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################################################################################
# Models for the solar flux density at 1 AU, to be used for image
# calibration.
#
# Mark Showalter, PDS Rings Node, December 2011
################################################################################
import numpy as np
import tabulation as tab
# Class constants
AU = 149597870.7 # km
C = 299792.458 # km/sec
# Converts from W/m^2 to erg/s/cm^2
TO_CGS = 1.e7 / 1.e4
# Converts from flux per micron to flux per Angstrom
TO_PER_ANGSTROM = 1.e-4
# Converts from flux per micron to flux per nanometer
TO_PER_NM = 1.e-3
################################################################################
# Models for the solar spectrum at 1 AU in absolute units of W/m^2/micron
################################################################################
# From Colina, L., R. C. Bohlin, and F. Castelli, 1996. The 0.12-2.5 micron
# absolute flux distribution of the Sun for comparison with solar analog stars.
# Astron. J. 112, 307-315.
#
# Column 1 is wavelength in microns
# Column 2 is solar flux at 1 AU in W/m^2/Hz
COLINA_ARRAY = np.array([
0.119500, 1.34269e-18,
0.120500, 1.06999e-17,
0.121500, 9.52491e-17,
0.122500, 2.28803e-17,
0.123500, 1.01461e-18,
0.124500, 6.70275e-19,
0.125500, 5.64521e-19,
0.126500, 7.06755e-19,
0.127500, 4.16554e-19,
0.128500, 3.42433e-19,
0.129500, 8.30623e-19,
0.130500, 2.49545e-18,
0.131500, 8.22167e-19,
0.132500, 8.66106e-19,
0.133500, 3.65061e-18,
0.134500, 9.71820e-19,
0.135500, 8.17521e-19,
0.136500, 6.78593e-19,
0.137500, 6.47147e-19,
0.138500, 9.14775e-19,
0.139500, 1.83748e-18,
0.140500, 1.42836e-18,
0.141500, 9.79902e-19,
0.142500, 1.10336e-18,
0.143500, 1.21897e-18,
0.144500, 1.23414e-18,
0.145500, 1.35663e-18,
0.146500, 1.75199e-18,
0.147500, 2.12249e-18,
0.148500, 2.07099e-18,
0.149500, 2.04349e-18,
0.150500, 2.25837e-18,
0.151500, 2.43692e-18,
0.152500, 3.13014e-18,
0.153500, 3.53133e-18,
0.154500, 5.73032e-18,
0.155500, 6.01256e-18,
0.156500, 5.15069e-18,
0.157500, 4.85219e-18,
0.158500, 4.78339e-18,
0.159500, 5.05043e-18,
0.160500, 5.65788e-18,
0.161500, 6.59066e-18,
0.162500, 7.57332e-18,
0.163500, 8.75741e-18,
0.164500, 9.22951e-18,
0.165500, 1.34151e-17,
0.166500, 1.25718e-17,
0.167500, 1.23288e-17,
0.168500, 1.45822e-17,
0.169500, 1.90190e-17,
0.170500, 2.16453e-17,
0.171500, 2.28768e-17,
0.172500, 2.43741e-17,
0.173500, 2.59527e-17,
0.174500, 3.11314e-17,
0.175500, 3.74844e-17,
0.176500, 4.29370e-17,
0.177500, 5.00440e-17,
0.178500, 5.56467e-17,
0.179500, 5.76053e-17,
0.180500, 6.77727e-17,
0.181500, 8.38527e-17,
0.182500, 8.46909e-17,
0.183500, 8.54608e-17,
0.184500, 7.92253e-17,
0.185500, 8.95792e-17,
0.186500, 1.05919e-16,
0.187500, 1.19293e-16,
0.188500, 1.31747e-16,
0.189500, 1.44541e-16,
0.190500, 1.53733e-16,
0.191500, 1.72064e-16,
0.192500, 1.72116e-16,
0.193500, 1.60183e-16,
0.194500, 2.22012e-16,
0.195500, 2.33932e-16,
0.196500, 2.60995e-16,
0.197500, 2.71977e-16,
0.198500, 2.74069e-16,
0.199500, 2.97805e-16,
0.200500, 3.30848e-16,
0.201500, 3.66079e-16,
0.202500, 3.79881e-16,
0.203500, 4.28110e-16,
0.204500, 4.80783e-16,
0.205500, 5.00059e-16,
0.206500, 5.30275e-16,
0.207500, 6.12630e-16,
0.208500, 7.31097e-16,
0.209500, 1.03990e-15,
0.210500, 1.37120e-15,
0.211500, 1.66168e-15,
0.212500, 1.56699e-15,
0.213500, 1.66689e-15,
0.214500, 2.03697e-15,
0.215500, 1.85841e-15,
0.216500, 1.67279e-15,
0.217500, 1.84036e-15,
0.218500, 2.34110e-15,
0.219500, 2.49932e-15,
0.220500, 2.54485e-15,
0.221500, 2.14450e-15,
0.222500, 2.70889e-15,
0.223500, 3.46657e-15,
0.224500, 3.27573e-15,
