documents/tutorials/Forward_modeling.ipynb
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Forward Modeling of an Emission Spectrum"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"from exojax.spec import rtransfer as rt"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"#ATMOSPHERE \n",
"NP=100\n",
"T0=1295.0 #K\n",
"Parr, dParr, k=rt.pressure_layer(NP=NP)\n",
"Tarr = T0*(Parr)**0.1"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"A T-P profile we assume is ... "
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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AwyM7MzungFHPLGDZVp1fX6SuU+HLafl8xj0XdWDaPX0xg2ufX8yEObmUlgXvb4QiUjkVvlSqZ0pTZt4/kJHdWvDnWeu5ftISdn531OtYInIOVPjyvRrHRvHXcT3489XnsWrHfkY8PZ8ZK3d6HUtEzpIKX6rEzLgmqw0f3j+Qdglx3Dflax586xudY1+kDlHhy1lJjW/A2/f05YGh6UxfsZORTy/QaRlE6ggVvpy1qAgfD17akbfv6Ut0pI/rJy3lNx/kcPS4zrwpEsxU+HLOeqQ0Zeb9A7i1XyovLdzC6PFavikSzFT4Ui31oyN57IquTLnjQopLyrhm4iL++OFanWdfJAip8KVG9EuL5+OfDuS6C1J4YX4eo8YvYNnWfV7HEpEKVPhSYxrWi+LxMZm8fvuFFJ8o4+qJi3lseg6Hi0u8jiYiqPAlAAakxzPrwUHc1KctLy/awvCn5zN/Q5HXsUTCngpfAiIuJpLfXtmNaXf3JTrCx82Tv+TBt75h3+HjXkcTCVsqfAmo3u2a8eEDA7n/4jRmrNzJ0L/M5e1l+TrtsogHVPgScPWiIvjZsE7MvH8g7eIb8PN/rGDcpCXkFh7yOppIWFHhS63pmNSQt+/pxx9/kMmanQcY9cwCnpy9Xks4RWqJCl9qlc9nXH9hCp89NJhRmS0Y/3kulz41j8/XFXgdTSTkqfDFEwkNY3h6bA+m3Hkh0RE+fvRyNne+ms32fUe8jiYSslT44ql+HeL56IFB/GJEJ77YuIdLnpzH059u0DSPSACo8MVz0ZE+fjI4jc8euohLMpJ4+tONXPLkPD5evUureURqkApfgkarJrFMuL4nU+68kPrREdzz+nJu+PtS1u8+6HU0kZCgwpeg069DPB/eP5DfXNGVnJ0HGPnMfH79/mq9aUukmlT4EpQiI3zc0i+VuT8fzA0XtuWNpdu46M9z+PuCPI6XlHkdT6ROUuFLUGvaIJrfXdWNjx8YSM+Upvx+5lqGPaX5fZFzocKXOiE9qSGv/Kg3L992AVERPu55fTnXTFzM8m36wBWRqlLhS50yuFMiHz0wkMfHZLJl7xHGPLuIe99YzpY9h72OJhL0LJh/Lc7KynLZ2dlex5Agdbi4hOfn5zFpfh4nSsu4/sIU/uPidBIaxngdTcRTZrbMOZf1b+MqfKnrCg8eY/xnG5n65XZiIn3cMbA9dw5sR8N6UV5HE/GECl9CXl7RIZ6YvZ4PV+2maf0o7h2Sxo192lIvKsLraCK16kyFX2tz+GbW3sxeNLO3a+trSnhpnxDHszf0Yvp9/enWujG/n7mWIU/MZeqX2zhRqqWcIlUqfDObbGaFZrb6lPERZrbezHLN7OHKnsM5l+ecu706YUWq4rzkJrx2+4VMufNCkhrV41fvruKSJ+fx3tf