NSE.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# !pipreqsnb --f\n",
    "# !pip3 install -q -r requirements.txt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "id": "X_gcCiaofjJW"
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "%matplotlib ipympl\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "import torch\n",
    "from torch import nn\n",
    "from torch.utils.data import Dataset, DataLoader\n",
    "from torchsummary import summary\n",
    "\n",
    "import os\n",
    "import itertools\n",
    "PATH = \"./nn\"\n",
    "\n",
    "import tqdm\n",
    "import tabulate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "('cpu', '2.1.0+cpu')"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "device = 'cuda' if torch.cuda.is_available() else 'cpu'\n",
    "device, torch.__version__"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 34
    },
    "id": "Va5CAu-yiXh7",
    "outputId": "f74065ef-20ba-4255-f6b1-519ca96a61f2"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2.220446049250313e-16"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "RSEED = 42\n",
    "# smallest possible number, -inf representation on this machine\n",
    "EPS = np.finfo(float).eps\n",
    "EPS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 122
    },
    "id": "T1sIQ2AHRVOY",
    "outputId": "a1f3efac-03a6-47c6-bb2e-bfa228a5be20"
   },
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/html": [
       "<div style=\"vertical-align: middle;\"><strong>PuRd_cr</strong> </div><div class=\"cmap\"><img alt=\"PuRd_cr colormap\" title=\"PuRd_cr\" style=\"border: 1px solid #555;\" src=\"data:image/png;base64,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\"></div><div style=\"vertical-align: middle; max-width: 514px; display: flex; justify-content: space-between;\"><div style=\"float: left;\"><div title=\"#d81b6aff\" style=\"display: inline-block; width: 1em; height: 1em; margin: 0; vertical-align: middle; border: 1px solid #555; background-color: #d81b6aff;\"></div> under</div><div style=\"margin: 0 auto; display: inline-block;\">bad <div title=\"#00000000\" style=\"display: inline-block; width: 1em; height: 1em; margin: 0; vertical-align: middle; border: 1px solid #555; background-color: #00000000;\"></div></div><div style=\"float: right;\">over <div title=\"#8d003bff\" style=\"display: inline-block; width: 1em; height: 1em; margin: 0; vertical-align: middle; border: 1px solid #555; background-color: #8d003bff;\"></div></div>"
      ],
      "text/plain": [
       "<matplotlib.colors.LinearSegmentedColormap at 0x11c1d47dcd0>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# create custom colormap without whites\n",
    "min_val, max_val = 0.3, 1.0\n",
    "n = 5\n",
    "colors = plt.cm.Blues(np.linspace(min_val, max_val, n))\n",
    "# create cmap object from a list of colours\n",
    "import matplotlib\n",
    "blues_cr = matplotlib.colors.LinearSegmentedColormap.from_list(\"Blues_cr\", colors)\n",
    "blues_cr\n",
    "\n",
    "# create almost constant custom colormap\n",
    "min_val, max_val = 0.7, 0.9\n",
    "n = 5\n",
    "colors = plt.cm.PuRd(np.linspace(min_val, max_val, n))\n",
    "\n",
    "PuRd_cr = matplotlib.colors.LinearSegmentedColormap.from_list(\"PuRd_cr\", colors)\n",
    "PuRd_cr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "id": "WJNr_zzMJ1B_"
   },
   "outputs": [],
   "source": [
    "def cl_plot(arr, title='Collocation data points', cm=blues_cr):\n",
    "  \"\"\"plots (N,3)-shaped array of points but also accepts (N,4)\"\"\"\n",
    "  pos = arr.detach().numpy()\n",
    "\n",
    "  fig = plt.figure(figsize=(6,6))\n",
    "  ax = plt.axes(projection='3d')\n",
    "  ax.invert_zaxis()\n",
    "  ax.set_xlabel('x')\n",
    "  ax.set_ylabel('y')\n",
    "  ax.set_zlabel('z = depth');\n",
    "\n",
    "  plt.title(title, fontsize=16)\n",
    "  ax.scatter3D(pos[:,0]+1, pos[:,1]+1, pos[:,2]+1, c=pos[:,2], s=10, cmap=cm,)\n",
    "  plt.show()\n",
    "  return fig, ax\n",
    "\n",
    "def add_wells(ax_object, well_coord):\n",
    "  \"\"\"adds well locations coloured by roles onto an existing plot\"\"\"\n",
    "  inj, prd = well_coord[0].to_numpy(), well_coord[1].to_numpy()\n",
    "  ax_object.scatter(inj[:,0], inj[:,1], s=60, c='green', alpha=1)\n",
    "  ax_object.scatter(prd[:,0], prd[:,1], s=100, c='red', alpha=1)\n",
    "  # return ax_object"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 327
    },
    "id": "0D_603RJbIiC",
    "outputId": "3571eb5f-86a9-4cf5-a215-3a27d56adfca"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "|       | cat   | group   |   date |           oil |       water |      liquid |         bhp |   status |   start_lag |   coef | is_base   |\n",
