added 11 notebooks and equivalent scripts (cambridge version)

notebooks/cl_ST.ipynb

@@ -0,0 +1,215 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "# import necessary modules\n",
+    "# uncomment to get plots displayed in notebook\n",
+    "%matplotlib inline\n",
+    "import matplotlib\n",
+    "import matplotlib.pyplot as plt\n",
+    "import numpy as np\n",
+    "from classy import Class\n",
+    "from scipy.optimize import fsolve\n",
+    "from scipy.interpolate import interp1d\n",
+    "import math"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "# esthetic definitions for the plots\n",
+    "font = {'size'   : 16, 'family':'STIXGeneral'}\n",
+    "axislabelfontsize='large'\n",
+    "matplotlib.rc('font', **font)\n",
+    "matplotlib.mathtext.rcParams['legend.fontsize']='medium'\n",
+    "plt.rcParams[\"figure.figsize\"] = [8.0,6.0]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "#############################################\n",
+    "#\n",
+    "# Cosmological parameters and other CLASS parameters\n",
+    "#\n",
+    "common_settings = {# wich output? ClTT, transfer functions delta_i and theta_i\n",
+    "                   'output':'tCl,pCl,lCl',\n",
+    "                   # LambdaCDM parameters\n",
+    "                   'h':0.67556,\n",
+    "                   'omega_b':0.022032,\n",
+    "                   'omega_cdm':0.12038,\n",
+    "                   'A_s':2.215e-9,\n",
+    "                   'tau_reio':0.0925,\n",
+    "                   # Take fixed value for primordial Helium (instead of automatic BBN adjustment)\n",
+    "                   'YHe':0.246}\n",
+    "                   # other output and precision parameters\n",
+    "                   #'l_max_scalars':3000}\n",
+    "###############\n",
+    "#    \n",
+    "# call CLASS \n",
+    "#\n",
+    "###############\n",
+    "#\n",
+    "# scalars only\n",
+    "#\n",
+    "M = Class()\n",
+    "M.set(common_settings)\n",
+    "M.set({'output':'tCl,pCl','modes':'s','lensing':'no','n_s':0.9619,'l_max_scalars':3000})\n",
+    "M.compute()\n",
+    "cls = M.raw_cl(3000)\n",
+    "M.struct_cleanup()\n",
+    "M.empty()\n",
+    "#\n",
+    "# tensors only\n",
+    "#\n",
+    "M = Class()\n",
+    "M.set(common_settings)\n",
+    "l_max_tensors = 600\n",
+    "M.set({'output':'tCl,pCl','modes':'t','lensing':'no','r':0.1,'n_t':0,'l_max_tensors':l_max_tensors})\n",
+    "# for l_max=600 we can keep default precision\n",
+    "# for l_max = 3000 we would need to import many high precision settings from the file cl_ref.pre\n",
+    "#M.set({'output':'tCl,pCl','modes':'t','lensing':'no','r':0.1,'n_t':0,'l_max_tensors':3000})\n",
+    "#M.set({\n",
+    "#'recfast_Nz0':100000,\n",
+    "#'tol_thermo_integration':1.e-5,\n",
+    "#'recfast_x_He0_trigger_delta':0.01,\n",
+    "#'recfast_x_H0_trigger_delta':0.01,\n",
+    "#'evolver':0,\n",
+    "#'k_min_tau0':0.002,\n",
+    "#'k_max_tau0_over_l_max':3.,\n",
+    "#'k_step_sub':0.015,\n",
+    "#'k_step_super':0.0001,\n",
+    "#'k_step_super_reduction':0.1,\n",
+    "#'start_small_k_at_tau_c_over_tau_h':0.0004,\n",
+    "#'start_large_k_at_tau_h_over_tau_k':0.05,\n",
+    "#'tight_coupling_trigger_tau_c_over_tau_h':0.005,\n",
+    "#'tight_coupling_trigger_tau_c_over_tau_k':0.008,\n",
+    "#'start_sources_at_tau_c_over_tau_h':0.006,\n",
+    "#'l_max_g':50,\n",
+    "#'l_max_pol_g':25,\n",
+    "#'l_max_ur':50,\n",
+    "#'tol_perturb_integration':1.e-6,\n",
