tutorials/pySonata/compartment-reports.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Compartment Reports\n",
    "\n",
    "SONATA's compartment reports are a hdf5-based format for storing cell time-series variables, like membrane potential or calcium concentration, for multi-compartment or point (eg single compartment) neurons. With an emphasis on recording values from large-scale simulations that involves hundreds to millions of indivdiual cells.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Recording compartment reports\n",
    "\n",
    "The pySonata reports module includes code for writing (and reading) SONATA compliant files. To start with we must create a CompartmentReport object with the name of the final file that will be generated (**output/membrane_potentials.h5**). As the name suggests we are simulating the recording of membrane potential (variable=mV) in units of mV. We assume that we are recording at uniform intervals at 0.1 ms for 100.0 ms total time."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "\n",
    "from sonata.reports.compartment import CompartmentReport"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "cr = CompartmentReport('output/membrane_potentials.h5', mode='w', tstart=0.0, tstop=100.0, dt=0.1, \n",
    "                       units='mV', variable='mV')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Before we start recording the membrane potential we must specify what nodes (eg cells) will be part of the recording. Every node is identified by a unique node_id and the population (in this case Visual Area 1) it belongs  to. \n",
    "\n",
    "A single cell has multiple points of recordings, which is identified by the element (eg segment) id and the position along the element being recorded from. Here was are setting:\n",
    " * node 0 has 100 segments, we are recording from the center of each one.\n",
    " * node 1 is a point neuron\n",
    " * node 2 may have multiple segments, but we are only recording from 3 equidistant points in segment 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "cr.add_cell(node_id=0, element_ids=range(100), element_pos=[0.5]*100, population='V1')\n",
    "cr.add_cell(node_id=1, element_ids=[0], element_pos=[0.0], population='V1')\n",
    "cr.add_cell(node_id=2, element_ids=[0, 0, 0], element_pos=[0.25, 0.5, 0.75], population='V1')\n",
    "cr.initialize()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next step is to actually record the variable across all nodes/segment. You can do that incrementally at each time-step:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "for t in range(0, 1000):\n",
    "    cr.record_cell(node_id=0, population='V1', vals=[-25.5]*100, tstep=t)\n",
    "    cr.record_cell(node_id=1, population='V1', vals=-60+t*0.6, tstep=t)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "or record a large block of times"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "cr.record_cell_block(node_id=2, population='V1', vals=np.random.uniform(-55.0, 10.0, size=(1000, 3)), \n",
    "                     beg_step=0, end_step=999)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "cr.close()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Extras"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Setting a default population\n",
    "\n",
    "Often there is only a single population of nodes being recorded from, which makes specifcying the *population* parameter during each call to add_cell redundant and cumbersome. In this case use the *default_population* parameter when initalizing the report:\n",
    "\n",
    "```python\n",
    "cr = Compartment_report('output/membrane_potentials.h5, mode='w, default_population='V1', ...)\n",
    "cr.add_cell(node_id=0, element_ids=range(100), element_pos=[0.5]*100)\n",
    "...\n",
    "```\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Non-uniform recording\n",
    "\n",
    "By default the sonata format assumes that the variables are being recorded at uniform intervals, which allows the time-trace to be stored and represented using only three values: *tstart*, *tstop*, *dt*. If the time trace is non-uniform then you can use the set_time_trace() method instead:\n",
    "\n",
    "```python\n",
