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615b06a
WIP
joezuntz Nov 6, 2025
8e804c8
Add DeltaSigma stages
joezuntz Nov 7, 2025
4ef186f
add doc
joezuntz Nov 7, 2025
84f7431
Merge branch 'master' into delta-sigma
joezuntz Apr 22, 2026
f8ab102
desi catalog ingestion and selection stage (initial commit)
myamamoto26 Apr 29, 2026
98d5c2e
change to iterator
myamamoto26 Apr 29, 2026
a696fa6
remove old delta-sigma version
joezuntz Apr 30, 2026
f1203cf
Update to using dSigma in delta-sigma calculation
joezuntz Apr 30, 2026
fa97573
Add dsigma to install
joezuntz Apr 30, 2026
8f5cb46
fix spec
joezuntz Apr 30, 2026
6baf2e6
mask working and add a new stage name to init
myamamoto26 Apr 30, 2026
a3530b8
Merge branch 'master' into delta-sigma
joezuntz May 1, 2026
9be2f99
Merge pull request #467 from LSSTDESC/desi_ingestor
joezuntz May 1, 2026
312cee8
made subclass for desi mocks due to file format difference. Tested on…
myamamoto26 May 1, 2026
818a685
make outputs compatible with dsigma step
myamamoto26 May 4, 2026
fadac55
updates to config options and select sources behind lens
myamamoto26 May 5, 2026
b84ed41
Add placeholder stage classes
joezuntz May 6, 2026
c20dead
joint mask working
myamamoto26 May 7, 2026
4a43be0
pipeline runs
myamamoto26 May 12, 2026
88ee762
remove apparently deleted lens_source_cut kwarg
joezuntz May 12, 2026
90105b3
expose n_jobs in delta_sigma
joezuntz May 12, 2026
07dfc7c
fix collecting of results under MPI
joezuntz May 12, 2026
37aaa94
another fix to results packing
joezuntz May 12, 2026
d2b1826
Use dataregistry and parallelism at NERSC
joezuntz May 12, 2026
82a351f
try getting covariance using jackknife feature of dsigma
joezuntz May 13, 2026
3c0997e
Allow using a random subsample of ther data
joezuntz May 13, 2026
8ebb23e
Add error bars to delta sigma plot if present
joezuntz May 13, 2026
bbcf639
add raw values to plot also
joezuntz May 18, 2026
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1 change: 1 addition & 0 deletions bin/environment-local.yml
Original file line number Diff line number Diff line change
Expand Up @@ -51,3 +51,4 @@ dependencies:
# Numpy has to be here to make sure that pypi doesn't
# try to install a different version
- numpy==2.3.*
- dsigma==1.1.*
2 changes: 2 additions & 0 deletions bin/environment-perlmutter.yml
Original file line number Diff line number Diff line change
Expand Up @@ -62,3 +62,5 @@ dependencies:
- numpy==2.3.*
# NERSC-specific
- git+https://github.com/LSSTDESC/dataregistry.git
- dsigma==1.1.*

286 changes: 286 additions & 0 deletions examples/desi_dr1_stage3/config.yml
Original file line number Diff line number Diff line change
@@ -0,0 +1,286 @@
# Values in this section are accessible to all the different stages.
# They can be overridden by individual stages though.
global:
# This is read by many stages that read complete
# catalog data, and tells them how many rows to read
# at once
chunk_rows: 100000
# These mapping options are also read by a range of stages
pixelization: healpix
nside: 512
sparse: true # Generate sparse maps - faster if using small areas

TXGCRTwoCatalogInput:
metacal_dir: /global/cscratch1/sd/desc/DC2/data/Run2.2i/dpdd/Run2.2i-t3828/metacal_table_summary
photo_dir: /global/cscratch1/sd/desc/DC2/data/Run2.2i/dpdd/Run2.2i-t3828/object_table_summary

TXMetacalGCRInput:
cat_name: dc2_object_run2.1i_dr1b_with_metacal_griz

TXExposureInfo:
dc2_name: 1.2p

TXShearCalibration:
use_true_shear: false
chunk_rows: 100000
subtract_mean_shear: true
extra_cols: ['']
shear_catalog_type: hsc

TXCosmoDC2Mock:
cat_name: cosmoDC2_v1.1.4_image
visits_per_band: 16
extra_cols: redshift_true size_true shear_1 shear_2
flip_g2: true # to match metacal

TXIngestRedmagic:
lens_zbin_edges: [0.1, 0.3, 0.5]

TXIngestDESI:
mock: false
lens_zbin_edges: [0.0, 3.0]
dz: 0.001

TXIngestDESIRandoms:
lens_zbin_edges: [0.0, 3.0]
ra_col: RA
dec_col: DEC
z_col: Z

TXDESISelector:
ra_col: RA
dec_col: DEC
z_col: Z
w_col: WEIGHT
apply_mask: false
zmin: 0.0

TXDeltaSigma:
source_bins: [0,1,2,3] # no non-tomograhpic redshift distribution.
lens_bins: [0]
lens_source_sep: 0.1
photoz: True
r_min: 0.35
r_max: 70.0
nbins: 15
lower_bin_edge: [0.0, 0.358, 0.631, 0.872]
source_cat_w_col: w
lens_cat_w_col: w_sys
n_jobs: 128

TXSourceSelectorHSC:
input_pz: true
true_z: false
bands: i #used for selection
T_cut: 0.0
s2n_cut: 10.0
max_rows: 10000000000
source_zbin_edges: [0.5, 1.5, 2.5, 3.5, 4.5]
shear_catalog_type: hsc


