P92

class dust_extinction.shapes.P92(BKG_amp=218.57142857142858, BKG_lambda=0.047, BKG_b=90.0, BKG_n=2.0, FUV_amp=18.545454545454547, FUV_lambda=0.07, FUV_b=4.0, FUV_n=6.5, NUV_amp=0.05961038961038961, NUV_lambda=0.22, NUV_b=- 1.95, NUV_n=2.0, SIL1_amp=0.0026493506493506496, SIL1_lambda=9.7, SIL1_b=- 1.95, SIL1_n=2.0, SIL2_amp=0.0026493506493506496, SIL2_lambda=18.0, SIL2_b=- 1.8, SIL2_n=2.0, FIR_amp=0.015896103896103898, FIR_lambda=25.0, FIR_b=0.0, FIR_n=2.0, **kwargs)[source]

Bases: astropy.modeling.Fittable1DModel

Pei (1992) 24 parameter shape model

Parameters
BKG_ampfloat

background term amplitude

BKG_lambdafloat

background term central wavelength

BKG_bfloat

background term b coefficient

BKG_nfloat

background term n coefficient [FIXED at n = 2]

FUV_ampfloat

far-ultraviolet term amplitude

FUV_lambdafloat

far-ultraviolet term central wavelength

FUV_bfloat

far-ultraviolet term b coefficent

FUV_nfloat

far-ultraviolet term n coefficient

NUV_ampfloat

near-ultraviolet (2175 A) term amplitude

NUV_lambdafloat

near-ultraviolet (2175 A) term central wavelength

NUV_bfloat

near-ultraviolet (2175 A) term b coefficent

NUV_nfloat

near-ultraviolet (2175 A) term n coefficient [FIXED at n = 2]

SIL1_ampfloat

1st silicate feature (~10 micron) term amplitude

SIL1_lambdafloat

1st silicate feature (~10 micron) term central wavelength

SIL1_bfloat

1st silicate feature (~10 micron) term b coefficent

SIL1_nfloat

1st silicate feature (~10 micron) term n coefficient [FIXED at n = 2]

SIL2_ampfloat

2nd silicate feature (~18 micron) term amplitude

SIL2_lambdafloat

2nd silicate feature (~18 micron) term central wavelength

SIL2_bfloat

2nd silicate feature (~18 micron) term b coefficient

SIL2_nfloat

2nd silicate feature (~18 micron) term n coefficient [FIXED at n = 2]

FIR_ampfloat

far-infrared term amplitude

FIR_lambdafloat

far-infrared term central wavelength

FIR_bfloat

far-infrared term b coefficent

FIR_nfloat

far-infrared term n coefficient [FIXED at n = 2]

Notes

From Pei (1992, ApJ, 395, 130)

Applicable from the extreme UV to far-IR

Example showing a P92 curve with components identified.

import numpy as np
import matplotlib.pyplot as plt
import astropy.units as u

from dust_extinction.shapes import P92

fig, ax = plt.subplots()

# generate the curves and plot them
lam = np.logspace(-3.0, 3.0, num=1000)
x = (1.0/lam)/u.micron

ext_model = P92()
ax.plot(1/x,ext_model(x),label='total')

ext_model = P92(FUV_amp=0., NUV_amp=0.0,
                SIL1_amp=0.0, SIL2_amp=0.0, FIR_amp=0.0)
ax.plot(1./x,ext_model(x),label='BKG only')

ext_model = P92(NUV_amp=0.0,
                SIL1_amp=0.0, SIL2_amp=0.0, FIR_amp=0.0)
ax.plot(1./x,ext_model(x),label='BKG+FUV only')

ext_model = P92(FUV_amp=0.,
                SIL1_amp=0.0, SIL2_amp=0.0, FIR_amp=0.0)
ax.plot(1./x,ext_model(x),label='BKG+NUV only')

ext_model = P92(FUV_amp=0., NUV_amp=0.0,
                SIL2_amp=0.0)
ax.plot(1./x,ext_model(x),label='BKG+FIR+SIL1 only')

ext_model = P92(FUV_amp=0., NUV_amp=0.0,
                SIL1_amp=0.0)
ax.plot(1./x,ext_model(x),label='BKG+FIR+SIL2 only')

ext_model = P92(FUV_amp=0., NUV_amp=0.0,
                SIL1_amp=0.0, SIL2_amp=0.0)
ax.plot(1./x,ext_model(x),label='BKG+FIR only')

# Milky Way observed extinction as tabulated by Pei (1992)
MW_x = [0.21, 0.29, 0.45, 0.61, 0.80, 1.11, 1.43, 1.82,
        2.27, 2.50, 2.91, 3.65, 4.00, 4.17, 4.35, 4.57, 4.76,
        5.00, 5.26, 5.56, 5.88, 6.25, 6.71, 7.18, 7.60,
        8.00, 8.50, 9.00, 9.50, 10.00]
MW_x = np.array(MW_x)
MW_exvebv = [-3.02, -2.91, -2.76, -2.58, -2.23, -1.60, -0.78, 0.00,
             1.00, 1.30, 1.80, 3.10, 4.19, 4.90, 5.77, 6.57, 6.23,
             5.52, 4.90, 4.65, 4.60, 4.73, 4.99, 5.36, 5.91,
             6.55, 7.45, 8.45, 9.80, 11.30]
MW_exvebv = np.array(MW_exvebv)
Rv = 3.08
MW_axav = MW_exvebv/Rv + 1.0
ax.plot(1./MW_x, MW_axav, 'o', label='MW Observed')

ax.set_xscale('log')
ax.set_yscale('log')

ax.set_ylim(1e-3,10.)

