def test_ensemble_returned_values():
""" Check that the ensemble returns values that are reasonable and within expected bounds """
tm = corrections.TaskManager(INPUT_DIR)
task = tm.get_task(starid=starid, camera=camera, ccd=ccd)
#Initiate the class
CorrClass = corrections.corrclass('ensemble')
corr = CorrClass(INPUT_DIR, plot=False)
inlc = corr.load_lightcurve(task)
outlc, status = corr.do_correction(inlc.copy())
# Check input validation
#with pytest.raises(ValueError) as err:
# outlc, status = corr.do_correction('hello world')
# assert('The input to `do_correction` is not a TessLightCurve object!' in err.value.args[0])
#C heck contents
assert len(outlc.flux) == len(
inlc.flux), "Input flux ix different length to output flux"
assert all(
inlc.time == outlc.time), "Input time is nonidentical to output time"
assert all(outlc.flux != inlc.flux), "Input and output flux are identical."
assert len(outlc.flux) == len(
outlc.time), "Check time and flux have same length"
# Check status
assert status == corrections.STATUS.OK, "STATUS was not set appropriately"
def test_corrclass_type():
"""Check that tesscorr.py returns the correct class"""
CorrClass = corrclass()
assert repr(CorrClass) == "<class 'corrections.ensemble.EnsembleCorrector'>"
CorrClass = corrclass('ensemble')
assert repr(CorrClass) == "<class 'corrections.ensemble.EnsembleCorrector'>"
CorrClass = corrclass('cbv')
assert repr(CorrClass) == "<class 'corrections.cbv_corrector.CBVCorrector.CBVCorrector'>"
CorrClass = corrclass('kasoc_filter')
assert repr(CorrClass) == "<class 'corrections.KASOCFilterCorrector.KASOCFilterCorrector'>"
with pytest.raises(ValueError) as err:
method = 'not-a-method'
CorrClass = corrclass('method')
assert err.value.args[0] == "Invalid method: '{0}'".format(method)
def test_corrclass_type():
"""Check that tesscorr.py returns the correct class"""
CorrClass = corrections.corrclass()
print(CorrClass)
assert CorrClass is corrections.EnsembleCorrector
CorrClass = corrections.corrclass('ensemble')
print(CorrClass)
assert CorrClass is corrections.EnsembleCorrector
CorrClass = corrections.corrclass('cbv')
print(CorrClass)
assert CorrClass is corrections.CBVCorrector
CorrClass = corrections.corrclass('kasoc_filter')
print(CorrClass)
assert CorrClass is corrections.KASOCFilterCorrector
method = 'not-a-method'
with pytest.raises(ValueError) as err:
CorrClass = corrections.corrclass(method)
assert err.value.args[0] == "Invalid method: '{0}'".format(method)
def test_run_metadata():
""" Check that the ensemble returns values that are reasonable and within expected bounds """
tm = corrections.TaskManager(INPUT_DIR)
task = tm.get_task(starid=starid, camera=camera, ccd=ccd)
#Initiate the class
CorrClass = corrections.corrclass('ensemble')
corr = CorrClass(INPUT_DIR, plot=False)
inlc = corr.load_lightcurve(task)
outlc, status = corr.do_correction(inlc.copy())
# Check metadata
#assert 'fmean' in outlc.meta, "Metadata is incomplete"
#assert 'fstd' in outlc.meta, "Metadata is incomplete"
#assert 'frange' in outlc.meta, "Metadata is incomplete"
#assert 'drange' in outlc.meta, "Metadata is incomplete"
assert outlc.meta['task']['starid'] == inlc.meta['task'][
'starid'], "Metadata is incomplete"
assert outlc.meta['task'] == inlc.meta['task'], "Metadata is incomplete"
def test_known_star(SHARED_INPUT_DIR, corrector, starid, cadence, var_goal, rms_goal, ptp_goal):
""" Check that the ensemble returns values that are reasonable and within expected bounds """
