def get(self, singleSnapshot=False):
"""
*geneate the pyephem positions*
**Key Arguments:**
- ``singleSnapshot`` -- just extract positions for a single pyephem snapshot (used for unit testing)
**Return:**
- ``None``
"""
self.log.info('starting the ``get`` method')
global xephemOE
global tileSide
global magLimit
# GRAB PARAMETERS FROM SETTINGS FILE
tileSide = float(self.settings["pyephem"]["atlas exposure match side"])
magLimit = float(self.settings["pyephem"]["magnitude limit"])
snapshotsRequired = 1
while snapshotsRequired > 0:
nextMjds, exposures, snapshotsRequired = self._get_exposures_requiring_pyephem_positions(
concurrentSnapshots=int(self.settings["pyephem"]
["batch size"]))
print "There are currently %(snapshotsRequired)s more pyephem snapshots required " % locals(
)
if snapshotsRequired == 0:
return
if len(xephemOE) == 0:
xephemOE = self._get_xephem_orbital_elements()
# DEFINE AN INPUT ARRAY
magLimit = self.settings["pyephem"]["magnitude limit"]
pyephemDB = fmultiprocess(log=self.log,
function=_generate_pyephem_snapshot,
timeout=300,
inputArray=nextMjds,
magLimit=magLimit)
matchedObjects = []
for p, e, m in zip(pyephemDB, exposures, nextMjds):
matchedObjects.append(
self._match_pyephem_snapshot_to_atlas_exposures(p, e, m))
self._add_matched_objects_to_database(matchedObjects)
self._update_database_flag(exposures)
if singleSnapshot:
snapshotsRequired = 0
self.log.info('completed the ``get`` method')
return None
def test_multiprocess_function_exception(self):
from fundamentals import fmultiprocess
try:
this = fmultiprocess(log=log,
settings=settings,
fakeKey="break the code")
this.get()
assert False
except Exception as e:
assert True
print(str(e))
def test_multiprocess_function_exception(self):
from fundamentals import fmultiprocess
try:
this = fmultiprocess(
log=log,
settings=settings,
fakeKey="break the code"
)
this.get()
assert False
except Exception, e:
assert True
print str(e)
def get(self):
"""
*match the orbfit predicted positions of known asteroids against the positions recored in the local cache of dophot files*
**Return:**
- None
**Usage:**
See class docstring
"""
self.log.info('starting the ``get`` method')
cachePath = self.settings["atlas archive path"]
global exposureIds
exposureIds, remaining = self._select_exposures_requiring_dophot_extraction(
batch=int(self.settings["dophot"]["batch size"]))
if remaining == 0:
print "%(remaining)s locally cached dophot files remain needing to be parsed for orbfit predicted known asteroid positions" % locals(
)
return None
# SELECT 100 EXPOSURES REQUIRING DOPHOT EXTRACTION
while remaining > 0:
exposureIds, remaining = self._select_exposures_requiring_dophot_extraction(
batch=int(self.settings["dophot"]["batch size"]))
print "%(remaining)s locally cached dophot files remain needing to be parsed for orbfit predicted known asteroid positions" % locals(
)
if remaining == 0:
continue
dophotMatches = fmultiprocess(log=self.log,
function=_extract_phot_from_exposure,
inputArray=range(len(exposureIds)),
poolSize=5,
timeout=300,
cachePath=cachePath,
settings=self.settings)
self._add_dophot_matches_to_database(dophotMatches=dophotMatches,
exposureIds=exposureIds)
dophotMatches = None
self._add_value_to_dophot_table()
self.log.info('completed the ``get`` method')
return None
def test_multiprocess_function(self):
from fundamentals import fmultiprocess
# DEFINE AN INPUT ARRAY
inputArray = range(1000)
t1 = time.time()
result = fmultiprocess(log=log, function=f,
inputArray=inputArray, anotherKeyword="cheese")
took = time.time() - t1
print "Multiprocessing took: %(took)s" % locals()
