"""
Supplies Layer and related classes that allow overlaying of Views,
including Overlay. A Layer is the final extension of View base class
that allows Views to be overlayed on top of each other.
Also supplies ViewMap which is the primary multi-dimensional Map type
for indexing, slicing and animating collections of Views.
"""
from functools import reduce
import numpy as np
import param
from .dimension import Dimension, Dimensioned, ViewableElement, ViewableTree
from .ndmapping import UniformNdMapping
from .layout import Composable, Layout, AdjointLayout
from .util import sanitize_identifier, unique_array, dimensioned_streams
[docs]class Overlayable(object):
"""
Overlayable provides a mix-in class to support the
mul operation for overlaying multiple elements.
"""
def __mul__(self, other):
"Overlay object with other object."
if type(other).__name__ == 'DynamicMap':
from .spaces import Callable
def dynamic_mul(*args, **kwargs):
element = other[args]
return self * element
callback = Callable(dynamic_mul, inputs=[self, other])
callback._is_overlay = True
return other.clone(shared_data=False, callback=callback,
streams=dimensioned_streams(other))
if isinstance(other, UniformNdMapping) and not isinstance(other, CompositeOverlay):
items = [(k, self * v) for (k, v) in other.items()]
return other.clone(items)
elif isinstance(other, (AdjointLayout, ViewableTree)) and not isinstance(other, Overlay):
return NotImplemented
return Overlay([self, other])
[docs]class CompositeOverlay(ViewableElement, Composable):
"""
CompositeOverlay provides a common baseclass for Overlay classes.
"""
_deep_indexable = True
[docs] def hist(self, dimension=None, num_bins=20, bin_range=None,
adjoin=True, index=0, **kwargs):
"""Computes and adjoins histogram along specified dimension(s).
Defaults to first value dimension if present otherwise falls
back to first key dimension.
Args:
dimension: Dimension(s) to compute histogram on
num_bins (int, optional): Number of bins
bin_range (tuple optional): Lower and upper bounds of bins
adjoin (bool, optional): Whether to adjoin histogram
index (int, optional): Index of layer to apply hist to
Returns:
AdjointLayout of element and histogram or just the
histogram
"""
valid_ind = isinstance(index, int) and (0 <= index < len(self))
valid_label = index in [el.label for el in self]
if not any([valid_ind, valid_label]):
raise TypeError("Please supply a suitable index or label for the histogram data")
hists = self.get(index).hist(
adjoin=False, dimension=dimension, bin_range=bin_range,
num_bins=num_bins, **kwargs)
if not isinstance(hists, Layout):
hists = [hists]
if not isinstance(dimension, list):
dimension = ['Default']
if adjoin:
layout = self
for hist in hists:
layout = layout << hist
layout.main_layer = index
elif len(dimension) > 1:
layout = hists
else:
layout = hists[0]
return layout
[docs] def dimension_values(self, dimension, expanded=True, flat=True):
"""Return the values along the requested dimension.
Args:
dimension: The dimension to return values for
expanded (bool, optional): Whether to expand values
Whether to return the expanded values, behavior depends
on the type of data:
* Columnar: If false returns unique values
* Geometry: If false returns scalar values per geometry
* Gridded: If false returns 1D coordinates
flat (bool, optional): Whether to flatten array
Returns:
NumPy array of values along the requested dimension
"""
values = []
found = False
for el in self:
if dimension in el.dimensions(label=True):
values.append(el.dimension_values(dimension))
found = True
if not found:
return super(CompositeOverlay, self).dimension_values(dimension, expanded, flat)
values = [v for v in values if v is not None and len(v)]
if not values:
return np.array()
vals = np.concatenate(values)
return vals if expanded else unique_array(vals)
[docs]class Overlay(ViewableTree, CompositeOverlay):
"""
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).
