{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python2.7/site-packages/matplotlib/rcsetup.py:342: UserWarning: axes.color_cycle is deprecated.  Use axes.prop_cycle instead. Will be removed in 2.1.0\n",
      "  warnings.warn(\"axes.color_cycle is deprecated.  Use axes.prop_cycle \"\n",
      "/usr/local/lib/python2.7/site-packages/matplotlib/__init__.py:872: UserWarning: axes.color_cycle is deprecated and replaced with axes.prop_cycle; please use the latter.\n",
      "  warnings.warn(self.msg_depr % (key, alt_key))\n"
     ]
    }
   ],
   "source": [
    "# Conditional Histograms for Boreal area of Variables conditioned to VCFF State\n",
    "%matplotlib inline\n",
    "import matplotlib\n",
    "#matplotlib.use('macosx')  # TkAgg Force mpl to use Tk backend\n",
    "import matplotlib.pyplot as plt\n",
    "from mpl_toolkits.basemap import Basemap, shiftgrid\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import datetime\n",
    "import netCDF4\n",
    "import sys\n",
    "import math \n",
    "import matplotlib.patches as mpatches\n",
    "# needs gridspec\n",
    "from matplotlib import gridspec\n",
    "from matplotlib.colors import ListedColormap\n",
    "import palettable \n",
    "from pandas import DataFrame \n",
    "from collections import Counter\n",
    "import pandas as pd\n",
    "\n",
    "\n",
    "dataforr_na_east = np.loadtxt(\"/Users/Beniamino/Documents/OneDrive/MPI-M/iPython_Notebooks/Boreal_Area/boreal_na_east_database_canadianupdate.txt\") # columns=[\"VCFF\", \"MAR\", \"MASM\", \"Tmin\", \"PZI\", \"FF\", \"GDD0\", \"State\", \"Elev\", \"Lon\", \"Lat\"]\n",
    "from Boreal_Variables import bare_na_east_update as bare\n",
    "from Boreal_Variables import savanna_na_east_update as savanna\n",
    "from Boreal_Variables import forest_na_east_update as forest \n",
    "\n",
    "\n",
    "\n",
    "savabmap = ListedColormap(palettable.colorbrewer.diverging.PuOr_5_r.mpl_colors)\n",
    "baremap = ListedColormap(palettable.colorbrewer.diverging.PuOr_5.mpl_colors)\n",
    "# savafmap and foremap are winter and summer\n",
    "\n",
    "sns.set_style(style=\"white\")\n",
    "\n",
    "# conditional histograms sectiondel_ind = []\n",
    "del_ind = []\n",
    "for i in range(len(forest[:,5])):\n",
    "    if forest[i,5]==0: del_ind.append(i)\n",
    "for_with_fire = np.delete(forest[:], del_ind, 0)\n",
    "\n",
    "del_ind = []\n",
    "for i in range(len(bare[:,5])):\n",
    "    if bare[i,5]==0: del_ind.append(i)\n",
    "bar_with_fire = np.delete(bare[:], del_ind, 0)\n",
    "\n",
    "del_ind = []\n",
    "for i in range(len(savanna[:,5])):\n",
    "    if savanna[i,5]==0: del_ind.append(i)\n",
    "sav_with_fire = np.delete(savanna[:], del_ind, 0)\n",
    "\n",
    "del_ind = []\n",
    "for i in range(len(dataforr_na_east[:,5])):\n",
    "    if dataforr_na_east[i,5]==0: del_ind.append(i)\n",
    "data_with_fire = np.delete(dataforr_na_east[:], del_ind, 0)\n",
    "\n",
    "cmapbare = sns.light_palette(\"#7570b3\", n_colors=5, reverse=False, as_cmap=True)\n",
    "cmapsava = sns.light_palette(\"#d95f02\", n_colors=5, reverse=False, as_cmap=True)\n",
