{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "# NBVAL_SKIP\n", "import os\n", "os.environ['SPS_HOME'] = '/home/annalena_data/sps_fsps'" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Dust extinction models in RUBIX\n", "\n", "This notebook shows the basics of the dust extinction models implemented in Rubix. We have closely followed the implementation by the [dust extinction package](https://dust-extinction.readthedocs.io/en/latest/index.html). Currently we only support a subset of all available models, namely the Cardelli, Clayton, & Mathis (1989) Milky Way R(V) dependent model, the Gordon et al. (2023) Milky Way R(V) dependent model and the Fitzpatrick & Massa (1990) 6 parameter ultraviolet shape model.\n", "\n", "We will demonstrate how to use these models to calculate and visualize the effects of dust extinction on stellar spectra. Additionally, we will show how to integrate these models into a Rubix pipeline to simulate the impact of dust on galaxy observations." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "First, we import the dust models from Rubix." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "# NBVAL_SKIP\n", "from rubix.spectra.dust.extinction_models import Cardelli89, Gordon23" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "# NBVAL_SKIP\n", "import matplotlib.pyplot as plt\n", "import numpy as np\n", "import jax.numpy as jnp" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We visulaize some of the aspects of the models, i.e. their A(x)/Av as a function of wavelength." ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# NBVAL_SKIP\n", "fig, ax = plt.subplots()\n", "\n", "# generate the curves and plot them\n", "x = np.arange(0.5,10.0,0.1) # in 1/microns\n", "Rvs = [2.0,3.0,4.0,5.0,6.0]\n", "for cur_Rv in Rvs:\n", " ext_model = Cardelli89(Rv=cur_Rv)\n", " ax.plot(x,ext_model(x),label='R(V) = ' + str(cur_Rv))\n", "\n", "ax.set_xlabel(r'$x$ [$\\mu m^{-1}$]')\n", "ax.set_ylabel(r'$A(x)/A(V)$')\n", "\n", "# for 2nd x-axis with lambda values\n", "axis_xs = np.array([0.1, 0.12, 0.15, 0.2, 0.3, 0.5, 1.0])\n", "new_ticks = 1 / axis_xs\n", "new_ticks_labels = [\"%.2f\" % z for z in axis_xs]\n", "tax = ax.twiny()\n", "tax.set_xlim(ax.get_xlim())\n", "tax.set_xticks(new_ticks)\n", "tax.set_xticklabels(new_ticks_labels)\n", "tax.set_xlabel(r\"$\\lambda$ [$\\mu$m]\")\n", "\n", "ax.legend(loc='best')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can now also use those models and show their effects on a black body spectrum. \n", "For that, we instantiate the Cardelli model, create a black body spectrum with astropy and apply the dust extinction with a fiducial Rv of 3.1 to the spectrum for a range of Av parameters. " ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "# NBVAL_SKIP\n", "# Let's import some packages\n", "from astropy.modeling.models import BlackBody\n", "import astropy.units as u\n", "from matplotlib.ticker import ScalarFormatter" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": [ "# NBVAL_SKIP\n", "# initialize cardelli model with Rv=3.1\n", "ext = Cardelli89(Rv=3.1)" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [], "source": [ "# NBVAL_SKIP\n", "# generate wavelengths between 3 and 10 microns\n", "# within the valid range for the Cardelli R(V) dependent model\n", "lam = np.logspace(np.log10(3), np.log10(10.0), num=1000)\n", "\n", "# setup