Source code for astroquery.alma.core

# Licensed under a 3-clause BSD style license - see LICENSE.rst

import os.path
import keyring
import numpy as np
import re
import tarfile
import string
import requests
import warnings

from pkg_resources import resource_filename
from bs4 import BeautifulSoup
import pyvo
from urllib.parse import urljoin

from astropy.table import Table, Column, vstack
from astroquery import log
from astropy.utils.console import ProgressBar
from astropy import units as u
from astropy.time import Time
from pyvo.dal.sia2 import SIA_PARAMETERS_DESC

from ..exceptions import LoginError
from ..utils import commons
from ..utils.process_asyncs import async_to_sync
from ..query import QueryWithLogin
from .tapsql import _gen_pos_sql, _gen_str_sql, _gen_numeric_sql,\
    _gen_band_list_sql, _gen_datetime_sql, _gen_pol_sql, _gen_pub_sql,\
    _gen_science_sql, _gen_spec_res_sql, ALMA_DATE_FORMAT
from . import conf, auth_urls
from astroquery.utils.commons import ASTROPY_LT_4_1
from astroquery.exceptions import CorruptDataWarning

__all__ = {'AlmaClass', 'ALMA_BANDS'}

__doctest_skip__ = ['AlmaClass.*']

ALMA_SIA_PATH = 'sia2'
ALMA_DATALINK_PATH = 'datalink/sync'

# Map from ALMA ObsCore result to ALMA original query result
# The map is provided in order to preserve the name of the columns in the
# original ALMA query original results and make it backwards compatible
# key - current column, value - original column name
    'proposal_id': 'Project code',
    'target_name': 'Source name',
    's_ra': 'RA',
    's_dec': 'Dec',
    'gal_longitude': 'Galactic longitude',
    'gal_latitude': 'Galactic latitude',
    'band_list': 'Band',
    's_region': 'Footprint',
    'em_resolution': 'Frequency resolution',
    'antenna_arrays': 'Array',
    'is_mosaic': 'Mosaic',
    't_exptime': 'Integration',
    'obs_release_date': 'Release date',
    'frequency_support': 'Frequency support',
    'velocity_resolution': 'Velocity resolution',
    'pol_states': 'Pol products',
    't_min': 'Observation date',
    'obs_creator_name': 'PI name',
    'schedblock_name': 'SB name',
    'proposal_authors': 'Proposal authors',
    'sensitivity_10kms': 'Line sensitivity (10 km/s)',
    'cont_sensitivity_bandwidth': 'Continuum sensitivity',
    'pwv': 'PWV',
    'group_ous_uid': 'Group ous id',
    'member_ous_uid': 'Member ous id',
    'asdm_uid': 'Asdm uid',
    'obs_title': 'Project title',
    'type': 'Project type',
    'scan_intent': 'Scan intent',
    's_fov': 'Field of view',
    'spatial_scale_max': 'Largest angular scale',
    'qa2_passed': 'QA2 Status',
    'science_keyword': 'Science keyword',
    'scientific_category': 'Scientific category'

    '3': (84*u.GHz, 116*u.GHz),
    '4': (125*u.GHz, 163*u.GHz),
    '5': (163*u.GHz, 211*u.GHz),
    '6': (211*u.GHz, 275*u.GHz),
    '7': (275*u.GHz, 373*u.GHz),
    '8': (385*u.GHz, 500*u.GHz),
    '9': (602*u.GHz, 720*u.GHz),
    '10': (787*u.GHz, 950*u.GHz)

