{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Surface-Volume Reactions\n",
    "\n",
    "<div class=\"admonition note\">\n",
    "**Topics**: Surface reactions, chained reactions, advanced ResultSelector usage.\n",
    "</div>\n",
    "\n",
    "The corresponding python script: [STEPS_Tutorial_IP3.py](https://github.com/CNS-OIST/STEPS_Example/tree/master/user_manual/source/API_2/scripts/STEPS_Tutorial_IP3.py)\n",
    "\n",
    "In the [previous chapter](STEPS_Tutorial_wm.ipynb) we declared reactions taking place inside a volume. In this chapter we consider another\n",
    "type of kinetic reaction, associated with the [steps.model.SurfaceSystem](API_model.rst#steps.API_2.model.SurfaceSystem) container, which defines a\n",
    "reaction taking place on a surface (or patch) connecting two compartments\n",
    "(arbitrarily naming one of them the “inner” compartment, and the other one\n",
    "the “outer” compartment). Reactants and products can therefore be freely moving\n",
    "around in a volume or embedded in a surface.\n",
    "Therefore, it is necessary to firstly specify the location of the reactant\n",
    "and product species.\n",
    "\n",
    "**_Note_**: *Surface reactions are designed to represent reactions where one\n",
    "   reactant is embedded in a membrane, but in fact if all reactants and\n",
    "   products belong to the same compartment and none appear on a patch\n",
    "   it will behave exactly like the equivalent volume reaction.*\n",
    "\n",
    "To become familiar with these reactions we will build a simplified version of\n",
    "the inositol 1,4,5-trisphosphate (IP $_{3}$) model\n",
    " (described in Doi T, et al,*Inositol\n",
    "   1,4,5-Triphosphate-Dependent* $Ca^{\\text{2+}}$ *Threshold Dynamics\n",
    "   Detect Spike Timing in Cerebellar Purkinje Cells*, J Neurosci 2005, 25(4):950-961) in STEPS.\n",
    "   \n",
    "![The IP3 receptor model](images/ip3_2.png)\n",
    " \n",
    "In the IP3 receptor model, reactions (i.e. receptor binding of calcium and IP3 molecules) take place on the membrane separating the Endoplasmic Reticulum (ER) and the cytosol. Therefore, we will need to declare surface reactions.\n",
    "   \n",
    "In the figure below we can see a  schematic diagram of the states\n",
    "and transitions in the model. IP3 receptors are embedded in the ER membrane, each “binding” reaction is described\n",
    "by a second order surface reaction and each “unbinding” reaction by a first order surface reaction.\n",
    " \n",
    "![The IP3 receptor kinetic scheme](images/ip3_model.png)\n",
    "\n",
    "\n",
    "We will go through the Python code to build this model in STEPS,\n",
    "but providing only brief descriptions of operations we are familiar\n",
    "with from the previous chapter.\n",
    "\n",
    "## Model declaration\n",
    "\n",
    "## Surface reactions\n",
    "\n",
    "STEPS surface reactions can deal with three types of reactions, classified by the locations of the reactants:\n",
    "\n",
    "- **Volume-Surface reactions**.   In this case molecules within a volume interact with molecules embedded in a surface and result in products that may reside within in a volume or a surface. The units for the reaction parameters in this case are the same as for ordinary volume reactions, namely: a first order reaction parameter has units $s^{-1}$; a second order reaction parameter has units $\\left(M.s\\right)^{-1}$; a third order reaction $\\left(M^{2}.s\\right)^{-1}$; and so on.\n",
    "\n",
    "- **Surface-Surface reactions**.   In this case the reactants are all embedded in a surface. Quite clearly, the dimensions of the reaction are different from a volume reaction and the reaction parameter is assumed to be two-dimensional. This is an important point because the reaction parameter will be treated differently from a volume-volume or volume-surface interaction. A further complication is that parameters for ordinary volume reactions are based on the litre, where there is no convenient equivalent 2D concentration unit.   Surface-surface reaction parameters are based on units of area of **square meters**. **A first order surface-surface reaction parameter is therefore required in units of** $s^{-1}$; **a second-order surface-surface reaction parameter has units** $\\left(mol.m^{-2}\\right)^{-1}.s^{-1}$; **a third-order surface-surface reaction parameter has units** $\\left(mol.m^{-2}\\right)^{-2}.s^{-1}$; and so on.   Zero-order surface reactions are not supported because of the ambiguity of interpreting the reaction parameter.\n",
