Docs updates for F20

docs/dust_extinction/choose_model.rst

@@ -49,8 +49,9 @@ model encompasses the average measured behavior of extinction curves in the MW,
 LMC, and SMC.  The :class:`~dust_extinction.parameter_averages.G16` model reduces
 to the :class:`~dust_extinction.parameter_averages.F99` model with f\ :sub:`A`\ =
 1.0.  If only MW type extinction is expected, then the
-:class:`~dust_extinction.parameter_averages.F04` model should be considered as it
-is based on significantly more extinction curves than the
+:class:`~dust_extinction.parameter_averages.F20` model should be considered as it
+is based on spectroscopic extinction curves in the optical and ultraviolet and
+significantly more extinction curves than the
 :class:`~dust_extinction.parameter_averages.CCM89` or
 :class:`~dust_extinction.parameter_averages.O94` models.
 
@@ -72,6 +73,8 @@ is based on significantly more extinction curves than the
 +----------+-------------+-------------+------------------+--------------+
 | G16      | R(V)_A, f_A |  0.3 - 10.0 |        0.1 - 3.3 | MW, LMC, SMC |
 +----------+-------------+-------------+------------------+--------------+
+| F99, F04 |  R(V)       |   0.3 - 8.7 |      0.115 - 3.3 |           MW |
++----------+-------------+-------------+------------------+--------------+
 
 Notes
 -----

docs/dust_extinction/extinguish.rst

@@ -23,11 +23,11 @@ Example: Extinguish a Blackbody
    import astropy.units as u
    from astropy.modeling.blackbody import blackbody_lambda
 
-   from dust_extinction.parameter_averages import F99
+   from dust_extinction.parameter_averages import F20
 
-   # generate wavelengths between 0.1 and 3 microns
-   #    within the valid range for the F99 R(V) dependent relationship
-   lam = np.logspace(np.log10(0.1), np.log10(3.0), num=1000)
+   # generate wavelengths between 0.12 and 3 microns
+   #    within the valid range for the F20 R(V) dependent relationship
+   lam = np.logspace(np.log10(0.12), np.log10(3.0), num=1000)
 
    # setup the inputs for the blackbody function
    wavelengths = lam*1e4*u.AA
@@ -37,7 +37,7 @@ Example: Extinguish a Blackbody
    flux = blackbody_lambda(wavelengths, temperature)
 
    # initialize the model
-   ext = F99(Rv=3.1)
+   ext = F20(Rv=3.1)
 
    # get the extinguished blackbody flux for different amounts of dust
    flux_ext_av05 = flux*ext.extinguish(wavelengths, Av=0.5)

docs/dust_extinction/model_flavors.rst

@@ -77,7 +77,7 @@ R(V) (+ other variables) dependent prediction models
    import astropy.units as u
 
    from dust_extinction.parameter_averages import (CCM89, O94, F99, F04,
-                                                   VCG04, GCC09, M14)
+                                                   VCG04, GCC09, M14, F20)
 
    fig, ax = plt.subplots()
 
@@ -86,7 +86,7 @@ R(V) (+ other variables) dependent prediction models
 
    Rv = 3.1
 
-   models = [CCM89, O94, F99, F04, VCG04, GCC09, M14]
+   models = [CCM89, O94, F99, F04, VCG04, GCC09, M14, F20]
 
    for cmodel in models:
       ext_model = cmodel(Rv=Rv)
@@ -112,7 +112,7 @@ R(V) (+ other variables) dependent prediction models
    import astropy.units as u
 
    from dust_extinction.parameter_averages import (CCM89, O94, F99, F04,
-                                                   VCG04, GCC09, M14)
+                                                   VCG04, GCC09, M14, F20)
 
    fig, ax = plt.subplots()
 
@@ -121,7 +121,7 @@ R(V) (+ other variables) dependent prediction models
 
    Rv = 2.0
 
-   models = [CCM89, O94, F99, F04, VCG04, GCC09, M14]
+   models = [CCM89, O94, F99, F04, VCG04, GCC09, M14, F20]
 
    for cmodel in models:
       ext_model = cmodel(Rv=Rv)
@@ -148,7 +148,7 @@ R(V) (+ other variables) dependent prediction models
    import astropy.units as u
 
    from dust_extinction.parameter_averages import (CCM89, O94, F99, F04,
-                                                   VCG04, GCC09, M14)
+                                                   VCG04, GCC09, M14, F20)
 
    fig, ax = plt.subplots()
 
