# Licensed under a 3-clause BSD style license - see LICENSE.rst
"""
======================
eHST Astroquery Module
======================
European Space Astronomy Centre (ESAC)
European Space Agency (ESA)
"""
import os
from urllib.parse import urlencode
import astroquery.esa.utils.utils as esautils
from astropy import units
from astropy.coordinates import SkyCoord
from astropy.coordinates import Angle
from numpy.ma import MaskedArray
from astroquery.utils.tap import TapPlus
from astroquery.query import BaseQuery
import json
import warnings
from astropy.utils.exceptions import AstropyDeprecationWarning
from astropy.utils.decorators import deprecated
from . import conf
from astroquery import log
__all__ = ['ESAHubble', 'ESAHubbleClass']
[docs]
class ESAHubbleClass(BaseQuery):
"""
Class to init ESA Hubble Module and communicate with eHST TAP
"""
TIMEOUT = conf.TIMEOUT
calibration_levels = {"AUXILIARY": 0, "RAW": 1, "CALIBRATED": 2,
"PRODUCT": 3}
product_types = ["SCIENCE", "PREVIEW", "THUMBNAIL", "AUXILIARY"]
copying_string = "Copying file to {0}..."
def __init__(self, *, tap_handler=None, show_messages=True):
if tap_handler is None:
self._tap = TapPlus(url=conf.EHST_TAP_SERVER,
data_context='data', client_id="ASTROQUERY")
else:
self._tap = tap_handler
if show_messages:
self.get_status_messages()
[docs]
def download_product(self, observation_id, *, calibration_level=None,
filename=None, folder=None, verbose=False, product_type=None):
"""
Download products from EHST based on their observation ID and the
calibration level or the product type.
Parameters
----------
observation_id : string
id of the observation to be downloaded, mandatory
The identifier of the observation we want to retrieve, regardless
of whether it is simple or composite.
calibration_level : string
calibration level, optional
The identifier of the data reduction/processing applied to the
data. By default, the most scientifically relevant level will be
chosen. RAW, CALIBRATED, PRODUCT or AUXILIARY
filename : string
File name to be used to store the artifact, optional, default
None
folder : string
optional, default current folder
Local folder to store the file
verbose : bool
optional, default 'False'
flag to display information about the process
product_type : string
type of product retrieval, optional
SCIENCE, PREVIEW, THUMBNAIL or AUXILIARY
------------
Deprecation Warning: PRODUCT, SCIENCE_PRODUCT or POSTCARD
are no longer supported.
------------
Returns
-------
None. It downloads the observation indicated
"""
if product_type and product_type in ['PRODUCT', 'SCIENCE_PRODUCT', 'POSTCARD']:
warnings.warn(
"PRODUCT, SCIENCE_PRODUCT or POSTCARD product types are no longer supported. "
"Please use SCIENCE, PREVIEW, THUMBNAIL or AUXILIARY instead.",
AstropyDeprecationWarning)
params = {"OBSERVATIONID": observation_id,
"TAPCLIENT": "ASTROQUERY",
"RETRIEVAL_TYPE": "OBSERVATION"}
if filename is None:
filename = observation_id
if calibration_level:
params["CALIBRATIONLEVEL"] = calibration_level
# Product type check to ensure backwards compatibility
product_type = self.__set_product_type(product_type)
if product_type:
self.__validate_product_type(product_type)
params["PRODUCTTYPE"] = product_type
filename = self._get_product_filename(product_type, filename)
output_file = self.__get_download_path(folder, filename)
self._tap.load_data(params_dict=params, output_file=output_file, verbose=verbose)
return esautils.check_rename_to_gz(filename=output_file)
def __get_download_path(self, folder, filename):
if folder is not None:
return os.path.join(folder, filename)
return filename
def __set_product_type(self, product_type):
if product_type:
if 'SCIENCE_PRODUCT' in product_type:
return 'SCIENCE'
elif 'PRODUCT' in product_type:
return None
elif 'POSTCARD' in product_type:
return 'PREVIEW'
return product_type
[docs]
def get_member_observations(self, observation_id):
"""
Returns the related members of simple and composite observations
Parameters
----------
observation_id : str
Observation identifier.
