fitvd

Fit DES and video data to models

Examples

config=fitvd-01.yaml

# generate the friends-of-friends groups from the r band
# MEDS file

fitvd-make-fofs \
    --conf=$config \
    --plot=SN-C3_C28_r3688p01_r_meds-Y3A2_DEEP-fofs-01.png \
    --output=SN-C3_C28_r3688p01_r_meds-Y3A2_DEEP-fofs-01.fits \
    SN-C3_C28_r3688p01/SN-C3_C28_r3688p01_r_meds-Y3A2_DEEP.fits.fz

# An example run over a subset of the FoF groups
# --seed=8431 seed for this subset of groups.  Use a different seed
#   for each subset
# --fofs specifies the FoF group file, created above
# --start=1000 means to start with FoF group number 1000
# --end=1009 means the last FoF group to process is number 1009

fitvd \
    --seed=8431 \
    --config=$config \
    --output=SN-C3_C28_r3688p01_r_meds-Y3A2_DEEP-fofs-01-001000-001009.fits \
    --fofs=SN-C3_C28_r3688p01_r_meds-Y3A2_DEEP-fofs-01.fits \
    --start=1000 --end=1009  \
    SN-C3_C28_r3688p01/SN-C3_C28_r3688p01_u_meds-Y3A2_DEEP.fits.fz \
    SN-C3_C28_r3688p01/SN-C3_C28_r3688p01_g_meds-Y3A2_DEEP.fits.fz \
    SN-C3_C28_r3688p01/SN-C3_C28_r3688p01_r_meds-Y3A2_DEEP.fits.fz \
    SN-C3_C28_r3688p01/SN-C3_C28_r3688p01_i_meds-Y3A2_DEEP.fits.fz \
    SN-C3_C28_r3688p01/SN-C3_C28_r3688p01_z_meds-Y3A2_DEEP.fits.fz \
    SN-C3_C28_r3688p01/SN-C3_C28_r3688p01_Y_meds-Y3A2_DEEP.fits.fz \
    SN-C3_C28_r3688p01/SN-C3_C28_r3688p01_J_meds-VIDEO_DEEP.fits.fz \
    SN-C3_C28_r3688p01/SN-C3_C28_r3688p01_H_meds-VIDEO_DEEP.fits.fz \
    SN-C3_C28_r3688p01/SN-C3_C28_r3688p01_Ks_meds-VIDEO_DEEP.fits.fz

# making a script for FoF generation.
# Use --system=shell to
# just write the bash script.  Set --system=condor or wq to
# also write submit script for those batch systems.
# make sure the environment variable FITVD_DIR is defined

# see below for an example run config

run_config=run-vd01.yaml

fitvd-make-batch-fofs \
    --system=shell \
    --fit-config=$config \
    --run-config=$run_config \
    SN-C3_C28_r3688p01/SN-C3_C28_r3688p01_r_meds-Y3A2_DEEP.fits.fz

# Write out batch scripts to process the FoF groups in chunks
# similar to above, using --system=shell just writes out bash
# scripts

fitvd-make-batch \
    --system=shell \
    --fit-config=$config \
    --run-config=$run_config \
    SN-C3_C28_r3688p01/SN-C3_C28_r3688p01_u_meds-Y3A2_DEEP.fits.fz \
    SN-C3_C28_r3688p01/SN-C3_C28_r3688p01_g_meds-Y3A2_DEEP.fits.fz \
    SN-C3_C28_r3688p01/SN-C3_C28_r3688p01_r_meds-Y3A2_DEEP.fits.fz \
    SN-C3_C28_r3688p01/SN-C3_C28_r3688p01_i_meds-Y3A2_DEEP.fits.fz \
    SN-C3_C28_r3688p01/SN-C3_C28_r3688p01_z_meds-Y3A2_DEEP.fits.fz \
    SN-C3_C28_r3688p01/SN-C3_C28_r3688p01_Y_meds-Y3A2_DEEP.fits.fz \
    SN-C3_C28_r3688p01/SN-C3_C28_r3688p01_J_meds-VIDEO_DEEP.fits.fz \
    SN-C3_C28_r3688p01/SN-C3_C28_r3688p01_H_meds-VIDEO_DEEP.fits.fz \
    SN-C3_C28_r3688p01/SN-C3_C28_r3688p01_Ks_meds-VIDEO_DEEP.fits.fz

An example config file. For more config files see https://github.com/esheldon/fitvd-config

# this is meant to be run on DES ugrizY and VIDEO JHKs
# note detband is 2 meaning r band for the size guess

parspace: 'ngmix'

hst_band: null

weight_type: 'circular-mask'

max_maskfrac: 0.45

fofs:
    method: 'radius'
    check_seg: false

    # name in meds file, or catalog if method is catalog_radius
    #radius_column: "iso_radius_arcsec"
    radius_column: "iso_radius"

    # factor to multiply radius this happens before clipping to [min_radius,
    # max_radius] for a low threshold, the isoarea is basically covering all
    # the observed flux, so mult of 1 makes sense
    radius_mult: 1.0

    # clip the radius in pixels=sqrt(isoarea_image/pi)
    # 5 pixels is about 3 sigma for a 1'' FWHM gaussian
    # this happens after the radius_mult is applied
    min_radius_arcsec: 1.0
    #max_radius_arcsec: null
    max_radius_arcsec: 2.0

    # This is added to the radius. This kind of padding makes sense for radii
    # based on the iso area.  Padding happens after mult and clipping
    padding_arcsec: 0.5

    # arcsec
    #extra_psf_fwhm_arcsec: 1.0
    extra_psf_fwhm_arcsec: 0.0

mof:

    model: 'bdf'

    # for guesses
    detband: 2
   
    priors:
        cen:
            type: 'normal2d'
            sigma: 0.263

        g:
            type: 'ba'
            sigma: 0.2

        T:
            type: 'flat'
            pars: [-1.0, 1.0e+09]

        flux:
            type: 'flat'
            pars: [-1000.0, 1.0e+09]

        fracdev:
            type: 'truncated-normal'
            mean: 0.5
            sigma: 0.1
            minval: -2.0
            maxval: 3.0

    psf:
        ntry: 4

        model: 'em3'

        em_pars:
            maxiter: 2000
            tol: 1.0e-4

Dependencies

Because of the numba requirement, it is best to work in a conda environment.

Available in anaconda (I recommend using conda forge)

package   version
-----------------
scipy     latest
numba     0.40 (newer versions have a bug)
fitsio    latest
pyyaml    latest

Not available in anaconda

repo    branch/tag
------------------
esutil  master
ngmix   v1.2.1
meds    v0.9.6
psfex   v0.4.0
mof     v0.9.0

# optional for visualization
biggles latest (use pip install biggles; depends on plotutils libplot-dev)
images  master (https://github.com/esheldon/images)

An example run config file.

# a global seed; each call to fitvd will have a different seed, and
# these are generated after first seeding a numpy rng using this seed

seed: 17624

# process the MEDS files in chunks of 10 FoF groups
# a script will be written out for each chunk of 10

chunksize: 10

# for condor
jobs_per_sub: 100