This project is a powerful tool for IC designers to efficiently size transistors based on specific operating conditions and performance requirements. It consists of two main phases: LUT (Look-Up Table) generation and data visualization.

• Support for complex conditional queries
• Dynamic plotting with customizable axes and color mapping
• Real-time display of operating points
• Handles large datasets (demonstrated with 900k points)

• Python script interfacing with Spectre simulator Generates comprehensive transistor operating point data

• Interactive GUI for data exploration and transistor sizing Built with Tkinter, Matplotlib, and Pandas

1. Load the DataFrame (e.g., "900kPoints.csv")
2. Add conditions using the sliding bars (e.g., VSB > 0.2, VSB < 0.4)
3. Configure graph settings (X-axis, Y-axis, hue variable, etc.)
4. Click "Plot" to visualize the data
5. Click on any point to display its full operating point information

The included demo showcases sizing the input NMOS pair of a 5T OTA:

• Conditions set: 0.2 < VSB < 0.4 (accounting for body effect), requirements for transistor parameteres (gm, rout)
• Plot: VGS vs. area, with drain current (id) as the hue variable
• Goal: Find the point with lowest VGS and area while maintaining reasonable power consumption
• Dataset: 900,000 operating points

This demo illustrates the power of the tool in quickly identifying optimal transistor sizes that meet multiple criteria simultaneously.

main_app.py: Contains the main GUI application logic DF_OPS.py: Handles dataframe operations and condition parsing

1. Clone this repository
2. Install required dependencies (Tkinter, Pandas, Matplotlib)
3. Run main_app.py to launch the application
4. Load your transistor operating point data and start exploring!

Note: The LUT generation phase is not included in this repository for security reasons. Users should generate their own LUT data using appropriate simulation tools before using this visualization application.