Source code for astroquery.sha.core

# Licensed under a 3-clause BSD style license - see LICENSE.rst
import re
import os
import io
import requests
import numpy as np
from astropy.table import Table
import astropy.io.fits as fits


__all__ = ['query', 'save_file', 'get_file']
id_parse = re.compile(r'ID\=(\d+)')

# should skip only if remote_data = False
__doctest_skip__ = ['query', 'save_file', 'get_file']

uri = 'http://sha.ipac.caltech.edu/applications/Spitzer/SHA/servlet/DataService?'


[docs]def query(coord=None, ra=None, dec=None, size=None, naifid=None, pid=None, reqkey=None, dataset=2, verbosity=3, return_response=False, return_payload=False): """ Query the Spitzer Heritage Archive (SHA). Four query types are valid to search by position, NAIFID, PID, and ReqKey:: position -> search a region naifid -> NAIF ID, which is a unique number allocated to solar system objects (e.g. planets, asteroids, comets, spacecraft) by the NAIF at JPL. pid -> program ID reqkey -> AOR ID: Astronomical Observation Request ID For a valid query, enter only parameters related to a single query type:: position -> ra, dec, size naifid -> naifid pid -> pid reqkey -> reqkey Parameters ---------- coord : astropy.coordinates.builtin_systems Astropy coordinate object. (query_type = 'position') ra : number Right ascension in degrees, alternative to using ``coord``. (query_type = 'position') dec : number Declination in degrees, alternative to using ``coord``. (query_type = 'position') size : number Region size in degrees. (query_type = 'position') naifid : number NAIF ID. (query_type = 'naifid') pid : number Program ID. (query_type = 'pid') reqkey : number Astronomical Observation Request ID. (query_type = 'reqkey') dataset : number, default 2 Data set. Valid options:: 1 -> BCD data 2 -> PBCD data verbosity : number, default 3 Verbosity level, controls the number of columns to output. Returns ------- table : `~astropy.table.Table` Examples -------- Position query using an astropy coordinate object >>> import astropy.coordinates as coord >>> import astropy.units as u >>> from astroquery import sha >>> pos_t = sha.query(coord=coord.SkyCoord(ra=163.6136, dec=-11.784, ... unit=(u.degree, u.degree)), size=0.5) Position query with optional ``ra`` and ``dec`` parameters >>> pos_t = sha.query(ra=163.6136, dec=-11.784, size=0.5) NAIFID query >>> nid_t = sha.query(naifid=2003226) PID query >>> pid_t = sha.query(pid=30080) ReqKey query >>> rqk_t = sha.query(reqkey=21641216) Notes ----- For column descriptions, metadata, and other information visit the SHA query API_ help page .. _API: http://sha.ipac.caltech.edu/applications/Spitzer/SHA/help/doc/api.html """ # Use Coordinate instance if supplied if coord is not None: try: ra = coord.transform_to('fk5').ra.degree dec = coord.transform_to('fk5').dec.degree except ValueError: raise ValueError('Cannot parse `coord` variable.') # Query parameters payload = {'RA': ra, 'DEC': dec, 'SIZE': size, 'NAIFID': naifid, 'PID': pid, 'REQKEY': reqkey, 'VERB': verbosity, 'DATASET': 'ivo://irsa.ipac.spitzer.level{0}'.format(dataset)} if return_payload: return payload # Make request response = requests.get(uri, params=payload) if return_response: return response response.raise_for_status() # Parse output # requests returns unicode strings, encode back to ascii # because of '|foo|bar|' delimiters, remove first and last empty columns raw_data = [line for line in response.text.split('\n')] field_widths = [len(s) + 1 for s in raw_data[1].split('|')][1:-1] col_names = [s.strip() for s in raw_data[1].split('|')][1:-1] type_names = [s.strip() for s in raw_data[2].split('|')][1:-1] cs = [0] + np.cumsum(field_widths).tolist() def parse_line(line, cs=cs): return [line[a:b] for a, b in zip(cs[:-1], cs[1:])] data = [parse_line(row) for row in raw_data[4:-1]] # Parse type names dtypes = _map_dtypes(type_names, field_widths) # To table # transpose data for appropriate table instance handling t = Table(list(zip(*data)), names=col_names, dtype=dtypes) return t
[docs]def save_file(url, out_dir='sha_tmp/', out_name=None): """ Download image to output directory given a URL from a SHA query. Parameters ---------- url : str Access URL from SHA query. Requires complete URL, valid URLs from the SHA query include columns:: accessUrl -> The URL to be used to retrieve an image or table withAnc1 -> The URL to be used to retrieve the image or spectra with important ancillary products (mask, uncertainty, etc.) as a zip archive out_dir : str Path for output table or image out_name : str Name for output table or image, if None use the file ID as name. Examples -------- >>> from astroquery import sha >>> url = sha.query(pid=30080)['accessUrl'][0] >>> sha.save_file(url) """ exten_types = {'image/fits': '.fits', 'text/plain; charset=UTF-8': '.tbl', 'application/zip': '.zip', } # Make request response = requests.get(url, stream=True) response.raise_for_status() # Name file using ID at end if out_name is None: out_name = 'shaID_' + id_parse.findall(url)[0] # Determine extension exten = exten_types[response.headers['Content-Type']] # Check if path exists if not os.path.exists(out_dir): os.makedirs(out_dir) # Write file with open(out_dir + out_name + exten, 'wb') as f: for block in response.iter_content(1024): f.write(block)
[docs]def get_file(url): """ Return object from SHA query URL. Currently only supports FITS files. Parameters ---------- url : str Access URL from SHA query. Requires complete URL, valid URLs from the SHA query include columns:: accessUrl -> The URL to be used to retrieve an image or table withAnc1 -> The URL to be used to retrieve the image or spectra with important ancillary products (mask, uncertainty, etc.) as a zip archive Returns ------- obj : `~astropy.table.Table`, `astropy.io.fits`, list Return object depending if link points to a table, fits image, or zip file of products. Examples -------- >>> from astroquery import sha >>> url = sha.query(pid=30080)['accessUrl'][0] >>> img = sha.get_file(url) """ # Make request response = requests.get(url, stream=True) response.raise_for_status() # Read fits iofile = io.BytesIO(response.content) content_type = response.headers['Content-Type'] if content_type == 'image/fits': obj = fits.open(iofile) else: raise Exception('Unknown content type: {0}.'.format(content_type)) return obj
def _map_dtypes(type_names, field_widths): """ Create dtype string based on column lengths and field type names. Parameters ---------- type_names : list List of type names from file header field_widths : list List of field width values Returns ------- dtypes : list List of dtype for each column in data """ dtypes = [] for i, name in enumerate(type_names): if name == 'int': dtypes.append('i8') elif name == 'double': dtypes.append('f8') elif name == 'char': dtypes.append('a{0}'.format(field_widths[i])) else: raise ValueError('Unexpected type name: {0}.'.format(name)) return dtypes