      "|------:|:------|:--------|-------:|--------------:|------------:|------------:|------------:|---------:|------------:|-------:|:----------|\n",
      "|  3738 | I2    | I       |     27 | nan           |  0.001267   |  0.001267   | 3.06986e+07 |        1 |          19 |   0.17 | False     |\n",
      "|  8739 | I3    | I       |      7 | nan           |  0.001254   |  0.001254   | 4.15301e+07 |        1 |           3 |   0.33 | False     |\n",
      "|  4191 | P2    | P       |     28 |  -0.000250695 | -0.00226548 | -0.00251618 | 2e+07       |        1 |          10 |   0.17 | False     |\n",
      "| 20223 | I2    | I       |     24 | nan           |  0.001267   |  0.001267   | 3.32648e+07 |        1 |          14 |   0.5  | False     |\n",
      "|  2396 | P2    | P       |     29 |  -0.000260283 | -0.00280763 | -0.00306792 | 2e+07       |        1 |          15 |   0.42 | False     |\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>cat</th>\n",
       "      <th>x</th>\n",
       "      <th>y</th>\n",
       "      <th>group</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>P1</td>\n",
       "      <td>190</td>\n",
       "      <td>190</td>\n",
       "      <td>P</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>P2</td>\n",
       "      <td>190</td>\n",
       "      <td>890</td>\n",
       "      <td>P</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>I1</td>\n",
       "      <td>890</td>\n",
       "      <td>190</td>\n",
       "      <td>I</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>I2</td>\n",
       "      <td>590</td>\n",
       "      <td>770</td>\n",
       "      <td>I</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>I3</td>\n",
       "      <td>670</td>\n",
       "      <td>510</td>\n",
       "      <td>I</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  cat    x    y group\n",
       "0  P1  190  190     P\n",
       "1  P2  190  890     P\n",
       "2  I1  890  190     I\n",
       "3  I2  590  770     I\n",
       "4  I3  670  510     I"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# load data\n",
    "path = \"./data.csv\"\n",
    "df = pd.read_csv(path)\n",
    "print(df.sample(5).to_markdown())\n",
    "# load metadata\n",
    "path = \"./meta.csv\"\n",
    "df_coords = pd.read_csv(path)\n",
    "df_coords[\"group\"] = df_coords[\"cat\"].str[0]\n",
    "df_coords"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 34
    },
    "id": "j9PxSzT7d0w1",
    "outputId": "5855b7b7-f58c-4db8-fcce-3ec36fefd6f6"
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "ee141febd1ca4b1abd1c932c0d984b74",
       "version_major": 2,
       "version_minor": 0
      },
      "image/png": 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      "text/html": [
       "\n",
       "            <div style=\"display: inline-block;\">\n",
       "                <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
       "                    Figure\n",
       "                </div>\n",
       "                <img 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' width=640.0/>\n",
       "            </div>\n",
       "        "
      ],
      "text/plain": [
       "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# create a dictionary that maps categories to colors\n",
    "color_dict = {\"P\": \"green\", \"I\": \"blue\"}\n",
    "# generate a scatter plot with color-coded points\n",
    "for group, color in color_dict.items():\n",
    "    df_cat = df_coords[df_coords[\"group\"] == group]\n",
    "    plt.scatter(df_cat[\"x\"], df_cat[\"y\"], s=50, alpha=0.5, color=color, label=group)\n",
    "\n",
    "for i, row in df_coords.iterrows():\n",
    "    plt.annotate(\n",
    "        row[\"cat\"],\n",
    "        (row[\"x\"], row[\"y\"]),\n",
    "        textcoords=\"offset points\",\n",
    "        xytext=(5, 5),\n",
    "        ha=\"center\",\n",
    "        color=\"k\",  # change the text color to red\n",
    "    )\n",
    "\n",
    "# add labels and legend\n",
    "plt.title(\"Well locations\")\n",
    "plt.xlabel(\"x\")\n",
    "plt.ylabel(\"y\")\n",
    "plt.grid(ls=\"--\")\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 104
    },
    "id": "dbcqZrXyZA-F",
    "outputId": "4c53461f-3a15-4048-ac4a-ca64a3e58616"
   },
   "outputs": [],
   "source": [
    "df_coords['z'] = 0\n",
    "injectors = df_coords[df_coords['group']=='I'][[\"x\",\"y\",\"z\"]]\n",
    "producers = df_coords[df_coords['group']=='P'][[\"x\",\"y\",\"z\"]]\n",
    "wells = torch.Tensor(np.concatenate([injectors,producers]))\n",
    "wells"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 423
    },
    "id": "APmRkEkCfd7l",
    "outputId": "0eff6ca3-42ef-48f1-9650-89a43cfac3c8"
   },
   "outputs": [],
   "source": [
    "# liquid feature is evidently excessive cause it's linearly dependent of two others == from now on I choose to forecast just the oil pr\n",
