Source code for holoviews.core.options

Options and OptionTrees allow different classes of options
(e.g. matplotlib-specific styles and plot specific parameters) to be
defined separately from the core data structures and away from
visualization specific code.

There are three classes that form the options system:


   Used to define infinite cycles over a finite set of elements, using
   either an explicit list or some pre-defined collection (e.g. from
   matplotlib rcParams). For instance, a Cycle object can be used loop
   a set of display colors for multiple curves on a single axis.


   Containers of arbitrary keyword values, including optional keyword
   validation, support for Cycle objects and inheritance.


   A subclass of AttrTree that is used to define the inheritance
   relationships between a collection of Options objects. Each node
   of the tree supports a group of Options objects and the leaf nodes
   inherit their keyword values from parent nodes up to the root.


   A singleton class that stores all global and custom options and
   links HoloViews objects, the chosen plotting backend and the IPython
   extension together.

import difflib
import inspect
import pickle
import traceback
from collections import defaultdict
from contextlib import contextmanager

import numpy as np
import param

from .accessors import Opts  # noqa (clean up in 2.0)
from .pprint import InfoPrinter
from .tree import AttrTree
from .util import group_sanitizer, label_sanitizer, sanitize_identifier

[docs]def cleanup_custom_options(id, weakref=None): """ Cleans up unused custom trees if all objects referencing the custom id have been garbage collected or tree is otherwise unreferenced. """ try: if Store._options_context: return weakrefs = Store._weakrefs.get(id, []) if weakref in weakrefs: weakrefs.remove(weakref) refs = [] for wr in list(weakrefs): r = wr() if r is None or != id: weakrefs.remove(wr) else: refs.append(r) if not refs: for bk in Store.loaded_backends(): if id in Store._custom_options[bk]: Store._custom_options[bk].pop(id) if not weakrefs: Store._weakrefs.pop(id, None) except Exception as e: raise Exception( f"Cleanup of custom options tree with id '{id}' failed " f"with the following exception: {e}, an unreferenced " "orphan tree may persist in memory." ) from e
[docs]def lookup_options(obj, group, backend): """ Given a HoloViews object, a plot option group (e.g. 'style') and backend, return the corresponding Options object. """ plot_class = None try: plot_class = Store.renderers[backend].plotting_class(obj) style_opts = plot_class.style_opts except SkipRendering: style_opts = None node = Store.lookup_options(backend, obj, group) if group == 'style' and style_opts is not None: return node.filtered(style_opts) elif group == 'plot' and plot_class: return node.filtered(list(plot_class.param)) else: return node
[docs]class CallbackError(RuntimeError): """ An error raised during a callback. """
[docs]class SkipRendering(Exception): """ A SkipRendering exception in the plotting code will make the display hooks fall back to a text repr. Used to skip rendering of DynamicMaps with exhausted element generators. """ def __init__(self, message="", warn=True): self.warn = warn super().__init__(message)
[docs]class OptionError(Exception): """ Custom exception raised when there is an attempt to apply invalid options. Stores the necessary information to construct a more readable message for the user if caught and processed appropriately. """ def __init__(self, invalid_keyword, allowed_keywords, group_name=None, path=None): super().__init__(self.message(invalid_keyword, allowed_keywords, group_name, path)) self.invalid_keyword = invalid_keyword self.allowed_keywords = allowed_keywords self.group_name =group_name self.path = path def message(self, invalid_keyword, allowed_keywords, group_name, path): msg = ( f"Invalid option {invalid_keyword!r}, valid options are: " f"{allowed_keywords}." ) if path and group_name: msg = f"Invalid key for group {group_name!r} on path {path};\n{msg}" return msg
[docs] def format_options_error(self): """ Return a fuzzy match message based on the OptionError """ allowed_keywords = self.allowed_keywords target = matches = allowed_keywords.fuzzy_match(self.invalid_keyword) if not matches: matches = allowed_keywords.values similarity = 'Possible' else: similarity = 'Similar' loaded_backends = Store.loaded_backends() target = f'for {target}' if target else '' if len(loaded_backends) == 1: loaded = f' in loaded backend {loaded_backends[0]!r}' else: backend_list = ', '.join([repr(b) for b in loaded_backends[:-1]]) loaded = f' in loaded backends {backend_list} and {loaded_backends[-1]!r}' group = f'{self.group_name} option' if self.group_name else 'keyword' return ( f"Unexpected {group} '{self.invalid_keyword}' {target}" f"{loaded}.\n\n{similarity} keywords in the currently " f"active '{Store.current_backend}' renderer are: " f"{matches}\n\nIf you believe this keyword is correct, " "please make sure the backend has been imported or loaded " "with the hv.extension." )
[docs]class AbbreviatedException(Exception): """ Raised by the abbreviate_exception context manager when it is appropriate to present an abbreviated the traceback and exception message in the notebook. Particularly useful when processing style options supplied by the user which may not be valid. """ def __init__(self, etype, value, traceback): self.etype = etype self.value = value self.traceback = traceback self.msg = str(value) def __str__(self): return ( f'{self.etype.__name__}: {self.msg}\n\n' 'To view the original traceback, catch this exception and ' 'call print_traceback() method.' )
[docs] def print_traceback(self): """ Print the traceback of the exception wrapped by the AbbreviatedException. """ traceback.print_exception(self.etype, self.value, self.traceback)
[docs]class abbreviated_exception: """ Context manager used to to abbreviate tracebacks using an AbbreviatedException when a backend may raise an error due to incorrect style options. """ def __enter__(self): return self def __exit__(self, etype, value, traceback): if isinstance(value, Exception): raise AbbreviatedException(etype, value, traceback)
[docs]@contextmanager def options_policy(skip_invalid, warn_on_skip): """ Context manager to temporarily set the skip_invalid and warn_on_skip class parameters on Options. """ settings = (Options.skip_invalid, Options.warn_on_skip) (Options.skip_invalid, Options.warn_on_skip) = (skip_invalid, warn_on_skip) try: yield finally: (Options.skip_invalid, Options.warn_on_skip) = settings