# All stars we check here come from the same sector and camera.
# Define these here for the future where we may test on other combinations of these:
sector = 1
camera = 1
__dir__ = os.path.abspath(os.path.dirname(__file__))
logger = logging.getLogger(__name__)
logger.info("-------------------------------------------------------------")
logger.info("CORRECTOR = %s, SECTOR=%d, CADENCE=%s, STARID=%d", corrector, sector, cadence, starid)
# All stars are from the same CCD, find the task for it:
with corrections.TaskManager(SHARED_INPUT_DIR) as tm:
task = tm.get_task(starid=starid, sector=sector, camera=camera, cadence=cadence)
# Check that task was actually found:
assert task is not None, "Task could not be found"
# Load lightcurve that will also be plotted together with the result:
# This lightcurve is of the same objects, at a state where it was deemed that the
# corrections were doing a good job.
compare_lc_path = os.path.join(__dir__, 'compare', f'compare-{corrector}-s{sector:04d}-c{cadence:04d}-tic{starid:011d}.ecsv.gz')
compare_lc = None
if os.path.isfile(compare_lc_path):
compare_lc = Table.read(compare_lc_path, format='ascii.ecsv')
else:
warnings.warn("Comparison data does not exist: " + compare_lc_path)
# Initiate the class
CorrClass = corrections.corrclass(corrector)
with tempfile.TemporaryDirectory() as tmpdir:
with CorrClass(SHARED_INPUT_DIR, plot=True) as corr:
# Check basic parameters of object (from BaseCorrector):
assert corr.input_folder == SHARED_INPUT_DIR, "Incorrect input folder"
assert corr.plot, "Plot parameter passed appropriately"
assert os.path.isdir(corr.data_folder), "DATA_FOLDER doesn't exist"
# Load the input lightcurve:
inlc = corr.load_lightcurve(task)
# Print input lightcurve properties:
print( inlc.show_properties() )
assert inlc.sector == sector
assert inlc.camera == camera
# Run correction:
tmplc = inlc.copy()
outlc, status = corr.do_correction(tmplc)
# Check status
assert outlc is not None, "Correction fails"
assert isinstance(outlc, TessLightCurve), "Should return TessLightCurve object"
assert isinstance(status, corrections.STATUS), "Should return a STATUS object"
assert status in (corrections.STATUS.OK, corrections.STATUS.WARNING), "STATUS was not set appropriately"
# Print output lightcurve properties:
print( outlc.show_properties() )
# Save the lightcurve to FITS file to be tested later on:
save_file = corr.save_lightcurve(outlc, output_folder=tmpdir)
# Check contents
assert len(outlc) == len(inlc), "Input flux ix different length to output flux"
assert isinstance(outlc.flux, np.ndarray), "FLUX is not a ndarray"
assert isinstance(outlc.flux_err, np.ndarray), "FLUX_ERR is not a ndarray"
assert isinstance(outlc.quality, np.ndarray), "QUALITY is not a ndarray"
assert outlc.flux.dtype.type is inlc.flux.dtype.type, "FLUX changes dtype"
assert outlc.flux_err.dtype.type is inlc.flux_err.dtype.type, "FLUX_ERR changes dtype"
assert outlc.quality.dtype.type is inlc.quality.dtype.type, "QUALITY changes dtype"
assert outlc.flux.shape == inlc.flux.shape, "FLUX changes shape"
assert outlc.flux_err.shape == inlc.flux_err.shape, "FLUX_ERR changes shape"
assert outlc.quality.shape == inlc.quality.shape, "QUALITY changes shape"
# Plot output lightcurves:
fig, (ax1, ax2, ax3) = plt.subplots(3, 1, squeeze=True, figsize=[10, 10])
ax1.plot(inlc.time, inlc.flux, lw=0.5)
ax1.set_title(f"{corrector} - Sector {sector:d} - {cadence}s - TIC {starid:d}")
if compare_lc:
ax2.plot(compare_lc['time'], compare_lc['flux'], label='Compare', lw=0.5)
ax3.axhline(0, lw=0.5, ls=':', color='0.7')
ax3.plot(outlc.time, outlc.flux - compare_lc['flux'], lw=0.5)
ax2.plot(outlc.time, outlc.flux, label='New', lw=0.5)
ax1.set_ylabel('Flux [e/s]')
ax1.minorticks_on()
ax2.set_ylabel('Relative Flux [ppm]')
ax2.minorticks_on()
ax2.legend()
ax3.set_ylabel('New - Compare [ppm]')
ax3.set_xlabel('Time [TBJD]')
ax3.minorticks_on()
fig.savefig(os.path.join(__dir__, f'test-{corrector}-s{sector:04d}-c{cadence:04d}-tic{starid:011d}.png'), bbox_inches='tight')
plt.close(fig)
# Check things that are allowed to change:
assert all(outlc.flux != inlc.flux), "Input and output flux are identical."
