doc/tutorials/create-tutorial-2.ipynb

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  {
   "cell_type": "markdown",
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   "source": [
    "# Replicas, streams, irregular chains"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "9f5ae534",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pyobs\n",
    "import numpy\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib notebook"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "0e37a805",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Random generator initialized with seed = 2458954236 [tutorial-v2]\n"
     ]
    }
   ],
   "source": [
    "mu = 0.5 # central values\n",
    "cov = (mu*0.5)**2 # error^2\n",
    "\n",
    "# autocorrelation time\n",
    "tau=4.0\n",
    "\n",
    "rng = pyobs.random.generator('tutorial-v2')\n",
    "data1 = rng.markov_chain(mu,cov,tau,1000)\n",
    "\n",
    "data2 = rng.markov_chain(mu,cov,tau,600)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "634fa543",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Observable with shape = (1,)\n",
      " - description: Observable A\n",
      " - created by mbruno at macthxbruno.fritz.box on Sat Aug 20 14:42:09 2022\n",
      " - size: 73 KB\n",
      " - mean: [0.57392611]\n",
      " - Ensemble EnsA\n",
      "    - Replica replica1 with ncnfg 1000\n",
      "    - Replica replica2 with ncnfg 600\n",
      "         temporary additional memory required 0.015 MB\n",
      "\n"
     ]
    }
   ],
   "source": [
    "obsA = pyobs.observable(description='Observable A')\n",
    "obsA.create('EnsA',[data1,data2],rname=['replica1','replica2'])\n",
    "obsA.peek()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a2f17cd7",
   "metadata": {},
   "source": [
    "Now we artificially create a stream with holes. To make sure that the autocorrelations are still treated properly we must provide the configuration index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "01ee647d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Observable with shape = (1,)\n",
      " - description: MC history w/o holes\n",
      " - created by mbruno at macthxbruno.fritz.box on Sat Aug 20 14:42:09 2022\n",
      " - size: 46 KB\n",
      " - mean: [0.77002284]\n",
      " - Ensemble EnsA\n",
      "    - Replica 0 with ncnfg 1000\n",
      "         temporary additional memory required 0.015 MB\n",
      "\n",
      "Observable with shape = (1,)\n",
      " - description: MC history w/ holes\n",
      " - created by mbruno at macthxbruno.fritz.box on Sat Aug 20 14:42:09 2022\n",
      " - size: 32 KB\n",
      " - mean: [0.6241264]\n",
      " - Ensemble EnsA\n",
      "    - Replica 0 with ncnfg 515\n",
      "         temporary additional memory required 0.015 MB\n",
      "\n"
     ]
    }
   ],
   "source": [
    "mask = rng.sample_boolean(1000)\n",
    "icnfg = numpy.arange(1000)\n",
    "\n",
    "obsB = pyobs.observable(description='MC history w/o holes')\n",
    "obsB.create('EnsA',data1, icnfg=list(icnfg))\n",
    "obsB.peek()\n",
    "\n",
    "obsC = pyobs.observable(description='MC history w/ holes')\n",
    "obsC.create('EnsA',data1[mask], icnfg=list(icnfg[mask]))\n",
    "obsC.peek()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "0caa3599",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Full MC history\n",
      "{'EnsA': [array([3.82836706]), array([1.05540797])]}\n",
      "MC history w/ holes\n",
      "{'EnsA': [array([3.91062104]), array([1.37858042])]}\n"
     ]
    }
   ],
   "source": [
    "print('Full MC history')\n",
    "print(obsB.tauint())\n",
    "print('MC history w/ holes')\n",
    "print(obsC.tauint())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "71580391",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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