Source code for

# Licensed under a 3-clause BSD style license - see LICENSE.rst
import collections
import copy
import logging
import numpy as np
from astropy import units as u
from astropy.coordinates import AltAz, Angle, SkyCoord
from astropy.coordinates.angle_utilities import angular_separation
from import fits
from astropy.table import Table
from astropy.table import vstack as vstack_tables
from astropy.visualization import quantity_support
import matplotlib.pyplot as plt
from gammapy.maps import MapAxis, MapCoord, RegionGeom, WcsNDMap
from gammapy.maps.axes import UNIT_STRING_FORMAT
from gammapy.utils.fits import earth_location_from_dict
from gammapy.utils.scripts import make_path
from gammapy.utils.testing import Checker
from gammapy.utils.time import time_ref_from_dict
from .gti import GTI

__all__ = ["EventList"]

log = logging.getLogger(__name__)

[docs]class EventList: """Event list. Event list data is stored as ``table`` (`~astropy.table.Table`) data member. The most important reconstructed event parameters are available as the following columns: - ``TIME`` - Mission elapsed time (sec) - ``RA``, ``DEC`` - ICRS system position (deg) - ``ENERGY`` - Energy (usually MeV for Fermi and TeV for IACTs) Note that ``TIME`` is usually sorted, but sometimes it is not. E.g. when simulating data, or processing it in certain ways. So generally any analysis code should assume ``TIME`` is not sorted. Other optional (columns) that are sometimes useful for high level analysis: - ``GLON``, ``GLAT`` - Galactic coordinates (deg) - ``DETX``, ``DETY`` - Field of view coordinates (deg) Note that when reading data for analysis you shouldn't use those values directly, but access them via properties which create objects of the appropriate class: - `time` for ``TIME`` - `radec` for ``RA``, ``DEC`` - `energy` for ``ENERGY`` - `galactic` for ``GLON``, ``GLAT`` Parameters ---------- table : `~astropy.table.Table` Event list table Examples -------- >>> from import EventList >>> events ="$GAMMAPY_DATA/cta-1dc/data/baseline/gps/gps_baseline_110380.fits") >>> print(events) EventList --------- <BLANKLINE> Instrument : None Telescope : CTA Obs. ID : 110380 <BLANKLINE> Number of events : 106217 Event rate : 59.273 1 / s <BLANKLINE> Time start : 59235.5 Time stop : 59235.52074074074 <BLANKLINE> Min. energy : 3.00e-02 TeV Max. energy : 1.46e+02 TeV Median energy : 1.02e-01 TeV <BLANKLINE> Max. offset : 5.0 deg <BLANKLINE> """ def __init__(self, table): self.table = table
[docs] @classmethod def read(cls, filename, **kwargs): """Read from FITS file. Format specification: :ref:`gadf:iact-events` Parameters ---------- filename : `pathlib.Path`, str Filename """ filename = make_path(filename) kwargs.setdefault("hdu", "EVENTS") table =, **kwargs) return cls(table=table)
[docs] def to_table_hdu(self, format="gadf"): """ Convert event list to a `` Parameters ---------- format: str Output format, currently only "gadf" is supported Returns ------- hdu: `` EventList converted to FITS representation """ if format != "gadf": raise ValueError(f"Only the 'gadf' format supported, got {format}") return fits.BinTableHDU(self.table, name="EVENTS")
[docs] def write(self, filename, gti=None, overwrite=False, format="gadf"): """Write the event list to a FITS file. If a GTI object is provided, it is saved into a second extension in the file. Parameters ---------- filename : `pathlib.Path`, str Filename gti : `` Good Time Intervals object to save to the same file. Default is None. overwrite : bool Overwrite existing file? format : str, optional FITS format convention. By default files will be written to the gamma-astro-data-formats (GADF) format. """ if format != "gadf": raise ValueError(f"{format} is not a valid EventList format.") meta_dict = self.table.meta