CurveFitter | Regression analysis algorithms from ImageJ1 for easy use | Testing library

by BinRoot Java Version: Current License: Unlicense

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | CurveFitter Summary

CurveFitter is a Java library typically used in Testing applications. CurveFitter has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However CurveFitter build file is not available. You can download it from GitHub.

A fork of [ImageJ CurveFitter] without any java.awt or GUI dependencies.

Support

Quality

Security

License

Reuse

Support

CurveFitter has a low active ecosystem.

It has 13 star(s) with 3 fork(s). There are 3 watchers for this library.

It had no major release in the last 6 months.

CurveFitter has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of CurveFitter is current.

Quality

CurveFitter has 0 bugs and 0 code smells.

Security

CurveFitter has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

CurveFitter code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

CurveFitter is licensed under the Unlicense License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

CurveFitter releases are not available. You will need to build from source code and install.

CurveFitter has no build file. You will be need to create the build yourself to build the component from source.

Installation instructions are not available. Examples and code snippets are available.

It has 1519 lines of code, 87 functions and 7 files.

It has high code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

kandi has reviewed CurveFitter and discovered the below as its top functions. This is intended to give you an instant insight into CurveFitter implemented functionality, and help decide if they suit your requirements.

Calculates the squared function for the given parameters
Determines the sum of squared residuals
Converts the full set of parameters to minimizer parameters
Convert the parameters to the full set of parameters
Get a string representation of the result
Returns the standard deviation of the points
Converts a number to a rounded formatted string
Returns the value of the fitted fit function
Set the maximum number of times to make sense
Sets the maximum number of minimizations to be performed
Get the maximum number of times to run
Get the maximum number of minutes to perform
Set the status of the optimization
Set the status and escape
Displays a simple complex vector
Shows a single vertex
Returns the value of the minimum function
Return the value of the vertex
Returns the best fit goodness
Get the number of parameters for the current fit formula
Get the maximum number of iterations allowed
Returns the code code of a fit with given name
Set the maximum error

Get all kandi verified functions for this library.

CurveFitter Key Features

No Key Features are available at this moment for CurveFitter.

CurveFitter Examples and Code Snippets

No Code Snippets are available at this moment for CurveFitter.

Community Discussions

Trending Discussions on CurveFitter

Python scipy.optimize.leastsq to Java org.apache.commons.math3.fitting.leastsquares

QUESTION

Python scipy.optimize.leastsq to Java org.apache.commons.math3.fitting.leastsquares

Asked 2017-Dec-15 at 04:37

I try to mimic this algorithm, developed in Python, that calculates geolocation based on seen Wifi stations positions, itself based on this idea.

This algorithm uses at first a Numpy function in order to calculate a basic weighted average of observed latitudes and longitudes. To minimize the impact of possible Wifi positions errors, it’s also use the “scipy.optimize.leastsq” method in order to calculate in an statistical way and if possible, a more precise position.

I want to implement the same behavior on the Java Android platform.

For all other calculations I successfully rely on org.apache.commons.math3. So for the least-squares problem I logically try to rely on https://commons.apache.org/proper/commons-math/userguide/leastsquares.html.

My problem, if I well understood, is that Scipy manage for me the complexity of Jacobian function definition and my poor mathematics skills doesn't allow me to define correctly the model of a LeastSquaresProblem. I tried some experimentations based on this example, that seems closed to what I need, but the results aren't good as I don't know how to deal with the "jacobian" parts.

As someone do for this post, could someone do the same thing for me and try to explain it in a simple way?

More details on how Python part is working :

The “scipy.optimize.leastsq” statement used is:

...

ANSWER

Answered 2017-Dec-15 at 04:37

The code is not easy to port because SciPy provides a more generic Least-squares minimization interface while Apache Commons Math provides curve fitting. Still many optimization problems can be restated as curve fitting. In the Python code you minimize

Source https://stackoverflow.com/questions/47819693

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install CurveFitter

You can download it from GitHub.
You can use CurveFitter like any standard Java library. Please include the the jar files in your classpath. You can also use any IDE and you can run and debug the CurveFitter component as you would do with any other Java program. Best practice is to use a build tool that supports dependency management such as Maven or Gradle. For Maven installation, please refer maven.apache.org. For Gradle installation, please refer gradle.org .

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

Find more information at: