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"""Miscellaneous core utilities."""
from __future__ import annotations
from abc import ABCMeta
from collections.abc import Sequence
import enum
from functools import cache
import importlib
import sys
import threading
import traceback
from typing import TYPE_CHECKING
from typing import TypeVar
import warnings
import numpy as np
from typing_extensions import Self
if TYPE_CHECKING:
from typing import Any
from pyvista._typing_core import ArrayLike
from pyvista._typing_core import NumpyArray
from pyvista._typing_core import VectorLike
_T = TypeVar('_T')
T = TypeVar('T', bound='AnnotatedIntEnum')
def assert_empty_kwargs(**kwargs) -> bool:
"""Assert that all keyword arguments have been used (internal helper).
If any keyword arguments are passed, a ``TypeError`` is raised.
Parameters
----------
**kwargs : dict
Keyword arguments passed to the function.
Returns
-------
bool
``True`` when successful.
Raises
------
TypeError
If any keyword arguments are passed, a ``TypeError`` is raised.
"""
n = len(kwargs)
if n == 0:
return True
caller = sys._getframe(1).f_code.co_name
keys = list(kwargs.keys())
bad_arguments = ', '.join([f'"{key}"' for key in keys])
grammar = 'is an invalid keyword argument' if n == 1 else 'are invalid keyword arguments'
message = f'{bad_arguments} {grammar} for `{caller}`'
raise TypeError(message)
def check_valid_vector(point: VectorLike[float], name: str = '') -> None:
"""Check if a vector contains three components.
Parameters
----------
point : VectorLike[float]
Input vector to check. Must be an iterable with exactly three components.
name : str, optional
Name to use in the error messages. If not provided, "Vector" will be used.
Raises
------
TypeError
If the input is not an iterable.
ValueError
If the input does not have exactly three components.
"""
if not isinstance(point, (Sequence, np.ndarray)):
msg = f'{name} must be a length three iterable of floats.'
raise TypeError(msg)
if len(point) != 3:
if name == '':
name = 'Vector'
msg = f'{name} must be a length three iterable of floats.'
raise ValueError(msg)
def abstract_class(cls_): # noqa: ANN001, ANN201 # numpydoc ignore=RT01
"""Decorate a class, overriding __new__.
Preventing a class from being instantiated similar to abc.ABCMeta
but does not require an abstract method.
Parameters
----------
cls_ : type
The class to be decorated as abstract.
"""
def __new__(cls, *args, **kwargs): # noqa: ANN001, ANN202, ARG001, N807
if cls is cls_:
msg = f'{cls.__name__} is an abstract class and may not be instantiated.'
raise TypeError(msg)
return super(cls_, cls).__new__(cls)
cls_.__new__ = __new__
return cls_
class AnnotatedIntEnum(int, enum.Enum):
"""Annotated enum type."""
annotation: str
def __new__(cls, value: int, annotation: str) -> Self:
"""Initialize."""
obj = int.__new__(cls, value)
obj._value_ = value
obj.annotation = annotation
return obj
@classmethod
def from_str(cls, input_str: str) -> Self:
"""Create an enum member from a string.
Parameters
----------
input_str : str
The string representation of the annotation for the enum member.
Returns
-------
AnnotatedIntEnum
The enum member with the specified annotation.
Raises
------
ValueError
If there is no enum member with the specified annotation.
"""
for value in cls:
if value.annotation.lower() == input_str.lower():
return value
msg = f'{cls.__name__} has no value matching {input_str}'
raise ValueError(msg)
@classmethod
def from_any(cls, value: AnnotatedIntEnum | int | str) -> Self:
"""Create an enum member from a string, int, etc.
Parameters
----------
value : int | str | AnnotatedIntEnum
The value used to determine the corresponding enum member.
Returns
-------
AnnotatedIntEnum
The enum member matching the specified value.
Raises
------
ValueError
If there is no enum member matching the specified value.
