hipscatalog_gen package

Subpackages

Submodules

hipscatalog_gen.cli module

Command-line interface for running the HiPS catalog pipeline.

main(argv=None)[source]

Entry point for the command-line interface.

Parameters:

argv (List[str] | None) – Command-line arguments excluding the program name.

Return type:

None

hipscatalog_gen.config module

Configuration parsing and validation for hipscatalog-gen.

class AlgoOpts(selection_mode, level_limit, moc_order, order_desc=False, tie_column=None, mg_order_desc=False, mag_column=None, flux_column=None, mag_offset=None, mag_min=None, mag_max=None, mag_adaptive_range='complete', mag_hist_nbins=2048, mag_keep_invalid_values=False, mag_tie_column=None, n_1=None, n_2=None, n_3=None, k_1=None, k_2=None, k_3=None, score_column=None, score_min=None, score_max=None, score_adaptive_range='complete', score_hist_nbins=2048, score_keep_invalid_values=False, score_tie_column=None, score_n_1=None, score_n_2=None, score_n_3=None, score_k_1=None, score_k_2=None, score_k_3=None, sg_order_desc=False, sdh_score_column=None, sdh_score_min=None, sdh_score_max=None, sdh_score_adaptive_range='complete', sdh_score_hist_nbins=2048, sdh_keep_invalid_values=False, sdh_tie_column=None, sdh_n_1=None, sdh_n_2=None, sdh_n_3=None, sdh_k_1=None, sdh_k_2=None, sdh_k_3=None, sdh_density_up_to_depth=4, sdh_density_bias_n1=1.0, sdh_density_bias_n2=1.0, sdh_density_bias_n3=1.0, sdh_order_desc=False)[source]

Bases: object

Algorithm options for HiPS selection and density profiles.

Common settings (all modes):

selection_mode: High-level strategy (“mag_global”, “score_global”, or “score_density_hybrid”). level_limit: Maximum HiPS order (NorderL). moc_order: HiPS order used for the MOC (defaults to level_limit). order_desc/tie_column/keep_invalid_values: global defaults for ordering, tie-breakers, and handling NaN/Inf (sentinel mapping only for adaptive_range=complete).

mag_global block:

mag_column or flux_column+mag_offset; mag_min/max; adaptive_range; hist_nbins; optional n_1/n_2/n_3 targets (or k_1/k_2/k_3 as “per active tile” aliases); order_desc/tie_column/keep_invalid_values (fall back to selection_defaults).

score_global block:

score_column; score_min/max; adaptive_range; hist_nbins; optional n_1/n_2/n_3 (or k_1/k_2/k_3) targets; order_desc/tie_column/keep_invalid_values (fall back to selection_defaults).

score_density_hybrid block:

score_column; score_min/max; adaptive_range; hist_nbins; density_up_to_depth; optional n_1/n_2/n_3 (or k_1/k_2/k_3) targets; density_bias_n1/n2/n3; order_desc/tie_column/keep_invalid_values (fall back to selection_defaults).

Parameters:

  • selection_mode (str)

  • level_limit (int)

  • moc_order (int)

  • order_desc (bool)

  • tie_column (str | None)

  • mg_order_desc (bool)

  • mag_column (str | None)

  • flux_column (str | None)

  • mag_offset (float | None)

  • mag_min (float | None)

  • mag_max (float | None)

  • mag_adaptive_range (str)

  • mag_hist_nbins (int)

  • mag_keep_invalid_values (bool)

  • mag_tie_column (str | None)

  • n_1 (int | None)

  • n_2 (int | None)

  • n_3 (int | None)

  • k_1 (int | None)

  • k_2 (int | None)

  • k_3 (int | None)

  • score_column (str | None)

  • score_min (float | None)

  • score_max (float | None)

  • score_adaptive_range (str)

  • score_hist_nbins (int)

  • score_keep_invalid_values (bool)

  • score_tie_column (str | None)

  • score_n_1 (int | None)

  • score_n_2 (int | None)

  • score_n_3 (int | None)

  • score_k_1 (int | None)

  • score_k_2 (int | None)

  • score_k_3 (int | None)

  • sg_order_desc (bool)

  • sdh_score_column (str | None)

  • sdh_score_min (float | None)

  • sdh_score_max (float | None)

  • sdh_score_adaptive_range (str)

  • sdh_score_hist_nbins (int)

  • sdh_keep_invalid_values (bool)

  • sdh_tie_column (str | None)

  • sdh_n_1 (int | None)

  • sdh_n_2 (int | None)

  • sdh_n_3 (int | None)

  • sdh_k_1 (int | None)

  • sdh_k_2 (int | None)

  • sdh_k_3 (int | None)

  • sdh_density_up_to_depth (int)

  • sdh_density_bias_n1 (float)

  • sdh_density_bias_n2 (float)

  • sdh_density_bias_n3 (float)

