{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Plotting Wind Properties\n",
    "As described under [Models](../output/model.rst), SIROCCO saves wind properties in binary wind_save files. This notebook explains how to read and plot wind variables for the ```cv_standard``` file found in the examples. Before running the python commands, you need to run the model from the command line. I suggest running the following commands, after you have compiled python:\n",
    "\n",
    "    mkdir cv_test\n",
    "    cd cv_test\n",
    "    cp $SIROCCO/examples/basic/cv_standard.pf .\n",
    "    sirocco cv_standard </code>\n",
    "\n",
    "The model will take about 5 minutes to run on a single core. It will not converge, but will give us a model to use as an example. You should then run ```windsave2table``` on the output\n",
    "\n",
    "    windsave2table cv_standard\n",
    "\n",
    "which will create a series of ascii files containing key variables in the wind cells. We will use these ascii files for our plots. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Making wind plots using PySi\n",
    "\n",
    "We will start by demonstrating how to use PySi to plot data from the wind files. In particular we will plot some key variables in the wind, followed by some ion fractions. \n",
    "\n",
    "PySi works by setting up a ```Wind``` class which reads in and stores all the useful data and attributes from the model. This class can be used to inspect data or to plot it directly. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pysi \n",
    "from pysi.wind import Wind\n",
    "root = \"cv_standard\"\n",
    "directory = \"cv_test/\"\n",
    "wind = Wind(root = root, directory = directory)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The data can be plotted easily using the ```plot_parameter``` method. This method returns Figure and Axes objects so the plot can be modified easily. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = wind.plot_parameter(\"t_e\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot = wind.plot_parameter(\"t_e\", \"linlin\")\n",
    "plt.xlim(0,2e11)\n",
    "_ = plt.ylim(0,2e11)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The ```get_windsave_descriptions``` method in the wind class comes provides a handy guide to the main columns in the .master.txt file, which can be plotted using the above methods, or accessed directly as, e.g., ```wind[\"ne\"]```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "x          --  left-hand lower cell corner x-coordinate, cm\n",
      "z          --  left-hand lower cell corner z-coordinate, cm\n",
      "xcen       --  cell centre x-coordinate, cm\n",
      "zcen       --  cell centre z-coordinate, cm\n",
      "i          --  cell index (column)\n",
      "j          --  cell index (row)\n",
      "inwind     --  is the cell in wind (0), partially in wind (1) or out of wind (<0)\n",
      "converge   --  how many convergence criteria is the cell failing?\n",
      "v_x        --  x-velocity, cm/s\n",
      "v_y        --  y-velocity, cm/s\n",
      "v_z        --  z-velocity, cm/s\n",
      "vol        --  volume in cm^3\n",
      "rho        --  density in g/cm^3\n",
      "ne         --  electron density in cm^-3\n",
      "t_e        --  electron temperature in K\n",
      "t_r        --  radiation temperature in K\n",
      "h1         --  H1 ion fraction\n",
      "he2        --  He2 ion fraction\n",
      "c4         --  C4 ion fraction\n",
      "n5         --  N5 ion fraction\n",
      "o6         --  O6 ion fraction\n",
      "dmo_dt_x   --  momentum rate, x-direction\n",
      "dmo_dt_y   --  momentum rate, y-direction\n",
      "dmo_dt_z   --  momentum rate, z-direction\n",
      "ip         --  U ionization parameter\n",
      "xi         --  xi ionization parameter\n",
      "ntot       --  total photons passing through cell\n",
      "nrad       --  total wind photons produced in cell\n",
      "nioniz     --  total ionizing photons passing through cell\n",
      "None\n"
     ]
    }
   ],
   "source": [
    "print (wind.get_windsave_descriptions())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can also use the multiplot command to generate multiple plots for specified wind parameters. \n",
    "This method creates subplots to visualize the specified wind parameters using either 1D or 2D \n",
    "representation based on the coordinate system."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 8 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = wind.multiplot( (\"ne\", \"t_e\", \"v_z\", \"ntot\") , \"loglog\", nrows = 2, ncols = 2)\n",