    "\n",
    "- **Volume-Volume reactions**. \n",
    "   It is possible for a surface reaction to contain reactant species that are all in a volume, in which case the reaction behaves similarly to an ordinary volume reaction, though products may belong to connected volumes or surfaces.\n",
    "\n",
    "As mentioned previously, to declare surface reactions we have to include some information about the location of the reaction:\n",
    "which compartment are the reactants to be found in, and are any molecules embedded in a surface and which of the two compartments that the surface connects are the products injected into? We supply this information to STEPS by labelling our compartments that a patch connects, arbitrarily choosing the labels 'inner' and 'outer'. When the surface reaction's parent surface system object is added to a certain patch, the compartment labelling in the surface reaction stoichiometry will match the compartment labelling in the patch definition. We will come to creating a patch later in this chapter.\n",
    "\n",
    "So, at this stage we must chose which compartment we will label 'outer'\n",
    "and which we will label 'inner' and make sure to maintain this labelling\n",
    "throughout our definitions, and also in our geometry description.\n",
    "We chose to label the cytosol as the 'outer' compartment and the ER\n",
    "as the 'inner' compartment, so should be very careful that this ties in correctly to our description when\n",
    "we create our [steps.geom.Patch](API_geom.rst#steps.API_2.geom.Patch) object to represent a surface to connect the two compartments.\n",
    "\n",
    "When writing a surface reaction, we can specify the location of each reactant in two different ways. The most verbose consist in using functions [In](API_model.rst#steps.API_2.model.In), [Out](API_model.rst#steps.API_2.model.Out) and [Surf](API_model.rst#steps.API_2.model.Surf) to refer respectively to the inner compartment, the outer compartment, and the patch surface:\n",
    "```python\n",
    "Surf(R) + Out(IP3) <r[1]> Surf(RIP3)\n",
    "```\n",
    "\n",
    "The same reactions can be declared in a slightly more concise way:\n",
    "```python\n",
    "R.s + IP3.o <r[1]> RIP3.s\n",
    "```\n",
    "\n",
    "Adding `.s`, `.i`, or `.o` after a reactant is a shorthand way to specify its location. This notation aims at imitating subscripts like in: $\\mathrm{R_s + IP3_o \\leftrightarrow RIP3_s}$\n",
    "\n",
    "<div class=\"admonition note\">\n",
    "**Note**: Reactant species cannot belong to different compartments, so attempting to create a surface reaction with both `Spec1.i` and `Spec2.o` will result in an error.\n",
    "</div>\n",
    "\n",
    "## Surface reactions declaration\n",
    "\n",
    "Let us now declare all our reactions. As in the previous chapter, we first import the required packages, create the `Model`, a `ReactionManager`, and declare `Species`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import steps.interface\n",
    "\n",
    "from steps.model import *\n",
    "from steps.geom import *\n",
    "from steps.rng import *\n",
    "from steps.sim import *\n",
    "from steps.saving import *\n",
    "\n",
    "r = ReactionManager()\n",
    "\n",
    "mdl = Model()\n",
    "\n",
    "with mdl:\n",
    "    Ca, IP3, R, RIP3, Ropen, RCa, R2Ca, R3Ca, R4Ca = Species.Create()\n",
    "    surfsys = SurfaceSystem.Create()\n",
    "    \n",
    "    with surfsys:\n",
    "        # IP3 and activating Ca binding\n",
