"""
pint.registry
~~~~~~~~~~~~~
Defines the Registry, a class to contain units and their relations.
The module actually defines 5 registries with different capabilites:
- BaseRegistry: Basic unit definition and querying.
Conversion between multiplicative units.
- NonMultiplicativeRegistry: Conversion between non multiplicative (offset) units.
(e.g. Temperature)
* Inherits from BaseRegistry
- ContextRegisty: Conversion between units with different dimensions according
to previously established relations (contexts) - e.g. in spectroscopy,
conversion between frequency and energy is possible. May also override
conversions between units on the same dimension - e.g. different
rounding conventions.
* Inherits from BaseRegistry
- SystemRegistry: Group unit and changing of base units.
(e.g. in MKS, meter, kilogram and second are base units.)
* Inherits from BaseRegistry
- UnitRegistry: Combine all previous capabilities, it is exposed by Pint.
:copyright: 2016 by Pint Authors, see AUTHORS for more details.
:license: BSD, see LICENSE for more details.
"""
import copy
import functools
import itertools
import locale
import os
import re
from collections import ChainMap, defaultdict
from contextlib import closing, contextmanager
from decimal import Decimal
from fractions import Fraction
from io import StringIO
from tokenize import NAME, NUMBER
import pkg_resources
from . import registry_helpers, systems
from .compat import babel_parse, tokenizer
from .context import Context, ContextChain
from .converters import ScaleConverter
from .definitions import (
AliasDefinition,
Definition,
DimensionDefinition,
PrefixDefinition,
UnitDefinition,
)
from .errors import (
DefinitionSyntaxError,
DimensionalityError,
RedefinitionError,
UndefinedUnitError,
)
from .pint_eval import build_eval_tree
from .util import (
ParserHelper,
SourceIterator,
UnitsContainer,
_is_dim,
find_connected_nodes,
find_shortest_path,
getattr_maybe_raise,
logger,
pi_theorem,
solve_dependencies,
string_preprocessor,
to_units_container,
)
_BLOCK_RE = re.compile(r" |\(")
@functools.lru_cache()
def pattern_to_regex(pattern):
if hasattr(pattern, "finditer"):
pattern = pattern.pattern
# Replace "{unit_name}" match string with float regex with unit_name as group
pattern = re.sub(
r"{(\w+)}", r"(?P<\1>[+-]?[0-9]+(?:.[0-9]+)?(?:[Ee][+-]?[0-9]+)?)", pattern
)
return re.compile(pattern)
class RegistryMeta(type):
"""This is just to call after_init at the right time
instead of asking the developer to do it when subclassing.
"""
def __call__(self, *args, **kwargs):
obj = super().__call__(*args, **kwargs)
obj._after_init()
return obj
class RegistryCache:
"""Cache to speed up unit registries"""
def __init__(self):
#: Maps dimensionality (UnitsContainer) to Units (str)
self.dimensional_equivalents = {}
#: Maps dimensionality (UnitsContainer) to Dimensionality (UnitsContainer)
self.root_units = {}
#: Maps dimensionality (UnitsContainer) to Units (UnitsContainer)
self.dimensionality = {}
#: Cache the unit name associated to user input. ('mV' -> 'millivolt')
self.parse_unit = {}
class ContextCacheOverlay:
"""Layer on top of the base UnitRegistry cache, specific to a combination of
active contexts which contain unit redefinitions.
"""
def __init__(self, registry_cache: RegistryCache):
self.dimensional_equivalents = registry_cache.dimensional_equivalents
self.root_units = {}
self.dimensionality = registry_cache.dimensionality
self.parse_unit = registry_cache.parse_unit
class BaseRegistry(metaclass=RegistryMeta):
"""Base class for all registries.
Capabilities:
- Register units, prefixes, and dimensions, and their relations.
- Convert between units.
- Find dimensionality of a unit.
- Parse units with prefix and/or suffix.
- Parse expressions.
- Parse a definition file.
- Allow extending the definition file parser by registering @ directives.
Parameters
----------
filename : str or None
path of the units definition file to load or line iterable object. Empty to load
the default definition file. None to leave the UnitRegistry empty.
force_ndarray : bool
convert any input, scalar or not to a numpy.ndarray.
force_ndarray_like : bool
convert all inputs other than duck arrays to a numpy.ndarray.
on_redefinition : str
action to take in case a unit is redefined: 'warn', 'raise', 'ignore'
auto_reduce_dimensions :
If True, reduce dimensionality on appropriate operations.
preprocessors :
list of callables which are iteratively ran on any input expression or unit
string
fmt_locale :
locale identifier string, used in `format_babel`
non_int_type : type
numerical type used for non integer values. (Default: float)
"""
#: Map context prefix to function
#: type: Dict[str, (SourceIterator -> None)]
_parsers = None
#: Babel.Locale instance or None
fmt_locale = None
def __init__(
self,
filename="",
force_ndarray=False,
force_ndarray_like=False,
on_redefinition="warn",
auto_reduce_dimensions=False,
preprocessors=None,
fmt_locale=None,
non_int_type=float,
):
self._register_parsers()
self._init_dynamic_classes()
self._filename = filename
self.force_ndarray = force_ndarray
self.force_ndarray_like = force_ndarray_like
self.preprocessors = preprocessors or []
#: Action to take in case a unit is redefined. 'warn', 'raise', 'ignore'
self._on_redefinition = on_redefinition
#: Determines if dimensionality should be reduced on appropriate operations.
self.auto_reduce_dimensions = auto_reduce_dimensions
#: Default locale identifier string, used when calling format_babel without explicit locale.
self.set_fmt_locale(fmt_locale)
#: Numerical type used for non integer values.
self.non_int_type = non_int_type
#: Map between name (string) and value (string) of defaults stored in the
#: definitions file.
self._defaults = {}
#: Map dimension name (string) to its definition (DimensionDefinition).
self._dimensions = {}
#: Map unit name (string) to its definition (UnitDefinition).
#: Might contain prefixed units.
self._units = {}
#: Map unit name in lower case (string) to a set of unit names with the right
#: case.
#: Does not contain prefixed units.
#: e.g: 'hz' - > set('Hz', )
self._units_casei = defaultdict(set)
#: Map prefix name (string) to its definition (PrefixDefinition).
self._prefixes = {"": PrefixDefinition("", "", (), 1)}
#: Map suffix name (string) to canonical , and unit alias to canonical unit name
self._suffixes = {"": "", "s": ""}
#: Map contexts to RegistryCache
self._cache = RegistryCache()
self._initialized = False
def _init_dynamic_classes(self):
"""Generate subclasses on the fly and attach them to self"""
from .unit import build_unit_class
self.Unit = build_unit_class(self)
from .quantity import build_quantity_class
self.Quantity = build_quantity_class(self)
from .measurement import build_measurement_class
self.Measurement = build_measurement_class(self)
def _after_init(self):
"""This should be called after all __init__"""
if self._filename == "":
self.load_definitions("default_en.txt", True)
elif self._filename is not None:
self.load_definitions(self._filename)
self._build_cache()
self._initialized = True
def _register_parsers(self):
self._register_parser("@defaults", self._parse_defaults)
def _parse_defaults(self, ifile):
"""Loader for a @default section.