5lJYF72+0IoFW1T38l4ERFQfMLAKYAIwEMoBxZpZhZplmNuOUS2KNphapgn4d4nnvJ/2YfGsWDaIjefCtFQx/ej4frNhJmYpfwlBkVe7knJtvZqmnDPcGcp1zeQBm9iZwpXPuceCyGk0pco7MjIs7JzG4YyIf5+zmqU828B9Tv+avn2/kgaEdGdmtBT6feR1TpFZUZw6/NbC9wu18/9hpmVlzM5sI9DCzX1Vyv7vMLNvMsouKiqoRT+R/+XzGqMyWfPzTQYwf14PSMse9U5YzavwCPly1S3v8EhaqtIdfE5xze4F7qnC/F4AXoHyVTqBzSXiJ8BlXdG/F6MyWzFi5k2c+28hP3lhOx6Q47rs4ndGZLYnQHr+EqOrs4e8A2lS4newfEwl6ET7jyvNb88mDFzF+XA+cg/unfs2wp+bxzrJ8reqRkFSdwv8KSDezdmYWDYwFptdMLJHacXKPf9ZPBzHh+p5ERfh46B8rGPLEXN5YupXiEn3yloSOqi7LnAosBjqZWb6Z3e6cKwHuA2YBa4FpzrmcwEUVCRyfzxh9Xks+emAgf785i+ZxMTzy3moG/U/5KZkPFZd4HVGk2vROW5HTcM6xMHcvf5uzkSV5+2gcG8UtfdtyS79UmsfpXD0S3HRqBZFztHzbt0ycu4nZawqoF+Vj7AUp3D6gHW2a1fc6mshpqfBFqmljwUEmzsvj/W924IDRmS25a1B7urVu7HU0kX+hwhepIbv2H+WlhVuYsnQbh4pLGJAWzx0D23FRxwTMtKRTvKfCF6lh+4+eYMrSbby0cDOFB4vpmBTHHQPac2WPVsRE6gyd4h0VvkiAHC8p44MVO5m0II91uw8SHxfDTX3ackOfFOJ1gFc8oMIXCTDnHIs27WXSgjzmri8iOtLHVee34rb+7ejSspHX8SSMnKnwa+3UCiKhzszonxZP/7R4cgsP8fKizbyzbAfTsvPp16E5t/ZLZWiXJJ26QTyjPXyRAPruyHGmfrmd1xZvYef+YyQ3jeWWvqlcm9WGxvX1EYwSGJrSEfFQSWkZn6wp4KVFW/hy8z5ioyK4qkdrbu7bVtM9UuNU+CJBYs3OA7y8aDPvf7OT4pIyeqc246a+bRnetQXRkbX2qaMSwlT4IkHmuyPHmZa9ndeXbGPbviMkNIxh3AVtGNs7hVZNYr2OJ3WYCl8kSJWVOeZtKOLVxVuYu6EIAy7unMSNfVIYlJ6gT+SSs6ZVOiJByuczhnROZEjnRLbvO8LUL7cxLXs7n64tIKVZfcb2bsPVvZJJbFjP66hSx2kPXyQIHS8p4+Oc3byxZCtLN+8j0mdcmpHE9Rem0L9DvPb6pVLawxepQ6IjfVzRvRVXdG/FpqJDvPnlNt5els9Hq3fTplksYy9I4epeySQ10l6/VJ328EXqiOKSUmblFDB16TYW5+3FZ3Bx50SuuyCFIZ0SiIzQCh8pp4O2IiFky57DTMvezj+W5VN0sJjEhjGM6ZnMNVnJdEiI8zqeeEyFLxKCSkrLmLO+iLe+2sac9UWUljl6tW3KtVnJjD6vFXExmrUNRyp8kRBXePAY7y3fwbTs7WwqOkxsVAQjM1twda9k+rRrrgO9YUSFLxImnHMs3/Yd/8jezsyVuzhYXELrJrH8sGdrxvRMJjW+gdcRJcBU+CJh6OjxUmav2c3by/L5IncPzkFW26aM6ZnM6MyWOoFbiFLhi4S53fuP8d7XO3hneT65hYeIjvAxtEsiY3omc1HHBJ3HJ4So8EUEKJ/yWb3jAO9+nc8HK3ay59BxmtaP4rLzWnFVj1b0TGmqz+at41T4IvJvTpSWsWBjEe8u38EnawooLimjTbNYruzemqt6tCItsaHXEeUcqPBFpFKHikuYtXo3/++bHSzM3UOZg66tGnFF91Zc3r2VzuBZh6jwRaTKCg8e44MVu5j+zQ5W5O8H4ILUplzRvRWjMlvSXB/OHtRU+CJyTrbsOcwHK3YyfcVONhYeIsJn9OvQnMvPa8Xwri200icIqfBFpFqcc6wvOMj0b3bywcqdbN93lKgIY1B6Apd1b8klXZJoWE/lHwxU+CJSY5xzrMzfz4yVO5m5chc79x8jOtLH4I4JjD6vJUO7JOm0Dh5S4YtIQJSVOb7e/i0frNjFR6t3UXCgmOhIHxd1TGBUZgvt+XvA88I3s/bAI0Bj59zVVXmMCl+kbikrcyzf9i0zV+3io1W72X3gGNERPgamxzOiWwsuzUiiSf1or2OGvIAUvplNBi4DCp1z3SqMjwCeASKAvzvn/m+Fv3tbhS8S+k7u+c9cuZuPV5dP+0T6jL4dmjOiWwuGZbQgoaFW+wRCoAp/EHAIePVk4ZtZBLABuBTIB74Cxjnn1vj/XoUvEmZOzvl/tLq8/LfsPYLPICu1GcO7tmB41ySSm9b3OmbICNiUjpmlAjMqFH5f4DHn3HD/7V8BOOce99+utPDN7C7gLoCUlJReW7durVY+EQkuzjnW7T7IR6t3M2v1btYXHASgW+tGDM9owfBuLUhPjNPpHaqhNgv/amCEc+4O/+2bgAuBR4E/UL7n//eT/wFURnv4IqFv857DzM7Zzayc3Szf9h0A7eIbMCwjiUszkuiR0pQIncv/rHj+IebOub3APbX19USkbmgX34C7L+rA3Rd1oPDAMWavKWBWzm4mL9zM8/PzaN4gmqFdEhmW0YIB6fHUi4rwOnKdFYjC3wG0qXA72T8mIlKpxEb1uLFPW27s05YDx04wb30Rn6wp4KNVu5mWnU9sVAQD0+O5pEsSQzon6qDvWQpE4X8FpJtZO8qLfixwfQC+joiEsEb1orjcf+K24yVlLN28l0/WFPDpmgJmrynADM5v04RLuiRxSZckOiZp3v/7VHeVzlRgMBAPFACPOudeNLNRwNOUL8uc7Jz7w7k8v+bwReRUzjnW7jrIp2sL+GxtwT9P7pbcNJahnRMZ0jmRPu2bh/XUj+dvvDoXKnwR+T6FB47x+bpCPl1bwBe5ezh2oozYqAj6p8UztEsiQzol0qJxPa9j1ioVvoiEvGMnSlmct5c56wr5bG0hO747CpSf139Ip0SGdE7g/Dahv+pHhS8iYcU5x4aCQ3y+rpDP1xWwfNt3lJY5mtSPYlB6AkM6JzAoPSEkz+2vwheRsLb/yAkW5BYxZ10R8zYUsedQMWZwXnITLuqYwOBOCXRPbhISe/8qfBERv7IyR87OA8xZX8ic9YWs2P4dZQ4ax0YxMD2eizomcFHHBBIb1c25fxW+iMgZfHfkOAs27mHehvK9/6KDxQB0admIQR3jGZSeQFZqU2Ii68bKHxW+iEgVnFz2OW9DEXPXF7J827ecKHXERkVwYftmDEpPYFDHeDokBO+6fxW+iMg5OFRcwtK8vczfUMSCjXvI23MYgFaN6zEgPZ4B6Qn079A8qA7+qvBFRGrA9n1HWLBxDws2FrEwdw8HjpUA5Us/B6THMzCtfPrHyzd+qfBFRGpYaZlj1Y79fLGxfO//5PRPTKSPC1Kb0T8tnv5pzenaqnGtrv5R4YuIBNjh4hK+3LyPBRv3sDB3zz/P9d84Noo+7ZsxIC2efmnxtI9vEND5f89PjywiEuoaxEQyxH8+H4Cig8Us2lRe/gtz9zIrpwCAlo3r0bd9c/p2aE6/tHhaN4mtlXzawxcRqQXOObbtO8LC3L0s3LSHJZv2svfwcQDaNq//z/8A+nZoTmLD6q3/15SOiEgQKStzbCg8yOJNe1m0aS9L8vZy0H8AOC0xjok39iQtseE5PbemdEREgojPZ3Ru0YjOLRpxW/92lJY51uw8wKJNe1iSt5eWjWt+mkeFLyISBCJ8RmZyYzKTG3P3RR0C8jV8AXlWEREJOip8EZEwocIXEQkTKnwRkTChwhcRCRMqfBGRMKHCFxEJEyp8EZEwEdSnVjCzImBrAJ46HtgTgOetaXUhpzLWDGWsOXUhZ6AztnXOJZw6GNSFHyhmln2680wEm7qQUxlrhjLWnLqQ06uMmtIREQkTKnwRkTARroX/gtcBqqgu5FTGmqGMNacu5PQkY1jO4YuIhKNw3cMXEQk7KnwRkTARkoVvZm3MbI6ZrTGzHDN7wD/+mJntMLNv/JdRFR7zKzPLNbP1Zja8lnJuMbNV/izZ/rFmZvaJmW30/9nUP25mNt6fcaWZ9ayFfJ0qbKtvzOyAmf00GLajmU02s0IzW11h7Ky3nZnd4r//RjO7pRYy/tnM1vlzvGdmTfzjqWZ2tMI2nVjhMb38r5Nc//dhAc541j9fMxvhH8s1s4drKl8lGd+qkG+LmX3jH/dqO56pc4LqNYlzLuQuQEugp/96Q2ADkAE8Bvz8NPfPAFYAMUA7YBMQUQs5twDxp4z9D/Cw//rDwJ/810cBHwEG9AGW1vI2jQB2A22DYTsCg4CewOpz3XZAMyDP/2dT//WmAc44DIj0X/9ThYypFe93yvN86c9t/u9jZIAzntXP13/ZBLQHov33yQhkxlP+/i/Arz3ejmfqnKB6TYbkHr5zbpdzbrn/+kFgLdC6kodcCbzpnCt2zm0GcoHegU96xiyv+K+/AlxVYfxVV24J0MTMWtZirqHAJudcZe98rrXt6JybD+w7zdc/m203HPjEObfPOfct8AkwIpAZnXOznXMl/ptLgOTKnsOfs5Fzbokrb4RXK3xfAclYiTP9fHsDuc65POfcceBN/30DntG/l34tMLWy56iF7Ximzgmq12RIFn5FZpYK9ACW+ofu8/8KNfnkr1eU/2C2V3hYPpX/B1FTHDDbzJaZ2V3+sSTn3C7/9d1AkscZTxrLv/6jCqbteNLZbjuv8/6I8r28k9qZ2ddmNs/MBvrHWvtznVRbGc/m5+vldhwIFDjnNlYY83Q7ntI5QfWaDOnCN7M44B3gp865A8BzQAfgfGAX5b8KemmAc64nMBK418wGVfxL/56I5+tmzSwauAL4h38o2LbjvwmWbXcmZvYIUAK84R/aBaQ453oAPwOmmFkjj+IF/c+3gnH8646Ip9vxNJ3zT8HwmgzZwjezKMo3/BvOuXcBnHMFzrlS51wZMIn/nW7YAbSp8PBk/1hAOed2+P8sBN7z5yk4OVXj/7PQy4x+I4HlzrkCf96g2o4VnO228ySvmd0KXAbc4C8B/NMke/3Xl1E+J97Rn6fitE/AM57Dz9er7RgJjAHeOjnm5XY8XecQZK/JkCx8/7zei8Ba59yTFcYrznn/ADh51H86MNbMYsysHZBO+QGeQGZsYGYNT16n/GDean+Wk0fmbwHer5DxZv/R/T7A/gq/Kgbav+xFBdN2PMXZbrtZwDAza+qfthjmHwsYMxsB/AK4wjl3pMJ4gplF+K+3p3zb5flzHjCzPv7X9c0Vvq9AZTzbn+9XQLqZtfP/NjjWf99AuwRY55z751SNV9vxTJ1DsL0ma+robzBdgAGU/+q0EvjGfxkFvAas8o9PB1pWeMwjlO8NrKcGj95XkrE95asZVgA5wCP+8ebAZ8BG4FOgmX/cgAn+jKuArFralg2AvUDjCmOeb0fK/wPaBZygfJ7z9nPZdpTPo+f6L7fVQsZcyudoT74uJ/rv+0P/6+AbYDlweYXnyaK8dDcBf8P/DvkAZjzrn6//39cG/989Eujt6B9/GbjnlPt6tR3P1DlB9ZrUqRVERMJESE7piIjIv1Phi4iECRW+iEiYUOGLiIQJFb6ISJhQ4YuIhAkVvohImPj/fgRKE3f3914AAAAASUVORK5CYII=",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"import matplotlib.pyplot as plt\n",
"plt.plot(Tarr,Parr)\n",
"plt.yscale(\"log\")\n",
"plt.gca().invert_yaxis()\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We set a wavenumber grid using wavenumber_grid."