    'Position': {
        'Source name (astropy Resolver)': ['source_name_resolver',
                                           'SkyCoord.from_name', _gen_pos_sql],
        'Source name (ALMA)': ['source_name_alma', 'target_name', _gen_str_sql],
        'RA Dec (Sexagesimal)': ['ra_dec', 's_ra, s_dec', _gen_pos_sql],
        'Galactic (Degrees)': ['galactic', 'gal_longitude, gal_latitude',
        'Angular resolution (arcsec)': ['spatial_resolution',
                                        'spatial_resolution', _gen_numeric_sql],
        'Largest angular scale (arcsec)': ['spatial_scale_max',
                                           'spatial_scale_max', _gen_numeric_sql],
        'Field of view (arcsec)': ['fov', 's_fov', _gen_numeric_sql]
    'Energy': {
        'Frequency (GHz)': ['frequency', 'frequency', _gen_numeric_sql],
        'Bandwidth (Hz)': ['bandwidth', 'bandwidth', _gen_numeric_sql],
        'Spectral resolution (KHz)': ['spectral_resolution',
                                      'em_resolution', _gen_spec_res_sql],
        'Band': ['band_list', 'band_list', _gen_band_list_sql]
    'Time': {
        'Observation date': ['start_date', 't_min', _gen_datetime_sql],
        'Integration time (s)': ['integration_time', 't_exptime',
    'Polarization': {
        'Polarisation type (Single, Dual, Full)': ['polarisation_type',
                                                   'pol_states', _gen_pol_sql]
    'Observation': {
        'Line sensitivity (10 km/s) (mJy/beam)': ['line_sensitivity',
        'Continuum sensitivity (mJy/beam)': ['continuum_sensitivity',
        'Water vapour (mm)': ['water_vapour', 'pvw', _gen_numeric_sql]
    'Project': {
        'Project code': ['project_code', 'proposal_id', _gen_str_sql],
        'Project title': ['project_title', 'obs_title', _gen_str_sql],
        'PI name': ['pi_name', 'obs_creator_name', _gen_str_sql],
        'Proposal authors': ['proposal_authors', 'proposal_authors', _gen_str_sql],
        'Project abstract': ['project_abstract', 'proposal_abstract', _gen_str_sql],
        'Publication count': ['publication_count', 'NA', _gen_str_sql],
        'Science keyword': ['science_keyword', 'science_keyword', _gen_str_sql]
    'Publication': {
        'Bibcode': ['bibcode', 'bib_reference', _gen_str_sql],
        'Title': ['pub_title', 'pub_title', _gen_str_sql],
        'First author': ['first_author', 'first_author', _gen_str_sql],
        'Authors': ['authors', 'authors', _gen_str_sql],
        'Abstract': ['pub_abstract', 'pub_abstract', _gen_str_sql],
        'Year': ['publication_year', 'pub_year', _gen_numeric_sql]
    'Options': {
        'Public data only': ['public_data', 'data_rights', _gen_pub_sql],
        'Science observations only': ['science_observation',
                                      'science_observation', _gen_science_sql]

def _gen_sql(payload):
    sql = 'select * from ivoa.obscore'
    where = ''
    unused_payload = payload.copy()
    if payload:
        for constraint in payload:
            for attrib_category in ALMA_FORM_KEYS.values():
                for attrib in attrib_category.values():
                    if constraint in attrib:
                        # use the value and the second entry in attrib which
                        # is the new name of the column
                        val = payload[constraint]
                        if constraint == 'em_resolution':
                            # em_resolution does not require any transformation
                            attrib_where = _gen_numeric_sql(constraint, val)
                            attrib_where = attrib[2](attrib[1], val)
                        if attrib_where:
                            if where:
                                where += ' AND '
                                where = ' WHERE '
                            where += attrib_where

                        # Delete this key to see what's left over afterward
                        # Use pop to avoid the slight possibility of trying to remove
                        # an already removed key

    if unused_payload:
        # Left over (unused) constraints passed.  Let the user know.
        remaining = [f'{p} -> {unused_payload[p]}' for p in unused_payload]
        raise TypeError(f'Unsupported arguments were passed:\n{remaining}')