"""
next(ifile)
for lineno, part in ifile.block_iter():
k, v = part.split("=")
self._defaults[k.strip()] = v.strip()
def __deepcopy__(self, memo):
new = object.__new__(type(self))
new.__dict__ = copy.deepcopy(self.__dict__, memo)
new._init_dynamic_classes()
return new
def __getattr__(self, item):
getattr_maybe_raise(self, item)
return self.Unit(item)
def __getitem__(self, item):
logger.warning(
"Calling the getitem method from a UnitRegistry is deprecated. "
"use `parse_expression` method or use the registry as a callable."
)
return self.parse_expression(item)
def __contains__(self, item):
"""Support checking prefixed units with the `in` operator
"""
try:
self.__getattr__(item)
return True
except UndefinedUnitError:
return False
def __dir__(self):
#: Calling dir(registry) gives all units, methods, and attributes.
#: Also used for autocompletion in IPython.
return list(self._units.keys()) + list(object.__dir__(self))
def __iter__(self):
"""Allows for listing all units in registry with `list(ureg)`.
Returns
-------
Iterator over names of all units in registry, ordered alphabetically.
"""
return iter(sorted(self._units.keys()))
def set_fmt_locale(self, loc):
"""Change the locale used by default by `format_babel`.
Parameters
----------
loc : str or None
None` (do not translate), 'sys' (detect the system locale) or a locale id string.
"""
if isinstance(loc, str):
if loc == "sys":
loc = locale.getdefaultlocale()[0]
# We call babel parse to fail here and not in the formatting operation
babel_parse(loc)
self.fmt_locale = loc
def UnitsContainer(self, *args, **kwargs):
return UnitsContainer(*args, non_int_type=self.non_int_type, **kwargs)
@property
def default_format(self):
"""Default formatting string for quantities."""
return self.Quantity.default_format
@default_format.setter
def default_format(self, value):
self.Unit.default_format = value
self.Quantity.default_format = value
def define(self, definition):
"""Add unit to the registry.
Parameters
----------
definition : str or Definition
a dimension, unit or prefix definition.
"""
if isinstance(definition, str):
for line in definition.split("\n"):
self._define(Definition.from_string(line, self.non_int_type))
else:
self._define(definition)
def _define(self, definition):
"""Add unit to the registry.
This method defines only multiplicative units, converting any other type
to `delta_` units.
Parameters
----------
definition : Definition
a dimension, unit or prefix definition.
Returns
-------
Definition, dict, dict
Definition instance, case sensitive unit dict, case insensitive unit dict.
"""
if isinstance(definition, DimensionDefinition):
d, di = self._dimensions, None
elif isinstance(definition, UnitDefinition):
d, di = self._units, self._units_casei
# For a base units, we need to define the related dimension
# (making sure there is only one to define)
if definition.is_base:
for dimension in definition.reference.keys():
if dimension in self._dimensions:
if dimension != "[]":
raise DefinitionSyntaxError(
"Only one unit per dimension can be a base unit"
)
continue
self.define(
DimensionDefinition(dimension, "", (), None, is_base=True)
)
elif isinstance(definition, PrefixDefinition):
d, di = self._prefixes, None
elif isinstance(definition, AliasDefinition):
d, di = self._units, self._units_casei
self._define_alias(definition, d, di)
return d[definition.name], d, di
else:
raise TypeError("{} is not a valid definition.".format(definition))
# define "delta_" units for units with an offset
if getattr(definition.converter, "offset", 0) != 0:
if definition.name.startswith("["):
d_name = "[delta_" + definition.name[1:]
else:
d_name = "delta_" + definition.name
if definition.symbol:
d_symbol = "Δ" + definition.symbol
else:
d_symbol = None
d_aliases = tuple("Δ" + alias for alias in definition.aliases) + tuple(
"delta_" + alias for alias in definition.aliases
)
d_reference = self.UnitsContainer(
{ref: value for ref, value in definition.reference.items()}
)
d_def = UnitDefinition(
d_name,
d_symbol,
d_aliases,
ScaleConverter(definition.converter.scale),
d_reference,
definition.is_base,
)
else:
d_def = definition
self._define_adder(d_def, d, di)
return definition, d, di
def _define_adder(self, definition, unit_dict, casei_unit_dict):
"""Helper function to store a definition in the internal dictionaries.
It stores the definition under its name, symbol and aliases.
"""
self._define_single_adder(
definition.name, definition, unit_dict, casei_unit_dict
)
if definition.has_symbol:
self._define_single_adder(
definition.symbol, definition, unit_dict, casei_unit_dict
)
for alias in definition.aliases:
if " " in alias:
logger.warn("Alias cannot contain a space: " + alias)
self._define_single_adder(alias, definition, unit_dict, casei_unit_dict)
def _define_single_adder(self, key, value, unit_dict, casei_unit_dict):
"""Helper function to store a definition in the internal dictionaries.
It warns or raise error on redefinition.
"""
if key in unit_dict:
if self._on_redefinition == "raise":
raise RedefinitionError(key, type(value))
elif self._on_redefinition == "warn":
logger.warning("Redefining '%s' (%s)" % (key, type(value)))
unit_dict[key] = value
if casei_unit_dict is not None:
casei_unit_dict[key.lower()].add(key)
def _define_alias(self, definition, unit_dict, casei_unit_dict):
unit = unit_dict[definition.name]
unit.add_aliases(*definition.aliases)
for alias in unit.aliases:
unit_dict[alias] = unit
casei_unit_dict[alias.lower()].add(alias)
def _register_parser(self, prefix, parserfunc):
"""Register a loader for a given @ directive..
Parameters
----------
prefix :
string identifying the section (e.g. @context)
parserfunc : SourceIterator -> None
A function that is able to parse a Definition section.
Returns
-------
"""
if self._parsers is None:
self._parsers = {}
if prefix and prefix[0] == "@":
self._parsers[prefix] = parserfunc
else:
raise ValueError("Prefix directives must start with '@'")
def load_definitions(self, file, is_resource=False):
"""Add units and prefixes defined in a definition text file.
