{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Einstein Tensor calculations using Symbolic module"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pytest\n",
    "import sympy\n",
    "from sympy import cos, simplify, sin, sinh, tensorcontraction\n",
    "from einsteinpy.symbolic import EinsteinTensor, MetricTensor, RicciScalar\n",
    "\n",
    "sympy.init_printing()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Defining the Anti-de Sitter spacetime Metric"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "syms = sympy.symbols(\"t chi theta phi\")\n",
    "t, ch, th, ph = syms\n",
    "m = sympy.diag(-1, cos(t) ** 2, cos(t) ** 2 * sinh(ch) ** 2, cos(t) ** 2 * sinh(ch) ** 2 * sin(th) ** 2).tolist()\n",
    "metric = MetricTensor(m, syms)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Calculating the Einstein Tensor (with both indices covariant)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/latex": [
       "$\\displaystyle \\left[\\begin{matrix}\\frac{0.5 \\left(\\left(\\sin^{2}{\\left(t \\right)} - 1\\right) \\sinh^{2}{\\left(\\chi \\right)} - 2 \\cos^{2}{\\left(t \\right)} \\sinh^{2}{\\left(\\chi \\right)}\\right)}{\\cos^{2}{\\left(t \\right)} \\sinh^{2}{\\left(\\chi \\right)}} + \\frac{0.5 \\left(\\left(\\sin^{2}{\\left(t \\right)} - 1\\right) \\sin^{2}{\\left(\\theta \\right)} \\sinh^{2}{\\left(\\chi \\right)} - 2 \\sin^{2}{\\left(\\theta \\right)} \\cos^{2}{\\left(t \\right)} \\sinh^{2}{\\left(\\chi \\right)}\\right)}{\\sin^{2}{\\left(\\theta \\right)} \\cos^{2}{\\left(t \\right)} \\sinh^{2}{\\left(\\chi \\right)}} & 0 & 0 & 0\\\\0 & - 0.5 \\left(\\frac{\\left(\\sin^{2}{\\left(t \\right)} - 1\\right) \\sinh^{2}{\\left(\\chi \\right)} - 2 \\cos^{2}{\\left(t \\right)} \\sinh^{2}{\\left(\\chi \\right)}}{\\cos^{2}{\\left(t \\right)} \\sinh^{2}{\\left(\\chi \\right)}} + \\frac{\\left(\\sin^{2}{\\left(t \\right)} - 1\\right) \\sin^{2}{\\left(\\theta \\right)} \\sinh^{2}{\\left(\\chi \\right)} - 2 \\sin^{2}{\\left(\\theta \\right)} \\cos^{2}{\\left(t \\right)} \\sinh^{2}{\\left(\\chi \\right)}}{\\sin^{2}{\\left(\\theta \\right)} \\cos^{2}{\\left(t \\right)} \\sinh^{2}{\\left(\\chi \\right)}} - 6\\right) \\cos^{2}{\\left(t \\right)} - 3 \\cos^{2}{\\left(t \\right)} & 0 & 0\\\\0 & 0 & \\left(\\sin^{2}{\\left(t \\right)} - 1\\right) \\sinh^{2}{\\left(\\chi \\right)} - 0.5 \\left(\\frac{\\left(\\sin^{2}{\\left(t \\right)} - 1\\right) \\sinh^{2}{\\left(\\chi \\right)} - 2 \\cos^{2}{\\left(t \\right)} \\sinh^{2}{\\left(\\chi \\right)}}{\\cos^{2}{\\left(t \\right)} \\sinh^{2}{\\left(\\chi \\right)}} + \\frac{\\left(\\sin^{2}{\\left(t \\right)} - 1\\right) \\sin^{2}{\\left(\\theta \\right)} \\sinh^{2}{\\left(\\chi \\right)} - 2 \\sin^{2}{\\left(\\theta \\right)} \\cos^{2}{\\left(t \\right)} \\sinh^{2}{\\left(\\chi \\right)}}{\\sin^{2}{\\left(\\theta \\right)} \\cos^{2}{\\left(t \\right)} \\sinh^{2}{\\left(\\chi \\right)}} - 6\\right) \\cos^{2}{\\left(t \\right)} \\sinh^{2}{\\left(\\chi \\right)} - 2 \\cos^{2}{\\left(t \\right)} \\sinh^{2}{\\left(\\chi \\right)} & 0\\\\0 & 0 & 0 & \\left(\\sin^{2}{\\left(t \\right)} - 1\\right) \\sin^{2}{\\left(\\theta \\right)} \\sinh^{2}{\\left(\\chi \\right)} - 0.5 \\left(\\frac{\\left(\\sin^{2}{\\left(t \\right)} - 1\\right) \\sinh^{2}{\\left(\\chi \\right)} - 2 \\cos^{2}{\\left(t \\right)} \\sinh^{2}{\\left(\\chi \\right)}}{\\cos^{2}{\\left(t \\right)} \\sinh^{2}{\\left(\\chi \\right)}} + \\frac{\\left(\\sin^{2}{\\left(t \\right)} - 1\\right) \\sin^{2}{\\left(\\theta \\right)} \\sinh^{2}{\\left(\\chi \\right)} - 2 \\sin^{2}{\\left(\\theta \\right)} \\cos^{2}{\\left(t \\right)} \\sinh^{2}{\\left(\\chi \\right)}}{\\sin^{2}{\\left(\\theta \\right)} \\cos^{2}{\\left(t \\right)} \\sinh^{2}{\\left(\\chi \\right)}} - 6\\right) \\sin^{2}{\\left(\\theta \\right)} \\cos^{2}{\\left(t \\right)} \\sinh^{2}{\\left(\\chi \\right)} - 2 \\sin^{2}{\\left(\\theta \\right)} \\cos^{2}{\\left(t \\right)} \\sinh^{2}{\\left(\\chi \\right)}\\end{matrix}\\right]$"
      ],
      "text/plain": [
       "⎡    ⎛⎛   2       ⎞     2           2        2   ⎞       ⎛⎛   2       ⎞    2  \n",
       "⎢0.5⋅⎝⎝sin (t) - 1⎠⋅sinh (χ) - 2⋅cos (t)⋅sinh (χ)⎠   0.5⋅⎝⎝sin (t) - 1⎠⋅sin (θ\n",
       "⎢───────────────────────────────────────────────── + ─────────────────────────\n",
       "⎢                    2        2                                              2\n",
       "⎢                 cos (t)⋅sinh (χ)                                        sin \n",
       "⎢                                                                             \n",
       "⎢                                                                             \n",
       "⎢                                                                             \n",
       "⎢                                                          0                  \n",
       "⎢                                                                             \n",
       "⎢                                                                             \n",
       "⎢                                                                             \n",
       "⎢                                                                             \n",
       "⎢                                                                             \n",
       "⎢                                                          0                  \n",
       "⎢                                                                             \n",
       "⎢                                                                             \n",
       "⎢                                                                             \n",
       "⎢                                                                             \n",
       "⎢                                                                             \n",
       "⎢                                                          0                  \n",
       "⎢                                                                             \n",
       "⎣                                                                             \n",
       "\n",
       "      2           2       2        2   ⎞                                      \n",
       ")⋅sinh (χ) - 2⋅sin (θ)⋅cos (t)⋅sinh (χ)⎠                                      \n",
       "────────────────────────────────────────                                      \n",
       "       2        2                                                             \n",
       "(θ)⋅cos (t)⋅sinh (χ)                                                          \n",
       "                                                                              \n",
       "                                                ⎛⎛   2       ⎞     2          \n",
       "                                                ⎜⎝sin (t) - 1⎠⋅sinh (χ) - 2⋅co\n",
       "                                          - 0.5⋅⎜─────────────────────────────\n",
       "                                                ⎜                 2        2  \n",
       "                                                ⎝              cos (t)⋅sinh (χ\n",
       "                                                                              \n",
       "                                                                              \n",
