add Paper_v2.0/paper_formating.py

examples/Paper_v2.0/fig_2halo_miscentering_boost_theory.ipynb

@@ -0,0 +1,204 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Figure to show the new 2-halo term and miscentering functionality"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "%matplotlib inline"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Imports specific to clmm "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import os\n",
+    "\n",
+    "os.environ[\n",
+    "    \"CLMM_MODELING_BACKEND\"\n",
+    "] = \"ccl\"  # here you may choose ccl, nc (NumCosmo) or ct (cluster_toolkit)\n",
+    "\n",
+    "import clmm\n",
+    "from clmm import Cosmology\n",
+    "import clmm.utils as u"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Make sure we know which version we're using"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "clmm.__version__"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Define a cosmology using astropy"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "cosmo = Cosmology(H0=67.0, Omega_dm0=0.315 - 0.045, Omega_b0=0.045, Omega_k0=0.0)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Define the galaxy cluster model.  Here, we choose parameters that describe the galaxy cluster model, including the mass definition, concentration, and mass distribution.  For the mass distribution, we choose a distribution that follows an NFW profile."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "moo = clmm.Modeling(massdef=\"mean\", delta_mdef=200, halo_profile_model=\"nfw\")\n",
+    "\n",
+    "mass_cl = 1.e14\n",
+    "z_cl = 0.4\n",
+    "\n",
+    "conc_cl = 5.4# Duffy08 value for this halo mass and redshift (see last commented cell)\n",
+    "halo_bias = 2.4 # Tkinker10 value for this halo mass and redshift (see last commented cell)\n",
+    "\n",
+    "moo.set_cosmo(cosmo)\n",
+    "moo.set_concentration(conc_cl)\n",
+    "moo.set_mass(mass_cl)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "r_proj = np.logspace(-2, 2, 100)\n",
+    "\n",
+    "DeltaSigma = moo.eval_excess_surface_density(r_proj, z_cl)\n",
+    "\n",
+    "# Miscentered DeltaSigma\n",
+    "DeltaSigma_mis = moo.eval_excess_surface_density(r_proj, z_cl, r_mis=0.2)\n",
+    "\n",
+    "# 2halo DeltaSigma\n",
+    "DeltaSigma_2h = moo.eval_excess_surface_density_2h(r_proj, z_cl, halobias=6)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "r_scale = 0.3\n",
+    "nfw_boost = u.compute_nfw_boost(r_proj, r_scale, boost0=0.2)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Plot the predicted profiles"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "fig, ax = plt.subplots(nrows=1, ncols=1, figsize=(7,6))\n",
+    "\n",
+    "ax.loglog(r_proj, DeltaSigma,label='1-halo, centered, reference', color='k')\n",
+    "ax.loglog(r_proj, DeltaSigma/nfw_boost, ls=':', label='1-halo, corrected with NFW boost model', color='grey')\n",
+    "ax.loglog(r_proj, DeltaSigma_mis , ls ='--', label='1-halo, miscentered, R_mis = 0.2 Mpc')\n",
+    "ax.loglog(r_proj, DeltaSigma_2h, ls='dashdot', label='2-halo', color='green')\n",
+    "ax.legend(loc=1, fontsize=13)\n",
+    "\n",
+    "ax.set_xlabel('R [Mpc]', fontsize=15)\n",
+    "ax.set_ylabel(r'$\\Delta\\Sigma$ [M$_\\odot$ Mpc$^{-2}$]', fontsize=15)\n",
+    "ax.tick_params(axis='x', labelsize=15)\n",
+    "ax.tick_params(axis='y', labelsize=15)\n",
+    "ax.set_ylim([8.e10, 1e16])\n",
+    "\n",
+    "fig.tight_layout()\n",
+    "fig.savefig('2h_miscentering_boost.png')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Typical values for halo_bias and concentration to use in the the example, computed using CCL\n",
+    "\n",
+    "import pyccl as ccl\n",
+    "\n",
+    "cosmo = ccl.Cosmology(Omega_c=0.27, Omega_b=0.045, h=0.67, sigma8=0.83, n_s=0.96)\n",
+    "\n",
+    "a = 1./(1+z_cl)\n",
+    "\n",
+    "bias = ccl.halos.HaloBiasTinker10(mass_def='200m', mass_def_strict=True)\n",
+    "conc = ccl.halos.concentration.ConcentrationDuffy08(mass_def='200m')\n",
+    "\n",
+    "bias(cosmo, mass_cl, a), conc(cosmo, mass_cl, a)\n"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "wrk",
+   "language": "python",
+   "name": "wrk"
+  },
+  "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": 4
+}