Parameters
----------
file :
can be a filename or a line iterable.
is_resource :
used to indicate that the file is a resource file
and therefore should be loaded from the package. (Default value = False)
Returns
-------
"""
# Permit both filenames and line-iterables
if isinstance(file, str):
try:
if is_resource:
with closing(pkg_resources.resource_stream(__name__, file)) as fp:
rbytes = fp.read()
return self.load_definitions(
StringIO(rbytes.decode("utf-8")), is_resource
)
else:
with open(file, encoding="utf-8") as fp:
return self.load_definitions(fp, is_resource)
except (RedefinitionError, DefinitionSyntaxError) as e:
if e.filename is None:
e.filename = file
raise e
except Exception as e:
msg = getattr(e, "message", "") or str(e)
raise ValueError("While opening {}\n{}".format(file, msg))
ifile = SourceIterator(file)
for no, line in ifile:
if line.startswith("@") and not line.startswith("@alias"):
if line.startswith("@import"):
if is_resource:
path = line[7:].strip()
else:
try:
path = os.path.dirname(file.name)
except AttributeError:
path = os.getcwd()
path = os.path.join(path, os.path.normpath(line[7:].strip()))
self.load_definitions(path, is_resource)
else:
parts = _BLOCK_RE.split(line)
loader = (
self._parsers.get(parts[0], None) if self._parsers else None
)
if loader is None:
raise DefinitionSyntaxError(
"Unknown directive %s" % line, lineno=no
)
try:
loader(ifile)
except DefinitionSyntaxError as ex:
if ex.lineno is None:
ex.lineno = no
raise ex
else:
try:
self.define(Definition.from_string(line, self.non_int_type))
except DefinitionSyntaxError as ex:
if ex.lineno is None:
ex.lineno = no
raise ex
except Exception as ex:
logger.error("In line {}, cannot add '{}' {}".format(no, line, ex))
def _build_cache(self):
"""Build a cache of dimensionality and base units."""
self._cache = RegistryCache()
deps = {
name: definition.reference.keys() if definition.reference else set()
for name, definition in self._units.items()
}
for unit_names in solve_dependencies(deps):
for unit_name in unit_names:
if "[" in unit_name:
continue
parsed_names = self.parse_unit_name(unit_name)
if parsed_names:
prefix, base_name, _ = parsed_names[0]
else:
prefix, base_name = "", unit_name
try:
uc = ParserHelper.from_word(base_name, self.non_int_type)
bu = self._get_root_units(uc)
di = self._get_dimensionality(uc)
self._cache.root_units[uc] = bu
self._cache.dimensionality[uc] = di
if not prefix:
dimeq_set = self._cache.dimensional_equivalents.setdefault(
di, set()
)
dimeq_set.add(self._units[base_name]._name)
except Exception as exc:
logger.warning(f"Could not resolve {unit_name}: {exc!r}")
def get_name(self, name_or_alias, case_sensitive=True):
"""Return the canonical name of a unit.
"""
if name_or_alias == "dimensionless":
return ""
try:
return self._units[name_or_alias]._name
except KeyError:
pass
candidates = self.parse_unit_name(name_or_alias, case_sensitive)
if not candidates:
raise UndefinedUnitError(name_or_alias)
elif len(candidates) == 1:
prefix, unit_name, _ = candidates[0]
else:
logger.warning(
"Parsing {} yield multiple results. "
"Options are: {}".format(name_or_alias, candidates)
)
prefix, unit_name, _ = candidates[0]
if prefix:
name = prefix + unit_name
symbol = self.get_symbol(name)
prefix_def = self._prefixes[prefix]
self._units[name] = UnitDefinition(
name,
symbol,
(),
prefix_def.converter,
self.UnitsContainer({unit_name: 1}),
)
return prefix + unit_name
return unit_name
def get_symbol(self, name_or_alias):
"""Return the preferred alias for a unit.
"""
candidates = self.parse_unit_name(name_or_alias)
if not candidates:
raise UndefinedUnitError(name_or_alias)
elif len(candidates) == 1:
prefix, unit_name, _ = candidates[0]
else:
logger.warning(
"Parsing {0} yield multiple results. "
"Options are: {1!r}".format(name_or_alias, candidates)
)
prefix, unit_name, _ = candidates[0]
return self._prefixes[prefix].symbol + self._units[unit_name].symbol
def _get_symbol(self, name):
return self._units[name].symbol
def get_dimensionality(self, input_units):
"""Convert unit or dict of units or dimensions to a dict of base dimensions
dimensions
"""
# TODO: This should be to_units_container(input_units, self)
# but this tries to reparse and fail for dimensions.
input_units = to_units_container(input_units)
return self._get_dimensionality(input_units)
def _get_dimensionality(self, input_units):
"""Convert a UnitsContainer to base dimensions.
"""
if not input_units:
return self.UnitsContainer()
cache = self._cache.dimensionality
try:
return cache[input_units]
except KeyError:
pass
accumulator = defaultdict(int)
self._get_dimensionality_recurse(input_units, 1, accumulator)
if "[]" in accumulator:
del accumulator["[]"]
dims = self.UnitsContainer({k: v for k, v in accumulator.items() if v != 0})
cache[input_units] = dims
return dims
def _get_dimensionality_recurse(self, ref, exp, accumulator):
for key in ref:
exp2 = exp * ref[key]
if _is_dim(key):
reg = self._dimensions[key]
if reg.is_base:
accumulator[key] += exp2
elif reg.reference is not None:
self._get_dimensionality_recurse(reg.reference, exp2, accumulator)
else:
reg = self._units[self.get_name(key)]
if reg.reference is not None:
self._get_dimensionality_recurse(reg.reference, exp2, accumulator)
def _get_dimensionality_ratio(self, unit1, unit2):
"""Get the exponential ratio between two units, i.e. solve unit2 = unit1**x for x.
Parameters
----------
unit1 : UnitsContainer compatible (str, Unit, UnitsContainer, dict)
first unit
unit2 : UnitsContainer compatible (str, Unit, UnitsContainer, dict)
second unit
Returns
-------
number or None
exponential proportionality or None if the units cannot be converted
"""
# shortcut in case of equal units
if unit1 == unit2:
return 1
dim1, dim2 = (self.get_dimensionality(unit) for unit in (unit1, unit2))
if not dim1 or not dim2 or dim1.keys() != dim2.keys(): # not comparable
return None
ratios = (dim2[key] / val for key, val in dim1.items())
first = next(ratios)
if all(r == first for r in ratios): # all are same, we're good
return first
return None
def get_root_units(self, input_units, check_nonmult=True):
"""Convert unit or dict of units to the root units.
If any unit is non multiplicative and check_converter is True,
then None is returned as the multiplicative factor.
Parameters
----------
input_units : UnitsContainer or str
units
check_nonmult : bool
if True, None will be returned as the
multiplicative factor if a non-multiplicative
units is found in the final Units. (Default value = True)
Returns
-------
Number, pint.Unit
multiplicative factor, base units
"""
input_units = to_units_container(input_units, self)
f, units = self._get_root_units(input_units, check_nonmult)
return f, self.Unit(units)
def _get_root_units(self, input_units, check_nonmult=True):
"""Convert unit or dict of units to the root units.
