{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "fda4c721",
   "metadata": {},
   "source": [
    "# Stand metrics and site enums"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7fb27b941602401d91542211134fc71a",
   "metadata": {},
   "source": [
    "## Notebook Objectives\n",
    "- Walk through stand/site enum usage and how they feed site-index-ready stand setup.\n",
    "- Provide runnable, copy-safe snippets that work in the docs build environment.\n",
    "\n",
    "## Prerequisites\n",
    "- Python environment with `pyforestry` installed from this repository.\n",
    "- Execute cells in order; random components should use fixed seeds where shown.\n",
    "\n",
    "## Sources\n",
    "- Swedish site primitives and enums in `pyforestry.sweden.site`.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c3f9b0c5",
   "metadata": {},
   "source": [
    "This notebook shows how to work with circular plots, site enums, and site index models."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d16d739a",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-07-17T18:03:38.210740Z",
     "iopub.status.busy": "2025-07-17T18:03:38.210552Z",
     "iopub.status.idle": "2025-07-17T18:03:38.530469Z",
     "shell.execute_reply": "2025-07-17T18:03:38.530055Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(12.75, 254.64790894703253)"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from pyforestry.base.helpers import CircularPlot, Stand, Tree, parse_tree_species\n",
    "\n",
    "plot1 = CircularPlot(\n",
    "    id=1,\n",
    "    radius_m=5.0,\n",
    "    trees=[\n",
    "        Tree(species=parse_tree_species(\"picea abies\"), diameter_cm=20),\n",
    "        Tree(species=parse_tree_species(\"pinus sylvestris\"), diameter_cm=25),\n",
    "    ],\n",
    ")\n",
    "plot2 = CircularPlot(\n",
    "    id=2,\n",
    "    radius_m=5.0,\n",
    "    trees=[\n",
    "        Tree(species=parse_tree_species(\"picea abies\"), diameter_cm=30),\n",
    "    ],\n",
    ")\n",
    "stand = Stand(plots=[plot1, plot2])\n",
    "stand.BasalArea.TOTAL.value, stand.Stems.TOTAL.value"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9ce79891",
   "metadata": {},
   "source": [
    "Site enums help provide structured parameters."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "46f3f709",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-07-17T18:03:38.533179Z",
     "iopub.status.busy": "2025-07-17T18:03:38.532452Z",
     "iopub.status.idle": "2025-07-17T18:03:38.544328Z",
     "shell.execute_reply": "2025-07-17T18:03:38.544013Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1, 16)"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from pyforestry.base.helpers import enum_code\n",
    "from pyforestry.sweden.site.enums import Sweden\n",
    "\n",
    "enum_code(Sweden.SoilMoistureEnum.DRY), enum_code(Sweden.County.UPPSALA)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "ebe4ef42",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-07-17T18:03:38.545985Z",
     "iopub.status.busy": "2025-07-17T18:03:38.545672Z",
     "iopub.status.idle": "2025-07-17T18:03:38.554448Z",
     "shell.execute_reply": "2025-07-17T18:03:38.553959Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "26.672815668837686"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from pyforestry.sweden.siteindex.sis.hagglund_lundmark_1977 import Hagglund_Lundmark_1977_SIS\n",
    "\n",
    "sis = Hagglund_Lundmark_1977_SIS(\n",
    "    species=\"Picea abies\",\n",
    "    latitude=60,\n",
    "    altitude=100,\n",
    "    soil_moisture=Sweden.SoilMoistureEnum.MESIC,\n",
    "    ground_layer=Sweden.BottomLayer.FRESH_MOSS,\n",
    "    vegetation=Sweden.FieldLayer.BILBERRY,\n",
    "    soil_texture=Sweden.SoilTextureTill.SANDY,\n",
    "    climate_code=Sweden.ClimateZone.K1,\n",
    "    lateral_water=Sweden.SoilWater.SELDOM_NEVER,\n",
    "    soil_depth=Sweden.SoilDepth.DEEP,\n",
    "    incline_percent=5,\n",
    "    aspect=0,\n",
    "    nfi_adjustments=True,\n",