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"xsmode assumes ESLOG in wavenumber space: mode=lpf\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/kawahara/exojax/src/exojax/utils/grids.py:124: UserWarning: Resolution may be too small. R=286712.70993002696\n",
" warnings.warn('Resolution may be too small. R=' + str(resolution),\n"
]
}
],
"source": [
"from exojax.utils.grids import wavenumber_grid\n",
"nus,wav,res=wavenumber_grid(22920,23000,1000,unit=\"AA\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Loading a molecular database of CO and CIA (H2-H2)... "
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Background atmosphere: H2\n",
"Reading .database/CO/12C-16O/Li2015/12C-16O__Li2015.trans.bz2\n",
".broad is used.\n",
"Broadening code level= a0\n",
"H2-H2\n"
]
}
],
"source": [
"from exojax.spec import api, contdb\n",
"mdbCO=api.MdbExomol('.database/CO/12C-16O/Li2015',nus,crit=1.e-46)\n",
"cdbH2H2=contdb.CdbCIA('.database/H2-H2_2011.cia',nus)"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
"from exojax.spec import molinfo\n",
"molmassCO=molinfo.molmass(\"CO\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Computing the relative partition function, "
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
"from jax import vmap\n",
"qt=vmap(mdbCO.qr_interp)(Tarr)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Pressure and Natural broadenings "
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
"from jax import jit\n",
"from exojax.spec.exomol import gamma_exomol\n",
"from exojax.spec import gamma_natural\n",
"\n",
"gammaLMP = jit(vmap(gamma_exomol,(0,0,None,None)))\\\n",
" (Parr,Tarr,mdbCO.n_Texp,mdbCO.alpha_ref)\n",
"gammaLMN=gamma_natural(mdbCO.A)\n",
"gammaLM=gammaLMP+gammaLMN[None,:]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Doppler broadening"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [],
"source": [
"from exojax.spec import doppler_sigma\n",
"sigmaDM=jit(vmap(doppler_sigma,(None,0,None)))\\\n",
" (mdbCO.nu_lines,Tarr,molmassCO)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"And line strength"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [],
"source": [
"from exojax.spec import SijT\n",
"SijM=jit(vmap(SijT,(0,None,None,None,0)))\\\n",
" (Tarr,mdbCO.logsij0,mdbCO.nu_lines,mdbCO.elower,qt)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"nu matrix"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [],
"source": [
"from exojax.spec import make_numatrix0\n",
"numatrix=make_numatrix0(nus,mdbCO.nu_lines)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Or you can use initspec.init_lpf instead."
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [],
"source": [
"#Or you can use initspec.init_lpf instead.\n",
"from exojax.spec import initspec\n",
"numatrix=initspec.init_lpf(mdbCO.nu_lines,nus)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Providing numatrix, thermal broadening, gamma, and line strength, we can compute cross section. "
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [],