If any unit is non multiplicative and check_converter is True,
then None is returned as the multiplicative factor.
Parameters
----------
input_units : UnitsContainer or dict
units
check_nonmult : bool
if True, None will be returned as the
multiplicative factor if a non-multiplicative
units is found in the final Units. (Default value = True)
Returns
-------
number, Unit
multiplicative factor, base units
"""
if not input_units:
return 1, self.UnitsContainer()
cache = self._cache.root_units
try:
return cache[input_units]
except KeyError:
pass
accumulators = [1, defaultdict(int)]
self._get_root_units_recurse(input_units, 1, accumulators)
factor = accumulators[0]
units = self.UnitsContainer(
{k: v for k, v in accumulators[1].items() if v != 0}
)
# Check if any of the final units is non multiplicative and return None instead.
if check_nonmult:
if any(not self._units[unit].converter.is_multiplicative for unit in units):
factor = None
cache[input_units] = factor, units
return factor, units
def get_base_units(self, input_units, check_nonmult=True, system=None):
"""Convert unit or dict of units to the base units.
If any unit is non multiplicative and check_converter is True,
then None is returned as the multiplicative factor.
Parameters
----------
input_units : UnitsContainer or str
units
check_nonmult : bool
If True, None will be returned as the multiplicative factor if
non-multiplicative units are found in the final Units.
(Default value = True)
system :
(Default value = None)
Returns
-------
Number, pint.Unit
multiplicative factor, base units
"""
return self.get_root_units(input_units, check_nonmult)
def _get_root_units_recurse(self, ref, exp, accumulators):
for key in ref:
exp2 = exp * ref[key]
key = self.get_name(key)
reg = self._units[key]
if reg.is_base:
accumulators[1][key] += exp2
else:
accumulators[0] *= reg._converter.scale ** exp2
if reg.reference is not None:
self._get_root_units_recurse(reg.reference, exp2, accumulators)
def get_compatible_units(self, input_units, group_or_system=None):
"""
"""
input_units = to_units_container(input_units)
equiv = self._get_compatible_units(input_units, group_or_system)
return frozenset(self.Unit(eq) for eq in equiv)
def _get_compatible_units(self, input_units, group_or_system):
"""
"""
if not input_units:
return frozenset()
src_dim = self._get_dimensionality(input_units)
return self._cache.dimensional_equivalents[src_dim]
def is_compatible_with(self, obj1, obj2, *contexts, **ctx_kwargs):
""" check if the other object is compatible
Parameters
----------
obj1, obj2
The objects to check against each other. Treated as
dimensionless if not a Quantity, Unit or str.
*contexts : str or pint.Context
Contexts to use in the transformation.
**ctx_kwargs :
Values for the Context/s
Returns
-------
bool
"""
if isinstance(obj1, (self.Quantity, self.Unit)):
return obj1.is_compatible_with(obj2, *contexts, **ctx_kwargs)
if isinstance(obj1, str):
return self.parse_expression(obj1).is_compatible_with(
obj2, *contexts, **ctx_kwargs
)
return not isinstance(obj2, (self.Quantity, self.Unit))
def convert(self, value, src, dst, inplace=False):
"""Convert value from some source to destination units.
Parameters
----------
value :
value
src : pint.Quantity or str
source units.
dst : pint.Quantity or str
destination units.
inplace :
(Default value = False)
Returns
-------
type
converted value
"""
src = to_units_container(src, self)
dst = to_units_container(dst, self)
if src == dst:
return value
return self._convert(value, src, dst, inplace)
def _convert(self, value, src, dst, inplace=False, check_dimensionality=True):
"""Convert value from some source to destination units.
Parameters
----------
value :
value
src : UnitsContainer
source units.
dst : UnitsContainer
destination units.
inplace :
(Default value = False)
check_dimensionality :
(Default value = True)
Returns
-------
type
converted value
"""
if check_dimensionality:
src_dim = self._get_dimensionality(src)
dst_dim = self._get_dimensionality(dst)
# If the source and destination dimensionality are different,
# then the conversion cannot be performed.
if src_dim != dst_dim:
raise DimensionalityError(src, dst, src_dim, dst_dim)
# Here src and dst have only multiplicative units left. Thus we can
# convert with a factor.
factor, _ = self._get_root_units(src / dst)
# factor is type float and if our magnitude is type Decimal then
# must first convert to Decimal before we can '*' the values
if isinstance(value, Decimal):
factor = Decimal(str(factor))
elif isinstance(value, Fraction):
factor = Fraction(str(factor))
if inplace:
value *= factor
else:
value = value * factor
return value
def parse_unit_name(self, unit_name, case_sensitive=True):
"""Parse a unit to identify prefix, unit name and suffix
by walking the list of prefix and suffix.
In case of equivalent combinations (e.g. ('kilo', 'gram', '') and
('', 'kilogram', ''), prefer those with prefix.
Parameters
----------
unit_name :
case_sensitive :
(Default value = True)
Returns
-------
tuple of tuples (str, str, str)
all non-equivalent combinations of (prefix, unit name, suffix)
"""
return self._dedup_candidates(
self._parse_unit_name(unit_name, case_sensitive=case_sensitive)
)
def _parse_unit_name(self, unit_name, case_sensitive=True):
"""Helper of parse_unit_name.
"""
stw = unit_name.startswith
edw = unit_name.endswith
for suffix, prefix in itertools.product(self._suffixes, self._prefixes):
if stw(prefix) and edw(suffix):
name = unit_name[len(prefix) :]
if suffix:
name = name[: -len(suffix)]
if len(name) == 1:
continue
if case_sensitive:
if name in self._units:
yield (
self._prefixes[prefix].name,
self._units[name].name,
self._suffixes[suffix],
)
else:
for real_name in self._units_casei.get(name.lower(), ()):
yield (
self._prefixes[prefix].name,
self._units[real_name].name,
self._suffixes[suffix],
)
@staticmethod
def _dedup_candidates(candidates):
"""Helper of parse_unit_name.
Given an iterable of unit triplets (prefix, name, suffix), remove those with
different names but equal value, preferring those with a prefix.
e.g. ('kilo', 'gram', '') and ('', 'kilogram', '')
"""
candidates = dict.fromkeys(candidates) # ordered set
for cp, cu, cs in list(candidates):
assert isinstance(cp, str)
assert isinstance(cu, str)
if cs != "":
raise NotImplementedError("non-empty suffix")
if cp:
candidates.pop(("", cp + cu, ""), None)
return tuple(candidates)
def parse_units(self, input_string, as_delta=None):
"""Parse a units expression and returns a UnitContainer with
the canonical names.
