"""
Utilities for computing intensity corrections.
"""
import os
import pathlib
import warnings
from urllib.parse import urljoin
import astropy.io.ascii
import astropy.units as u
import drms
import numpy as np
from astropy.table import QTable
from astropy.time import Time
from erfa.core import ErfaWarning
from sunpy import log
from sunpy.data import manager
from sunpy.net import attrs, jsoc
from aiapy import _SSW_MIRRORS
from aiapy.util.decorators import validate_channel
__all__ = ["get_correction_table", "get_pointing_table", "get_error_table"]
# Default version of the degradation calibration curve to use.
# This needs to be incremented as the calibration is updated in JSOC.
CALIBRATION_VERSION = 10
# Error table filename available from SSW
AIA_ERROR_FILE = "sdo/aia/response/aia_V{}_error_table.txt"
# Most recent version number for error tables; increment as new versions become available
ERROR_VERSION = 3
# URLs and SHA-256 hashes for each version of the error tables
URL_HASH = {
2: (
[urljoin(mirror, AIA_ERROR_FILE.format(2)) for mirror in _SSW_MIRRORS],
"ac97ccc48057809723c27e3ef290c7d78ee35791d9054b2188baecfb5c290d0a",
),
3: (
[urljoin(mirror, AIA_ERROR_FILE.format(3)) for mirror in _SSW_MIRRORS],
"66ff034923bb0fd1ad20e8f30c7d909e1a80745063957dd6010f81331acaf894",
),
}
[docs]
def get_correction_table(*, correction_table=None):
"""
Return table of degradation correction factors.
This function returns a table of parameters for estimating the
time-dependent degradation of the instrument. By default, this table
is queried from ``aia.response`` series in
`JSOC <http://jsoc.stanford.edu/>`__. The correction table can also be read
from a file by passing a filepath to ``correction_table``. These files are
typically included in the SDO tree of an SSW installation in
``$SSW/sdo/aia/response/`` with filenames like ``aia_V*_response_table.txt``.
Parameters
----------
correction_table: `str` or `~astropy.table.QTable`, optional
Path to correction table file or an existing correction table. If None,
the table will be queried from JSOC.
Returns
-------
`~astropy.table.QTable`
See Also
--------
aiapy.calibrate.degradation
"""
if isinstance(correction_table, astropy.table.QTable):
return correction_table
if correction_table is not None:
if isinstance(correction_table, str | pathlib.Path):
table = QTable(astropy.io.ascii.read(correction_table))
else:
msg = "correction_table must be a file path, an existing table, or None."
raise ValueError(msg)
else:
# NOTE: the [!1=1!] disables the drms PrimeKey logic and enables
# the query to find records that are ordinarily considered
# identical because the PrimeKeys for this series are WAVE_STR
# and T_START. Without the !1=1! the query only returns the
# latest record for each unique combination of those keywords.
table = drms.Client().query("aia.response[][!1=1!]", key="**ALL**")
table = QTable.from_pandas(table)
selected_cols = [
"DATE",
"VER_NUM",
"WAVE_STR",
"WAVELNTH",
"T_START",
"T_STOP",
"EFFA_P1",
"EFFA_P2",
"EFFA_P3",
"EFF_AREA",
"EFF_WVLN",
]
table = table[selected_cols]
table["T_START"] = Time(table["T_START"], scale="utc")
# NOTE: The warning from erfa here is due to the fact that dates in
# this table include at least one date from 2030 and converting this
# date to UTC is ambiguous as the UTC conversion is not well defined
# at this date.
with warnings.catch_warnings():
warnings.simplefilter("ignore", category=ErfaWarning)
table["T_STOP"] = Time(table["T_STOP"], scale="utc")
table["WAVELNTH"].unit = "Angstrom"
table["EFF_WVLN"].unit = "Angstrom"
table["EFF_AREA"].unit = "cm2"
return table
@u.quantity_input
@validate_channel("channel")
def _select_epoch_from_correction_table(channel: u.angstrom, obstime, table, *, version=None):
"""
Return correction table with only the first epoch and the epoch in which
``obstime`` falls and for only one given calibration version.
