def test_particle_input_simple(func, args, kwargs, symbol):
"""
Test that simple functions decorated by particle_input correctly
return the correct Particle object.
"""
try:
expected = Particle(symbol)
except Exception as e:
raise ParticleError(
f"Cannot create Particle class from symbol {symbol}") from e
try:
result = func(*args, **kwargs)
except Exception as e:
raise ParticleError(
f"An exception was raised while trying to execute "
f"{func} with args = {args} and kwargs = {kwargs}.") from e
assert result == expected, (
f"The result {repr(result)} does not equal the expected value of "
f"{repr(expected)}.\n\n"
f"func = {func}\n"
f"args = {args}\n"
f"kwargs = {kwargs}\nsymbol = {symbol}\n"
f"{result._attributes}\n"
f"{expected._attributes}\n")
def __init__(
self,
particle: Particle,
ionic_fractions=None,
*,
T_e: u.K = np.nan * u.K,
T_i: u.K = None,
kappa: Real = np.inf,
n_elem: u.m**-3 = np.nan * u.m**-3,
tol: Union[float, int] = 1e-15,
):
"""
Initialize an `~plasmapy.particles.ionization_state.IonizationState`
instance.
"""
self._number_of_particles = particle.atomic_number + 1
if particle.is_ion or particle.is_category(require=("uncharged",
"element")):
if ionic_fractions is None:
ionic_fractions = np.zeros(self._number_of_particles)
ionic_fractions[particle.charge_number] = 1.0
particle = Particle(
particle.isotope if particle.isotope else particle.element)
else:
raise ParticleError(
"The ionic fractions must not be specified when "
"the input particle to IonizationState is an ion.")
self._particle = particle
try:
self.tol = tol
self.T_e = T_e
self.T_i = T_i
self.kappa = kappa
if (not np.isnan(n_elem)
and isinstance(ionic_fractions, u.Quantity)
and ionic_fractions.si.unit == u.m**-3):
raise ParticleError(
"Cannot simultaneously provide number density "
"through both n_elem and ionic_fractions.")
self.n_elem = n_elem
self.ionic_fractions = ionic_fractions
if ionic_fractions is None and not np.isnan(self.T_e):
warnings.warn(
"Collisional ionization equilibration has not yet "
"been implemented in IonizationState; cannot set "
"ionic fractions.")
except Exception as exc:
raise ParticleError(
f"Unable to create IonizationState object for {particle.symbol}."
) from exc
def T_e(self, value: u.K):
"""Set the electron temperature."""
try:
value = value.to(u.K, equivalencies=u.temperature_energy())
except (AttributeError, u.UnitsError, u.UnitConversionError):
raise ParticleError("Invalid temperature.") from None
else:
if value < 0 * u.K:
raise ParticleError("T_e cannot be negative.")
self._T_e = value
def abundances(self, abundances_dict: Optional[Dict[ParticleLike, Real]]):
"""
Set the elemental (or isotopic) abundances. The elements and
isotopes must be the same as or a superset of the elements whose
ionization states are being tracked.
"""
if abundances_dict is None:
self._pars["abundances"] = {elem: np.nan for elem in self.base_particles}
elif not isinstance(abundances_dict, dict):
raise TypeError(
f"The abundances attribute must be a dict with "
f"elements or isotopes as keys and real numbers "
f"representing relative abundances as values."
)
else:
old_keys = abundances_dict.keys()
try:
new_keys_dict = {}
for old_key in old_keys:
new_keys_dict[particle_symbol(old_key)] = old_key
except Exception:
raise ParticleError(
f"The key {repr(old_key)} in the abundances "
f"dictionary is not a valid element or isotope."
)
new_elements = new_keys_dict.keys()
old_elements_set = set(self.base_particles)
new_elements_set = set(new_elements)
if old_elements_set - new_elements_set:
raise ParticleError(
f"The abundances of the following particles are "
f"missing: {old_elements_set - new_elements_set}"
)
new_abundances_dict = {}
for element in new_elements:
inputted_abundance = abundances_dict[new_keys_dict[element]]
try:
inputted_abundance = float(inputted_abundance)
except Exception:
raise TypeError(
f"The abundance for {element} was provided as"
f"{inputted_abundance}, which cannot be "
f"converted to a real number."
) from None
if inputted_abundance < 0:
raise ParticleError(f"The abundance of {element} is negative.")
new_abundances_dict[element] = inputted_abundance
self._pars["abundances"] = new_abundances_dict
def number_densities(self, value: u.m**-3):
"""Set the number densities for each state."""
if np.any(value.value < 0):
raise ParticleError("Number densities cannot be negative.")
if len(value) != self.atomic_number + 1:
raise ParticleError(
f"Incorrect number of charge states for {self.base_particle}")
value = value.to(u.m**-3)
self._n_elem = value.sum()
self._ionic_fractions = value / self._n_elem
def n0(self, n: u.m ** -3):
"""Set the number density scaling factor."""
try:
n = n.to(u.m ** -3)
except u.UnitConversionError as exc:
raise ParticleError("Units cannot be converted to u.m ** -3.") from exc
except Exception as exc:
raise ParticleError(f"{n} is not a valid number density.") from exc
if n < 0 * u.m ** -3:
raise ParticleError("Number density cannot be negative.")
self._pars["n"] = n.to(u.m ** -3)
def T_e(self, electron_temperature: u.K):
"""Set the electron temperature."""
try:
temperature = electron_temperature.to(
u.K, equivalencies=u.temperature_energy())
except (AttributeError, u.UnitsError):
raise ParticleError(
f"{electron_temperature} is not a valid temperature."
