add rest of characteristics

.gitignore

@@ -1,2 +1,4 @@
 venv/*
-__pycache__/*
+__pycache__/
+*.pyc
+graphs/__pycache__/model_characteristics.cpython-39.pyc

app.py

@@ -4,7 +4,7 @@ import pandas as pd
 import pickle
 import plotly.express as px
 from graphs.model_market_share import create_plotly_stacked_area_chart
-from graphs.model_characteristics import create_plotly_language_concentration_chart
+from graphs.model_characteristics import create_plotly_language_concentration_chart, create_plotly_publication_curves_with_legend
 
 # Incorporate data
 df = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/gapminder2007.csv')
@@ -24,6 +24,10 @@ with open('data_frames/language_concentration_df.pkl', 'rb') as f:
     language_concentration_df = pickle.load(f)
 with open('data_frames/download_license_cumsum_df.pkl', 'rb') as f:
     license_concentration_df = pickle.load(f)
+with open('data_frames/download_method_cumsum_df.pkl', 'rb') as f:
+    download_method_cumsum_df = pickle.load(f)
+with open('data_frames/download_arch_cumsum_df.pkl', 'rb') as f:
+    download_arch_cumsum_df = pickle.load(f)
 
 TEMP_MODEL_EVENTS = {
     # "Yolo World Mirror": "2024-03-01",
@@ -72,10 +76,32 @@ fig3 = create_plotly_language_concentration_chart(
     license_concentration_df, 'period', 'status', 'percent', LICENSE_SEGMENT_ORDER, PALETTE_0
 )
 
+METHOD_PLOT_CHOICES = {
+    "cumulative": "none", # none, mean, sum
+    "y_col": "percent", # percent count
+    "y_log": False, # True, False
+    "period": "W",
+}
+fig4 = create_plotly_publication_curves_with_legend(
+    download_method_cumsum_df, METHOD_PLOT_CHOICES, PALETTE_0
+)
+
+ARCHITECTURE_PLOT_CHOICES = {
+    "cumulative": "none", # none, mean, sum
+    "y_col": "percent", # percent count
+    "y_log": False, # True, False
+    "period": "W",
+}
+fig5 = create_plotly_publication_curves_with_legend(
+    download_arch_cumsum_df, ARCHITECTURE_PLOT_CHOICES, PALETTE_0
+)
+
 # Make global font family
 fig.update_layout(font_family="Inter")
 fig2.update_layout(font_family="Inter")
 fig3.update_layout(font_family="Inter")
+fig4.update_layout(font_family="Inter")
+fig5.update_layout(font_family="Inter")
 
 # App layout
 app.layout = html.Div(
@@ -108,6 +134,10 @@ def update_graph(selected_metric):
         return fig2
     elif selected_metric == 'License':
         return fig3
+    elif selected_metric == 'Method':
+        return fig4
+    elif selected_metric == 'Architecture':
+        return fig5
 
 # Run the app
 if __name__ == '__main__':

graphs/model_characteristics.py

@@ -79,4 +79,83 @@ def create_plotly_language_concentration_chart(
         gridwidth=1
     )
     
+    return fig
+
+def create_plotly_publication_curves_with_legend(
+    download_method_cumsum_df,
+    METHOD_PLOT_CHOICES,
+    color_palette=None
+):
+    """
+    Version with traditional legend instead of inline labels
+    """
+    
+    fig = go.Figure()
+    
+    groups = download_method_cumsum_df['status'].unique()
+    
+    if color_palette is None:
+        color_palette = px.colors.qualitative.Set1
+    
+    for i, group in enumerate(groups):
+        group_data = download_method_cumsum_df[download_method_cumsum_df['status'] == group]
+        group_data = group_data.sort_values('period')
+        
+        x_vals = group_data['period']
+        y_vals = group_data[METHOD_PLOT_CHOICES["y_col"]]
+        
+        if METHOD_PLOT_CHOICES.get("y_format") == "percent":
+            y_vals = y_vals * 100
+        
+        fig.add_trace(
+            go.Scatter(
+                x=x_vals,
+                y=y_vals,
+                name=group,
+                mode='lines',
+                line=dict(
+                    color=color_palette[i % len(color_palette)],
+                    width=3
+                ),
+                opacity=0.85,
+                hovertemplate='<b>%{fullData.name}</b><br>' +
+                             'Period: %{x}<br>' +
+                             'Value: %{y:.2f}%<extra></extra>' if METHOD_PLOT_CHOICES.get("y_format") == "percent" 
+                             else '<b>%{fullData.name}</b><br>Period: %{x}<br>Value: %{y}<extra></extra>'
+            )
+        )
+    
+    fig.update_layout(
+        width=1125,
+        height=225,
+        showlegend=True,
+        legend=dict(
+            orientation="h",
+            yanchor="bottom",
+            y=1.02,
+            xanchor="right",
+            x=1
+        ),
+        margin=dict(l=60, r=60, t=60, b=60),
+        plot_bgcolor='white',
+        hovermode='x unified'
+    )
+    
+    fig.update_xaxes(
+        title_text="Period",
+        showgrid=False,
+        zeroline=False
+    )
+    
+    y_title = METHOD_PLOT_CHOICES["y_col"]
+    if METHOD_PLOT_CHOICES.get("y_format") == "percent":
+        y_title += " (%)"
+    
+    fig.update_yaxes(
+        title_text=y_title,
+        showgrid=False,
+        zeroline=False,
+        type='log' if METHOD_PLOT_CHOICES.get("y_log") else 'linear'
+    )
+    
     return fig

start.sh

@@ -0,0 +1,10 @@
+# /bin/sh
+
+# Create a virtual environment
+python -m venv venv
+source venv/bin/activate
+pip install --upgrade pip
+pip install -r requirements.txt
+
+# Run the Dash app
+python app.py