    return sql + where

[docs]@async_to_sync class AlmaClass(QueryWithLogin): TIMEOUT = conf.timeout archive_url = conf.archive_url USERNAME = conf.username def __init__(self): # sia service does not need disambiguation but tap does super().__init__() self._sia = None self._tap = None self._datalink = None self.sia_url = None self.tap_url = None self.datalink_url = None @property def datalink(self): if not self._datalink: base_url = self._get_dataarchive_url() if base_url.endswith('/'): self.datalink_url = base_url + ALMA_DATALINK_PATH else: self.datalink_url = base_url + '/' + ALMA_DATALINK_PATH self._datalink = pyvo.dal.adhoc.DatalinkService( baseurl=self.datalink_url) return self._datalink @property def sia(self): if not self._sia: base_url = self._get_dataarchive_url() if base_url.endswith('/'): self.sia_url = base_url + ALMA_SIA_PATH else: self.sia_url = base_url + '/' + ALMA_SIA_PATH self._sia = pyvo.dal.sia2.SIAService(baseurl=self.sia_url) return self._sia @property def tap(self): if not self._tap: base_url = self._get_dataarchive_url() if base_url.endswith('/'): self.tap_url = base_url + ALMA_TAP_PATH else: self.tap_url = base_url + '/' + ALMA_TAP_PATH self._tap = pyvo.dal.tap.TAPService(baseurl=self.tap_url) return self._tap
[docs] def query_object_async(self, object_name, *, public=True, science=True, payload=None, **kwargs): """ Query the archive for a source name. Parameters ---------- object_name : str The object name. Will be resolved by astropy.coord.SkyCoord public : bool True to return only public datasets, False to return private only, None to return both science : bool True to return only science datasets, False to return only calibration, None to return both payload : dict Dictionary of additional keywords. See `help`. """ if payload is not None: payload['source_name_resolver'] = object_name else: payload = {'source_name_resolver': object_name} return self.query_async(public=public, science=science, payload=payload, **kwargs)
[docs] def query_region_async(self, coordinate, radius, *, public=True, science=True, payload=None, **kwargs): """ Query the ALMA archive with a source name and radius Parameters ---------- coordinates : str / `astropy.coordinates` the identifier or coordinates around which to query. radius : str / `~astropy.units.Quantity`, optional the radius of the region public : bool True to return only public datasets, False to return private only, None to return both science : bool True to return only science datasets, False to return only calibration, None to return both payload : dict Dictionary of additional keywords. See `help`. """ rad = radius if not isinstance(radius, u.Quantity): rad = radius*u.deg obj_coord = commons.parse_coordinates(coordinate).icrs ra_dec = '{}, {}'.format(obj_coord.to_string(), if payload is None: payload = {} if 'ra_dec' in payload: payload['ra_dec'] += ' | {}'.format(ra_dec) else: payload['ra_dec'] = ra_dec return self.query_async(public=public, science=science, payload=payload, **kwargs)
[docs] def query_async(self, payload, *, public=True, science=True, legacy_columns=False, get_query_payload=None, maxrec=None, **kwargs): """ Perform a generic query with user-specified payload Parameters ---------- payload : dictionary Please consult the `help` method public : bool True to return only public datasets, False to return private only, None to return both science : bool True to return only science datasets, False to return only calibration, None to return both legacy_columns : bool True to return the columns from the obsolete ALMA advanced query, otherwise return the current columns based on ObsCore model. get_query_payload : bool Flag to indicate whether to simply return the payload. maxrec : integer Cap on the amount of records returned. Default is no limit. Returns ------- Table with results. Columns are those in the ALMA ObsCore model (see ``help_tap``) unless ``legacy_columns`` argument is set to True. """ if payload is None: payload = {} for arg in kwargs: value = kwargs[arg] if 'band_list' == arg and isinstance(value, list): value = ' '.join([str(_) for _ in value]) if arg in payload: payload[arg] = '{} {}'.format(payload[arg], value) else: payload[arg] = value if science is not None: payload['science_observation'] = science if public is not None: payload['public_data'] = public if get_query_payload: return payload query = _gen_sql(payload) result = self.query_tap(query, maxrec=maxrec) if result is not None: result = result.to_table() else: # Should not happen raise RuntimeError('BUG: Unexpected result None') if legacy_columns: legacy_result = Table() # add 'Observation date' column for col_name in _OBSCORE_TO_ALMARESULT: if col_name in result.columns: if col_name == 't_min': legacy_result['Observation date'] = \ [Time(_['t_min'], format='mjd').strftime( ALMA_DATE_FORMAT) for _ in result] else: legacy_result[_OBSCORE_TO_ALMARESULT[col_name]] = \ result[col_name] else: log.error("Invalid column mapping in OBSCORE_TO_ALMARESULT: " "{}:{}. Please " "report this as an Issue." .format(col_name, _OBSCORE_TO_ALMARESULT[col_name])) return legacy_result return result
