How to use none_shall_pass method in Robotframework

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checks.py

Source:checks.py

1"""2Decorator for checking input/output arguments of functions.3"""4__all__ = [5 "check_values",6 "check_units",7 "check_relativistic",8 "CheckBase",9 "CheckUnits",10 "CheckValues",11]12import collections13import functools14import inspect15import numpy as np16import warnings17from astropy import units as u18from astropy.constants import c19from functools import reduce20from typing import Any, Dict, List, Tuple, Union21from plasmapy.utils.decorators.helpers import preserve_signature22from plasmapy.utils.exceptions import (23 PlasmaPyWarning,24 RelativityError,25 RelativityWarning,26)27try:28 from astropy.units.equivalencies import Equivalency29except ImportError:30 # TODO: remove once we have dependency Astropy >= 3.2.131 # astropy defined the Equivalency class in v3.2.132 class Equivalency:33 pass34class CheckBase:35 """36 Base class for 'Check' decorator classes.37 Parameters38 ----------39 checks_on_return40 specified checks on the return of the wrapped function41 **checks42 specified checks on the input arguments of the wrapped function43 """44 def __init__(self, checks_on_return=None, **checks):45 self._checks = checks46 if checks_on_return is not None:47 self._checks["checks_on_return"] = checks_on_return48 @property49 def checks(self):50 """51 Requested checks on the decorated function's input arguments52 and/or return.53 """54 return self._checks55class CheckValues(CheckBase):56 """57 A decorator class to 'check' -- limit/control -- the values of input and return58 arguments to a function or method.59 Parameters60 ----------61 checks_on_return: Dict[str, bool]62 Specifications for value checks on the return of the function being wrapped.63 (see `check values`_ for valid specifications)64 **checks: Dict[str, Dict[str, bool]]65 Specifications for value checks on the input arguments of the function66 being wrapped. Each keyword argument in `checks` is the name of a function67 argument to be checked and the keyword value contains the value check68 specifications.69 .. _`check values`:70 The value check specifications are defined within a dictionary containing71 the keys defined below. If the dictionary is empty or omitting keys,72 then the default value will be assumed for the missing keys.73 ================ ======= ================================================74 Key Type Description75 ================ ======= ================================================76 can_be_negative `bool` [DEFAULT `True`] values can be negative77 can_be_complex `bool` [DEFAULT `False`] values can be complex numbers78 can_be_inf `bool` [DEFAULT `True`] values can be :data:`~numpy.inf`79 can_be_nan `bool` [DEFAULT `True`] values can be :data:`~numpy.nan`80 none_shall_pass `bool` [DEFAULT `False`] values can be a python `None`81 ================ ======= ================================================82 Notes83 -----84 * Checking of function arguments `*args` and `**kwargs` is not supported.85 Examples86 --------87 .. code-block:: python88 from plasmapy.utils.decorators.checks import CheckValues89 @CheckValues(arg1={'can_be_negative': False, 'can_be_nan': False},90 arg2={'can_be_inf': False},91 checks_on_return={'none_shall_pass': True)92 def foo(arg1, arg2):93 return None94 # on a method95 class Foo:96 @CheckValues(arg1={'can_be_negative': False, 'can_be_nan': False},97 arg2={'can_be_inf': False},98 checks_on_return={'none_shall_pass': True)99 def bar(self, arg1, arg2):100 return None101 """102 #: Default values for the possible 'check' keys.103 # To add a new check to the class, the following needs to be done:104 # 1. Add a key & default value to the `__check_defaults` dictionary105 # 2. Add a corresponding if-statement to method `_check_value`106 #107 __check_defaults = {108 "can_be_negative": True,109 "can_be_complex": False,110 "can_be_inf": True,111 "can_be_nan": True,112 "none_shall_pass": False,113 }114 def __init__(115 self, checks_on_return: Dict[str, bool] = None, **checks: Dict[str, bool]116 ):117 super().__init__(checks_on_return=checks_on_return, **checks)118 def __call__(self, f):119 """120 Parameters121 ----------122 f123 Function to be wrapped124 Returns125 -------126 function127 wrapped function of `f`128 """129 self.f = f130 wrapped_sign = inspect.signature(f)131 @preserve_signature132 @functools.wraps(f)133 def wrapper(*args, **kwargs):134 # map args and kwargs to function parameters135 bound_args = wrapped_sign.bind(*args, **kwargs)136 bound_args.apply_defaults()137 # get checks138 checks = self._get_value_checks(bound_args)139 # check input arguments140 for arg_name in checks:141 # skip check of output/return142 if arg_name == "checks_on_return":143 continue144 # check argument145 self._check_value(146 bound_args.arguments[arg_name], arg_name, checks[arg_name]147 )148 # call function149 _return = f(**bound_args.arguments)150 # check function return151 if "checks_on_return" in checks:152 self._check_value(153 _return, "checks_on_return", checks["checks_on_return"]154 )155 return _return156 return wrapper157 def _get_value_checks(158 self, bound_args: inspect.BoundArguments159 ) -> Dict[str, Dict[str, bool]]:160 """161 Review :attr:`checks` and function bound arguments to build a complete 'checks'162 dictionary. If a check key is omitted from the argument checks, then a default163 value is assumed (see `check values`_).164 Parameters165 ----------166 bound_args: :class:`inspect.BoundArguments`167 arguments passed into the function being wrapped168 .. code-block:: python169 bound_args = inspect.signature(f).bind(*args, **kwargs)170 Returns171 -------172 Dict[str, Dict[str, bool]]173 A complete 'checks' dictionary for checking function input arguments174 and return.175 """176 # initialize validation dictionary177 out_checks = {}178 # Iterate through function bound arguments + return and build `out_checks:179 #180 # artificially add "return" to parameters181 things_to_check = bound_args.signature.parameters.copy()182 things_to_check["checks_on_return"] = inspect.Parameter(183 "checks_on_return",184 inspect.Parameter.POSITIONAL_ONLY,185 annotation=bound_args.signature.return_annotation,186 )187 for param in things_to_check.values():188 # variable arguments are NOT checked189 # e.g. in foo(x, y, *args, d=None, **kwargs) variable arguments190 # *args and **kwargs will NOT be checked191 #192 if param.kind in (193 inspect.Parameter.VAR_KEYWORD,194 inspect.Parameter.VAR_POSITIONAL,195 ):196 continue197 # grab the checks dictionary for the desired parameter198 try:199 param_in_checks = self.checks[param.name]200 except KeyError:201 # checks for parameter not specified202 continue203 # build `out_checks`204 # read checks and/or apply defaults values205 out_checks[param.name] = {}206 for v_name, v_default in self.__check_defaults.items():207 try:208 out_checks[param.name][v_name] = param_in_checks.get(209 v_name, v_default210 )211 except AttributeError:212 # for the case that checks are defined for an argument,213 # but is NOT a dictionary214 # (e.g. CheckValues(x=u.cm) ... this scenario could happen215 # during subclassing)216 out_checks[param.name][v_name] = v_default217 # Does `self.checks` indicate arguments not used by f?218 missing_params = [219 param for param in set(self.checks.keys()) - set(out_checks.keys())220 ]221 if len(missing_params) > 0:222 params_str = ", ".join(missing_params)223 warnings.warn(224 PlasmaPyWarning(225 f"Expected to value check parameters {params_str} but they "226 f"are missing from the call to {self.f.__name__}"227 )228 )229 return out_checks230 def _check_value(self, arg, arg_name: str, arg_checks: Dict[str, bool]):231 """232 Perform checks `arg_checks` on function argument `arg`.233 Parameters234 ----------235 arg236 The argument to be checked237 arg_name: str238 The name of the argument to be checked239 arg_checks: Dict[str, bool]240 The requested checks for the argument241 Raises242 ------243 ValueError244 raised if a check fails245 """246 if arg_name == "checks_on_return":247 valueerror_msg = f"The return value "248 else:249 valueerror_msg = f"The argument '{arg_name}' "250 valueerror_msg += f"to function {self.f.__name__}() can not contain"251 # check values252 # * 'none_shall_pass' always needs to be checked first253 ckeys = list(self.__check_defaults.keys())254 ckeys.remove("none_shall_pass")255 ckeys = ("none_shall_pass",) + tuple(ckeys)256 for ckey in ckeys:257 if ckey == "none_shall_pass":258 if arg is None and arg_checks[ckey]:259 break260 elif arg is None:261 raise ValueError(f"{valueerror_msg} Nones.")262 elif ckey == "can_be_negative":263 if not arg_checks[ckey]:264 # Allow NaNs through without raising a warning265 with np.errstate(invalid="ignore"):266 isneg = np.any(arg < 0)267 if isneg:268 raise ValueError(f"{valueerror_msg} negative numbers.")269 elif ckey == "can_be_complex":270 if not arg_checks[ckey] and np.any(np.iscomplexobj(arg)):271 raise ValueError(f"{valueerror_msg} complex numbers.")272 elif ckey == "can_be_inf":273 if not arg_checks[ckey] and np.any(np.isinf(arg)):274 raise ValueError(f"{valueerror_msg} infs.")275 elif ckey == "can_be_nan":276 if not arg_checks["can_be_nan"] and np.any(np.isnan(arg)):277 raise ValueError(f"{valueerror_msg} NaNs.")278class CheckUnits(CheckBase):279 """280 A decorator class to 'check' -- limit/control -- the units of input and return281 arguments to a function or method.282 Parameters283 ----------284 checks_on_return: list of astropy :mod:`~astropy.units` or dict of unit specifications285 Specifications for unit checks on the return of the function being wrapped.286 (see `check units`_ for valid specifications)287 **checks: list of astropy :mod:`~astropy.units` or dict of unit specifications288 Specifications for unit checks on the input arguments of the function289 being wrapped. Each keyword argument in `checks` is the name of a function290 argument to be checked and the keyword value contains the unit check291 specifications.292 .. _`check units`:293 Unit checks can be defined by passing one of the astropy294 :mod:`~astropy.units`, a list of astropy units, or a dictionary containing295 the keys defined below. Units can also be defined with function296 annotations, but must be consistent with decorator `**checks` arguments if297 used concurrently. If a key is omitted, then the default value will be assumed.298 ====================== ======= ================================================299 Key Type Description300 ====================== ======= ================================================301 units list of desired astropy :mod:`~astropy.units`302 equivalencies | [DEFAULT `None`] A list of equivalent pairs to303 try if304 | the units are not directly convertible.305 | (see :mod:`~astropy.units.equivalencies`,306 and/or `astropy equivalencies`_)307 pass_equivalent_units `bool` | [DEFAULT `False`] allow equivalent units308 | to pass309 ====================== ======= ================================================310 Notes311 -----312 * Checking of function arguments `*args` and `**kwargs` is not supported.313 * Decorator does NOT perform any unit conversions.314 * If it is desired that `None` values do not raise errors or warnings, then315 include `None` in the list of units or as a default value for the function316 argument.317 * If units are not specified in `checks`, then the decorator will attempt318 to identify desired units by examining the function annotations.319 Examples320 --------321 Define units with decorator parameters::322 import astropy.units as u323 from plasmapy.utils.decorators import CheckUnits324 @CheckUnits(arg1={'units': u.cm},325 arg2=u.cm,326 checks_on_return=[u.cm, u.km])327 def foo(arg1, arg2):328 return arg1 + arg2329 # or on a method330 class Foo:331 @CheckUnits(arg1={'units': u.cm},332 arg2=u.cm,333 checks_on_return=[u.cm, u.km])334 def bar(self, arg1, arg2):335 return arg1 + arg2336 Define units with function annotations::337 import astropy.units as u338 from plasmapy.utils.decorators import CheckUnits339 @CheckUnits()340 def foo(arg1: u.cm, arg2: u.cm) -> u.cm:341 return arg1 + arg2342 # or on a method343 class Foo:344 @CheckUnits()345 def bar(self, arg1: u.cm, arg2: u.cm) -> u.cm:346 return arg1 + arg2347 Allow `None` values to pass, on input and output::348 import astropy.units as u349 from plasmapy.utils.decorators import CheckUnits350 @CheckUnits(checks_on_return=[u.cm, None])351 def foo(arg1: u.cm = None):352 return arg1353 Allow return values to have equivalent units::354 import astropy.units as u355 from plasmapy.utils.decorators import CheckUnits356 @CheckUnits(arg1={'units': u.cm},357 checks_on_return={'units': u.km,358 'pass_equivalent_units': True})359 def foo(arg1):360 return arg1361 Allow equivalent units to pass with specified equivalencies::362 import astropy.units as u363 from plasmapy.utils.decorators import CheckUnits364 @CheckUnits(arg1={'units': u.K,365 'equivalencies': u.temperature_energy(),366 'pass_equivalent_units': True})367 def foo(arg1):368 return arg1369 .. _astropy equivalencies:370 https://docs.astropy.org/en/stable/units/equivalencies.html371 """372 #: Default values for the possible 'check' keys.373 # To add a new check the the class, the following needs to be done:374 # 1. Add a key & default value to the `__check_defaults` dictionary375 # 2. Add a corresponding conditioning statement to `_get_unit_checks`376 # 3. Add a corresponding behavior to `_check_unit`377 #378 __check_defaults = {379 "units": None,380 "equivalencies": None,381 "pass_equivalent_units": False,382 "none_shall_pass": False,383 }384 def __init__(385 self,386 checks_on_return: Union[u.Unit, List[u.Unit], Dict[str, Any]] = None,387 **checks: Union[u.Unit, List[u.Unit], Dict[str, Any]],388 ):389 super().