PZPDFMLZ:
nz: 301
zmax: 3.0


PZRailTrainSource:
class_name: BPZ_lite
zmin: 0.0
zmax: 3.0
dz: 0.01
columns_file: ./data/bpz_riz.columns
data_path: ./data/example/rail-bpz-inputs
spectra_file: CWWSB4.list
prior_band: i
# Not sure about this
prior_file: hdfn_gen
p_min: 0.005
gauss_kernel: 0.0
mag_err_min: 0.005
inform_options: {save_train: false, load_model: false, modelfile: BPZpriormodel.out}
madau_reddening: no
bands: riz
zp_errors: [0.01, 0.01, 0.01]

PZRailEstimateSource:
convert_unseen: true # needed for BPZ


# Mock version of stacking:
TXSourceTrueNumberDensity:
nz: 301
zmax: 3.0

# Mock version of stacking:
TXTrueNumberDensity:
nz: 301
zmax: 3.0

TXSourceSelectorMetacal:
input_pz: false
true_z: true
bands: riz #used for selection
T_cut: 0.5
s2n_cut: 10.0
max_rows: 1000
delta_gamma: 0.02
source_zbin_edges: [0.5, 0.7, 0.9, 1.1, 2.0]

TXSourceTomography:
bands: riz #used for selection
source_zbin_edges: [0.5, 0.7, 0.9, 1.1, 2.0]

TXTruthLensSelector:
# Mag cuts
input_pz: false
true_z: true
lens_zbin_edges: [0.1, 0.3, 0.5]
cperp_cut: 0.2
r_cpar_cut: 13.5
r_lo_cut: 16.0
r_hi_cut: 21.6
i_lo_cut: 17.5
i_hi_cut: 21.9
r_i_cut: 2.0
# may also need one for r_cpar_cut

TXMeanLensSelector:
# Mag cuts
lens_zbin_edges: [0.0, 0.2, 0.4]
cperp_cut: 0.2
r_cpar_cut: 13.5
r_lo_cut: 16.0
r_hi_cut: 21.6
i_lo_cut: 17.5
i_hi_cut: 21.9
r_i_cut: 2.0

TXModeLensSelector:
# Mag cuts
lens_zbin_edges: [0.0, 0.2, 0.4]
cperp_cut: 0.2
r_cpar_cut: 13.5
r_lo_cut: 16.0
r_hi_cut: 21.6
i_lo_cut: 17.5
i_hi_cut: 21.9
r_i_cut: 2.0

TXRandomCat:
density: 10 # gals per sq arcmin

TXTwoPoint:
bin_slop: 0.1
delta_gamma: 0.02
do_pos_pos: true
do_shear_shear: true
do_shear_pos: true
flip_g2: true # use true when using metacal shears
min_sep: 2.5
max_sep: 60.0
nbins: 10
verbose: 0
subtract_mean_shear: true

TXGammaTBrightStars: {}

TXGammaTDimStars: {}

TXGammaTRandoms: {}

TXGammaTFieldCenters: {}

TXBlinding:
seed: 1972 ## seed uniquely specifies the shift in parameters
Omega_b: [0.0485, 0.001] ## fiducial_model_value, shift_sigma
Omega_c: [0.2545, 0.01]
w0: [-1.0, 0.1]
h: [0.682, 0.02]
sigma8: [0.801, 0.01]
n_s: [0.971, 0.03]
b0: 0.95 ## we use bias of the form b0/g
delete_unblinded: true

TXSourceDiagnosticPlots:
nbins: 20
g_min: -0.01
g_max: 0.01
psfT_min: 0.2
psfT_max: 0.28
T_min: 0.01
T_max: 2.1
s2n_min: 1.25
s2n_max: 300

TXDiagnosticMaps:
sparse: true # Generate sparse maps - faster if using small areas
snr_threshold: 10.0
snr_delta: 1.0
# pixelization: gnomonic
pixel_size: 0.2
ra_cent: 62.
dec_cent: -35.
npix_x: 60
npix_y: 60
depth_cut: 23.0

TXSourceMaps:
sparse: true # Generate sparse maps - faster if using small areas

TXLensMaps:
sparse: true # Generate sparse maps - faster if using small areas

# For redmagic mapping
TXExternalLensMaps:
chunk_rows: 100000
sparse: true
pixelization: healpix
nside: 512



TXAuxiliarySourceMaps:
flag_exponent_max: 8

TXAuxiliaryLensMaps:
flag_exponent_max: 8
bright_obj_threshold: 22.0 # The magnitude threshold for a object to be counted as bright
depth_band: i
snr_threshold: 10.0 # The S/N value to generate maps for (e.g. 5 for 5-sigma depth)
snr_delta: 1.0 # The range threshold +/- delta is used for finding objects at the boundary

TXRealGaussianCovariance:
min_sep: 2.5
max_sep: 60.
nbins: 10
pickled_wigner_transform: data/example/inputs/wigner.pkl


TXJackknifeCenters:
npatch: 5


TXTwoPointFourier:
flip_g2: true
bandwidth: 100

TXSimpleMask:
depth_cut: 23.5
bright_object_max: 10.0

TXMapCorrelations:
supreme_path_root: data/example/inputs/supreme
outlier_fraction: 0.05
nbin: 20

TXPhotozPlotSource:
name: TXPhotozPlotSource
TXPhotozPlotLens:
name: TXPhotozPlotLens
TXTruePhotozStackSource:
name: TXTruePhotozStackSource
weight_col: metacal/weight
redshift_group: metacal
zmax: 2.0
nz: 201
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