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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
Getting Help
Frequently Asked Questions
How can I fit multi-dimensional data?
How can I fit complex data?
Can I constrain values to have integer values?
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
Composite Models : adding (or multiplying) 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
User-defined Models
ExpressionModel
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
]