0.225500, 2.93781e-15,
0.226500, 2.23724e-15,
0.227500, 2.27021e-15,
0.228500, 2.98963e-15,
0.229500, 2.76912e-15,
0.230500, 3.05319e-15,
0.231500, 3.01122e-15,
0.232500, 3.17036e-15,
0.233500, 2.69786e-15,
0.234500, 2.36627e-15,
0.235500, 3.13942e-15,
0.236500, 2.99997e-15,
0.237500, 3.01701e-15,
0.238500, 2.63206e-15,
0.239500, 2.79599e-15,
0.240500, 2.52204e-15,
0.241500, 3.29617e-15,
0.242500, 4.57020e-15,
0.243500, 4.34437e-15,
0.244500, 4.02143e-15,
0.245500, 3.29116e-15,
0.246500, 3.38153e-15,
0.247500, 3.75057e-15,
0.248500, 3.11131e-15,
0.249500, 3.86988e-15,
0.250500, 4.17228e-15,
0.251500, 3.22581e-15,
0.252500, 2.92139e-15,
0.253500, 3.65574e-15,
0.254500, 4.25814e-15,
0.255500, 5.69637e-15,
0.256500, 7.36479e-15,
0.257500, 9.15304e-15,
0.258500, 9.20300e-15,
0.259500, 7.75243e-15,
0.260500, 6.41940e-15,
0.261500, 6.75103e-15,
0.262500, 7.89616e-15,
0.263500, 1.24909e-14,
0.264500, 1.92332e-14,
0.265500, 1.96370e-14,
0.266500, 1.95139e-14,
0.267500, 1.97859e-14,
0.268500, 1.93795e-14,
0.269500, 1.91195e-14,
0.270500, 2.15520e-14,
0.271500, 1.82195e-14,
0.272500, 1.61400e-14,
0.273500, 1.62983e-14,
0.274500, 1.10451e-14,
0.275500, 1.46209e-14,
0.276500, 2.04461e-14,
0.277500, 1.98793e-14,
0.278500, 1.36119e-14,
0.279500, 7.50850e-15,
0.280500, 8.33037e-15,
0.281500, 1.82368e-14,
0.282500, 2.58056e-14,
0.283500, 2.77411e-14,
0.284500, 2.10194e-14,
0.285500, 1.46680e-14,
0.286500, 2.90368e-14,
0.287500, 3.05115e-14,
0.288500, 2.93994e-14,
0.289500, 4.35028e-14,
0.290500, 5.57442e-14,
0.291500, 5.42579e-14,
0.292500, 4.89752e-14,
0.293500, 5.06817e-14,
0.294500, 4.84786e-14,
0.295500, 5.29174e-14,
0.296500, 4.90460e-14,
0.297500, 4.92694e-14,
0.298500, 4.55690e-14,
0.299500, 4.77355e-14,
0.300500, 4.17886e-14,
0.301500, 4.55973e-14,
0.302500, 4.92160e-14,
0.303500, 6.29952e-14,
0.304500, 6.15369e-14,
0.305500, 6.10752e-14,
0.306500, 5.75185e-14,
0.307500, 6.40597e-14,
0.308500, 6.41336e-14,
0.309500, 5.24908e-14,
0.310500, 6.63080e-14,
0.311500, 7.78755e-14,
0.312500, 7.05428e-14,
0.313500, 7.56877e-14,
0.314500, 7.22200e-14,
0.315500, 6.93743e-14,
0.316500, 6.97244e-14,
0.317500, 8.58353e-14,
0.318500, 7.43056e-14,
0.319500, 7.99990e-14,
0.320500, 9.09963e-14,
0.321500, 7.96163e-14,
0.322500, 7.88488e-14,
0.323500, 7.62016e-14,
0.324500, 8.82206e-14,
0.325500, 1.02289e-13,
0.326500, 1.14863e-13,
0.327500, 1.12472e-13,
0.328500, 1.09015e-13,
0.329500, 1.26718e-13,
0.330500, 1.22099e-13,
0.331500, 1.16758e-13,
0.332500, 1.16214e-13,
0.333500, 1.12689e-13,
0.334500, 1.17996e-13,
0.335500, 1.16750e-13,
0.336500, 1.00873e-13,
0.337500, 1.05583e-13,
0.338500, 1.16227e-13,
0.339500, 1.21617e-13,
0.340500, 1.28307e-13,
0.341500, 1.18606e-13,
0.342500, 1.28263e-13,
0.343500, 1.23574e-13,
0.344500, 1.04127e-13,
0.345500, 1.23301e-13,
0.346500, 1.22391e-13,
0.347500, 1.19825e-13,
0.348500, 1.20039e-13,
0.349500, 1.19796e-13,
0.350500, 1.41755e-13,
0.351500, 1.33257e-13,
0.352500, 1.24247e-13,
0.353500, 1.42071e-13,
0.354500, 1.53410e-13,
0.355500, 1.45359e-13,
0.356500, 1.27124e-13,
0.357500, 1.12005e-13,
0.358500, 9.83348e-14,
0.359500, 1.41312e-13,
0.360500, 1.38583e-13,
0.361500, 1.26451e-13,
0.362500, 1.44377e-13,
0.363500, 1.44965e-13,
0.364500, 1.48160e-13,
0.365500, 1.69598e-13,
0.366500, 1.82285e-13,
0.367500, 1.75615e-13,
0.368500, 1.64757e-13,
0.369500, 1.84702e-13,
0.370500, 1.72668e-13,
0.371500, 1.78653e-13,
0.372500, 1.61434e-13,
0.373500, 1.41720e-13,
0.374500, 1.39414e-13,
0.375500, 1.65017e-13,
0.376500, 1.69657e-13,
0.377500, 2.01179e-13,
0.378500, 2.09086e-13,
0.379500, 1.69239e-13,
0.380500, 1.91331e-13,
0.381500, 1.72726e-13,
0.382500, 1.27217e-13,
