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 pickle
import traceback
from contextlib import contextmanager
from collections import OrderedDict

import numpy as np

import param
from .tree import AttrTree
from .util import sanitize_identifier, group_sanitizer,label_sanitizer
from .pprint import InfoPrinter

[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(SkipRendering, self).__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(OptionError, self).__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 = ("Invalid option %s, valid options are: %s" % (repr(invalid_keyword), str(sorted(list(set(allowed_keywords)))))) if path and group_name: msg = ("Invalid key for group %r on path %r;\n" % (group_name, path)) + msg return msg
[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): abbrev = '%s: %s' % (self.etype.__name__, self.msg) msg = ('To view the original traceback, catch this exception ' 'and call print_traceback() method.') return '%s\n\n%s' % (abbrev, msg)
[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(object): """ 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]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', 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, **params): super(Cycle, self).__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: return self.default_cycles[self.key] 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.get_param_values(), values=values, **params)) def __len__(self): return len(self.values) def __repr__(self): return "%s(values=%s)" % (type(self).__name__, [str(el) for el in self.values])
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(param.Parameterized): """ 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. """ allowed_keywords = param.List(default=None, allow_None=True, doc=""" Optional list of strings corresponding to the allowed keywords.""") key = param.String(default=None, allow_None=True, doc=""" Optional specification of the options key name. For instance, key could be 'plot' or 'style'.""") merge_keywords = param.Boolean(default=True, doc=""" Whether to merge with the existing keywords if the corresponding node already exists""") skip_invalid = param.Boolean(default=True, doc=""" Whether all Options instances should skip invalid keywords or raise and exception. May only be specified at the class level.""") warn_on_skip = param.Boolean(default=True, doc=""" Whether all Options instances should generate warnings when skipping over invalid keywords or not. May only be specified at the class level.""") def __init__(self, key=None, allowed_keywords=None, merge_keywords=True, **kwargs): invalid_kws = [] for kwarg in sorted(kwargs.keys()): if allowed_keywords and kwarg not in allowed_keywords: if self.skip_invalid: kwargs.pop(kwarg) invalid_kws.append(kwarg) else: raise OptionError(kwarg, allowed_keywords) if invalid_kws and self.warn_on_skip: self.warning("Invalid options %s, valid options are: %s" % (repr(invalid_kws), str(sorted(list(set(allowed_keywords)))))) self.kwargs = kwargs self._options = self._expand_options(kwargs) allowed_keywords = sorted(allowed_keywords) if allowed_keywords else None super(Options, self).__init__(allowed_keywords=allowed_keywords, merge_keywords=merge_keywords, key=key)
[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. """ allowed_keywords=self.allowed_keywords if allowed_keywords is None else allowed_keywords inherited_style = dict(allowed_keywords=allowed_keywords, **kwargs) return self.__class__(key=self.key, **dict(self.kwargs, **inherited_style)) def _expand_options(self, kwargs): """ Expand out Cycle objects into multiple sets of keyword values. To elaborate, the full Cartesian product over the supplied Cycle objects is expanded into a list, allowing infinite, cyclic indexing in the __getitem__ method.""" filter_static = dict((k,v) for (k,v) in kwargs.items() if not isinstance(v, Cycle)) filter_cycles = [(k,v) for (k,v) in kwargs.items() if isinstance(v, Cycle)] if not filter_cycles: return [kwargs] filter_names, filter_values = list(zip(*filter_cycles)) cyclic_tuples = list(zip(*[val.values for val in filter_values])) return [dict(zip(filter_names, tps), **filter_static) for tps in cyclic_tuples]
[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 Cycle objects to a maximum number of Cycles and returns a new Options object with the truncated or resampled Cycles. """ kwargs = {kw: (arg[num] if isinstance(arg, Cycle) else arg) for kw, arg in self.kwargs.items()} return self(**kwargs)
def __getitem__(self, index): """ Infinite cyclic indexing of options over the integers, looping over the set of defined Cycle objects. """ return dict(self._options[index % len(self._options)]) @property def options(self): "Access of the options keywords when no cycles are defined." if len(self._options) == 1: return dict(self._options[0]) else: raise Exception("The options property may only be used with non-cyclic Options.") def __repr__(self): kws = ', '.join("%s=%r" % (k,v) for (k,v) in self.kwargs.items()) return "%s(%s)" % (self.__class__.__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, **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__['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. """ override_kwargs = dict(options.kwargs) allowed_kws = [] if options.allowed_keywords is None else options.allowed_keywords old_allowed = self[identifier][group_name].allowed_keywords if identifier in self.children else [] old_allowed = [] if old_allowed is None else old_allowed override_kwargs['allowed_keywords'] = sorted(allowed_kws + old_allowed) if group_name not in self.groups: raise KeyError("Group %s not defined on SettingTree" % group_name) 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) try: return (group_options(**override_kwargs) if options.merge_keywords else Options(group_name, **override_kwargs)) except OptionError as e: raise OptionError(e.invalid_keyword, e.allowed_keywords, group_name=group_name, path = self.path) def __getitem__(self, item): if item in self.groups: return self.groups[item] return super(OptionTree, self).