[docs] def query_sia(self, *, pos=None, band=None, time=None, pol=None, field_of_view=None, spatial_resolution=None, spectral_resolving_power=None, exptime=None, timeres=None, publisher_did=None, facility=None, collection=None, instrument=None, data_type=None, calib_level=None, target_name=None, res_format=None, maxrec=None, **kwargs): """ Use standard SIA2 attributes to query the ALMA SIA service. Parameters ---------- _SIA2_PARAMETERS Returns ------- Results in `pyvo.dal.SIAResults` format. result.table in Astropy table format """ return pos=pos, band=band, time=time, pol=pol, field_of_view=field_of_view, spatial_resolution=spatial_resolution, spectral_resolving_power=spectral_resolving_power, exptime=exptime, timeres=timeres, publisher_did=publisher_did, facility=facility, collection=collection, instrument=instrument, data_type=data_type, calib_level=calib_level, target_name=target_name, res_format=res_format, maxrec=maxrec, **kwargs)
# SIA_PARAMETERS_DESC contains links that Sphinx can't resolve. for var in ('POLARIZATION_STATES', 'CALIBRATION_LEVELS'): SIA_PARAMETERS_DESC = SIA_PARAMETERS_DESC.replace(f'`pyvo.dam.obscore.{var}`', f'pyvo.dam.obscore.{var}') query_sia.__doc__ = query_sia.__doc__.replace('_SIA2_PARAMETERS', SIA_PARAMETERS_DESC)
[docs] def query_tap(self, query, maxrec=None): """ Send query to the ALMA TAP. Results in pyvo.dal.TapResult format. result.table in Astropy table format Parameters ---------- maxrec : int maximum number of records to return """ log.debug('TAP query: {}'.format(query)) return, language='ADQL', maxrec=maxrec)
[docs] def help_tap(self): print('Table to query is "voa.ObsCore".') print('For example: "select top 1 * from ivoa.ObsCore"') print('The scheme of the table is as follows.\n') print(' {0:20s} {1:15s} {2:10} {3}'. format('Name', 'Type', 'Unit', 'Description')) print('-'*90) for tb in self.tap.tables.items(): if tb[0] == 'ivoa.obscore': for col in tb[1].columns: if col.datatype.content == 'char': type = 'char({})'.format(col.datatype.arraysize) else: type = str(col.datatype.content) unit = col.unit if col.unit else '' print(' {0:20s} {1:15s} {2:10} {3}'. format(, type, unit, col.description))
# update method pydocs query_region_async.__doc__ = query_region_async.__doc__.replace( '_SIA2_PARAMETERS', pyvo.dal.sia2.SIA_PARAMETERS_DESC) query_object_async.__doc__ = query_object_async.__doc__.replace( '_SIA2_PARAMETERS', pyvo.dal.sia2.SIA_PARAMETERS_DESC) query_async.__doc__ = query_async.__doc__.replace( '_SIA2_PARAMETERS', pyvo.dal.sia2.SIA_PARAMETERS_DESC) def _get_dataarchive_url(self): """ If the generic ALMA URL is used, query it to determine which mirror to access for querying data """ if not hasattr(self, 'dataarchive_url'): if self.archive_url in ('', ''): response = self._request('GET', self.archive_url, cache=False) response.raise_for_status() # Jan 2017: we have to force https because the archive doesn't # tell us it needs https. self.dataarchive_url = response.url.replace( "/asax/", "").replace("/aq/", "").replace("http://", "https://") else: self.dataarchive_url = self.archive_url elif self.dataarchive_url in ('', ''): raise ValueError("'dataarchive_url' was set to a disambiguation " "page that is meant to redirect to a real " "archive. You should only reach this message " "if you manually specified Alma.dataarchive_url. " "If you did so, instead consider setting " "Alma.archive_url. Otherwise, report an error " "on github.") return self.dataarchive_url
[docs] def get_data_info(self, uids, *, expand_tarfiles=False, with_auxiliary=True, with_rawdata=True): """ Return information about the data associated with ALMA uid(s) Parameters ---------- uids : list or str A list of valid UIDs or a single UID. UIDs should have the form: 'uid://A002/X391d0b/X7b' expand_tarfiles : bool False to return information on the tarfiles packages containing the data or True to return information about individual files in these packages with_auxiliary : bool True to include the auxiliary packages, False otherwise with_rawdata : bool True to include raw data, False otherwise Returns ------- Table with results or None. Table has the following columns: id (UID), access_url (URL to access data), content_length, content_type (MIME type), semantics, description (optional), error_message (optional) """ if uids is None: raise AttributeError('UIDs required') if isinstance(uids, (str, bytes)): uids = [uids] if not isinstance(uids, (list, tuple, np.ndarray)): raise TypeError("Datasets must be given as a list of strings.") # TODO remove this loop and send uids at once when pyvo fixed result = None for uid in uids: res = self.datalink.run_sync(uid) if res.status[0] != 'OK': raise Exception('ERROR {}: {}'.format(res.status[0], res.status[1])) temp = res.to_table() if ASTROPY_LT_4_1: # very annoying for col in [x for x in temp.colnames if x not in ['content_length', 