Source code for pint.facets.context.objects


    :copyright: 2022 by Pint Authors, see AUTHORS for more details.
    :license: BSD, see LICENSE for more details.

from __future__ import annotations

import weakref
from collections import ChainMap, defaultdict
from typing import Optional, Tuple

from ...facets.plain import UnitDefinition
from ...util import UnitsContainer, to_units_container
from .definitions import ContextDefinition

[docs]class Context: """A specialized container that defines transformation functions from one dimension to another. Each Dimension are specified using a UnitsContainer. Simple transformation are given with a function taking a single parameter. Conversion functions may take optional keyword arguments and the context can have default values for these arguments. Additionally, a context may host redefinitions. A redefinition must be performed among units that already exist in the registry. It cannot change the dimensionality of a unit. The symbol and aliases are automatically inherited from the registry. See ContextDefinition for the definition file syntax. Parameters ---------- name : str or None, optional Name of the context (must be unique within the registry). Use None for anonymous Context. (Default value = None). aliases : iterable of str Other names for the context. defaults : None or dict Maps variable names to values. Example ------- >>> from pint.util import UnitsContainer >>> from pint import Context, UnitRegistry >>> ureg = UnitRegistry() >>> timedim = UnitsContainer({'[time]': 1}) >>> spacedim = UnitsContainer({'[length]': 1}) >>> def time_to_len(ureg, time): ... 'Time to length converter' ... return 3. * time >>> c = Context() >>> c.add_transformation(timedim, spacedim, time_to_len) >>> c.transform(timedim, spacedim, ureg, 2) 6.0 >>> def time_to_len_indexed(ureg, time, n=1): ... 'Time to length converter, n is the index of refraction of the material' ... return 3. * time / n >>> c = Context(defaults={'n':3}) >>> c.add_transformation(timedim, spacedim, time_to_len_indexed) >>> c.transform(timedim, spacedim, ureg, 2) 2.0 >>> c.redefine("pound = 0.5 kg") """ def __init__( self, name: Optional[str] = None, aliases: Tuple[str, ...] = (), defaults: Optional[dict] = None, ) -> None: = name self.aliases = aliases #: Maps (src, dst) -> transformation function self.funcs = {} #: Maps defaults variable names to values self.defaults = defaults or {} # Store Definition objects that are context-specific self.redefinitions = [] # Flag set to True by the Registry the first time the context is enabled self.checked = False #: Maps (src, dst) -> self #: Used as a convenience dictionary to be composed by ContextChain self.relation_to_context = weakref.WeakValueDictionary() @classmethod def from_context(cls, context: Context, **defaults) -> Context: """Creates a new context that shares the funcs dictionary with the original context. The default values are copied from the original context and updated with the new defaults. If defaults is empty, return the same context. Parameters ---------- context : pint.Context Original context. **defaults Returns ------- pint.Context """ if defaults: newdef = dict(context.defaults, **defaults) c = cls(, context.aliases, newdef) c.funcs = context.funcs c.redefinitions = context.redefinitions for edge in context.funcs: c.relation_to_context[edge] = c return c return context @classmethod def from_lines(cls, lines, to_base_func=None, non_int_type=float) -> Context: cd = ContextDefinition.from_lines(lines, non_int_type) return cls.from_definition(cd, to_base_func) @classmethod def from_definition(cls, cd: ContextDefinition, to_base_func=None) -> Context: ctx = cls(, cd.aliases, cd.defaults) for definition in cd.redefinitions: ctx._redefine(definition) for relation in cd.relations: try: if to_base_func: src = to_base_func(relation.src) dst = to_base_func(relation.dst) else: src, dst = relation.src, relation.dst ctx.add_transformation(src, dst, relation.transformation) if relation.bidirectional: ctx.add_transformation(dst, src, relation.transformation) except Exception as exc: raise ValueError( f"Could not add Context {} relation {relation}" ) from exc return ctx def add_transformation(self, src, dst, func) -> None: """Add a transformation function to the context.""" _key = self.__keytransform__(src, dst) self.funcs[_key] = func self.relation_to_context[_key] = self def remove_transformation(self, src, dst) -> None: """Add a transformation function to the context.""" _key = self.__keytransform__(src, dst) del self.funcs[_key] del self.relation_to_context[_key] @staticmethod def __keytransform__(src, dst) -> Tuple[UnitsContainer, UnitsContainer]: return to_units_container(src), to_units_container(dst) def transform(self, src, dst, registry, value): """Transform a value.""" _key = self.__keytransform__(src, dst) return self.funcs[_key](registry, value, **self.defaults) def redefine(self, definition: str) -> None: """Override the definition of a unit in the registry. Parameters ---------- definition : str <unit> = <new definition>``, e.g. ``pound = 0.5 kg`` """ from ...delegates import ParserConfig, txt_defparser # TODO: kept for backwards compatibility. # this is not a good idea as we have no way of known the correct non_int_type cfg = ParserConfig(float) parser = txt_defparser.DefParser(cfg, None) pp = parser.parse_string(definition) for definition in parser.iter_parsed_project(pp): if isinstance(definition, UnitDefinition): self._redefine(definition) def _redefine(self, definition: UnitDefinition): self.redefinitions.append(definition) def hashable( self, ) -> Tuple[Optional[str], Tuple[str, ...], frozenset, frozenset, tuple]: """Generate a unique hashable and comparable representation of self, which can be used as a key in a dict. This class cannot define ``__hash__`` because it is mutable, and the Python interpreter does cache the output of ``__hash__``. Returns ------- tuple """ return (, tuple(self.aliases), frozenset((k, id(v)) for k, v in self.funcs.items()), frozenset(self.defaults.items()), tuple(self.redefinitions), )
class ContextChain(ChainMap): """A specialized ChainMap for contexts that simplifies finding rules to transform from one dimension to another. """ def __init__(self): super().__init__() self.contexts = [] self.maps.clear() # Remove default empty map self._graph = None def insert_contexts(self, *contexts): """Insert one or more contexts in reversed order the chained map. (A rule in last context will take precedence) To facilitate the identification of the context with the matching rule, the *relation_to_context* dictionary of the context is used. """ self.contexts = list(reversed(contexts)) + self.contexts self.maps = [ctx.relation_to_context for ctx in reversed(contexts)] + self.maps self._graph = None def remove_contexts(self, n: int = None): """Remove the last n inserted contexts from the chain. Parameters ---------- n: int (Default value = None) """ del self.contexts[:n] del self.maps[:n] self._graph = None @property def defaults(self): for ctx in self.values(): return ctx.defaults return {} @property def graph(self): """The graph relating""" if self._graph is None: self._graph = defaultdict(set) for fr_, to_ in self: self._graph[fr_].add(to_) return self._graph def transform(self, src, dst, registry, value): """Transform the value, finding the rule in the chained context. (A rule in last context will take precedence) """ return self[(src, dst)].transform(src, dst, registry, value) def hashable(self): """Generate a unique hashable and comparable representation of self, which can be used as a key in a dict. This class cannot define ``__hash__`` because it is mutable, and the Python interpreter does cache the output of ``__hash__``. """ return tuple(ctx.hashable() for ctx in self.contexts)