Adding caching and row plotting

src/display.py

@@ -5,7 +5,7 @@
 from st_aggrid import GridOptionsBuilder, AgGrid
 import streamlit as st
 from .load_data import load_dataframe, sort_by
-from .plot import plot_radar_chart_index, plot_radar_chart_name
+from .plot import plot_radar_chart_name, plot_radar_chart_rows
 
 
 def display_app():
@@ -69,9 +69,8 @@ def display_app():
 
     with column2:
         if grid_response['selected_rows'] is not None and len(grid_response['selected_rows']) > 0:
-            model_name = grid_response['selected_rows'][0]["model_name"]
-            figure = plot_radar_chart_name(dataframe=dataframe, model_name=model_name)
-            st.plotly_chart(figure, use_container_width=False)
+            figure = plot_radar_chart_rows(rows=grid_response['selected_rows'])
+            st.plotly_chart(figure, use_container_width=True)
         else:
             if len(subdata)>0:
                 figure = plot_radar_chart_name(dataframe=subdata, model_name=model_name)
@@ -80,6 +79,4 @@ def display_app():
     if grid_response['selected_rows'] is not None and len(grid_response['selected_rows']) > 0:
         st.markdown("**Model name:**   %s" % grid_response['selected_rows'][0]["model_name"])
     else:
-        st.markdown("**Model name:**   %s" % model_name)
-
-
+        st.markdown("**Model name:**   %s" % model_name)    

src/load_data.py

@@ -1,5 +1,7 @@
+import streamlit as st
 import pandas as pd
 
+@st.cache_data
 def load_dataframe() -> pd.DataFrame:
     """
     Load dataframe from the csv file in public directory
@@ -11,6 +13,7 @@ def load_dataframe() -> pd.DataFrame:
     dataframe = dataframe.drop(columns = "Unnamed: 0")
     return dataframe
 
+@st.cache_data
 def sort_by(dataframe: pd.DataFrame, column_name: str, ascending:bool = False) -> pd.DataFrame:
     """
     Sort the dataframe by column_name

src/plot.py

@@ -1,3 +1,4 @@
+import streamlit as st
 import plotly.graph_objects as go
 import numpy as np
 import pandas as pd
@@ -11,7 +12,12 @@ opacity = 0.75
 
 # categories to show radar chart
 categories = ["ARC", "GSM8K", "TruthfulQA", "Winogrande", "HellaSwag", "MMLU"]
+# Dataset columns
+columns = ["model_name", "ARC", "HellaSwag", "TruthfulQA", "Winogrande", "GSM8K",
+                    "MMLU", "Average"]
 
+
+@st.cache_data
 def plot_radar_chart_index(dataframe: pd.DataFrame, index: int, categories: list = categories, fillcolor: str = fillcolor, line_color:str = line_color):
     """
     plot the index-th row of the dataframe
@@ -56,6 +62,7 @@ def plot_radar_chart_index(dataframe: pd.DataFrame, index: int, categories: list
 
     return fig
 
+@st.cache_data
 def plot_radar_chart_name(dataframe: pd.DataFrame, model_name: str, categories: list = categories, fillcolor: str = fillcolor, line_color:str = line_color):
     """
     plot the results of the model named model_name row of the dataframe
@@ -98,4 +105,95 @@ def plot_radar_chart_name(dataframe: pd.DataFrame, model_name: str, categories:
       showlegend=False
     )
 
+    return fig
+
+
+@st.cache_data
+def plot_radar_chart_index(dataframe: pd.DataFrame, index: int, categories: list = categories, fillcolor: str = fillcolor, line_color:str = line_color):
+    """
+    plot the index-th row of the dataframe
+    
+    Arguments:
+    dataframe: a pandas DataFrame 
+    index: the index of the row we want to plot
+    categories: the list of the metrics
+    fillcolor: a string specifying the color to fill the area
+    line_color: a string specifying the color of the lines in the graph
+    """
+    fig = go.Figure()
+    data = dataframe.loc[index,categories].to_numpy()*100
+    data  = data.astype(float)
+    # rounding data
+    data = data.round(decimals = 2)
+    
+    # add data to close the area of the radar chart
+    data = np.append(data, data[0])
+    categories_theta = categories.copy()
+    categories_theta.append(categories[0])
+    model_name = dataframe.loc[index,"model_name"] 
+    #print("Printing data ", data, " for ", model_name)
+
+    fig.add_trace(go.Scatterpolar(
+          r=data,
+          theta=categories_theta,
+          fill='toself',
+          fillcolor = fillcolor,
+          opacity = opacity,
+          line=dict(color = line_color),
+          name= model_name
+    ))
+    fig.update_layout(
+      polar=dict(
+        radialaxis=dict(
+          visible=True,
+          range=[0, 100.]
+        )),
+      showlegend=False
+    )
+
+    return fig
+
+@st.cache_data
+def plot_radar_chart_rows(rows: object, columns:list = columns, categories: list = categories, fillcolor: str = fillcolor, line_color:str = line_color):
+    """
+    plot the results of the model selected by the checkbox
+    
+    Arguments:
+    rows: an iterable whose elements are dicts with columns as their keys 
+    columns: the list of the columns to use
+    categories: the list of the metrics
+    fillcolor: a string specifying the color to fill the area
+    line_color: a string specifying the color of the lines in the graph
+    """
+    fig = go.Figure()
+    dataset = pd.DataFrame(rows, columns=columns)
+    data = dataset[categories].to_numpy()
+    data  = data.astype(float)
+    
+    # add data to close the area of the radar chart
+    data = np.append(data, data[:,0].reshape((-1,1)), axis=1)
+    categories_theta = categories.copy()
+    categories_theta.append(categories[0])
+     
+    #print("Printing data ", data, " for ", model_name)
+    for i in range(len(dataset)):
+
+      fig.add_trace(go.Scatterpolar(
+            r=data[i,:],
+            theta=categories_theta,
+            fill='toself',
+            fillcolor = fillcolor,
+            opacity = opacity,
+            line=dict(color = line_color),
+            name= dataset.loc[i,"model_name"]
+      ))
+      fig.update_layout(
+        polar=dict(
+          radialaxis=dict(
+            visible=True,
+            range=[0, 100.]
+          )),
+        showlegend=False
+      )
+
     return fig