assert not np.any(np.isinf(outlc.flux)), "FLUX contains Infinite"
assert not np.any(np.isinf(outlc.flux_err)), "FLUX_ERR contains Infinite"
assert np.sum(np.isnan(outlc.flux)) < 0.5*len(outlc), "More than half the lightcurve is NaN"
assert allnan(outlc.flux_err[np.isnan(outlc.flux)]), "FLUX_ERR should be NaN where FLUX is"
# TODO: Check that quality hasn't changed in ways that are not allowed:
# - Only values defined in CorrectorQualityFlags
# - No removal of flags already set
assert all(outlc.quality >= 0)
assert all(outlc.quality <= 128)
assert all(outlc.quality >= inlc.quality)
# Things that shouldn't chance from the corrections:
assert outlc.targetid == inlc.targetid, "TARGETID has changed"
assert outlc.label == inlc.label, "LABEL has changed"
assert outlc.sector == inlc.sector, "SECTOR has changed"
assert outlc.camera == inlc.camera, "CAMERA has changed"
assert outlc.ccd == inlc.ccd, "CCD has changed"
assert outlc.quality_bitmask == inlc.quality_bitmask, "QUALITY_BITMASK has changed"
assert outlc.ra == inlc.ra, "RA has changed"
assert outlc.dec == inlc.dec, "DEC has changed"
assert outlc.mission == 'TESS', "MISSION has changed"
assert outlc.time_format == 'btjd', "TIME_FORMAT has changed"
assert outlc.time_scale == 'tdb', "TIME_SCALE has changed"
assert_array_equal(outlc.time, inlc.time, "TIME has changed")
assert_array_equal(outlc.timecorr, inlc.timecorr, "TIMECORR has changed")
assert_array_equal(outlc.cadenceno, inlc.cadenceno, "CADENCENO has changed")
assert_array_equal(outlc.pixel_quality, inlc.pixel_quality, "PIXEL_QUALITY has changed")
assert_array_equal(outlc.centroid_col, inlc.centroid_col, "CENTROID_COL has changed")
assert_array_equal(outlc.centroid_row, inlc.centroid_row, "CENTROID_ROW has changed")
# Check metadata
assert tmplc.meta == inlc.meta, "Correction changed METADATA in-place"
assert outlc.meta['task'] == inlc.meta['task'], "Metadata is incomplete"
assert isinstance(outlc.meta['additional_headers'], fits.Header)
# Check performance metrics:
#logger.warning("VAR: %e", nanvar(outlc.flux))
if var_goal is not None:
var_in = nanvar(inlc.flux)
var_out = nanvar(outlc.flux)
var_diff = np.abs(var_out - var_goal) / var_goal
logger.info("VAR: %f - %f - %f", var_in, var_out, var_diff)
assert_array_less(var_diff, 0.05, "VARIANCE changed outside interval")
#logger.warning("RMS: %e", rms_timescale(outlc))
if rms_goal is not None:
rms_in = rms_timescale(inlc)
rms_out = rms_timescale(outlc)
rms_diff = np.abs(rms_out - rms_goal) / rms_goal
logger.info("RMS: %f - %f - %f", rms_in, rms_out, rms_diff)
assert_array_less(rms_diff, 0.05, "RMS changed outside interval")
#logger.warning("PTP: %e", ptp(outlc))
if ptp_goal is not None:
ptp_in = ptp(inlc)
ptp_out = ptp(outlc)
ptp_diff = np.abs(ptp_out - ptp_goal) / ptp_goal
logger.info("PTP: %f - %f - %f", ptp_in, ptp_out, ptp_diff)
assert_array_less(ptp_diff, 0.05, "PTP changed outside interval")
# Check FITS file:
with fits.open(os.path.join(tmpdir, save_file), mode='readonly') as hdu:
# Lightcurve FITS table:
fitslc = hdu['LIGHTCURVE'].data
hdr = hdu['LIGHTCURVE'].header
# Simple checks of header values:
assert hdu[0].header['TICID'] == starid
# Checks of things in FITS table that should not have changed at all:
assert_array_equal(fitslc['TIME'], inlc.time, "FITS: TIME has changed")
assert_array_equal(fitslc['TIMECORR'], inlc.timecorr, "FITS: TIMECORR has changed")
assert_array_equal(fitslc['CADENCENO'], inlc.cadenceno, "FITS: CADENCENO has changed")
assert_array_equal(fitslc['FLUX_RAW'], inlc.flux, "FITS: FLUX_RAW has changed")
assert_array_equal(fitslc['FLUX_RAW_ERR'], inlc.flux_err, "FITS: FLUX_RAW_ERR has changed")
assert_array_equal(fitslc['MOM_CENTR1'], inlc.centroid_col, "FITS: CENTROID_COL has changed")
assert_array_equal(fitslc['MOM_CENTR2'], inlc.centroid_row, "FITS: CENTROID_ROW has changed")
# Some things are allowed to change, but still within some requirements:
assert all(fitslc['FLUX_CORR'] != inlc.flux), "FITS: Input and output flux are identical."