__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): 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): 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) else: raise ValueError('OptionTree only accepts a dictionary of Options.') super(OptionTree, self).__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): """ 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 """ components = (obj.__class__.__name__, group_sanitizer(, label_sanitizer(obj.label)) target = '.'.join([c for c in components if c]) return self.find(components).options(group, target=target)
[docs] def options(self, group, target=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 if self.parent is None and target and (self is not Store.options()): root_name = self.__class__.__name__ replacement = root_name + ('' if len(target) == len(root_name) else '.') option_key = target.replace(replacement,'') match = Store.options().find(option_key) if match is not Store.options(): return match.options(group) else: return Options() elif self.parent is None: return self.groups[group] return Options(**dict(self.parent.options(group,target=target).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 seperator 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,'dict(%s)' % ', '.join('%s=%r' % (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([sep+'%r : %s' % (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 'OptionTree(groups=%s,\n%s\n)' % (groups.keys(), gsep.join(gspecs))
[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 ElementOperation 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'.""") operation = param.Parameter(doc=""" The ElementOperation 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 overlayed 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(doc=""" The group identifier for the output of this particular compositor""") kwargs = param.Dict(doc=""" Optional set of parameters to pass to the operation.""") operations = [] # The operations that can be used to define compositors. definitions = [] # The set of all the compositor instances @classmethod
[docs] def strongest_match(cls, overlay, mode): """ 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] matches = [(match[0], op, match[1]) for (match, op) in match_strength if match is not None] if matches == []: return None else: return sorted(matches)[0]
[docs] def collapse_element(cls, overlay, key=None, ranges=None, mode='data'): """ Finds any applicable compositor and applies it. """ from .overlay import Overlay match = cls.strongest_match(overlay, mode) if match is None: return overlay (_, applicable_op, (start, stop)) = match values = overlay.values() sliced = Overlay.from_values(values[start:stop]) result = applicable_op.apply(sliced, ranges, key=key) result = result.relabel( output = Overlay.from_values(values[:start]+[result]+values[stop:]) = return output
[docs] 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, key, ranges, mode) return clone
@classmethod def register(cls, compositor): defined_groups = [ for op in cls.definitions] if in defined_groups: cls.definitions.pop(defined_groups.index( cls.definitions.append(compositor) if compositor.operation not in cls.operations: cls.operations.append(compositor.operation) def __init__(self, pattern, operation, group, mode, **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 = '' super(Compositor, self).__init__(group=group, pattern=pattern, operation=operation, mode=mode, kwargs=kwargs) @property def output_type(self): """ Returns the operation output_type unless explicitly overridden in the kwargs. """ if 'output_type' in self.kwargs: return self.kwargs['output_type'] else: return 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, key=None): """ Apply the compositor on the input with the given input ranges. """ from .overlay import CompositeOverlay if isinstance(value, CompositeOverlay) and len(value) == 1: value = value.values()[0] if key is None: return self.operation(value, input_ranges=input_ranges, **self.kwargs) return self.operation.instance(input_ranges=input_ranges, **self.kwargs).process_element(value, key)
[docs]class Store(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. """ renderers = OrderedDict() # 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'] # Once register_plotting_classes is called, this OptionTree is # populated for the given backend. _options = {} # 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' @classmethod def options(cls, val=None, backend=None): backend = cls.current_backend if backend is None else backend if val is None: return cls._options[backend] else: cls._options[backend] = val @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 @classmethod
[docs] 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] 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] 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] 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] def info(cls, obj, ansi=True, backend='matplotlib', visualization=True, recursive=False, pattern=None, elements=[]): """ Show information about a particular object or component class including the applicable style and plot options. Returns None if the object is not parameterized. """ 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): # Current custom_options dict may not have entry for if in cls._custom_options[backend]: return cls._custom_options[backend][].closest(obj, group) else: return cls._options[backend].closest(obj, group) @classmethod