    "fig.tight_layout(pad=0.05)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can also check all the possible things to plot, some of which are intuitive and some of which aren't! "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "dict_keys(['x', 'z', 'xcen', 'zcen', 'i', 'j', 'inwind', 'converge', 'v_x', 'v_y', 'v_z', 'vol', 'rho', 'ne', 't_e', 't_r', 'h1', 'he2', 'c4', 'n5', 'o6', 'dmo_dt_x', 'dmo_dt_y', 'dmo_dt_z', 'ip', 'xi', 'ntot', 'nrad', 'nioniz', 'w', 'ave_freq', 'J', 'J_direct', 'J_scatt', 'lum_tot', 'heat_tot', 'heat_comp', 'heat_line', 'heat_ff', 'heat_phot', 'heat_auge', 'cool_tot', 'cool_comp', 'lum_lines', 'cool_dr', 'lum_ff', 'lum_rr', 'cool_rr', 'cool_adia', 'heat_shoc', 'ht_ln_mac', 'ht_ph_mac', 'dv_x_dx', 'dv_y_dx', 'dv_z_dx', 'dv_x_dy', 'dv_y_dy', 'dv_z_dy', 'dv_x_dz', 'dv_y_dz', 'dv_z_dz', 'div_v', 'dvds_max', 'gamma', 'dfudge', 't_e_old', 'dt_e', 'dt_e_old', 't_r_old', 'heat_tot_', 'gain', 'macro_bf_', 'H_i01_frac', 'H_i02_frac', 'He_i01_frac', 'He_i02_frac', 'He_i03_frac', 'C_i01_frac', 'C_i02_frac', 'C_i03_frac', 'C_i04_frac', 'C_i05_frac', 'C_i06_frac', 'C_i07_frac', 'N_i01_frac', 'N_i02_frac', 'N_i03_frac', 'N_i04_frac', 'N_i05_frac', 'N_i06_frac', 'N_i07_frac', 'N_i08_frac', 'O_i01_frac', 'O_i02_frac', 'O_i03_frac', 'O_i04_frac', 'O_i05_frac', 'O_i06_frac', 'O_i07_frac', 'O_i08_frac', 'O_i09_frac', 'Na_i01_frac', 'Na_i02_frac', 'Na_i03_frac', 'Na_i04_frac', 'Na_i05_frac', 'Na_i06_frac', 'Na_i07_frac', 'Na_i08_frac', 'Na_i09_frac', 'Na_i10_frac', 'Na_i11_frac', 'Na_i12_frac', 'Si_i01_frac', 'Si_i02_frac', 'Si_i03_frac', 'Si_i04_frac', 'Si_i05_frac', 'Si_i06_frac', 'Si_i07_frac', 'Si_i08_frac', 'Si_i09_frac', 'Si_i10_frac', 'Si_i11_frac', 'Si_i12_frac', 'Si_i13_frac', 'Si_i14_frac', 'Si_i15_frac', 'Ca_i01_frac', 'Ca_i02_frac', 'Ca_i03_frac', 'Ca_i04_frac', 'Ca_i05_frac', 'Ca_i06_frac', 'Ca_i07_frac', 'Ca_i08_frac', 'Ca_i09_frac', 'Ca_i10_frac', 'Ca_i11_frac', 'Ca_i12_frac', 'Ca_i13_frac', 'Ca_i14_frac', 'Ca_i15_frac', 'Ca_i16_frac', 'Ca_i17_frac', 'Ca_i18_frac', 'Ca_i19_frac', 'Ca_i20_frac', 'Ca_i21_frac', 'Fe_i01_frac', 'Fe_i02_frac', 'Fe_i03_frac', 'Fe_i04_frac', 'Fe_i05_frac', 'Fe_i06_frac', 'Fe_i07_frac', 'Fe_i08_frac', 'Fe_i09_frac', 'Fe_i10_frac', 'Fe_i11_frac', 'Fe_i12_frac', 'Fe_i13_frac', 'Fe_i14_frac', 'Fe_i15_frac', 'Fe_i16_frac', 'Fe_i17_frac', 'Fe_i18_frac', 'Fe_i19_frac', 'Fe_i20_frac', 'Fe_i21_frac', 'Fe_i22_frac', 'Fe_i23_frac', 'Fe_i24_frac', 'Fe_i25_frac', 'Fe_i26_frac', 'Fe_i27_frac', 'spec_freq', 'spec_flux', 'model_freq', 'model_flux', 'v_l', 'v_rot', 'v_r'])\n"
     ]
    }
   ],
   "source": [
    "print (wind.things_read_in)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plotting ions using PySi \n",
    "\n",
    "PySi also allows one to plot ion fractions or densities (fractions by default), which are accessed through strings like ```Fe_i01_frac```, using astronomical notation for the ion stage. An example multiplot of the first six ionic stages of Carbon would be as follows. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x1000 with 12 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ions_to_plot = [\"C_i{:02d}_frac\".format(i+1) for i in range(6)] \n",
    "fig, ax = wind.multiplot(ions_to_plot, \"loglog\", nrows = 3, ncols = 2, figsize=(8,10))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "All the ions in the simulation can be viewed using the ```ions_read_in``` list. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['H_i01_frac', 'H_i02_frac', 'He_i01_frac', 'He_i02_frac', 'He_i03_frac', 'C_i01_frac', 'C_i02_frac', 'C_i03_frac', 'C_i04_frac', 'C_i05_frac', 'C_i06_frac', 'C_i07_frac', 'N_i01_frac', 'N_i02_frac', 'N_i03_frac', 'N_i04_frac', 'N_i05_frac', 'N_i06_frac', 'N_i07_frac', 'N_i08_frac', 'O_i01_frac', 'O_i02_frac', 'O_i03_frac', 'O_i04_frac', 'O_i05_frac', 'O_i06_frac', 'O_i07_frac', 'O_i08_frac', 'O_i09_frac', 'Na_i01_frac', 'Na_i02_frac', 'Na_i03_frac', 'Na_i04_frac', 'Na_i05_frac', 'Na_i06_frac', 'Na_i07_frac', 'Na_i08_frac', 'Na_i09_frac', 'Na_i10_frac', 'Na_i11_frac', 'Na_i12_frac', 'Si_i01_frac', 'Si_i02_frac', 'Si_i03_frac', 'Si_i04_frac', 'Si_i05_frac', 'Si_i06_frac', 'Si_i07_frac', 'Si_i08_frac', 'Si_i09_frac', 'Si_i10_frac', 'Si_i11_frac', 'Si_i12_frac', 'Si_i13_frac', 'Si_i14_frac', 'Si_i15_frac', 'Ca_i01_frac', 'Ca_i02_frac', 'Ca_i03_frac', 'Ca_i04_frac', 'Ca_i05_frac', 'Ca_i06_frac', 'Ca_i07_frac', 'Ca_i08_frac', 'Ca_i09_frac', 'Ca_i10_frac', 'Ca_i11_frac', 'Ca_i12_frac', 'Ca_i13_frac', 'Ca_i14_frac', 'Ca_i15_frac', 'Ca_i16_frac', 'Ca_i17_frac', 'Ca_i18_frac', 'Ca_i19_frac', 'Ca_i20_frac', 'Ca_i21_frac', 'Fe_i01_frac', 'Fe_i02_frac', 'Fe_i03_frac', 'Fe_i04_frac', 'Fe_i05_frac', 'Fe_i06_frac', 'Fe_i07_frac', 'Fe_i08_frac', 'Fe_i09_frac', 'Fe_i10_frac', 'Fe_i11_frac', 'Fe_i12_frac', 'Fe_i13_frac', 'Fe_i14_frac', 'Fe_i15_frac', 'Fe_i16_frac', 'Fe_i17_frac', 'Fe_i18_frac', 'Fe_i19_frac', 'Fe_i20_frac', 'Fe_i21_frac', 'Fe_i22_frac', 'Fe_i23_frac', 'Fe_i24_frac', 'Fe_i25_frac', 'Fe_i26_frac', 'Fe_i27_frac']\n"
     ]
    }
   ],
   "source": [
    "print (wind.ions_read_in)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## More direct data access\n",
    "\n",
    "We recommend using PySi where possible. You may, however, wish to get more direct access to the data, which can be done easily by reading in the ```cv_standard.master.txt``` file, for example using ```astropy```. In the next code block, we read in the data file and print out the columns."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['x', 'z', 'xcen', 'zcen', 'i', 'j', 'inwind', 'converge', 'v_x', 'v_y', 'v_z', 'vol', 'rho', 'ne', 't_e', 't_r', 'h1', 'he2', 'c4', 'n5', 'o6', 'dmo_dt_x', 'dmo_dt_y', 'dmo_dt_z', 'ip', 'xi', 'ntot', 'nrad', 'nioniz']\n"
     ]
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import astropy.io.ascii as io\n",
    "\n",
    "fname = f\"{directory}{root}.master.txt\"\n",
