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Python wrapper for the CircleCI API

Project description

spacekit

PyPi Machine Learning Utility Package for Astrophysical Data Science

spacekit
└── spacekit_pkg
    └── __init__.py
    └── analyzer.py
    └── builder.py
    └── computer.py
    └── radio.py
    └── transformer.py
└── setup.py
└── tests
└── LICENSE
└── README.md
  • Radio: downloading data from MAST s3 bucket on AWS

    • mast_aws: downlaods fits files for list of kepler/TESS targets
  • Analyzer: flux-timeseries signal analysis

    • atomic_vector_plotter: Plots scatter and line plots of time series signal values.
    • make_specgram: generate and save spectographs of flux signal frequencies
    • planet_hunter: calculate period, plot folded lightcurve from .fits files
  • Transformer: tools for converting and preprocessing signals as numpy arrays

    • hypersonic_pliers:
    • thermo_fusion_chisel:
    • babel_fish_dispenser: adds a 1D uniform noise filter using timesteps
    • fast_fourier: fast fourier transform utility function
  • Builder: building and fitting convolutional neural networks

    • build_cnn: builds keras 1D CNN architecture
    • fit_cnn: trains keras CNN
  • Computer: gets model predictions and evaluates metrics

    • get_preds
    • fnfp
    • keras_history
    • roc_plots
    • compute

spacekit.Radio()

downloading data from MAST s3 bucket on AWS

mast_aws()

from spacekit import radio
target_list = ['K2-66','K2-100','K2-27']
R = Radio()
R.mast_aws(target_list)

spacekit.Analyzer()

flux-timeseries signal analysis

atomic_vector_plotter

Plots scatter and line plots of time series signal values.

from spacekit import analyzer
signal = array([  93.85,   83.81,   20.1 ,  -26.98,  -39.56, -124.71, -135.18,
        -96.27,  -79.89, -160.17, -207.47, -154.88, -173.71, -146.56,
       -120.26, -102.85,  -98.71,  -48.42,  -86.57,   -0.84,  -25.85,
        -67.39,  -36.55,  -87.01,  -97.72, -131.59, -134.8 , -186.97,
       -244.32, -225.76, -229.6 , -253.48, -145.74, -145.74,   30.47,
       -173.39, -187.56, -192.88, -182.76, -195.99, -317.51, -167.69,
        -56.86,    7.56,   37.4 ,  -81.13,  -20.1 ,  -30.34, -320.48,
       -320.48, -287.72, -351.25,  -70.07, -194.34, -106.47,  -14.8 ,
         63.13,  130.03,   76.43,  131.9 , -193.16, -193.16,  -89.26,
        -17.56,  -17.31,  125.62,   68.87,  100.01,   -9.6 ,  -25.39,
        -16.51,  -78.07, -102.15, -102.15,   25.13,   48.57,   92.54,
         39.32,   61.42,    5.08,  -39.54])
A = Analyzer()
A.atomic_vector_plotter(signal)

make_specgram

generate and save spectographs of flux signal frequencies

A = Analyzer()
spec = A.make_specgram(signal)

planet_hunter

calculates period and plots folded light curve from single or multiple .fits files

A = Analyzer()
data = './DATA/mast/'
files = os.listdir(data)
f9 =files[9]
A.planet_hunter(f9, fmt='kepler.fits')

spacekit.Transformer()

tools for converting and preprocessing signals as numpy arrays

hypersonic_pliers

thermo_fusion_chisel

babel_fish_dispenser

fast_fourier

spacekit.Builder()

building and fitting convolutional neural networks

build_cnn

fit_cnn

spacekit.Computer()

gets model predictions and evaluates metrics

get_preds

fnfp

keras_history

fusion_matrix

roc_plots

compute

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