be automatically wrapped in one.

streams = List(bounds=(0, None), constant=True, default=[], label='Streams')

List of Stream instances to associate with the DynamicMap. The set of parameter values across these streams will be supplied as keyword arguments to the callback when the events are received, updating the streams. Can also be supplied as a dictionary that maps parameters or panel widgets to callback argument names that will then be automatically converted to the equivalent list format.

cache_size = Integer(bounds=(1, None), default=500, inclusive_bounds=(True, True), label='Cache size')

The number of entries to cache for fast access. This is an LRU cache where the least recently used item is overwritten once the cache is full.

positional_stream_args = Boolean(constant=True, default=False, label='Positional stream args')

If False, stream parameters are passed to the callback as keyword arguments. If True, stream parameters are passed to callback as positional arguments. Each positional argument is a dict containing the contents of a stream. The positional stream arguments follow the positional arguments for each kdim, and they are ordered to match the order of the DynamicMap’s streams list.

add_dimension(dimension, dim_pos, dim_val, vdim=False, **kwargs)[source]#

Adds a dimension and its values to the object

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.

Parameters:
dimension

Dimension or dimension spec to add

dim_pospython:int

Integer index to insert dimension at

dim_valscalar or ndarray

Dimension value(s) to add

vdim

Disabled, this type does not have value dimensions

**kwargs

Keyword arguments passed to the cloned element

Returns:
Cloned object containing the new dimension
clone(data=None, shared_data=True, new_type=None, link=True, *args, **overrides)[source]#

Clones the object, overriding data and parameters.

Parameters:
data

New data replacing the existing data

shared_databool, optional

Whether to use existing data

new_typeoptional

Type to cast object to

linkbool, optional

Whether clone should be linked Determines whether Streams and Links attached to original object will be inherited.

*args

Additional arguments to pass to constructor

**overrides

New keyword arguments to pass to constructor

Returns:
Cloned object
collate()[source]#

Unpacks DynamicMap into container of DynamicMaps

Collation allows unpacking DynamicMaps which return Layout, NdLayout or GridSpace objects into a single such object containing DynamicMaps. Assumes that the items in the layout or grid that is returned do not change.

Returns:
Collated container containing DynamicMaps
property current_key#

Returns the current key value.

decollate()[source]#

Packs DynamicMap of nested DynamicMaps into a single DynamicMap that returns a non-dynamic element

Decollation allows packing a DynamicMap of nested DynamicMaps into a single DynamicMap that returns a simple (non-dynamic) element. All nested streams are lifted to the resulting DynamicMap, and are available in the streams property. The callback property of the resulting DynamicMap is a pure, stateless function of the stream values. To avoid stream parameter name conflicts, the resulting DynamicMap is configured with positional_stream_args=True, and the callback function accepts stream values as positional dict arguments.

Returns:
DynamicMap that returns a non-dynamic element
drop_dimension(dimensions)[source]#

Drops dimension(s) from keys

Parameters:
dimensions

Dimension(s) to drop

Returns:
Clone of object with with dropped dimension(s)
event(**kwargs)[source]#

Updates attached streams and triggers events

Automatically find streams matching the supplied kwargs to update and trigger events on them.

Parameters:
**kwargs

Events to update streams with

grid(dimensions=None, **kwargs)[source]#

Groups data by supplied dimension(s) laying the groups along the dimension(s) out in a GridSpace.

Parameters:
dimensionsDimension/str or python:list

Dimension or list of dimensions to group by

Returns:
gridGridSpace

GridSpace with supplied dimensions

groupby(dimensions=None, container_type=None, group_type=None, **kwargs)[source]#

Groups DynamicMap by one or more dimensions

Applies groupby operation over the specified dimensions returning an object of type container_type (expected to be dictionary-like) containing the groups.

Parameters:
dimensionsDimension(s) to group by
container_typeType to cast group container to
group_typeType to cast each group to
dynamicWhether to return a DynamicMap
**kwargs: Keyword arguments to pass to each group
Returns:
Returns object of supplied container_type containing the
groups. If dynamic=True returns a DynamicMap instead.
hist(dimension=None, num_bins=20, bin_range=None, adjoin=True, **kwargs)[source]#

Computes and adjoins histogram along specified dimension(s).

Defaults to first value dimension if present otherwise falls back to first key dimension.

Parameters:
dimensionDimension(s) to compute histogram on
num_binspython:int, optional

Number of bins

bin_rangepython:tuple, optional

Lower and upper bounds of bins

adjoinbool, optional

Whether to adjoin histogram

Returns:
AdjointLayout of DynamicMap and adjoined histogram if
adjoin=True, otherwise just the histogram
layout(dimensions=None, **kwargs)[source]#

Groups data by supplied dimension(s) laying the groups along the dimension(s) out in a NdLayout.

Parameters:
dimensionsDimension/str or python:list

Dimension or list of dimensions to group by

Returns:
layoutNdLayout

NdLayout with supplied dimensions

map(map_fn, specs=None, clone=True, link_inputs=True)[source]#

Map a function to all objects matching the specs

Recursively replaces elements using a map function when the specs apply, by default applies to all objects, e.g. to apply the function to all contained Curve objects:

dmap.map(fn, hv.Curve)

Parameters:
map_fnFunction to apply to each object
specsList of specs to match

List of types, functions or type[.group][.label] specs to select objects to return, by default applies to all objects.

cloneWhether to clone the object or transform inplace
Returns:
Returns the object after the map_fn has been applied
options(*args, **kwargs)[source]#

Applies simplified option definition returning a new object.

Applies options defined in a flat format to the objects returned by the DynamicMap. If the options are to be set directly on the objects returned by the DynamicMap 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)})

Parameters:
*args

Sets of options to apply to object Supports a number of formats including lists of Options objects, a type[.group][.label] followed by a set of keyword options to apply and a dictionary indexed by type[.group][.label] specs.

backendoptional

Backend to apply options to Defaults to current selected backend

clonebool, optional

Whether to clone object Options can be applied inplace with clone=False

**kwargs

Keywords of options Set of options to apply to the object

Returns:
Returns the cloned object with the options applied
overlay(dimensions=None, **kwargs)[source]#

Group by supplied dimension(s) and overlay each group

Groups data by supplied dimension(s) overlaying the groups along the dimension(s).

Parameters:
dimensionsDimension(s) of dimensions to group by
Returns:
NdOverlay object(s) with supplied dimensions
reindex(kdims=None, force=False)[source]#

Reorders key dimensions on DynamicMap

Create a new object with a reordered set of key dimensions. Dropping dimensions is not allowed on a DynamicMap.

Parameters:
kdimsList of dimensions to reindex the mapping with
forceNot applicable to a DynamicMap
Returns:
Reindexed DynamicMap
relabel(label=None, group=None, depth=1)[source]#

Clone object and apply new group and/or label.

Applies relabeling to children up to the supplied depth.

Parameters:
labelpython:str, optional

New label to apply to returned object

grouppython:str, optional

New group to apply to returned object

depthpython:int, optional

Depth to which relabel will be applied If applied to container allows applying relabeling to contained objects up to the specified depth

Returns:
Returns relabelled object
reset()[source]#

Clear the DynamicMap cache

select(selection_specs=None, **kwargs)[source]#

Applies selection by dimension name

Applies a selection along the dimensions of the object using keyword arguments. The selection may be narrowed to certain objects using selection_specs. For container objects the selection will be applied to all children as well.

Selections may select a specific value, slice or set of values:

  • value: Scalar values will select rows along with an exact

    match, e.g.:

    ds.select(x=3)

  • slice: Slices may be declared as tuples of the upper and

    lower bound, e.g.:

    ds.select(x=(0, 3))

  • values: A list of values may be selected using a list or

    set, e.g.:

    ds.select(x=[0, 1, 2])

Parameters:
selection_specsList of specs to match on

A list of types, functions, or type[.group][.label] strings specifying which objects to apply the selection on.

**selection: Dictionary declaring selections by dimension

Selections can be scalar values, tuple ranges, lists of discrete values and boolean arrays

Returns:
Returns an Dimensioned object containing the selected data
or a scalar if a single value was selected
property unbounded#

Returns a list of key dimensions that are unbounded, excluding stream parameters. If any of these key dimensions are unbounded, the DynamicMap as a whole is also unbounded.

class geoviews.EdgePaths(data=None, kdims=None, vdims=None, **kwargs)[source]#

Bases: Path

EdgePaths is a simple Element representing the paths of edges connecting nodes in a graph.

Parameter Definitions

Parameters inherited from:

group = String(constant=True, default='EdgePaths', label='Group')

A string describing the data wrapped by the object.

class geoviews.Feature(data, kdims=None, vdims=None, **params)[source]#

Bases: _GeoFeature

A Feature represents a geographical feature specified as a cartopy Feature type.

Methods

clone([data, shared_data, new_type])

Clones the object, overriding data and parameters.

geoms([scale, bounds, as_element])

Returns the geometries held by the Feature.

range(dim[, data_range, dimension_range])

Return the lower and upper bounds of values along dimension.

Parameter Definitions

Parameters inherited from:

holoviews.core.dimension.LabelledData: label

holoviews.core.dimension.Dimensioned: cdims, vdims

holoviews.core.element.Element2D: extents

geoviews.element.geo._Element: kdims, crs

group = String(default='Feature', label='Group')

A string describing the data wrapped by the object.

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

Clones the object, overriding data and parameters.

Parameters:
data

New data replacing the existing data

shared_databool, optional

Whether to use existing data

new_typeoptional

Type to cast object to

linkbool, optional

Whether clone should be linked Determines whether Streams and Links attached to original object will be inherited.

*args

Additional arguments to pass to constructor

**overrides

New keyword arguments to pass to constructor

Returns:
Cloned object
geoms(scale=None, bounds=None, as_element=True)[source]#

Returns the geometries held by the Feature.

Parameters:
scalepython:str

Scale of the geometry to return expressed as string. Available scales depends on the Feature type.

NaturalEarthFeature:

‘10m’, ‘50m’, ‘110m’

GSHHSFeature:

‘auto’, ‘coarse’, ‘low’, ‘intermediate’, ‘high’, ‘full’

boundspython:tuple

Tuple of a bounding region to query for geometries in

as_elementbool

Whether to wrap the geometries in an element

Returns:
geometriesPolygons/Path

Polygons or Path object wrapping around returned geometries

range(dim, data_range=True, dimension_range=True)[source]#

Return the lower and upper bounds of values along dimension.

Parameters:
dimension

The dimension to compute the range on.

data_rangebool

Compute range from data values

dimension_rangebool

Include Dimension ranges Whether to include Dimension range and soft_range in range calculation

Returns:
Tuple containing the lower and upper bound
class geoviews.FilledContours(data=None, kdims=None, vdims=None, **kwargs)[source]#

Bases: QuadMesh

Contours represents a 2D array of some quantity with some associated coordinates, which may be discretized into one or more filled contours.

Parameter Definitions

Parameters inherited from:

group = String(default='FilledContours', label='Group')

A string describing the data wrapped by the object.

exception geoviews.GeoviewsDeprecationWarning[source]#

Bases: DeprecationWarning

A Geoviews-specific DeprecationWarning subclass.

Used to selectively filter Geoviews deprecations for unconditional display.

exception geoviews.GeoviewsUserWarning[source]#

Bases: UserWarning

A Geoviews-specific UserWarning subclass.

Used to selectively filter Geoviews warnings for unconditional display.

class geoviews.Graph(data=None, kdims=None, vdims=None, **kwargs)[source]#

Bases: _Element, Graph

Attributes:
edgepaths

Returns the fixed EdgePaths or computes direct connections between supplied nodes.

Methods

edge_type

alias of EdgePaths

node_type

alias of Nodes

Parameter Definitions

Parameters inherited from:

group = String(constant=True, default='Graph', label='Group')

A string describing the data wrapped by the object.

edge_type[source]#

alias of EdgePaths

property edgepaths#

Returns the fixed EdgePaths or computes direct connections between supplied nodes.

node_type[source]#

alias of Nodes

class geoviews.GridSpace(initial_items=None, kdims=None, **params)[source]#

Bases: Layoutable, UniformNdMapping

Grids are distinct from Layouts as they ensure all contained elements to be of the same type. Unlike Layouts, which have integer keys, Grids usually have floating point keys, which correspond to a grid sampling in some two-dimensional space. This two-dimensional space may have to arbitrary dimensions, e.g. for 2D parameter spaces.

Attributes:
last

The last of a GridSpace is another GridSpace constituted of the last of the individual elements.

shape

Returns the 2D shape of the GridSpace as (rows, cols).

Methods

decollate()

Packs GridSpace of DynamicMaps into a single DynamicMap that returns a GridSpace

keys([full_grid])

Returns the keys of the GridSpace

Parameter Definitions

Parameters inherited from:

kdims = List(bounds=(1, 2), default=[Dimension('X'), Dimension('Y')], label='Kdims')

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.

decollate()[source]#

Packs GridSpace of DynamicMaps into a single DynamicMap that returns a GridSpace

Decollation allows packing a GridSpace of DynamicMaps into a single DynamicMap that returns a GridSpace of simple (non-dynamic) elements. All nested streams are lifted to the resulting DynamicMap, and are available in the streams property. The callback property of the resulting DynamicMap is a pure, stateless function of the stream values. To avoid stream parameter name conflicts, the resulting DynamicMap is configured with positional_stream_args=True, and the callback function accepts stream values as positional dict arguments.

Returns:
DynamicMap that returns a GridSpace
keys(full_grid=False)[source]#

Returns the keys of the GridSpace

Parameters:
full_gridbool, optional

Return full cross-product of keys

Returns:
List of keys
property last#

The last of a GridSpace is another GridSpace constituted of the last of the individual elements. To access the elements by their X,Y position, either index the position directly or use the items() method.

property shape#

Returns the 2D shape of the GridSpace as (rows, cols).

class geoviews.HexTiles(data=None, kdims=None, vdims=None, **kwargs)[source]#

Bases: _Element, HexTiles

Points represent a collection of points with an associated cartopy coordinate-reference system.

Parameter Definitions

Parameters inherited from:

group = String(default='HexTiles', label='Group')

A string describing the data wrapped by the object.

class geoviews.HoloMap(initial_items=None, kdims=None, group=None, label=None, **params)[source]#

Bases: Layoutable, UniformNdMapping, Overlayable

A HoloMap is an n-dimensional mapping of viewable elements or overlays. Each item in a HoloMap has an tuple key defining the values along each of the declared key dimensions, defining the discretely sampled space of values.

The visual representation of a HoloMap consists of the viewable objects inside the HoloMap which can be explored by varying one or more widgets mapping onto the key dimensions of the HoloMap.

Attributes:
opts

Methods

collate([merge_type, drop, drop_constant])

Collate allows reordering nested containers

decollate()

Packs HoloMap of DynamicMaps into a single DynamicMap that returns an HoloMap

grid([dimensions])

Group by supplied dimension(s) and lay out groups in grid

hist([dimension, num_bins, bin_range, ...])

Computes and adjoins histogram along specified dimension(s).

layout([dimensions])

Group by supplied dimension(s) and lay out groups

options(*args, **kwargs)

Applies simplified option definition returning a new object

overlay([dimensions])

Group by supplied dimension(s) and overlay each group

relabel([label, group, depth])

Clone object and apply new group and/or label.

Parameter Definitions

Parameters inherited from:

collate(merge_type=None, drop=None, drop_constant=False)[source]#

Collate allows reordering nested containers

Collation allows collapsing nested mapping types by merging their dimensions. In simple terms in merges nested containers into a single merged type.

In the simple case a HoloMap containing other HoloMaps can easily be joined in this way. However collation is particularly useful when the objects being joined are deeply nested, e.g. you want to join multiple Layouts recorded at different times, collation will return one Layout containing HoloMaps indexed by Time. Changing the merge_type will allow merging the outer Dimension into any other UniformNdMapping type.

Parameters:
merge_type

Type of the object to merge with

drop

List of dimensions to drop

drop_constant

Drop constant dimensions automatically

Returns:
Collated Layout or HoloMap
decollate()[source]#

Packs HoloMap of DynamicMaps into a single DynamicMap that returns an HoloMap

Decollation allows packing a HoloMap of DynamicMaps into a single DynamicMap that returns an HoloMap of simple (non-dynamic) elements. All nested streams are lifted to the resulting DynamicMap, and are available in the streams property. The callback property of the resulting DynamicMap is a pure, stateless function of the stream values. To avoid stream parameter name conflicts, the resulting DynamicMap is configured with positional_stream_args=True, and the callback function accepts stream values as positional dict arguments.

Returns:
DynamicMap that returns an HoloMap
grid(dimensions=None, **kwargs)[source]#

Group by supplied dimension(s) and lay out groups in grid

Groups data by supplied dimension(s) laying the groups along the dimension(s) out in a GridSpace.

Parameters:
dimensionsDimension/str or python:list

Dimension or list of dimensions to group by

Returns:
GridSpace with supplied dimensions
hist(dimension=None, num_bins=20, bin_range=None, adjoin=True, individually=True, **kwargs)[source]#

Computes and adjoins histogram along specified dimension(s).

Defaults to first value dimension if present otherwise falls back to first key dimension.

Parameters:
dimension

Dimension(s) to compute histogram on

num_binspython:int, optional

Number of bins

bin_rangepython:tuple, optional

Lower and upper bounds of bins

adjoinbool, optional

Whether to adjoin histogram

Returns:
AdjointLayout of HoloMap and histograms or just the
histograms
layout(dimensions=None, **kwargs)[source]#

Group by supplied dimension(s) and lay out groups

Groups data by supplied dimension(s) laying the groups along the dimension(s) out in a NdLayout.

Parameters:
dimensions

Dimension(s) to group by

Returns:
NdLayout with supplied dimensions
options(*args, **kwargs)[source]#

Applies simplified option definition returning a new object

Applies options defined in a flat format to the objects returned by the DynamicMap. If the options are to be set directly on the objects in the HoloMap 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)})

Parameters:
*args

Sets of options to apply to object Supports a number of formats including lists of Options objects, a type[.group][.label] followed by a set of keyword options to apply and a dictionary indexed by type[.group][.label] specs.

backendoptional

Backend to apply options to Defaults to current selected backend

clonebool, optional

Whether to clone object Options can be applied inplace with clone=False

**kwargs: Keywords of options

Set of options to apply to the object

Returns:
Returns the cloned object with the options applied
overlay(dimensions=None, **kwargs)[source]#

Group by supplied dimension(s) and overlay each group

Groups data by supplied dimension(s) overlaying the groups along the dimension(s).

Parameters:
dimensions

Dimension(s) of dimensions to group by

Returns:
NdOverlay object(s) with supplied dimensions
relabel(label=None, group=None, depth=1)[source]#

Clone object and apply new group and/or label.

Applies relabeling to children up to the supplied depth.

Parameters:
labelpython:str, optional

New label to apply to returned object

grouppython:str, optional

New group to apply to returned object

depthpython:int, optional

Depth to which relabel will be applied If applied to container allows applying relabeling to contained objects up to the specified depth

Returns:
Returns relabelled object
class geoviews.Image(data=None, kdims=None, vdims=None, **kwargs)[source]#

Bases: _Element, Image

Image represents a 2D array of some quantity with some associated coordinates.

Methods

from_xarray

Parameter Definitions

Parameters inherited from:

holoviews.core.dimension.LabelledData: label

holoviews.core.dimension.Dimensioned: cdims

holoviews.core.element.Element2D: extents

holoviews.element.raster.Image: datatype, bounds, rtol

geoviews.element.geo._Element: kdims, crs

group = String(default='Image', label='Group')

A string describing the data wrapped by the object.

vdims = List(bounds=(1, None), default=[Dimension('z')], label='Vdims')

The dimension description of the data held in the matrix.

class geoviews.ImageStack(data=None, kdims=None, vdims=None, **kwargs)[source]#

Bases: _Element, ImageStack

ImageStack expands the capabilities of Image to by supporting multiple layers of images.

As there is many ways to represent multiple layers of images, the following options are supported:

  1. A 3D Numpy array with the shape (y, x, level)

  2. A list of 2D Numpy arrays with identical shape (y, x)

  3. A dictionary where the keys will be set as the vdims and the

    values are 2D Numpy arrays with identical shapes (y, x). If the dictionary’s keys matches the kdims of the element, they need to be 1D arrays.

  4. A tuple containing (x, y, level_0, level_1, …),

    where the level is a 2D Numpy array in the shape of (y, x).

  5. An xarray DataArray or Dataset where its coords contain the kdims.

If no kdims are supplied, x and y are used.

If no vdims are supplied, and the naming can be inferred like with a dictionary the levels will be named level_0, level_1, etc.

Parameter Definitions

Parameters inherited from:

holoviews.core.dimension.LabelledData: label

holoviews.core.dimension.Dimensioned: cdims

holoviews.core.element.Element2D: extents

holoviews.element.raster.Image: datatype, bounds, rtol

geoviews.element.geo._Element: kdims, crs

group = String(constant=True, default='ImageStack', label='Group')

A string describing the data wrapped by the object.

vdims = List(bounds=(1, None), default=[Dimension('z')], label='Vdims')

The dimension description of the data held in the matrix.

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

Bases: _Element, Labels

Points represent a collection of points with an associated cartopy coordinate-reference system.

Parameter Definitions

Parameters inherited from:

group = String(default='Labels', label='Group')

A string describing the data wrapped by the object.

class geoviews.Layout(items=None, identifier=None, parent=None, **kwargs)[source]#

Bases: Layoutable, ViewableTree

A Layout is an ViewableTree with ViewableElement objects as leaf values.

Unlike ViewableTree, a Layout supports a rich display, displaying leaf items in a grid style layout. In addition to the usual ViewableTree indexing, Layout supports indexing of items by their row and column index in the layout.

The maximum number of columns in such a layout may be controlled with the cols method.

Attributes:
shape

Tuple indicating the number of rows and columns in the Layout.

Methods

clone(*args, **overrides)

Clones the Layout, overriding data and parameters.

cols(ncols)

Sets the maximum number of columns in the NdLayout.

decollate()

Packs Layout of DynamicMaps into a single DynamicMap that returns a Layout

relabel([label, group, depth])

Clone object and apply new group and/or label.

grid_items

Parameter Definitions

Parameters inherited from:

group = String(constant=True, default='Layout', label='Group')

A string describing the data wrapped by the object.

clone(*args, **overrides)[source]#

Clones the Layout, overriding data and parameters.

Parameters:
data

New data replacing the existing data

shared_databool, optional

Whether to use existing data

new_typeoptional

Type to cast object to

*args

Additional arguments to pass to constructor

**overrides

New keyword arguments to pass to constructor

Returns:
Cloned Layout object
cols(ncols)[source]#

Sets the maximum number of columns in the NdLayout.

Any items beyond the set number of cols will flow onto a new row. The number of columns control the indexing and display semantics of the NdLayout.

Parameters:
ncolspython:int

Number of columns to set on the NdLayout

decollate()[source]#

Packs Layout of DynamicMaps into a single DynamicMap that returns a Layout

Decollation allows packing a Layout of DynamicMaps into a single DynamicMap that returns a Layout of simple (non-dynamic) elements. All nested streams are lifted to the resulting DynamicMap, and are available in the streams property. The callback property of the resulting DynamicMap is a pure, stateless function of the stream values. To avoid stream parameter name conflicts, the resulting DynamicMap is configured with positional_stream_args=True, and the callback function accepts stream values as positional dict arguments.

Returns:
DynamicMap that returns a Layout
relabel(label=None, group=None, depth=1)[source]#

Clone object and apply new group and/or label.

Applies relabeling to children up to the supplied depth.