  • sdh_order_desc (bool)

selection_mode: str
level_limit: int
moc_order: int
order_desc: bool = False
tie_column: str | None = None
mg_order_desc: bool = False
mag_column: str | None = None
flux_column: str | None = None
mag_offset: float | None = None
mag_min: float | None = None
mag_max: float | None = None
mag_adaptive_range: str = 'complete'
mag_hist_nbins: int = 2048
mag_keep_invalid_values: bool = False
mag_tie_column: str | None = None
n_1: int | None = None
n_2: int | None = None
n_3: int | None = None
k_1: int | None = None
k_2: int | None = None
k_3: int | None = None
score_column: str | None = None
score_min: float | None = None
score_max: float | None = None
score_adaptive_range: str = 'complete'
score_hist_nbins: int = 2048
score_keep_invalid_values: bool = False
score_tie_column: str | None = None
score_n_1: int | None = None
score_n_2: int | None = None
score_n_3: int | None = None
score_k_1: int | None = None
score_k_2: int | None = None
score_k_3: int | None = None
sg_order_desc: bool = False
sdh_score_column: str | None = None
sdh_score_min: float | None = None
sdh_score_max: float | None = None
sdh_score_adaptive_range: str = 'complete'
sdh_score_hist_nbins: int = 2048
sdh_keep_invalid_values: bool = False
sdh_tie_column: str | None = None
sdh_n_1: int | None = None
sdh_n_2: int | None = None
sdh_n_3: int | None = None
sdh_k_1: int | None = None
sdh_k_2: int | None = None
sdh_k_3: int | None = None
sdh_density_up_to_depth: int = 4
sdh_density_bias_n1: float = 1.0
sdh_density_bias_n2: float = 1.0
sdh_density_bias_n3: float = 1.0
sdh_order_desc: bool = False
class ColumnsCfg(ra, dec, keep=None)[source]

Bases: object

Column mapping for RA/DEC and extra fields.

Parameters:

  • ra (str)

  • dec (str)

  • keep (List[str] | None)

ra: str
dec: str
keep: List[str] | None = None
class InputCfg(paths, format, header, ascii_format=None)[source]

Bases: object

Input catalog configuration.

Parameters:

  • paths (List[str])

  • format (str)

  • header (bool)

  • ascii_format (str | None)

paths: List[str]
format: str
header: bool
ascii_format: str | None = None
class ClusterCfg(mode, n_workers, threads_per_worker, memory_per_worker, slurm=None, low_memory_mode=None, diagnostics_mode='global')[source]

Bases: object

Dask cluster configuration.

Parameters:

  • mode (str)

  • n_workers (int)

  • threads_per_worker (int)

  • memory_per_worker (str)

  • slurm (Dict | None)

  • low_memory_mode (bool | None)

  • diagnostics_mode (str)

mode: str
n_workers: int
threads_per_worker: int
memory_per_worker: str
slurm: Dict | None = None
low_memory_mode: bool | None = None
diagnostics_mode: str = 'global'
class OutputCfg(out_dir, cat_name, target, creator_did=None, obs_title=None, overwrite=False)[source]

Bases: object

Output HiPS catalog configuration.

Parameters:

  • out_dir (str)

  • cat_name (str)

  • target (str)

  • creator_did (str | None)

  • obs_title (str | None)

  • overwrite (bool)

out_dir: str
cat_name: str
target: str
creator_did: str | None = None
obs_title: str | None = None
overwrite: bool = False
class Config(input, columns, algorithm, cluster, output)[source]

Bases: object

Top-level configuration container for the HiPS pipeline.

Parameters:
input: InputCfg
columns: ColumnsCfg
algorithm: AlgoOpts
cluster: ClusterCfg
output: OutputCfg
load_config(path)[source]

Load configuration from a YAML file.

The YAML structure must follow the sections described in display_available_configs(). For an overview of all available configuration keys (required vs optional, and defaults), call:

from hipscatalog_gen.config import display_available_configs display_available_configs()

Parameters:

path (str) – Path to the YAML configuration file.

Returns:

Parsed Config instance.

Raises:

ValueError – If algorithm options are inconsistent.

Return type:

Config

load_config_from_dict(cfg_dict)[source]

Build configuration from an in-memory mapping.

This is useful in interactive environments (e.g., notebooks) where the configuration is defined directly as a Python dict instead of a YAML file. The mapping must follow the same structure described in display_available_configs(). For a summary of all configuration keys, call:

from hipscatalog_gen.config import display_available_configs display_available_configs()

Parameters:

cfg_dict (Mapping[str, Any]) – Mapping with the same structure expected in the YAML file.

Returns:

Parsed Config instance.

Raises:

ValueError – If algorithm options are inconsistent.

Return type:

Config

display_available_configs()[source]

Display a concise reference of all configuration options.

This prints a structured summary of all available configuration keys, grouped by top-level section (input, columns, algorithm, cluster, output), indicating which parameters are required, which are optional, and the default values for optional parameters.

This function is intended for interactive use, e.g.:

from hipscatalog_gen.config import display_available_configs display_available_configs()

Return type:

None

Module contents

Public entrypoints for the HiPS catalog generation library.

class Config(input, columns, algorithm, cluster, output)[source]

Bases: object

Top-level configuration container for the HiPS pipeline.

Parameters:
input: InputCfg
columns: ColumnsCfg
algorithm: AlgoOpts
cluster: ClusterCfg
output: OutputCfg
load_config(path)[source]

Load configuration from a YAML file.

The YAML structure must follow the sections described in display_available_configs(). For an overview of all available configuration keys (required vs optional, and defaults), call:

from hipscatalog_gen.config import display_available_configs display_available_configs()

Parameters:

path (str) – Path to the YAML configuration file.

Returns:

Parsed Config instance.

Raises:

ValueError – If algorithm options are inconsistent.

Return type:

Config

run_pipeline(*args, **kwargs)[source]

Lazily import and invoke the pipeline entrypoint.