Source code for astwro.pydaophot.Allstar

from __future__ import absolute_import, division, print_function
__metaclass__ = type
# see https://wiki.python.org/moin/PortingToPy3k/BilingualQuickRef
from .DAORunner import DAORunner
from .OutputProviders import *
from astwro.config import find_opt_file
import astwro.starlist


[docs]class Allstar(DAORunner): """ `daophot` runner Object of this class maintains single process of `allstar` and it's working directory. Instance attributes: :var str allstaropt: allstar.opt file to be copied into runner dir :var DPOP_OPtion OPtion_result: initial options reported by `allstar` :var DPOP_ATtach ATtach_result: results of command ATtach :var str image: image which will be automatically used if not provided in `ALlstars` command :var dict options: options which will be automatically set as OPTION command before every run, can be either: dictionary: >>> dp = Allstar() >>> dp.options = {'PROFILE ERROR': 5, 'FI': '6.0'} iterable of tuples: >>> dp.options = [('PR', 5.0), ('FITTING RADIUS', 6.0)] """ def __init__(self, dir=None, image=None, allstaropt=None, options=None, batch=False): # type: ([str,object], [str], [str], [list,dict], bool) -> Allstar """ :param [str] dir: pathname or TmpDir object - working directory for daophot, if None temp dir will be used and deleted on `Allstar.close()` :param [str] image: if provided this file will be used if not provided in `ALlstars` command setting image property has same effect :param [str] allstaropt: allstar.opt file, if None build in default file will be used, can be added later by `Runner.copy_to_runner_dir(file, 'allstar.opt')` :param [list,dict] options: if provided options will be set on beginning of each process list of tuples or dict :param bool batch: whether Allstar have to work in batch mode. """ if allstaropt is not None: self.allstaropt = allstaropt else: self.allstaropt = find_opt_file('allstar.opt', package='pydaophot') self.image = self.expand_path(image) self.options = {'WA': 0} # suppress animations if options: self.options.update(dict(options)) super(Allstar, self).__init__(dir=dir, batch=batch) # base implementation of __init__ calls `_reset` also self._update_executable('allstar') def _reset(self): super(Allstar, self)._reset() self.OPtion_result = None self.ALlstars_result = None def __deepcopy__(self, memo): from copy import deepcopy new = super(Allstar, self).__deepcopy__(memo) new.allstaropt = deepcopy(self.allstaropt, memo) # new.OPtion_result = deepcopy(self.OPtion_result, memo) # new.ALlstars_result = deepcopy(self.ALlstars_result, memo) new.image = deepcopy(self.image, memo) new.options = deepcopy(self.options, memo) return new def _pre_run(self, wait): if not self.ALlstars_result: raise Allstar.RunnerException('Add ALlstar command before run.', self) super(Allstar, self)._pre_run(wait) # set options, and prepare options parser commands = '' if self.options: # set options before options = self.options if isinstance(options, dict): options = options.items() # options is dict # else options is list of pairs commands += ''.join('%s=%.2f\n' % (k, float(v)) for k, v in options if v is not None) commands += '\n' processor = AsOp_opt() self.OPtion_result = processor self._insert_processing_step(commands, output_processor=processor, on_beginning=True) def _init_workdir_files(self, dir): super(Allstar, self)._init_workdir_files(dir) self.link_to_runner_dir(self.allstaropt, 'allstar.opt')
[docs] def set_options(self, options, value=None): # type: ([str,dict,list], [str,float]) -> None """set option(s) before run. Options can be either: dictionary: `dp.OPtion({'GAIN': 9, 'FI': '6.0'})` iterable of tuples: `dp.OPtion([('GA', 9.0), ('FITTING RADIUS', '6.0')])` option key, followed by value in 'value' parameter: `dp.OPtion('GA', 9.0)` filename string of allstar.opt-formatted file (file will be symlinked as `allstar.opt`): `dp.OPtion('opts/newallstar.opt')` Once set, options will stay set in next runs, set option to `None` to unset """ if isinstance(options, str) and value is None: # filename # allstar operates in his tmp dir and has limited buffer for file path # so symlink file to its working dir self.link_to_runner_dir(options, 'allstar.opt') else: if self.options is None: self.options = {} if value is not None: # single value options = {options:value} elif isinstance(options, list): options = dict(options) self.options.update(options)
[docs] def ALlstar(self, image_file=None, psf_file='i.psf', stars='i.ap', profile_photometry_file='i.als', subtracted_image_file=None): # type: ([str], str, [str,object], str, str) -> AsOp_result """ Runs (or adds to execution queue in batch mode) daophot PICK command. :param [str] image_file: input image filepath, if None, one set in constructor or 'i.fits' will be used :param str psf_file: input file with psf from daophot PSF command :param str stars: input magnitudes file, e.g. from aperture photometry done by :func:`Daophot.PHotometry`. :param str profile_photometry_file: output file with aperture photometry results, default: i.als :param str subtracted_image_file: output file with subtracted FITS image, default: do not generate image :return: results object also accessible as :var:`Allstar.ALlstars_result` property :rtype: AsOp_result """ self._get_ready_for_commands() # wait for completion before changes in working dir if not image_file: image_file = self.image if not image_file: image_file = 'i.fits' l_img, a_img = self._prepare_input_file(image_file) l_psf, a_psf = self._prepare_input_file(psf_file) l_pht, a_pht = self._prepare_input_file(stars, astwro.starlist.DAO.XY_FILE) l_als, a_als = self._prepare_output_file(profile_photometry_file) l_sub, a_sub = self._prepare_output_file(subtracted_image_file) commands = '{}\n{}\n{}\n{}\n{}'.format(l_img, l_psf, l_pht, l_als, l_sub) if l_sub: commands += '\n' # if subtracted image not needed, EOF (without new line) should be answer for it (allstar) processor = AsOp_result(profile_photometry_file=a_als, subtracted_image_file=a_sub) self._insert_processing_step(commands, output_processor=processor) self.ALlstars_result = processor if not self.batch_mode: self.run() return processor