0.383500, 1.10944e-13,
0.384500, 1.55798e-13,
0.385500, 1.64857e-13,
0.386500, 1.65317e-13,
0.387500, 1.65536e-13,
0.388500, 1.63269e-13,
0.389500, 1.95500e-13,
0.390500, 2.08640e-13,
0.391500, 2.25647e-13,
0.392500, 1.72778e-13,
0.393500, 9.93242e-14,
0.394500, 1.75534e-13,
0.395500, 2.25800e-13,
0.396500, 1.47468e-13,
0.397500, 1.60744e-13,
0.398500, 2.65634e-13,
0.399500, 2.91693e-13,
0.400500, 2.96474e-13,
0.401500, 3.09929e-13,
0.402500, 3.13796e-13,
0.403500, 3.02228e-13,
0.404500, 3.01731e-13,
0.405500, 3.02091e-13,
0.406500, 2.89469e-13,
0.407500, 2.97414e-13,
0.408500, 3.18617e-13,
0.409500, 3.15998e-13,
0.410500, 2.68910e-13,
0.411500, 3.27357e-13,
0.412500, 3.23895e-13,
0.413500, 3.19299e-13,
0.414500, 3.17381e-13,
0.415500, 3.18365e-13,
0.416500, 3.39962e-13,
0.417500, 3.08676e-13,
0.418500, 3.13687e-13,
0.419500, 3.18362e-13,
0.420500, 3.30576e-13,
0.421500, 3.39690e-13,
0.422500, 3.00393e-13,
0.423500, 3.26366e-13,
0.424500, 3.38807e-13,
0.425500, 3.26382e-13,
0.426500, 3.28497e-13,
0.427500, 3.05024e-13,
0.428500, 3.09960e-13,
0.429500, 2.89486e-13,
0.430500, 2.23780e-13,
0.431500, 3.33873e-13,
0.432500, 3.27484e-13,
0.433500, 3.45948e-13,
0.434500, 3.35327e-13,
0.435500, 3.47538e-13,
0.436500, 3.90983e-13,
0.437500, 3.67797e-13,
0.438500, 3.20515e-13,
0.439500, 3.75061e-13,
0.440500, 3.53505e-13,
0.441500, 4.00406e-13,
0.442500, 4.12402e-13,
0.443500, 3.99450e-13,
0.444500, 4.14671e-13,
0.445500, 3.84529e-13,
0.446500, 4.01065e-13,
0.447500, 4.42385e-13,
0.448500, 4.22167e-13,
0.449500, 4.35629e-13,
0.450500, 4.62764e-13,
0.451500, 4.57250e-13,
0.452500, 4.22779e-13,
0.453500, 4.30978e-13,
0.454500, 4.34853e-13,
0.455500, 4.48877e-13,
0.456500, 4.60358e-13,
0.457500, 4.67485e-13,
0.458500, 4.40757e-13,
0.459500, 4.51195e-13,
0.460500, 4.60136e-13,
0.461500, 4.65526e-13,
0.462500, 4.78667e-13,
0.463500, 4.66151e-13,
0.464500, 4.53513e-13,
0.465500, 4.70642e-13,
0.466500, 4.44727e-13,
0.467500, 4.68434e-13,
0.468500, 4.65549e-13,
0.469500, 4.66603e-13,
0.470500, 4.42051e-13,
0.471500, 4.77191e-13,
0.472500, 4.84666e-13,
0.473500, 4.74825e-13,
0.474500, 4.91167e-13,
0.475500, 4.84843e-13,
0.476500, 4.72429e-13,
0.477500, 5.03203e-13,
0.478500, 4.89279e-13,
0.479500, 5.07671e-13,
0.480500, 4.99747e-13,
0.481500, 5.15359e-13,
0.482500, 5.00952e-13,
0.483500, 5.02038e-13,
0.484500, 4.91664e-13,
0.485500, 4.58932e-13,
0.486500, 4.09091e-13,
0.487500, 4.62720e-13,
0.488500, 4.85889e-13,
0.489500, 4.99576e-13,
0.490500, 5.13617e-13,
0.491500, 4.87262e-13,
0.492500, 4.89247e-13,
0.493500, 4.89168e-13,
0.494500, 5.35261e-13,
0.495500, 5.03041e-13,
0.496500, 5.28875e-13,
0.497500, 5.31270e-13,
0.498500, 4.93330e-13,
0.499500, 5.22843e-13,
0.500500, 4.94904e-13,
0.501500, 4.84875e-13,
0.502500, 5.08781e-13,
0.503500, 5.21567e-13,
0.504500, 5.06087e-13,
0.505500, 5.41715e-13,
0.506500, 5.35150e-13,
0.507500, 5.22235e-13,
0.508500, 5.27862e-13,
0.509500, 5.29114e-13,
0.510500, 5.39765e-13,
0.511500, 5.55762e-13,
0.512500, 5.21707e-13,
0.513500, 5.22067e-13,
0.514500, 5.27753e-13,
0.515500, 5.37138e-13,
0.516500, 4.73555e-13,
0.517500, 4.91587e-13,
0.518500, 4.72950e-13,
0.519500, 5.24888e-13,
0.520500, 5.27773e-13,
0.521500, 5.51446e-13,
0.522500, 5.29520e-13,
0.523500, 5.52194e-13,
0.524500, 5.72987e-13,
0.525500, 5.66970e-13,
0.526500, 4.93540e-13,
0.527500, 5.41179e-13,
0.528500, 5.63682e-13,
0.529500, 5.72064e-13,
0.530500, 5.84380e-13,
0.531500, 5.89882e-13,
0.532500, 5.34037e-13,
0.533500, 5.82250e-13,
0.534500, 5.64731e-13,
0.535500, 6.07009e-13,
0.536500, 5.72935e-13,
0.537500, 5.78445e-13,
0.538500, 5.87369e-13,
0.539500, 5.67317e-13,
0.540500, 5.49893e-13,
0.541500, 5.86775e-13,