'readable']]: temp[col] = temp[col].astype(str) result = temp if result is None else vstack([result, temp]) to_delete = [] for index, rr in enumerate(result): if rr['error_message'] is not None and \ rr['error_message'].strip(): log.warning('Error accessing info about file {}: {}'. format(rr['access_url'], rr['error_message'])) # delete from results. Good thing to do? to_delete.append(index) result.remove_rows(to_delete) if not with_auxiliary: result = result[np.core.defchararray.find( result['semantics'], '#aux') == -1] if not with_rawdata: result = result[np.core.defchararray.find( result['semantics'], '#progenitor') == -1] # primary data delivery type is files packaged in tarballs. However # some type of data has an alternative way to retrieve each individual # file as an alternative (semantics='#datalink' and # 'content_type=application/x-votable+xml;content=datalink'). They also # require an extra call to the datalink service to get the list of # files. DATALINK_FILE_TYPE = 'application/x-votable+xml;content=datalink' DATALINK_SEMANTICS = '#datalink' if expand_tarfiles: # identify the tarballs that can be expandable and replace them # with the list of components expanded_result = None to_delete = [] for index, row in enumerate(result): if DATALINK_SEMANTICS in row['semantics'] and \ row['content_type'] == DATALINK_FILE_TYPE: # subsequent call to datalink file_id = row['access_url'].split('ID=')[1] expanded_tar = self.get_data_info(file_id) expanded_tar = expanded_tar[ expanded_tar['semantics'] != '#cutout'] if not expanded_result: expanded_result = expanded_tar else: expanded_result = vstack( [expanded_result, expanded_tar], join_type='exact') to_delete.append(index) # cleanup result.remove_rows(to_delete) # add the extra rows if expanded_result: result = vstack([result, expanded_result], join_type='exact') else: result = result[np.logical_or(np.core.defchararray.find( result['semantics'].astype(str), DATALINK_SEMANTICS) == -1, result['content_type'].astype(str) != DATALINK_FILE_TYPE)] return result
[docs] def is_proprietary(self, uid): """ Given an ALMA UID, query the servers to determine whether it is proprietary or not. """ query = "select distinct data_rights from ivoa.obscore where " \ "member_ous_uid='{}'".format(uid) result = self.query_tap(query) if result: tableresult = result.to_table() if not result or len(tableresult) == 0: raise AttributeError('{} not found'.format(uid)) if len(tableresult) == 1 and tableresult[0][0] == 'Public': return False return True
def _HEADER_data_size(self, files): """ Given a list of file URLs, return the data size. This is useful for assessing how much data you might be downloading! (This is discouraged by the ALMA archive, as it puts unnecessary load on their system) """ totalsize = 0 * u.B data_sizes = {} pb = ProgressBar(len(files)) for index, fileLink in enumerate(files): response = self._request('HEAD', fileLink, stream=False, cache=False, timeout=self.TIMEOUT) filesize = (int(response.headers['content-length']) * u.B).to(u.GB) totalsize += filesize data_sizes[fileLink] = filesize log.debug("File {0}: size {1}".format(fileLink, filesize)) pb.update(index + 1) response.raise_for_status() return data_sizes,
[docs] def download_files(self, files, *, savedir=None, cache=True, continuation=True, skip_unauthorized=True, verify_only=False): """ Given a list of file URLs, download them Note: Given a list with repeated URLs, each will only be downloaded once, so the return may have a different length than the input list Parameters ---------- files : list List of URLs to download savedir : None or str The directory to save to. Default is the cache location. cache : bool Cache the download? continuation : bool Attempt to continue where the download left off (if it was broken) skip_unauthorized : bool If you receive "unauthorized" responses for some of the download requests, skip over them. If this is False, an exception will be raised. verify_only : bool Option to go through the process of checking the files to see if they're the right size, but not actually download them. This option may be useful if a previous download run failed partway. """ if self.USERNAME: auth = self._get_auth_info(self.USERNAME) else: auth = None downloaded_files = [] if savedir is None: savedir = self.cache_location for file_link in unique(files): log.debug("Downloading {0} to {1}".format(file_link, savedir)) try: check_filename = self._request('HEAD', file_link, auth=auth) check_filename.raise_for_status() except requests.HTTPError as ex: if ex.response.status_code == 401: if skip_unauthorized:"Access denied to {url}. Skipping to" " next file".format(url=file_link)) continue else: raise(ex) try: filename ="filename=(.