documents/tutorials/Forward_modeling_for_metal_line.ipynb
{
"cells": [
{
"cell_type": "markdown",
"id": "ed0286c4",
"metadata": {},
"source": [
"<div id=\"toc\"></div>"
]
},
{
"cell_type": "markdown",
"id": "0d697997",
"metadata": {},
"source": [
"# Forward modeling of the emission spectrum using VALD3"
]
},
{
"cell_type": "markdown",
"id": "d74a46bd",
"metadata": {},
"source": [
"Tako Ishikawa, Hajime Kawahara \n",
"created: : 2021/07/20, last update: 2024/06/14 \n",
"\n",
"<!-- \n",
"written with reference to : \n",
"\"exojax/examples/tutorial/Forward\\ modeling.ipynb\" \n",
"\"ghR/exojax_0/examples/testlines/line_strength_CO.py\" \n",
"\n",
"cd ~/work\n",
"\n",
"-->"
]
},
{
"cell_type": "markdown",
"id": "e82619f2",
"metadata": {},
"source": [
"This example provides how to use VALD3 for forward modeling of the emission spectrum. Currenty, we use exojax.spec.moldb as API for VALD3 because we have not implemented the VALD3 API in radis.api yet. \n",
"Someday, we (or someone who is reading this document.) would include the VALD3 API in radis.api! "
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "d0df12a8",
"metadata": {
"execution": {
"iopub.execute_input": "2022-10-30T01:16:25.553082Z",
"iopub.status.busy": "2022-10-30T01:16:25.551434Z",
"iopub.status.idle": "2022-10-30T01:16:28.069689Z",
"shell.execute_reply": "2022-10-30T01:16:28.069336Z"
}
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"An NVIDIA GPU may be present on this machine, but a CUDA-enabled jaxlib is not installed. Falling back to cpu.\n"
]
}
],
"source": [
"from exojax.utils.grids import wavenumber_grid\n",
"from exojax.atm.atmprof import pressure_layer_logspace\n",
"from exojax.spec import moldb, molinfo, contdb\n",
"from exojax.spec import atomll\n",
"from exojax.spec.hitran import line_strength\n",
"from exojax.spec import doppler_sigma\n",
"import matplotlib.pyplot as plt\n",
"import jax.numpy as jnp\n",
"from jax import vmap, jit\n",
"import numpy as np\n",
"import os"
]
},
{
"cell_type": "markdown",
"id": "c397c78a",
"metadata": {},
"source": [
"## Wavenumber"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "1a2b45af",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"xsmode = lpf\n",
"xsmode assumes ESLOG in wavenumber space: mode=lpf\n",
"======================================================================\n",
"The wavenumber grid should be in ascending order.\n",
"The users can specify the order of the wavelength grid by themselves.\n",
"Your wavelength grid is in *** ascending *** order\n",
"======================================================================\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/tako/ghR/exojax/src/exojax/spec/unitconvert.py:62: UserWarning: Both input wavelength and output wavenumber are in ascending order.\n",
" warnings.warn(\n",
"/home/tako/ghR/exojax/src/exojax/spec/unitconvert.py:62: UserWarning: Both input wavelength and output wavenumber are in ascending order.\n",
" warnings.warn(\n"
]
}
],
"source": [
"#We set a wavenumber grid using wavenumber_grid.\n",
"nu_grid,wav,res = wavenumber_grid(10380, 10430, 4500, xsmode=\"lpf\", unit=\"AA\", wavelength_order=\"ascending\") "
