{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Quick Start\n",
    "\n",
    "In this quick start we create an extension of the Grid object, generate a random instance of it and perform power flow calculations and modifications.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Setting up a grid extension\n",
    "\n",
    "This shows how to add extra values to a `Grid` object. If these are present in the PGM output they will be updated after a power flow calculation.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from dataclasses import dataclass\n",
    "from typing import ClassVar\n",
    "\n",
    "import numpy as np\n",
    "from numpy.typing import NDArray\n",
    "\n",
    "from power_grid_model_ds import GraphContainer, Grid\n",
    "from power_grid_model_ds.arrays import LineArray, NodeArray\n",
    "\n",
    "\n",
    "class ExtendedNodeArray(NodeArray):\n",
    "    \"\"\"Extends the node array with an output value\"\"\"\n",
    "\n",
    "    _defaults: ClassVar = {\"u\": 0}\n",
    "\n",
    "    u: NDArray[np.float64]\n",
    "\n",
    "\n",
    "class ExtendedLineArray(LineArray):\n",
    "    \"\"\"Extends the line array with an output value\"\"\"\n",
    "\n",
    "    _defaults: ClassVar = {\"i_from\": 0}\n",
    "\n",
    "    i_from: NDArray[np.float64]\n",
    "\n",
    "\n",
    "@dataclass\n",
    "class ExtendedGrid(Grid):\n",
    "    \"\"\"\n",
    "    This is my own grid to extend.\n",
    "    \"\"\"\n",
    "\n",
    "    node: ExtendedNodeArray\n",
    "    line: ExtendedLineArray\n",
    "    graphs: GraphContainer"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Grid Generation\n",
    "\n",
    "The `RadialGridGenerator` can be used to create a randomised grid of the preferred size\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from power_grid_model_ds.generators import RadialGridGenerator\n",
    "\n",
    "grid_generator = RadialGridGenerator(grid_class=ExtendedGrid, nr_nodes=5, nr_sources=1, nr_nops=0)\n",
    "grid = grid_generator.run(seed=0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Feeder IDs\n",
    "\n",
    "To analyse network structure from the arrays, you can use feeder ids which identify how the network is connected. All structures connected to a substation node through the same feeding branch get the same feeder_branch_id.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "grid.set_feeder_ids()\n",
    "print(grid.node)\n",
    "print(grid.line)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Performing power flow calculations\n",
    "\n",
    "Using the `PowerGridModelInterface` the `Grid` data can be provided to the calculation engine. Using `update_grid` values can be transferred to the `Grid` object.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from power_grid_model_ds import PowerGridModelInterface\n",
    "\n",
    "core_interface = PowerGridModelInterface(grid=grid)\n",
    "\n",
    "core_interface.create_input_from_grid()\n",
    "core_interface.calculate_power_flow()\n",
    "core_interface.update_grid()\n",
    "\n",
    "print(grid.node)\n",
    "print(grid.line)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Modifying the Grid\n",
    "\n",
    "The Grid object can be changed by adding objects or changing normally open points (NOPs).\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "new_line = ExtendedLineArray(\n",
    "    from_node=[3],\n",
    "    to_node=[1],\n",
    "    r1=[0.6],\n",
    "    x1=[0.2],\n",
    "    i_n=[100],\n",
    "    tan1=[0.0],\n",
    "    from_status=[1],\n",
    "    to_status=[1],\n",
    "    c1=[0.0],\n",
    ")\n",
    "\n",
    "grid.append(new_line)\n",
    "\n",
    "old_line = grid.line.get(19)\n",
    "grid.make_inactive(branch=old_line)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This will give new outputs of the previous functions\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "core_interface = PowerGridModelInterface(grid=grid)\n",
    "core_interface.create_input_from_grid()\n",
    "core_interface.calculate_power_flow()\n",
    "core_interface.update_grid()\n",
    "\n",
    "grid.set_feeder_ids()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print(grid.node)\n",
    "print(grid.line)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Analyzing Grid structure\n",
    "\n",
    "The `Grid` also contains a graph representation which can be used for analyzing structure. Such as finding the shortest path between two nodes.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "path, length = grid.graphs.active_graph.get_shortest_path(1, 4)\n",
    "print(f\"Shortest path: {path}, Length: {length}\")"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": ".venv",
   "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"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}