    "cr = Compartment_report('output/membrane_potentials.h5, mode='w, default_population='V1', n_steps=1000)\n",
    "cr.set_time_trace(np.logspace(0.0, 2.0, num=1000))\n",
    "...\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Parallelized Recordings\n",
    "\n",
    "The API is designed to work with MPI when running a simulation across multiple cores, assuming different cells (or different elements of a cell) are divided up among each core. \n",
    "\n",
    "```python\n",
    "from mpi4py import MPI\n",
    "rank = MPI.COMM_WORLD.comm.Get_rank()\n",
    "\n",
    "cr = CompartmentReport('output/membrane_potentials.h5', mode='w', tstart=0.0, tstop=100.0, dt=0.1, \n",
    "                       units='mV', variable='mV')\n",
    "\n",
    "if rank == 0:\n",
    "    cr.add_cell(node_id=0, element_ids=range(100), element_pos=[0.5]*100, population='V1')\n",
    "    cr.initalize()\n",
    "    cr.record_cell_block(node_id=0, population='V1', vals=np.random.uniform(-55.0, 10.0, size=(1000, 100)),\n",
    "                         beg_step=0, end_step=999)\n",
    "elif rank == 1:\n",
    "    cr.add_cell(node_id=1, element_ids=[0], element_pos=[0.0], population='V1')\n",
    "    cr.initalize()\n",
    "    cr.record_cell_block(node_id=1, population='V1', vals=np.random.uniform(-55.0, 10.0, size=1000), \n",
    "                         beg_step=0, end_step=999)\n",
    "\n",
    "cr.close()\n",
    "\n",
    "```\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Reading\n",
    "\n",
    "Now that we have generated (or given) a compartmental report we want to be able to read it into our code. To do so make sure to open the hdf5 file in read (**r**) mode:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "cr = CompartmentReport('output/membrane_potentials.h5', mode='r')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A report may contain multiple populations of nodes. In the above case there was only one (V1):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "populations: ['V1']\n",
      "V1\n",
      " node ids: [0 1 2]\n",
      " variable: mV\n",
      " units: mV\n"
     ]
    }
   ],
   "source": [
    "print('populations: {}'.format(cr.populations))\n",
    "print('V1')\n",
    "v1_voltages = cr['V1']\n",
    "print(' node ids: {}'.format(v1_voltages.node_ids()))\n",
    "print(' variable: {}'.format(v1_voltages.units()))\n",
    "print(' units: {}'.format(v1_voltages.units()))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can also get the time-trace for the simulation as a numpy array."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "simulation steps: [  0.           0.1001001    0.2002002    0.3003003    0.4004004\n",
      "   0.5005005    0.6006006    0.7007007    0.8008008    0.9009009\n",
      "   1.001001     1.1011011    1.2012012    1.3013013    1.4014014\n",
      "   1.5015015    1.6016016    1.7017017    1.8018018    1.9019019\n",
      "   2.002002     2.1021021    2.2022022    2.3023023    2.4024024\n",
      "   2.5025025    2.6026026    2.7027027    2.8028028    2.9029029\n",
      "   3.003003     3.1031031    3.2032032    3.3033033    3.4034034\n",
      "   3.5035035    3.6036036    3.7037037    3.8038038    3.9039039\n",
      "   4.004004     4.1041041    4.2042042    4.3043043    4.4044044\n",
      "   4.5045045    4.6046046    4.7047047    4.8048048    4.9049049\n",
      "   5.00500501   5.10510511   5.20520521   5.30530531   5.40540541\n",
      "   5.50550551   5.60560561   5.70570571   5.80580581   5.90590591\n",
      "   6.00600601   6.10610611   6.20620621   6.30630631   6.40640641\n",
      "   6.50650651   6.60660661   6.70670671   6.80680681   6.90690691\n",
      "   7.00700701   7.10710711   7.20720721   7.30730731   7.40740741\n",
      "   7.50750751   7.60760761   7.70770771   7.80780781   7.90790791\n",
      "   8.00800801   8.10810811   8.20820821   8.30830831   8.40840841\n",
      "   8.50850851   8.60860861   8.70870871   8.80880881   8.90890891\n",
      "   9.00900901   9.10910911   9.20920921   9.30930931   9.40940941\n",
      "   9.50950951   9.60960961   9.70970971   9.80980981   9.90990991\n",
      "  10.01001001  10.11011011  10.21021021  10.31031031  10.41041041\n",
      "  10.51051051  10.61061061  10.71071071  10.81081081  10.91091091\n",