    "        R.s    + IP3.o <r['r1']> RIP3.s\n",
    "        RIP3.s + Ca.o  <r['r2']> Ropen.s\n",
    "        r['r1'].K = 1000e6, 25800\n",
    "        r['r2'].K = 8000e6, 2000\n",
    "        \n",
    "        # Inactivating Ca binding\n",
    "        R.s    + Ca.o <r['r3']> RCa.s\n",
    "        RCa.s  + Ca.o <r['r4']> R2Ca.s\n",
    "        R2Ca.s + Ca.o <r['r5']> R3Ca.s\n",
    "        R3Ca.s + Ca.o <r['r6']> R4Ca.s\n",
    "        r['r3'].K = 8.889e6, 5\n",
    "        r['r4'].K = 20e6, 10\n",
    "        r['r5'].K = 40e6, 15\n",
    "        r['r6'].K = 60e6, 20\n",
    "\n",
    "        # Ca ions passing through open IP3R channel\n",
    "        Ca.i + Ropen.s >r[1]> Ropen.s + Ca.o\n",
    "        r[1].K = 2e8"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note that each possible state of an IP3 receptor is declared as a dinstinct species.\n",
    "We then declare a `SurfaceSystem` instead of a `VolumeSystem` and the reactions are declared using the context manager `with` keyword, as previously seen.\n",
    "All reactions are reversible (using `<r[...]>`) except for the last one (using `>r[...]>`), that represents calcium leaving the ER through the open IP3R channel.\n",
    "\n",
    "By using the `.K` property, we set all reaction constants' default values (see Doi T, et al,*Inositol\n",
    "   1,4,5-Triphosphate-Dependent* $Ca^{\\text{2+}}$ *Threshold Dynamics\n",
    "   Detect Spike Timing in Cerebellar Purkinje Cells*, J Neurosci 2005, 25(4):950-961). Since these are volume-surface interactions, we must make\n",
    "sure to supply our values in Molar units as  discussed previously in this chapter.\n",
    "\n",
    "Note that, when several reactants bind sequentially (to a receptor like here for example), it is possible to chain the reactions using parentheses:\n",
    "```python\n",
    "(R.s + IP3.o <r[1]> RIP3.s) + Ca.o <r[2]> Ropen.s\n",
    "```\n",
    "Reactions that are in parentheses are equivalent to their right hand side. The above line thus first declares the reaction in the parentheses `R.s + IP3.o <r[1]> RIP3.s` and replaces it by its right hand side; the line then reads `RIP3.s + Ca.o <r[2]> Ropen.s` and this reaction is declared. The whole process is thus equivalent to declaring the reactions on two separate lines.\n",
    "\n",
    "<div class=\"admonition warning\">\n",
    "**Warning**: Chained reactions can be a bit hard to read so their use should probably be restricted to sequential bindings.\n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Geometry specification\n",
    "\n",
    "The next step is to create the geometry for the model. We will choose well-mixed\n",
    "geometry, as in the [chapter on well-mixed models](STEPS_Tutorial_wm.ipynb), but we now have two compartments which\n",
    "are connected by a surface 'patch'. We create two [steps.geom.Compartment](API_geom.rst#steps.API_2.geom.Compartment) objects\n",
    "to represent the Endoplasmic Reticulum (which we intend to label the 'inner'\n",
    "compartment) and the cytosol ('outer' compartment), and a [steps.geom.Patch](API_geom.rst#steps.API_2.geom.Patch)\n",
    "object to represent the ER membrane between the ER and cytosol."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "geom = Geometry()\n",
    "with geom:\n",
    "    # Create the cytosol and Endoplasmic Reticulum compartments\n",
    "    cyt, ER = Compartment.Create()\n",
    "    cyt.Vol = 1.6572e-19\n",
    "    ER.Vol = 1.968e-20\n",
    "\n",
    "    # ER is the 'inner' compartment, cyt is the 'outer' compartment\n",
    "    memb = Patch.Create(ER, cyt, surfsys)\n",
    "    memb.Area = 0.4143e-12"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First we create the two well-mixed compartments at once with `cyt, ER = Compartment.Create()`. Since no parameters were given to `Create()`, we explicitely set the volume of each compartment by using the `.Vol` property.\n",
    "Since we only defined a `SurfaceSystem` in the model, we do not need to associate our compartment with a `VolumeSystem`.\n",
    "\n",
