Martin's latest, small changes

aux/CFIS/tiles_202007/tiles_W3.txt

@@ -210,3 +210,5 @@
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aux/CFIS/tiles_202007/tiles_W3_m2.txt

@@ -0,0 +1,212 @@
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example/cfis/config_MCCD_inv_opt.ini

@@ -0,0 +1,116 @@
+# Configuration file for the MCCD method
+
+[INPUTS]
+INPUT_DIR = .
+PREPROCESSED_OUTPUT_DIR = ./output
+OUTPUT_DIR = ./output
+INPUT_REGEX_FILE_PATTERN = star_split_ratio_80-*-*.fits
+INPUT_SEPARATOR = -
+MIN_N_STARS = 20
+OUTLIER_STD_MAX = 100.
+USE_SNR_WEIGHTS = False
+
+[INSTANCE]
+N_COMP_LOC = 2
+D_COMP_GLOB = 6
+KSIG_LOC = 0.0000
+KSIG_GLOB = 0.000
+FILTER_PATH = None
+
+[FIT]
+LOC_MODEL = poly
+PSF_SIZE = 6.2
+PSF_SIZE_TYPE = R2
+N_EIGENVECTS = 5
+N_ITER_RCA = 1
+N_ITER_GLOB = 1
+N_ITER_LOC = 1
+NB_SUBITER_S_LOC = 300
+NB_SUBITER_A_LOC = 400
+NB_SUBITER_S_GLOB = 100
+NB_SUBITER_A_GLOB = 200
+
+[VALIDATION]
+VAL_DATA_INPUT_DIR = .
+VAL_PREPROCESSED_OUTPUT_DIR = ./output
+VAL_MODEL_INPUT_DIR = ./output
+VAL_OUTPUT_DIR = ./output
+VAL_REGEX_FILE_PATTERN = star_split_ratio_20-*-*.fits
+VAL_SEPARATOR = -
+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.
+# 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.
+# 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.
+#
+#
+# [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.
+#
+#
+# [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]
+# VAL_DATA_INPUT_DIR : (Required) Must be a valid directory which contains the
+#                      validation input data (test dataset).
+# VAL_PREPROCESSED_OUTPUT_DIR : (Required) Must be a valid directory where the
+#                               preprocessed input file will be saved.
+# VAL_MODEL_INPUT_DIR : (Required) Must be a valid directory which contains the
+#                   saved trained models.
+# VAL_OUTPUT_DIR : (Required) Must be a valid directory where to save the
+#                  validation outputs, test PSFs and interpolated PSFs.
+# VAL_REGEX_FILE_PATTERN : Same as INPUT_REGEX_FILE_PATTERN but for validation.
+# VAL_SEPARATOR : Same as INPUT_SEPARATOR but for validation.
+# 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.
+#