The expression can only contain products, ratios and powers of units.
Parameters
----------
input_string : str
as_delta : bool or None
if the expression has multiple units, the parser will
interpret non multiplicative units as their `delta_` counterparts. (Default value = None)
Returns
-------
"""
for p in self.preprocessors:
input_string = p(input_string)
units = self._parse_units(input_string, as_delta)
return self.Unit(units)
def _parse_units(self, input_string, as_delta=True):
"""Parse a units expression and returns a UnitContainer with
the canonical names.
"""
cache = self._cache.parse_unit
# Issue #1097: it is possible, when a unit was defined while a different context
# was active, that the unit is in self._cache.parse_unit but not in self._units.
# If this is the case, force self._units to be repopulated.
if as_delta and input_string in cache and input_string in self._units:
return cache[input_string]
if not input_string:
return self.UnitsContainer()
# Sanitize input_string with whitespaces.
input_string = input_string.strip()
units = ParserHelper.from_string(input_string, self.non_int_type)
if units.scale != 1:
raise ValueError("Unit expression cannot have a scaling factor.")
ret = {}
many = len(units) > 1
for name in units:
cname = self.get_name(name)
value = units[name]
if not cname:
continue
if as_delta and (many or (not many and value != 1)):
definition = self._units[cname]
if not definition.is_multiplicative:
cname = "delta_" + cname
ret[cname] = value
ret = self.UnitsContainer(ret)
if as_delta:
cache[input_string] = ret
return ret
def _eval_token(self, token, case_sensitive=True, use_decimal=False, **values):
# TODO: remove this code when use_decimal is deprecated
if use_decimal:
raise DeprecationWarning(
"`use_decimal` is deprecated, use `non_int_type` keyword argument when instantiating the registry.\n"
">>> from decimal import Decimal\n"
">>> ureg = UnitRegistry(non_int_type=Decimal)"
)
token_type = token[0]
token_text = token[1]
if token_type == NAME:
if token_text == "dimensionless":
return 1 * self.dimensionless
elif token_text in values:
return self.Quantity(values[token_text])
else:
return self.Quantity(
1,
self.UnitsContainer(
{self.get_name(token_text, case_sensitive=case_sensitive): 1}
),
)
elif token_type == NUMBER:
return ParserHelper.eval_token(token, non_int_type=self.non_int_type)
else:
raise Exception("unknown token type")
def parse_pattern(
self, input_string, pattern, case_sensitive=True, use_decimal=False, many=False
):
"""Parse a string with a given regex pattern and returns result.
Parameters
----------
input_string :
pattern_string:
The regex parse string
case_sensitive :
(Default value = True)
use_decimal :
(Default value = False)
many :
Match many results
(Default value = False)
Returns
-------
"""
if not input_string:
return [] if many else None
# Parse string
pattern = pattern_to_regex(pattern)
matched = re.finditer(pattern, input_string)
# Extract result(s)
results = []
for match in matched:
# Extract units from result
match = match.groupdict()
# Parse units
units = []
for unit, value in match.items():
# Construct measure by multiplying value by unit
units.append(
float(value)
* self.parse_expression(unit, case_sensitive, use_decimal)
)
# Add to results
results.append(units)
# Return first match only
if not many:
return results[0]
return results
def parse_expression(
self, input_string, case_sensitive=True, use_decimal=False, **values
):
"""Parse a mathematical expression including units and return a quantity object.
Numerical constants can be specified as keyword arguments and will take precedence
over the names defined in the registry.
Parameters
----------
input_string :
case_sensitive :
(Default value = True)
use_decimal :
(Default value = False)
**values :
Returns
-------
"""
# TODO: remove this code when use_decimal is deprecated
if use_decimal:
raise DeprecationWarning(
"`use_decimal` is deprecated, use `non_int_type` keyword argument when instantiating the registry.\n"
">>> from decimal import Decimal\n"
">>> ureg = UnitRegistry(non_int_type=Decimal)"
)
if not input_string:
return self.Quantity(1)
for p in self.preprocessors:
input_string = p(input_string)
input_string = string_preprocessor(input_string)
gen = tokenizer(input_string)
return build_eval_tree(gen).evaluate(
lambda x: self._eval_token(x, case_sensitive=case_sensitive, **values)
)
__call__ = parse_expression
class NonMultiplicativeRegistry(BaseRegistry):
"""Handle of non multiplicative units (e.g. Temperature).
Capabilities:
- Register non-multiplicative units and their relations.
- Convert between non-multiplicative units.
Parameters
----------
default_as_delta : bool
If True, non-multiplicative units are interpreted as
their *delta* counterparts in multiplications.
autoconvert_offset_to_baseunit : bool
If True, non-multiplicative units are
converted to base units in multiplications.
"""
def __init__(
self, default_as_delta=True, autoconvert_offset_to_baseunit=False, **kwargs
):
super().__init__(**kwargs)
#: When performing a multiplication of units, interpret
#: non-multiplicative units as their *delta* counterparts.
self.default_as_delta = default_as_delta
# Determines if quantities with offset units are converted to their
# base units on multiplication and division.
self.autoconvert_offset_to_baseunit = autoconvert_offset_to_baseunit
def _parse_units(self, input_string, as_delta=None):
"""
"""
if as_delta is None:
as_delta = self.default_as_delta
return super()._parse_units(input_string, as_delta)
def _define(self, definition):
"""Add unit to the registry.
In addition to what is done by the BaseRegistry,
registers also non-multiplicative units.
Parameters
----------
definition : str or Definition
A dimension, unit or prefix definition.
Returns
-------
Definition, dict, dict
Definition instance, case sensitive unit dict, case insensitive unit dict.
"""
definition, d, di = super()._define(definition)
# define additional units for units with an offset
if getattr(definition.converter, "offset", 0) != 0:
self._define_adder(definition, d, di)
return definition, d, di
def _is_multiplicative(self, u):
if u in self._units:
return self._units[u].is_multiplicative
# If the unit is not in the registry might be because it is not
# registered with its prefixed version.
# TODO: Might be better to register them.
names = self.parse_unit_name(u)
assert len(names) == 1
_, base_name, _ = names[0]
try:
return self._units[base_name].is_multiplicative
except KeyError:
raise UndefinedUnitError(u)
def _validate_and_extract(self, units):
nonmult_units = [
(u, e) for u, e in units.items() if not self._is_multiplicative(u)
]
# Let's validate source offset units
if len(nonmult_units) > 1:
# More than one src offset unit is not allowed
raise ValueError("more than one offset unit.")
elif len(nonmult_units) == 1:
# A single src offset unit is present. Extract it
# But check that:
# - the exponent is 1
# - is not used in multiplicative context
nonmult_unit, exponent = nonmult_units.pop()
if exponent != 1:
raise ValueError("offset units in higher order.")
if len(units) > 1 and not self.autoconvert_offset_to_baseunit:
raise ValueError("offset unit used in multiplicative context.")
return nonmult_unit
return None
def _convert(self, value, src, dst, inplace=False):
"""Convert value from some source to destination units.