    "We then create the `Patch` using the automatic naming syntax. This time, the `Create` method needs to receive at least the inner compartment. \n",
    "It is vital that care is taken in the order of the compartment objects to the constructor, so that the required labelling from our surface reaction\n",
    "definitions is maintained. **Note**: *A Patch must have an inner compartment by convention,\n",
    "   but does not require an outer compartment. This is an easy way to remember the order to the constructor; since an inner compartment is always required it must come first to the constructor, and the optional outer compartment comes after. Obviously any surface reaction\n",
    "   rules that contain reactants or products in the outer compartment cannot be\n",
    "   added to a Patch that doesn't have an outer compartment.*\n",
    "\n",
    "We can also specify the area of the patch during creation, like so:\n",
    "```python\n",
    "patchName = Patch.Create(innerComp, outerComp, surfSys, area)\n",
    "```\n",
    "In our example, we set the area of a patch after creation using the `.Area` property.\n",
    "\n",
    "We can check the labelling is as desired after object construction if we like with properties [steps.geom.Patch.innerComp](API_geom.rst#steps.API_2.geom.Patch.innerComp) and [steps.geom.Patch.outerComp](API_geom.rst#steps.API_2.geom.Patch.outerComp).:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ER\n",
      "cyt\n"
     ]
    }
   ],
   "source": [
    "print(memb.innerComp)\n",
    "print(memb.outerComp)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Simulation declaration and data saving\n",
    "\n",
    "We first create the random number generator and the `Simulation`. Like in the previous chapter, we will use the well-mixed `'Wmdirect'` solver:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model checking:\n",
      "No errors were found\n"
     ]
    }
   ],
   "source": [
    "rng = RNG('mt19937', 512, 7233)\n",
    "\n",
    "sim = Simulation('Wmdirect', mdl, geom, rng)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We then specify which data should be saved, this time we will declare two result selectors:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "rs = ResultSelector(sim)\n",
    "\n",
    "Rstates = rs.memb.MATCH('R.*').Count\n",
    "\n",
    "Reacs = rs.memb.MATCH('r[1-6]')['fwd'].Extent + rs.memb.MATCH('r[1-6]')['bkw'].Extent"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We have two `ResultSelector`s, `Rstates` and `Reacs`. `Rstates` makes use of the `MATCH(...)` function that only selects objects whose name matches the [regular expression](https://docs.python.org/3/howto/regex.html) given as a parameter. In our case, it will match all objects inside `memb` whose name starts with 'R', i.e. all receptors. It is equivalent to the longer:\n",
    "```python\n",
    "Rstates = rs.memb.LIST(R, RIP3, Ropen, RCa, R2Ca, R3Ca, R4Ca).Count\n",
    "```\n",
    "In our specific case, it happens to be equivalent to `rs.memb.ALL(Species).Count` because we did not define any other species on the ER membrane. The `MATCH` version is however preferable since it will still work if we decide to add other species.\n",
    "\n",
    "### Combining ResultSelectors\n",
    "\n",
    "<img src=\"images/resultselector_syntax.png\"/>\n",
    "\n",
    "The second `ResultSelector`, `Reacs` will save the extent of each reaction from 'r1' to 'r6', taking into account both forward and backward subreactions. To understand its declaration, we first need to see how reactions interact with `ResultSelector`s.\n",
    "The following `ResultSelector` will save both forward and backward extent of reaction 'r1':\n",
    "```python\n",
    "rs.memb.r1.Extent\n",
    "```\n",
    "Since it saves two values for each run and for each timestep (i.e. the third dimension of the associated data structure is 2, cf. previous tutorial), and for the sake of simplicity, we will say that it has length 2. To save specifically the forward extent, we write:\n",
    "```python\n",
