⚡ DSP Lab Automation Engine

A clean, reproducible workspace designed to automate the process of executing Digital Signal Processing (DSP) lab sheets, capturing graphical results, and compiling a simple, compact 1st-year BTech student style LaTeX report with student credentials.

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🛠️ System Architecture & Workflow

The workspace is structured to parse lab requirements, run simulations, and compile reports with zero manual formatting residue:

                      ┌────────────────────────┐
                      │  input/labsheet.pdf    │ (Raw Input)
                      └───────────┬────────────┘
                                  ▼ [markitdown]
                      ┌────────────────────────┐
                      │  input/labsheet.md     │ (Converted)
                      └───────────┬────────────┘
                                  ▼
                      ┌────────────────────────┐
                      │    Octave Scripts      │ ◄─── (Written inside src/)
                      └───────────┬────────────┘
                                  ▼
            ┌─────────────────────┴─────────────────────┐
            ▼                                           ▼
    ┌───────────────┐                           ┌───────────────┐
    │  src/*.png    │ (Plots)                   │  src/*.txt    │ (Console Logs)
    └───────┬───────┘                           └───────┬───────┘
            │                                           │
            └─────────────────────┬─────────────────────┘
                                  ▼
                      ┌────────────────────────┐
                      │  output/report.tex     │ ◄─── (LaTeX)
                      └───────────┬────────────┘
                                  ▼
                      ┌────────────────────────┐
                      │  output/report.pdf     │ ◄─── (Compiled PDF)
                      └────────────────────────┘

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✨ Features

• Beginner-Style Code Generation: Octave scripts are written with simple, clear variables (e.g., x1, yval) without underscores, matching typical student coding styles.
• One-Click Compilation: The generate_report.py script executes all laboratory tasks sequentially, captures console logs, formats plots side-by-side, and compiles the final LaTeX report.
• LaTeX Report Template: A simple, compact report.tex template designed to look like a student's basic work:
  • Uses narrow margins (geometry) to keep the page count minimal.
  • Stamps name and roll number in a simple block at the top of the report.
  • Positions plot images side-by-side using minipage elements with minimal labels/captions to save maximum space.
  • Uses listings to import and highlight .m script files directly from the disk.
  • Uses graphicx to embed plots.
• Clean Repository State: A robust .gitignore isolates build logs, temporary auxiliary files, and plot images so that you can reuse the directory for subsequent labsheets without cluttering Git history.

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📂 Project Structure

.
├── .env                # User config (STUDENT_NAME/ROLL/MATLAB_DIR/INPUT_DIR/OUTPUT_DIR)
├── .env.example        # Environment template file
├── .gitignore          # Keeps your Git repository clean
├── README.md           # This document
├── workflow.md         # Implementation steps & guidelines
├── SKILL.md            # LLM assistant instructions and rules
├── generate_report.py  # Dynamically executes MATLAB scripts and generates LaTeX report
├── input/              # Raw labsheet inputs and converted markdown files
│   └── .gitkeep        # Tracks directory in git
├── output/             # Output LaTeX reports and compiled PDFs
│   └── .gitkeep        # Tracks directory in git
└── src/                # Folder containing all MATLAB/Octave scripts
    ├── example.m       # Example task script
    └── ...             # Other lab tasks

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🚀 How to Run

Prerequisites

Make sure GNU Octave, Python 3, pdfTeX, and Microsoft MarkItDown are installed:

sudo apt install octave python3 texlive-latex-extra
pip install markitdown

Execution

1. Place your raw labsheet file (e.g. labsheet.pdf) inside the input/ folder.
2. Convert it to markdown using markitdown:

   markitdown input/labsheet.pdf -o input/labsheet.md

3. Read the converted input/labsheet.md and write the corresponding MATLAB/Octave .m scripts in the src/ folder.
4. Run the automation generator script:

   python3 generate_report.py

   Note: If you have already executed the scripts and manually placed screenshots (e.g. 1.1.png for LS1_01.m and an optional inference.txt), run with the --skip-run (or -s) flag to compile the report directly without running Octave:

   python3 generate_report.py --skip-run

This will run/skip scripts in src/, compile console logs, associate manual/generated screenshots, attach inferences from inference.txt, create output/report.tex, and compile the final PDF.

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🔄 Reusing for Next Labsheets

To process a new lab sheet:

1. Place the new labsheet in input/ and convert it using markitdown.
2. Clear old .m files in src/ and paste/write the new ones.
3. Run python3 generate_report.py.
4. Your new output/report.pdf will be compiled immediately with your name and roll number.