if "HDUCLAS1" in meta_dict.keys() and meta_dict["HDUCLAS1"] != "EVENTS": raise ValueError("The HDUCLAS1 keyword must be 'EVENTS' for an EventList") else: meta_dict["HDUCLAS1"] = "EVENTS" if "HDUCLASS" in meta_dict.keys() and meta_dict["HDUCLASS"] != "GADF": raise ValueError("The HDUCLASS must be 'GADF' for format 'gadf'") else: meta_dict["HDUCLASS"] = "GADF" filename = make_path(filename) primary_hdu = fits.PrimaryHDU() hdu_evt = self.to_table_hdu(format=format) hdu_all = fits.HDUList([primary_hdu, hdu_evt]) if gti is not None: if not isinstance(gti, GTI): raise TypeError("gti must be an instance of GTI") hdu_gti = gti.to_table_hdu(format=format) hdu_all.append(hdu_gti) hdu_all.writeto(filename, overwrite=overwrite)
[docs] @classmethod def from_stack(cls, event_lists, **kwargs): """Stack (concatenate) list of event lists. Calls `~astropy.table.vstack`. Parameters ---------- event_lists : list list of `` to stack """ tables = [_.table for _ in event_lists] stacked_table = vstack_tables(tables, **kwargs) return cls(stacked_table)
[docs] def stack(self, other): """Stack with another EventList in place. Calls `~astropy.table.vstack`. Parameters ---------- other : `` Event list to stack to self """ self.table = vstack_tables([self.table, other.table])
def __str__(self): info = self.__class__.__name__ + "\n" info += "-" * len(self.__class__.__name__) + "\n\n" instrument = self.table.meta.get("INSTRUME") info += f"\tInstrument : {instrument}\n" telescope = self.table.meta.get("TELESCOP") info += f"\tTelescope : {telescope}\n" obs_id = self.table.meta.get("OBS_ID", "") info += f"\tObs. ID : {obs_id}\n\n" info += f"\tNumber of events : {len(self.table)}\n" rate = len(self.table) / self.observation_time_duration info += f"\tEvent rate : {rate:.3f}\n\n" info += f"\tTime start : {self.observation_time_start}\n" info += f"\tTime stop : {self.observation_time_stop}\n\n" info += f"\tMin. energy : {np.min(}\n" info += f"\tMax. energy : {np.max(}\n" info += f"\tMedian energy : {np.median(}\n\n" if self.is_pointed_observation: offset_max = np.max(self.offset) info += f"\tMax. offset : {offset_max:.1f}\n" return info.expandtabs(tabsize=2) @property def time_ref(self): """Time reference (`~astropy.time.Time`).""" return time_ref_from_dict(self.table.meta) @property def time(self): """Event times (`~astropy.time.Time`). Notes ----- Times are automatically converted to 64-bit floats. With 32-bit floats times will be incorrect by a few seconds when e.g. adding them to the reference time. """ met = u.Quantity(self.table["TIME"].astype("float64"), "second") return self.time_ref + met @property def observation_time_start(self): """Observation start time (`~astropy.time.Time`).""" return self.time_ref + u.Quantity(self.table.meta["TSTART"], "second") @property def observation_time_stop(self): """Observation stop time (`~astropy.time.Time`).""" return self.time_ref + u.Quantity(self.table.meta["TSTOP"], "second") @property def radec(self): """Event RA / DEC sky coordinates (`~astropy.coordinates.SkyCoord`).""" lon, lat = self.table["RA"], self.table["DEC"] return SkyCoord(lon, lat, unit="deg", frame="icrs") @property def galactic(self): """Event Galactic sky coordinates (`~astropy.coordinates.SkyCoord`). Always computed from RA / DEC using Astropy. """ return self.radec.galactic @property def energy(self): """Event energies (`~astropy.units.Quantity`).""" return self.table["ENERGY"].quantity @property def galactic_median(self): """Median position in radec""" galactic = self.galactic median_lon = np.median(galactic.l.wrap_at("180d")) median_lat = np.median(galactic.b) return SkyCoord(median_lon, median_lat, frame="galactic")