) from None
if temperature < 0 * u.K:
raise ParticleError("The electron temperature cannot be negative.")
self._pars["T_e"] = temperature
def __init__(
self,
inputs: Union[Dict[str, np.ndarray], List, Tuple],
*,
T_e: u.K = np.nan * u.K,
abundances: Optional[Dict[str, Real]] = None,
log_abundances: Optional[Dict[str, Real]] = None,
n0: u.m ** -3 = np.nan * u.m ** -3,
tol: Real = 1e-15,
kappa: Real = np.inf,
):
abundances_provided = abundances is not None or log_abundances is not None
set_abundances = True
if isinstance(inputs, dict):
all_quantities = np.all(
[isinstance(fracs, u.Quantity) for fracs in inputs.values()]
)
if all_quantities:
right_units = np.all(
[fracs[0].si.unit == u.m ** -3 for fracs in inputs.values()]
)
if not right_units:
raise ParticleError(
"Units must be inverse volume for number densities."
)
if abundances_provided:
raise ParticleError(
"Abundances cannot be provided if inputs "
"provides number density information."
)
set_abundances = False
try:
self._pars = dict()
self.T_e = T_e
self.n0 = n0
self.tol = tol
self.ionic_fractions = inputs
if set_abundances:
self.abundances = abundances
self.log_abundances = log_abundances
self.kappa = kappa
except Exception as exc:
raise ParticleError(
"Unable to create IonizationStateCollection object."
) from exc
def process_particles_list(
unformatted_particles_list: List[Union[str,
Particle]]) -> List[Particle]:
"""
Take an unformatted list of particles and puts each
particle into standard form, while allowing an integer and
asterisk immediately preceding a particle to act as a
multiplier. A string argument will be treated as a list
containing that string as its sole item.
"""
if isinstance(unformatted_particles_list, str):
unformatted_particles_list = [unformatted_particles_list]
if not isinstance(unformatted_particles_list, (list, tuple)):
raise TypeError("The input to process_particles_list should be a "
"string, list, or tuple.")
particles = []
for original_item in unformatted_particles_list:
try:
item = original_item.strip()
if item.count("*") == 1 and item[0].isdigit():
multiplier_str, item = item.split("*")
multiplier = int(multiplier_str)
else:
multiplier = 1
try:
particle = Particle(item)
except (InvalidParticleError) as exc:
raise ParticleError(errmsg) from exc
if particle.element and not particle.isotope:
raise ParticleError(errmsg)
[particles.append(particle) for i in range(multiplier)]
except Exception:
raise ParticleError(
f"{original_item} is not a valid reactant or "
"product in a nuclear reaction.") from None
return particles
def test_particle_input_classes():
instance = Test_particle_input()
symbol = "muon"
expected = Particle(symbol)
try:
result_noparens = instance.method_noparens(symbol)
except Exception as e:
raise ParticleError("Problem with method_noparens") from e
try:
result_parens = instance.method_parens(symbol)
except Exception as e:
raise ParticleError("Problem with method_parens") from e
assert result_parens == result_noparens == expected
def __init__(self, ion: Particle, ionic_fraction=None, number_density=None):
try:
self.ion = ion
self.ionic_fraction = ionic_fraction
self.number_density = number_density
except Exception as exc:
raise ParticleError("Unable to create IonicLevel object") from exc
def function_to_test_annotations(particles: Union[Tuple, List],
resulting_particles):
"""
Test that a function with an argument annotated with (Particle,
Particle, ...) or [Particle] returns a tuple of expected Particle
instances.
Arguments
=========
particles: tuple or list
A collection containing many items, each of which may be a valid
representation of a particle or a `~plasmapy.particles.Particle`
instance
"""
expected = [
particle if isinstance(particle, Particle) else Particle(particle)
for particle in particles
]
# Check that the returned values are Particle instances because
# running:
# Particle('p+') == 'p+'
# will return True because of how Particle.__eq__ is set up.
returned_particle_instances = all(
isinstance(p, Particle) for p in resulting_particles)
returned_correct_instances = all(expected[i] == resulting_particles[i]
for i in range(len(particles)))
if not returned_particle_instances:
raise ParticleError(
f"A function decorated by particle_input did not return "
f"a collection of Particle instances for input of "
f"{repr(particles)}, and instead returned"
f"{repr(resulting_particles)}.")
if not returned_correct_instances:
raise ParticleError(
f"A function decorated by particle_input did not return "
f"{repr(expected)} as expected, and instead returned "
f"{repr(resulting_particles)}.")
def __eq__(self, other):
if not isinstance(other, IonizationStateCollection):
raise TypeError(
"IonizationStateCollection instance can only be compared with "
"other IonizationStateCollection instances.")
if self.base_particles != other.base_particles:
raise ParticleError(
"Two IonizationStateCollection instances can be compared only "
"if the base particles are the same.")
