Merge pull request #17 from kraina-ai/fix-mlinpl

Fix issues with MLinPL version of tutorial

Author: simonusher

answers/MLinPL/05_bikes_transfer_learning.ipynb

@@ -255,7 +255,7 @@
     "positive_samples[\"is_positive\"] = True\n",
     "\n",
     "# Mark remaining regions as negative\n",
-    "negative_samples = regions_gdf.copy()[~regions_gdf.index.isin(positive_samples_new.index)]\n",
+    "negative_samples = regions_gdf.copy()[~regions_gdf.index.isin(positive_samples.index)]\n",
     "negative_samples[\"is_positive\"] = False\n",
     "\n",
     "# Just to keep everything balanced - undersampling\n",
@@ -473,7 +473,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.6"
+   "version": "3.10.9"
   },
   "rise": {
    "controls": false,

answers/MLinPL/06_trip_flow_prediction.ipynb

@@ -6,7 +6,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "%pip install srai[torch]"
+    "%pip install srai[torch] \"xgboost<3\" \"annoy<2\""
    ]
   },
   {
@@ -33,7 +33,7 @@
     "with zipfile.ZipFile('../../data/trips_hexes.zip', \"r\") as zf:\n",
     "    for member in tqdm(zf.infolist(), desc=\"\"):\n",
     "        try:\n",
-    "            zf.extract(member, 'data')\n",
+    "            zf.extract(member, '../../data/')\n",
     "        except zipfile.error:\n",
     "            pass"
    ]
@@ -238,7 +238,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "scrolled": false
+   },
    "outputs": [],
    "source": [
     "buffered_regions = ring_buffer_h3_regions_gdf(regions_gdf=portugal_h3_regions, distance=neighbours_distance)\n",
@@ -354,7 +356,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "scrolled": false
+    "scrolled": true
    },
    "outputs": [],
    "source": [
@@ -397,36 +399,6 @@
     ")"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import matplotlib.pyplot as plt\n",
-    "\n",
-    "fig = plt.figure(figsize=(14,9))\n",
-    "ax = fig.add_subplot(111, \n",
-    "                     projection='3d')\n",
-    " \n",
-    "for idx in pca_embeddings.index:\n",
-    "    ax.scatter(pca_embeddings.loc[idx][0],\n",
-    "               pca_embeddings.loc[idx][1],\n",
-    "               pca_embeddings.loc[idx][2],\n",
-    "               s=60)\n",
-    "\n",
-    "ax.set_xlabel(\"PC1\", \n",
-    "              fontsize=12)\n",
-    "ax.set_ylabel(\"PC2\", \n",
-    "              fontsize=12)\n",
-    "ax.set_zlabel(\"PC3\", \n",
-    "              fontsize=12)\n",
-    " \n",
-    "ax.view_init(30, 125)\n",
-    "plt.title(\"3D PCA plot\")\n",
-    "plt.show()"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -723,7 +695,7 @@
     "\n",
     "trainer_kwargs = {\n",
     "    # \"max_epochs\": 50, # uncomment for a longer training\n",
-    "    \"max_epochs\": 25,\n",
+    "    \"max_epochs\": 5,\n",
     "    # \"accelerator\": \"cpu\",\n",
     "}\n",
     "\n",
@@ -940,7 +912,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.4"
+   "version": "3.10.9"
   }
  },
  "nbformat": 4,

requirements.txt

@@ -5,4 +5,5 @@ notebook>=6,<7 # RISE not compatible with version 7
 pydeck==0.8.0
 RISE==5.7.1
 osmnx==1.7.0
-nbgrader==0.8.5
+nbgrader==0.8.5
+h3>=4.0.0b1,<4.0.0b3

tutorial/MLinPL/05_bikes_transfer_learning.ipynb

@@ -431,7 +431,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.6"
+   "version": "3.10.9"
   },
   "rise": {
    "controls": false,

tutorial/MLinPL/06_trip_flow_prediction.ipynb

@@ -6,7 +6,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "%pip install srai[torch]"
+    "%pip install srai[torch] \"xgboost<3\" \"annoy<2\""
    ]
   },
   {
@@ -33,7 +33,7 @@
     "with zipfile.ZipFile('../../data/trips_hexes.zip', \"r\") as zf:\n",
     "    for member in tqdm(zf.infolist(), desc=\"\"):\n",
     "        try:\n",
-    "            zf.extract(member, 'data')\n",
+    "            zf.extract(member, '../../data/')\n",
     "        except zipfile.error:\n",
     "            pass"
    ]
@@ -395,36 +395,6 @@
     ")"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import matplotlib.pyplot as plt\n",
-    "\n",
-    "fig = plt.figure(figsize=(14,9))\n",
-    "ax = fig.add_subplot(111, \n",
-    "                     projection='3d')\n",
-    " \n",
-    "for idx in pca_embeddings.index:\n",
-    "    ax.scatter(pca_embeddings.loc[idx][0],\n",
-    "               pca_embeddings.loc[idx][1],\n",
-    "               pca_embeddings.loc[idx][2],\n",
-    "               s=60)\n",
-    "\n",
-    "ax.set_xlabel(\"PC1\", \n",
-    "              fontsize=12)\n",
-    "ax.set_ylabel(\"PC2\", \n",
-    "              fontsize=12)\n",
-    "ax.set_zlabel(\"PC3\", \n",
-    "              fontsize=12)\n",
-    " \n",
-    "ax.view_init(30, 125)\n",
-    "plt.title(\"3D PCA plot\")\n",
-    "plt.show()"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -719,7 +689,7 @@
     "\n",
     "trainer_kwargs = {\n",
     "    # \"max_epochs\": 50, # uncomment for a longer training\n",
-    "    \"max_epochs\": 25,\n",
+    "    \"max_epochs\": 5,\n",
     "    # \"accelerator\": \"cpu\",\n",
     "}\n",
     "\n",
@@ -936,7 +906,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.4"
+   "version": "3.10.9"
   }
  },
  "nbformat": 4,