[docs] def select_row_subset(self, row_specifier): """Select table row subset. Parameters ---------- row_specifier : slice, int, or array of ints Specification for rows to select, passed on to ``self.table[row_specifier]``. Returns ------- event_list : `EventList` New event list with table row subset selected Examples -------- >>> from import EventList >>> import numpy as np >>> filename = "$GAMMAPY_DATA/cta-1dc/data/baseline/gps/gps_baseline_110380.fits" >>> events = >>> #Use a boolean mask as ``row_specifier``: >>> mask = events.table['MC_ID'] == 1 >>> events2 = events.select_row_subset(mask) >>> print(len(events2.table)) 97978 >>> #Use row index array as ``row_specifier``: >>> idx = np.where(events.table['MC_ID'] == 1)[0] >>> events2 = events.select_row_subset(idx) >>> print(len(events2.table)) 97978 """ table = self.table[row_specifier] return self.__class__(table=table)
[docs] def select_energy(self, energy_range): """Select events in energy band. Parameters ---------- energy_range : `~astropy.units.Quantity` Energy range ``[energy_min, energy_max)`` Returns ------- event_list : `EventList` Copy of event list with selection applied. Examples -------- >>> from astropy import units as u >>> from import EventList >>> filename = "$GAMMAPY_DATA/fermi_3fhl/fermi_3fhl_events_selected.fits.gz" >>> event_list = >>> energy_range =[1, 20] * u.TeV >>> event_list = event_list.select_energy(energy_range=energy_range) """ energy = mask = energy_range[0] <= energy mask &= energy < energy_range[1] return self.select_row_subset(mask)
[docs] def select_time(self, time_interval): """Select events in time interval. Parameters ---------- time_interval : `astropy.time.Time` Start time (inclusive) and stop time (exclusive) for the selection. Returns ------- events : `EventList` Copy of event list with selection applied. """ time = self.time mask = time_interval[0] <= time mask &= time < time_interval[1] return self.select_row_subset(mask)
[docs] def select_region(self, regions, wcs=None): """Select events in given region. Parameters ---------- regions : str, `~regions.Region` or list of `~regions.Region` Region or list of regions (pixel or sky regions accepted). A region can be defined as a string ind DS9 format as well. See for details. wcs : `~astropy.wcs.WCS` World coordinate system transformation Returns ------- event_list : `EventList` Copy of event list with selection applied. """ geom = RegionGeom.from_regions(regions, wcs=wcs) mask = geom.contains(self.radec) return self.select_row_subset(mask)
[docs] def select_parameter(self, parameter, band): """Select events with respect to a specified parameter. Parameters ---------- parameter : str Parameter used for the selection. Must be present in `self.table`. band : tuple or `astropy.units.Quantity` Min and max value for the parameter to be selected (min <= parameter < max). If parameter is not dimensionless you have to provide a Quantity. Returns ------- event_list : `EventList` Copy of event list with selection applied. Examples -------- >>> from astropy import units as u >>> from import EventList >>> filename = "$GAMMAPY_DATA/fermi_3fhl/fermi_3fhl_events_selected.fits.gz" >>> event_list = >>> zd = (0, 30) * u.deg >>> event_list = event_list.select_parameter(parameter='ZENITH_ANGLE', band=zd) >>> print(len(event_list.table)) 123944 """ mask = band[0] <= self.table[parameter].quantity mask &= self.table[parameter].quantity < band[1] return self.select_row_subset(mask)
@property def _default_plot_energy_axis(self): energy = return MapAxis.from_energy_bounds( energy_min=energy.min(), energy_max=energy.max(), nbin=50 )