[docs]class Keywords(param.Parameterized): """ A keywords objects represents a set of Python keywords. It is list-like and ordered but it is also a set without duplicates. When passed as **kwargs, Python keywords are not ordered but this class always lists keywords in sorted order. In addition to containing the list of keywords, Keywords has an optional target which describes what the keywords are applicable to. This class is for internal use only and should not be in the user namespace. """ values = param.List(doc="Set of keywords as a sorted list.") target = param.String(allow_None=True, doc=""" Optional string description of what the keywords apply to.""") def __init__(self, values=None, target=None): if values is None: values = [] strings = [isinstance(v, str) for v in values] if False in strings: raise ValueError(f'All keywords must be strings: {values}') super().__init__(values=sorted(values), target=target) def __add__(self, other): if ( and and ( != raise Exception('Targets must match to combine Keywords') target = or return Keywords(sorted(set(self.values + other.values)), target=target)
[docs] def fuzzy_match(self, kw): """ Given a string, fuzzy match against the Keyword values, returning a list of close matches. """ return difflib.get_close_matches(kw, self.values)
def __repr__(self): if msg = 'Keywords({values}, target={target})' info = dict(values=self.values, else: msg = 'Keywords({values})' info = dict(values=self.values) return msg.format(**info) def __str__(self): return str(self.values) def __iter__(self): return iter(self.values) def __bool__(self): return bool(self.values) def __contains__(self, val): return val in self.values
[docs]class Cycle(param.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. """ key = param.String(default='default_colors', allow_None=True, doc=""" The key in the default_cycles dictionary used to specify the color cycle if values is not supplied. """) values = param.List(default=[], doc=""" The values the cycle will iterate over.""") default_cycles = {'default_colors': []} def __init__(self, cycle=None, **params): if cycle is not None: if isinstance(cycle, str): params['key'] = cycle else: params['values'] = cycle params['key'] = None super().__init__(**params) self.values = self._get_values() def __getitem__(self, num): return self(values=self.values[:num]) def _get_values(self): if self.values: return self.values elif self.key and self.key in self.default_cycles: return list(self.default_cycles[self.key]) elif self.key: current = Store.current_backend others = " or ".join({"matplotlib", "bokeh", "plotly"} - {current}) raise ValueError( "The key you have supplied is not available " f"for the {current} backend. Try to switch to {others} " "with 'hv.extension(backend)'." ) else: raise ValueError("Supply either a key or explicit values.") def __call__(self, values=None, **params): values = values if values else self.values return self.__class__(**dict(self.param.values(), values=values, **params)) def __len__(self): return len(self.values) def __repr__(self): if self.key == self.param.objects(False)['key'].default: vrepr = '' elif self.key: vrepr = repr(self.key) else: vrepr = [str(el) for el in self.values] return f"{type(self).__name__}({vrepr})"
def grayscale(val): return (val, val, val, 1.0)
[docs]class Palette(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. """ key = param.String(default='grayscale', doc=""" Palettes look up the Palette values based on some key.""") range = param.NumericTuple(default=(0, 1), doc=""" The range from which the Palette values are sampled.""") samples = param.Integer(default=32, doc=""" The number of samples in the given range to supply to the sample_fn.""") sample_fn = param.Callable(default=np.linspace, doc=""" The function to generate the samples, by default linear.""") reverse = param.Boolean(default=False, doc=""" Whether to reverse the palette.""") # A list of available colormaps colormaps = {'grayscale': grayscale} def __init__(self, key, **params): super(Cycle, self).__init__(key=key, **params) self.values = self._get_values() def __getitem__(self, slc): """ Provides a convenient interface to override the range and samples parameters of the Cycle. Supplying a slice step or index overrides the number of samples. Unsupplied slice values will be inherited. """ (start, stop), step = self.range, self.samples if isinstance(slc, slice): if slc.start is not None: start = slc.start if slc.stop is not None: stop = slc.stop if slc.step is not None: step = slc.step else: step = slc return self(range=(start, stop), samples=step) def _get_values(self): cmap = self.colormaps[self.key] (start, stop), steps = self.range, self.samples samples = [cmap(n) for n in self.sample_fn(start, stop, steps)] return samples[::-1] if self.reverse else samples
[docs]class Options: """ An Options object holds a collection of keyword options. In addition, Options support (optional) keyword validation as well as infinite indexing over the set of supplied cyclic values. Options support inheritance of setting values via the __call__ method. By calling an Options object with additional keywords, you can create a new Options object inheriting the parent options. """ # Whether all Options instances should skip invalid keywords or # raise and exception. skip_invalid = True # Whether all Options instances should generate warnings when # skipping over invalid keywords or not. May only be specified at # the class level. warn_on_skip = True _option_groups = ['style', 'plot', 'norm', 'output'] _output_allowed_kws = ['backend'] def __init__(self, key=None, allowed_keywords=None, merge_keywords=True, max_cycles=None, **kwargs): if allowed_keywords is None: allowed_keywords = [] invalid_kws = [] for kwarg in sorted(kwargs.keys()): if allowed_keywords and kwarg not in allowed_keywords: if self.skip_invalid: invalid_kws.append(kwarg) else: raise OptionError(kwarg, allowed_keywords) if key and key[0].islower() and key not in self._option_groups: raise Exception('Key {} does not start with a capitalized element class name and is not a group in {}'.format(repr(key), ', '.join(repr(el) for el in self._option_groups))) for invalid_kw in invalid_kws: error = OptionError(invalid_kw, allowed_keywords, group_name=key) StoreOptions.record_skipped_option(error) if invalid_kws and self.warn_on_skip: self.param.warning(f"Invalid options {invalid_kws!r}, valid options are: {allowed_keywords!s}") self.kwargs = dict([(k,kwargs[k]) for k in sorted(kwargs.keys()) if k not in invalid_kws]) self._options = [] self._max_cycles = max_cycles allowed_keywords = (allowed_keywords if isinstance(allowed_keywords, Keywords) else Keywords(allowed_keywords)) self.allowed_keywords = allowed_keywords self.merge_keywords = merge_keywords self.key = key
[docs] def keywords_target(self, target): """ Helper method to easily set the target on the allowed_keywords Keywords. """ = target return self
[docs] def filtered(self, allowed): """ Return a new Options object that is filtered by the specified list of keys. Mutating self.kwargs to filter is unsafe due to the option expansion that occurs on initialization. """ kws = {k:v for k,v in self.kwargs.items() if k in allowed} return self.__class__(key=self.key, allowed_keywords=self.allowed_keywords, merge_keywords=self.merge_keywords, **kws)
