MinkasiWrapper

A Wrapper for the Minkasi Map Maker

This package wraps the Minkasi map mapker as an external map maker package for the TolTEC camera.

Minkasi Map Maker

Minkasi is a Python/C-based mapper for Mustang.

TODO: add credit and license of Minkasi.

Installation

Minkasi depends on fftw3, and requires an OpenMP-capable C compiler to work.

On macOS, this can be done with Homebrew:

$ brew install llvm libomp fftw3
$ export CC=/usr/local/opt/bin/clang
$ export LDFLAGS=-L/usr/local/opt/llvm/lib
$ export CPPFLAGS=-I/usr/local/opt/llvm/include

On Ubuntu, install the packages with:

$ sudo apt install gcc-10 fftw-dev

One can also use customized FFTW installation. This leverages the pkg-config stub that gets created in the fftw lib path:

$ export PKG_CONFIG_PATH=/path/to/fftw3/install/prefix/lib/pkgconfig

Once the preparation is done, install minkasi_wrapper with pip:

$ pip install git+https://github.com/toltec-astro/minkasi_wrapper

Usage

High-level API

To be implemented.

Low-level API

The minkasi_wrapper module exposes the low level minkasi.py API as the minkasi_wrapper.minkasi submodule:

from minkasi_wrapper import minkasi

tod = minkasi.Tod(...)

Please see the API documentation for details.

License

This project is Copyright (c) Zhiyuan Ma and licensed under the terms of the BSD 3-Clause license. This package is based upon the Astropy package template which is licensed under the BSD 3-clause license. See the licenses folder for more information.

Reference/API

minkasi_wrapper Package

minkasi_wrapper.extern.minkasi.minkasi Module

apply_noise(tod[, dat])
barrier()
cut_blacklist(tod_names, blacklist)
decimate(vec[, nrep])
derivs_from_elliptical_gauss(params, tod, ...)
derivs_from_elliptical_isobeta(params, tod, ...)
derivs_from_gauss_c(params, tod, *args, **kwargs)
derivs_from_isobeta_c(params, tod, *args, ...)
derivs_from_map(pars, tod, fun, map, dpar[, ...])
downsample_array_r2r(arr, fac)
downsample_tod(dat[, fac])
downsample_vec_r2r(vec, fac)
find_bad_skew_kurt(dat[, skew_thresh, ...])
find_good_fft_lens(n[, primes])
find_jumps(dat[, width, pad, thresh, rat])
find_spikes(dat[, inner, outer, rad, ...])
fit_cm_plus_poly(dat[, ord, cm_ord, niter, ...])
fit_jumps_from_cm(dat, jumps, cm[, ...])
fit_linear_ps_uncorr(dat, vecs[, tol, ...])
fit_mat_vecs_poly_nonoise(dat, mat, order[, ...])
fit_timestreams_with_derivs(func, pars, tods)
fit_timestreams_with_derivs_manyfun(funcs, ...)
fit_ts_ps(dat[, dt, ind, nu_min, nu_max, ...])
gapfill_eig(dat, cuts[, tod, thresh, ...])
get_aligned_map_subregion_car(lims[, fname, ...])	Get a wcs for a subregion of a map, with optionally finer pixellization.
get_curve_deriv_powspec(fitp, nu_scale, ...)
get_curve_deriv_tod_isosrc(pars, tod[, ...])
get_curve_deriv_tod_manygauss(pars, tod[, ...])
get_derivs_tod_isosrc(pars, tod[, niso])
get_ft_vec(n)
get_grad_mask_2d(map[, todvec, thresh, ...])	make a mask that has an estimate of the gradient within a pixel.
get_nthread()
get_timestream_chisq_curve_deriv_from_func(...)
get_timestream_chisq_from_func(func, pars, tods)
get_ts_curve_derivs_many_funcs(todvec, pars, ...)
get_ts_derivs_many_funcs(tod, pars, ...[, ...])
get_type(nbyte)
get_wcs(lims, pixsize[, proj, cosdec, ref_equ])
invsafe(mat[, thresh])
invscale(mat[, do_invsafe])
isobeta_src_chisq(params, tods)
make_hits(todvec, map[, do_weights])
make_rings(edges, cent, map[, pixsize, ...])
make_rings_wSlope(edges, cent, vals, map[, ...])
map2tod(dat, map, ipix[, do_add, do_omp])
mask_dict(mydict, mask)
nsphere_vol(npp)
partition_interval(start, stop[, seg_len, ...])
planck_g([freq])	conversion between T_CMB and T_RJ as a function of frequency.
plot_ps(vec[, downsamp])
polmap2tod(dat, map, poltag, twogamma, ipix)
poltag2pols(poltag)
read_fits_map(fname[, hdu, do_trans])
read_octave_struct(fname)
read_tod_from_fits(fname[, hdu, branch])
read_tod_from_fits_cbass(fname[, dopol, ...])
read_tod_from_toltec_nc(fname, arrayindex[, ...])
report_mpi()
run_pcg(b, x0, tods[, precon, maxiter, ...])
run_pcg_wprior(b, x0, tods[, prior, precon, ...])
run_pcg_wprior_old(b, x0, tods, prior[, ...])
scaled_airmass_from_el(mat)
segs_from_vec(vec[, pad])	return the starting/stopping points of regions marked False in vec.
set_nthread(nthread)
slice_with_copy(arr, ind)
smooth_many_vecs(vecs[, fwhm])
smooth_spectra(spec, fwhm)
smooth_vec(vec[, fwhm])
split_dict(mydict, vec, thresh)
split_partitioned_vec(start, stop[, breaks, ...])
timestreams_from_gauss(ra, dec, fwhm, tod[, ...])
timestreams_from_isobeta(params, tod)
timestreams_from_isobeta_c(params, tod[, pred])
tod2map_cached(map, dat, ipix)
tod2map_everyone(map, dat, ipix, edges)
tod2map_omp(map, dat, ipix[, atomic])
tod2map_simple(map, dat, ipix)
tod2polmap(map, dat, poltag, twogamma, ipix)
todvec_from_files_octave(fnames)
truncate_tod(dat[, primes])
update_lamda(lamda, success)
write_fits_map_wheader(map, fname, header[, ...])
y2rj([freq])	conversion to multiply a y map by to get a Rayleigh-Jeans normalized map note that it doesn't have the T_cmb at the end, so the value for low frequencies is -2.