"""
if isinstance(value, cls):
return value
elif isinstance(value, int):
return cls(value) # type: ignore[call-arg]
elif isinstance(value, str):
return cls.from_str(value)
else:
msg = f'Invalid type {type(value)} for class {cls.__name__}.' # type: ignore[unreachable]
raise TypeError(msg)
@cache
def has_module(module_name: str) -> bool:
"""Return if a module can be imported.
Parameters
----------
module_name : str
Name of the module to check.
Returns
-------
bool
``True`` if the module can be imported, otherwise ``False``.
"""
module_spec = importlib.util.find_spec(module_name)
return module_spec is not None
def try_callback(func, *args) -> None: # noqa: ANN001
"""Wrap a given callback in a try statement.
Parameters
----------
func : callable
Callable object.
*args
Any arguments.
"""
try:
func(*args)
except Exception: # noqa: BLE001 # pragma: no cover
etype, exc, tb = sys.exc_info()
stack = traceback.extract_tb(tb)[1:]
formatted_exception = 'Encountered issue in callback (most recent call last):\n' + ''.join(
traceback.format_list(stack) + traceback.format_exception_only(etype, exc),
).rstrip('\n')
warnings.warn(formatted_exception)
def threaded(fn): # noqa: ANN001, ANN201
"""Call a function using a thread.
Parameters
----------
fn : callable
Callable object.
Returns
-------
function
Wrapped function.
"""
def wrapper(*args, **kwargs): # noqa: ANN202
thread = threading.Thread(target=fn, args=args, kwargs=kwargs)
thread.start()
return thread
return wrapper
class conditional_decorator: # noqa: N801
"""Conditional decorator for methods.
Parameters
----------
dec : callable
The decorator to be applied conditionally.
condition : bool
Condition to match. If ``True``, the decorator is applied. If
``False``, the function is returned unchanged.
"""
def __init__(self, dec, condition) -> None: # noqa: ANN001
"""Initialize."""
self.decorator = dec
self.condition = condition
def __call__(self, func): # noqa: ANN001, ANN204
"""Call the decorated function if condition is matched."""
if not self.condition:
# Return the function unchanged, not decorated.
return func
return self.decorator(func)
def _check_range(value: float, rng: Sequence[float], parm_name: str) -> None:
"""Check if a parameter is within a range."""
if value < rng[0] or value > rng[1]:
msg = (
f'The value {float(value)} for `{parm_name}` is outside the '
f'acceptable range {tuple(rng)}.'
)
raise ValueError(msg)
class _AutoFreezeMeta(type):
"""Metaclass to automatically freeze a class when called."""
def __call__(cls: type[_T], *args, **kwargs) -> _T:
obj = super().__call__(*args, **kwargs) # type: ignore[misc]
obj._no_new_attributes(cls)
return obj
class _AutoFreezeABCMeta(_AutoFreezeMeta, ABCMeta):
"""Metaclass to combine automatic attribute freezing with ABC support."""
class _NoNewAttrMixin(metaclass=_AutoFreezeABCMeta):
"""Mixin to prevent adding new attributes.
This class is mainly used to prevent users from setting the wrong attributes on an
object. It freezes the attributes when called and prevents setting new ones via
"normal" methods like ``obj.foo = 42``.
"""
def _no_new_attributes(self, this_class: type) -> None:
"""Prevent setting additional attributes."""
object.__setattr__(self, '__frozen', True)
object.__setattr__(self, '__frozen_by_class', this_class)
def __setattr__(self, key: str, value: Any) -> None:
"""Prevent adding new attributes to classes using "normal" methods."""
if not key.startswith('_'):
# Check if this class froze itself. Any frozen state already set by parent classes,
# e.g. by calling super().__init__(), will be ignored. This allows subclasses to set
# attributes during init without being affect by a parent class init.
frozen = self.__dict__.get('__frozen', False)
frozen_by = self.__dict__.get('__frozen_by_class', None)
if (
frozen
and frozen_by is type(self)
and not (key in type(self).__dict__ or hasattr(self, key))
):
from pyvista import PyVistaAttributeError # noqa: PLC0415
msg = (
f'Attribute {key!r} does not exist and cannot be added to class '
f'{self.__class__.__name__!r}\nUse `pv.set_new_attribute` to set new '
f'attributes or consider setting a private variable (with `_` prefix) instead.'