In addition to what is done by the BaseRegistry,
converts between non-multiplicative units.
Parameters
----------
value :
value
src : UnitsContainer
source units.
dst : UnitsContainer
destination units.
inplace :
(Default value = False)
Returns
-------
type
converted value
"""
# Conversion needs to consider if non-multiplicative (AKA offset
# units) are involved. Conversion is only possible if src and dst
# have at most one offset unit per dimension. Other rules are applied
# by validate and extract.
try:
src_offset_unit = self._validate_and_extract(src)
except ValueError as ex:
raise DimensionalityError(src, dst, extra_msg=f" - In source units, {ex}")
try:
dst_offset_unit = self._validate_and_extract(dst)
except ValueError as ex:
raise DimensionalityError(
src, dst, extra_msg=f" - In destination units, {ex}"
)
if not (src_offset_unit or dst_offset_unit):
return super()._convert(value, src, dst, inplace)
src_dim = self._get_dimensionality(src)
dst_dim = self._get_dimensionality(dst)
# If the source and destination dimensionality are different,
# then the conversion cannot be performed.
if src_dim != dst_dim:
raise DimensionalityError(src, dst, src_dim, dst_dim)
# clean src from offset units by converting to reference
if src_offset_unit:
value = self._units[src_offset_unit].converter.to_reference(value, inplace)
src = src.remove([src_offset_unit])
# clean dst units from offset units
if dst_offset_unit:
dst = dst.remove([dst_offset_unit])
# Convert non multiplicative units to the dst.
value = super()._convert(value, src, dst, inplace, False)
# Finally convert to offset units specified in destination
if dst_offset_unit:
value = self._units[dst_offset_unit].converter.from_reference(
value, inplace
)
return value
class ContextRegistry(BaseRegistry):
"""Handle of Contexts.
Conversion between units with different dimenstions according
to previously established relations (contexts).
(e.g. in the spectroscopy, conversion between frequency and energy is possible)
Capabilities:
- Register contexts.
- Enable and disable contexts.
- Parse @context directive.
"""
def __init__(self, **kwargs):
# Map context name (string) or abbreviation to context.
self._contexts = {}
# Stores active contexts.
self._active_ctx = ContextChain()
# Map context chain to cache
self._caches = {}
# Map context chain to units override
self._context_units = {}
super().__init__(**kwargs)
# Allow contexts to add override layers to the units
self._units = ChainMap(self._units)
def _register_parsers(self):
super()._register_parsers()
self._register_parser("@context", self._parse_context)
def _parse_context(self, ifile):
try:
self.add_context(
Context.from_lines(
ifile.block_iter(),
self.get_dimensionality,
non_int_type=self.non_int_type,
)
)
except KeyError as e:
raise DefinitionSyntaxError(f"unknown dimension {e} in context")
def add_context(self, context: Context) -> None:
"""Add a context object to the registry.
The context will be accessible by its name and aliases.
Notice that this method will NOT enable the context;
see :meth:`enable_contexts`.
"""
if not context.name:
raise ValueError("Can't add unnamed context to registry")
if context.name in self._contexts:
logger.warning(
"The name %s was already registered for another context.", context.name
)
self._contexts[context.name] = context
for alias in context.aliases:
if alias in self._contexts:
logger.warning(
"The name %s was already registered for another context",
context.name,
)
self._contexts[alias] = context
def remove_context(self, name_or_alias: str) -> Context:
"""Remove a context from the registry and return it.
Notice that this methods will not disable the context;
see :meth:`disable_contexts`.
"""
context = self._contexts[name_or_alias]
del self._contexts[context.name]
for alias in context.aliases:
del self._contexts[alias]
return context
def _build_cache(self) -> None:
super()._build_cache()
self._caches[()] = self._cache
def _switch_context_cache_and_units(self) -> None:
"""If any of the active contexts redefine units, create variant self._cache
and self._units specific to the combination of active contexts.
The next time this method is invoked with the same combination of contexts,
reuse the same variant self._cache and self._units as in the previous time.
"""
del self._units.maps[:-1]
units_overlay = any(ctx.redefinitions for ctx in self._active_ctx.contexts)
if not units_overlay:
# Use the default _cache and _units
self._cache = self._caches[()]
return
key = self._active_ctx.hashable()
try:
self._cache = self._caches[key]
self._units.maps.insert(0, self._context_units[key])
except KeyError:
pass
# First time using this specific combination of contexts and it contains
# unit redefinitions
base_cache = self._caches[()]
self._caches[key] = self._cache = ContextCacheOverlay(base_cache)
self._context_units[key] = units_overlay = {}
self._units.maps.insert(0, units_overlay)
on_redefinition_backup = self._on_redefinition
self._on_redefinition = "ignore"
try:
for ctx in reversed(self._active_ctx.contexts):
for definition in ctx.redefinitions:
self._redefine(definition)
finally:
self._on_redefinition = on_redefinition_backup
def _redefine(self, definition: UnitDefinition) -> None:
"""Redefine a unit from a context
"""
# Find original definition in the UnitRegistry
candidates = self.parse_unit_name(definition.name)
if not candidates:
raise UndefinedUnitError(definition.name)
candidates_no_prefix = [c for c in candidates if not c[0]]
if not candidates_no_prefix:
raise ValueError(f"Can't redefine a unit with a prefix: {definition.name}")
assert len(candidates_no_prefix) == 1
_, name, _ = candidates_no_prefix[0]
try:
basedef = self._units[name]
except KeyError:
raise UndefinedUnitError(name)
# Rebuild definition as a variant of the base
if basedef.is_base:
raise ValueError("Can't redefine a base unit to a derived one")
dims_old = self._get_dimensionality(basedef.reference)
dims_new = self._get_dimensionality(definition.reference)
if dims_old != dims_new:
raise ValueError(
f"Can't change dimensionality of {basedef.name} "
f"from {dims_old} to {dims_new} in a context"
)
# Do not modify in place the original definition, as (1) the context may
# be shared by other registries, and (2) it would alter the cache key
definition = UnitDefinition(
name=basedef.name,
symbol=basedef.symbol,
aliases=basedef.aliases,
is_base=False,
reference=definition.reference,
converter=definition.converter,
)
# Write into the context-specific self._units.maps[0] and self._cache.root_units
self.define(definition)
def enable_contexts(self, *names_or_contexts, **kwargs) -> None:
"""Enable contexts provided by name or by object.
