model_parameter_analyses.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from scipy.special import expit\n",
    "from scipy.stats import pearsonr\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import pandas as pd\n",
    "\n",
    "from utils_hpd import hpd_grid\n",
    "from utils_dataset import *\n",
    "from utils_sampling import *\n",
    "from utils_models import *\n",
    "from funcs_model_predictions import *\n",
    "from funcs_model_fit_evaluate import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from IPython.display import set_matplotlib_formats\n",
    "set_matplotlib_formats('png', 'pdf')\n",
    "plt.rcParams.update({'font.size': 28})\n",
    "plt.rcParams.update({'font.family': 'arial'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "datasetName = 'takahashi2016roesch2009burton2018Valid'\n",
    "dataValid = pd.read_csv('data/' + datasetName + '.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "def transform_beta(x):\n",
    "    # Phi_approx(x) = logit^{-1}(0.07056 x^3 + 1.5976 x)\n",
    "    return expit(0.07056*(x**3) + 1.5976*x)*10\n",
    "\n",
    "def transform_w(x):\n",
    "    # Phi_approx(x) = logit^{-1}(0.07056 x^3 + 1.5976 x)\n",
    "    return expit(0.07056*(x**3) + 1.5976*x)\n",
    "\n",
    "def transform_eta(x):\n",
    "    # Phi_approx(x) = logit^{-1}(0.07056 x^3 + 1.5976 x)\n",
    "    return expit(0.07056*(x**3) + 1.5976*x)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Load fitted parameters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "allSamples = pd.read_csv('model_fits/' + datasetName + '_hybridValue_full_allSamples.csv')\n",
    "\n",
    "NStates = [4,6]\n",
    "w = dict.fromkeys([str(NState)+'group' for NState in NStates] + [str(NState) for NState in NStates])\n",
    "w['w4group'] = allSamples.loc[allSamples['warmup']==0, 'mu_pr[2]'].values\n",
    "w['w4'] = allSamples.loc[allSamples['warmup']==0, [col for col in allSamples if col.startswith('w4[')>0]].values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "allSamples = pd.read_csv('model_fits/'+datasetName+'_hybridLearning_full_allSamples.csv')\n",
    "\n",
    "etaNameList = ['eta', 'eta4state']\n",
    "etas = dict.fromkeys([etaName+'_group' for etaName in etaNameList] + etaNameList)\n",
    "for etaName in etaNameList:\n",
    "    etas[etaName+'_group'] = allSamples.loc[allSamples['warmup']==0, 'mu_pr[' + str(etaNameList.index(etaName)+2) + ']'].values\n",
    "    etas[etaName] = allSamples.loc[allSamples['warmup']==0, [col for col in allSamples if col.startswith(etaName+'[')>0]].values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.DataFrame()\n",
    "df['avgreward'] = [dataValid.groupby('rat')['rewardAmount'].mean()[iRat] for iRat in dataValid['rat'].unique()]\n",