]
},
{
"cell_type": "markdown",
"id": "1e3bcbcc",
"metadata": {},
"source": [
"## T-P profile "
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "cc46d690",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"rtsolver: ibased\n",
"Intensity-based n-stream solver, isothermal layer (e.g. NEMESIS, pRT like)\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/tako/ghR/exojax/src/exojax/spec/dtau_mmwl.py:14: FutureWarning: dtau_mmwl might be removed in future.\n",
" warnings.warn(\"dtau_mmwl might be removed in future.\", FutureWarning)\n"
]
},
{
"data": {
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",
"text/plain": [
"<Figure size 600x400 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# Assume ATMOSPHERE \n",
"from exojax.spec.atmrt import ArtEmisPure\n",
"\n",
"nlayer=100\n",
"T0 = 3000. #10000. #3000. #1295.0 #K\n",
"alpha = 0.1\n",
"Tlow = 500.0\n",
"Thigh = 4500.0\n",
"art = ArtEmisPure(nu_grid=nu_grid, pressure_top=1.e-8, pressure_btm=1.e2, nlayer=nlayer)\n",
"art.change_temperature_range(Tlow, Thigh)\n",
"Tarr = art.powerlaw_temperature(T0, alpha)\n",
"Parr = art.pressure\n",
"dParr = art.dParr\n",
"\n",
"H_He_HH_VMR = [0.0, 0.16, 0.84] # typical quasi-\"solar-fraction\"\n",
"PH = Parr * H_He_HH_VMR[0]\n",
"PHe = Parr * H_He_HH_VMR[1]\n",
"PHH = Parr * H_He_HH_VMR[2]\n",
"\n",
"fig = plt.figure(figsize=(6, 4))\n",
"plt.plot(Tarr, Parr, label=\"$P_\\mathrm{total}$\")\n",
"plt.plot(Tarr, PH, \"--\", label=\"$P_\\mathrm{H}$\")\n",
"plt.plot(Tarr, PHH, \"--\", label=\"$P_\\mathrm{H_2}$\")\n",
"plt.plot(Tarr, PHe, \"--\", label=\"$P_\\mathrm{He}$\")\n",
"plt.plot(Tarr[80], Parr[80], marker=\"*\", markersize=15)\n",
"plt.yscale(\"log\")\n",
"plt.xlabel(\"temperature (K)\")\n",
"plt.ylabel(\"pressure (bar)\")\n",
"plt.gca().invert_yaxis()\n",
"plt.legend()\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"id": "1f3be0d9",
"metadata": {},
"source": [
"## Load a database of atomic lines from VALD3"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "91c057e3",
"metadata": {
"execution": {
"iopub.execute_input": "2022-10-30T01:16:28.800196Z",
"iopub.status.busy": "2022-10-30T01:16:28.798951Z",
"iopub.status.idle": "2022-10-30T01:16:31.935843Z",
"shell.execute_reply": "2022-10-30T01:16:31.935562Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Reading VALD file\n"
]
}
],
"source": [
"#Loading a database of a few atomic lines from VALD3 #BU: CO and CIA (H2-H2)... \n",
"\"\"\"\n",
" path_valdlines: fullpath to the input line list obtained from VALD3 (http://vald.astro.uu.se/):\n",
" VALD data access is free but requires registration through the Contact form (http://vald.astro.uu.se/~vald/php/vald.php?docpage=contact.html). \n",
" After the registration, you can login and select one of the following modes depending on your purpose: \"Extract All\", \"Extract Stellar\", or \"Extract Element\".\n",
" For a example in this notebook, the request form of \"Extract All\" mode was filled as:\n",
" Extract All\n",
" Starting wavelength : 10380\n",
" Ending wavelength : 10430\n",
" Extraction format : Long format\n",
" Retrieve data via : FTP\n",
" (Hyperfine structure: N/A)\n",