    "cmapfore = sns.light_palette(\"#1b9e77\", n_colors=5, reverse=False, as_cmap=True)\n",
    "colbare = '#7570b3'\n",
    "colsava = '#d95f02'\n",
    "colfore = '#1b9e77'\n",
    "\n",
    "columns_2=[\"VCFF [%]\", \"MAR - [\"+r'mm yr$^{-1}$'+\"]\", \"Mean_Spring_SM - [\"+r'mm'+\"]\", \"Mean_Tmin - [\"+r'$^\\circ$C'+\"]\",\\\n",
    "           \"PZI\", \"FF - [\"+r'fires yr$^{-1}$'+\"]\", \"GDD0 - [\"+r'$^\\circ$C yr$^{-1}$'+\"]\", \"PTD\", \"ST\", \"State\",\"Elev\", \"Lon\", \"Lat\" ]\n",
    "columns=[\"VCFF\", \"MAR\", \"Mean_Spring_SM\", \"Mean_Tmin\", \"PZI\", \"FF\", \"GDD0\", \"PTD\", \"ST\", \"State\",\"Elev\", \"Lon\", \"Lat\" ]\n",
    "\n",
    "# create plot with conditional histograms and joint scatterplot\n",
    "def scatter_rug_hist_plot(bare, savanna, forest, dataforr_ea_east, index, index_2):\n",
    "    if index==1:\n",
    "        binBoundaries = np.linspace(np.min(dataforr_ea_east[:,index])+0.01,np.max(dataforr_ea_east[:,index]),51)#np.linspace(0,1000,51)\n",
    "    else:\n",
    "        binBoundaries = np.linspace(np.min(dataforr_ea_east[:,index])+0.01,np.max(dataforr_ea_east[:,index]),51)\n",
    "    \n",
    "    if index_2==1:\n",
    "        binBoundaries2 = np.linspace(np.min(dataforr_ea_east[:,index_2]),np.max(dataforr_ea_east[:,index_2]),51)#np.linspace(0,1000,51)\n",
    "    else:\n",
    "        binBoundaries2 = np.linspace(np.min(dataforr_ea_east[:,index_2]),np.max(dataforr_ea_east[:,index_2]),51)\n",
    "    xmin, ymin = np.min(binBoundaries), np.min(binBoundaries2)\n",
    "    xmax, ymax = np.max(binBoundaries), np.max(binBoundaries2)\n",
    "\n",
    "    xmax, xmin = tuple(np.array([xmax, xmin]) + 0.25*(xmax - xmin)*np.array([1, -1]))\n",
    "    ymax, ymin = tuple(np.array([ymax, ymin]) + 0.25*(ymax - ymin)*np.array([1, -1]))\n",
    "    #Define grid for subplots\n",
    "    gs = gridspec.GridSpec(2, 2, width_ratios=[3, 1], height_ratios = [1, 4])\n",
    "\n",
    "        \n",
    "    #Create scatter plot\n",
    "    fig = plt.figure(figsize=(12,8))\n",
    "    ax = plt.subplot(gs[1, 0],frameon = False,xticks=[],yticks=[], xlim = (xmin, xmax), ylim = (ymin, ymax))\n",
    "    \n",
    "    cax = ax.scatter(bare[:,index], bare[:,index_2], alpha=.5, color = colbare)\n",
    "    sns.rugplot(bare[:,index], color=colbare, ax=ax, height=0.02, linewidth=0.02)\n",
    "    sns.rugplot(bare[:,index_2], color=colbare,vertical=True, ax=ax, height=0.02, linewidth=0.02);\n",
    "    \n",
    "    cax1 = ax.scatter(savanna[:,index], savanna[:,index_2], color = colsava, alpha=.5)\n",
    "    sns.rugplot(savanna[:,index], color=colsava, ax=ax, height=0.02, linewidth=0.02)\n",
    "    sns.rugplot(savanna[:,index_2], color=colsava,vertical=True, ax=ax, height=0.02, linewidth=0.02);\n",
    "    \n",
    "    cax2 = ax.scatter(forest[:,index], forest[:,index_2], color=colfore, alpha=.5)\n",
    "    sns.rugplot(forest[:,index], color=colfore, ax=ax, height=0.02, linewidth=0.02)\n",
    "    sns.rugplot(forest[:,index_2], color=colfore,vertical=True, ax=ax, height=0.02, linewidth=0.02);\n",
    "    \n",
    "    \n",