    "(df[\"oil\"] + df[\"water\"] - df[\"liquid\"]).sum()\n",
    "# dfv1 = df.drop(columns=[\"liquid\"])\n",
    "dfv1 = df.drop(columns=[\"water\", 'oil'])\n",
    "# also there is one column with clearly boolean values\n",
    "dfv1[\"status\"] = dfv1[\"status\"].astype(\"bool\")\n",
    "# separate test case (3 inj wells, 2 prod wells), all normal operation except for I3\n",
    "dfv1_test = dfv1[dfv1[\"is_base\"] == False].drop(columns=[\"is_base\"])\n",
    "# we have just 3 columns that contains some NaNs\n",
    "NaN_cols = dfv1_test.columns[dfv1_test.isna().any()]\n",
    "# when I3 pump is turned off, those corresponding 2592 water\\oil\\bhp NaN values could and should be interpreted as zeros\n",
    "I3_off_condition = (\n",
    "    (dfv1_test[NaN_cols].isna().any(axis=1))\n",
    "    & (dfv1_test[\"status\"] == False)\n",
    "    & (dfv1_test[\"cat\"] == \"I3\")\n",
    ")\n",
    "dfv1_test[I3_off_condition] = dfv1_test[I3_off_condition].fillna(0)\n",
    "# Remaining 14688 oil column NaNs are caused by injecting wells that don't produce any oil, and therefore could be set as zero\n",
    "inj_wells_oil_condition = (dfv1_test[[\"liquid\"]].isna().any(axis=1)) & (\n",
    "    dfv1_test[\"group\"] == \"I\"\n",
    ")\n",
    "dfv1_test.isna().sum()\n",
    "dfv1_test[inj_wells_oil_condition] = dfv1_test[inj_wells_oil_condition].fillna(0)\n",
    "# our DF hasn't been yet arranged by 'date', from now on it's sequential\n",
    "dfT = dfv1_test.sort_values(by=[\"date\"])\n",
    "# --------------------------------------------------------\n",
    "data_ = dfT.drop(columns=[\"status\", 'group'])\n",
    "data_ = data_.merge(right=df_coords.drop(columns=['group']), on='cat', how='left')\n",
    "data_['z'] = 0\n",
    "data_['v'] = 0\n",
    "data_['u'] = 0\n",
    "\n",
    "data = data_[['coef', 'start_lag', 'cat', 'u', 'v', 'liquid', 'bhp', 'x', 'y', 'z','date']].rename(columns={\"date\":'t', 'liquid':'w', 'bhp':'P'})\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "vEJDVNRW21zN"
   },
   "outputs": [],
   "source": [
    "# df_coords[df_coords['cat']=='I3'][['x','y']].values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "a-YkHMGujh46"
   },
   "outputs": [],
   "source": [
    "# maxes = pos[:,:3].max(axis=0)\n",
    "# minis = pos[:,:3].min(axis=0)\n",
    "# X, Y, Z = np.stack([minis, maxes], axis=1)\n",
    "# vertices = [(x,y,z) for x in X for y in Y for z in Z]\n",
    "# # just an effort to draw cuboid from a set of vertices effectively -- unused"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "l_yYrnbQ4Vvy"
   },
   "outputs": [],
   "source": [
    "class SuDS(Dataset):\n",
    "  '''receives original dataframe, separates experiments, splits 4D coordinates from fields and outputs 2 numpy arrays per experiment #part'''\n",
    "  def __init__(self, data, part=0):\n",
    "    super().__init__()\n",
    "    # group all experimental combinations and separate from each other\n",
    "    exp_g = [g.drop(columns=[\"coef\", \"start_lag\",'cat']) for i, g in data.groupby([\"coef\", \"start_lag\"])]\n",
    "    # exp_g[0] - 5x 4D values per each of 30 timesteps\n",
    "    # exp_g[0][exp_g[0]['t'] == 0]\n",
    "    self.exp_split = []\n",
    "    assert part < len(exp_g), 'wrong cfg'\n",
    "    # capture part of an experiment\n",
    "    self.nexp = part\n",
    "    for e in exp_g:\n",
    "      # feature-target split dataframe, convert to numpy arrays\n",
    "      e = e.reset_index()\n",
    "      self.exp_split.append((torch.tensor(e[['x', 'y', 'z','t']].to_numpy(), dtype=torch.float, requires_grad=True),\n",
    "                             torch.tensor(e[['u', 'v', 'w','P']].to_numpy(), dtype=torch.float, requires_grad=True)))\n",
    "    print(f\"We have chosen #{self.nexp} of {len(exp_g)} experiments with {len(exp_g[0])} 4D points each, splitted as f-t\")\n",
    "    # exp_split[0][0].shape, exp_split[0][1].shape\n",
    "    # for each such experiment, we want to simulate vector streamline and scalar pressure field's evolution over time\n",
    "\n",
    "  def __getitem__(self, idx):\n",
    "    return self.exp_split[self.nexp][0][idx], self.exp_split[self.nexp][1][idx]\n",
    "  def __len__(self):\n",
    "    return len(self.exp_split[self.nexp][0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "MuFfBTbYh65-"
   },
   "outputs": [],
   "source": [
    "# suppose that the liquid has just 1 phase with constant viscosity and density\n",
    "MU = 0.001 #pascal*secs\n",
    "RHO = 0.997 #kg/m3\n",
    "# Our model reservoir is considered to be rectangular DWL (depth=Zaxis)\n",
    "L=1000\n",
    "W=1000\n",
    "D=500\n",
    "T=30\n",
    "# we have 3 inlets, 2 outlets => 5 point sources on boundary dO\n",