[docs] def lookup(cls, backend, obj): """ Given an object, lookup the corresponding customized option tree if a single custom tree is applicable. """ ids = set([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][list(ids)[0]]
[docs] 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("Component %r not registered to a plotting class" % component) 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] def register(cls, associations, backend, style_aliases={}): """ Register the supplied dictionary of associations between elements and plotting classes to the specified backend. """ from .overlay import CompositeOverlay if backend not in cls.registry: cls.registry[backend] = {} cls.registry[backend].update(associations) groups = ['style', 'plot', 'norm'] if backend not in cls._options: cls._options[backend] = OptionTree([], groups=groups) 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(set(opt for opt in (expanded_opts + plot.style_opts) if opt not in plot._disabled_opts)) plot_opts = [k for k in plot.params().keys() if k not in ['name']] with param.logging_level('CRITICAL'): plot.style_opts = style_opts opt_groups = {'plot': Options(allowed_keywords=plot_opts)} if not isinstance(view_class, CompositeOverlay) or hasattr(plot, 'style_opts'): opt_groups.update({'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]class StoreOptions(object): """ A collection of utilities for advanced users for creating and setting customized option tress 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. """ #===============# # ID management # #===============# @classmethod def get_object_ids(cls, obj): return set(el for el in obj.traverse(lambda x: getattr(x, 'id', None))) @classmethod
[docs] 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] def propagate_ids(cls, obj, match_id, new_id, applied_keys): """ 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 """ if not new_id in Store.custom_options(): raise AssertionError("The set_ids method requires " "Store.custom_options to contain" " a tree with id %d" % new_id) def propagate(o): if == match_id or (o.__class__.__name__ == 'DynamicMap'): setattr(o, 'id', new_id) obj.traverse(propagate, specs=set(applied_keys) | {'DynamicMap'})
[docs] 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: getattr(o, 'id'))
[docs] 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] 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()} options[str(key)] = customization return options
[docs] def validate_spec(cls, spec, skip=Options.skip_invalid): """ Given a specification, validated it against the default options tree (Store.options). Only tends to be useful when invalid keywords generate exceptions instead of skipping. """ if skip: return options = OptionTree(items=Store.options().data.items(), groups=Store.options().groups) return cls.apply_customizations(spec, options)
[docs] 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 = { 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] def create_custom_trees(cls, obj, options=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 for tree_id in obj_ids: if tree_id is not None and tree_id in Store.custom_options(): original = Store.custom_options()[tree_id] clone = OptionTree(items = original.items(), groups = original.groups) clones[tree_id + offset + 1] = clone id_mapping.append((tree_id, tree_id + offset + 1)) else: clone = OptionTree(groups=Store.options().groups) clones[offset] = clone id_mapping.append((tree_id, offset)) # Nodes needed to ensure allowed_keywords is respected for k in Store.options(): if k in [(opt.split('.')[0],) for opt in options]: group = {grp:Options( allowed_keywords=opt.allowed_keywords) for (grp, opt) in Store.options()[k].groups.items()} clone[k] = group return {k:cls.apply_customizations(options, t) if options else t for k,t in clones.items()}, id_mapping
[docs] 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("All keys must be a subset of %s" % ', '.join(groups)) options = {} if (options is None) else dict(**options) all_keys = set(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] 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)
@classmethod @contextmanager
[docs] 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 None) and kwargs == {}: yield else: optstate = cls.state(obj) groups = Store.options().groups.keys() options = cls.merge_options(groups, options, **kwargs) cls.set_options(obj, options) yield if options is not None: cls.state(obj, state=optstate)
[docs] 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(): store_ids = 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] def update_backends(cls, id_mapping, custom_trees): """ 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. """ # Update the custom option entries for the current backend Store.custom_options().update(custom_trees) # Update the entries in other backends so the ids match correctly for backend in [k for k in Store.renderers.keys() if k != Store.current_backend]: for (old_id, new_id) in id_mapping: tree = Store._custom_options[backend].pop(old_id, None) if tree is not None: Store._custom_options[backend][new_id] = tree
[docs] def set_options(cls, obj, options=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.ipython.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')]} options = cls.merge_options(Store.options().groups.keys(), options, **kwargs) spec, compositor_applied = cls.expand_compositor_keys(options) custom_trees, id_mapping = cls.create_custom_trees(obj, spec) cls.update_backends(id_mapping, custom_trees) for (match_id, new_id) in id_mapping: cls.propagate_ids(obj, match_id, new_id, compositor_applied+list(spec.keys())) return obj