0.542500, 5.71458e-13,
0.543500, 5.90491e-13,
0.544500, 5.92666e-13,
0.545500, 6.01791e-13,
0.546500, 5.97028e-13,
0.547500, 5.84584e-13,
0.548500, 5.96298e-13,
0.549500, 6.08727e-13,
0.550500, 6.00333e-13,
0.551500, 6.05421e-13,
0.552500, 5.99521e-13,
0.553500, 6.13395e-13,
0.554500, 6.20834e-13,
0.555500, 6.22748e-13,
0.556500, 6.00018e-13,
0.557500, 6.10421e-13,
0.558500, 5.93086e-13,
0.559500, 6.02187e-13,
0.560500, 6.16008e-13,
0.561500, 6.11852e-13,
0.562500, 6.22762e-13,
0.563500, 6.28685e-13,
0.564500, 6.28551e-13,
0.565500, 6.11779e-13,
0.566500, 6.24500e-13,
0.567500, 6.46526e-13,
0.568500, 6.22402e-13,
0.569500, 6.41800e-13,
0.570500, 6.12630e-13,
0.571500, 6.33493e-13,
0.572500, 6.59708e-13,
0.573500, 6.56431e-13,
0.574500, 6.55570e-13,
0.575500, 6.44852e-13,
0.576500, 6.52737e-13,
0.577500, 6.58896e-13,
0.578500, 6.34903e-13,
0.579500, 6.53135e-13,
0.580500, 6.58966e-13,
0.581500, 6.66620e-13,
0.582500, 6.76115e-13,
0.583500, 6.72659e-13,
0.584500, 6.76054e-13,
0.585500, 6.50361e-13,
0.586500, 6.69739e-13,
0.587500, 6.78617e-13,
0.588500, 6.44549e-13,
0.589500, 5.95857e-13,
0.590500, 6.72616e-13,
0.591500, 6.65244e-13,
0.592500, 6.75317e-13,
0.593500, 6.73114e-13,
0.594500, 6.66759e-13,
0.595500, 6.72390e-13,
0.596500, 6.83334e-13,
0.597500, 6.76157e-13,
0.598500, 6.69680e-13,
0.599500, 6.78403e-13,
0.600500, 6.69572e-13,
0.601500, 6.73724e-13,
0.602500, 6.63640e-13,
0.603500, 6.92510e-13,
0.604500, 6.90542e-13,
0.605500, 6.87771e-13,
0.606500, 6.88484e-13,
0.607500, 6.89973e-13,
0.608500, 6.86353e-13,
0.609500, 6.89005e-13,
0.610500, 6.75053e-13,
0.611500, 6.94327e-13,
0.612500, 6.80280e-13,
0.613500, 6.73717e-13,
0.614500, 6.87935e-13,
0.615500, 6.90176e-13,
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1.67800, 6.36140e-13,
1.68000, 6.08532e-13,
1.68200, 5.99633e-13,
1.68400, 6.29073e-13,
1.68600, 6.32920e-13,
1.68800, 6.33499e-13,
1.69000, 6.29329e-13,
1.69200, 6.41040e-13,
1.69400, 6.38429e-13,
1.69600, 6.37710e-13,
1.69800, 6.36531e-13,
1.70000, 6.27541e-13,
1.70200, 6.24004e-13,
1.70400, 6.26401e-13,
1.70600, 6.28900e-13,
1.70800, 6.19666e-13,
1.71000, 6.25262e-13,
1.71200, 6.01648e-13,
1.71400, 6.30154e-13,
1.71600, 6.24652e-13,
1.71800, 6.23657e-13,
1.72000, 6.15724e-13,
1.72200, 6.16649e-13,
1.72400, 5.97561e-13,
1.72600, 6.11763e-13,
1.72800, 6.10277e-13,
1.73000, 6.15037e-13,
1.73200, 6.04261e-13,
1.73400, 5.75066e-13,
1.73600, 5.61680e-13,
1.73800, 5.82457e-13,
1.74000, 5.99830e-13,
1.74200, 5.95712e-13,
1.74400, 6.06618e-13,
1.74600, 5.95533e-13,
1.74800, 5.94371e-13,
1.75000, 5.97109e-13,
1.75200, 5.95446e-13,
1.75400, 6.03188e-13,
1.75600, 6.01572e-13,
1.75800, 6.01717e-13,
1.76000, 6.00923e-13,
1.76200, 5.85140e-13,
1.76400, 5.95785e-13,
1.76600, 6.00909e-13,
1.76800, 5.95708e-13,
1.77000, 5.92095e-13,
1.77200, 5.95963e-13,
1.77400, 5.97032e-13,
1.77600, 5.86732e-13,
1.77800, 5.83875e-13,
1.78000, 5.86063e-13,
1.78200, 5.85395e-13,
1.78400, 5.85874e-13,
1.78600, 5.83927e-13,
1.78800, 5.91676e-13,
1.79000, 5.87261e-13,
1.79200, 5.84003e-13,
1.79400, 5.80302e-13,
1.79600, 5.81186e-13,
1.79800, 5.81319e-13,
1.80000, 5.79641e-13,
1.80200, 5.70133e-13,
1.80400, 5.78704e-13,
1.80600, 5.76185e-13,
1.80800, 5.76595e-13,
1.81000, 5.76716e-13,
1.81200, 5.71652e-13,
1.81400, 5.66361e-13,
1.81600, 5.52284e-13,
1.81800, 5.13590e-13,
1.82000, 5.50944e-13,
1.82200, 5.47623e-13,
1.82400, 5.65915e-13,
1.82600, 5.66850e-13,
1.82800, 5.60324e-13,
1.83000, 5.66457e-13,
1.83200, 5.62532e-13,
1.83400, 5.60541e-13,
1.83600, 5.61536e-13,
1.83800, 5.55460e-13,
1.84000, 5.57606e-13,
1.84200, 5.47818e-13,
1.84400, 5.53545e-13,
1.84600, 5.58365e-13,
