{ "cells": [ { "cell_type": "markdown", "id": "40960888", "metadata": {}, "source": [ "# Generating model spectra\n", "\n", "Spectuner implements the one-dimensional LTE spectral model, which is introduced in the [user guide](../guide/sl_model.rst). As a basic functionality, this tutorial demonstrates how to generate model spectra.\n", "\n", "Set ``fname_db`` below to the path of the CDMS database file." ] }, { "cell_type": "code", "execution_count": 1, "id": "0710947a", "metadata": {}, "outputs": [], "source": [ "import numpy as np\n", "import matplotlib.pyplot as plt\n", "import spectuner\n", "\n", "fname_db = \"path/to/the/cdms/database \"" ] }, { "cell_type": "markdown", "id": "faa28a9b", "metadata": {}, "source": [ "## Generating model spectra of one molecule\n", "\n", "To gnerate model spectra, we need to specify the frequency range and the beam size of the observation. The latter is used to compute the beam filling factor. After the configuration, we should create a [SpectralLineModelFactory](../api/slm_factory.rst#spectuner.slm_factory.SpectralLineModelFactory) instance, which is the primary interface to create callable objects for generating model spectra. " ] }, { "cell_type": "code", "execution_count": 2, "id": "4c3fa16b", "metadata": {}, "outputs": [], "source": [ "config = spectuner.load_default_config()\n", "\n", "config.set_fname_db(fname_db)\n", "\n", "freq = np.linspace(220200., 220850, 10000) # MHz\n", "beam_info = (1./3600, 1./3600) # deg\n", "config.append_spectral_window_simple(freq, beam_info)\n", "\n", "slm_factory = spectuner.SpectralLineModelFactory(config)" ] }, { "cell_type": "markdown", "id": "5d72bbc5", "metadata": {}, "source": [ "The next step is to specify the molecule of the spectral line model and then create the callable." ] }, { "cell_type": "code", "execution_count": 3, "id": "6f4f66d7", "metadata": {}, "outputs": [], "source": [ "specie_list = spectuner.create_specie_list(\"CH3CN;v=0;\")\n", "sl_model = slm_factory.create_sl_model(config[\"obs_info\"], specie_list)" ] }, { "cell_type": "markdown", "id": "f2ad6312", "metadata": {}, "source": [ "As described in the [user guide](../guide/sl_model.rst), the spectral line model has five parameters. By default, they should be in the following order and units:\n", "\n", "- ``theta``: Source size in arcsec.\n", "- ``T_ex``: Excitation temperature in K.\n", "- ``N_tot``: Column density in cm^-2. This parameter is in log scale by default.\n", "- ``delta_v``: Velocity width in km/s.\n", "- ``v_offset``: Velocity offset in km/s.\n", "\n", "As an example, ``params`` below means ``(theta = 1.0 arcsec, T_ex = 100 K, N_tot = 10^16 cm^-2, delta_v = 5 km/s, v_offset =-1 km/s)``.\n", "\n", "Since we often work with multiple spectral windows, ``sl_model`` returns a list, with each element being the spectrum of a spectral window." ] }, { "cell_type": "code", "execution_count": 4, "id": "d6c51bc2", "metadata": {}, "outputs": [], "source": [ "params = np.array([1., 100., 16., 5., -1.])\n", "T_pred_data = sl_model(params)" ] }, { "cell_type": "code", "execution_count": 5, "id": "bef84a07", "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig, ax = plt.subplots(figsize=(8, 4))\n", "\n", "ax.plot(freq, T_pred_data[0])\n", "\n", "ax.set_ylabel(\"Intensity [K]\")\n", "ax.set_xlabel(\"Frequency [MHz]\");" ] }, { "cell_type": "markdown", "id": "406b2fe1", "metadata": {}, "source": [ "## Generating model spectra of multiple molecules with shared parameters\n", "\n", "Spectuner allows to compute spectra of multiple molecules with shared parameters. We may use [set_param_info](../api/config.rst#spectuner.config.Config.set_param_info) to specify the shared parameters. The code block below gives an example of computing spectra of CH3CN and C2H5CN with a shared velocity offset. In addition, the model sums the spectra of all molecules linearly." ] }, { "cell_type": "code", "execution_count": 6, "id": "3de08fba", "metadata": {}, "outputs": [], "source": [ "config = spectuner.load_default_config()\n", "\n", "config.set_fname_db(fname_db)\n", "\n", "freq = np.linspace(220200., 220850, 10000) # MHz\n", "beam_info = (1./3600, 1./3600) # deg\n", "config.append_spectral_window_simple(freq, beam_info)\n", "\n", "# Set shared parameters\n", "config.set_param_info(\"v_offset\", is_log=False, is_shared=True)\n", "\n", "slm_factory = spectuner.SpectralLineModelFactory(config)\n", "\n", "specie_list = spectuner.create_specie_list([\"CH3CN;v=0;\", \"C2H5CN;v=0;\"])\n", "sl_model = slm_factory.create_sl_model(config[\"obs_info\"], specie_list)" ] }, { "cell_type": "markdown", "id": "6e66d189", "metadata": {}, "source": [ "The shared parameters should be given before the independent parameters. As an example, ``params`` below indicates:\n", "\n", "- ``(theta = 1.0 arcsec, T_ex = 100 K, N_tot = 10^16 cm^-2, delta_v = 5 km/s, v_offset =-1 km/s)`` for ``CH3CN;v=0;``.\n", "- ``(theta = 1.0 arcsec, T_ex = 300 K, N_tot = 10^17 cm^-2, delta_v = 4 km/s, v_offset =-1 km/s)`` for ``C2H5CN;v=0;``." ] }, { "cell_type": "code", "execution_count": 7, "id": "17409f47", "metadata": {}, "outputs": [], "source": [ "params = np.array([-1., 1., 1., 100, 300, 16, 17, 5., 4.])\n", "T_pred_data = sl_model(params)\n", "T_dict = sl_model.compute_individual_spectra(params)" ] }, { "cell_type": "code", "execution_count": 8, "id": "8214a069", "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig, ax = plt.subplots(figsize=(12, 4))\n", "\n", "for key, T_data in T_dict.items():\n", " ax.plot(freq, T_data[0], label=key)\n", "ax.plot(freq, T_pred_data[0], \"k--\", label=\"total\")\n", "\n", "ax.legend(frameon=False, loc=\"upper left\")\n", "\n", "ax.set_ylabel(\"Intensity [K]\")\n", "ax.set_xlabel(\"Frequency [MHz]\");" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "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": "3.10.9" } }, "nbformat": 4, "nbformat_minor": 5 }