def __call__(self, allowed_keywords=None, **kwargs): """ Create a new Options object that inherits the parent options. """ if 'key' not in kwargs: kwargs['key'] = self.key allowed_keywords=self.allowed_keywords if allowed_keywords in [None,[]] else allowed_keywords inherited_style = dict(allowed_keywords=allowed_keywords, **kwargs) return self.__class__(**dict(self.kwargs, **inherited_style))
[docs] def keys(self): "The keyword names across the supplied options." return sorted(list(self.kwargs.keys()))
[docs] def max_cycles(self, num): """ Truncates all contained Palette objects to a maximum number of samples and returns a new Options object containing the truncated or resampled Palettes. """ kwargs = {kw: (arg[num] if isinstance(arg, Palette) else arg) for kw, arg in self.kwargs.items()} return self(max_cycles=num, **kwargs)
@property def cyclic(self): "Returns True if the options cycle, otherwise False" return any(isinstance(val, Cycle) for val in self.kwargs.values()) def __getitem__(self, index): """ Infinite cyclic indexing of options over the integers, looping over the set of defined Cycle objects. """ if len(self.kwargs) == 0: return {} cycles = {k:v.values for k,v in self.kwargs.items() if isinstance(v, Cycle)} options = {} for key, values in cycles.items(): options[key] = values[index % len(values)] static = {k:v for k,v in self.kwargs.items() if not isinstance(v, Cycle)} return dict(static, **options) @property def options(self): "Access of the options keywords when no cycles are defined." if not self.cyclic: return self[0] else: raise Exception("The options property may only be used" " with non-cyclic Options.") def __repr__(self): kws = ', '.join(f"{k}={self.kwargs[k]!r}" for k in sorted(self.kwargs.keys())) cls_name = type(self).__name__ if self.key and self.key[0].isupper() and kws: return f"{cls_name}({self.key!r}, {kws})" elif self.key and self.key[0].isupper(): return f"{cls_name}({self.key!r})" else: return f"{cls_name}({kws})" def __str__(self): return repr(self)
[docs]class OptionTree(AttrTree): """ A subclass of AttrTree that is used to define the inheritance relationships between a collection of Options objects. Each node of the tree supports a group of Options objects and the leaf nodes inherit their keyword values from parent nodes up to the root. Supports the ability to search the tree for the closest valid path using the find method, or compute the appropriate Options value given an object and a mode. For a given node of the tree, the options method computes a Options object containing the result of inheritance for a given group up to the root of the tree. When constructing an OptionTree, you can specify the option groups as a list (i.e. empty initial option groups at the root) or as a dictionary (e.g. groups={'style':Option()}). You can also initialize the OptionTree with the options argument together with the **kwargs - see StoreOptions.merge_options for more information on the options specification syntax. You can use the string specifier '.' to refer to the root node in the options specification. This acts as an alternative was of specifying the options groups of the current node. Note that this approach method may only be used with the group lists format. """ def __init__(self, items=None, identifier=None, parent=None, groups=None, options=None, backend=None, **kwargs): if groups is None: raise ValueError('Please supply groups list or dictionary') _groups = {g:Options() for g in groups} if isinstance(groups, list) else groups self.__dict__['backend'] = backend self.__dict__['groups'] = _groups self.__dict__['_instantiated'] = False AttrTree.__init__(self, items, identifier, parent) self.__dict__['_instantiated'] = True options = StoreOptions.merge_options(_groups.keys(), options, **kwargs) root_groups = options.pop('.', None) if root_groups and isinstance(groups, list): self.__dict__['groups'] = {g:Options(**root_groups.get(g,{})) for g in _groups.keys()} elif root_groups: raise Exception( "Group specification as a dictionary only supported if " "the root node '.' syntax not used in the options." ) if options: StoreOptions.apply_customizations(options, self) def _merge_options(self, identifier, group_name, options): """ Computes a merged Options object for the given group name from the existing Options on the node and the new Options which are passed in. """ if group_name not in self.groups: raise KeyError(f"Group {group_name} not defined on SettingTree.") if identifier in self.children: current_node = self[identifier] group_options = current_node.groups[group_name] else: # When creating a node (nothing to merge with) ensure it is empty group_options = Options( group_name, allowed_keywords=self.groups[group_name].allowed_keywords ) override_kwargs = dict(options.kwargs) old_allowed = group_options.allowed_keywords override_kwargs['allowed_keywords'] = options.allowed_keywords + old_allowed try: if options.merge_keywords: return group_options(**override_kwargs) else: return Options(group_name, **override_kwargs) except OptionError as e: raise OptionError(e.invalid_keyword, e.allowed_keywords, group_name=group_name, path = self.path) from e def __getitem__(self, item): if item in self.groups: return self.groups[item] return super().__getitem__(item) def __getattr__(self, identifier): """ Allows creating sub OptionTree instances using attribute access, inheriting the group options. """ try: return super(AttrTree, self).__getattr__(identifier) except AttributeError: pass if identifier.startswith('_'): raise AttributeError(str(identifier)) elif self.fixed==True: raise AttributeError(self._fixed_error % identifier) valid_id = sanitize_identifier(identifier, escape=False) if valid_id in self.children: return self.__dict__[valid_id] # When creating a intermediate child node, leave kwargs empty self.__setattr__(identifier, {k:Options(k, allowed_keywords=v.allowed_keywords) for k,v in self.groups.items()}) return self[identifier] def __setattr__(self, identifier, val): # Invalidate the lookup cache whenever an option is changed Store._lookup_cache[self.backend] = {} identifier = sanitize_identifier(identifier, escape=False) new_groups = {} if isinstance(val, dict): group_items = val elif isinstance(val, Options) and val.key is None: raise AttributeError( "Options object needs to have a group name specified." ) elif isinstance(val, Options) and val.key[0].isupper(): groups = ', '.join(repr(el) for el in Options._option_groups) raise AttributeError( f"OptionTree only accepts Options using keys that are one of {groups}." ) elif isinstance(val, Options): group_items = {val.key: val} elif isinstance(val, OptionTree): group_items = val.groups current_node = self[identifier] if identifier in self.children else self for group_name in current_node.groups: options = group_items.get(group_name, False) if options: new_groups[group_name] = self._merge_options(identifier, group_name, options) else: new_groups[group_name] = current_node.groups[group_name] if new_groups: data = self[identifier].items() if identifier in self.children else None new_node = OptionTree(data, identifier=identifier, parent=self, groups=new_groups, backend=self.backend) else: raise ValueError('OptionTree only accepts a dictionary of Options.') super().__setattr__(identifier, new_node) if isinstance(val, OptionTree): for subtree in val: self[identifier].__setattr__(subtree.identifier, subtree)