__init__(checks_on_return=checks_on_return, **checks)390 def __call__(self, f):391 """392 Parameters393 ----------394 f395 Function to be wrapped396 Returns397 -------398 function399 wrapped function of `f`400 """401 self.f = f402 wrapped_sign = inspect.signature(f)403 @preserve_signature404 @functools.wraps(f)405 def wrapper(*args, **kwargs):406 # combine args and kwargs into dictionary407 bound_args = wrapped_sign.bind(*args, **kwargs)408 bound_args.apply_defaults()409 # get checks410 checks = self._get_unit_checks(bound_args)411 # check (input) argument units412 for arg_name in checks:413 # skip check of output/return414 if arg_name == "checks_on_return":415 continue416 # check argument417 self._check_unit(418 bound_args.arguments[arg_name], arg_name, checks[arg_name]419 )420 # call function421 _return = f(**bound_args.arguments)422 # check output423 if "checks_on_return" in checks:424 self._check_unit(425 _return, "checks_on_return", checks["checks_on_return"]426 )427 return _return428 return wrapper429 def _get_unit_checks(430 self, bound_args: inspect.BoundArguments431 ) -> Dict[str, Dict[str, Any]]:432 """433 Review :attr:`checks` and function bound arguments to build a complete 'checks'434 dictionary. If a check key is omitted from the argument checks, then a default435 value is assumed (see `check units`_)436 Parameters437 ----------438 bound_args: :class:`inspect.BoundArguments`439 arguments passed into the function being wrapped440 .. code-block:: python441 bound_args = inspect.signature(f).bind(*args, **kwargs)442 Returns443 -------444 Dict[str, Dict[str, Any]]445 A complete 'checks' dictionary for checking function input arguments446 and return.447 """448 # initialize validation dictionary449 out_checks = {}450 # Iterate through function bound arguments + return and build `out_checks`:451 #452 # artificially add "return" to parameters453 things_to_check = bound_args.signature.parameters.copy()454 things_to_check["checks_on_return"] = inspect.Parameter(455 "checks_on_return",456 inspect.Parameter.POSITIONAL_ONLY,457 annotation=bound_args.signature.return_annotation,458 )459 for param in things_to_check.values():460 # variable arguments are NOT checked461 # e.g. in foo(x, y, *args, d=None, **kwargs) variable arguments462 # *args and **kwargs will NOT be checked463 #464 if param.kind in (465 inspect.Parameter.VAR_KEYWORD,466 inspect.Parameter.VAR_POSITIONAL,467 ):468 continue469 # grab the checks dictionary for the desired parameter470 try:471 param_checks = self.checks[param.name]472 except KeyError:473 param_checks = None474 # -- Determine target units `_units` --475 # target units can be defined in one of three ways (in476 # preferential order):477 # 1. direct keyword pass-through478 # i.e. CheckUnits(x=u.cm)479 # CheckUnits(x=[u.cm, u.s])480 # 2. keyword pass-through via dictionary definition481 # i.e. CheckUnits(x={'units': u.cm})482 # CheckUnits(x={'units': [u.cm, u.s]})483 # 3. function annotations484 #485 # * if option (3) is used simultaneously with option (1) or (2), then486 # checks defined by (3) must be consistent with checks from (1) or (2)487 # to avoid raising an error.488 # * if None is included in the units list, then None values are allowed489 #490 _none_shall_pass = False491 _units = None492 _units_are_from_anno = False493 if param_checks is not None:494 # checks for argument were defined with decorator495 try:496 _units = param_checks["units"]497 except TypeError:498 # if checks is NOT None and is NOT a dictionary, then assume499 # only units were specified500 # e.g. CheckUnits(x=u.cm)501 #502 _units = param_checks503 except KeyError:504 # if checks does NOT have 'units' but is still a dictionary,505 # then other check conditions may have been specified and the506 # user is relying on function annotations to define desired507 # units508 _units = None509 # If no units have been specified by decorator checks, then look for510 # function annotations.511 #512 # Reconcile units specified by decorator checks and function annotations513 _units_anno = None514 if param.annotation is not inspect.Parameter.empty:515 # unit annotations defined516 _units_anno = param.annotation517 if _units is None and _units_anno is None and param_checks is None:518 # no checks specified and no unit annotations defined519 continue520 elif _units is None and _units_anno is None:521 # checks specified, but NO unit checks522 msg = f"No astropy.units specified for "523 if param.name == "checks_on_return":524 msg += f"return value "525 else:526 msg += f"argument {param.name} "527 msg += f"of function {self.f.__name__}()."528 raise ValueError(msg)529 elif _units is None:530 _units = _units_anno531 _units_are_from_anno = True532 _units_anno = None533 # Ensure `_units` is an iterable534 if not isinstance(_units, collections.abc.Iterable):535 _units = [_units]536 if not isinstance(_units_anno, collections.abc.Iterable):537 _units_anno = [_units_anno]538 # Is None allowed?539 if None in _units or param.default is None:540 _none_shall_pass = True541 # Remove Nones542 if None in _units:543 _units = [t for t in _units if t is not None]544 if None in _units_anno:545 _units_anno = [t for t in _units_anno if t is not None]546 # ensure all _units are astropy.units.Unit or physical types &547 # define 'units' for unit checks &548 # define 'none_shall_pass' check549 _units = self._condition_target_units(550 _units, from_annotations=_units_are_from_anno551 )552 _units_anno = self._condition_target_units(553 _units_anno, from_annotations=True554 )555 if not all(_u in _units for _u in _units_anno):556 raise ValueError(557 f"For argument '{param.name}', "558 f"annotation units ({_units_anno}) are not included in the units "559 f"specified by decorator arguments ({_units}). Use either "560 f"decorator arguments or function annotations to defined unit "561 f"types, or make sure annotation specifications match decorator "562 f"argument specifications."563 )564 if len(_units) == 0 and len(_units_anno) == 0 and param_checks is None:565 # annotations did not specify units566 continue567 elif len(_units) == 0 and len(_units_anno) == 0:568 # checks specified, but NO unit checks569 msg = f"No astropy.units specified for "570 if param.name == "checks_on_return":571 msg += f"return value "572 else:573 msg += f"argument {param.name} "574 msg += f"of function {self.f.__name__}()."575 raise ValueError(msg)576 out_checks[param.name] = {577 "units": _units,578 "none_shall_pass": _none_shall_pass,579 }580 # -- Determine target equivalencies --581 # Unit equivalences can be defined by:582 # 1. keyword pass-through via dictionary definition583 # e.g. CheckUnits(x={'units': u.C,584 # 'equivalencies': u.temperature})585 #586 # initialize equivalencies587 try:588 _equivs = param_checks["equivalencies"]589 except (KeyError, TypeError):590 _equivs = self.__check_defaults["equivalencies"]591 # ensure equivalences are properly formatted592 if _equivs is None or _equivs == [None]:593 _equivs = None594 elif isinstance(_equivs, Equivalency):595 pass596 elif isinstance(_equivs, (list, tuple)):597 # flatten list to non-list elements598 if isinstance(_equivs, tuple):599 _equivs = [_equivs]600 else:601 _equivs = self._flatten_equivalencies_list(_equivs)602 # ensure passed equivalencies list is structured properly603 # [(), ...]604 # or [Equivalency(), ...]605 #606 # * All equivalencies must be a list of 2, 3, or 4 element tuples607 # structured like...608 # (from_unit, to_unit, forward_func, backward_func)609 #610 if all(isinstance(el, Equivalency) for el in _equivs):611 _equivs = reduce(lambda x, y: x + y, _equivs)612 else:613 _equivs = self._normalize_equivalencies(_equivs)614 out_checks[param.name]["equivalencies"] = _equivs615 # -- Determine if equivalent units pass --616 try:617 peu = param_checks.get(618 "pass_equivalent_units",619 self.__check_defaults["pass_equivalent_units"],620 )621 except (AttributeError, TypeError):622 peu = self.__check_defaults["pass_equivalent_units"]623 out_checks[param.name]["pass_equivalent_units"] = peu624 # Does `self.checks` indicate arguments not used by f?625 missing_params = [626 param for param in set(self.checks.keys()) - set(out_checks.keys())627 ]628 if len(missing_params) > 0:629 params_str = ", ".join(missing_params)630 warnings.warn(631 PlasmaPyWarning(632 f"Expected to unit check parameters {params_str} but they "633 f"are missing from the call to {self.f.__name__}"634 )635 )636 return out_checks637 def _check_unit(self, arg, arg_name: str, arg_checks: Dict[str, Any]):638 """639 Perform unit checks `arg_checks` on function argument `arg`.640 Parameters641 ----------642 arg643 The argument to be checked644 arg_name: str645 The name of the argument to be checked646 arg_checks: Dict[str, Any]647 The requested checks for the argument648 Raises649 ------650 ValueError651 If `arg` is `None` when `arg_checks['none_shall_pass']=False`652 TypeError653 If `arg` does not have `units`654 :class:`astropy.units.UnitTypeError`655 If the units of `arg` do not satisfy conditions of `arg_checks`656 """657 arg, unit, equiv, err = self._check_unit_core(arg, arg_name, arg_checks)658 if err is not None:659 raise err660 def _check_unit_core(661 self, arg, arg_name: str, arg_checks: Dict[str, Any]662 ) -> Tuple[663 Union[None, u.Quantity],664 Union[None, u.Unit],665 Union[None, List[Any]],666 Union[None, Exception],667 ]:668 """669 Determines if `arg` passes unit checks `arg_checks` and if the units of670 `arg` is equivalent to any units specified in `arg_checks`.671 Parameters672 ----------673 arg674 The argument to be checked675 arg_name: str676 The name of the argument to be checked677 arg_checks: Dict[str, Any]678 The requested checks for the argument679 Returns680 -------681 (`arg`, `unit`, `equivalencies`, `error`)682 * `arg` is the original input argument `arg` or `None` if unit683 checks fail684 * `unit` is the identified astropy :mod:`~astropy.units` that `arg`685 can be converted to or `None` if none exist686 * `equivalencies` is the astropy :mod:`~astropy.units.equivalencies`687 used for the unit conversion or `None`688 * `error` is the `Exception` associated with the failed unit checks689 or `None` for successful unit checks690 """691 # initialize str for error messages692 if arg_name == "checks_on_return":693 err_msg = f"The return value "694 else:695 err_msg = f"The argument '{arg_name}' "696 err_msg += f"to function {self.f.__name__}()"697 # initialize ValueError message698 valueerror_msg = f"{err_msg} can not contain"699 # initialize TypeError message700 typeerror_msg = f"{err_msg} should be an astropy Quantity with "701 if len(arg_checks["units"]) == 1:702 typeerror_msg += f"the following unit: {arg_checks['units'][0]}"703 else:704 typeerror_msg += "one of the following units: "705 for unit in arg_checks["units"]:706 typeerror_msg += str(unit)707 if unit != arg_checks["units"][-1]:708 typeerror_msg += ", "709 if arg_checks["none_shall_pass"]:710 typeerror_msg += "or None "711 # pass Nones if allowed712 if arg is None:713 if arg_checks["none_shall_pass"]:714 return arg, None, None, None715 else:716 return None, None, None, ValueError(f"{valueerror_msg} Nones")717 # check units718 in_acceptable_units = []719 equiv = arg_checks["equivalencies"]720 for unit in arg_checks["units"]:721 try:722 in_acceptable_units.append(723 arg.unit.is_equivalent(unit, equivalencies=equiv)724 )725 except AttributeError:726 if hasattr(arg, "unit"):727 err_specifier = (728 "a 'unit' attribute without an 'is_equivalent' method"729 )730 else:731 err_specifier = "no 'unit' attribute"732 msg = (733 f"{err_msg} has {err_specifier}. "734 f"Use an astropy Quantity instead."735 )736 return None, None, None, TypeError(msg)737 # How many acceptable units?738 nacceptable = np.count_nonzero(in_acceptable_units)739 unit = None740 equiv = None741 err = None742 if nacceptable == 0:743 # NO equivalent units744 arg = None745 err = u.UnitTypeError(typeerror_msg)746 else:747 # is there an exact match?748 units_arr = np.array(arg_checks["units"])749 units_equal_mask = np.equal(units_arr, arg.unit)750 units_mask = np.logical_and(units_equal_mask, in_acceptable_units)751 if np.count_nonzero(units_mask) == 1:752 # matched exactly to a desired unit753 unit = units_arr[units_mask][0]754 equiv = arg_checks["equivalencies"]755 elif nacceptable == 1:756 # there is a match to 1 equivalent unit757 unit = units_arr[in_acceptable_units][0]758 equiv = arg_checks["equivalencies"]759 if not arg_checks["pass_equivalent_units"]:760 err = u.UnitTypeError(typeerror_msg)761 elif arg_checks["pass_equivalent_units"]:762 # there is a match to more than one equivalent units763 pass764 else:765 # there is a match to more than 1 equivalent units766 arg = None767 err = u.UnitTypeError(typeerror_msg)768 return arg, unit, equiv, err769 @staticmethod770 def _condition_target_units(targets: List, from_annotations: bool = False):771 """772 From a list of target units (either as a string or astropy773 :class:`~astropy.units.Unit` objects), return a list of conditioned774 :class:`~astropy.units.Unit` objects.775 Parameters776 ----------777 targets: list of target units778 list of units (either as a string or :class:`~astropy.units.Unit`)779 to be conditioned into astropy :class:`~astropy.units.Unit` objects780 from_annotations: bool781 (Default `False`) Indicates if `targets` originated from function/method782 annotations versus decorator input arguments.783 Returns784 -------785 list:786 list of `targets` converted into astropy787 :class:`~astropy.units.Unit` objects788 Raises789 ------790 TypeError791 If `target` is not a valid type for :class:`~astropy.units.Unit` when792 `from_annotations == True`,793 ValueError794 If a `target` is a valid unit type but not a valid value for795 :class:`~astropy.units.Unit`.796 """797 # Note: this method does not allow for astropy physical types. This is798 # done because we expect all use cases of CheckUnits to define the799 # exact units desired.800 #801 allowed_units = []802 for target in targets:803 try:804 target_unit = u.Unit(target)805 allowed_units.append(target_unit)806 except TypeError as err:807 # not a unit type808 if not from_annotations:809 raise err810 continue811 return allowed_units812 @staticmethod813 def _normalize_equivalencies(equivalencies):814 """815 Normalizes equivalencies to ensure each is in a 4-tuple form::816 (from_unit, to_unit, forward_func, backward_func)817 `forward_func` maps `from_unit` into `to_unit` and `backward_func` does818 the reverse.819 Parameters820 ----------821 equivalencies: list of equivalent pairs822 list of astropy :mod:`~astropy.units.equivalencies` to be normalized823 Raises824 ------825 ValueError826 if an equivalency can not be interpreted827 Notes828 -----829 * the code here was copied and modified from830 :func:`astropy.units.core._normalize_equivalencies` from AstroPy831 version 3.2.3832 * this will work on both the old style list equivalencies (pre AstroPy v3.2.1)833 and the modern equivalencies defined with the834 :class:`~astropy.units.equivalencies.Equivalency` class835 """836 if equivalencies is None:837 return []838 normalized = []839 for i, equiv in enumerate(equivalencies):840 if len(equiv) == 2:841 from_unit, to_unit = equiv842 a = b = lambda x: x843 elif len(equiv) == 3:844 from_unit, to_unit, a = equiv845 b = a846 elif len(equiv) == 4:847 from_unit, to_unit, a, b = equiv848 else:849 raise ValueError(f"Invalid equivalence entry {i}: {equiv!r}")850 if not (851 from_unit is u.Unit(from_unit)852 and (to_unit is None or to_unit is u.Unit(to_unit))853 and callable(a)854 and callable(b)855 ):856 raise ValueError(f"Invalid equivalence entry {i}: {equiv!r}")857 normalized.append((from_unit, to_unit, a, b))858 return normalized859 def _flatten_equivalencies_list(self, elist):860 """861 Given a list of equivalencies, flatten out any sub-element lists862 Parameters863 ----------864 elist: list865 list of astropy :mod:`~astropy.units.equivalencies` to be flattened866 Returns867 -------868 list869 a flattened list of astropy :mod:`~astropy.units.equivalencies`870 """871 new_list = []872 for el in elist:873 if not isinstance(el, list):874 new_list.append(el)875 else:876 new_list.extend(self._flatten_equivalencies_list(el))877 return new_list878def check_units(879 func=None, checks_on_return: Dict[str, Any] = None, **checks: Dict[str, Any]880):881 """882 A decorator to 'check' -- limit/control -- the units of input and return883 arguments to a function or method.884 Parameters885 ----------886 func:887 The function to be decorated888 checks_on_return: list of astropy :mod:`~astropy.units` or dict of unit specifications889 Specifications for unit checks on the return of the function being wrapped.890 (see `check units`_ for valid specifications)891 **checks: list of astropy :mod:`~astropy.units` or dict of unit specifications892 Specifications for unit checks on the input arguments of the function893 being wrapped. Each keyword argument in `checks` is the name of a function894 argument to be checked and the keyword value contains the unit check895 specifications.896 .. _`check units`:897 Unit checks can be defined by passing one of the astropy898 :mod:`~astropy.units`, a list of astropy units, or a dictionary containing899 the keys defined below. Units can also be defined with function900 annotations, but must be consistent with decorator `**checks` arguments if901 used concurrently. If a key is omitted, then the default value will be assumed.902 ====================== ======= ================================================903 Key Type Description904 ====================== ======= ================================================905 units list of desired astropy :mod:`~astropy.units`906 equivalencies | [DEFAULT `None`] A list of equivalent pairs to907 try if908 | the units are not directly convertible.909 | (see :mod:`~astropy.units.equivalencies`,910 and/or `astropy equivalencies`_)911 pass_equivalent_units `bool` | [DEFAULT `False`] allow equivalent units912 | to pass913 ====================== ======= ================================================914 Notes915 -----916 * Checking of function arguments `*args` and `**kwargs` is not supported.917 * Decorator does NOT perform any unit conversions, look to918 :func:`~plasmapy.utils.decorators.validate_quantities` if that functionality is919 desired.920 * If it is desired that `None` values do not raise errors or warnings, then921 include `None` in the list of units or as a default value for the function922 argument.923 * If units are not specified in `checks`, then the decorator will attempt924 to identify desired units by examining the function annotations.925 * Full functionality is defined by the class :class:`CheckUnits`.926 Examples927 --------928 Define units with decorator parameters::929 import astropy.units as u930 from plasmapy.utils.decorators import check_units931 @check_units(arg1={'units': u.cm},932 arg2=u.cm,933 checks_on_return=[u.cm, u.km])934 def foo(arg1, arg2):935 return arg1 + arg2936 # or on a method937 class Foo:938 @check_units(arg1={'units': u.cm},939 arg2=u.cm,940 checks_on_return=[u.cm, u.km])941 def bar(self, arg1, arg2):942 return arg1 + arg2943 Define units with function annotations::944 import astropy.units as u945 from plasmapy.utils.decorators import check_units946 @check_units947 def foo(arg1: u.cm, arg2: u.cm) -> u.cm:948 return arg1 + arg2949 # or on a method950 class Foo:951 @check_units952 def bar(self, arg1: u.cm, arg2: u.cm) -> u.cm:953 return arg1 + arg2954 Allow `None` values to pass::955 import astropy.units as u956 from plasmapy.utils.decorators import check_units957 @check_units(checks_on_return=[u.cm, None])958 def foo(arg1: u.cm = None):959 return arg1960 Allow return values to have equivalent units::961 import astropy.units as u962 from plasmapy.utils.decorators import check_units963 @check_units(arg1={'units': u.cm},964 checks_on_return={'units': u.km,965 'pass_equivalent_units': True})966 def foo(arg1):967 return arg1968 Allow equivalent units to pass with specified equivalencies::969 import astropy.units as u970 from plasmapy.utils.decorators import check_units971 @check_units(arg1={'units': u.K,972 'equivalencies': u.temperature(),973 'pass_equivalent_units': True})974 def foo(arg1):975 return arg1976 .. _astropy equivalencies:977 https://docs.astropy.org/en/stable/units/equivalencies.html978 """979 if checks_on_return is not None:980 checks["checks_on_return"] = checks_on_return981 if func is not None:982 # `check_units` called as a function983 return CheckUnits(**checks)(func)984 else:985 # `check_units` called as a decorator "sugar-syntax"986 return CheckUnits(**checks)987def check_values(988 func=None, checks_on_return: Dict[str, bool] = None, **checks: Dict[str, bool]989):990 """991 A decorator to 'check' -- limit/control -- the values of input and return992 arguments to a function or method.993 Parameters994 ----------995 func:996 The function to be decorated997 checks_on_return: Dict[str, bool]998 Specifications for value checks on the return of the function being wrapped.999 (see `check values`_ for valid specifications)1000 **checks: Dict[str, Dict[str, bool]]1001 Specifications for value checks on the input arguments of the function1002 being wrapped. Each keyword argument in `checks` is the name of a function1003 argument to be checked and the keyword value contains the value check1004 specifications.1005 .. _`check values`:1006 The value check specifications are defined within a dictionary containing1007 the keys defined below. If the dictionary is empty or omitting keys,1008 then the default value will be assumed for the missing keys.1009 ================ ======= ================================================1010 Key Type Description1011 ================ ======= ================================================1012 can_be_negative `bool` [DEFAULT `True`] values can be negative1013 can_be_complex `bool` [DEFAULT `False`] values can be complex numbers1014 can_be_inf `bool` [DEFAULT `True`] values can be :data:`~numpy.inf`1015 can_be_nan `bool` [DEFAULT `True`] values can be :data:`~numpy.nan`1016 none_shall_pass `bool` [DEFAULT `False`] values can be a python `None`1017 ================ ======= ================================================1018 Notes1019 -----1020 * Checking of function arguments `*args` and `**kwargs` is not supported.1021 * Full functionality is defined by the class :class:`CheckValues`.1022 Examples1023 --------1024 .. code-block:: python1025 from plasmapy.utils.decorators import check_values1026 @check_values(arg1={'can_be_negative': False, 'can_be_nan': False},1027 arg2={'can_be_inf': False},1028 checks_on_return={'none_shall_pass': True)1029 def foo(arg1, arg2):1030 return None1031 # on a method1032 class Foo:1033 @check_values(arg1={'can_be_negative': False, 'can_be_nan': False},1034 arg2={'can_be_inf': False},1035 checks_on_return={'none_shall_pass': True)1036 def bar(self, arg1, arg2):1037 return None1038 """1039 if checks_on_return is not None:1040 checks["checks_on_return"] = checks_on_return1041 if func is not None:1042 # `check_values` called as a function1043 return CheckValues(**checks)(func)1044 else:1045 # `check_values` called as a decorator "sugar-syntax"1046 return CheckValues(**checks)1047def check_relativistic(func=None, betafrac=0.05):1048 r"""1049 Warns or raises an exception when the output of the decorated1050 function is greater than `betafrac` times the speed of light.1051 Parameters1052 ----------1053 func : `function`, optional1054 The function to decorate.1055 betafrac : float, optional1056 The minimum fraction of the speed of light that will raise a1057 `~plasmapy.utils.RelativityWarning`. Defaults to 5%.1058 Returns1059 -------1060 function1061 Decorated function.1062 Raises1063 ------1064 TypeError1065 If `V` is not a `~astropy.units.Quantity`.1066 ~astropy.units.UnitConversionError1067 If `V` is not in units of velocity.1068 ValueError1069 If `V` contains any `~numpy.nan` values.1070 ~plasmapy.utils.exceptions.RelativityError1071 If `V` is greater than or equal to the speed of light.1072 Warns1073 -----1074 : `~plasmapy.utils.exceptions.RelativityWarning`1075 If `V` is greater than or equal to `betafrac` times the speed of light,1076 but less than the speed of light.1077 Examples1078 --------1079 >>> from astropy import units as u1080 >>> @check_relativistic1081 ... def speed():1082 ... return 1 * u.m / u.s1083 Passing in a custom `betafrac`:1084 >>> @check_relativistic(betafrac=0.01)1085 ... def speed():1086 ... return 1 * u.m / u.s1087 """1088 def decorator(f):1089 @preserve_signature1090 @functools.wraps(f)1091 def wrapper(*args, **kwargs):1092 return_ = f(*args, **kwargs)1093 _check_relativistic(return_, f.__name__, betafrac=betafrac)1094 return return_1095 return wrapper1096 if func:1097 return decorator(func)1098 return decorator1099def _check_relativistic(V, funcname, betafrac=0.05):1100 r"""1101 Warn or raise error for relativistic or superrelativistic1102 velocities.1103 Parameters1104 ----------1105 V : ~astropy.units.Quantity1106 A velocity.1107 funcname : str1108 The name of the original function to be printed in the error1109 messages.1110 betafrac : float, optional1111 The minimum fraction of the speed of light that will generate1112 a warning. Defaults to 5%.1113 Raises1114 ------1115 TypeError1116 If `V` is not a `~astropy.units.Quantity`.1117 ~astropy.units.UnitConversionError1118 If `V` is not in units of velocity.1119 ValueError1120 If `V` contains any `~numpy.nan` values.1121 RelativityError1122 If `V` is greater than or equal to the speed of light.1123 Warns1124 -----1125 ~plasmapy.utils.RelativityWarning1126 If `V` is greater than or equal to the specified fraction of the1127 speed of light.1128 Examples1129 --------1130 >>> from astropy import units as u1131 >>> _check_relativistic(1*u.m/u.s, 'function_calling_this')1132 """1133 # TODO: Replace `funcname` with func.__name__?1134 errmsg = "V must be a Quantity with units of velocity in _check_relativistic"1135 if not isinstance(V, u.Quantity):1136 raise TypeError(errmsg)1137 try:1138 V_over_c = (V / c).to_value(u.dimensionless_unscaled)1139 except Exception:1140 raise u.UnitConversionError(errmsg)1141 beta = np.max(np.abs((V_over_c)))1142 if beta == np.inf:1143 raise RelativityError(f"{funcname} is yielding an infinite velocity.")1144 elif beta >= 1:1145 raise RelativityError(1146 f"{funcname} is yielding a velocity that is {str(round(beta, 3))} "1147 f"times the speed of light."1148 )1149 elif beta >= betafrac:1150 warnings.warn(1151 f"{funcname} is yielding a velocity that is "1152 f"{str(round(beta * 100, 3))}% of the speed of "1153 f"light. Relativistic effects may be important.",1154 RelativityWarning,...