Parameters:
labelpython:str, optional

New label to apply to returned object

grouppython:str, optional

New group to apply to returned object

depthpython:int, optional

Depth to which relabel will be applied If applied to container allows applying relabeling to contained objects up to the specified depth

Returns:
Returns relabelled object
property shape#

Tuple indicating the number of rows and columns in the Layout.

class geoviews.LineContours(data=None, kdims=None, vdims=None, **kwargs)[source]#

Bases: QuadMesh

LineContours represents a 2D array of some quantity with some associated coordinates, which may be discretized into one or more line contours.

Parameter Definitions

Parameters inherited from:

group = String(default='LineContours', label='Group')

A string describing the data wrapped by the object.

class geoviews.NdLayout(initial_items=None, kdims=None, **params)[source]#

Bases: Layoutable, UniformNdMapping

NdLayout is a UniformNdMapping providing an n-dimensional data structure to display the contained Elements and containers in a layout. Using the cols method the NdLayout can be rearranged with the desired number of columns.

Attributes:
last

Returns another NdLayout constituted of the last views of the individual elements (if they are maps).

shape

Tuple indicating the number of rows and columns in the NdLayout.

uniform

Methods

clone(*args, **overrides)

Clones the NdLayout, overriding data and parameters.

cols(ncols)

Sets the maximum number of columns in the NdLayout.

grid_items()

Compute a dict of {(row,column): (key, value)} elements from the current set of items and specified number of columns.

Parameter Definitions

Parameters inherited from:

clone(*args, **overrides)[source]#

Clones the NdLayout, overriding data and parameters.

Parameters:
data

New data replacing the existing data

shared_databool, optional

Whether to use existing data

new_typeoptional

Type to cast object to

*args

Additional arguments to pass to constructor

**overrides

New keyword arguments to pass to constructor

Returns:
Cloned NdLayout object
cols(ncols)[source]#

Sets the maximum number of columns in the NdLayout.

Any items beyond the set number of cols will flow onto a new row. The number of columns control the indexing and display semantics of the NdLayout.

Parameters:
ncolspython:int

Number of columns to set on the NdLayout

grid_items()[source]#

Compute a dict of {(row,column): (key, value)} elements from the current set of items and specified number of columns.

property last#

Returns another NdLayout constituted of the last views of the individual elements (if they are maps).

property shape#

Tuple indicating the number of rows and columns in the NdLayout.

class geoviews.NdOverlay(overlays=None, kdims=None, **params)[source]#

Bases: Overlayable, UniformNdMapping, CompositeOverlay

An NdOverlay allows a group of NdOverlay to be overlaid together. NdOverlay can be indexed out of an overlay and an overlay is an iterable that iterates over the contained layers.

Methods

decollate()

Packs NdOverlay of DynamicMaps into a single DynamicMap that returns an NdOverlay

Parameter Definitions

Parameters inherited from:

kdims = List(bounds=(0, None), constant=True, default=[Dimension('Element')], label='Kdims')

List of dimensions the NdOverlay can be indexed by.

decollate()[source]#

Packs NdOverlay of DynamicMaps into a single DynamicMap that returns an NdOverlay

Decollation allows packing a NdOverlay of DynamicMaps into a single DynamicMap that returns an NdOverlay of simple (non-dynamic) elements. All nested streams are lifted to the resulting DynamicMap, and are available in the streams property. The callback property of the resulting DynamicMap is a pure, stateless function of the stream values. To avoid stream parameter name conflicts, the resulting DynamicMap is configured with positional_stream_args=True, and the callback function accepts stream values as positional dict arguments.

Returns:
DynamicMap that returns an NdOverlay
class geoviews.Nodes(data=None, kdims=None, vdims=None, **kwargs)[source]#

Bases: _Element, Nodes

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.

Parameter Definitions

Parameters inherited from:

group = String(constant=True, default='Nodes', label='Group')

A string describing the data wrapped by the object.

kdims = List(bounds=(3, 3), default=[Dimension('Longitude'), Dimension('Latitude'), Dimension('index')], label='Kdims')

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.

class geoviews.Overlay(items=None, group=None, label=None, **params)[source]#

Bases: ViewableTree, CompositeOverlay, Layoutable, Overlayable

An Overlay consists of multiple Elements (potentially of heterogeneous type) presented one on top each other with a particular z-ordering.

Overlays along with elements constitute the only valid leaf types of a Layout and in fact extend the Layout structure. Overlays are constructed using the * operator (building an identical structure to the + operator).

Attributes:
ddims

The list of deep dimensions

shape

Methods

clone([data, shared_data, new_type, link])

Clones the object, overriding data and parameters.

collate()

Collates any objects in the Overlay resolving any issues the recommended nesting structure.

decollate()

Packs Overlay of DynamicMaps into a single DynamicMap that returns an Overlay

get(identifier[, default])

Get a layer in the Overlay.

Parameter Definitions

Parameters inherited from:

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

Clones the object, overriding data and parameters.

Parameters:
data

New data replacing the existing data

shared_databool, optional

Whether to use existing data

new_typeoptional

Type to cast object to

linkbool, optional

Whether clone should be linked Determines whether Streams and Links attached to original object will be inherited.

*args

Additional arguments to pass to constructor

**overrides

New keyword arguments to pass to constructor

Returns:
Cloned object
collate()[source]#

Collates any objects in the Overlay resolving any issues the recommended nesting structure.

property ddims#

The list of deep dimensions

decollate()[source]#

Packs Overlay of DynamicMaps into a single DynamicMap that returns an Overlay

Decollation allows packing an Overlay of DynamicMaps into a single DynamicMap that returns an Overlay of simple (non-dynamic) elements. All nested streams are lifted to the resulting DynamicMap, and are available in the streams property. The callback property of the resulting DynamicMap is a pure, stateless function of the stream values. To avoid stream parameter name conflicts, the resulting DynamicMap is configured with positional_stream_args=True, and the callback function accepts stream values as positional dict arguments.

Returns:
DynamicMap that returns an Overlay
get(identifier, default=None)[source]#

Get a layer in the Overlay.

Get a particular layer in the Overlay using its path string or an integer index.

Parameters:
identifier

Index or path string of the item to return

default

Value to return if no item is found

Returns:
The indexed layer of the Overlay
property group#

str(object=’’) -> str str(bytes_or_buffer[, encoding[, errors]]) -> str

Create a new string object from the given object. If encoding or errors is specified, then the object must expose a data buffer that will be decoded using the given encoding and error handler. Otherwise, returns the result of object.__str__() (if defined) or repr(object). encoding defaults to sys.getdefaultencoding(). errors defaults to ‘strict’.

property label#

str(object=’’) -> str str(bytes_or_buffer[, encoding[, errors]]) -> str

Create a new string object from the given object. If encoding or errors is specified, then the object must expose a data buffer that will be decoded using the given encoding and error handler. Otherwise, returns the result of object.__str__() (if defined) or repr(object). encoding defaults to sys.getdefaultencoding(). errors defaults to ‘strict’.

class geoviews.Palette(key, **params)[source]#

Bases: Cycle

Palettes allow easy specifying a discrete sampling of an existing colormap. Palettes may be supplied a key to look up a function function in the colormap class attribute. The function should accept a float scalar in the specified range and return a RGB(A) tuple. The number of samples may also be specified as a parameter.

The range and samples may conveniently be overridden with the __getitem__ method.

Parameter Definitions

Parameters inherited from:

key = String(default='grayscale', label='Key')

Palettes look up the Palette values based on some key.

range = NumericTuple(default=(0, 1), label='Range', length=2)

The range from which the Palette values are sampled.

samples = Integer(default=32, inclusive_bounds=(True, True), label='Samples')

The number of samples in the given range to supply to the sample_fn.

sample_fn = Callable(default=<function linspace at 0x10e67e670>, label='Sample fn')

The function to generate the samples, by default linear.

reverse = Boolean(default=False, label='Reverse')

Whether to reverse the palette.

sample_fn(stop, num=50, endpoint=True, retstep=False, dtype=None, axis=0, *, device=None)[source]#

Return evenly spaced numbers over a specified interval.