    "df['dataset'] = [rat2dataset[iRat] for iRat in dataValid['rat'].unique()]\n",
    "df['w4'] = [np.mean(w['w4'][:,iRat-1]) for iRat in dataValid['rat'].unique()]\n",
    "df['eta'] = [np.mean(etas['eta'][:,iRat-1]) for iRat in dataValid['rat'].unique()]\n",
    "df['etag'] = [np.mean(etas['eta4state'][:,iRat-1]) for iRat in dataValid['rat'].unique()]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "### $w_4$ (hybrid-value model)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Group-level parameters (95% HDI)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "95% HDI w4_group: (0.05, 0.28)\n"
     ]
    },
    {
     "data": {
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\n",
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "intervals4 = hpd_grid(transform_w(w['w4group']), alpha=0.05)[0][0]\n",
    "intervals6 = hpd_grid(1 - transform_w(w['w4group']), alpha=0.05)[0][0]\n",
    "intervals_diff = hpd_grid(1 - transform_w(w['w4group'])-transform_w(w['w4group']), alpha=0.05)[0][0]\n",
    "\n",
    "fig, ax = plt.subplots()\n",
    "# sns.distplot(1 - transform_w(w['w4group']), label='w(6-state)')\n",
    "sns.distplot(transform_w(w['w4group']), kde=False, hist_kws={'alpha':0.6}, color='k') #, label='w(4-state)'\n",
    "ymin, ymax = ax.get_ylim()\n",
    "# ax.vlines(x=intervals6, ymin=ymin, ymax=ymax, color='C0', linestyle='--', linewidth=2)\n",
    "ax.vlines(x=intervals4, ymin=ymin, ymax=ymax, color='k', linestyle='--', linewidth=2)\n",
    "\n",
    "ax.set_xlabel('$w_4$')\n",
    "ax.set_yticklabels('')\n",
    "ax.tick_params(axis='y', length=0)\n",
    "ax.set_xlim([-0.05,1.05])\n",
    "ax.tick_params(axis='x', width=1.5, pad=10)\n",
    "ax.spines['bottom'].set_linewidth(1.5)\n",
    "ax.xaxis.labelpad = 10\n",
    "sns.despine()\n",
    "ax.spines['left'].set_visible(False)\n",
    "\n",
    "print('95% HDI w4_group:', intervals4)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Individual animals (Correlate with average reward)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(0.6353430617214064, 0.0014868590737657868)\n"
     ]
    },
    {
     "data": {
      "application/pdf": 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\n",
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(5,4))\n",
    "for dataset in datasets:\n",
    "    sns.regplot(x='w4', y='avgreward', data=df[df['dataset']==dataset], color='k', fit_reg=False, marker=dataset2marker[dataset], scatter_kws={'s':150*ratio_s[dataset]}, label=dataset_labels[dataset])\n",
    "sns.regplot(x='w4', y='avgreward', data=df, color='k', line_kws={'linestyle':'--'}, scatter=False)\n",
    "\n",
    "ax.set_xlabel('$w_4$')\n",
    "ax.set_ylabel('Average reward')\n",