the inputs for the blackbody function\n", "wavelengths = lam*1e4 # Angstroem\n", "temperature = 10000 # Kelvin" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [], "source": [ "# NBVAL_SKIP\n", "# get the blackbody flux\n", "bb_lam = BlackBody(10000*u.K, scale=1.0 * u.erg / (u.cm ** 2 * u.AA * u.s * u.sr))\n", "flux = bb_lam(wavelengths)" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [], "source": [ "# NBVAL_SKIP\n", "# get the extinguished blackbody flux for different amounts of dust\n", "flux_ext_av05 = flux*ext.extinguish(lam, Av=0.5)\n", "flux_ext_av15 = flux*ext.extinguish(lam, Av=1.5)\n", "flux_ext_ebv10 = flux*ext.extinguish(lam, Ebv=1.0)" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "<>:10: SyntaxWarning: invalid escape sequence '\\l'\n", "<>:10: SyntaxWarning: invalid escape sequence '\\l'\n", "/tmp/ipykernel_1807103/1777885020.py:10: SyntaxWarning: invalid escape sequence '\\l'\n", " ax.set_xlabel('$\\lambda$ [$\\AA$]')\n" ] }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# NBVAL_SKIP\n", "# plot the intrinsic and extinguished fluxes\n", "fig, ax = plt.subplots()\n", "\n", "ax.plot(wavelengths, flux, label='Intrinsic')\n", "ax.plot(wavelengths, flux_ext_av05, label='$A(V) = 0.5$')\n", "ax.plot(wavelengths, flux_ext_av15, label='$A(V) = 1.5$')\n", "ax.plot(wavelengths, flux_ext_ebv10, label='$E(B-V) = 1.0$')\n", "\n", "ax.set_xlabel('$\\lambda$ [$\\AA$]')\n", "ax.set_ylabel('$Flux$')\n", "\n", "ax.set_xscale('log')\n", "ax.xaxis.set_major_formatter(ScalarFormatter())\n", "ax.set_yscale('log')\n", "\n", "ax.set_title('Example extinguishing a blackbody')\n", "\n", "ax.legend(loc='best')\n", "plt.tight_layout()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We see that the Cardelli model has some limited range in wavelength. \n", "Now let's try the same for the Gordon et al. model which has a broader wavelength support. " ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# NBVAL_SKIP\n", "# generate wavelengths between 0.092 and 31 microns\n", "# within the valid range for the Gordon23 R(V) dependent relationship\n", "lam = jnp.logspace(np.log10(0.092), np.log10(31.0), num=1000)\n", "\n", "# setup the inputs for the blackbody function\n", "wavelengths = lam*1e4 # Angstroem\n", "temperature = 10000 # Kelvin\n", "\n", "# get the blackbody flux\n", "bb_lam = BlackBody(10000*u.K, scale=1.0 * u.erg / (u.cm ** 2 * u.AA * u.s * u.sr))\n", "flux = bb_lam(wavelengths)\n", "\n", "# initialize the model\n", "ext = Gordon23(Rv=3.1)\n", "\n", "# get the extinguished blackbody flux for different amounts of dust\n", "flux_ext_av05 = flux*ext.extinguish(lam, Av=0.5)\n", "flux_ext_av15 = flux*ext.extinguish(lam, Av=1.5)\n", "flux_ext_ebv10 = flux*ext.extinguish(lam, Ebv=1.0)\n", "\n", "# plot the intrinsic and extinguished fluxes\n", "fig, ax = plt.subplots()\n", "\n", "ax.plot(wavelengths, flux, label='Intrinsic')\n", "ax.plot(wavelengths, flux_ext_av05, label='$A(V) = 0.5$')\n", "ax.plot(wavelengths, flux_ext_av15, label='$A(V) = 1.5$')\n", "ax.plot(wavelengths, flux_ext_ebv10, label='$E(B-V) = 1.0$')\n", "\n", "ax.set_xlabel(r'$\\lambda$ [$\\AA$]')\n", "ax.set_ylabel('$Flux$')\n", "\n", "ax.set_xscale('log')\n", "ax.xaxis.set_major_formatter(ScalarFormatter())\n", "ax.set_yscale('log')\n", "\n", "ax.set_title('Example extinguishing a blackbody')\n", "\n", "ax.legend(loc='best')\n", "plt.tight_layout()\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We see, as expected, the impact of dust is most important for short wavelength, i.e. the blue part of the spectrum." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Run the RUBIX pipeline with dust\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We now turn to running the RUBIX pipeline with dust included. For this, we first need to setup the config accordingly. That is as easy as replacing `\"pipeline\":{\"name\": \"calc_ifu\"}` with `\"pipeline\":{\"name\": \"calc_dusty_ifu\"}` in the config.\n", "\n", "In order to comapre a dusty and non dusty IFU cube, we first run a normal RUBIX pipeline." ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [], "source": [ "#import os\n", "#os.environ[\"SPS_HOME\"] = '/Users/buck/Documents/Nexus/codes/fsps'\n", "#ILLUSTRIS_API_KEY = 'c0112e1fa11489ef0e6164480643d1c8'" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "2025-07-01 11:50:32,236 - rubix - INFO - \n", " ___ __ _____ _____ __\n", " / _ \\/ / / / _ )/ _/ |/_/\n", " / , _/ /_/ / _ |/ /_> <\n", "/_/|_|\\____/____/___/_/|_|\n", "\n", "\n", "2025-07-01 11:50:32,236 - rubix - INFO - Rubix version: 0.0.post467+g61e4558.d20250616\n", "2025-07-01 11:50:32,237 - rubix - INFO - JAX version: 0.6.0\n", "2025-07-01 11:50:32,237 - rubix - INFO - Running on [CpuDevice(id=0)] devices\n" ] } ], "source": [ "#NBVAL_SKIP\n", "\n", "import matplotlib.pyplot as plt\n", "from rubix.core.pipeline import RubixPipeline \n", "import os\n", "config = {\n", " \"pipeline\":{\"name\": \"calc_ifu_memory\"},\n", " \n", " \"logger\": {\n", " \"log_level\": \"DEBUG\",\n", " \"log_file_path\": None,\n", " \"format\": \"%(asctime)s - %(name)s - %(levelname)s - %(message)s\",\n", " },\n", " \"data\": {\n", " \"name\": \"IllustrisAPI\",\n", " \"args\": {\n", " \"api_key\": os.environ.get(\"ILLUSTRIS_API_KEY\"),\n", " \"particle_type\": [\"stars\", \"gas\"],\n", " \"simulation\": \"TNG50-1\",\n", " \"snapshot\": 99,\n", " \"save_data_path\": \"data\",\n", " },\n", " \n", " \"load_galaxy_args\": {\n", " \"id\": 11,\n", " \"reuse\": False,\n", " },\n", " \n", " \"subset\": {\n", " \"use_subset\": True,\n", " \"subset_size\": 50000,\n", " },\n", " },\n", " \"simulation\": {\n", " \"name\": \"IllustrisTNG\",\n", " \"args\": {\n", " \"path\": \"data/galaxy-id-11.hdf5\",\n", " },\n", " \n", " },\n", " \"output_path\": \"output\",\n", "\n", " \"telescope\":\n", " {\"name\": \"MUSE\",\n", " \"psf\": {\"name\": \"gaussian\", \"size\": 5, \"sigma\": 0.6},\n", " \"lsf\": {\"sigma\": 0.5},\n", " \"noise\": {\"signal_to_noise\": 1,\"noise_distribution\": \"normal\"},},\n", " \"cosmology\":\n", " {\"name\": \"PLANCK15\"},\n", " \n", " \"galaxy\":\n", " {\"dist_z\": 0.1,\n", " \"rotation\": {\"type\": \"edge-on\"},\n", " },\n", " \n", " \"ssp\": {\n", " \"template\": {\n", " \"name\": \"BruzualCharlot2003\"\n", " },\n", " \"dust\": {\n", " \"extinction_model\": \"Cardelli89\", #\"Gordon23\", \n", " \"dust_to_gas_ratio\": 0.01, # need to check Remyer's paper\n", " \"dust_to_metals_ratio\": 0.4, # do we need this ratio if we set the dust_to_gas_ratio?