{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "9eb831f3-66b4-4601-9e84-fe801e7aa9fc",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "source": [
    "# Solute and water transport parameters"
   ]
  },
  {
   "cell_type": "code",
   "id": "b6cc47ef-4c99-4005-b041-b44dcb72312d",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": [],
    "ExecuteTime": {
     "end_time": "2026-02-26T10:28:32.239372Z",
     "start_time": "2026-02-26T10:28:31.363049Z"
    }
   },
   "source": [
    "from openalea.widgets.plantgl import PlantGL # notebook viewer 3D\n",
    "from openalea.plantgl.algo.view import view # 2D view\n",
    "\n",
    "from openalea.hydroroot.main import root_builder, hydroroot_solute_flow\n",
    "from openalea.hydroroot.init_parameter import Parameters\n",
    "from openalea.hydroroot.read_file import read_archi_data\n",
    "from openalea.hydroroot.display import mtg_scene\n"
   ],
   "outputs": [],
   "execution_count": 1
  },
  {
   "cell_type": "markdown",
   "id": "6d85c30b-723a-420a-8491-1da6c84f697c",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "source": [
    "Read the yaml file and set the Parameters variables, assuming that the code is run from the example folder"
   ]
  },
  {
   "cell_type": "code",
   "id": "e8f87e3b-3e41-476a-9aa2-c2ad676606cf",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": [],
    "ExecuteTime": {
     "end_time": "2026-02-26T10:28:32.253194Z",
     "start_time": "2026-02-26T10:28:32.245188Z"
    }
   },
   "source": [
    "parameter = Parameters()\n",
    "parameter.read_file('parameters_Ctr-3P2.yml')"
   ],
   "outputs": [],
   "execution_count": 2
  },
  {
   "cell_type": "markdown",
   "id": "11548f4b-dd19-43b3-b4e8-5ceff22b2684",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "source": [
    "Read the architecture file and build the MTG"
   ]
  },
  {
   "cell_type": "code",
   "id": "62a1f2a1-0aa6-492c-8b6f-5c20a7ab3f28",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": [],
    "ExecuteTime": {
     "end_time": "2026-02-26T10:28:32.393348Z",
     "start_time": "2026-02-26T10:28:32.293820Z"
    }
   },
   "source": [
    "fname = parameter.archi['input_dir'] + parameter.archi['input_file'][0]\n",
    "df = read_archi_data(fname)\n",
    "g, primary_length, total_length, surface, seed = root_builder( primary_length = parameter.archi['primary_length'],\n",
    "                                                                delta = parameter.archi['branching_delay'],\n",
    "                                                                nude_length = parameter.archi['nude_length'], \n",
    "                                                                df = df,\n",
    "                                                                segment_length = parameter.archi['segment_length'],\n",
    "                                                                length_data = parameter.archi['length_data'],\n",
    "                                                                order_max = parameter.archi['order_max'],\n",
    "                                                                order_decrease_factor = parameter.archi['order_decrease_factor'],\n",
    "                                                                ref_radius = parameter.archi['ref_radius'])"
   ],
   "outputs": [],
   "execution_count": 3
  },
  {
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "cell_type": "markdown",
   "source": "In the code the concentration are in $mol.\\mu L^{-1}$, then we convert them from $mol.m^{-3}$",
   "id": "b7185f39f382a967"
  },
  {
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": [],
    "ExecuteTime": {
     "end_time": "2026-02-26T10:28:32.408579Z",
     "start_time": "2026-02-26T10:28:32.406473Z"
    }
   },
   "cell_type": "code",
   "source": [
    "Cse = parameter.solute['Cse'] * 1e-9 # mol/m3 -> mol/microL, external permeating solute concentration\n",
    "Ce = parameter.solute['Ce'] * 1e-9 # mol/m3 -> mol/microL, external non-permeating solute concentration"
   ],
   "id": "8865eb091ed8b66c",
   "outputs": [],
   "execution_count": 4
  },
  {
   "cell_type": "markdown",
   "id": "28d53799-afd2-4df8-9178-8b7204706d59",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "source": "Perform the calculation"
  },
  {
   "cell_type": "code",
   "id": "f5c05023-42e7-4aef-b4cf-eee675a24f5e",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": [],
    "ExecuteTime": {
     "end_time": "2026-02-26T10:28:32.771414Z",
     "start_time": "2026-02-26T10:28:32.453761Z"
    }
   },
   "source": [
    "g, Jv = hydroroot_solute_flow(g, psi_e = parameter.exp['psi_e'],\n",
    "                                psi_base = parameter.exp['psi_base'],\n",
    "                                k0 = parameter.hydro['k0'],\n",
    "                                axial_conductivity_data = parameter.hydro['axial_conductance_data'],\n",
    "                                J_s = parameter.solute['J_s'],\n",
    "                                Ps=parameter.solute['P_s'],\n",
    "                                Cse = Cse,\n",
    "                                Ce=Ce,\n",
    "                                sigma = parameter.solute['Sigma'])"
   ],
   "outputs": [],
   "execution_count": 5
  },
  {
   "cell_type": "code",
   "id": "8cb74613-2f9c-418a-af07-8247f6d5b4a6",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": [],
    "ExecuteTime": {
     "end_time": "2026-02-26T10:28:32.783465Z",
     "start_time": "2026-02-26T10:28:32.778675Z"
    }
   },
   "source": [
    "result=f\"\"\"\n",
    "primary length (m): {primary_length}\n",
