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Non-Linear Least-Squares Minimization and Curve-Fitting for Python
Introduction
Parameters
Models
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Contents
ΒΆ
Getting started with Non-Linear Least-Squares Fitting
Downloading and Installation
Prerequisites
Downloads
Installation
Development Version
Testing
Acknowledgements
License
Parameter
and
Parameters
The
Parameter
class
The
Parameters
class
Simple Example
Performing Fits, Analyzing Outputs
The
minimize()
function
Writing a Fitting Function
Choosing Different Fitting Methods
Goodness-of-Fit and estimated uncertainty and correlations
Using the
Minimizer
class
Getting and Printing Fit Reports
Modeling Data and Curve Fitting
Example: Fit data to Gaussian profile
The
Model
class
Model
class Methods
Model
class Attributes
Determining parameter names and independent variables for a function
Explicitly specifying
independent_vars
Functions with keyword arguments
Defining a
prefix
for the Parameters
Initializing model parameters
Using parameter hints
The
ModelFit
class
ModelFit
methods
ModelFit
attributes
Creating composite models
Model names for composite models
Built-in Fitting Models in the
models
module
Peak-like models
GaussianModel
LorentzianModel
VoigtModel
PseudoVoigtModel
Pearson7Model
StudentsTModel
BreitWignerModel
LognormalModel
DampedOcsillatorModel
ExponentialGaussianModel
SkewedGaussianModel
DonaichModel
Linear and Polynomial Models
ConstantModel
LinearModel
QuadraticModel
ParabolicModel
PolynomialModel
Step-like models
StepModel
RectangleModel
Exponential and Power law models
ExponentialModel
PowerLawModel
Example 1: Fit Peaked data to Gaussian, Lorentzian, and Voigt profiles
Example 2: Fit data to a Composite Model with pre-defined models
Example 3: Fitting Multiple Peaks – and using Prefixes
Calculation of confidence intervals
Method used for calculating confidence intervals
A basic example
An advanced example
Documentation of methods
Bounds Implementation
Using Mathematical Constraints
Overview
Supported Operators, Functions, and Constants
Using Inequality Constraints
Advanced usage of Expressions in lmfit
Navigation
index
[
intro
|
parameters
|
minimize
|
model
|
builtin models
|
confidence intervals
|
bounds
|
constraints
]