Returns num evenly spaced samples, calculated over the interval [start, stop].

The endpoint of the interval can optionally be excluded.

Changed in version 1.20.0: Values are rounded towards -inf instead of 0 when an integer dtype is specified. The old behavior can still be obtained with np.linspace(start, stop, num).astype(int)

Parameters:
startnumpy:array_like

The starting value of the sequence.

stopnumpy:array_like

The end value of the sequence, unless endpoint is set to False. In that case, the sequence consists of all but the last of num + 1 evenly spaced samples, so that stop is excluded. Note that the step size changes when endpoint is False.

numpython:int, optional

Number of samples to generate. Default is 50. Must be non-negative.

endpointbool, optional

If True, stop is the last sample. Otherwise, it is not included. Default is True.

retstepbool, optional

If True, return (samples, step), where step is the spacing between samples.

dtypedtype, optional

The type of the output array. If dtype is not given, the data type is inferred from start and stop. The inferred dtype will never be an integer; float is chosen even if the arguments would produce an array of integers.

axispython:int, optional

The axis in the result to store the samples. Relevant only if start or stop are array-like. By default (0), the samples will be along a new axis inserted at the beginning. Use -1 to get an axis at the end.

devicepython:str, optional

The device on which to place the created array. Default: None. For Array-API interoperability only, so must be "cpu" if passed.

Added in version 2.0.0.

Returns:
samplesndarray

There are num equally spaced samples in the closed interval [start, stop] or the half-open interval [start, stop) (depending on whether endpoint is True or False).

steppython:float, optional

Only returned if retstep is True

Size of spacing between samples.

See also

arange

Similar to linspace, but uses a step size (instead of the number of samples).

geomspace

Similar to linspace, but with numbers spaced evenly on a log scale (a geometric progression).

logspace

Similar to geomspace, but with the end points specified as logarithms.

how-to-partition

Examples

>>> import numpy as np
>>> np.linspace(2.0, 3.0, num=5)
array([2.  , 2.25, 2.5 , 2.75, 3.  ])
>>> np.linspace(2.0, 3.0, num=5, endpoint=False)
array([2. ,  2.2,  2.4,  2.6,  2.8])
>>> np.linspace(2.0, 3.0, num=5, retstep=True)
(array([2.  ,  2.25,  2.5 ,  2.75,  3.  ]), 0.25)

Graphical illustration:

>>> import matplotlib.pyplot as plt
>>> N = 8
>>> y = np.zeros(N)
>>> x1 = np.linspace(0, 10, N, endpoint=True)
>>> x2 = np.linspace(0, 10, N, endpoint=False)
>>> plt.plot(x1, y, 'o')
[<matplotlib.lines.Line2D object at 0x...>]
>>> plt.plot(x2, y + 0.5, 'o')
[<matplotlib.lines.Line2D object at 0x...>]
>>> plt.ylim([-0.5, 1])
(-0.5, 1)
>>> plt.show()
class geoviews.Path(data=None, kdims=None, vdims=None, **kwargs)[source]#

Bases: _Element, Path

The Path Element contains a list of Paths stored as Nx2 numpy arrays along with a coordinate reference system.

Methods

geom([union, projection])

Converts the Path to a shapely geometry.

Parameter Definitions

Parameters inherited from:

group = String(constant=True, default='Path', label='Group')

A string describing the data wrapped by the object.

geom(union=False, projection=None)[source]#

Converts the Path to a shapely geometry.

Parameters:
unionbool, default=False

Whether to compute a union between the geometries

projectionEPSG python:str | Cartopy CRS | python:None

Whether to project the geometry to other coordinate system

Returns:
A shapely geometry
class geoviews.Points(data=None, kdims=None, vdims=None, **kwargs)[source]#

Bases: _Element, Points

Points represent a collection of points with an associated cartopy coordinate-reference system.

Methods

geom([union, projection])

Converts the Points to a shapely geometry.

Parameter Definitions

Parameters inherited from:

group = String(default='Points', label='Group')

A string describing the data wrapped by the object.

geom(union=False, projection=None)[source]#

Converts the Points to a shapely geometry.

Parameters:
unionbool, default=False

Whether to compute a union between the geometries

projectionEPSG python:str | Cartopy CRS | python:None

Whether to project the geometry to other coordinate system

Returns:
A shapely geometry
class geoviews.Polygons(data=None, kdims=None, vdims=None, **kwargs)[source]#

Bases: _Element, Polygons

Polygons is a Path Element type that may contain any number of closed paths with an associated value and a coordinate reference system.

Methods

geom([union, projection])

Converts the Path to a shapely geometry.

Parameter Definitions

Parameters inherited from:

group = String(constant=True, default='Polygons', label='Group')

A string describing the data wrapped by the object.

geom(union=False, projection=None)[source]#

Converts the Path to a shapely geometry.

Parameters:
unionbool, default=False

Whether to compute a union between the geometries

projectionEPSG python:str | Cartopy CRS | python:None

Whether to project the geometry to other coordinate system

Returns:
A shapely geometry
class geoviews.QuadMesh(data=None, kdims=None, vdims=None, **kwargs)[source]#

Bases: _Element, QuadMesh

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.

Methods

trimesh()

Converts a QuadMesh into a TriMesh.

from_xarray

Parameter Definitions

Parameters inherited from:

group = String(default='QuadMesh', label='Group')

A string describing the data wrapped by the object.

vdims = List(bounds=(1, None), default=[Dimension('z')], label='Vdims')

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.

datatype = List(bounds=(0, None), default=['grid', 'xarray'], label='Datatype')

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).

trimesh()[source]#

Converts a QuadMesh into a TriMesh.

class geoviews.RGB(data=None, kdims=None, vdims=None, **kwargs)[source]#

Bases: _Element, RGB

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.

Methods

from_xarray(da[, crs, apply_transform, ...])

Returns an RGB or Image element given an xarray DataArray loaded using xr.open_rasterio.

Parameter Definitions

Parameters inherited from:

holoviews.core.dimension.LabelledData: label

holoviews.core.dimension.Dimensioned: cdims

holoviews.core.element.Element2D: extents

holoviews.element.raster.Image: datatype, bounds, rtol

holoviews.element.raster.RGB: alpha_dimension

geoviews.element.geo._Element: kdims, crs

group = String(constant=True, default='RGB', label='Group')

A string describing the data wrapped by the object.

vdims = List(bounds=(3, 4), default=[Dimension('R'), Dimension('G'), Dimension('B')], label='Vdims')

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.

classmethod from_xarray(da, crs=None, apply_transform=False, nan_nodata=False, **kwargs)[source]#

Returns an RGB or Image element given an xarray DataArray loaded using xr.open_rasterio.

If a crs attribute is present on the loaded data it will attempt to decode it into a cartopy projection otherwise it will default to a non-geographic HoloViews element.

Parameters:
daxarray.DataArray

DataArray to convert to element

crsCartopy CRS or EPSG python:str (optional)

Overrides CRS inferred from the data

apply_transformbool

Whether to apply affine transform if defined on the data

nan_nodatabool

If data contains nodata values convert them to NaNs

**kwargs

Keyword arguments passed to the HoloViews/GeoViews element

Returns:
element

Image/RGB/QuadMesh element

class geoviews.Rectangles(data=None, kdims=None, vdims=None, **kwargs)[source]#

Bases: _Element, Rectangles

Rectangles represent a collection of axis-aligned rectangles in 2D space.

Methods

geom([union, projection])

Converts the Rectangles to a shapely geometry.

Parameter Definitions

Parameters inherited from:

group = String(constant=True, default='Rectangles', label='Group')

A string describing the data wrapped by the object.

kdims = List(bounds=(4, 4), constant=True, default=[Dimension('lon0'), Dimension('lat0'), Dimension('lon1'), Dimension('lat1')], label='Kdims')

The key dimensions of the Rectangles element represent the bottom-left (lon0, lat0) and top right (lon1, lat1) coordinates of each box.

geom(union=False, projection=None)[source]#

Converts the Rectangles to a shapely geometry.