min_tol = np.min([self.tol, other.tol])
# Check any of a whole bunch of equality measures, recalling
# that np.nan == np.nan is False.
for attribute in ["T_e", "n_e", "kappa"]:
this = getattr(self, attribute)
that = getattr(other, attribute)
# TODO: Maybe create a function in utils called same_enough
# TODO: that would take care of all of these disparate
# TODO: equality measures.
this_equals_that = np.any([
this == that,
this is that,
np.isnan(this) and np.isnan(that),
np.isinf(this) and np.isinf(that),
u.quantity.allclose(this, that, rtol=min_tol),
])
if not this_equals_that:
return False
for attribute in ["ionic_fractions", "number_densities"]:
this_dict = getattr(self, attribute)
that_dict = getattr(other, attribute)
for particle in self.base_particles:
this = this_dict[particle]
that = that_dict[particle]
this_equals_that = np.any([
this is that,
np.all(np.isnan(this)) and np.all(np.isnan(that)),
u.quantity.allclose(this, that, rtol=min_tol),
])
if not this_equals_that:
return False
return True
def ionic_fractions(self, fractions):
"""
Set the ionic fractions, while checking that the new values are
valid and normalized to one.
"""
if fractions is None or np.all(np.isnan(fractions)):
self._ionic_fractions = np.full(self.atomic_number + 1,
np.nan,
dtype=np.float64)
return
try:
if np.min(fractions) < 0:
raise ParticleError("Cannot have negative ionic fractions.")
if len(fractions) != self.atomic_number + 1:
raise ParticleError("The length of ionic_fractions must be "
f"{self.atomic_number + 1}.")
if isinstance(fractions, u.Quantity):
fractions = fractions.to(u.m**-3)
self.n_elem = np.sum(fractions)
self._ionic_fractions = np.array(fractions / self.n_elem)
else:
fractions = np.array(fractions, dtype=np.float64)
sum_of_fractions = np.sum(fractions)
all_nans = np.all(np.isnan(fractions))
if not all_nans:
if np.any(fractions < 0) or np.any(fractions > 1):
raise ParticleError(
"Ionic fractions must be between 0 and 1.")
if not np.isclose(
sum_of_fractions, 1, rtol=0, atol=self.tol):
raise ParticleError("Ionic fractions must sum to one.")
self._ionic_fractions = fractions
except Exception as exc:
raise ParticleError(
f"Unable to set ionic fractions of {self.element} to {fractions}."
) from exc
def log_abundances(self, value: Optional[Dict[str, Real]]):
"""Set the base 10 logarithm of the relative abundances."""
if value is not None:
try:
new_abundances_input = {}
for key in value.keys():
new_abundances_input[key] = 10**value[key]
self.abundances = new_abundances_input
except Exception:
raise ParticleError("Invalid log_abundances.") from None
def log_abundances(self, value: Optional[Dict[str, Real]]):
"""Set the base 10 logarithm of the relative abundances."""
if value is not None:
try:
new_abundances_input = {
atom: 10**log_abundance
for atom, log_abundance in value.items()
}
self.abundances = new_abundances_input
except ParticleError:
raise ParticleError("Invalid log_abundances.") from None
def __init__(self,
ion: Particle,
ionic_fraction=None,
number_density=None,
T_i=None):
try:
self.ion = ion
self.ionic_fraction = ionic_fraction
self.number_density = number_density
self.T_i = T_i
except (ValueError, TypeError) as exc:
raise ParticleError("Unable to create IonicLevel object") from exc
def test_list_annotation(particles: Union[Tuple, List]):
try:
resulting_particles = function_with_list_annotation(particles,
"ignore",
x="ignore")
except Exception as exc2:
raise ParticleError(
f"Unable to evaluate a function decorated by particle_input"
f" with an annotation of [Particle] for inputs of"
f" {repr(particles)}.") from exc2
function_to_test_annotations(particles, resulting_particles)
def test_that_ionic_fractions_are_set_correctly(self, test_name):
errmsg = ""
elements_actual = self.instances[test_name].base_particles
inputs = tests[test_name]["inputs"]
if isinstance(inputs, dict):
input_keys = list(tests[test_name]["inputs"].keys())
input_keys = sorted(
input_keys,
key=lambda k: (
atomic_number(k),
mass_number(k) if Particle(k).isotope else 0,
),
)
for element, input_key in zip(elements_actual, input_keys):
expected = tests[test_name]["inputs"][input_key]
if isinstance(expected, u.Quantity):
expected = np.array(expected.value /
np.sum(expected.value))
actual = self.instances[test_name].ionic_fractions[element]
if not np.allclose(actual, expected):
errmsg += (
f"\n\nThere is a discrepancy in ionic fractions for "
f"({test_name}, {element}, {input_key})\n"
f" expected = {expected}\n"
f" actual = {actual}")
if not isinstance(actual, np.ndarray) or isinstance(
actual, u.Quantity):
raise ParticleError(
f"\n\nNot a numpy.ndarray: ({test_name}, {element})")
else:
elements_expected = {
particle_symbol(element)
for element in inputs
}
assert set(
self.instances[test_name].base_particles) == elements_expected
for element in elements_expected:
assert all(
np.isnan(
self.instances[test_name].ionic_fractions[element]))
if errmsg:
pytest.fail(errmsg)
def test_Particle_class(arg, kwargs, expected_dict):
"""
Test that `~plasmapy.particles.Particle` objects for different
subatomic particles, elements, isotopes, and ions return the
expected properties. Provide a detailed error message that lists
all of the inconsistencies with the expected results.