[docs] def find(self, path, mode='node'): """ Find the closest node or path to an the arbitrary path that is supplied down the tree from the given node. The mode argument may be either 'node' or 'path' which determines the return type. """ path = path.split('.') if isinstance(path, str) else list(path) item = self for child in path: escaped_child = sanitize_identifier(child, escape=False) matching_children = (c for c in item.children if child.endswith(c) or escaped_child.endswith(c)) matching_children = sorted(matching_children, key=lambda x: -len(x)) if matching_children: item = item[matching_children[0]] else: continue return item if mode == 'node' else item.path
[docs] def closest(self, obj, group, defaults=True, backend=None): """ This method is designed to be called from the root of the tree. Given any LabelledData object, this method will return the most appropriate Options object, including inheritance. In addition, closest supports custom options by checking the object """ opts_spec = ( obj.__class__.__name__, group_sanitizer(, label_sanitizer(obj.label) ) # Try to get a cache hit in the backend lookup cache backend = backend or Store.current_backend cache = Store._lookup_cache.get(backend, {}) cache_key = opts_spec+(group, defaults, id(self.root)) if cache_key in cache: return cache[cache_key] target = '.'.join(c for c in opts_spec if c) options = self.find(opts_spec).options( group, target=target, defaults=defaults, backend=backend) cache[cache_key] = options return options
[docs] def options(self, group, target=None, defaults=True, backend=None): """ Using inheritance up to the root, get the complete Options object for the given node and the specified group. """ if target is None: target = self.path if self.groups.get(group, None) is None: return None options = Store.options(backend=backend) if self.parent is None and target and (self is not options) and defaults: root_name = self.__class__.__name__ replacement = root_name + ('' if len(target) == len(root_name) else '.') option_key = target.replace(replacement, '') match = options.find(option_key) if match is not options: return match.options(group) else: return EMPTY_OPTIONS elif self.parent is None: return self.groups[group] parent_opts = self.parent.options(group, target, defaults, backend=backend) return Options(**dict(parent_opts.kwargs, **self.groups[group].kwargs))
def __repr__(self): """ Evalable representation of the OptionTree. """ groups = self.__dict__['groups'] # Tab and group entry separators tab, gsep = ' ', ',\n\n' # Entry separator and group specifications esep, gspecs = (",\n"+(tab*2)), [] for group in groups.keys(): especs, accumulator = [], [] if groups[group].kwargs != {}: accumulator.append(('.', groups[group].kwargs)) for t, v in sorted(self.items()): kwargs = v.groups[group].kwargs accumulator.append(('.'.join(t), kwargs)) for (t, kws) in accumulator: if group=='norm' and all(kws.get(k, False) is False for k in ['axiswise','framewise']): continue elif kws: especs.append((t, kws)) if especs: format_kws = [ (t, f"dict({', '.join(f'{k}={v}' for k, v in sorted(kws.items()))})") for t, kws in especs ] ljust = max(len(t) for t,_ in format_kws) sep = (tab*2) if len(format_kws) >1 else '' entries = sep + esep.join([f'{sep}{t.ljust(ljust)} : {v}' for t,v in format_kws]) gspecs.append(('%s%s={\n%s}' if len(format_kws)>1 else '%s%s={%s}') % (tab, group, entries)) return f'OptionTree(groups={groups.keys()},\n{gsep.join(gspecs)}\n)'
[docs]class Compositor(param.Parameterized): """ A Compositor is a way of specifying an operation to be automatically applied to Overlays that match a specified pattern upon display. Any Operation that takes an Overlay as input may be used to define a compositor. For instance, a compositor may be defined to automatically display three overlaid monochrome matrices as an RGB image as long as the values names of those matrices match 'R', 'G' and 'B'. """ mode = param.ObjectSelector(default='data', objects=['data', 'display'], doc=""" The mode of the Compositor object which may be either 'data' or 'display'.""") backends = param.List(default=[], doc=""" Defines which backends to apply the Compositor for.""") operation = param.Parameter(doc=""" The Operation to apply when collapsing overlays.""") pattern = param.String(doc=""" The overlay pattern to be processed. An overlay pattern is a sequence of elements specified by dotted paths separated by * . For instance the following pattern specifies three overlaid matrices with values of 'RedChannel', 'GreenChannel' and 'BlueChannel' respectively: 'Image.RedChannel * Image.GreenChannel * Image.BlueChannel. This pattern specification could then be associated with the RGB operation that returns a single RGB matrix for display.""") group = param.String(allow_None=True, doc=""" The group identifier for the output of this particular compositor""") kwargs = param.Dict(doc=""" Optional set of parameters to pass to the operation.""") transfer_options = param.Boolean(default=False, doc=""" Whether to transfer the options from the input to the output.""") transfer_parameters = param.Boolean(default=False, doc=""" Whether to transfer plot options which match to the operation.""") operations = [] # The operations that can be used to define compositors. definitions = [] # The set of all the compositor instances
[docs] @classmethod def strongest_match(cls, overlay, mode, backend=None): """ Returns the single strongest matching compositor operation given an overlay. If no matches are found, None is returned. The best match is defined as the compositor operation with the highest match value as returned by the match_level method. """ match_strength = [ (op.match_level(overlay), op) for op in cls.definitions if op.mode == mode and (not op.backends or backend in op.backends) ] matches = [ (match[0], op, match[1]) for (match, op) in match_strength if match is not None ] if matches == []: return None return sorted(matches)[0]