Parameters:
unionbool, default=False

Whether to compute a union between the geometries

projectionEPSG python:str | Cartopy CRS | python:None

Whether to project the geometry to other coordinate system

Returns:
A shapely geometry
class geoviews.Segments(data=None, kdims=None, vdims=None, **kwargs)[source]#

Bases: _Element, Segments

Segments represent a collection of lines in 2D space.

Methods

geom([union, projection])

Converts the Segments to a shapely geometry.

Parameter Definitions

Parameters inherited from:

group = String(constant=True, default='Segments', label='Group')

A string describing the data wrapped by the object.

kdims = List(bounds=(4, 4), constant=True, default=[Dimension('lon0'), Dimension('lat0'), Dimension('lon1'), Dimension('lat1')], label='Kdims')

The key dimensions of the Segments element represent the bottom-left (lon0, lat0) and top-right (lon1, lat1) coordinates of each segment.

geom(union=False, projection=None)[source]#

Converts the Segments to a shapely geometry.

class geoviews.Shape(data=None, kdims=None, vdims=None, **kwargs)[source]#

Bases: Dataset

Shape wraps any shapely geometry type.

Methods

from_records(records[, dataset, on, value, ...])

Load data from a collection of cartopy.io.shapereader.Record objects and optionally merge it with a dataset to assign values to each polygon and form a chloropleth.

from_shapefile(shapefile, *args, **kwargs)

Loads a shapefile from disk and optionally merges it with a dataset.

geom([union, projection])

Returns the Shape as a shapely geometry

Parameter Definitions

Parameters inherited from:

group = String(default='Shape', label='Group')

A string describing the data wrapped by the object.

vdims = List(bounds=(0, None), default=[], label='Vdims')

Shape optionally accept a value dimension, corresponding to the supplied values.

datatype = List(bounds=(0, None), default=['geom_dictionary'], label='Datatype')

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).

level = Number(allow_None=True, inclusive_bounds=(True, True), label='Level')

Optional level associated with the set of Contours.

classmethod from_records(records, dataset=None, on=None, value=None, index=None, drop_missing=False, element=None, **kwargs)[source]#

Load data from a collection of cartopy.io.shapereader.Record objects and optionally merge it with a dataset to assign values to each polygon and form a chloropleth. Supplying just records will return an NdOverlayof Shape Elements with a numeric index. If a dataset is supplied, a mapping between the attribute names in the records and the dimension names in the dataset must be supplied. The values assigned to each shape file can then be drawn from the dataset by supplying a value and keys the Shapes are indexed by specifying one or index dimensions.

Parameters:
recordspython:list of cartopy.io.shapereader.Record

Iterator containing Records.

datasetholoviews.Dataset

Any HoloViews Dataset type.

onpython:str or python:list or python:dict

A mapping between the attribute names in the records and the dimensions in the dataset.

valuepython:str

The value dimension in the dataset the values will be drawn from.

indexpython:str or python:list

One or more dimensions in the dataset the Shapes will be indexed by.

drop_missingbool

Whether to drop shapes which are missing from the provides dataset.

Returns:
shapesPolygons or Path object

A Polygons or Path object containing the geometries

classmethod from_shapefile(shapefile, *args, **kwargs)[source]#

Loads a shapefile from disk and optionally merges it with a dataset. See from_records for full signature.

Parameters:
recordspython:list of cartopy.io.shapereader.Record

Iterator containing Records.

datasetholoviews.Dataset

Any HoloViews Dataset type.

onpython:str or python:list or python:dict

A mapping between the attribute names in the records and the dimensions in the dataset.

valuepython:str

The value dimension in the dataset the values will be drawn from.

indexpython:str or python:list

One or more dimensions in the dataset the Shapes will be indexed by.

drop_missingbool

Whether to drop shapes which are missing from the provides dataset.

Returns:
shapesPolygons or Path object

A Polygons or Path object containing the geometries

geom(union=False, projection=None)[source]#

Returns the Shape as a shapely geometry

Parameters:
unionbool, default=False

Whether to compute a union between the geometries

projectionEPSG python:str | Cartopy CRS | python:None

Whether to project the geometry to other coordinate system

Returns:
A shapely geometry
class geoviews.Store[source]#

Bases: object

The Store is what links up HoloViews objects to their corresponding options and to the appropriate classes of the chosen backend (e.g. for rendering).

In addition, Store supports pickle operations that automatically pickle and unpickle the corresponding options for a HoloViews object.

Methods

info(obj[, ansi, backend, visualization, ...])

Show information about a particular object or component class including the applicable style and plot options.

options
classmethod add_style_opts(component, new_options, backend=None)[source]#

Given a component such as an Element (e.g. Image, Curve) or a container (e.g. Layout) specify new style options to be accepted by the corresponding plotting class.

Note : This is supplied for advanced users who know which additional style keywords are appropriate for the corresponding plotting class.

classmethod dump(obj, file, protocol=0)[source]#

Equivalent to pickle.dump except that the HoloViews option tree is saved appropriately.

classmethod dumps(obj, protocol=0)[source]#

Equivalent to pickle.dumps except that the HoloViews option tree is saved appropriately.

classmethod info(obj, ansi=True, backend='matplotlib', visualization=True, recursive=False, pattern=None, elements=None)[source]#

Show information about a particular object or component class including the applicable style and plot options. Returns None if the object is not parameterized.

classmethod load(filename)[source]#

Equivalent to pickle.load except that the HoloViews trees is restored appropriately.

classmethod loaded_backends()[source]#

Returns a list of the backends that have been loaded, based on the available OptionTrees.

classmethod loads(pickle_string)[source]#

Equivalent to pickle.loads except that the HoloViews trees is restored appropriately.

classmethod lookup(backend, obj)[source]#

Given an object, lookup the corresponding customized option tree if a single custom tree is applicable.

output_settings[source]#

alias of OutputSettings

classmethod register(associations, backend, style_aliases=None)[source]#

Register the supplied dictionary of associations between elements and plotting classes to the specified backend.

classmethod render(obj)[source]#

Using any display hooks that have been registered, render the object to a dictionary of MIME types and metadata information.

classmethod set_current_backend(backend)[source]#

Use this method to set the backend to run the switch hooks

classmethod set_display_hook(group, objtype, hook)[source]#

Specify a display hook that will be applied to objects of type objtype. The group specifies the set to which the display hook belongs, allowing the Store to compute the precedence within each group.

classmethod transfer_options(obj, new_obj, backend=None, names=None, level=3)[source]#

Transfers options for all backends from one object to another. Drops any options defined in the supplied drop list.

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

Bases: Text, _Element

An annotation containing some text at an x, y coordinate along with a coordinate reference system.

Parameter Definitions

Parameters inherited from:

holoviews.core.dimension.LabelledData: label

holoviews.core.dimension.Dimensioned: cdims, vdims

holoviews.core.element.Element2D: extents

geoviews.element.geo._Element: crs

holoviews.element.annotation.Annotation: kdims

holoviews.element.annotation.Text: group, x, y, text, fontsize, rotation, halign, valign

class geoviews.Tiles(data, kdims=None, vdims=None, **params)[source]#

Bases: WMTS

Tiles represents an image tile source to dynamically load data from depending on the zoom level.

Parameter Definitions

Parameters inherited from:

group = String(default='Tiles', label='Group')

A string describing the data wrapped by the object.

class geoviews.TriMesh(data=None, kdims=None, vdims=None, **kwargs)[source]#

Bases: TriMesh, Graph

Attributes:
edgepaths

Returns the fixed EdgePaths or computes direct connections between supplied nodes.

