def blsTask(clip):
# import dave.blsCode.bls_ktwo as bls
import bls
time_days = clip['serve.time']
flux_norm = clip['detrend.flux_frac']
flags = clip['detrend.flags']
minPeriod = 1.
maxPeriod = 20.
period, epoch, duration, depth, bls_search_periods, convolved_bls = \
bls.doSearch(time_days[~flags], flux_norm[~flags], minPeriod, maxPeriod)
out = clipboard.Clipboard()
out['period'] = period
out['epoch'] = epoch
ut['duration_hrs'] = duration * 24
out['depth'] = depth
clip['bls'] = out
##Enforce contract
clip['bls.period']
clip['bls.epoch']
clip['bls.duration_hrs']
return clip
def createConfig(detrendType, sector, tic, planetNum, period, tepoch, tdepth, tdur, debugMode=True):
cfg = dict()
cfg['debug'] = debugMode
cfg['sector'] = sector
cfg['campaign'] = sector
cfg['tic'] = tic
cfg['planetNum'] = planetNum
cfg['value'] = tic
cfg['detrendType'] = detrendType#"eleanor"#"tess"#
cfg['period'] = period
cfg['tepoch'] = tepoch
cfg['tdepth'] = tdepth
cfg['tdur'] = tdur
#TODO This shouldn't be hardcoded, but passed as a parameter
cfg['dvtLocalPath'] = "/Users/.eleanor/"
#TODO Need modshift paths
cfg['lppMapFile'] = "/Users/LPP_map/combMapDR25AugustMapDV_6574.mat"
cfg['modshiftBasename'] = "/Users/justVet/"
cfg['onepageBasename'] = "/Users/justVet/"
if detrendType == 'tess':
cfg['taskList'] = ['serveTask', 'trapezoidFitTask','modshiftTask', 'sweetTask', 'lppMetricTask','centroidsTask', 'dispositionTask']
elif detrendType == 'eleanor':
cfg['taskList'] = ['serveTask', 'detrendTask', 'trapezoidFitTask','modshiftTask', 'sweetTask', 'lppMetricTask', 'centroidsTask', 'dispositionTask']
clip = clipboard.Clipboard(cfg)
return clip
def dispositionTask(clip):
"""Decide whether an event is a planet candidate or not
TODO:
Much of this should be parcelled off into a function
"""
#Thresholds
snrThreshold = clip['config.minSnrForDetection']
lppThreshold = clip['config.maxLppForTransit']
minProbForFail = clip['config.minProbDiffImgCentroidForFail']
snr = clip['trapFit.snr']
modshiftDict = clip['modshift']
centroidArray = clip['diffImg.centroid_timeseries']
out = clipboard.Clipboard(isSignificantEvent=True, isCandidate=True, \
reasonForFail="None")
#Compute centroid offset and significance
centVet = {'Warning': "None"}
try:
prob, chisq = cent.measureOffsetProbabilityInTimeseries(centroidArray)
except ValueError, e:
centVet['Warning'] = "Probability not computed: %s" % (e)
prob = 0
chisq = 0
def getMilesLightcurveTask(clip):
# get input data from clip
cube = clip['serve.cube']
time = clip['serve.time']
flags = clip['serve.flags'] > 0
flags |= ~np.isfinite(time)
nt, nr, nc = cube.shape
pixSeries, pixSeriesNorm = milesPCA.pixSeriesPrep(cube, flags)
totLightcurve = milesPCA.getRawLightcurve(pixSeries)
# package results
out = clipboard.Clipboard()
out['rawLightcurve'] = totLightcurve
out['time'] = time
out['pixSeries'] = pixSeries
out['pixSeriesNorm'] = pixSeriesNorm
out['flags'] = flags
clip['extract'] = out
#Enforce contract
clip['extract.rawLightcurve']
clip['extract.time']
clip['extract.pixSeries']
clip['extract.pixSeriesNorm']
clip['extract.flags']
return clip
def loadMultipleDetrendings(epic, campaign, dataStorePath, detrendTypes):
#Definition of the different kinds of detrendings and how to
#parse the output of their archive class
dTypeDict = dict()
dTypeDict['PDC'] = (mastio.K2Archive(), pdcParser, "PDC")
dTypeDict['AGP'] = (mastio.K2SCArchive(), agpParser, "K2SC")
dTypeDict['EVEREST'] = (mastio.EverestArchive(), everestParser, "Everest")
dTypeDict['SFF'] = (mastio.VanderburgArchive(), sffParser,
"Vanderburg SFF")
out = dpc.Clipboard()
#Load the TPF data cube
ar = mastio.K2Archive(dataStorePath)
fits, hdr = ar.getLongTpf(epic, campaign, header=True, mmap=False)
hdr0 = ar.getLongTpf(epic, campaign, ext=0, mmap=False)
cube = tpf.getTargetPixelArrayFromFits(fits, hdr)
out['time'] = fits['TIME']
out['cube'] = cube
out['tpfHeader'] = hdr
out['tpfHeader0'] = hdr0
#Load PA data
fits = ar.getLongCadence(epic, campaign)
out['rawFlux'] = fits['SAP_FLUX']
#Load lightcurves from a specific detrending, and replace
#the pdc time series with the new detrending
nDetrend = 0
for i, dType in enumerate(detrendTypes):
key = dType.upper()
if key not in dTypeDict:
raise IOError("Unrecognised detrended %s" % (key))
ar, parser, label = dTypeDict[key]
data = ar.getLongCadence(epic, campaign)
flux = parser(out['time'], data)
typeName = "type%i" % (i + 1)
out[typeName] = key
fluxName = "flux%i" % (i + 1)
out[fluxName] = flux
labelName = "label%i" % (i + 1)
out[labelName] = label
nDetrend += 1
out['numDetrendings'] = nDetrend
#Enforce contract
out['flux1']
out['label1']
out['cube']
return out
def runOneEphem(k2id, period, epoch, config, duration=2, depth=.0001):
"""
Run just the vetting and return an output.