test_checks.py

Source:test_checks.py

1"""2Tests for 'check` decorators (i.e. decorators that only check objects but do not3change them).4"""5import inspect6import numpy as np7import pytest8from astropy import units as u9from astropy.constants import c10from types import LambdaType11from typing import Any, Dict12from unittest import mock13from plasmapy.utils.decorators.checks import (14 _check_relativistic,15 check_relativistic,16 check_units,17 check_values,18 CheckBase,19 CheckUnits,20 CheckValues,21)22from plasmapy.utils.exceptions import (23 PlasmaPyWarning,24 RelativityError,25 RelativityWarning,26)27# ----------------------------------------------------------------------------------------28# Test Decorator class `CheckBase`29# ----------------------------------------------------------------------------------------30class TestCheckBase:31 """32 Test for decorator class :class:`~plasmapy.utils.decorators.checks.CheckBase`.33 """34 def test_for_members(self):35 assert hasattr(CheckUnits, "checks")36 def test_checks(self):37 _cases = [38 {"input": (None, {"x": 1, "y": 2}), "output": {"x": 1, "y": 2}},39 {40 "input": (6, {"x": 1, "y": 2}),41 "output": {"x": 1, "y": 2, "checks_on_return": 6},42 },43 ]44 for case in _cases:45 cb = CheckBase(checks_on_return=case["input"][0], **case["input"][1])46 assert cb.checks == case["output"]47# ----------------------------------------------------------------------------------------48# Test Decorator class `CheckValues` and decorator `check_values`49# ----------------------------------------------------------------------------------------50class TestCheckUnits:51 """52 Tests for decorator :func:`~plasmapy.utils.decorators.checks.check_units` and53 decorator class :class:`~plasmapy.utils.decorators.checks.CheckUnits`.54 """55 check_defaults = CheckUnits._CheckUnits__check_defaults # type: Dict[str, Any]56 @staticmethod57 def foo_no_anno(x, y):58 return x + y59 @staticmethod60 def foo_partial_anno(x: u.Quantity, y: u.cm) -> u.Quantity:61 return x.value + y.value62 @staticmethod63 def foo_return_anno(x, y) -> u.um:64 return x.value + y.value65 @staticmethod66 def foo_stars(x: u.Quantity, *args, y=3 * u.cm, **kwargs):67 return x.value + y.value68 @staticmethod69 def foo_with_none(x: u.Quantity, y: u.cm = None):70 return x.value + y.value71 def test_inheritance(self):72 assert issubclass(CheckUnits, CheckBase)73 def test_cu_default_check_values(self):74 """Test the default check dictionary for CheckUnits."""75 cu = CheckUnits()76 assert hasattr(cu, "_CheckUnits__check_defaults")77 assert isinstance(cu._CheckUnits__check_defaults, dict)78 _defaults = [79 ("units", None),80 ("equivalencies", None),81 ("pass_equivalent_units", False),82 ("none_shall_pass", False),83 ]84 for key, val in _defaults:85 assert cu._CheckUnits__check_defaults[key] == val86 def test_cu_method__flatten_equivalencies_list(self):87 assert hasattr(CheckUnits, "_flatten_equivalencies_list")88 cu = CheckUnits()89 pairs = [([1, 2, 4], [1, 2, 4]), ([1, 2, (3, 4), [5, 6]], [1, 2, (3, 4), 5, 6])]90 for pair in pairs:91 assert cu._flatten_equivalencies_list(pair[0]) == pair[1]92 def test_cu_method__condition_target_units(self):93 """Test method `CheckUnits._condition_target_units`."""94 assert hasattr(CheckUnits, "_condition_target_units")95 cu = CheckUnits()96 targets = ["cm", u.km, u.Quantity, float]97 conditioned_targets = [u.cm, u.km]98 with pytest.raises(TypeError):99 cu._condition_target_units(targets)100 assert (101 cu._condition_target_units(targets, from_annotations=True)102 == conditioned_targets103 )104 with pytest.raises(ValueError):105 cu._condition_target_units(["five"])106 def test_cu_method__normalize_equivalencies(self):107 """Test method `CheckUnits._normalize_equivalencies`."""108 assert hasattr(CheckUnits, "_normalize_equivalencies")109 cu = CheckUnits()110 assert cu._normalize_equivalencies(None) == []111 # 2 element equivalency112 norme = cu._normalize_equivalencies([(u.cm, u.cm)])113 assert len(norme) == 1114 assert isinstance(norme[0], tuple)115 assert len(norme[0]) == 4116 assert norme[0][0] == norme[0][1]117 assert norme[0][2] == norme[0][3]118 assert isinstance(norme[0][2], LambdaType)119 assert norme[0][1] == norme[0][2](norme[0][0])120 assert norme[0][0] == norme[0][3](norme[0][1])121 # 3 element equivalency122 norme = cu._normalize_equivalencies([(u.cm, u.cm, lambda x: x)])123 assert len(norme) == 1124 assert isinstance(norme[0], tuple)125 assert len(norme[0]) == 4126 assert norme[0][0] == norme[0][1]127 assert norme[0][2] == norme[0][3]128 assert isinstance(norme[0][2], LambdaType)129 assert norme[0][1] == norme[0][2](norme[0][0])130 assert norme[0][0] == norme[0][3](norme[0][1])131 # 3 element equivalency132 norme = cu._normalize_equivalencies(133 [(u.K, u.deg_C, lambda x: x - 273.15, lambda x: x + 273.15)]134 )135 assert len(norme) == 1136 assert isinstance(norme[0], tuple)137 assert len(norme[0]) == 4138 assert norme[0][0] == u.K139 assert norme[0][1] == u.deg_C140 assert isinstance(norme[0][2], LambdaType)141 assert isinstance(norme[0][3], LambdaType)142 for val in [-20.0, 50.0, 195.0]:143 assert norme[0][2](val) == (lambda x: x - 273.15)(val)144 assert norme[0][3](val) == (lambda x: x + 273.15)(val)145 # not a 2, 3, or 4-tuple146 with pytest.raises(ValueError):147 cu._normalize_equivalencies([(u.cm,)])148 # input is not a astropy.unit.Unit149 with pytest.raises(ValueError):150 cu._normalize_equivalencies([("cm", u.cm)])151 def test_cu_method__get_unit_checks(self):152 """153 Test functionality/behavior of the method `_get_unit_checks` on `CheckUnits`.154 This method reviews the decorator `checks` arguments and wrapped function155 annotations to build a complete checks dictionary.156 """157 # methods must exist158 assert hasattr(CheckUnits, "_get_unit_checks")159 # setup default checks160 default_checks = {161 **self.check_defaults.copy(),162 "units": [self.check_defaults["units"]],163 }164 # setup test cases165 # 'setup' = arguments for `_get_unit_checks`166 # 'output' = expected return from `_get_unit_checks`167 # 'raises' = if `_get_unit_checks` raises an Exception168 # 'warns' = if `_get_unit_checks` issues a warning169 #170 equivs = [171 # list of astropy Equivalency objects172 [u.temperature_energy(), u.temperature()],173 # list of equivalencies (pre astropy v3.2.1 style)174 list(u.temperature()),175 ]176 _cases = [177 {178 "descr": "x units are defined via decorator kwarg of CheckUnits\n"179 "y units are defined via decorator annotations, additional\n"180 " checks thru CheckUnits kwarg",181 "setup": {182 "function": self.foo_partial_anno,183 "args": (2 * u.cm, 3 * u.cm),184 "kwargs": {},185 "checks": {"x": {"units": [u.cm], "equivalencies": equivs[0][0]}},186 },187 "output": {188 "x": {"units": [u.cm], "equivalencies": equivs[0][0]},189 "y": {"units": [u.cm]},190 },191 },192 {193 "descr": "x units are defined via decorator kwarg of CheckUnits\n"194 "y units are defined via function annotations, additional\n"195 " checks thru CheckUnits kwarg",196 "setup": {197 "function": self.foo_partial_anno,198 "args": (2 * u.cm, 3 * u.cm),199 "kwargs": {},200 "checks": {201 "x": {"units": [u.cm], "equivalencies": equivs[0]},202 "y": {"pass_equivalent_units": False},203 },204 },205 "output": {206 "x": {207 "units": [u.cm],208 "equivalencies": equivs[0][0] + equivs[0][1],209 },210 "y": {"units": [u.cm], "pass_equivalent_units": False},211 },212 },213 {214 "descr": "equivalencies are a list instead of astropy Equivalency objects",215 "setup": {216 "function": self.foo_no_anno,217 "args": (2 * u.K, 3 * u.K),218 "kwargs": {},219 "checks": {220 "x": {"units": [u.K], "equivalencies": equivs[1][0]},221 "y": {"units": [u.K], "equivalencies": equivs[1]},222 },223 },224 "output": {225 "x": {"units": [u.K], "equivalencies": [equivs[1][0]]},226 "y": {"units": [u.K], "equivalencies": equivs[1]},227 },228 },229 {230 "descr": "number of checked arguments exceed number of function arguments",231 "setup": {232 "function": self.foo_partial_anno,233 "args": (2 * u.cm, 3 * u.cm),234 "kwargs": {},235 "checks": {236 "x": {"units": [u.cm]},237 "y": {"units": [u.cm]},238 "z": {"units": [u.cm]},239 },240 },241 "warns": PlasmaPyWarning,242 "output": {"x": {"units": [u.cm]}, "y": {"units": [u.cm]}},243 },244 {245 "descr": "arguments passed via *args and **kwargs are ignored",246 "setup": {247 "function": self.foo_stars,248 "args": (2 * u.cm, "hello"),249 "kwargs": {"z": None},250 "checks": {251 "x": {"units": [u.cm]},252 "y": {"units": [u.cm]},253 "z": {"units": [u.cm]},254 },255 },256 "warns": PlasmaPyWarning,257 "output": {"x": {"units": [u.cm]}, "y": {"units": [u.cm]}},258 },259 {260 "descr": "arguments can be None values",261 "setup": {262 "function": self.foo_with_none,263 "args": (2 * u.cm, 3 * u.cm),264 "kwargs": {},265 "checks": {"x": {"units": [u.cm, None]}},266 },267 "output": {268 "x": {"units": [u.cm], "none_shall_pass": True},269 "y": {"units": [u.cm], "none_shall_pass": True},270 },271 },272 {273 "descr": "checks and annotations do not specify units",274 "setup": {275 "function": self.foo_no_anno,276 "args": (2 * u.cm, 3 * u.cm),277 "kwargs": {},278 "checks": {"x": {"pass_equivalent_units": True}},279 },280 "raises": ValueError,281 },282 {283 "descr": "units are directly assigned to the check kwarg",284 "setup": {285 "function": self.foo_partial_anno,286 "args": (2 * u.cm, 3 * u.cm),287 "kwargs": {},288 "checks": {"x": u.cm},289 },290 "output": {"x": {"units": [u.cm]}, "y": {"units": [u.cm]}},291 },292 {293 "descr": "return units are assigned via checks",294 "setup": {295 "function": self.foo_no_anno,296 "args": (2 * u.km, 3 * u.km),297 "kwargs": {},298 "checks": {"checks_on_return": u.km},299 },300 "output": {"checks_on_return": {"units": [u.km]}},301 },302 {303 "descr": "return units are assigned via annotations",304 "setup": {305 "function": self.foo_return_anno,306 "args": (2 * u.cm, 3 * u.cm),307 "kwargs": {},308 "checks": {},309 },310 "output": {"checks_on_return": {"units": [u.um]}},311 },312 {313 "descr": "return units are assigned via annotations and checks arg, but"314 "are not consistent",315 "setup": {316 "function": self.foo_return_anno,317 "args": (2 * u.cm, 3 * u.cm),318 "kwargs": {},319 "checks": {"checks_on_return": {"units": u.km}},320 },321 "raises": ValueError,322 },323 {324 "descr": "return units are not specified but other checks are",325 "setup": {326 "function": self.foo_no_anno,327 "args": (2 * u.cm, 3 * u.cm),328 "kwargs": {},329 "checks": {"checks_on_return": {"pass_equivalent_units": True}},330 },331 "raises": ValueError,332 },333 {334 "descr": "no parameter checks for x are defined, but a non-unit annotation"335 "is used",336 "setup": {337 "function": self.foo_partial_anno,338 "args": (2 * u.cm, 3 * u.cm),339 "kwargs": {},340 "checks": {},341 },342 "output": {"y": {"units": [u.cm]}},343 },344 {345 "descr": "parameter checks defined for x but unit checks calculated from"346 "function annotations. Function annotations do NOT define "347 "a proper unit type.",348 "setup": {349 "function": self.foo_partial_anno,350 "args": (2 * u.cm, 3 * u.cm),351 "kwargs": {},352 "checks": {"x": {"pass_equivalent_units": True}},353 },354 "raises": ValueError,355 },356 {357 "descr": "parameter checks defined for return argument but unit checks "358 "calculated from function annotations. Function annotations do "359 "NOT define a proper unit type.",360 "setup": {361 "function": self.foo_partial_anno,362 "args": (2 * u.cm, 3 * u.cm),363 "kwargs": {},364 "checks": {"checks_on_return": {"pass_equivalent_units": True}},365 },366 "raises": ValueError,367 },368 ]369 # perform tests370 for ii, case in enumerate(_cases):371 sig = inspect.signature(case["setup"]["function"])372 bound_args = sig.bind(*case["setup"]["args"], **case["setup"]["kwargs"])373 cu = CheckUnits(**case["setup"]["checks"])374 cu.f = case["setup"]["function"]375 if "warns" in case:376 with pytest.warns(case["warns"]):377 checks = cu._get_unit_checks(bound_args)378 elif "raises" in case:379 with pytest.raises(case["raises"]):380 cu._get_unit_checks(bound_args)381 continue382 else:383 checks = cu._get_unit_checks(bound_args)384 # only expected argument checks exist385 assert sorted(checks.keys()) == sorted(case["output"].keys())386 # if check key-value not specified then default is assumed387 for arg_name in case["output"].keys():388 arg_checks = checks[arg_name]389 for key in default_checks.keys():390 if key in case["output"][arg_name]:391 val = case["output"][arg_name][key]392 else:393 val = default_checks[key]394 assert arg_checks[key] == val395 def test_cu_method__check_unit(self):396 """397 Test functionality/behavior of the methods `_check_unit` and `_check_unit_core`398 on `CheckUnits`. These methods do the actual checking of the argument units399 and should be called by `CheckUnits.__call__()`.400 """401 # methods must exist402 assert hasattr(CheckUnits, "_check_unit")403 assert hasattr(CheckUnits, "_check_unit_core")404 # setup default checks405 check = {**self.check_defaults, "units": [u.cm]}406 # check = self.check_defaults.copy()407 # check['units'] = [u.cm]408 # check['equivalencies'] = [None]409 # make a class w/ improper units410 class MyQuantity:411 unit = None412 # setup test cases413 # 'input' = arguments for `_check_unit_core` and `_check_unit`414 # 'output' = expected return from `_check_unit_core`415 #416 # add cases for 'units' checks417 _cases = [418 # argument does not have units419 {"input": (5.0, "arg", check), "output": (None, None, None, TypeError)},420 # argument does match desired units421 # * set arg_name = 'checks_on_return' to cover if-else statement422 # in initializing error string423 {424 "input": (5.0 * u.kg, "checks_on_return", check),425 "output": (None, None, None, u.UnitTypeError),426 },427 # argument has equivalent but not matching unit428 {429 "input": (5.0 * u.km, "arg", check),430 "output": (5.0 * u.km, u.cm, None, u.UnitTypeError),431 },432 # argument is equivalent to many specified units but exactly matches one433 {434 "input": (5.0 * u.km, "arg", {**check, "units": [u.cm, u.km]}),435 "output": (5.0 * u.km, u.km, None, None),436 },437 # argument is equivalent to many specified units and438 # does NOT exactly match one439 {440 "input": (5.0 * u.m, "arg", {**check, "units": [u.cm, u.km]}),441 "output": (None, None, None, u.UnitTypeError),442 },443 # argument has attr unit but unit does not have is_equivalent444 {445 "input": (MyQuantity, "arg", check),446 "output": (None, None, None, TypeError),447 },448 ]449 # add cases for 'none_shall_pass' checks450 _cases.extend(451 [452 # argument is None and none_shall_pass = False453 {454 "input": (None, "arg", {**check, "none_shall_pass": False}),455 "output": (None, None, None, ValueError),456 },457 # argument is None and none_shall_pass = True458 {459 "input": (None, "arg", {**check, "none_shall_pass": True}),460 "output": (None, None, None, None),461 },462 ]463 )464 # add cases for 'pass_equivalent_units' checks465 _cases.extend(466 [467 # argument is equivalent to 1 to unit,468 # does NOT exactly match the unit,469 # and 'pass_equivalent_units' = True and argument470 {471 "input": (472 5.0 * u.km,473 "arg",474 {**check, "pass_equivalent_units": True},475 ),476 "output": (5.0 * u.km, u.cm, None, None),477 },478 # argument is equivalent to more than 1 unit,479 # does NOT exactly match any unit,480 # and 'pass_equivalent_units' = True and argument481 {482 "input": (483 5.0 * u.km,484 "arg",485 {**check, "units": [u.cm, u.m], "pass_equivalent_units": True},486 ),487 "output": (5.0 * u.km, None, None, None),488 },489 ]490 )491 # setup wrapped function492 cu = CheckUnits()493 cu.f = self.foo_no_anno494 # perform tests495 for ii, case in enumerate(_cases):496 arg, arg_name, arg_checks = case["input"]497 _results = cu._check_unit_core(arg, arg_name, arg_checks)498 assert _results[0:3] == case["output"][0:3]499 if _results[3] is None:500 assert _results[3] is case["output"][3]501 assert cu._check_unit(arg, arg_name, arg_checks) is None502 else:503 assert isinstance(_results[3], case["output"][3])504 with pytest.raises(case["output"][3]):505 cu._check_unit(arg, arg_name, arg_checks)506 def test_cu_called_as_decorator(self):507 """508 Test behavior of `CheckUnits.__call__` (i.e. used as a decorator).509 """510 # setup test cases511 # 'setup' = arguments for `CheckUnits` and wrapped function512 # 'output' = expected return from wrapped function513 # 'raises' = if an Exception is expected to be raised514 # 'warns' = if a warning is expected to be issued515 #516 _cases = [517 # clean execution518 {519 "setup": {520 "function": self.foo_no_anno,521 "args": (2 * u.cm, 3 * u.cm),522 "kwargs": {},523 "checks": {"x": u.cm, "y": u.cm, "checks_on_return": u.cm},524 },525 "output": 5 * u.cm,526 },527 # argument fails checks528 {529 "setup": {530 "function": self.foo_no_anno,531 "args": (2 * u.cm, 3 * u.cm),532 "kwargs": {},533 "checks": {"x": u.g, "y": u.cm, "checks_on_return": u.cm},534 },535 "raises": u.UnitTypeError,536 },537 # return fails checks538 {539 "setup": {540 "function": self.foo_no_anno,541 "args": (2 * u.cm, 3 * u.cm),542 "kwargs": {},543 "checks": {"x": u.cm, "y": u.cm, "checks_on_return": u.km},544 },545 "raises": u.UnitTypeError,546 },547 ]548 # test549 for case in _cases:550 wfoo = CheckUnits(**case["setup"]["checks"])(case["setup"]["function"])551 args = case["setup"]["args"]552 kwargs = case["setup"]["kwargs"]553 if "raises" in case:554 with pytest.raises(case["raises"]):555 wfoo(*args, **kwargs)556 else:557 assert wfoo(*args, **kwargs) == case["output"]558 # test on class method559 class Foo:560 @CheckUnits()561 def __init__(self, y: u.cm):562 self.y = y563 @CheckUnits(x=u.cm)564 def bar(self, x) -> u.cm:565 return x + self.y566 foo = Foo(10.0 * u.cm)567 assert foo.bar(-3 * u.cm) == 7 * u.cm568 def test_cu_preserves_signature(self):569 """Test `CheckValues` preserves signature of wrapped function."""570 # I'd like to directly test the @preserve_signature is used (??)571 wfoo = CheckUnits()(self.foo_no_anno)572 assert hasattr(wfoo, "__signature__")573 assert wfoo.__signature__ == inspect.signature(self.foo_no_anno)574 @mock.patch(575 CheckUnits.__module__ + "." + CheckUnits.__qualname__,576 side_effect=CheckUnits,577 autospec=True,578 )579 def test_decorator_func_def(self, mock_cu_class):580 """581 Test that :func:`~plasmapy.utils.decorators.checks.check_units` is582 properly defined.583 """584 # create mock function (mock_foo) from function to mock (self.foo_no_anno)585 mock_foo = mock.Mock(586 side_effect=self.foo_no_anno, name="mock_foo", autospec=True587 )588 mock_foo.__name__ = "mock_foo"589 mock_foo.__signature__ = inspect.signature(self.foo_no_anno)590 # setup test cases591 # 'setup' = arguments for `check_units` and wrapped function592 # 'output' = expected return from wrapped function593 # 'raises' = a raised Exception is expected594 # 'warns' = an issued warning is expected595 #596 _cases = [597 # only argument checks598 {599 "setup": {600 "args": (2 * u.cm, 3 * u.cm),601 "kwargs": {},602 "checks": {"x": u.cm, "y": u.cm},603 },604 "output": 5 * u.cm,605 },606 # argument and return checks607 {608 "setup": {609 "args": (2 * u.cm, 3 * u.cm),610 "kwargs": {},611 "checks": {"x": u.cm, "checks_on_return": u.cm},612 },613 "output": 5 * u.cm,614 },615 ]616 for case in _cases:617 for ii in range(2):618 # decorate619 if ii == 0:620 # functional decorator call621 wfoo = check_units(mock_foo, **case["setup"]["checks"])622 elif ii == 1:623 # sugar decorator call624 #625 # @check_units(x=check)626 # def foo(x):627 # return x628 #629 wfoo = check_units(**case["setup"]["checks"])(mock_foo)630 else:631 continue632 # test633 args = case["setup"]["args"]634 kwargs = case["setup"]["kwargs"]635 assert wfoo(*args, **kwargs) == case["output"]636 assert mock_cu_class.called637 assert mock_foo.called638 assert mock_cu_class.call_args[0] == ()639 assert sorted(mock_cu_class.call_args[1].keys()) == sorted(640 case["setup"]["checks"].keys()641 )642 for arg_name, checks in case["setup"]["checks"].items():643 assert mock_cu_class.call_args[1][arg_name] == checks644 # reset645 mock_cu_class.reset_mock()646 mock_foo.reset_mock()647# ----------------------------------------------------------------------------------------648# Test Decorator class `CheckValues` and decorator `check_values`649# ----------------------------------------------------------------------------------------650class TestCheckValues:651 """652 Tests for decorator :func:`~plasmapy.utils.decorators.checks.check_values` and653 decorator class :class:`~plasmapy.utils.decorators.checks.CheckValues`.654 """655 check_defaults = CheckValues._CheckValues__check_defaults # type: Dict[str, bool]656 @staticmethod657 def foo(x, y):658 return x + y659 @staticmethod660 def foo_stars(x, *args, y=3, **kwargs):661 return x + y662 def test_inheritance(self):663 assert issubclass(CheckValues, CheckBase)664 def test_cv_default_check_values(self):665 """Test the default check dictionary for CheckValues"""666 cv = CheckValues()667 assert hasattr(cv, "_CheckValues__check_defaults")668 assert isinstance(cv._CheckValues__check_defaults, dict)669 _defaults = [670 ("can_be_negative", True),671 ("can_be_complex", False),672 ("can_be_inf", True),673 ("can_be_nan", True),674 ("none_shall_pass", False),675 ]676 for key, val in _defaults:677 assert cv._CheckValues__check_defaults[key] == val678 def test_cv_method__get_value_checks(self):679 """680 Test functionality/behavior of the method `_get_value_checks` on `CheckValues`.681 This method