ifitpy 0.0.8

Simple data fitting package

Pyfit

This an ongoing project!

pip install ifitpy

Fitter Package Instructions

1. Creating a Fitter Instance

f = Fitter("linear")  # Available types: "linear", "expo", "gaussian", "gaussian2d", "poly"

This package provides fitting capabilities for given x, y data, encapsulating both iminuit and curve_fit.

Functions are categorized as:

• Simple: "linear", "expo"
• Complex: "gaussian", "gaussian2d", "poly"

2. Performing a Fit

Simple Functions (linear, expo)

f.fit(x, y)  # Estimates initial parameters automatically  
f.fit(x, y, p0)  # Uses provided initial parameters (p0)

Complex Functions (gaussian, gaussian2d, poly)

f.fit(x, y, n)  # Fits using `n` components (e.g., a sum of `n` Gaussians or an `n`-degree polynomial)  
f.fit(x, y, p0)  # Uses provided initial parameters  
f.fit(x, y, n, p0)  # Uses both `n` components and provided initialization parameters  

Note: For fit(x, y, n, p0), the length of p0 must be n * parameters_to_fit.

3. Binned Fitting

The fitBinned function allows fitting a profile histogram instead of raw data, which is often faster and accounts for statistical fluctuations.

f.fitBinned(x, y, bins=50)

4. Extracting Fit Results

f.fit([0, 10], [0, -10])
p = f.getParams()

print(p)         # Prints a summary of available variables  
print(p.vars)    # List of fit results  
print(p.m)       # Slope for the "linear" type  
print(p.b)       # Intercept for the "linear" type  

5. Evaluating the Fitted Function

print(f.evaluate([20]))  # Evaluates the function at x = 20 (useful for plotting)