1.84800, 5.36435e-13,
1.85000, 5.58834e-13,
1.85200, 5.55610e-13,
1.85400, 5.52216e-13,
1.85600, 5.44047e-13,
1.85800, 5.51977e-13,
1.86000, 5.43388e-13,
1.86200, 5.40151e-13,
1.86400, 5.43588e-13,
1.86600, 5.35598e-13,
1.86800, 5.36669e-13,
1.87000, 5.42668e-13,
1.87200, 5.26123e-13,
1.87400, 5.12178e-13,
1.87600, 4.46945e-13,
1.87800, 5.23286e-13,
1.88000, 5.29141e-13,
1.88200, 5.37328e-13,
1.88400, 5.35457e-13,
1.88600, 5.25875e-13,
1.88800, 5.38056e-13,
1.89000, 5.24510e-13,
1.89200, 5.23547e-13,
1.89400, 5.18181e-13,
1.89600, 5.08546e-13,
1.89800, 5.27070e-13,
1.90000, 5.24053e-13,
1.90200, 5.36481e-13,
1.90400, 5.25945e-13,
1.90600, 5.29258e-13,
1.90800, 5.25797e-13,
1.91000, 5.30504e-13,
1.91200, 5.19116e-13,
1.91400, 5.29884e-13,
1.91600, 5.25962e-13,
1.91800, 5.24187e-13,
1.92000, 5.15858e-13,
1.92200, 5.26272e-13,
1.92400, 5.19278e-13,
1.92600, 5.23667e-13,
1.92800, 5.11027e-13,
1.93000, 5.10823e-13,
1.93200, 5.05342e-13,
1.93400, 5.14171e-13,
1.93600, 5.13959e-13,
1.93800, 5.16829e-13,
1.94000, 5.00300e-13,
1.94200, 5.07327e-13,
1.94400, 4.64664e-13,
1.94600, 4.59172e-13,
1.94800, 5.00963e-13,
1.95000, 5.01190e-13,
1.95200, 4.87167e-13,
1.95400, 5.12530e-13,
1.95600, 5.10517e-13,
1.95800, 5.10310e-13,
1.96000, 5.07188e-13,
1.96200, 5.03740e-13,
1.96400, 4.89288e-13,
1.96600, 4.98149e-13,
1.96800, 5.08054e-13,
1.97000, 5.04290e-13,
1.97200, 4.89168e-13,
1.97400, 4.98210e-13,
1.97600, 5.02646e-13,
1.97800, 4.88209e-13,
1.98000, 4.93516e-13,
1.98200, 4.94868e-13,
1.98400, 4.95495e-13,
1.98600, 4.81433e-13,
1.98800, 5.00503e-13,
1.99000, 4.99770e-13,
1.99200, 4.92971e-13,
1.99400, 4.84237e-13,
1.99600, 4.92170e-13,
1.99800, 4.87685e-13,
2.00000, 4.94915e-13,
2.00200, 4.90296e-13,
2.00400, 4.87558e-13,
2.00600, 4.86984e-13,
2.00800, 4.92660e-13,
2.01000, 4.91268e-13,
2.01200, 4.89777e-13,
2.01400, 4.87242e-13,
2.01600, 4.88962e-13,
2.01800, 4.88320e-13,
2.02000, 4.82207e-13,
2.02200, 4.73967e-13,
2.02400, 4.82121e-13,
2.02600, 4.83177e-13,
2.02800, 4.80140e-13,
2.03000, 4.69698e-13,
2.03200, 4.82197e-13,
2.03400, 4.75758e-13,
2.03600, 4.75972e-13,
2.03800, 4.63999e-13,
2.04000, 4.78615e-13,
2.04200, 4.75565e-13,
2.04400, 4.78015e-13,
2.04600, 4.77576e-13,
2.04800, 4.74283e-13,
2.05000, 4.74405e-13,
2.05200, 4.68979e-13,
2.05400, 4.71633e-13,
2.05600, 4.72506e-13,
2.05800, 4.70368e-13,
2.06000, 4.61923e-13,
2.06200, 4.71428e-13,
2.06400, 4.53109e-13,
2.06600, 4.69738e-13,
2.06800, 4.67044e-13,
2.07000, 4.58812e-13,
2.07200, 4.63702e-13,
2.07400, 4.66966e-13,
2.07600, 4.66063e-13,
2.07800, 4.65679e-13,
2.08000, 4.55948e-13,
2.08200, 4.62139e-13,
2.08400, 4.54139e-13,
2.08600, 4.61937e-13,
2.08800, 4.60898e-13,
2.09000, 4.61020e-13,
2.09200, 4.46627e-13,
2.09400, 4.51786e-13,
2.09600, 4.50793e-13,
2.09800, 4.54576e-13,
2.10000, 4.55058e-13,
2.10200, 4.54163e-13,
2.10400, 4.55588e-13,
2.10600, 4.56493e-13,
2.10800, 4.54663e-13,
2.11000, 4.46787e-13,
2.11200, 4.52948e-13,
2.11400, 4.51579e-13,
2.11600, 4.43895e-13,
2.11800, 4.49794e-13,
2.12000, 4.45070e-13,
2.12200, 4.47130e-13,
2.12400, 4.40436e-13,
2.12600, 4.43971e-13,
2.12800, 4.47359e-13,
2.13000, 4.45428e-13,
2.13200, 4.46850e-13,
2.13400, 4.45599e-13,
2.13600, 4.36500e-13,
2.13800, 4.44875e-13,
2.14000, 4.42963e-13,
2.14200, 4.42987e-13,
2.14400, 4.40377e-13,
2.14600, 4.37239e-13,
2.14800, 4.41022e-13,
2.15000, 4.40132e-13,
2.15200, 4.37460e-13,
2.15400, 4.37087e-13,
2.15600, 4.37303e-13,
2.15800, 4.36489e-13,
2.16000, 4.33322e-13,
2.16200, 4.29252e-13,
2.16400, 4.20974e-13,
2.16600, 3.78746e-13,
2.16800, 4.14123e-13,
2.17000, 4.25559e-13,
2.17200, 4.28047e-13,
2.17400, 4.29030e-13,
2.17600, 4.25064e-13,