)
raise PyVistaAttributeError(msg)
object.__setattr__(self, key, value)
def set_new_attribute(obj: object, name: str, value: Any) -> None:
"""Set a new attribute for this object.
Python allows arbitrarily setting new attributes on objects at any time,
but PyVista's classes do not allow this. If an attribute is not part of
PyVista's API, an ``AttributeError`` is normally raised when attempting
to set it.
Use :func:`set_new_attribute` to override this and set a new attribute anyway.
Examples
--------
Set a new custom attribute on a mesh.
>>> import pyvista as pv
>>> mesh = pv.PolyData()
>>> pv.set_new_attribute(mesh, 'foo', 42)
>>> mesh.foo
42
.. versionadded:: 0.46
"""
if hasattr(obj, name):
from pyvista import PyVistaAttributeError # noqa: PLC0415
msg = (
f'Attribute {name!r} already exists. '
'`set_new_attribute` can only be used for setting NEW attributes.'
)
raise PyVistaAttributeError(msg)
object.__setattr__(obj, name, value)
def _reciprocal(
x: ArrayLike[float], tol: float = 1e-8, value_if_division_by_zero: float = 0.0
) -> NumpyArray[float]:
"""Compute the element-wise reciprocal and avoid division by zero.
The reciprocal of elements with an absolute value less than a
specified tolerance has the value specified by ``default_if_div_by_zero``.
Parameters
----------
x : array_like
Input array.
tol : float
Tolerance value. Values smaller than ``tol`` have a reciprocal of zero.
value_if_division_by_zero : float
Default value given to values less than ``tol``, i.e. the value given if division
by zero is detected.
Returns
-------
numpy.ndarray
Element-wise reciprocal of the input.
"""
x = np.array(x)
x = x if np.issubdtype(x.dtype, np.floating) else x.astype(float)
zero = np.abs(x) < tol
x[~zero] = np.reciprocal(x[~zero])
x[zero] = value_if_division_by_zero
return x
class _classproperty(property): # noqa: N801
"""Read-only class property decorator.
Use this decaorator as an alternative to chaining `@classmethod`
and `@property` which is deprecated.
See:
- https://docs.python.org/library/functions.html#classmethod
- https://stackoverflow.com/a/13624858
Examples
--------
>>> from pyvista.core.utilities.misc import _classproperty
>>> class Foo:
... @_classproperty
... def bar(cls): ...
"""
def __get__(self: property, owner_self: Any, owner_cls: type | None = None) -> Any:
return self.fget(owner_cls) # type: ignore[misc]
class _NameMixin:
"""Add a 'name' property to a class.
.. versionadded:: 0.45
"""
@property
def name(self) -> str: # numpydoc ignore=RT01
"""Get or set the unique name identifier used by PyVista."""
if not hasattr(self, '_name') or self._name is None:
address = (
self.GetAddressAsString('')
if hasattr(self, 'GetAddressAsString')
else hex(id(self))
)
return f'{type(self).__name__}({address})'
return self._name
@name.setter
def name(self, value: str) -> None:
if not value:
msg = 'Name must be truthy.'
raise ValueError(msg)
object.__setattr__(self, '_name', str(value))
class _BoundsSizeMixin:
@property
def bounds_size(self) -> tuple[float, float, float]:
"""Return the size of each axis of the object's bounding box.
.. versionadded:: 0.46
Returns
-------
tuple[float, float, float]
Size of each x-y-z axis.
Examples
--------
Get the size of a cube. The cube has edge lengths af ``(1.0, 1.0, 1.0)``
by default.
>>> import pyvista as pv
>>> mesh = pv.Cube()
>>> mesh.bounds_size
(1.0, 1.0, 1.0)
"""
bounds = self.bounds # type: ignore[attr-defined]
return (
bounds.x_max - bounds.x_min,
bounds.y_max - bounds.y_min,
bounds.z_max - bounds.z_min,
)
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