#
# See top-level LICENSE.rst file for Copyright information
#
# -*- coding: utf-8 -*-
"""
desispec.pipeline.tasks.psf
===========================
"""
from __future__ import absolute_import, division, print_function
from collections import OrderedDict
from ..defs import (task_name_sep, task_state_to_int, task_int_to_state)
from ...util import option_list
from ...io import findfile
from .base import (BaseTask, task_classes)
from desiutil.log import get_logger
import sys,re,os
# NOTE: only one class in this file should have a name that starts with "Task".
[docs]class TaskPSF(BaseTask):
"""Class containing the properties of one PSF task.
"""
def __init__(self):
super(TaskPSF, self).__init__()
# then put int the specifics of this class
# _cols must have a state
self._type = "psf"
self._cols = [
"night",
"band",
"spec",
"expid",
"state"
]
self._coltypes = [
"integer",
"text",
"integer",
"integer",
"integer"
]
# _name_fields must also be in _cols
self._name_fields = ["night","band","spec","expid"]
self._name_formats = ["08d","s","d","08d"]
[docs] def _paths(self, name):
"""See BaseTask.paths.
"""
props = self.name_split(name)
camera = "{}{}".format(props["band"], props["spec"])
return [ findfile("psf", night=props["night"], expid=props["expid"],
camera=camera, groupname=None, nside=None, band=props["band"],
spectrograph=props["spec"]) ]
[docs] def _deps(self, name, db, inputs):
"""See BaseTask.deps.
"""
from .base import task_classes
props = self.name_split(name)
deptasks = {
"input-image" : task_classes["preproc"].name_join(props)
}
return deptasks
def _run_max_procs(self):
# 20 bundles per camera
return 20
def _run_time(self, name, procs, db):
# Time when running on max procs on machine with scale
# factor 1.0
mprc = self._run_max_procs()
return (20.0 / procs) * mprc
[docs] def _run_defaults(self):
"""See BaseTask.run_defaults.
"""
opts = {}
opts["trace-deg-wave"] = 7
opts["trace-deg-x"] = 7
opts["trace-prior-deg"] = 4
envname="DESI_SPECTRO_CALIB"
if not envname in os.environ :
raise KeyError("need to set DESI_SPECTRO_CALIB env. variable")
return opts
[docs] def _option_list(self, name, opts):
"""Build the full list of options.
This includes appending the filenames and incorporating runtime
options.
"""
from .base import task_classes, task_type
options = OrderedDict()
deps = self.deps(name)
props = self.name_split(name)
# make a copy, so we can remove some entries
opts_copy = opts.copy()
options["input-image"] = task_classes["preproc"].paths(deps["input-image"])[0]
options["output-psf"] = self.paths(name)
if "specmin" in opts_copy:
options["specmin"] = opts_copy["specmin"]
del opts_copy["specmin"]
if "nspec" in opts_copy:
options["nspec"] = opts_copy["nspec"]
del opts_copy["nspec"]
if len(opts_copy) > 0:
extarray = option_list(opts_copy)
options["extra"] = " ".join(extarray)
return option_list(options)
[docs] def _run_cli(self, name, opts, procs, db):
"""See BaseTask.run_cli.
"""
entry = "desi_compute_psf"
if procs > 1:
entry = "desi_compute_psf_mpi"
return "{} {}".format(entry, " ".join(self._option_list(name, opts)))
[docs] def _run(self, name, opts, comm, db):
"""See BaseTask.run.
"""
from ...scripts import specex
optlist = self._option_list(name, opts)
args = specex.parse(optlist)
specex.main(args, comm=comm)
return
[docs] def postprocessing(self, db, name, cur):
"""For successful runs, postprocessing on DB"""
# run getready on all psfnight with same night,band,spec
props = self.name_split(name)
log = get_logger()
tt="psfnight"
cmd = "select name from {} where night={} and band='{}' and spec={} and state=0".format(tt,props["night"],props["band"],props["spec"])
cur.execute(cmd)
tasks = [ x for (x,) in cur.fetchall() ]
log.debug("checking {}".format(tasks))
for task in tasks :
task_classes[tt].getready( db=db,name=task,cur=cur)