waveformtools.transforms
Methods to transform the waveform
Functions
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Spin-weighted spherical harmonics data defined as a function of zeta and phi, for qlm data decomposition. |
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Spin-weighted spherical harmonics data defined as a function of zeta and phi, for qlm data decomposition. |
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Spin-weighted spherical harmonics data defined as a function of zeta and phi, for qlm data decomposition. |
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Find the FFT of the samples in time-space, and return with the frequencies. |
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Find the inverse FFT of the samples in frequency-space, and return with the time axis. |
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Make a numppy fft consistent with the chosen conventions. |
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Make an actual conventional fft consistent with numpy's conventions. |
- waveformtools.transforms.Yslm(spin_weight, ell, emm, theta, phi)[source]
Spin-weighted spherical harmonics data defined as a function of zeta and phi, for qlm data decomposition.
- Returns:
- Yslmfloat
The value of Yslm at :math:`theta, phi’.
- waveformtools.transforms.Yslm_pres(spin_weight, ell, emm, theta, phi, pres=16)[source]
Spin-weighted spherical harmonics data defined as a function of zeta and phi, for qlm data decomposition.
- waveformtools.transforms.Yslm_vec(spin_weight, ell, emm, theta_grid, phi_grid)[source]
Spin-weighted spherical harmonics data defined as a function of zeta and phi, for qlm data decomposition.
- Returns:
- Yslmfloat
The value of Yslm at :math:`theta, phi’.
- waveformtools.transforms.compute_fft(udata_x, delta_x)[source]
Find the FFT of the samples in time-space, and return with the frequencies.
- Parameters:
- udata_x: 1d array
The samples in time-space.
- delta_x: float
The stepping delta_x
- Returns:
- freqs: 1d array
The frequency axis, shifted approriately.
- utilde: 1d array
The samples in frequency space, with conventions applied.
- waveformtools.transforms.compute_ifft(utilde, delta_f)[source]
Find the inverse FFT of the samples in frequency-space, and return with the time axis.
- Parameters:
- utilde1d array
The samples in frequency-space.
- delta_f: float
The frequency stepping
- Returns:
- time_axis: 1d array
The time axis.
- udata_time: 1d array
The samples in time domain.
- waveformtools.transforms.set_fft_conven(utilde_orig)[source]
- Make a numppy fft consistent with the chosen conventions.
This takes care of the zero mode factor and array position. Also, it shifts the negative frequencies using numpy’s fftshift.
- Parameters:
- utilde_orig: 1d array
The result of a numpy fft.
- Returns:
- utilde_conven: 1d array
The fft with set conventions.