"""
call = call_string(Particle, arg, kwargs)
errmsg = ""
try:
particle = Particle(arg, **kwargs)
except Exception as exc:
raise ParticleError(f"Problem creating {call}") from exc
for key in expected_dict.keys():
expected = expected_dict[key]
if inspect.isclass(expected) and issubclass(expected, Exception):
# Exceptions are expected to be raised when accessing certain
# attributes for some particles. For example, accessing a
# neutrino's mass should raise a MissingParticleDataError since
# only upper limits of neutrino masses are presently available.
# If expected_dict[key] is an exception, then check to make
# sure that this exception is raised.
try:
with pytest.raises(expected):
exec(f"particle.{key}")
except pytest.fail.Exception:
errmsg += f"\n{call}[{key}] does not raise {expected}."
except Exception:
errmsg += (f"\n{call}[{key}] does not raise {expected} but "
f"raises a different exception.")
else:
try:
result = eval(f"particle.{key}")
assert result == expected or u.isclose(result, expected)
except AssertionError:
errmsg += (f"\n{call}.{key} returns {result} instead "
f"of the expected value of {expected}.")
except Exception:
errmsg += f"\n{call}.{key} raises an unexpected exception."
if len(errmsg) > 0:
raise Exception(f"Problems with {call}:{errmsg}")
def __getitem__(self, value) -> IonicLevel:
"""Return information for a single ionization level."""
if isinstance(value, slice):
return [
IonicLevel(
ion=Particle(self.base_particle, Z=val),
ionic_fraction=self.ionic_fractions[val],
number_density=self.number_densities[val],
T_i=self.T_i[val],
) for val in range(0, self._number_of_particles)[value]
]
if isinstance(value, Integral) and 0 <= value <= self.atomic_number:
result = IonicLevel(
ion=Particle(self.base_particle, Z=value),
ionic_fraction=self.ionic_fractions[value],
number_density=self.number_densities[value],
T_i=self.T_i[value],
)
else:
if not isinstance(value, Particle):
try:
value = Particle(value)
except InvalidParticleError as exc:
raise InvalidParticleError(
f"{value} is not a valid charge number or particle."
) from exc
same_element = value.element == self.element
same_isotope = value.isotope == self.isotope
has_charge_info = value.is_category(
any_of=["charged", "uncharged"])
if same_element and same_isotope and has_charge_info:
Z = value.charge_number
result = IonicLevel(
ion=Particle(self.base_particle, Z=Z),
ionic_fraction=self.ionic_fractions[Z],
number_density=self.number_densities[Z],
T_i=self.T_i[Z],
)
else:
if not same_element or not same_isotope:
raise ParticleError("Inconsistent element or isotope.")
elif not has_charge_info:
raise ChargeError("No charge number provided.")
return result
def T_i(self, value: u.K):
"""Set the ion temperature."""
if value is None:
self._T_i = np.repeat(self._T_e, self._number_of_particles)
return
if value.size == 1:
self._T_i = np.repeat(value, self._number_of_particles)
elif value.size == self._number_of_particles:
self._T_i = value
else:
error_str = (
"T_i must be set with either one common temperature"
f" for all ions, or a set of {self._number_of_particles} of them. "
)
if value.size == 5 and self._number_of_particles != 5:
error_str += " For {self.base_particle}, five is right out."
raise ParticleError(error_str)
def Z_most_abundant(self) -> List[Integral]:
"""
A `list` of the charge numbers with the highest ionic fractions.
Examples
--------
>>> He = IonizationState('He', [0.2, 0.5, 0.3])
>>> He.Z_most_abundant
[1]
>>> Li = IonizationState('Li', [0.4, 0.4, 0.2, 0.0])
>>> Li.Z_most_abundant
[0, 1]
"""
if np.any(np.isnan(self.ionic_fractions)):
raise ParticleError(
f"Cannot find most abundant ion of {self.base_particle} "
f"because the ionic fractions have not been defined.")
return np.flatnonzero(
self.ionic_fractions == self.ionic_fractions.max()).tolist()
def __getitem__(self, value) -> IonicFraction:
"""Return information for a single ionization level."""
if isinstance(value, slice):
raise TypeError("IonizationState instances cannot be sliced.")
if isinstance(value, Integral) and 0 <= value <= self.atomic_number:
result = IonicFraction(
ion=Particle(self.base_particle, Z=value),
ionic_fraction=self.ionic_fractions[value],
number_density=self.number_densities[value],
)
else:
if not isinstance(value, Particle):
try:
value = Particle(value)
except InvalidParticleError as exc:
raise InvalidParticleError(
f"{value} is not a valid integer charge or particle."