    "# with injection/production along Z-direction, i.e. velocity_5pts = (0,0,w)\n",
    "\n",
    "# NS problem is well-posed given all-Dirichlet boundary conditions for velocity:\n",
    "# In case of incompressible fluid, we could use Poisson identity to relate\n",
    "# pressure to velocity thus we don't specify any conditions for pressures"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "vUjk7H8Iljii"
   },
   "source": [
    "Unlike typical PDE solvers (finite-element, finite-volume) based on advanced meshgrid, PINN approach is in fact **mesh-free**, that means we could sample a random cloud $O \\subset R^n$ thus skip this time-consuming step and also evade (by randomness) possible pattern priors in our solution caused by spatial grid"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "DD1d-chnP4Oo"
   },
   "outputs": [],
   "source": [
    "# # we could use 4D meshgrid with an equal spacing\n",
    "# xs = torch.linspace(0, L-1, steps=5)\n",
    "# ys = torch.linspace(0, W-1, steps=5)\n",
    "# zs = torch.linspace(0, D-1, steps=5)\n",
    "ts = torch.linspace(0, T-1, steps=30)\n",
    "# x, y, z, t = torch.meshgrid(xs, ys, zs, ts, indexing='xy')\n",
    "# # get exact 4D coordinates instead of indexing 4x arrays simultaneously on the fly\n",
    "# positions = torch.vstack(list(map(torch.ravel, (x, y, z, t)))).T\n",
    "# # allow gradient computations wrt to those as inputs\n",
    "# # positions.requires_grad_()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "dmGghAI3pqrj"
   },
   "outputs": [],
   "source": [
    "def disjoin(left, right, invert=False):\n",
    "  \"\"\"this function provides split of disjoint union of non-intersection for 2D tensors\"\"\"\n",
    "  # difference of two tensors ~ elements that appear just once in their cat\n",
    "  combined = torch.cat((left, right))\n",
    "  # get unique 4D rows, counts[e] == 1 means that uniques[e] is unique\n",
    "  # idx is a lookup table orig_idx --> #bin w/ one (or more) elements\n",
    "  uniques_, idx, counts_ = combined.unique(return_counts=True, return_inverse=True, dim=0)\n",
    "  # for now that's a disjoint union w/ elements of both sets, let's filter out\n",
    "  # list counts per each element of combined tensor, mask out unique elements\n",
    "  counts = counts_[idx] == 1\n",
    "  # left, right unique elements masks (false for idx_e if e in intersection)\n",
    "  lu, ru = counts[:len(left)], counts[len(left):]\n",
    "  # apply masks to both sides correspondingly\n",
    "  if invert:\n",
    "    # allows to get their intersection (splitted!)\n",
    "    lu, ru = ~lu, ~ru\n",
    "  lu_idx, ru_idx = torch.arange(len(left))[lu], torch.arange(len(right))[ru]\n",
    "  # diff = uniques_[counts_ == 1]\n",
    "  # we won't use uniques, just counts for masking out NSE results\n",
    "  def aux(lst):\n",
    "    check = True if len(lst)!=0 else False\n",
    "    if check:\n",
    "      # returns tensor w/ unique indices\n",
    "      return lst\n",
    "    else:\n",
    "      #returns None by default\n",
    "      print('given tensors contain one another or no intersection')\n",
    "  return aux(lu_idx), aux(ru_idx)\n",
    "\n",
    "# disjoin(initial[100:], initial, True)[0]\n",
    "# initial[100:].shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "az_YdaOzlY8W"
   },
   "outputs": [],
   "source": [
    "N_COLL = 100\n",
    "# Likewise, just create uniformly-distributed cloud of 3D points and stretch\n",
    "torch.manual_seed(RSEED)\n",
    "cloud = torch.rand(N_COLL, 3)@torch.diag(torch.Tensor((L,W,D)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 52
    },
    "id": "kJKnEi2vODeM",
    "outputId": "933b2db9-16fd-4973-f93e-0c10fee456c8"
   },
   "outputs": [],
   "source": [
    "# let's generate and put apart whole border dO to evade conditions in training loop\n",
    "N_BOR = 36\n",
    "# max amount of border points (equally distributed across all 6 planes)\n",
    "limits = torch.Tensor((L,W,D))\n",
    "planes = []\n",
    "for axis in range(3):\n",
    "  rest = list(range(3))\n",
    "  del rest[axis]\n",
    "  curr_limits = limits[rest]\n",
    "  for wall in set((0, limits[axis])):\n",
    "    normal = torch.ones((N_BOR//6, 1))*wall\n",
    "    # generate points on the plane\n",
    "    torch.manual_seed(RSEED)\n",
    "    plane = torch.split(torch.rand(N_BOR//6,2)@torch.diag(torch.Tensor(limits[rest])), 1, dim=1)\n",
    "    # retain XYZ order with a help of dict\n",
    "    parts = {axis:normal, rest[0]:plane[0], rest[1]: plane[1]}\n",
    "    triplets = [parts[idx] for idx in range(3)]\n",
    "    planes.append(torch.cat(triplets, dim=-1))\n",
    "border = torch.cat(planes, dim=0)\n",
    "\n",
    "# ensure that wells don't coincide with collocation points jic\n",