[docs] def plot_energy(self, ax=None, **kwargs): """Plot counts as a function of energy. Parameters ---------- ax : `~matplotlib.axes.Axes` or None Axes **kwargs : dict Keyword arguments passed to `~matplotlib.pyplot.hist` Returns ------- ax : `~matplotlib.axes.Axes` or None Axes """ ax = plt.gca() if ax is None else ax energy_axis = self._default_plot_energy_axis kwargs.setdefault("log", True) kwargs.setdefault("histtype", "step") kwargs.setdefault("bins", energy_axis.edges) with quantity_support(): ax.hist(, **kwargs) energy_axis.format_plot_xaxis(ax=ax) ax.set_ylabel("Counts") ax.set_yscale("log") return ax
[docs] def plot_time(self, ax=None, **kwargs): """Plots an event rate time curve. Parameters ---------- ax : `~matplotlib.axes.Axes` or None Axes **kwargs : dict Keyword arguments passed to `~matplotlib.pyplot.errorbar` Returns ------- ax : `~matplotlib.axes.Axes` Axes """ ax = plt.gca() if ax is None else ax # Note the events are not necessarily in time order time = self.table["TIME"] time = time - np.min(time) ax.set_xlabel(f"Time [{u.s.to_string(UNIT_STRING_FORMAT)}]") ax.set_ylabel("Counts") y, x_edges = np.histogram(time, bins=20) xerr = np.diff(x_edges) / 2 x = x_edges[:-1] + xerr yerr = np.sqrt(y) kwargs.setdefault("fmt", "none") ax.errorbar(x=x, y=y, xerr=xerr, yerr=yerr, **kwargs) return ax
[docs] def plot_offset2_distribution( self, ax=None, center=None, max_percentile=98, **kwargs ): """Plot offset^2 distribution of the events. The distribution shown in this plot is for this quantity:: offset = center.separation(events.radec).deg offset2 = offset ** 2 Note that this method is just for a quicklook plot. If you want to do computations with the offset or offset^2 values, you can use the line above. As an example, here's how to compute the 68% event containment radius using `numpy.percentile`:: import numpy as np r68 = np.percentile(offset, q=68) Parameters ---------- ax : `~matplotlib.axes.Axes` (optional) Axes center : `astropy.coordinates.SkyCoord` Center position for the offset^2 distribution. Default is the observation pointing position. max_percentile : float Define the percentile of the offset^2 distribution used to define the maximum offset^2 value. **kwargs : Extra keyword arguments are passed to `~matplotlib.pyplot.hist`. Returns ------- ax : `~matplotlib.axes.Axes` Axes Examples -------- Load an example event list: >>> from import EventList >>> from astropy import units as u >>> filename = "$GAMMAPY_DATA/hess-dl3-dr1/data/hess_dl3_dr1_obs_id_023523.fits.gz" >>> events = >>> #Plot the offset^2 distribution wrt. the observation pointing position >>> #(this is a commonly used plot to check the background spatial distribution): >>> events.plot_offset2_distribution() # doctest: +SKIP Plot the offset^2 distribution wrt. the Crab pulsar position (this is commonly used to check both the gamma-ray signal and the background spatial distribution): >>> import numpy as np >>> from astropy.coordinates import SkyCoord >>> center = SkyCoord(83.63307, 22.01449, unit='deg') >>> bins = np.linspace(start=0, stop=0.3 ** 2, num=30) * u.deg ** 2 >>> events.plot_offset2_distribution(center=center, bins=bins) # doctest: +SKIP Note how we passed the ``bins`` option of `matplotlib.pyplot.hist` to control the histogram binning, in this case 30 bins ranging from 0 to (0.3 deg)^2. """ ax = plt.gca() if ax is None else ax if center is None: center = self._plot_center offset2 = center.separation(self.radec) ** 2 max2 = np.percentile(offset2, q=max_percentile) kwargs.setdefault("histtype", "step") kwargs.setdefault("bins", 30) kwargs.setdefault("range", (0.0, max2.value)) with quantity_support(): ax.hist(offset2, **kwargs) ax.set_xlabel(rf"Offset$^2$ [{ax.xaxis.units.to_string(UNIT_STRING_FORMAT)}]") ax.set_ylabel("Counts") return ax
