diff --git a/Dockerfile.jupyter b/Dockerfile.jupyter index fc24a75f0..828c1bfac 100644 --- a/Dockerfile.jupyter +++ b/Dockerfile.jupyter @@ -1,7 +1,7 @@ # Dockerfile for ShapePipe Jupyter Lab # Uses the shared base image -FROM ghcr.io/cosmostat/shapepipe:v2.0 +FROM ghcr.io/cosmostat/shapepipe:develop # Default command starts Jupyter Lab ENTRYPOINT ["jupyter","lab","--ip=0.0.0.0","--port=8888","--no-browser","--allow-root"] diff --git a/bin/canfar_monitor.py b/bin/canfar_monitor.py new file mode 100755 index 000000000..e01872201 --- /dev/null +++ b/bin/canfar_monitor.py @@ -0,0 +1,3 @@ +#!/usr/bin/env python +from shapepipe.canfar_run import run_log +run_log() diff --git a/bin/canfar_monitor_log.py b/bin/canfar_monitor_log.py new file mode 100755 index 000000000..1ef99aa04 --- /dev/null +++ b/bin/canfar_monitor_log.py @@ -0,0 +1,3 @@ +#!/usr/bin/env python +from shapepipe.canfar_run import run_monitor_log +run_monitor_log() diff --git a/bin/canfar_submit_job.py b/bin/canfar_submit_job.py new file mode 100755 index 000000000..202e9d274 --- /dev/null +++ b/bin/canfar_submit_job.py @@ -0,0 +1,3 @@ +#!/usr/bin/env python +from shapepipe.canfar_run import run_job +run_job() diff --git a/bin/shapepipe_run.py b/bin/shapepipe_run.py new file mode 100755 index 000000000..dedfc5093 --- /dev/null +++ b/bin/shapepipe_run.py @@ -0,0 +1,3 @@ +#!/usr/bin/env python +from shapepipe.shapepipe_run import main +main() diff --git a/bin/summary_run.py b/bin/summary_run.py new file mode 100755 index 000000000..a59689e41 --- /dev/null +++ b/bin/summary_run.py @@ -0,0 +1,3 @@ +#!/usr/bin/env python +from shapepipe.summary_run import main +main() diff --git a/example/cfis/config_exp_mccd.ini b/example/cfis/config_exp_mccd.ini index 470c1a6b2..8307a6aeb 100644 --- a/example/cfis/config_exp_mccd.ini +++ b/example/cfis/config_exp_mccd.ini @@ -236,5 +236,3 @@ PSF_MODEL_PATTERN = fitted_model # PSF model separator PSF_MODEL_SEPARATOR = - -# For multi-epoch purposes -ME_LOG_WCS = $SP_RUN/output/run_sp_exp_Mh/merge_headers_runner/output/log_exp_headers.sqlite diff --git a/example/cfis/config_onthefly.mask b/example/cfis/config_onthefly.mask index 9a147bdcd..7c185c602 100644 --- a/example/cfis/config_onthefly.mask +++ b/example/cfis/config_onthefly.mask @@ -3,7 +3,7 @@ ## Paths to executables [PROGRAM_PATH] -WW_PATH = ww +WW_PATH = weightwatcher WW_CONFIG_FILE = $SP_CONFIG/mask_default/default.ww # Indicate cds client executable if no external star catalogue is available diff --git a/example/cfis/config_save.mask b/example/cfis/config_save.mask index 887110ff5..497dedda9 100644 --- a/example/cfis/config_save.mask +++ b/example/cfis/config_save.mask @@ -3,7 +3,7 @@ ## Paths to executables [PROGRAM_PATH] -WW_PATH = ww +WW_PATH = weightwatcher WW_CONFIG_FILE = $SP_CONFIG/mask_default/default.ww # Indicate cds client executable if no external star catalogue is available diff --git a/example/cfis/config_tile_Git_cat_vos.ini b/example/cfis/config_tile_Git_cat_vos.ini new file mode 100644 index 000000000..d2a18d816 --- /dev/null +++ b/example/cfis/config_tile_Git_cat_vos.ini @@ -0,0 +1,90 @@ +# ShapePipe configuration file for: get external tile catalogue + + +## Default ShapePipe options +[DEFAULT] + +# verbose mode (optional), default: True, print messages on terminal +VERBOSE = False + +# Name of run (optional) default: shapepipe_run +RUN_NAME = run_sp_tile_Gic + +# Add date and time to RUN_NAME, optional, default: False +RUN_DATETIME = True + + +## ShapePipe execution options +[EXECUTION] + +# Module name, single string or comma-separated list of valid module runner names +MODULE = get_images_runner + +# Parallel processing mode, SMP or MPI +MODE = SMP + + +## ShapePipe file handling options +[FILE] + +# Log file master name, optional, default: shapepipe +LOG_NAME = log_sp + +# Runner log file name, optional, default: shapepipe_runs +RUN_LOG_NAME = log_run_sp + +# Input directory, containing input files, single string or list of names +INPUT_DIR = $SP_RUN + +# Output directory +OUTPUT_DIR = $SP_RUN/output + + +## ShapePipe job handling options +[JOB] + +# Batch size of parallel processing (optional), default is 1, i.e. run all jobs in serial +SMP_BATCH_SIZE = 1 + +# Timeout value (optional), default is None, i.e. no timeout limit applied +TIMEOUT = 96:00:00 + + +## Module options + +# Get external tile catalogue +[GET_IMAGES_RUNNER] + +FILE_PATTERN = tile_numbers + +FILE_EXT = .txt + +# NUMBERING_SCHEME (optional) string with numbering pattern for input files +NUMBERING_SCHEME = + +# Paths + +# Input path where catalogues are stored +INPUT_PATH = vos:cfis/tiles_DR6 + +# Input file pattern including tile number as dummy template +INPUT_FILE_PATTERN = CFIS.000.000.r + +# Input file extensions +INPUT_FILE_EXT = .cat + +# Input numbering scheme, python regexp +INPUT_NUMBERING = \d{3}\.\d{3} + +# Output file pattern without number +OUTPUT_FILE_PATTERN = CFIS_cat- + +# Copy/download method, one in 'vos', 'symlink' +RETRIEVE = vos + +# If RETRIEVE=vos, number of attempts to download +# Optional, default=3 +N_TRY = 3 + +# Copy command options, optional +RETRIEVE_OPTIONS = --certfile=$HOME/.ssl/cadcproxy.pem diff --git a/example/cfis/config_exp_Mh.ini b/example/cfis/config_tile_Mh_exp.ini similarity index 98% rename from example/cfis/config_exp_Mh.ini rename to example/cfis/config_tile_Mh_exp.ini index f99f01562..0d3f9f8b3 100644 --- a/example/cfis/config_exp_Mh.ini +++ b/example/cfis/config_tile_Mh_exp.ini @@ -11,7 +11,7 @@ VERBOSE = True # Name of run (optional) default: shapepipe_run -RUN_NAME = run_sp_exp_Mh +RUN_NAME = run_sp_tile_Mh_exp # Add date and time to RUN_NAME, optional, default: True RUN_DATETIME = False diff --git a/example/cfis/config_tile_MiViSmVi.ini b/example/cfis/config_tile_MiViSmVi.ini index 7b5989894..4a6eb79cc 100644 --- a/example/cfis/config_tile_MiViSmVi.ini +++ b/example/cfis/config_tile_MiViSmVi.ini @@ -57,11 +57,11 @@ TIMEOUT = 96:00:00 [MCCD_INTERP_RUNNER] -INPUT_DIR = last:sextractor_runner_run_1 +INPUT_DIR = last:sextractor_runner_run_1, run_sp_exp_Mh:merge_headers_runner -FILE_PATTERN = sexcat +FILE_PATTERN = sexcat, log_exp_headers -FILE_EXT = .fits +FILE_EXT = .fits, .sqlite # NUMBERING_SCHEME (optional) string with numbering pattern for input files NUMBERING_SCHEME = -000-000 @@ -84,9 +84,6 @@ PSF_MODEL_PATTERN = fitted_model PSF_MODEL_SEPARATOR = - -# Multi-epoch mode: Path to file with single-exposure WCS header information -ME_LOG_WCS = $SP_RUN/output/run_sp_exp_Mh/merge_headers_runner/output/log_exp_headers.sqlite - [VIGNETMAKER_RUNNER_RUN_1] @@ -146,11 +143,11 @@ OUTPUT_MODE = new # Create multi-epoch vignets for tiles corresponding to # positions on single-exposures -INPUT_DIR = last:sextractor_runner_run_1 +INPUT_DIR = last:sextractor_runner_run_1, run_sp_exp_Mh:merge_headers_runner -FILE_PATTERN = sexcat +FILE_PATTERN = sexcat, log_exp_headers -FILE_EXT = .fits +FILE_EXT = .fits, .sqlite # NUMBERING_SCHEME (optional) string with numbering pattern for input files NUMBERING_SCHEME = -000-000 @@ -178,4 +175,3 @@ PREFIX = # run outputs ME_IMAGE_DIR = split_exp_runner, split_exp_runner, split_exp_runner, sextractor_runner_run_2 ME_IMAGE_PATTERN = flag, image, weight, background -ME_LOG_WCS = $SP_RUN/output/run_sp_exp_Mh/merge_headers_runner/output/log_exp_headers.sqlite diff --git a/example/cfis/config_tile_Ng_batch_psfex_uc.ini b/example/cfis/config_tile_Ng_batch_psfex_uc.ini new file mode 100644 index 000000000..9b57396c5 --- /dev/null +++ b/example/cfis/config_tile_Ng_batch_psfex_uc.ini @@ -0,0 +1,76 @@ +# ShapePipe configuration file for tiles: ngmix + + +## Default ShapePipe options +[DEFAULT] + +# verbose mode (optional), default: True, print messages on terminal +VERBOSE = True + +# Name of run (optional) default: shapepipe_run +RUN_NAME = run_sp_tile_Ng + +# Add date and time to RUN_NAME, optional, default: False +RUN_DATETIME = False + + +## ShapePipe execution options +[EXECUTION] + +# Module name, single string or comma-separated list of valid module runner names +MODULE = ngmix_runner + +# Parallel processing mode, SMP or MPI +MODE = SMP + + +## ShapePipe file handling options +[FILE] + +# Log file master name, optional, default: shapepipe +LOG_NAME = log_sp + +# Runner log file name, optional, default: shapepipe_runs +RUN_LOG_NAME = log_run_sp + +# Input directory, containing input files, single string or list of names +INPUT_DIR = . + +# Output directory +OUTPUT_DIR = $SP_RUN/output + + +## ShapePipe job handling options +[JOB] + +# Batch size of parallel processing (optional), default is 1, i.e. run all jobs in serial +SMP_BATCH_SIZE = 24 + +# Timeout value (optional), default is None, i.e. no timeout limit applied +TIMEOUT = 96:00:00 + + +## Module options + +# Model-fitting shapes with ngmix +[NGMIX_RUNNER] + +INPUT_DIR = run_sp_tile_Uc:read_ext_sexcat_runner,last:psfex_interp_runner,last:vignetmaker_runner_run_2,run_sp_tile_Mh_exp:merge_headers_runner + +FILE_PATTERN = sexcat, image_vignet, background_vignet, galaxy_psf, weight_vignet, flag_vignet, log_exp_headers + +FILE_EXT = .fits, .sqlite, .sqlite, .sqlite, .sqlite, .sqlite, .sqlite + +# NUMBERING_SCHEME (optional) string with numbering pattern for input files +NUMBERING_SCHEME = -000-000 + +# Magnitude zero-point +MAG_ZP = 30.0 + +# Pixel scale in arcsec +PIXEL_SCALE = 0.186 + +SAVE_BATCH = 1000 + +ID_OBJ_MIN = -1 +ID_OBJ_MAX = -1 diff --git a/example/cfis/config_tile_Ng_template.ini b/example/cfis/config_tile_Ng_template.ini index 8799042cf..70cf91de7 100644 --- a/example/cfis/config_tile_Ng_template.ini +++ b/example/cfis/config_tile_Ng_template.ini @@ -55,18 +55,15 @@ TIMEOUT = 96:00:00 # Model-fitting shapes with ngmix [NGMIX_RUNNER] -INPUT_DIR = run_sp_tile_Sx:sextractor_runner,last:X_interp_runner,last:vignetmaker_runner_run_2 +INPUT_DIR = run_sp_tile_Sx:sextractor_runner,last:X_interp_runner,last:vignetmaker_runner_run_2,run_sp_exp_Mh:merge_headers_runner -FILE_PATTERN = sexcat, image_vignet, background_vignet, galaxy_psf, weight_vignet, flag_vignet +FILE_PATTERN = sexcat, image_vignet, background_vignet, galaxy_psf, weight_vignet, flag_vignet, log_exp_headers -FILE_EXT = .fits, .sqlite, .sqlite, .sqlite, .sqlite, .sqlite +FILE_EXT = .fits, .sqlite, .sqlite, .sqlite, .sqlite, .sqlite, .sqlite # NUMBERING_SCHEME (optional) string with numbering pattern for input files NUMBERING_SCHEME = -000-000 -# Multi-epoch mode: Path to file with single-exposure WCS header information -LOG_WCS = $SP_RUN/output/run_sp_exp_Mh/merge_headers_runner/output/log_exp_headers.sqlite - # Magnitude zero-point MAG_ZP = 30.0 diff --git a/example/cfis/config_tile_Ng_template_batch.ini b/example/cfis/config_tile_Ng_template_batch.ini index 38146cc9d..1ddb00d44 100644 --- a/example/cfis/config_tile_Ng_template_batch.ini +++ b/example/cfis/config_tile_Ng_template_batch.ini @@ -55,18 +55,15 @@ TIMEOUT = 96:00:00 # Model-fitting shapes with ngmix [NGMIX_RUNNER] -INPUT_DIR = run_sp_tile_Sx:sextractor_runner,last:X_interp_runner,last:vignetmaker_runner_run_2 +INPUT_DIR = run_sp_tile_Sx:sextractor_runner,last:X_interp_runner,last:vignetmaker_runner_run_2,run_sp_exp_Mh:merge_headers_runner -FILE_PATTERN = sexcat, image_vignet, background_vignet, galaxy_psf, weight_vignet, flag_vignet +FILE_PATTERN = sexcat, image_vignet, background_vignet, galaxy_psf, weight_vignet, flag_vignet, log_exp_headers -FILE_EXT = .fits, .sqlite, .sqlite, .sqlite, .sqlite, .sqlite +FILE_EXT = .fits, .sqlite, .sqlite, .sqlite, .sqlite, .sqlite, .sqlite # NUMBERING_SCHEME (optional) string with numbering pattern for input files NUMBERING_SCHEME = -000-000 -# Multi-epoch mode: Path to file with single-exposure WCS header information -LOG_WCS = $SP_RUN/output/run_sp_exp_Mh/merge_headers_runner/output/log_exp_headers.sqlite - # Directory of previous run, optional. CHECK_EXISTING_DIR = $SP_RUN/output/run_sp_tile_ngmix_Ng1u_prev/ngmix_runner/output diff --git a/example/cfis/config_tile_PiViVi_canfar.ini b/example/cfis/config_tile_PiViVi_canfar_sx.ini similarity index 78% rename from example/cfis/config_tile_PiViVi_canfar.ini rename to example/cfis/config_tile_PiViVi_canfar_sx.ini index 0f94ba15a..dcd8a48cc 100644 --- a/example/cfis/config_tile_PiViVi_canfar.ini +++ b/example/cfis/config_tile_PiViVi_canfar_sx.ini @@ -9,7 +9,7 @@ VERBOSE = True # Name of run (optional) default: shapepipe_run -RUN_NAME = run_sp_tile_PsViSmVi +RUN_NAME = run_sp_tile_PiViVi # Add date and time to RUN_NAME, optional, default: False ; RUN_DATETIME = False @@ -57,11 +57,11 @@ TIMEOUT = 96:00:00 [PSFEX_INTERP_RUNNER] -INPUT_DIR = run_sp_tile_Sx:sextractor_runner +INPUT_DIR = run_sp_tile_Sx:sextractor_runner, run_sp_tile_Mh_exp:merge_headers_runner, last:find_exposures_runner -FILE_PATTERN = sexcat +FILE_PATTERN = sexcat, log_exp_headers, exp_numbers -FILE_EXT = .fits +FILE_EXT = .fits, .sqlite, .txt # NUMBERING_SCHEME (optional) string with numbering pattern for input files NUMBERING_SCHEME = -000-000 @@ -86,14 +86,14 @@ CHI2_THRESH = 2 # Multi-epoch mode parameters -ME_DOT_PSF_DIR = all:psfex_runner +# Root directory of per-exposure work directories; replaces ME_DOT_PSF_DIR +# for v2.0 per-exposure pipeline. psfex_runner/output/ dirs are discovered +# by scanning $SP_EXP for the exposures listed in the exp_numbers input file. +ME_DOT_PSF_EXP_DIR = $SP_EXP # Input psf file pattern ME_DOT_PSF_PATTERN = star_split_ratio_80 -# Multi-epoch mode: Path to file with single-exposure WCS header information -ME_LOG_WCS = $SP_RUN/output/run_sp_exp_Mh/merge_headers_runner/output/log_exp_headers.sqlite - # Create vignets for tiles weights [VIGNETMAKER_RUNNER_RUN_1] @@ -132,11 +132,11 @@ PREFIX = weight # Create multi-epoch vignets for tiles corresponding to # positions on single-exposures -INPUT_DIR = run_sp_tile_Sx:sextractor_runner +INPUT_DIR = run_sp_tile_Sx:sextractor_runner, run_sp_tile_Mh_exp:merge_headers_runner, last:find_exposures_runner -FILE_PATTERN = sexcat +FILE_PATTERN = sexcat, log_exp_headers, exp_numbers -FILE_EXT = .fits +FILE_EXT = .fits, .sqlite, .txt # NUMBERING_SCHEME (optional) string with numbering pattern for input files NUMBERING_SCHEME = -000-000 @@ -161,7 +161,8 @@ STAMP_SIZE = 51 PREFIX = # Additional parameters for path and file pattern corresponding to single-exposure -# run outputs -ME_IMAGE_DIR = all:split_exp_runner, all:split_exp_runner, all:split_exp_runner, all:sextractor_runner +# run outputs. ME_IMAGE_EXP_DIR/ME_IMAGE_EXP_RUNNERS replace ME_IMAGE_DIR for +# the v2.0 per-exposure pipeline; output dirs are discovered by scanning $SP_EXP. +ME_IMAGE_EXP_DIR = $SP_EXP +ME_IMAGE_EXP_RUNNERS = split_exp_runner, split_exp_runner, split_exp_runner, sextractor_runner ME_IMAGE_PATTERN = flag, image, weight, background -ME_LOG_WCS = $SP_RUN/output/run_sp_exp_Mh/merge_headers_runner/output/log_exp_headers.sqlite diff --git a/example/cfis/config_tile_PiViVi_canfar_uc.ini b/example/cfis/config_tile_PiViVi_canfar_uc.ini new file mode 100644 index 000000000..32c530788 --- /dev/null +++ b/example/cfis/config_tile_PiViVi_canfar_uc.ini @@ -0,0 +1,166 @@ +# ShapePipe configuration file for tile, from detection up to shape measurement. +# PSFEx PSF model. + + +## Default ShapePipe options +[DEFAULT] + +# verbose mode (optional), default: True, print messages on terminal +VERBOSE = True + +# Name of run (optional) default: shapepipe_run +RUN_NAME = run_sp_tile_PiViVi + +# Add date and time to RUN_NAME, optional, default: False +; RUN_DATETIME = False + + +## ShapePipe execution options +[EXECUTION] + +# Module name, single string or comma-separated list of valid module runner names +MODULE = psfex_interp_runner, vignetmaker_runner, vignetmaker_runner + +# Parallel processing mode, SMP or MPI +MODE = SMP + + +## ShapePipe file handling options +[FILE] + +# Log file master name, optional, default: shapepipe +LOG_NAME = log_sp + +# Runner log file name, optional, default: shapepipe_runs +RUN_LOG_NAME = log_run_sp + +# Input directory, containing input files, single string or list of names +INPUT_DIR = . + +# Output directory +OUTPUT_DIR = $SP_RUN/output + + +## ShapePipe job handling options +[JOB] + +# Batch size of parallel processing (optional), default is 1, i.e. run all jobs in serial +SMP_BATCH_SIZE = 16 + +# Timeout value (optional), default is None, i.e. no timeout limit applied +TIMEOUT = 96:00:00 + + +## Module options + +[PSFEX_INTERP_RUNNER] + +INPUT_DIR = run_sp_tile_Uc:read_ext_sexcat_runner, run_sp_tile_Mh_exp:merge_headers_runner, last:find_exposures_runner + +FILE_PATTERN = sexcat, log_exp_headers, exp_numbers + +FILE_EXT = .fits, .sqlite, .txt + +# NUMBERING_SCHEME (optional) string with numbering pattern for input files +NUMBERING_SCHEME = -000-000 + +# Run mode for psfex interpolation: +# CLASSIC: 'classical' run, interpolate to object positions +# MULTI-EPOCH: interpolate for multi-epoch images +# VALIDATION: validation for single-epoch images +MODE = MULTI-EPOCH + +# Column names of position parameters +POSITION_PARAMS = XWIN_WORLD,YWIN_WORLD + +# If True, measure and store ellipticity of the PSF +GET_SHAPES = True + +# Number of stars threshold +STAR_THRESH = 20 + +# chi^2 threshold +CHI2_THRESH = 2 + +# Multi-epoch mode parameters + +# Root directory of per-exposure work directories; replaces ME_DOT_PSF_DIR +# for v2.0 per-exposure pipeline. psfex_runner/output/ dirs are discovered +# by scanning $SP_EXP for the exposures listed in the exp_numbers input file. +ME_DOT_PSF_EXP_DIR = $SP_EXP + +# Input psf file pattern +ME_DOT_PSF_PATTERN = star_split_ratio_80 + + +# Create vignets for tiles weights +[VIGNETMAKER_RUNNER_RUN_1] + +INPUT_DIR = run_sp_tile_Uc:read_ext_sexcat_runner, last:uncompress_fits_runner + +FILE_PATTERN = sexcat, CFIS_weight + +FILE_EXT = .fits, .fits + +# NUMBERING_SCHEME (optional) string with numbering pattern for input files +NUMBERING_SCHEME = -000-000 + +MASKING = False +MASK_VALUE = 0 + +# Run mode for psfex interpolation: +# CLASSIC: 'classical' run, interpolate to object positions +# MULTI-EPOCH: interpolate for multi-epoch images +# VALIDATION: validation for single-epoch images +MODE = CLASSIC + +# Coordinate frame type, one in PIX (pixel frame), SPHE (spherical coordinates) +COORD = PIX +POSITION_PARAMS = XWIN_IMAGE,YWIN_IMAGE + +# Vignet size in pixels +STAMP_SIZE = 51 + +# Output file name prefix, file name is _vignet.fits +PREFIX = weight + + +[VIGNETMAKER_RUNNER_RUN_2] + +# Create multi-epoch vignets for tiles corresponding to +# positions on single-exposures + +INPUT_DIR = run_sp_tile_Uc:read_ext_sexcat_runner, run_sp_tile_Mh_exp:merge_headers_runner, last:find_exposures_runner + +FILE_PATTERN = sexcat, log_exp_headers, exp_numbers + +FILE_EXT = .fits, .sqlite, .txt + +# NUMBERING_SCHEME (optional) string with numbering pattern for input files +NUMBERING_SCHEME = -000-000 + +MASKING = False +MASK_VALUE = 0 + +# Run mode for psfex interpolation: +# CLASSIC: 'classical' run, interpolate to object positions +# MULTI-EPOCH: interpolate for multi-epoch images +# VALIDATION: validation for single-epoch images +MODE = MULTI-EPOCH + +# Coordinate frame type, one in PIX (pixel frame), SPHE (spherical coordinates) +COORD = SPHE +POSITION_PARAMS = XWIN_WORLD,YWIN_WORLD + +# Vignet size in pixels +STAMP_SIZE = 51 + +# Output file name prefix, file name is vignet.fits +PREFIX = + +# Additional parameters for path and file pattern corresponding to single-exposure +# run outputs. ME_IMAGE_EXP_DIR/ME_IMAGE_EXP_RUNNERS replace ME_IMAGE_DIR for +# the v2.0 per-exposure pipeline; output dirs are discovered by scanning $SP_EXP. +ME_IMAGE_EXP_DIR = $SP_EXP +ME_IMAGE_EXP_RUNNERS = split_exp_runner, split_exp_runner, split_exp_runner, sextractor_runner +ME_IMAGE_PATTERN = flag, image, weight, background diff --git a/example/cfis/config_tile_Sx.ini b/example/cfis/config_tile_Sx.ini index 6ac5c5440..085b4fb5a 100644 --- a/example/cfis/config_tile_Sx.ini +++ b/example/cfis/config_tile_Sx.ini @@ -55,11 +55,11 @@ TIMEOUT = 96:00:00 [SEXTRACTOR_RUNNER] -INPUT_DIR = run_sp_Git:get_images_runner, last:uncompress_fits_runner, run_sp_Ma_tile:mask_runner +INPUT_DIR = run_sp_Git:get_images_runner, last:uncompress_fits_runner, run_sp_Ma_tile:mask_runner, run_sp_tile_Mh_exp:merge_headers_runner -FILE_PATTERN = CFIS_image, CFIS_weight, pipeline_flag +FILE_PATTERN = CFIS_image, CFIS_weight, pipeline_flag, log_exp_headers -FILE_EXT = .fits, .fits, .fits +FILE_EXT = .fits, .fits, .fits, .sqlite # NUMBERING_SCHEME (optional) string with numbering pattern for input files NUMBERING_SCHEME = -000-000 @@ -107,9 +107,6 @@ SUFFIX = sexcat # Necessary for tiles, to enable multi-exposure processing MAKE_POST_PROCESS = True -# Multi-epoch mode: Path to file with single-exposure WCS header information -LOG_WCS = $SP_RUN/output/run_sp_exp_Mh/merge_headers_runner/output/log_exp_headers.sqlite - # World coordinate keywords, SExtractor output. Format: KEY_X,KEY_Y WORLD_POSITION = XWIN_WORLD,YWIN_WORLD diff --git a/example/cfis/config_tile_Sx_nomask.ini b/example/cfis/config_tile_Sx_nomask.ini index d9e4e94ab..81bb89c61 100644 --- a/example/cfis/config_tile_Sx_nomask.ini +++ b/example/cfis/config_tile_Sx_nomask.ini @@ -55,11 +55,11 @@ TIMEOUT = 96:00:00 [SEXTRACTOR_RUNNER] -INPUT_DIR = run_sp_Git:get_images_runner, last:uncompress_fits_runner +INPUT_DIR = run_sp_Git:get_images_runner, last:uncompress_fits_runner, run_sp_exp_Mh:merge_headers_runner -FILE_PATTERN = CFIS_image, CFIS_weight +FILE_PATTERN = CFIS_image, CFIS_weight, log_exp_headers -FILE_EXT = .fits, .fits +FILE_EXT = .fits, .fits, .sqlite # NUMBERING_SCHEME (optional) string with numbering pattern for input files NUMBERING_SCHEME = -000-000 @@ -107,9 +107,6 @@ SUFFIX = sexcat # Necessary for tiles, to enable multi-exposure processing MAKE_POST_PROCESS = True -# Multi-epoch mode: Path to file with single-exposure WCS header information -LOG_WCS = $SP_RUN/output/run_sp_exp_Mh/merge_headers_runner/output/log_exp_headers.sqlite - # World coordinate keywords, SExtractor output. Format: KEY_X,KEY_Y WORLD_POSITION = XWIN_WORLD,YWIN_WORLD diff --git a/example/cfis/config_tile_Uc.ini b/example/cfis/config_tile_Uc.ini index da7535909..628e81a0c 100644 --- a/example/cfis/config_tile_Uc.ini +++ b/example/cfis/config_tile_Uc.ini @@ -54,13 +54,13 @@ TIMEOUT = 96:00:00 ## Module options -[READ_EXT_CAT_RUNNER] +[READ_EXT_SEXCAT_RUNNER] -INPUT_DIR = run_sp_Gic:get_images_runner, run_sp_Git:get_images_runner +INPUT_DIR = run_sp_tile_Gic:get_images_runner, run_sp_tile_Git:get_images_runner, run_sp_tile_Mh_exp:merge_headers_runner -FILE_PATTERN = CFIS_cat, CFIS_image +FILE_PATTERN = CFIS_cat, CFIS_image, log_exp_headers -FILE_EXT = .cat, .fits +FILE_EXT = .cat, .fits, .sqlite # NUMBERING_SCHEME (optional) string with numbering pattern for input files NUMBERING_SCHEME = -000-000 @@ -77,9 +77,6 @@ VIGNET_SIZE = 51 # Necessary for tiles, to enable multi-exposure processing MAKE_POST_PROCESS = True -# Multi-epoch mode: Path to file with single-exposure WCS header information -LOG_WCS = $SP_RUN/output/run_sp_exp_Mh/merge_headers_runner/output/log_exp_headers.sqlite - # World coordinate keywords, SExtractor output. Format: KEY_X,KEY_Y WORLD_POSITION = ALPHA_J2000,DELTA_J2000 diff --git a/example/cfis/config_tile_onthefly.mask b/example/cfis/config_tile_onthefly.mask index bcd7663ad..18cf5db2d 100644 --- a/example/cfis/config_tile_onthefly.mask +++ b/example/cfis/config_tile_onthefly.mask @@ -3,7 +3,7 @@ ## Paths to executables [PROGRAM_PATH] -WW_PATH = ww +WW_PATH = weightwatcher WW_CONFIG_FILE = $SP_CONFIG/mask_default/default.ww # Indicate cds client executable if no external star catalogue is available diff --git a/example/cfis/config_tile_save.mask b/example/cfis/config_tile_save.mask index 4b5fbb7f8..1de738301 100644 --- a/example/cfis/config_tile_save.mask +++ b/example/cfis/config_tile_save.mask @@ -3,7 +3,7 @@ ## Paths to executables [PROGRAM_PATH] -WW_PATH = ww +WW_PATH = weightwatcher WW_CONFIG_FILE = $SP_CONFIG/mask_default/default.ww # Indicate cds client executable if no external star catalogue is available diff --git a/example/cfis/config_tile_PiViSmVi.ini b/example/cfis/defunct/config_tile_PiViSmVi.ini similarity index 91% rename from example/cfis/config_tile_PiViSmVi.ini rename to example/cfis/defunct/config_tile_PiViSmVi.ini index 6c6f0f868..03ebf5fbb 100644 --- a/example/cfis/config_tile_PiViSmVi.ini +++ b/example/cfis/defunct/config_tile_PiViSmVi.ini @@ -58,11 +58,11 @@ TIMEOUT = 96:00:00 [PSFEX_INTERP_RUNNER] -INPUT_DIR = last:sextractor_runner_run_1 +INPUT_DIR = last:sextractor_runner_run_1, run_sp_exp_Mh:merge_headers_runner -FILE_PATTERN = sexcat +FILE_PATTERN = sexcat, log_exp_headers -FILE_EXT = .fits +FILE_EXT = .fits, .sqlite # NUMBERING_SCHEME (optional) string with numbering pattern for input files NUMBERING_SCHEME = -000-000 @@ -92,9 +92,6 @@ ME_DOT_PSF_DIR = psfex_runner # Input psf file pattern ME_DOT_PSF_PATTERN = star_split_ratio_80 -# Multi-epoch mode: Path to file with single-exposure WCS header information -ME_LOG_WCS = $SP_RUN/output/run_sp_exp_Mh/merge_headers_runner/output/log_exp_headers.sqlite - # Create vignets for tiles weights [VIGNETMAKER_RUNNER_RUN_1] @@ -153,11 +150,11 @@ OUTPUT_MODE = new # Create multi-epoch vignets for tiles corresponding to # positions on single-exposures -INPUT_DIR = last:sextractor_runner_run_1 +INPUT_DIR = last:sextractor_runner_run_1, run_sp_exp_Mh:merge_headers_runner -FILE_PATTERN = sexcat +FILE_PATTERN = sexcat, log_exp_headers -FILE_EXT = .fits +FILE_EXT = .fits, .sqlite # NUMBERING_SCHEME (optional) string with numbering pattern for input files NUMBERING_SCHEME = -000-000 @@ -185,4 +182,3 @@ PREFIX = # run outputs ME_IMAGE_DIR = split_exp_runner, split_exp_runner, split_exp_runner, sextractor_runner_run_2 ME_IMAGE_PATTERN = flag, image, weight, background -ME_LOG_WCS = $SP_RUN/output/run_sp_exp_Mh/merge_headers_runner/output/log_exp_headers.sqlite diff --git a/example/cfis/config_tile_PiViSmVi_canfar.ini b/example/cfis/defunct/config_tile_PiViSmVi_canfar.ini similarity index 90% rename from example/cfis/config_tile_PiViSmVi_canfar.ini rename to example/cfis/defunct/config_tile_PiViSmVi_canfar.ini index d9244ded0..ceb356855 100644 --- a/example/cfis/config_tile_PiViSmVi_canfar.ini +++ b/example/cfis/defunct/config_tile_PiViSmVi_canfar.ini @@ -58,11 +58,11 @@ TIMEOUT = 96:00:00 [PSFEX_INTERP_RUNNER] -INPUT_DIR = run_sp_tile_Sx:sextractor_runner +INPUT_DIR = run_sp_tile_Sx:sextractor_runner, run_sp_exp_Mh:merge_headers_runner -FILE_PATTERN = sexcat +FILE_PATTERN = sexcat, log_exp_headers -FILE_EXT = .fits +FILE_EXT = .fits, .sqlite # NUMBERING_SCHEME (optional) string with numbering pattern for input files NUMBERING_SCHEME = -000-000 @@ -92,9 +92,6 @@ ME_DOT_PSF_DIR = all:psfex_runner # Input psf file pattern ME_DOT_PSF_PATTERN = star_split_ratio_80 -# Multi-epoch mode: Path to file with single-exposure WCS header information -ME_LOG_WCS = $SP_RUN/output/run_sp_exp_Mh/merge_headers_runner/output/log_exp_headers.sqlite - # Create vignets for tiles weights [VIGNETMAKER_RUNNER_RUN_1] @@ -153,11 +150,11 @@ OUTPUT_MODE = new # Create multi-epoch vignets for tiles corresponding to # positions on single-exposures -INPUT_DIR = run_sp_tile_Sx:sextractor_runner +INPUT_DIR = run_sp_tile_Sx:sextractor_runner, run_sp_exp_Mh:merge_headers_runner -FILE_PATTERN = sexcat +FILE_PATTERN = sexcat, log_exp_headers -FILE_EXT = .fits +FILE_EXT = .fits, .sqlite # NUMBERING_SCHEME (optional) string with numbering pattern for input files NUMBERING_SCHEME = -000-000 @@ -185,4 +182,3 @@ PREFIX = # run outputs ME_IMAGE_DIR = all:split_exp_runner, all:split_exp_runner, all:split_exp_runner, all:sextractor_runner ME_IMAGE_PATTERN = flag, image, weight, background -ME_LOG_WCS = $SP_RUN/output/run_sp_exp_Mh/merge_headers_runner/output/log_exp_headers.sqlite diff --git a/pyproject.toml b/pyproject.toml index 0c2114092..4a817db0d 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -8,7 +8,8 @@ authors = [ { name = "Axel Guinot", email = "axel.guinot@cea.fr" }, { name = "Martin Kilbinger", email = "martin.kilbinger@cea.fr" } ] -license = { "file" = "LICENSE" } +license = "MIT" +license-files = ["LICENSE"] requires-python = ">=3.12" # Abstract runtime constraints. Exact versions live in `uv.lock` — pyproject # is the single source of truth for *what* shapepipe needs, the lockfile for @@ -41,9 +42,7 @@ dependencies = [ "termcolor", "tqdm>=4.63", "vos>=3.6", - # ngmix is pinned to Axel's stable_version branch until upstream ngmix - # absorbs the fixes — tracked separately, do not modernize this line. - "ngmix @ git+https://github.com/aguinot/ngmix@stable_version", + "ngmix>=2.4", ] @@ -78,11 +77,29 @@ fitsio = ["fitsio"] dev = ["shapepipe[doc,jupyter,lint,release,test,fitsio]"] [project.scripts] -shapepipe_run = "shapepipe.shapepipe_run:main" -summary_run = "shapepipe.summary_run:main" -canfar_submit_job = "shapepipe.canfar_run:run_job" -canfar_monitor = "shapepipe.canfar_run:run_log" -canfar_monitor_log = "shapepipe.canfar_run:run_monitor_log" +shapepipe_run = "shapepipe.shapepipe_run:main" +summary_run = "shapepipe.summary_run:main" +canfar_submit_job = "shapepipe.canfar_run:run_job" +canfar_monitor = "shapepipe.canfar_run:run_log" +canfar_monitor_log = "shapepipe.canfar_run:run_monitor_log" + +[tool.uv] +# shapepipe targets Linux only; skip Windows/macOS wheel resolution +environments = ["sys_platform == 'linux'"] + +[tool.uv.sources] +ngmix = { git = "https://github.com/esheldon/ngmix", tag = "v2.4.0" } + +[tool.setuptools] +script-files = [ + "scripts/python/update_runs_log_file.py", + "scripts/sh/init_run_v2.0.sh", + "scripts/sh/run_job_sp_canfar_v2.0.bash", + "scripts/sh/job_sp_canfar_v2.0.bash", +] + +[tool.setuptools.packages.find] +where = ["src"] [tool.pytest.ini_options] addopts = "--verbose --cov=shapepipe" diff --git a/scripts/jupyter/test_centroid_shift.py b/scripts/jupyter/test_centroid_shift.py new file mode 100644 index 000000000..1940509e3 --- /dev/null +++ b/scripts/jupyter/test_centroid_shift.py @@ -0,0 +1,688 @@ +#!/usr/bin/env python +# coding: utf-8 + +# In[14]: + + +import numpy as np +import galsim + +import ngmix + +from shapepipe.modules.ngmix_package.ngmix import ( + get_noise, +) + +#print("Use shapepipe version of metacal") +#from shapepipe.modules.ngmix_package.ngmix import do_ngmix_metacal + +print("Use this version of metacal") + +from modopt.math.stats import sigma_mad +from ngmix import Observation, ObsList +from numpy.random import uniform as urand + + +# ### Simu + +# In[15]: + + +def make_data(rng, shear, noise=1e-5, n_epochs=1, share_shift=False): + """ + simulate an exponential object with moffat psf + + Parameters + ---------- + rng: np.random.RandomState + The random number generator + noise: float + Noise for the image + shear: (g1, g2) + The shear in each component + + Returns + ------- + Lists + """ + + psf_noise = 1.0e-6 + + img_size = 201 + scale = 0.1857 + wcs = galsim.PixelScale(scale) + + psf_fwhm = 0.55 + gal_hlr = 0.3 + + if share_shift: + dy, dx = rng.uniform(low=-scale/2, high=scale/2, size=2) + + + gals = [] + psfs = [] + psfs_sigmas = [] + weights = [] + flags = [] + jacob_lists = [] + for epoch in range(n_epochs): + if not share_shift: + dy, dx = rng.uniform(low=-scale/2, high=scale/2, size=2) + psf = galsim.Moffat( + beta=2.5, fwhm=psf_fwhm, + ) + + obj0 = galsim.Exponential( + half_light_radius=gal_hlr, + flux=1000, + ).shear( + g1=shear[0], + g2=shear[1], + ) + + obj = galsim.Convolve(psf, obj0) + obj = obj.shift(dx, dy) + + psf_im_ = psf.drawImage(nx=img_size, ny=img_size, wcs=wcs) + s = galsim.hsm.FindAdaptiveMom(psf_im_) + psfs_sigmas.append(s.moments_sigma) + psf_im = psf_im_.array.astype(np.float64) + im = obj.drawImage(nx=img_size, ny=img_size, wcs=wcs).array.astype(np.float64) + + psf_im += rng.normal(scale=psf_noise, size=psf_im.shape) + im += rng.normal(scale=noise, size=im.shape) + + + wt = im*0 + 1.0/noise**2 + flag = im*0 + + weights.append(wt) + psfs.append(psf_im) + flags.append(flag) + gals.append(im) + jacob_lists.append(wcs.jacobian()) + + return gals, psfs, psfs_sigmas, weights, flags, jacob_lists + + +# ### From shapepipe + +# In[16]: + + +def get_prior(pixel_scale, rng=None): + """Get Prior. + + Return prior for the different parameters. + + Returns + ------- + ngmix.priors + Priors for the different parameters + + """ + if rng is None: + rng = np.random.default_rng() + + # Prior on ellipticity. Details do not matter, as long + # as it regularizes the fit. From Bernstein & Armstrong 2014 + g_sigma = 0.4 + g_prior = ngmix.priors.GPriorBA(g_sigma, rng=rng) + + # 2-d Gaussian prior on the center row and column center + # (relative to the center of the jacobian, which + # would be zero) and the sigma of the Gaussians. + # Units same as jacobian, probably arcsec + row, col = 0.0, 0.0 + row_sigma, col_sigma = pixel_scale, pixel_scale + cen_prior = ngmix.priors.CenPrior(row, col, row_sigma, col_sigma, rng=rng) + + # Size prior. Instead of flat, two-sided error function (TwoSidedErf) + # could be used + Tminval = -10.0 # arcsec squared + Tmaxval = 1.0e6 + T_prior = ngmix.priors.FlatPrior(Tminval, Tmaxval, rng=rng) + + # Flux prior. Bounds need to make sense for + # images in question + Fminval = -1.0e4 + Fmaxval = 1.0e9 + F_prior = ngmix.priors.FlatPrior(Fminval, Fmaxval, rng=rng) + + # Joint prior, combine all individual priors + prior = ngmix.joint_prior.PriorSimpleSep( + cen_prior, g_prior, T_prior, F_prior + ) + + return prior + + +# In[17]: + + +def make_galsimfit(obs, model, guess0, prior=None, ntry=5): + """Make GalSim Fit. + + Fit image using simple GalSim model. + + Parameters + ---------- + obs : ngmix.observation.Observation + Image to fit + model : str + Model for fit + guess0 : numpy.ndarray + Parameters of first model guess + prior : ngmix.prior, optional + Prior for fit paraemeters + ntry : int, optional + Number of tries for fit, the default is ``5`` + + Returns + ------- + dict + Results + + Raises + ------ + ngmix.BootGalFailure + Failure to bootstrap galaxy + + """ + limit = 0.1 + + guess = np.copy(guess0) + fres = {} + for it in range(ntry): + guess[0:5] += urand(low=-limit, high=limit) + guess[5:] *= 1 + urand(low=-limit, high=limit) + fres["flags"] = 1 + try: + fitter = ngmix.fitting.GalsimFitter(model, prior=prior) + fres = fitter.go(obs, guess) + if fres["flags"] == 0 and "T" not in fres: + fres["T"] = fres["pars"][4] + fres["T_err"] = np.sqrt(fres["pars_cov"][4, 4]) + except: + continue + + if fres["flags"] == 0: + break + + if fres["flags"] != 0: + raise ngmix.gexceptions.BootGalFailure( + "Failed to fit galaxy image with galsimfit" + ) + + fres["ntry"] = it + 1 + + return fres + + +# In[18]: + + +def do_ngmix_metacal( + gals, psfs, psfs_sigma, weights, flags, jacob_list, prior, pixel_scale, sig_noise=None, +): + """Do Ngmix Metacal. + + Perform the metacalibration on a multi-epoch object and return the joint + shape measurement with NGMIX. + + Parameters + ---------- + gals : list + List of the galaxy vignets + psfs : list + List of the PSF vignets + psfs_sigma : list + List of the sigma PSFs + weights : list + List of the weight vignets + flags : list + List of the flag vignets + jacob_list : list + List of the Jacobians + prior : ngmix.priors + Priors for the fitting parameters + pixel_scale : float + pixel scale in arcsec + + Returns + ------- + dict + Dictionary containing the results of NGMIX metacal + + """ + n_epoch = len(gals) + + if n_epoch == 0: + raise ValueError("0 epoch to process") + + # Make observation + gal_obs_list = ObsList() + T_guess_psf = [] + psf_res_gT = { + "g_PSFo": np.array([0.0, 0.0]), + "g_err_PSFo": np.array([0.0, 0.0]), + "T_PSFo": 0.0, + "T_err_PSFo": 0.0, + } + gal_guess = [] + gal_guess_flag = True + wsum = 0 + for n_e in range(n_epoch): + + psf_jacob = ngmix.Jacobian( + row=(psfs[0].shape[0] - 1) / 2, + col=(psfs[0].shape[1] - 1) / 2, + wcs=jacob_list[n_e], + ) + + psf_obs = Observation(psfs[n_e], jacobian=psf_jacob) + + psf_T = psfs_sigma[n_e] * 1.17741 * pixel_scale + + weight_map = np.copy(weights[n_e]) + weight_map[np.where(flags[n_e] != 0)] = 0.0 + weight_map[weight_map != 0] = 1 + + psf_guess = np.array([0.0, 0.0, 0.0, 0.0, psf_T, 1.0]) + try: + psf_res = make_galsimfit(psf_obs, "gauss", psf_guess) + except Exception: + continue + + # Gal guess via adaptive moments + try: + _gim = galsim.Image(gals[n_e], scale=pixel_scale) + _hsm = galsim.hsm.FindAdaptiveMom(_gim, strict=False) + if _hsm.error_message != "": + raise galsim.hsm.GalSimHSMError(_hsm.error_message) + _cen = _hsm.moments_centroid - _gim.center # pixels (centroid_unit="img") + _size = 2 * (_hsm.moments_sigma * pixel_scale) ** 2 # T in arcsec^2 + gal_guess_tmp = np.array([_cen.x, _cen.y, 0.0, 0.0, _size, _hsm.moments_amp]) + except Exception: + gal_guess_flag = False + gal_guess_tmp = np.array([0.0, 0.0, 0.0, 0.0, 1, 100]) + + # Recenter jacobian if necessary + gal_jacob = ngmix.Jacobian( + row=(gals[n_e].shape[0] - 1) / 2 + gal_guess_tmp[1], + col=(gals[n_e].shape[1] - 1) / 2 + gal_guess_tmp[0], + wcs=jacob_list[n_e], + ) + + # Noise handling + if sig_noise is None: + if gal_guess_flag: + sig_noise = get_noise( + gals[n_e], + weight_map, + gal_guess_tmp, + pixel_scale, + ) + else: + sig_noise = sigma_mad(gals[n_e]) + + noise_img = np.random.randn(*gals[n_e].shape) * sig_noise + noise_img_gal = np.random.randn(*gals[n_e].shape) * sig_noise + + gal_masked = np.copy(gals[n_e]) + if len(np.where(weight_map == 0)[0]) != 0: + gal_masked[weight_map == 0] = noise_img_gal[weight_map == 0] + + weight_map *= 1 / sig_noise**2 + + # Original PSF fit + w_tmp = np.sum(weight_map) + psf_res_gT["g_PSFo"] += psf_res["g"] * w_tmp + psf_res_gT["g_err_PSFo"] += ( + np.array([psf_res["pars_err"][2], psf_res["pars_err"][3]]) * w_tmp + ) + psf_res_gT["T_PSFo"] += psf_res["T"] * w_tmp + psf_res_gT["T_err_PSFo"] += psf_res["T_err"] * w_tmp + wsum += w_tmp + + gal_obs = Observation( + gal_masked, + weight=weight_map, + jacobian=gal_jacob, + psf=psf_obs, + noise=noise_img, + ) + + if gal_guess_flag: + # gal_guess_tmp[:2] = 0 + final_gal_guess = np.copy(gal_guess_tmp) + final_gal_guess[:2] = 0 + gal_guess.append(final_gal_guess) + + gal_obs_list.append(gal_obs) + T_guess_psf.append(psf_T) + gal_guess_flag = True + + if wsum == 0: + raise ZeroDivisionError("Sum of weights = 0, division by zero") + + # Normalize PSF fit output + for key in psf_res_gT.keys(): + psf_res_gT[key] /= wsum + + # Gal guess handling + fail_get_guess = False + if len(gal_guess) == 0: + fail_get_guess = True + gal_pars = [0.0, 0.0, 0.0, 0.0, 1, 100] + else: + gal_pars = np.mean(gal_guess, 0) + + psf_model = "gauss" + gal_model = "gauss" + + # metacal specific parameters + metacal_pars = { + "types": ["noshear", "1p", "1m"], + "step": 0.01, + "psf": "gauss", + "fixnoise": True, + "use_noise_image": True, + } + + Tguess = np.mean(T_guess_psf) + + # retry the fit twice + obs_dict_mcal = ngmix.metacal.get_all_metacal(gal_obs_list, **metacal_pars) + res = {"mcal_flags": 0} + + ntry = 5 + + for key in sorted(obs_dict_mcal): + + fres = make_galsimfit( + obs_dict_mcal[key], gal_model, gal_pars, prior=prior + ) + # print(fres["pars"][0:2]) + # fres = make_fit( + # obs_dict_mcal[key], gal_model, gal_pars, prior=prior + # ) + + res["mcal_flags"] |= fres["flags"] + tres = {} + + for name in fres.keys(): + tres[name] = fres[name] + tres["flags"] = fres["flags"] + + wsum = 0 + Tpsf_sum = 0 + gpsf_sum = np.zeros(2) + npsf = 0 + for obs in obs_dict_mcal[key]: + + if hasattr(obs, "psf_nopix"): + try: + psf_res = make_galsimfit( + obs.psf_nopix, + psf_model, + np.array([0.0, 0.0, 0.0, 0.0, Tguess, 1.0]), + ntry=ntry, + ) + except Exception: + continue + g1, g2 = psf_res["g"] + T = psf_res["T"] + else: + try: + psf_res = make_galsimfit( + obs.psf, + psf_model, + np.array([0.0, 0.0, 0.0, 0.0, Tguess, 1.0]), + ) + except Exception: + continue + g1, g2 = psf_res["g"] + T = psf_res["T"] + + # TODO we sometimes use other weights + twsum = obs.weight.sum() + + wsum += twsum + gpsf_sum[0] += g1 * twsum + gpsf_sum[1] += g2 * twsum + Tpsf_sum += T * twsum + npsf += 1 + + tres["gpsf"] = gpsf_sum / wsum + tres["Tpsf"] = Tpsf_sum / wsum + + res[key] = tres + + # result dictionary, keyed by the types in metacal_pars above + metacal_res = res + + metacal_res.update(psf_res_gT) + metacal_res["moments_fail"] = fail_get_guess + + return metacal_res + + +# ### Extra func modified from: [metacal example](https://github.com/esheldon/ngmix/blob/master/examples/metacal/metacal.py) + +# In[19]: + + +def progress(total, miniters=1): + last_print_n = 0 + last_printed_len = 0 + sl = str(len(str(total))) + mf = '%'+sl+'d/%'+sl+'d %3d%%' + for i in range(total): + yield i + + num = i+1 + if i == 0 or num == total or num - last_print_n >= miniters: + meter = mf % (num, total, 100*float(num) / total) + nspace = max(last_printed_len-len(meter), 0) + + print('\r'+meter+' '*nspace, flush=True, end='') + last_printed_len = len(meter) + if i > 0: + last_print_n = num + + print(flush=True) + + +# In[20]: + + +def make_struct(res, shear_type): + """ + make the data structure + + Parameters + ---------- + res: dict + With keys 's2n', 'e', and 'T' + obs: ngmix.Observation + The observation for this shear type + shear_type: str + The shear type + + Returns + ------- + 1-element array with fields + """ + dt = [ + ('flags', 'i4'), + ('shear_type', 'U7'), + ('s2n', 'f8'), + ('g', 'f8', 2), + ('T', 'f8'), + ('Tpsf', 'f8'), + ] + data = np.zeros(1, dtype=dt) + data['shear_type'] = shear_type + data['flags'] = res['flags'] + if res['flags'] == 0: + s2n = res["flux"]/res["flux_err"] + data['s2n'] = s2n + # for moments we are actually measureing e, the elliptity + data['g'] = res['g'] + data['T'] = res['T'] + else: + data['s2n'] = np.nan + data['g'] = np.nan + data['T'] = np.nan + data['Tpsf'] = np.nan + + # we only have one epoch and band, so we can get the psf T from the + # observation rather than averaging over epochs/bands + data['Tpsf'] = res["Tpsf"] + + return data + + +# In[21]: + + +def select(data, shear_type): + """ + select the data by shear type and size + + Parameters + ---------- + data: array + The array with fields shear_type and T + shear_type: str + e.g. 'noshear', '1p', etc. + + Returns + ------- + array of indices + """ + + w, = np.where( + (data['flags'] == 0) & (data['shear_type'] == shear_type) + ) + return w + + +# In[22]: + + +gals, psfs, psfs_sigmas, weights, flags, jacob_lists = make_data(rng=np.random.RandomState(10), noise=1.e-10, shear=(0.02, 0.0), n_epochs=3, share_shift=False) + + +# In[23]: + + +pixel_scale = 0.1857 +prior = get_prior(pixel_scale, rng=np.random.default_rng(42)) + + +# In[24]: + + +res = do_ngmix_metacal(gals, psfs, psfs_sigmas, weights, flags, jacob_lists, prior=prior, pixel_scale=pixel_scale, sig_noise=1e-10) + + +# In[25]: + + +sig_noise = 1e-10 +ntrial = 50 +seed = 42 +shear_types = ["noshear", "1p", "1m"] +rng = np.random.RandomState(seed) +seeds = rng.randint(0, 2**30, size=ntrial) + +dlist_p_ = [] +dlist_m_ = [] +for i in progress(ntrial, miniters=10): + + d_ = [] + for shear_true in [(0.02, 0.00), (-0.02, 0.00)]: + + gals, psfs, psfs_sigmas, weights, flags, jacob_lists = make_data(rng=np.random.RandomState(seeds[i]), noise=sig_noise, shear=shear_true, n_epochs=3, share_shift=False) + try: + resdict = do_ngmix_metacal(gals, psfs, psfs_sigmas, weights, flags, jacob_lists, prior=prior, pixel_scale=pixel_scale, sig_noise=sig_noise) + stt = [] + for stype in shear_types: + st = make_struct(res=resdict[stype], shear_type=stype) + stt.append(st) + except: + continue + d_.append(np.hstack(stt)) + if len(d_) != 2: + continue + dlist_p_.extend(d_[0]) + dlist_m_.extend(d_[1]) + +print() + +data_p = np.hstack(dlist_p_) +data_m = np.hstack(dlist_m_) + +# P shear +w = select(data=data_p, shear_type='noshear') +w_1p = select(data=data_p, shear_type='1p') +w_1m = select(data=data_p, shear_type='1m') + +g_p = data_p['g'][w] +g1_1p_p = data_p['g'][w_1p, 0] +g1_1m_p = data_p['g'][w_1m, 0] +R11_p = np.atleast_2d((g1_1p_p - g1_1m_p)/0.02).T + +# M shear +w = select(data=data_m, shear_type='noshear') +w_1p = select(data=data_m, shear_type='1p') +w_1m = select(data=data_m, shear_type='1m') + +g_m = data_m['g'][w] +g1_1p_m = data_m['g'][w_1p, 0] +g1_1m_m = data_m['g'][w_1m, 0] +R11_m = np.atleast_2d((g1_1p_m - g1_1m_m)/0.02).T + +shear_ = (g_p - g_m) / (R11_p + R11_m) +shear = np.mean(shear_, axis=0) +shear_err = np.std(shear_, axis=0)/np.sqrt(len(shear_)) + +m = shear[0]/0.02-1 +merr = shear_err[0]/0.02 + +s2n = data_p['s2n'][w].mean() + +print('S/N: %g' % s2n) +print('R11: %g %g' % (np.mean(R11_p), np.mean(R11_m))) +print('m[1e-3, 3sigmas]: %g +/- %g (99.7%% conf)' % (m/1e-3, merr*3/1e-3)) +print('c[1e-5, 3sigmas]: %g +/- %g (99.7%% conf)' % (shear[1]/1e-5, shear_err[1]*3/1e-5)) + + +# # Below is from Axel + +# ## Before the fix +# +# S/N: 342.343 +# +# R11: 0.926435 0.926423 +# +# m[1e-3, 3sigmas]: -27.8983 +/- 6.50568 (99.7% conf) +# +# c[1e-5, 3sigmas]: 0.0068871 +/- 0.18067 (99.7% conf) + +# ## After the fix +# +# 50/50 100% +# +# S/N: 1006.71 +# +# R11: 0.922675 0.922739 +# +# m[1e-3, 3sigmas]: 0.308435 +/- 0.597766 (99.7% conf) +# +# c[1e-5, 3sigmas]: 0.0981643 +/- 0.435279 (99.7% conf) +# + +# diff --git a/scripts/python/check_nobj_ngmix_mc.py b/scripts/python/check_nobj_ngmix_mc.py deleted file mode 100755 index cfe11d1f8..000000000 --- a/scripts/python/check_nobj_ngmix_mc.py +++ /dev/null @@ -1,113 +0,0 @@ -#!