+    "#'perturb_sampling_stepsize':0.01,\n",
+    "#'radiation_streaming_approximation':2,\n",
+    "#'radiation_streaming_trigger_tau_over_tau_k':240.,\n",
+    "#'radiation_streaming_trigger_tau_c_over_tau':100.,\n",
+    "#'ur_fluid_approximation':2,\n",
+    "#'ur_fluid_trigger_tau_over_tau_k':50.,\n",
+    "#'l_logstep':1.026,\n",
+    "#'l_linstep':25,\n",
+    "#'hyper_sampling_flat':12.,\n",
+    "#'hyper_nu_sampling_step':10.,\n",
+    "#'hyper_phi_min_abs':1.e-10,\n",
+    "#'hyper_x_tol':1.e-4,\n",
+    "#'hyper_flat_approximation_nu':1.e6,\n",
+    "#'q_linstep':0.20,\n",
+    "#'q_logstep_spline':20.,\n",
+    "#'q_logstep_trapzd':0.5,\n",
+    "#'q_numstep_transition':250,\n",
+    "#'transfer_neglect_delta_k_T_t2':100.,\n",
+    "#'transfer_neglect_delta_k_T_e':100.,\n",
+    "#'transfer_neglect_delta_k_T_b':100.,\n",
+    "#'neglect_CMB_sources_below_visibility':1.e-30,\n",
+    "#'transfer_neglect_late_source':3000.\n",
+    "#})\n",
+    "M.compute()\n",
+    "clt = M.raw_cl(l_max_tensors)\n",
+    "M.struct_cleanup()\n",
+    "M.empty()\n",
+    "#\n",
+    "# scalars + tensors (only in this case we can get the correct lensed ClBB)\n",
+    "#\n",
+    "M = Class()\n",
+    "M.set(common_settings)\n",
+    "M.set({'output':'tCl,pCl,lCl','modes':'s,t','lensing':'yes','r':0.1,'n_s':0.9619,'n_t':0,'l_max_scalars':3000,'l_max_tensors':l_max_tensors})\n",
+    "M.compute()\n",
+    "cl_tot = M.raw_cl(3000)\n",
+    "cl_lensed = M.lensed_cl(3000)\n",
+    "M.struct_cleanup()\n",
+    "M.empty()\n",
+    "#\n",
+    "#################\n",
+    "#\n",
+    "# start plotting\n",
+    "#\n",
+    "#################\n",
+    "#\n",
+    "plt.xlim([2,3000])\n",
+    "plt.ylim([1.e-8,10])\n",
+    "plt.xlabel(r\"$\\ell$\")\n",
+    "plt.ylabel(r\"$\\ell (\\ell+1) C_l^{XY} / 2 \\pi \\,\\,\\, [\\times 10^{10}]$\")\n",
+    "plt.title(r\"$r=0.1$\")\n",
+    "plt.grid()\n",
+    "#\n",
+    "ell = cl_tot['ell']\n",
+    "ellt = clt['ell']\n",
+    "factor = 1.e10*ell*(ell+1.)/2./math.pi\n",
+    "factort = 1.e10*ellt*(ellt+1.)/2./math.pi\n",
+    "#\n",
+    "plt.loglog(ell,factor*cls['tt'],'r-',label=r'$\\mathrm{TT(s)}$')\n",
+    "plt.loglog(ellt,factort*clt['tt'],'r:',label=r'$\\mathrm{TT(t)}$')\n",
+    "plt.loglog(ell,factor*cls['ee'],'b-',label=r'$\\mathrm{EE(s)}$')\n",
+    "plt.loglog(ellt,factort*clt['ee'],'b:',label=r'$\\mathrm{EE(t)}$')\n",
+    "plt.loglog(ellt,factort*clt['bb'],'g:',label=r'$\\mathrm{BB(t)}$')\n",
+    "plt.loglog(ell,factor*(cl_lensed['bb']-cl_tot['bb']),'g-',label=r'$\\mathrm{BB(lensing)}$')\n",
+    "plt.legend(loc='right',bbox_to_anchor=(1.4, 0.5))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "plt.savefig('cl_ST.pdf',bbox_inches='tight')"
+   ]
+  }
+ ],
+ "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": "2.7.13"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}

notebooks/cltt_terms.ipynb

@@ -0,0 +1,167 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "# import necessary modules\n",
+    "# uncomment to get plots displayed in notebook\n",
+    "%matplotlib inline\n",
+    "import matplotlib\n",
+    "import matplotlib.pyplot as plt\n",
+    "import numpy as np\n",
+    "from classy import Class\n",
+    "from scipy.optimize import fsolve\n",
+    "from scipy.interpolate import interp1d\n",
+    "import math"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "# esthetic definitions for the plots\n",
+    "font = {'size'   : 16, 'family':'STIXGeneral'}\n",