"source": [
"from exojax.spec.lpf import xsmatrix\n",
"xsm=xsmatrix(numatrix,sigmaDM,gammaLM,SijM)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"xsmatrix has the shape of (# of layers, # of nu grid)"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(100, 1000)"
]
},
"execution_count": 14,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import numpy as np\n",
"np.shape(xsm)"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [
{
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAXAAAABECAYAAACYhW4wAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjQuMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/MnkTPAAAACXBIWXMAAAsTAAALEwEAmpwYAAAN80lEQVR4nO2dW6wdVRnHf9/u9vRweno7LTSVEoHYaIiJgEQh8qAiisSID8RATOwDSV80ojExJT75aGJETAyReAkxKiqCkD6AWHmubSPhVgoFCrQKpUghpamHnf35MGt1r7M6s/fsue3b90t25rbm+9Zt/mvNWjOzRVUxDMMwJo/WqCNgGIZhFMME3DAMY0IxATcMw5hQTMANwzAmFBNwwzCMCcUE3DAMY0IpJeAicoOIHBKRwyKyq6pIGYZhGIORos+Bi8gq4HngeuAosA+4VVWfrS56hmEYRhZleuCfBA6r6kuqugzcB9xUTbQMwzCMQbRLnHsh8FqwfRT4VBxIRHYCO93mJ0r4MwzDmFVOqOr58c4yAp4LVb0HuAdAROy9fcMwjOF5JW1nmSGUY8BFwfY2t88wDMNogDICvg/YLiKXiMgccAvwcDXRMgzDMAZReAhFVTsi8i3gUWAV8GtVfaaymBmGYRh9KfwYYSFnNgZuGIZRhAOqelW8097ENAzDmFBMwA3DMCaUsRHwsYmIYRjGhDA2utmi+ciMTeINwzAKMDYaNoqITGODMTYFahhG7YzN9d5mOgW1aV91+xmbCmMYxvhcj6MQ8KZ9TkMPvC77Y1MRDWOCGJvrZo4GPswS0aSAt2kmfXX7qMt+HeUwNpXbMGoiVx0XkSMi8pSIPCEi+92+JRF5TERecMuNZSIyTyLiTTJPs0MbTQh43Xk4iwJe1QS7NShG1QxTpz6rqpcHbwPtAvao6nZgj9suzALNC/gC09cDn6/Zfl1lVHXejOKppjqZprQY1VGmXtwE3OvW7wW+WiYii4xGwJsatpmjfnGFJE11Ulca6ij7qsq2isagrI2i5w57njUUk0Xe8lLgbyJywP1BA8AWVf2PW38d2JJ2oojsFJH9fugli3XULz5pPpsS8HmaEfDFmu3XKeBVikeVQ1ZV2SpjwwTcSCNvnbpWVY+JyAXAYyLyXHhQVTXrQ1V5/9BhHXAyZ2SqYiPN9fqbEvB1JBdht0b7dVB1492iurKtYrK7bCPQBpYLntcZInzedPpw/epZv3pYZx2dJXKVl6oec8vjwIMk/4f5hohsBXDL42UiskT9vceYTTQjqpAIVBPpW6rRdov6BHyRant/baor2yrmL6oQ8CL5M6zPYXwMClskvmnn2F1BNgPzRkTWiMhavw58AXia5M8bdrhgO4CHykRkI7C2jIECnE9zAr5IfeLnaZEIeJ3Pam+oyb6/c6iKNtX16uco35tvUa6uFT132HjnDZ9nTL/f8TxlPW0T0XWQp4HeAjwoIj7871X1ERHZB/xJRG4j+b+2r5WJyFIb1g9zr1cBW+Zh/kwzvtYBaxrwcwH1VvpNNdldz3gLeNm4lb0j8I+8DjvsUJeA5xEOP3yTFue22x8e84LdDba75BuumVUGloOqvgR8PGX/W8B1VUVk0xJsKDUIMxwtYPNmWDzajL911H+H0QI2L0D7dLHx0kG0SQS86vHLlrNb5YTyHNUNWVXxvkBZAS/yyGuL4Rsx31gNKt88veN+5dkKlqGvUNhbwa+O+jwNjMUdSgvYsKG+2/Msn0tL1Y+9ZvlaS/W9zJg2SZrqfFZ7fbueZ7bXUm2856lWwMv25udK2igq4MM0PsOED+cFssL7xiDteNq8gp8naAVh4n3GSkaeL/5pgYUFWNNuprB8pVhcTIY1mvC3nnobC3/xLS7W84apt792sfoGok1PwKt643EeOI9qJh8XKJ+nXsCLTkQWeVN5WAGHlWXQ77w8n77oN/nrr/NWtC8W8HZOX7PKSAXcF+A80GrBefP9W+0qfS4AnU4irHU2Gr6B8pXQX1BVP/Ps0/R+pzchWLWPRaDbTdJQVZ6FIlPVm7He1mrKxzMsv6J2vI08vdY0QiEbplzbrBTFPEMesYim4TtA/eLjw6T5jo/F+1us9GECns3I8iUspHXAyZOJOCySTHz4+cyqx1pDn2/9t9cz6lbsM+xFePv/c+vLgY+yvs5J04neW61+3LCMj9D+InDy3cTPu5TPL293ATjFyjdj4wmuvPagd9F3SBqHcG48r83QVrge2shjKxSibrD0Y7x5xprDc8OJvX7n+s5Cl3x54P3AyroTh29Fv7BBCicfw+GP+Fn08NywnMNz4m2/bhOZK2lcwMPbM3/xbgBeeRXe6yTrZ9wvfiilSOGltfDe54uHk4q6zvk6k+KjqIj4SjpH7yUlL7JnSPwWTV9WmhaAl072xmzDRqmoD2/fv4j0Gr0hhbiM8gqaX54dPiN5ldd/bmBYu2lx7ZI0Mr7BjJ+G6PeCSRi/eXpi5u16W/0EJWzA/eTlGXpiGgpXbCNOzxxwOljPSkt8Xtv59D