GModelFit is a general purpose, data-driven model fitting framework for Julia.
Warning
The code in version 0.3.0 underwent a signficant refactoring, and a few details may break your code. Please have a look at ChangeLog.md !!
Install with:
]add GModelFitusing GModelFit
# Prepare vectors with domain points, empirical measures and uncertainties
x = [0.1, 1.1, 2.1, 3.1, 4.1]
meas = [6.29, 7.27, 10.41, 18.67, 25.3]
unc = [1.1, 1.1, 1.1, 1.2, 1.2]
dom = Domain(x)
data = Measures(dom, meas, unc)
# Create a model using an explicit mathematical expression, and provide the
# initial guess values:
model = Model(@fd (x, a2=1, a1=1, a0=5) -> (a2 .* x.^2 .+ a1 .* x .+ a0))
# Fit model to the data
bestfit, stats = fit(model, data)The output is as follows:
(Components:
╭───────────┬───────┬───────┬─────────────┬───────────┬───────────┬───────────┬─────────╮
│ Component │ Type │ #Free │ Eval. count │ Min │ Max │ Mean │ NaN/Inf │
├───────────┼───────┼───────┼─────────────┼───────────┼───────────┼───────────┼─────────┤
│ main │ FComp │ 3 │ 76 │ 6.088 │ 25.84 │ 13.56 │ 0 │
╰───────────┴───────┴───────┴─────────────┴───────────┴───────────┴───────────┴─────────╯
Parameters:
╭───────────┬───────┬────────┬──────────┬───────────┬───────────┬────────┬───────╮
│ Component │ Type │ Param. │ Range │ Value │ Uncert. │ Actual │ Patch │
├───────────┼───────┼────────┼──────────┼───────────┼───────────┼────────┼───────┤
│ main │ FComp │ a2 │ -Inf:Inf │ 1.201 │ 0.3051 │ │ │
│ │ │ a1 │ -Inf:Inf │ -0.106 │ 1.317 │ │ │
│ │ │ a0 │ -Inf:Inf │ 6.087 │ 1.142 │ │ │
╰───────────┴───────┴────────┴──────────┴───────────┴───────────┴────────┴───────╯
, Fit results: #data: 5, #free pars: 3, red. fit stat.: 1.0129, Status: OK
)