    "    \n",
    "    plt.xlabel(columns_2[index])\n",
    "    plt.ylabel(columns_2[index_2])\n",
    "\n",
    "    sns.despine()\n",
    "    #Turn off all axes\n",
    "    #_=ax.axis('off')\n",
    "\n",
    "    #Create Y-marginal (right)\n",
    "    axr = plt.subplot(gs[1, 1], xticks=[], frameon = False,  ylim = (ymin, ymax))\n",
    "    hist_Y = axr.hist([bare[:,index_2], savanna[:,index_2], forest[:,index_2]], label=[\"treeless\", \"open woodland\", \"forest\"],stacked=True,\\\n",
    "             bins=binBoundaries2, alpha=0.8,normed=False, orientation='horizontal', color = [colbare, colsava, colfore])#bare[:,3], color = '#5673E0', orientation = 'horizontal', normed = True)\n",
    "    mi, qua, mid, triqua, ma = 0, (np.min(hist_Y[0])+np.max(hist_Y[0]))/4,(np.min(hist_Y[0])+np.max(hist_Y[0]))/2,(np.min(hist_Y[0])+np.max(hist_Y[0]))/4+(np.min(hist_Y[0])+np.max(hist_Y[0]))/2, np.max(hist_Y[0])\n",
    "    axr.set_xticks([int(mi), int(qua), int(mid), int(triqua), int(ma)])\n",
    "    \n",
    "    #Create X-marginal (top)\n",
    "    axt = plt.subplot(gs[0,0], frameon = False,  yticks = [], xlim = (xmin, xmax))\n",
    "    axt.set_title('Eastern North America '+str(columns[index])+' vs '+str(columns[index_2]))\n",
    "    hist_X = axt.hist([bare[:,index], savanna[:,index], forest[:,index]], label=[\"treeless\", \"open woodland\", \"forest\"],stacked=True,\\\n",
    "             bins=binBoundaries, alpha=0.8,normed=False, color = [colbare, colsava, colfore])#hist(bare[:,1], color = '#5673E0', normed = True)\n",
    "    mi, qua, mid, triqua, ma = 0, (np.min(hist_X[0])+np.max(hist_X[0]))/4,(np.min(hist_X[0])+np.max(hist_X[0]))/2,(np.min(hist_X[0])+np.max(hist_X[0]))/4+(np.min(hist_X[0])+np.max(hist_X[0]))/2, np.max(hist_X[0])\n",
    "    axt.set_yticks([int(mi), int(qua), int(mid), int(triqua), int(ma)])\n",
    "\n",
    "    #Create ax for legend with data that will not appear\n",
    "    axl = plt.subplot(gs[0, 1],frameon = False,  xticks=[],yticks = [], xlim=(xmin-100,xmin-50))\n",
    "    axl.hist([bare[0:2,index], savanna[0:2,index], forest[0:2,index]], label=[\"treeless\", \"open woodland\", \"forest\"],alpha=0.8,\\\n",
    "             normed=True, color = [colbare, colsava, colfore])\n",
    "    leg = axl.legend( loc=\"lower left\", ncol = 1, labels=['Treeless','Open woodland','Forest'])\n",
    "\n",
    "    #plt.savefig('/Users/Beniamino/Documents/OneDrive/MPI-M/My_Papers/First_Paper_First_Draft/Conditional/bor_na_east_joint_scatter_'+str(columns[index])+'_'+str(columns[index_2])+'.pdf',dpi=300, transparent=False)\n",
    "    plt.show()\n",
    "\n",
    "def kde_rug_hist_plot(bare, savanna, forest, dataforr_ea_east, index, index_2, fsize = 16, figsize = (12,8)):\n",
    "    # Define limits and bins for histograms \n",
    "    if index==1:\n",
    "        binBoundaries = np.linspace(np.min(dataforr_ea_east[:,index])+0.01,np.max(dataforr_ea_east[:,index]),51)#np.linspace(0,1000,51)\n",
    "    else:\n",
    "        binBoundaries = np.linspace(np.min(dataforr_ea_east[:,index])+0.01,np.max(dataforr_ea_east[:,index]),51)\n",
    "    \n",
