lensit¶
This lensit package contains some convenience functions in its __init__.py for quick startup.
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lensit.get_fidcls(ellmax_sky=6000)[source]¶ Returns lensit fiducial CMB spectra (Planck 2015 cosmology)
Parameters: ellmax_sky – optionally reduces outputs spectra \(\ell_{\rm max}\) Returns: unlensed and lensed CMB spectra (dicts)
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lensit.get_lencmbs_lib(res=14, cache_sims=True, nsims=120, num_threads=1)[source]¶ Default lensed CMB simulation library
Lensing is always performed at resolution of \(0.75\) arcmin
Parameters: - res – lensed CMBs are generated on a square box with of physical size \(\sim 0.74 \cdot 2^{\rm res}\) arcmin
- cache_sims – saves the lensed CMBs when produced for the first time
- nsims – number of simulations in the library
- num_threads – number of threads used by the pyFFTW fft-engine.
Note
All simulations random phases will be generated at the very first call if not performed previously; this might take some time
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lensit.get_maps_lib(exp, LDres, HDres=14, cache_lenalms=True, cache_maps=False, nsims=120, num_threads=1)[source]¶ Default CMB data maps simulation library
Parameters: - exp – experimental configuration (see get_config)
- LDres – the data is generated on a square patch with :math:` 2^{rm LDres}` pixels on a side
- HDres – The physical size of the path is \(\sim 0.74 \cdot 2^{\rm HDres}\) arcmin
- cache_lenalms – saves the lensed CMBs when produced for the first time (defaults to True)
- cache_maps – saves the data maps when produced for the first time (defaults to False)
- nsims – number of simulations in the library
- num_threads – number of threads used by the pyFFTW fft-engine.
Note
All simulations random phases (CMB sky and noise) will be generated at the very first call if not performed previously; this might take some time