2.17800, 4.18623e-13,
2.18000, 4.30053e-13,
2.18200, 4.21488e-13,
2.18400, 4.27992e-13,
2.18600, 4.28594e-13,
2.18800, 4.14800e-13,
2.19000, 4.23539e-13,
2.19200, 4.26734e-13,
2.19400, 4.25392e-13,
2.19600, 4.24615e-13,
2.19800, 4.25316e-13,
2.20000, 4.23993e-13,
2.20200, 4.22401e-13,
2.20400, 4.23343e-13,
2.20600, 4.01944e-13,
2.20800, 4.12401e-13,
2.21000, 4.20265e-13,
2.21200, 4.20399e-13,
2.21400, 4.19323e-13,
2.21600, 4.15336e-13,
2.21800, 4.15640e-13,
2.22000, 4.18398e-13,
2.22200, 4.16883e-13,
2.22400, 4.15840e-13,
2.22600, 4.07600e-13,
2.22800, 4.13185e-13,
2.23000, 4.13555e-13,
2.23200, 4.13935e-13,
2.23400, 4.14172e-13,
2.23600, 4.12628e-13,
2.23800, 4.04914e-13,
2.24000, 4.08110e-13,
2.24200, 4.08163e-13,
2.24400, 4.09332e-13,
2.24600, 4.09809e-13,
2.24800, 4.02980e-13,
2.25000, 4.07687e-13,
2.25200, 4.06088e-13,
2.25400, 3.99432e-13,
2.25600, 4.03032e-13,
2.25800, 4.05353e-13,
2.26000, 4.05240e-13,
2.26200, 3.96348e-13,
2.26400, 4.02010e-13,
2.26600, 3.99723e-13,
2.26800, 4.02059e-13,
2.27000, 4.01889e-13,
2.27200, 3.99818e-13,
2.27400, 3.98066e-13,
2.27600, 4.00711e-13,
2.27800, 4.00697e-13,
2.28000, 3.99013e-13,
2.28200, 3.82156e-13,
2.28400, 3.95939e-13,
2.28600, 3.94788e-13,
2.28800, 3.96657e-13,
2.29000, 3.96396e-13,
2.29200, 3.95144e-13,
2.29400, 3.81872e-13,
2.29600, 3.85539e-13,
2.29800, 3.85464e-13,
2.30000, 3.88166e-13,
2.30200, 3.89663e-13,
2.30400, 3.89708e-13,
2.30600, 3.89602e-13,
2.30800, 3.89369e-13,
2.31000, 3.87762e-13,
2.31200, 3.87987e-13,
2.31400, 3.88549e-13,
2.31600, 3.83863e-13,
2.31800, 3.80911e-13,
2.32000, 3.85783e-13,
2.32200, 3.78113e-13,
2.32400, 3.70837e-13,
2.32600, 3.71319e-13,
2.32800, 3.78927e-13,
2.33000, 3.80441e-13,
2.33200, 3.76653e-13,
2.33400, 3.79304e-13,
2.33600, 3.74665e-13,
2.33800, 3.73766e-13,
2.34000, 3.79136e-13,
2.34200, 3.79169e-13,
2.34400, 3.78885e-13,
2.34600, 3.77304e-13,
2.34800, 3.77992e-13,
2.35000, 3.78001e-13,
2.35200, 3.63148e-13,
2.35400, 3.62496e-13,
2.35600, 3.69338e-13,
2.35800, 3.64649e-13,
2.36000, 3.69969e-13,
2.36200, 3.71970e-13,
2.36400, 3.70799e-13,
2.36600, 3.70861e-13,
2.36800, 3.70827e-13,
2.37000, 3.66784e-13,
2.37200, 3.69144e-13,
2.37400, 3.56081e-13,
2.37600, 3.67741e-13,
2.37800, 3.70410e-13,
2.38000, 3.69127e-13,
2.38200, 3.65147e-13,
2.38400, 3.46836e-13,
2.38600, 3.47862e-13,
2.38800, 3.60854e-13,
2.39000, 3.62207e-13,
2.39200, 3.60859e-13,
2.39400, 3.61537e-13,
2.39600, 3.60933e-13,
2.39800, 3.63447e-13,
2.40000, 3.58613e-13,
2.40200, 3.62200e-13,
2.40400, 3.61443e-13,
2.40600, 3.60373e-13,
2.40800, 3.60272e-13,
2.41000, 3.60351e-13,
2.41200, 3.60728e-13,
2.41400, 3.45870e-13,
2.41600, 3.36563e-13,
2.41800, 3.54201e-13,
2.42000, 3.52558e-13,
2.42200, 3.54307e-13,
2.42400, 3.52192e-13,
2.42600, 3.52508e-13,
2.42800, 3.52698e-13,
2.43000, 3.54692e-13,
2.43200, 3.53261e-13,
2.43400, 3.50906e-13,
2.43600, 3.47889e-13,
2.43800, 3.48242e-13,
2.44000, 3.52491e-13,
2.44200, 3.51656e-13,
2.44400, 3.51277e-13,
2.44600, 3.43920e-13,
2.44800, 3.41251e-13,
2.45000, 3.40821e-13,
2.45200, 3.40944e-13,
2.45400, 3.45357e-13,
2.45600, 3.39709e-13,
2.45800, 3.36053e-13,
2.46000, 3.46337e-13,
2.46200, 3.45695e-13,
2.46400, 3.46047e-13,
2.46600, 3.44790e-13,
2.46800, 3.44971e-13,
2.47000, 3.34644e-13,
2.47200, 3.44618e-13,
2.47400, 3.38220e-13,
2.47600, 3.43582e-13,
2.47800, 3.41573e-13,
2.48000, 3.27900e-13,
2.48200, 3.28511e-13,
2.48400, 3.39852e-13,
2.48600, 3.27966e-13,
2.48800, 3.38553e-13,
2.49000, 3.39015e-13,
2.49200, 3.38429e-13,
2.49400, 3.35157e-13,
2.49600, 3.36748e-13,
2.49800, 3.35981e-13,
2.50000, 3.37610e-13
])
COLINA_ARRAY = COLINA_ARRAY.reshape(COLINA_ARRAY.size//2,2)