Returns
-------
A list of strings with the observation_id of the associated
observations
"""
observation_type = self.get_observation_type(observation_id)
if 'Composite' in observation_type:
oids = self._select_related_members(observation_id)
elif 'Simple' in observation_type:
oids = self._select_related_composite(observation_id)
else:
raise ValueError("Invalid observation id")
return oids
[docs]
def get_hap_hst_link(self, observation_id):
"""
Returns the related members of hap and hst observations
Parameters
----------
observation_id : string
id of the observation to be downloaded, mandatory
The identifier of the observation we want to retrieve, regardless
of whether it is simple or composite.
Returns
-------
A list of strings with the observation_id of the associated
observations
"""
observation_type = self.get_observation_type(observation_id)
if 'Composite' in observation_type:
raise ValueError("HAP-HST link is only available for simple observations. Input observation is Composite.")
elif 'HAP' in observation_type:
oids = self._select_related_members(observation_id)
elif 'HST' in observation_type:
query = ("select observation_id from ehst.observation where obs_type='HAP Simple' "
f"and members like '%{observation_id}%'")
job = self.query_tap(query=query)
oids = job["observation_id"]
else:
raise ValueError("Invalid observation id")
return oids
[docs]
def get_observation_type(self, observation_id):
"""
Returns the type of an observation
Parameters
----------
observation_id : string
id of the observation to be downloaded, mandatory
The identifier of the observation we want to retrieve, regardless
of whether it is simple or composite.
Returns
-------
String with the observation type
"""
if observation_id is None:
raise ValueError("Please input an observation id")
query = f"select obs_type from ehst.observation where observation_id='{observation_id}'"
job = self.query_tap(query=query)
if any(job["obs_type"]):
obs_type = self._get_decoded_string(string=job["obs_type"][0])
else:
raise ValueError("Invalid Observation ID")
return obs_type
[docs]
def get_observations_from_program(self, program, *, output_file=None,
output_format="votable", verbose=False):
"""
Retrieves all the observations associated to a program/proposal ID
Parameters
----------
program : int
Program or Proposal ID associated to the observations
output_file : string
optional, default None
file name to be used to store the result
output_format : string
results format. Options are:
'votable': str, binary VOTable format
'csv': str, comma-separated values format
verbose : bool
optional, default 'False'
flag to display information about the process
Returns
-------
A table object
"""
return self.query_criteria(proposal=program, output_file=output_file,
output_format=output_format, async_job=False, verbose=verbose)
[docs]
def download_files_from_program(self, program, *, folder=None, calibration_level=None,
data_product_type=None, intent=None,
obs_collection=None, instrument_name=None,
filters=None, only_fits=False):
"""
Download artifacts from EHST. Artifact is a single Hubble product file.
Parameters
----------
program : int
Program or Proposal ID associated to the observations
folder : string
optional, default current path
Local folder to store the file
calibration_level : str or int, optional
The identifier of the data reduction/processing applied to the
data. RAW (1), CALIBRATED (2), PRODUCT (3) or AUXILIARY (0)
data_product_type : str, optional
High level description of the product.
image, spectrum or timeseries.
intent : str, optional
The intent of the original observer in acquiring this observation.
SCIENCE or CALIBRATION
obs_collection : list of str, optional
List of collections that are available in eHST catalogue.