       "                                                                              \n",
       "                                                                              \n",
       "                                                                              \n",
       "                                                                              \n",
       "                                                                              \n",
       "                                                                              \n",
       "                                                                              \n",
       "                                                                              \n",
       "                                                                              \n",
       "                                                                              \n",
       "\n",
       "                                                                              \n",
       "                                                                              \n",
       "                                0                                             \n",
       "                                                                              \n",
       "                                                                              \n",
       "                                                                              \n",
       " 2        2      ⎛   2       ⎞    2        2           2       2        2     \n",
       "s (t)⋅sinh (χ)   ⎝sin (t) - 1⎠⋅sin (θ)⋅sinh (χ) - 2⋅sin (θ)⋅cos (t)⋅sinh (χ)  \n",
       "────────────── + ─────────────────────────────────────────────────────────── -\n",
       "                                      2       2        2                      \n",
       ")                                  sin (θ)⋅cos (t)⋅sinh (χ)                   \n",
       "                                                                              \n",
       "                                                                              \n",
       "                                                                              \n",
       "                                0                                             \n",
       "                                                                              \n",
       "                                                                              \n",
       "                                                                              \n",
       "                                                                              \n",
       "                                                                              \n",
       "                                0                                             \n",
       "                                                                              \n",
       "                                                                              \n",
       "\n",
       "                                                                              \n",
       "                                                                              \n",
       "                                                                              \n",
       "                                                                              \n",
       "                                                                              \n",
       "                                                                              \n",
       "  ⎞                                                                           \n",
       "  ⎟    2           2                                                          \n",
       " 6⎟⋅cos (t) - 3⋅cos (t)                                                       \n",
       "  ⎟                                                                           \n",
       "  ⎠                                                                           \n",
       "                                                                              \n",
       "                                                      ⎛⎛   2       ⎞     2    \n",
       "                         ⎛   2       ⎞     2          ⎜⎝sin (t) - 1⎠⋅sinh (χ) \n",
       "                         ⎝sin (t) - 1⎠⋅sinh (χ) - 0.5⋅⎜───────────────────────\n",
       "                                                      ⎜                 2     \n",
       "                                                      ⎝              cos (t)⋅s\n",
       "                                                                              \n",
       "                                                                              \n",
       "                                                                              \n",
       "                                                                              \n",
       "                                                                              \n",
       "                                                                              \n",
       "\n",
       "                                                                              \n",
       "                                                                              \n",
       "                                   0                                          \n",
       "                                                                              \n",
       "                                                                              \n",
       "                                                                              \n",
       "                                                                              \n",
       "                                                                              \n",
       "                                   0                                          \n",
       "                                                                              \n",
       "                                                                              \n",
       "                                                                              \n",
       "       2        2      ⎛   2       ⎞    2        2           2       2        \n",
       "- 2⋅cos (t)⋅sinh (χ)   ⎝sin (t) - 1⎠⋅sin (θ)⋅sinh (χ) - 2⋅sin (θ)⋅cos (t)⋅sinh\n",
       "──────────────────── + ───────────────────────────────────────────────────────\n",
       "   2                                        2       2        2                \n",
       "inh (χ)                                  sin (θ)⋅cos (t)⋅sinh (χ)             \n",
       "                                                                              \n",
       "                                                                              \n",
       "                                                                              \n",
       "                                   0                                          \n",
       "                                                                              \n",
       "                                                                              \n",