reviews the decorator `checks` arguments to build a complete682 checks dictionary.683 """684 # methods must exist685 assert hasattr(CheckValues, "_get_value_checks")686 # setup default checks687 default_checks = self.check_defaults.copy()688 # setup test cases689 # 'setup' = arguments for `_get_value_checks`690 # 'output' = expected return from `_get_value_checks`691 # 'raises' = if `_get_value_checks` raises an Exception692 # 'warns' = if `_get_value_checks` issues a warning693 #694 _cases = [695 # define some checks696 {697 "setup": {698 "function": self.foo,699 "args": (2, 3),700 "kwargs": {},701 "checks": {702 "x": {703 "can_be_negative": False,704 "can_be_complex": True,705 "can_be_inf": False,706 },707 "checks_on_return": {708 "can_be_nan": False,709 "none_shall_pass": True,710 },711 },712 },713 "output": {714 "x": {715 "can_be_negative": False,716 "can_be_complex": True,717 "can_be_inf": False,718 },719 "checks_on_return": {"can_be_nan": False, "none_shall_pass": True},720 },721 },722 # arguments passed via *args and **kwargs are ignored723 {724 "setup": {725 "function": self.foo_stars,726 "args": (2, "hello"),727 "kwargs": {"z": None},728 "checks": {729 "x": {"can_be_negative": False},730 "y": {"can_be_inf": False},731 "z": {"none_shall_pass": True},732 },733 },734 "output": {"x": {"can_be_negative": False}, "y": {"can_be_inf": False}},735 "warns": PlasmaPyWarning,736 },737 # check argument is not a dictionary (default is assumed)738 {739 "setup": {740 "function": self.foo,741 "args": (2, 3),742 "kwargs": {},743 "checks": {"x": u.cm},744 },745 "output": {"x": {}},746 },747 ]748 # perform tests749 for case in _cases:750 sig = inspect.signature(case["setup"]["function"])751 args = case["setup"]["args"]752 kwargs = case["setup"]["kwargs"]753 bound_args = sig.bind(*args, **kwargs)754 cv = CheckValues(**case["setup"]["checks"])755 cv.f = case["setup"]["function"]756 if "warns" in case:757 with pytest.warns(case["warns"]):758 checks = cv._get_value_checks(bound_args)759 elif "raises" in case:760 with pytest.raises(case["raises"]):761 cv._get_value_checks(bound_args)762 continue763 else:764 checks = cv._get_value_checks(bound_args)765 # only expected keys exist766 assert sorted(checks.keys()) == sorted(case["output"].keys())767 # if check key-value not specified then default is assumed768 for arg_name in case["output"].keys():769 arg_checks = checks[arg_name]770 for key in default_checks.keys():771 if key in case["output"][arg_name]:772 val = case["output"][arg_name][key]773 else:774 val = default_checks[key]775 assert arg_checks[key] == val776 def test_cv_method__check_value(self):777 """778 Test functionality/behavior of the `_check_value` method on `CheckValues`.779 This method does the actual checking of the argument values and should be780 called by `CheckValues.__call__()`.781 """782 # setup wrapped function783 cv = CheckValues()784 wfoo = cv(self.foo)785 # methods must exist786 assert hasattr(cv, "_check_value")787 # setup default checks788 default_checks = self.check_defaults.copy()789 # setup test cases790 # 'setup' = arguments for `CheckUnits` and wrapped function791 # 'raises' = if an Exception is expected to be raised792 # 'warns' = if a warning is expected to be issued793 #794 _cases = [795 # tests for check 'can_be_negative'796 {797 "input": {798 "args": [799 -5,800 -5.0,801 np.array([-1, 2]),802 np.array([-3.0, 2.0]),803 -3 * u.cm,804 np.array([-4.0, 3.0]) * u.kg,805 ],806 "arg_name": "arg",807 "checks": {**default_checks, "can_be_negative": False},808 },809 "raises": ValueError,810 },811 {812 "input": {813 "args": [814 -5,815 -5.0,816 np.array([-1, 2]),817 np.array([-3.0, 2.0]),818 -3 * u.cm,819 np.array([-4.0, 3.0]) * u.kg,820 ],821 "arg_name": "arg",822 "checks": {**default_checks, "can_be_negative": True},823 }824 },825 # tests for check 'can_be_complex'826 {827 "input": {828 "args": [829 complex(5),830 complex(2, 3),831 np.complex(3.0),832 complex(4.0, 2.0) * u.cm,833 np.array([complex(4, 5), complex(1)]) * u.kg,834 ],835 "arg_name": "checks_on_return",836 "checks": {**default_checks, "can_be_complex": False},837 },838 "raises": ValueError,839 },840 {841 "input": {842 "args": [843 complex(5),844 complex(2, 3),845 np.complex(3.0),846 complex(4.0, 2.0) * u.cm,847 np.array([complex(4, 5), complex(1)]) * u.kg,848 ],849 "arg_name": "checks_on_return",850 "checks": {**default_checks, "can_be_complex": True},851 }852 },853 # tests for check 'can_be_inf'854 {855 "input": {856 "args": [857 np.inf,858 np.inf * u.cm,859 np.array([1.0, 2.0, np.inf, 10.0]),860 np.array([1.0, 2.0, np.inf, np.inf]) * u.kg,861 ],862 "arg_name": "arg",863 "checks": {**default_checks, "can_be_inf": False},864 },865 "raises": ValueError,866 },867 {868 "input": {869 "args": [870 np.inf,871 np.inf * u.cm,872 np.array([1.0, 2.0, np.inf, 10.0]),873 np.array([1.0, 2.0, np.inf, np.inf]) * u.kg,874 ],875 "arg_name": "arg",876 "checks": {**default_checks, "can_be_inf": True},877 }878 },879 # tests for check 'can_be_nan'880 {881 "input": {882 "args": [883 np.nan,884 np.nan * u.cm,885 np.array([1.0, 2.0, np.nan, 10.0]),886 np.array([1.0, 2.0, np.nan, np.nan]) * u.kg,887 ],888 "arg_name": "arg",889 "checks": {**default_checks, "can_be_nan": False},890 },891 "raises": ValueError,892 },893 {894 "input": {895 "args": [896 np.nan,897 np.nan * u.cm,898 np.array([1.0, 2.0, np.nan, 10.0]),899 np.array([1.0, 2.0, np.nan, np.nan]) * u.kg,900 ],901 "arg_name": "arg",902 "checks": {**default_checks, "can_be_nan": True},903 }904 },905 # tests for check 'none_shall_pass'906 {907 "input": {908 "args": [None],909 "arg_name": "arg",910 "checks": {**default_checks, "none_shall_pass": False},911 },912 "raises": ValueError,913 },914 {915 "input": {916 "args": [None],917 "arg_name": "arg",918 "checks": {**default_checks, "none_shall_pass": True},919 }920 },921 ]922 # test923 for case in _cases:924 arg_name = case["input"]["arg_name"]925 checks = case["input"]["checks"]926 for arg in case["input"]["args"]:927 if "raises" in case:928 with pytest.raises(case["raises"]):929 cv._check_value(arg, arg_name, checks)930 elif "warns" in case:931 with pytest.warns(case["warns"]):932 cv._check_value(arg, arg_name, checks)933 else:934 assert cv._check_value(arg, arg_name, checks) is None935 def test_cv_called_as_decorator(self):936 """937 Test behavior of `CheckValues.__call__` (i.e. used as a decorator).938 """939 # setup test cases940 # 'setup' = arguments for `CheckUnits` and wrapped function941 # 'output' = expected return from wrapped function942 # 'raises' = if an Exception is expected to be raised943 # 'warns' = if a warning is expected to be issued944 #945 _cases = [946 # clean execution947 {948 "setup": {949 "function": self.foo,950 "args": (2, -3),951 "kwargs": {},952 "checks": {953 "x": {"can_be_negative": True},954 "y": {"can_be_negative": True},955 "checks_on_return": {"can_be_negative": True},956 },957 },958 "output": -1,959 },960 # argument fails checks961 {962 "setup": {963 "function": self.foo,964 "args": (2, -3),965 "kwargs": {},966 "checks": {967 "x": {"can_be_negative": True},968 "y": {"can_be_negative": False},969 "checks_on_return": {"can_be_negative": True},970 },971 },972 "raises": ValueError,973 },974 # return fails checks975 {976 "setup": {977 "function": self.foo,978 "args": (2, -3),979 "kwargs": {},980 "checks": {981 "x": {"can_be_negative": True},982 "y": {"can_be_negative": True},983 "checks_on_return": {"can_be_negative": False},984 },985 },986 "raises": ValueError,987 },988 ]989 # test on function990 for case in _cases:991 wfoo = CheckValues(**case["setup"]["checks"])(case["setup"]["function"])992 args = case["setup"]["args"]993 kwargs = case["setup"]["kwargs"]994 if "raises" in case:995 with pytest.raises(case["raises"]):996 wfoo(*args, **kwargs)997 else:998 assert wfoo(*args, **kwargs) == case["output"]999 # test on class method1000 class Foo:1001 @CheckValues(y={"can_be_negative": True})1002 def __init__(self, y):1003 self.y = y1004 @CheckValues(1005 x={"can_be_negative": True}, checks_on_return={"can_be_negative": False}1006 )1007 def bar(self, x):1008 return x + self.y1009 foo = Foo(-5)1010 assert foo.bar(6) == 11011 with pytest.raises(ValueError):1012 foo.bar(1)1013 def test_cv_preserves_signature(self):1014 """Test CheckValues preserves signature of wrapped function."""1015 # I'd like to directly test the @preserve_signature is used (??)1016 wfoo = CheckValues()(self.foo)1017 assert hasattr(wfoo, "__signature__")1018 assert wfoo.__signature__ == inspect.signature(self.foo)1019 @mock.patch(1020 CheckValues.__module__ + "." + CheckValues.__qualname__,1021 side_effect=CheckValues,1022 autospec=True,1023 )1024 def test_decorator_func_def(self, mock_cv_class):1025 """1026 Test that :func:`~plasmapy.utils.decorators.checks.check_values` is1027 properly defined.1028 """1029 # create mock function (mock_foo) from function to mock (self.foo)1030 mock_foo = mock.Mock(side_effect=self.foo, name="mock_foo", autospec=True)1031 mock_foo.__name__ = "mock_foo"1032 mock_foo.__signature__ = inspect.signature(self.foo)1033 # setup test cases1034 # 'setup' = arguments for `check_units` and wrapped function1035 # 'output' = expected return from wrapped function1036 # 'raises' = a raised Exception is expected1037 # 'warns' = an issued warning is expected1038 #1039 _cases = [1040 # only argument checks1041 {1042 "setup": {1043 "args": (-4, 3),1044 "kwargs": {},1045 "checks": {1046 "x": {"can_be_negative": True},1047 "y": {"can_be_nan": False},1048 },1049 },1050 "output": -1,1051 },1052 # argument and return checks1053 {1054 "setup": {1055 "args": (-4, 3),1056 "kwargs": {},1057 "checks": {1058 "x": {"can_be_negative": True},1059 "checks_on_return": {"can_be_negative": True},1060 },1061 },1062 "output": -1,1063 },1064 ]1065 for case in _cases:1066 for ii in range(2):1067 # decorate1068 if ii == 0:1069 # functional decorator call1070 wfoo = check_values(mock_foo, **case["setup"]["checks"])1071 elif ii == 1:1072 # sugar decorator call1073 #1074 # @check_values(x=check)1075 # def foo(x):1076 # return x1077 #1078 wfoo = check_values(**case["setup"]["checks"])(mock_foo)1079 else:1080 continue1081 # test1082 args = case["setup"]["args"]1083 kwargs = case["setup"]["kwargs"]1084 assert wfoo(*args, **kwargs) == case["output"]1085 assert mock_cv_class.called1086 assert mock_foo.called1087 assert mock_cv_class.call_args[0] == ()1088 assert sorted(mock_cv_class.call_args[1].keys()) == sorted(1089 case["setup"]["checks"].keys()1090 )1091 for arg_name, checks in case["setup"]["checks"].items():1092 assert mock_cv_class.call_args[1][arg_name] == checks1093 # reset1094 mock_cv_class.reset_mock()1095 mock_foo.reset_mock()1096# ----------------------------------------------------------------------------------------1097# Test