" (Require lines to have a known value of : N/A)\n",
" Linelist configuration : Default\n",
" Unit selection: Energy unit: eV - Medium: vacuum - Wavelength unit: angstrom - VdW syntax: default\n",
" Please assign the fullpath of the output file sent by VALD ([user_name_at_VALD].[request_number_at_VALD].gz; \"vald2600.gz\" in the code below) to the variable \"path_valdlines\".\n",
" Note that the number of spectral lines that can be extracted in a single request is limited to 1000 in VALD (https://www.astro.uu.se/valdwiki/Restrictions%20on%20extraction%20size).\n",
"\"\"\"\n",
"\n",
"path_valdlines = '.database/HiroyukiIshikawa.4214450.gz'\n",
"\n",
"import urllib.request\n",
"from exojax.utils.url import url_developer_data\n",
"if not os.path.isdir(path_valdlines.split('/')[0]):\n",
" print(\"Directory '\" + path_valdlines.split('/')[0] + \"' NOT found! This causes below.\")\n",
"if not os.path.isfile(path_valdlines):\n",
" try:\n",
" url = url_developer_data() + path_valdlines.split('/')[-1]\n",
" urllib.request.urlretrieve(url, path_valdlines)\n",
" except:\n",
" print('could not download ', url)\n",
" \n",
"adbFe = moldb.AdbVald(path_valdlines, nu_grid)\n"
]
},
{
"cell_type": "markdown",
"id": "d19c40e3",
"metadata": {},
"source": [
"## Relative partition function"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "8cfac58a",
"metadata": {
"execution": {
"iopub.execute_input": "2022-10-30T01:16:31.939671Z",
"iopub.status.busy": "2022-10-30T01:16:31.939123Z",
"iopub.status.idle": "2022-10-30T01:16:33.434807Z",
"shell.execute_reply": "2022-10-30T01:16:33.435092Z"
}
},
"outputs": [],
"source": [
"#Computing the relative partition function,\n",
"\n",
"qt_284 = vmap(adbFe.QT_interp_284)(Tarr)\n",
"qt = qt_284[:, adbFe.QTmask]\n",
"qr = qt / adbFe.QTref_284[adbFe.QTmask]"
]
},
{
"cell_type": "markdown",
"id": "03211469",
"metadata": {},
"source": [
"## Pressure and Natural broadenings (Lorentzian width) \n"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "dc425d2f",
"metadata": {},
"outputs": [],
"source": [
"# volume mixing ratio (VMR) for e-\n",
"vmre = 10**-7 # assume an arbitrary uniform value here\n",
"\n",
"from exojax.atm.idealgas import number_density\n",
"narr = number_density(Parr, Tarr)\n",
"number_density_e = vmre * narr"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "86b06243",
"metadata": {
"execution": {
"iopub.execute_input": "2022-10-30T01:16:33.471985Z",
"iopub.status.busy": "2022-10-30T01:16:33.441342Z",
"iopub.status.idle": "2022-10-30T01:16:33.636198Z",
"shell.execute_reply": "2022-10-30T01:16:33.635891Z"
}
},
"outputs": [],
"source": [
"gammaLMP = jit(vmap(atomll.gamma_vald3,(0,0,0,0,None,None,None,None,None,None,None,None,None,None,None,0)))\\\n",
" (Tarr, PH, PHH, PHe, adbFe.ielem, adbFe.iion, \\\n",
" adbFe.dev_nu_lines, adbFe.elower, adbFe.eupper, adbFe.atomicmass, adbFe.ionE, \\\n",
" adbFe.gamRad, adbFe.gamSta, adbFe.vdWdamp, 1.0, number_density_e) "
]
},
{
"cell_type": "markdown",
"id": "92d2a9f9",
"metadata": {},
"source": [
"## Doppler broadening"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "cdb9a41f",
"metadata": {
"execution": {
"iopub.execute_input": "2022-10-30T01:16:33.646382Z",