HLA, HST, HAP
instrument_name : str or list of str, optional
Name(s) of the instrument(s) used to generate the dataset
filters : list of str, optional
Name(s) of the filter(s) used to generate the dataset
only_fits : bool
optional, default 'False'
flag to download only FITS files
Returns
-------
None. It downloads the artifact indicated
"""
observations = self.query_criteria(calibration_level=calibration_level,
data_product_type=data_product_type,
intent=intent, obs_collection=obs_collection,
instrument_name=instrument_name,
filters=filters,
proposal=program,
async_job=False)
if only_fits:
self.download_fits_files(observation_id=observations['observation_id'], folder=folder)
else:
files = self.get_associated_files(observation_id=observations['observation_id'])
for file in files['filename']:
self.download_file(file=file, folder=folder)
def _select_related_members(self, observation_id):
query = f"select members from ehst.observation where observation_id='{observation_id}'"
job = self.query_tap(query=query)
oids = self._get_decoded_string(string=job["members"][0]).replace("caom:HST/", "").split(" ")
return oids
def _select_related_composite(self, observation_id):
query = f"select observation_id from ehst.observation where members like '%{observation_id}%'"
job = self.query_tap(query=query)
oids = job["observation_id"]
return oids
def __validate_product_type(self, product_type):
if (product_type not in self.product_types):
raise ValueError("This product_type is not allowed")
def _get_product_filename(self, product_type, filename):
if (product_type == "THUMBNAIL" or product_type == "PREVIEW"):
log.info("This is an image, the filename will be "
f"renamed to {filename}.jpg")
return f"{filename}.jpg"
else:
return f"{filename}.zip"
[docs]
def get_artifact(self, artifact_id, *, filename=None, folder=None, verbose=False):
"""
Download artifacts from EHST. Artifact is a single Hubble product file.
Parameters
----------
artifact_id : string
filename to be downloaded, mandatory
The identifier of the physical product (file) we want to retrieve.
filename : string
file name to be used to store the artifact, optional, default None
File name for the artifact
folder : string
optional, default current path
Local folder to store the file
verbose : bool
optional, default 'False'
flag to display information about the process
Returns
-------
None. It downloads the artifact indicated
"""
return self.download_file(file=artifact_id, filename=filename, folder=folder, verbose=verbose)
[docs]
def get_associated_files(self, observation_id, *, verbose=False):
"""
Retrieves all the files associated to an observation
Parameters
----------
observation_id : string or list of strings
id(s) of the observation(s) to be downloaded, mandatory
The identifier of the observation we want to retrieve, regardless
of whether it is simple or composite.
verbose : bool
optional, default 'False'
flag to display information about the process
Returns
-------
None. The file is associated
"""
if isinstance(observation_id, list) or isinstance(observation_id, MaskedArray):
observation_id = "', '".join(observation_id)
query = (f"select art.artifact_id as filename, p.calibration_level, art.archive_class as type, "
f"pg_size_pretty(art.size_uncompr) as size_uncompressed from ehst.artifact art "
f"join ehst.plane p on p.plane_id = art.plane_id where "
f"art.observation_id in ('{observation_id}')")
return self.query_tap(query=query)
[docs]
def download_fits_files(self, observation_id, *, folder=None, verbose=False):
"""
Retrieves all the FITS files associated to an observation
Parameters
----------
observation_id : string or list of strings
id of the observation to be downloaded, mandatory
The identifier of the observation we want to retrieve, regardless
of whether it is simple or composite.
folder : string
optional, default current path
Local folder to store the file
verbose : bool
optional, default 'False'
flag to display information about the process
Returns
-------
None. The file is associated
"""
results = self.get_associated_files(observation_id=observation_id, verbose=verbose)
for file in [i['filename'] for i in results if i['filename'].endswith('.fits')]:
if verbose:
print(f"Downloading {file} ...")
self.download_file(file=file, filename=file, folder=folder, verbose=verbose)
[docs]
def download_file(self, file, *, filename=None, folder=None, verbose=False):
"""
Download a file from eHST based on its filename.
Parameters
----------
file : string
file name of the artifact to be downloaded
filename : string
file name to be used to store the file, optional, default None
folder : string
optional, default current path
Local folder to store the file
verbose : bool
optional, default 'False'
flag to display information about the process
Returns
-------
None. The file is associated
"""
params = {"RETRIEVAL_TYPE": "PRODUCT", "ARTIFACTID": file, "TAPCLIENT": "ASTROQUERY"}
if filename is None:
filename = file
output_file = self.__get_download_path(folder, filename)
self._tap.load_data(params_dict=params, output_file=output_file, verbose=verbose)
return esautils.check_rename_to_gz(filename=output_file)
[docs]
def get_postcard(self, observation_id, *, calibration_level="RAW",
resolution=256, filename=None, verbose=False):
"""
Download postcards from EHST
Parameters
----------
observation_id : string
id of the observation for which download the postcard, mandatory
The identifier of the observation we want to retrieve, regardless
of whether it is simple or composite.