    "data = io.read(fname)\n",
    "\n",
    "print (data.colnames)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "```py_plot_util```, found in the ```$SIROCCO/py_progs/``` directory, also contains some routines for reshaping and masking arrays and so on. One of the most useful for plotting is the ```wind_to_masked``` function which turns the raw 1D flattened data into a masked 2D array with the right shape which can be easily used with ```pcolormesh``` and so on. Here's an example plot of the electron density in the model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/matthewsj/.mpi_temp/ipykernel_40675/3684827325.py:3: RuntimeWarning: divide by zero encountered in log10\n",
      "  plt.pcolormesh(x,z, np.log10(ne))\n"
     ]
    },
    {
     "data": {
      "image/png": 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kAbPLTXeW/M0vndtBF0glSR9AAADgZamagfDm2hAAAFLE2QDCzmHqfG/OPnXqlL72ta/p+uuv18SJE1VQUKC7775bhw4dMmqDAAIAABclIoA435uz33//fe3bt08PPfSQ9u3bpxdeeEEHDhzQvHnzjNpgCAMAgBRzvjdn5+Tk6OWXXx5U9sQTT6iiokLvvPOOioqKRtVG0gcQrMIAAHiZJXtLMc9unBAKhQaVO/lSyZ6eHvl8Pl1yySWjrpP0Qxh+v19tbW1qbm5OdFcAABjCqSGMwsJC5eTkRI/6+npH+nfy5El97Wtf0+c//3llZ2ePul7SZyAAABgLOjs7B/2CdyL7cOrUKd1xxx2yLEtPPvmkUV0CCAAAXOTUMs7s7GyjDMGFnA0e3n77bf3mN78xvjcBBAAALvLiPhBng4f/+q//0s6dOzVlyhTjexBAAACQYs735uzLLrtMt99+u/bt26dt27YpHA6rq6tLkpSbm6uMjIxRtZH0AQSrMACpdOljxnVMt6ZOi+F/MZ/p1tQx/KHli5z/5X4f9bvND5o3AtiQiAzE+d6cvWrVKv385z+XJJWVlQ2qt3PnTlVWVo6qjaQPIHgXBgDAyyzLJ8tGABFL3Qu9OftCb9UejaRfxgkAAOIv6TMQAAB4WUQ+WxtJ2anrJgIIAABc5MVVGE4ggAAAwEWJmAMRD8yBAAAAxpI+A8EyTgCAl6XqEEbSZyB4mRYAwMvODmHYObwo6QMIAAAQf0k/hAEAgJdZNocwvJqBIIAAPKhkmdnW1L4s8zZ8htOGLNNtqSWlGf7ci2W77D0//Yp5JSCOLEl2Nn60v2ekOxjCAAAAxshAAADgooh88rETJQAAMMFGUgAAAB9K+gwEG0kBALwsYvnkYyMp72EjKQCAl1mW/cOLkj4DAQCAlzEHAgAA4ENkIAAAcFGqZiAIIAAAcFGqTqIkgABcds03zballiTfBMPrY1iElHbKvI6p17/7v91vBEBCEEAAAOAiuyspWIUBAMAYdCaAsDMHwsHOOIhVGAAAwBgZCAAAXMQqDAAAYMz68LBT34uSfggjGAyquLhY5eXlie4KAABjRtIHELwLAwDgZWeHMOwcXsQQBgAAbkrRMQwCCAAA3GQ3i0AGAkgNV61da1bBcFdJSfKFzX5gxGNXyf9Xz66SAP6MAAIAABexEyUAADCWqvtAJP0qDAAAEH9kIAAAcJPlszcR0qMZCAIIAABclKpzIBjCAAAAxshAAADgJjaSAgAApliFAQAA8CEyEAAAuM2jwxB2EEBgTJv+/W+bVzLcmtp0W2pJ8p02rmHcxptfZ2tqIB4YwvCoYDCo4uJilZeXJ7orAAAMZTlwGGpsbNTcuXNVUFAgn8+nrVu3Dvr8hRde0C233KIpU6bI5/OptbXVuI2kDyD8fr/a2trU3Nyc6K4AAOAJfX19Ki0tVTAYHPHzm266SY8++mjMbTCEAQCAq3yKZZhxcH0ztbW1qq2tHfHzRYsWSZLeeuutWDtFAAEAgKsc2gciFAoNKs7MzFRmZqaNG9uT9EMYAACMBYWFhcrJyYke9fX1Ce0PGQgAANzkUAais7NT2dnZ0eJEZh8kAggAANzl0Ns4s7OzBwUQicYQBgAAMEYGAgAAFyXidd69vb1qb2+Pnnd0dKi1tVW5ubkqKirS8ePH9c477+jQoUOSpAMHDkiS8vPzlZ+fP6o2yEAAAOCmBGwktXfvXs2YMUMzZsyQJAUCAc2YMUMrVqyQJP385z/XjBkzdOutt0qS7rrrLs2YMUPr168fdRtkIJAyrnw+hhnJE2IYl4yY1bFOxRKnm9VpfyAQQxsAUlVlZaWs86Qu7rnnHt1zzz222iCAAADATQ5NovQaAggAAFzks84cdup7EQEEAABucmgfCK9hEiUAADBGBgIAADcxBwIAABhjCAMAAOAMMhAAALgpRTMQBBAAALgpRQMIhjAAAIAxMhDwrP+x5WGj6zMuMp+pHAmbx9Dh02Z1DHe+liR13PegeSUA3pSiqzASkoFYuHChJk+erNtvv31Q+bZt23TNNdfo6quv1g9/+MNEdA0AAEed3YnSzuFFCQkg7r//fm3cuHFQ2enTpxUIBPSb3/xGv//977VmzRr96U9/SkT3AADABSQkgKisrNSkSZMGlTU1NamkpETTpk3TxRdfrNraWr300kuJ6B4AAM5JwOu848E4gGhsbNTcuXNVUFAgn8+nrVu3DrkmGAxq+vTpysrK0uzZs9XU1HTB+x46dEjTpk2Lnk+bNk0HDx407R4AAIgD4wCir69PpaWlCgaDw36+adMmBQIBrVy5Uvv27VNpaalqamp05MgR250FACDZ+GRzDkSiv8AIjAOI2tpaPfLII1q4cOGwn69du1b33XefFi9erOLiYq1fv14XXXSRnnnmmfPet6CgYFDG4eDBgyooKBjx+v7+foVCoUEHAACID0fnQAwMDKilpUXV1dV/biAtTdXV1dqzZ89561ZUVOgPf/iDDh48qN7eXv36179WTU3NiNfX19crJycnehQWFjr2PQAAcMzZZZx2Dg9yNIA4duyYwuGw8vLyBpXn5eWpq6srel5dXa3Pfe5z+tWvfqXLL79ce/bs0bhx4/Sd73xHVVVVKisr01e+8hVNmTJlxLaWL1+unp6e6NHZ2enkVwEAwBkpOokyIRtJ7dixY9jyefPmad68eaO6R2ZmpjIzM53sFgAAGCVHA4ipU6cqPT1d3d3dg8q7u7uVn5/vZFMAACSHFH0XhqMBREZGhmbOnKmGhgYtWLBAkhSJRNTQ0KAlS5Y42VRUMBhUMBhUOBx25f5wxo0vLjeuM2mC2bhfOIZxwoFT5v8L9KeZ1TkV9ub4JYD4sLubpFd3ojT+6dnb26v29vboeUdHh1pbW5Wbm6uioiIFAgHV1dVp1qxZqqio0Lp169TX16fFixc72vGz/H6//H6/QqGQcnJyXGkDAAAMZhxA7N27V1VVVdHzQCAgSaqrq9OGDRt055136ujRo1qxYoW6urpUVlam7du3D5lYCQDAmMAQxhmVlZWyrPN/myVLlrg2ZAEAQFJJ0QAiIe/CAAAAyS3pA4hgMKji4mKVl5cnuisAAAzB67w9yu/3q62tTc3NzYnuCgAAQ6XoTpQJ2UgKAIAxgzkQAAAAZ5CBAADARWwk5VHsRJkcJk9437jO6YhZguxUON24jfdj+D8zYjge+eb/fMi4DQAphCEMb2ISJQAA8Zf0GQgAADzN7lJMj2YgCCAAAHATQxgAAABnkIEAAMBNZCC8ia2sAQBexlbWHsUqDAAA4i/pAwgAABB/zIEAAMBNKToHggACAAAXsZU1cI66pi8aXT810/x1tAMRs8fz/dPjjduIRdNf/5+4tAMAsWpsbNSaNWvU0tKiw4cPa8uWLVqwYEH0c8uytHLlSj311FM6ceKE/uqv/kpPPvmkrr766lG3wRwIAADcZtk4YtDX16fS0lIFg8FhP//Wt76l733ve1q/fr1ee+01TZw4UTU1NTp58uSo2yADAQCAmxyaAxEKhQYVZ2ZmKjMzc9gqtbW1qq2tHf52lqV169bp61//uubPny9J2rhxo/Ly8rR161bdddddo+pW0mcg2AcCADAWFBYWKicnJ3rU19fHdJ+Ojg51dXWpuro6WpaTk6PZs2drz549o75P0mcg/H6//H6/QqGQcnJyEt0dAAAGcWoSZWdnp7Kzs6PlI2UfLqSrq0uSlJeXN6g8Ly8v+tloJH0AAQCApzk0hJGdnT0ogEi0pB/CAAAAo5efny9J6u7uHlTe3d0d/Ww0CCAAAHCR196FceWVVyo/P18NDQ3RslAopNdee01z5swZ9X0YwgAAwE0J2Imyt7dX7e3t0fOOjg61trYqNzdXRUVFeuCBB/TII4/o6quv1pVXXqmHHnpIBQUFg/aKuBACCAAAUszevXtVVVUVPQ8EApKkuro6bdiwQV/96lfV19enL33pSzpx4oRuuukmbd++XVlZWaNugwACAAA3JSADUVlZKcsauaLP59M3vvENfeMb34i5WwQQiMnHMnuNrj8VMZ9u02+4lfW4tNFHzmf94lOPG9cBABOp+i6MpJ9EyUZSAABPs7ONtd3shYuSPoDw+/1qa2tTc3NzorsCAMCYwRAGAABuSsAciHgggAAAwEXMgQAAAPgQGQgAANzEEAYAADDFEAYAAMCHyEAAAOAmhjAAAIAxAgikqm+11RrXuXS82fUnI4YVJL0fyTCuAwCIj6SfA8FW1gAAL/M5cHhR0gcQbGUNAPC0FH0XBkMYAAC4iGWcAAAAHyIDAQCAm1iFAQAAYuLRIMAOhjAAAIAxMhAAALgoVSdREkAAAOCmFJ0DwRAGAAAwRgYCyhvfY1znlJVudH0sW1mPj2QZXf9/b/iZcRsA4DaGMAAAgDmGMAAAAM4gAwEAgIsYwgAAAOZSdAiDAAIAADelaACR9HMggsGgiouLVV5enuiuAAAwZiR9AOH3+9XW1qbm5uZEdwUAgCHOzoGwc3gRQxgAALiJIQwAAIAzyEBAuem9xnWMd6JMyzBuY3w4bFwHALzGZ1nyWbGnEezUdRMBBAAAbmIIAwAA4AwyEAAAuIidKAEAgDmGMAAAAM4gAwEAgIsYwgAAAOZSdAiDAAIAABelagaCORAAAKSY9957Tw888ICuuOIKTZgwQZ/85Ccdf2cUAQQAAG6yHDgM/f3f/71efvllPffcc3rjjTd0yy23qLq6WgcPHrT/fT7EEEYK2v32Xxhdf0maeRwZMYw9T1r9xm2kK2JcBwC8KJ7DEB988IH+7d/+Tf/+7/+uT3/605KkVatW6Re/+IWefPJJPfLII460QwABAEASCIVCg84zMzOVmZk55LrTp08rHA4rKytrUPmECRP0yiuvONYfhjAAAHCTZdk/JBUWFionJyd61NfXD9vcpEmTNGfOHH3zm9/UoUOHFA6H9fzzz2vPnj06fPiwY1+LDAQAAC5yahVGZ2ensrOzo+XDZR/Oeu6553Tvvfdq2rRpSk9P11/+5V/q85//vFpaWmLvyEeQgQAAIAlkZ2cPOs4XQFx11VX6j//4D/X29qqzs1NNTU06deqU/uIvzObInQ8BBAAAbkrAKoyzJk6cqMsuu0zvvvuuXnzxRc2fPz/2m30EQxgAALjIFzlz2Klv6sUXX5RlWbrmmmvU3t6uBx98UNdee60WL14ce0c+ggwEAAAppqenR36/X9dee63uvvtu3XTTTXrxxRc1fvx4x9rwVADx7W9/WyUlJbruuuv0/PPPJ7o7AADYl4AhjDvuuEP//d//rf7+fh0+fFhPPPGEcnJy7H+Xc3hmCOONN97QT37yE7W0tMiyLFVVVelv//ZvdckllyS6awAAxIx3Ybjsj3/8o+bMmaOsrCxNmDBBpaWl2r59e6K7BQCAPQ7tA+E1jmUgGhsbtWbNGrW0tOjw4cPasmWLFixYMOiaYDCoNWvWqKurS6WlpXr88cdVUVEhSbruuuv08MMP68SJE7IsS7t27dInPvEJp7o3plySZrZtdFg+4zYillmdk5Znkl0AAAc4loHo6+tTaWmpgsHgsJ9v2rRJgUBAK1eu1L59+1RaWqqamhodOXJEklRcXKylS5fq5ptv1m233aYbb7xR6enpI7bX39+vUCg06AAAwGvODmHYObzIsQCitrZWjzzyiBYuXDjs52vXrtV9992nxYsXq7i4WOvXr9dFF12kZ555JnrNl7/8Ze3bt087d+7U+PHjdfXVV4/YXn19/aAtPQsLC536KgAAOCeB+0C4KS5zIAYGBtTS0qLq6uo/N5yWpurqau3ZsydadjYbceDAATU1NammpmbEey5fvlw9PT3Ro7Oz070vAAAABonLwPSxY8cUDoeVl5c3qDwvL0/79++Pns+fP189PT2aOHGifvSjH2ncuJG7N9JbyAAA8JJUXYXhqZlt52YjAABICXZXUnh0FUZchjCmTp2q9PR0dXd3Dyrv7u5Wfn5+PLoAAAAcFJcAIiMjQzNnzlRDQ0O0LBKJqKGhQXPmzLF172AwqOLiYpWXl9vtJgAAjkvVVRiODWH09vaqvb09et7R0aHW1lbl5uaqqKhIgUBAdXV1mjVrlioqKrRu3Tr19fXZfrGH3++X3+9XKBRyfJtOAABss7uSItUDiL1796qqqip6HggEJEl1dXXasGGD7rzzTh09elQrVqxQV1eXysrKtH379iETKwEASCVMoryAyspKWReY6LFkyRItWbLEqSYBAECCeGoVRiyCwaCCwaDC4XCiu+IZk9LMXh4fjiG6jRjufj3eMn+h/ewrOozrAIDnRKwzh536HuSZl2nFyu/3q62tTc3NzYnuCgAAQ7ETJQAAwBlJP4QBAICX+WRzEqVjPXEWAQQAAG5iJ0oAAIAzkj6AYCdKAICXpepOlEkfQLAKAwDgaazCAAAAOINJlAAAuMhnWfLZmAhpp66bCCAAAHBT5MPDTn0PIoAAAMBFqZqBSPo5EKzCAAAg/pI+gGAVBgDA01J0FQZDGAAAuImdKAEAAM4gAwEAgIvs7ibp1Z0oCSAAAHATQxgAAABnJH0AwTJOAICX+SL2Dy9K+gCCZZwAAE87O4Rh5/CgpA8gAABA/DGJEgAAN9ndDMqbCQgCCAAA3JSq78IggAAAwE0s4wQAADiDDAQAAG6yJNlZiunNBAQBBAAAbkrVORBJP4TBRlIAAMRf0gcQbCQFAPA0SzY3kjJrLhwO66GHHtKVV16pCRMm6KqrrtI3v/lNWQ5nMhjCAADATXFehfHoo4/qySef1LPPPquSkhLt3btXixcvVk5OjpYuXRp7Pz6CAAIAgBSye/duzZ8/X7feeqskafr06frpT3+qpqYmR9tJ+iEMAAA8LeLAISkUCg06+vv7h23uk5/8pBoaGvTmm29Kkl5//XW98sorqq2tdfRrkYFIQdPSJ7neRsRwTdIpK+xSTwDA25xahVFYWDiofOXKlVq1atWQ65ctW6ZQKKRrr71W6enpCofDWr16tb7whS/E3IfhEEAAAJAEOjs7lZ2dHT3PzMwc9rp//dd/1Y9//GP95Cc/UUlJiVpbW/XAAw+ooKBAdXV1jvWHAAIAADc5NIkyOzt7UAAxkgcffFDLli3TXXfdJUm6/vrr9fbbb6u+vp4AAgCApBHnVRjvv/++0tIGT3FMT09XJGJnO8yhCCAAAHBTnAOIuXPnavXq1SoqKlJJSYl+//vfa+3atbr33ntj78MwCCAAAEghjz/+uB566CH94z/+o44cOaKCggJ9+ctf1ooVKxxthwACAAA3RST5bNY3MGnSJK1bt07r1q2z0eiFJf0+ELwLAwDgZWeXcdo5vCjpAwjehQEAQPwxhAEAgJviPIkyXgggAABwU8SSfDaCgIg3A4ikH8IAAADxRwYCAAA3MYQBAADM2Qwg5M0AgiEMAABgjAwEAABuYggDAAAYi1iyNQzh0VUYBBAAALjJipw57NT3IOZAAAAAY2QgAABwE3MgAACAsRSdA8EQBgAAMEYGAgAAN6XoEEbSZyCCwaCKi4tVXl6e6K4AADCUpT8HETEdif4Cw0v6AMLv96utrU3Nzc2J7goAAGMGQxgAALgpRYcwCCAAAHBTJCLJxmZQETaSAgAAKYIMBAAAbmIIAwAAGCOAAAAAxtiJEgAA4AwyEAAAuMiyIrJsvJLbTl03EUAAAOAmy7I3DOHRORAMYQAAAGNkIAAAcJNlcxKlRzMQBBAAALgpEpF8NuYxeHQOBEMYAADAGBkIAADcxBAGAAAwZUUismwMYXh1GSdDGAAAwBgZCAAA3MQQBgAAMBaxJB8BBAAAMGFZkuws4/RmAMEcCAAAYMxTAcRjjz2mkpISFRcXa+nSpbI8GnUBADBaVsSyfXiRZwKIo0eP6oknnlBLS4veeOMNtbS06NVXX010twAAsMeK2D88yFNzIE6fPq2TJ09Kkk6dOqVLL700wT0CAADDcSwD0djYqLlz56qgoEA+n09bt24dck0wGNT06dOVlZWl2bNnq6mpKfrZxz72Mf3zP/+zioqKVFBQoOrqal111VVOdQ8AgIRgCOMC+vr6VFpaqmAwOOznmzZtUiAQ0MqVK7Vv3z6VlpaqpqZGR44ckSS9++672rZtm9566y0dPHhQu3fvVmNjo1PdAwAgMRjCOL/a2lrV1taO+PnatWt13333afHixZKk9evX65e//KWeeeYZLVu2TDt27NDHP/5x5ebmSpJuvfVWvfrqq/r0pz897P36+/vV398fPe/p6ZEkhUIhp75S0oq8F3a/DcNNUU7F8D/AqYn8WwJwx9nfFfGYrH9ap2ztI3Vap5zrjIPiMgdiYGBALS0tWr58ebQsLS1N1dXV2rNnjySpsLBQu3fv1smTJzV+/Hjt2rVLX/rSl0a8Z319vR5++OEh5YWFhc5/ASRITqI7ACDF/elPf1JOjjs/azIyMpSfn69Xun5l+175+fnKyMhwoFfOiUsAcezYMYXDYeXl5Q0qz8vL0/79+yVJN954o/7mb/5GM2bMUFpamj7zmc9o3rx5I95z+fLlCgQC0fMTJ07oiiuu0DvvvOPaw2BXeXm5mpubPXvvWO4x2jqjue5C14z0+XDloVBIhYWF6uzsVHZ29gX7lwhuPg9O3D9Zn4eRPhvrz4SXn4fRXmv6b36+z3p6elRUVBTNershKytLHR0dGhgYsH2vjIwMZWVlOdAr53hqFcbq1au1evXqUV2bmZmpzMzMIeU5OTme/eGQnp7uWt+cuHcs9xhtndFcd6FrRvr8fPWys7PH5PPgxP2T9Xm40Gdj9Znw8vMw2mtj/Tc/32dpae7uZpCVleW5X/xOics+EFOnTlV6erq6u7sHlXd3dys/Pz8eXfAEv9/v6XvHco/R1hnNdRe6ZqTP3fzv6ia3+233/sn6PJj0w2u8/DPCzedhtNfG+m+erM+D1/ksF2aQ+Hw+bdmyRQsWLIiWzZ49WxUVFXr88cclSZFIREVFRVqyZImWLVtmu81QKKScnBz19PR49q8LxA/PAz6KZwLn4nmwz7EhjN7eXrW3t0fPOzo61NraqtzcXBUVFSkQCKiurk6zZs1SRUWF1q1bp76+vuiqDLsyMzO1cuXKYYc1MPbwPOCjeCZwLp4H+xzLQOzatUtVVVVDyuvq6rRhwwZJ0hNPPKE1a9aoq6tLZWVl+t73vqfZs2c70TwAAIgjV4YwAABAavPMy7QAAEDyIIAAAADGCCAAAIAxAggAAGBszAQQ3/72t1VSUqLrrrtOzz//fKK7gwRYuHChJk+erNtvv31Q+bZt23TNNdfo6quv1g9/+MME9Q7xNtLzMFI5Uttw/+6dnZ2qrKxUcXGxbrjhBm3evDmBPfSeMbEK44033lBdXZ12794ty7JUVVWl7du365JLLkl01xBHu3bt0nvvvadnn31WP/vZzyRJp0+fVnFxsXbu3KmcnBzNnDlTu3fv1pQpUxLcW7htuOfhfOVIbcP9ux8+fFjd3d0qKytTV1eXZs6cqTfffFMTJ05McG+9YUxkIP74xz9qzpw5ysrK0oQJE1RaWqrt27cnuluIs8rKSk2aNGlQWVNTk0pKSjRt2jRdfPHFqq2t1UsvvZSgHiKehnsezleO1Dbcv/tll12msrIySWfehjl16lQdP348Ab3zpqQIIBobGzV37lwVFBTI5/Np69atQ64JBoOaPn26srKyNHv2bDU1NUU/u+6667Rr1y6dOHFC7777rnbt2qWDBw/G8RvALrvPwEgOHTqkadOmRc+nTZvGs5EE3HoekJzi8Ty0tLQoHA6rsLDQoV4nv6QIIPr6+lRaWqpgMDjs55s2bVIgENDKlSu1b98+lZaWqqamRkeOHJEkFRcXa+nSpbr55pt122236cYbb1R6eno8vwJssvsMILXwPOBcbj8Px48f1913360f/OAHTnY7+VlJRpK1ZcuWQWUVFRWW3++PnofDYaugoMCqr68f9h5f/OIXrW3btrnZTbjIzjOwc+dO67Of/Wz0/He/+521YMGC6Pn9999v/fjHP3an43CFk8/DhcrhfU4/DydPnrQ+9alPWRs3bnStz8kqKTIQ5zMwMKCWlhZVV1dHy9LS0lRdXa09e/ZEy85GmgcOHFBTU5Nqamri3le4Y7TPwHAqKir0hz/8QQcPHlRvb69+/etf82wkOTvPA1KPnefBsizdc889uvnmm7Vo0SK3u5p0HHsbZ6IcO3ZM4XBYeXl5g8rz8vK0f//+6Pn8+fPV09OjiRMn6kc/+pHGjUv6r44PjfYZqK6u1uuvv66+vj5dfvnl2rx5s+bMmaPvfOc7qqqqUiQS0Ve/+lVWYCQ5u8/DSOVITnaeh3A4rE2bNumGG26Izqt47rnndP3118fzK3jWmPktyl8e2LFjx7Dl8+bN07x58+LcGyTaSM/DSOVIbSP9u0cikTj3JHkk/RDG1KlTlZ6eru7u7kHl3d3dys/PT1CvEE88AzgXzwPOxfPgnqQPIDIyMjRz5kw1NDREyyKRiBoaGkg7jhE8AzgXzwPOxfPgnqQYwujt7VV7e3v0vKOjQ62trcrNzVVRUZECgYDq6uo0a9YsVVRUaN26derr69PixYsT2Gs4iWcA5+J5wLl4HhIk0ctARmPnzp2WpCFHXV1d9JrHH3/cKioqsjIyMqyKigrr1VdfTVyH4TieAZyL5wHn4nlIjDHxLgwAAOCspJ8DAQAA4o8AAgAAGCOAAAAAxgggAACAMQIIAABgjAACAAAYI4AAAADGCCAAAIAxAggAAGCMAAIAABgjgAAAAMYIIAAAgLH/D1a1GlAm17HMAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import py_plot_util as util\n",
    "x, z, ne, inwind = util.wind_to_masked(data, value_string=\"ne\", return_inwind=True)\n",
    "plt.pcolormesh(x,z, np.log10(ne))\n",
    "plt.loglog()\n",
    "plt.xlim(1e9,1e12)\n",
    "plt.ylim(1e8,1e12)\n",
    "cbar = plt.colorbar()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This procedure can be used to plot any of the variables in the masterfile and is a good starting point for delving into the properties of the wind if not using PySi. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Ion populations outputted from ```windsave2table``` are stored in files like ```cv_standard.C.frac.txt```, where the letter before frac denotes the element. Plots of the C III ion fraction can thus be made through commands like the following, where strings like ```i05``` index the ion for each file. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/matthewsj/.mpi_temp/ipykernel_40675/4163463376.py:3: RuntimeWarning: divide by zero encountered in log10\n",
      "  plt.pcolormesh(x,z, np.log10(c3_frac))\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "carbon_ion = io.read(\"cv_test/cv_standard.C.frac.txt\")\n",
    "x, z, c3_frac, inwind = util.wind_to_masked(carbon_ion, value_string=\"i03\", return_inwind=True)\n",
    "plt.pcolormesh(x,z, np.log10(c3_frac))\n",
    "plt.loglog()\n",
    "plt.xlim(1e9,1e12)\n",
    "plt.ylim(1e8,1e12)\n",
    "cbar = plt.colorbar()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Make A Basic Quick Look Wind Plot\n",
    "\n",
    "The simplest way to make a quick look plot of the electron temperature is using the ```plot_wind.py``` routine in ```$SIROCCO/py_progs```. In this example, I will assume py_progs has been added to ```$PATH``` and to ```$PYTHONPATH```. ```plot_wind.py``` can be run from the command line using\n",
    "\n",
    "    plot_wind.py cv_standard t_e\n",
    "    \n",
    "where the second argument is the variable to plot. Alternatively, it can be run from within a python script by doing (where we are now assuming you are running this code from one directory above cv_test):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'cv_test/cv_standard_log_t_e.png'"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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/b2qcgMwk7r//fq1du1bx8fEaNmyY/vjHP7ZrM3XqVI0aNUpffvmlhg8frjFjxmjEiBFKSkrSkSNHtGnTJn3++ecaOXKkHnroIT/8FAAAoKuVlZXpySefVHp6eqftSkpKNH36dI0dO1Y9evTQihUrlJmZqV27dmnAAGMT/AMyaWp7wW59fb2WL1/eYZvU1FSNGjVKp556qm677Ta9//772rhxo77++mv17NlTI0aM0O9+9zvdfvvt6tmzZzdGDwBAiAuQeUj19fWaOXOm1qxZ02GB5Yf+53/+x+1zQUGBXnzxRb311lsnXc+xTQD8yO0VFhaqsLDQUFu73a7HH3+8awMCgABn2+5D5wt86PuBD30LfFlI+Csf+t7hdU+nM3Afhw8FP15c+mRPt8+fP1/XXHONJk6ceNKk6ccaGxvV3NysU0891XCfgJzTBAAAAliETqwKbtX2XTaSkpLitth0Xl6exxA2bNigHTt2dNqmMzk5Oerfv78mTpxouE9AVpoAAED4qa6udltT0VOVqbq6WgsWLNCbb76pHj16mB4nPz9fGzZsUElJian+JE0AAMAcq+c0ffduErvdbmhF8A8//FBHjx7V6NGjXftaW1u1ZcsWPf7442pqavL41P3KlSuVn5+vTZs2nXTy+I+RNAEAgKAyYcIEVVRUuO3Lzs7W8OHDlZOT4zFhevDBB7V8+XIVFxfrggvMT+YjaQIAAOZ0UaXJqF69euncc8912xcXF6c+ffq49mdlZWnAgAGuOU8rVqzQH/7wBxUVFSk1NVWHDx+WJMXHxys+Pt7QuEwEBwAAIaeqqkqHDh1yfV69erWOHz+uX/ziF0pOTnZtK1euNHxOKk0AAMCctqferOLw/RQlJSWdfm5bA9IXVJoAAAAMoNIEAADM8fOcJn8haQIAAOZEytoMwoLbc92B23MAAAAGUGkCAADmWD0R3MpzdSEqTQAAAAZQaQIAAOZYPRGcOU0AAAChg0oTAAAwJ0wrTSRNABAgTleV951TTve+70ex3vdd731XpZz8bfaeXeR1T6cPlxnhjaQJAACYE6aVJuY0AQAAGEClCQAAmBMha9dWCpISTpCECQAA4F9UmgAAgDlWz2lqtfBcXYhKEwAAgAFUmgAAgDlUmgAAAOAJlSYAAGBOpKx9es7Kc3UhKk0AAAAGUGkCAADmMKcJAAAAnlBpAgAA5kTK2gyixcJzdSEqTQAAAAZQaQIAAOZYPacpSLKRIAkTAILDRL3mdd8+6u9136OfDPK6r97zvqsG+tDXh1syznd9GBfwEkkTAAAwJ0zXaSJpAgAA5oTp7TkmggMAABgQJLkdAAAIGFSaAAAA4EmQ5HYAACBgRMjaydtBUsIJkjABAAD8i0oTAAAwhzlNAAAA8CRIcjsAABAwqDQBAADAkyDJ7QAAQMAI09eoUGkCAAAwgEoTAAAwhzlNAAAA8CRIcjsA6B53KN+n/n2U7HXft6omez/w/3nfVX287+p8xodxEbwiZW0GwZwmAACA0EGlCQAAmMOcJgAAAHgSJLkdAAAIGKzTBAAAAE+oNAEAAHOY0wQAAABPgiS3AwAAASNMK01BEiYAAAgYEbJ28naQ3PcKkjABAAD8i0oTAAAwJ0xvz1FpAgAAMCBIcjsAABAwqDQBAADAkyDJ7QAAQMDgNSoAAADwhEoTgID0vH7mdd9vlOh131T19LqvJBVphvedP/Dhn+RR3nd1/s77vghTzGkKHAcOHNCjjz6qzMxMDRo0SDExMUpKStLPf/5zbd++vcM+tbW1uvPOOzV48GDFxsYqNTVV99xzj+rr67s5egAAEIoCMml67LHHdMcdd2jv3r3KzMzUXXfdpYsvvlivvPKKxo4dq7/+9a9u7RsaGjR+/Hg98sgjGj58uO644w6dddZZWrlypa644godO3bMTz8JAAAhKFLfV5us2Hyc05Sfny+bzaaFCxd22u7555/X8OHD1aNHD40cOVIbN240NU5AJk0XXnihSkpK9Omnn6qgoEB5eXl64YUXtHnzZkVGRurWW29VU1OTq/2DDz6o8vJy5eTkqLi4WPn5+SouLlZOTo7Kysr0yCOP+PGnAQAAXaWsrExPPvmk0tPTO2337rvvavr06br55pu1c+dOTZ06VVOnTtX//d//GR4rIJOmG264QePHj2+3/5JLLtHll1+ur7/+WhUVFZIkp9OpgoICxcfHa8mSJW7tlyxZovj4eBUUFHRL3AAAhAUrq0w+zI+qr6/XzJkztWbNGvXu3bvTtqtWrdKVV16pe+65RyNGjNCyZcs0evRoPf7444bHC8ikqTPR0dGSpKioE1d4z549OnjwoMaNG6e4uDi3tnFxcRo3bpz27t2r6urqbo8VAAAYV1tb67b98K5SR+bPn69rrrlGEydOPOm5//GPf7RrN3nyZP3jH/8wHF9QJU1VVVXatGmTkpOTNXLkSEknkiZJSktL67BP2/62dgAAwEeRXbBJSklJUUJCgmvLy8vzGMKGDRu0Y8eOTtv80OHDh3X66ae77Tv99NN1+PBhQ/2loHnIT2pubtasWbPU1NSkFStWKDLyxBWuqamRJCUkJHTYz263u7XrSFNTk1s2W1tba1XYAADAoOrqatfvbUmKjY312G7BggV688031aNHj+4KLziSJofDoTlz5mjLli2aN2+eZs2aZen58/LydN9991l6TgAAQlYXrdNkt9vdkiZPPvzwQx09elSjR4927WttbdWWLVv0+OOPq6mpyVVcaZOUlKQjR4647Tty5IiSkpIMhxnwt+ccDoduuukmFRUV6de//rWeeOIJt+NtFSZPlaS2qpGnSpQkLVq0SDU1Na6N+U8AAASuCRMmqKKiQuXl5a7tggsu0MyZM1VeXt4uYZKkjIwMvfXWW2773nzzTWVkZBgeN6ArTQ6HQ9nZ2Vq3bp2mT5+uwsJCRUS453knm7N0sjlP0onyn6cSIAAA+JG2dZqsPJ8JvXr10rnnnuu2Ly4uTn369HHtz8rK0oABA1xznhYsWKDx48frT3/6k6655hpt2LBBH3zwgZ566inD4wZspemHCdO0adP03HPPdZg5pqWlqX///tq2bZsaGhrcjjU0NGjbtm0aMmSIUlJSuit0AADgZ1VVVTp06JDr89ixY1VUVKSnnnpK5513nl544QW9/PLL7ZKvzgRkpantlty6det04403av369R0mTJJks9k0d+5c3X///Vq2bJny8/Ndx5YtW6b6+nrde++93RU6AACh7wdPvFl2Ph+VlJR0+lmSbrzxRt14441ejxGQSdP999+vtWvXKj4+XsOGDdMf//jHdm2mTp2qUaNGSZJ+//vf65VXXtGKFSu0c+dOjR49Wjt27NAbb7yhMWPGnHRZdQAAgJMJyKSpsrJS0omVPpcvX95hm9TUVFfSFBcXp9LSUi1dulQvvviiNm/erOTkZN11113Kzc1Vz56+vbUcAAD8QBc9PRfoAjLMwsJCFRYWmuqTkJCgRx55hPfMAQDQ1UiaAMBata3eP5V6QWQfr/tWaKTXfZfrP73uK0mtDu8nZ0SMazh5I0/jnh538kYAfELSBAAAzAnTSlPALjkAAAAQSIIktwMAAIHCGSE5LVxywBkkJZwgCRMAAMC/qDQBAABTWqNObFaeLxhQaQIAADAgSHI7AAAQKKg0AQAAwKMgye0AAECgaIm0qSXSZuH5nJKclp2vq1BpAgAAMIBKEwAAMKU1KkqtUdZVmlqjnJKaLTtfV6HSBAAAYACVJgAAYEprZKRaLZzT1BpJpQkAACBkUGkCAACmOBSpVllXaXIEwZNzEpUmAAAAQ6g0AejcBu//mrSneD/swXExXvd9TVd73beP/u11X0lqjfD+1e//Pn2cT2MD3aVFkWqxsNLUQqUJAAAgdFBpAgAAprQqUq0W1l1a5bDsXF2JShMAAIABVJoAAIAp1learJsf1ZWoNAEAABhApQkAAJgSrpUmkiYAAGBKuCZN3J4DAAAwgEoTAAAwpVWRaqHSBAAAgI5QaQIAAKa0KorFLQEAANAxKk0AAMCUVkWoVd6/nLr9+YIDlSYAAAADqDQBAABTTqzTFH6VJpImIBxc58PjvGk+jDve+64f62yv+56tj73u2+rjP4sbdYNP/QEELpImAABgSosi1WJhpanFsjN1LeY0AQAAGEClCQAAmOJQlKVzmhysCA4AABA6qDQBAABTwvXpOSpNAAAABlBpAgAAplBpAgAAgEdUmgAAgCnWv3vOadm5uhKVJgAAAAOoNAEAAFOsXxGcShMAAEDIoNIEAABMaVWUzy+3dj9fcCBpAgAApjgsXnLAwe05AACA0EGlCQgSX0V7/0LLU8f5MPBPve9aldzP675DVOl13y/V1+u+BZrvdV8gXFi/uCWVJgAAgJBBpQkAAJjSogiLlxxwWHaurkSlCQAAwAAqTQAAwBTrlxxgThMAAEDIoNIEAABMsf7pOeY0AQAAhAySJgAAYEpbpcnKzYzVq1crPT1ddrtddrtdGRkZev311zvt8+ijj+qss85Sz549lZKSojvuuEPHjh0zNS635wAAQFAZOHCg8vPzlZaWJqfTqbVr1+q6667Tzp07dc4557RrX1RUpP/4j//QM888o7Fjx2r37t2aM2eObDabHn74YcPjkjQBAABTWhVp6TpNZuc0TZkyxe3z8uXLtXr1ar333nsdJk3vvvuuxo0bpxkzZkiSUlNTNX36dG3fvt3UuNyeAwAAAaG2ttZta2pqOmmf1tZWbdiwQQ0NDcrIyOiwzdixY/Xhhx/q/ffflyTt3btXGzdu1NVXX20qPipNAADAlK5apyklJcVtf25urpYuXdphn4qKCmVkZOjYsWOKj4/XSy+9pLPPPrvDtjNmzNC///1vXXzxxXI6nWppadFvf/tb3XvvvabiJGkCAAABobq6Wna73fU5NjbWY9uzzjpL5eXlqqmp0QsvvKDZs2ertLS0w8SppKREDzzwgP785z/roosu0qeffqoFCxZo2bJlWrJkieH4SJoAAIAprYqweJ2mVklyPQ1nRExMjM4880xJ0vnnn6+ysjKtWrVKTz75ZLu2S5Ys0axZszR37lxJ0siRI9XQ0KDf/OY3+s///E9FRBibrcScJgAAEPQcDofHOVCNjY3tEqPIyBNJn9Np/BUuVJoAAIAp1q8Ibu5cixYt0lVXXaVBgwaprq5ORUVFKikpUXFxsSQpKytLAwYMUF5enqQTT9s9/PDD+slPfuK6PbdkyRJNmTLFlTwZQdIEdKP/Z7N53XdKgg8DX+BD33O97zqo+qj3fVOOeN33J173BBAMjh49qqysLB06dEgJCQlKT09XcXGxJk2aJEmqqqpyqywtXrxYNptNixcv1oEDB3TaaadpypQpWr58ualxAzZpWr9+vd555x19+OGHqqio0PHjx/Xss89qzpw57douXbpU9913n8dz7du3T6mpqV0XLAAAYcTflaann3660+MlJSVun6OiopSbm6vc3Fyzobmfx6feXWjx4sXav3+/+vbtq+TkZO3fv/+kfWbPnt1hcpSYmGh9gAAAIKwEbNJUUFCgtLQ0DR48WPn5+Vq0aNFJ+8yZM0eXXXZZ1wcHAEAYs35FcOvO1ZUCNmmaOHGiv0MAAABwCdikyRtbtmzR9u3bFRERobS0NE2cOFHx8fH+DgsAgJBi/Yrg5t495y8hlTT9eIJXYmKiVq1apaysLD9FBABA6PH3RHB/CYnFLc877zw988wz2rt3r7799lvt27dPjz32mGw2m+bMmaNXX3210/5NTU3tXhIIAADwQyFRabr++uvdPqempur222/XiBEjNGnSJC1evFg/+9nPPPbPy8vrdMkCAADwPetfoxIcNZzgiNJLEyZM0NChQ1VRUdFp9WjRokWqqalxbdXV1d0YJQAACAYhUWnqTN++ffXpp5+qsbHR40sAY2NjO32TMgAA+F6LxUsOWHmurhTSlaaGhgbt2rVLcXFx6tu3r7/DAQAAQSzoK011dXU6dOiQhg0b5rb/22+/1bx581RXV6fs7GxFRQX9jwoAQECwfsmBVsvO1ZUCNpMoKCjQ1q1bJUkVFRWufW3vk7n44os1d+5cffnllxo+fLjGjBmjESNGKCkpSUeOHNGmTZv0+eefa+TIkXrooYf89WMAAIAQYShpqqqqkiQNGDBAkZGRrs9G2Gw2nXLKKerTp4+pwLZu3aq1a9e67du2bZu2bdvm+jx37lydeuqpuu222/T+++9r48aN+vrrr9WzZ0+NGDFCv/vd73T77berZ8+epsYGAACeOSxep8kRJHOaDCVNqampioiI0Mcff6xhw4YpNTVVNpvN1ECnnnqqsrOztXz5ckVHR5+0fWFhoQoLC0/azm636/HHHzcVCwAAgFmGkqZBgwbJZrO5kp22z0Y1Njbqiy++0J/+9CdFRkYqLy/Pu2iBAPCwyT8YfmimD+NGZ/rQOc6Hvp2vDdu53zt96AwgUIXriuCGkqbKyspOPxuxd+9eXXTRRSoqKiJpAgAAQafblhw444wzdNlll+nQoUPdNSQAAOgCbSuCW7cFxwpI3fr03MKFC3Xttdd255AAAACW6Nakady4cRo3blx3DgkAACzWokhFsiI4AAAAOhKwi1sCAIDAZP2K4MGRjlBpAgAAMCA4UjsAABAwwnVFcCpNAAAABlBpAgAApoTriuBUmgAAAAyg0gQAAExpUaQiwnCdJpImAABgyonbc1YuORAcSRO35wAAAAyg0gQAAEwJ14ngJE0ISw/bbF73nenDuKdf7UPnOB/6HvWh72qnD50BIHSQNAEAAFPCtdLEnCYAAAADqDQBAABTeI0KAAAAPKLSBAAATGlRpGxhuLgllSYAAAADqDQBAABTWhWpCFYEBwAAQEeoNAEAAFNaLX5hL5UmAACAEEKlCQAAmEKlCQAAAB5RaQIAAKawThMAAAA8otIEAABMcShKrRamEI4gSUeoNAEAABgQHKkd0IHHbDav+07zYdzTf+pDZ180+dD3WadlYQBAq8Vzmnh6DgAAIIRQaQIAAKa0KsLiSlNw1HBImgAAgCknlghgyQEAAAB0gEoTAAAwpVVRslmYQli5fEFXotIEAABgQHCkdgAAIGA4FGnpMgEO5jQBAACEDipNAADAlFaLn55jcUsAAIAQQqUJAACYQqUJAAAAHpE0AQAAU1oUoRZFWriZS0dWr16t9PR02e122e12ZWRk6PXXX++0zzfffKP58+crOTlZsbGxGjZsmDZu3GhqXG7PAQCAoDJw4EDl5+crLS1NTqdTa9eu1XXXXaedO3fqnHPOadf++PHjmjRpkvr166cXXnhBAwYM0P79+5WYmGhqXJImAABgyokVvP23IviUKVPcPi9fvlyrV6/We++912HS9Mwzz+irr77Su+++q+joaElSamqq6ThJmuBXq202r/ve4MO4A37qQ+cEH/oO8qHvaqcPnQEg8NXW1rp9jo2NVWxsbKd9Wltb9fzzz6uhoUEZGRkdtnn11VeVkZGh+fPn65VXXtFpp52mGTNmKCcnR5GRxiehkzQBAABTuurpuZSUFLf9ubm5Wrp0aYd9KioqlJGRoWPHjik+Pl4vvfSSzj777A7b7t27V2+//bZmzpypjRs36tNPP9Vtt92m5uZm5ebmGo6TpAkAAASE6upq2e121+fOqkxnnXWWysvLVVNToxdeeEGzZ89WaWlph4mTw+FQv3799NRTTykyMlLnn3++Dhw4oIceeoikCQAAdB2HxZWmtnfPtT0NZ0RMTIzOPPNMSdL555+vsrIyrVq1Sk8++WS7tsnJyYqOjna7FTdixAgdPnxYx48fV0xMjKExWXIAAAAEPYfDoaampg6PjRs3Tp9++qkcDodr3+7du5WcnGw4YZJImgAAgEnWrtF0YjNj0aJF2rJliyorK1VRUaFFixappKREM2fOlCRlZWVp0aJFrva33nqrvvrqKy1YsEC7d+/Wa6+9pgceeEDz5883NS635wAAQFA5evSosrKydOjQISUkJCg9PV3FxcWaNGmSJKmqqkoREd/XhVJSUlRcXKw77rhD6enpGjBggBYsWKCcnBxT45I0AQAAU1oVKaeFKYTDZKXp6aef7vR4SUlJu30ZGRl67733TI3zY9yeAwAAMIBKEwAAMOVEpcn6p+cCHZUmAAAAA6g0AQAAU8K10kTSBAAATGl1RMrpsDBpsvBcXYnbcwAAAAZQaQIAAKa0tkTK0WJddchp4bm6EpUmAAAAA6g0AQAAU1pbomRrsS6FcFp4rq4UHFEioD1ss3ndd5oP4w4Y70PnOB/6+uJLP40LAPBZwN6eW79+vW655RZdcMEFio2Nlc1mU2Fhocf2tbW1uvPOOzV48GDFxsYqNTVV99xzj+rr67svaAAAwkBrS4RaWyIt3AI2HXETsJWmxYsXa//+/erbt6+Sk5O1f/9+j20bGho0fvx4lZeXKzMzU9OnT9fOnTu1cuVKlZaWasuWLerRo0c3Rg8AAEJNwKZ2BQUFqqys1BdffKHf/va3nbZ98MEHVV5erpycHBUXFys/P1/FxcXKyclRWVmZHnnkkW6KGgCA0GdtlenEFgwCNmmaOHGiBg8efNJ2TqdTBQUFio+P15IlS9yOLVmyRPHx8SooKOiqMAEAQJgI2KTJqD179ujgwYMaN26c4uLcZ/fGxcVp3Lhx2rt3r6qrq/0UIQAAoaWlJVItzRZuVJq6x549eyRJaWlpHR5v29/WDgAAwBsBOxHcqJqaGklSQkJCh8ftdrtbu440NTWpqanJ9bm2ttbCCAEACC3O1ig5Wy1MIaw8VxcK+kqTFfLy8pSQkODaUlJS/B0SAAAIMEGfNLVVmDxVktqqRp4qUZK0aNEi1dTUuDbmPwEA0ImWSOu3IBAc9bBOnGzO0snmPElSbGysYmNjrQ8OAACEjJBImvr3769t27apoaHB7Qm6hoYGbdu2TUOGDOGWGwAAVrG6OhQklaagvz1ns9k0d+5c1dfXa9myZW7Hli1bpvr6es2bN89P0QEAgFARsJWmgoICbd26VZJUUVHh2ldSUiJJuvjiizV37lxJ0u9//3u98sorWrFihXbu3KnRo0drx44deuONNzRmzBgtXLjQHz8CAAChqdUmtXj/svYOzxcEAjZp2rp1q9auXeu2b9u2bdq2bZvrc1vSFBcXp9LSUi1dulQvvviiNm/erOTkZN11113Kzc1Vz549uzV2AAAQemxOp9Pp7yACTW1trRISElRTU+Na5wmePWzz/i+EaT6MO2C8D53jTt6kS/gy7t/4vyqA7tPR78K2fdpeI8Vb+Puxvla6KPB/7wZspQnBY5wPfQd4fqjx5Ab50LfKh75f+dD3f0l8ACBYkTQBAABzWr7brDxfECBpAgAA5oRp0hT0Sw4AAAB0BypNAADAnBZJzRafLwhQaQIAADCAShMAADCn9bvNyvMFASpNAAAABlBpAgAA5vD0HAAAADyh0gQAAMyh0gQAAABPqDQBAABzqDQBAADAEypNAADAnFZZWx1inSYAAIDQQaUJkqT/Z7N53feqOO/HbT7qfd/ovd731Vc+9P3Y6UNnAAgBzGkCAACAJ1SaAACAOVSaAAAA4AmVJgAAYE7zd5uV5wsCVJoAAAAMoNIEAADMaZW1ayuxThMAAEDooNIEAADMYUVwAAAAeEKlCQAAmBOm6zSRNAEAAHPCNGni9hwAAIABVJoAAIA5VJoAAADgCZUmAABgDksOAAAAwBMqTZAknepD3yMN3vcdkOB93+b/875v9DdO7zsDQLhjThMAAAA8IWkCAADmNHfBZsLq1auVnp4uu90uu92ujIwMvf7664b6btiwQTabTVOnTjU3qEiaAABAkBk4cKDy8/P14Ycf6oMPPtAVV1yh6667Trt27eq0X2Vlpe6++25dcsklXo1L0gQAAMxp7YLNhClTpujqq69WWlqahg0bpuXLlys+Pl7vvfee55BbWzVz5kzdd999OuOMM8wN+B2SJgAAEBBqa2vdtqamppP2aW1t1YYNG9TQ0KCMjAyP7e6//37169dPN998s9fx8fQcAAAwp4uenktJSXHbnZubq6VLl3bYpaKiQhkZGTp27Jji4+P10ksv6eyzz+6w7datW/X000+rvLzcpzBJmgAAQECorq6W3W53fY6NjfXY9qyzzlJ5eblqamr0wgsvaPbs2SotLW2XONXV1WnWrFlas2aN+vbt61N8JE0AAMCcLloRvO1pOCNiYmJ05plnSpLOP/98lZWVadWqVXryySfd2n322WeqrKzUlClTXPscDockKSoqSv/61780dOhQQ2OSNAEAgKDncDg6nAM1fPhwVVRUuO1bvHix6urqtGrVqna3BDtD0gQAAMxpkRRp8flMWLRoka666ioNGjRIdXV1KioqUklJiYqLiyVJWVlZGjBggPLy8tSjRw+de+65bv0TExMlqd3+kyFpAgAAQeXo0aPKysrSoUOHlJCQoPT0dBUXF2vSpEmSpKqqKkVEWL9AAEkTAAAwp1nWLlpkckXwp59+utPjJSUlnR4vLCw0N+B3WKcJAADAACpNAADAHC9W8T7p+YIAlSYAAAADqDSFkEKbzeu+I3wYN9qHvnUN3vc94sMaIb78vAAQ9rponaZAR9IEAADMaZG196qsTMC6ELfnAAAADKDSBAAAzGmW5P2MkI7PFwSoNAEAABhApQkAAJjDkgMAAADwhEoTAAAwh6fnAAAA4AmVJgAAYE6YLm5JpQkAAMAAKk0AAMAcq9dVYp0mAACA0EGlCQAAmNMqa8suzGkCAAAIHVSaAACAOS2y9t1zQbJOE0lTCPHXd67Wh76NPgQ9wun0YWQAAMwhaQIAAOaEaaUpZOY0paamymazdbhddtll/g4PAAAEuZCqNCUkJGjhwoXt9qempnZ7LAAAhCyrK0NBUmkKqaQpMTFRS5cu9XcYAAAgBIVU0gQAALpBq6yd0xQk6zSFVNLU1NSkwsJCHTx4UHa7XWPGjNFFF13k77AAAEAICKmk6fDhw8rOznbbN2bMGP3lL3/R0KFD/RQVAAAhJkznNIXM03PZ2dl66623dOTIETU0NGjnzp2aNWuWysrKNGHCBNXV1Xns29TUpNraWrcNAADgh0ImacrNzdUVV1yhfv366ZRTTtGoUaO0bt06zZo1S/v379eaNWs89s3Ly1NCQoJrS0lJ6cbIAQAIMi1dsAWBkEmaPLnlllskSdu2bfPYZtGiRaqpqXFt1dXV3RUeAADBp0VSs4VbkCRNITWnqSN9+/aVJDU0NHhsExsbq9jY2O4KCQAABKGQT5q2b98uiQUuAQCwjNVLBATJkgMhcXvuk08+UWNjY4f7c3JyJEkzZszo7rAAAEAICYlK04YNG/Twww/r0ksv1eDBgxUXF6fdu3dr48aNam5u1qJFi3TppZf6O0wAAEJDiySnhecLkkpTSCRNl19+uf75z39q586deuedd9TY2Ki+ffvq6quv1m233abMzEx/hwgAAIJcSCRN48eP1/jx4/0dBgAA4YFKE8KZL0979vShb2qaD50BAOhGJE0AAMCcFkkOC89n5bm6UEg8PQcAANDVqDQBAABzWmXtnCYqTQAAAKGDShMAADCnRdaWXag0AQAAhA4qTQAAwBwqTQAAAPCEShMAADCnWVSaAAAA0DEqTQAAwByHrF2nycpzdSEqTQAAAAZQaQIAAOa0SLJZeD4qTQAAAKGDShMAADAnTCtNJE0B5j6b99/C0T6M28uHvqnjfOic5kNfAIB/NCsskyZuzwEAABhApQkAAJjTKipNAAAA6BiVJgAAYF6QVIesRKUJAADAAJImAAAAA0iaAAAADCBpAgAAQWX16tVKT0+X3W6X3W5XRkaGXn/9dY/t16xZo0suuUS9e/dW7969NXHiRL3//vumxyVpAgAAQWXgwIHKz8/Xhx9+qA8++EBXXHGFrrvuOu3atavD9iUlJZo+fbo2b96sf/zjH0pJSVFmZqYOHDhgalyb0+kMw/nvnautrVVCQoJqampkt9u7dWx/rQg+2Ie+6f5aEfxZvroA0FU6+l3Ytk+qkWTl78daSb793j311FP10EMP6eabbz5p29bWVvXu3VuPP/64srKyDI/BkgMAACAg1NbWun2OjY1VbGxsp31aW1v1/PPPq6GhQRkZGYbGaWxsVHNzs0499VRT8XF7DgAAmNTcBZuUkpKihIQE15aXl+cxgoqKCsXHxys2Nla//e1v9dJLL+nss882FH1OTo769++viRMnmvqpqTQBAICAUF1d7XZ7rrMq01lnnaXy8nLV1NTohRde0OzZs1VaWnrSxCk/P18bNmxQSUmJevToYSo+kiYAAGBSy3ebleeT62k4I2JiYnTmmWdKks4//3yVlZVp1apVevLJJz32WblypfLz87Vp0yalp6ebjpKkCQAABD2Hw6GmpiaPxx988EEtX75cxcXFuuCCC7wag6QJAACY9P08JOvOZ9yiRYt01VVXadCgQaqrq1NRUZFKSkpUXFwsScrKytKAAQNcc6JWrFihP/zhDyoqKlJqaqoOHz4sSYqPj1d8fLzhcUmaAkwvP42b3t+Hzhf70NfcgwsAAOjo0aPKysrSoUOHlJCQoPT0dBUXF2vSpEmSpKqqKkVEfP+s2+rVq3X8+HH94he/cDtPbm6uli5danhckiYAAGBS18xpMurpp5/u9HhJSYnb58rKSpPxdIwlBwAAAAyg0gQAAExqkbVzmqysWnUdKk0AAAAGUGkCAAAm+ffpOX8haQIAACb5dyK4v3B7DgAAwAAqTQAAwCQmggMAAMADKk0AAMAk5jQBAADAAypNAADApPBccoBKEwAAgAFUmgAAgEnMaQIAAIAHVJoCjC+59nBfBp7rfdeWu7zvG2V3et8ZAOAnrNMEAAAAD6g0AQAAk5jTBAAAAA+oNAEAAJNYpwkAAAAeUGkCAAAmMacJAAAAHlBpAgAAJrFOEwAAADyg0gQAAExiThMAAAA8oNIEAABMYp0mAAAAeEClCQAAmBSelSaSJgAAYFJ4TgQnaQowvvwPktbfh843et91nX2G131v8n5YAAC6FUkTAAAwicUtg15ZWZmuvvpqJSYmKi4uTj/96U/1t7/9zd9hAQCAEBAylabNmzdr8uTJ6tGjh371q1+pV69eevHFFzVt2jRVV1frrrvu8neIAACEiPCc0xQSlaaWlhbNmzdPERER2rJli5566in96U9/0kcffaRhw4bp3nvv1f79+/0dJgAACGIhkTS9/fbb+uyzzzRjxgyNGjXKtT8hIUH33nuvjh8/rrVr1/ovQAAAQkpzF2yBLySSppKSEklSZmZmu2OTJ0+WJJWWlnZnSAAAIMSExJymPXv2SJLS0tLaHUtKSlJ8fLyrDQAA8FV4zmkKiaSppqZG0onbcR2x2+2uNh1pampSU1OT63Ntba21AQIAgKAXErfnfJWXl6eEhATXlpKS4u+QAAAIYG3rNFm1BUelKSSSprYKk6dqUm1trccqlCQtWrRINTU1rq26urpL4gQAAMErJG7Ptc1l2rNnj84//3y3Y4cPH1Z9fb0uvPBCj/1jY2MVGxvbpTECABA6wnNOU0hUmsaPHy9JeuONN9odKy4udmsDAADgjZBImiZMmKAzzjhDRUVFKi8vd+2vqanRAw88oJiYGGVlZfkvQAAAQkp4rtMUErfnoqKiVFBQoMmTJ+vSSy91e43K/v37tXLlSqWmpvo7TAAAEMRCImmSpMsvv1xbt25Vbm6u/vrXv6q5uVkjR47UihUrNG3aNH+HBwBACAnPOU0hkzRJ0oUXXqjXX3/d5/M4nU5J/lmv6ZgPfWsdPnSu977rt7Xel1VrxZpYABCI2n4Htv1OdNfUwT5fWH2+rmFzdnw1wtrnn3/OWk0AAEiqrq7WwIEDJUnHjh3TkCFDdPjwYcvHSUpK0r59+9SjRw/Lz20VkqYOOBwOHTx4UL169ZLNZmt3vLa2VikpKaqurpbdbvdDhMGDa2Uc18o4rpVxXCvjuFbunE6n6urq1L9/f0VEfP/c2LFjx3T8+HHLx4uJiQnohEkKsdtzVomIiHBl1Z2x2+38H8sgrpVxXCvjuFbGca2M41p9r6OFoXv06BHwyU1XCYklBwAAALoaSRMAAIABJE1eiI2NVW5uLq9eMYBrZRzXyjiulXFcK+O4VjgZJoIDAAAYQKUJAADAAJImAAAAA0iaAAAADCBpMqGsrExXX321EhMTFRcXp5/+9Kf629/+5u+wAk5qaqpsNluH22WXXebv8Pxi/fr1uuWWW3TBBRcoNjZWNptNhYWFHtvX1tbqzjvv1ODBgxUbG6vU1FTdc889qq/34X03QcLMtVq6dKnH75rNZlNlZWW3xt6dDhw4oEcffVSZmZkaNGiQYmJilJSUpJ///Ofavn17h33C9Xtl9lqF8/cKnWNxS4M2b96syZMnq0ePHvrVr36lXr166cUXX9S0adNUXV2tu+66y98hBpSEhAQtXLiw3f7U1NRujyUQLF68WPv371ffvn2VnJys/fv3e2zb0NCg8ePHq7y8XJmZmZo+fbp27typlStXqrS0VFu2bAnpheXMXKs2s2fP7vC7lZiYaH2AAeKxxx7TihUrNHToUGVmZuq0007Tnj179PLLL+vll19WUVGR28vKw/l7ZfZatQnH7xVOwomTam5udg4dOtQZGxvr3Llzp2v/N9984xw2bJgzJibGWVlZ6b8AA8zgwYOdgwcP9ncYAeXNN990fUfy8vKckpzPPvtsh23/8Ic/OCU5c3Jy3Pbn5OQ4JTkfeOCBrg7Xr8xcq9zcXKck5+bNm7svwADx4osvOktKStrt37JlizM6OtrZu3dv57Fjx1z7w/l7ZfZahfP3Cp3j9pwBb7/9tj777DPNmDFDo0aNcu1PSEjQvffeq+PHj2vt2rX+CxABb+LEiRo8ePBJ2zmdThUUFCg+Pl5LlixxO7ZkyRLFx8eroKCgq8IMCEavVbi74YYbNH78+Hb7L7nkEl1++eX6+uuvVVFRIYnvlZlrBXSG23MGlJSUSJIyMzPbHZs8ebIkqbS0tDtDCnhNTU0qLCzUwYMHZbfbNWbMGF100UX+Divg7dmzRwcPHtTkyZMVFxfndiwuLk7jxo1TcXGxqqurlZKS4qcoA8+WLVu0fft2RUREKC0tTRMnTlR8fLy/w/Kb6OhoSVJU1Il/4vleefbja/VDfK/wYyRNBuzZs0eSlJaW1u5YUlKS4uPjXW1wwuHDh5Wdne22b8yYMfrLX/6ioUOH+imqwNfZd61tf3Fxsfbs2RN2v9w6k5ub6/Y5MTFRq1atUlZWlp8i8p+qqipt2rRJycnJGjlypCS+V550dK1+iO8VfozbcwbU1NRI6vhtz9KJN2K3tYGUnZ2tt956S0eOHFFDQ4N27typWbNmqaysTBMmTFBdXZ2/QwxYRr5rP2wX7s477zw988wz2rt3r7799lvt27dPjz32mGw2m+bMmaNXX33V3yF2q+bmZs2aNUtNTU1asWKFIiMjJfG96oinayXxvYJnVJpguR//dTZq1CitW7dOkvTcc89pzZo1uvPOO/0RGkLM9ddf7/Y5NTVVt99+u0aMGKFJkyZp8eLF+tnPfuan6LqXw+HQnDlztGXLFs2bN0+zZs3yd0gB62TXiu8VPKHSZEDbX2ee/gqrra31+BccvnfLLbdIkrZt2+bnSAKXke/aD9uhYxMmTNDQoUNVUVHhumahzOFw6KabblJRUZF+/etf64knnnA7zvfqeye7Vp0Jt+8V2iNpMqBtHkBH85YOHz6s+vp6j3MF8L2+fftKOrFeDDrW2Xfth/v5vp1c2/etsbHRz5F0LYfDoezsbK1du1bTp09XYWGhIiLc/2nne3WCkWt1MuHyvULHSJoMaHtU9Y033mh3rLi42K0NPGtbeTdcF7g0Ii0tTf3799e2bdvaJZcNDQ3atm2bhgwZElaTdb3R0NCgXbt2KS4uzvVLLhS1JQHr1q3TtGnT9Nxzz7nNzWnD98r4tepMuHyv4BlJkwETJkzQGWecoaKiIpWXl7v219TU6IEHHlBMTAxPU3znk08+6fAvsE8++UQ5OTmSpBkzZnR3WEHDZrNp7ty5qq+v17Jly9yOLVu2TPX19Zo3b56fogssdXV12r17d7v93377rebNm6e6ujr98pe/7PBR8lDQdptp3bp1uvHGG7V+/XqPSUC4f6/MXKtw/16hczan0+n0dxDBwNNrVPbv36+VK1fyGpXvLF26VA8//LAuvfRSDR48WHFxcdq9e7c2btyo5uZmLVq0SA888IC/w+x2BQUF2rp1qySpoqJCO3bs0Lhx43TmmWdKki6++GLNnTtX0om/ZseNG6ePPvpImZmZGj16tHbs2KE33nhDY8aMUWlpqXr27Om3n6WrGb1WlZWVOuOMMzRmzBiNGDFCSUlJOnLkiDZt2qTPP/9cI0eO1ObNm9WnTx9//jhdZunSpbrvvvsUHx+vBQsWdPhLfOrUqa4FecP5e2XmWoX79won4d8FyYPL9u3bnVdeeaXTbrc7e/bs6bzwwgudGzZs8HdYAaWkpMT5y1/+0pmWlua02+3OqKgoZ1JSkvO6665zFhcX+zs8v5k9e7ZTksdt9uzZbu2/+eYb58KFC50pKSnO6Oho56BBg5x33XWXs7a21j8/QDcyeq1qamqc8+fPd44ZM8Z52mmnOaOiopy9evVyXnjhhc4HH3zQ2djY6N8fpIud7Dqpg9fPhOv3ysy1CvfvFTpHpQkAAMAA5jQBAAAYQNIEAABgAEkTAACAASRNAAAABpA0AQAAGEDSBAAAYABJEwAAgAEkTQAAAAaQNAEAABhA0gQg4KSmpspms6mystLfoQCAC0kTAACAAbx7DkDA+eyzz9Tc3KyhQ4cqOjra3+EAgCSSJgAAAEO4PQcg4DCnCUAgImkCAAAwgKQJAADAAJImAAAAA0iaAAAADCBpAgAAMICkCQAAwACSJgAAAANImgAAAAwgaQIAADCApAkAAMAAkiYAAAADeGEvAACAAVSaAAAADCBpAgAAMICkCQAAwACSJgAAAANImgAAAAwgaQIAADCApAkAAMAAkiYAAAADSJoAAAAMIGkCAAAwgKQJAADAAJImAAAAA0iaAAAADPj/PDK/XhEs/p4AAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 600x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import plot_wind\n",
    "fname = \"cv_test/cv_standard.master.txt\"\n",
    "plot_wind.doit(fname, var=\"t_e\")"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.12.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}