Methods

edge_type

alias of EdgePaths

node_type

alias of Nodes

point_type

alias of Points

Parameter Definitions

Parameters inherited from:

group = String(constant=True, default='TriMesh', label='Group')

A string describing the data wrapped by the object.

edge_type[source]#

alias of EdgePaths

property edgepaths#

Returns the fixed EdgePaths or computes direct connections between supplied nodes.

node_type[source]#

alias of Nodes

point_type[source]#

alias of Points

class geoviews.VectorField(data=None, kdims=None, vdims=None, **kwargs)[source]#

Bases: _Element, VectorField

A VectorField contains is a collection of vectors where each vector has an associated position. The vectors should be specified by defining an angle in radians and a magnitude.

Parameter Definitions

Parameters inherited from:

group = String(constant=True, default='VectorField', label='Group')

A string describing the data wrapped by the object.

vdims = List(bounds=(1, None), default=[Dimension('Angle'), Dimension('Magnitude')], label='Vdims')

Value dimensions can be associated with a geometry.

class geoviews.WMTS(data, kdims=None, vdims=None, **params)[source]#

Bases: _GeoFeature

The WMTS Element represents a Web Map Tile Service specified as URL containing different template variables or xyzservices.TileProvider.

These variables correspond to three different formats for specifying the spatial location and zoom level of the requested tiles:

  • Web mapping tiles sources containing {x}, {y}, and {z} variables

  • Bounding box tile sources containing {XMIN}, {XMAX}, {YMIN}, {YMAX} variables

  • Quadkey tile sources containing a {Q} variable

Tiles are defined in a pseudo-Mercator projection (EPSG:3857) defined as eastings and northings. Any data overlaid on a tile source therefore has to be defined in those coordinates or be projected.

Parameter Definitions

Parameters inherited from:

holoviews.core.dimension.LabelledData: label

holoviews.core.dimension.Dimensioned: cdims, vdims

holoviews.core.element.Element2D: extents

geoviews.element.geo._Element: kdims

group = String(default='WMTS', label='Group')

A string describing the data wrapped by the object.

crs = ClassSelector(class_=<class 'cartopy.crs.CRS'>, default=<Bound CRS: +proj=merc +a=6378137.0 +b=6378137.0 +nadgrids=@nu ...> Name: unknown Axis Info [cartesian]: - E[east]: Easting (metre) - N[north]: Northing (metre) Area of Use: - undefined Coordinate Operation: - name: unknown to WGS84 - method: NTv2 Datum: unknown using nadgrids=@null - Ellipsoid: unknown - Prime Meridian: Greenwich Source CRS: unknown , label='Crs')

Cartopy coordinate-reference-system specifying the coordinate system of the data. Inferred automatically when _Element wraps cartopy Feature object.

layer = String(default='', label='Layer')

The layer on the tile service

class geoviews.WindBarbs(data=None, kdims=None, vdims=None, **kwargs)[source]#

Bases: _Element, Selection2DExpr, Geometry

Methods

from_uv

Parameter Definitions

Parameters inherited from:

group = String(constant=True, default='WindBarbs', label='Group')

A string describing the data wrapped by the object.

vdims = List(bounds=(2, None), default=[Dimension('Angle'), Dimension('Magnitude')], label='Vdims')

Value dimensions can be associated with a geometry.

class geoviews.annotate(*, annotations, annotator, edit_vertices, empty_value, num_objects, show_vertices, table_opts, table_transforms, vertex_annotations, vertex_style, name)[source]#

Bases: ParameterizedFunction

The annotate function allows drawing, editing and annotating any given Element (if it is supported). The annotate function returns a Layout of the editable plot and an Overlay of table(s), which allow editing the data of the element. The edited and annotated data may be accessed using the element and selected properties.

Attributes:
annotated
selected

Methods

compose(*annotators)

Composes multiple annotator layouts and elements

Parameter Definitions

annotator = Parameter(allow_None=True, label='Annotator')

The current Annotator instance.

annotations = ClassSelector(class_=(<class 'dict'>, <class 'list'>), default=[], label='Annotations')

Annotations to associate with each object.

edit_vertices = Boolean(default=True, label='Edit vertices')

Whether to add tool to edit vertices.

empty_value = Parameter(allow_None=True, label='Empty value')

The value to insert on annotation columns when drawing a new element.

num_objects = Integer(allow_None=True, bounds=(0, None), inclusive_bounds=(True, True), label='Num objects')

The maximum number of objects to draw.

show_vertices = Boolean(default=True, label='Show vertices')

Whether to show vertices when drawing the Path.

table_transforms = HookList(bounds=(0, None), default=[], label='Table transforms')

Transform(s) to apply to element when converting data to Table. The functions should accept the Annotator and the transformed element as input.

table_opts = Dict(class_=<class 'dict'>, default={'editable': True, 'width': 400}, label='Table opts')

Opts to apply to the editor table(s).

vertex_annotations = ClassSelector(class_=(<class 'dict'>, <class 'list'>), default=[], label='Vertex annotations')

Columns to annotate the Polygons with.

vertex_style = Dict(class_=<class 'dict'>, default={'nonselection_alpha': 0.5}, label='Vertex style')

Options to apply to vertices during drawing and editing.

classmethod compose(*annotators)[source]#

Composes multiple annotator layouts and elements

The composed Layout will contain all the elements in the supplied annotators and an overlay of all editor tables.

Parameters:
annotators

Annotator layouts or elements to compose

Returns:
A new layout consisting of the overlaid plots and tables
class geoviews.dim(obj, *args, **kwargs)[source]#

Bases: object

dim transform objects are a way to express deferred transforms on Datasets. dim transforms support all mathematical and bitwise operators, NumPy ufuncs and methods, and provide a number of useful methods for normalizing, binning and categorizing data.

Attributes:
iloc

Methods

apply(dataset[, flat, expanded, ranges, ...])

Evaluates the transform on the supplied dataset.

clone([dimension, ops, dim_type])

Creates a clone of the dim expression optionally overriding the dim and ops.
applies(dataset, strict=False)[source]#

Determines whether the dim transform can be applied to the Dataset, i.e. whether all referenced dimensions can be resolved.

apply(dataset, flat=False, expanded=None, ranges=None, all_values=False, keep_index=False, compute=True, strict=False)[source]#

Evaluates the transform on the supplied dataset.

Parameters:
dataset

Dataset object to evaluate the expression on

flat

Whether to flatten the returned array

expanded

Whether to use the expanded expand values

ranges

Dictionary for ranges for normalization

all_values

Whether to evaluate on all values Whether to evaluate on all available values, for some element types, such as Graphs, this may include values not included in the referenced column

keep_index

For data types that support indexes, whether the index should be preserved in the result.

compute

For data types that support lazy evaluation, whether the result should be computed before it is returned.

strict

Whether to strictly check for dimension matches (if False, counts any dimensions with matching names as the same)

Returns:
values

NumPy array computed by evaluating the expression

bin(bins, labels=None)[source]#

Bins continuous values.

Bins continuous using the provided bins and assigns labels either computed from each bins center point or from the supplied labels.

Parameters:
binsList or array containing the bin boundaries
labelsList of labels to assign to each bin

If the bins are length N the labels should be length N-1

categorize(categories, default=None)[source]#

Replaces discrete values with supplied categories

Replaces discrete values in input array into a fixed set of categories defined either as a list or dictionary.

Parameters:
categories

List or dict of categories to map inputs to

default

Default value to assign if value not in categories

clone(dimension=None, ops=None, dim_type=None)[source]#

Creates a clone of the dim expression optionally overriding the dim and ops.

lognorm(limits=None)[source]#
Unity-based normalization log scale.

Apply the same transformation as matplotlib.colors.LogNorm

Parameters:
limits

tuple of (min, max) defining the normalization range

norm(limits=None)[source]#

Unity-based normalization to scale data into 0-1 range.

(values - min) / (max - min)

Parameters:
limits

tuple of (min, max) defining the normalization range

classmethod pipe(func, *args, **kwargs)[source]#

Wrapper to give multidimensional transforms a more intuitive syntax. For a custom function func with signature (*args, **kwargs), call as dim.pipe(func, *args, **kwargs).

classmethod register(key, function)[source]#

Register a custom dim transform function which can from then on be referenced by the key.

property str#

Casts values to strings or provides str accessor.

class geoviews.extension(*, name)[source]#

Bases: extension

Helper utility used to load holoviews extensions. These can be plotting extensions, element extensions or anything else that can be registered to work with HoloViews.

