{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-09-26T06:39:45.474473Z",
     "start_time": "2019-09-26T06:39:42.982516Z"
    },
    "execution": {
     "iopub.execute_input": "2020-12-03T12:24:51.391546Z",
     "iopub.status.busy": "2020-12-03T12:24:51.390477Z",
     "iopub.status.idle": "2020-12-03T12:24:53.037544Z",
     "shell.execute_reply": "2020-12-03T12:24:53.038375Z"
    },
    "papermill": {
     "duration": 1.668252,
     "end_time": "2020-12-03T12:24:53.038754",
     "exception": false,
     "start_time": "2020-12-03T12:24:51.370502",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "%matplotlib inline \n",
    "import json\n",
    "import numpy as np\n",
    "import os\n",
    "import pylab as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-12-03T12:24:53.146244Z",
     "iopub.status.busy": "2020-12-03T12:24:53.145295Z",
     "iopub.status.idle": "2020-12-03T12:24:53.148182Z",
     "shell.execute_reply": "2020-12-03T12:24:53.149014Z"
    },
    "papermill": {
     "duration": 0.098183,
     "end_time": "2020-12-03T12:24:53.149286",
     "exception": false,
     "start_time": "2020-12-03T12:24:53.051103",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "import matplotlib as mpl\n",
    "mpl.rc('font', family='Times New Roman')\n",
    "plt.rcParams[\"mathtext.fontset\"] = \"stix\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-12-03T12:24:53.182949Z",
     "iopub.status.busy": "2020-12-03T12:24:53.181947Z",
     "iopub.status.idle": "2020-12-03T12:24:53.184560Z",
     "shell.execute_reply": "2020-12-03T12:24:53.185393Z"
    },
    "papermill": {
     "duration": 0.019958,
     "end_time": "2020-12-03T12:24:53.185684",
     "exception": false,
     "start_time": "2020-12-03T12:24:53.165726",
     "status": "completed"
    },
    "tags": [
     "parameters"
    ]
   },
   "outputs": [],
   "source": [
    "input_file = 'output.json'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-12-03T12:24:53.213857Z",
     "iopub.status.busy": "2020-12-03T12:24:53.212809Z",
     "iopub.status.idle": "2020-12-03T12:24:53.215719Z",
     "shell.execute_reply": "2020-12-03T12:24:53.216494Z"
    },
    "papermill": {
     "duration": 0.019281,
     "end_time": "2020-12-03T12:24:53.216738",
     "exception": false,
     "start_time": "2020-12-03T12:24:53.197457",
     "status": "completed"
    },
    "tags": [
     "injected-parameters"
    ]
   },
   "outputs": [],
   "source": [
    "# Parameters\n",
    "input_file = \"output.json\"\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-12-03T12:24:53.242986Z",
     "iopub.status.busy": "2020-12-03T12:24:53.241999Z",
     "iopub.status.idle": "2020-12-03T12:24:53.244744Z",
     "shell.execute_reply": "2020-12-03T12:24:53.244132Z"
    },
    "papermill": {
     "duration": 0.016615,
     "end_time": "2020-12-03T12:24:53.244888",
     "exception": false,
     "start_time": "2020-12-03T12:24:53.228273",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Values from a previous calculation can be inserted here to reproduce the results \n",
    "step_dict = {}\n",
    "if os.path.exists(input_file):\n",
    "    with open(input_file, 'r') as f:\n",
    "        step_dict_str = json.load(f)\n",
    "    for k,v in step_dict_str.items():\n",
    "        step_dict[int(k)] = v"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-12-03T12:24:53.264135Z",
     "iopub.status.busy": "2020-12-03T12:24:53.263214Z",
     "iopub.status.idle": "2020-12-03T12:24:53.265950Z",
     "shell.execute_reply": "2020-12-03T12:24:53.265330Z"
    },
    "papermill": {
     "duration": 0.014843,
     "end_time": "2020-12-03T12:24:53.266094",
     "exception": false,
     "start_time": "2020-12-03T12:24:53.251251",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "ind, temp_lst = [], []\n",
    "for k,v in step_dict.items():\n",
    "    ind.append(k)\n",
    "    temp_lst.append(v['temperature_next'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-12-03T12:24:53.284421Z",
     "iopub.status.busy": "2020-12-03T12:24:53.283779Z",
     "iopub.status.idle": "2020-12-03T12:24:53.286672Z",
     "shell.execute_reply": "2020-12-03T12:24:53.286059Z"
    },
    "papermill": {
     "duration": 0.014147,
     "end_time": "2020-12-03T12:24:53.286814",
     "exception": false,
     "start_time": "2020-12-03T12:24:53.272667",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "temp_array = np.array(temp_lst)[np.array(ind)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-12-03T12:24:53.377923Z",
     "iopub.status.busy": "2020-12-03T12:24:53.376888Z",
     "iopub.status.idle": "2020-12-03T12:24:53.827618Z",
     "shell.execute_reply": "2020-12-03T12:24:53.828380Z"
    },
    "papermill": {
     "duration": 0.535412,
     "end_time": "2020-12-03T12:24:53.828655",
     "exception": false,
     "start_time": "2020-12-03T12:24:53.293243",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Temperature (K)')"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot the convergence of loop calculations\n",
    "plt.plot(np.arange(1, len(temp_array)), temp_array[0:-1], 'ro-', label=r\"$T^e$\")\n",
    "plt.plot(np.arange(1, len(temp_array)), temp_array[1:], 'bo-', label=r\"$T^p$\")\n",
    "plt.legend(fontsize=14)\n",
    "plt.tick_params(axis='both', labelsize=14)\n",
    "plt.xlabel('Number of loops', fontsize=14)\n",
    "plt.ylabel('Temperature (K)', fontsize=14)\n"
   ]
  }
 ],
 "metadata": {
  "celltoolbar": "Tags",
  "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": "3.9.0"
  },
  "papermill": {
   "default_parameters": {},
   "duration": 5.65011,
   "end_time": "2020-12-03T12:24:54.252406",
   "environment_variables": {},
   "exception": null,
   "input_path": "./scripts/plot.ipynb",
   "output_path": "plot.nbconvert.ipynb",
   "parameters": {
    "input_file": "output.json"
   },
   "start_time": "2020-12-03T12:24:48.602296",
   "version": "2.2.2"
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {
    "height": "120px",
    "width": "252px"
   },
   "number_sections": true,
   "sideBar": true,
   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {
    "height": "calc(100% - 180px)",
    "left": "10px",
    "top": "150px",
    "width": "166.796875px"
   },
   "toc_section_display": "block",
   "toc_window_display": false
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}