joblib dump

src/report/report.py

@@ -320,7 +320,7 @@ def report(*args):
         latex_report += r"""
         \begin{figure}[H]
         \centering
-        \includegraphics[width=1\linewidth]{Histogram.png}
+        \includegraphics[width=1\linewidth]{kdeplot.png}
         \caption{Kde plot visualizing the distribution of the target variable, a subset of training, and testing sets}
         \label{fig:Histogram}
         \end{figure}
@@ -351,16 +351,17 @@ def report(*args):
         latex_report += df1.style.format("${:.2f}$").to_latex(position_float = 'centering', hrules = True, caption = 'Model performances summary', label= 'table:reg_perf')
 
         if "PLS" in to_report:
-            latex_report += r"""To identify the most important and influential spectral regions in the model, Selectivity ratio (SR) \cite{kvalheim2020variable, farres2015comparison} test applied, and the important variables in the model were 
-            visualized in \cref{fig:importance}. \par
+            # latex_report += r"""To identify the most important and influential spectral regions in the model, Selectivity ratio (SR) \cite{kvalheim2020variable, farres2015comparison} test applied, and the important variables in the model were 
+            # visualized in \cref{fig:importance}. \par
             
-            \begin{figure}[h]
-            \centering
-            \includegraphics[width=1\linewidth]{Variable_importance.png}
-            \caption{Visualizing important spectral regions identified in the PLS model on the raw and preprocessed average spectrum}
-            \label{fig:importance}
-            \end{figure}
-            """
+            # \begin{figure}[h]
+            # \centering
+            # \includegraphics[width=1\linewidth]{Variable_importance.png}
+            # \caption{Visualizing important spectral regions identified in the PLS model on the raw and preprocessed average spectrum}
+            # \label{fig:importance}
+            # \end{figure}
+            # """
+            pass
         elif "LW-PLS" in to_report:
             latex_report += r"""The average of raw and preprocessed spectra is visualized in \cref{fig:importance}. \par
             

src/shared_imports.py

@@ -45,7 +45,7 @@ import pyodbc
 import json
 
 # save models
-from joblib import dump, load, hash
+from joblib import load, hash
 
 st.set_option('deprecation.showPyplotGlobalUse', False)