def __init__(
self,
coefficient,
x=None,
quantum_yield=1.0,
phase_function=None,
hist=False,
name="Scatterer",
):
"""
Parameters
----------
coefficient: float, list, tuple or numpy.ndarray
Specifies the scattering coefficient per unit length. Constant values
can be supplied or a spectrum per nanometer per unit length.
x: list, tuple of numpy.ndarray (optional)
Wavelength values in nanometers. Required when specifying a the
`coefficient` with an list or tuple.
quantum_yield: float (optional)
Default value is 1.0. To include non-radiative scattering use values
between less than 1.0.
phase_function callable (optional)
Determines the direction of scattering. If None is supplied scattering
is isotropic.
hist: Bool
Specifies how the coefficient spectrum is sampled. If `True` the values
are treated as a histogram. If `False` the values are linearly
interpolated.
name: str
A user-defined identifier string
"""
super(Scatterer, self).__init__(name=name)
# Make absorption/scattering spectrum distribution
self._coefficient = coefficient
if coefficient is None:
raise ValueError("Coefficient must be specified.")
elif isinstance(coefficient, (float, np.float)):
self._abs_dist = Distribution(x=None, y=coefficient, hist=hist)
elif isinstance(coefficient, np.ndarray):
self._abs_dist = Distribution(x=coefficient[:, 0],
y=coefficient[:, 1],
hist=hist)
elif isinstance(coefficient, (list, tuple)):
if x is None:
raise ValueError("Requires `x`.")
self._abs_dist = Distribution.from_functions(x,
coefficient,
hist=hist)
self.quantum_yield = quantum_yield
self.phase_function = (phase_function
if phase_function is not None else isotropic)
def __init__(
self,
coefficient,
emission=None,
x=None,
hist=False,
quantum_yield=1.0,
phase_function=None,
name="Luminophore",
):
""" coefficient: float, list, tuple or numpy.ndarray
Specifies the absorption coefficient per unit length. Constant values
can be supplied or a spectrum per nanometer per unit length.
If using a list of tuple you should also specify the wavelengths using
the `x` keyword.
If using a numpy array use `column_stack` to supply a single array with
a wavelength and coefficient values.
emission: float, list, tuple or numpy.ndarray (optional)
Specifies the emission line-shape per nanometer.
If `None` will use a Gaussian centred at 600nm.
If using a list of tuple you should also specify the wavelengths using
the `x` keyword.
If using a numpy array use `column_stack` to supply a single array with
a wavelength and coefficient values.
x: list, tuple of numpy.ndarray (optional)
Wavelength values in nanometers. Required when specifying a the
`coefficient` with an list or tuple.
quantum_yield: float (optional)
The probability of re-emitting a ray.
phase_function callable (optional)
Specifies the direction of emitted rays.
hist: Bool
Specifies how the absorption and emission spectra are sampled. If `True`
the values are treated as a histogram. If `False` the values are
linearly interpolated.
name: str
A user-defined identifier string
"""
super(Luminophore, self).__init__(
coefficient,
x=x,
quantum_yield=quantum_yield,
phase_function=phase_function,
hist=hist,
name=name,
)
# Make emission spectrum distribution
self._emission = emission
if emission is None:
self._ems_dist = Distribution.from_functions(
x, [lambda x: gaussian(x, 1.0, 600.0, 40.0)], hist=hist)
elif isinstance(emission, np.ndarray):
self._ems_dist = Distribution(x=emission[:, 0],
y=emission[:, 1],
hist=hist)
elif isinstance(emission, (tuple, list)):
if x is None:
raise ValueError("Requires `x`.")
self._ems_dist = Distribution.from_functions(x,
emission,
hist=hist)
else:
raise ValueError("Luminophore `emission` arg has wrong type.")
def __init__(self,
coefficient,
x=None,
quantum_yield=1.0,
phase_function=None,
hist=False,
name="Scatterer"):
""" coefficient: float, list, tuple or numpy.ndarray
Specifies the scattering coefficient per unit length. Constant values
can be supplied or a spectrum per nanometer per unit length.
If using a list of tuple you should also specify the wavelengths using
the `x` keyword::
x = numpy.linspace(600, 800) # nanometer values
coefficient = list(numpy.ones(x.shape) * 1.5) # per nm per unit length
Scatterer(
coefficient,
x=x
)
If using a numpy array use `column_stack` to supply a single array with
a wavelength and coefficient values::
Scatterer(
coefficient=numpy.column_stack((x, y))
)
x: list, tuple of numpy.ndarray (optional)
Wavelength values in nanometers. Required when specifying a the
`coefficient` with an list or tuple.
quantum_yield: float (optional)
Default value is 1.0. To include non-radiative scattering use values
between less than 1.0.
phase_function callable (optional)
Determines the direction of scattering. If None is supplied scattering
is isotropic.
hist: Bool
Specifies how the coefficient spectrum is sampled. If `True` the values
are treated as a histogram. If `False` the values are linearly
interpolated.
name: str
A user-defined identifier string
"""
super(Scatterer, self).__init__(name=name)
# Make absorption/scattering spectrum distribution
self._coefficient = coefficient
if coefficient is None:
raise ValueError("Coefficient must be specified.")
elif isinstance(coefficient, (float, np.float)):
self._abs_dist = Distribution(x=None, y=coefficient, hist=hist)
elif isinstance(coefficient, np.ndarray):
self._abs_dist = Distribution(x=coefficient[:, 0],
y=coefficient[:, 1],
hist=hist)
elif isinstance(coefficient, (list, tuple)):
if x is None:
raise ValueError("Requires `x`.")
self._abs_dist = Distribution.from_functions(x,
coefficient,
hist=hist)
self.quantum_yield = quantum_yield
self.phase_function = phase_function if phase_function is not None else isotropic