) from exc
same_element = value.element == self.element
same_isotope = value.isotope == self.isotope
has_charge_info = value.is_category(
any_of=["charged", "uncharged"])
if same_element and same_isotope and has_charge_info:
Z = value.integer_charge
result = IonicFraction(
ion=Particle(self.base_particle, Z=Z),
ionic_fraction=self.ionic_fractions[Z],
number_density=self.number_densities[Z],
)
else:
if not same_element or not same_isotope:
raise ParticleError("Inconsistent element or isotope.")
elif not has_charge_info:
raise ChargeError("No integer charge provided.")
return result
def ionic_fractions(self, inputs: Union[Dict, List, Tuple]):
"""
Set the ionic fractions.
Notes
-----
The ionic fractions are initialized during instantiation of
`~plasmapy.particles.IonizationStateCollection`. After this, the
only way to reset the ionic fractions via the ``ionic_fractions``
attribute is via a `dict` with elements or isotopes that are a
superset of the previous elements or isotopes. However, you may
use item assignment of the `~plasmapy.particles.IonizationState`
instance to assign new ionic fractions one element or isotope
at a time.
Raises
------
`~plasmapy.particles.exceptions.ParticleError`
If the ionic fractions cannot be set.
`TypeError`
If ``inputs`` is not a `list`, `tuple`, or `dict` during
instantiation, or if ``inputs`` is not a `dict` when it is
being set.
"""
# A potential problem is that using item assignment on the
# ionic_fractions attribute could cause the original attributes
# to be overwritten without checks being performed. We might
# eventually want to create a new class or subclass of UserDict
# that goes through these checks. In the meantime, we should
# make it clear to users to set ionic_fractions by using item
# assignment on the IonizationStateCollection instance as a whole. An
# example of the problem is `s = IonizationStateCollection(["He"])` being
# followed by `s.ionic_fractions["He"] = 0.3`.
if hasattr(self, "_ionic_fractions"):
if not isinstance(inputs, dict):
raise TypeError(
"Can only reset ionic_fractions with a dict if "
"ionic_fractions has been set already."
)
old_particles = set(self.base_particles)
new_particles = {particle_symbol(key) for key in inputs.keys()}
missing_particles = old_particles - new_particles
if missing_particles:
raise ParticleError(
"Can only reset ionic fractions with a dict if "
"the new base particles are a superset of the "
"prior base particles. To change ionic fractions "
"for one base particle, use item assignment on the "
"IonizationStateCollection instance instead."
)
if isinstance(inputs, dict):
original_keys = inputs.keys()
ionfrac_types = {type(inputs[key]) for key in original_keys}
inputs_have_quantities = u.Quantity in ionfrac_types
if inputs_have_quantities and len(ionfrac_types) != 1:
raise TypeError(
"Ionic fraction information may only be inputted "
"as a Quantity object if all ionic fractions are "
"Quantity arrays with units of inverse volume."
)
try:
particles = {key: Particle(key) for key in original_keys}
except (InvalidParticleError, TypeError) as exc:
raise ParticleError(
"Unable to create IonizationStateCollection instance "
"because not all particles are valid."
) from exc
# The particles whose ionization states are to be recorded
# should be elements or isotopes but not ions or neutrals.
for key in particles.keys():
is_element = particles[key].is_category("element")
has_charge_info = particles[key].is_category(
any_of=["charged", "uncharged"]
)
if not is_element or has_charge_info:
raise ParticleError(
f"{key} is not an element or isotope without "
f"charge information."
)
# We are sorting the elements/isotopes by atomic number and
# mass number since we will often want to plot and analyze
# things and this is the most sensible order.
def _sort_entries_by_atomic_and_mass_numbers(k):
return (
particles[k].atomic_number,
particles[k].mass_number if particles[k].isotope else 0,
)
sorted_keys = sorted(
original_keys, key=_sort_entries_by_atomic_and_mass_numbers
)
_elements_and_isotopes = []
_particle_instances = []
new_ionic_fractions = {}
if inputs_have_quantities:
n_elems = {}
for key in sorted_keys:
new_key = particles[key].symbol
_particle_instances.append(particles[key])
if new_key in _elements_and_isotopes:
raise ParticleError(
"Repeated particles in IonizationStateCollection."
)
nstates_input = len(inputs[key])
nstates = particles[key].atomic_number + 1
if nstates != nstates_input:
raise ParticleError(
f"The ionic fractions array for {key} must "
f"have a length of {nstates}."
)
_elements_and_isotopes.append(new_key)
if inputs_have_quantities:
try:
number_densities = inputs[key].to(u.m ** -3)
n_elem = np.sum(number_densities)
new_ionic_fractions[new_key] = np.array(
number_densities / n_elem
)
n_elems[key] = n_elem
except u.UnitConversionError as exc:
raise ParticleError("Units are not inverse volume.") from exc
elif (
isinstance(inputs[key], np.ndarray)
and inputs[key].dtype.kind == "f"
):
new_ionic_fractions[particles[key].symbol] = inputs[key]
else:
try:
new_ionic_fractions[particles[key].symbol] = np.array(
inputs[key], dtype=np.float
)
except ValueError as exc:
raise ParticleError(
f"Inappropriate ionic fractions for {key}."
