Visualize Transforms

This is a project to visualize the transforms of discrete signals and operations between two or multiple discrete signals (mainly DFT and convolution)

Installation

1. Install fftw3 in /usr/include
2. Inside /src/signals/ folder run gcc signal_computer.c -lm -lfftw3 -o signal_computer_exec
3. Activate a nodejs environment
4. Run pnpm install
5. Run pnpm run dev

Code Improvements

• Use structs to encapsulate parameters

• Make global argv, argc as such:

  char **gargv;
  int gargc;

Snippet from here

Another way of doing a similar thing here

IDEAS

• IndexedDB for function domain instead of csv?
• Let the user adjust the necessary parameters and you can save those function parameters and combine them (sum, product, convolution) with other saved functions
  • Input is done with buttons:
    • A signal button, you can choose between the square, triangle, sine, etc. icons
    • Amplitude, frequency, range wheels
  • Chain functions to simulate operations (add, subtract, multiply, divide, convolve, correlate, circular convolution???, etc.)
  • Discrete sums and products (look for periodization in IPAV)
  • Also delta of kronecker
• Real, Imaginary & Complex graph
• Add the sum of cos & sin
• Add complex exponential (cos+isin)
• Load your signal with a formatted text/JSON/whatever file
• Use IPC message passing or memory sharing instead of using node to invoke execution
• Add auto set button
• Fix rounding errors (for freq)
• Show only a narrow window of frequencies (different for cos, sin, exp, etc.)
• Add debug mode (with #ifndef)
• Allow only parametrized input (you can only input the parameters to the function that I permit, with limited degrees of freedom)
• Lead to the discovery of the ft by convolution (like in Mark Newman's video)
• Build an FFT and convolution algorithm
• Other transforms (Cosine, sine, sinc transforms...)
• Load graphs by chunks (first 100 samples, etc.) or lazy load (load average of every 10, 5, 2 samples etc.)
• Try using another plotting library (canvas, function plot, etc.)

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