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Clay-foundation · Feb 9, 2024 · 567a73a · 567a73a
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diff --git a/docs/partial-inputs-flood-tutorial.ipynb b/docs/partial-inputs-flood-tutorial.ipynb
@@ -419,7 +419,7 @@
     "multi_model = CLAYModule.load_from_checkpoint(\n",
     "    CKPT_PATH,\n",
     "    mask_ratio=0.0,\n",
-    "    band_groups={\"rgb\": (2, 1, 0), \"nir\": (3,), \"swir\": (4,5)},\n",
+    "    band_groups={\"rgb\": (2, 1, 0), \"nir\": (3,), \"swir\": (4, 5)},\n",
     "    bands=6,\n",
     "    strict=False,  # ignore the extra parameters in the checkpoint\n",
     ")\n",
@@ -436,7 +436,6 @@
     "        2893.86,  # nir\n",
     "        2303.00,  # swir16\n",
     "        1807.79,  # swir22\n",
-    "        \n",
     "    ]\n",
     "    STD = [\n",
     "        2026.96,  # red\n",
@@ -481,7 +480,7 @@
     "        batch[\"pixels\"] = batch[\"pixels\"].to(multi_model.device)\n",
     "        # Pass just the specific band through the model\n",
     "        batch[\"timestep\"] = batch[\"timestep\"].to(multi_model.device)\n",
-    "        batch[\"timestep_non_norm\"] = batch[\"timestep_non_norm\"] #.to(rgb_model.device)\n",
+    "        batch[\"timestep_non_norm\"] = batch[\"timestep_non_norm\"]  # .to(rgb_model.device)\n",
     "        batch[\"latlon\"] = batch[\"latlon\"].to(multi_model.device)\n",
     "\n",
     "        # Pass pixels, latlon, timestep through the encoder to create encoded patches\n",
@@ -606,7 +605,6 @@
    "outputs": [],
    "source": [
     "from sklearn.manifold import TSNE\n",
-    "from sklearn.ensemble import IsolationForest\n",
     "\n",
     "# List to store date tuples\n",
     "all_date_tuples = []\n",
@@ -617,8 +615,11 @@
     "    year_tensor, month_tensor, day_tensor = tensor_list\n",
     "\n",
     "    # Reshape into list of tuples\n",
-    "    date_tuples = [(int(year), int(month), int(day)) for year, month, day in zip(year_tensor, month_tensor, day_tensor)]\n",
-    "    \n",
+    "    date_tuples = [\n",
+    "        (int(year), int(month), int(day))\n",
+    "        for year, month, day in zip(year_tensor, month_tensor, day_tensor)\n",
+    "    ]\n",
+    "\n",
     "    # Append to the list of all date tuples\n",
     "    all_date_tuples.extend(date_tuples)\n",
     "\n",
@@ -651,11 +652,11 @@
     "\n",
     "# Annotate each point with the corresponding date\n",
     "for i, (x, y) in enumerate(zip(X_tsne[:, 0], X_tsne[:, 1])):\n",
-    "    plt.annotate(f'{all_date_tuples[i]}', (x, y))\n",
+    "    plt.annotate(f\"{all_date_tuples[i]}\", (x, y))\n",
     "\n",
-    "plt.title('t-SNE Visualization')\n",
-    "plt.xlabel('t-SNE Component 1')\n",
-    "plt.ylabel('t-SNE Component 2')\n",
+    "plt.title(\"t-SNE Visualization\")\n",
+    "plt.xlabel(\"t-SNE Component 1\")\n",
+    "plt.ylabel(\"t-SNE Component 2\")\n",
     "plt.show()"
    ]
   },

diff --git a/src/datamodule.py b/src/datamodule.py
@@ -19,6 +19,7 @@
 os.environ["GDAL_DISABLE_READDIR_ON_OPEN"] = "EMPTY_DIR"
 os.environ["GDAL_HTTP_MERGE_CONSECUTIVE_RANGES"] = "YES"
 
+
 # %%
 # Regular torch Dataset
 class ClayDataset(Dataset):
@@ -60,7 +61,14 @@ def read_chip(self, chip_path):
 
         # read timestep & normalize
         date = chip.tags()["date"]  # YYYY-MM-DD
-        year, month, day, year_non_norm, month_non_norm, day_non_norm = self.normalize_timestamp(date)
+        (
+            year,
+            month,
+            day,
+            year_non_norm,
+            month_non_norm,
+            day_non_norm,
+        ) = self.normalize_timestamp(date)
 
         # read lat,lon from UTM to WGS84 & normalize
         bounds = chip.bounds  # xmin, ymin, xmax, ymax