*)", check_filename.headers['Content-Disposition']).groups()[0] except KeyError:"Unable to find filename for {file_link} " "(missing Content-Disposition in header). " "Skipping to next file.") continue if savedir is not None: filename = os.path.join(savedir, filename) if verify_only: existing_file_length = os.stat(filename).st_size if 'content-length' in check_filename.headers: length = int(check_filename.headers['content-length']) if length == 0: warnings.warn('URL {0} has length=0'.format(url)) elif existing_file_length == length:"Found cached file {filename} with expected size {existing_file_length}.") elif existing_file_length < length:"Found cached file {filename} with size {existing_file_length} < expected " f"size {length}. The download should be continued.") elif existing_file_length > length: warnings.warn(f"Found cached file {filename} with size {existing_file_length} > expected " f"size {length}. The download is likely corrupted.", CorruptDataWarning) else: warnings.warn(f"Could not verify {url} because it has no 'content-length'") try: if not verify_only: self._download_file(file_link, filename, timeout=self.TIMEOUT, auth=auth, cache=cache, method='GET', head_safe=False, continuation=continuation) downloaded_files.append(filename) except requests.HTTPError as ex: if ex.response.status_code == 401: if skip_unauthorized:"Access denied to {url}. Skipping to" " next file".format(url=file_link)) continue else: raise(ex) elif ex.response.status_code == 403: log.error("Access denied to {url}".format(url=file_link)) if 'dataPortal' in file_link and 'sso' not in file_link: log.error("The URL may be incorrect. Try using " "{0} instead of {1}" .format(file_link.replace('dataPortal/', 'dataPortal/sso/'), file_link)) raise ex elif ex.response.status_code == 500: # empirically, this works the second time most of the time... self._download_file(file_link, filename, timeout=self.TIMEOUT, auth=auth, cache=cache, method='GET', head_safe=False, continuation=continuation) downloaded_files.append(filename) else: raise ex return downloaded_files
def _parse_result(self, response, verbose=False): """ Parse a VOtable response """ if not verbose: commons.suppress_vo_warnings() return response
[docs] def retrieve_data_from_uid(self, uids, *, cache=True): """ Stage & Download ALMA data. Will print out the expected file size before attempting the download. Parameters ---------- uids : list or str A list of valid UIDs or a single UID. UIDs should have the form: 'uid://A002/X391d0b/X7b' cache : bool Whether to cache the downloads. Returns ------- downloaded_files : list A list of the downloaded file paths """ if isinstance(uids, (str, bytes)): uids = [uids] if not isinstance(uids, (list, tuple, np.ndarray)): raise TypeError("Datasets must be given as a list of strings.") files = self.get_data_info(uids) file_urls = files['access_url'] totalsize = files['content_length'].sum()*u.B # each_size, totalsize = self.data_size(files)"Downloading files of size {0}...".format( # TODO: Add cache=cache keyword here. Currently would have no effect. downloaded_files = self.download_files(file_urls) return downloaded_files
def _get_auth_info(self, username, *, store_password=False, reenter_password=False): """ Get the auth info (user, password) for use in another function """ if username is None: if not self.USERNAME: raise LoginError("If you do not pass a username to login(), " "you should configure a default one!") else: username = self.USERNAME if hasattr(self, '_auth_url'): auth_url = self._auth_url else: raise LoginError("Login with .login() to acquire the appropriate" " login URL") # Get password from keyring or prompt password, password_from_keyring = self._get_password( "astroquery:{0}".format(auth_url), username, reenter=reenter_password) # When authenticated, save password in keyring if needed if password_from_keyring is None and store_password: keyring.set_password("astroquery:{0}".format(auth_url), username, password) return username, password def _login(self, username=None, store_password=False, reenter_password=False, auth_urls=auth_urls): """ Login to the ALMA Science Portal. Parameters ---------- username : str, optional Username to the ALMA Science Portal. If not given, it should be specified in the config file. store_password : bool, optional Stores the password securely in your keyring. Default is False. reenter_password : bool, optional Asks for the password even if it is already stored in the keyring. This is the way to overwrite an already stored passwork on the keyring. Default is False. """ success = False for auth_url in auth_urls: # set session cookies (they do not get set otherwise) cookiesetpage = self._request("GET", urljoin(self._get_dataarchive_url(), 'rh/forceAuthentication'), cache=False) self._login_cookiepage = cookiesetpage cookiesetpage.raise_for_status() if (auth_url+'/cas/login' in cookiesetpage.request.url): # we've hit a target, we're good success = True break if not success: raise LoginError("Could not log in to any of the known ALMA " "authorization portals: {0}".format(auth_urls)) # Check if already logged in loginpage = self._request("GET", "https://{auth_url}/cas/login".format(auth_url=auth_url), cache=False) root = BeautifulSoup(loginpage.content, 