Cuts(tod[, do_add])
CutsCompact(tod)
HealMap([proj, nside, tag])
HealPolMap([poltag, proj, nside, tag, ...])
MapNoiseWhite(ivar_map[, isinv, nfac])
Mapset()
NoiseBinnedDet(dat, dt[, freqs, scale_facs])
NoiseBinnedEig(dat, dt[, freqs, scale_facs, ...])
NoiseCMWhite(dat)
NoiseSmoothedSVD(dat_use[, fwhm, prewhiten, ...])
NoiseWhite(dat)
NoiseWhiteNotch(dat, numin, numax, tod)
PolMap(lims, pixsize[, poltag, proj, pad, ...])
SkyMap(lims[, pixsize, proj, pad, primes, ...])
SkyMapCar(lims[, pixsize, proj, pad, ...])
SkyMapCarOld(lims, pixsize)
SkyMapCoarse(map)
SkyMapTwoRes(map_lowres, lims[, osamp, ...])	A pair of maps to serve as a prior for multi-experiment mapping.
Tod(info)
TodVec()
detOffset([tod])
null_precon()
tsAirmass([tod, order])
tsBinnedAz(tod[, lims, nbin])
tsBinnedAzShared([ndet, lims, nbin])
tsCalib([tod, model])
tsCommon([tod])
tsDetAz(tod[, npoly])
tsGeneric([tod])
tsModel([todvec, modelclass])
tsMultiModel([todvec, todtags, modelclass, tag])	A class to hold timestream models that are shared between groups of TODs.
tsNotch(tod, numin, numax)
tsPoly(tod[, order])
tsStripes(tod[, seg_len, do_slope, tthresh])
tsStripes_old(tod[, seg_len, do_slope])
tsVecs(tod, vecs)

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