    "    dlan=Sweden.County.UPPSALA,\n",
    "    peat=False,\n",
    "    gotland=False,\n",
    "    coast=False,\n",
    "    limes_norrlandicus=False,\n",
    ")\n",
    "float(sis)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Generate Site Categories From Requested SIS\n",
    "Use `predict_site_categories_county_tree` to get all categorical site inputs from\n",
    "`species`, requested `sis_hagglund_1979`, and county, then compare requested vs achieved SIS.\n"
   ],
   "id": "generated-site-cats"
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "\n",
    "from pyforestry.sweden.siteindex.sis.generated_site_category_trees import (\n",
    "    predict_site_categories_county_tree,\n",
    ")\n",
    "\n",
    "requested_sis = 24.0\n",
    "species = \"Picea abies\"\n",
    "county = Sweden.County.UPPSALA\n",
    "\n",
    "predicted_categories = predict_site_categories_county_tree(\n",
    "    sis_hagglund_1979=requested_sis,\n",
    "    species=species,\n",
    "    Direktlan=county,\n",
    ")\n",
    "\n",
    "achieved_sis = Hagglund_Lundmark_1977_SIS(\n",
    "    species=species,\n",
    "    latitude=60,\n",
    "    altitude=100,\n",
    "    soil_moisture=predicted_categories[\"soil_moisture\"],\n",
    "    ground_layer=predicted_categories[\"bottom_layer\"],\n",
    "    vegetation=predicted_categories[\"field_layer\"],\n",
    "    soil_texture=predicted_categories[\"soil_texture\"],\n",
    "    climate_code=Sweden.ClimateZone.K1,\n",
    "    lateral_water=predicted_categories[\"soil_water\"],\n",
    "    soil_depth=predicted_categories[\"soil_depth\"],\n",
    "    incline_percent=5,\n",
    "    aspect=0,\n",
    "    nfi_adjustments=True,\n",
    "    dlan=county,\n",
    "    ditched=bool(predicted_categories[\"ditched\"]),\n",
    "    peat=False,\n",
    "    gotland=False,\n",
    "    coast=False,\n",
    "    limes_norrlandicus=False,\n",
    ")\n",
    "\n",
    "summary = pd.DataFrame(\n",
    "    [\n",
    "        {\n",
    "            \"requested_sis\": requested_sis,\n",
    "            \"achieved_sis\": float(achieved_sis),\n",
    "            \"sis_abs_error\": abs(float(achieved_sis) - requested_sis),\n",
    "            \"sis_rel_error_pct\": 100.0 * abs(float(achieved_sis) - requested_sis) / requested_sis,\n",
    "        }\n",
    "    ]\n",
    ")\n",
    "display(summary)\n",
    "predicted_categories\n"
   ],
   "id": "generated-site-closeness"
  },
  {
   "cell_type": "markdown",
   "id": "371dc2e4",
   "metadata": {},
   "source": [
    "Geographic utilities and climate calculations."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "bf113048",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-07-17T18:03:38.556113Z",
     "iopub.status.busy": "2025-07-17T18:03:38.555948Z",
     "iopub.status.idle": "2025-07-17T18:03:38.693810Z",
     "shell.execute_reply": "2025-07-17T18:03:38.693242Z"
    }
   },
   "outputs": [],
   "source": [
    "from pyforestry.sweden.geo import Moren_Perttu_radiation_1994, RetrieveGeoCode\n",
    "\n",
    "RetrieveGeoCode.getDistanceToCoast(14.784528, 56.892405)\n",
    "RetrieveGeoCode.getClimateCode(14.784528, 56.892405)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "52f63767",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-07-17T18:03:38.696289Z",
     "iopub.status.busy": "2025-07-17T18:03:38.696072Z",
     "iopub.status.idle": "2025-07-17T18:03:38.700315Z",
     "shell.execute_reply": "2025-07-17T18:03:38.699787Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1216.3800000000003, 1266.3800000000003)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "calc = Moren_Perttu_radiation_1994(latitude=60, altitude=100, july_avg_temp=17, jan_avg_temp=-8)\n",
    "(\n",
    "    calc.calculate_temperature_sum_1000m(threshold_temperature=5),\n",
    "    calc.get_corrected_temperature_sum(threshold_temperature=5),\n",
    ")"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.11.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}