t2 = time.time()
result = []
for i in inputArray:
result.append(f(i))
took = time.time() - t2
print "Serial processing took: %(took)s" % locals()
def test_multiprocess_function(self):
from fundamentals import fmultiprocess
# DEFINE AN INPUT ARRAY
inputArray = list(range(1000))
t1 = time.time()
result = fmultiprocess(log=log,
function=f,
inputArray=inputArray,
anotherKeyword="cheese")
took = time.time() - t1
print("Multiprocessing took: %(took)s" % locals())
t2 = time.time()
result = []
for i in inputArray:
result.append(f(i))
took = time.time() - t2
print("Serial processing took: %(took)s" % locals())
def _match_pyephem_snapshot_to_atlas_exposures(self, pyephemDB, exposures,
mjd):
"""*match pyephem snapshot to atlas exposures*
**Key Arguments:**
- ``pyephemDB`` -- the pyephem solar-system snapshot database
- ``exposures`` -- the atlas exposures to match against the snapshot
- ``mjd`` -- the MJD of the pyephem snapshot
**Return:**
- ``matchedObjects`` -- these objects matched in the neighbourhood of the ATLAS exposures (list of dictionaries)
"""
self.log.info(
'starting the ``_match_pyephem_snapshot_to_atlas_exposures`` method'
)
global DEG_TO_RAD_FACTOR
global RAD_TO_DEG_FACTOR
global moversDict
e = len(exposures)
print "Matching %(e)s ATLAS exposures against the pyephem snapshot for MJD = %(mjd)s" % locals(
)
# MAKE SURE HEALPIX SMALL ENOUGH TO MATCH FOOTPRINTS CORRECTLY
global nside
# GRAB PARAMETERS FROM SETTINGS FILE
tileSide = float(self.settings["pyephem"]["atlas exposure match side"])
magLimit = float(self.settings["pyephem"]["magnitude limit"])
# EXPLODE OUT THE PYEPHEM DATABASE
ra = pyephemDB["ra_deg"]
dec = pyephemDB["dec_deg"]
healpix = pyephemDB["healpix"]
objects = pyephemDB["object_name"]
mpc_numbers = pyephemDB["mpc_number"]
mag = pyephemDB["mag"]
# INDEX PYEPHEM MOVERS IN DICTIONARY BY HEALPIX ID
moversDict = defaultdict(list)
for ind, (p, r, d, o, m, g) in enumerate(
zip(healpix, ra, dec, objects, mpc_numbers, mag)):
moversDict[p].append({
"object_name": o,
"ra_deg": r,
"dec_deg": d,
"mpc_number": m,
"mag": g
})
# MATCH THE PYEPHEM MOVERS AGAINST THE ATLAS EXPOSURES
matchedObjects = []
results = fmultiprocess(
log=self.log,
function=_match_single_exposure_against_pyephem_db,
timeout=120,
inputArray=exposures)
for r in results:
matchedObjects += r
self.log.info(
'completed the ``_match_pyephem_snapshot_to_atlas_exposures`` method'
)
return matchedObjects
def plot(self):
"""*generate a batch of lightcurves using multiprocessing given their transientBucketIds*
**Return**
- ``filepath`` -- path to the last generated plot file
**Usage**
```python
from marshallEngine.lightcurves import marshall_lightcurves
lc = marshall_lightcurves(
log=log,
dbConn=dbConn,
settings=settings,
transientBucketIds=[28421489, 28121353, 4637952, 27409808]
)
lc.plot()
```
"""
self.log.debug('starting the ``plot`` method')
# DEFINE AN INPUT ARRAY
total = len(self.transientBucketIds)
thisDict = {"database settings": self.settings["database settings"]}
if total:
print("updating lightcurves for %(total)s transients" % locals())
print()
# USE IF ISSUES IN _plot_one FUNCTION
# for transientBucketId in self.transientBucketIds:
# _plot_one(
# transientBucketId=transientBucketId,
# log=self.log,
# settings=self.settings
# )
results = fmultiprocess(log=self.log,
function=_plot_one,
inputArray=self.transientBucketIds,
poolSize=False,
timeout=3600,
settings=self.settings)
sqlQuery = ""
updatedTransientBucketIds = []
for t, r in zip(self.transientBucketIds, results):
if not r[0]:
# LIGHTCURVE NOT GENERATED
continue
updatedTransientBucketIds.append(t)