\n", " \"dust_grain_density\": 3.5, # g/cm^3 #check this value\n", " \"Rv\": 3.1,\n", " },\n", " }, \n", "}" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/home/annalena/.conda/envs/rubix/lib/python3.12/site-packages/rubix/telescope/factory.py:26: UserWarning: No telescope config provided, using default stored in /home/annalena/.conda/envs/rubix/lib/python3.12/site-packages/rubix/telescope/telescopes.yaml\n", " warnings.warn(\n" ] }, { "ename": "TypeError", "evalue": "RubixPipeline.run() missing 1 required positional argument: 'inputdata'", "output_type": "error", "traceback": [ "\u001b[31m---------------------------------------------------------------------------\u001b[39m", "\u001b[31mTypeError\u001b[39m Traceback (most recent call last)", "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[14]\u001b[39m\u001b[32m, line 4\u001b[39m\n\u001b[32m 1\u001b[39m \u001b[38;5;66;03m#NBVAL_SKIP\u001b[39;00m\n\u001b[32m 2\u001b[39m pipe = RubixPipeline(config)\n\u001b[32m----> \u001b[39m\u001b[32m4\u001b[39m rubixdata = \u001b[43mpipe\u001b[49m\u001b[43m.\u001b[49m\u001b[43mrun\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n", "\u001b[31mTypeError\u001b[39m: RubixPipeline.run() missing 1 required positional argument: 'inputdata'" ] } ], "source": [ "#NBVAL_SKIP\n", "pipe = RubixPipeline(config)\n", "\n", "inputdata = pipe.prepare_data()\n", "rubixdata = pipe.run_sharded(inputdata)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now we run the pipeline including the effects of dust.\n", "\n", "Next to setting `\"pipeline\":{\"name\": \"calc_ifu\"}` there are some more nobs under the section `ssp` for `dust` that we can tweek if needed.\n", "\n", "Options to consider are as follows:\n", "* the exact \"extinction_model\" to use. Currently Rubix supports \"Cardelli89\" or \"Gordon23\" \n", "* the \"dust_to_gas_model\" to use. This currently refers to the fitting formula used by Remy-Ruyer et al. 2014. See their Table 1 for more info.\n", "* the \"Xco\" model used by Remy-Ruyer et al 2014. Either \"Z\" or \"MW\"\n", "* the \"dust_grain_density\" which depends on the type of dust at hand, see e.g. the NIST tables.\n", "* the \"Rv\" value in case one uses an Rv dependent dust model." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "#NBVAL_SKIP\n", "\n", "import matplotlib.pyplot as plt\n", "from rubix.core.pipeline import RubixPipeline \n", "import os\n", "config = {\n", " \"pipeline\":{\"name\": \"calc_dusty_ifu_memory\"},\n", " \n", " \"logger\": {\n", " \"log_level\": \"DEBUG\",\n", " \"log_file_path\": None,\n", " \"format\": \"%(asctime)s - %(name)s - %(levelname)s - %(message)s\",\n", " },\n", " \"data\": {\n", " \"name\": \"IllustrisAPI\",\n", " \"args\": {\n", " \"api_key\": os.environ.get(\"ILLUSTRIS_API_KEY\"),\n", " \"particle_type\": [\"stars\", \"gas\"],\n", " \"simulation\": \"TNG50-1\",\n", " \"snapshot\": 99,\n", " \"save_data_path\": \"data\",\n", " },\n", " \n", " \"load_galaxy_args\": {\n", " \"id\": 11,\n", " \"reuse\": True,\n", " },\n", " \n", " \"subset\": {\n", " \"use_subset\": True,\n", " \"subset_size\": 50000,\n", " },\n", " },\n", " \"simulation\": {\n", " \"name\": \"IllustrisTNG\",\n", " \"args\": {\n", " \"path\": \"data/galaxy-id-11.hdf5\",\n", " },\n", " \n", " },\n", " \"output_path\": \"output\",\n", "\n", " \"telescope\":\n", " {\"name\": \"MUSE\",\n", " \"psf\": {\"name\": \"gaussian\", \"size\": 5, \"sigma\": 0.6},\n", " \"lsf\": {\"sigma\": 0.5},\n", " \"noise\": {\"signal_to_noise\": 1,\"noise_distribution\": \"normal\"},},\n", " \"cosmology\":\n", " {\"name\": \"PLANCK15\"},\n", " \n", " \"galaxy\":\n", " {\"dist_z\": 