Inputs:
-------------
k2id
(int) Epic id of the target to run on.
period
(float) period of the target
epoch
(float) Time in days
config
(dict) Dictionary of configuration parameters
"""
tasks = """dpp.checkDirExistTask dpp.serveTask dpp.extractLightcurveFromTpfTask
dpp.computeCentroidsTask dpp.rollPhaseTask dpp.cotrendSffDataTask
dpp.detrendDataTask dpp.trapezoidFitTask dpp.lppMetricTask
dpp.modshiftTask dpp.measureDiffImgCentroidsTask dpp.dispositionTask
dpp.saveOnError""".split()
taskList = tasks
clip = clipboard.Clipboard()
clip['config'] = config
clip['value'] = k2id
out = clipboard.Clipboard()
out['period'] = period
out['epoch'] = epoch
out['duration_hrs'] = duration
out['depth'] = depth
clip['bls'] = out
#Check that all the tasks are properly defined
for t in taskList:
f = eval(t)
#Now run them.
for t in taskList:
f = eval(t)
clip = f(clip)
return clip
def dispositionTask(clip):
"""Decide whether an event is a planet candidate or not
TODO:
Much of this should be parcelled off into a function
"""
#Thresholds
snrThreshold = clip['config.minSnrForDetection']
# lppThreshold = clip['config.maxLppForTransit']
offsetThreshold_sigma = clip['config.minCentroidSignifForFp']
#Data on which to make a decision
snr = clip['trapFit.snr']
modshiftDict = clip['modshift']
centroidArray = clip['diffImg.centroid_timeseries']
out = clipboard.Clipboard(isSignificantEvent=True, isCandidate=True, \
reasonForFail="None")
if snr < snrThreshold:
out['isSignificantEvent'] = False
out['isCandidate'] = False
out['reasonForFail'] = "SNR (%.1f) below threshold %.1f" \
%(snr, snrThreshold)
return out
#Parse modshift results
fluxVetDict = RoboVet.roboVet(modshiftDict)
out['fluxVet'] = fluxVetDict
assert (fluxVetDict['disp'] in ["candidate", "false positive"])
if fluxVetDict['disp'] == "false positive":
out['isCandidate'] = False
out['reasonForFail'] = fluxVetDict['comments']
return out
#Compute centroid offset and significance
result = cent.measureOffsetInTimeseries(centroidArray)
out['centroidVet'] = result
signif = result['signif']
offset = result['offset']
if signif > offsetThreshold_sigma:
out['isCandidate'] = False
out['reasonForFail'] = "Centroid offset of %.2f (%.1f sigma) detected" \
%( offset, signif)
return out
clip['disposition'] = out
#Enforce contract
clip['disposition.isSignificantEvent']
clip['disposition.isCandidate']
clip['disposition.reasonForFail']
return clip
def runOneDv(detrendType , sector, tic, planetNum, period, epoch, tdepth, tdur, debugMode=True):
cfg = createConfig(detrendType, sector, tic, planetNum, period, epoch, tdepth, tdur, debugMode=True)
clip = tessPipeline.runOne(cfg,returnClip=True)
out = clipboard.Clipboard(isSignificantEvent=True, isCandidate=True, reasonForFail="None")
# This is an attempt at quickly vetting the signals.
# This should be its own task.
return clip
def runOneEphem(k2id,period,epoch,config,duration=3.5,depth=.0001):
"""
Run just the vetting and return an output.
