:py:mod:`gwsnr.numba` ===================== .. py:module:: gwsnr.numba Submodules ---------- .. toctree:: :titlesonly: :maxdepth: 1 njit_functions/index.rst njit_interpolators/index.rst Package Contents ---------------- Functions ~~~~~~~~~ .. autoapisummary:: gwsnr.numba.findchirp_chirptime gwsnr.numba.antenna_response_plus gwsnr.numba.antenna_response_cross gwsnr.numba.antenna_response_array gwsnr.numba.noise_weighted_inner_product gwsnr.numba.effective_distance gwsnr.numba.effective_distance_array gwsnr.numba.linear_interpolator gwsnr.numba.get_interpolated_snr_aligned_spins_numba gwsnr.numba.get_interpolated_snr_no_spins_numba .. py:function:: findchirp_chirptime(m1, m2, fmin) Time taken from f_min to f_lso (last stable orbit). 3.5PN in fourier phase considered. :Parameters: **m1** : `float` Mass of the first body in solar masses. **m2** : `float` Mass of the second body in solar masses. **fmin** : `float` Lower frequency cutoff. :Returns: **chirp_time** : float Time taken from f_min to f_lso (last stable orbit frequency). .. !! processed by numpydoc !! .. py:function:: antenna_response_plus(ra, dec, time, psi, detector_tensor) Function to calculate the antenna response :Parameters: **ra** : `float` Right ascension of the source in radians. **dec** : float Declination of the source in radians. **time** : `float` GPS time of the source. **psi** : `float` Polarization angle of the source. **detector_tensor** : array-like Detector tensor for the detector (3x3 matrix) **mode** : `str` Mode of the polarization. Default is 'plus'. :Returns: antenna_response: `float` Antenna response of the detector. .. !! processed by numpydoc !! .. py:function:: antenna_response_cross(ra, dec, time, psi, detector_tensor) Function to calculate the antenna response :Parameters: **ra** : `float` Right ascension of the source in radians. **dec** : float Declination of the source in radians. **time** : `float` GPS time of the source. **psi** : `float` Polarization angle of the source. **detector_tensor** : array-like Detector tensor for the detector (3x3 matrix) **mode** : `str` Mode of the polarization. Default is 'plus'. :Returns: antenna_response: `float` Antenna response of the detector. .. !! processed by numpydoc !! .. py:function:: antenna_response_array(ra, dec, time, psi, detector_tensor) Function to calculate the antenna response in array form. :Parameters: **ra** : `numpy.ndarray` Right ascension of the source in radians. **dec** : `numpy.ndarray` Declination of the source in radians. **time** : `numpy.ndarray` GPS time of the source. **psi** : `numpy.ndarray` Polarization angle of the source. **detector_tensor** : array-like Detector tensor for the multiple detectors (nx3x3 matrix), where n is the number of detectors. :Returns: antenna_response: `numpy.ndarray` Antenna response of the detector. Shape is (n, len(ra)). .. !! processed by numpydoc !! .. py:function:: noise_weighted_inner_product(signal1, signal2, psd, duration) Noise weighted inner product of two time series data sets. :Parameters: **signal1: `numpy.ndarray` or `float`** First series data set. **signal2: `numpy.ndarray` or `float`** Second series data set. **psd: `numpy.ndarray` or `float`** Power spectral density of the detector. **duration: `float`** Duration of the data. .. !! processed by numpydoc !! .. py:function:: effective_distance(luminosity_distance, theta_jn, ra, dec, geocent_time, psi, detector_tensor) Function to calculate the effective distance of the source. :Parameters: **luminosity_distance** : `float` Luminosity distance of the source in Mpc. **theta_jn** : `float` Angle between the line of sight and the orbital angular momentum vector. **ra** : `float` Right ascension of the source in radians. **dec** : `float` Declination of the source in radians. **time** : `float` GPS time of the source. **psi** : `float` Polarization angle of the source. **detector_tensor** : array-like Detector tensor for the detector (3x3 matrix). :Returns: effective_distance: `float` Effective distance of the source in Mpc. .. !! processed by numpydoc !! .. py:function:: effective_distance_array(luminosity_distance, theta_jn, ra, dec, geocent_time, psi, detector_tensor) Function to calculate the effective distance of the source in array form. :Parameters: **luminosity_distance** : `numpy.ndarray` Luminosity distance of the source in Mpc. **theta_jn** : `numpy.ndarray` Angle between the line of sight and the orbital angular momentum vector. **ra** : `numpy.ndarray` Right ascension of the source in radians. **dec** : `numpy.ndarray` Declination of the source in radians. **time** : `numpy.ndarray` GPS time of the source. **psi** : `numpy.ndarray` Polarization angle of the source. **detector_tensor** : array-like Detector tensor for the multiple detectors (nx3x3 matrix), where n is the number of detectors. :Returns: effective_distance: `numpy.ndarray` Effective distance of the source in Mpc. Shape is (n, len(ra)). .. !! processed by numpydoc !! .. py:function:: linear_interpolator(xnew_array, y_array, x_array, fill_value=np.inf) Linear interpolator for 1D data. :Parameters: **xnew_array** : `numpy.ndarray` New x values to interpolate. **y_array** : `numpy.ndarray` y values corresponding to the x_array. **x_array** : `numpy.ndarray` Original x values. :Returns: **result** : `numpy.ndarray` Interpolated y values at xnew_array. .. !! processed by numpydoc !! .. py:function:: get_interpolated_snr_aligned_spins_numba(mass_1, mass_2, luminosity_distance, theta_jn, psi, geocent_time, ra, dec, a_1, a_2, detector_tensor, snr_partialscaled, ratio_arr, mtot_arr, a1_arr, a_2_arr, batch_size=100000) .. py:function:: get_interpolated_snr_no_spins_numba(mass_1, mass_2, luminosity_distance, theta_jn, psi, geocent_time, ra, dec, a_1, a_2, detector_tensor, snr_partialscaled, ratio_arr, mtot_arr, a1_arr, a_2_arr, batch_size=100000)