+    "axislabelfontsize='large'\n",
+    "matplotlib.rc('font', **font)\n",
+    "matplotlib.mathtext.rcParams['legend.fontsize']='medium'\n",
+    "plt.rcParams[\"figure.figsize\"] = [8.0,6.0]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "#############################################\n",
+    "#\n",
+    "# Cosmological parameters and other CLASS parameters\n",
+    "#\n",
+    "common_settings = {# wich output? ClTT, transfer functions delta_i and theta_i\n",
+    "                   'output':'tCl,pCl,lCl',\n",
+    "                   'lensing':'yes',\n",
+    "                   # LambdaCDM parameters\n",
+    "                   'h':0.67556,\n",
+    "                   'omega_b':0.022032,\n",
+    "                   'omega_cdm':0.12038,\n",
+    "                   'A_s':2.215e-9,\n",
+    "                   'n_s':0.9619,\n",
+    "                   'tau_reio':0.0925,\n",
+    "                   # Take fixed value for primordial Helium (instead of automatic BBN adjustment)\n",
+    "                   'YHe':0.246,\n",
+    "                   # other output and precision parameters\n",
+    "                   'l_max_scalars':5000}\n",
+    "###############\n",
+    "#    \n",
+    "# call CLASS \n",
+    "#\n",
+    "M = Class()\n",
+    "M.set(common_settings)\n",
+    "M.compute()\n",
+    "cl_tot = M.raw_cl(3000)\n",
+    "cl_lensed = M.lensed_cl(3000)\n",
+    "M.struct_cleanup()  # clean output\n",
+    "M.empty()           # clean input\n",
+    "#\n",
+    "M.set(common_settings) # new input\n",
+    "M.set({'temperature contributions':'tsw'}) \n",
+    "M.compute()\n",
+    "cl_tsw = M.raw_cl(3000) \n",
+    "M.struct_cleanup()\n",
+    "M.empty()\n",
+    "#\n",
+    "M.set(common_settings)\n",
+    "M.set({'temperature contributions':'eisw'})\n",
+    "M.compute()\n",
+    "cl_eisw = M.raw_cl(3000) \n",
+    "M.struct_cleanup()\n",
+    "M.empty()\n",
+    "#\n",
+    "M.set(common_settings)\n",
+    "M.set({'temperature contributions':'lisw'})\n",
+    "M.compute()\n",
+    "cl_lisw = M.raw_cl(3000) \n",
+    "M.struct_cleanup()\n",
+    "M.empty()\n",
+    "#\n",
+    "M.set(common_settings)\n",
+    "M.set({'temperature contributions':'dop'})\n",
+    "M.compute()\n",
+    "cl_dop = M.raw_cl(3000) \n",
+    "#\n",
+    "#################\n",
+    "#\n",
+    "# start plotting\n",
+    "#\n",
+    "#################\n",
+    "#\n",
+    "plt.xlim([2,3000])\n",
+    "plt.xlabel(r\"$\\ell$\")\n",
+    "plt.ylabel(r\"$\\ell (\\ell+1) C_l^{TT} / 2 \\pi \\,\\,\\, [\\times 10^{10}]$\")\n",
+    "plt.grid()\n",
+    "#\n",
+    "ell = cl_tot['ell']\n",
+    "factor = 1.e10*ell*(ell+1.)/2./math.pi\n",
+    "plt.semilogx(ell,factor*cl_tsw['tt'],'c-',label=r'$\\mathrm{T+SW}$')\n",
+    "plt.semilogx(ell,factor*cl_eisw['tt'],'r-',label=r'$\\mathrm{early-ISW}$')\n",
+    "plt.semilogx(ell,factor*cl_lisw['tt'],'y-',label=r'$\\mathrm{late-ISW}$')\n",
+    "plt.semilogx(ell,factor*cl_dop['tt'],'g-',label=r'$\\mathrm{Doppler}$')\n",
+    "plt.semilogx(ell,factor*cl_tot['tt'],'r-',label=r'$\\mathrm{total}$')\n",
+    "plt.semilogx(ell,factor*cl_lensed['tt'],'k-',label=r'$\\mathrm{lensed}$')\n",
+    "#\n",
+    "plt.legend(loc='right',bbox_to_anchor=(1.4, 0.5))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "plt.savefig('cltt_terms.pdf',bbox_inches='tight')"
+   ]
+  }
+ ],
+ "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": "2.7.13"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}