    "rs.memb.r1['fwd'].Extent\n",
    "```\n",
    "and this `ResultSelector` has length 1. To save the total extent (the sum of forward and backward), one could write:\n",
    "```python\n",
    "rs.SUM(rs.memb.r1.Extent)\n",
    "```\n",
    "the `rs.SUM(...)` function takes a `ResultSelector` as an argument and returns a `ResultSelector` whose length is 1 and corresponds to the sum of all the values defined by the argument. In our case, it would be equivalent to:\n",
    "```python\n",
    "rs.memb.r1['fwd'].Extent + rs.memb.r1['bkw'].Extent\n",
    "```\n",
    "This `+` notation is also valid; standard arithmetic operators (`+`, `-`, `*`, `/`, and `**`) can all be used with `ResultSelector`s and behave in the same way as they do in numpy. The above example sums two `ResultSelector`s of length 1 and thus results in a `ResultSelector` of length one as well. If the length of the operands is higher than one, like in:\n",
    "```python\n",
    "rs.memb.LIST(r1, r2)['fwd'].Extent + rs.memb.LIST(r1, r2)['bkw'].Extent\n",
    "```\n",
    "the resulting `ResultSelector` has length 2, like the operands, and is equivalent to:\n",
    "```python\n",
    "rs.memb.r1['fwd'].Extent + rs.memb.r1['bkw'].Extent << rs.memb.r2['fwd'].Extent + rs.memb.r2['bkw'].Extent\n",
    "```\n",
    "In our main example, `Reacs` has length 6 and saves the total extent of each reaction whose name matches the regular expression 'r\\[1-6\\]' (the name has to start with character 'r' and then a number between 1 and 6).\n",
    "\n",
    "### Editing labels\n",
    "\n",
    "As we saw in the previous tutorial, labels are automatically generated when using `ResultSelector`s and can be accessed with e.g. `Rstates.labels`. With the same notation, it is also possible to provide custom labels by simply using:\n",
    "```python\n",
    "selector.labels = ['label 1', 'label2', ...]\n",
    "```\n",
    "The length of the list needs to match the length of the `ResultSelector`. Here, we will modify the automatically generated labels of `Rstates` which currently look like this: "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['memb.R.Count', 'memb.R2Ca.Count', 'memb.R3Ca.Count', 'memb.R4Ca.Count', 'memb.RCa.Count', 'memb.RIP3.Count', 'memb.Ropen.Count']\n"
     ]
    }
   ],
   "source": [
    "print(Rstates.labels)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Instead, we would like to only keep the species name:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['R', 'R2Ca', 'R3Ca', 'R4Ca', 'RCa', 'RIP3', 'Ropen']\n"
     ]
    }
   ],
   "source": [
    "Rstates.labels = [l.split('.')[1] for l in Rstates.labels]\n",
    "\n",
    "print(Rstates.labels)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Data saving\n",
    "\n",
    "As previously, we associate both `ResultSelector`s to the simulation and specify how frequently they should be saved:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "sim.toSave(Rstates, Reacs, dt=0.001)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If the results needed to be saved at different intervals, we could of course write:\n",
    "```python\n",
    "sim.toSave(Rstates, dt=0.001)\n",
    "sim.toSave(Reacs, dt=0.005)\n",
    "```\n",
    "In addition, if we wanted to save the data at specified timepoints, we could use the `timePoints` argument:\n",
    "```python\n",
    "sim.toSave(Reacs, timePoints=[0.0, 0.01, 0.03, 0.15])\n",
    "```\n",
    "\n",
    "### Running the simulation\n",
    "\n",
    "Having defined and added all `ResultSelector`s, we can then run the simulation:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "NITER = 100\n",
    "ENDT = 0.201\n",
    "\n",
    "for i in range (0, NITER):\n",
    "    sim.newRun()\n",
    "\n",
    "    sim.cyt.Ca.Conc = 3.30657e-8\n",
    "    sim.cyt.IP3.Count = 6\n",
    "    sim.ER.Ca.Conc = 150e-6\n",
    "    sim.ER.Ca.Clamped = True\n",
    "    sim.memb.R.Count = 160\n",
    "\n",
    "    sim.run(ENDT)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plotting the results\n",
    "\n",