calibration_level : string
calibration level, optional, default 'RAW'
The identifier of the data reduction/processing applied to the
data. By default, the most scientifically relevant level will be
chosen. RAW, CALIBRATED, PRODUCT or AUXILIARY
resolution : integer
postcard resolution, optional, default 256
Resolution of the retrieved postcard. 256 or 1024
filename : string
file name to be used to store the postcard, optional, default None
File name for the artifact
verbose : bool
optional, default 'False'
Flag to display information about the process
Returns
-------
None. It downloads the observation postcard indicated
"""
params = {"RETRIEVAL_TYPE": "OBSERVATION",
"OBSERVATIONID": observation_id,
"PRODUCTTYPE": "PREVIEW",
"TAPCLIENT": "ASTROQUERY"}
if calibration_level:
params["CALIBRATIONLEVEL"] = calibration_level
if resolution:
params["PRODUCTTYPE"] = self.__get_product_type_by_resolution(resolution)
if filename is None:
filename = observation_id
self._tap.load_data(params_dict=params, output_file=filename, verbose=verbose)
return filename
def __get_product_type_by_resolution(self, resolution):
if resolution == 256:
return 'THUMBNAIL'
elif resolution == 1024:
return 'PREVIEW'
else:
raise ValueError("Resolution must be 256 or 1024")
[docs]
def cone_search(self, coordinates, radius, *, filename=None,
output_format='votable', cache=True,
async_job=False, verbose=False):
"""
To execute a cone search defined by a coordinate and a radius
Parameters
----------
coordinates : astropy.coordinate, mandatory
coordinates of the center in the cone search
radius : float or quantity
radius in arcmin (int, float) or quantity of the cone_search
filename : str, default None
Path and name of the file to store the results.
If the filename is defined, the file will be
automatically saved
output_format : string
results format. Options are:
'votable': str, binary VOTable format
'csv': str, comma-separated values format
async_job : bool, optional, default 'False'
executes the query (job) in asynchronous/synchronous mode (default
synchronous)
cache : bool
optional, default 'True'
Flag to save the results in the local cache
verbose : bool, optional, default 'False'
flag to display information about the process
Returns
-------
astropy.table.Table with the result of the cone_search
"""
coord = self._getCoordInput(coordinates)
if isinstance(radius, int) or isinstance(radius, float):
radius_in_grades = Angle(radius, units.arcmin).deg
else:
radius_in_grades = radius.to(units.deg).value
ra = coord.ra.deg
dec = coord.dec.deg
query = ("select o.observation_id, "
"o.start_time, o.end_time, o.start_time_mjd, "
"o.end_time_mjd, o.exposure_duration, o.release_date, "
"o.run_id, o.program_id, o.set_id, o.collection, "
"o.members_number, o.instrument_configuration, "
"o.instrument_name, o.obs_type, o.target_moving, "
"o.target_name, o.target_description, o.proposal_id, "
"o.pi_name, prop.title, pl.metadata_provenance, "
"pl.data_product_type, pl.software_version, pos.ra, "
"pos.dec, pos.gal_lat, pos.gal_lon, pos.ecl_lat, "
"pos.ecl_lon, pos.fov_size, en.wave_central, "
"en.wave_bandwidth, en.wave_max, en.wave_min, "
"en.filter from ehst.observation o join ehst.proposal "
"prop on o.proposal_id=prop.proposal_id join ehst.plane "
"pl on pl.observation_id=o.observation_id join "
"ehst.position pos on pos.plane_id = pl.plane_id join "
"ehst.energy en on en.plane_id=pl.plane_id where "
"pl.main_science_plane='true' and 1=CONTAINS(POINT('ICRS', "
f"pos.ra, pos.dec),CIRCLE('ICRS', {str(ra)}, {str(dec)}, {str(radius_in_grades)})) order "
"by prop.proposal_id desc")
if verbose:
log.info(query)
table = self.query_tap(query=query, async_job=async_job,
output_file=filename,
output_format=output_format,
verbose=verbose)
return table
[docs]
def cone_search_criteria(self, radius, *, target=None,
coordinates=None,
calibration_level=None,
data_product_type=None,
intent=None,
obs_collection=None,
instrument_name=None,
filters=None,
proposal=None,
async_job=True,
filename=None,
output_format='votable',
save=False,
cache=True,
verbose=False):
"""
To execute a cone search defined by a coordinate (an
astropy.coordinate element or a target name which is resolved),
a radius and a set of criteria to filter the results. This function
comprises the outputs of query_target, cone_search and query_criteria
methods.
