"""
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
from .ndmapping import UniformNdMapping
from .layout import Composable, Layout, AdjointLayout
from .util import sanitize_identifier, unique_array
[docs]class Overlayable(object):
"""
Overlayable provides a mix-in class to support the
mul operation for overlaying multiple elements.
"""
def __mul__(self, other):
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=[])
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):
return NotImplemented
return Overlay.from_values([self, other])
[docs]class CompositeOverlay(ViewableElement, Composable):
"""
CompositeOverlay provides a common baseclass for Overlay classes.
"""
_deep_indexable = True
def hist(self, index=0, adjoin=True, dimension=None, **kwargs):
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, **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
def dimension_values(self, dimension, expanded=True, flat=True):
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(Layout, CompositeOverlay):
"""
An Overlay consists of multiple Views (potentially of
heterogeneous type) presented one on top each other with a
particular z-ordering.
Overlays along with Views 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) and are the only objects that inherit both from
Layout and CompositeOverlay.
"""
def __init__(self, items=None, group=None, label=None, **params):
view_params = ViewableElement.params().keys()
self.__dict__['_fixed'] = False
self.__dict__['_group'] = group
self.__dict__['_label'] = label
Layout.__init__(self, items,
**{k:v for k,v in params.items() if k not in view_params})
ViewableElement.__init__(self, self.data,
**{k:v for k,v in params.items() if k in view_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()])
def get(self, identifier, default=None):
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):
return Layout.from_values([self, other])
def __mul__(self, other):
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=[])
elif not isinstance(other, ViewableElement):
raise NotImplementedError
return Overlay.from_values([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 collapse(self, function):
"""
Collapses all the Elements in the Overlay using the
supplied function if they share a common type and group.
"""
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))
@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
[docs]class NdOverlay(UniformNdMapping, CompositeOverlay, Overlayable):
"""
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)
__all__ = list(set([_k for _k, _v in locals().items()
if isinstance(_v, type) and issubclass(_v, Dimensioned)])) + ['Overlayable']