    "ax.spines['bottom'].set_linewidth(1.5)\n",
    "ax.spines['left'].set_linewidth(1.5)\n",
    "ax.tick_params(axis='both', width=1.5, length=5, pad=10)\n",
    "sns.despine()\n",
    "ax.legend(frameon=False, loc='center left', bbox_to_anchor=(1, 0.5), fontsize=26, handletextpad=-0.3)\n",
    "\n",
    "print(pearsonr(df['w4'], df['avgreward']))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "### $\\eta$ vs $\\eta_g$ (hybrid-learning model)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Group-level parameters (95% HDI)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:matplotlib.legend:No handles with labels found to put in legend.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "95% HDI of eta: (0.22, 0.28)\n",
      "95% HDI of etag: (0.0, 0.01)\n"
     ]
    },
    {
     "data": {
      "application/pdf": 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\n",
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "intervals_eta = hpd_grid(transform_eta(etas['eta_group']), alpha=0.05)[0][0]\n",
    "intervals_eta4state = hpd_grid(transform_eta(etas['eta4state_group']), alpha=0.05)[0][0]\n",
    "intervals_diff = hpd_grid(transform_eta(etas['eta_group'])-transform_eta(etas['eta4state_group']), alpha=0.05)[0][0]\n",
    "\n",
    "fig, ax = plt.subplots()\n",
    "sns.distplot(transform_eta(etas['eta4state_group']), kde=False, color='C1', hist_kws={'alpha':0.8}) #, label='$\\eta_g$'\n",
    "sns.distplot(transform_eta(etas['eta_group']), kde=False, color='C2', hist_kws={'alpha':0.8}) #, label='$\\eta$'\n",
    "ymin, ymax = ax.get_ylim()\n",
    "ax.vlines(x=intervals_eta, ymin=ymin/2, ymax=ymax/2, color='C2', linestyle='--', linewidth=2)\n",
    "ax.vlines(x=intervals_eta4state, ymin=ymin, ymax=ymax, color='C1', linestyle='--', linewidth=2)\n",
    "\n",
    "ax.legend(frameon=False, loc='best')\n",
    "# ax.set_xlabel('Learning/Generalization rate')\n",
    "ax.set_yticklabels('')\n",
    "ax.tick_params(axis='y', length=0)\n",
    "ax.set_xlim([-0.05,0.45])\n",
    "ax.tick_params(axis='x', width=1.5, pad=10)\n",
    "ax.spines['bottom'].set_linewidth(1.5)\n",
    "ax.xaxis.labelpad = 10\n",
    "sns.despine()\n",
    "ax.spines['left'].set_visible(False)\n",
    "\n",
    "print('95% HDI of eta:', intervals_eta)\n",
    "print('95% HDI of etag:', intervals_eta4state)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Individual animals"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:matplotlib.legend:No handles with labels found to put in legend.\n"
     ]
    },
    {
     "data": {