[docs] @classmethod def collapse_element(cls, overlay, ranges=None, mode='data', backend=None): """ Finds any applicable compositor and applies it. """ from .element import Element from .overlay import CompositeOverlay, Overlay unpack = False if not isinstance(overlay, CompositeOverlay): overlay = Overlay([overlay]) unpack = True prev_ids = () processed = defaultdict(list) while True: match = cls.strongest_match(overlay, mode, backend) if match is None: if unpack and len(overlay) == 1: return overlay.values()[0] return overlay (_, applicable_op, (start, stop)) = match if isinstance(overlay, Overlay): values = overlay.values() sliced = Overlay(values[start:stop]) else: values = overlay.items() sliced = overlay.clone(values[start:stop]) items = sliced.traverse(lambda x: x, [Element]) if applicable_op and all(el in processed[applicable_op] for el in items): if unpack and len(overlay) == 1: return overlay.values()[0] return overlay result = applicable_op.apply(sliced, ranges, backend) if result = result.relabel( if isinstance(overlay, Overlay): result = [result] else: result = list(zip(sliced.keys(), [result])) processed[applicable_op] += [el for r in result for el in r.traverse(lambda x: x, [Element])] overlay = overlay.clone(values[:start]+result+values[stop:]) # Guard against infinite recursion for no-ops spec_fn = lambda x: not isinstance(x, CompositeOverlay) new_ids = tuple(overlay.traverse(lambda x: id(x), [spec_fn])) if new_ids == prev_ids: return overlay prev_ids = new_ids
[docs] @classmethod def collapse(cls, holomap, ranges=None, mode='data'): """ Given a map of Overlays, apply all applicable compositors. """ # No potential compositors if cls.definitions == []: return holomap # Apply compositors clone = holomap.clone(shared_data=False) data = zip(ranges[1], if ranges else for key, overlay in data: clone[key] = cls.collapse_element(overlay, ranges, mode) return clone
[docs] @classmethod def map(cls, obj, mode='data', backend=None): """ Applies compositor operations to any HoloViews element or container using the map method. """ from .overlay import CompositeOverlay element_compositors = [c for c in cls.definitions if len(c._pattern_spec) == 1] overlay_compositors = [c for c in cls.definitions if len(c._pattern_spec) > 1] if overlay_compositors: obj = obj: cls.collapse_element(obj, mode=mode, backend=backend), [CompositeOverlay]) element_patterns = [c.pattern for c in element_compositors] if element_compositors and obj.traverse(lambda x: x, element_patterns): obj = obj: cls.collapse_element(obj, mode=mode, backend=backend), element_patterns) return obj
@classmethod def register(cls, compositor): defined_patterns = [op.pattern for op in cls.definitions] if compositor.pattern in defined_patterns: cls.definitions.pop(defined_patterns.index(compositor.pattern)) cls.definitions.append(compositor) if compositor.operation not in cls.operations: cls.operations.append(compositor.operation) def __init__(self, pattern, operation, group, mode, transfer_options=False, transfer_parameters=False, output_type=None, backends=None, **kwargs): self._pattern_spec, labels = [], [] for path in pattern.split('*'): path_tuple = tuple(el.strip() for el in path.strip().split('.')) self._pattern_spec.append(path_tuple) if len(path_tuple) == 3: labels.append(path_tuple[2]) if len(labels) > 1 and not all(l==labels[0] for l in labels): raise KeyError("Mismatched labels not allowed in compositor patterns") elif len(labels) == 1: self.label = labels[0] else: self.label = '' self._output_type = output_type super().__init__(group=group, pattern=pattern, operation=operation, mode=mode, backends=backends or [], kwargs=kwargs, transfer_options=transfer_options, transfer_parameters=transfer_parameters) @property def output_type(self): """ Returns the operation output_type unless explicitly overridden in the kwargs. """ return self._output_type or self.operation.output_type def _slice_match_level(self, overlay_items): """ Find the match strength for a list of overlay items that must be exactly the same length as the pattern specification. """ level = 0 for spec, el in zip(self._pattern_spec, overlay_items): if spec[0] != type(el).__name__: return None level += 1 # Types match if len(spec) == 1: continue group = [, group_sanitizer(, escape=False)] if spec[1] in group: level += 1 # Values match else: return None if len(spec) == 3: group = [el.label, label_sanitizer(el.label, escape=False)] if (spec[2] in group): level += 1 # Labels match else: return None return level
[docs] def match_level(self, overlay): """ Given an overlay, return the match level and applicable slice of the overall overlay. The level an integer if there is a match or None if there is no match. The level integer is the number of matching components. Higher values indicate a stronger match. """ slice_width = len(self._pattern_spec) if slice_width > len(overlay): return None # Check all the possible slices and return the best matching one best_lvl, match_slice = (0, None) for i in range(len(overlay)-slice_width+1): overlay_slice = overlay.values()[i:i+slice_width] lvl = self._slice_match_level(overlay_slice) if lvl is None: continue if lvl > best_lvl: best_lvl = lvl match_slice = (i, i+slice_width) return (best_lvl, match_slice) if best_lvl != 0 else None
[docs] def apply(self, value, input_ranges, backend=None): """ Apply the compositor on the input with the given input ranges. """ from .overlay import CompositeOverlay if backend is None: backend = Store.current_backend kwargs = {k: v for k, v in self.kwargs.items() if k != 'output_type'} if isinstance(value, CompositeOverlay) and len(value) == 1: value = value.values()[0] if self.transfer_parameters: plot_opts = Store.lookup_options(backend, value, 'plot').kwargs kwargs.update({k: v for k, v in plot_opts.items() if k in self.operation.param}) transformed = self.operation(value, input_ranges=input_ranges, **kwargs) if self.transfer_options and value is not transformed: Store.transfer_options(value, transformed, backend) return transformed
[docs]class Store: """ 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. """ renderers = {} # The set of available Renderers across all backends. # A mapping from ViewableElement types to their corresponding plot # types grouped by the backend. Set using the register method. registry = {} # A list of formats to be published for display on the frontend (e.g # IPython Notebook or a GUI application) display_formats = ['html'] # A mapping from Dimensioned type to display hook _display_hooks = defaultdict(dict) # Once register_plotting_classes is called, this OptionTree is # populated for the given backend. _options = {} # Weakrefs to record objects per id _weakrefs = {} _options_context = False # Backend option caches _lookup_cache = {} # A list of hooks to call after registering the plot and style options option_setters = [] # A dictionary of custom OptionTree by custom object id by backend _custom_options = {'matplotlib': {}} load_counter_offset = None save_option_state = False current_backend = 'matplotlib' _backend_switch_hooks = []
[docs] @classmethod def set_current_backend(cls, backend): "Use this method to set the backend to run the switch hooks" for hook in cls._backend_switch_hooks: hook(backend) cls.current_backend = backend
@classmethod def options(cls, backend=None, val=None): backend = cls.current_backend if backend is None else backend if val is None: return cls._options[backend] else: cls._lookup_cache[backend] = {} cls._options[backend] = val
