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    Linear Data Fitting

    This example demonstrates a simple usage of fit() to fit 3 data points to the line y=mx+b. This is all you need to get started!

    dataset=(1,1),(2,1),(3,2)

    Try plotting the data points and program output in a graphing calculator! Does it fit?

    Follow these steps to create a new project workspace and install the datafit dependency to run this example.

    # Create and open project folder
    mkdir Linear_Data_Fitting_demo
    cd Linear_Data_Fitting_demo
    # Initialize project and install dependencies
    npm init -y
    npm i datafit@1.4.8
    # Create and open source file
    touch "Linear Data Fitting.mjs"
    open "Linear Data Fitting.mjs"

    Copy and paste this source code into Linear Data Fitting.mjs.

    import { fit } from 'datafit';

    // Define our model function: y=mx+b
    function f(x, m, b) {
    return m * x + b;
    }

    // Define our dataset
    const data = [
    { x: 1, y: -1 },
    { x: 2, y: 1 },
    { x: 3, y: 2 },
    ];

    // Compute the best fit parameters to
    // get `m` and `b`, and print result.
    const summary = fit(f, data);
    const m_fit = summary.params[0];
    const b_fit = summary.params[1];
    console.log('The best-fit line is y = ' + m_fit.toFixed(2) + 'x + ' + b_fit.toFixed(2));

    In Linear_Data_Fitting_demo/, execute Linear Data Fitting.mjs with NodeJS to generate an output.

    node "Linear Data Fitting.mjs"
    

    You should expect to see an output similar to the one below.

    The best-fit line is y = 1.49x + -2.32
    
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