Pushing the docs to dev/ for branch: main, commit 48a3c0b143e3d62050a582eff2c106e17e9dea77

Author: sklearn-ci

dev/_downloads/07fcc19ba03226cd3d83d4e40ec44385/auto_examples_python.zip

@@ -148,7 +148,7 @@
       },
       "outputs": [],
       "source": [
-        "import numpy as np\nfrom mpl_toolkits.mplot3d import Axes3D\nfrom sklearn.inspection import partial_dependence\n\nfig = plt.figure()\n\nfeatures = (\"AveOccup\", \"HouseAge\")\npdp = partial_dependence(\n    est, X_train, features=features, kind=\"average\", grid_resolution=10\n)\nXX, YY = np.meshgrid(pdp[\"values\"][0], pdp[\"values\"][1])\nZ = pdp.average[0].T\nax = Axes3D(fig)\nfig.add_axes(ax)\n\nsurf = ax.plot_surface(XX, YY, Z, rstride=1, cstride=1, cmap=plt.cm.BuPu, edgecolor=\"k\")\nax.set_xlabel(features[0])\nax.set_ylabel(features[1])\nax.set_zlabel(\"Partial dependence\")\n# pretty init view\nax.view_init(elev=22, azim=122)\nplt.colorbar(surf)\nplt.suptitle(\n    \"Partial dependence of house value on median\\n\"\n    \"age and average occupancy, with Gradient Boosting\"\n)\nplt.subplots_adjust(top=0.9)\nplt.show()"
+        "import numpy as np\n\n# unused but required import for doing 3d projections with matplotlib < 3.2\nimport mpl_toolkits.mplot3d  # noqa: F401\n\nfrom sklearn.inspection import partial_dependence\n\nfig = plt.figure()\n\nfeatures = (\"AveOccup\", \"HouseAge\")\npdp = partial_dependence(\n    est, X_train, features=features, kind=\"average\", grid_resolution=10\n)\nXX, YY = np.meshgrid(pdp[\"values\"][0], pdp[\"values\"][1])\nZ = pdp.average[0].T\nax = fig.add_subplot(projection=\"3d\")\nfig.add_axes(ax)\n\nsurf = ax.plot_surface(XX, YY, Z, rstride=1, cstride=1, cmap=plt.cm.BuPu, edgecolor=\"k\")\nax.set_xlabel(features[0])\nax.set_ylabel(features[1])\nax.set_zlabel(\"Partial dependence\")\n# pretty init view\nax.view_init(elev=22, azim=122)\nplt.colorbar(surf)\nplt.suptitle(\n    \"Partial dependence of house value on median\\n\"\n    \"age and average occupancy, with Gradient Boosting\"\n)\nplt.subplots_adjust(top=0.9)\nplt.show()"
       ]
     }
   ],

dev/_downloads/21b82d82985712b5de6347f382c77c86/plot_partial_dependence.ipynb

@@ -261,7 +261,10 @@
 # Let's make the same partial dependence plot for the 2 features interaction,
 # this time in 3 dimensions.
 import numpy as np
-from mpl_toolkits.mplot3d import Axes3D
+
+# unused but required import for doing 3d projections with matplotlib < 3.2
+import mpl_toolkits.mplot3d  # noqa: F401
+
 from sklearn.inspection import partial_dependence
 
 fig = plt.figure()
@@ -272,7 +275,7 @@
 )
 XX, YY = np.meshgrid(pdp["values"][0], pdp["values"][1])
 Z = pdp.average[0].T
-ax = Axes3D(fig)
+ax = fig.add_subplot(projection="3d")
 fig.add_axes(ax)
 
 surf = ax.plot_surface(XX, YY, Z, rstride=1, cstride=1, cmap=plt.cm.BuPu, edgecolor="k")