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config_MCCD.ini
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config_MCCD.ini
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# Configuration file for the MCCD method
[INPUTS]
INPUT_DIR = full_path_to/mccd/data/sextractor_inputs/
INPUT_REGEX_FILE_PATTERN = sexcat-*-*.fits
INPUT_SEPARATOR = -
MIN_N_STARS = 20
OUTLIER_STD_MAX = 100.
USE_SNR_WEIGHTS = False
PREPROCESSED_OUTPUT_DIR = full_path_to/mccd/data/sextractor_preprocessed/
OUTPUT_DIR = full_path_to/mccd/data/outputs/
[INSTANCE]
N_COMP_LOC = 4
D_COMP_GLOB = 6
KSIG_LOC = 0.00
KSIG_GLOB = 0.00
FILTER_PATH = None
D_HYB_LOC = 2
MIN_D_COMP_GLOB = None
RMSE_THRESH = 1.25
CCD_STAR_THRESH = 0.15
FP_GEOMETRY = CFIS
[FIT]
LOC_MODEL = hybrid
PSF_SIZE = 6.2
PSF_SIZE_TYPE = R2
N_EIGENVECTS = 5
N_ITER_RCA = 1
N_ITER_GLOB = 2
N_ITER_LOC = 2
NB_SUBITER_S_LOC = 300
NB_SUBITER_A_LOC = 400
NB_SUBITER_S_GLOB = 100
NB_SUBITER_A_GLOB = 200
[VALIDATION]
VAL_MODEL_INPUT_DIR = full_path_to/mccd/data/outputs/
VAL_DATA_INPUT_DIR = full_path_to/mccd/data/sextractor_inputs/
VAL_PREPROCESSED_OUTPUT_DIR = full_path_to/mccd/data/sextractor_preprocessed/
VAL_REGEX_FILE_PATTERN = test-star_selection-*-*.fits
VAL_SEPARATOR = -
VAL_OUTPUT_DIR = full_path_to/mccd/data/outputs/
APPLY_DEGRADATION = True
MCCD_DEBUG = False
GLOBAL_POL_INTERP = False
# Parameter description:
#
#
# [INPUTS]
# INPUT_DIR : (Required) Must be a valid directory containing the input
# MCCD files.
# INPUT_REGEX_FILE_PATTERN : File pattern of the input files to use. It should
# follow regex (regular expression) standards.
# INPUT_SEPARATOR : Separator of the different fields in the filename,
# ie sexcat[SEP]catalog_id[SEP]CCD_id.fits
# MIN_N_STARS : Minimum number of stars to keep a CCD for the training.
# OUTLIER_STD_MAX : Maximum standard deviation used for the outlier rejection.
# Should not be too low as a hihg quantity of low quality
# stars will be rejected. ie 9 is a conservative rejection.
# USE_SNR_WEIGHTS : Boolean to determine if the SNR weighting strategy will
# be used.
# For now, it needs the SNR estimations from SExtractor.
# PREPROCESSED_OUTPUT_DIR : (Required) Must be a valid directory to write the
# preprocessed input files.
# OUTPUT_DIR : (Required) Must be a valid directory to write the output files.
# The constructed models will be saved.
#
#
# [INSTANCE]
# N_COMP_LOC : Number of components of the Local model. If LOC_MODEL is poly,
# will be the max degree D of the polynomial.
# D_COMP_GLOB : Max degree of the global polynomial model.
# KSIG_LOC : Denoising parameter of the local model.
# ie 1 is a normal denoising, 3 is a hard denoising.
# KSIG_GLOB : Denoising parameter of the global model.
# ie 1 is a normal denoising, 3 is a hard denoising.
# FILTER_PATH : Path for predefined filters.
# D_HYB_LOC : Degree of the polynomial component for the local part in case
# the LOC_MODEL used is 'hybrid'.
# MIN_D_COMP_GLOB : The minimum degree of the polynomial for the global
# component. For example, if the paramter is set to 1, the
# polynomials of degree 0 and 1 will be excluded from the
# global polynomial variations. ``None`` means that we are
# not excluding any degree.
# RMSE_THRESH : Parameter concerning the CCD outlier rejection. Once the PSF
# model is calculated we perform an outlier check on the training
# stars. We divide each star in two parts with a given circle.
# The inner part corresponds to the most of the PSF/star energy
# while the outer part corresponds to the observation background.
# The outer part is used to calculate the noise level and the inner
# part to calculate the model residual
# (star observation - PSF model reconstruction). If the RMSE error
# of the residual divided by the noise level is over the RMSE_THRESH,
# the star will be considered an outlier. A perfect reconstruction
# would have RMSE_THRESH equal to 1.
# CCD_STAR_THRESH : Parameter concerning the CCD outlier rejection. If the
# percentage of outlier stars in a single CCD is bigger than
# CCD_STAR_THRESH, the CCD is considered to be an outlier.
# In this case, the CCD is rejected from the PSF model.
# A value lower than 0 means that no outlier rejection
# will be done.
# FP_GEOMETRY : Defines the geometry of the focal plane. For the moment the two
# available options are 'CFIS' and 'EUCLID'. If the parameter is
# not specified it defaults to 'CFIS'.
#
#
#
# [FIT]
# LOC_MODEL : Defines the type of local model to use, it can be: 'rca',
# 'poly' or 'hybrid'.
# When the poly model is used, N_COMP_LOC should be used
# as the D_LOC (max degree of the poly model)
# PSF_SIZE : First guess of the PSF size. A size estimation is done anyways.
# PSF_SIZE_TYPE : Type of the size information. It can be: fwhm, R2, sigma
# N_EIGENVECTS : Number of eigenvectors to keep for the graph constraint
# construction.
# N_ITER_RCA : Number of global epochs in the algorithm. Alternation between
# global and local estimations.
# N_ITER_GLOB : Number of epochs for each global optimization. Alternations
# between A_GLOB and S_GLOB.
# N_ITER_LOC : Number of epochs for each local optimization. Alternations
# between the different A_LOC and S_LOC.
# NB_SUBITER_S_LOC : Iterations for the optimization algorithm over S_LOC.
# NB_SUBITER_A_LOC : Iterations for the optimization algorithm over A_LOC.
# NB_SUBITER_S_GLOB : Iterations for the optimization algorithm over S_GLOB.
# NB_SUBITER_A_GLOB : Iterations for the optimization algorithm over A_GLOB.
#
#
# [VALIDATION]
# MODEL_INPUT_DIR : (Required) Must be a valid directory which contains the
# saved trained models.
# VAL_DATA_INPUT_DIR : (Required) Must be a valid directory which contains the
# validation input data (test dataset).
# VAL_REGEX_FILE_PATTERN : Same as INPUT_REGEX_FILE_PATTERN but for validation.
# VAL_SEPARATOR : Same as INPUT_SEPARATOR but for validation.
# VAL_OUTPUT_DIR : (Required) Must be a valid directory where to save the
# validation outputs, test PSFs and interpolated PSFs.
# APPLY_DEGRADATION : Whether the PSF models should be degraded
# (sampling/shifts/flux) to match stars; use True if you
# plan on making pixel-based comparisons (residuals etc.).
# MCCD_DEBUG : Debug mode. Returns the local and global contributions.
# GLOBAL_POL_INTERP : Uses polynomial interpolation for the global model
# instead of RBF kernel interpolation.
#