    "assert disjoin(border, wells, True)[0] is None, 'border points fail'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 1000,
     "referenced_widgets": [
      "cf0d399b8fd14f1f96a0d502560239c2",
      "44d3323929534891a2d7423d1bd50d0e",
      "99cb3963e95b409096f9b4a5acc5bdcf",
      "5fa69d48a9a1417bb26bff31bc554821",
      "f39bf08d384f4121a7225e48eed4367c",
      "00d27d88f6b9468c8720cb2111ce0c5b",
      "c4c7f6cf4b52410a8ab24635748f40cd",
      "16dc46f4dbcd418aab73c2c64e453f0f"
     ]
    },
    "id": "a_fS5sNq2lsi",
    "outputId": "7c795426-1f2a-4e24-8cb3-355d377ae67f"
   },
   "outputs": [],
   "source": [
    "# cloud visualization\n",
    "fa = cl_plot(cloud, 'Collocation random cloud (interior)')\n",
    "add_wells(fa[1], (injectors, producers))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "fa_b = cl_plot(border, 'Border points', cm=PuRd_cr)\n",
    "add_wells(fa_b[1], (injectors, producers))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 52
    },
    "id": "4ftr7oiLrm-E",
    "outputId": "470a3069-fe22-4f5e-cb22-bcecfaaf0a98"
   },
   "outputs": [],
   "source": [
    "print(f'We have {border.shape[0]:.0f} border points dO and {cloud.shape[0]:.0f} interior points in our grid O')\n",
    "# use same cloud at each timestep\n",
    "clouds = cloud.unsqueeze(-1).repeat(1,1,T)\n",
    "# transform and duplicate time axis such that ts[0, :, 5] = 5th timestep\n",
    "times = ts[(None,)*2].repeat(cloud.shape[0],1,1)\n",
    "# concatenate, merge time and count dimension into a single batch dimension\n",
    "positions = torch.flatten(torch.cat((clouds, times), dim=1).permute(0,2,1), 0, 1)\n",
    "\n",
    "# use same border at each timestep\n",
    "borders = border.unsqueeze(-1).repeat(1,1,T)\n",
    "times = ts[(None,)*2].repeat(border.shape[0],1,1)\n",
    "positions_b = torch.flatten(torch.cat((borders, times), dim=1).permute(0,2,1), 0, 1)\n",
    "\n",
    "# our initial condition requires all O and dO elements with T=0, 5^3 pts\n",
    "initial = positions[positions[:,3]==0]\n",
    "\n",
    "# enable gradient computation in regard to all these\n",
    "# positions.requires_grad_()\n",
    "# positions_b.requires_grad_()\n",
    "# initial.requires_grad_()\n",
    "collocation = torch.cat((positions, positions_b), dim=0)\n",
    "collocation.requires_grad_()\n",
    "# collocation.shape\n",
    "print('Gradients enabled')\n",
    "\n",
    "# positions.shape, positions_b.shape, initial.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "qv_utGzqFe2N"
   },
   "source": [
    "Data = Supervised(original) + Unsupervised(generated,collocation)\n",
    "\n",
    "Supervised data contains just 5pts on boundary dO of our reservoir O (but 30 timesteps)\n",
    "\n",
    "Unsupervised data contains the rest boundary dO(walls) and int(O) volume"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 34
    },
    "id": "TpsCLrTsYNq1",
    "outputId": "656d7173-9c24-4f89-dd2f-546ca41a50bb"
   },
   "outputs": [],
   "source": [
    "#create dataset and dataloaders\n",
    "uns_dl = DataLoader(collocation, shuffle=True, batch_size=len(collocation))\n",
    "\n",
    "supervised_data = SuDS(data, part=0)\n",
    "sup_dl = DataLoader(supervised_data, batch_size=len(supervised_data))\n",
    "# next(iter(sup_dl))[0].requires_grad"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "AYzFxGkFkK-u"
   },
   "outputs": [],
   "source": [
    "def NS_equation(point_4d, net_function, viscosity=MU, density=RHO, la=None):\n",
    "  \"\"\"takes net output, performs differentiation by inputs and\n",
    "  calculates the residual of Navier-Stokes 3D ODE at this point\"\"\"\n",
    "  # WE CAN'T USE SLICES=VIEWS OF INPUTS CAUSE IT BREAKS AUTOGRAD\n",
    "  # x, y, z, t = torch.split(point_4d, 1, dim=1)\n",
    "  # possible degrees of freedom - learnable parameters for NSE\n",
    "  if la:\n",
    "    lambda_1 = la[0]\n",
    "    lambda_2 = la[1]\n",
    "  else:\n",
    "    lambda_1=lambda_2=torch.tensor(1, dtype=torch.float, requires_grad=True)\n",
    "  # net outputs include batch dimension\n",
    "  Ax, Ay, Az, p_field = torch.split(net_function, 1, dim=1)\n",
    "  # we can calculate the gradient of pressure field immediately (3D only!)\n",
    "  gr_p = torch.autograd.grad(p_field, point_4d, grad_outputs=torch.ones_like(p_field), create_graph=True)[0][:,:3]\n",
    "  # we want (vector) velocity field to automatically satisfy continuity equation,\n",
    "  # suppose we have vector potential, C2-diff 3D vector field A => div(rotA)=0\n",
    "  # implying that, reconstruct our velocity_field from its vector potential\n",
    "  # thus rewrite velocity = rot A in a component form:\n",
    "  # INEFFICIENT, TO BE REPLACED BY FUNCTIONAL JACOBIAN\n",
    "  gr_Ax = torch.autograd.grad(Ax, point_4d, grad_outputs=torch.ones_like(Ax), create_graph=True)[0]\n",