Parameters
----------
*names_or_contexts :
one or more contexts or context names/aliases
**kwargs :
keyword arguments for the context(s)
Examples
--------
See :meth:`context`
"""
# If present, copy the defaults from the containing contexts
if self._active_ctx.defaults:
kwargs = dict(self._active_ctx.defaults, **kwargs)
# For each name, we first find the corresponding context
ctxs = [
self._contexts[name] if isinstance(name, str) else name
for name in names_or_contexts
]
# Check if the contexts have been checked first, if not we make sure
# that dimensions are expressed in terms of base dimensions.
for ctx in ctxs:
if ctx.checked:
continue
funcs_copy = dict(ctx.funcs)
for (src, dst), func in funcs_copy.items():
src_ = self._get_dimensionality(src)
dst_ = self._get_dimensionality(dst)
if src != src_ or dst != dst_:
ctx.remove_transformation(src, dst)
ctx.add_transformation(src_, dst_, func)
ctx.checked = True
# and create a new one with the new defaults.
ctxs = tuple(Context.from_context(ctx, **kwargs) for ctx in ctxs)
# Finally we add them to the active context.
self._active_ctx.insert_contexts(*ctxs)
self._switch_context_cache_and_units()
def disable_contexts(self, n: int = None) -> None:
"""Disable the last n enabled contexts.
Parameters
----------
n : int
Number of contexts to disable. Default: disable all contexts.
"""
self._active_ctx.remove_contexts(n)
self._switch_context_cache_and_units()
@contextmanager
def context(self, *names, **kwargs):
"""Used as a context manager, this function enables to activate a context
which is removed after usage.
Parameters
----------
*names :
name(s) of the context(s).
**kwargs :
keyword arguments for the contexts.
Examples
--------
Context can be called by their name:
>>> import pint
>>> ureg = pint.UnitRegistry()
>>> ureg.add_context(pint.Context('one'))
>>> ureg.add_context(pint.Context('two'))
>>> with ureg.context('one'):
... pass
If a context has an argument, you can specify its value as a keyword argument:
>>> with ureg.context('one', n=1):
... pass
Multiple contexts can be entered in single call:
>>> with ureg.context('one', 'two', n=1):
... pass
Or nested allowing you to give different values to the same keyword argument:
>>> with ureg.context('one', n=1):
... with ureg.context('two', n=2):
... pass
A nested context inherits the defaults from the containing context:
>>> with ureg.context('one', n=1):
... # Here n takes the value of the outer context
... with ureg.context('two'):
... pass
"""
# Enable the contexts.
self.enable_contexts(*names, **kwargs)
try:
# After adding the context and rebuilding the graph, the registry
# is ready to use.
yield self
finally:
# Upon leaving the with statement,
# the added contexts are removed from the active one.
self.disable_contexts(len(names))
def with_context(self, name, **kwargs):
"""Decorator to wrap a function call in a Pint context.
Use it to ensure that a certain context is active when
calling a function::
Parameters
----------
name :
name of the context.
**kwargs :
keyword arguments for the context
Returns
-------
callable
the wrapped function.
Example
-------
>>> @ureg.with_context('sp')
... def my_cool_fun(wavelength):
... print('This wavelength is equivalent to: %s', wavelength.to('terahertz'))
"""
def decorator(func):
assigned = tuple(
attr for attr in functools.WRAPPER_ASSIGNMENTS if hasattr(func, attr)
)
updated = tuple(
attr for attr in functools.WRAPPER_UPDATES if hasattr(func, attr)
)
@functools.wraps(func, assigned=assigned, updated=updated)
def wrapper(*values, **wrapper_kwargs):
with self.context(name, **kwargs):
return func(*values, **wrapper_kwargs)
return wrapper
return decorator
def _convert(self, value, src, dst, inplace=False):
"""Convert value from some source to destination units.
In addition to what is done by the BaseRegistry,
converts between units with different dimensions by following
transformation rules defined in the context.
Parameters
----------
value :
value
src : UnitsContainer
source units.
dst : UnitsContainer
destination units.
inplace :
(Default value = False)
Returns
-------
callable
converted value
"""
# If there is an active context, we look for a path connecting source and
# destination dimensionality. If it exists, we transform the source value
# by applying sequentially each transformation of the path.
if self._active_ctx:
src_dim = self._get_dimensionality(src)
dst_dim = self._get_dimensionality(dst)
path = find_shortest_path(self._active_ctx.graph, src_dim, dst_dim)
if path:
src = self.Quantity(value, src)
for a, b in zip(path[:-1], path[1:]):
src = self._active_ctx.transform(a, b, self, src)
value, src = src._magnitude, src._units
return super()._convert(value, src, dst, inplace)
def _get_compatible_units(self, input_units, group_or_system):
src_dim = self._get_dimensionality(input_units)
ret = super()._get_compatible_units(input_units, group_or_system)
if self._active_ctx:
ret = ret.copy() # Do not alter self._cache
nodes = find_connected_nodes(self._active_ctx.graph, src_dim)
if nodes:
for node in nodes:
ret |= self._cache.dimensional_equivalents[node]
return ret
class SystemRegistry(BaseRegistry):
"""Handle of Systems and Groups.
Conversion between units with different dimenstions according
to previously established relations (contexts).
(e.g. in the spectroscopy, conversion between frequency and energy is possible)
Capabilities:
- Register systems and groups.
- List systems
- Get or get the default system.
- Parse @system and @group directive.
"""
def __init__(self, system=None, **kwargs):
super().__init__(**kwargs)
#: Map system name to system.
#: :type: dict[ str | System]
self._systems = {}
#: Maps dimensionality (UnitsContainer) to Dimensionality (UnitsContainer)
self._base_units_cache = dict()
#: Map group name to group.
#: :type: dict[ str | Group]
self._groups = {}
self._groups["root"] = self.Group("root")
self._default_system = system
def _init_dynamic_classes(self):
super()._init_dynamic_classes()
self.Group = systems.build_group_class(self)
self.System = systems.build_system_class(self)
def _after_init(self):
"""Invoked at the end of ``__init__``.
- Create default group and add all orphan units to it
- Set default system
"""
super()._after_init()
#: Copy units not defined in any group to the default group
if "group" in self._defaults:
grp = self.get_group(self._defaults["group"], True)
group_units = frozenset(
[
member
for group in self._groups.values()
if group.name != "root"
for member in group.members
]
)
all_units = self.get_group("root", False).members
grp.add_units(*(all_units - group_units))
#: System name to be used by default.
self._default_system = self._default_system or self._defaults.get(
"system", None
)
def _register_parsers(self):
super()._register_parsers()
self._register_parser("@group", self._parse_group)
self._register_parser("@system", self._parse_system)
def _parse_group(self, ifile):
self.Group.from_lines(ifile.block_iter(), self.define, self.non_int_type)
def _parse_system(self, ifile):
self.System.from_lines(
ifile.block_iter(), self.get_root_units, self.non_int_type
)
def get_group(self, name, create_if_needed=True):
"""Return a Group.
