iminuit | Jupyter-friendly Python interface for C++ MINUIT2 | Machine Learning library

by scikit-hep Python Version: 2.25.2 License: Non-SPDX

X-Ray Key Features Code Snippets(3)Community Discussions(3)Vulnerabilities Install Support

kandi X-RAY | iminuit Summary

iminuit is a Python library typically used in Artificial Intelligence, Machine Learning, Jupyter applications. iminuit has no bugs, it has no vulnerabilities, it has build file available and it has low support. However iminuit has a Non-SPDX License. You can install using 'pip install iminuit' or download it from GitHub, PyPI.

Jupyter-friendly Python interface for C++ MINUIT2

Support

Quality

Security

License

Reuse

Support

iminuit has a low active ecosystem.

It has 236 star(s) with 67 fork(s). There are 15 watchers for this library.

There were 3 major release(s) in the last 6 months.

There are 10 open issues and 286 have been closed. On average issues are closed in 34 days. There are 3 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of iminuit is 2.25.2

Quality

iminuit has no bugs reported.

Security

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

License

iminuit has a Non-SPDX License.

Non-SPDX licenses can be open source with a non SPDX compliant license, or non open source licenses, and you need to review them closely before use.

Reuse

iminuit releases are available to install and integrate.

Deployable package is available in PyPI.

Build file is available. You can build the component from source.

Top functions reviewed by kandi - BETA

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

Show a plot
Return a MnMachinePrecision instance
Estimate EDM goal
Generate a Minuit
Draw the minimization matrix
Return the error probability for a given class cl
Calculate the mn user profile
Calculate the MnContour
Convert to table
Visualize the model
Draw the mn profile
Expand a callable
Compute the Poisson density of a template
Private method to set parameter value
Compute the chi - squared chi squared
Calculate the poisson distribution
Wrapper function
Set the loss function
Evaluate the function
Calculate the chi - squared chi coefficient for a template
R Compute the Jacobian of a function
Create a Minuit Minuit
Draw a contour plot
Return a table as a table
Create a callable with the given replacement
Visualize the components

Get all kandi verified functions for this library.

iminuit Key Features

No Key Features are available at this moment for iminuit.

iminuit Examples and Code Snippets

python setup.py install does not work with latest setuptools: no scripts in '<*>.egg-info'

Python

Lines of Code : 3

License : Strong Copyleft (CC BY-SA 4.0)

Copy

cd .. # or cd anywhere outside your build folder
picca_deltas.py

Constraints on fitting parameters in iminuit?

Python

Lines of Code : 10

License : Strong Copyleft (CC BY-SA 4.0)

Copy

def chi( paras ):
    mpi = paras[ 0 : 32 ]
    s = paras[ 32 ]
    a = np.log( np.sum( np.array( mpi )**2 ) )
    cf = a - np.exp( -s )
    chif = 0
    for i in range( 32 ):
        chif += ( ( fpi - f( mpi, cf ) ) / error )**2
    retur

Iminuit fitting algorithm?

Python

Lines of Code : 12

License : Strong Copyleft (CC BY-SA 4.0)

Copy

void MnStrategy::SetMediumStrategy() {
   // set minimum strategy (1) the default
   fStrategy = 1;
   SetGradientNCycles(3);
   SetGradientStepTolerance(0.3);
   SetGradientTolerance(0.05);
   SetHessianNCycles(5);
   SetHessianStepTolera

Community Discussions

Trending Discussions on iminuit

Constrain on parameters for Negative Log Likelihood Minimization

Adding constraints to iminuit fitter

Iminuit fitting algorithm?

QUESTION

Constrain on parameters for Negative Log Likelihood Minimization

Asked 2020-Jul-11 at 22:44

I am trying to fit a 5 parameter (a, b, c, d, e) model, where one of the parameters is constrained by another, let's say,

0< d < 1

e < |d|

I am currently using zfit which as far as I know, uses iMinuit

I have only created the zfit.Parameters and put the limits such that the ranges accessible to them are valid, again, let's say:

d = zfit.Parameter('d', value=0.5, lower_limit=0.3, upper_limit=1.0, step_size=0.01)

e = zfit.Parameter('e', value=0.1, lower_limit=0.0, upper_limit=0.3, step_size=0.01)

It has been working well so far, but I think it is not the right way to do it.

So my question is, what is the correct way to deal with this kind of constraint?

Cheers

...

ANSWER

Answered 2020-Jul-11 at 22:44

I would use this limits with caution, as they block the variables, ideally, they should be far off the final value.

There are two ways to achieve what you want:

either impose a constraint "mathematically" as a logical consequence, so define one parameter from another using a composed parameter (which is a function of other parameters). If possible, this should be the preferred way.
Another option is to impose this restrictions in the likelihood with an additional term. This, however, can have repercussions as you modify the likelihood. The minimizer will find a minimum, but this is maybe not the minimum you have looked for. What you can use are SimpleConstraints and add a penalty term to the likelihood if any of the above is violated (e.g. tf.cast(tf.greater(d, 1), tf.float64) * 100.). Maybe make also sure that minuit is run with use_minuit_grad.

Source https://stackoverflow.com/questions/62855017

QUESTION

Adding constraints to iminuit fitter

Asked 2017-May-12 at 02:54

I am trying to add a constraint to a very complicated minimization problem I have but I am not sure how to implement it, even after reading the docs.

I have a simple example that if answered will help me with my original problem. Here is the code:

...

ANSWER

Answered 2017-May-12 at 02:54

Answer to my own question is don't bother using minuit. Use scipy.optimize with method SLSQP. It has equality and inequality constraint methods built in.

Source https://stackoverflow.com/questions/43462911

QUESTION

Iminuit fitting algorithm?

Asked 2017-Jan-11 at 17:44

Does anyone knows what algorithm is used for the python iminuit fitting package, when no attribute is specified?

...

ANSWER

Answered 2017-Jan-11 at 17:44

The documentation says it uses the Quasi Newton Method and DFP formula.

You can see in the source code what the default strategy looks like:

Source https://stackoverflow.com/questions/41597221

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

Vulnerabilities

No vulnerabilities reported

Install iminuit

You can install using 'pip install iminuit' or download it from GitHub, PyPI.
You can use iminuit like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

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: