Update app.py

app.py

@@ -1,24 +1,20 @@
 import pandas as pd
 import numpy as np
-import plotly.graph_objects as go
+import matplotlib.pyplot as plt
+import plotly.graph_objs as go
 import gradio as gr
 
-def plot_usage_volume():
-    # Define system rollout parameters
-    systems = ["App_1", "App_2", "App_3"]
-    users = [1000, 500, 2000]  # Estimated number of users after rollout completion
-    timelines = [12, 18, 24]   # Timeline for rollout in months
-
+def plot_usage_volume(system1, users1, timeline1, system2, users2, timeline2, system3, users3, timeline3):
     # Create empty dataframe to hold usage data
     data = pd.DataFrame(columns=["System", "Month", "Usage"])
 
     # Generate usage data for each system based on typical rollout behaviors
-    for i, system in enumerate(systems):
+    for i, system in enumerate([system1, system2, system3]):
         # Calculate the monthly usage volume based on the estimated number of users and timeline
         usage = np.concatenate([
-            np.linspace(0, users[i], int(timelines[i] * 0.25)),
-            np.linspace(users[i] * 0.5, users[i], int(timelines[i] * 0.5)),
-            np.linspace(users[i], users[i] * 0.75, int(timelines[i] * 0.25))
+            np.linspace(0, [users1, users2, users3][i], int([timeline1, timeline2, timeline3][i] * 0.25)),
+            np.linspace([users1, users2, users3][i] * 0.5, [users1, users2, users3][i], int([timeline1, timeline2, timeline3][i] * 0.5)),
+            np.linspace([users1, users2, users3][i], [users1, users2, users3][i] * 0.75, int([timeline1, timeline2, timeline3][i] * 0.25))
         ])
 
         # Add the usage data to the dataframe
@@ -26,24 +22,41 @@ def plot_usage_volume():
         system_data = pd.DataFrame({"System": [system] * len(usage), "Month": months, "Usage": usage})
         data = pd.concat([data, system_data], axis=0)
 
-    # Create a line plot that aggregates the usage of all systems
+    # Create a larger plot with multiple subplots
     fig = go.Figure()
-    aggregated_data = data.groupby("Month").sum().reset_index()
-    fig.add_trace(go.Scatter(x=aggregated_data["Month"], y=aggregated_data["Usage"], name="All Systems", line=dict(dash="dash", width=3)))
 
     # Plot the usage volume for each system
-    for system in systems:
+    for i, system in enumerate([system1, system2, system3]):
         system_data = data[data["System"] == system]
-        fig.add_trace(go.Scatter(x=system_data["Month"], y=system_data["Usage"], name=system))
+        fig.add_trace(go.Scatter(x=system_data["Month"], y=system_data["Usage"], mode='lines', name=system))
 
-    # Update layout settings
-    fig.update_layout(xaxis_title="Month", yaxis_title="Usage Volume", title="Usage Volume for Various Systems")
+    # Add a line plot that aggregates the usage of all systems
+    aggregated_data = data.groupby("Month").sum().reset_index()
+    fig.add_trace(go.Scatter(x=aggregated_data["Month"], y=aggregated_data["Usage"], mode='lines', name="All Systems", line=dict(dash="dash", width=4)))
 
-    # Return the Plotly figure
+    # Set the layout of the plot
+    fig.update_layout(xaxis_title="Month", yaxis_title="Usage Volume", title="System Rollout Usage Volume Plot")
+
+    # Return the plot as a Gradio output
     return fig
 
-# Create the Gradio interface
-iface = gr.Interface(fn=plot_usage_volume, title="System Rollout Usage Volume Plot", layout="horizontal", 
-                     description="This app generates a line plot showing the usage volume for various systems based on typical rollout behaviors.")
+# Define the input components
+inputs = [
+    gr.inputs.Textbox(label="System 1 Name", default="System1"),
+    gr.inputs.Number(label="System 1 Users", default=1000),
+    gr.inputs.Number(label="System 1 Timeline (months)", default=12),
+    gr.inputs.Textbox(label="System 2 Name", default="System2"),
+    gr.inputs.Number(label="System 2 Users", default=500),
+    gr.inputs.Number(label="System 2 Timeline (months)", default=18),
+    gr.inputs.Textbox(label="System 3 Name", default="System3"),
+    gr.inputs.Number(label="System 3 Users", default=2000),
+    gr.inputs.Number(label="System 3 Timeline (months)", default=24)]
+
+#Define the output component
+output = gr.outputs.Plotly(fig)
+
+#Create the interface
+iface = gr.Interface(fn=plot_usage_volume, title="System Rollout Usage Volume Plot", inputs=inputs, outputs=output, layout="horizontal")
+
+#Launch the interface
 iface.launch()
-