[docs] @classmethod def loaded_backends(cls): """ Returns a list of the backends that have been loaded, based on the available OptionTrees. """ return sorted(cls._options.keys())
@classmethod def custom_options(cls, val=None, backend=None): backend = cls.current_backend if backend is None else backend if val is None: return cls._custom_options[backend] else: cls._custom_options[backend] = val
[docs] @classmethod def load(cls, filename): """ Equivalent to pickle.load except that the HoloViews trees is restored appropriately. """ cls.load_counter_offset = StoreOptions.id_offset() val = pickle.load(filename) cls.load_counter_offset = None return val
[docs] @classmethod def loads(cls, pickle_string): """ Equivalent to pickle.loads except that the HoloViews trees is restored appropriately. """ cls.load_counter_offset = StoreOptions.id_offset() val = pickle.loads(pickle_string) cls.load_counter_offset = None return val
[docs] @classmethod def dump(cls, obj, file, protocol=0): """ Equivalent to pickle.dump except that the HoloViews option tree is saved appropriately. """ cls.save_option_state = True pickle.dump(obj, file, protocol=protocol) cls.save_option_state = False
[docs] @classmethod def dumps(cls, obj, protocol=0): """ Equivalent to pickle.dumps except that the HoloViews option tree is saved appropriately. """ cls.save_option_state = True val = pickle.dumps(obj, protocol=protocol) cls.save_option_state = False return val
[docs] @classmethod def info(cls, obj, ansi=True, backend='matplotlib', visualization=True, recursive=False, pattern=None, elements=None): """ Show information about a particular object or component class including the applicable style and plot options. Returns None if the object is not parameterized. """ if elements is None: elements = [] parameterized_object = isinstance(obj, param.Parameterized) parameterized_class = (isinstance(obj,type) and issubclass(obj,param.Parameterized)) info = None if parameterized_object or parameterized_class: info =, ansi=ansi, backend=backend, visualization=visualization, pattern=pattern, elements=elements) if parameterized_object and recursive: hierarchy = obj.traverse(lambda x: type(x)) listed = [] for c in hierarchy[1:]: if c not in listed: inner_info =, ansi=ansi, backend=backend, visualization=visualization, pattern=pattern) black = '\x1b[1;30m%s\x1b[0m' if ansi else '%s' info += '\n\n' + (black % inner_info) listed.append(c) return info
@classmethod def lookup_options(cls, backend, obj, group, defaults=True): # Current custom_options dict may not have entry for if in cls._custom_options[backend]: return cls._custom_options[backend][].closest( obj, group, defaults, backend=backend) elif not defaults: return Options() else: return cls._options[backend].closest(obj, group, defaults, backend=backend)
[docs] @classmethod def lookup(cls, backend, obj): """ Given an object, lookup the corresponding customized option tree if a single custom tree is applicable. """ ids = {el for el in obj.traverse(lambda x: if el is not None} if len(ids) == 0: raise Exception("Object does not own a custom options tree") elif len(ids) != 1: idlist = ",".join([str(el) for el in sorted(ids)]) raise Exception("Object contains elements combined across " "multiple custom trees (ids %s)" % idlist) return cls._custom_options[backend][next(iter(ids))]
[docs] @classmethod def transfer_options(cls, obj, new_obj, backend=None, names=None, level=3): """ Transfers options for all backends from one object to another. Drops any options defined in the supplied drop list. """ if obj is new_obj: return backend = cls.current_backend if backend is None else backend type_name = type(new_obj).__name__ group = type_name if == type(obj).__name__ else spec = '.'.join([s for s in (type_name, group, obj.label)[:level] if s]) options = [] for group in Options._option_groups: opts = cls.lookup_options(backend, obj, group) if not opts: continue new_opts = cls.lookup_options(backend, new_obj, group, defaults=False) existing = new_opts.kwargs if new_opts else {} filtered = {k: v for k, v in opts.kwargs.items() if (names is None or k in names) and k not in existing} if filtered: options.append(Options(group, **filtered)) if options: StoreOptions.set_options(new_obj, {spec: options}, backend)
[docs] @classmethod def add_style_opts(cls, component, new_options, backend=None): """ 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. """ backend = cls.current_backend if backend is None else backend if component not in cls.registry[backend]: raise ValueError( f"Component {component!r} not registered to a plotting class." ) if not isinstance(new_options, list) or not all(isinstance(el, str) for el in new_options): raise ValueError( "Please supply a list of style option keyword strings" ) with param.logging_level('CRITICAL'): for option in new_options: if option not in cls.registry[backend][component].style_opts: plot_class = cls.registry[backend][component] plot_class.style_opts = sorted(plot_class.style_opts+[option]) cls._options[backend][] = Options( 'style', merge_keywords=True, allowed_keywords=new_options )
[docs] @classmethod def register(cls, associations, backend, style_aliases=None): """ Register the supplied dictionary of associations between elements and plotting classes to the specified backend. """ if style_aliases is None: style_aliases = {} if backend not in cls.registry: cls.registry[backend] = {} cls.registry[backend].update(associations) groups = Options._option_groups if backend not in cls._options: cls._options[backend] = OptionTree([], groups=groups, backend=backend) if backend not in cls._custom_options: cls._custom_options[backend] = {} for view_class, plot in cls.registry[backend].items(): expanded_opts = [opt for key in plot.style_opts for opt in style_aliases.get(key, [])] style_opts = sorted({opt for opt in (expanded_opts + plot.style_opts) if opt not in plot._disabled_opts}) # Special handling for PlotSelector which just proxies parameters params = list(plot.param) if hasattr(plot, 'param') else plot.params() plot_opts = [k for k in params if k not in ['name']] with param.logging_level('CRITICAL'): plot.style_opts = style_opts plot_opts = Keywords(plot_opts, target=view_class.__name__) style_opts = Keywords(style_opts, target=view_class.__name__) opt_groups = { 'plot': Options(allowed_keywords=plot_opts), 'output': Options(allowed_keywords=Options._output_allowed_kws), 'style': Options(allowed_keywords=style_opts), 'norm': Options(framewise=False, axiswise=False, allowed_keywords=['framewise', 'axiswise']) } name = view_class.__name__ cls._options[backend][name] = opt_groups
[docs] @classmethod def set_display_hook(cls, group, objtype, hook): """ 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. """ cls._display_hooks[group][objtype] = hook
[docs] @classmethod def render(cls, obj): """ Using any display hooks that have been registered, render the object to a dictionary of MIME types and metadata information. """ class_hierarchy = inspect.getmro(type(obj)) hooks = [] for _, type_hooks in cls._display_hooks.items(): for cls in class_hierarchy: if cls in type_hooks: hooks.append(type_hooks[cls]) break data, metadata = {}, {} for hook in hooks: ret = hook(obj) if ret is None: continue d, md = ret data.update(d) metadata.update(md) return data, metadata