    "  Ax_y, Ax_z = gr_Ax[:,1], gr_Ax[:,2]\n",
    "  gr_Ay = torch.autograd.grad(Ay, point_4d, grad_outputs=torch.ones_like(Ay), create_graph=True)[0]\n",
    "  Ay_x, Ay_z = gr_Ay[:,0], gr_Ay[:,2]\n",
    "  gr_Az = torch.autograd.grad(Ay, point_4d, grad_outputs=torch.ones_like(Az), create_graph=True)[0]\n",
    "  Az_x, Az_y = gr_Az[:,0], gr_Az[:,1]\n",
    "  u, v, w = Az_y - Ay_z, Ax_z - Az_x, Ay_x - Ax_y\n",
    "  velocity_field = torch.stack((u, v, w), dim=-1)\n",
    "  # for correctness of future elementwise multiplication\n",
    "  u, v, w = u.unsqueeze(-1), v.unsqueeze(-1), w.unsqueeze(-1)\n",
    "  # then we need their first-order derivatives\n",
    "  gr_u = torch.autograd.grad(u, point_4d, grad_outputs=torch.ones_like(u), create_graph=True)[0]\n",
    "  u_x, u_y, u_z, u_t = torch.split(gr_u, 1, dim=1)\n",
    "  gr_v = torch.autograd.grad(v, point_4d, grad_outputs=torch.ones_like(v), create_graph=True)[0]\n",
    "  v_x, v_y, v_z, v_t = torch.split(gr_v, 1, dim=1)\n",
    "  gr_w = torch.autograd.grad(w, point_4d, grad_outputs=torch.ones_like(w), create_graph=True)[0]\n",
    "  w_x, w_y, w_z, w_t = torch.split(gr_w, 1, dim=1)\n",
    "  # and unmixed 2nd-order derivatives to form vector laplacian\n",
    "  u_xx = torch.autograd.grad(u_x, point_4d, grad_outputs=torch.ones_like(u_x), retain_graph=True)[0][:,0]\n",
    "  u_yy = torch.autograd.grad(u_y, point_4d, grad_outputs=torch.ones_like(u_y), retain_graph=True)[0][:,1]\n",
    "  u_zz = torch.autograd.grad(u_z, point_4d, grad_outputs=torch.ones_like(u_z), retain_graph=True)[0][:,2]\n",
    "\n",
    "  v_xx = torch.autograd.grad(v_x, point_4d, grad_outputs=torch.ones_like(v_x), retain_graph=True)[0][:,0]\n",
    "  v_yy = torch.autograd.grad(v_y, point_4d, grad_outputs=torch.ones_like(v_y), retain_graph=True)[0][:,1]\n",
    "  v_zz = torch.autograd.grad(v_z, point_4d, grad_outputs=torch.ones_like(v_z), retain_graph=True)[0][:,2]\n",
    "\n",
    "  w_xx = torch.autograd.grad(w_x, point_4d, grad_outputs=torch.ones_like(w_x), retain_graph=True)[0][:,0]\n",
    "  w_yy = torch.autograd.grad(w_y, point_4d, grad_outputs=torch.ones_like(w_y), retain_graph=True)[0][:,1]\n",
    "  w_zz = torch.autograd.grad(w_z, point_4d, grad_outputs=torch.ones_like(w_z), retain_graph=True)[0][:,2]\n",
    "  # now we are ready to use NS, start from diffusion terms:\n",
    "  DTx = (viscosity/density)*(u_xx+u_yy+u_zz)\n",
    "  DTy = (viscosity/density)*(v_xx+v_yy+v_zz)\n",
    "  DTz = (viscosity/density)*(w_xx+w_yy+w_zz)\n",
    "  # convection terms\n",
    "  CTx = (u*u_x+v*u_y+w*u_z).squeeze()\n",
    "  CTy = (u*v_x+v*v_y+w*v_z).squeeze()\n",
    "  CTz = (u*w_x+v*w_y+w*w_z).squeeze()\n",
    "  # this results in 3D NS residuals implying continuity part by construction\n",
    "  Rx = u_t.squeeze() + lambda_1*CTx - DTx + lambda_2*gr_p[:,0]/density\n",
    "  Ry = v_t.squeeze() + lambda_1*CTy - DTy + lambda_2*gr_p[:,1]/density\n",
    "  Rz = w_t.squeeze() + lambda_1*CTz - DTz + lambda_2*gr_p[:,2]/density\n",
    "  residuals = torch.stack((Rx, Ry, Rz), dim=-1)\n",
    "  return velocity_field, residuals"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "GQTpS8-q26d2"
   },
   "outputs": [],
   "source": [
    "class NSE_lambda(nn.Module):\n",
    "  \"\"\"NSE with additional learnable parameters injected\"\"\"\n",
    "  def __init__(self):\n",
    "    super().__init__()\n",
    "    self.la_1 = nn.Parameter(torch.tensor(1.))\n",
    "    self.la_2 = nn.Parameter(torch.tensor(1.))\n",
    "\n",
    "  def forward(self, net_in, net_out):\n",
    "    return NS_equation(net_in, net_out, la=(self.la_1, self.la_2))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "0a4qRi_khceY"
   },
   "outputs": [],
   "source": [
    "from torch.nn.modules.activation import Sigmoid\n",
    "class PINNNS(nn.Module):\n",
    "  \"\"\"Navier-Stokes physics-informed NN\n",
    "  4D -> 3D streamline potential + scalar pressure fields\"\"\"\n",
    "  def __init__(self, n_hidden=48, nonlinearity=nn.Sigmoid()):\n",
    "    super().__init__()\n",
    "    # inputs are 4D spatial coordinates x,y,z,t\n",
    "    self.n_inp = 4\n",
    "    # outputs are 3D velocity field potential (Ax, Ay, Az) and scalar pressure field P\n",
    "    self.n_out = 4\n",
    "    self.n_hid = n_hidden\n",
    "    self.nonlinear = nonlinearity\n",
    "    self.inp = nn.Linear(in_features=self.n_inp, out_features=self.n_hid)\n",
    "    self.inter = nn.Sequential(\n",
    "        nn.Linear(self.n_hid, self.n_hid),\n",
    "        self.nonlinear,\n",
    "        nn.Linear(self.n_hid, self.n_hid),\n",
    "        self.nonlinear,\n",
    "    )\n",
    "    self.out = nn.Linear(in_features=self.n_hid, out_features=self.n_out)\n",
    "  def forward(self, x):\n",
