Prepare for first GitHub workflow

sarahshi · Dec 7, 2023 · dc489ef · dc489ef
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Showing 8 changed files with 15,864 additions and 273 deletions.
diff --git a/Train_Supervised_Variational.py b/Train_Supervised_Variational.py
@@ -115,8 +115,8 @@
 
 # Step 2: Read in your DataFrame, drop rows with NaN in specific oxide columns, fill NaNs, and filter minerals
 lepr_df_load = mm.load_df('Validation_Data/lepr_allphases_lim_sp.csv')
-lepr_df, lepr_df_ex = mm.prep_df(lepr_df_load)
-lepr_df_pred, lepr_probability_matrix = mm.predict_class_prob(lepr_df)
+lepr_df, lepr_df_ex = mm.prep_df_nn(lepr_df_load)
+lepr_df_pred, lepr_probability_matrix = mm.predict_class_prob_nn(lepr_df)
 
 lepr_bayes_valid_report = classification_report(
     lepr_df_pred['Mineral'], lepr_df_pred['Predict_Mineral'], zero_division=0

diff --git a/Validation_Data/testfile.csv b/Validation_Data/testfile.csv
diff --git a/mineralML_colab.ipynb b/mineralML_colab.ipynb
@@ -15,7 +15,7 @@
     "import pandas as pd\n",
     "from sklearn.metrics import classification_report\n",
     "\n",
-    "!pip install Cython hdbscan\n",
+    "!pip install Cython\n",
     "!pip install -i https://test.pypi.org/simple/ mineralML==0.0.0.4\n",
     "import mineralML as mm\n",
     "\n",
@@ -119,8 +119,6 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "\n",
-    "# Look at the predicted mineral dataframe. \n",
     "\n",
     "df_pred_nn\n"
    ]