Updating to latest version

Author: Product team

notebooks/Dimensionality_reduction.ipynb

@@ -1067,7 +1067,7 @@
     }
    ],
    "source": [
-    "predictions = emulator1.predict(df_eval)\n",
+    "predictions = emulator1.predict(df_eval[input_columns])\n",
     "result_df = pd.concat([predictions[0], predictions[1]], axis=1)\n",
     "df_mean1, df_std1 = (\n",
     "    result_df.iloc[\n",
@@ -1480,7 +1480,7 @@
     ")\n",
     "\n",
     "# Use test data to predict the results\n",
-    "predictions2 = emulator2.predict(df_eval)\n",
+    "predictions2 = emulator2.predict(df_eval[input_columns])\n",
     "result_df2 = pd.concat([predictions2[0], predictions2[1]], axis=1)\n",
     "df_mean2, df_std2 = (\n",
     "    result_df2.iloc[:, : len(output_columns)],\n",

notebooks/Update.ipynb

@@ -356,8 +356,7 @@
     }
    ],
    "source": [
-    "# process_id = \"<INSERT-PROCESS-ID-HERE>\"\n",
-    "process_id = \"predict-mini-tundra-fanatic\"\n",
+    "process_id = \"<INSERT-PROCESS-ID-HERE>\"\n",
     "mean, std = emulator.get_process(process_id=process_id,verbose=True)"
    ]
   },

notebooks/bayesian_optimisation.ipynb

@@ -636,7 +636,7 @@
     "new_emulator.train(dataset=dataset, inputs=[\"x\", \"y\"], outputs=[\"z\"], verbose=True)\n",
     "\n",
     "# Inference on test data\n",
-    "predictions = new_emulator.predict(df_test)\n",
+    "predictions = new_emulator.predict(df_test[[\"x\", \"y\"]])\n",
     "result_df = pd.concat([predictions[0], predictions[1]], axis=1)\n",
     "df_mean, df_stdev = result_df.iloc[:, 0], result_df.iloc[:, 1]\n",
     "z_mean, z_stdev = df_mean.values, df_stdev.values"