       "\n",
       "                                                                              \n",
       "                                                                              \n",
       "                                                                              \n",
       "                                                                              \n",
       "                                                                              \n",
       "                                                                              \n",
       "                                                                              \n",
       "                                                                              \n",
       "                                                                              \n",
       "                                                                              \n",
       "                                                                              \n",
       "                                                                              \n",
       "2       ⎞                                                                     \n",
       " (χ)    ⎟    2        2           2        2                                  \n",
       "──── - 6⎟⋅cos (t)⋅sinh (χ) - 2⋅cos (t)⋅sinh (χ)                               \n",
       "        ⎟                                                                     \n",
       "        ⎠                                                                     \n",
       "                                                                              \n",
       "                                                                              \n",
       "                                                 ⎛   2       ⎞    2        2  \n",
       "                                                 ⎝sin (t) - 1⎠⋅sin (θ)⋅sinh (χ\n",
       "                                                                              \n",
       "                                                                              \n",
       "\n",
       "                                                                              \n",
       "                                                                              \n",
       "                                                                       0      \n",
       "                                                                              \n",
       "                                                                              \n",
       "                                                                              \n",
       "                                                                              \n",
       "                                                                              \n",
       "                                                                       0      \n",
       "                                                                              \n",
       "                                                                              \n",
       "                                                                              \n",
       "                                                                              \n",
       "                                                                              \n",
       "                                                                       0      \n",
       "                                                                              \n",
       "                                                                              \n",
       "                                                                              \n",
       "        ⎛⎛   2       ⎞     2           2        2      ⎛   2       ⎞    2     \n",
       "        ⎜⎝sin (t) - 1⎠⋅sinh (χ) - 2⋅cos (t)⋅sinh (χ)   ⎝sin (t) - 1⎠⋅sin (θ)⋅s\n",
       ") - 0.5⋅⎜─────────────────────────────────────────── + ───────────────────────\n",
       "        ⎜                 2        2                                        2 \n",
       "        ⎝              cos (t)⋅sinh (χ)                                  sin (\n",
       "\n",
       "                                                                              \n",
       "                                                                              \n",
       "                                                                              \n",
       "                                                                              \n",
       "                                                                              \n",
       "                                                                              \n",
       "                                                                              \n",
       "                                                                              \n",
       "                                                                              \n",
       "                                                                              \n",
       "                                                                              \n",
       "                                                                              \n",
       "                                                                              \n",
       "                                                                              \n",
       "                                                                              \n",
       "                                                                              \n",
       "                                                                              \n",
       "                                                                              \n",
       "   2           2       2        2       ⎞                                     \n",
       "inh (χ) - 2⋅sin (θ)⋅cos (t)⋅sinh (χ)    ⎟    2       2        2           2   \n",
       "──────────────────────────────────── - 6⎟⋅sin (θ)⋅cos (t)⋅sinh (χ) - 2⋅sin (θ)\n",
       "      2        2                        ⎟                                     \n",
       "θ)⋅cos (t)⋅sinh (χ)                     ⎠                                     \n",
       "\n",
       "                 ⎤\n",
       "                 ⎥\n",
       "                 ⎥\n",
       "                 ⎥\n",
       "                 ⎥\n",
       "                 ⎥\n",
       "                 ⎥\n",
       "                 ⎥\n",
       "                 ⎥\n",
       "                 ⎥\n",
       "                 ⎥\n",
       "                 ⎥\n",
       "                 ⎥\n",
       "                 ⎥\n",
       "                 ⎥\n",
       "                 ⎥\n",
       "                 ⎥\n",
       "                 ⎥\n",
       "                 ⎥\n",
       "    2        2   ⎥\n",
       "⋅cos (t)⋅sinh (χ)⎥\n",
       "                 ⎥\n",
       "                 ⎦"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "einst = EinsteinTensor.from_metric(metric)\n",
    "einst.tensor()"
   ]
  }
 ],
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