'html5lib') if root.find('div', class_='success'):"Already logged in.") return True self._auth_url = auth_url username, password = self._get_auth_info(username=username, store_password=store_password, reenter_password=reenter_password) # Authenticate"Authenticating {0} on {1} ...".format(username, auth_url)) # Do not cache pieces of the login process data = {kw: root.find('input', {'name': kw})['value'] for kw in ('execution', '_eventId')} data['username'] = username data['password'] = password data['submit'] = 'LOGIN' login_response = self._request("POST", "https://{0}/cas/login".format(auth_url), params={'service': self._get_dataarchive_url()}, data=data, cache=False) # save the login response for debugging purposes self._login_response = login_response # do not expose password back to user del data['password'] # but save the parameters for debug purposes self._login_parameters = data authenticated = ('You have successfully logged in' in login_response.text) if authenticated:"Authentication successful!") self.USERNAME = username else: log.exception("Authentication failed!") return authenticated
[docs] def get_cycle0_uid_contents(self, uid): """ List the file contents of a UID from Cycle 0. Will raise an error if the UID is from cycle 1+, since those data have been released in a different and more consistent format. See for details. """ # First, check if UID is in the Cycle 0 listing if uid in self.cycle0_table['uid']: cycle0id = self.cycle0_table[ self.cycle0_table['uid'] == uid][0]['ID'] contents = [row['Files'] for row in self._cycle0_tarfile_content if cycle0id in row['ID']] return contents else: info_url = urljoin( self._get_dataarchive_url(), 'documents-and-tools/cycle-2/ALMAQA2Productsv1.01.pdf') raise ValueError("Not a Cycle 0 UID. See {0} for details about " "cycle 1+ data release formats.".format(info_url))
@property def _cycle0_tarfile_content(self): """ In principle, this is a static file, but we'll retrieve it just in case """ if not hasattr(self, '_cycle0_tarfile_content_table'): url = urljoin(self._get_dataarchive_url(), 'alma-data/archive/cycle-0-tarfile-content') response = self._request('GET', url, cache=True) # html.parser is needed because some <tr>'s have form: # <tr width="blah"> which the default parser does not pick up root = BeautifulSoup(response.content, 'html.parser') html_table = root.find('table', class_='grid listing') data = list(zip(*[(x.findAll('td')[0].text, x.findAll('td')[1].text) for x in html_table.findAll('tr')])) columns = [Column(data=data[0], name='ID'), Column(data=data[1], name='Files')] tbl = Table(columns) assert len(tbl) == 8497 self._cycle0_tarfile_content_table = tbl else: tbl = self._cycle0_tarfile_content_table return tbl @property def cycle0_table(self): """ Return a table of Cycle 0 Project IDs and associated UIDs. The table is distributed with astroquery and was provided by Felix Stoehr. """ if not hasattr(self, '_cycle0_table'): filename = resource_filename( 'astroquery.alma', 'data/cycle0_delivery_asdm_mapping.txt') self._cycle0_table =, format='ascii.no_header') self._cycle0_table.rename_column('col1', 'ID') self._cycle0_table.rename_column('col2', 'uid') return self._cycle0_table
[docs] def get_files_from_tarballs(self, downloaded_files, *, regex=r'.*\.fits$', path='cache_path', verbose=True): """ Given a list of successfully downloaded tarballs, extract files with names matching a specified regular expression. The default is to extract all FITS files NOTE: alma now supports direct listing and downloads of tarballs. See ``get_data_info`` and ``download_and_extract_files`` Parameters ---------- downloaded_files : list A list of downloaded files. These should be paths on your local machine. regex : str A valid regular expression path : 'cache_path' or str If 'cache_path', will use the astroquery.Alma cache directory (``Alma.cache_location``), otherwise will use the specified path. Note that the subdirectory structure of the tarball will be maintained. Returns ------- filelist : list A list of the extracted file locations on disk """ if path == 'cache_path': path = self.cache_location elif not os.path.isdir(path): raise OSError("Specified an invalid path {0}.".format(path)) fitsre = re.compile(regex) filelist = [] for fn in downloaded_files: tf = for member in tf.getmembers(): if fitsre.match( if verbose:"Extracting {0} to {1}".format(, path)) tf.extract(member, path) filelist.append(os.path.join(path, return filelist
