G16

class dust_extinction.parameter_averages.G16(**kwargs)

Bases: BaseExtRvAfAModel

Gordon et al (2016) Milky Way, LMC, & SMC R(V) and f_A dependent model

Mixture model between the F99 R(V) dependent model (component A) and the G03_SMCBar model (component B)

Parameters:

RvA: float

R_A(V) = A(V)/E(B-V) = total-to-selective extinction R(V) of the A component

fA: float

f_A is the mixture coefficent between the R(V)

Raises:

InputParameterError

Input RvA values outside of defined range Input fA values outside of defined range

Notes

From Gordon et al. (2016, ApJ, 826, 104)

Example showing G16 curves for a range of R_A(V) values and f_A values.

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

from dust_extinction.parameter_averages import G16

fig, ax = plt.subplots()

# temp model to get the correct x range
text_model = G16()

# generate the curves and plot them
x = np.arange(text_model.x_range[0],
              text_model.x_range[1],0.1)/u.micron

Rvs = ['2.0','3.0','4.0','5.0','6.0']
for cur_Rv in Rvs:
   ext_model = G16(RvA=cur_Rv, fA=1.0)
   ax.plot(x,ext_model(x),label=r'$R_A(V) = ' + str(cur_Rv) + '$')

ax.set_xlabel(r'$x$ [$\mu m^{-1}$]')
ax.set_ylabel(r'$A(x)/A(V)$')

# for 2nd x-axis with lambda values
axis_xs = np.array([0.1, 0.12, 0.15, 0.2, 0.3, 0.5, 1.0])
new_ticks = 1 / axis_xs
new_ticks_labels = ["%.2f" % z for z in axis_xs]
tax = ax.twiny()
tax.set_xlim(ax.get_xlim())
tax.set_xticks(new_ticks)
tax.set_xticklabels(new_ticks_labels)
tax.set_xlabel(r"$\lambda$ [$\mu$m]")

ax.legend(loc='best', title=r'$f_A = 1.0$')
plt.show()

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

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

from dust_extinction.parameter_averages import G16

fig, ax = plt.subplots()

# temp model to get the correct x range
text_model = G16()

# generate the curves and plot them
x = np.arange(text_model.x_range[0],
              text_model.x_range[1],0.1)/u.micron

fAs = [0.0, 0.2, 0.4, 0.6, 0.8, 1.0]
for cur_fA in fAs:
   ext_model = G16(RvA=3.1, fA=cur_fA)
   ax.plot(x,ext_model(x),label=r'$f_A = ' + str(cur_fA) + '$')

ax.set_xlabel(r'$x$ [$\mu m^{-1}$]')
ax.set_ylabel(r'$A(x)/A(V)$')

# for 2nd x-axis with lambda values
axis_xs = np.array([0.1, 0.12, 0.15, 0.2, 0.3, 0.5, 1.0])
new_ticks = 1 / axis_xs
new_ticks_labels = ["%.2f" % z for z in axis_xs]
tax = ax.twiny()
tax.set_xlim(ax.get_xlim())
tax.set_xticks(new_ticks)
tax.set_xticklabels(new_ticks_labels)
tax.set_xlabel(r"$\lambda$ [$\mu$m]")

ax.legend(loc='best', title=r'$R_A(V) = 3.1$')
plt.show()

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

Attributes Summary

RvA_range
fA_range
x_range

Methods Summary

evaluate(x, RvA, fA)

G16 function

Attributes Documentation

RvA_range = [2.0, 6.0]

fA_range = [0.0, 1.0]

x_range = [0.3, 10.0]

Methods Documentation

static evaluate(x, RvA, fA)

G16 function

Parameters:

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