      "application/pdf": 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3IDY2NwoyNzggMjc4IDI3OCAyNzggNzIyIDcyMiA3NzggNzc4IDc3OCA3NzggNzc4IDU4NCA3NzggNzIyIDcyMiA3MjIgNzIyIDY2NyA2NjcKNjExIDU1NiA1NTYgNTU2IDU1NiA1NTYgNTU2IDg4OSA1MDAgNTU2IDU1NiA1NTYgNTU2IDI3OCAyNzggMjc4IDI3OCA1NTYgNTU2CjU1NiA1NTYgNTU2IDU1NiA1NTYgNTQ5IDYxMSA1NTYgNTU2IDU1NiA1NTYgNTAwIDU1NiA1MDAgXQplbmRvYmoKMTggMCBvYmoKPDwgL2ZvdXIgMTkgMCBSIC9wZXJpb2QgMjAgMCBSIC90d28gMjEgMCBSIC96ZXJvIDIyIDAgUiA+PgplbmRvYmoKMjcgMCBvYmoKPDwgL0JCb3ggWyAtMTAxNiAtMzUxIDE2NjAgMTA2OCBdIC9GaWx0ZXIgL0ZsYXRlRGVjb2RlIC9MZW5ndGggMTY1Ci9TdWJ0eXBlIC9Gb3JtIC9UeXBlIC9YT2JqZWN0ID4+CnN0cmVhbQp4nD2QQQ4DMQgD73kFH6hEwJDwnpV6av9/rclWe4iwMDGTjFgl7irfgQV5mS75DN+PxN7idlRRcRoVgrkEWwVwuQaSnaTj3TXxuus1HHV3mIVMseWcSjrmdBRiTPI06W2uRWdiiXJf3GWmS6ABLB7Vi3iJKkEgxvDErIMaZ4FHSUTD0Emiup9KXD6gVRAhwMqM0MYNPrZzo4ipnPp/zjXeP6OYOCsKZW5kc3RyZWFtCmVuZG9iagoyOCAwIG9iago8PCAvRmlsdGVyIC9GbGF0ZURlY29kZSAvTGVuZ3RoIDM5OSA+PgpzdHJlYW0KeJw9ksmR3TAMRO+KAglMFbFxiee7fJrJ/+rXlO2DihBJNHrhzLZhGfYVY1mfaT2H/fLnlrXs5+mRNrd9P7Wba2XVw75OWA1Wz22fJ+tQ7rLY/kI5/bf4PD7r717eosz5oRgcbmGctm4B7EvFlzAFeZy5C0gfbYdu9zZ3DYsQdKXKY74ul2TufovPExeTModAfVkmnXuK8OKM8zzCcit9IluAb6nNk/hhCflUp9udGOAvixnYFpgxrsDN6gG1bWprNqcb7GuaV2iJobkqeupG8g+J7GIbaQVJDzoKGK7UlgZZ0bgV6O+gORWLhsYkr04LFCizRKhWtM13p4ZzA0T86dSY0mh8qAU+ROtwa0pWjzfu7//BkzcSEsI/b6W7JF/IFGKRD4hjg4bFix3eR5bfFRaaQxXSRsrBrSJK5SJf8BPGVdsC1yp14uLEc/Ml07H06nqDnhfJSVC53tU1R5Wj2OHjvGa9BPcXzW1jHaZidMy7iNi+xk+iGXIJ1NaMIii9zsuNSP/p/zy//wCZvpWqCmVuZHN0cmVhbQplbmRvYmoKMjUgMCBvYmoKPDwgL0Jhc2VGb250IC9EZWphVnVTYW5zLU9ibGlxdWUgL0NoYXJQcm9jcyAyNiAwIFIKL0VuY29kaW5nIDw8IC9EaWZmZXJlbmNlcyBbIDEwMyAvZyBdIC9UeXBlIC9FbmNvZGluZyA+PiAvRmlyc3RDaGFyIDAKL0ZvbnRCQm94IFsgLTEwMTYgLTM1MSAxNjYwIDEwNjggXSAvRm9udERlc2NyaXB0b3IgMjQgMCBSCi9Gb250TWF0cml4IFsgMC4wMDEgMCAwIDAuMDAxIDAgMCBdIC9MYXN0Q2hhciAyNTUgL05hbWUgL0RlamFWdVNhbnMtT2JsaXF1ZQovU3VidHlwZSAvVHlwZTMgL1R5cGUgL0ZvbnQgL1dpZHRocyAyMyAwIFIgPj4KZW5kb2JqCjI0IDAgb2JqCjw8IC9Bc2NlbnQgOTI5IC9DYXBIZWlnaHQgMCAvRGVzY2VudCAtMjM2IC9GbGFncyA5NgovRm9udEJCb3ggWyAtMTAxNiAtMzUxIDE2NjAgMTA2OCBdIC9Gb250TmFtZSAvRGVqYVZ1U2Fucy1PYmxpcXVlCi9JdGFsaWNBbmdsZSAwIC9NYXhXaWR0aCAxMzUwIC9TdGVtViAwIC9UeXBlIC9Gb250RGVzY3JpcHRvciAvWEhlaWdodCAwID4+CmVuZG9iagoyMyAwIG9iagpbIDYwMCA2MDAgNjAwIDYwMCA2MDAgNjAwIDYwMCA2MDAgNjAwIDYwMCA2MDAgNjAwIDYwMCA2MDAgNjAwIDYwMCA2MDAgNjAwCjYwMCA2MDAgNjAwIDYwMCA2MDAgNjAwIDYwMCA2MDAgNjAwIDYwMCA2MDAgNjAwIDYwMCA2MDAgMzE4IDQwMSA0NjAgODM4IDYzNgo5NTAgNzgwIDI3NSAzOTAgMzkwIDUwMCA4MzggMzE4IDM2MSAzMTggMzM3IDYzNiA2MzYgNjM2IDYzNiA2MzYgNjM2IDYzNiA2MzYKNjM2IDYzNiAzMzcgMzM3IDgzOCA4MzggODM4IDUzMSAxMDAwIDY4NCA2ODYgNjk4IDc3MCA2MzIgNTc1IDc3NSA3NTIgMjk1CjI5NSA2NTYgNTU3IDg2MyA3NDggNzg3IDYwMyA3ODcgNjk1IDYzNSA2MTEgNzMyIDY4NCA5ODkgNjg1IDYxMSA2ODUgMzkwIDMzNwozOTAgODM4IDUwMCA1MDAgNjEzIDYzNSA1NTAgNjM1IDYxNSAzNTIgNjM1IDYzNCAyNzggMjc4IDU3OSAyNzggOTc0IDYzNCA2MTIKNjM1IDYzNSA0MTEgNTIxIDM5MiA2MzQgNTkyIDgxOCA1OTIgNTkyIDUyNSA2MzYgMzM3IDYzNiA4MzggNjAwIDYzNiA2MDAgMzE4CjM1MiA1MTggMTAwMCA1MDAgNTAwIDUwMCAxMzUwIDYzNSA0MDAgMTA3MCA2MDAgNjg1IDYwMCA2MDAgMzE4IDMxOCA1MTggNTE4CjU5MCA1MDAgMTAwMCA1MDAgMTAwMCA1MjEgNDAwIDEwMjggNjAwIDUyNSA2MTEgMzE4IDQwMSA2MzYgNjM2IDYzNiA2MzYgMzM3CjUwMCA1MDAgMTAwMCA0NzEgNjE3IDgzOCAzNjEgMTAwMCA1MDAgNTAwIDgzOCA0MDEgNDAxIDUwMCA2MzYgNjM2IDMxOCA1MDAKNDAxIDQ3MSA2MTcgOTY5IDk2OSA5NjkgNTMxIDY4NCA2ODQgNjg0IDY4NCA2ODQgNjg0IDk3NCA2OTggNjMyIDYzMiA2MzIgNjMyCjI5NSAyOTUgMjk1IDI5NSA3NzUgNzQ4IDc4NyA3ODcgNzg3IDc4NyA3ODcgODM4IDc4NyA3MzIgNzMyIDczMiA3MzIgNjExIDYwOAo2MzAgNjEzIDYxMyA2MTMgNjEzIDYxMyA2MTMgOTk1IDU1MCA2MTUgNjE1IDYxNSA2MTUgMjc4IDI3OCAyNzggMjc4IDYxMiA2MzQKNjEyIDYxMiA2MTIgNjEyIDYxMiA4MzggNjEyIDYzNCA2MzQgNjM0IDYzNCA1OTIgNjM1IDU5MiBdCmVuZG9iagoyNiAwIG9iago8PCAvZyAyOCAwIFIgPj4KZW5kb2JqCjMgMCBvYmoKPDwgL0YxIDE3IDAgUiAvRjIgMjUgMCBSID4+CmVuZG9iago0IDAgb2JqCjw8IC9BMSA8PCAvQ0EgMCAvVHlwZSAvRXh0R1N0YXRlIC9jYSAxID4+Ci9BMiA8PCAvQ0EgMSAvVHlwZSAvRXh0R1N0YXRlIC9jYSAxID4+ID4+CmVuZG9iago1IDAgb2JqCjw8ID4+CmVuZG9iago2IDAgb2JqCjw8ID4+CmVuZG9iago3IDAgb2JqCjw8IC9EZWphVnVTYW5zLU9ibGlxdWUtZXRhIDI3IDAgUiAvTTAgMTIgMCBSIC9NMSAxMyAwIFIgL00yIDE0IDAgUiA+PgplbmRvYmoKMTIgMCBvYmoKPDwgL0JCb3ggWyAtNy44MjEwNjc4MTE5IC03LjgyMTA2NzgxMTkgNy44MjEwNjc4MTE5IDcuODIxMDY3ODExOSBdCi9GaWx0ZXIgL0ZsYXRlRGVjb2RlIC9MZW5ndGggNDYgL1N1YnR5cGUgL0Zvcm0gL1R5cGUgL1hPYmplY3QgPj4Kc3RyZWFtCnicM1TI4jJQ8OLSNdczMDc0MLNQMFDI5ULi5AClEZK5QB6ck8PF5cQFAJP5DCAKZW5kc3RyZWFtCmVuZG9iagoxMyAwIG9iago8PCAvQkJveCBbIC00LjQ1Mjg0NzA3NTIgLTQuNDUyODQ3MDc1MiA0LjQ1Mjg0NzA3NTIgNC40NTI4NDcwNzUyIF0KL0ZpbHRlciAvRmxhdGVEZWNvZGUgL0xlbmd0aCAxMzkgL1N1YnR5cGUgL0Zvcm0gL1R5cGUgL1hPYmplY3QgPj4Kc3RyZWFtCnicbZA7EsMwCER7TqELrAYLY8ltylzDTcYzvn/rX0QUi0aDFngLDGElDm86HkicNZUxh42GyGMRzo2YIquUdCoqk+gh5Fm5aIBFC9Ukarn1w5gm8dXw/TTpyr8JRm9sfvS71mNbuJDjjScCng+ew6CfF3/7wFkY3VXgHg/djeG6oFntQ/SiHRXFVqoKZW5kc3RyZWFtCmVuZG9iagoxNCAwIG9iago8PCAvQkJveCBbIC02Ljg3MzcyNDM1NyAtNi44NzM3MjQzNTcgNi44NzM3MjQzNTcgNi44NzM3MjQzNTcgXQovRmlsdGVyIC9GbGF0ZURlY29kZSAvTGVuZ3RoIDQ1IC9TdWJ0eXBlIC9Gb3JtIC9UeXBlIC9YT2JqZWN0ID4+CnN0cmVhbQp4nDNUyOIyUPDi4tI10zM0MjY3MlFAsHK54Ew4IwdJJTaFukgquZy4AGsIEhAKZW5kc3RyZWFtCmVuZG9iagoyIDAgb2JqCjw8IC9Db3VudCAxIC9LaWRzIFsgMTAgMCBSIF0gL1R5cGUgL1BhZ2VzID4+CmVuZG9iagoyOSAwIG9iago8PCAvQ3JlYXRpb25EYXRlIChEOjIwMjExMDE5MTQzMTA1LTA0JzAwJykKL0NyZWF0b3IgKG1hdHBsb3RsaWIgMy4wLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZykKL1Byb2R1Y2VyIChtYXRwbG90bGliIHBkZiBiYWNrZW5kIDMuMC4yKSA+PgplbmRvYmoKeHJlZgowIDMwCjAwMDAwMDAwMDAgNjU1MzUgZiAKMDAwMDAwMDAxNiAwMDAwMCBuIAowMDAwMDA3NDIxIDAwMDAwIG4gCjAwMDAwMDY0MjcgMDAwMDAgbiAKMDAwMDAwNjQ3MCAwMDAwMCBuIAowMDAwMDA2NTY5IDAwMDAwIG4gCjAwMDAwMDY1OTAgMDAwMDAgbiAKMDAwMDAwNjYxMSAwMDAwMCBuIAowMDAwMDAwMDY1IDAwMDAwIG4gCjAwMDAwMDA0MDAgMDAwMDAgbiAKMDAwMDAwMDIwOCAwMDAwMCBuIAowMDAwMDAxNDE3IDAwMDAwIG4gCjAwMDAwMDY2OTYgMDAwMDAgbiAKMDAwMDAwNjkwOCAwMDAwMCBuIAowMDAwMDA3MjE0IDAwMDAwIG4gCjAwMDAwMDI5MjEgMDAwMDAgbiAKMDAwMDAwMjcyMSAwMDAwMCBuIAowMDAwMDAyMzk4IDAwMDAwIG4gCjAwMDAwMDM5NzIgMDAwMDAgbiAKMDAwMDAwMTQzNyAwMDAwMCBuIAowMDAwMDAxNTk5IDAwMDAwIG4gCjAwMDAwMDE3MTMgMDAwMDAgbiAKMDAwMDAwMjA1MyAwMDAwMCBuIAowMDAwMDA1MzQyIDAwMDAwIG4gCjAwMDAwMDUxMzQgMDAwMDAgbiAKMDAwMDAwNDgxOCAwMDAwMCBuIAowMDAwMDA2Mzk1IDAwMDAwIG4gCjAwMDAwMDQwNDcgMDAwMDAgbiAKMDAwMDAwNDM0NiAwMDAwMCBuIAowMDAwMDA3NDgxIDAwMDAwIG4gCnRyYWlsZXIKPDwgL0luZm8gMjkgMCBSIC9Sb290IDEgMCBSIC9TaXplIDMwID4+CnN0YXJ0eHJlZgo3NjM1CiUlRU9GCg==\n",
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\n",
      "text/plain": [
       "<Figure size 288x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(4,4))\n",
    "for dataset in datasets:\n",
    "    ax.scatter([np.mean(etas['eta'][:,rat-1]) for rat in dataset2rat[dataset]], [np.mean(etas['eta4state'][:,rat-1]) for rat in dataset2rat[dataset]], color='k', marker=dataset2marker[dataset], s=150*ratio_s[dataset])\n",
    "ax.legend(frameon=False)\n",
    "ax.set_xlabel('$\\eta$')\n",
    "ax.set_ylabel('$\\eta_g$')\n",
    "ymin, ymax = ax.get_ylim()\n",
    "ax.plot([0,0.45],[0,0.45],linestyle='--', color='k', linewidth=2)\n",
    "ax.plot([0,0.45],[0,0],linestyle='--', color='k', linewidth=2)\n",
    "ax.set(xlim=[-0.02,0.4],ylim=[-0.02,0.4], xticks=[0,0.2,0.4])\n",
    "ax.spines['bottom'].set_linewidth(1.5)\n",
    "ax.spines['left'].set_linewidth(1.5)\n",
    "ax.yaxis.labelpad = 10\n",
    "ax.tick_params(axis='both', width=1.5, length=5, pad=10)\n",
    "sns.despine()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Correlation of parameters between models"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(0.9869294878571961, 0.0002551409595560176)\n"
     ]
    },
    {
     "data": {
      "application/pdf": 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\n",
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(5,4))\n",
    "for dataset in datasets:\n",
    "    sns.regplot(x='w4', y='etag', data=df[df['dataset']==dataset], color='k', line_kws={'linestyle':'--'}, fit_reg=False, marker=dataset2marker[dataset], scatter_kws={'s':150*ratio_s[dataset]}, label=dataset_labels[dataset])\n",
    "sns.regplot(x='w4', y='etag', data=df, color='k', line_kws={'linestyle':'--'}, scatter=False)\n",
    "    \n",
    "ax.set_xlabel('$w_4$')\n",
    "ax.set_ylabel('$\\eta_g$')\n",
    "ax.spines['bottom'].set_linewidth(1.5)\n",
    "ax.spines['left'].set_linewidth(1.5)\n",
    "ax.tick_params(axis='both', width=1.5, length=5, pad=10)\n",
    "sns.despine()\n",
    "\n",
    "print(pearsonr(df.loc[df['dataset']==dataset, 'w4'], df.loc[df['dataset']==dataset, 'etag']))"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.7.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}