    "    return self.out(self.inter(self.nonlinear(self.inp(x))))\n",
    "    # return self.out(self.nonlinear(self.inp(x)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "qIPuDKeKijLR"
   },
   "outputs": [],
   "source": [
    "def RMSE_f(inp, tar):\n",
    "  return torch.sqrt(torch.nn.functional.mse_loss(inp, tar))\n",
    "\n",
    "# loss = Loss_data + Loss_NS3D + Loss_boundary + Loss_initial\n",
    "def supervised_loss(net_in, net_out, target, lambda_mode=False):\n",
    "  \"\"\"combined loss at single 4D point net_in, calculated as Loss_data + Loss_NS3D on data\"\"\"\n",
    "  # get (vector of) velocity and residuals\n",
    "  if lambda_mode:\n",
    "    velocity, residuals = lambda_mode(net_in, net_out)\n",
    "  else:\n",
    "    velocity, residuals = NS_equation(net_in, net_out)\n",
    "  # separate pressure to stack with velocity instead of its potential\n",
    "  pressure = net_out[:,3].unsqueeze(-1)\n",
    "  net_out_v = torch.cat((velocity, pressure), dim=-1)\n",
    "  # we have 5 wells, each has velocity and pressure data (supervised loss)\n",
    "  data_loss = torch.mean(RMSE_f(net_out_v, target))/1e07\n",
    "  # moreover, they should obey NS3D as a part of boundary and initial condition\n",
    "  NS3D_loss = torch.mean(torch.norm(residuals, dim=-1))\n",
    "  return data_loss + NS3D_loss\n",
    "\n",
    "def unsupervised_batch_loss(net_in, net_out, lambda_mode=False):\n",
    "  \"\"\"process whole batch and filter out proper results by mask\"\"\"\n",
    "  if lambda_mode:\n",
    "    velocity, residuals = lambda_mode(net_in, net_out)\n",
    "  else:\n",
    "    velocity, residuals = NS_equation(net_in, net_out)\n",
    "  loss_0, loss_i = torch.tensor(0.), torch.tensor(0.)\n",
    "  # We have initial conditions on velocity\n",
    "  # velocity_5pts = (0,0,w) in supervised, velocity_else = (0,0,0) in both O and dO\n",
    "  # intersect batch w/ initial\n",
    "  s_mask = disjoin(net_in, initial, True)[0]\n",
    "  if s_mask is not None:\n",
    "    loss_0 = torch.mean(torch.norm(velocity[s_mask], dim=-1))\n",
    "  # We have initial conditions on border\n",
    "  # dO/5pts follows non-slip and impermeability BC, i.e. vel_b_rest = (0,0,0)\n",
    "  # intersect batch w/ boundary\n",
    "  b_mask_ = disjoin(net_in, positions_b, True)[0]\n",
    "  # purify to exclude possible init points on boundary(already processed)\n",
    "  b_mask = disjoin(b_mask_, s_mask)[0]\n",
    "  if b_mask is not None:\n",
    "    loss_b = torch.mean(torch.norm(velocity[b_mask], dim=-1))\n",
    "  # the rest is NSE3D loss on O (not masked = at any timestep and location)\n",
    "  loss_i = torch.mean(torch.norm(residuals, dim=-1))\n",
    "  return loss_0 + loss_b + loss_i"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "b2dZUts61_HF"
   },
   "outputs": [],
   "source": [
    "def train(model, dl_original, dl_collocation, optimizer, n_epochs=300, gpu=device, beta=torch.tensor(0.5), la=None):\n",
    "  \"\"\"training loop for PINN model with weight updates per epoch,\n",
    "  beta in [0,1] is a hyperparameter relating losses of different origin,\n",
    "  larger beta <=> more unsupervised\"\"\"\n",
    "  epochs = tqdm.trange(n_epochs)\n",
    "  losses = []\n",
    "  for e in epochs:\n",
    "    model.train()\n",
    "    # this optimizer calls closure multiple times!!\n",
    "    def closure():\n",
    "      \"\"\"A closure callback that reevaluates the model and returns the loss\n",
    "      backprop, zeroing gradients is embedded into closure callback for LBFGS,\n",
    "      forward has been put here too cause otherwise it doesn't work\"\"\"\n",
    "      # these losses are implemented like that just in case we will use batches\n",
    "      # u_loss = torch.tensor(0., device=gpu)\n",
    "      # s_loss = torch.tensor(0., device=gpu)\n",
    "\n",
    "      # forward pass A\n",
    "      for X_batch, y_batch in dl_original:\n",
    "        # NOT ACTUALLY BATCHED FOR LBFGS (FULL BM)\n",
    "        X_batch, y_batch = X_batch.to(gpu), y_batch.to(gpu)\n",
    "        y_pred = model(X_batch)\n",
    "        s_loss = supervised_loss(X_batch, y_pred, y_batch, lambda_mode=la)# + s_loss\n",
    "      # forward pass B\n",
    "      for X_batch_B in dl_collocation:\n",
    "        # NOT ACTUALLY BATCHED FOR LBFGS (FULL BM)\n",
    "        X_batch_B = X_batch_B.to(gpu)\n",
    "        y_pred_B = model(X_batch_B)\n",
    "        u_loss = unsupervised_batch_loss(X_batch_B, y_pred_B, lambda_mode=la)#+ u_loss\n",
    "      # print('\\n Collocation stage')\n",
    "\n",
    "      # sum up both losses with adjustments\n",
    "      loss = (1.-beta)*s_loss/len(dl_original) + beta*u_loss/len(dl_collocation)\n",
    "      # print(s_loss.item(), u_loss.item(), loss.item())\n",