    "We first plot the number of open IP3 receptors as a function of time:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from matplotlib import pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "plt.figure(figsize=(10, 7))\n",
    "\n",
    "RopenInd = Rstates.labels.index('Ropen')\n",
    "RopenData = Rstates.data[:, :, RopenInd]\n",
    "\n",
    "time = Rstates.time[0]\n",
    "mean = np.mean(RopenData, axis=0)\n",
    "std = np.std(RopenData, axis=0)\n",
    "\n",
    "plt.plot(time, mean, linewidth=2, label='Average')\n",
    "plt.fill_between(time, mean - std, mean + std, alpha=0.2, label='Std. Dev.')\n",
    "\n",
    "for t, d in zip(Rstates.time, RopenData):\n",
    "    plt.plot(t, d, color='grey', linewidth=0.1, zorder=-1)\n",
    "\n",
    "plt.ylim(0)\n",
    "plt.margins(0, 0.05)\n",
    "plt.xlabel('Time [s]')\n",
    "plt.ylabel('Number of open IP3R')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We first need to extract the data for `Ropen` from `Rstates`. We do so by using `Rstates.labels`; we are interested in `memb.Ropen.Count` so we simply call the python `index` method that returns the index of the `Ropen` data in the whole selector.\n",
    "We then get the corresponding data with `Rstates.data[:, :, RopenInd]`, the two first dimensions (runs and time) are untouched and we only take the data relative to `Ropen`.\n",
    "\n",
    "In order to display the trace corresponding to each run, we iterate on the data with:\n",
    "```python\n",
    "for t, d in zip(Rstates.time, RopenData):\n",
    "    plt.plot(t, d, color='grey', linewidth=0.1, zorder=-1)\n",
    "```\n",
    "\n",
    "We would then like to look at the time course of all receptor states:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10, 7))\n",
    "\n",
    "time = Rstates.time[0]\n",
    "mean = np.mean(Rstates.data, axis=0)\n",
    "std = np.std(Rstates.data, axis=0)\n",
    "\n",
    "plt.plot(time, mean, linewidth=2)\n",
    "for m, s in zip(mean.T, std.T):\n",
    "    plt.fill_between(time, m - s, m + s, alpha=0.2)\n",
    "\n",
    "plt.legend(Rstates.labels)\n",
    "plt.xlabel('Time [s]')\n",
    "plt.ylabel('Number of receptors')\n",
    "plt.ylim(0)\n",
    "plt.margins(0, 0.05)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Since `fill_between` cannot take all data at once, like `plot` can, we needed to iterate over the different receptor states in `mean` and `std`. To do so, we used:\n",
    "```python\n",
    "for m, s in zip(mean.T, std.T):\n",
    "    plt.fill_between(time, m - s, m + s, alpha=0.2)\n",
    "```\n",
    "both `mean` and `std` have dimension `(nbT, nbR)` with `nbT` the number of saved time points and `nbR` the number of receptor states. Since the first dimension corresponds to time, if we were to directly iterate over `mean` and `std`, we would iterate over time instead of iterating over receptor states. We thus first transpose the matrices with `mean.T` and `std.T`.\n",
    "\n",
    "We then turn to plotting data from `Reacs`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10, 7))\n",
    "\n",
    "time = Reacs.time[0]\n",
    "dt = time[1] - time[0]\n",
    "meanDeriv = np.mean(np.gradient(Reacs.data, dt, axis=1), axis=0)\n",
    "\n",
    "plt.stackplot(time, meanDeriv.T)\n",
    "\n",
    "plt.legend([f'd{l} / dt' for l in Reacs.labels])\n",
    "plt.margins(0, 0.05)\n",
    "plt.xlabel('Time [s]')\n",
    "plt.ylabel('Total reaction rate [1/s]')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here we want to look at the repartition of the actual rates of reactions. We use the [np.gradient](https://numpy.org/doc/stable/reference/generated/numpy.gradient.html) function that computes the derivative of the data with respect to the time axis (`axis=1`). We then average the values across runs using `np.mean` with `axis=0`. This time derivative of the extent of each reaction is a good proxy for the instantaneous actual rate of this reaction."
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.10.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}