    "    if index_2==1:\n",
    "        binBoundaries2 = np.linspace(np.min(dataforr_ea_east[:,index_2]),np.max(dataforr_ea_east[:,index_2]),51)#np.linspace(0,1000,51)\n",
    "    else:\n",
    "        binBoundaries2 = np.linspace(np.min(dataforr_ea_east[:,index_2]),np.max(dataforr_ea_east[:,index_2]),51)\n",
    "    xmin, ymin = np.min(binBoundaries), np.min(binBoundaries2)\n",
    "    xmax, ymax = np.max(binBoundaries), np.max(binBoundaries2)\n",
    "    xmax, xmin = tuple(np.array([xmax, xmin]) + 0.25*(xmax - xmin)*np.array([1, -1]))\n",
    "    ymax, ymin = tuple(np.array([ymax, ymin]) + 0.25*(ymax - ymin)*np.array([1, -1]))\n",
    "\n",
    "    #Define grid for subplots\n",
    "    gs = gridspec.GridSpec(2, 2, width_ratios=[3, 1], height_ratios = [1, 4])\n",
    "\n",
    "    #Create kdeplot with rugplot\n",
    "\n",
    "    fig = plt.figure(figsize=figsize)\n",
    "    ax = plt.subplot(gs[1, 0],frameon = False,xticks=[],yticks=[], xlim = (xmin, xmax), ylim = (ymin, ymax))\n",
    "    \n",
    "\n",
    "    sns.kdeplot(bare[:,index], bare[:,index_2], ax=ax,cmap=cmapbare, linewidths = 2)\n",
    "    sns.rugplot(bare[:,index], color='#7570b3', ax=ax, height=0.02, linewidth=0.2)\n",
    "    sns.rugplot(bare[:,index_2], color='#7570b3',vertical=True, ax=ax, height=0.02, linewidth=0.2);\n",
    "    \n",
    "    sns.kdeplot(savanna[:,index], savanna[:,index_2], ax=ax,cmap=cmapsava, linewidths = 2)\n",
    "    sns.rugplot(savanna[:,index], color='#d95f02', ax=ax, height=0.02, linewidth=0.2)\n",
    "    sns.rugplot(savanna[:,index_2], color='#d95f02',vertical=True, ax=ax, height=0.02, linewidth=0.2);\n",
    "\n",
    "    sns.kdeplot(forest[:,index], forest[:,index_2], ax=ax,cmap=cmapfore, linewidths = 2)\n",
    "    sns.rugplot(forest[:,index], color='#1b9e77', ax=ax, height=0.02, linewidth=0.2)\n",
    "    sns.rugplot(forest[:,index_2], color='#1b9e77',vertical=True, ax=ax, height=0.02, linewidth=0.2);\n",
    "    \n",
    "    plt.xlabel(columns_2[index], fontsize=fsize)\n",
    "    plt.ylabel(columns_2[index_2], fontsize=fsize)\n",
    "\n",
    "    sns.despine()\n",
    "#Turn off all axes\n",
    "#_=ax.axis('off')\n",
    "\n",
    "#Create Y-marginal (right)\n",
    "    axr = plt.subplot(gs[1, 1], xticks=[], frameon = False,  ylim = (ymin, ymax))\n",
    "    hist_Y = axr.hist([bare[:,index_2], savanna[:,index_2], forest[:,index_2]], label=[\"treeless\", \"open woodland\", \"forest\"],\\\n",
    "             stacked=True,bins=binBoundaries2, alpha=0.8,normed=False, orientation='horizontal', color = ['#7570b3', '#d95f02', '#1b9e77'])#bare[:,3], color = '#5673E0', orientation = 'horizontal', normed = True)\n",
    "    mi, qua, mid, triqua, ma = 0, (np.min(hist_Y[0])+np.max(hist_Y[0]))/4,(np.min(hist_Y[0])+np.max(hist_Y[0]))/2,(np.min(hist_Y[0])+np.max(hist_Y[0]))/4+(np.min(hist_Y[0])+np.max(hist_Y[0]))/2, np.max(hist_Y[0])\n",
    "    axr.set_xticks([int(mi), int(qua), int(mid), int(triqua), int(ma)])\n",
    "    plt.xticks(fontsize = fsize)\n",
    "    plt.yticks(fontsize = fsize)\n",
    "\n",
    "\n",
    "#Create X-marginal (top)\n",