    "      # prevent accumulation of gradients from prev steps\n",
    "      optimizer.zero_grad()\n",
    "      # backward pass\n",
    "      loss.backward()\n",
    "      losses.append(loss.item())\n",
    "      return loss\n",
    "\n",
    "    # gradient update\n",
    "    optimizer.step(closure)\n",
    "\n",
    "    if e % 10 == 0:\n",
    "      model.eval()\n",
    "      with torch.inference_mode():\n",
    "        # print(losses[-1])\n",
    "        epochs.set_description(f\"test loss: {losses[-1]:g}\", refresh=True)"
   ]
  },
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   "execution_count": null,
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    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 416
    },
    "id": "EBJK77PWOmbF",
    "outputId": "fa3a0123-e877-476f-b716-772faee2621f"
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   "source": [
    "N_EPOCHS = 300\n",
    "PHYS_FACTOR = 0.2\n",
    "\n",
    "torch.manual_seed(RSEED)\n",
    "# torch.autograd.set_detect_anomaly(False)\n",
    "\n",
    "pinny = PINNNS().to(device)\n",
    "# equip NSE with learnable parameters\n",
    "nsel = NSE_lambda()\n",
    "# chain two generators (or just conv to list and join, use as iterable)\n",
    "learnable_params = itertools.chain(pinny.parameters(), nsel.parameters())\n",
    "# not recommended to use SGD or any batch methods as they tend to stuck in a local minima\n",
    "# optimizer = torch.optim.SGD(pinny.parameters(), lr=0.1)\n",
    "optimizer = torch.optim.LBFGS(learnable_params, lr=0.8, max_iter=200000,\n",
    "                              max_eval=50000, history_size=50,\n",
    "                              tolerance_grad=3e-05,\n",
    "                              tolerance_change=0.5*EPS,\n",
    "                              line_search_fn='strong_wolfe')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "D-uZNT6YN35U"
   },
   "outputs": [],
   "source": [
    "x=next(iter(sup_dl))[0]\n",
    "# NS_equation(x, pinny(x))\n",
    "summary(pinny, x.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 338
    },
    "id": "CbMkuLGawsz9",
    "outputId": "692adae4-5444-4a8e-d838-f09bd1dc865d"
   },
   "outputs": [],
   "source": [
    "train(pinny, sup_dl, uns_dl, optimizer, N_EPOCHS, device, PHYS_FACTOR, la=nsel)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 52
    },
    "id": "5ajEf1-Mgr29",
    "outputId": "49765b69-cf06-4dc0-93f9-1511ea8766d0"
   },
   "outputs": [],
   "source": [
    "for name, param in nsel.named_parameters():\n",
    "  if param.requires_grad:\n",
    "    print(name, param.data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "JUgTh4R1429l"
   },
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   "source": [
    "def get_stream(model, la_nse, dl):\n",
    "  model.eval()\n",
    "  model.cpu()\n",
    "  # with torch.inference_mode():\n",
    "  for X in dl:\n",
    "    # Full-batch mode\n",
    "    y = model(X)\n",
    "    # pressure scalar field contains as is\n",
    "    pressure = y[:,3]\n",
    "    # apply NSE with lambda-corrections to retrieve velocity\n",
    "    velocity, residuals = la_nse(X, y)\n",
    "    return velocity\n",
    "\n",
    "# get_stream(pinny, nsel, uns_dl)\n",
    "\n",
    "def plot_vf(coord_4, field_3, moment=0):\n",
    "  # get all field vectors, for all points and timesteps\n",
    "  pos = coord_4.detach()\n",
    "  field = field_3.detach()\n",
    "  # mask out exact timestep using 4D array\n",
    "  t_mask = pos[:,3] == moment\n",
    "  # apply same mask to both arrays to get corresponding parts, conv to numpy\n",
    "  x, y, z, t = np.split(pos[t_mask].numpy(), range(1,4), axis=1)\n",
    "  u, v, w = np.split(field[t_mask].numpy(), range(1,3), axis=1)\n",
    "  # configure axes and aux data\n",
    "  fig = plt.figure(figsize=(6,6))\n",
    "  ax = plt.axes(projection='3d')\n",
    "  ax.invert_zaxis()\n",
    "  ax.set_xlabel('x')\n",
    "  ax.set_ylabel('y')\n",
    "  ax.set_zlabel('z = depth');\n",
    "  plt.title('Reservoir model grid', fontsize=16)\n",
    "\n",
    "  # add 5 wells\n",
    "  add_wells(ax, (injectors, producers))\n",
    "\n",
    "  # plot grid w/ depth\n",
    "  reservoir = ax.scatter3D(x, y, z, c=z, s=10, cmap=blues_cr)\n",
    "\n",
    "  # plot streamline field\n",
    "  return ax.quiver(x, y, z, u, v, w, length=50, normalize=True, color='darkviolet')"
   ]
  },
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    "plot_vf(collocation, get_stream(pinny, nsel, uns_dl),5)"
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        "square-o",
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",
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",
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