3YQYLvXxbqFz4UeoL4pNXJTmC3G50D2QI+x7nCHTbKRRr3aWUkAh5WTP8Rq0OdXo/Ji0+L7MeQhvHnl96nHwJ4luTC8OIUXpxlGoswjV7sjrlj8TdRyvQ0QxH0Nl9gZc8zTbzy+ohFtgMcccd9foVpyNuj9Esf7xbw7yDew9qNe4Re8DrBNuR7IzEUXn/uKbfPC8iguKUJ6TJJg+JtLkfh415uGIe2O9f3wr3/ThSe6LyWi7vP6/DONo6vP+d0lFYvzuFTIaHwhgISCnE7OLedcrwbHQt77XPBelxfSEnDLIt5owIurKyUvqCWgcMujL/ofM/HizgML3ZhBQh9zpH0TI7QEzd/mxoKXl5R8r5Cn2E6O4D/aEwn8OW3iwpgKFj+YvWiHVb4OA/D5bD2lwP7vvLkSUNsNxa3E5x7wcd243in2fRp9sLlRSbsEAxKfzw8cCo43i9uaXa8EPm7rm6KjbR0xWJ5mpWi16/xCHvA/m4mTE/oL/Tl63/oJ61xCfMxLVwYx3DbE6+HcQiPx2UeD9cMqnOzIOyimvl5kspZJaJ+nDMWubCwOsGvm/ILSbugw/UW514Qsc/QV7gM7ecR1rjnFd8GxunrMpyvVsqyHS3jyp2Wh1k+0uzHPvy5afZju/GtfWgz7RfaHjTMEMc7y54/NxbLPAIel2lWXexXB7Pik1WfYzuxwMbxz2rQ4riEYfvdMcTkCZunLmUd77ce2o+vzawy6KcP/ZgAsT8QfMr7LCMZQvGZ5Xu7eSpaXInz+gqX0Cv8tBcDQtthLyc+luUnXI/TmOUnzVdamDiP4rDLKfvSwmddUDFpgpM1BBGWTR77cR4NEtNBdtPSPUhUBglnbCO2G4vyILLiM8hGWv3rly958imvzzxhw/jktdlvf78898Rj5/06EP3sx/GoQsSbbggaF/BBvYBBZFXovD6LFtQwwpTmd9hz8+ZHWoXP6yMvefOriP0ieTMKm2XPq8NOkTpZBVWWc7+yGtSbjhuaQZ2gQYKeV+xHQVZcRibgefYXEbFR0kQ86rggjR7Tlr9pw1hV2WzKRl7NiMU7rVM06JysY4PiUuacPIyFgHfh1Gk41KTPMWYzydydYXkRYnnRw/Kix4fSdjbdAz+UNhA/i4jIfsuLBMuLHpYXPSwvBjNtd4yGYRgzgwm4YRjGhNK0gN/TsL9xxvKih+VFD8uLHpYXA2j0RR7DMAyjOmwIxTAMY0IxATcMw5hQGhFwEblBRA6JyGER2dWEz1EiIheJyOMi8qyIPCMit7v9SyLymIi84JYb3X4RkZ+5/HlSRK4cbQqqR0RWici/RGS3275ERPa6NP9RRObc/tVu+7A7fvFII14xIrJBRO4XkedE5KCIXDOr9UJEvuuuj6dF5A8iMj+r9aIotQu4iKwCfg58CbgMuFVELqvb74jpAN9T1cuAq4FvujTvAvao6nZgj9uGJG+2u99O4O7mo1w7twMHg+0fAXeq6oeBt4Hb3P7bgLfd/jtduGniLuARVf0oyZ+FH2QG64WIXAh8G7hKVT8GrAJuYXbrRTFUtdYfcA3waLB9B3BH3X7H6Qc8BFxP8hbqVrdvK8mLTQC/AG4Nwp8NNw0/YBuJMH0O2E3yZeETQDuuI8CjwDVuve3CyajTUFE+rAdejtMzi/UCuJDk/0GWXDnvBr44i/WizK+JIRRfUJ6jbt9M4G71rgD2AltU1X8a/HVgi1uf9jz6KfB9ep902AScVFX/gcMwvWfzwh1/x4WfBi4B3gR+44aTfikia5jBeqGqx4AfA6+SfC7/HeAAs1kvCmOTmDUiIovAX4DvqOq74TFNuhJT/wyniHwZOK6qB0YdlzGgDVwJ3K2qVwDv0RsuAWaqXmwEbiJp1D4IrAFuGGmkJpAmBPwYcFGwvY3eP4xNLSLyARLx/p2qPuB2vyEiW93xrcBxt3+a8+jTwFdE5AhwH8kwyl3ABhHx3+IJ03s2L9zx9cBbTUa4Ro4CR1V1r9u+n0TQZ7FefB54WVXfVNX3gQdI6sos1ovCNCHg+4DtbnZ5jmSi4uEG/I4MERHgV8BBVf1JcOhhYIdb30EyNu73f8M9dXA18E5wSz3RqOodqrpNVS8mKft/qOrXgceBm12wOC98Ht3swk9Fj1RVXwdeE5GPuF3Xkfw168zVC5Khk6tFZMFdLz4vZq5elKKhCYsbgeeBF4EfjHrgv4H0XktyG/wk8IT73UgyZreH5L+H/w4sufBC8qTOi8BTJDPzI09HDfnyGWC3W78U+CfJ36H+GVjt9s+77cPu+KWjjnfFeXA5sN/Vjb8CG2e1XgA/BJ4DngZ+C6ye1XpR9Gev0huGYUwoNolpGIYxoZiAG4ZhTCgm4IZhGBOKCbhhGMaEYgJuGIYxoZiAG4ZhTCgm4IZhGBPK/wEDYhT6iMS0oAAAAABJRU5ErkJggg==",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"import numpy as np\n",
"plt.imshow(xsm,cmap=\"afmhot\")\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"computing delta tau for CO"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [],
"source": [
"from exojax.spec.rtransfer import dtauM\n",
"Rp=0.88\n",
"Mp=33.2\n",
"g=2478.57730044555*Mp/Rp**2\n",
"#g=1.e5 #gravity cm/s2\n",
"MMR=0.0059 #mass mixing ratio\n",
"dtaum=dtauM(dParr,xsm,MMR*np.ones_like(Tarr),molmassCO,g)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"computing delta tau for CIA"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [],
