removing notebook

88750074 · Eric Duminil · 97ec5d80 · 97ec5d80 · 88750074
Commit 88750074 authored Nov 20, 2024 by Eric Duminil
--- a/python_scripts/add_trees_to_open_street_map/Parse OSM data.ipynb
+++ b/python_scripts/add_trees_to_open_street_map/Parse OSM data.ipynb
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "id": "4888de6c",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from pathlib import Path"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "id": "bb724cab",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import pickle"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "id": "b584ca38",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import pandas as pd"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "id": "e74c7f88",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from pyproj import Transformer\n",
-    "from shapely import LineString"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "id": "9eac1a09",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "EPSG_ID = 25832\n",
-    "to_local = Transformer.from_crs(\"EPSG:4326\", f\"EPSG:{EPSG_ID}\", always_xy=True)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 6,
-   "id": "0fed9052",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "pd.set_option('display.max_columns', None)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 7,
-   "id": "89e9aff8",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "[WindowsPath('cache/48_864071__48_866928__9_196641__9_203522.pickle'),\n",
-       " WindowsPath('cache/49_80081__49_803063__9_947011__9_95511.pickle'),\n",
-       " WindowsPath('cache/49_802665__49_804083__9_942116__9_945581.pickle'),\n",
-       " WindowsPath('cache/49_802698__49_804055__9_942167__9_945563.pickle'),\n",
-       " WindowsPath('cache/49_802704__49_803486__9_944034__9_945488.pickle')]"
-      ]
-     },
-     "execution_count": 7,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "list(Path('cache').glob('*.pickle'))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 8,
-   "id": "8aac3681",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "def load_cache(cache_path):\n",
-    "    with open(Path('cache') / '49_802698__49_804055__9_942167__9_945563.pickle', 'rb') as f:\n",
-    "        return pickle.load(f)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 9,
-   "id": "d050a116",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "def get_way_dict(way):\n",
-    "    # Length\n",
-    "    url = f'https://www.openstreetmap.org/way/{way.id}'\n",
-    "    xy_s = [to_local.transform(node.lon, node.lat) for node in way.nodes]\n",
-    "    path = LineString(xy_s)\n",
-    "    other_info = {'id': way.id,\n",
-    "                  'URL': f'=HYPERLINK(\"{url}\"; \"{url}\")',\n",
-    "                  'length [m]': round(path.length, 1)}\n",
-    "    return other_info | way.tags"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 10,
-   "id": "7a9f108b",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "numerical_columns = ['maxspeed [km/h]', 'width [m]', 'length [m]']"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 11,
-   "id": "741fa825",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "def create_table(ways):\n",
-    "    df = pd.DataFrame([get_way_dict(way) for way in ways]).set_index('id').rename(columns={'width': 'width [m]', 'maxspeed': 'maxspeed [km/h]'})\n",
-    "    for col in numerical_columns:\n",
-    "        df[col] = pd.to_numeric(df[col])\n",
-    "    df.fillna('')\n",
-    "    return df"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 16,
-   "id": "a12d5684",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "for cache_path in Path('cache').glob('*.pickle'):\n",
-    "    df = create_table(load_cache(cache_path))\n",
-    "    df.to_csv(Path('output') / f'OSM_infos_{cache_path.stem}.csv',\n",
-    "          sep=';',\n",
-    "          decimal=',',\n",
-    "          encoding='utf-8-sig'\n",
-    "    )"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "328d048f",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  }
- ],
- "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": "3.11.5"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 5
-}
-%% Cell type:code id:4888de6c tags:
-
-``` python
-from pathlib import Path
-```
-
-%% Cell type:code id:bb724cab tags:
-
-``` python
-import pickle
-```
-
-%% Cell type:code id:b584ca38 tags:
-
-``` python
-import pandas as pd
-```
-
-%% Cell type:code id:e74c7f88 tags:
-
-``` python
-from pyproj import Transformer
-from shapely import LineString
-```
-