ax.set_xlabel(r'$\lambda$ [$\mu$m]')
ax.set_ylabel(r'$A(x)/A(V)$')

ax.legend(loc='best')
plt.show()

(Source code, png, hires.png, pdf)

../_images/dust_extinction-shapes-P92-1.png

Attributes Summary

AbAv

BKG_amp

BKG_b

BKG_lambda

BKG_n

FIR_amp

FIR_b

FIR_lambda

FIR_n

FUV_amp

FUV_b

FUV_lambda

FUV_n

NUV_amp

NUV_b

NUV_lambda

NUV_n

SIL1_amp

SIL1_b

SIL1_lambda

SIL1_n

SIL2_amp

SIL2_b

SIL2_lambda

SIL2_n

fit_deriv

Function (similar to the model's evaluate) to compute the derivatives of the model with respect to its parameters, for use by fitting algorithms.

n_inputs

The number of inputs.

n_outputs

The number of outputs.

param_names

Names of the parameters that describe models of this type.

x_range

Methods Summary

__call__(*inputs[, model_set_axis, ...])

Evaluate this model using the given input(s) and the parameter values that were specified when the model was instantiated.

evaluate(in_x, BKG_amp, BKG_lambda, BKG_b, ...)

P92 function

Attributes Documentation

AbAv = 1.3246753246753247
BKG_amp = Parameter('BKG_amp', value=218.57142857142858, bounds=(0.0, None))
BKG_b = Parameter('BKG_b', value=90.0)
BKG_lambda = Parameter('BKG_lambda', value=0.047)
BKG_n = Parameter('BKG_n', value=2.0, fixed=True)
FIR_amp = Parameter('FIR_amp', value=0.015896103896103898, bounds=(0.0, None))
FIR_b = Parameter('FIR_b', value=0.0)
FIR_lambda = Parameter('FIR_lambda', value=25.0, bounds=(20.0, 30.0))
FIR_n = Parameter('FIR_n', value=2.0, fixed=True)
FUV_amp = Parameter('FUV_amp', value=18.545454545454547, bounds=(0.0, None))
FUV_b = Parameter('FUV_b', value=4.0)
FUV_lambda = Parameter('FUV_lambda', value=0.07, bounds=(0.06, 0.08))
FUV_n = Parameter('FUV_n', value=6.5)
NUV_amp = Parameter('NUV_amp', value=0.05961038961038961, bounds=(0.0, None))
NUV_b = Parameter('NUV_b', value=-1.95)
NUV_lambda = Parameter('NUV_lambda', value=0.22, bounds=(0.2, 0.24))
NUV_n = Parameter('NUV_n', value=2.0, fixed=True)
SIL1_amp = Parameter('SIL1_amp', value=0.0026493506493506496, bounds=(0.0, None))
SIL1_b = Parameter('SIL1_b', value=-1.95)
SIL1_lambda = Parameter('SIL1_lambda', value=9.7, bounds=(7.0, 13.0))
SIL1_n = Parameter('SIL1_n', value=2.0, fixed=True)
SIL2_amp = Parameter('SIL2_amp', value=0.0026493506493506496, bounds=(0.0, None))
SIL2_b = Parameter('SIL2_b', value=-1.8)
SIL2_lambda = Parameter('SIL2_lambda', value=18.0, bounds=(15.0, 21.0))
SIL2_n = Parameter('SIL2_n', value=2.0, fixed=True)
fit_deriv = None

Function (similar to the model’s evaluate) to compute the derivatives of the model with respect to its parameters, for use by fitting algorithms. In other words, this computes the Jacobian matrix with respect to the model’s parameters.

n_inputs = 1

The number of inputs.

n_outputs = 1

The number of outputs.

param_names = ('BKG_amp', 'BKG_lambda', 'BKG_b', 'BKG_n', 'FUV_amp', 'FUV_lambda', 'FUV_b', 'FUV_n', 'NUV_amp', 'NUV_lambda', 'NUV_b', 'NUV_n', 'SIL1_amp', 'SIL1_lambda', 'SIL1_b', 'SIL1_n', 'SIL2_amp', 'SIL2_lambda', 'SIL2_b', 'SIL2_n', 'FIR_amp', 'FIR_lambda', 'FIR_b', 'FIR_n')

Names of the parameters that describe models of this type.

The parameters in this tuple are in the same order they should be passed in when initializing a model of a specific type. Some types of models, such as polynomial models, have a different number of parameters depending on some other property of the model, such as the degree.

When defining a custom model class the value of this attribute is automatically set by the Parameter attributes defined in the class body.

x_range = [0.001, 1000.0]

Methods Documentation

__call__(*inputs, model_set_axis=None, with_bounding_box=False, fill_value=nan, equivalencies=None, inputs_map=None, **new_inputs)

Evaluate this model using the given input(s) and the parameter values that were specified when the model was instantiated.

evaluate(in_x, BKG_amp, BKG_lambda, BKG_b, BKG_n, FUV_amp, FUV_lambda, FUV_b, FUV_n, NUV_amp, NUV_lambda, NUV_b, NUV_n, SIL1_amp, SIL1_lambda, SIL1_b, SIL1_n, SIL2_amp, SIL2_lambda, SIL2_b, SIL2_n, FIR_amp, FIR_lambda, FIR_b, FIR_n)[source]

P92 function

Parameters
in_x: float

expects either x in units of wavelengths or frequency or assumes wavelengths in wavenumbers [1/micron]

internally wavenumbers are used

Returns
axav: np array (float)

A(x)/A(V) extinction curve [mag]

Raises
ValueError

Input x values outside of defined range