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      "  11.51151151  11.61161161  11.71171171  11.81181181  11.91191191\n",
      "  12.01201201  12.11211211  12.21221221  12.31231231  12.41241241\n",
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      "  30.03003003  30.13013013  30.23023023  30.33033033  30.43043043\n",
      "  30.53053053  30.63063063  30.73073073  30.83083083  30.93093093\n",
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      "  32.03203203  32.13213213  32.23223223  32.33233233  32.43243243\n",
      "  32.53253253  32.63263263  32.73273273  32.83283283  32.93293293\n",
      "  33.03303303  33.13313313  33.23323323  33.33333333  33.43343343\n",
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      "  34.03403403  34.13413413  34.23423423  34.33433433  34.43443443\n",
      "  34.53453453  34.63463463  34.73473473  34.83483483  34.93493493\n",
      "  35.03503504  35.13513514  35.23523524  35.33533534  35.43543544\n",
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      "  36.53653654  36.63663664  36.73673674  36.83683684  36.93693694\n",
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      "  38.53853854  38.63863864  38.73873874  38.83883884  38.93893894\n",
      "  39.03903904  39.13913914  39.23923924  39.33933934  39.43943944\n",
      "  39.53953954  39.63963964  39.73973974  39.83983984  39.93993994\n",
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      "  40.54054054  40.64064064  40.74074074  40.84084084  40.94094094\n",
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      "  65.06506507  65.16516517  65.26526527  65.36536537  65.46546547\n",
      "  65.56556557  65.66566567  65.76576577  65.86586587  65.96596597\n",
      "  66.06606607  66.16616617  66.26626627  66.36636637  66.46646647\n",
      "  66.56656657  66.66666667  66.76676677  66.86686687  66.96696697\n",
      "  67.06706707  67.16716717  67.26726727  67.36736737  67.46746747\n",
      "  67.56756757  67.66766767  67.76776777  67.86786787  67.96796797\n",
      "  68.06806807  68.16816817  68.26826827  68.36836837  68.46846847\n",
      "  68.56856857  68.66866867  68.76876877  68.86886887  68.96896897\n",
      "  69.06906907  69.16916917  69.26926927  69.36936937  69.46946947\n",
      "  69.56956957  69.66966967  69.76976977  69.86986987  69.96996997\n",
      "  70.07007007  70.17017017  70.27027027  70.37037037  70.47047047\n",
      "  70.57057057  70.67067067  70.77077077  70.87087087  70.97097097\n",
      "  71.07107107  71.17117117  71.27127127  71.37137137  71.47147147\n",
      "  71.57157157  71.67167167  71.77177177  71.87187187  71.97197197\n",
      "  72.07207207  72.17217217  72.27227227  72.37237237  72.47247247\n",
      "  72.57257257  72.67267267  72.77277277  72.87287287  72.97297297\n",
      "  73.07307307  73.17317317  73.27327327  73.37337337  73.47347347\n",
      "  73.57357357  73.67367367  73.77377377  73.87387387  73.97397397\n",
      "  74.07407407  74.17417417  74.27427427  74.37437437  74.47447447\n",
      "  74.57457457  74.67467467  74.77477477  74.87487487  74.97497497\n",
      "  75.07507508  75.17517518  75.27527528  75.37537538  75.47547548\n",
      "  75.57557558  75.67567568  75.77577578  75.87587588  75.97597598\n",
      "  76.07607608  76.17617618  76.27627628  76.37637638  76.47647648\n",
      "  76.57657658  76.67667668  76.77677678  76.87687688  76.97697698\n",
      "  77.07707708  77.17717718  77.27727728  77.37737738  77.47747748\n",
      "  77.57757758  77.67767768  77.77777778  77.87787788  77.97797798\n",
      "  78.07807808  78.17817818  78.27827828  78.37837838  78.47847848\n",
      "  78.57857858  78.67867868  78.77877878  78.87887888  78.97897898\n",
      "  79.07907908  79.17917918  79.27927928  79.37937938  79.47947948\n",
      "  79.57957958  79.67967968  79.77977978  79.87987988  79.97997998\n",
      "  80.08008008  80.18018018  80.28028028  80.38038038  80.48048048\n",
      "  80.58058058  80.68068068  80.78078078  80.88088088  80.98098098\n",
      "  81.08108108  81.18118118  81.28128128  81.38138138  81.48148148\n",
      "  81.58158158  81.68168168  81.78178178  81.88188188  81.98198198\n",
      "  82.08208208  82.18218218  82.28228228  82.38238238  82.48248248\n",