[docs] def download_and_extract_files(self, urls, *, delete=True, regex=r'.*\.fits$', include_asdm=False, path='cache_path', verbose=True): """ Given a list of tarball URLs, it extracts all the FITS files (or whatever matches the regex) Parameters ---------- urls : str or list A single URL or a list of URLs include_asdm : bool Only affects cycle 1+ data. If set, the ASDM files will be downloaded in addition to the script and log files. By default, though, this file will be downloaded and deleted without extracting any information: you must change the regex if you want to extract data from an ASDM tarball """ if isinstance(urls, str): urls = [urls] if not isinstance(urls, (list, tuple, np.ndarray)): raise TypeError("Datasets must be given as a list of strings.") filere = re.compile(regex) all_files = [] tar_files = [] expanded_files = [] for url in urls: if url[-4:] != '.tar': raise ValueError("URLs should be links to tarballs.") tarfile_name = os.path.split(url)[-1] if tarfile_name in self._cycle0_tarfile_content['ID']: # It is a cycle 0 file: need to check if it contains FITS match = (self._cycle0_tarfile_content['ID'] == tarfile_name) if not any(re.match(regex, x) for x in self._cycle0_tarfile_content['Files'][match]):"No FITS files found in {0}".format(tarfile_name)) continue else: if 'asdm' in tarfile_name and not include_asdm:"ASDM tarballs do not contain FITS files; " "skipping.") continue tar_file = url.split('/')[-1] files = self.get_data_info(tar_file) if files: expanded_files += [x for x in files['access_url'] if filere.match(x.split('/')[-1])] else: tar_files.append(url) try: # get the tar files downloaded = self.download_files(tar_files, savedir=path) fitsfilelist = self.get_files_from_tarballs(downloaded, regex=regex, path=path, verbose=verbose) if delete: for tarball_name in downloaded:"Deleting {0}".format(tarball_name)) os.remove(tarball_name) all_files += fitsfilelist # download the other files all_files += self.download_files(expanded_files, savedir=path) except requests.ConnectionError as ex: self.partial_file_list = all_files log.error("There was an error downloading the file. " "A partially completed download list is " "in Alma.partial_file_list") raise ex except requests.HTTPError as ex: if ex.response.status_code == 401:"Access denied to {url}. Skipping to" " next file".format(url=url)) else: raise ex return all_files
[docs] def help(self, cache=True): """ Return the valid query parameters """ print("\nMost common ALMA query keywords are listed below. These " "keywords are part of the ALMA ObsCore model, an IVOA standard " "for metadata representation (3rd column). They were also " "present in original ALMA Web form and, for backwards " "compatibility can be accessed with their old names (2nd " "column).\n" "More elaborate queries on the ObsCore model " "are possible with `query_sia` or `query_tap` methods") print(" {0:33s} {1:35s} {2:35s}".format("Description", "Original ALMA keyword", "ObsCore keyword")) print("-"*103) for title, section in ALMA_FORM_KEYS.items(): print() print(title) for row in section.items(): print(" {0:33s} {1:35s} {2:35s}".format(row[0], row[1][0], row[1][1])) print('\nExamples of queries:') print("Alma.query('proposal_id':'2011.0.00131.S'}") print("Alma.query({'band_list': ['5', '7']}") print("Alma.query({'source_name_alma': 'GRB021004'})") print("Alma.query(payload=dict(project_code='2017.1.01355.L', " "source_name_alma='G008.67'))")
[docs] def get_project_metadata(self, projectid, *, cache=True): """ Get the metadata - specifically, the project abstract - for a given project ID. """ if len(projectid) != 14: raise AttributeError('Wrong length for project ID') if not projectid[4] == projectid[6] == projectid[12] == '.': raise AttributeError('Wrong format for project ID') result = self.query_tap( "select distinct proposal_abstract from " "ivoa.obscore where proposal_id='{}'".format(projectid)) if ASTROPY_LT_4_1: return [result[0]['proposal_abstract'].astype(str)] else: return [result[0]['proposal_abstract']]
Alma = AlmaClass() def clean_uid(uid): """ Return a uid with all unacceptable characters replaced with underscores """ if not hasattr(uid, 'replace'): return clean_uid(str(uid.astype('S'))) try: return uid.decode('utf-8').replace(u"/", u"_").replace(u":", u"_") except AttributeError: return uid.replace("/", "_").replace(":", "_") def reform_uid(uid): """ Convert a uid with underscores to the original format """ return uid[:3] + "://" + "/".join(uid[6:].split("_")) def unique(seq): """ Return unique elements of a list, preserving order """ seen = set() seen_add = seen.add return [x for x in seq if not (x in seen or seen_add(x))] def filter_printable(s): """ extract printable characters from a string """ return filter(lambda x: x in string.printable, s) def uid_json_to_table(jdata, productlist=['ASDM', 'PIPELINE_PRODUCT', 'PIPELINE_PRODUCT_TARFILE', 'PIPELINE_AUXILIARY_TARFILE']): rows = [] def flatten_jdata(this_jdata, mousID=None): if isinstance(this_jdata, list): for item in this_jdata: if item['type'] in productlist: item['mous_uid'] = mousID rows.append(item) elif len(item['children']) > 0: if len(item['allMousUids']) == 1: flatten_jdata(item['children'], item['allMousUids'][0]) else: flatten_jdata(item['children']) flatten_jdata(jdata['children']) keys = rows[-1].keys() columns = [Column(data=[row[key] for row in rows], name=key) for key in keys if key not in ('children', 'allMousUids')] columns = [col.astype(str) if == 'object' else col for col in columns] return Table(columns)