/usr/bin/env python - -import os -import glob -from astropy.io import fits - -# Base directory for the tile runs -tile_runs_dir = "tile_runs" - - -def get_naxis2_value(file_path): - """Get the NAXIS2 value from HDU #1 of a FITS file.""" - try: - hdu_list = fits.open(file_path) - except: - raise OSError(f"problem with opening {file_path}") - - try: - return hdu_list[1].header.get("NAXIS2", None) - except: - raise IndexError(f"problem with {file_path} header") - - hdu_list.close() - - -# Iterate through directories -for ID in os.listdir(tile_runs_dir): - id_path = os.path.join(tile_runs_dir, ID, "output") - - # Check if ID has the correct format - if not os.path.isdir(id_path): # or not ID.replace(".", "", 1).isdigit(): - print(f"{ID} -- path {id_path} not found") - continue - - IDx = ID.replace(".", "-") - - # Define file paths - ngmix_file_pattern = os.path.join( - id_path, - f"run_sp_Ms_202*/merge_sep_cats_runner/output/ngmix-{IDx}.fits", - ) - mc_file_pattern = os.path.join( - id_path, - f"run_sp_Mc_202*/make_cat_runner/output/final_cat-{IDx}.fits", - ) - - # Resolve file names using glob to handle wildcard - ngmix_files = [f for f in glob.glob(ngmix_file_pattern)] - mc_files = [f for f in glob.glob(mc_file_pattern)] - - if not ngmix_files: - print(f"{ID} -- ngmix cats {ngmix_file_pattern} not found") - continue - if not mc_files: - print(f"{ID} -- mc cats not found {mc_file_pattern}") - continue - - # Get newest files - ngmix_file = max(ngmix_files, key=lambda f: os.path.getmtime(f)) - mc_file = max(mc_files, key=lambda f: os.path.getmtime(f)) - - # Get NAXIS2 values - ngmix_naxis2 = get_naxis2_value(ngmix_file) - mc_naxis2 = get_naxis2_value(mc_file) - - # Look at separate ngmix cats - sep_ngmix_file_pattern = os.path.join( - id_path, - f"run_sp_tile_ngmix_Ng*/ngmix_runner/output/ngmix-{IDx}.fits", - ) - sep_ngmix_files = [f for f in glob.glob(sep_ngmix_file_pattern)] - sep_ngmix_file = max(sep_ngmix_files, key=lambda f: os.path.getmtime(f)) - - if not sep_ngmix_files: - raise ValueError(f"No separate ngmix files found for ID {ID}") - sep_naxis2 = 0 - for sep_ngmix_file in sep_ngmix_files: - sep_naxis2 += get_naxis2_value(sep_ngmix_file) - - if ngmix_naxis2 is None: - print(f"{ID} -- no NAXIS2 keyword found in ngmix cat {ngmix_file}") - continue - if mc_naxis2 is None: - print(f"{ID} -- no NAXIS2 keyword found in mc cat") - continue - - # Check run time of 128, 256, and 512 jobs - if ( - os.path.getmtime(ngmix_file) > os.path.getmtime(mc_file) - or os.path.getmtime(mc_file) < os.path.getmtime(sep_ngmix_file) - ): - print(f"{ID} -- mc, sep, and/or merged ngmix file out of order") - - # Compare values and output ID if they differ - elif ngmix_naxis2 != sep_naxis2: - print( - f"{ID} -- ngmix differ between sep {sep_naxis2} and merged" - + f" {ngmix_naxis2}" - ) - - elif ngmix_naxis2 != mc_naxis2: - ratio = float(ngmix_naxis2) / float(mc_naxis2) - if ratio < 0.75: - - print( - f"{ID} -- NAXIS2 differ {ngmix_naxis2} / {mc_naxis2} =" - + f" {ratio:.3f} (sum {len(sep_ngmix_files)} sep_ng =" - + f" {sep_naxis2})" - ) - else: - print(f"{ID} -- similar NAXIS2, {ngmix_naxis2} / {mc_naxis2} = {ratio:.3f}") - else: - print(f"{ID} -- identcal NAXIS2 {ngmix_naxis2} {mc_naxis2}") diff --git a/scripts/python/count_shdu_special.py b/scripts/python/count_shdu_special.py deleted file mode 100755 index dfe9f7d17..000000000 --- a/scripts/python/count_shdu_special.py +++ /dev/null @@ -1,57 +0,0 @@ -#!/usr/bin/env python - -import os -import re -import sys - -ID = sys.argv[1] -print(f"Checking tile ID {ID}...") - -# Base directory for the tile runs -tile_runs_dir = "tile_runs" - -sum_dir = "summary" -specials = ["special_job_32_setools_runner_0", "special_job_32_setools_runner_1"] - - -shdu_IDs = [] -print("Going through links...") -#3for ID in os.listdir(tile_runs_dir): -if True: - id_path = os.path.join(tile_runs_dir, ID, "output") - - for filename in os.listdir(id_path): - if ( - filename.startswith("run_sp_exp_SxSePsf") - and os.path.islink(os.path.join(id_path, filename)) - ): - symlink_path = os.path.join(id_path, filename) - target_path = os.readlink(symlink_path) - - pattern = r"/exp_runs/([^/]+)/output/" - - match = re.search(pattern, target_path) - if match: - shdu_IDs.append(match.group(1)) - else: - print(f"{filename} -> No match in target path: {target_path}") - -if len(shdu_IDs) == 0: - print("No shdus found, exiting") - sys.exit(1) -else: - print(f"Found {len(shdu_IDs)} links in dir {id_path}") - - -print("Going through special files...") -count = 0 -for special in specials: - print(f"special {special}...") - path = f"{sum_dir}/{special}.txt" - with open(path, "r") as f: - content = f.read() - for shdu_ID in shdu_IDs: - if re.search(shdu_ID, content): - count += 1 - -print(f"Found {count} / {len(shdu_IDs)} = {count / len(shdu_IDs):.2%}") diff --git a/scripts/python/create_sample_results.py b/scripts/python/create_sample_results.py deleted file mode 100755 index 0e0223ffe..000000000 --- a/scripts/python/create_sample_results.py +++ /dev/null @@ -1,323 +0,0 @@ -#!/usr/bin/env python - -"""Script create_sample_results.py - -Create directory with links to results for a given (sub-)sample. - -:Author: Martin Kilbinger - -:Date: 07/2020 -""" - -import re -import os -import sys -import glob -import copy -import io -from contextlib import redirect_stdout -from optparse import OptionParser -from shapepipe.utilities import cfis -from shapepipe.utilities.file_system import mkdir - - -def params_default(): - """Set default parameter values. - - Parameters - ---------- - None - - Returns - ------- - p_def: class cfis.param - parameter values - """ - - p_def = cfis.param(psf="mccd") - - return p_def - - -def parse_options(p_def): - """Parse command line options. - - Parameters - ---------- - p_def: class cfis.param - parameter values - - Returns - ------- - options: tuple - Command line options - args: str - Command line string - """ - - usage = "%prog [OPTIONS]" - parser = OptionParser(usage=usage) - - # I/O - parser.add_option( - "", - "--input_IDs", - dest="input_IDs", - type="string", - help="input tile ID file specifying sample", - ) - parser.add_option( - "-i", - "--input_dir", - dest="input_dir", - type="string", - help="input directory name", - ) - parser.add_option( - "-o", - "--output_dir", - dest="output_dir", - type="string", - help="output directory name", - ) - - # Misc - parser.add_option( - "-p", - "--psf", - dest="psf", - type="string", - default=p_def.psf, - help=f"PSF model, one in ['psfex'|'mccd'], default='{p_def.psf}'", - ) - - # Control - parser.add_option( - "-v", - "--verbose", - dest="verbose", - action="store_true", - help="verbose output", - ) - - options, args = parser.parse_args() - - return options, args - - -def check_options(options): - """Check command line options. - - Parameters - ---------- - options: tuple - Command line options - - Returns - ------- - erg: bool - Result of option check. False if invalid option value. - """ - - if options.input_IDs is None: - print("No input ID file list given (option '--input_IDs')") - return False - if options.input_dir is None: - print("No input directory name given (option '--input_dir')") - return False - if options.output_dir is None: - print("No output directory name given (option '--output_dir')") - return False - - return True - - -def update_param(p_def, options): - """Return default parameter, updated and complemented according to options. - - Parameters - ---------- - p_def: class param - parameter values - optiosn: tuple - command line options - - Returns - ------- - param: class param - updated paramter values - """ - - param = copy.copy(p_def) - - # Update keys in param according to options values - for key in vars(param): - if key in vars(options): - setattr(param, key, getattr(options, key)) - - # Add remaining keys from options to param - for key in vars(options): - if not key in vars(param): - setattr(param, key, getattr(options, key)) - - # Do extra stuff if necessary - - return param - - -def read_ID_list(input_ID_path, verbose=False): - """Return input ID list from file. - - Parameters - ---------- - input_ID_path: str - input ID file path - verbose: bool, optional, default=False - verbose output if True - - Returns - ------- - input_IDs: list of str - input ID list - """ - - if verbose: - print("Reading input ID list...") - - input_IDs = [] - with open(input_ID_path) as f: - for line in f: - input_IDs.append(line.rstrip()) - - if verbose: - print("{} IDs found in input file".format(len(input_IDs))) - - return input_IDs - - -def create_links( - input_dir, output_dir, input_IDs, result_base_names, verbose=False -): - """Create symbolic links to result files corresponding to (sub-)sample. - - Parameters - ---------- - input_dir: str - input directory - output_dir: str - output directory - input_IDs: list of str - tile ID list - results_base_names: list of str - file base names - verbose: bool, optional, default=False - verbose output if True - """ - - if verbose: - print("Creating links...") - - n_total = {} - n_created = 0 - n_existed = 0 - for ID in input_IDs: - n_total[ID] = 0 - for base in result_base_names: - name = "{}_{}.tgz".format(base, ID) - src = "{}/{}".format(os.path.abspath(input_dir), name) - link_name = "{}/{}".format(output_dir, name) - - # if verbose: - # print('Creating link {} <- {}'.format(src, link_name)) - - if not os.path.exists(src): - # raise IOError('Source file \'{}\' does not exist'.format(src)) - print("Source file '{}' does not exist, skipping".format(src)) - elif not os.path.exists(link_name): - os.symlink(src, link_name) - n_created = n_created + 1 - else: - n_existed = n_existed + 1 - - n_total[ID] = n_total[ID] + 1 - - n_expected = len(input_IDs) * len(result_base_names) - if verbose: - print("{:5d} links created".format(n_created)) - print("{:5d} links existed already".format(n_existed)) - print( - "{:5d}/{} links available now".format( - n_created + n_existed, n_expected - ) - ) - n_tot = sum(n_total.values()) - print("{:5d} as cross-check".format(n_tot)) - - -def main(argv=None): - - # Set default parameters - p_def = params_default() - - # Command line options - options, args = parse_options(p_def) - # Without option parsing, this would be: args = argv[1:] - - if check_options(options) is False: - return 1 - - param = update_param(p_def, options) - - # Save calling command - cfis.log_command(argv) - if param.verbose: - cfis.log_command(argv, name="sys.stdout") - - ### Start main program ### - - if param.verbose: - print("Start of program {}".format(os.path.basename(argv[0]))) - - input_IDs = read_ID_list(param.input_IDs, verbose=param.verbose) - - result_base_names = [ - "final_cat", - "logs", - "setools_mask", - "setools_stat", - "setools_plot", - "pipeline_flag", - ] - if param.psf == "psfex": - result_base_names.append("psfex_interp_exp") - elif param.psf == "mccd": - result_base_names.append("mccd_fit_val_runner") - - if os.path.isdir(param.output_dir): - if param.verbose: - print( - "Directory {} already exists, continuing...".format( - param.output_dir - ) - ) - else: - mkdir(param.output_dir) - - create_links( - param.input_dir, - param.output_dir, - input_IDs, - result_base_names, - verbose=param.verbose, - ) - - ### End main program - - if param.verbose: - print("End of program {}".format(os.path.basename(argv[0]))) - - return 0 - - -if __name__ == "__main__": - sys.exit(main(sys.argv)) diff --git a/scripts/python/fitting.py b/scripts/python/fitting.py new file mode 100644 index 000000000..84c48a8d5 --- /dev/null +++ b/scripts/python/fitting.py @@ -0,0 +1,265 @@ +""" +example fitting an exponential model. The psf is fit +using a set of coelliptical gaussians + +Despite this being a fit to single image we use the full fitting framework. We +use a generic bootstrapper to "bootstrap" the process, first fitting the psf +and then a psf flux for the object. Then the object is fit including the PSF, +so the inferred parameters are "pre-psf". The guess for the fit is made +based on the psf flux fit and a generic rough guess for size. + +To faciliate this bootstrapping process we define the fitters for psf and +object as well as objects to provide guesses. + +Bootstrappers are especially useful when you will perform the same fit on many +objects. + +A run of the code should produce output something like thid + + > python fitting_bd_empsf.py + + S/N: 920.5078121454815 + true flux: 100 meas flux: 95.3763 +/- 0.653535 (99.7% conf) + true g1: 0.05 meas g1: 0.0508 +/- 0.00960346 (99.7% conf) + true g2: -0.02 meas g2: -0.0261123 +/- 0.0095837 (99.7% conf) + true fracdev: 0.5 meas fracdev: 0.514028 +/- 0.011873 (99.7% conf) +""" +import numpy as np +import galsim +import ngmix + + +def main(): + + args = get_args() + rng = np.random.RandomState(args.seed) + + nepoch=3 + obs, obj_pars = make_data(rng=rng, noise=args.noise) + gal_obs_list = ngmix.observation.ObsList() + for i in np.arange(nepoch): + gal_obs_list.append(obs) + print(len(gal_obs_list)) + # fit the object to an exponential disk + prior = get_prior(rng=rng, scale=obs.jacobian.scale) + # fit using the levenberg marquards algorithm + fitter = ngmix.fitting.Fitter(model='gauss', prior=prior) + # make parameter guesses based on a psf flux and a rough T + guesser = ngmix.guessers.TPSFFluxAndPriorGuesser( + rng=rng, + T=0.25, + prior=prior, + ) + + # psf fitting with coelliptical gaussians + psf_ngauss = 1 + psf_fitter = fitter + # special guesser for coelliptical gaussians + psf_guesser = ngmix.guessers.TFluxGuesser(rng=rng, + T=0.25, + prior=prior, + flux=100, + + ) + # this runs the fitter. We set ntry=2 to retry the fit if it fails + psf_runner = ngmix.runners.PSFRunner( + fitter=psf_fitter, guesser=psf_guesser, + ntry=2, + ) + runner = ngmix.runners.Runner( + fitter=fitter, guesser=guesser, + ntry=2, + ) + + metacal_pars = { + 'types': ['noshear', '1p', '1m', '2p', '2m'], + 'step': 0.01, + 'psf': 'fitgauss', + 'fixnoise': True, + 'use_noise_image': False + } + # this bootstraps the process, first fitting psfs then the object + boot = ngmix.metacal.MetacalBootstrapper( + runner=runner, + psf_runner=psf_runner, + rng=rng + ) + + res, obsdict = boot.go(gal_obs_list) + print(res.keys()) + print(res['noshear'].keys()) + print('psf_options',obsdict['noshear'][0].weight.sum()) + #print('psf_options',obsdict['noshear'].psf.meta['result'].keys()) + print('S/N:', res['noshear']['s2n']) + print('true flux: %g meas flux: %g +/- %g (99.7%% conf)' % ( + obj_pars['flux'], res['noshear']['flux'], res['noshear']['flux_err']*3, + )) + print('true g1: %g meas g1: %g +/- %g (99.7%% conf)' % ( + obj_pars['g1'], res['noshear']['g'][0], res['noshear']['g_err'][0]*3, + )) + print('true g2: %g meas g2: %g +/- %g (99.7%% conf)' % ( + obj_pars['g2'], res['noshear']['g'][1], res['noshear']['g_err'][1]*3, + )) + print( + "Delta g / sig g = (" + + f"{(obj_pars['g1'] - res['noshear']['g'][0]) / res['noshear']['g_err'][0]:.2f}," + + f" {(obj_pars['g2'] - res['noshear']['g'][1]) / res['noshear']['g_err'][1]:.2f})" + ) + + if args.show: + try: + import images + except ImportError: + from espy import images + + imfit = res.make_image() + + images.compare_images(obs.image, imfit) + + +def get_prior(*, rng, scale, T_range=None, F_range=None, nband=None): + """ + get a prior for use with the maximum likelihood fitter + + Parameters + ---------- + rng: np.random.RandomState + The random number generator + scale: float + Pixel scale + T_range: (float, float), optional + The range for the prior on T + F_range: (float, float), optional + Fhe range for the prior on flux + nband: int, optional + number of bands + """ + if T_range is None: + T_range = [-1.0, 1.e3] + if F_range is None: + F_range = [-100.0, 1.e9] + + g_prior = ngmix.priors.GPriorBA(sigma=0.1, rng=rng) + cen_prior = ngmix.priors.CenPrior( + cen1=0, cen2=0, sigma1=scale, sigma2=scale, rng=rng, + ) + T_prior = ngmix.priors.FlatPrior(minval=T_range[0], maxval=T_range[1], rng=rng) + F_prior = ngmix.priors.FlatPrior(minval=F_range[0], maxval=F_range[1], rng=rng) + + if nband is not None: + F_prior = [F_prior]*nband + + prior = ngmix.joint_prior.PriorSimpleSep( + cen_prior=cen_prior, + g_prior=g_prior, + T_prior=T_prior, + F_prior=F_prior, + ) + + return prior + + +def make_data(rng, noise, g1=0.05, g2=-0.02, flux=100.0): + """ + simulate an exponential object with moffat psf + + Parameters + ---------- + rng: np.random.RandomState + The random number generator + noise: float + Noise for the image + g1: float + object g1, default 0.05 + g2: float + object g2, default -0.02 + flux: float, optional + default 100 + + Returns + ------- + ngmix.Observation, pars dict + """ + + psf_noise = 1.0e-6 + + scale = 0.263 + + psf_fwhm = 0.9 + gal_hlr = 0.5 + dy, dx = rng.uniform(low=-scale/2, high=scale/2, size=2) + + psf = galsim.Moffat( + beta=2.5, fwhm=psf_fwhm, + ).shear( + g1=-0.01, + g2=-0.01, + ) + + obj0 = galsim.Exponential( + half_light_radius=gal_hlr, + flux=flux, + ).shear( + g1=g1, + g2=g2, + ).shift( + dx=dx, + dy=dy, + ) + + obj = galsim.Convolve(psf, obj0) + + psf_im = psf.drawImage(scale=scale).array + im = obj.drawImage(scale=scale).array + + psf_im += rng.normal(scale=psf_noise, size=psf_im.shape) + im += rng.normal(scale=noise, size=im.shape) + + cen = (np.array(im.shape)-1.0)/2.0 + psf_cen = (np.array(psf_im.shape)-1.0)/2.0 + + jacobian = ngmix.DiagonalJacobian( + row=cen[0] + dy/scale, col=cen[1] + dx/scale, scale=scale, + ) + psf_jacobian = ngmix.DiagonalJacobian( + row=psf_cen[0], col=psf_cen[1], scale=scale, + ) + + wt = im*0 + 1.0/noise**2 + psf_wt = psf_im*0 + 1.0/psf_noise**2 + + psf_obs = ngmix.Observation( + psf_im, + weight=psf_wt, + jacobian=psf_jacobian, + ) + + obs = ngmix.Observation( + im, + weight=wt, + jacobian=jacobian, + psf=psf_obs, + ) + + obj_pars = { + 'g1': g1, + 'g2': g2, + 'flux': flux, + } + return obs, obj_pars + + +def get_args(): + import argparse + parser = argparse.ArgumentParser() + parser.add_argument('--seed', type=int, default=42, + help='seed for rng') + parser.add_argument('--show', action='store_true', + help='show plot comparing model and data') + parser.add_argument('--noise', type=float, default=0.01, + help='noise for images') + return parser.parse_args() + + +if __name__ == '__main__': + main() diff --git a/scripts/python/update_runs_log_file.py b/scripts/python/update_runs_log_file.py index debbe9c85..42721ef31 100755 --- a/scripts/python/update_runs_log_file.py +++ b/scripts/python/update_runs_log_file.py @@ -53,23 +53,12 @@ def update_log_file(module_runs, log_name): with open(log_name, "w") as f_out: for key in module_runs: - print(key, file=f_out, end=" ") + print(os.path.abspath(key), file=f_out, end=" ") print(",".join(module_runs[key]), file=f_out) def main(argv=None): - # Set default parameters - # p_def = params_default() - - # Command line options - # options, args = parse_options(p_def) - - # if check_options(options) is False: - # return 1 - - # param = update_param(p_def, options) - base_dir = "./output" pattern = "run_sp_" log_name = f"{base_dir}/log_run_sp.txt" diff --git a/scripts/sh/job_list_help.bash b/scripts/sh/job_list_help.bash index 3213e762e..52430a434 100644 --- a/scripts/sh/job_list_help.bash +++ b/scripts/sh/job_list_help.bash @@ -14,5 +14,7 @@ JOB_LIST_HELP="\ \t 64: process stars on exposures, PSF model (offline)\n\ \t 128: merge exposure WCS headers into tile-level sqlite log\n\ \t 256: object selection on tiles (online if UNIONS catalogue or tar_cat_for_mask=onthefly)\n\ - \t 512: create final catalogue\n\ - \t1024: process tiles (PSF interp, vignet, shape measurement)\n" + \t 512: postage stamp creation\n\ + \t1024: multi-epoch shape measurement\n\ + \t2048: create final catalogue\n\ +" diff --git a/scripts/sh/job_sp.bash b/scripts/sh/job_sp.bash deleted file mode 100755 index 2a207d807..000000000 --- a/scripts/sh/job_sp.bash +++ /dev/null @@ -1,524 +0,0 @@ -#!/usr/bin/env bash - -# Name: job_sp.bash -# Description: General script to process one or more tiles -# with all contributing exposures. -# This works as job submission script for -# the canfar batch system. -# called in interactive mode on a virtual -# machine. -# Author: Martin Kilbinger - - -# VM home, required for canfar run. -## On other machines set to $HOME -export VM_HOME=/home/ubuntu -if [ ! -d "$VM_HOME" ]; then - export VM_HOME=$HOME -fi - -# Command line arguments -## Default values -job=255 -#config_dir='vos:cfis/cosmostat/kilbinger/cfis' -config_dir=$VM_HOME/shapepipe/example/cfis -psf='mccd' -retrieve='vos' -star_cat_for_mask='onthefly' -results='cosmostat/kilbinger/results_v1' -n_smp=-1 -nsh_step=-1 -nsh_max=-1 -nsh_jobs=8 - -## Help string -usage="Usage: $(basename "$0") [OPTIONS] TILE_ID_1 [TILE_ID_2 [...]] -\n\nOptions:\n - -h\tthis message\n - -j, --job JOB\tRunning JOB, bit-coded\n - \t 1: retrieve images (online if method=vos)\n - \t 2: prepare images (offline)\n - \t 4: mask (online)\n - \t 8: detection of galaxies on tiles; processing of stars on exposures (offline)\n - \t 16: galaxy selection on tiles (offline)\n - \t 32: shapes and morphology (offline)\n - \t 64: paste catalogues (offline)\n - \t 128: upload results (online)\n - -c, --config_dir DIR\n - \t config file directory, default='$config_dir'\n - -p, --psf MODEL\n - \tPSF model, one in ['psfex'|'mccd'], default='$psf'\n - -r, --retrieve METHOD\n - \tmethod to retrieve images, allowed are 'vos', 'symlink', default='$retrieve'\n - -s, --star_cat_for_mask\n - \tcatalogue for masking bright stars, allowed are 'onthefly', 'save',\n - \tdefault is '${star_cat_for_mask}'\n - -o, --output_dir\n - \toutput (upload) directory on vos:cfis, default='$results'\n - -n, --n_smp\n - \tnumber of jobs (SMP mode only), default from original config files\n - --nsh_step NSTEP\n - --nsh_jobs NJOB\n - \tnumber of shape measurement parallel jobs, default=$nsh_jobs\n - \tnumber of objects per parallel shape module call, \n - \tdefault: optimal number is computed\n - --nsh_max NMAX\n - \tmax number of objects per parallel shape module call, \n - \tdefault: unlimited; has precedent over --nsh_step\n - TILE_ID_i\n - \ttile ID(s), e.g. 283.247 214.242\n -" - -## Help if no arguments -if [ -z $1 ]; then - echo -ne $usage - exit 1 -fi - -## Parse command line -TILE_ARR=() -while [ $# -gt 0 ]; do - case "$1" in - -h) - echo -ne $usage - exit 0 - ;; - -j|--job) - job="$2" - shift - ;; - -c|--config_dir) - config_dir="$2" - shift - ;; - -p|--psf) - psf="$2" - shift - ;; - -r|--retrieve) - retrieve="$2" - shift - ;; - -s|--star_cat_for_mask) - star_cat_for_mask="$2" - shift - ;; - -o|--output_dir) - results="$2" - shift - ;; - -n|--n_smp) - n_smp="$2" - shift - ;; - --nsh_max) - nsh_max="$2" - shift - ;; - --nsh_step) - nsh_step="$2" - shift - ;; - --nsh_jobs) - nsh_jobs="$2" - shift - ;; - *) - TILE_ARR+=("$1") - ;; - esac - shift -done - -## Check options -if [ "$psf" != "psfex" ] && [ "$psf" != "mccd" ]; then - echo "PSF (option -p) needs to be 'psfex' or 'mccd'" - exit 2 -fi - -if [ "$star_cat_for_mask" != "onthefly" ] && [ "$star_cat_for_mask" != "save" ]; then - echo "Star cat for mask (option -s) needs to be 'onthefly' or 'save'" - exit 4 -fi - -if [ "$retrieve" != "vos" ] && [ "$retrieve" != "symlink" ]; then - echo "method to retrieve images (option -r) needs to be 'vos' or 'symlink'" - exit 5 -fi - -n_tile=${#TILE_ARR[@]} -if [ "$n_tile" == "0" ]; then - echo "No tile ID given" - exit 3 -fi - -if [ $nsh_max != -1 ]; then - nsh_step=$nsh_max -fi - -# For tar archives. Should be unique to each job -export ID=`echo ${TILE_ARR[@]} | tr ' ' '_'` - -## Paths - -# SExtractor library bug work-around -export PATH="$PATH:$VM_HOME/bin" - -## Path variables used in shapepipe config files - -# Run path and location of input image directories -export SP_RUN=`pwd` - -# Config file path -export SP_CONFIG=$SP_RUN/cfis -export SP_CONFIG_MOD=$SP_RUN/cfis_mod - -## Other variables - -# Input tile numbers ASCII file -export TILE_NUMBERS_PATH=tile_numbers.txt - -# Output -OUTPUT=$SP_RUN/output - -# For tar archives -output_rel=`realpath --relative-to=. $OUTPUT` - -# Stop on error, default=1 -STOP=1 - -# Verbose mode (1: verbose, 0: quiet) -VERBOSE=1 - -# VCP options -export CERTFILE=$VM_HOME/.ssl/cadcproxy.pem -export VCP="vcp --certfile=$CERTFILE" - - -## Functions - -# Print string, executes command, and prints return value. -function command () { - cmd=$1 - str=$2 - - RED='\033[0;31m' - GREEN='\033[0;32m' - NC='\033[0m' # No Color - # Color escape characters show up in log files - #RED='' - #GREEN='' - #NC='' - - - if [ $# == 2 ]; then - if [ $VERBOSE == 1 ]; then - echo "$str: running '$cmd'" - fi - $cmd - else - if [ $VERBOSE == 1 ]; then - echo "$str: running '$cmd $4 \"$5 $6\"'" - fi - $cmd $4 "$5 $6" - fi - res=$? - - if [ $VERBOSE == 1 ]; then - if [ $res == 0 ]; then - echo -e "${GREEN}success, return value = $res${NC}" - else - echo -e "${RED}error, return value = $res${NC}" - if [ $STOP == 1 ]; then - echo "${RED}exiting 'canfar_sp.bash', error in command '$cmd'${NC}" - exit $res - else - echo "${RED}continuing 'canfar_sp.bash', error in command '$cmd'${NC}" - fi - fi - fi -} - -# Run shapepipe command. If error occurs, upload sp log files before stopping script. -function command_sp() { - local cmd=$1 - local str=$2 - - command "$1" "$2" -} - -# Set up config file and call shapepipe_run -function command_cfg_shapepipe() { - local config_name=$1 - local str=$2 - local _n_smp=$3 - - config_upd=$(set_config_n_smp $config_name $_n_smp) - local cmd="shapepipe_run -c $config_upd" - command_sp "$cmd" "$str" -} - -# Tar and upload files to vos -function upload() { - base=$1 - shift - ID=$1 - shift - verbose=$1 - shift - upl=("$@") - - echo "Counting upload files" - n_upl=(`ls -l ${upl[@]} | wc`) - if [ $n_upl == 0 ]; then - if [ $STOP == 1 ]; then - echo "Exiting script, no file found for '$base' tar ball" - exit 3 - fi - fi - tar czf ${base}_${ID}.tgz ${upl[@]} - command "$VCP ${base}_${ID}.tgz vos:cfis/$results" "Upload tar ball" -} - -# Upload log files -function upload_logs() { - id=$1 - verbose=$2 - - upl="$output_rel/*/*/logs $output_rel/*/logs" - upload "logs" "$id" "$verbose" "${upl[@]}" -} - -function set_config_n_smp() { - local config_name=$1 - local _n_smp=$2 - - local config_orig="$SP_CONFIG/$config_name" - - if [[ $_n_smp != -1 ]]; then - # Update SMP batch size - local config_upd="$SP_CONFIG_MOD/$config_name" - update_config $config_orig $config_upd "SMP_BATCH_SIZE" $_n_smp - else - # Keep original config file - local config_upd=$config_orig - fi - - # Set "return" value (stdout) - echo "$config_upd" -} - -# Update config file -function update_config() { - local config_orig=$1 - local config_upd=$2 - local key=$3 - local val_upd=$4 - - cat $config_orig \ - | perl -ane 's/'$key'\s+=.