{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Figure S2: Influence of parameter choice on the phase diagram"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To study to what extend the phase diagram depends on the cost of infection $c_{\\rm inf}$, and on the trade-off shapes $c_{\\rm def}(c_{\\rm con}), c_{\\rm uptake}(p_{\\rm uptake})$ we plot the phase diagram for a number of different choices in the following."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Import packages."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "use czrecursion, cztogrowthrate\n",
      "use cstepmarkov\n"
     ]
    }
   ],
   "source": [
    "from cycler import cycler\n",
    "import sys\n",
    "sys.path.append('../lib')\n",
    "import numpy as np\n",
    "import matplotlib.colors\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib import transforms, gridspec, ticker\n",
    "import palettable\n",
    "import shapely.ops\n",
    "%matplotlib inline\n",
    "import plotting\n",
    "import evolimmune\n",
    "import misc\n",
    "import analysis\n",
    "%load_ext autoreload\n",
    "%autoreload 2\n",
    "plt.style.use(['paper'])\n",
    "plt.rc('lines', linewidth=1.0)\n",
    "plt.rc('axes', labelpad=1.0)\n",
    "eps = 1e-8"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Read in and summarize data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-----------------------------------------------------\n",
      "values of columns with no more than 10 unique entries\n",
      "\n",
      "boundary: ac; ap; cm; io; mi; pc; pi; pm; po\n",
      "boundtol: 0.005\n",
      "cup: 0.1*pup+pup**2; 0.05*pup+2*pup**2; 0.2*pup+2*pup**2\n",
      "deltainit: 0.02\n",
      "deltatol: 0.0005\n",
      "lambda_: 1.5; 3.0; 4.5\n",
      "logfeps: -9.0\n",
      "mus: 0.5*(1.0-2.0*epsilon/(1.0+epsilon)), 0.5*(1.0+0.8*epsilon); 1.0-2.0*epsilon/(1.0+epsilon), 1.0+0.8*epsilon; 1.0-epsilon, 1.4-0.6*(1.0-epsilon)+0.2*(1.0-epsilon)**2; 1.5*(1.0-2.0*epsilon/(1.0+epsilon)), 1.5*(1.0+0.8*epsilon)\n",
      "nburnin: 10000.0\n",
      "niter: 1000000.0\n",
      "qboundtol: 0.0005\n",
      "xtol: 0.025\n",
      "xtolbound: 0.01\n",
      "-----------------------------------------------------\n",
      "summary statistics of other columns\n",
      "\n",
      "              aenv     pienvbnd\n",
      "count  1005.000000  1005.000000\n",
      "mean      0.500825     0.555374\n",
      "std       0.353774     0.289091\n",
      "min       0.000015    -0.408107\n",
      "25%       0.133078     0.373598\n",
      "50%       0.523847     0.575282\n",
      "75%       0.855588     0.769385\n",
      "max       0.951229     1.003422\n",
      "-----------------------------------------------------\n"
     ]
    }
   ],
   "source": [
    "df = analysis.loadnpz('data/phases.npz')\n",
    "analysis.intelligent_describe(df, nunique=10)\n",
    "dfg = df.groupby(['lambda_', 'mus', 'cup'])\n",
    "nparams = len(dfg)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "define colors used in plot and phasenames"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "black = matplotlib.rcParams['text.color']\n",
    "colors = np.asarray(palettable.colorbrewer.qualitative.Set3_6.mpl_colors)[[4, 0, 2, 3, 5, 1]]\n",
    "strategies_s = ['a', 'p', 'o', 'i', 'm', 'c']\n",
    "color_dict = dict(zip(strategies_s, colors))\n",
    "linecolors = palettable.colorbrewer.qualitative.Dark2_6.mpl_colors\n",
    "plt.rc('axes', prop_cycle=cycler('color', linecolors))\n",
    "phasenames = misc.DefaultIdentityDict(o='$i$', i='$ib$')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Define plotting functions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def plotmus(ax, musstr, alpha=1.0, label=True):\n",
    "    epsilon = np.linspace(0.0, 1.0, 100)\n",