"iopub.status.busy": "2022-10-30T01:16:33.646095Z",
"iopub.status.idle": "2022-10-30T01:16:33.704943Z",
"shell.execute_reply": "2022-10-30T01:16:33.704639Z"
}
},
"outputs": [],
"source": [
"sigmaDM=jit(vmap(doppler_sigma,(None,0,None)))\\\n",
" (adbFe.nu_lines, Tarr, adbFe.atomicmass)"
]
},
{
"cell_type": "markdown",
"id": "040516c5",
"metadata": {},
"source": [
"## Line strength"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "bd733b7d",
"metadata": {
"execution": {
"iopub.execute_input": "2022-10-30T01:16:33.709972Z",
"iopub.status.busy": "2022-10-30T01:16:33.709688Z",
"iopub.status.idle": "2022-10-30T01:16:33.830093Z",
"shell.execute_reply": "2022-10-30T01:16:33.829791Z"
}
},
"outputs": [],
"source": [
"SijM=jit(vmap(line_strength,(0,None,None,None,0,None)))\\\n",
" (Tarr, adbFe.logsij0, adbFe.nu_lines, adbFe.elower, qr, adbFe.Tref)"
]
},
{
"cell_type": "markdown",
"id": "641c7bcd",
"metadata": {},
"source": [
"## nu matrix"
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "be3d3cd3",
"metadata": {
"execution": {
"iopub.execute_input": "2022-10-30T01:16:33.832475Z",
"iopub.status.busy": "2022-10-30T01:16:33.832201Z",
"iopub.status.idle": "2022-10-30T01:16:33.849070Z",
"shell.execute_reply": "2022-10-30T01:16:33.848800Z"
}
},
"outputs": [],
"source": [
"from exojax.spec.initspec import init_lpf\n",
"numatrix=init_lpf(adbFe.nu_lines,nu_grid)"
]
},
{
"cell_type": "markdown",
"id": "ce3d1cff",
"metadata": {},
"source": [
"## Compute dtau for each atomic species (or ion) in a SEPARATE array"
]
},
{
"cell_type": "markdown",
"id": "bd2ebe20",
"metadata": {},
"source": [
"Separate species"
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "5177f919",
"metadata": {
"execution": {
"iopub.execute_input": "2022-10-30T01:16:33.854781Z",
"iopub.status.busy": "2022-10-30T01:16:33.854498Z",
"iopub.status.idle": "2022-10-30T01:16:33.920980Z",
"shell.execute_reply": "2022-10-30T01:16:33.920641Z"
}
},
"outputs": [],
"source": [
"def get_unique_list(seq):\n",
" seen = []\n",
" return [x for x in seq if x not in seen and not seen.append(x)]\n",
"\n",
"uspecies = get_unique_list(jnp.vstack([adbFe.ielem, adbFe.iion]).T.tolist())"
]
},
{
"cell_type": "markdown",
"id": "3b868ff6",
"metadata": {},
"source": [
"Set the stellar/planetary parameters"
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "be8acf41",
"metadata": {
"execution": {
"iopub.execute_input": "2022-10-30T01:16:33.923627Z",
"iopub.status.busy": "2022-10-30T01:16:33.923312Z",
"iopub.status.idle": "2022-10-30T01:16:33.924983Z",
"shell.execute_reply": "2022-10-30T01:16:33.925195Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"logg: 4.849799190511717\n"
]
}
],
"source": [
"#Parameters of Objects\n",
"Rp = 0.36*10 #R_sun*10 #Rp=0.88 #[R_jup]\n",
"Mp = 0.37*1e3 #M_sun*1e3 #Mp=33.2 #[M_jup]\n",
"g = 2478.57730044555*Mp/Rp**2\n",
"print('logg: '+str(np.log10(g))) #check"
]
},
{
"cell_type": "markdown",
"id": "a1da54c7",
"metadata": {},
"source": [
"Calculate delta tau"
]
},
{
"cell_type": "code",
"execution_count": 14,
"id": "fce512a3",
"metadata": {
"execution": {
"iopub.execute_input": "2022-10-30T01:16:33.929460Z",
"iopub.status.busy": "2022-10-30T01:16:33.929158Z",
