Create app.py

app.py

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+import gradio as gr
+import pandas as pd
+
+# Function to find solutions with floating-point comparison tolerance
+def find_solutions(i_1, i_2):
+    m1_range = range(3, 7)  # m1 between 3 and 7
+    m2_range = range(3, 7)  # m2 between 3 and 7
+    valid_solutions = []
+    
+    # z1 and z3 ranges under 50
+    z1_range = range(18, 40)
+    z3_range = range(18, 40)
+
+    tolerance = 1e-9  # Set a tolerance for floating-point comparison
+
+    # Iterating over all possible combinations
+    for m1 in m1_range:
+        for m2 in m2_range:
+            for z1 in z1_range:
+                for z3 in z3_range:
+                    # Calculate left-hand side and right-hand side of the equation
+                    lhs = (i_1 + 1) * m1 * z1
+                    rhs = (i_2 + 1) * m2 * z3
+                    
+                    # Use a tolerance to compare floating-point numbers
+                    if abs(lhs - rhs) < tolerance:
+                        valid_solutions.append((m1, m2, z1, z3))
+
+    # Convert the list of solutions to a pandas DataFrame
+    df = pd.DataFrame(valid_solutions, columns=['m1', 'm2', 'z1', 'z3'])
+
+    return df
+
+# Create the Gradio app
+demo = gr.Interface(
+    fn=find_solutions,
+    inputs=[gr.Number(label="i_1"), gr.Number(label="i_2")],
+    outputs=gr.DataFrame(label="Solutions"),
+    title="iSolver | Find Valid Parameter Sets",
+    description="""
+    **Find all valid solutions** to satisfy the axle spacing equation of a two-speed manual transmission system.
+
+    - **Equation**: (i_1 + 1) * m_1 * z_1 = (i_2 + 1) * m_2 * z_3
+    - **i_i**: Conversion rates between gears
+    - **m_i**: Modules of gears
+    - **z_1** and **z_3**: The number of teeth on gears 1 and 3
+
+    Enter two values for **i_1** and **i_2** below:
+    """
+)
+
+# Launch the app
+demo.launch(share=True)