    "    mus = evolimmune.mus_from_str(musstr)\n",
    "    mu1, mu2 = mus(epsilon)\n",
    "    if label:\n",
    "        ax.plot(mu1, mu2, c=linecolors[1], alpha=alpha, label='defense')\n",
    "    else:\n",
    "        ax.plot(mu1, mu2, c=linecolors[1], alpha=alpha)\n",
    "    ax.plot(mu1[0], mu2[0], 'o', markeredgecolor='none', markersize=3, c=linecolors[1], alpha=alpha)\n",
    "    \n",
    "def plotstatecosts(ax, musstr, musstrref=None, lambda_=None):\n",
    "    if lambda_:\n",
    "        ax.text(1, 1, '${0}={1}$'.format(r'c_{\\rm inf}', lambda_),\n",
    "               transform=ax.transAxes, ha='right', va='top')\n",
    "    if musstrref is not None:\n",
    "        plotmus(ax, musstrref, alpha=0.25, label=False)\n",
    "    plotmus(ax, musstr)\n",
    "    ax.set_xlabel(evolimmune.varname_to_tex['cconstitutive'])\n",
    "    ax.set_ylabel(evolimmune.varname_to_tex['cdefense'])\n",
    "    ax.set_xlim(0, 1.5)\n",
    "    ax.set_ylim(0, 2.7)\n",
    "    ax.locator_params(nbins=3)\n",
    "\n",
    "def plotcup(ax, cupstr, cupstrref=None):\n",
    "    pup = np.linspace(0.0, 0.2, 100)\n",
    "    if cupstrref is not None:\n",
    "        cup = evolimmune.cup_from_str(cupstrref)\n",
    "        ax.plot(pup, cup(pup), c=linecolors[2], alpha=.25)\n",
    "    cup = evolimmune.cup_from_str(cupstr)\n",
    "    ax.plot(pup, cup(pup), c=linecolors[2])\n",
    "    ax.set_xlabel(evolimmune.varname_to_tex['pup'])\n",
    "    ax.set_ylabel(evolimmune.varname_to_tex['cup'])\n",
    "    ax.set_ylim(0, 0.1)\n",
    "    ax.locator_params(nbins=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Putting it all together into one figure"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3.0 1.0-2.0*epsilon/(1.0+epsilon), 1.0+0.8*epsilon 0.1*pup+pup**2\n",
      "3.0 1.0-2.0*epsilon/(1.0+epsilon), 1.0+0.8*epsilon 0.2*pup+2*pup**2\n",
      "3.0 1.0-2.0*epsilon/(1.0+epsilon), 1.0+0.8*epsilon 0.05*pup+2*pup**2\n",
      "1.5 0.5*(1.0-2.0*epsilon/(1.0+epsilon)), 0.5*(1.0+0.8*epsilon) 0.1*pup+pup**2\n",
      "4.5 1.5*(1.0-2.0*epsilon/(1.0+epsilon)), 1.5*(1.0+0.8*epsilon) 0.1*pup+pup**2\n",
      "4.5 1.0-2.0*epsilon/(1.0+epsilon), 1.0+0.8*epsilon 0.1*pup+pup**2\n",
      "3.0 0.5*(1.0-2.0*epsilon/(1.0+epsilon)), 0.5*(1.0+0.8*epsilon) 0.1*pup+pup**2\n",
      "3.0 1.0-epsilon, 1.4-0.6*(1.0-epsilon)+0.2*(1.0-epsilon)**2 0.1*pup+pup**2\n"
     ]
    },
    {
     "data": {
      "image/png": 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XZ4q3K3FD9PgRH75DMJWGI5qn1zzxIIlEAoAqEvPPZXHxYgBqa08Entux44/xcmcE4vgF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bDAY2b96MxWLB4/GM2n68b98+9u7dGxAuq9XKsWPHcLlcmEwmOaxTEISIEa0SBCEeRBVUjRWp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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f7198379a10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(6, 7))\n",
    "nrow = 4\n",
    "nsubrow = 3\n",
    "height_ratios = [1, 10, 10]\n",
    "gsglobal = gridspec.GridSpec(4, 2)\n",
    "import param1\n",
    "lambdaref, musref, cupref = param1.lambda_, param1.mus, param1.cup\n",
    "label_axes = []\n",
    "for i in range(1, 9):\n",
    "    p = __import__('param{}'.format(i))\n",
    "    lambda_ = p.lambda_\n",
    "    mus = p.mus\n",
    "    cup = p.cup\n",
    "    dfg = df[(df.mus==mus)&(df.cup==cup)&(df.lambda_==lambda_)]\n",
    "    print lambda_, mus, cup\n",
    "    gs = gridspec.GridSpecFromSubplotSpec(3, 2, subplot_spec=gsglobal[(i-1)%nrow, (i-1)//nrow],\n",
    "                                          width_ratios=[1, 2], height_ratios=[1, 30, 20],\n",
    "                                          hspace=1.5, wspace=0.6)\n",
    "    axlambda = fig.add_subplot(gs[0, 0])\n",
    "    axlambda.text(0.5, -3.0, '${0}={1}$'.format(r'c_{\\rm inf}', lambda_),\n",
    "               transform=axlambda.transAxes, ha='center', va='top')\n",
    "    axlambda.axis('off')\n",
    "    axmu = fig.add_subplot(gs[1, 0])\n",
    "    plotstatecosts(axmu, mus, musref)\n",
    "    axcup = fig.add_subplot(gs[2, 0])\n",
    "    plotcup(axcup, cup, cupref)\n",
    "    for ax in [axmu, axcup]:\n",
    "        plotting.despine(ax)\n",
    "    axm = fig.add_subplot(gs[:, 1])\n",
    "    try:\n",
    "        polygons = evolimmune.polygons_from_boundaries(dfg, yconv=evolimmune.to_tau)\n",
    "        phases = evolimmune.phases_from_polygons(polygons)\n",
    "    except:\n",
    "        pass\n",
    "    else:\n",
    "        for phasename, phase in phases.iteritems():\n",
    "            try:\n",
    "                axm.add_patch(analysis.shapely_to_mpl(phase, ec='None',\n",
    "                                                      fc=color_dict[phasename],\n",
    "                                                      lw=1.0)) \n",
    "                phaset = shapely.ops.transform(lambda x, y, z=None: (x, np.log(y+eps)), phase)\n",
    "                axm.text(phaset.centroid.x, np.exp(phaset.centroid.y),\n",
    "                         r'$\\mathbf{%s}$'%phasenames[phasename][1:-1],\n",
    "                         ha='center', va='center')\n",
    "            except:\n",
    "                pass\n",
    "\n",
    "\n",
    "    axm.set_ylim(evolimmune.to_tau(df.aenv.min()), evolimmune.to_tau(df.aenv.max()))\n",
    "    axm.set_yscale('log')\n",
    "    axm.yaxis.set_major_formatter(ticker.ScalarFormatter())\n",
    "    axm.set_xlabel('$\\pi_{env}$')\n",
    "    axm.set_ylabel(r'$\\tau_{env}$')\n",
    "    axm.grid(which='major', alpha=0.75)\n",
    "    axm.grid(which='minor', lw=0.4, alpha=0.5)\n",
    "    axm.set_axisbelow(False)\n",
    "    plotting.despine(axm, spines='all')\n",
    "    label_axes.append((i, axlambda))\n",
    "label_axes = [ax for i, ax in sorted(label_axes)]\n",
    "plotting.label_axes(label_axes, xy=(-0.6, 1.0), fontsize='large', va='top')\n",
    "gsglobal.tight_layout(fig, h_pad=1.0, w_pad=2.0)\n",
    "fig.savefig('SIaltphases.pdf')\n",
    "fig.savefig('SIaltphases.svg')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
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   "source": [
    "**Influence of parameter choice on the phase diagram presented in Fig. 2.**\n",
    "For every panel the parameter choices are shown on the left and the phase boundaries between **p**roto-adaptive, **i**nnate, **i**nnate **b**et hedging, **m**ixed and **C**RISPR-like strategies are shown on the right. As a reference, lines in lighter color show trade-off and uptake cost for parameter set used in Fig. 2.\n",
    "**(A)** Phase diagram for parameters used in Fig. 2.\n",
    "**(B)** More expensive active acquisition ($c_{\\rm uptake}$ multiplied by a factor of two).\n",
    "**(C)** Different functional form for cost of active acqusition: $c_{\\rm uptake} = 0.05 \\times p_{\\rm uptake} + 2 \\times p_{\\rm uptake}^2$.\n",
    "**(D)** More permissive state-dependent costs (costs multiplied by a factor of 0.5).\n",
    "**(E)** Less permissive state-dependent costs (costs multiplied by a factor of 1.5).\n",
    "**(F)** Higher cost of infection.\n",
    "**(G)** Higher cost of immune protection.\n",
    "**(H)** Different functional form for cost trade-off, $c_{\\rm defense} = 1.4-0.6\\times c_{\\rm constitutive}+0.2 \\times c_{\\rm constitutive}^2$"
   ]
  },
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   "cell_type": "code",
   "execution_count": null,
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   "source": []
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