"iopub.status.idle": "2022-10-30T01:16:41.414238Z",
"shell.execute_reply": "2022-10-30T01:16:41.413913Z"
}
},
"outputs": [],
"source": [
"#For now, ASSUME all atoms exist as neutral atoms.\n",
"#In fact, we can't ignore the effect of molecular formation e.g. TiO (」゜□゜)」\n",
"\n",
"from exojax.spec.lpf import xsmatrix\n",
"from exojax.spec.layeropacity import layer_optical_depth\n",
"from exojax.spec.atomllapi import load_atomicdata\n",
"\n",
"ipccd = load_atomicdata()\n",
"ieleml = jnp.array(ipccd['ielem'])\n",
"Narr = jnp.array(10**(12 + ipccd['solarA'])) #number density\n",
"massarr = jnp.array(ipccd['mass']) #mass of each neutral atom\n",
"Nmassarr = Narr * massarr #mass of each neutral species\n",
"\n",
"dtaual = np.zeros([len(uspecies), len(Tarr), len(nu_grid)])\n",
"maskl = np.zeros(len(uspecies)).tolist()\n",
"\n",
"for i, sp in enumerate(uspecies):\n",
" maskl[i] = (adbFe.ielem==sp[0])\\\n",
" * (adbFe.iion==sp[1])\n",
"\n",
" #Currently not dealing with ionized species yet... (#tako %\\\\\\\\20210814)\n",
" if sp[1] > 1:\n",
" continue\n",
"\n",
" #Providing numatrix, thermal broadening, gamma, and line strength, we can compute cross section.\n",
" xsm = xsmatrix(numatrix[maskl[i]], sigmaDM.T[maskl[i]].T,\n",
" gammaLMP.T[maskl[i]].T, SijM.T[maskl[i]].T)\n",
" #Computing delta tau for atomic absorption\n",
" MMR_X_I = Nmassarr[jnp.where(ieleml == sp[0])[0][0]] / jnp.sum(Nmassarr)\n",
" mass_X_I = massarr[jnp.where(ieleml == sp[0])[0][\n",
" 0]] #MMR and mass of neutral atom X (if all elemental species are neutral)\n",
" dtaual[i] = layer_optical_depth(dParr, xsm, MMR_X_I * np.ones_like(Tarr), mass_X_I, g)\n"
]
},
{
"cell_type": "markdown",
"id": "7490e3bf",
"metadata": {},
"source": [
"compute delta tau for CIA"
]
},
{
"cell_type": "code",
"execution_count": 15,
"id": "7dbcf408",
"metadata": {
"execution": {
"iopub.execute_input": "2022-10-30T01:16:41.417148Z",
"iopub.status.busy": "2022-10-30T01:16:41.416821Z",
"iopub.status.idle": "2022-10-30T01:16:45.911531Z",
"shell.execute_reply": "2022-10-30T01:16:45.911280Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"H2-H2\n"
]
}
],
"source": [
"cdbH2H2=contdb.CdbCIA('.database/H2-H2_2011.cia', nu_grid)\n",
"\n",
"from exojax.spec.layeropacity import layer_optical_depth_CIA\n",
"mmw=2.33 #mean molecular weight\n",
"mmrH2=0.74\n",
"molmassH2=molinfo.molmass(\"H2\")\n",
"vmrH2=(mmrH2*mmw/molmassH2) #VMR\n",
"dtaucH2H2=layer_optical_depth_CIA(nu_grid,Tarr,Parr,dParr,vmrH2,vmrH2,\\\n",
" mmw,g,cdbH2H2.nucia,cdbH2H2.tcia,cdbH2H2.logac)"
]
},
{
"cell_type": "markdown",
"id": "f92626f5",
"metadata": {},
"source": [
"## Total delta tau"
]
},
{
"cell_type": "code",
"execution_count": 16,
"id": "3a2a5ae0",
"metadata": {
"execution": {
"iopub.execute_input": "2022-10-30T01:16:45.913765Z",
"iopub.status.busy": "2022-10-30T01:16:45.913412Z",
"iopub.status.idle": "2022-10-30T01:16:45.960951Z",
"shell.execute_reply": "2022-10-30T01:16:45.960688Z"
}
},
"outputs": [],
"source": [
"dtau = np.sum(dtaual, axis=0) + dtaucH2H2"
]
},
{
"cell_type": "markdown",
"id": "db3cb7c7",
"metadata": {},
"source": [
"## Plot contribution function"
]
},
{