Parameters
----------
radius : float or quantity
radius in arcmin (int, float) or quantity of the cone_search
target : str, mandatory if no coordinates is provided
name of the target, that will act as center in the cone search
coordinates : astropy.coordinate, mandatory if no target is provided
coordinates of the center in the cone search
calibration_level : str or int, optional
The identifier of the data reduction/processing applied to the
data. RAW (1), CALIBRATED (2), PRODUCT (3) or AUXILIARY (0)
data_product_type : str, optional
High level description of the product.
image, spectrum or timeseries.
intent : str, optional
The intent of the original observer in acquiring this observation.
SCIENCE or CALIBRATION
collection : list of str, optional
List of collections that are available in eHST catalogue.
HLA, HST
instrument_name : list of str, optional
Name(s) of the instrument(s) used to generate the dataset
filters : list of str, optional
Name(s) of the filter(s) used to generate the dataset
proposal : int, optional
Proposal ID associated to the observations
async_job : bool, optional, default 'False'
executes the query (job) in asynchronous/synchronous mode (default
synchronous)
filename : str, default None
Path and name of the file to store the results.
If the filename is defined, the file will be
automatically saved
output_format : string
results format. Options are:
'votable': str, binary VOTable format
'csv': str, comma-separated values format
save : bool
optional, default 'False'
Flag to save the result in a file. If the filename
is not defined, it will use a formatted name to save
the file
cache : bool
optional, default 'True'
Flag to save the results in the local cache
verbose : bool, optional, default 'False'
flag to display information about the process
Returns
-------
astropy.table.Table with the result of the cone_search
"""
crit_query = self.query_criteria(calibration_level=calibration_level,
data_product_type=data_product_type,
intent=intent,
obs_collection=obs_collection,
instrument_name=instrument_name,
filters=filters,
proposal=proposal,
async_job=True,
get_query=True)
if crit_query.endswith(")"):
crit_query = crit_query[:-1] + " AND "
else:
crit_query = crit_query + " WHERE ("
if target and coordinates:
raise TypeError("Please use only target or coordinates as"
"parameter.")
if target:
coord = self._query_tap_target(target)
else:
coord = self._getCoordInput(coordinates)
ra = coord.ra.deg
dec = coord.dec.deg
if isinstance(radius, int) or isinstance(radius, float):
radius_in_grades = Angle(radius, units.arcmin).deg
else:
radius_in_grades = radius.to(units.deg).value
cone_query = "1=CONTAINS(POINT('ICRS', ra, dec)," \
"CIRCLE('ICRS', {0}, {1}, {2}))". \
format(str(ra), str(dec), str(radius_in_grades))
query = "{}{})".format(crit_query, cone_query)
if verbose:
log.info(query)
table = self.query_tap(query=query, async_job=async_job,
output_file=filename,
output_format=output_format,
verbose=verbose)
return table
def _query_tap_target(self, target):
try:
params = {"TARGET_NAME": target,
"RESOLVER_TYPE": "ALL",
"FORMAT": "json",
"TAPCLIENT": "ASTROQUERY"}
subContext = conf.EHST_TARGET_ACTION
connHandler = self._tap._TapPlus__getconnhandler()
data = urlencode(params)
target_response = connHandler.execute_secure(subContext, data, verbose=True)
for line in target_response:
target_result = json.loads(line.decode("utf-8"))
if target_result['objects']:
ra = target_result['objects'][0]['raDegrees']
dec = target_result['objects'][0]['decDegrees']
return SkyCoord(ra=ra, dec=dec, unit="deg")
except (ValueError, KeyError):
raise ValueError("This target cannot be resolved")
[docs]
def query_target(self, name, *, filename=None, output_format='votable',
verbose=False, async_job=False, radius=7):
"""
It executes a query over EHST and download the xml with the results.