filepath = r[0]
currentMagnitude = r[1]
gradient = r[2]
sqlQuery += """update transientBucketSummaries set currentMagnitudeEstimate = %(currentMagnitude)s, currentMagnitudeEstimateUpdated = NOW(), recentSlopeOfLightcurve = %(gradient)s where transientBucketId = %(t)s;
""" % locals()
ids = []
ids[:] = [str(i) for i in updatedTransientBucketIds]
updatedTransientBucketIds = (",").join(ids)
sqlQuery += "update pesstoObjects set master_pessto_lightcurve = 1 where transientBucketId in (%(updatedTransientBucketIds)s);" % locals(
)
if len(updatedTransientBucketIds):
writequery(
log=self.log,
sqlQuery=sqlQuery,
dbConn=self.dbConn,
)
else:
filepath = False
self.log.debug('completed the ``plot`` method')
return filepath
def generate_atlas_lightcurves(dbConn, log, settings):
"""generate all atlas FP lightcurves (clipped and stacked)
**Key Arguments**
- ``dbConn`` -- mysql database connection
- ``log`` -- logger
- ``settings`` -- settings for the marshall.
```python
from marshallEngine.feeders.atlas.lightcurve import generate_atlas_lightcurves
generate_atlas_lightcurves(
log=log,
dbConn=dbConn,
settings=settings
)
```
"""
log.debug('starting the ``generate_atlas_lightcurves`` function')
# SELECT SOURCES THAT NEED THEIR ATLAS FP LIGHTCURVES CREATED/UPDATED
sqlQuery = u"""
SELECT
t.transientBucketId
FROM
transientBucket t ,pesstoObjects p
WHERE
p.transientBucketId=t.transientBucketId
and t.survey = 'ATLAS FP' and t.limitingMag = 0
and ((p.atlas_fp_lightcurve < t.dateCreated and p.atlas_fp_lightcurve != 0) or p.atlas_fp_lightcurve is null)
GROUP BY t.transientBucketId;
"""
rows = readquery(log=log, sqlQuery=sqlQuery, dbConn=dbConn)
transientIds = [r["transientBucketId"] for r in rows]
total = len(transientIds)
if total > 1000:
print(
"ATLAS lightcurves need generated for %(total)s sources - generating next 1000"
% locals())
transientIds = transientIds[:1000]
total = len(transientIds)
else:
print("Generating ATLAS lightcurves for %(total)s sources" % locals())
# SETUP THE INITIAL FIGURE FOR THE PLOT (ONLY ONCE)
fig = plt.figure(num=None,
figsize=(10, 10),
dpi=100,
facecolor=None,
edgecolor=None,
frameon=True)
mpl.rc('ytick', labelsize=18)
mpl.rc('xtick', labelsize=18)
mpl.rcParams.update({'font.size': 22})
# FORMAT THE AXES
ax = fig.add_axes([0.1, 0.1, 0.8, 0.8], polar=False, frameon=True)
ax.set_xlabel('MJD', labelpad=20)
ax.set_yticks([2.2])
# RHS AXIS TICKS
plt.setp(ax.xaxis.get_majorticklabels(),
rotation=45,
horizontalalignment='right')
ax.xaxis.set_major_formatter(mtick.FormatStrFormatter('%5.0f'))
y_formatter = mpl.ticker.FormatStrFormatter("%2.1f")
ax.yaxis.set_major_formatter(y_formatter)
ax.xaxis.grid(False)
# ADD SECOND Y-AXIS
ax2 = ax.twinx()
ax2.yaxis.set_major_formatter(y_formatter)
ax2.set_ylabel('Flux ($\mu$Jy)', rotation=-90., labelpad=27)
ax2.grid(False)
# ADD SECOND X-AXIS
ax3 = ax.twiny()
ax3.grid(True)
plt.setp(ax3.xaxis.get_majorticklabels(),
rotation=45,
horizontalalignment='left')
# CONVERTER TO CONVERT MJD TO DATE
converter = conversions(log=log)
if len(transientIds) < 3:
plotPaths = []
for transientBucketId in transientIds:
plotPaths.append(
plot_single_result(log=log,
transientBucketId=transientBucketId,
fig=fig,
converter=converter,
ax=ax,
settings=settings))
else:
log.info("""starting multiprocessing""")
plotPaths = fmultiprocess(log=log,
function=plot_single_result,
inputArray=transientIds,
poolSize=False,
timeout=7200,
fig=fig,
converter=converter,
ax=ax,
settings=settings)
log.info("""finished multiprocessing""")
# REMOVE MISSING PLOTStrn
transientIdGood = [t for p, t in zip(plotPaths, transientIds) if p]