      "  82.58258258  82.68268268  82.78278278  82.88288288  82.98298298\n",
      "  83.08308308  83.18318318  83.28328328  83.38338338  83.48348348\n",
      "  83.58358358  83.68368368  83.78378378  83.88388388  83.98398398\n",
      "  84.08408408  84.18418418  84.28428428  84.38438438  84.48448448\n",
      "  84.58458458  84.68468468  84.78478478  84.88488488  84.98498498\n",
      "  85.08508509  85.18518519  85.28528529  85.38538539  85.48548549\n",
      "  85.58558559  85.68568569  85.78578579  85.88588589  85.98598599\n",
      "  86.08608609  86.18618619  86.28628629  86.38638639  86.48648649\n",
      "  86.58658659  86.68668669  86.78678679  86.88688689  86.98698699\n",
      "  87.08708709  87.18718719  87.28728729  87.38738739  87.48748749\n",
      "  87.58758759  87.68768769  87.78778779  87.88788789  87.98798799\n",
      "  88.08808809  88.18818819  88.28828829  88.38838839  88.48848849\n",
      "  88.58858859  88.68868869  88.78878879  88.88888889  88.98898899\n",
      "  89.08908909  89.18918919  89.28928929  89.38938939  89.48948949\n",
      "  89.58958959  89.68968969  89.78978979  89.88988989  89.98998999\n",
      "  90.09009009  90.19019019  90.29029029  90.39039039  90.49049049\n",
      "  90.59059059  90.69069069  90.79079079  90.89089089  90.99099099\n",
      "  91.09109109  91.19119119  91.29129129  91.39139139  91.49149149\n",
      "  91.59159159  91.69169169  91.79179179  91.89189189  91.99199199\n",
      "  92.09209209  92.19219219  92.29229229  92.39239239  92.49249249\n",
      "  92.59259259  92.69269269  92.79279279  92.89289289  92.99299299\n",
      "  93.09309309  93.19319319  93.29329329  93.39339339  93.49349349\n",
      "  93.59359359  93.69369369  93.79379379  93.89389389  93.99399399\n",
      "  94.09409409  94.19419419  94.29429429  94.39439439  94.49449449\n",
      "  94.59459459  94.69469469  94.79479479  94.89489489  94.99499499\n",
      "  95.0950951   95.1951952   95.2952953   95.3953954   95.4954955\n",
      "  95.5955956   95.6956957   95.7957958   95.8958959   95.995996\n",
      "  96.0960961   96.1961962   96.2962963   96.3963964   96.4964965\n",
      "  96.5965966   96.6966967   96.7967968   96.8968969   96.996997\n",
      "  97.0970971   97.1971972   97.2972973   97.3973974   97.4974975\n",
      "  97.5975976   97.6976977   97.7977978   97.8978979   97.997998\n",
      "  98.0980981   98.1981982   98.2982983   98.3983984   98.4984985\n",
      "  98.5985986   98.6986987   98.7987988   98.8988989   98.998999\n",
      "  99.0990991   99.1991992   99.2992993   99.3993994   99.4994995\n",
      "  99.5995996   99.6996997   99.7997998   99.8998999  100.        ]\n"
     ]
    }
   ],
   "source": [
    "print('simulation steps: {}'.format(cr.time_trace('V1')))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Use the **data()** method to get the recorded values for each cell. \n",
    "\n",
    "For a point neuron the **data** method returns a vector:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
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       "       [539.4]])"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "v1_voltages.data(node_id=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "When there are multiple recordings a matrix is returned, where the rows indicate a time-point and each column a different segement/position. You can use the **element_ids** and **element_pos** methods to map each column."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "element_ids: \n",
      "[0 0 0]\n",
      "element_pos: \n",
      "[0.25 0.5  0.75]\n",
      "data: \n",
      "[[-26.68004873 -44.57869137 -36.35318618]\n",
      " [-27.65466567 -30.37087527 -31.90339667]\n",
      " [-45.72573791  -7.59687698  -6.1168696 ]\n",
      " ...\n",
      " [-25.30565698 -40.37708363   8.16683852]\n",
      " [-42.98827417 -10.66182614 -45.61760536]\n",
      " [-47.5588135  -52.18320142  -8.49817789]]\n"
     ]
    }
   ],
   "source": [
    "print('element_ids: \\n{}'.format(v1_voltages.element_ids(node_id=2)))\n",
    "print('element_pos: \\n{}'.format(v1_voltages.element_pos(node_id=2)))\n",
    "print('data: \\n{}'.format(v1_voltages.data(node_id=2)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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