deepextractor.generation.generate_timeseries
============================================

.. py:module:: deepextractor.generation.generate_timeseries

.. autoapi-nested-parse::

   Generate synthetic time-domain training data.

   Usage::

       deepextractor-generate --output-dir data/ --num-train 250000 --bilby-noise







Module Contents
---------------

.. py:data:: SAMPLE_RATE
   :value: 4096


.. py:data:: T
   :value: 2.0


.. py:data:: T_INJ
   :value: 1.0


.. py:data:: LENGTH
   :value: 0


.. py:data:: MINIMUM_FREQUENCY
   :value: 20.0


.. py:data:: SNR_SCALING_FACTOR_BILBY
   :value: 31.970149253731343


.. py:data:: SIGNAL_TYPES
   :value: ['chirp', 'sine', 'sine_gaussian', 'gaussian_pulse', 'ringdown']


.. py:data:: SIGNAL_FUNCTION_MAP

.. py:function:: generate_gaussian_noise(mean, std_dev, num_samples, sample_shape, bilby_noise=False, sample_rate=SAMPLE_RATE, duration=T, minimum_frequency=MINIMUM_FREQUENCY, detector='L1')

   Generate Gaussian noise samples (pycbc or bilby).


.. py:function:: generate_synthetic_data(gaussian_noise_samples, bilby_noise=False, phase='train', t_min=0.125, t_max=2.0, snr_min=SNR_MIN, snr_max=SNR_MAX)

   Generate synthetic noisy glitch and background data arrays.


.. py:function:: main()