# Licensed under a 3-clause BSD style license - see LICENSE.rst
import json
import logging
from collections import defaultdict
from enum import Enum
from pathlib import Path
from typing import List
from astropy.coordinates import Angle
from astropy.time import Time
from astropy.units import Quantity
import yaml
from pydantic import BaseModel, FilePath
from pydantic.utils import deep_update
from gammapy.cube import MapDatasetMaker
from gammapy.utils.scripts import make_path, read_yaml
__all__ = ["AnalysisConfig"]
CONFIG_PATH = Path(__file__).resolve().parent / "config"
DOCS_FILE = CONFIG_PATH / "docs.yaml"
log = logging.getLogger(__name__)
class AngleType(Angle):
@classmethod
def __get_validators__(cls):
yield cls.validate
@classmethod
def validate(cls, v):
return Angle(v)
class EnergyType(Quantity):
@classmethod
def __get_validators__(cls):
yield cls.validate
@classmethod
def validate(cls, v):
v = Quantity(v)
if v.unit.physical_type != "energy":
raise ValueError(f"Invalid unit for energy: {v.unit!r}")
return v
class TimeType(Time):
@classmethod
def __get_validators__(cls):
yield cls.validate
@classmethod
def validate(cls, v):
return Time(v)
class ReductionTypeEnum(str, Enum):
spectrum = "1d"
cube = "3d"
class FrameEnum(str, Enum):
icrs = "icrs"
galactic = "galactic"
class BackgroundMethodEnum(str, Enum):
reflected = "reflected"
class SafeMaskMethodsEnum(str, Enum):
aeff_default = "aeff-default"
aeff_max = "aeff-max"
edisp_bias = "edisp-bias"
offset_max = "offset-max"
bkg_peak = "bkg-peak"
class MapSelectionEnum(str, Enum):
counts = "counts"
exposure = "exposure"
background = "background"
psf = "psf"
edisp = "edisp"
class GammapyBaseConfig(BaseModel):
class Config:
validate_all = True
validate_assignment = True
extra = "forbid"
json_encoders = {
Angle: lambda v: f"{v.value} {v.unit}",
Quantity: lambda v: f"{v.value} {v.unit}",
Time: lambda v: f"{v.value}",
}
class SkyCoordConfig(GammapyBaseConfig):
frame: FrameEnum = None
lon: AngleType = None
lat: AngleType = None
class EnergyAxisConfig(GammapyBaseConfig):
min: EnergyType = "0.1 TeV"
max: EnergyType = "10 TeV"
nbins: int = 30
class SpatialCircleConfig(GammapyBaseConfig):
frame: FrameEnum = None
lon: AngleType = None
lat: AngleType = None
radius: AngleType = None
class EnergyRangeConfig(GammapyBaseConfig):
min: EnergyType = "0.1 TeV"
max: EnergyType = "10 TeV"
class TimeRangeConfig(GammapyBaseConfig):
start: TimeType = None
stop: TimeType = None
class FluxPointsConfig(GammapyBaseConfig):
energy: EnergyAxisConfig = EnergyAxisConfig()
source: str = "source"
params: dict = {}
class FitConfig(GammapyBaseConfig):
fit_range: EnergyRangeConfig = EnergyRangeConfig()
class BackgroundConfig(GammapyBaseConfig):
method: BackgroundMethodEnum = BackgroundMethodEnum.reflected
exclusion: FilePath = None
class SafeMaskConfig(GammapyBaseConfig):
methods: List[SafeMaskMethodsEnum] = [SafeMaskMethodsEnum.aeff_default]
settings: dict = {}
class EnergyAxesConfig(GammapyBaseConfig):
energy: EnergyAxisConfig = EnergyAxisConfig()
energy_true: EnergyAxisConfig = EnergyAxisConfig()
class SelectionConfig(GammapyBaseConfig):
offset_max: AngleType = "2.5 deg"
class FovConfig(GammapyBaseConfig):
width: AngleType = "5 deg"
height: AngleType = "5 deg"
class WcsConfig(GammapyBaseConfig):
skydir: SkyCoordConfig = SkyCoordConfig()
binsize: AngleType = "0.02 deg"
fov: FovConfig = FovConfig()
binsize_irf: AngleType = "0.2 deg"
class GeomConfig(GammapyBaseConfig):
wcs: WcsConfig = WcsConfig()
selection: SelectionConfig = SelectionConfig()