COLINA_WAVELENGTH_MICRON = COLINA_ARRAY[:,0]
COLINA_FLUX_PER_HZ = COLINA_ARRAY[:,1] * np.pi # Column is F, not pi*F
# w = wavelength in microns
# f = frequency in Hz
#
# flux_w dw = flux_f df
#
# flux_w = flux_f |df/dw|
#
# f = C/w
#
# |df/dw| = C/w^2
SPEED_OF_LIGHT_MICRON_PER_SEC = C * 1.e9
COLINA_FLUX_PER_MICRON = COLINA_FLUX_PER_HZ * (SPEED_OF_LIGHT_MICRON_PER_SEC /
COLINA_WAVELENGTH_MICRON**2)
# W/m^2/micron
# Returns flux density in W/m^2/micron given wavelength in microns
FLUX_DENSITY_COLINA = tab.Tabulation(COLINA_WAVELENGTH_MICRON,
COLINA_FLUX_PER_MICRON)
# From Bohlin, Dickinson, & Calzetti 2001, Astron. J., for HST STIS
# To read the file instead of using the hard-wired table...
# HST_SUN_REFERENCE = os.environ["HST_SUN_REFERENCE"]
# f = pyfits.open(HST_SUN_REFERENCE)
# wavelength_angstrom = f[1].data.WAVELENGTH # Angstrom
# flux_cgs_per_angstrom = f[1].data.FLUX # erg/s/cm**2/A
# f.close()
STIS_ARRAY = np.array([
1195.000, 8.8615008E-03,
1205.000, 6.9449998E-02,
1215.000, 0.6080999,
1225.000, 0.1437000,
1235.000, 6.2695001E-03,
1245.000, 4.0755002E-03,
1255.000, 3.3780001E-03,
1265.000, 4.1625001E-03,
1275.000, 2.4150000E-03,
1285.000, 1.9545001E-03,
1295.000, 4.6680002E-03,
1305.000, 1.3810000E-02,
1315.000, 4.4809999E-03,
1325.000, 4.6494999E-03,
1335.000, 1.9305000E-02,
1345.000, 5.0630001E-03,
1355.000, 4.1964999E-03,
1365.000, 3.4324999E-03,
1375.000, 3.2259999E-03,
1385.000, 4.4944999E-03,
1395.000, 8.8989995E-03,
1405.000, 6.8195001E-03,
1415.000, 4.6124998E-03,
1425.000, 5.1210001E-03,
1435.000, 5.5789999E-03,
1445.000, 5.5705002E-03,
1455.000, 6.0394998E-03,
1465.000, 7.6934998E-03,
1475.000, 9.1944998E-03,
1485.000, 8.8510001E-03,
1495.000, 8.6170007E-03,
1505.000, 9.3970001E-03,
1515.000, 1.0006500E-02,
1525.000, 1.2685000E-02,
1535.000, 1.4125000E-02,
1545.000, 2.2624999E-02,
1555.000, 2.3435000E-02,
1565.000, 1.9819999E-02,
1575.000, 1.8435000E-02,
1585.000, 1.7945001E-02,
1595.000, 1.8710000E-02,
1605.000, 2.0700000E-02,
1615.000, 2.3815000E-02,
1625.000, 2.7030000E-02,
1635.000, 3.0874999E-02,
1645.000, 3.2145001E-02,
1655.000, 4.6160001E-02,
1665.000, 4.2739999E-02,
1675.000, 4.1414998E-02,
1685.000, 4.8404999E-02,
1695.000, 6.2390000E-02,
1705.000, 7.0175000E-02,
1715.000, 7.3305003E-02,
1725.000, 7.7200003E-02,
1735.000, 8.1254996E-02,
1745.000, 9.6354999E-02,
1755.000, 0.1147000,
1765.000, 0.1299000,
1775.000, 0.1497000,
1785.000, 0.1646000,
1795.000, 0.1685000,
1805.000, 0.1960500,
1815.000, 0.2399000,
1825.000, 0.2396500,
1835.000, 0.2392000,
1845.000, 0.2193500,
1855.000, 0.2453500,
1865.000, 0.2870000,
1875.000, 0.3198000,
1885.000, 0.3494500,
1895.000, 0.3793500,
1905.000, 0.3992500,
1915.000, 0.4422000,
1925.000, 0.4377500,
1935.000, 0.4032000,
1945.000, 0.5531000,
1955.000, 0.5768500,
1965.000, 0.6370500,
1975.000, 0.6571500,
1985.000, 0.6555500,
1995.000, 0.7052000,
2005.649, 0.7756500,
2015.651, 0.8497500,
2025.653, 0.8731000,
2035.654, 0.9743000,
2045.656, 1.083500,
2055.658, 1.116000,
2065.660, 1.172000,
2075.662, 1.341000,
2085.664, 1.585000,
2095.666, 2.233000,
2105.668, 2.916500,
2115.670, 3.501000,
2125.672, 3.270500,
2135.674, 3.446500,
2145.676, 4.172500,
2155.678, 3.771500,
2165.680, 3.363500,
2175.682, 3.666500,
2185.684, 4.621500,
2195.686, 4.889000,
2205.688, 4.933000,
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26457.22, 4.105946,
26557.24, 4.057827,
26657.27, 3.974363,
26757.30, 3.944365,
26857.32, 3.913914,
26957.35, 3.858138
])
STIS_ARRAY = STIS_ARRAY.reshape(STIS_ARRAY.size//2,2)
STIS_WAVELENGTH_MICRON = STIS_ARRAY[:,0] * 1.e-4
STIS_FLUX_PER_MICRON = STIS_ARRAY[:,1] * 1.e-7 * 1.e4 * 1.e4 # W/m^2/micron