assert np.sum(np.isnan(fitslc['FLUX_CORR'])) < 0.5*len(fitslc['TIME']), "FITS: More than half the lightcurve is NaN"
assert allnan(fitslc['FLUX_CORR_ERR'][np.isnan(fitslc['FLUX_CORR'])]), "FITS: FLUX_ERR should be NaN where FLUX is"
if corrector == 'ensemble':
# Check special headers:
assert np.isfinite(hdr['ENS_MED']) and hdr['ENS_MED'] > 0
assert isinstance(hdr['ENS_NUM'], int) and hdr['ENS_NUM'] > 0
assert hdr['ENS_DLIM'] == 1.0
assert hdr['ENS_DREL'] == 10.0
assert hdr['ENS_RLIM'] == 0.4
# Special extension for ensemble:
tic = hdu['ENSEMBLE'].data['TIC']
bzeta = hdu['ENSEMBLE'].data['BZETA']
assert len(tic) == len(bzeta)
assert len(np.unique(tic)) == len(tic), "TIC numbers in ENSEMBLE table are not unique"
assert len(tic) == hdr['ENS_NUM'], "Not the same number of targets in ENSEMBLE table as specified in header"
elif corrector == 'cbv':
# Check special headers:
assert isinstance(hdr['CBV_NUM'], int) and hdr['CBV_NUM'] > 0
# Check coefficients:
for k in range(0, hdr['CBV_NUM']+1):
assert np.isfinite(hdr['CBV_C%d' % k])
for k in range(1, hdr['CBV_NUM']+1):
assert np.isfinite(hdr['CBVS_C%d' % k])
# Check that no other coefficients are present
assert 'CBV_C%d' % (hdr['CBV_NUM']+1) not in hdr
assert 'CBVS_C%d' % (hdr['CBV_NUM']+1) not in hdr
elif corrector == 'kasoc_filter':
# Check special headers:
assert hdr['KF_POSS'] == 'None'
assert np.isfinite(hdr['KF_LONG']) and hdr['KF_LONG'] > 0
assert np.isfinite(hdr['KF_SHORT']) and hdr['KF_SHORT'] > 0
assert hdr['KF_SCLIP'] == 4.5
assert hdr['KF_TCLIP'] == 5.0
assert hdr['KF_TWDTH'] == 1.0
assert hdr['KF_PSMTH'] == 200
assert isinstance(hdr['NUM_PER'], int) and hdr['NUM_PER'] >= 0
for k in range(1, hdr['NUM_PER']+1):
assert np.isfinite(hdr['PER_%d' % k]) and hdr['PER_%d' % k] > 0
# Check that no other periods are present
assert 'PER_%d' % (hdr['NUM_PER'] + 1) not in hdr
# Test that the Gzip FITS file has the correct uncompressed file name, by simply
# decompressing the Gzip file, asking to keep the original file name.
# This uses the system GZIP utility, since there doesn't seem to be a way to do this
# through the Python gzip module:
fpath = os.path.join(tmpdir, save_file)
fpath_uncompressed = fpath.replace('.fits.gz', '.fits')
assert not os.path.exists(fpath_uncompressed), "Uncompressed file already exists"
gzip_output = subprocess.check_output(['gzip', '-dkNv', os.path.basename(fpath)],
cwd=os.path.dirname(fpath),
stderr=subprocess.STDOUT,
encoding='utf8')
print("Gzip output:")
print(gzip_output)
assert os.path.isfile(fpath_uncompressed), "Incorrect uncompressed file name"
# Just see if we can in fact also open the uncompressed FITS file and get a simple header:
with fits.open(fpath_uncompressed, mode='readonly') as hdu:
assert hdu[0].header['TICID'] == starid
def main():
# Parse command line arguments:
parser = argparse.ArgumentParser(
description='Run TESS Corrections in parallel using MPI.')
