{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Statistics in physt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Necessary import evil\n",
    "import physt\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "np.random.seed(42)   # Repeatable results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = np.random.normal(150, 25, 1000000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "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": [
    "h = physt.h1(data)\n",
    "h.plot(show_stats=True);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "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": [
    "h = physt.h1(data, weights=data)\n",
    "h.plot(show_stats=[\"total\", \"mean\"]);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "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": [
    "h = physt.h1(data, range=(120, 140))\n",
    "h.plot(show_stats=True);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Statistics(sum=149960006.08864358, sum2=23113238494.210587, min=29.26409978722107, max=266.9737275094181, weight=1000000)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "h._stats"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "229977"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "h.total"
   ]
  }
 ],
 "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": "3.8.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}