[docs] def plot_energy_offset(self, ax=None, center=None, **kwargs): """Plot counts histogram with energy and offset axes Parameters ---------- ax : `~matplotlib.pyplot.Axis` Plot axis center : `~astropy.coordinates.SkyCoord` Sky coord from which offset is computed **kwargs : dict Keyword arguments forwarded to `~matplotlib.pyplot.pcolormesh` Returns ------- ax : `~matplotlib.pyplot.Axis` Plot axis """ from matplotlib.colors import LogNorm ax = plt.gca() if ax is None else ax if center is None: center = self._plot_center energy_axis = self._default_plot_energy_axis offset = center.separation(self.radec) offset_axis = MapAxis.from_bounds( 0 * u.deg, offset.max(), nbin=30, name="offset" ) counts = np.histogram2d(, y=offset, bins=(energy_axis.edges, offset_axis.edges), )[0] kwargs.setdefault("norm", LogNorm()) with quantity_support(): ax.pcolormesh(energy_axis.edges, offset_axis.edges, counts.T, **kwargs) energy_axis.format_plot_xaxis(ax=ax) offset_axis.format_plot_yaxis(ax=ax) return ax
[docs] def check(self, checks="all"): """Run checks. This is a generator that yields a list of dicts. """ checker = EventListChecker(self) return
[docs] def map_coord(self, geom): """Event map coordinates for a given geometry. Parameters ---------- geom : `~gammapy.maps.Geom` Geometry Returns ------- coord : `~gammapy.maps.MapCoord` Coordinates """ coord = {"skycoord": self.radec} cols = {k.upper(): v for k, v in self.table.columns.items()} for axis in geom.axes: try: col = cols[] coord[] = u.Quantity(col).to(axis.unit) except KeyError: raise KeyError(f"Column not found in event list: {!r}") return MapCoord.create(coord)
[docs] def select_mask(self, mask): """Select events inside a mask (`EventList`). Parameters ---------- mask : `~gammapy.maps.Map` Mask Returns ------- event_list : `EventList` Copy of event list with selection applied. Examples -------- >>> from import EventList >>> from gammapy.maps import WcsGeom, Map >>> geom = WcsGeom.create(skydir=(0,0), width=(4, 4), frame="galactic") >>> mask = geom.region_mask("galactic;circle(0, 0, 0.5)") >>> filename = "$GAMMAPY_DATA/cta-1dc/data/baseline/gps/gps_baseline_110380.fits" >>> events = >>> masked_event = events.select_mask(mask) >>> len(masked_event.table) 5594 """ coord = self.map_coord(mask.geom) values = mask.get_by_coord(coord) valid = values > 0 return self.select_row_subset(valid)
@property def observatory_earth_location(self): """Observatory location (`~astropy.coordinates.EarthLocation`).""" return earth_location_from_dict(self.table.meta) @property def observation_time_duration(self): """Observation time duration in seconds (`~astropy.units.Quantity`). This is a keyword related to IACTs The wall time, including dead-time. """ time_delta = (self.observation_time_stop - self.observation_time_start).sec return u.Quantity(time_delta, "s") @property def observation_live_time_duration(self): """Live-time duration in seconds (`~astropy.units.Quantity`). The dead-time-corrected observation time. - In Fermi-LAT it is automatically provided in the header of the event list. - In IACTs is computed as ``t_live = t_observation * (1 - f_dead)`` where ``f_dead`` is the dead-time fraction. """ return u.Quantity(self.table.meta["LIVETIME"], "second") @property def observation_dead_time_fraction(self): """Dead-time fraction (float). This is a keyword related to IACTs Defined as dead-time over observation time. Dead-time is defined as the time during the observation where the detector didn't record events: The dead-time fraction is used in the live-time computation, which in turn is used in the exposure and flux computation. """ return 1 - self.table.meta["DEADC"] @property def altaz_frame(self): """ALT / AZ frame (`~astropy.coordinates.AltAz`).""" return AltAz(obstime=self.time, location=self.observatory_earth_location) @property def altaz(self): """ALT / AZ position computed from RA / DEC (`~astropy.coordinates.SkyCoord`).""" return self.radec.transform_to(self.altaz_frame) @property def altaz_from_table(self): """ALT / AZ position from table (`~astropy.coordinates.SkyCoord`).""" lon = self.table["AZ"] lat = self.table["ALT"] return SkyCoord(lon, lat, unit="deg", frame=self.altaz_frame) @property def pointing_radec(self): """Pointing RA / DEC sky coordinates (`~astropy.coordinates.SkyCoord`).""" info = self.table.meta lon, lat = info["RA_PNT"], info["DEC_PNT"] return SkyCoord(lon, lat, unit="deg", frame="icrs") @property def offset(self): """Event offset from the array pointing position (`~astropy.coordinates.Angle`).""" position = self.radec center = self.pointing_radec offset = center.separation(position) return Angle(offset, unit="deg") @property def offset_from_median(self): """Event offset from the median position (`~astropy.coordinates.Angle`).""" position = self.radec center = self.galactic_median offset = center.separation(position) return Angle(offset, unit="deg")
[docs] def select_offset(self, offset_band): """Select events in offset band. Parameters ---------- offset_band : `~astropy.coordinates.Angle` offset band ``[offset_min, offset_max)`` Returns ------- event_list : `EventList` Copy of event list with selection applied. Examples -------- >>> from import EventList >>> import astropy.units as u >>> filename = "$GAMMAPY_DATA/cta-1dc/data/baseline/gps/gps_baseline_110380.fits" >>> events = >>> selected_events = events.select_offset([0.3, 0.9]*u.deg) >>> len(selected_events.table) 12688 """ offset = self.offset mask = offset_band[0] <= offset mask &= offset < offset_band[1] return self.select_row_subset(mask)
[docs] def select_rad_max(self, rad_max, position=None): """Select energy dependent offset Parameters ---------- rad_max : `~gamapy.irf.RadMax2D` Rad max definition position : `~astropy.coordinates.SkyCoord` Center position. By default the pointing position is used. Returns ------- event_list : `EventList` Copy of event list with selection applied. """ if position is None: position = self.pointing_radec offset = position.separation(self.pointing_radec) separation = position.separation(self.radec) rad_max_for_events = rad_max.evaluate( method="nearest",, offset=offset ) selected = separation <= rad_max_for_events return self.select_row_subset(selected)
@property def is_pointed_observation(self): """Whether observation is pointed""" return "RA_PNT" in self.table.meta
[docs] def peek(self, allsky=False): """Quick look plots. Parameters ---------- allsky : bool Whether to look at the events allsky """ import matplotlib.gridspec as gridspec if allsky: gs = gridspec.GridSpec(nrows=2, ncols=2) fig = plt.figure(figsize=(8, 8)) else: gs = gridspec.GridSpec(nrows=2, ncols=3) fig = plt.figure(figsize=(12, 8)) # energy plot ax_energy = fig.add_subplot(gs[1, 0]) self.plot_energy(ax=ax_energy) # offset plots if not allsky: ax_offset = fig.add_subplot(gs[0, 1]) self.plot_offset2_distribution(ax=ax_offset) ax_energy_offset = fig.add_subplot(gs[0, 2]) self.plot_energy_offset(ax=ax_energy_offset) # time plot ax_time = fig.add_subplot(gs[1, 1]) self.plot_time(ax=ax_time) # image plot m = self._counts_image(allsky=allsky) if allsky: ax_image = fig.add_subplot(gs[0, :], projection=m.geom.wcs) else: ax_image = fig.add_subplot(gs[0, 0], projection=m.geom.wcs) m.plot(ax=ax_image, stretch="sqrt", vmin=0) plt.subplots_adjust(wspace=0.3)
@property def _plot_center(self): if self.is_pointed_observation: return self.pointing_radec else: return self.galactic_median @property def _plot_width(self): if self.is_pointed_observation: offset = self.offset else: offset = self.offset_from_median return 2 * offset.max() def _counts_image(self, allsky): if allsky: opts = { "npix": (360, 180), "binsz": 1.0, "proj": "AIT", "frame": "galactic", } else: opts = { "width": self._plot_width, "binsz": 0.05, "proj": "TAN", "frame": "galactic", "skydir": self._plot_center, } m = WcsNDMap.create(**opts) m.fill_by_coord(self.radec) m = m.smooth(width=0.5) return m
