def cd(self, value):
"""
Validates that the input CD matrix is a 2x2 2D array.
"""
if np.shape(value) != (2, 2):
raise InputParameterError("Expected CD matrix to be a 2x2 array")
def __init__(self, modelname="MWRV31", **kwargs):
if modelname not in self.possnames.keys():
raise InputParameterError("modelname not recognized")
filename = self.possnames[modelname][0]
self.Rv = self.possnames[modelname][1]
# get the tabulated information
data_path = pkg_resources.resource_filename("dust_extinction", "data/")
a = Table.read(
data_path + filename,
data_start=1,
header_start=None,
format="ascii.basic",
)
self.data_x = 1.0 / a["col1"].data
# normalized by wavelength closest to V band
sindxs = np.argsort(np.absolute(self.data_x - 1.0 / 0.55))
self.data_axav = a["col10"].data / a["col10"].data[sindxs[0]]
# accuracy of the data based on calculations
self.data_tolerance = 1e-6
super().__init__(**kwargs)
def shift(self, value):
"""
Validates that the shift vector is a 2D vector. This allows
either a "row" vector.
"""
if not (np.ndim(value) == 1 and np.shape(value) == (2, )):
raise InputParameterError( # pragma: no cover
"Expected 'shift' to be a 2 element row vector.")
def matrix(self, value):
"""
Validates that the input matrix is a 2x2 2D array.
"""
if np.shape(value) != (2, 2):
raise InputParameterError(
"Expected transformation matrix to be a 2x2 array")
def crpix(self, value):
"""
Validates that the crpix vector is a 2D vector. This allows
either a "row" vector.
"""
if not (np.ndim(value) == 1 and np.shape(value) == (2, )):
raise InputParameterError(
"Expected 'crpix' to be a 2 element row vector.")
def Av(self, value):
"""
Check that Av is in the valid range
Parameters
----------
value: float
Av value to check
Raises
------
InputParameterError
Input Av values outside of defined range
"""
if (value < 0.0):
raise InputParameterError("parameter Av must be positive")
def ampl(self, value):
"""
Check that ampl is in the valid range
Parameters
----------
value: float
ampl value to check
Raises
------
InputParameterError
Input ampl values outside of defined range
"""
if value < 0.0:
raise InputParameterError("parameter ampl must be positive")
def fA(self, value):
"""
Check that fA is in the valid range
Parameters
----------
value: float
fA value to check
Raises
------
InputParameterError
Input fA values outside of defined range
"""
if not (self.fA_range[0] <= value <= self.fA_range[1]):
raise InputParameterError("parameter fA must be between " +
str(self.fA_range[0]) + " and " +
str(self.fA_range[1]))
def Rv(self, value):
"""
Check that Rv is in the valid range
Parameters
----------
value: float
R(V) value to check
Raises
------
InputParameterError
Input Rv values outside of defined range
"""
if not (self.Rv_range[0] <= value <= self.Rv_range[1]):
raise InputParameterError("parameter Rv must be between " +
str(self.Rv_range[0]) + " and " +
str(self.Rv_range[1]))
def slope(self, value):
"""
Check that the slope is in the valid range
Parameters
----------
value: float
slope value to check
Raises
------
InputParameterError
Input slope values outside of defined range
"""
if (value < -3.0) or (value > 3.0):
raise InputParameterError("parameter slope must be between "
"-3.0 and 3.0")
def extinguish(self, x, Av=None, Ebv=None):
"""
Calculate the extinction as a fraction
Parameters
----------
x: float
expects either x in units of wavelengths or frequency
or assumes wavelengths in wavenumbers [1/micron]
internally wavenumbers are used
Av: float
A(V) value of dust column
Av or Ebv must be set
Ebv: float
E(B-V) value of dust column
Av or Ebv must be set
Returns
-------
frac_ext: np array (float)
fractional extinction as a function of x
"""
# get the extinction curve
axav = self(x)
# check that av or ebv is set
if (Av is None) and (Ebv is None):
raise InputParameterError('neither Av or Ebv passed, one required')
# if Av is not set and Ebv set, convert to Av
if Av is None:
Av = self.Rv * Ebv
# return fractional extinction
return np.power(10.0, -0.4 * axav * Av)