    "surface (m2): {surface}\n",
    "total length (m): {total_length}\n",
    "flux (microL/s): {Jv}\n",
    "\"\"\"\n",
    "print(result)"
   ],
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "primary length (m): 0.434\n",
      "surface (m2): 0.005643500494241343\n",
      "total length (m): 3.979\n",
      "flux (microL/s): 0.025700314390474904\n",
      "\n"
     ]
    }
   ],
   "execution_count": 6
  },
  {
   "cell_type": "markdown",
   "id": "0707c4b6-d135-4e8f-9ac0-7ee15962a0e7",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "source": [
    "Display the concentration in the architecture 3D view"
   ]
  },
  {
   "cell_type": "code",
   "id": "7fc6e80b-5927-429a-ac7b-a2c90ffa30d5",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": [],
    "ExecuteTime": {
     "end_time": "2026-02-26T10:28:33.924358Z",
     "start_time": "2026-02-26T10:28:32.827790Z"
    }
   },
   "source": [
    "s = mtg_scene(g, prop_cmap = 'C') # create a scene from the mtg with the property j is the radial flux in ul/s\n",
    "PlantGL(s)"
   ],
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Plot(antialias=3, axes=['x', 'y', 'z'], axes_helper=1.0, axes_helper_colors=[16711680, 65280, 255], background…"
      ],
      "application/vnd.jupyter.widget-view+json": {
       "version_major": 2,
       "version_minor": 0,
       "model_id": "584d9a2bf0734c209206a738e1942f32"
      }
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 7
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-02-26T10:28:34.201735Z",
     "start_time": "2026-02-26T10:28:33.947700Z"
    }
   },
   "cell_type": "code",
   "source": [
    "g, Jv = hydroroot_solute_flow(g, psi_e = parameter.exp['psi_base'],\n",
    "                                psi_base = parameter.exp['psi_base'],\n",
    "                                k0 = parameter.hydro['k0'],\n",
    "                                axial_conductivity_data = parameter.hydro['axial_conductance_data'],\n",
    "                                J_s = parameter.solute['J_s'],\n",
    "                                Ps=parameter.solute['P_s'],\n",
    "                                Cse = Cse,\n",
    "                                Ce=Ce,\n",
    "                                sigma = parameter.solute['Sigma'])\n",
    "result=f\"\"\"\n",
    "primary length (m): {primary_length:.3f}\n",
    "surface (m2): {surface:.3e}\n",
    "total length (m): {total_length:.3f}\n",
    "flux (microL/s): {Jv:.4f}\n",
    "\"\"\"\n",
    "print(result)"
   ],
   "id": "30bb6ef9b4de542a",
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "primary length (m): 0.434\n",
      "surface (m2): 5.644e-03\n",
      "total length (m): 3.979\n",
      "flux (microL/s): 0.0072\n",
      "\n"
     ]
    }
   ],
   "execution_count": 8
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": [
    "#### Adjustement of Js\n",
    "\n",
    "Let try to adjust the active pumping rate `Js` to simulate a higher flux `Jv_to_fit`\n",
    "\n",
    "The adjustement is done by a simple Newton-Raphson scheme"
   ],
   "id": "379068dc79a7c3b0"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-02-26T10:28:38.446573Z",
     "start_time": "2026-02-26T10:28:34.207862Z"
    }
   },
   "cell_type": "code",
   "source": [
    "Jv_to_fit = 0.01\n",
    "Js_old = parameter.solute['J_s']\n",
    "F_old = (Jv - Jv_to_fit) ** 2.0  # the objective function\n",
    "Js = 1.1*parameter.solute['J_s']  # to initiate a simulation in the loop to compare with the previous one\n",
    "eps = 1e-10  # the accuracy wanted\n",
    "F = 1.  # to launch the loop\n",
    "# Newton-Raphson loop to get Js\n",
    "while (F > eps):\n",
    "    g, Jv = hydroroot_solute_flow(g, psi_e = parameter.exp['psi_e'],\n",
    "                                    psi_base = parameter.exp['psi_base'],\n",
    "                                    k0 = parameter.hydro['k0'],\n",
    "                                    axial_conductivity_data = parameter.hydro['axial_conductance_data'],\n",
    "                                    J_s = Js,\n",
    "                                    Ps=parameter.solute['P_s'],\n",
    "                                    Cse = Cse,\n",
    "                                    Ce=Ce,\n",
    "                                    sigma = parameter.solute['Sigma'])\n",
    "\n",
    "    F = (Jv - Jv_to_fit) ** 2.0  # the objective function\n",
    "    if abs(F) > eps:\n",
    "        dfdJs = (F - F_old) / (Js - Js_old)  # the derivative of F according to Js\n",
    "        Js_old = Js\n",
    "        Js = Js_old - F / dfdJs  # new estimate\n",
    "        F_old = F"
   ],
   "id": "de146e8361e19cd2",
   "outputs": [],
   "execution_count": 9
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-02-26T10:28:38.695810Z",
     "start_time": "2026-02-26T10:28:38.692685Z"
    }
   },
   "cell_type": "code",
   "source": [
    "result=f\"\"\"\n",
    "Jv to fit: {Jv_to_fit:.4f}\n",
    "Simulated Jv: {Jv:.4f}\n",
    "Js 1st guess: {parameter.solute['J_s']:.3e}\n",
    "adjusted Js: {Js:.3e}\n",
    "\"\"\"\n",
    "print(result)"
   ],
   "id": "855f3d719ef3fed2",
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Jv to fit: 0.0100\n",
      "Simulated Jv: 0.0100\n",
      "Js 1st guess: 1.714e-07\n",
      "adjusted Js: 2.864e-07\n",
      "\n"
     ]
    }
   ],
   "execution_count": 10
  }
 ],
 "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": "3.13.12"
  },
  "widgets": {
   "application/vnd.jupyter.widget-state+json": {
    "state": {},
    "version_major": 2,
    "version_minor": 0
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}