"""
def __init__(self, items=None, group=None, label=None, **params):
self.__dict__['_fixed'] = False
self.__dict__['_group'] = group
self.__dict__['_label'] = label
super(Overlay, self).__init__(items, **params)
def __getitem__(self, key):
"""
Allows transparently slicing the Elements in the Overlay
to select specific layers in an Overlay use the .get method.
"""
return Overlay([(k, v[key]) for k, v in self.items()])
[docs] def get(self, identifier, default=None):
"""Get a layer in the Overlay.
Get a particular layer in the Overlay using its path string
or an integer index.
Args:
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
"""
if isinstance(identifier, int):
values = list(self.data.values())
if 0 <= identifier < len(values):
return values[identifier]
else:
return default
return super(Overlay, self).get(identifier, default)
def __add__(self, other):
"Composes Overlay with other object into a Layout"
return Layout([self, other])
def __mul__(self, other):
"Adds layer(s) from other object to Overlay"
if type(other).__name__ == 'DynamicMap':
from .spaces import Callable
def dynamic_mul(*args, **kwargs):
element = other[args]
return self * element
callback = Callable(dynamic_mul, inputs=[self, other])
callback._is_overlay = True
return other.clone(shared_data=False, callback=callback,
streams=dimensioned_streams(other))
elif not isinstance(other, ViewableElement):
return NotImplemented
return Overlay([self, other])
[docs] def collate(self):
"""
Collates any objects in the Overlay resolving any issues
the recommended nesting structure.
"""
return reduce(lambda x,y: x*y, self.values())
[docs] def decollate(self):
"""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
"""
from .decollate import decollate
return decollate(self)
@property
def group(self):
if self._group:
return self._group
elements = [el for el in self if not el._auxiliary_component]
values = {el.group for el in elements}
types = {type(el) for el in elements}
if values:
group = list(values)[0]
vtype = list(types)[0].__name__
else:
group, vtype = [], ''
if len(values) == 1 and group != vtype:
return group
else:
return type(self).__name__
@group.setter
def group(self, group):
if not sanitize_identifier.allowable(group):
raise ValueError("Supplied group %s contains invalid characters." %
group)
else:
self._group = group
@property
def label(self):
if self._label:
return self._label
labels = {el.label for el in self
if not el._auxiliary_component}
if len(labels) == 1:
return list(labels)[0]
else:
return ''
@label.setter
def label(self, label):
if not sanitize_identifier.allowable(label):
raise ValueError("Supplied group %s contains invalid characters." %
label)
self._label = label
@property
def ddims(self):
dimensions = []
dimension_names = []
for el in self:
for dim in el.dimensions():
if dim.name not in dimension_names:
dimensions.append(dim)
dimension_names.append(dim.name)
return dimensions
@property
def shape(self):
raise NotImplementedError
# Deprecated methods
[docs] def collapse(self, function):
"Deprecated method to collapse layers in the Overlay."
self.param.warning('Overlay.collapse is deprecated, to'
'collapse multiple elements use a HoloMap.')
elements = list(self)
types = [type(el) for el in elements]
values = [el.group for el in elements]
if not len(set(types)) == 1 and len(set(values)) == 1:
raise Exception("Overlay is not homogeneous in type or group "
"and cannot be collapsed.")
else:
return elements[0].clone(types[0].collapse_data([el.data for el in elements],
function, self.kdims))
[docs]class NdOverlay(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.
"""
kdims = param.List(default=[Dimension('Element')], constant=True, doc="""
List of dimensions the NdOverlay can be indexed by.""")
_deep_indexable = True
def __init__(self, overlays=None, kdims=None, **params):
super(NdOverlay, self).__init__(overlays, kdims=kdims, **params)
[docs] def decollate(self):
"""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
"""
from .decollate import decollate
return decollate(self)
__all__ = list(set([_k for _k, _v in locals().items()
if isinstance(_v, type) and issubclass(_v, Dimensioned)])) + ['Overlayable']
