Upload YEL_2_0_Inference.ipynb

YEL_2_0_Inference.ipynb

@@ -20,7 +20,7 @@
     "| `building_height` | Building height at the point (m) |\n",
     "| `u_ratio` | Atmospheric-profile velocity at `z_relative`, divided by reference velocity |\n",
     "\n",
-    "The notebook reads these features from `Test.csv` in the current working directory."
+    "By default, the notebook loads these features from the public `Test.csv` file in the YEL 2.0 Hugging Face repository. You can instead provide a local or uploaded CSV file."
    ]
   },
   {
@@ -58,7 +58,8 @@
     "REQUIRED_COLUMNS = [\"x\", \"y\", \"z_relative\", \"sdf\", \"building_height\", \"u_ratio\"]\n",
     "\n",
     "# User settings\n",
-    "INPUT_CSV = Path(\"Test.csv\")\n",
+    "INPUT_CSV_URL = \"https://huggingface.co/SustainableUrbanSystemsLab/Yel-2.0/resolve/main/Test.csv\"\n",
+    "LOCAL_CSV = None  # Example: Path(\"/content/my_features.csv\")\n",
     "WIND_DIRECTIONS_DEG = list(range(0, 360, 45))  # 0°, 45°, ..., 315°\n",
     "REFERENCE_WIND_SPEED = 5.0  # Uref in m/s\n",
     "OUTPUT_CSV = Path(\"yel_predictions.csv\")"
@@ -68,7 +69,17 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## Load features from `Test.csv`"
+    "## Load input CSV\n",
+    "\n",
+    "The hosted `Test.csv` is used when `LOCAL_CSV` is `None`.\n",
+    "\n",
+    "To use your own file in Google Colab:\n",
+    "\n",
+    "1. Open the **Files** panel on the left.\n",
+    "2. Click **Upload to session storage** and select your CSV.\n",
+    "3. Set `LOCAL_CSV = Path(\"/content/your_file.csv\")` in the settings cell.\n",
+    "\n",
+    "Your CSV must contain the required columns listed at the top of this notebook."
    ]
   },
   {
@@ -77,14 +88,15 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "if not INPUT_CSV.is_file():\n",
-    "    raise FileNotFoundError(\n",
-    "        f\"Could not find {INPUT_CSV.resolve()}. Upload Test.csv to the Colab session \"\n",
-    "        \"before running this cell.\"\n",
-    "    )\n",
-    "\n",
-    "features = pd.read_csv(INPUT_CSV)\n",
-    "print(f\"Loaded {len(features):,} rows from {INPUT_CSV.resolve()}\")\n",
+    "if LOCAL_CSV is None:\n",
+    "    input_source = INPUT_CSV_URL\n",
+    "else:\n",
+    "    input_source = Path(LOCAL_CSV)\n",
+    "    if not input_source.is_file():\n",
+    "        raise FileNotFoundError(f\"Could not find local CSV: {input_source.resolve()}\")\n",
+    "\n",
+    "features = pd.read_csv(input_source)\n",
+    "print(f\"Loaded {len(features):,} rows from {input_source}\")\n",
     "\n",
     "missing = sorted(set(REQUIRED_COLUMNS) - set(features.columns))\n",
     "if missing:\n",