+/'$key' = '$val_upd'/; print' > $config_upd -} - -### Start ### - -echo "Start" - -echo "Processing $n_tile tile(s)" - -# Create input and output directories -mkdir -p $SP_RUN -cd $SP_RUN -mkdir -p $OUTPUT -mkdir -p $SP_CONFIG_MOD - -# Processing - -## Retrieve config files and images (online if retrieve=vos) -## Retrieve and save star catalogues for masking (if star_cat_for_mask=save) -(( do_job= $job & 1 )) -if [[ $do_job != 0 ]]; then - - # Write tile numbers to ASCII input file - rm -rf $TILE_NUMBERS_PATH - for TILE in ${TILE_ARR[@]}; do - echo $TILE >> $TILE_NUMBERS_PATH - done - - ### Retrieve config files - if [[ $config_dir == *"vos:"* ]]; then - command_sp "$VCP $config_dir ." "Retrieve shapepipe config files" - else - if [[ ! -L cfis ]]; then - command_sp "ln -s $config_dir cfis" "Retrieve shapepipe config files" - fi - fi - - ### Retrieve files - command_sp "shapepipe_run -c $SP_CONFIG/config_GitFeGie_$retrieve.ini" "Retrieve images" - - ### Retrieve and save star catalogues for masking - if [ "$star_cat_for_mask" == "save" ]; then - #### For tiles - mkdir $SP_RUN/star_cat_tiles - command_sp "create_star_cat $SP_RUN/output/run_sp_GitFeGie_*/get_images_runner_run_1/output $SP_RUN/star_cat_tiles" "Save star cats for masking (tile)" - - #### For single-exposures - mkdir $SP_RUN/star_cat_exp - command_sp "create_star_cat $SP_RUN/output/run_sp_GitFeGie_*/get_images_runner_run_2/output $SP_RUN/star_cat_exp exp" "Save star cats for masking (exp)" - fi - -fi - -## Prepare images (offline) -(( do_job= $job & 2 )) -if [[ $do_job != 0 ]]; then - - ### Uncompress tile weights - command_cfg_shapepipe "config_tile_Uz.ini" "Run shapepipe (uncompress tile weights)" $n_smp - - ### Split images into single-HDU files, merge headers for WCS info - command_cfg_shapepipe "config_exp_SpMh.ini" "Run shapepipe (split images, merge headers)" $n_smp - -fi - -## Mask tiles and exposures: add star, halo, and Messier object masks (online if "star_cat_for_mask" is "onthefly") -(( do_job= $job & 4 )) -if [[ $do_job != 0 ]]; then - - ### Mask tiles and exposures - command_cfg_shapepipe "config_MaMa_$star_cat_for_mask.ini" "Run shapepipe (mask)" $n_smp - -fi - - -## Remaining exposure processing (offline) -(( do_job= $job & 8 )) -if [[ $do_job != 0 ]]; then - - ### Star detection, selection, PSF model. setools can exit with an error for CCD with insufficient stars, - ### the script should continue - STOP=0 - command_cfg_shapepipe "config_tile_Sx_exp_${psf}.ini" "Run shapepipe (tile detection, exp $psf)" $n_smp - STOP=1 - -fi - -## Process tiles up to shape measurement -(( do_job= $job & 16 )) -if [[ $do_job != 0 ]]; then - - ### PSF model letter: 'P' (psfex) or 'M' (mccd) - letter=${psf:0:1} - Letter=${letter^} - command_sp "shapepipe_run -c $SP_CONFIG/config_tile_${Letter}iViSmVi.ini" "Run shapepipe (tile PsfInterp=$Letter}: up to ngmix+galsim)" - -fi - -## Shape measurement (offline) -(( do_job= $job & 32 )) -if [[ $do_job != 0 ]]; then - - ### Prepare config files - n_min=0 - if [[ $nsh_step == -1 ]]; then - n_obj=`get_number_objects.py` - nsh_step=`echo "$(($n_obj/$nsh_jobs))"` - fi - - n_max=$((nsh_step - 1)) - for k in $(seq 1 $nsh_jobs); do - cat $SP_CONFIG/config_tile_Ng_template.ini | \ - perl -ane \ - 's/(ID_OBJ_MIN =) X/$1 '$n_min'/; s/(ID_OBJ_MAX =) X/$1 '$n_max'/; s/NgXu/Ng'$k'u/; s/X_interp/'$psf'_interp/g; print' \ - > $SP_CONFIG_MOD/config_tile_Ng${k}u.ini - n_min=$((n_min + nsh_step)) - if [ "$k" == $((nsh_jobs - 1)) ] && [ $nsh_max == -1 ]; then - n_max=-1 - else - n_max=$((n_min + nsh_step - 1)) - fi - done - - ### Shapes, run $nsh_jobs parallel processes - VERBOSE=0 - for k in $(seq 1 $nsh_jobs); do - command_sp "shapepipe_run -c $SP_CONFIG_MOD/config_tile_Ng${k}u.ini" "Run shapepipe (tile: ngmix+galsim $k)" & - done - wait - VERBOSE=1 - -fi - -## Create final catalogues (offline) -(( do_job= $job & 64 )) -if [[ $do_job != 0 ]]; then - - cat $SP_CONFIG/config_merge_sep_cats_template.ini | \ - perl -ane \ - 's/(N_SPLIT_MAX =) X/$1 '$nsh_jobs'/; print' \ - > $SP_CONFIG_MOD/config_merge_sep_cats.ini - - ### Merge separated shapes catalogues - command_sp "shapepipe_run -c $SP_CONFIG_MOD/config_merge_sep_cats.ini" "Run shapepipe (tile: merge sep cats)" "$VERBOSE" "$ID" - - ### Merge all relevant information into final catalogue - command_sp "shapepipe_run -c $SP_CONFIG/config_make_cat_$psf.ini" "Run shapepipe (tile: create final cat $psf)" "$VERBOSE" "$ID" - -fi - -## Upload results (online) -(( do_job= $job & 128 )) -if [[ $do_job != 0 ]]; then - - ### module and pipeline log files - upload_logs "$ID" "$VERBOSE" - - ### Final shape catalog - ### pipeline_flags are the tile masks, for random cats - ### SETools masks (selection), stats and plots - ### ${psf}_interp_exp for diagnostics, validation with leakage, - ### validation with residuals, rho stats - - NAMES=( - "final_cat" - "pipeline_flag" - "setools_mask" - "setools_stat" - "setools_plot" - ) - DIRS=( - "*/make_cat_runner/output" - "*/mask_runner_run_1/output" - "*/setools_runner/output/mask" - "*/setools_runner/output/stat" - "*/setools_runner/output/plot" - ) - PATTERNS=( - "final_cat-*" - "pipeline_flag-???-???*" - "*" - "*" - "*" - ) - - # PSF validation - pattern="validation_psf-*" - if [ "$psf" == "psfex" ]; then - name="psfex_interp_exp" - dir="*/psfex_interp_runner/output" - else - name="mccd_fit_val_runner" - dir="*/mccd_fit_val_runner/output" - fi - upl=$output_rel/$dir/$pattern - upload "$name" "$ID" "$VERBOSE" "${upl[@]}" - - for n in "${!NAMES[@]}"; do - name=${NAMES[$n]} - dir=${DIRS[$n]} - pattern=${PATTERNS[$n]} - upl=$output_rel/$dir/$pattern - upload "$name" "$ID" "$VERBOSE" "${upl[@]}" - done - -fi diff --git a/scripts/sh/job_sp_canfar_v2.0.bash b/scripts/sh/job_sp_canfar_v2.0.bash index 3fbe7b684..c1fa6cd29 100755 --- a/scripts/sh/job_sp_canfar_v2.0.bash +++ b/scripts/sh/job_sp_canfar_v2.0.bash @@ -164,18 +164,22 @@ export SP_RUN=`pwd` # Config file path export SP_CONFIG=$SP_RUN/cfis -export SP_CONFIG_MOD=$SP_RUN/cfis_mod # Root directory for per-exposure work directories. # Set SP_EXP in the environment to override; otherwise falls back to the # conventional layout (SP_RUN = .../v2.0/tiles/IDra/ID, three levels up + exp). if [ -z "${SP_EXP}" ]; then export SP_EXP=$(realpath "$SP_RUN/../../../exp") - echo "SP_EXP not set, using computed path: $SP_EXP" + echo "Setting SP_EXP to $SP_EXP" fi ## Other variables +# Override OMP_NUM_THREADS if the CANFAR provisioning template was not expanded +if [[ "${OMP_NUM_THREADS}" == *'${'* ]] || [[ "${OMP_NUM_THREADS}" == *'.'* ]]; then + export OMP_NUM_THREADS=1 +fi + # Output OUTPUT=$SP_RUN/output @@ -239,11 +243,12 @@ function command () { fi } -# Set up config file and call shapepipe_run +# Set up config file and call shapepipe_run. +# Batch size is passed via --batch_size flag; no config editing needed. function command_cfg_shapepipe() { local config_name=$1 local str=$2 - local _n_smp=$3 + local _n_smp=$3 local _exclusive=$4 if [ "$exclusive" != "" ]; then @@ -252,40 +257,14 @@ function command_cfg_shapepipe() { exclusive_flag="" fi - config_upd=$(set_config_n_smp $config_name $_n_smp) - #local cmd="/arc/home/kilbinger/.conda/envs/shapepipe/bin/shapepipe_run -c $config_upd $exclusive_flag" - local cmd="shapepipe_run -c $config_upd $exclusive_flag" - command "$cmd" "$str" -} - -function set_config_n_smp() { - local config_name=$1 - local _n_smp=$2 - - local config_orig="$SP_CONFIG/$config_name" - - if [[ $_n_smp != -1 ]]; then - # Update SMP batch size - local config_upd="$SP_CONFIG_MOD/$config_name" - update_config $config_orig $config_upd "SMP_BATCH_SIZE" $_n_smp - else - # Keep original config file - local config_upd=$config_orig - fi - - # Set "return" value (stdout) - echo "$config_upd" -} - -# Update config file -function update_config() { - local config_orig=$1 - local config_upd=$2 - local key=$3 - local val_upd=$4 + local batch_flag="" + if [[ $_n_smp != -1 ]]; then + batch_flag="--batch_size $_n_smp" + fi - cat $config_orig \ - | perl -ane 's/'$key'\s+=.+/'$key' = '$val_upd'/; print' > $config_upd + local config="$SP_CONFIG/$config_name" + local cmd="shapepipe_run.py -c $config $exclusive_flag $batch_flag" + command "$cmd" "$str" } ### Start ### @@ -296,7 +275,6 @@ echo "Start processing" mkdir -p $SP_RUN cd $SP_RUN mkdir -p $OUTPUT -mkdir -p $SP_CONFIG_MOD # Processing @@ -320,18 +298,14 @@ if [[ $do_job != 0 ]]; then command \ "create_star_cat $SP_RUN/output/run_sp_tile_Git_*/get_images_runner_run/output $SP_RUN/star_cat_tiles" \ "Save star cats for masking (tile)" - - #### For single-exposures - # TODO fi fi -## Prepare images (offline) +## Uncompress tile weights (( do_job = $job & 2 )) if [[ $do_job != 0 ]]; then - ### Uncompress tile weights command_cfg_shapepipe "config_tile_Uz.ini" "Run shapepipe (uncompress tile weights)" $n_smp $exclusive fi @@ -340,7 +314,6 @@ fi (( do_job = $job & 4 )) if [[ $do_job != 0 ]]; then - ### Uncompress tile weights command_cfg_shapepipe "config_tile_Fe.ini" "Run shapepipe (find exposures)" $n_smp $exclusive fi @@ -349,7 +322,6 @@ fi (( do_job = $job & 8 )) if [[ $do_job != 0 ]]; then - ### Retrieve exposure images command_cfg_shapepipe \ "config_exp_Gie_vos.ini" \ "Run shapepipe (get exposure images)" \ @@ -358,10 +330,10 @@ if [[ $do_job != 0 ]]; then fi +## Split images into single-HDU files, merge headers for WCS info (( do_job = $job & 16 )) if [[ $do_job != 0 ]]; then - ### Split images into single-HDU files, merge headers for WCS info command_cfg_shapepipe \ "config_exp_Sp.ini" \ "Run shapepipe (split images, merge headers)" \ @@ -370,10 +342,10 @@ if [[ $do_job != 0 ]]; then fi +## Mask exposures (( do_job = $job & 32 )) if [[ $do_job != 0 ]]; then - ### Mask exposures command_cfg_shapepipe \ "config_exp_Ma_${star_cat_for_mask}.ini" \ "Run shapepipe (mask exposures)" \ @@ -398,19 +370,19 @@ if [[ $do_job != 0 ]]; then fi +## Merge single-exposure WCS headers into tile-level sqlite log. (( do_job = $job & 128 )) if [[ $do_job != 0 ]]; then - ### Merge single-exposure WCS headers into tile-level sqlite log. - ### Must run before object detection/selection (make_post_process needs it). command_cfg_shapepipe \ - "config_exp_Mh.ini" \ + "config_tile_Mh_exp.ini" \ "Run shapepipe (merge exp headers)" \ $n_smp \ $exclusive fi +## Select objects on tiles (( do_job = $job & 256 )) if [[ $do_job != 0 ]]; then @@ -463,37 +435,35 @@ if [[ $do_job != 0 ]]; then fi -## Process tiles up to shape measurement -(( do_job = $job & 1024 )) +## Process tiles up to shape measurement: postage stamp creation +(( do_job = $job & 512 )) if [[ $do_job != 0 ]]; then ### PSF model letter: 'P' (psfex) or 'M' (mccd) letter=${psf:0:1} Letter=${letter^} command_cfg_shapepipe \ - "config_tile_${Letter}iViVi_canfar.ini" \ - "Run shapepipe (tile PsfInterp=${Letter}: up to ngmix+galsim)" \ + "config_tile_${Letter}iViVi_canfar_${tile_det}.ini" \ + "Run shapepipe (tile PsfInterp=${Letter}: postage stamp creation)" \ $n_smp \ $exclusive fi -## Create final catalogues (offline) +## Process tiles up to shape measurement: postage stamp creation (( do_job = $job & 1024 )) if [[ $do_job != 0 ]]; then - cat $SP_CONFIG/config_merge_sep_cats_template.ini | \ - perl -ane \ - 's/(N_SPLIT_MAX =) X/$1 '$nsh_jobs'/; print' \ - > $SP_CONFIG_MOD/config_merge_sep_cats.ini - - ### Merge separated shapes catalogues - command \ - "shapepipe_run -c $SP_CONFIG_MOD/config_tile_merge_sep_cats.ini" \ - "Run shapepipe (tile: merge sep cats)" + command_cfg_shapepipe \ + "config_tile_Ng_batch_${psf}_${tile_det}.ini" \ + "Run shapepipe (tile): shape measurement" \ + $n_smp \ + $exclusive + fi -(( do_job = $job & 512 )) +## Create final catalogues (offline) +(( do_job = $job & 2048 )) if [[ $do_job != 0 ]]; then suff_sm="_nosm" diff --git a/scripts/sh/run_job_sp_canfar_v2.0.bash b/scripts/sh/run_job_sp_canfar_v2.0.bash index c59dafca9..9da08f598 100755 --- a/scripts/sh/run_job_sp_canfar_v2.0.bash +++ b/scripts/sh/run_job_sp_canfar_v2.0.bash @@ -14,7 +14,7 @@ version="2.0" job=-1 ID=-1 psf='psfex' -tile_det='sx' +tile_det='uc' tile_mask=0 N_SMP=1 dry_run=0 @@ -43,7 +43,7 @@ ${JOB_LIST_HELP} -e, --exclusive ID\timage ID\n -N, --N_SMP N_SMP\tnumber of SMP jobs, default from original config files\n -d, --directory DIR\trun directory, default is pwd ($dir)\n -S, --scratch DIR\tprocessing scratch directory, default=none\n - -n, --dry_run\t\tdry run, no actual processing; default is $dry_run\n + -n, --dry_run\t\tDRY RUN, no actual processing; default is $dry_run\n --debug_out PATH\tdebug output file PATH, default=none\n --test\t\t\ttest mode, no processing\n --check\t\tcheck download completeness only (job 8), no processing\n @@ -164,13 +164,20 @@ function init_exp_work_dir() { # Run a per-exposure job (e.g. job 8, 16). -# Args: $1 = job number, $2 = run_sp output dir prefix (e.g. "Gie") -# $3 = space-separated list of "runner_subdir:N" completeness checks -# all pairs must pass for an exposure to be considered complete +# Args: $1 = job number +# $2 = space-separated list of run_sp_exp output dir prefixes (e.g. "Gie") +# first prefix is the main one; all are force-removed when --force is set +# $3 = space-separated list of completeness checks, each in one of two forms: +# "runner_subdir:N[:subpath[:warn]]" +# check runner_subdir/output in the main (first) prefix run dir +# "run_prefix:runner_subdir:N[:subpath[:warn]]" +# check runner_subdir/output in run_sp_exp_run_prefix* dir +# all non-warn checks must pass for an exposure to be considered complete function run_exp_job() { local exp_job=$1 - local run_prefix=$2 + local run_prefixes=$2 local complete_checks=$3 + local main_prefix="${run_prefixes%% *}" exp_numbers_file=$(ls -t "$work_dir/output/run_sp_tile_Fe"*/find_exposures_runner/output/"exp_numbers-${IDra}-${IDdec}.txt" 2>/dev/null | head -1) @@ -203,25 +210,43 @@ function run_exp_job() { # Create exp_numbers-000-000.txt and cfis link if not existent init_exp_work_dir "$exp_id" "$exp_work_dir" - # --force: remove all existing run directories for this prefix before running + # force: remove all existing run directories for each prefix before running if [ "$force" == "1" ]; then - local dirs_to_remove - dirs_to_remove=$(ls -d "$exp_work_dir/output/run_sp_exp_${run_prefix}"* 2>/dev/null) - if [ -n "$dirs_to_remove" ]; then - for d in $dirs_to_remove; do - message "Force-removing $d" "$debug_out" -1 - command "rm -rf $d" $dry_run - done - fi + local run_prefix + for run_prefix in $run_prefixes; do + local dirs_to_remove + dirs_to_remove=$(ls -d "$exp_work_dir/output/run_sp_exp_${run_prefix}"* 2>/dev/null) + if [ -n "$dirs_to_remove" ]; then + for d in $dirs_to_remove; do + message "Force-removing $d" "$debug_out" -1 + command "rm -rf $d" $dry_run + done + fi + done fi - # Check completeness of existing run output - local run_dir=$(ls -dt "$exp_work_dir/output/run_sp_exp_${run_prefix}"* 2>/dev/null | head -1) + # Check completeness of existing run output (main prefix) + local run_dir=$(ls -dt "$exp_work_dir/output/run_sp_exp_${main_prefix}"* 2>/dev/null | head -1) local is_complete=1 local check_desc="" for check_pair in $complete_checks; do - local subdir="${check_pair%%:*}" - local rest="${check_pair#*:}" + local field1="${check_pair%%:*}" + local rest1="${check_pair#*:}" + local field2="${rest1%%:*}" + + local check_run_dir subdir rest + if [[ "$field2" =~ ^[0-9]+$ ]]; then + # "subdir:N[...]" — check in main run dir + check_run_dir="$run_dir" + subdir="$field1" + rest="$rest1" + else + # "run_prefix:subdir:N[...]" — check in that prefix's run dir + check_run_dir=$(ls -dt "$exp_work_dir/output/run_sp_exp_${field1}"* 2>/dev/null | head -1) + subdir="$field2" + rest="${rest1#*:}" + fi + local n_threshold="${rest%%:*}" local rest2="${rest#*:}" local subpath="" @@ -234,10 +259,11 @@ function run_exp_job() { fi local n_out=0 + local out_dir if [ -n "$subpath" ]; then - out_dir="$run_dir/${subdir}/output/${subpath}" + out_dir="${check_run_dir}/${subdir}/output/${subpath}" else - out_dir="$run_dir/${subdir}/output" + out_dir="${check_run_dir}/${subdir}/output" fi # Remove broken symlinks in module output dir @@ -248,7 +274,7 @@ function run_exp_job() { fi done - [ -n "$run_dir" ] && n_out=$(ls "$out_dir/" 2>/dev/null | wc -l) + [ -n "$check_run_dir" ] && n_out=$(ls "$out_dir/" 2>/dev/null | wc -l) check_desc+="${subdir}:${n_out}/${n_threshold} " if [ "$n_out" -lt "$n_threshold" ]; then if [ "$warn_only" == "1" ]; then @@ -261,7 +287,7 @@ function run_exp_job() { done if [ "$is_complete" == "1" ]; then - message "Complete $exp_id_disp: run_sp_exp_${run_prefix} ( $check_desc)" "$debug_out" -1 + message "Complete $exp_id_disp: run_sp_exp_${main_prefix} ( $check_desc)" "$debug_out" -1 (( n_complete++ )) continue fi @@ -286,10 +312,8 @@ function run_exp_job() { echo "$(basename "$0") -j $exp_job -e $exp_id" > "$exp_log_file" echo "pwd=`pwd`" - command "job_sp_canfar_v2.0 -p $psf --tile_det $tile_det --tile_mask $tile_mask -j $exp_job --n_smp $N_SMP --nsh_jobs $N_SMP $debug_flag" $dry_run 2>&1 | tee -a "$exp_log_file" - echo "Done with job_sp_canfar_v2.0" - - #cd "$dir" + command "job_sp_canfar_v2.0.bash -p $psf --tile_det $tile_det --tile_mask $tile_mask -j $exp_job --n_smp $N_SMP --nsh_jobs $N_SMP $debug_flag" $dry_run 2>&1 | tee -a "$exp_log_file" + echo "Done with job_sp_canfar_v2.0.bash" done < "$exp_numbers_file" @@ -304,37 +328,74 @@ function run_exp_job() { # Run a tile-level job (jobs 1, 2, 4, 128, 256, ...). # Args: $1 = job number -# $2 = run_sp output dir prefix (e.g. "Fe", "tile_Sx", "exp_Mh") -# $3 = space-separated completeness checks "runner_subdir:N[:subpath[:warn]]" +# $2 = space-separated list of run_sp_tile output dir prefixes (e.g. "Fe") +# first prefix is the main one; all are force-removed when --force is set +# $3 = space-separated completeness checks, each in one of two forms: +# "runner_subdir:N[:subpath[:warn]]" +# check runner_subdir/output in the main (first) prefix run dir +# "run_prefix:runner_subdir:N[:subpath[:warn]]" +# check runner_subdir/output in run_sp_tile_run_prefix* dir # omit or pass "" to skip the completeness check and always run + function run_tile_job() { local tile_job=$1 - local run_prefix=$2 + local run_prefixes=$2 local complete_checks=$3 + local main_prefix="${run_prefixes%% *}" - # --force: remove all existing run directories for this prefix before running + # force: remove all existing run directories for each prefix before running if [ "$force" == "1" ]; then - local dirs_to_remove - dirs_to_remove=$(ls -d "$work_dir/output/run_sp_tile_${run_prefix}"* 2>/dev/null) - if [ -n "$dirs_to_remove" ]; then - for d in $dirs_to_remove; do - message "Force-removing $d" "$debug_out" -1 - command "rm -rf $d" $dry_run - done - fi + local run_prefix + for run_prefix in $run_prefixes; do + local dirs_to_remove + dirs_to_remove=$(ls -d "$work_dir/output/run_sp_tile_${run_prefix}"* 2>/dev/null) + if [ -n "$dirs_to_remove" ]; then + for d in $dirs_to_remove; do + message "Force-removing $d" "$debug_out" -1 + command "rm -rf $d" $dry_run + done + fi + done fi - # Locate most recent existing run directory for this prefix + # Locate most recent existing run directory for the main prefix local run_dir - run_dir=$(ls -dt "$work_dir/output/run_sp_tile_${run_prefix}"* 2>/dev/null | head -1) + run_dir=$(ls -dt "$work_dir/output/run_sp_tile_${main_prefix}"* 2>/dev/null | head -1) local is_complete=1 local check_desc="" if [ -n "$complete_checks" ]; then - for check_pair in $complete_checks; do - local subdir="${check_pair%%:*}" - local rest="${check_pair#*:}" + + # turn inputs into arrays + read -r -a run_prefix_array <<< "$run_prefixes" + read -r -a check_array <<< "$complete_checks" + + # sanity check (optional but strongly recommended) + if [ "${#run_prefix_array[@]}" -ne "${#check_array[@]}" ]; then + echo "Error: run_prefixes and complete_checks must have same length" + return 1 + fi + + # zip loop + for i in "${!run_prefix_array[@]}"; do + run_prefix="${run_prefix_array[$i]}" + check_pair="${check_array[$i]}" + + local field1="${check_pair%%:*}" + local rest1="${check_pair#*:}" + local field2="${rest1%%:*}" + + local check_run_dir subdir rest + check_run_dir=$(ls -dt "$work_dir/output/run_sp_tile_${run_prefix}"* 2>/dev/null | head -1) + if [[ "$field2" =~ ^[0-9]+$ ]]; then + subdir="$field1" + rest="$rest1" + else + subdir="$field2" + rest="${rest1#*:}" + fi + local n_threshold="${rest%%:*}" local rest2="${rest#*:}" local subpath="" @@ -346,14 +407,14 @@ function run_tile_job() { local out_dir if [ -n "$subpath" ]; then - out_dir="$run_dir/${subdir}/output/${subpath}" + out_dir="${check_run_dir}/${subdir}/output/${subpath}" else - out_dir="$run_dir/${subdir}/output" + out_dir="${check_run_dir}/${subdir}/output" fi local n_out=0 - [ -n "$run_dir" ] && n_out=$(ls "$out_dir/" 2>/dev/null | wc -l) - check_desc+="${subdir}:${n_out}/${n_threshold} " + [ -n "$check_run_dir" ] && n_out=$(ls "$out_dir/" 2>/dev/null | wc -l) + check_desc+="${run_prefix}/${subdir}:${n_out}/${n_threshold} " if [ "$n_out" -lt "$n_threshold" ]; then [ "$warn_only" != "1" ] && is_complete=0 fi @@ -361,15 +422,15 @@ function run_tile_job() { fi if [ "$is_complete" == "1" ] && [ -n "$complete_checks" ]; then - message "Complete: run_sp_tile_${run_prefix} ( $check_desc)" "$debug_out" -1 + message "Complete: ( $check_desc)" "$debug_out" -1 return 0 fi if [ "$check" == "1" ]; then if [ -n "$run_dir" ]; then - message "Incomplete: run_sp_tile_${run_prefix} ($check_desc)" "$debug_out" -1 + message "Incomplete: ($check_desc)" "$debug_out" -1 else - message "Missing: run_sp_tile_${run_prefix}" "$debug_out" -1 + message "Missing: ($check_desc)" "$debug_out" -1 fi return 0 fi @@ -382,11 +443,12 @@ function run_tile_job() { ln -sf ~/shapepipe/example/cfis "cfis" fi + command "update_runs_log_file.py" $dry_run + # Run job script - command "job_sp_canfar_v2.0 -p $psf --tile_det $tile_det --tile_mask $tile_mask -j $tile_job --n_smp $N_SMP --nsh_jobs $N_SMP $debug_flag" $dry_run 2>&1 | tee -a "$log_file" + command "job_sp_canfar_v2.0.bash -p $psf --tile_det $tile_det --tile_mask $tile_mask -j $tile_job --n_smp $N_SMP --nsh_jobs $N_SMP $debug_flag" $dry_run 2>&1 | tee -a "$log_file" } - # Init message if [ "$test_only" == "1" ]; then message "$(basename "$0") test mode, exiting." "$debug_out" 0 @@ -454,6 +516,7 @@ fi echo -n "pwd: "; pwd + # Avoid Qt error with setools export DISPLAY=:1.0 @@ -520,14 +583,14 @@ fi (( do_job = job & 128 )) if [[ $do_job != 0 ]]; then # Job 128: merge exposure WCS headers into tile-level sqlite log - run_tile_job 128 "exp_Mh" "merge_headers_runner:1" + run_tile_job 128 "Mh_exp" "merge_headers_runner:1" fi (( do_job = job & 256 )) if [[ $do_job != 0 ]]; then # Job 256: object selection on tiles if [ "$tile_det" == "uc" ]; then - run_tile_job 256 "Uc" "read_ext_sexcat_runner:1" + run_tile_job 256 "Gic Uc" "get_images_runner:2 read_ext_sexcat_runner:1" else run_tile_job 256 "Sx" "sextractor_runner:1" fi @@ -535,14 +598,14 @@ fi (( do_job = job & 512 )) if [[ $do_job != 0 ]]; then - # Job 512: create final catalogue - run_tile_job 512 "Mc" "make_cat_runner:1" + # Job 512: process tiles (PSF interp, vignet) + run_tile_job 512 "${Letter}iViVi ${Letter}iViVi ${Letter}iViVi" "psfex_interp_runner:1 vignetmaker_runner_run_1:1 vignetmaker_runner_run_2:4" fi (( do_job = job & 1024 )) if [[ $do_job != 0 ]]; then - # Job 1024: process tiles (PSF interp, vignet, shape measurement) - run_tile_job 1024 "tile_${Letter}sViSmVi" "" + # Job 1024: shape measurement + run_tile_job 1024 "Ng" "ngmix_interp_runner:1" fi if [ -n "$scratch" ]; then diff --git a/scripts/sh/untar_results.bash b/scripts/sh/untar_results.bash deleted file mode 100755 index 9db70404e..000000000 --- a/scripts/sh/untar_results.bash +++ /dev/null @@ -1,92 +0,0 @@ -#!