0.1,\n", " \"rotation\": {\"type\": \"edge-on\"},\n", " },\n", " \n", " \"ssp\": {\n", " \"template\": {\n", " \"name\": \"BruzualCharlot2003\"\n", " },\n", " \"dust\": {\n", " \"extinction_model\": \"Cardelli89\", #\"Gordon23\", \n", " \"dust_to_gas_model\": \"broken power law fit\", # from Remyer's paper see their Table 1\n", " \"Xco\": \"Z\", # from Remyer's paper, see their Table 1\n", " \"dust_grain_density\": 3.0, # #check this value, reverse engeneered from Ibarrra-Medel 2018\n", " \"Rv\": 3.1,\n", " },\n", " }, \n", "}" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "#NBVAL_SKIP\n", "pipe = RubixPipeline(config)\n", "\n", "inputdata = pipe.prepare_data()\n", "rubixdata_dust = pipe.run_sharded(inputdata)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Let's compare one example spaxel spectrum with and without dust." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "#NBVAL_SKIP\n", "wave = pipe.telescope.wave_seq\n", "\n", "spectra = rubixdata # Spectra of all stars\n", "dusty_spectra = rubixdata_dust # Spectra of all stars\n", "print(spectra.shape)\n", "print(dusty_spectra.shape)\n", "\n", "plt.plot(wave, spectra[12,12,:])\n", "plt.plot(wave, dusty_spectra[12,12,:])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Now let's visualize a nice edge-on galaxy in SDSS broad-band images with some nice dust lanes... " ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# NBVAL_SKIP\n", "from rubix.telescope.filters import load_filter, convolve_filter_with_spectra" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# NBVAL_SKIP\n", "# load all fliter curves for SLOAN\n", "curves = load_filter(\"SLOAN\")" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# NBVAL_SKIP\n", "wave = pipe.telescope.wave_seq\n", "filters,images = curves.apply_filter_curves(rubixdata_dust, wave).values()\n", "\n", "for i_dust,name in zip(images, filters):\n", " plt.figure()\n", " plt.imshow(i_dust)\n", " plt.colorbar()\n", " plt.title(name)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Sanity check: overlay gas column density map over the dusty emission image" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# NBVAL_SKIP\n", "idx = np.where(inputdata.gas.mass != 0)\n", "gas_map = np.histogram2d(inputdata.gas.coords[:,0][idx], inputdata.gas.coords[:,1][idx], bins=(25,25), weights=np.squeeze(inputdata.gas.mass)[idx])" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# NBVAL_SKIP\n", "plt.figure()\n", "plt.imshow(gas_map[0].T, cmap='inferno')\n", "plt.colorbar()\n", "plt.title(\"gas map\")" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# NBVAL_SKIP\n", "plt.figure()\n", "plt.imshow(i)\n", "plt.imshow(gas_map[0].T, cmap='inferno', alpha=0.6)\n", "plt.colorbar()\n", "plt.title(\"emission and gas map overlayed\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# And in comparison to this, the same galaxy without dust..." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# NBVAL_SKIP\n", "wave = pipe.telescope.wave_seq\n", "filters,images = curves.apply_filter_curves(rubixdata, wave).values()\n", "\n", "for i,name in zip(images, filters):\n", " plt.figure()\n", " plt.imshow(i)\n", " plt.colorbar()\n", " plt.title(name)" ] } ], "metadata": { "kernelspec": { "display_name": "rubix", "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": "3.11.11" } }, "nbformat": 4, "nbformat_minor": 2 }