1. Getting Started¶

This chapter covers installation, your first curve fit, and how to interpret results.

1.4. Chapter Overview¶

Installation (5 min): Install NLSQ and verify your setup, including optional GPU support.
First Fit (10 min): Fit an exponential decay model to data using the simplest possible approach.
Understanding Results (10 min): Learn what popt and pcov mean and how to calculate parameter uncertainties.

1.5. Quick Example¶

After completing this chapter, you’ll be able to:

from nlsq import fit
import jax.numpy as jnp


def model(x, a, b):
    return a * jnp.exp(-b * x)


# Fit the data
popt, pcov = fit(model, xdata, ydata, p0=[2.0, 0.5])

# Extract results
a_fit, b_fit = popt
a_err, b_err = np.sqrt(np.diag(pcov))

print(f"a = {a_fit:.3f} +/- {a_err:.3f}")
print(f"b = {b_fit:.3f} +/- {b_err:.3f}")