[docs] def plot_image(self, ax=None, allsky=False): """Quick look counts map sky plot. Parameters ---------- ax : `~matplotlib.pyplot.Axes` Axes to plot on. allsky : bool, Whether to plot on an all sky geom """ if ax is None: ax = plt.gca() m = self._counts_image(allsky=allsky) m.plot(ax=ax, stretch="sqrt")
[docs] def copy(self): """Copy event list (`EventList`)""" return copy.deepcopy(self)
class EventListChecker(Checker): """Event list checker. Data format specification: ref:`gadf:iact-events` Parameters ---------- event_list : `` Event list """ CHECKS = { "meta": "check_meta", "columns": "check_columns", "times": "check_times", "coordinates_galactic": "check_coordinates_galactic", "coordinates_altaz": "check_coordinates_altaz", } accuracy = {"angle": Angle("1 arcsec"), "time": u.Quantity(1, "microsecond")} # # noqa: E501 meta_required = [ "HDUCLASS", "HDUDOC", "HDUVERS", "HDUCLAS1", "OBS_ID", "TSTART", "TSTOP", "ONTIME", "LIVETIME", "DEADC", "RA_PNT", "DEC_PNT", # TODO: what to do about these? # They are currently listed as required in the spec, # but I think we should just require ICRS and those # are irrelevant, should not be used. # 'RADECSYS', # 'EQUINOX', "ORIGIN", "TELESCOP", "INSTRUME", "CREATOR", # # noqa: E501 "MJDREFI", "MJDREFF", "TIMEUNIT", "TIMESYS", "TIMEREF", # # noqa: E501 "GEOLON", "GEOLAT", "ALTITUDE", ] _col = collections.namedtuple("col", ["name", "unit"]) columns_required = [ _col(name="EVENT_ID", unit=""), _col(name="TIME", unit="s"), _col(name="RA", unit="deg"), _col(name="DEC", unit="deg"), _col(name="ENERGY", unit="TeV"), ] def __init__(self, event_list): self.event_list = event_list def _record(self, level="info", msg=None): obs_id = self.event_list.table.meta["OBS_ID"] return {"level": level, "obs_id": obs_id, "msg": msg} def check_meta(self): meta_missing = sorted(set(self.meta_required) - set(self.event_list.table.meta)) if meta_missing: yield self._record( level="error", msg=f"Missing meta keys: {meta_missing!r}" ) def check_columns(self): t = self.event_list.table if len(t) == 0: yield self._record(level="error", msg="Events table has zero rows") for name, unit in self.columns_required: if name not in t.colnames: yield self._record(level="error", msg=f"Missing table column: {name!r}") else: if u.Unit(unit) != (t[name].unit or ""): yield self._record( level="error", msg=f"Invalid unit for column: {name!r}" ) def check_times(self): dt = (self.event_list.time - self.event_list.observation_time_start).sec if dt.min() < self.accuracy["time"].to_value("s"): yield self._record(level="error", msg="Event times before obs start time") dt = (self.event_list.time - self.event_list.observation_time_stop).sec if dt.max() > self.accuracy["time"].to_value("s"): yield self._record(level="error", msg="Event times after the obs end time") if np.min(np.diff(dt)) <= 0: yield self._record(level="error", msg="Events are not time-ordered.") def check_coordinates_galactic(self): """Check if RA / DEC matches GLON / GLAT.""" t = self.event_list.table if "GLON" not in t.colnames: return galactic = SkyCoord(t["GLON"], t["GLAT"], unit="deg", frame="galactic") separation = self.event_list.radec.separation(galactic).to("arcsec") if separation.max() > self.accuracy["angle"]: yield self._record( level="error", msg="GLON / GLAT not consistent with RA / DEC" ) def check_coordinates_altaz(self): """Check if ALT / AZ matches RA / DEC.""" t = self.event_list.table if "AZ" not in t.colnames: return altaz_astropy = self.event_list.altaz separation = angular_separation(,, t["AZ"].quantity, t["ALT"].quantity, ) if separation.max() > self.accuracy["angle"]: yield self._record( level="error", msg="ALT / AZ not consistent with RA / DEC" )