Parameters
----------
name : str
Name of the group to be
create_if_needed : bool
If True, create a group if not found. If False, raise an Exception.
(Default value = True)
Returns
-------
type
Group
"""
if name in self._groups:
return self._groups[name]
if not create_if_needed:
raise ValueError("Unkown group %s" % name)
return self.Group(name)
@property
def sys(self):
return systems.Lister(self._systems)
@property
def default_system(self):
return self._default_system
@default_system.setter
def default_system(self, name):
if name:
if name not in self._systems:
raise ValueError("Unknown system %s" % name)
self._base_units_cache = {}
self._default_system = name
def get_system(self, name, create_if_needed=True):
"""Return a Group.
Parameters
----------
name : str
Name of the group to be
create_if_needed : bool
If True, create a group if not found. If False, raise an Exception.
(Default value = True)
Returns
-------
type
System
"""
if name in self._systems:
return self._systems[name]
if not create_if_needed:
raise ValueError("Unkown system %s" % name)
return self.System(name)
def _define(self, definition):
# In addition to the what is done by the BaseRegistry,
# this adds all units to the `root` group.
definition, d, di = super()._define(definition)
if isinstance(definition, UnitDefinition):
# We add all units to the root group
self.get_group("root").add_units(definition.name)
return definition, d, di
def get_base_units(self, input_units, check_nonmult=True, system=None):
"""Convert unit or dict of units to the base units.
If any unit is non multiplicative and check_converter is True,
then None is returned as the multiplicative factor.
Unlike BaseRegistry, in this registry root_units might be different
from base_units
Parameters
----------
input_units : UnitsContainer or str
units
check_nonmult : bool
if True, None will be returned as the
multiplicative factor if a non-multiplicative
units is found in the final Units. (Default value = True)
system :
(Default value = None)
Returns
-------
type
multiplicative factor, base units
"""
input_units = to_units_container(input_units)
f, units = self._get_base_units(input_units, check_nonmult, system)
return f, self.Unit(units)
def _get_base_units(self, input_units, check_nonmult=True, system=None):
if system is None:
system = self._default_system
# The cache is only done for check_nonmult=True and the current system.
if (
check_nonmult
and system == self._default_system
and input_units in self._base_units_cache
):
return self._base_units_cache[input_units]
factor, units = self.get_root_units(input_units, check_nonmult)
if not system:
return factor, units
# This will not be necessary after integration with the registry
# as it has a UnitsContainer intermediate
units = to_units_container(units, self)
destination_units = self.UnitsContainer()
bu = self.get_system(system, False).base_units
for unit, value in units.items():
if unit in bu:
new_unit = bu[unit]
new_unit = to_units_container(new_unit, self)
destination_units *= new_unit ** value
else:
destination_units *= self.UnitsContainer({unit: value})
base_factor = self.convert(factor, units, destination_units)
if check_nonmult:
self._base_units_cache[input_units] = base_factor, destination_units
return base_factor, destination_units
def _get_compatible_units(self, input_units, group_or_system):
if group_or_system is None:
group_or_system = self._default_system
ret = super()._get_compatible_units(input_units, group_or_system)
if group_or_system:
if group_or_system in self._systems:
members = self._systems[group_or_system].members
elif group_or_system in self._groups:
members = self._groups[group_or_system].members
else:
raise ValueError(
"Unknown Group o System with name '%s'" % group_or_system
)
return frozenset(ret & members)
return ret
class UnitRegistry(SystemRegistry, ContextRegistry, NonMultiplicativeRegistry):
"""The unit registry stores the definitions and relationships between units.
Parameters
----------
filename :
path of the units definition file to load or line-iterable object.
Empty to load the default definition file.
None to leave the UnitRegistry empty.
force_ndarray : bool
convert any input, scalar or not to a numpy.ndarray.
force_ndarray_like : bool
convert all inputs other than duck arrays to a numpy.ndarray.
default_as_delta :
In the context of a multiplication of units, interpret
non-multiplicative units as their *delta* counterparts.
autoconvert_offset_to_baseunit :
If True converts offset units in quantites are
converted to their base units in multiplicative
context. If False no conversion happens.
on_redefinition : str
action to take in case a unit is redefined.
'warn', 'raise', 'ignore'
auto_reduce_dimensions :
If True, reduce dimensionality on appropriate operations.
preprocessors :
list of callables which are iteratively ran on any input expression
or unit string
fmt_locale :
locale identifier string, used in `format_babel`. Default to None
"""
def __init__(
self,
filename="",
force_ndarray=False,
force_ndarray_like=False,
default_as_delta=True,
autoconvert_offset_to_baseunit=False,
on_redefinition="warn",
system=None,
auto_reduce_dimensions=False,
preprocessors=None,
fmt_locale=None,
non_int_type=float,
):
super().__init__(
filename=filename,
force_ndarray=force_ndarray,
force_ndarray_like=force_ndarray_like,
on_redefinition=on_redefinition,
default_as_delta=default_as_delta,
autoconvert_offset_to_baseunit=autoconvert_offset_to_baseunit,
system=system,
auto_reduce_dimensions=auto_reduce_dimensions,
preprocessors=preprocessors,
fmt_locale=fmt_locale,
non_int_type=non_int_type,
)
def pi_theorem(self, quantities):
"""Builds dimensionless quantities using the Buckingham π theorem
Parameters
----------
quantities : dict
mapping between variable name and units
Returns
-------
list
a list of dimensionless quantities expressed as dicts
"""
return pi_theorem(quantities, self)
def setup_matplotlib(self, enable=True):
"""Set up handlers for matplotlib's unit support.
Parameters
----------
enable : bool
whether support should be enabled or disabled (Default value = True)
"""
# Delays importing matplotlib until it's actually requested
from .matplotlib import setup_matplotlib_handlers
setup_matplotlib_handlers(self, enable)
wraps = registry_helpers.wraps
check = registry_helpers.check
class LazyRegistry:
def __init__(self, args=None, kwargs=None):
self.__dict__["params"] = args or (), kwargs or {}
def __init(self):
args, kwargs = self.__dict__["params"]
kwargs["on_redefinition"] = "raise"
self.__class__ = UnitRegistry
self.__init__(*args, **kwargs)
self._after_init()
def __getattr__(self, item):
if item == "_on_redefinition":
return "raise"
self.__init()
return getattr(self, item)
def __setattr__(self, key, value):
if key == "__class__":
super().__setattr__(key, value)
else:
self.__init()
setattr(self, key, value)
def __getitem__(self, item):
self.__init()
return self[item]
def __call__(self, *args, **kwargs):
self.__init()
return self(*args, **kwargs)