"cell_type": "code",
"execution_count": 17,
"id": "b91e4c66",
"metadata": {
"execution": {
"iopub.execute_input": "2022-10-30T01:16:45.982047Z",
"iopub.status.busy": "2022-10-30T01:16:45.963286Z",
"iopub.status.idle": "2022-10-30T01:16:46.767987Z",
"shell.execute_reply": "2022-10-30T01:16:46.767695Z"
}
},
"outputs": [
{
"data": {
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"text/plain": [
"<Figure size 2000x300 with 3 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"from exojax.plot.atmplot import plotcf\n",
"plotcf(nu_grid, dtau, Tarr, Parr, dParr)\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"id": "125f5be0",
"metadata": {},
"source": [
"## Radiative transfer"
]
},
{
"cell_type": "code",
"execution_count": 18,
"id": "c99e5b61",
"metadata": {
"execution": {
"iopub.execute_input": "2022-10-30T01:16:47.115956Z",
"iopub.status.busy": "2022-10-30T01:16:47.115143Z",
"iopub.status.idle": "2022-10-30T01:16:47.235753Z",
"shell.execute_reply": "2022-10-30T01:16:47.235505Z"
}
},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 500x300 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"F0 = art.run(dtau, Tarr)\n",
"\n",
"fig=plt.figure(figsize=(5, 3))\n",
"plt.plot(wav[::-1], F0)\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 19,
"id": "2af5bcd5",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 32 38 39 59 60 64\n",
" 65 66 70 80 90]\n"
]
}
],
"source": [
"#Check line species\n",
"print(np.unique(adbFe.ielem))"
]
},
{
"cell_type": "markdown",
"id": "0978b630",
"metadata": {},
"source": [
"## Rotational & instrumental broadening"
]
},
{
"cell_type": "code",
"execution_count": 20,
"id": "ca7cc545",
"metadata": {
"execution": {
"iopub.execute_input": "2022-10-30T01:16:47.243326Z",
"iopub.status.busy": "2022-10-30T01:16:47.243001Z",
"iopub.status.idle": "2022-10-30T01:16:48.550901Z",
"shell.execute_reply": "2022-10-30T01:16:48.550586Z"
}
},
"outputs": [],
"source": [
"from exojax.spec.response import ipgauss_sampling\n",
"from exojax.spec.spin_rotation import convolve_rigid_rotation\n",
"from exojax.utils.constants import c #[km/s]\n",
"import jax.numpy as jnp\n",
"\n",
"wavd = jnp.linspace(10380, 10430,500) #observational wavelength grid\n",
"nu_grid_d = 1.e8/wavd[::-1]\n",
"\n",
"RV = 10.0 #RV km/s\n",
"vsini = 20.0 #Vsini km/s\n",
"vsini_max = 100.0\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",
"from exojax.utils.grids import velocity_grid\n",
"vr_array = velocity_grid(res, vsini_max)\n",
"\n",
"Frot = convolve_rigid_rotation(F0, vr_array, vsini, u1, u2)\n",
"F = ipgauss_sampling(nu_grid_d, nu_grid, Frot, beta, RV, varr_kernel=vr_array)"
]
},
{
"cell_type": "code",
"execution_count": 21,
"id": "f297c399",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 500x300 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"fig=plt.figure(figsize=(5, 3))\n",
"plt.plot(wav[::-1],F0, label='F0')\n",
"plt.plot(wavd[::-1],F, label='F')\n",
"plt.legend()\n",
"plt.show()"
]
}
],
"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": "3.9.1"
},
"vscode": {
"interpreter": {
"hash": "72bc7f8b1808a6f5ada3c6a20601509b8b1843160436d276d47f2ba819b3753b"
}
}
},
"nbformat": 4,
"nbformat_minor": 5
}