#parser.add_argument('-d', '--debug', help='Print debug messages.', action='store_true')
#parser.add_argument('-q', '--quiet', help='Only report warnings and errors.', action='store_true')
parser.add_argument('-m',
'--method',
help='Corrector method to use.',
default=None,
choices=('ensemble', 'cbv', 'kasoc_filter'))
parser.add_argument('-o',
'--overwrite',
help='Overwrite existing results.',
action='store_true')
parser.add_argument('-p',
'--plot',
help='Save plots when running.',
action='store_true')
parser.add_argument('--camera',
type=int,
choices=(1, 2, 3, 4),
default=None,
help='TESS Camera. Default is to run all cameras.')
parser.add_argument('--ccd',
type=int,
choices=(1, 2, 3, 4),
default=None,
help='TESS CCD. Default is to run all CCDs.')
parser.add_argument('--datasource',
type=str,
choices=('ffi', 'tpf'),
default='ffi',
help='Data source or cadence.')
parser.add_argument(
'input_folder',
type=str,
help=
'Input directory. This directory should contain a TODO-file and corresponding lightcurves.',
nargs='?',
default=None)
args = parser.parse_args()
# Get input and output folder from environment variables:
input_folder = args.input_folder
if input_folder is None:
input_folder = os.environ.get('TESSCORR_INPUT')
if not input_folder:
parser.error("Please specify an INPUT_FOLDER.")
output_folder = os.environ.get('TESSCORR_OUTPUT',
os.path.join(input_folder, 'lightcurves'))
# Define MPI message tags
tags = enum.IntEnum('tags', ('READY', 'DONE', 'EXIT', 'START'))
# Initializations and preliminaries
comm = MPI.COMM_WORLD # get MPI communicator object
size = comm.size # total number of processes
rank = comm.rank # rank of this process
status = MPI.Status() # get MPI status object
if rank == 0:
try:
with corrections.TaskManager(input_folder,
cleanup=True,
overwrite=args.overwrite,
summary=os.path.join(
output_folder,
'summary_corr.json')) as tm:
# Get list of tasks:
numtasks = tm.get_number_tasks(camera=args.camera,
ccd=args.ccd,
datasource=args.datasource)
tm.logger.info("%d tasks to be run", numtasks)
# Start the master loop that will assign tasks
# to the workers:
num_workers = size - 1
closed_workers = 0
tm.logger.info("Master starting with %d workers", num_workers)
while closed_workers < num_workers:
# Ask workers for information:
data = comm.recv(source=MPI.ANY_SOURCE,
tag=MPI.ANY_TAG,
status=status)
source = status.Get_source()
tag = status.Get_tag()
if tag == tags.DONE:
# The worker is done with a task
tm.logger.info("Got data from worker %d: %s", source,
data)
tm.save_results(data)
if tag in (tags.DONE, tags.READY):
# Worker is ready, so send it a task
task = tm.get_task(camera=args.camera,
ccd=args.ccd,
datasource=args.datasource)
if task:
task_index = task['priority']
tm.start_task(task_index)
comm.send(task, dest=source, tag=tags.START)
tm.logger.info("Sending task %d to worker %d",
task_index, source)
else:
comm.send(None, dest=source, tag=tags.EXIT)
elif tag == tags.EXIT:
# The worker has exited
tm.logger.info("Worker %d exited.", source)
closed_workers += 1
else:
# This should never happen, but just to
# make sure we don't run into an infinite loop:
raise Exception(
"Master received an unknown tag: '{0}'".format(
tag))
tm.logger.info("Master finishing")
except:
# If something fails in the master
print(traceback.format_exc().strip())
comm.Abort(1)
else:
# Worker processes execute code below
# Configure logging within photometry:
formatter = logging.Formatter(
'%(asctime)s - %(levelname)s - %(message)s')
console = logging.StreamHandler()
console.setFormatter(formatter)
logger = logging.getLogger('corrections')
logger.addHandler(console)
logger.setLevel(logging.WARNING)
# Get the class for the selected method:
CorrClass = corrections.corrclass(args.method)
try:
with CorrClass(input_folder, plot=args.plot) as corr:
# Send signal that we are ready for task:
comm.send(None, dest=0, tag=tags.READY)
while True:
# Receive a task from the master:
tic = default_timer()
task = comm.recv(source=0, tag=MPI.ANY_TAG, status=status)
tag = status.Get_tag()
toc = default_timer()
if tag == tags.START:
result = task.copy()
# Run the correction:
try:
result = corr.correct(task)
except:
# Something went wrong
error_msg = traceback.format_exc().strip()
result.update({
'status_corr': corrections.STATUS.ERROR,
'details': {
'errors': error_msg
},
})
result.update({'worker_wait_time': toc - tic})
# Send the result back to the master:
comm.send(result, dest=0, tag=tags.DONE)
