Source code for astroquery.jplspec.core

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

import astropy.units as u
from astropy.io import ascii
from ..query import BaseQuery
from ..utils import async_to_sync
# import configurable items declared in __init__.py
from . import conf
from . import lookup_table


__all__ = ['JPLSpec', 'JPLSpecClass']


def data_path(filename):
    data_dir = os.path.join(os.path.dirname(__file__), 'data')
    return os.path.join(data_dir, filename)


[docs]@async_to_sync class JPLSpecClass(BaseQuery): # use the Configuration Items imported from __init__.py URL = conf.server TIMEOUT = conf.timeout
[docs] def query_lines_async(self, min_frequency, max_frequency, min_strength=-500, max_lines=2000, molecule='All', flags=0, parse_name_locally=False, get_query_payload=False, cache=True): """ Creates an HTTP POST request based on the desired parameters and returns a response. Parameters ---------- min_frequency : `astropy.units` Minimum frequency (or any spectral() equivalent) max_frequency : `astropy.units` Maximum frequency (or any spectral() equivalent) min_strength : int, optional Minimum strength in catalog units, the default is -500 max_lines : int, optional Maximum number of lines to query, the default is 2000. The most the query allows is 100000 molecule : list, string of regex if parse_name_locally=True, optional Identifiers of the molecules to search for. If this parameter is not provided the search will match any species. Default is 'All'. flags : int, optional Regular expression flags. Default is set to 0 parse_name_locally : bool, optional When set to True it allows the method to parse through catdir.cat in order to match the regex inputted in the molecule parameter and request the corresponding tags of the matches instead. Default is set to False get_query_payload : bool, optional When set to `True` the method should return the HTTP request parameters as a dict. Default value is set to False Returns ------- response : `requests.Response` The HTTP response returned from the service. Examples -------- >>> table = JPLSpec.query_lines(min_frequency=100*u.GHz, ... max_frequency=200*u.GHz, ... min_strength=-500, molecule=18003) # doctest: +REMOTE_DATA >>> print(table) # doctest: +SKIP FREQ ERR LGINT DR ELO GUP TAG QNFMT QN' QN" ----------- ------ -------- --- --------- --- ------ ----- -------- -------- 115542.5692 0.6588 -13.2595 3 4606.1683 35 18003 1404 17 810 0 18 513 0 139614.293 0.15 -9.3636 3 3080.1788 87 -18003 1404 14 6 9 0 15 312 0 177317.068 0.15 -10.3413 3 3437.2774 31 -18003 1404 15 610 0 16 313 0 183310.087 0.001 -3.6463 3 136.1639 7 -18003 1404 3 1 3 0 2 2 0 0 """ # first initialize the dictionary of HTTP request parameters payload = dict() if min_frequency is not None and max_frequency is not None: # allow setting payload without having *ANY* valid frequencies set min_frequency = min_frequency.to(u.GHz, u.spectral()) max_frequency = max_frequency.to(u.GHz, u.spectral()) if min_frequency > max_frequency: min_frequency, max_frequency = max_frequency, min_frequency payload['MinNu'] = min_frequency.value payload['MaxNu'] = max_frequency.value if max_lines is not None: payload['MaxLines'] = max_lines payload['UnitNu'] = 'GHz' payload['StrLim'] = min_strength if molecule is not None: if parse_name_locally: self.lookup_ids = build_lookup() payload['Mol'] = tuple(self.lookup_ids.find(molecule, flags)) if len(molecule) == 0: raise ValueError('No matching species found. Please\ refine your search or read the Docs\ for pointers on how to search.') else: payload['Mol'] = molecule self.maxlines = max_lines payload = list(payload.items()) if get_query_payload: return payload # BaseQuery classes come with a _request method that includes a # built-in caching system response = self._request(method='POST', url=self.URL, data=payload, timeout=self.TIMEOUT, cache=cache) return response