Parameters
----------
channel : `~astropy.units.Quantity`
obstime : `~astropy.time.Time`
table : `~astropy.table.QTable`
version : `int`
"""
version = CALIBRATION_VERSION if version is None else version
# Select only this channel
# NOTE: The WAVE_STR prime keys for the aia.response JSOC series for the
# non-EUV channels do not have a thick/thin designation
thin = "_THIN" if channel not in (1600, 1700, 4500) * u.angstrom else ""
wave = channel.to(u.angstrom).value
table = table[table["WAVE_STR"] == f"{wave:.0f}{thin}"]
table = table[table["VER_NUM"] == version]
table.sort("DATE") # Newest entries will be last
if len(table) == 0:
extra_msg = " Max version is 3." if channel == 4500 * u.AA else ""
raise ValueError(
f"Correction table does not contain calibration for version {version} for {channel}." + extra_msg,
)
# Select the epoch for the given observation time
obstime_in_epoch = np.logical_and(obstime >= table["T_START"], obstime < table["T_STOP"])
if not obstime_in_epoch.any():
msg = f"No valid calibration epoch for {obstime}"
raise ValueError(msg)
# NOTE: In some cases, there may be multiple entries for a single epoch. We want to
# use the most up-to-date one.
i_epoch = np.where(obstime_in_epoch)[0]
if i_epoch.shape[0] > 1:
log.debug(
f"Multiple valid epochs for {obstime}. Using the most recent one",
)
# Create new table with only first and obstime epochs
return QTable(table[[0, i_epoch[-1]]])
[docs]
def get_pointing_table(start, end):
"""
Retrieve 3-hourly master pointing table from the JSOC.
This function queries `JSOC <http://jsoc.stanford.edu/>`__ for
the 3-hourly master pointing table (MPT) in the interval defined by
``start`` and ``end``.
The 3-hourly MPT entries are computed from limb fits of images with
``T_OBS`` between ``T_START`` and ``T_STOP``.
.. note:: A MPT entry covers the interval ``[T_START:T_STOP)``;
that is, the interval includes ``T_START`` and excludes
``T_STOP``.
.. note:: While it is generally true that ``TSTOP = T_START + 3 hours``,
there are edge cases where ``T_STOP`` is more than 3 hours
after ``T_START`` because of a calibration, an eclipse,
or other reasons, but the fits are still calculated based
on images from ``T_START`` to ``T_START + 3 hours``.
Pointing is not stable during these periods, so the question
of which MPT entry to use is not relevant.
Parameters
----------
start : `~astropy.time.Time`
end : `~astropy.time.Time`
Returns
-------
`~astropy.table.QTable`
See Also
--------
aiapy.calibrate.update_pointing
"""
q = jsoc.JSOCClient().search(
attrs.Time(start, end=end),
attrs.jsoc.Series.aia_master_pointing3h,
)
table = QTable(q)
if len(table.columns) == 0:
# If there's no pointing information available between these times,
# JSOC will raise a cryptic KeyError
# (see https://github.com/LM-SAL/aiapy/issues/71)
msg = f"Could not find any pointing information between {start} and {end}"
raise RuntimeError(msg)
table["T_START"] = Time(table["T_START"], scale="utc")
table["T_STOP"] = Time(table["T_STOP"], scale="utc")
for c in table.colnames:
if "X0" in c or "Y0" in c:
table[c].unit = "pixel"
if "IMSCALE" in c:
table[c].unit = "arcsecond / pixel"
if "INSTROT" in c:
table[c].unit = "degree"
# Remove masking on columns with pointing parameters
for c in table.colnames:
if any(n in c for n in ["X0", "Y0", "IMSCALE", "INSTROT"]) and hasattr(table[c], "mask"):
table[c] = table[c].filled(np.nan)
return table
[docs]
def get_error_table(error_table=None):
if error_table is None:
# This is to work around a parfive bug
# https://github.com/Cadair/parfive/issues/121
os.environ["PARFIVE_DISABLE_RANGE"] = "1"
error_table = fetch_error_table()
os.environ.pop("PARFIVE_DISABLE_RANGE")
if isinstance(error_table, str | pathlib.Path):
table = astropy.io.ascii.read(error_table)
elif isinstance(error_table, QTable):
table = error_table
else:
msg = f"error_table must be a file path, an existing table, or None, not {type(error_table)}"
raise TypeError(msg)
table = QTable(table)
table["DATE"] = Time(table["DATE"], scale="utc")
table["T_START"] = Time(table["T_START"], scale="utc")
# NOTE: The warning from erfa here is due to the fact that dates in
# this table include at least one date from 2030 and converting this
# date to UTC is ambiguous as the UTC conversion is not well defined
# at this date.
with warnings.catch_warnings():
warnings.simplefilter("ignore", category=ErfaWarning)
table["T_STOP"] = Time(table["T_STOP"], scale="utc")
table["WAVELNTH"] = u.Quantity(table["WAVELNTH"], "Angstrom")
table["DNPERPHT"] = u.Quantity(table["DNPERPHT"], "DN photon-1")
return table
@manager.require("error_table", *URL_HASH[ERROR_VERSION])
def fetch_error_table():
return manager.get("error_table")