The plotting extension is the most commonly used and is used to select the plotting backend. The plotting extension can be loaded using the backend name, e.g. ‘bokeh’, ‘matplotlib’ or ‘plotly’.

Methods

register_backend_callback(backend, callback)

Registers a hook which is run when a backend is loaded

Examples

Activate the bokeh plotting extension:

`python import holoviews as hv hv.extension("bokeh") `

Parameter Definitions

classmethod register_backend_callback(backend, callback)[source]#

Registers a hook which is run when a backend is loaded

geoviews.from_xarray(da, crs=None, apply_transform=False, nan_nodata=False, **kwargs)[source]#

Returns an RGB or Image element given an xarray DataArray loaded using xr.open_rasterio.

If a crs attribute is present on the loaded data it will attempt to decode it into a cartopy projection otherwise it will default to a non-geographic HoloViews element.

Parameters:
daxarray.DataArray

DataArray to convert to element

crsCartopy CRS or EPSG python:str, optional

Overrides CRS inferred from the data

apply_transformbool

Whether to apply affine transform if defined on the data

nan_nodatabool

If data contains nodata values convert them to NaNs

**kwargs

Keyword arguments passed to the HoloViews/GeoViews element

Returns:
element

Image/RGB/QuadMesh element

geoviews.help(obj, visualization=True, ansi=True, backend=None, recursive=False, pattern=None)[source]#

Extended version of the built-in help that supports parameterized functions and objects. A pattern (regular expression) may be used to filter the output and if recursive is set to True, documentation for the supplied object is shown. Note that the recursive option will only work with an object instance and not a class.

If ansi is set to False, all ANSI color codes are stripped out.

class geoviews.opts(*args, **params)[source]#

Bases: ParameterizedFunction

Utility function to set options at the global level or to provide an Options object that can be used with the .options method of an element or container.

Option objects can be generated and validated in a tab-completable way (in appropriate environments such as Jupyter notebooks) using completers such as opts.Curve, opts.Image, opts.Overlay, etc.

To set opts globally you can pass these option objects into opts.defaults:

opts.defaults(*options)

For instance:

opts.defaults(opts.Curve(color=’red’))

To set opts on a specific object, you can supply these option objects to the .options method.

For instance:

curve = hv.Curve([1,2,3]) curve.options(opts.Curve(color=’red’))

The options method also accepts lists of Option objects.

Methods

apply_groups(obj[, options, backend, clone])

Applies nested options definition grouped by type.

defaults(*options, **kwargs)

Set default options for a session.

Parameter Definitions

strict = Boolean(default=False, label='Strict')

Whether to be strict about the options specification. If not set to strict (default), any invalid keywords are simply skipped. If strict, invalid keywords prevent the options being applied.

classmethod apply_groups(obj, options=None, backend=None, clone=True, **kwargs)[source]#

Applies nested options definition grouped by type.

Applies options on an object or nested group of objects, returning a new object with the options applied. This method accepts the separate option namespaces explicitly (i.e. ‘plot’, ‘style’, and ‘norm’).

If the options are to be set directly on the object a simple format may be used, e.g.:

opts.apply_groups(obj, 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.:

opts.apply_groups(obj, {‘Image’: {‘plot’: {‘show_title’: False},

‘style’: {‘cmap’: ‘viridis}}})

If no opts are supplied all options on the object will be reset.

Parameters:
optionspython:dict

Options specification Options specification should be indexed by type[.group][.label] or option type (‘plot’, ‘style’, ‘norm’).

backendoptional

Backend to apply options to Defaults to current selected backend

clonebool, optional

Whether to clone object Options can be applied inplace with clone=False

**kwargs: Keywords of options by type

Applies options directly to the object by type (e.g. ‘plot’, ‘style’, ‘norm’) specified as dictionaries.

Returns:
Returns the object or a clone with the options applied
classmethod defaults(*options, **kwargs)[source]#

Set default options for a session.

Set default options for a session. whether in a Python script or a Jupyter notebook.

Parameters:
*options

Option objects used to specify the defaults.

backend

The plotting extension the options apply to

class geoviews.output(*args, **params)[source]#

Bases: ParameterizedFunction

Helper used to set HoloViews display options. Arguments are supplied as a series of keywords in any order:

backend : The backend used by HoloViews fig : The static figure format holomap : The display type for holomaps widgets : The widget mode for widgets fps : The frames per second used for animations max_frames : The max number of frames rendered (default 500) size : The percentage size of displayed output dpi : The rendered dpi of the figure filename : The filename of the saved output, if any (default None) info : The information to page about the displayed objects (default False) css : Optional css style attributes to apply to the figure image tag widget_location : The position of the widgets relative to the plot

Methods

info

Parameter Definitions

class geoviews.project(*, projection, dynamic, group, input_ranges, link_inputs, streams, name)[source]#

Bases: Operation

Projects GeoViews Element types to the specified projection.

Parameter Definitions

Parameters inherited from:

holoviews.core.operation.Operation: group, dynamic, input_ranges, link_inputs, streams

projection = ClassSelector(class_=<class 'cartopy.crs.Projection'>, default=<Bound CRS: +proj=merc +a=6378137.0 +b=6378137.0 +nadgrids=@nu ...> Name: unknown Axis Info [cartesian]: - E[east]: Easting (metre) - N[north]: Northing (metre) Area of Use: - undefined Coordinate Operation: - name: unknown to WGS84 - method: NTv2 Datum: unknown using nadgrids=@null - Ellipsoid: unknown - Prime Meridian: Greenwich Source CRS: unknown , label='Projection')

Projection the image type is projected to.

geoviews.render(obj, backend=None, **kwargs)[source]#

Renders the HoloViews object to the corresponding object in the specified backend, e.g. a Matplotlib or Bokeh figure.

The backend defaults to the currently declared default backend. The resulting object can then be used with other objects in the specified backend. For instance, if you want to make a multi-part Bokeh figure using a plot type only available in HoloViews, you can use this function to return a Bokeh figure that you can use like any hand-constructed Bokeh figure in a Bokeh layout.

Parameters:
objHoloViews object

The HoloViews object to render

backendpython:str

A valid HoloViews rendering backend

**kwargs: dict

Additional keyword arguments passed to the renderer, e.g. fps for animations

Returns:
rendered

The rendered representation of the HoloViews object, e.g. if backend=’matplotlib’ a matplotlib Figure or FuncAnimation

geoviews.renderer(name)[source]#

Helper utility to access the active renderer for a given extension.

geoviews.save(obj, filename, fmt='auto', backend=None, resources='cdn', toolbar=None, title=None, **kwargs)[source]#

Saves the supplied object to file.

The available output formats depend on the backend being used. By default and if the filename is a string the output format will be inferred from the file extension. Otherwise an explicit format will need to be specified. For ambiguous file extensions such as html it may be necessary to specify an explicit fmt to override the default, e.g. in the case of ‘html’ output the widgets will default to fmt=’widgets’, which may be changed to scrubber widgets using fmt=’scrubber’.

Parameters:
objHoloViews object

The HoloViews object to save to file

filenamepython:str or IO object

The filename or BytesIO/StringIO object to save to

fmtpython:str

The format to save the object as, e.g. png, svg, html, or gif and if widgets are desired either ‘widgets’ or ‘scrubber’

backendpython:str

A valid HoloViews rendering backend, e.g. bokeh or matplotlib

resourcespython:str or bokeh.resource.Resources

Bokeh resources used to load bokehJS components. Defaults to CDN, to embed resources inline for offline usage use ‘inline’ or bokeh.resources.INLINE.

toolbarbool or python:None

Whether to include toolbars in the exported plot. If None, display the toolbar unless fmt is png and backend is bokeh. If True, always include the toolbar. If False, do not include the toolbar.

titlepython:str

Custom title for exported HTML file

**kwargs: dict

Additional keyword arguments passed to the renderer, e.g. fps for animations

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