Metadata-Version: 2.1
Name: km3services
Version: 0.3.0
Summary: Microservices for KM3NeT
Home-page: https://git.km3net.de/km3py/km3services
Author: Tamas Gal
Author-email: tgal@km3net.de
License: UNKNOWN
Description: Microservices for KM3NeT
        ========================
        
        .. image:: https://git.km3net.de/km3py/km3services/badges/master/pipeline.svg
            :target: https://git.km3net.de/km3py/km3services/pipelines
        
        .. image:: https://git.km3net.de/km3py/km3services/badges/master/coverage.svg
            :target: https://tgal.pages.km3net.de/km3services/coverage
        
        .. image:: https://examples.pages.km3net.de/km3badges/docs-latest-brightgreen.svg
            :target: https://tgal.pages.km3net.de/km3services
        
        This Python package provides access to KM3NeT microservices. It's in an early development
        stage and the API will likely change any until v1.0.0 is released.
        
        Installation
        ------------
        
        As usual, install with ``pip``::
        
          pip install km3services
        
        Available Microservices
        -----------------------
        
        OscProb
        ~~~~~~~
        
        The ``km3services.oscprob`` module wraps the ``OscProb`` package to calculate neutrino
        oscillation probabilities. Here is an example how to calculate the transition
        probabilities from muon to electron neutrino (the API will be polished soon):
        
        .. code-block:: python3
        
          import km3services
          import numpy as np
        
          n = 1000
          energies = np.random.randint(1, 50, n)  # generate `n` energies between 1-50 GeV
          cos_zeniths = -np.random.rand(n) / 2
          flav_in = 0   # electron neutrino
          flav_out = 1  # muon neutrino
        
          probabilities = km3services.oscprob.oscillationprobabilities(flav_in, flav_out, energies, cos_zeniths)
          print(probabilities)
        
        The returned ``probabilities`` is a numpy array::
        
         [4.20254330e-03 7.46278836e-05 6.18139696e-04 4.03814960e-03
         3.38002558e-03 3.33962606e-04 4.53159234e-02 5.03111960e-02
         ...
         2.23391190e-03 2.07540790e-03 6.71385177e-03 3.03348121e-02
         1.86633322e-02 4.81416626e-03 4.55362912e-05 3.59935810e-03]
        
Platform: any
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Programming Language :: Python
Requires-Python: >=3.6
Provides-Extra: dev
Provides-Extra: oscprob-server