) from exc
for key in _elements_and_isotopes:
fractions = new_ionic_fractions[key]
if not np.all(np.isnan(fractions)):
if np.min(fractions) < 0 or np.max(fractions) > 1:
raise ParticleError(
f"Ionic fractions for {key} are not between 0 and 1."
)
if not np.isclose(np.sum(fractions), 1, atol=self.tol, rtol=0):
raise ParticleError(
f"Ionic fractions for {key} are not normalized to 1."
)
# When the inputs provide the densities, the abundances must
# not have been provided because that would be redundant
# or contradictory information. The number density scaling
# factor might or might not have been provided. Have the
# number density scaling factor default to the total number
# of neutrals and ions across all elements and isotopes, if
# it was not provided. Then go ahead and calculate the
# abundances based on that. However, we need to be careful
# that the abundances are not overwritten during the
# instantiation of the class.
if inputs_have_quantities:
if np.isnan(self.n0):
new_n = 0 * u.m ** -3
for key in _elements_and_isotopes:
new_n += n_elems[key]
self.n0 = new_n
new_abundances = {}
for key in _elements_and_isotopes:
new_abundances[key] = np.float(n_elems[key] / self.n0)
self._pars["abundances"] = new_abundances
elif isinstance(inputs, (list, tuple)):
try:
_particle_instances = [Particle(particle) for particle in inputs]
except (InvalidParticleError, TypeError) as exc:
raise ParticleError(
"Invalid inputs to IonizationStateCollection."
) from exc
_particle_instances.sort(key=_atomic_number_and_mass_number)
_elements_and_isotopes = [
particle.symbol for particle in _particle_instances
]
new_ionic_fractions = {
particle.symbol: np.full(
particle.atomic_number + 1, fill_value=np.nan, dtype=np.float64
)
for particle in _particle_instances
}
else:
raise TypeError("Incorrect inputs to set ionic_fractions.")
for i in range(1, len(_particle_instances)):
if _particle_instances[i - 1].element == _particle_instances[i].element:
if (
not _particle_instances[i - 1].isotope
and _particle_instances[i].isotope
):
raise ParticleError(
"Cannot have an element and isotopes of that element."
)
self._particle_instances = _particle_instances
self._base_particles = _elements_and_isotopes
self._ionic_fractions = new_ionic_fractions
def __setitem__(self, key, value):
errmsg = (
f"Cannot set item for this IonizationStateCollection instance for "
f"key = {repr(key)} and value = {repr(value)}"
)
try:
particle = particle_symbol(key)
self.ionic_fractions[key]
except (ParticleError, TypeError):
raise KeyError(
f"{errmsg} because {repr(key)} is an invalid particle."
) from None
except KeyError:
raise KeyError(
f"{errmsg} because {repr(key)} is not one of the base "
f"particles whose ionization state is being kept track "
f"of."
) from None
if isinstance(value, u.Quantity) and value.unit != u.dimensionless_unscaled:
try:
new_number_densities = value.to(u.m ** -3)
except u.UnitConversionError:
raise ValueError(
f"{errmsg} because the units of value do not "
f"correspond to a number density."
) from None
old_n_elem = np.sum(self.number_densities[particle])
new_n_elem = np.sum(new_number_densities)
density_was_nan = np.all(np.isnan(self.number_densities[particle]))
same_density = u.quantity.allclose(old_n_elem, new_n_elem, rtol=self.tol)
if not same_density and not density_was_nan:
raise ValueError(
f"{errmsg} because the old element number density "
f"of {old_n_elem} is not approximately equal to "
f"the new element number density of {new_n_elem}."
)
value = (new_number_densities / new_n_elem).to(u.dimensionless_unscaled)
# If the abundance of this particle has not been defined,
# then set the abundance if there is enough (but not too
# much) information to do so.
abundance_is_undefined = np.isnan(self.abundances[particle])
isnan_of_abundance_values = np.isnan(list(self.abundances.values()))
all_abundances_are_nan = np.all(isnan_of_abundance_values)
n_is_defined = not np.isnan(self.n0)
if abundance_is_undefined:
if n_is_defined:
self._pars["abundances"][particle] = new_n_elem / self.n0
elif all_abundances_are_nan:
self.n0 = new_n_elem
self._pars["abundances"][particle] = 1
else:
raise ParticleError(
f"Cannot set number density of {particle} to "
f"{value * new_n_elem} when the number density "
f"scaling factor is undefined, the abundance "
f"of {particle} is undefined, and some of the "
f"abundances of other elements/isotopes is "
f"defined."
)
try:
new_fractions = np.array(value, dtype=np.float64)
except Exception as exc:
raise TypeError(
f"{errmsg} because value cannot be converted into an "
f"array that represents ionic fractions."
) from exc
# TODO: Create a separate function that makes sure ionic
# TODO: fractions are valid to reduce code repetition. This
# TODO: would probably best go as a private function in
# TODO: ionization_state.py.
required_nstates = atomic_number(particle) + 1
new_nstates = len(new_fractions)
if new_nstates != required_nstates:
raise ValueError(
f"{errmsg} because value must have {required_nstates} "
f"ionization levels but instead corresponds to "
f"{new_nstates} levels."
)
all_nans = np.all(np.isnan(new_fractions))
if not all_nans and (new_fractions.min() < 0 or new_fractions.max() > 1):
raise ValueError(
f"{errmsg} because the new ionic fractions are not "
f"all between 0 and 1."
)
normalized = np.isclose(np.sum(new_fractions), 1, rtol=self.tol)
if not normalized and not all_nans:
raise ValueError(
f"{errmsg} because the ionic fractions are not normalized to one."
)
self._ionic_fractions[particle][:] = new_fractions[:]
def get_particle(argname, params, already_particle, funcname):
argval, Z, mass_numb = params
"""
Convert the argument to a
`~plasmapy.particles.particle_class.Particle` object if it is
not already one.
"""
if not already_particle:
if not isinstance(argval, (numbers.Integral, str, tuple, list)):
raise TypeError(
f"The argument {argname} to {funcname} must be "
f"a string, an integer or a tuple or list of them "
f"corresponding to an atomic number, or a "
f"Particle object.")
try:
particle = Particle(argval, Z=Z, mass_numb=mass_numb)
except InvalidParticleError as e:
raise InvalidParticleError(
_particle_errmsg(argname, argval, Z, mass_numb,
funcname)) from e
# We will need to do the same error checks whether or not the
# argument is already an instance of the Particle class.
if already_particle:
particle = argval
# If the name of the argument annotated with Particle in the
# decorated function is element, isotope, or ion; then this
# decorator should raise the appropriate exception when the
# particle ends up not being an element, isotope, or ion.
cat_table = [
("element", particle.element, InvalidElementError),
("isotope", particle.isotope, InvalidIsotopeError),
("ion", particle.ionic_symbol, InvalidIonError),
]
for category_name, category_symbol, CategoryError in cat_table:
if argname == category_name and not category_symbol:
raise CategoryError(
f"The argument {argname} = {repr(argval)} to "
f"{funcname} does not correspond to a valid "
f"{argname}.")
# Some functions require that particles be charged, or
# at least that particles have charge information.
_charge_number = particle._attributes["charge number"]
must_be_charged = "charged" in require
must_have_charge_info = set(any_of) == {"charged", "uncharged"}
uncharged = _charge_number == 0
lacks_charge_info = _charge_number is None
if must_be_charged and (uncharged or must_have_charge_info):
raise ChargeError(
f"A charged particle is required for {funcname}.")
if must_have_charge_info and lacks_charge_info:
raise ChargeError(
f"Charge information is required for {funcname}.")
# Some functions require particles that belong to more complex
# classification schemes. Again, be sure to provide a
# maximally useful error message.
if not particle.is_category(
require=require, exclude=exclude, any_of=any_of):
raise ParticleError(
_category_errmsg(particle, require, exclude, any_of, funcname))
return particle
def wrapper(*args, **kwargs):
annotations = wrapped_function.__annotations__
bound_args = wrapped_signature.bind(*args, **kwargs)
default_arguments = bound_args.signature.parameters
arguments = bound_args.arguments
argnames = bound_args.signature.parameters.keys()
# Handle optional-only arguments in function declaration
for default_arg in default_arguments:
# The argument is not contained in `arguments` if the
# user does not explicitly pass an optional argument.
# In such cases, manually add it to `arguments` with
# the default value of parameter.
if default_arg not in arguments:
arguments[default_arg] = default_arguments[
default_arg].default
funcname = wrapped_function.__name__
args_to_become_particles = []
for argname in annotations.keys():
if isinstance(annotations[argname], tuple):
if argname == "return":
continue
annotated_argnames = annotations[argname]
expected_params = len(annotated_argnames)
received_params = len(arguments[argname])
if expected_params != received_params:
raise ValueError(
f"Number of parameters allowed in the tuple "
f"({expected_params} parameters) are "
f"not equal to number of parameters passed in "
f"the tuple ({received_params} parameters).")
elif isinstance(annotations[argname], list):
annotated_argnames = annotations[argname]
expected_params = len(annotated_argnames)
if expected_params > 1:
raise TypeError(
"Put in [Particle] as the annotation to "
"accept arbitrary number of Particle arguments.")
else:
annotated_argnames = (annotations[argname], )
for annotated_argname in annotated_argnames:
is_particle = (annotated_argname is Particle
or annotated_argname is Optional[Particle])
if is_particle and argname != "return":
args_to_become_particles.append(argname)
if not args_to_become_particles:
raise ParticleError(
f"None of the arguments or keywords to {funcname} "
f"have been annotated with Particle, as required "
f"by the @particle_input decorator.")
elif len(args_to_become_particles) > 1:
if "Z" in argnames or "mass_numb" in argnames:
raise ParticleError(
f"The arguments Z and mass_numb in {funcname} are not "
f"allowed when more than one argument or keyword is "
f"annotated with Particle in functions decorated "
f"with @particle_input.")
for x in args_to_become_particles:
if (annotations[x] is Particle
and isinstance(arguments[x], (tuple, list))
and len(arguments[x]) > 1):
raise TypeError(
f"You cannot pass a tuple or list containing "
f"Particles when only single Particle was "
f"expected, instead found {arguments[x]}. If you "
f"intend to pass more than 1 Particle instance, "
f"use a tuple or a list type. "
f"That is use (Particle, Particle, ...) or "
f"[Particle] in function declaration.")