transientIdBad = [t for p, t in zip(plotPaths, transientIds) if p is None]
# UPDATE THE atlas_fp_lightcurve DATE FOR TRANSIENTS WE HAVE JUST
# GENERATED PLOTS FOR
if len(transientIdGood):
transientIdGood = (",").join([str(t) for t in transientIdGood])
sqlQuery = f"""update pesstoObjects set atlas_fp_lightcurve = NOW() where transientBucketID in ({transientIdGood})"""
writequery(log=log, sqlQuery=sqlQuery, dbConn=dbConn)
# UPDATE THE atlas_fp_lightcurve DATE FOR TRANSIENTS WE HAVE JUST
# GENERATED PLOTS FOR
if len(transientIdBad):
transientIdBad = (",").join([str(t) for t in transientIdBad])
sqlQuery = f"""update pesstoObjects set atlas_fp_lightcurve = 0 where transientBucketID in ({transientIdBad})"""
writequery(log=log, sqlQuery=sqlQuery, dbConn=dbConn)
log.debug('completed the ``generate_atlas_lightcurves`` function')
return None
def orbfit_ephemeris(log,
objectId,
mjd,
settings,
obscode=500,
verbose=False,
astorbPath=False):
"""Given a known solar-system object ID (human-readable name or MPC number but *NOT* an MPC packed format) or list of names and one or more specific epochs, return the calculated ephemerides
**Key Arguments:**
- ``log`` -- logger
- ``objectId`` -- human-readable name, MPC number or solar-system object name, or list of names
- ``mjd`` -- a single MJD, or a list MJDs to generate an ephemeris for
- ``settings`` -- the settings dictionary for rockfinder
- ``obscode`` -- the observatory code for the ephemeris generation. Default **500** (geocentric)
- ``verbose`` -- return extra information with each ephemeris
- ``astorbPath`` -- override the default path to astorb.dat orbital elements file
**Return:**
- ``resultList`` -- a list of ordered dictionaries containing the returned ephemerides
**Usage:**
To generate a an ephemeris for a single epoch run,using ATLAS Haleakala as your observatory:
.. code-block:: python
from rockfinder import orbfit_ephemeris
eph = orbfit_ephemeris(
log=log,
objectId=1,
obscode="T05"
mjd=57916.,
)
or to generate an ephemeris for multiple epochs:
.. code-block:: python
from rockfinder import orbfit_ephemeris
eph = orbfit_ephemeris(
log=log,
objectId="ceres",
mjd=[57916.1,57917.234,57956.34523]
verbose=True
)
Note by passing `verbose=True` the essential ephemeris data is supplimented with some extra data
It's also possible to pass in an array of object IDs:
.. code-block:: python
from rockfinder import orbfit_ephemeris
eph = orbfit_ephemeris(
log=log,
objectId=[1,5,03547,"Shikoku"],
mjd=[57916.1,57917.234,57956.34523]
)
And finally you override the default path to astorb.dat orbital elements file by passing in a custom path (useful for passing in a trimmed orbital elements database):
.. code-block:: python
from rockfinder import orbfit_ephemeris
eph = orbfit_ephemeris(
log=log,
objectId=[1,5,03547,"Shikoku"],
mjd=[57916.1,57917.234,57956.34523],
astorbPath="/path/to/astorb.dat"
)
"""
log.debug('starting the ``orbfit_ephemeris`` function')
global cmdList
# MAKE SURE MJDs ARE IN A LIST
if not isinstance(mjd, list):
mjdList = [str(mjd)]
else:
mjdList = mjd
if not isinstance(objectId, list):
objectList = [objectId]
else:
objectList = objectId
ephem = settings["path to ephem binary"]
home = expanduser("~")
results = []
tmpCmdList = []
for o in objectList:
for m in mjdList:
if not isinstance(o, int) and "'" in o:
cmd = """%(ephem)s %(obscode)s %(m)s "%(o)s" """ % locals()
else:
cmd = """%(ephem)s %(obscode)s %(m)s '%(o)s'""" % locals()
if astorbPath:
cmd += " '%(astorbPath)s'" % locals()
tmpCmdList.append((cmd, o))
def chunks(l, n):
"""Yield successive n-sized chunks from l."""
