{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "## MESA dataset processing example\n", "\n", "We will need `NumPy` for array processing, `MatPlotLib` for plots and the `operator` is required for my method of sorting multidimensional arrays." ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [], "source": [ "import numpy as np\n", "import matplotlib.pyplot as plt\n", "import operator\n", "\n", "%matplotlib inline" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Solar luminosity to present luminosity-temperature diagrams in their conventional form. The dataset itself stores luminosities in SI." ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [], "source": [ "solar_lum = 3.826e26 # SI [W]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "A helper function to obtain isochrones for any physical parameters from the dataset. The function performs linear interpolation to obtain ages that are not directly available. If an age outside of the range is requested, a warning will be shown." ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [], "source": [ "def get_isochrone(mass_all, age_all, age, dependent):\n", " \"\"\"\n", " Generate an isochrone for a MESA grid as a function of mass. All values of MESA masses,\n", " ages and dependent variables (e.g. temperature, luminosity and the like) are expected in\n", " \"mass_all\", \"age_all\" and \"dependent\". \"dependent\" is a list of NumPy arrays. Every NumPy array in\n", " \"dependent\" as well as \"mass_all\" and \"age_all\" must have the same dimension.\n", " \"age\" is the age of the required isochrone.\n", " Returns a list of NumPy arrays, where the zeroth entry is the independent variable (mass) and\n", " every subsequent element is dependent variables in the same order as they are provided in \"dependent\".\n", " \"\"\"\n", " mass_unique = sorted(list(set(mass_all)))\n", " output = np.zeros([len(dependent), len(mass_unique)])\n", " for i, mass in enumerate(mass_unique):\n", " for j, quantity in enumerate(output):\n", " L = sorted(zip(age_all[mass_all == mass], dependent[j][mass_all == mass]), key = operator.itemgetter(0))\n", " L = np.array(zip(*L))\n", " if age > max(L[0]) or age < min(L[0]):\n", " warnings.warn(\"The age requested is outside of the grid ({},{},{})\".format(min(L[0]), age, max(L[0])))\n", " output[j, i] = np.interp(age, *L)\n", " return [mass_unique] + list(output)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Load the dataset using standard `NumPy` file operations." ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [], "source": [ "filename = 'mesa/omega_cen_regular.dat' # Point this to your MESA datafile\n", "\n", "# Load the data\n", "mesa_r, mesa_t, mesa_l, mesa_a, mesa_m = np.loadtxt(filename, unpack = True, delimiter = ',')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Use `MatPlotLib` to plot a few isochrones." ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(-0.5, 0.6)" ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "isochrones = np.linspace(1.0e9, 13.5e9, 10)\n", "for index, isochrone in enumerate(isochrones):\n", " iso_m, iso_t, iso_l = get_isochrone(mesa_m, mesa_a, isochrone, [mesa_t, mesa_l])\n", " plt.plot(iso_t, np.log10(iso_l / solar_lum), '-', ms = 3, label = '$' + str(int(isochrone / 1e8)/10.0) + '\\ \\mathrm{GYr}$')\n", "plt.xlabel('Temperature [$\\mathrm{K}$]')\n", "plt.ylabel('Luminosity [$\\log(L/L_{\\odot})$]')\n", "plt.grid()\n", "plt.gca().invert_xaxis()\n", "plt.legend(fontsize = 8)\n", "plt.xlim(6600, 6000)\n", "plt.ylim(-0.5, 0.6)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Plot evolutionary tracks." ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 15, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "mass_unique = sorted(list(set(mesa_m)))\n", "for mass in mass_unique[::10]:\n", " plt.plot(mesa_t[mass == mesa_m], np.log10(mesa_l[mass == mesa_m] / solar_lum), '-', label = '$' + str(mass) + 'M_{\\odot}$')\n", "plt.xlabel('Temperature [$\\mathrm{K}$]')\n", "plt.ylabel('Luminosity [$\\log(L/L_{\\odot})$]')\n", "plt.grid()\n", "plt.gca().invert_xaxis()\n", "plt.legend(fontsize = 8)" ] } ], "metadata": { "kernelspec": { "display_name": "Python 2", "language": "python", "name": "python2" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 2 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython2", "version": "2.7.10" } }, "nbformat": 4, "nbformat_minor": 2 }