[docs]class StoreOptions: """ A collection of utilities for advanced users for creating and setting customized option trees on the Store. Designed for use by either advanced users or the %opts line and cell magics which use this machinery. This class also holds general classmethods for working with OptionTree instances: as OptionTrees are designed for attribute access it is best to minimize the number of methods implemented on that class and implement the necessary utilities on StoreOptions instead. Lastly this class offers a means to record all OptionErrors generated by an option specification. This is used for validation purposes. """ #=======================# # OptionError recording # #=======================# _errors_recorded = None
[docs] @classmethod def start_recording_skipped(cls): """ Start collecting OptionErrors for all skipped options recorded with the record_skipped_option method """ cls._errors_recorded = []
[docs] @classmethod def stop_recording_skipped(cls): """ Stop collecting OptionErrors recorded with the record_skipped_option method and return them """ if cls._errors_recorded is None: raise Exception('Cannot stop recording before it is started') recorded = cls._errors_recorded[:] cls._errors_recorded = None return recorded
[docs] @classmethod def record_skipped_option(cls, error): """ Record the OptionError associated with a skipped option if currently recording """ if cls._errors_recorded is not None: cls._errors_recorded.append(error)
#===============# # ID management # #===============# @classmethod def get_object_ids(cls, obj): return {el for el in obj.traverse(lambda x: getattr(x, 'id', None))}
[docs] @classmethod def tree_to_dict(cls, tree): """ Given an OptionTree, convert it into the equivalent dictionary format. """ specs = {} for k in tree.keys(): spec_key = '.'.join(k) specs[spec_key] = {} for grp in tree[k].groups: kwargs = tree[k].groups[grp].kwargs if kwargs: specs[spec_key][grp] = kwargs return specs
[docs] @classmethod def propagate_ids(cls, obj, match_id, new_id, applied_keys, backend=None): """ Recursively propagate an id through an object for components matching the applied_keys. This method can only be called if there is a tree with a matching id in Store.custom_options """ applied = [] def propagate(o): if == match_id or (o.__class__.__name__ == 'DynamicMap'): = new_id applied.append(o) obj.traverse(propagate, specs=set(applied_keys) | {'DynamicMap'}) # Clean up the custom tree if it was not applied if new_id not in Store.custom_options(backend=backend): raise AssertionError("New option id %d does not match any " "option trees in Store.custom_options." % new_id) return applied
[docs] @classmethod def capture_ids(cls, obj): """ Given an list of ids, capture a list of ids that can be restored using the restore_ids. """ return obj.traverse(lambda o:
[docs] @classmethod def restore_ids(cls, obj, ids): """ Given an list of ids as captured with capture_ids, restore the ids. Note the structure of an object must not change between the calls to capture_ids and restore_ids. """ ids = iter(ids) obj.traverse(lambda o: setattr(o, 'id', next(ids)))
[docs] @classmethod def apply_customizations(cls, spec, options): """ Apply the given option specs to the supplied options tree. """ for key in sorted(spec.keys()): if isinstance(spec[key], (list, tuple)): customization = {v.key: v for v in spec[key]} else: customization = {k: (Options(**v) if isinstance(v, dict) else v) for k,v in spec[key].items()} # Set the Keywords target on Options from the {type} part of the key. customization = {k: v.keywords_target(key.split('.')[0]) for k,v in customization.items()} options[str(key)] = customization return options
[docs] @classmethod def validate_spec(cls, spec, backends=None): """ Given a specification, validated it against the options tree for the specified backends by raising OptionError for invalid options. If backends is None, validates against all the currently loaded backend. Only useful when invalid keywords generate exceptions instead of skipping, i.e. Options.skip_invalid is False. """ loaded_backends = Store.loaded_backends() if backends is None else backends error_info = {} backend_errors = defaultdict(set) for backend in loaded_backends: cls.start_recording_skipped() with options_policy(skip_invalid=True, warn_on_skip=False): options = OptionTree( items=Store.options(backend).data.items(), groups=Store.options(backend).groups, backend=backend ) cls.apply_customizations(spec, options) for error in cls.stop_recording_skipped(): error_key = (error.invalid_keyword,, error.group_name) error_info[error_key+(backend,)] = error.allowed_keywords backend_errors[error_key].add(backend) for ((keyword, target, group_name), backends) in backend_errors.items(): # If the keyword failed for the target across all loaded backends... if set(backends) == set(loaded_backends): key = (keyword, target, group_name, Store.current_backend) raise OptionError(keyword, group_name=group_name, allowed_keywords=error_info[key])
[docs] @classmethod def validation_error_message(cls, spec, backends=None): """ Returns an options validation error message if there are any invalid keywords. Otherwise returns None. """ try: cls.validate_spec(spec, backends=backends) except OptionError as e: return e.format_options_error()
[docs] @classmethod def expand_compositor_keys(cls, spec): """ Expands compositor definition keys into {type}.{group} keys. For instance a compositor operation returning a group string 'Image' of element type RGB expands to 'RGB.Image'. """ expanded_spec = {} applied_keys = [] compositor_defs = { el.output_type.__name__ for el in Compositor.definitions } for key, val in spec.items(): if key not in compositor_defs: expanded_spec[key] = val else: # Send id to Overlays applied_keys = ['Overlay'] type_name = compositor_defs[key] expanded_spec[str(type_name+'.'+key)] = val return expanded_spec, applied_keys