axes: EnergyAxesConfig = EnergyAxesConfig()
class DatasetsConfig(GammapyBaseConfig):
type: ReductionTypeEnum = ReductionTypeEnum.spectrum
stack: bool = True
geom: GeomConfig = GeomConfig()
map_selection: List[MapSelectionEnum] = MapDatasetMaker.available_selection
background: BackgroundConfig = BackgroundConfig()
safe_mask: SafeMaskConfig = SafeMaskConfig()
on_region: SpatialCircleConfig = SpatialCircleConfig()
containment_correction: bool = True
class ObservationsConfig(GammapyBaseConfig):
datastore: Path = Path("$GAMMAPY_DATA/hess-dl3-dr1/")
obs_ids: List[int] = []
obs_file: FilePath = None
obs_cone: SpatialCircleConfig = SpatialCircleConfig()
obs_time: TimeRangeConfig = TimeRangeConfig()
class LogConfig(GammapyBaseConfig):
level: str = "info"
filename: Path = None
filemode: str = None
format: str = None
datefmt: str = None
class GeneralConfig(GammapyBaseConfig):
log: LogConfig = LogConfig()
outdir: str = "."
[docs]class AnalysisConfig(GammapyBaseConfig):
"""Gammapy analysis configuration."""
general: GeneralConfig = GeneralConfig()
observations: ObservationsConfig = ObservationsConfig()
datasets: DatasetsConfig = DatasetsConfig()
fit: FitConfig = FitConfig()
flux_points: FluxPointsConfig = FluxPointsConfig()
def __str__(self):
"""Display settings in pretty YAML format."""
info = self.__class__.__name__ + "\n\n\t"
data = self.to_yaml()
data = data.replace("\n", "\n\t")
info += data
return info.expandtabs(tabsize=4)
[docs] @classmethod
def read(cls, path):
"""Reads from YAML file."""
config = read_yaml(path)
return AnalysisConfig(**config)
[docs] @classmethod
def from_yaml(cls, config_str):
"""Create from YAML string."""
settings = yaml.safe_load(config_str)
return AnalysisConfig(**settings)
[docs] def write(self, path, overwrite=False):
"""Write to YAML file."""
path = make_path(path)
if path.exists() and not overwrite:
raise IOError(f"File exists already: {path}")
path.write_text(self.to_yaml())
[docs] def to_yaml(self):
"""Convert to YAML string."""
# Here using `dict()` instead of `json()` would be more natural.
# We should change this once pydantic adds support for custom encoders
# to `dict()`. See https://github.com/samuelcolvin/pydantic/issues/1043
config = json.loads(self.json())
return yaml.dump(
config, sort_keys=False, indent=4, width=80, default_flow_style=None
)
[docs] def set_logging(self):
"""Set logging config.
Calls ``logging.basicConfig``, i.e. adjusts global logging state.
"""
self.general.log.level = self.general.log.level.upper()
logging.basicConfig(**self.general.log.dict())
log.info("Setting logging config: {!r}".format(self.general.log.dict()))
[docs] def update(self, config=None):
"""Update config with provided settings.
Parameters
----------
config : string dict or `AnalysisConfig` object
Configuration settings provided in dict() syntax.
"""
if isinstance(config, str):
other = AnalysisConfig.from_yaml(config)
elif isinstance(config, AnalysisConfig):
other = config
else:
raise TypeError(f"Invalid type: {config}")
config_new = deep_update(
self.dict(exclude_defaults=True), other.dict(exclude_defaults=True)
)
return AnalysisConfig(**config_new)
@staticmethod
def _get_doc_sections():
"""Returns dict with commented docs from docs file"""
doc = defaultdict(str)
with open(DOCS_FILE) as f:
for line in filter(lambda line: not line.startswith("---"), f):
line = line.strip("\n")
if line.startswith("# Section: "):
keyword = line.replace("# Section: ", "")
doc[keyword] += line + "\n"
return doc