Parameters
----------
name : string
target name to be requested, mandatory
filename : string
file name to be used to store the metadata, optional, default None
output_format : string
optional, default 'votable'
output format of the query
verbose : bool
optional, default 'False'
Flag to display information about the process
async_job : bool, optional, default 'False'
executes the query (job) in asynchronous/synchronous mode (default
synchronous)
radius : int
optional, default 7
radius in arcmin (int, float) or quantity of the cone_search
Returns
-------
Table with the result of the query. It downloads metadata as a file.
"""
coordinates = self._query_tap_target(name)
table = self.cone_search(coordinates, radius, filename=filename, output_format=output_format,
verbose=verbose, async_job=async_job)
return table
[docs]
def query_tap(self, query, *, async_job=False, output_file=None,
output_format="votable", verbose=False):
"""Launches a synchronous or asynchronous job to query the HST tap
Parameters
----------
query : str, mandatory
query (adql) to be executed
async_job : bool, optional, default 'False'
executes the query (job) in asynchronous/synchronous mode (default
synchronous)
output_file : str, optional, default None
file name where the results are saved if dumpToFile is True.
If this parameter is not provided, the jobid is used instead
output_format : str, optional, default 'votable'
results format
verbose : bool, optional, default 'False'
flag to display information about the process
Returns
-------
A table object
"""
if async_job:
job = self._tap.launch_job_async(query=query,
output_file=output_file,
output_format=output_format,
verbose=verbose,
dump_to_file=output_file is not None)
else:
job = self._tap.launch_job(query=query, output_file=output_file,
output_format=output_format,
verbose=verbose,
dump_to_file=output_file is not None)
table = job.get_results()
return table
[docs]
@deprecated(since="0.4.7", alternative="query_tap")
def query_hst_tap(self, query, *, async_job=False, output_file=None,
output_format="votable", verbose=False):
"""Launches a synchronous or asynchronous job to query the HST tap
Parameters
----------
query : str, mandatory
query (adql) to be executed
async_job : bool, optional, default 'False'
executes the query (job) in asynchronous/synchronous mode (default
synchronous)
output_file : str, optional, default None
file name where the results are saved if dumpToFile is True.
If this parameter is not provided, the jobid is used instead
output_format : str, optional, default 'votable'
results format
verbose : bool, optional, default 'False'
flag to display information about the process
Returns
-------
A table object
"""
self.query_tap(query=query, async_job=False, output_file=None,
output_format="votable", verbose=False)
[docs]
def query_criteria(self, *, calibration_level=None,
data_product_type=None, intent=None,
obs_collection=None, instrument_name=None,
filters=None, proposal=None, async_job=True, output_file=None,
output_format="votable", verbose=False,
get_query=False):
"""
Launches a synchronous or asynchronous job to query the HST tap
using calibration level, data product type, intent, collection,
instrument name, and filters as criteria to create and execute the
associated query.
Parameters
----------
calibration_level : str or int, optional
The identifier of the data reduction/processing applied to the
data. RAW (1), CALIBRATED (2), PRODUCT (3) or AUXILIARY (0)
data_product_type : str, optional
High level description of the product.
image, spectrum or timeseries.
intent : str, optional
The intent of the original observer in acquiring this observation.
SCIENCE or CALIBRATION
obs_collection : list of str, optional
List of collections that are available in eHST catalogue.
HLA, HST, HAP
instrument_name : str or list of str, optional
Name(s) of the instrument(s) used to generate the dataset
filters : list of str, optional
Name(s) of the filter(s) used to generate the dataset
proposal : int, optional
Proposal ID associated to the observations
async_job : bool, optional, default 'True'
executes the query (job) in asynchronous/synchronous mode (default
synchronous)
output_file : str, optional, default None
file name where the results are saved if dumpToFile is True.
If this parameter is not provided, the jobid is used instead
output_format : str, optional, default 'votable'
results format
verbose : bool, optional, default 'False'
flag to display information about the process
get_query : bool, optional, default 'False'
flag to return the query associated to the criteria as the result
of this function.
Returns
-------
A table object
"""
parameters = []
if calibration_level is not None:
parameters.append("calibration_level={}".format(
self.__get_calibration_level(calibration_level)))
if data_product_type is not None:
if isinstance(data_product_type, str):
parameters.append("data_product_type LIKE '%{}%'".format(
data_product_type))
else:
raise ValueError("data_product_type must be a string")
if intent is not None:
if isinstance(intent, str):
parameters.append("intent LIKE '%{}%'".format(intent.lower()))
else:
raise ValueError("intent must be a string")
if proposal is not None:
if isinstance(proposal, int):
parameters.append("proposal_id = '{}'".format(proposal))
else:
raise ValueError("Proposal ID must be an integer")
if self.__check_list_strings(obs_collection):
parameters.append("(collection LIKE '%{}%')".format(
"%' OR collection LIKE '%".join(obs_collection)
))
if self.__check_list_strings(instrument_name):
if isinstance(instrument_name, str):
instrument_name = [instrument_name]
parameters.append("(instrument_name LIKE '%{}%')".format(
"%' OR instrument_name LIKE '%".join(instrument_name)
))
if self.__check_list_strings(filters):
parameters.append("(filter LIKE '%{}%')"
.format("%' OR filter "
"LIKE '%".join(filters)))
query = "select * from ehst.archive"
if parameters:
query += " where({})".format(" AND ".join(parameters))
if verbose:
log.info(query)
if get_query:
return query
table = self.query_tap(query=query, async_job=async_job,
output_file=output_file,
output_format=output_format,
verbose=verbose)
return table
def __get_calibration_level(self, calibration_level):
condition = ""
if (calibration_level is not None):
if isinstance(calibration_level, int):
if calibration_level < 4:
condition = calibration_level
else:
raise KeyError("Calibration level must be between 0 and 3")
elif isinstance(calibration_level, str):
condition = self.calibration_levels[calibration_level]
else:
raise KeyError("Calibration level must be either "
"a string or an integer")
return condition
def __check_list_strings(self, list):
if list is None:
return False
if list and all(isinstance(elem, str) for elem in list):
return True
else:
raise ValueError("One of the lists is empty or there are "
"elements that are not strings")
[docs]
def get_tables(self, *, only_names=True, verbose=False):
"""Get the available table in EHST TAP service
Parameters
----------
only_names : bool, TAP+ only, optional, default 'False'
True to load table names only
verbose : bool, optional, default 'False'
flag to display information about the process
Returns
-------
A list of tables
"""
tables = self._tap.load_tables(only_names=only_names,
include_shared_tables=False,
verbose=verbose)
if only_names is True:
table_names = []
for t in tables:
table_names.append(t.name)
return table_names
else:
return tables
[docs]
def get_status_messages(self):
"""Retrieve the messages to inform users about
the status of eHST TAP
"""
try:
subContext = conf.EHST_MESSAGES
connHandler = self._tap._TapPlus__getconnhandler()
response = connHandler.execute_tapget(subContext, verbose=False)
if response.status == 200:
for line in response:
string_message = line.decode("utf-8")
print(string_message[string_message.index('=') + 1:])
except OSError:
print("Status messages could not be retrieved")
[docs]
def get_columns(self, table_name, *, only_names=True, verbose=False):
"""Get the available columns for a table in EHST TAP service
Parameters
----------
table_name : string, mandatory, default None
table name of which, columns will be returned
only_names : bool, TAP+ only, optional, default 'False'
True to load table names only
verbose : bool, optional, default 'False'
flag to display information about the process
Returns
-------
A list of columns
"""
tables = self._tap.load_tables(only_names=False,
include_shared_tables=False,
verbose=verbose)
columns = None
for t in tables:
if str(t.name) == str(table_name):
columns = t.columns
break
if columns is None:
raise ValueError("table name specified is not found in "
"EHST TAP service")
if only_names is True:
column_names = []
for c in columns:
column_names.append(c.name)
return column_names
else:
return columns
def _getCoordInput(self, value):
if not (isinstance(value, str) or isinstance(value, SkyCoord)):
raise ValueError("Coordinates must be either a string or astropy.coordinates")
if isinstance(value, str):
return SkyCoord(value)
else:
return value
def _get_decoded_string(self, string):
try:
return string.decode('utf-8')
except (UnicodeDecodeError, AttributeError):
return string
ESAHubble = ESAHubbleClass()