# Attempt some cleanup:
# TODO: Is this even needed?
del task, result
elif tag == tags.EXIT:
# We were told to EXIT, so lets do that
break
else:
# This should never happen, but just to
# make sure we don't run into an infinite loop:
raise Exception(
"Worker received an unknown tag: '{0}'".format(
tag))
except:
logger.exception("Something failed in worker")
finally:
comm.send(None, dest=0, tag=tags.EXIT)
if input_folder is None:
test_folder = os.path.abspath(
os.path.join(os.path.dirname(__file__), 'tests', 'input'))
if args.test:
input_folder = test_folder
else:
input_folder = os.environ.get('TESSCORR_INPUT', test_folder)
output_folder = os.environ.get('TESSCORR_OUTPUT',
os.path.join(input_folder, 'lightcurves'))
logger.info("Loading input data from '%s'", input_folder)
logger.info("Putting output data in '%s'", output_folder)
# Get the class for the selected method:
CorrClass = corrections.corrclass(args.method)
# Initialize the corrector class:
with CorrClass(input_folder, plot=args.plot) as corr:
# Start the TaskManager:
with corrections.TaskManager(input_folder) as tm:
while True:
if args.all:
task = tm.get_task()
if task is None: break
elif args.starid is not None:
task = tm.get_task(starid=args.starid)
elif args.random:
task = tm.get_random_task()
def main():
# Parse command line arguments:
parser = argparse.ArgumentParser(
description='Run TESS Corrections in parallel using MPI.')
parser.add_argument('-d',
'--debug',
help='Print debug messages.',
action='store_true')
parser.add_argument('-q',
'--quiet',
help='Only report warnings and errors.',
action='store_true')
parser.add_argument('-m',
'--method',
help='Corrector method to use.',
default='cbv',
choices=('ensemble', 'cbv', 'kasoc_filter'))
parser.add_argument('-o',
'--overwrite',
help='Overwrite existing results.',
action='store_true')
parser.add_argument('-p',
'--plot',
help='Save plots when running.',
action='store_true')
group = parser.add_argument_group('Filter which targets to process')
group.add_argument('--sector', type=int, default=None, help='TESS Sector.')
group.add_argument('--cadence',
type=CadenceType,
choices=('ffi', 1800, 600, 120, 20),
default=None,
help='Cadence. Default is to run all.')
group.add_argument('--camera',
type=int,
choices=(1, 2, 3, 4),
default=None,
help='TESS Camera. Default is to run all cameras.')
group.add_argument('--ccd',
type=int,
choices=(1, 2, 3, 4),
default=None,
help='TESS CCD. Default is to run all CCDs.')
parser.add_argument(
'input_folder',
type=str,
help=
'Input directory. This directory should contain a TODO-file and corresponding lightcurves.',
nargs='?',
default=None)
parser.add_argument('output_folder',
type=str,
help='Directory to save output in.',
nargs='?',
default=None)
args = parser.parse_args()
# Set logging level:
logging_level = logging.INFO
if args.quiet:
logging_level = logging.WARNING
elif args.debug:
logging_level = logging.DEBUG
# Get input and output folder from environment variables:
input_folder = args.input_folder
if input_folder is None:
input_folder = os.environ.get('TESSCORR_INPUT')
if not input_folder:
parser.error("Please specify an INPUT_FOLDER.")
output_folder = args.output_folder
if output_folder is None:
output_folder = os.environ.get(
'TESSCORR_OUTPUT',
os.path.join(os.path.dirname(input_folder), 'lightcurves'))
# Define MPI message tags
tags = enum.IntEnum('tags', ('INIT', 'READY', 'DONE', 'EXIT', 'START'))
# Initializations and preliminaries
comm = MPI.COMM_WORLD # get MPI communicator object
size = comm.size # total number of processes
rank = comm.rank # rank of this process
status = MPI.Status() # get MPI status object
if rank == 0:
try:
# Constraints on which targets to process:
constraints = {
'sector': args.sector,
'cadence': args.cadence,
'camera': args.camera,
'ccd': args.ccd
}
# File path to write summary to:
summary_file = os.path.join(output_folder,
f'summary_corr_{args.method:s}.json')