Inputs:
-------------
k2id
(int) Epic id of the target to run on.
period
(float) period of the target
epoch
(float) Time in days
config
(dict) Dictionary of configuration parameters
"""
taskList = config['taskList'];
clip = clipboard.Clipboard()
clip['config'] = config
clip['value'] = k2id
out = clipboard.Clipboard()
out['period'] = period
out['epoch'] = epoch
out['duration_hrs'] = duration
out['depth'] = depth
clip['bls'] = out
#Check that all the tasks are properly defined
for t in taskList:
f = eval(t)
#Now run them.
for t in taskList:
f = eval(t)
clip = f(clip)
return clip
def placeholderBls(clip):
"""Debugging code. Returns the ephemeris of the largest event in
K2Id 206103150
"""
out = clipboard.Clipboard()
out['period'] = 4.15892
out['epoch'] = 2145.76
out['duration_hrs'] = 1.94443
out['depth'] = .01112825
clip['bls'] = out
return clip
def searchForEvent(clip):
subClip = clip.shallowCopy()
originalKeyList = subClip.keys()
taskList = clip['config.searchTaskList']
#Set the flags attribute of the new subclip
#Problem with this code is it closely tied to the behaviour
#of multiEventSearchTask
try:
tmp = clip.eventList[-1]
flags = tmp['flags']
except (IndexError, KeyError):
flags = clip['detrend.flags']
subClip['flags'] = flags
#Check that all the tasks are properly defined
for t in taskList:
f = eval(t)
#Now run them.
for t in taskList:
f = eval(t)
subClip = f(subClip)
# #@TODO List of tasks to run should be config param
# subClip = placeholderBls(subClip)
# subClip = trapezoidFitTask(subClip)
# subClip = modshiftTask(subClip)
# subClip = measureDiffImgCentroidsTask(subClip)
# subClip = dispositionTask(subClip)
newKeys = list(set(subClip.keys()) - set(originalKeyList))
out = clipboard.Clipboard(__meta__=subClip['__meta__'])
for k in newKeys:
out[k] = subClip[k]
#Mark all locations for this event as data not to be used.
time = subClip['serve.time']
period_days = subClip['trapFit.period_days']
epoch_bkjd = subClip['trapFit.epoch_bkjd']
duration_days = subClip['trapFit.duration_hrs'] / 24.
# assert(np.all(np.isfinite(time[~flags])))
# assert(np.any(flags))
idx = kplrfits.markTransitCadences(time, period_days, epoch_bkjd, \
duration_days, numberOfDurations=2, flags=flags)
out['flags'] = flags | idx
return out
def runOne(k2id, config, returnClip=False):
"""Run the pipeline on a single target.
Inputs:
------------
k2id
(int) Epic id of target to run on.
config
(dict) Dictionary of configuration parameters as created by, e.g
loadMyConfiguration()
Returns:
---------
A clipboard containing the results.
Notes:
---------
Don't edit this function. The pipeline can recover gracefully from
errors in any individual task, but an error in this function will crash
the pipeline
"""
taskList = config['taskList']
clip = clipboard.Clipboard()
clip['config'] = config
clip['value'] = k2id
#Check that all the tasks are properly defined
print "Checking tasks exist"
for t in taskList:
f = eval(t)
#Now run them.
for t in taskList:
print "Running %s" % (t)
f = eval(t)
clip = f(clip)
gc.collect()
if returnClip:
return clip
def runOne(k2id, config):
taskList = config['taskList']
clip = clipboard.Clipboard()
clip['config'] = config
clip['value'] = k2id
#clip['dataStorePath'] = config['dataStorePath']
#Check that all the tasks are properly defined
for t in taskList:
f = eval(t)
#Now run them.