# Returns flux density in W/m^2/micron given wavelength in microns
FLUX_DENSITY_STIS = tab.Tabulation(STIS_WAVELENGTH_MICRON,
STIS_FLUX_PER_MICRON)
# Combined function
SOLAR_FLUX_MODELS = {"COLINA": FLUX_DENSITY_COLINA,
"STIS": FLUX_DENSITY_STIS}
def flux_density(model="STIS"):
"""Returns the solar flux density at 1 AU in units of Watts per square meter
per micron of wavelength.
Input:
model name of the model, either "STIS" or "COLINA". "STIS" is
the default.
Return: a Tabulation of flux density (W/m^2/micron) vs.
wavelength (micron) at 1 AU.
"""
return SOLAR_FLUX_MODELS[model]
################################################################################
# Means over filter bandpasses
################################################################################
def bandpass_flux_density(bandpass, sun_range=1., model="STIS"):
"""Returns the solar flux density averaged over a filter bandpass.
Input:
bandpass a Tabulation of a filter bandpass.
sun_range the distance from the Sun to the target body in units of
AU.
model the ame of the model for solar flux density, either
"STIS" or "COLINA"; "STIS" is the default.
Return: the mean solar flux density within the filter bandpass,
in units of W/m^2/micron.
"""
# Multiply the bandpass and the solar spectrum
product = bandpass * flux_density(model)
# Resample the bandpass at the same wavelengths for a more reliable
# normalization
bandpass = bandpass.resample(product.x)
# Return the ratio of integrals
return product.integral() / (bandpass.integral() * sun_range**2)
def mean_flux_density(center, width, sun_range=1., model="STIS"):
"""Returns the solar flux density averaged over the bandpass of a "boxcar"
filter, given its center and full width.
Input:
center the center of the bandpass in microns.
width the full width of the bandpass in microns.
sun_range the distance from the Sun to the target body in units of
AU.
model the ame of the model for solar flux density, either
"STIS" or "COLINA"; "STIS" is the default.
Return: the mean solar flux density within the filter bandpass,
in units of W/m^2/micron.
"""
# Create a boxcar filter Tabulation
bandpass = tab.Tabulation((center - width/2., center + width/2.), (1.,1.))
# Return the mean over the filter
return bandpass_flux_density(bandpass, sun_range, model)
def bandpass_f(bandpass, sun_range=1., model="STIS"):
"""Returns the solar F averaged over a filter bandpass. F is defined such
that pi*F is the solar flux density.
Input:
bandpass a tuple (wavelength,throughput) of 1-D arrays,
describing the throughput of a filter as a function
of wavelength in microns.
sun_range the distance from the Sun to the target body in units of
AU.
model the ame of the model for solar flux density, either
"STIS" or "COLINA"; "STIS" is the default.
Return: the mean solar flux density within the filter bandpass,
in units of W/m^2/micron.
"""
return bandpass_flux_density(bandpass, sun_range, model) / np.pi
def mean_f(center, width, sun_range=1., model="STIS"):
"""Returns the solar F averaged over the bandpass of a "boxcar" filter,
given its center and full width. F is defined such that pi*F is the solar
flux density.
Input:
center the center of the bandpass in microns.
width the full width of the bandpass in microns.
sun_range the distance from the Sun to the target body in units of
AU.
model the ame of the model for solar flux density, either
"STIS" or "COLINA"; "STIS" is the default.
Return: the mean solar flux density within the filter bandpass,
in units of W/m^2/micron.
"""
return mean_flux_density(center, width, sun_range, model) / np.pi
################################################################################