# Invoke the TaskManager to ensure that the input TODO-file has the correct columns
# and indicies, which is automatically created by the TaskManager init function.
with corrections.TaskManager(input_folder,
cleanup=True,
overwrite=args.overwrite,
cleanup_constraints=constraints):
pass
# Signal that workers are free to initialize:
comm.Barrier() # Barrier 1
# Wait for all workers to initialize:
comm.Barrier() # Barrier 2
# Start TaskManager, which keeps track of the task that needs to be performed:
with corrections.TaskManager(input_folder,
overwrite=args.overwrite,
cleanup_constraints=constraints,
summary=summary_file) as tm:
# Set level of TaskManager logger:
tm.logger.setLevel(logging_level)
# Get list of tasks:
numtasks = tm.get_number_tasks(**constraints)
tm.logger.info("%d tasks to be run", numtasks)
# Start the master loop that will assign tasks
# to the workers:
num_workers = size - 1
closed_workers = 0
tm.logger.info("Master starting with %d workers", num_workers)
while closed_workers < num_workers:
# Get information from worker:
data = comm.recv(source=MPI.ANY_SOURCE,
tag=MPI.ANY_TAG,
status=status)
source = status.Get_source()
tag = status.Get_tag()
if tag == tags.DONE:
# The worker is done with a task
tm.logger.debug("Got data from worker %d: %s", source,
data)
tm.save_results(data)
if tag in (tags.DONE, tags.READY):
# Worker is ready for a new task, so send it a task
tasks = tm.get_task(**constraints, chunk=10)
if tasks:
tm.start_task(tasks)
tm.logger.debug("Sending %d tasks to worker %d",
len(tasks), source)
comm.send(tasks, dest=source, tag=tags.START)
else:
comm.send(None, dest=source, tag=tags.EXIT)
elif tag == tags.EXIT:
# The worker has exited
tm.logger.info("Worker %d exited.", source)
closed_workers += 1
else:
# This should never happen, but just to
# make sure we don't run into an infinite loop:
raise RuntimeError(
f"Master received an unknown tag: '{tag}'")
tm.logger.info("Master finishing")
except: # noqa: E722, pragma: no cover
# If something fails in the master
print(traceback.format_exc().strip())
comm.Abort(1)
else:
# Worker processes execute code below
# Configure logging within photometry:
formatter = logging.Formatter(
'%(asctime)s - %(levelname)s - %(message)s')
console = logging.StreamHandler()
console.setFormatter(formatter)
logger = logging.getLogger('corrections')
logger.addHandler(console)
logger.setLevel(logging.WARNING)
# Get the class for the selected method:
CorrClass = corrections.corrclass(args.method)
try:
# Wait for signal that we are okay to initialize:
comm.Barrier() # Barrier 1
# We can now safely initialize the corrector on the input file:
with CorrClass(input_folder, plot=args.plot) as corr:
# Wait for all workers do be done initializing:
comm.Barrier() # Barrier 2
# Send signal that we are ready for task:
comm.send(None, dest=0, tag=tags.READY)
while True:
# Receive a task from the master:
tic = default_timer()
tasks = comm.recv(source=0, tag=MPI.ANY_TAG, status=status)
tag = status.Get_tag()
toc = default_timer()
if tag == tags.START:
# Make sure we can loop through tasks,
# even in the case we have only gotten one:
results = []
if not isinstance(tasks, (list, tuple)):
tasks = list(tasks)
# Loop through the tasks given to us:
for task in tasks:
result = task.copy()
# Run the correction:
try:
result = corr.correct(task)
except: # noqa: E722
# Something went wrong
error_msg = traceback.format_exc().strip()
result.update({
'status_corr':
corrections.STATUS.ERROR,
'details': {
'errors': [error_msg]
},
})
result.update({'worker_wait_time': toc - tic})
results.append(result)
# Send the result back to the master:
comm.send(results, dest=0, tag=tags.DONE)
elif tag == tags.EXIT:
# We were told to EXIT, so lets do that
break
else:
# This should never happen, but just to
# make sure we don't run into an infinite loop:
raise RuntimeError(
f"Worker received an unknown tag: '{tag}'")
except: # noqa: E722, pragma: no cover
logger.exception("Something failed in worker")
finally:
comm.send(None, dest=0, tag=tags.EXIT)
def main():
# Parse command line arguments:
parser = argparse.ArgumentParser(
description='Run TESS Corrector pipeline on single star.')