# If the number of arguments and keywords annotated with
# Particle is exactly one, then the Z and mass_numb keywords
# can be used without potential for ambiguity.
Z = arguments.get("Z", None)
mass_numb = arguments.get("mass_numb", None)
# Go through the argument names and check whether or not they are
# annotated with Particle. If they aren't, include the name and
# value of the argument as an item in the new keyword arguments
# dictionary unchanged. If they are annotated with Particle, then
# either convert the representation of a Particle to a Particle if
# it is not already a Particle and then do error checks.
new_kwargs = {}
for argname in argnames:
raw_argval = arguments[argname]
if isinstance(raw_argval, (tuple, list)):
# Input argument value is a tuple or list
# of corresponding particles or atomic values.
argval_tuple = raw_argval
particles = []
else:
# Otherwise convert it to tuple anyway so it can work
# with loops too.
argval_tuple = (raw_argval, )
for pos, argval in enumerate(argval_tuple):
should_be_particle = argname in args_to_become_particles
# If the argument is not annotated with Particle, then we just
# pass it through to the new keywords without doing anything.
if not should_be_particle:
new_kwargs[argname] = raw_argval
continue
# Occasionally there will be functions where it will be
# useful to allow None as an argument.
# In case annotations[argname] is a collection (which looks
# like (Particle, Optional[Particle], ...) or [Particle])
if isinstance(annotations[argname], tuple):
optional_particle = (annotations[argname][pos] is
Optional[Particle])
elif isinstance(annotations[argname], list):
optional_particle = annotations[argname] == [
Optional[Particle]
]
else:
# Otherwise annotations[argname] must be a Particle itself
optional_particle = annotations[argname] is Optional[
Particle]
if (optional_particle
or none_shall_pass) and argval is None:
particle = None
else:
params = (argval, Z, mass_numb)
already_particle = isinstance(argval, Particle)
particle = get_particle(argname, params,
already_particle, funcname)
if isinstance(raw_argval, (tuple, list)):
# If passed argument is a tuple or list, keep
# appending them.
particles.append(particle)
# Set appended values if current iteration is the
# last iteration.
if (pos + 1) == len(argval_tuple):
new_kwargs[argname] = tuple(particles)
del particles
else:
# Otherwise directly set values
new_kwargs[argname] = particle
return wrapped_function(**new_kwargs)
def T_e(self) -> u.K:
"""Return the electron temperature."""
if self._T_e is None:
raise ParticleError("No electron temperature has been specified.")
return self._T_e.to(u.K, equivalencies=u.temperature_energy())
def average_ion(
self,
*,
include_neutrals: bool = True,
use_rms_charge: bool = False,
use_rms_mass: bool = False,
) -> CustomParticle:
"""
Return a |CustomParticle| representing the mean particle
included across all ionization states.
By default, this method will use the weighted mean to calculate
the properties of the |CustomParticle|, where the weights for
each ionic level is given by its ionic fraction multiplied by
the abundance of the base element or isotope. If
``use_rms_charge`` or ``use_rms_mass`` is `True`, then this
method will return the root mean square of the charge or mass,
respectively.
Parameters
----------
include_neutrals : `bool`, optional, keyword-only
If `True`, include neutrals when calculating the mean values
of the different particles. If `False`, exclude neutrals.
Defaults to `True`.
use_rms_charge : `bool`, optional, keyword-only
If `True`, use the root mean square charge instead of the
mean charge. Defaults to `False`.
use_rms_mass : `bool`, optional, keyword-only
If `True`, use the root mean square mass instead of the mean
mass. Defaults to `False`.
Raises
------
`~plasmapy.particles.exceptions.ParticleError`
If the abundance of any of the elements or isotopes is not
defined and the |IonizationStateCollection| instance includes
more than one element or isotope.
Returns
-------
~plasmapy.particles.particle_class.CustomParticle
Examples
--------
>>> states = IonizationStateCollection(
... {"H": [0.1, 0.9], "He": [0, 0.1, 0.9]},
... abundances={"H": 1, "He": 0.1}
... )
>>> states.average_ion()
CustomParticle(mass=2.12498...e-27 kg, charge=1.5876...e-19 C)
>>> states.average_ion(include_neutrals=False, use_rms_charge=True, use_rms_mass=True)
CustomParticle(mass=2.633...e-27 kg, charge=1.805...e-19 C)
"""
min_charge = 0 if include_neutrals else 1
all_particles = ParticleList()
all_abundances = []
for base_particle in self.base_particles:
ionization_state = self[base_particle]
ionic_levels = ionization_state.to_list()[min_charge:]
all_particles.extend(ionic_levels)
base_particle_abundance = self.abundances[base_particle]
if np.isnan(base_particle_abundance):
if len(self) == 1:
base_particle_abundance = 1
else:
raise ParticleError(
"Unable to provide an average particle without abundances."
)
ionic_fractions = ionization_state.ionic_fractions[min_charge:]
ionic_abundances = base_particle_abundance * ionic_fractions
all_abundances.extend(ionic_abundances)
return all_particles.average_particle(
use_rms_charge=use_rms_charge,
use_rms_mass=use_rms_mass,
abundances=all_abundances,
)