@@ -157,7 +157,7 @@ R(V) (+ other variables) dependent prediction models
 
    Rv = 5.5
 
-   models = [CCM89, O94, F99, F04, VCG04, GCC09, M14]
+   models = [CCM89, O94, F99, F04, VCG04, GCC09, M14, F20]
 
    for cmodel in models:
       ext_model = cmodel(Rv=Rv)

dust_extinction/parameter_averages.py

@@ -13,7 +13,7 @@
 from .averages import G03_SMCBar
 from .shapes import _curve_F99_method
 
-__all__ = ["CCM89", "O94", "F99", "F04", "VCG04", "GCC09", "M14", "G16", "F19"]
+__all__ = ["CCM89", "O94", "F99", "F04", "VCG04", "GCC09", "M14", "G16", "F20"]
 
 x_range_CCM89 = [0.3, 10.0]
 x_range_O94 = x_range_CCM89
@@ -23,7 +23,7 @@
 x_range_GCC09 = [3.3, 11.0]
 x_range_M14 = [0.3, 3.3]
 x_range_G16 = [0.3, 10.0]
-x_range_F19 = [0.3, 8.7]
+x_range_F20 = [0.3, 8.7]
 
 
 class CCM89(BaseExtRvModel):
@@ -1136,11 +1136,11 @@ def evaluate(in_x, RvA, fA):
         return alav
 
 
-class F19(BaseExtRvModel):
+class F20(BaseExtRvModel):
     """
-    F19 extinction model calculation
+    F20 extinction model calculation
 
-    Fitzpatrick, Massa, Gordon et al. (2019, in prep) model.
+    Fitzpatrick, Massa, Gordon et al. (2020, almost submitted) model.
     Based on a sample of stars observed spectroscopically in the
     optical with HST/STIS.
 
@@ -1156,9 +1156,9 @@ class F19(BaseExtRvModel):
 
     Notes
     -----
-    F19 Milky Way R(V) dependent extinction model
+    F20 Milky Way R(V) dependent extinction model
 
-    Example showing F19 curves for a range of R(V) values.
+    Example showing F20 curves for a range of R(V) values.
 
     .. plot::
         :include-source:
@@ -1167,20 +1167,20 @@ class F19(BaseExtRvModel):
         import matplotlib.pyplot as plt
         import astropy.units as u
 
-        from dust_extinction.parameter_averages import F19
+        from dust_extinction.parameter_averages import F20
 
         fig, ax = plt.subplots()
 
         # temp model to get the correct x range
-        text_model = F19()
+        text_model = F20()
 
         # 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 = F19(Rv=cur_Rv)
+           ext_model = F20(Rv=cur_Rv)
            ax.plot(x,ext_model(x),label='R(V) = ' + str(cur_Rv))
 
         ax.set_xlabel(r'$x$ [$\mu m^{-1}$]')
@@ -1191,11 +1191,11 @@ class F19(BaseExtRvModel):
     """
 
     Rv_range = [2.0, 6.0]
-    x_range = x_range_F19
+    x_range = x_range_F20
 
     def evaluate(self, in_x, Rv):
         """
-        F19 function
+        F20 function
 
         Parameters
         ----------
@@ -1225,15 +1225,15 @@ def evaluate(self, in_x, Rv):
         x = x_quant.value
 
         # check that the wavenumbers are within the defined range
-        _test_valid_x_range(x, x_range_F19, "F19")
+        _test_valid_x_range(x, x_range_F20, "F20")
 
         # ensure Rv is a single element, not numpy array
         Rv = Rv[0]
 
         # get the tabulated information
         data_path = pkg_resources.resource_filename("dust_extinction", "data/")
 
-        a = Table.read(data_path + "F19_tabulated.dat", format="ascii")
+        a = Table.read(data_path + "F20_tabulated.dat", format="ascii")
 
         # compute E(lambda-55)/E(B-55) on the tabulated x points
         k_rV_tab_x = a["k_3.02"].data + a["deltak"].data * (Rv - 3.10) * 0.990