for i in range(0, len(l), n):
yield l[i:i + n]
# BATCH INTO 10s
cmdList = [c for c in chunks(tmpCmdList, 10)]
# DEFINE AN INPUT ARRAY
results = fmultiprocess(log=log,
function=_generate_one_ephemeris,
inputArray=range(len(cmdList)))
if verbose == True:
order = [
"object_name", "mjd", "ra_deg", "dec_deg", "apparent_mag",
"observer_distance", "heliocentric_distance", "phase_angle",
"obscode", "sun_obs_target_angle", "galactic_latitude",
"ra_arcsec_per_hour", "dec_arcsec_per_hour"
]
else:
order = [
"object_name", "mjd", "ra_deg", "dec_deg", "apparent_mag",
"observer_distance", "heliocentric_distance", "phase_angle"
]
# ORDER THE RESULTS
resultList = []
for r2 in results:
if not r2:
continue
for r in r2:
if not r:
continue
orderDict = collections.OrderedDict({})
for i in order:
orderDict[i] = r[i]
resultList.append(orderDict)
log.debug('completed the ``orbfit_ephemeris`` function')
return resultList
def get(self, days):
"""
*download a cache of ATLAS nights data*
**Key Arguments:**
- ``days`` -- the number of days data to cache locally
**Return:**
- None
**Usage:**
See class docstring
"""
self.log.info('starting the ``get`` method')
self._remove_processed_data()
archivePath = self.settings["atlas archive path"]
self._update_day_tracker_table()
mjds = self._determine_mjds_to_download(days=days)
if len(mjds) == 0:
return
dbConn = self.atlasMoversDBConn
# DOWNLOAD THE DATA IN PARALLEL
results = fmultiprocess(log=self.log,
function=_download_one_night_of_atlas_data,
timeout=3600,
inputArray=mjds,
archivePath=archivePath)
global dbSettings
dbSettings = self.settings["database settings"]["atlasMovers"]
for d in results:
if d and len(d[0]):
insert_list_of_dictionaries_into_database_tables(
dbConn=dbConn,
log=self.log,
dictList=d[0],
dbTableName="atlas_exposures",
dateModified=True,
batchSize=10000,
replace=True,
dbSettings=dbSettings)
# UPDATE BOOKKEEPING
mjds = []
mjds[:] = [r[1] for r in results if (r and r[1] is not None)]
mjds = (',').join(mjds)
if len(mjds):
sqlQuery = """update atlas_exposures set local_data = 1 where floor(mjd) in (%(mjds)s);
update day_tracker set processed = 1 where mjd in (%(mjds)s);""" % locals(
)
writequery(
log=self.log,
sqlQuery=sqlQuery,
dbConn=self.atlasMoversDBConn,
)
bk = bookkeeper(log=self.log, settings=self.settings, fullUpdate=False)
bk.clean_all()
self.log.info('completed the ``get`` method')
return None