"source": [
"from exojax.spec.rtransfer import dtauCIA\n",
"mmw=2.33 #mean molecular weight\n",
"mmrH2=0.74\n",
"molmassH2=molinfo.molmass(\"H2\")\n",
"vmrH2=(mmrH2*mmw/molmassH2) #VMR\n",
"dtaucH2H2=dtauCIA(nus,Tarr,Parr,dParr,vmrH2,vmrH2,\\\n",
" mmw,g,cdbH2H2.nucia,cdbH2H2.tcia,cdbH2H2.logac)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The total delta tau is a summation of them"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {
"scrolled": true
},
"outputs": [],
"source": [
"dtau=dtaum+dtaucH2H2"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"you can plot a contribution function using exojax.plot.atmplot "
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 1440x216 with 3 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"from exojax.plot.atmplot import plotcf\n",
"plotcf(nus,dtau,Tarr,Parr,dParr)\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"radiative transfering..."
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {},
"outputs": [],
"source": [
"from exojax.spec import planck\n",
"from exojax.spec.rtransfer import rtrun\n",
"sourcef = planck.piBarr(Tarr,nus)\n",
"F0=rtrun(dtau,sourcef)"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[<matplotlib.lines.Line2D at 0x7f2baa2c2970>]"
]
},
"execution_count": 21,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plt.plot(wav[::-1],F0)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"applying an instrumental response and planet/stellar rotation to the raw spectrum"
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {},
"outputs": [],
"source": [
"from exojax.spec import response\n",
"from exojax.utils.constants import c\n",
"import jax.numpy as jnp\n",
"\n",
"wavd=jnp.linspace(22920,23000,500) #observational wavelength grid\n",
"nusd = 1.e8/wavd[::-1]\n",
"\n",
"RV=10.0 #RV km/s\n",
"vsini=20.0 #Vsini km/s\n",
"u1=0.0 #limb darkening u1\n",
"u2=0.0 #limb darkening u2\n",
"\n",
"R=100000.\n",
"beta=c/(2.0*np.sqrt(2.0*np.log(2.0))*R) #IP sigma need check \n",
"\n",
"Frot=response.rigidrot(nus,F0,vsini,u1,u2)\n",
"F=response.ipgauss_sampling(nusd,nus,Frot,beta,RV)"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[<matplotlib.lines.Line2D at 0x7f2baa4ff190>]"
]
},
"execution_count": 23,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plt.plot(wav[::-1],F0)\n",
"plt.plot(wavd[::-1],F)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The flux decreases at the edges of the left and right sides are artificial due to the convolution. You might need to some margins of the wavenumber range to eliminate these artifacts."
]
},
{
"cell_type": "code",
"execution_count": 25,
"metadata": {},
"outputs": [],
"source": [
"np.savetxt(\"spectrum.txt\",np.array([wavd,F]).T,delimiter=\",\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3.8.8 ('base')",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.8"
},
"vscode": {
"interpreter": {
"hash": "72bc7f8b1808a6f5ada3c6a20601509b8b1843160436d276d47f2ba819b3753b"
}
}
},
"nbformat": 4,
"nbformat_minor": 2
}