/usr/bin/env bash - -# Name: untar_results.bash -# Description: Untar .tgz files = results of ShapePipe runs -# Author: Martin Kilbinger -# Date: 05/2020 -# Package: shapepipe - -# Command line arguments - -## Default values -psf="mccd" -output="" - -## Help string -usage="Usage: $(basename "$0") [OPTIONS] -\n\nOptions:\n - -h\tthis message\n - -p, --psf MODEL\n - \tPSF model, one in ['psfex'|'mccd'], default='$psf'\n - -o, --output FILE\n - \tOutput file to list untared archives, default None\n -" - -## Parse command line -while [ $# -gt 0 ]; do - case "$1" in - -h) - echo -ne $usage - exit 0 - ;; - -p|--psf) - psf="$2" - shift - ;; - -o|--output) - output="$2" - shift - ;; - *) - echo -ne usage - exit 1 - ;; - esac - shift -done - - -NAMES=( - "final_cat" - "setools_mask" - "setools_stat" - "setools_plot" - "pipeline_flag" - ) - -if [ "$psf" == "psfex" ]; then - NAMES+=( - "psfex_interp_exp" - ) -elif [ "$psf" == "mccd" ]; then - NAMES+=( - "mccd_fit_val_runner" - ) -fi - -if [[ "$output" != "" ]]; then - echo "Resetting output file $output" - rm -f $output -fi - -# Check number of files -for out in ${NAMES[@]}; do - echo "$out" - FILES=${out}_*.tgz - n_files=${#FILES[@]} - n_ok=0 - n_fail=0 - for file in $FILES; do - tar xf $file - res=$? - if [ $res == 0 ]; then - ((n_ok=n_ok+1)) - if [[ "$output" != "" ]]; then - echo $file >> $output - fi - else - ((n_fail=n_fail+1)) - fi - done - echo " $n_files tgz files, $n_ok successful untar commands, $n_fail failures" -done diff --git a/scripts/validation/centroid/centroid_bias.py b/scripts/validation/centroid/centroid_bias.py new file mode 100644 index 000000000..d9c0e0fbd --- /dev/null +++ b/scripts/validation/centroid/centroid_bias.py @@ -0,0 +1,402 @@ +#!/usr/bin/env python +"""centroid_bias.py + +Metacal multiplicative-bias validation for ShapePipe/ngmix. + +Measures the multiplicative shear bias m by running metacalibration on +simulated exponential galaxies with a Moffat PSF and comparing recovered +shear to the true input shear. + +Simulation data (make_data) is imported from shapepipe.testing.simulate so +it stays stable across branches. All processing code here is +version-specific and changes with each shapepipe/ngmix branch. + +Usage +----- + python centroid_bias.py [--ntrial N] [--seed S] [--noise SIGMA] + +Expected output (centroid_bug branch, ngmix stable_version): + m ~ -28e-3 (large negative bias, the bug) + +Expected output (centroid_fix branch, ngmix fix_jac_centroid): + m ~ 0 (bias consistent with zero) + +Autors +------ + Axel Guinot + Martin Kilbinger +""" + +import argparse + +import numpy as np +import ngmix +from ngmix import Observation, ObsList +from numpy.random import uniform as urand + +from shapepipe.modules.ngmix_package.ngmix import get_guess, get_noise +from shapepipe.testing.simulate import make_data +from modopt.math.stats import sigma_mad + + +# --------------------------------------------------------------------------- +# Priors (ngmix-version-specific) +# --------------------------------------------------------------------------- + +def get_prior(pixel_scale): + """Build ngmix joint prior for 6-parameter galaxy model.""" + g_prior = ngmix.priors.GPriorBA(0.4) + cen_prior = ngmix.priors.CenPrior(0.0, 0.0, pixel_scale, pixel_scale) + T_prior = ngmix.priors.FlatPrior(-10.0, 1.0e6) + F_prior = ngmix.priors.FlatPrior(-1.0e4, 1.0e9) + return ngmix.joint_prior.PriorSimpleSep(cen_prior, g_prior, T_prior, F_prior) + + +# --------------------------------------------------------------------------- +# Fitting (ngmix-version-specific) +# --------------------------------------------------------------------------- + +def make_galsimfit(obs, model, guess0, prior=None, ntry=5): + """Fit an observation with GalsimSimple, retrying with perturbed guesses. + + Parameters + ---------- + obs : ngmix.Observation or ObsList + model : str + guess0 : numpy.ndarray shape (6,) + prior : ngmix prior, optional + ntry : int, optional + + Returns + ------- + dict + Fit result with flags, g, T, T_err, pars, pars_err, etc. + + Raises + ------ + ngmix.gexceptions.BootGalFailure + """ + limit = 0.1 + guess = np.copy(guess0) + fres = {"flags": 1} + + for it in range(ntry): + guess[0:5] += urand(low=-limit, high=limit) + guess[5:] *= 1 + urand(low=-limit, high=limit) + try: + fitter = ngmix.galsimfit.GalsimSimple(obs, model, prior=prior) + fitter.go(guess) + fres = fitter.get_result() + except Exception: + continue + if fres["flags"] == 0: + break + + if fres["flags"] != 0: + raise ngmix.gexceptions.BootGalFailure( + "Failed to fit galaxy image with galsimfit" + ) + fres["ntry"] = it + 1 + return fres + + +# --------------------------------------------------------------------------- +# Metacal pipeline (ngmix-version-specific) +# --------------------------------------------------------------------------- + +def do_ngmix_metacal( + gals, psfs, psfs_sigma, weights, flags, jacob_list, + prior, pixel_scale, sig_noise=None, +): + """Run metacalibration on a multi-epoch object. + + Parameters + ---------- + gals, psfs, psfs_sigma, weights, flags : lists + Per-epoch image arrays and metadata. + jacob_list : list of galsim Jacobians + prior : ngmix joint prior + pixel_scale : float [arcsec] + sig_noise : float or None + If None, estimated from the first epoch. + + Returns + ------- + dict + Metacal result dict keyed by shear type ('noshear', '1p', '1m'). + """ + n_epoch = len(gals) + if n_epoch == 0: + raise ValueError("0 epochs to process") + + gal_obs_list = ObsList() + T_guess_psf = [] + psf_res_gT = { + "g_PSFo": np.array([0.0, 0.0]), + "g_err_PSFo": np.array([0.0, 0.0]), + "T_PSFo": 0.0, + "T_err_PSFo": 0.0, + } + gal_guess = [] + gal_guess_flag = True + wsum = 0 + + for n_e in range(n_epoch): + psf_jacob = ngmix.Jacobian( + row=(psfs[0].shape[0] - 1) / 2, + col=(psfs[0].shape[1] - 1) / 2, + wcs=jacob_list[n_e], + ) + psf_obs = Observation(psfs[n_e], jacobian=psf_jacob) + psf_T = psfs_sigma[n_e] * 1.17741 * pixel_scale + + weight_map = np.copy(weights[n_e]) + weight_map[flags[n_e] != 0] = 0.0 + weight_map[weight_map != 0] = 1 + + psf_guess = np.array([0.0, 0.0, 0.0, 0.0, psf_T, 1.0]) + try: + psf_res = make_galsimfit(psf_obs, "gauss", psf_guess) + except Exception: + continue + + try: + gal_guess_tmp = get_guess( + gals[n_e], pixel_scale, + guess_size_type="T", guess_centroid_unit="img", + ) + except Exception: + gal_guess_flag = False + gal_guess_tmp = np.array([0.0, 0.0, 0.0, 0.0, 1, 100]) + + gal_jacob = ngmix.Jacobian( + row=(gals[n_e].shape[0] - 1) / 2 + gal_guess_tmp[1], + col=(gals[n_e].shape[1] - 1) / 2 + gal_guess_tmp[0], + wcs=jacob_list[n_e], + ) + + if sig_noise is None: + sig_noise = ( + get_noise(gals[n_e], weight_map, gal_guess_tmp, pixel_scale) + if gal_guess_flag + else sigma_mad(gals[n_e]) + ) + + noise_img = np.random.randn(*gals[n_e].shape) * sig_noise + noise_img_gal = np.random.randn(*gals[n_e].shape) * sig_noise + + gal_masked = np.copy(gals[n_e]) + if (weight_map == 0).any(): + gal_masked[weight_map == 0] = noise_img_gal[weight_map == 0] + weight_map *= 1 / sig_noise ** 2 + + w_tmp = np.sum(weight_map) + psf_res_gT["g_PSFo"] += psf_res["g"] * w_tmp + psf_res_gT["g_err_PSFo"] += ( + np.array([psf_res["pars_err"][2], psf_res["pars_err"][3]]) * w_tmp + ) + psf_res_gT["T_PSFo"] += psf_res["T"] * w_tmp + psf_res_gT["T_err_PSFo"] += psf_res["T_err"] * w_tmp + wsum += w_tmp + + gal_obs = Observation( + gal_masked, weight=weight_map, + jacobian=gal_jacob, psf=psf_obs, noise=noise_img, + ) + if gal_guess_flag: + final_gal_guess = np.copy(gal_guess_tmp) + final_gal_guess[:2] = 0 + gal_guess.append(final_gal_guess) + + gal_obs_list.append(gal_obs) + T_guess_psf.append(psf_T) + gal_guess_flag = True + + if wsum == 0: + raise ZeroDivisionError("Sum of weights = 0") + + for key in psf_res_gT: + psf_res_gT[key] /= wsum + + fail_get_guess = len(gal_guess) == 0 + gal_pars = [0.0, 0.0, 0.0, 0.0, 1, 100] if fail_get_guess else np.mean(gal_guess, 0) + + metacal_pars = { + "types": ["noshear", "1p", "1m"], + "step": 0.01, + "psf": "gauss", + "fixnoise": True, + "cheatnoise": False, + "symmetrize_psf": False, + "use_noise_image": True, + } + Tguess = np.mean(T_guess_psf) + + obs_dict_mcal = ngmix.metacal.get_all_metacal(gal_obs_list, **metacal_pars) + res = {"mcal_flags": 0} + + for key in sorted(obs_dict_mcal): + fres = make_galsimfit(obs_dict_mcal[key], "gauss", gal_pars, prior=prior) + res["mcal_flags"] |= fres["flags"] + tres = dict(fres) + + wsum_psf = 0 + Tpsf_sum = 0 + gpsf_sum = np.zeros(2) + for obs in obs_dict_mcal[key]: + psf_obs_fit = getattr(obs, "psf_nopix", obs.psf) + try: + psf_res = make_galsimfit( + psf_obs_fit, "gauss", + np.array([0.0, 0.0, 0.0, 0.0, Tguess, 1.0]), + ) + except Exception: + continue + tw = obs.weight.sum() + wsum_psf += tw + gpsf_sum += np.array(psf_res["g"]) * tw + Tpsf_sum += psf_res["T"] * tw + + tres["gpsf"] = gpsf_sum / wsum_psf if wsum_psf > 0 else np.zeros(2) + tres["Tpsf"] = Tpsf_sum / wsum_psf if wsum_psf > 0 else 0.0 + res[key] = tres + + res.update(psf_res_gT) + res["moments_fail"] = fail_get_guess + return res + + +# --------------------------------------------------------------------------- +# Analysis utilities (stable) +# --------------------------------------------------------------------------- + +def progress(total, miniters=1): + """Minimal progress printer.""" + sl = str(len(str(total))) + fmt = "%" + sl + "d/%" + sl + "d %3d%%" + last_print_n = 0 + last_len = 0 + for i in range(total): + yield i + num = i + 1 + if i == 0 or num == total or num - last_print_n >= miniters: + meter = fmt % (num, total, 100 * num // total) + print("\r" + meter + " " * max(last_len - len(meter), 0), + end="", flush=True) + last_len = len(meter) + last_print_n = num + print(flush=True) + + +def make_struct(res, shear_type): + """Pack a metacal result into a structured array row.""" + dt = [ + ("flags", "i4"), ("shear_type", "U7"), + ("s2n", "f8"), ("g", "f8", 2), ("T", "f8"), ("Tpsf", "f8"), + ] + data = np.zeros(1, dtype=dt) + data["shear_type"] = shear_type + data["flags"] = res["flags"] + if res["flags"] == 0: + data["s2n"] = res["flux"] / res["flux_err"] + data["g"] = res["g"] + data["T"] = res["T"] + data["Tpsf"] = res["Tpsf"] + else: + data["s2n"] = data["g"] = data["T"] = data["Tpsf"] = np.nan + return data + + +def select(data, shear_type): + """Return indices where flags==0 and shear_type matches.""" + return np.where( + (data["flags"] == 0) & (data["shear_type"] == shear_type) + )[0] + + +# --------------------------------------------------------------------------- +# Main +# --------------------------------------------------------------------------- + +def main(ntrial=50, seed=42, sig_noise=1e-10, n_epochs=3, pixel_scale=0.1857): + rng_prior = np.random.RandomState(seed) + prior = get_prior(pixel_scale) + shear_types = ["noshear", "1p", "1m"] + + rng = np.random.RandomState(seed) + seeds = rng.randint(0, 2 ** 30, size=ntrial) + + dlist_p, dlist_m = [], [] + + for i in progress(ntrial, miniters=10): + d_ = [] + for shear_true in [(0.02, 0.00), (-0.02, 0.00)]: + gals, psfs, psfs_sigmas, weights, flags, jacob_lists = make_data( + rng=np.random.RandomState(seeds[i]), + noise=sig_noise, + shear=shear_true, + n_epochs=n_epochs, + share_shift=False, + ) + try: + resdict = do_ngmix_metacal( + gals, psfs, psfs_sigmas, weights, flags, jacob_lists, + prior=prior, pixel_scale=pixel_scale, sig_noise=sig_noise, + ) + stt = [make_struct(resdict[st], st) for st in shear_types] + except Exception: + continue + d_.append(np.hstack(stt)) + + if len(d_) != 2: + continue + dlist_p.extend(d_[0]) + dlist_m.extend(d_[1]) + + print() + + data_p = np.hstack(dlist_p) + data_m = np.hstack(dlist_m) + + w = select(data_p, "noshear") + w_1p = select(data_p, "1p") + w_1m = select(data_p, "1m") + R11_p = np.atleast_2d((data_p["g"][w_1p, 0] - data_p["g"][w_1m, 0]) / 0.02).T + + w = select(data_m, "noshear") + w_1p = select(data_m, "1p") + w_1m = select(data_m, "1m") + R11_m = np.atleast_2d((data_m["g"][w_1p, 0] - data_m["g"][w_1m, 0]) / 0.02).T + + g_p = data_p["g"][select(data_p, "noshear")] + g_m = data_m["g"][select(data_m, "noshear")] + shear_ = (g_p - g_m) / (R11_p + R11_m) + shear = np.mean(shear_, axis=0) + shear_err = np.std(shear_, axis=0) / np.sqrt(len(shear_)) + + m = shear[0] / 0.02 - 1 + merr = shear_err[0] / 0.02 + s2n = data_p["s2n"][select(data_p, "noshear")].mean() + + print("S/N: %g" % s2n) + print("R11: %g %g" % (np.mean(R11_p), np.mean(R11_m))) + print("m[1e-3, 3sigmas]: %g +/- %g (99.7%% conf)" % (m / 1e-3, merr * 3 / 1e-3)) + print("c[1e-5, 3sigmas]: %g +/- %g (99.7%% conf)" % (shear[1] / 1e-5, shear_err[1] * 3 / 1e-5)) + + +if __name__ == "__main__": + parser = argparse.ArgumentParser(description="Metacal centroid bias validation") + parser.add_argument("--ntrial", type=int, default=50, help="number of trials") + parser.add_argument("--seed", type=int, default=42, help="random seed") + parser.add_argument("--noise", type=float, default=1e-10, help="per-pixel noise sigma") + parser.add_argument("--n-epochs", type=int, default=3, help="epochs per galaxy") + parser.add_argument("--pixel-scale", type=float, default=0.1857, help="pixel scale [arcsec]") + args = parser.parse_args() + + main( + ntrial=args.ntrial, + seed=args.seed, + sig_noise=args.noise, + n_epochs=args.n_epochs, + pixel_scale=args.pixel_scale, + ) diff --git a/scripts/validation/centroid/centroid_bias_v2.py b/scripts/validation/centroid/centroid_bias_v2.py new file mode 100644 index 000000000..d5ac59dc2 --- /dev/null +++ b/scripts/validation/centroid/centroid_bias_v2.py @@ -0,0 +1,164 @@ +#!/usr/bin/env python +"""centroid_bias_v2.py + +Metacal multiplicative-bias validation using the ShapePipe ngmix v2.0 interface. + +Simulation from shapepipe.testing.simulate; fitting via +shapepipe.modules.ngmix_package.ngmix (Postage_stamp, do_ngmix_metacal, get_prior). + +Usage +----- + python centroid_bias_v2.py [--ntrial N] [--seed S] [--noise SIGMA] +""" + +import argparse + +import numpy as np + +from shapepipe.modules.ngmix_package.ngmix import ( + Postage_stamp, + do_ngmix_metacal, + get_prior, +) +from shapepipe.testing.simulate import make_data + + +# --------------------------------------------------------------------------- +# Analysis utilities +# --------------------------------------------------------------------------- + +def progress(total, miniters=1): + """Minimal progress printer.""" + sl = str(len(str(total))) + fmt = "%" + sl + "d/%" + sl + "d %3d%%" + last_print_n = 0 + last_len = 0 + for i in range(total): + yield i + num = i + 1 + if i == 0 or num == total or num - last_print_n >= miniters: + meter = fmt % (num, total, 100 * num // total) + print("\r" + meter + " " * max(last_len - len(meter), 0), + end="", flush=True) + last_len = len(meter) + last_print_n = num + print(flush=True) + + +def make_struct(res, shear_type): + """Pack a metacal result into a structured array row.""" + dt = [ + ("flags", "i4"), ("shear_type", "U7"), + ("s2n", "f8"), ("g", "f8", 2), ("T", "f8"), + ] + data = np.zeros(1, dtype=dt) + data["shear_type"] = shear_type + data["flags"] = res["flags"] + if res["flags"] == 0: + data["s2n"] = res.get("s2n", np.nan) + data["g"] = res["g"] + data["T"] = res.get("T", np.nan) + else: + data["s2n"] = data["g"] = data["T"] = np.nan + return data + + +def select(data, shear_type): + """Return indices where flags==0 and shear_type matches.""" + return np.where( + (data["flags"] == 0) & (data["shear_type"] == shear_type) + )[0] + + +# --------------------------------------------------------------------------- +# Main +# --------------------------------------------------------------------------- + +def main(ntrial=50, seed=42, sig_noise=1e-10, n_epochs=3, pixel_scale=0.1857): + + dg = 0.02 + + rng = np.random.RandomState(seed) + prior = get_prior(pixel_scale, rng) + shear_types = ["noshear", "1p", "1m"] + + seeds = rng.randint(0, 2 ** 30, size=ntrial) + + dlist_p, dlist_m = [], [] + + for i in progress(ntrial, miniters=10): + d_ = [] + for shear_true in [(dg, 0.00), (-dg, 0.00)]: + gals, psfs, psfs_sigmas, weights, flags, jacob_lists = make_data( + rng=np.random.RandomState(seeds[i]), + noise=sig_noise, + shear=shear_true, + n_epochs=n_epochs, + share_shift=False, + ) + + stamp = Postage_stamp(bkg_sub=False, megacam_flip=False) + stamp.gals = gals + stamp.psfs = psfs + stamp.weights = weights + stamp.flags = flags + stamp.jacobs = jacob_lists + + try: + resdict, psf_res = do_ngmix_metacal(stamp, prior, 1.0, rng) + stt = [make_struct(resdict[st], st) for st in shear_types] + except Exception: + continue + d_.append(np.hstack(stt)) + + if len(d_) != 2: + continue + dlist_p.extend(d_[0]) + dlist_m.extend(d_[1]) + + print() + + data_p = np.hstack(dlist_p) + data_m = np.hstack(dlist_m) + + w_p = select(data_p, "noshear") + R11_p = np.atleast_2d( + (data_p["g"][select(data_p, "1p"), 0] - data_p["g"][select(data_p, "1m"), 0]) / dg + ).T + w_m = select(data_m, "noshear") + R11_m = np.atleast_2d( + (data_m["g"][select(data_m, "1p"), 0] - data_m["g"][select(data_m, "1m"), 0]) / dg + ).T + + shear_ = (data_p["g"][w_p] - data_m["g"][w_m]) / (R11_p + R11_m) + shear = np.mean(shear_, axis=0) + shear_err = np.std(shear_, axis=0) / np.sqrt(len(shear_)) + + m = shear[0] / dg - 1 + merr = shear_err[0] / dg + s2n = data_p["s2n"][w_p].mean() + + print("S/N: %g" % s2n) + print("R11: %g %g" % (np.mean(R11_p), np.mean(R11_m))) + print("m[1e-3, 3sigmas]: %g +/- %g (99.7%% conf)" % (m / 1e-3, merr * 3 / 1e-3)) + print("c[1e-5, 3sigmas]: %g +/- %g (99.7%% conf)" % (shear[1] / 1e-5, shear_err[1] * 3 / 1e-5)) + + +if __name__ == "__main__": + parser = argparse.ArgumentParser( + description="Metacal centroid bias validation (v2 interface)" + ) + parser.add_argument("--ntrial", type=int, default=50) + parser.add_argument("--seed", type=int, default=42) + parser.add_argument("--noise", type=float, default=1e-10) + parser.add_argument("--n-epochs", type=int, default=3) + parser.add_argument("--pixel-scale", type=float, default=0.1857) + args = parser.parse_args() + + main( + ntrial=args.ntrial, + seed=args.seed, + sig_noise=args.noise, + n_epochs=args.n_epochs, + pixel_scale=args.pixel_scale, + ) diff --git a/scripts/validation/centroid/configs/centroid_bug.yaml b/scripts/validation/centroid/configs/centroid_bug.yaml new file mode 100644 index 000000000..a73cd2afe --- /dev/null +++ b/scripts/validation/centroid/configs/centroid_bug.yaml @@ -0,0 +1,7 @@ +conda_env: sp_centroid_bug +description: test_centroid_bug branch + aguinot/ngmix@stable_version (1.3.6) — shows + large m bias +name: centroid_bug +shapepipe_branch: test_centroid_bug +shapepipe_path: /automnt/n17data/mkilbing/astro/repositories/github/shapepipe_test_centroid_bug +test_script: scripts/validation/centroid/centroid_bias.py diff --git a/scripts/validation/centroid/configs/centroid_fix.yaml b/scripts/validation/centroid/configs/centroid_fix.yaml new file mode 100644 index 000000000..6cd997799 --- /dev/null +++ b/scripts/validation/centroid/configs/centroid_fix.yaml @@ -0,0 +1,7 @@ +conda_env: sp_centroid_fix +description: test_centroid_bug branch + aguinot/ngmix@fix_jac_centroid — preliminary + centroid fix +name: centroid_fix +shapepipe_branch: test_centroid_bug +shapepipe_path: /automnt/n17data/mkilbing/astro/repositories/github/shapepipe_test_centroid_bug +test_script: scripts/validation/centroid/centroid_bias.py diff --git a/scripts/validation/centroid/configs/centroid_v2.yaml b/scripts/validation/centroid/configs/centroid_v2.yaml new file mode 100644 index 000000000..8e72b6e67 --- /dev/null +++ b/scripts/validation/centroid/configs/centroid_v2.yaml @@ -0,0 +1,5 @@ +conda_env: sp_centroid_v2 +description: ngmix_v2.0 branch + ngmix v2.4+ (GalsimFitter, new prior API) +name: centroid_v2 +shapepipe_branch: ngmix_v2.0 +test_script: scripts/validation/centroid/centroid_bias_v2.py diff --git a/scripts/validation/centroid/envs_config/centroid_bug.yml b/scripts/validation/centroid/envs_config/centroid_bug.yml new file mode 100644 index 000000000..e26234fe5 --- /dev/null +++ b/scripts/validation/centroid/envs_config/centroid_bug.yml @@ -0,0 +1,19 @@ +name: sp_centroid_bug +# Minimal environment for the centroid bias test script. +# Only packages directly needed by test_centroid_shift.py and the +# shapepipe ngmix module it imports. +channels: + - conda-forge + - nodefaults +dependencies: + - python=3.10 + - astropy + - galsim + - numba + - numpy + - tqdm + - pip: + - cs_util==0.1 + - modopt + - sqlitedict + - git+https://github.com/aguinot/ngmix@stable_version diff --git a/scripts/validation/centroid/envs_config/centroid_fix.yml b/scripts/validation/centroid/envs_config/centroid_fix.yml new file mode 100644 index 000000000..e6fe329bf --- /dev/null +++ b/scripts/validation/centroid/envs_config/centroid_fix.yml @@ -0,0 +1,19 @@ +name: sp_centroid_fix +# Minimal environment for the centroid bias test script. +# Only packages directly needed by test_centroid_shift.py and the +# shapepipe ngmix module it imports. +channels: + - conda-forge + - nodefaults +dependencies: + - python=3.10 + - astropy + - galsim + - numba + - numpy + - tqdm + - pip: + - cs_util==0.1 + - modopt + - sqlitedict + - git+https://github.com/aguinot/ngmix@fix_jac_centroid diff --git a/scripts/validation/centroid/envs_config/centroid_v2.yml b/scripts/validation/centroid/envs_config/centroid_v2.yml new file mode 100644 index 000000000..6afb27939 --- /dev/null +++ b/scripts/validation/centroid/envs_config/centroid_v2.yml @@ -0,0 +1,14 @@ +name: sp_centroid_v2 +# Minimal environment for centroid_bias_v2.py (ngmix_v2.0 branch). +# Uses ngmix v2.4+ (GalsimFitter, new prior API). +channels: + - conda-forge + - nodefaults +dependencies: + - python=3.12 + - astropy + - galsim + - ngmix>=2.4 + - numba + - numpy + - tqdm diff --git a/scripts/validation/centroid/run_all.sh b/scripts/validation/centroid/run_all.sh new file mode 100755 index 000000000..d85dc8fda --- /dev/null +++ b/scripts/validation/centroid/run_all.sh @@ -0,0 +1,112 @@ +#!