Decorator `check_relativistic` (& function `_check_relativistic`1098# ----------------------------------------------------------------------------------------1099# (speed, betafrac)1100non_relativistic_speed_examples = [1101 (0 * u.m / u.s, 0.1),1102 (0.0099999 * c, 0.1),1103 (-0.009 * c, 0.1),1104 (5 * u.AA / u.Gyr, 0.1),1105]1106# (speed, betafrac, error)1107relativistic_error_examples = [1108 (u.m / u.s, 0.1, TypeError),1109 (51513.35, 0.1, TypeError),1110 (5 * u.m, 0.1, u.UnitConversionError),1111 (1.0 * c, 0.1, RelativityError),1112 (1.1 * c, 0.1, RelativityError),1113 (np.inf * u.cm / u.s, 0.1, RelativityError),1114 (-1.0 * c, 0.1, RelativityError),1115 (-1.1 * c, 0.1, RelativityError),1116 (-np.inf * u.cm / u.s, 0.1, RelativityError),1117]1118# (speed, betafrac, warning)1119relativistic_warning_examples = [1120 (0.11 * c, 0.1),1121 (-0.11 * c, 0.1),1122 (2997924581 * u.cm / u.s, 0.1),1123 (0.02 * c, 0.01),1124]1125# Tests for _check_relativistic1126@pytest.mark.parametrize("speed, betafrac", non_relativistic_speed_examples)1127def test__check_relativisitc_valid(speed, betafrac):1128 _check_relativistic(speed, "f", betafrac=betafrac)1129@pytest.mark.parametrize("speed, betafrac, error", relativistic_error_examples)1130def test__check_relativistic_errors(speed, betafrac, error):1131 with pytest.raises(error):1132 _check_relativistic(speed, "f", betafrac=betafrac)1133@pytest.mark.parametrize("speed, betafrac", relativistic_warning_examples)1134def test__check_relativistic_warnings(speed, betafrac):1135 with pytest.warns(RelativityWarning):1136 _check_relativistic(speed, "f", betafrac=betafrac)1137# Tests for check_relativistic decorator1138@pytest.mark.parametrize("speed, betafrac", non_relativistic_speed_examples)1139def test_check_relativistic_decorator(speed, betafrac):1140 @check_relativistic(betafrac=betafrac)1141 def speed_func():1142 return speed1143 speed_func()1144@pytest.mark.parametrize("speed", [item[0] for item in non_relativistic_speed_examples])1145def test_check_relativistic_decorator_no_args(speed):1146 @check_relativistic1147 def speed_func():1148 return speed1149 speed_func()1150@pytest.mark.parametrize("speed", [item[0] for item in non_relativistic_speed_examples])1151def test_check_relativistic_decorator_no_args_parentheses(speed):1152 @check_relativistic()1153 def speed_func():1154 return speed1155 speed_func()1156@pytest.mark.parametrize("speed, betafrac, error", relativistic_error_examples)1157def test_check_relativistic_decorator_errors(speed, betafrac, error):1158 @check_relativistic(betafrac=betafrac)1159 def speed_func():1160 return speed1161 with pytest.raises(error):...

test_decorators.py

Source:test_decorators.py

...330 with pytest.raises(expected_exception):331 decorated_function(particle)332 else:333 decorated_function(particle)334def test_none_shall_pass():335 """Tests the `none_shall_pass` keyword argument in is_particle.336 If `none_shall_pass=True`, then an annotated argument should allow337 `None` to be passed through to the decorated function."""338 @particle_input(none_shall_pass=True)339 def func_none_shall_pass(particle: Particle) -> Optional[Particle]:340 return particle341 @particle_input(none_shall_pass=True)342 def func_none_shall_pass_with_tuple(343 particles: (Particle, Particle)344 ) -> (Optional[Particle], Optional[Particle]):345 return particles346 @particle_input(none_shall_pass=True)347 def func_none_shall_pass_with_list(particles: [Particle]) -> [Optional[Particle]]:348 return particles349 assert func_none_shall_pass(None) is None, (350 "The none_shall_pass keyword in the particle_input decorator is set "351 "to True, but is not passing through None."352 )353 assert func_none_shall_pass_with_tuple((None, None)) == (None, None), (354 "The none_shall_pass keyword in the particle_input decorator is set "355 "to True, but is not passing through None."356 )357 assert func_none_shall_pass_with_list((None, None)) == (None, None), (358 "The none_shall_pass keyword in the particle_input decorator is set "359 "to True, but is not passing through None."360 )361def test_none_shall_not_pass():362 """Tests the `none_shall_pass` keyword argument in is_particle.363 If `none_shall_pass=False`, then particle_input should raise a...

validators.py

Source:validators.py

1"""2Various decorators to validate input/output arguments to functions.3"""4__all__ = ["validate_quantities", "ValidateQuantities"]5import astropy.units as u6import functools7import inspect8import warnings9from typing import Any, Dict10from plasmapy.utils.decorators.checks import CheckUnits, CheckValues11from plasmapy.utils.decorators.helpers import preserve_signature12class ValidateQuantities(CheckUnits, CheckValues):13 """14 A decorator class to 'validate' -- control and convert -- the units and values15 of input and return arguments to a function or method. Arguments are expected to16 be astropy :class:`~astropy.units.quantity.Quantity` objects.17 Parameters18 ----------19 validations_on_return: dictionary of validation specifications20 Specifications for unit and value validations on the return of the21 function being wrapped. (see `quantity validations`_ for valid22 specifications.23 **validations: dictionary of validation specifications24 Specifications for unit and value validations on the input arguments of the25 function being wrapped. Each keyword argument in `validations` is the26 name of a function argument to be validated and the keyword value contains27 the unit and value validation specifications.28 .. _`quantity validations`:29 Unit and value validations can be defined by passing one of the astropy30 :mod:`~astropy.units`, a list of astropy units, or a dictionary containing31 the keys defined below. Units can also be defined with function annotations,32 but must be consistent with decorator `**validations` arguments if used33 concurrently. If a key is omitted, then the default value will be assumed.34 ====================== ======= ================================================35 Key Type Description36 ====================== ======= ================================================37 units list of desired astropy :mod:`~astropy.units`38 equivalencies | [DEFAULT `None`] A list of equivalent pairs to39 try if40 | the units are not directly convertible.41 | (see :mod:`~astropy.units.equivalencies`,42 and/or `astropy equivalencies`_)43 pass_equivalent_units `bool` | [DEFAULT `False`] allow equivalent units44 | to pass45 can_be_negative `bool` [DEFAULT `True`] values can be negative46 can_be_complex `bool` [DEFAULT `False`] values can be complex numbers47 can_be_inf `bool` [DEFAULT `True`] values can be :data:`~numpy.inf`48 can_be_nan `bool` [DEFAULT `True`] values can be :data:`~numpy.nan`49 none_shall_pass `bool` [DEFAULT `False`] values can be a python `None`50 ====================== ======= ================================================51 Notes52 -----53 * Validation of function arguments `*args` and `**kwargs` is not supported.54 * `None` values will pass when `None` is included in the list of specified units,55 is set as a default value for the function argument, or `none_shall_pass` is56 set to `True`. If `none_shall_pass` is doubly/triply defined through the57 mentioned options, then they all must be consistent with each other.58 * If units are not specified in `validations`, then the decorator will attempt59 to identify desired units by examining the function annotations.60 Examples61 --------62 Define unit and value validations with decorator parameters::63 import astropy.units as u64 from plasmapy.utils.decorators import ValidateQuantities65 @ValidateQuantities(mass={'units': u.g,66 'can_be_negative': False},67 vel=u.cm / u.s,68 validations_on_return=[u.g * u.cm / u.s, u.kg * u.m / u.s])69 def foo(mass, vel):70 return mass * vel71 # on a method72 class Foo:73 @ValidateQuantities(mass={'units': u.g,74 'can_be_negative': False},75 vel=u.cm / u.s,76 validations_on_return=[u.g * u.cm / u.s,77 u.kg * u.m / u.s])78 def bar(self, mass, vel):79 return mass * vel80 Define units with function annotations::81 import astropy.units as u82 from plasmapy.utils.decorators import ValidateQuantities83 @ValidateQuantities(mass={'can_be_negative': False})84 def foo(mass: u.g, vel: u.cm / u.s) -> u.g * u.cm / u.s:85 return mass * vel86 # on a method87 class Foo:88 @ValidateQuantities(mass={'can_be_negative': False})89 def bar(self, mass: u.g, vel: u.cm / u.s) -> u.g * u.cm / u.s:90 return mass * vel91 Allow `None` values to pass::92 import astropy.units as u93 from plasmapy.utils.decorators import ValidateQuantities94 @ValidateQuantities(checks_on_return=[u.cm, None])95 def foo(arg1: u.cm = None):96 return arg197 Allow return values to have equivalent units::98 import astropy.units as u99 from plasmapy.utils.decorators import ValidateQuantities100 @ValidateQuantities(arg1={'units': u.cm},101 checks_on_return={'units': u.km,102 'pass_equivalent_units': True})103 def foo(arg1):104 return arg1105 Allow equivalent units to pass with specified equivalencies::106 import astropy.units as u107 from plasmapy.utils.decorators import ValidateQuantities108 @ValidateQuantities(arg1={'units': u.K,109 'equivalencies': u.temperature(),110 'pass_equivalent_units': True})111 def foo(arg1):112 return arg1113 .. _astropy equivalencies:114 https://docs.astropy.org/en/stable/units/equivalencies.html115 """116 def __init__(self, validations_on_return=None, **validations: Dict[str, Any]):117 if "checks_on_return" in validations:118 raise TypeError(119 f"keyword argument 'checks_on_return' is not allowed, "120 f"use 'validations_on_return' to set validations "121 f"on the return variable"122 )123 self._validations = validations124 checks = validations.copy()125 if validations_on_return is not None:126 self._validations["validations_on_return"] = validations_on_return127 checks["checks_on_return"] = validations_on_return128 super().