[docs] @classmethod def create_custom_trees(cls, obj, options=None, backend=None): """ Returns the appropriate set of customized subtree clones for an object, suitable for merging with Store.custom_options (i.e with the ids appropriately offset). Note if an object has no integer ids a new OptionTree is built. The id_mapping return value is a list mapping the ids that need to be matched as set to their new values. """ clones, id_mapping = {}, [] obj_ids = cls.get_object_ids(obj) offset = cls.id_offset() obj_ids = [None] if len(obj_ids) == 0 else obj_ids used_obj_types = [(opt.split('.')[0],) for opt in options] backend = backend or Store.current_backend available_options = Store.options(backend=backend) used_options = {} for obj_type in available_options: if obj_type in used_obj_types: opts_groups = available_options[obj_type].groups used_options[obj_type] = { grp: Options( allowed_keywords=opt.allowed_keywords, backend=backend, ) for (grp, opt) in opts_groups.items() } custom_options = Store.custom_options(backend=backend) for tree_id in obj_ids: if tree_id is not None and tree_id in custom_options: original = custom_options[tree_id] clone = OptionTree( items=original.items(), groups=original.groups, backend=original.backend ) clones[tree_id + offset + 1] = clone id_mapping.append((tree_id, tree_id + offset + 1)) else: clone = OptionTree(groups=available_options.groups, backend=backend) clones[offset] = clone id_mapping.append((tree_id, offset)) # Nodes needed to ensure allowed_keywords is respected for obj_type, opts in used_options.items(): clone[obj_type] = opts return {k: cls.apply_customizations(options, t) if options else t for k,t in clones.items()}, id_mapping
[docs] @classmethod def merge_options(cls, groups, options=None,**kwargs): """ Given a full options dictionary and options groups specified as a keywords, return the full set of merged options: >>> options={'Curve':{'style':dict(color='b')}} >>> style={'Curve':{'linewidth':10 }} >>> merged = StoreOptions.merge_options(['style'], options, style=style) >>> sorted(merged['Curve']['style'].items()) [('color', 'b'), ('linewidth', 10)] """ groups = set(groups) if (options is not None and set(options.keys()) <= groups): kwargs, options = options, None elif (options is not None and any(k in groups for k in options)): raise Exception( f"All keys must be a subset of {', '.join(groups)}." ) options = {} if (options is None) else dict(**options) all_keys = {k for d in kwargs.values() for k in d} for spec_key in all_keys: additions = {} for k, d in kwargs.items(): if spec_key in d: kws = d[spec_key] additions.update({k:kws}) if spec_key not in options: options[spec_key] = {} for key in additions: if key in options[spec_key]: options[spec_key][key].update(additions[key]) else: options[spec_key][key] = additions[key] return options
[docs] @classmethod def state(cls, obj, state=None): """ Method to capture and restore option state. When called without any state supplied, the current state is returned. Then if this state is supplied back in a later call using the same object, the original state is restored. """ if state is None: ids = cls.capture_ids(obj) original_custom_keys = set(Store.custom_options().keys()) return (ids, original_custom_keys) else: (ids, original_custom_keys) = state current_custom_keys = set(Store.custom_options().keys()) for key in current_custom_keys.difference(original_custom_keys): del Store.custom_options()[key] cls.restore_ids(obj, ids)
[docs] @classmethod @contextmanager def options(cls, obj, options=None, **kwargs): """ Context-manager for temporarily setting options on an object (if options is None, no options will be set) . Once the context manager exits, both the object and the Store will be left in exactly the same state they were in before the context manager was used. See holoviews.core.options.set_options function for more information on the options specification format. """ if (options is not None) or kwargs: Store._options_context = True optstate = cls.state(obj) groups = Store.options().groups.keys() options = cls.merge_options(groups, options, **kwargs) cls.set_options(obj, options) try: yield finally: if options is not None: Store._options_context = True cls.state(obj, state=optstate)
[docs] @classmethod def id_offset(cls): """ Compute an appropriate offset for future id values given the set of ids currently defined across backends. """ max_ids = [] for backend in Store.renderers.keys(): # Ensure store_ids is immediately cast to list to avoid a # race condition (#5533) store_ids = list(Store.custom_options(backend=backend).keys()) max_id = max(store_ids)+1 if len(store_ids) > 0 else 0 max_ids.append(max_id) # If no backends defined (e.g. plotting not imported) return zero return max(max_ids) if len(max_ids) else 0
[docs] @classmethod def update_backends(cls, id_mapping, custom_trees, backend=None): """ Given the id_mapping from previous ids to new ids and the new custom tree dictionary, update the current backend with the supplied trees and update the keys in the remaining backends to stay linked with the current object. """ backend = Store.current_backend if backend is None else backend # Update the custom option entries for the current backend Store.custom_options(backend=backend).update(custom_trees) Store._lookup_cache[backend] = {} # Propagate option ids for non-selected backends for b in Store.loaded_backends(): if b == backend: continue backend_trees = Store._custom_options[b] for (old_id, new_id) in id_mapping: tree = backend_trees.get(old_id, None) if tree is not None: backend_trees[new_id] = tree
[docs] @classmethod def set_options(cls, obj, options=None, backend=None, **kwargs): """ Pure Python function for customize HoloViews objects in terms of their style, plot and normalization options. The options specification is a dictionary containing the target for customization as a {type}.{group}.{label} keys. An example of such a key is 'Image' which would customize all Image components in the object. The key 'Image.Channel' would only customize Images in the object that have the group 'Channel'. The corresponding value is then a list of Option objects specified with an appropriate category ('plot', 'style' or 'norm'). For instance, using the keys described above, the specs could be: {'Image:[Options('style', cmap='jet')]} Or setting two types of option at once: {'Image.Channel':[Options('plot', size=50), Options('style', cmap='Blues')]} Relationship to the %%opts magic ---------------------------------- This function matches the functionality supplied by the %%opts cell magic in the IPython extension. In fact, you can use the same syntax as the IPython cell magic to achieve the same customization as shown above: from holoviews.util.parser import OptsSpec set_options(my_image, OptsSpec.parse("Image (cmap='jet')")) Then setting both plot and style options: set_options(my_image, OptsSpec.parse("Image [size=50] (cmap='Blues')")) """ # Note that an alternate, more verbose and less recommended # syntax can also be used: # {'Image.Channel:{'plot': Options(size=50), # 'style': Options('style', cmap='Blues')]} groups = Store.options(backend=backend).groups.keys() options = cls.merge_options(groups, options, **kwargs) spec, compositor_applied = cls.expand_compositor_keys(options) custom_trees, id_mapping = cls.create_custom_trees(obj, spec, backend=backend) cls.update_backends(id_mapping, custom_trees, backend=backend) # Propagate ids to the objects not_used = [] for (match_id, new_id) in id_mapping: key = compositor_applied+list(spec.keys()) applied = cls.propagate_ids( obj, match_id, new_id, key, backend=backend ) if not applied: not_used.append(new_id) # Clean up unused custom option trees for new_id in set(not_used): cleanup_custom_options(new_id) return obj