def _parse_result(self, response, verbose=False): """ Parse a response into an `~astropy.table.Table` The catalog data files are composed of 80-character card images, with one card image per spectral line. The format of each card image is: FREQ, ERR, LGINT, DR, ELO, GUP, TAG, QNFMT, QN', QN" (F13.4,F8.4, F8.4, I2,F10.4, I3, I7, I4, 6I2, 6I2) FREQ: Frequency of the line in MHz. ERR: Estimated or experimental error of FREQ in MHz. LGINT: Base 10 logarithm of the integrated intensity in units of nm^2 MHz at 300 K. DR: Degrees of freedom in the rotational partition function (0 for atoms, 2 for linear molecules, and 3 for nonlinear molecules). ELO: Lower state energy in cm^{-1} relative to the ground state. GUP: Upper state degeneracy. TAG: Species tag or molecular identifier. A negative value flags that the line frequency has been measured in the laboratory. The absolute value of TAG is then the species tag and ERR is the reported experimental error. The three most significant digits of the species tag are coded as the mass number of the species. QNFMT: Identifies the format of the quantum numbers QN': Quantum numbers for the upper state. QN": Quantum numbers for the lower state. """ result = ascii.read(response.text, header_start=None, data_start=0, # start at 0 since regex was applied # Warning for a result with more than 1000 lines: # THIS form is currently limited to 1000 lines. comment=r'THIS|^\s{12,14}\d{4,6}.*', names=('FREQ', 'ERR', 'LGINT', 'DR', 'ELO', 'GUP', 'TAG', 'QNFMT', 'QN\'', 'QN"'), col_starts=(0, 13, 21, 29, 31, 41, 44, 51, 55, 67), format='fixed_width') if len(result) > self.maxlines: warnings.warn("This form is currently limited to {0} lines." "Please limit your search.".format(self.maxlines)) result['FREQ'].unit = u.MHz result['ERR'].unit = u.MHz result['LGINT'].unit = u.nm**2 * u.MHz result['ELO'].unit = u.cm**(-1) return result
[docs] def get_species_table(self, catfile='catdir.cat'): """ A directory of the catalog is found in a file called 'catdir.cat.' Each element of this directory is an 80-character record with the following format: | TAG, NAME, NLINE, QLOG, VER | (I6,X, A13, I6, 7F7.4, I2) Parameters ----------- catfile : str, name of file, default 'catdir.cat' The catalog file, installed locally along with the package Returns -------- Table: `~astropy.table.Table` | TAG : The species tag or molecular identifier. | NAME : An ASCII name for the species. | NLINE : The number of lines in the catalog. | QLOG : A seven-element vector containing the base 10 logarithm of the partition function for temperatures of 300 K, 225 K, 150 K, 75 K, 37.5 K, 18.75 K, and 9.375 K, respectively. | VER : The version of the calculation for this species in the catalog. The version number is followed by * if the entry is newer than the last edition of the catalog. """ result = ascii.read(data_path(catfile), header_start=None, data_start=0, names=('TAG', 'NAME', 'NLINE', 'QLOG1', 'QLOG2', 'QLOG3', 'QLOG4', 'QLOG5', 'QLOG6', 'QLOG7', 'VER'), col_starts=(0, 6, 20, 26, 33, 40, 47, 54, 61, 68, 75), format='fixed_width') # store the corresponding temperatures as metadata result['QLOG1'].meta = {'Temperature (K)': 300} result['QLOG2'].meta = {'Temperature (K)': 225} result['QLOG3'].meta = {'Temperature (K)': 150} result['QLOG4'].meta = {'Temperature (K)': 75} result['QLOG5'].meta = {'Temperature (K)': 37.5} result['QLOG6'].meta = {'Temperature (K)': 18.75} result['QLOG7'].meta = {'Temperature (K)': 9.375} result.meta = {'Temperature (K)': [300, 225, 150, 75, 37.5, 18.5, 9.375]} return result
JPLSpec = JPLSpecClass() def build_lookup(): result = JPLSpec.get_species_table() keys = list(result[1][:]) # convert NAME column to list values = list(result[0][:]) # convert TAG column to list dictionary = dict(zip(keys, values)) # make k,v dictionary lookuptable = lookup_table.Lookuptable(dictionary) # apply the class above return lookuptable