/bin/bash +# run_all.sh +# Run centroid bias validation tests. +# One-time setup steps are skipped if already done. +# +# Usage: run_all.sh [case] +# case One of: centroid_bug, centroid_fix, centroid_v2 (default: all three) + +ALL_CASES=(centroid_bug centroid_fix centroid_v2) + +if [[ $# -gt 0 ]]; then + case "$1" in + centroid_bug|centroid_fix|centroid_v2) + RUN_CASES=("$1") ;; + *) + echo "Unknown case '$1'. Valid options: ${ALL_CASES[*]}" >&2 + exit 1 ;; + esac +else + RUN_CASES=("${ALL_CASES[@]}") +fi + +path_to_val_cen=$HOME/astro/repositories/github/shapepipe/scripts/validation/centroid +path_to_envs=$path_to_val_cen/envs_config +script=$path_to_val_cen/run_bias_test.sh + +RUNDIR="$(pwd)" +SP_WORKTREE=/automnt/n17data/mkilbing/astro/repositories/github/shapepipe_test_centroid_bug +SP_MAIN=/automnt/n17data/mkilbing/astro/repositories/github/shapepipe + +export SP_ENV_DIR="${RUNDIR}/envs" + +# --------------------------------------------------------------------------- +# One-time setup (each step is skipped if already done) +# --------------------------------------------------------------------------- + +## Worktree for test_centroid_bug branch +if [[ ! -d "${SP_WORKTREE}" ]]; then + echo "Creating worktree for test_centroid_bug..." + git -C "${SP_MAIN}" worktree add "${SP_WORKTREE}" test_centroid_bug +else + echo "Worktree already exists: ${SP_WORKTREE}" +fi + +## Conda envs +for cfg in "${ALL_CASES[@]}"; do + env_name="sp_${cfg}" + if [[ ! -d "${SP_ENV_DIR}/${env_name}" ]]; then + echo "Creating conda env ${env_name}..." + CONDARC=~/.condarc mamba env create -y \ + -f "${path_to_envs}/${cfg}.yml" \ + --prefix "${SP_ENV_DIR}/${env_name}" + else + echo "Conda env already exists: ${env_name}" + fi +done + +## Install shapepipe into each env (editable, no deps) +declare -A ENV_SP_PATH=( + [sp_centroid_bug]="${SP_WORKTREE}" + [sp_centroid_fix]="${SP_WORKTREE}" + [sp_centroid_v2]="${SP_MAIN}" +) +for env_name in sp_centroid_bug sp_centroid_fix; do + pip_bin="${SP_ENV_DIR}/${env_name}/bin/pip" + sp_path="${ENV_SP_PATH[$env_name]}" + if [[ -f "${pip_bin}" ]]; then + if ! "${pip_bin}" show shapepipe &>/dev/null; then + echo "Installing shapepipe into ${env_name}..." + "${pip_bin}" install -e "${sp_path}" --no-deps -q + else + echo "shapepipe already installed in ${env_name}" + fi + fi +done + +## sp_centroid_v2: shapepipe + pip-only deps +## pip install is unreliable here (user ~/.local shadows env, requires-python mismatch), +## so we use direct --target installs and a .pth file for shapepipe. +python_v2="${SP_ENV_DIR}/sp_centroid_v2/bin/python" +pip_bin="${SP_ENV_DIR}/sp_centroid_v2/bin/pip" +if [[ -f "${python_v2}" ]]; then + site_pkg=$(PYTHONNOUSERSITE=1 "${python_v2}" -c "import site; print(site.getsitepackages()[0])") + + # shapepipe: .pth file into env site-packages (bypasses requires-python check) + pth_file="${site_pkg}/shapepipe.pth" + if [[ ! -f "${pth_file}" ]]; then + echo "Adding shapepipe src to sp_centroid_v2 via .pth file..." + echo "${SP_MAIN}/src" > "${pth_file}" + else + echo "shapepipe.pth already present in sp_centroid_v2" + fi + + # pip-only deps: use --target to install into env site-packages regardless + # of what is visible in ~/.local (pip --prefix sees user packages as satisfied) + for pkg in cs_util modopt sqlitedict; do + import_name="${pkg//-/_}" + if ! PYTHONNOUSERSITE=1 "${python_v2}" -c "import ${import_name}" 2>/dev/null; then + echo "Installing ${pkg} into sp_centroid_v2..." + "${pip_bin}" install "${pkg}" -q --target "${site_pkg}" + fi + done +fi + +# --------------------------------------------------------------------------- +# Run tests +# --------------------------------------------------------------------------- + +cd "${RUNDIR}" +for case in "${RUN_CASES[@]}"; do + "${script}" "${case}" +done diff --git a/scripts/validation/centroid/run_bias_test.sh b/scripts/validation/centroid/run_bias_test.sh new file mode 100755 index 000000000..1ff4da20b --- /dev/null +++ b/scripts/validation/centroid/run_bias_test.sh @@ -0,0 +1,100 @@ +#!/bin/bash +# run_bias_test.sh +# +# Run a centroid-bias test under the conda environment and shapepipe branch +# defined in configs/.yaml. +# +# The shapepipe repo root is derived automatically from this script's +# location (scripts/validation/centroid/ -> root). +# +# Results are written to ${SP_RESULTS_DIR}// where +# SP_RESULTS_DIR defaults to ~/astro/Runs/shapepipe/CFIS/centroid_bug/results +# and can be overridden by setting the environment variable. +# +# Conda envs are looked for at ${SCRIPT_DIR}/envs_config/. +# They are not committed; create them with: +# mamba env create -f envs_config/.yml --prefix envs/ +# i.e.: +# mamba env create -f envs_config/centroid_bug.yml --prefix envs/sp_centroid_bug +# mamba env create -f envs_config/centroid_fix.yml --prefix envs/sp_centroid_fix +# +# Usage: +# ./run_bias_test.sh centroid_bug +# ./run_bias_test.sh centroid_fix + +set -euo pipefail + +SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)" +# Repo root is 3 levels up from scripts/validation/centroid/ +REPO_ROOT="$(cd "${SCRIPT_DIR}/../../.." && pwd)" + +CONFIG_NAME="${1:?Usage: $0 }" +CONFIG_FILE="${SCRIPT_DIR}/configs/${CONFIG_NAME}.yaml" + +if [[ ! -f "$CONFIG_FILE" ]]; then + echo "ERROR: config not found: $CONFIG_FILE" + exit 1 +fi + +# Parse YAML config with Python (avoids yq dependency) +eval "$(python3 - < config value > default +DEFAULT_RESULTS="${HOME}/astro/Runs/shapepipe/CFIS/centroid_bug/results/${CONFIG_NAME}" +RESULTS_DIR="${SP_RESULTS_DIR:-${RESULTS_DIR:-${DEFAULT_RESULTS}}}" + +echo "=== Bias test: ${NAME} ===" +echo " ${DESCRIPTION}" +echo " conda env : ${CONDA_ENV}" +echo " branch : ${SHAPEPIPE_BRANCH}" +echo " shapepipe : ${SHAPEPIPE_PATH}" +echo " test script : ${TEST_SCRIPT}" +echo " results : ${RESULTS_DIR}" +echo + +# Verify branch +CURRENT_BRANCH=$(git -C "${SHAPEPIPE_PATH}" branch --show-current 2>/dev/null || echo "unknown") +if [[ "${CURRENT_BRANCH}" != "${SHAPEPIPE_BRANCH}" ]]; then + echo "ERROR: ${SHAPEPIPE_PATH} is on branch '${CURRENT_BRANCH}', expected '${SHAPEPIPE_BRANCH}'." + echo " Check out the correct branch or add a git worktree." + exit 1 +fi + +mkdir -p "${RESULTS_DIR}" +LOG="${RESULTS_DIR}/run_$(date +%Y%m%d_%H%M%S).log" +echo "Logging to ${LOG}" +echo + +# Conda envs: SP_ENV_DIR overrides the default (next to this script) +ENV_DIR="${SP_ENV_DIR:-${SCRIPT_DIR}/envs}" +ENV_PREFIX="${ENV_DIR}/${CONDA_ENV}" +if [[ ! -d "${ENV_PREFIX}" ]]; then + echo "ERROR: conda env not found at ${ENV_PREFIX}. Create it with:" + echo " CONDARC=~/.condarc mamba env create -f ${SCRIPT_DIR}/envs_config/${CONFIG_NAME}.yml --prefix ${ENV_PREFIX}" + echo " (set SP_ENV_DIR to use a custom env location)" + exit 1 +fi +echo " env prefix : ${ENV_PREFIX}" +echo + +# Call the env's Python directly to avoid mamba run lockfile issues. +# PYTHONNOUSERSITE=1 prevents ~/.local site-packages from overriding the +# conda env packages (e.g. a system-wide ngmix install). +PYTHONNOUSERSITE=1 \ +CONDARC="${HOME}/.condarc" \ +PYTHONPATH="${SHAPEPIPE_PATH}/src:${PYTHONPATH:-}" \ + "${ENV_PREFIX}/bin/python" "${SHAPEPIPE_PATH}/${TEST_SCRIPT}" \ + 2>&1 | tee "${LOG}" + +echo +echo "Done. Results in ${RESULTS_DIR}" diff --git a/src/shapepipe/modules/mask_package/mask.py b/src/shapepipe/modules/mask_package/mask.py index d4282bc60..17e052a6e 100644 --- a/src/shapepipe/modules/mask_package/mask.py +++ b/src/shapepipe/modules/mask_package/mask.py @@ -168,7 +168,7 @@ def _get_config(self): "PROGRAM_PATH", "WW_PATH" ) else: - self._config["PATH"]["WW"] = "ww" + self._config["PATH"]["WW"] = "weightwatcher" self._config["PATH"]["WW_configfile"] = conf.getexpanded( "PROGRAM_PATH", "WW_CONFIG_FILE" ) diff --git a/src/shapepipe/modules/mask_runner.py b/src/shapepipe/modules/mask_runner.py index 8cfd9375a..13fbf9b6c 100644 --- a/src/shapepipe/modules/mask_runner.py +++ b/src/shapepipe/modules/mask_runner.py @@ -15,7 +15,7 @@ file_pattern=["image", "weight", "flag"], file_ext=[".fits", ".fits", ".fits"], depends=["numpy", "astropy"], - executes=["ww"], + executes=["weightwatcher"], numbering_scheme="_0", ) def mask_runner( diff --git a/src/shapepipe/modules/mccd_interp_runner.py b/src/shapepipe/modules/mccd_interp_runner.py index 1428e44d6..1e3a28d50 100644 --- a/src/shapepipe/modules/mccd_interp_runner.py +++ b/src/shapepipe/modules/mccd_interp_runner.py @@ -90,9 +90,8 @@ def mccd_interp_runner( module = config.getexpanded(module_config_sec, "PSF_MODEL_DIR") psf_model_dir = get_last_dir(run_dirs["run_log"], module) psf_model_pattern = config.get(module_config_sec, "PSF_MODEL_PATTERN") - f_wcs_path = config.getexpanded(module_config_sec, "ME_LOG_WCS") - galcat_path = input_file_list[0] + f_wcs_path = input_file_list[1] inst = mccd_interp.MCCDinterpolator( None, diff --git a/src/shapepipe/modules/merge_headers_package/merge_headers.py b/src/shapepipe/modules/merge_headers_package/merge_headers.py index 5c0a2213e..1b15a1a5f 100644 --- a/src/shapepipe/modules/merge_headers_package/merge_headers.py +++ b/src/shapepipe/modules/merge_headers_package/merge_headers.py @@ -15,7 +15,7 @@ from sqlitedict import SqliteDict -def merge_headers(input_file_list, output_dir): +def merge_headers(input_file_list, output_dir, tile_number=None): """Merge Headers. This function opens the files in the input file list and merges them into @@ -27,6 +27,8 @@ def merge_headers(input_file_list, output_dir): List of input files output_dir : str Output path + tile_number : str, optional + Tile number ID stored under the key ``"TILE_ID"``, default is ``None`` Raises ------ @@ -41,10 +43,14 @@ def merge_headers(input_file_list, output_dir): ) # Open SqliteDict file - final_file = SqliteDict(f"{output_dir}/log_exp_headers.sqlite") + suffix = tile_number if tile_number else "" + final_file = SqliteDict(f"{output_dir}/log_exp_headers{suffix}.sqlite") # Set matching pattern pattern = "headers-" + if tile_number: + final_file["TILE_ID"] = tile_number + for file_path in input_file_list: # Extract file path file_path_scalar = file_path[0] diff --git a/src/shapepipe/modules/merge_headers_runner.py b/src/shapepipe/modules/merge_headers_runner.py index a176a493b..9bee35159 100644 --- a/src/shapepipe/modules/merge_headers_runner.py +++ b/src/shapepipe/modules/merge_headers_runner.py @@ -2,10 +2,13 @@ Module runner for ``merge_headers``. -:Author: Axel Guinot +:Authors: Axel Guinot, Martin Kilbinger """ +import os +import re + from shapepipe.modules.merge_headers_package.merge_headers import merge_headers from shapepipe.modules.module_decorator import module_runner from shapepipe.pipeline.exp_utils import get_exp_output_files @@ -48,7 +51,11 @@ def merge_headers_runner( ".npy", w_log=w_log, ) - merge_headers(headers_file_list, output_dir) + # Extract tile number from the exp_numbers filename, e.g. + # "exp_numbers-284.272-1.000.txt" -> "-284.272-1.000" + base = os.path.splitext(os.path.basename(exp_numbers_file))[0] + tile_number = re.sub(r"^exp_numbers", "", base) + merge_headers(headers_file_list, output_dir, tile_number) w_log.info(f"Merged {len(headers_file_list)} exposure header files") else: # Per-exposure mode: input_file_list already contains the header files. diff --git a/src/shapepipe/modules/ngmix_package/__init__.py b/src/shapepipe/modules/ngmix_package/__init__.py index 909631097..db546523e 100644 --- a/src/shapepipe/modules/ngmix_package/__init__.py +++ b/src/shapepipe/modules/ngmix_package/__init__.py @@ -2,7 +2,7 @@ This package contains the module for ``ngmix``. -:Author: Axel Guinot +:Author: Lucie Baumont, Axel Guinot :Parent modules: diff --git a/src/shapepipe/modules/ngmix_package/ngmix.py b/src/shapepipe/modules/ngmix_package/ngmix.py index 001c76e25..e62c83707 100644 --- a/src/shapepipe/modules/ngmix_package/ngmix.py +++ b/src/shapepipe/modules/ngmix_package/ngmix.py @@ -2,27 +2,171 @@ This module contains a class for ngmix shape measurement. -:Author: Axel Guinot +:Authors: Lucie Baumont, Axel Guinot """ -import re import os - -import galsim +import re import ngmix +import galsim import numpy as np from shutil import copyfile from astropy.io import fits from modopt.math.stats import sigma_mad -from ngmix.fitting import LMSimple -from ngmix.observation import MultiBandObsList, Observation, ObsList -from numpy.random import uniform as urand +from ngmix.observation import Observation, ObsList from sqlitedict import SqliteDict from shapepipe.pipeline import file_io +def get_prior(pixel_scale, rng, T_range=None, F_range=None): + """Build ngmix joint prior for a 6-parameter galaxy model. + + Parameters + ---------- + pixel_scale : float + Pixel scale in arcsec (sets centroid prior width). + rng : numpy.random.RandomState + Random state for all priors. + T_range : tuple of float, optional + (min, max) for flat size prior; default (-1, 1e3). + F_range : tuple of float, optional + (min, max) for flat flux prior; default (-100, 1e9). + + Returns + ------- + ngmix.joint_prior.PriorSimpleSep + """ + if T_range is None: + T_range = [-1.0, 1.0e3] + if F_range is None: + F_range = [-100.0, 1.0e9] + + cen_prior = ngmix.priors.CenPrior( + cen1=0.0, cen2=0.0, + sigma1=pixel_scale, sigma2=pixel_scale, + rng=rng, + ) + g_prior = ngmix.priors.GPriorBA(sigma=0.4, rng=rng) + T_prior = ngmix.priors.FlatPrior(minval=T_range[0], maxval=T_range[1], rng=rng) + F_prior = ngmix.priors.FlatPrior(minval=F_range[0], maxval=F_range[1], rng=rng) + + return ngmix.joint_prior.PriorSimpleSep( + cen_prior=cen_prior, + g_prior=g_prior, + T_prior=T_prior, + F_prior=F_prior, + ) + + +# I still don't know how to handle this +class Tile_cat(): + """Tile_cat. + + catalog measured on a tile + + Parameters + ---------- + cat_path + + """ + def __init__( + self, + cat_path + ): + self.cat_path = cat_path + if cat_path: + self.get_data(cat_path) + + def get_data(self, cat_path): + tile_cat = file_io.FITSCatalogue( + cat_path, + SEx_catalogue=True, + ) + tile_cat.open() + data = tile_cat.get_data() + cols = data.dtype.names + + self.obj_id = np.copy(data['NUMBER']) + self.ra = np.copy(data['XWIN_WORLD']) + self.dec = np.copy(data['YWIN_WORLD']) + + # Optional columns — may be absent in external (non-SExtractor) catalogs + self.flux = np.copy(data['FLUX_AUTO']) if 'FLUX_AUTO' in cols else None + self.vign = np.copy(data['VIGNET']) if 'VIGNET' in cols else None + self.size = np.copy(data['FWHM_WORLD']) if 'FWHM_WORLD' in cols else None + self.e = np.copy(data['ELLIPTICITY']) if 'ELLIPTICITY' in cols else None + self.theta = np.copy(data['THETA_WIN_WORLD']) if 'THETA_WIN_WORLD' in cols else None + + tile_cat.close() + +class Postage_stamp(): + """Galaxy Postage Stamp. + + Class to hold catalog of postage stamps for a single galaxy + + Parameters + ---------- + bkg_sub: bool + + megacam_flip: bool + We probably want to put weight and flag options here too + + """ + def __init__( + self, + bkg_sub=True, + megacam_flip=True + + ): + self.gals = [] + self.psfs = [] + self.weights = [] + self.flags = [] + self.jacobs = [] + self.bkg_sub = bkg_sub + self.megacam_flip = megacam_flip + +class Vignet(): + """Vignet. + + Class to hold catalog of postage stamps + + Parameters + ---------- + gal_vignet_path + bkg_vignet_path + psf_vignet_path + weight_vignet_path + flag_vignet_path + f_wcs_path + """ + def __init__( + self, + gal_vignet_path, + bkg_vignet_path, + psf_vignet_path, + weight_vignet_path, + flag_vignet_path, + f_wcs_path + + ): + self.f_wcs_file = SqliteDict(f_wcs_path) + self.gal_vign_cat = SqliteDict(gal_vignet_path) + self.bkg_vign_cat = SqliteDict(bkg_vignet_path) + self.psf_vign_cat = SqliteDict(psf_vignet_path) + self.weight_vign_cat = SqliteDict(weight_vignet_path) + self.flag_vign_cat = SqliteDict(flag_vignet_path) + + def close(self): + self.f_wcs_file.close() + self.gal_vign_cat.close() + self.bkg_vign_cat.close() + self.flag_vign_cat.close() + self.weight_vign_cat.close() + self.psf_vign_cat.close() + class Ngmix(object): """Ngmix. @@ -85,11 +229,21 @@ def __init__( ) self._tile_cat_path = input_file_list[0] - self._gal_vignet_path = input_file_list[1] - self._bkg_vignet_path = input_file_list[2] - self._psf_vignet_path = input_file_list[3] - self._weight_vignet_path = input_file_list[4] - self._flag_vignet_path = input_file_list[5] + self._vignet_cat = Vignet( + input_file_list[1], + input_file_list[2], + input_file_list[3], + input_file_list[4], + input_file_list[5], + f_wcs_path + ) + #self._gal_vignet_path = input_file_list[1] + #self._bkg_vignet_path = input_file_list[2] + #self._psf_vignet_path = input_file_list[3] + #self._weight_vignet_path = input_file_list[4] + #self._flag_vignet_path = input_file_list[5] + + self._output_dir = output_dir self._file_number_string = file_number_string @@ -97,6 +251,7 @@ def __init__( self._zero_point = zero_point self._pixel_scale = pixel_scale + # MKDEBUG check whether still used self._f_wcs_path = f_wcs_path self._check_existing_dir = check_existing_dir @@ -107,16 +262,17 @@ def __init__( self._w_log = w_log # Initiatlise random generator - seed = int("".join(re.findall(r"\d+", self._file_number_string))) - np.random.seed(seed) - self._w_log.info(f"Random generator initialisation seed = {seed}") + seed = int(''.join(re.findall(r'\d+', self._file_number_string))) + self._rng = np.random.RandomState(seed) + self._w_log.info(f'Random generator initialisation seed = {seed}') @classmethod def MegaCamFlip(self, vign, ccd_nb): """Flip for MegaCam. - MegaCam has CCDs that are upside down. This function flips the - postage stamps in these CCDs. + MegaPipe has CCDs that are upside down. This function flips the + postage stamps in these CCDs. TO DO: This will give incorrect results + when used with THELI ccds. Fix this. Parameters ---------- @@ -134,58 +290,28 @@ def MegaCamFlip(self, vign, ccd_nb): if ccd_nb < 18 or ccd_nb in [36, 37]: # swap x axis so origin is on top-right return np.rot90(vign, k=2) + print('rotating megapipe image') else: # swap y axis so origin is on bottom-left return vign - def get_prior(self): + def get_prior(self, T_range=None, F_range=None): """Get Prior. - Return prior for the different parameters. - Returns ------- - ngmix.priors - Priors for the different parameters - + ngmix.joint_prior.PriorSimpleSep """ - # Prior on ellipticity. Details do not matter, as long - # as it regularizes the fit. From Bernstein & Armstrong 2014 - g_sigma = 0.4 - g_prior = ngmix.priors.GPriorBA(g_sigma) - - # 2-d Gaussian prior on the center row and column center - # (relative to the center of the jacobian, which - # would be zero) and the sigma of the Gaussians. - # Units same as jacobian, probably arcsec - row, col = 0.0, 0.0 - row_sigma, col_sigma = self._pixel_scale, self._pixel_scale - cen_prior = ngmix.priors.CenPrior(row, col, row_sigma, col_sigma) - - # Size prior. Instead of flat, two-sided error function (TwoSidedErf) - # could be used - Tminval = -10.0 # arcsec squared - Tmaxval = 1.0e6 - T_prior = ngmix.priors.FlatPrior(Tminval, Tmaxval) - - # Flux prior. Bounds need to make sense for - # images in question - Fminval = -1.0e4 - Fmaxval = 1.0e9 - F_prior = ngmix.priors.FlatPrior(Fminval, Fmaxval) - - # Joint prior, combine all individual priors - prior = ngmix.joint_prior.PriorSimpleSep( - cen_prior, g_prior, T_prior, F_prior + return get_prior( + self._pixel_scale, self._rng, + T_range=T_range, F_range=F_range, ) - return prior - def compile_results(self, results): """Compile Results. - Prepare the results of NGMIX before saving. - + Prepare the results of NGMIX before saving. TO DO: add snr_r and T_r + This needs to be updated Parameters ---------- results : dict @@ -195,6 +321,7 @@ def compile_results(self, results): ------- dict Compiled results ready to be written to a file + note: psfo is the original image psf from psfex or mccd Raises ------ @@ -204,32 +331,37 @@ def compile_results(self, results): """ names = ["1m", "1p", "2m", "2p", "noshear"] names2 = [ - "id", - "n_epoch_model", - "moments_fail", - "ntry_fit", - "g1_psfo_ngmix", - "g2_psfo_ngmix", - "T_psfo_ngmix", - "g1_err_psfo_ngmix", - "g2_err_psfo_ngmix", - "T_err_psfo_ngmix", - "g1", - "g1_err", - "g2", - "g2_err", - "T", - "T_err", - "Tpsf", - "g1_psf", - "g2_psf", - "flux", - "flux_err", - "s2n", - "mag", - "mag_err", - "flags", - "mcal_flags", + 'id', + 'n_epoch_model', + 'moments_fail', + 'ntry_fit', + 'g1_psfo_ngmix', + 'g2_psfo_ngmix', + 'T_psfo_ngmix', + 'T_err_psfo_ngmix', + 'r50_psfo_ngmix', + 'g1_err_psfo_ngmix', + 'g2_err_psfo_ngmix', + 'r50_err_psfo_ngmix', + 'g1', + 'g1_err', + 'g2', + 'g2_err', + 'T', + 'T_err', + 'Tpsf', + 'r50', + 'r50_err', + 'r50psf', + 'g1_psf', + 'g2_psf', + 'flux', + 'flux_err', + 's2n', + 'mag', + 'mag_err', + 'flags', + 'mcal_flags' ] output_dict = {k: {kk: [] for kk in names2} for k in names} for idx in range(len(results)): @@ -252,7 +384,7 @@ def compile_results(self, results): output_dict[name]["moments_fail"].append( results[idx]["moments_fail"] ) - output_dict[name]["ntry_fit"].append(results[idx][name]["ntry"]) + output_dict[name]["ntry_fit"].append(results[idx][name]["nfev"]) output_dict[name]["g1_psfo_ngmix"].append( results[idx]["g_PSFo"][0] ) @@ -269,27 +401,30 @@ def compile_results(self, results): output_dict[name]["T_err_psfo_ngmix"].append( results[idx]["T_err_PSFo"] ) - output_dict[name]["g1"].append(results[idx][name]["g"][0]) - output_dict[name]["g1_err"].append( - results[idx][name]["pars_err"][2] + output_dict[name]['r50_psfo_ngmix'].append( + results[idx]['r50_PSFo'] ) - output_dict[name]["g2"].append(results[idx][name]["g"][1]) - output_dict[name]["g2_err"].append( - results[idx][name]["pars_err"][3] + output_dict[name]['r50_err_psfo_ngmix'].append( + results[idx]['r50_err_PSFo'] ) output_dict[name]["T"].append(results[idx][name]["T"]) output_dict[name]["T_err"].append(results[idx][name]["T_err"]) - output_dict[name]["Tpsf"].append(results[idx][name]["Tpsf"]) - output_dict[name]["g1_psf"].append( - results[idx][name]["gpsf"][0] + output_dict[name]["Tpsf"].append(results[idx]["T_PSFo"]) + output_dict[name]["g1_psf"].append(results[idx]["g_PSFo"][0]) + output_dict[name]["g2_psf"].append(results[idx]["g_PSFo"][1]) + output_dict[name]['r50'].append(results[idx][name]['pars'][4]) + output_dict[name]['r50_err'].append(results[idx][name]['pars_err'][4]) + output_dict[name]['r50psf'].append(results[idx]["r50_PSFo"]) + output_dict[name]["g1"].append(results[idx][name]["g"][0]) + output_dict[name]["g2"].append(results[idx][name]["g"][1]) + output_dict[name]["g1_err"].append( + np.sqrt(results[idx][name]["g_cov"][0, 0]) ) - output_dict[name]["g2_psf"].append( - results[idx][name]["gpsf"][1] + output_dict[name]["g2_err"].append( + np.sqrt(results[idx][name]["g_cov"][1, 1]) ) output_dict[name]["flux"].append(results[idx][name]["flux"]) - output_dict[name]["flux_err"].append( - results[idx][name]["flux_err"] - ) + output_dict[name]["flux_err"].append(results[idx][name]["flux_err"]) output_dict[name]["mag"].append(mag) output_dict[name]["mag_err"].append(mag_err) @@ -302,7 +437,7 @@ def compile_results(self, results): output_dict[name]["flags"].append(results[idx][name]["flags"]) output_dict[name]["mcal_flags"].append( - results[idx]["mcal_flags"] + results[idx].get("mcal_flags", 0) ) return output_dict @@ -365,8 +500,8 @@ def get_last_id(self, cat_path): for hdu_no in range(2, 6): if id_last != cat._cat_data[hdu_no].data["id"][-1]: raise ValueError( - "Last ID {cat._cat_data[hdu_no].data['id'][-1]} in HDU" - + f" #{hdu_no} inconsistent with {id_las}" + f"Last ID {cat._cat_data[hdu_no].data['id'][-1]} in HDU" + + f" #{hdu_no} inconsistent with {id_last}" ) return id_last @@ -462,234 +597,124 @@ def process(self): """Process. Funcion to processs NGMIX. - + organizes object cutouts from detection catalog in image, + weight, and flag files + per object: + gathers wcs and psf info from exposures + background subtracts (make this an option) + scales by relative zeropoints + runs metacal convolutions and ngmix fitting Returns ------- dict Dictionary containing the NGMIX metacal results """ - tile_cat = file_io.FITSCatalogue( - self._tile_cat_path, - SEx_catalogue=True, - ) - tile_cat.open() - obj_id = np.copy(tile_cat.get_data()["NUMBER"]) - tile_vign = np.copy(tile_cat.get_data()["VIGNET"]) - tile_ra = np.copy(tile_cat.get_data()["XWIN_WORLD"]) - tile_dec = np.copy(tile_cat.get_data()["YWIN_WORLD"]) - tile_cat.close() - - f_wcs_file = SqliteDict(self._f_wcs_path) - gal_vign_cat = SqliteDict(self._gal_vignet_path) - bkg_vign_cat = SqliteDict(self._bkg_vignet_path) - psf_vign_cat = SqliteDict(self._psf_vignet_path) - weight_vign_cat = SqliteDict(self._weight_vignet_path) - flag_vign_cat = SqliteDict(self._flag_vignet_path) + tile_cat = Tile_cat(self._tile_cat_path) + vignet_cat = self._vignet_cat final_res = [] prior = self.get_prior() count = 0 + n_empty_cat = 0 + n_no_epoch = 0 + n_ngmix_fail = 0 + n_fitted = 0 id_first = -1 id_last = -1 - - saved_batch_cumul = 0 count_batch = 0 + saved_batch_cumul = 0 - if self._save_batch > 0: - self._w_log.info( - f"Batch save mode, save every {self._save_batch} objectsa" - ) - else: - self._w_log.info(f"No batch mode") - - id_last = -1 - if self._check_existing_dir: - output_path_prev = self.get_output_path(self._check_existing_dir) - output_name_new = self.get_output_path(self._output_dir) - if os.path.exists(output_path_prev): - self._w_log.info( - f"Copy previous cat {output_path_prev} to {output_name_new}" - ) - copyfile(output_path_prev, output_name_new) - id_last = self.get_last_id(output_name_new) - else: - self._w_log.info( - f"No previous cat found in {self._check_existing_dir}," - + " starting from scratch" - ) - - self._w_log.info( - f"Processing objects # {self._id_obj_min} ... {self._id_obj_max}" - ) - for i_tile, id_tmp in enumerate(obj_id): - - # Continue if ID outside range of predefined IDs (in config file) - if self._id_obj_min > 0 and id_tmp < self._id_obj_min: + for i_tile, obj_id in enumerate(tile_cat.obj_id): + if self._id_obj_min > 0 and obj_id < self._id_obj_min: continue - if self._id_obj_max > 0 and id_tmp > self._id_obj_max: - continue - - # Continue if ID before last ID from previous run - if id_last > 0 and id_tmp < id_last: + if self._id_obj_max > 0 and obj_id > self._id_obj_max: continue - if id_first == -1: - id_first = id_tmp - id_last = id_tmp - str_id_tmp = str(id_tmp) - - gal_vign = [] - psf_vign = [] - sigma_psf = [] - weight_vign = [] - flag_vign = [] - jacob_list = [] - if psf_vign_cat[str_id_tmp] == "empty": - self._w_log.info(f"Skipping object {id_tmp}: empty PSF vignet") + id_first = obj_id + id_last = obj_id + count += 1 + + # Skip objects with no multi-epoch PSF or vignet data + if (vignet_cat.psf_vign_cat[str(obj_id)] == 'empty' + or vignet_cat.gal_vign_cat[str(obj_id)] == 'empty'): + n_empty_cat += 1 continue - self.check_key(str_id_tmp, gal_vign_cat, self._gal_vignet_path) - self.check_key(str_id_tmp, bkg_vign_cat, self._bkg_vignet_path) - self.check_key(str_id_tmp, flag_vign_cat, self._flag_vignet_path) - self.check_key(str_id_tmp, weight_vign_cat, self._weight_vignet_path) - if gal_vign_cat[str_id_tmp] == "empty": - self._w_log.info( - f"Skipping object {id_tmp}: empty galaxy vignet" - ) - continue + stamp = prepare_postage_stamps(vignet_cat, obj_id, i_tile, tile_cat) - psf_expccd_name = list(psf_vign_cat[str(id_tmp)].keys()) - for expccd_name_tmp in psf_expccd_name: - - self.check_key(expccd_name_tmp, gal_vign_cat[str_id_tmp], self._gal_vignet_path) - self.check_key(expccd_name_tmp, bkg_vign_cat[str_id_tmp], self._bkg_vignet_path) - self.check_key(expccd_name_tmp, flag_vign_cat[str_id_tmp], self._flag_vignet_path) - self.check_key(expccd_name_tmp, weight_vign_cat[str_id_tmp], self._weight_vignet_path) - - exp_name, ccd_n = re.split("-", expccd_name_tmp) - - gal_vign_tmp = gal_vign_cat[str_id_tmp][expccd_name_tmp][ - "VIGNET" - ] - if len(np.where(gal_vign_tmp.ravel() == 0)[0]) != 0: - self._w_log.info( - f"Skipping exp {expccd_name_tmp} for object {id_tmp}: zero-length galaxy vignet" - ) - continue - - bkg_vign_tmp = bkg_vign_cat[str_id_tmp][expccd_name_tmp][ - "VIGNET" - ] - gal_vign_sub_bkg = gal_vign_tmp - bkg_vign_tmp - - tile_vign_tmp = Ngmix.MegaCamFlip( - np.copy(tile_vign[i_tile]), int(ccd_n) - ) - - flag_vign_tmp = flag_vign_cat[str_id_tmp][expccd_name_tmp][ - "VIGNET" - ] - flag_vign_tmp[np.where(tile_vign_tmp == -1e30)] = 2**10 - v_flag_tmp = flag_vign_tmp.ravel() - if len(np.where(v_flag_tmp != 0)[0]) / (51 * 51) > 1 / 3.0: - self._w_log.info( - f"Skipping exp {expccd_name_tmp} for object {id_tmp}: mask > 1/3" - ) - continue - - weight_vign_tmp = weight_vign_cat[str_id_tmp][expccd_name_tmp][ - "VIGNET" - ] - - jacob_tmp = get_jacob( - f_wcs_file[exp_name][int(ccd_n)]["WCS"], - tile_ra[i_tile], - tile_dec[i_tile], - ) - - header_tmp = fits.Header.fromstring( - f_wcs_file[exp_name][int(ccd_n)]["header"] - ) - Fscale = header_tmp["FSCALE"] - - gal_vign_scaled = gal_vign_sub_bkg * Fscale - weight_vign_scaled = weight_vign_tmp * 1 / Fscale**2 - - gal_vign.append(gal_vign_scaled) - psf_vign.append( - psf_vign_cat[str_id_tmp][expccd_name_tmp]["VIGNET"] - ) - sigma_psf.append( - psf_vign_cat[str_id_tmp][expccd_name_tmp]["SHAPES"][ - "SIGMA_PSF_HSM" - ] - ) - weight_vign.append(weight_vign_scaled) - flag_vign.append(flag_vign_tmp) - jacob_list.append(jacob_tmp) - - if len(gal_vign) == 0: - self._w_log.info( - f"Skipping object {id_tmp}: no exposure vignets added" - ) + if len(stamp.gals) == 0: + n_no_epoch += 1 continue + try: - res = do_ngmix_metacal( - gal_vign, - psf_vign, - sigma_psf, - weight_vign, - flag_vign, - jacob_list, + flux_guess = ( + tile_cat.flux[i_tile] + if tile_cat.flux is not None + else 1.0 + ) + res, psf_res = do_ngmix_metacal( + stamp, prior, - self._pixel_scale, + flux_guess, + self._rng, ) except Exception as ee: self._w_log.info( - f"ngmix failed for object ID={id_tmp}.\nMessage: {ee}" + f'ngmix failed for object ID={obj_id}.\nMessage: {ee}' ) + n_ngmix_fail += 1 continue - count = count + 1 - count_batch = count_batch + 1 - - - res["obj_id"] = id_tmp - res["n_epoch_model"] = len(gal_vign) + res['obj_id'] = obj_id + res['n_epoch_model'] = len(stamp.gals) + res['moments_fail'] = sum( + 1 for k in ['noshear', '1p', '1m', '2p', '2m'] + if res.get(k, {}).get('flags', 0) != 0 + ) + r50_psfo = np.sqrt(max(psf_res['T_psf'], 0) / 2) + res['g_PSFo'] = psf_res['g_psf'] + res['g_err_PSFo'] = psf_res['g_psf_err'] + res['T_PSFo'] = psf_res['T_psf'] + res['T_err_PSFo'] = psf_res['T_psf_err'] + res['r50_PSFo'] = r50_psfo + res['r50_err_PSFo'] = ( + psf_res['T_psf_err'] / (2 * r50_psfo) if r50_psfo > 0 else np.nan + ) + res['mcal_flags'] = 0 final_res.append(res) + n_fitted += 1 + count_batch += 1 - if count_batch == self._save_batch: - - # Put batch results together + if self._save_batch > 0 and count_batch == self._save_batch: res_dict = self.compile_results(final_res) - - # Save batch to disk self.save_results(res_dict) - saved_batch_cumul += count_batch - self._w_log.info( - f"Batch-saved {count_batch} ({len(res_dict)} valid) objects to" - + f" file, cumul={saved_batch_cumul}" + f"Batch-saved {count_batch} ({len(res_dict)} valid) objects," + + f" cumul={saved_batch_cumul}" ) - - # Reset for next batch final_res = [] count_batch = 0 + if count % 1000 == 0: + self._w_log.info( + f"Progress: {count} iterated, {n_empty_cat} empty catalog," + + f" {n_no_epoch} no valid epoch, {n_ngmix_fail} fit failed," + + f" {n_fitted} fitted" + ) + self._w_log.info( - f"ngmix loop over objects finished, measured {count} " - + f"objects, id first/last={id_first}/{id_last}" + f"ngmix loop finished: {count} iterated" + + f" (id {id_first}/{id_last})," + + f" {n_empty_cat} empty catalog," + + f" {n_no_epoch} no valid epoch," + + f" {n_ngmix_fail} fit failed," + + f" {n_fitted} fitted" ) - f_wcs_file.close() - gal_vign_cat.close() - bkg_vign_cat.close() - flag_vign_cat.close() - weight_vign_cat.close() - psf_vign_cat.close() + vignet_cat.close() # Put all results together res_dict = self.compile_results(final_res) @@ -697,187 +722,133 @@ def process(self): # Save results self.save_results(res_dict) - self._w_log.info( - f"Saved {count} ({len(res_dict)}) objects to file" - ) - - -def get_guess( - img, - pixel_scale, - guess_flux_unit="img", - guess_size_type="T", - guess_size_unit="sky", - guess_centroid=True, - guess_centroid_unit="sky", -): - r"""Get Guess. - - Get the guess vector for the NGMIX shape measurement - ``[center_x, center_y, g1, g2, size_T, flux]``. - No guesses are given for the ellipticity ``(0, 0)``. - - Parameters - ---------- - img : numpy.ndarray - Array containing the image - pixel_scale : float - Approximation of the pixel scale - guess_flux_unit : str - If ``img`` returns the flux in pixel units, otherwise if ``sky`` - returns the flux in :math:`{\rm arcsec}^{-2}` - guess_size_type : str - If ``T`` returns the size in quadrupole moments definition - :math:`2\sigma^2`, otherwise if ``sigma`` returns the moments - :math:`\sigma` - guess_size_unit : str - If ``img`` returns the size in pixel units, otherwise if ``sky`` - returns the size in arcsec - guess_centroid : bool - If ``True``, will return a guess on the object centroid, otherwise if - ``False``, will return the image centre - guess_centroid_unit : str - If ``img`` returns the centroid in pixel unit, otherwise if ``sky`` - returns the centroid in arcsec - - Returns - ------- - numpy.ndarray - Return the guess array ``[center_x, center_y, g1, g2, size_T, flux]`` - - Raises - ------ - GalSimHSMError - For an error in the computation of adaptive moments - ValueError - For invalid unit guess types - - """ - galsim_img = galsim.Image(img, scale=pixel_scale) +def prepare_postage_stamps(vignet, obj_id, i_tile, tile_cat): + # define per-object lists of individual exposures to go into ngmix + stamp = Postage_stamp() + #identify exposure and ccd number from psf catalog + psf_expccd_names = list(vignet.psf_vign_cat[str(obj_id)].keys()) + for expccd_name in psf_expccd_names: + exp_name, ccd_n = re.split('-', expccd_name) - hsm_shape = galsim.hsm.FindAdaptiveMom(galsim_img, strict=False) + gal_vign = ( + vignet.gal_vign_cat[str(obj_id)][expccd_name]['VIGNET'] + ) - error_msg = hsm_shape.error_message + if np.all(gal_vign == 0): + continue + + if stamp.bkg_sub: + bkg_vign = ( + vignet.bkg_vign_cat[str(obj_id)][expccd_name]['VIGNET'] + ) + gal_vign_sub_bkg = background_subtract( + gal_vign, + bkg_vign + ) + else: + gal_vign_sub_bkg = gal_vign - if error_msg != "": - raise galsim.hsm.GalSimHSMError( - f"Error in adaptive moments :\n{error_msg}" + tile_vign = ( + np.copy(tile_cat.vign[i_tile]) + if tile_cat.vign is not None + else None ) + if stamp.megacam_flip and tile_vign is not None: + tile_vign = Ngmix.MegaCamFlip(tile_vign, int(ccd_n)) - if guess_flux_unit == "img": - guess_flux = hsm_shape.moments_amp - elif guess_flux_unit == "sky": - guess_flux = hsm_shape.moments_amp / pixel_scale**2 - else: - raise ValueError( - f"invalid guess_flux_unit '{guess_flux_unit}'," - + " must be one of 'img', 'sky'" + flag_vign = ( + vignet.flag_vign_cat[str(obj_id)][expccd_name]['VIGNET'] ) + if tile_vign is not None: + flag_vign[np.where(tile_vign == -1e30)] = 2**10 + v_flag_tmp = flag_vign.ravel() + # remove objects that are more than 1/3 masked + if len(np.where(v_flag_tmp != 0)[0]) / (51 * 51) > 1 / 3.0: + continue - if guess_size_unit == "img": - size_unit = 1.0 - elif guess_size_unit == "sky": - size_unit = pixel_scale - else: - raise ValueError( - "invalid guess_size_unit '{guess_size_unit}'," - + "must be one of 'img', 'sky'" + weight_vign = ( + vignet.weight_vign_cat[str(obj_id)][expccd_name]['VIGNET'] ) - if guess_size_type == "sigma": - guess_size = hsm_shape.moments_sigma * size_unit - elif guess_size_type == "T": - guess_size = 2 * (hsm_shape.moments_sigma * size_unit) ** 2 - - if guess_centroid_unit == "img": - centroid_unit = 1 - elif guess_centroid_unit == "sky": - centroid_unit = pixel_scale - else: - raise ValueError( - f"invalid guess_centroid_unit '{guess_centroid_unit}'," - + " must be one of 'img', 'sky'" + jacob = get_galsim_jacobian( + vignet.f_wcs_file[exp_name][int(ccd_n)]['WCS'], + tile_cat.ra[i_tile], + tile_cat.dec[i_tile] ) - if guess_centroid: - guess_centroid = ( - hsm_shape.moments_centroid - galsim_img.center - ) * centroid_unit - else: - guess_centroid = galsim_img.center * centroid_unit - - guess = np.array( - [guess_centroid.x, guess_centroid.y, 0.0, 0.0, guess_size, guess_flux] - ) - - return guess - + header = fits.Header.fromstring( + vignet.f_wcs_file[exp_name][int(ccd_n)]['header'] + ) -def make_galsimfit(obs, model, guess0, prior=None, ntry=5): - """Make GalSim Fit. + # rescale by relative zero-points + gal_vign_scaled, weight_vign_scaled = rescale_epoch_fluxes( + gal_vign_sub_bkg, + weight_vign, + header + ) - Fit image using simple GalSim model. + # gather postage stamps in all of the epochs + stamp.gals.append(gal_vign_scaled) + stamp.psfs.append( + vignet.psf_vign_cat[str(obj_id)][expccd_name]['VIGNET'] + ) + stamp.weights.append(weight_vign_scaled) + stamp.flags.append(flag_vign) + stamp.jacobs.append(jacob) + + return stamp +def background_subtract(gal,bkg): + """background subtraction. + Parameters ---------- - obs : ngmix.observation.Observation - Image to fit - model : str - Model for fit - guess0 : numpy.ndarray - Parameters of first model guess - prior : ngmix.prior, optional - Prior for fit paraemeters - ntry : int, optional - Number of tries for fit, the default is ``5`` - + gal : numpy.ndarray + galaxy image + bkg : numpy.ndarray + background + Returns ------- - dict - Results - - Raises - ------ - ngmix.BootGalFailure - Failure to bootstrap galaxy - + numpy.ndarray + background subtracted galaxy """ - limit = 0.1 - - guess = np.copy(guess0) - fres = {} - for it in range(ntry): - guess[0:5] += urand(low=-limit, high=limit) - guess[5:] *= 1 + urand(low=-limit, high=limit) - fres["flags"] = 1 - try: - fitter = ngmix.galsimfit.GalsimSimple( - obs, - model, - prior=prior, - ) - fitter.go(guess) - fres = fitter.get_result() - except Exception: - continue - - if fres["flags"] == 0: - break - if fres["flags"] != 0: - raise ngmix.gexceptions.BootGalFailure( - "Failed to fit galaxy image with galsimfit" - ) + # background subtraction + gal_vign_sub_bkg = gal - bkg - fres["ntry"] = it + 1 + return gal_vign_sub_bkg - return fres +def rescale_epoch_fluxes(gal,weight,header): + """rescale epochs by relative zeropoints to be on the same flux scale + + Parameters + ---------- + gal : numpy.ndarray + background subtracted galaxy image + weight : numpy.ndarray + weight image + header : + image header + + Returns + ------- + numpy.ndarray + rescaled galaxy image + numpy.ndarray + rescaled weight image + """ + Fscale = header['FSCALE'] + gal_scaled = gal * Fscale + weight_scaled = weight * 1 / Fscale ** 2 -def get_jacob(wcs, ra, dec): - """Get Jacobian. + return gal_scaled, weight_scaled - Return the Jacobian of the WCS at the required position. +def get_galsim_jacobian(wcs, ra, dec): + """Get local wcs. + This produces a galsim jacobian at a point. We call it local_wcs because we convert to a ngmix object to create the jacobian later. + TO DO: can we do this within ngmix? Parameters ---------- @@ -905,8 +876,8 @@ def get_jacob(wcs, ra, dec): def get_noise(gal, weight, guess, pixel_scale, thresh=1.2): - r"""Get Noise. - + """Get Noise. + TO DO: modify guess, pixel scale Compute the sigma of the noise from an object postage stamp. Use a guess on the object size, ellipticity and flux to create a window function. @@ -919,12 +890,12 @@ def get_noise(gal, weight, guess, pixel_scale, thresh=1.2): Weight image guess : list Gaussian parameters fot the window function - ``[x0, y0, g1, g2, T, flux]`` + ``[x0, y0, g1, g2, r50, flux]`` pixel_scale : float Pixel scale of the galaxy image thresh : float, optional Threshold to cut the window function, - cut = ``thresh`` * :math:`\sigma_{\rm noise}`; the default is ``1.2`` + cut = ``thresh`` * sigma_noise; the default is ``1.2`` Returns ------- @@ -933,7 +904,6 @@ def get_noise(gal, weight, guess, pixel_scale, thresh=1.2): """ img_shape = gal.shape - m_weight = weight != 0 sig_tmp = sigma_mad(gal[m_weight]) @@ -950,241 +920,239 @@ def get_noise(gal, weight, guess, pixel_scale, thresh=1.2): return sig_noise - -def do_ngmix_metacal( - gals, psfs, psfs_sigma, weights, flags, jacob_list, prior, pixel_scale -): - """Do Ngmix Metacal. - - Perform the metacalibration on a multi-epoch object and return the joint - shape measurement with NGMIX. +def prepare_ngmix_weights(gal, weight, flag): + """bookkeeping for ngmix weights. runs on a single galaxy and epoch + pixel scale and galaxy guess + TO DO: decide if we want galaxy guess stuff Parameters ---------- - gals : list - List of the galaxy vignets - psfs : list - List of the PSF vignets - psfs_sigma : list - List of the sigma PSFs - weights : list - List of the weight vignets - flags : list - List of the flag vignets - jacob_list : list - List of the Jacobians - prior : ngmix.priors - Priors for the fitting parameters - pixel_scale : float - pixel scale in arcsec + gal : numpy.ndarray + weight : numpy.ndarray + flag : numpy.ndarray Returns ------- - dict - Dictionary containing the results of NGMIX metacal - + numpy.ndarray + Galaxy image with masked pixels replaced by noise. + numpy.ndarray + Variance map for NGMIX. + numpy.ndarray + Noise image. """ - n_epoch = len(gals) + weight_map = np.copy(weight) + weight_map[flag != 0] = 0.0 - if n_epoch == 0: - raise ValueError("0 epoch to process") + sig_noise = sigma_mad(gal) - # Make observation - gal_obs_list = ObsList() - T_guess_psf = [] - psf_res_gT = { - "g_PSFo": np.array([0.0, 0.0]), - "g_err_PSFo": np.array([0.0, 0.0]), - "T_PSFo": 0.0, - "T_err_PSFo": 0.0, - } - gal_guess = [] - gal_guess_flag = True - wsum = 0 - for n_e in range(n_epoch): + noise_img = np.random.randn(*gal.shape) * sig_noise + noise_img_gal = np.random.randn(*gal.shape) * sig_noise - psf_jacob = ngmix.Jacobian( - row=(psfs[0].shape[0] - 1) / 2, - col=(psfs[0].shape[1] - 1) / 2, - wcs=jacob_list[n_e], - ) - - psf_obs = Observation(psfs[n_e], jacobian=psf_jacob) + gal_masked = np.copy(gal) + if (weight_map == 0).any(): + gal_masked[weight_map == 0] = noise_img_gal[weight_map == 0] - psf_T = psfs_sigma[n_e] * 1.17741 * pixel_scale + weight_map *= 1 / sig_noise ** 2 - weight_map = np.copy(weights[n_e]) - weight_map[np.where(flags[n_e] != 0)] = 0.0 - weight_map[weight_map != 0] = 1 - - psf_guess = np.array([0.0, 0.0, 0.0, 0.0, psf_T, 1.0]) - try: - psf_res = make_galsimfit(psf_obs, "gauss", psf_guess) - except Exception: - continue + return gal_masked, weight_map, noise_img - # Gal guess - try: - gal_guess_tmp = get_guess( - gals[n_e], pixel_scale, guess_size_type="sigma" - ) - except Exception: - gal_guess_flag = False - gal_guess_tmp = np.array([0.0, 0.0, 0.0, 0.0, 1, 100]) - - # Recenter jacobian if necessary - gal_jacob = ngmix.Jacobian( - row=(gals[0].shape[0] - 1) / 2 + gal_guess_tmp[0], - col=(gals[0].shape[1] - 1) / 2 + gal_guess_tmp[1], - wcs=jacob_list[n_e], - ) +def make_ngmix_observation(gal, weight, flag, psf, wcs): + """Build an ngmix Observation for a single galaxy epoch. - # Noise handling - if gal_guess_flag: - sig_noise = get_noise( - gals[n_e], - weight_map, - gal_guess_tmp, - pixel_scale, - ) - else: - sig_noise = sigma_mad(gals[n_e]) + The galaxy Jacobian is re-centered on the HSM centroid so that the + centroid prior (centered at the Jacobian origin) does not bias the fit. - noise_img = np.random.randn(*gals[n_e].shape) * sig_noise - noise_img_gal = np.random.randn(*gals[n_e].shape) * sig_noise + Parameters + ---------- + gal : numpy.ndarray + weight : numpy.ndarray + flag : numpy.ndarray + psf : numpy.ndarray + wcs : galsim.BaseWCS + Local WCS Jacobian at the object position. - gal_masked = np.copy(gals[n_e]) - if len(np.where(weight_map == 0)[0]) != 0: - gal_masked[weight_map == 0] = noise_img_gal[weight_map == 0] + Returns + ------- + ngmix.observation.Observation + """ + psf_jacob = ngmix.Jacobian( + row=(psf.shape[0] - 1) / 2, + col=(psf.shape[1] - 1) / 2, + wcs=wcs, + ) + psf_obs = Observation(psf, jacobian=psf_jacob) - weight_map *= 1 / sig_noise**2 + gal_masked, weight_map, noise_img = prepare_ngmix_weights(gal, weight, flag) - # Original PSF fit - w_tmp = np.sum(weight_map) - psf_res_gT["g_PSFo"] += psf_res["g"] * w_tmp - psf_res_gT["g_err_PSFo"] += ( - np.array([psf_res["pars_err"][2], psf_res["pars_err"][3]]) * w_tmp - ) - psf_res_gT["T_PSFo"] += psf_res["T"] * w_tmp - psf_res_gT["T_err_PSFo"] += psf_res["T_err"] * w_tmp - wsum += w_tmp - - gal_obs = Observation( - gal_masked, - weight=weight_map, - jacobian=gal_jacob, - psf=psf_obs, - noise=noise_img, + # Re-center Jacobian on HSM centroid (pixel offset from stamp center). + # Fixes: centroid prior biases fit when galaxy is offset from stamp center. + try: + _hsm = galsim.hsm.FindAdaptiveMom( + galsim.Image(gal, scale=1.0), strict=False ) + if _hsm.error_message != "": + raise galsim.hsm.GalSimHSMError(_hsm.error_message) + _cen = _hsm.moments_centroid - galsim.Image(gal, scale=1.0).center + cen_row, cen_col = _cen.y, _cen.x + except Exception: + cen_row, cen_col = 0.0, 0.0 + + gal_jacob = ngmix.Jacobian( + row=(gal.shape[0] - 1) / 2 + cen_row, + col=(gal.shape[1] - 1) / 2 + cen_col, + wcs=wcs, + ) - if gal_guess_flag: - gal_guess_tmp[:2] = 0 - gal_guess.append(gal_guess_tmp) + return Observation( + gal_masked, + weight=weight_map, + jacobian=gal_jacob, + psf=psf_obs, + noise=noise_img, + ) - gal_obs_list.append(gal_obs) - T_guess_psf.append(psf_T) - gal_guess_flag = True +def average_multiepoch_psf(obsdict): + """ averages psf information over multiple epochs + we may need to do this for original psf as well + Parameters + ---------- + obsdict : dict + Observation dict returned by MetacalBootstrapper.go(). - if wsum == 0: - raise ZeroDivisionError("Sum of weights = 0, division by zero") + Returns + ------- + dict + Keys: 'g_psf', 'g_psf_err', 'T_psf', 'T_psf_err' (weighted averages). + """ + # create dictionary + names = ['T_psf', 'T_psf_err', 'g_psf', 'g_psf_err'] + psf_dict = {k: [] for k in names} + nepoch = len(obsdict['noshear']) + wsum = 0 + g_psf_sum = np.array([0., 0.]) + g_psf_err_sum = np.array([0., 0.]) + T_psf_sum = 0 + T_psf_err_sum = 0 + for n_e in np.arange(nepoch): + T_psf=obsdict['noshear'][n_e].psf.meta['result']['T'] + T_psf_err=obsdict['noshear'][n_e].psf.meta['result']['T_err'] + g_psf=obsdict['noshear'][n_e].psf.meta['result']['g'] + g_psf_err=obsdict['noshear'][n_e].psf.meta['result']['g_err'] + ne_wsum = obsdict['noshear'][n_e].weight.sum() + + wsum += ne_wsum + g_psf_sum += g_psf * ne_wsum + g_psf_err_sum += g_psf_err * ne_wsum + T_psf_sum += T_psf * ne_wsum + T_psf_err_sum += T_psf_err * ne_wsum - # Normalize PSF fit output - for key in psf_res_gT.keys(): - psf_res_gT[key] /= wsum + if wsum == 0: + raise ZeroDivisionError('Sum of weights = 0, division by zero') - # Gal guess handling - fail_get_guess = False - if len(gal_guess) == 0: - fail_get_guess = True - gal_pars = [0.0, 0.0, 0.0, 0.0, 1, 100] - else: - gal_pars = np.mean(gal_guess, 0) + psf_dict['g_psf'] = g_psf_sum / wsum + psf_dict['g_psf_err'] = g_psf_err_sum / wsum + psf_dict['T_psf'] = T_psf_sum / wsum + psf_dict['T_psf_err'] = T_psf_err_sum / wsum - psf_model = "gauss" - gal_model = "gauss" + return psf_dict - # metacal specific parameters - metacal_pars = { - "types": ["noshear", "1p", "1m", "2p", "2m"], - "step": 0.01, - "psf": "gauss", - "fixnoise": True, - "cheatnoise": False, - "symmetrize_psf": False, - "use_noise_image": True, - } - Tguess = np.mean(T_guess_psf) +def do_ngmix_metacal(stamp, prior, flux_guess, rng): + """Do Ngmix Metacal. - # retry the fit twice - ntry = 2 + Performs metacalibration on a single multi-epoch object and returns the + joint shape measurement with NGMIX. - obs_dict_mcal = ngmix.metacal.get_all_metacal(gal_obs_list, **metacal_pars) - res = {"mcal_flags": 0} + Parameters + ---------- + stamp : Postage_stamp + Postage stamps for all epochs of one galaxy. + prior : ngmix.joint_prior.PriorSimpleSep + Priors for the fitting parameters. + flux_guess : float + Initial flux guess. + rng : numpy.random.RandomState + Random state for guesses and priors. - ntry = 5 + Returns + ------- + tuple + (resdict, psf_res) where resdict is the MetacalBootstrapper result + dict and psf_res is the averaged PSF dict from average_multiepoch_psf. + """ + n_epoch = len(stamp.gals) + if n_epoch == 0: + raise ValueError("0 epoch to process") - for key in sorted(obs_dict_mcal): + psf_model = 'gauss' + gal_model = 'gauss' - fres = make_galsimfit( - obs_dict_mcal[key], gal_model, gal_pars, prior=prior + gal_obs_list = ObsList() + for n_e in range(n_epoch): + gal_obs = make_ngmix_observation( + stamp.gals[n_e], + stamp.weights[n_e], + stamp.flags[n_e], + stamp.psfs[n_e], + stamp.jacobs[n_e], ) + gal_obs_list.append(gal_obs) - res["mcal_flags"] |= fres["flags"] - tres = {} - - for name in fres.keys(): - tres[name] = fres[name] - tres["flags"] = fres["flags"] - - wsum = 0 - Tpsf_sum = 0 - gpsf_sum = np.zeros(2) - npsf = 0 - for obs in obs_dict_mcal[key]: - - if hasattr(obs, "psf_nopix"): - try: - psf_res = make_galsimfit( - obs.psf_nopix, - psf_model, - np.array([0.0, 0.0, 0.0, 0.0, Tguess, 1.0]), - ntry=ntry, - ) - except Exception: - continue - g1, g2 = psf_res["g"] - T = psf_res["T"] - else: - try: - psf_res = make_galsimfit( - obs.psf, - psf_model, - np.array([0.0, 0.0, 0.0, 0.0, Tguess, 1.0]), - ) - except Exception: - continue - g1, g2 = psf_res["g"] - T = psf_res["T"] + fitter = ngmix.fitting.Fitter(model=gal_model, prior=prior) + guesser = ngmix.guessers.TPSFFluxAndPriorGuesser(rng=rng, T=0.25, prior=prior) + + psf_fitter = ngmix.fitting.Fitter(model=psf_model, prior=prior) + psf_guesser = ngmix.guessers.TFluxGuesser(rng=rng, T=0.25, prior=prior, flux=flux_guess) + + psf_runner = ngmix.runners.PSFRunner(fitter=psf_fitter, guesser=psf_guesser, ntry=2) + runner = ngmix.runners.Runner(fitter=fitter, guesser=guesser, ntry=5) - # TODO we sometimes use other weights - twsum = obs.weight.sum() + metacal_pars = { + 'types': ['noshear', '1p', '1m', '2p', '2m'], + 'step': 0.01, + 'psf': 'fitgauss', + 'fixnoise': True, + 'use_noise_image': True, + } - wsum += twsum - gpsf_sum[0] += g1 * twsum - gpsf_sum[1] += g2 * twsum - Tpsf_sum += T * twsum - npsf += 1 + boot = ngmix.metacal.MetacalBootstrapper( + runner=runner, + psf_runner=psf_runner, + ignore_failed_psf=True, + rng=rng, + **metacal_pars, + ) + resdict, obsdict = boot.go(gal_obs_list) + psf_res = average_multiepoch_psf(obsdict) + return resdict, psf_res - tres["gpsf"] = gpsf_sum / wsum - tres["Tpsf"] = Tpsf_sum / wsum - res[key] = tres +# Define the SExtractor parameters for a galaxy +def sextractor_e1e2(e,theta): + """sextractor_e1e2 - # result dictionary, keyed by the types in metacal_pars above - metacal_res = res + computes ellipticity from sextrator quantities + Parameters + ---------- + stamp : Postage_stamp + List of the galaxy vignets. List indices run over epochs + prior : ngmix.priors + Priors for the fitting parameters + flux_guess : np.ndarray + guess for flux + pixel_scale : float + pixel scale in arcsec + rng : numpy.random.RandomState + Random state for guesses and priors - metacal_res.update(psf_res_gT) - metacal_res["moments_fail"] = fail_get_guess + Returns + ------- + np.ndarray + ellipticity - return metacal_res + """ + # Convert the position angle from degrees to radians + phi = np.radians(theta) - np.pi/2 + # Calculate the ellipticity vector + e_vec = e * np.array([np.cos(2*phi), np.sin(2*phi)]) + return e_vec diff --git a/src/shapepipe/modules/ngmix_runner.py b/src/shapepipe/modules/ngmix_runner.py index fbdc533c7..b0e91a236 100644 --- a/src/shapepipe/modules/ngmix_runner.py +++ b/src/shapepipe/modules/ngmix_runner.py @@ -16,6 +16,7 @@ "sextractor_runner", "psfex_interp_runner", "vignetmaker_runner", + "merge_headers_runner", ], file_pattern=[ "tile_sexcat", @@ -24,8 +25,9 @@ "galaxy_psf", "weight", "flag", + "log_exp_headers", ], - file_ext=[".fits", ".sqlite", ".sqlite", ".sqlite", ".sqlite", ".sqlite"], + file_ext=[".fits", ".sqlite", ".sqlite", ".sqlite", ".sqlite", ".sqlite", ".sqlite"], depends=["numpy", "ngmix", "galsim", "sqlitedict", "astropy"], ) def ngmix_runner( @@ -46,7 +48,7 @@ def ngmix_runner( pixel_scale = config.getfloat(module_config_sec, "PIXEL_SCALE") # Path to merged single-exposure single-HDU headers - f_wcs_path = config.getexpanded(module_config_sec, "LOG_WCS") + f_wcs_path = input_file_list[6] # Input directory to check for already retrieved files if config.has_option(module_config_sec, "CHECK_EXISTING_DIR"): @@ -72,8 +74,9 @@ def ngmix_runner( id_obj_max = config.getint(module_config_sec, "ID_OBJ_MAX") # Initialise class instance + # input_file_list[6] is log_exp_headers, already extracted as f_wcs_path ngmix_inst = Ngmix( - input_file_list, + input_file_list[:6], run_dirs["output"], file_number_string, zero_point, diff --git a/src/shapepipe/modules/psfex_interp_package/psfex_interp.py b/src/shapepipe/modules/psfex_interp_package/psfex_interp.py index da12f2582..956092f2e 100644 --- a/src/shapepipe/modules/psfex_interp_package/psfex_interp.py +++ b/src/shapepipe/modules/psfex_interp_package/psfex_interp.py @@ -625,6 +625,8 @@ def _interpolate_me(self): array_id = None array_shape = None array_exp_name = None + n_ccd_valid = 0 + n_ccd_total = sum(1 for c in ccd_list if c != -1) for ccd in ccd_list: if ccd == -1: continue @@ -718,9 +720,22 @@ def _interpolate_me(self): else: array_exp_name = np.concatenate((array_exp_name, exp_name_tmp)) - final_list.append( - [array_id, array_psf, array_shape, array_exp_name] - ) + n_ccd_valid += 1 + + if array_id is not None: + n_psf = len(array_id) + self._w_log.info( + f"Exposure {exp_name}: {n_psf} PSFs from" + + f" {n_ccd_valid}/{n_ccd_total} CCDs" + ) + final_list.append( + [array_id, array_psf, array_shape, array_exp_name] + ) + else: + self._w_log.info( + f"All CCDs skipped for exposure {exp_name} " + + "(no valid PSF model); epoch excluded from output" + ) self._f_wcs_file.close() cat.close() diff --git a/src/shapepipe/modules/psfex_interp_runner.py b/src/shapepipe/modules/psfex_interp_runner.py index 55d8d73c1..c382184f1 100644 --- a/src/shapepipe/modules/psfex_interp_runner.py +++ b/src/shapepipe/modules/psfex_interp_runner.py @@ -9,6 +9,7 @@ from shapepipe.modules.module_decorator import module_runner from shapepipe.modules.psfex_interp_package import psfex_interp +from shapepipe.pipeline.exp_utils import get_exp_output_dirs from shapepipe.pipeline.run_log import get_last_dir, get_all_dirs @@ -62,29 +63,38 @@ def psfex_interp_runner( elif mode == "MULTI-EPOCH": # Fetch multi-epoch parameters - module = config.getexpanded( - module_config_sec, - "ME_DOT_PSF_DIR", - ) - module_name = module.split(":")[-1] - if "last" in module: - dot_psf_dirs = [get_last_dir(run_dirs["run_log"], module_name)] - elif "all" in module: - dot_psf_dirs = get_all_dirs(run_dirs["run_log"], module_name) + if config.has_option(module_config_sec, "ME_DOT_PSF_EXP_DIR"): + # v2.0: locate psfex_runner output dirs via the $SP_EXP tree + exp_base_dir = config.getexpanded( + module_config_sec, "ME_DOT_PSF_EXP_DIR" + ) + exp_numbers_file = input_file_list[2] + dot_psf_dirs = get_exp_output_dirs( + exp_base_dir, exp_numbers_file, "psfex_runner", w_log + ) else: - raise ValueError( - "Expected qualifier 'last:' or 'all' before module" - + f" '{module}' in config entry 'ME_DOT_PSF_DIR'" + module = config.getexpanded( + module_config_sec, + "ME_DOT_PSF_DIR", ) + module_name = module.split(":")[-1] + if "last" in module: + dot_psf_dirs = [get_last_dir(run_dirs["run_log"], module_name)] + elif "all" in module: + dot_psf_dirs = get_all_dirs(run_dirs["run_log"], module_name) + else: + raise ValueError( + "Expected qualifier 'last:' or 'all' before module" + + f" '{module}' in config entry 'ME_DOT_PSF_DIR'" + ) dot_psf_pattern = config.get( module_config_sec, "ME_DOT_PSF_PATTERN", ) - f_wcs_path = config.getexpanded(module_config_sec, "ME_LOG_WCS") - # Set input paths galcat_path = input_file_list[0] + f_wcs_path = input_file_list[1] # Create instance of PSFExInterpolator psfex_interp_inst = psfex_interp.PSFExInterpolator( diff --git a/src/shapepipe/modules/read_ext_sexcat_runner.py b/src/shapepipe/modules/read_ext_sexcat_runner.py index 949f5a7c7..57035a9b6 100644 --- a/src/shapepipe/modules/read_ext_sexcat_runner.py +++ b/src/shapepipe/modules/read_ext_sexcat_runner.py @@ -61,7 +61,7 @@ def read_ext_sexcat_runner( ) if config.getboolean(module_config_sec, "MAKE_POST_PROCESS"): - f_wcs_path = config.getexpanded(module_config_sec, "LOG_WCS") + f_wcs_path = input_file_list[2] pos_params = config.getlist(module_config_sec, "WORLD_POSITION") ccd_size = config.getlist(module_config_sec, "CCD_SIZE") w_log.info("Running post-processing") diff --git a/src/shapepipe/modules/sextractor_runner.py b/src/shapepipe/modules/sextractor_runner.py index 87bc02c2c..dfc28c8f9 100644 --- a/src/shapepipe/modules/sextractor_runner.py +++ b/src/shapepipe/modules/sextractor_runner.py @@ -68,6 +68,12 @@ def sextractor_runner( else: prefix = None + # When post-processing is enabled the sqlite WCS file is the last input; + # remove it before passing the image files to SExtractorCaller. + if config.getboolean(module_config_sec, "MAKE_POST_PROCESS"): + f_wcs_path = input_file_list[-1] + input_file_list = list(input_file_list[:-1]) + # Create sextractor caller class instance ss_inst = ss.SExtractorCaller( input_file_list, @@ -101,7 +107,6 @@ def sextractor_runner( # Run sextractor post processing if config.getboolean(module_config_sec, "MAKE_POST_PROCESS"): - f_wcs_path = config.getexpanded(module_config_sec, "LOG_WCS") pos_params = config.getlist(module_config_sec, "WORLD_POSITION") ccd_size = config.getlist(module_config_sec, "CCD_SIZE") ss.make_post_process(ss_inst.path_output_file, f_wcs_path, pos_params, ccd_size) diff --git a/src/shapepipe/modules/vignetmaker_package/vignetmaker.py b/src/shapepipe/modules/vignetmaker_package/vignetmaker.py index f599ab677..74e26915b 100644 --- a/src/shapepipe/modules/vignetmaker_package/vignetmaker.py +++ b/src/shapepipe/modules/vignetmaker_package/vignetmaker.py @@ -318,7 +318,13 @@ def _get_stamp_me(self, image_dirs, image_pattern): else: array_exp_name = np.concatenate((array_exp_name, exp_name_tmp)) - final_list.append([array_id, array_vign, array_exp_name]) + if array_id is not None: + final_list.append([array_id, array_vign, array_exp_name]) + else: + self._w_log.info( + f"All CCDs skipped for exposure {exp_name} " + + "(ccd == -1 for all); epoch excluded from output" + ) cat.close() diff --git a/src/shapepipe/modules/vignetmaker_runner.py b/src/shapepipe/modules/vignetmaker_runner.py index 5b9663e71..d3061ec8f 100644 --- a/src/shapepipe/modules/vignetmaker_runner.py +++ b/src/shapepipe/modules/vignetmaker_runner.py @@ -9,6 +9,7 @@ from shapepipe.modules.module_decorator import module_runner from shapepipe.modules.vignetmaker_package import vignetmaker as vm +from shapepipe.pipeline.exp_utils import get_exp_output_dirs from shapepipe.pipeline.run_log import get_last_dir, get_all_dirs @@ -104,21 +105,37 @@ def vignetmaker_runner( elif mode == "MULTI-EPOCH": # Multi-epoch exposures - # Get input image directory and file patterns - modules = config.getlist(module_config_sec, "ME_IMAGE_DIR") - image_dirs = [] - for module in modules: - module_name = module.split(":")[-1] - if "last" in module: - dirs = [get_last_dir(run_dirs["run_log"], module_name)] - elif "all" in module: - dirs = get_all_dirs(run_dirs["run_log"], module_name) - else: - raise ValueError( - "Expected qualifier 'last:' or 'all' before module" - + f" '{module}' in config entry 'ME_IMAGE_DIR'" + if config.has_option(module_config_sec, "ME_IMAGE_EXP_DIR"): + # v2.0: locate runner output dirs via the $SP_EXP tree + exp_base_dir = config.getexpanded( + module_config_sec, "ME_IMAGE_EXP_DIR" + ) + exp_numbers_file = input_file_list[2] + exp_runner_names = config.getlist( + module_config_sec, "ME_IMAGE_EXP_RUNNERS" + ) + image_dirs = [] + for runner_name in exp_runner_names: + dirs = get_exp_output_dirs( + exp_base_dir, exp_numbers_file, runner_name, w_log ) - image_dirs.append(dirs) + image_dirs.append(dirs) + else: + # v1: run-log based lookup via symlinked exposure run dirs + modules = config.getlist(module_config_sec, "ME_IMAGE_DIR") + image_dirs = [] + for module in modules: + module_name = module.split(":")[-1] + if "last" in module: + dirs = [get_last_dir(run_dirs["run_log"], module_name)] + elif "all" in module: + dirs = get_all_dirs(run_dirs["run_log"], module_name) + else: + raise ValueError( + "Expected qualifier 'last:' or 'all' before module" + + f" '{module}' in config entry 'ME_IMAGE_DIR'" + ) + image_dirs.append(dirs) image_pattern = config.getlist( module_config_sec, @@ -126,7 +143,7 @@ def vignetmaker_runner( ) # Get WCS log file path - f_wcs_path = config.getexpanded(module_config_sec, "ME_LOG_WCS") + f_wcs_path = input_file_list[1] # Process inputs vm_inst.process_me(image_dirs, image_pattern, f_wcs_path, radius) diff --git a/src/shapepipe/pipeline/args.py b/src/shapepipe/pipeline/args.py index 8d52875f0..d402132f2 100644 --- a/src/shapepipe/pipeline/args.py +++ b/src/shapepipe/pipeline/args.py @@ -140,5 +140,14 @@ def create_arg_parser(): "--exclusive", help="exclusive input file number string", ) + + optional.add_argument( + "-b", + "--batch_size", + type=int, + default=None, + help="SMP batch size; overrides SMP_BATCH_SIZE in the config file", + ) + # Return parser return parser.parse_args() diff --git a/src/shapepipe/pipeline/exp_utils.py b/src/shapepipe/pipeline/exp_utils.py index 56987a025..8f0df784a 100644 --- a/src/shapepipe/pipeline/exp_utils.py +++ b/src/shapepipe/pipeline/exp_utils.py @@ -124,3 +124,95 @@ def get_exp_output_files( w_log.info(f"Found {len(file_list)} exposure output files") return file_list + + +def get_exp_output_dirs( + exp_base_dir, + exp_numbers_file, + runner_name, + w_log=None, +): + """Return the most-recent output directory of runner_name for each exposure. + + For each exposure ID listed in ``exp_numbers_file``, the most recent + runner output directory is located at:: + + ///output/run_sp_*//output/ + + Parameters + ---------- + exp_base_dir : str + Root directory containing all per-exposure work directories. + exp_numbers_file : str + Path to a text file listing one exposure ID per line. + runner_name : str + Module runner directory name whose output directory is needed, + e.g. ``psfex_runner``. + w_log : logging.Logger, optional + Pipeline logger. + + Returns + ------- + list of str + One output directory path per exposure, in the order they appear + in ``exp_numbers_file``. + + Raises + ------ + FileNotFoundError + If ``exp_numbers_file`` does not exist or a runner output directory + is absent for one or more exposures. + + """ + if not os.path.exists(exp_numbers_file): + raise FileNotFoundError( + f"Exposure numbers file not found: {exp_numbers_file}" + ) + + with open(exp_numbers_file) as fh: + exp_ids = [line.strip() for line in fh if line.strip()] + + if w_log: + w_log.info( + f"Collecting {runner_name}/output dirs " + f"for {len(exp_ids)} exposures from {exp_base_dir}" + ) + + dir_list = [] + missing = [] + + for exp_id in exp_ids: + exp_prefix = exp_id[:2] + exp_base = exp_id[:-1] + + pattern = os.path.join( + exp_base_dir, + exp_prefix, + exp_base, + "output", + "run_sp_*", + runner_name, + "output", + ) + matches = sorted(glob.glob(pattern)) + + if matches: + chosen = matches[-1] # most recent run (lexicographic sort on datetime) + dir_list.append(chosen) + if w_log: + w_log.debug(f" {exp_id}: {chosen}") + else: + missing.append(exp_id) + if w_log: + w_log.warning(f" {exp_id}: no match for {pattern}") + + if missing: + raise FileNotFoundError( + f"No {runner_name} output directory found for " + f"{len(missing)} exposure(s): {missing}" + ) + + if w_log: + w_log.info(f"Found {len(dir_list)} exposure output directories") + + return dir_list diff --git a/src/shapepipe/pipeline/file_io.py b/src/shapepipe/pipeline/file_io.py index d7a442d06..0bb8fb763 100644 --- a/src/shapepipe/pipeline/file_io.py +++ b/src/shapepipe/pipeline/file_io.py @@ -1570,7 +1570,7 @@ def _get_fits_col_type(self, col_data): col_type = "D" elif type(col_data[0]) is bool: col_type = "L" - elif type(col_data[0]) in [str, np.str_, np.str0]: + elif type(col_data[0]) in [str, np.str_]: col_type = "A" else: col_type = "D" diff --git a/src/shapepipe/run.py b/src/shapepipe/run.py index fe2093a0d..e64a44b2d 100644 --- a/src/shapepipe/run.py +++ b/src/shapepipe/run.py @@ -341,6 +341,7 @@ def run_smp(pipe): job_type=pipe.run_method[module], exclusive=pipe.exclusive, verbose=pipe.verbose, + batch_size=pipe._args.batch_size, ) # Submit jobs @@ -400,6 +401,7 @@ def run_mpi(pipe, comm): parallel_mode="mpi", exclusive=pipe.exclusive, verbose=verbose, + batch_size=pipe._args.batch_size, ) # Get job type diff --git a/src/shapepipe/testing/__init__.py b/src/shapepipe/testing/__init__.py new file mode 100644 index 000000000..188000214 --- /dev/null +++ b/src/shapepipe/testing/__init__.py @@ -0,0 +1 @@ +"""ShapePipe testing utilities.""" diff --git a/src/shapepipe/testing/simulate.py b/src/shapepipe/testing/simulate.py new file mode 100644 index 000000000..1b3d65ca5 --- /dev/null +++ b/src/shapepipe/testing/simulate.py @@ -0,0 +1,95 @@ +"""Simulation utilities for ShapePipe validation tests. + +Stable across shapepipe branches and ngmix versions — contains only galsim +and numpy, no shapepipe processing or ngmix fitting code. + +Author: Axel Guinot +""" + +import numpy as np +import galsim + + +def make_data( + rng, + shear, + noise=1e-5, + n_epochs=1, + share_shift=False, + gal_hlr=0.3, + gal_flux=1000.0, + psf_fwhm=0.55, + pixel_scale=0.1857, + img_size=201, +): + """Simulate an exponential galaxy with Moffat PSF. + + Parameters + ---------- + rng : numpy.random.RandomState + Random number generator. + shear : tuple of float + True shear (g1, g2). + noise : float, optional + Per-pixel noise sigma. Default 1e-5. + n_epochs : int, optional + Number of epochs. Default 1. + share_shift : bool, optional + If True, all epochs share the same sub-pixel shift. + If False, each epoch draws an independent shift. + gal_hlr : float, optional + Galaxy half-light radius in arcsec. Default 0.3. + gal_flux : float, optional + Galaxy flux. Default 1000. + psf_fwhm : float, optional + PSF FWHM in arcsec. Default 0.55. + pixel_scale : float, optional + Pixel scale in arcsec/pixel. Default 0.1857. + img_size : int, optional + Stamp size in pixels (square). Default 201. + + Returns + ------- + gals : list of numpy.ndarray + psfs : list of numpy.ndarray + psfs_sigmas : list of float + weights : list of numpy.ndarray + flags : list of numpy.ndarray + jacob_lists : list of galsim.BaseWCS + """ + psf_noise = 1.0e-6 + scale = pixel_scale + wcs = galsim.PixelScale(scale) + + if share_shift: + dy, dx = rng.uniform(low=-scale / 2, high=scale / 2, size=2) + + gals, psfs, psfs_sigmas, weights, flags, jacob_lists = [], [], [], [], [], [] + + for epoch in range(n_epochs): + if not share_shift: + dy, dx = rng.uniform(low=-scale / 2, high=scale / 2, size=2) + + psf = galsim.Moffat(beta=2.5, fwhm=psf_fwhm) + obj = galsim.Convolve( + psf, + galsim.Exponential(half_light_radius=gal_hlr, flux=gal_flux).shear( + g1=shear[0], g2=shear[1] + ), + ).shift(dx, dy) + + psf_im_ = psf.drawImage(nx=img_size, ny=img_size, wcs=wcs) + psfs_sigmas.append(galsim.hsm.FindAdaptiveMom(psf_im_).moments_sigma) + psf_im = psf_im_.array.astype(np.float64) + im = obj.drawImage(nx=img_size, ny=img_size, wcs=wcs).array.astype(np.float64) + + psf_im += rng.normal(scale=psf_noise, size=psf_im.shape) + im += rng.normal(scale=noise, size=im.shape) + + gals.append(im) + psfs.append(psf_im) + weights.append(im * 0 + 1.0 / noise ** 2) + flags.append(im * 0) + jacob_lists.append(wcs.jacobian()) + + return gals, psfs, psfs_sigmas, weights, flags, jacob_lists diff --git a/uv.lock b/uv.lock index fc0ac0f1d..5ada34bbd 100644 --- a/uv.lock +++ b/uv.lock @@ -2,12 +2,11 @@ version = 1 revision = 3 requires-python = ">=3.12" resolution-markers = [ - 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