__init__(**checks)129 def __call__(self, f):130 """131 Parameters132 ----------133 f134 Function to be wrapped135 Returns136 -------137 function138 wrapped function of `f`139 """140 self.f = f141 wrapped_sign = inspect.signature(f)142 @preserve_signature143 @functools.wraps(f)144 def wrapper(*args, **kwargs):145 # combine args and kwargs into dictionary146 bound_args = wrapped_sign.bind(*args, **kwargs)147 bound_args.apply_defaults()148 # get conditioned validations149 validations = self._get_validations(bound_args)150 # validate (input) argument units and values151 for arg_name in validations:152 # skip check of output/return153 if arg_name == "validations_on_return":154 continue155 # validate argument & update for conversion156 arg = self._validate_quantity(157 bound_args.arguments[arg_name], arg_name, validations[arg_name]158 )159 bound_args.arguments[arg_name] = arg160 # call function161 _return = f(**bound_args.arguments)162 # validate output163 if "validations_on_return" in validations:164 _return = self._validate_quantity(165 _return,166 "validations_on_return",167 validations["validations_on_return"],168 )169 return _return170 return wrapper171 def _get_validations(172 self, bound_args: inspect.BoundArguments173 ) -> Dict[str, Dict[str, Any]]:174 """175 Review :attr:`validations` and function bound arguments to build a complete176 'validations' dictionary. If a validation key is omitted from the argument177 validations, then a default value is assumed (see `quantity validations`_).178 Parameters179 ----------180 bound_args: :class:`inspect.BoundArguments`181 arguments passed into the function being wrapped182 .. code-block:: python183 bound_args = inspect.signature(f).bind(*args, **kwargs)184 Returns185 -------186 Dict[str, Dict[str, Any]]187 A complete 'validations' dictionary for validating function input arguments188 and return.189 """190 unit_checks = self._get_unit_checks(bound_args)191 value_checks = self._get_value_checks(bound_args)192 # combine all validations193 # * `unit_checks` will encompass all argument "checks" defined either by194 # function annotations or **validations.195 # * `value_checks` may miss some arguments if **validations only defines196 # unit validations or some validations come from function annotations197 validations = unit_checks.copy()198 for arg_name in validations:199 # augment 'none_shall_pass' (if needed)200 try:201 # if 'none_shall_pass' was in the original passed-in validations,202 # then override the value determined by CheckUnits203 _none_shall_pass = self.validations[arg_name]["none_shall_pass"]204 # if validations[arg_name]['none_shall_pass'] != _none_shall_pass:205 if (206 _none_shall_pass is False207 and validations[arg_name]["none_shall_pass"] is True208 ):209 raise ValueError(210 f"Validation 'none_shall_pass' for argument '{arg_name}' is "211 f"inconsistent between function annotations "212 f"({validations[arg_name]['none_shall_pass']}) and decorator "213 f"argument ({_none_shall_pass})."214 )215 validations[arg_name]["none_shall_pass"] = _none_shall_pass216 except (KeyError, TypeError):217 # 'none_shall_pass' was not in the original passed-in validations, so218 # rely on the value determined by CheckUnits219 pass220 finally:221 try:222 del value_checks[arg_name]["none_shall_pass"]223 except KeyError:224 dvc = self._CheckValues__check_defaults.copy()225 del dvc["none_shall_pass"]226 value_checks[arg_name] = dvc227 # update the validations dictionary228 validations[arg_name].update(value_checks[arg_name])229 if "checks_on_return" in validations:230 validations["validations_on_return"] = validations.pop("checks_on_return")231 return validations232 def _validate_quantity(self, arg, arg_name: str, arg_validations: Dict[str, Any]):233 """234 Perform validations `arg_validations` on function argument `arg`235 named `arg_name`.236 Parameters237 ----------238 arg239 The argument to be validated.240 arg_name: str241 The name of the argument to be validated242 arg_validations: Dict[str, Any]243 The requested validations for the argument244 Raises245 ------246 TypeError247 if argument is not an AstroPy :class:`~astropy.units.Quantity`248 or not convertible to a :class:`~astropy.units.Quantity`249 ValueError250 if validations fail251 """252 # rename to work with "check" methods253 if arg_name == "validations_on_return":254 arg_name = "checks_on_return"255 # initialize str for error message256 if arg_name == "checks_on_return":257 err_msg = f"The return value "258 else:259 err_msg = f"The argument '{arg_name}' "260 err_msg += f"to function {self.f.__name__}()"261 # initialize TypeError message262 typeerror_msg = (263 f"{err_msg} should be an astropy Quantity with units"264 f" equivalent to one of ["265 )266 for ii, unit in enumerate(arg_validations["units"]):267 typeerror_msg += f"{unit}"268 if ii != len(arg_validations["units"]) - 1:269 typeerror_msg += f", "270 typeerror_msg += f"]"271 # add units to arg if possible272 # * a None value will be taken care of by `_check_unit_core`273 #274 if arg is None or hasattr(arg, "unit"):275 pass276 elif len(arg_validations["units"]) != 1:277 raise TypeError(typeerror_msg)278 else:279 try:280 arg = arg * arg_validations["units"][0]281 except (TypeError, ValueError):282 raise TypeError(typeerror_msg)283 else:284 warnings.warn(285 u.UnitsWarning(286 f"{err_msg} has no specified units. Assuming units of "287 f"{arg_validations['units'][0]}. To silence this warning, "288 f"explicitly pass in an astropy Quantity "289 f"(e.g. 5. * astropy.units.cm) "290 f"(see http://docs.astropy.org/en/stable/units/)"291 )292 )293 # check units294 arg, unit, equiv, err = self._check_unit_core(arg, arg_name, arg_validations)295 # convert quantity296 if (297 arg is not None298 and unit is not None299 and not arg_validations["pass_equivalent_units"]300 ):301 arg = arg.to(unit, equivalencies=equiv)302 elif err is not None:303 raise err304 # check value305 self._check_value(arg, arg_name, arg_validations)306 return arg307 @property308 def validations(self):309 """310 Requested validations on the decorated function's input arguments and311 return variable.312 """313 return self._validations314def validate_quantities(func=None, validations_on_return=None, **validations):315 """316 A decorator to 'validate' -- control and convert -- the units and values317 of input and return arguments to a function or method. Arguments are expected to318 be astropy :class:`~astropy.units.quantity.Quantity` objects.319 Parameters320 ----------321 func:322 The function to be decorated323 validations_on_return: dictionary of validation specifications324 Specifications for unit and value validations on the return of the325 function being wrapped. (see `quantity validations`_ for valid326 specifications.327 **validations: dictionary of validation specifications328 Specifications for unit and value validations on the input arguments of the329 function being wrapped. Each keyword argument in `validations` is the330 name of a function argument to be validated and the keyword value contains331 the unit and value validation specifications.332 .. _`quantity validations`:333 Unit and value validations can be defined by passing one of the astropy334 :mod:`~astropy.units`, a list of astropy units, or a dictionary containing335 the keys defined below. Units can also be defined with function annotations,336 but must be consistent with decorator `**validations` arguments if used337 concurrently. If a key is omitted, then the default value will be assumed.338 ====================== ======= ================================================339 Key Type Description340 ====================== ======= ================================================341 units list of desired astropy :mod:`~astropy.units`342 equivalencies | [DEFAULT `None`] A list of equivalent pairs to343 try if344 | the units are not directly convertible.345 | (see :mod:`~astropy.units.equivalencies`,346 and/or `astropy equivalencies`_)347 pass_equivalent_units `bool` | [DEFAULT `False`] allow equivalent units348 | to pass349 can_be_negative `bool` [DEFAULT `True`] values can be negative350 can_be_complex `bool` [DEFAULT `False`] values can be complex numbers351 can_be_inf `bool` [DEFAULT `True`] values can be :data:`~numpy.inf`352 can_be_nan `bool` [DEFAULT `True`] values can be :data:`~numpy.nan`353 none_shall_pass `bool` [DEFAULT `False`] values can be a python `None`354 ====================== ======= ================================================355 Notes356 -----357 * Validation of function arguments `*args` and `**kwargs` is not supported.358 * `None` values will pass when `None` is included in the list of specified units,359 is set as a default value for the function argument, or `none_shall_pass` is360 set to `True`. If `none_shall_pass` is doubly/triply defined through the361 mentioned options, then they all must be consistent with each other.362 * If units are not specified in `validations`, then the decorator will attempt363 to identify desired units by examining the function annotations.364 * Full functionality is defined by the class :class:`ValidateQuantities`.365 Examples366 --------367 Define unit and value validations with decorator parameters::368 import astropy.units as u369 from plasmapy.utils.decorators import validate_quantities370 @validate_quantities(mass={'units': u.g,371 'can_be_negative': False},372 vel=u.cm / u.s,373 validations_on_return=[u.g * u.cm / u.s, u.kg * u.m / u.s])374 def foo(mass, vel):375 return mass * vel376 # on a method377 class Foo:378 @validate_quantities(mass={'units': u.g,379 'can_be_negative': False},380 vel=u.cm / u.s,381 validations_on_return=[u.g * u.cm / u.s,382 u.kg * u.m / u.s])383 def bar(self, mass, vel):384 return mass * vel385 Define units with function annotations::386 import astropy.units as u387 from plasmapy.utils.decorators import validate_quantities388 @validate_quantities(mass={'can_be_negative': False})389 def foo(mass: u.g, vel: u.cm / u.s) -> u.g * u.cm / u.s:390 return mass * vel391 # rely only on annotations392 @validate_quantities393 def foo(x: u.cm, time: u.s) -> u.cm / u.s:394 return x / time395 # on a method396 class Foo:397 @validate_quantities(mass={'can_be_negative': False})398 def bar(self, mass: u.g, vel: u.cm / u.s) -> u.g * u.cm / u.s:399 return mass * vel400 Allow `None` values to pass::401 import astropy.units as u402 from plasmapy.utils.decorators import validate_quantities403 @validate_quantities(arg2={'none_shall_pass': True},404 checks_on_return=[u.cm, None])405 def foo(arg1: u.cm = None, arg2: u.cm):406 return None407 Allow return values to have equivalent units::408 import astropy.units as u409 from plasmapy.utils.decorators import validate_quantities410 @validate_quantities(arg1={'units': u.cm},411 checks_on_return={'units': u.km,412 'pass_equivalent_units': True})413 def foo(arg1):414 return arg1415 Allow equivalent units to pass with specified equivalencies::416 import astropy.units as u417 from plasmapy.utils.decorators import validate_quantities418 @validate_quantities(arg1={'units': u.K,419 'equivalencies': u.temperature(),420 'pass_equivalent_units': True})421 def foo(arg1):422 return arg1423 .. _astropy equivalencies:424 https://docs.astropy.org/en/stable/units/equivalencies.html425 """426 if validations_on_return is not None:427 validations["validations_on_return"] = validations_on_return428 if func is not None:429 # `validate_quantities` called as a function430 return ValidateQuantities(**validations)(func)431 else:432 # `validate_quantities` called as a decorator "sugar-syntax"...

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