for t in taskList:
f = eval(t)
clip = f(clip)
return clip
def createConfig(sector, tic, planetNum, debugMode=True):
cfg = dict()
cfg['debug'] = debugMode
cfg['sector'] = sector
cfg['tic'] = tic
cfg['planetNum'] = planetNum
#TODO This shouldn't be hardcoded, but passed as a parameter
cfg['dvtLocalPath'] = "/home/fergal/data/tess/dvt/sector1"
#TODO Need modshift paths
cfg['lppMapFile'] = "/home/fergal/data/tess/lppmaps/combMapDR25AugustMapDV_6574.mat"
cfg['modshiftBasename'] = "/home/fergal/data/tess/daveOutput/"
# cfg['taskList'] = ['serveTask', 'lppMetricTask', 'modshiftTask']
cfg['taskList'] = ['serveTask', 'sweetTask']
clip = clipboard.Clipboard(cfg)
return clip
def dispositionTask(clip):
"""Decide whether an event is a planet candidate or not
"""
out = clipboard.Clipboard(isSignificantEvent=True, isCandidate=True, reasonForFail="None")
# CENTROID VET
minProbForFail = 0.99
centVet = {'Warning':"None"}
try:
centroids = clip['diffImgCentroids.results']
ootCol_prf, ootRow_prf = np.mean([centroids[:,0],centroids[:,4]], axis = 0), np.mean([centroids[:,1],centroids[:,5]], axis = 0)
diffCol_prf, diffRow_prf = centroids[:,2], centroids[:,3]
diffC, diffR = (ootCol_prf - diffCol_prf), (ootRow_prf - diffRow_prf)
prob, chisq = covar.computeProbabilityOfObservedOffset(diffC, diffR)
except ValueError, e:
centVet['Warning'] = "Probability not computed: %s" %(e)
prob = 0
chisq = 0
def createConfig(sector, tic, planetNum, debugMode=True):
cfg = dict()
cfg['debug'] = debugMode
cfg['sector'] = sector
cfg['tic'] = tic
cfg['planetNum'] = planetNum
cfg['value'] = tic
#TODO This shouldn't be hardcoded, but passed as a parameter
cfg['dvtLocalPath'] = "/Users/smullally/TESS/TCEs/Sector1/dvt/"
#TODO Need modshift paths
cfg['lppMapFile'] = "/Users/smullally/Code/lpptransitlikemetric/data/maps/combMapDR25AugustMapDV_6574.mat"
cfg['modshiftBasename'] = "/Users/smullally/TESS/TCEs/Sector1/dave"
cfg['taskList'] = ['serveTask', 'lppMetricTask','sweetTask']
clip = clipboard.Clipboard(cfg)
return clip
def runOne(k2id, config):
print "WARN: This function is deprecated. See main.py instead."
taskList = config['taskList']
clip = clipboard.Clipboard()
clip['config'] = config
clip['value'] = k2id
#clip['dataStorePath'] = config['dataStorePath']
#Check that all the tasks are properly defined
for t in taskList:
f = eval(t)
#Now run them.
for t in taskList:
f = eval(t)
clip = f(clip)
if 'vet' in clip.keys(
): # Jeff edits here - See if vetting has been done yet
if 'reasonForFail' in clip.vet.keys(
): # Make sure a value for reason to fail exists else program may crash
if 'ODD_EVEN_DIFF' in clip[
'vet.reasonForFail']: # If it failed due to odd-even, then
clip['bls.period'] = 2 * clip[
'bls.period'] # Double the period
taskList = """trapezoidFitTask vetTask plotTask""".split(
) # And re-fit, re-vet, and re-plot
clip['vet.fluxVet.comments'] = clip[
'vet.fluxVet.comments'] + "Re-fit at twice period due to odd/even" # Make a note we re-fit at 2*period
for t in taskList:
f = eval(t)
clip = f(clip)
print "WARN: This function is deprecated. See main.py instead."
return clip
def vetTask(clip):
print "WARN: vetTask is deprecated. Use dispostionTask instead"
snr = clip['trapFit.snr']
snrThreshold = clip['config.minSnrForDetection']
lppThreshold = clip['config.maxLppForTransit']
offsetThreshold_sigma = clip['config.minCentroidSignifForFp']
out = clipboard.Clipboard(isCandidate=True, reasonForFail="None")
if snr < snrThreshold:
out['isCandidate'] = False
out['reasonForFail'] = "SNR (%.1f) below threshold %.1f" \
%(snr, snrThreshold)
# clip['vet'] = out
# return clip
clip = lppMetricTask(clip)
if 'exception' in clip.keys():
return clip
# Tlpp = clip['lpp.TLpp']
# if Tlpp > lppThreshold:
# out['isCandidate'] = False
# out['reasonForFail'] = "TLpp (%.1f) above threshold %.1f" \
# %(Tlpp, lppThreshold)
## clip['vet'] = out
## return clip
clip = modshiftTask(clip)
if 'exception' in clip.keys():
return clip
modshift = clip['modshift']
fluxVetDict = RoboVet.roboVet(modshift)
out['fluxVet'] = fluxVetDict
assert (fluxVetDict['disp'] in ["candidate", "false positive"])
if fluxVetDict['disp'] == "false positive":
out['isCandidate'] = False
out['reasonForFail'] = fluxVetDict['comments']
# clip['vet'] = out
# return clip
clip = measureDiffImgCentroidsTask(clip)
if 'exception' in clip.keys():
return clip
centroids = clip['diffImg.centroid_timeseries']
result = cent.measureOffsetInTimeseries(centroids)
out['centroidVet'] = result
signif = result['signif']
offset = result['offset']
if signif > offsetThreshold_sigma:
out['isCandidate'] = False
out['reasonForFail'] = "Centroid offset of %.2f (%.1f sigma) detected" \
%( offset, signif)
# clip['vet'] = out
# return clip
clip['vet'] = out
#Enforce contract
clip['vet.isCandidate']
clip['vet.reasonForFail']
return clip