-%% Cell type:code id:9eac1a09 tags:
-
-``` python
-EPSG_ID = 25832
-to_local = Transformer.from_crs("EPSG:4326", f"EPSG:{EPSG_ID}", always_xy=True)
-```
-
-%% Cell type:code id:0fed9052 tags:
-
-``` python
-pd.set_option('display.max_columns', None)
-```
-
-%% Cell type:code id:89e9aff8 tags:
-
-``` python
-list(Path('cache').glob('*.pickle'))
-```
-
-%% Output
-
-    [WindowsPath('cache/48_864071__48_866928__9_196641__9_203522.pickle'),
-     WindowsPath('cache/49_80081__49_803063__9_947011__9_95511.pickle'),
-     WindowsPath('cache/49_802665__49_804083__9_942116__9_945581.pickle'),
-     WindowsPath('cache/49_802698__49_804055__9_942167__9_945563.pickle'),
-     WindowsPath('cache/49_802704__49_803486__9_944034__9_945488.pickle')]
-
-%% Cell type:code id:8aac3681 tags:
-
-``` python
-def load_cache(cache_path):
-    with open(Path('cache') / '49_802698__49_804055__9_942167__9_945563.pickle', 'rb') as f:
-        return pickle.load(f)
-```
-
-%% Cell type:code id:d050a116 tags:
-
-``` python
-def get_way_dict(way):
-    # Length
-    url = f'https://www.openstreetmap.org/way/{way.id}'
-    xy_s = [to_local.transform(node.lon, node.lat) for node in way.nodes]
-    path = LineString(xy_s)
-    other_info = {'id': way.id,
-                  'URL': f'=HYPERLINK("{url}"; "{url}")',
-                  'length [m]': round(path.length, 1)}
-    return other_info | way.tags
-```
-
-%% Cell type:code id:7a9f108b tags:
-
-``` python
-numerical_columns = ['maxspeed [km/h]', 'width [m]', 'length [m]']
-```
-
-%% Cell type:code id:741fa825 tags:
-
-``` python
-def create_table(ways):
-    df = pd.DataFrame([get_way_dict(way) for way in ways]).set_index('id').rename(columns={'width': 'width [m]', 'maxspeed': 'maxspeed [km/h]'})
-    for col in numerical_columns:
-        df[col] = pd.to_numeric(df[col])
-    df.fillna('')
-    return df
-```
-
-%% Cell type:code id:a12d5684 tags:
-
-``` python
-for cache_path in Path('cache').glob('*.pickle'):
-    df = create_table(load_cache(cache_path))
-    df.to_csv(Path('output') / f'OSM_infos_{cache_path.stem}.csv',
-          sep=';',
-          decimal=',',
-          encoding='utf-8-sig'
-    )
-```
-
-%% Cell type:code id:328d048f tags:
-
-``` python
-```
--- a/python_scripts/flow_chart/cgsc - paper.dot
+++ b/python_scripts/flow_chart/cgsc - paper.dot
+digraph G{
+    ratio="fill";
+    size="10,6!";
+    margin=0;
+    dpi=180;
+    rankdir="LR";
+    graph [fontname = "Ubuntu"];
+    node [fontname = "Ubuntu"];
+    edge [fontname = "Ubuntu"];
+    node [shape=ellipse];
+    compound=true;
+
+    citygml [label="CityGML", shape=box3d];
+    a [label="OpenStreetMap", shape=note];
+    b [label="Cadastre", shape=note];
+    c [label="Custom DB", shape=note];
+    trees [label="Trees.shp", shape=note];
+    # floors [label="Floors.csv", shape=note];
+    # dreso [label="DreSo.csv", shape=note];
+    # lib [label="Physics.lib", shape=component];
+    weather [label="Weather data", shape=component];
+    
+    
+    
+    
+    subgraph cluster_sim {
+      label="Simulation";
+      node [shape=note, style=rounded];
+      simstadt [label="<sim>SimStadt | <green> Green-Water analysis | <heat>Heating & Cooling demand", shape=record];
+      green [label="Green library", shape=cylinder];
+      # archetypes [label="Quarter archetypes", shape=cylinder];
+      color=lightgrey;
+      # green -> simstadt;
+    }    
+    # green -> simstadt;
+    a -> trees;
+    b -> trees;
+    c -> trees;
+
+
+
+    citygml -> simstadt:sim;
+    trees -> citygml;
+    # dreso -> citygml [label="?"];
+    # floors -> citygml [label="add-floor.py"];
+    # lib -> simstadt:sim [label="window_ratio.py"];
+    weather -> simstadt:green;
+    weather -> simstadt:heat;
+
+    #shp [label="Results.shp", shape=note];
+
+    subgraph cluster_1 {
+      label="Outputs";
+      node [shape=record];
+      csv1 [label="Heating.csv"];
+      csv2 [label="Cooling.csv"];
+      csv3 [label="Water.csv |{ Missing water | Evapotranspiration | Cooling effect}"];
+      color=lightgrey;
+    }
+
+    # optimizer [label="TUM optimizer.py", style=filled, shape=cylinder];
+    # gis [label="ArcGIS", style=filled, shape=cylinder];
+
+    #csv3 -> optimizer [ltail=cluster_1];
+    #csv3 -> gis [ltail=cluster_1];
+
+    simstadt:heat -> csv1;
+    simstadt:heat -> csv2;
+    simstadt:green -> csv3;
+    #shp -> gis;
+
+
+
+    #optimizer -> lib [style=dotted];
+    #optimizer -> floors [style=dotted];
+    #gis -> trees [style=dotted];
+
+    { rank=min; a; b; c}
+    { rank=max; csv1; csv2; csv3}
+}