    "    axt = plt.subplot(gs[0,0], frameon = False, yticks=[], xlim = (xmin, xmax)) #,  yticks = []\n",
    "    axt.set_title('Eastern North America '+str(columns[index])+' vs '+str(columns[index_2]), fontsize=fsize)\n",
    "    hist_X = axt.hist([bare[:,index], savanna[:,index], forest[:,index]], label=[\"treeless\", \"open woodland\", \"forest\"],\\\n",
    "             stacked=True,bins=binBoundaries, alpha=0.8,normed=False, color = ['#7570b3', '#d95f02', '#1b9e77'])#hist(bare[:,1], color = '#5673E0', normed = True)\n",
    "    mi, qua, mid, triqua, ma = 0, (np.min(hist_X[0])+np.max(hist_X[0]))/4,(np.min(hist_X[0])+np.max(hist_X[0]))/2,(np.min(hist_X[0])+np.max(hist_X[0]))/4+(np.min(hist_X[0])+np.max(hist_X[0]))/2, np.max(hist_X[0])\n",
    "    axt.set_yticks([int(mi), int(qua), int(mid), int(triqua), int(ma)])\n",
    "    plt.xticks(fontsize = fsize)\n",
    "    plt.yticks(fontsize = fsize)\n",
    "\n",
    "#Create ax for legend with data that will not appear\n",
    "\n",
    "    axl = plt.subplot(gs[0, 1],frameon = False,  xticks=[],yticks = [], xlim=(xmin-100,xmin-50))\n",
    "    axl.hist([bare[0:2,index], savanna[0:2,index], forest[0:2,index]], label=[\"grassland\", \"savanna\", \"forest\"],\\\n",
    "             alpha=0.8,normed=True, color = ['#7570b3', '#d95f02', '#1b9e77'])\n",
    "    leg = axl.legend( loc=\"lower left\", ncol = 1, labels=['Treeless','Open woodland','Forest'] , fontsize=fsize)\n",
    "\n",
    "\n",
    "\n",
    "    #plt.savefig('/Users/Beniamino/Documents/OneDrive/MPI-M/My_Papers/First_Paper_First_Draft/Conditional/bor_na_east_joint_kde_'+str(columns[index])+'_'+str(columns[index_2])+'.pdf',\\\n",
    "    #            dpi=300, transparent=True)\n",
    "    plt.show()\n",
    "    return\n",
    "    #plt.close()\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
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   "outputs": [
    {
     "data": {
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JiYmhSZMmGuvOnz9PcHAwnTp1wtLSUu56snTpUq1uatevXwdef4tj5cqVefjw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\nSweltiucNISGxt2tPt/5/4hObs/+3/v/HH1le/b/7vlz7T2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NDcOGDWPGjBn86Ec/avUG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sA6mgRKuPvzubG8Eb6hhftCkqSrweJd6IYk4sCUuniNO7G3fgAPKIZF8RiqPVzEGtnYMSqUII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\naqQeJwpRi7j+uObEQ1t76soHAYZ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phJCmZ6sujdW+L9uVfF+Ar6AbKkYQKmeaK5ODF0fK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ZPJEAgEDmLUQoijRYIHIYQQ4lPsnnvuOeDnvP/++9x22220t7dzzTXX8L3vfa/X9vz8fIAB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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10eaedf10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "kde_rug_hist_plot(bare,savanna,forest,dataforr_na_east,2,3, fsize = 20, figsize = (12,8))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "kde_rug_hist_plot(bar_with_fire,sav_with_fire,for_with_fire,data_with_fire,3,5)\n"
   ]
  }
 ],
 "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": 0
}