parser.add_argument('-m',
'--method',
help='Corrector method to use.',
default=None,
choices=('ensemble', 'cbv', 'kasoc_filter'))
parser.add_argument('-d',
'--debug',
help='Print debug messages.',
action='store_true')
parser.add_argument('-q',
'--quiet',
help='Only report warnings and errors.',
action='store_true')
parser.add_argument('-p',
'--plot',
help='Save plots when running.',
action='store_true')
parser.add_argument('-r',
'--random',
help='Run on random target from TODO-list.',
action='store_true')
parser.add_argument(
'-t',
'--test',
help='Use test data and ignore TESSCORR_INPUT environment variable.',
action='store_true')
parser.add_argument('-a',
'--all',
help='Run correction on all targets.',
action='store_true')
parser.add_argument('-o',
'--overwrite',
help='Overwrite previous runs and start over.',
action='store_true')
group = parser.add_argument_group('Filter which targets to process')
group.add_argument('--priority',
type=int,
default=None,
help='Priority of target.')
group.add_argument('--starid',
type=int,
default=None,
help='TIC identifier of target.')
group.add_argument('--sector', type=int, default=None, help='TESS Sector.')
group.add_argument('--cadence',
type=CadenceType,
choices=('ffi', 1800, 600, 120, 20),
default=None,
help='Cadence. Default is to run all.')
group.add_argument('--camera',
type=int,
choices=(1, 2, 3, 4),
default=None,
help='TESS Camera. Default is to run all cameras.')
group.add_argument('--ccd',
type=int,
choices=(1, 2, 3, 4),
default=None,
help='TESS CCD. Default is to run all CCDs.')
parser.add_argument(
'input_folder',
type=str,
help=
'Input directory. This directory should contain a TODO-file and corresponding lightcurves.',
nargs='?',
default=None)
parser.add_argument('output_folder',
type=str,
help='Directory to save output in.',
nargs='?',
default=None)
args = parser.parse_args()
# Make sure at least one setting is given:
if not args.all and args.starid is None and args.priority is None and not args.random:
parser.error(
"Please select either a specific STARID, PRIORITY or RANDOM.")
# Set logging level:
logging_level = logging.INFO
if args.quiet:
logging_level = logging.WARNING
elif args.debug:
logging_level = logging.DEBUG
# Setup logging:
formatter = logging.Formatter('%(asctime)s - %(levelname)s - %(message)s')
console = logging.StreamHandler()
console.setFormatter(formatter)
logger = logging.getLogger(__name__)
if not logger.hasHandlers():
logger.addHandler(console)
logger.setLevel(logging_level)
logger_parent = logging.getLogger('corrections')
if not logger_parent.hasHandlers():
logger_parent.addHandler(console)
logger_parent.setLevel(logging_level)
# Get input and output folder from environment variables:
input_folder = args.input_folder
if input_folder is None:
test_folder = os.path.abspath(
os.path.join(os.path.dirname(__file__), 'tests', 'input'))
if args.test:
input_folder = test_folder
else:
input_folder = os.environ.get('TESSCORR_INPUT', test_folder)
output_folder = args.output_folder
if output_folder is None:
output_folder = os.environ.get(
'TESSCORR_OUTPUT',
os.path.join(os.path.dirname(input_folder), 'lightcurves'))
logger.info("Loading input data from '%s'", input_folder)
logger.info("Putting output data in '%s'", output_folder)
# Make sure the output directory exists:
os.makedirs(output_folder, exist_ok=True)
# Constraints on which targets to process:
constraints = {
'priority': args.priority,
'starid': args.starid,
'sector': args.sector,
'cadence': args.cadence,
'camera': args.camera,
'ccd': args.ccd
}
# Get the class for the selected method:
CorrClass = corrections.corrclass(args.method)
# Start the TaskManager:
with corrections.TaskManager(input_folder,
overwrite=args.overwrite,
cleanup_constraints=constraints) as tm:
# Initialize the corrector class:
with CorrClass(input_folder, plot=args.plot) as corr:
while True:
if args.random:
task = tm.get_random_task()
else:
task = tm.get_task(**constraints)
if task is None:
break
# Run the correction:
result = corr.correct(task, output_folder=output_folder)
# Construct results to return to TaskManager:
tm.save_results(result)
if not args.all:
break