4. Data Handling

This chapter covers how to prepare and input data for curve fitting.

• 4.1. Basic Data
• 4.2. Uncertainties (Sigma)
• 4.3. Parameter Bounds
• 4.4. Large Datasets

4.5. Chapter Overview

Basic Data (5 min)

Loading and preparing x, y data arrays.

Uncertainties (10 min)

Using measurement errors for weighted fitting.

Bounds (5 min)

Constraining parameters to valid ranges.

Large Datasets (10 min)

Handling datasets with millions of points.

4.6. Quick Reference

from nlsq import fit
import numpy as np

# Basic fit
popt, pcov = fit(model, x, y, p0=[...])

# With uncertainties
popt, pcov = fit(model, x, y, p0=[...], sigma=errors)

# With bounds
popt, pcov = fit(model, x, y, p0=[...], bounds=([lower], [upper]))

# Large dataset (automatic handling)
popt, pcov = fit(model, x_large, y_large, p0=[...])
# NLSQ auto-detects size and uses appropriate strategy