DM-20163: Use PixelAreaBoundedField in fgcmcal calibration outputs

fgcm/_version.py

@@ -1,5 +1,5 @@
 from __future__ import division, absolute_import, print_function
 
-__version__ = '2.3.2'
+__version__ = '2.4.0'
 
 __version_info__ = __version__.split('.')

fgcm/fgcmConfig.py

@@ -123,6 +123,7 @@ class FgcmConfig(object):
     nCore = ConfigField(int, default=1)
     randomSeed = ConfigField(int, required=False)
     logger = ConfigField(None, required=False)
+    outputFgcmcalZpts = ConfigField(bool, default=False)
 
     brightObsGrayMax = ConfigField(float, default=0.15)
     minStarPerCCD = ConfigField(int, default=5)

fgcm/fgcmLUT.py

@@ -936,7 +936,7 @@ def computeI0(self, lnPwv, o3, lnTau, alpha, secZenith, pmb, indices):
         dSecZenith = secZenith - (self.secZenith[0] + indices[5] * self.secZenithDelta)
 
         indicesSecZenithPlus = np.array(indices[:-1])
-        indicesSecZenithPlus[5] += 1
+        indicesSecZenithPlus[5] = np.clip(indicesSecZenithPlus[5] + 1, 0, self.secZenith.size - 1)
         indicesPwvPlus = np.array(indices[:-1])
         indicesPwvPlus[1] = np.clip(indicesPwvPlus[1] + 1, 0, self.lnPwv.size-1)
 
@@ -981,7 +981,7 @@ def computeI1(self, lnPwv, o3, lnTau, alpha, secZenith, pmb, indices):
         dSecZenith = secZenith - (self.secZenith[0] + indices[5] * self.secZenithDelta)
 
         indicesSecZenithPlus = np.array(indices[:-1])
-        indicesSecZenithPlus[5] += 1
+        indicesSecZenithPlus[5] = np.clip(indicesSecZenithPlus[5] + 1, 0, self.secZenith.size - 1)
         indicesPwvPlus = np.array(indices[:-1])
         indicesPwvPlus[1] = np.clip(indicesPwvPlus[1] + 1, 0, self.lnPwv.size-1)
 

fgcm/fgcmSigmaRef.py

@@ -77,10 +77,10 @@ def computeSigmaRef(self):
         offsetRef = np.zeros(self.fgcmStars.nBands)
         sigmaRef = np.zeros(self.fgcmStars.nBands)
 
-        if goodRefStars.size < 100:
-            # Arbitrarily do 100 as the cutoff between small and large number...
+        if goodRefStars.size < 50:
+            # Arbitrarily do 50 as the cutoff between small and large number...
 
-            self.fgcmLog.info('Found %d refstars (< 100), so computing "small-number" statistics:' % (goodRefStars.size))
+            self.fgcmLog.info('Found %d refstars (< 50), so computing "small-number" statistics:' % (goodRefStars.size))
 
             for bandIndex, band in enumerate(self.fgcmStars.bands):
                 # Filter on previous bad refstars
@@ -103,7 +103,7 @@ def computeSigmaRef(self):
 
         else:
             # Large numbers
-            self.fgcmLog.debug('More than 100 reference stars, so computing "large-number" statistics.')
+            self.fgcmLog.debug('More than 50 reference stars, so computing "large-number" statistics.')
 
             # and we do 4 runs: full, blue 25%, middle 50%, red 25%
 

fgcm/fgcmStars.py

@@ -116,6 +116,8 @@ def __init__(self,fgcmConfig):
 
         self.seeingSubExposure = fgcmConfig.seeingSubExposure
 
+        self.secZenithRange = 1. / np.cos(np.radians(fgcmConfig.zenithRange))
+
         self.starsLoaded = False
 
     def loadStarsFromFits(self,fgcmPars,computeNobs=True):
@@ -426,10 +428,18 @@ def loadStars(self, fgcmPars,
         self.fgcmLog.debug('Applying sigma0Phot = %.4f to mag errs' %
                            (self.sigma0Phot))
 
+        obsMagADU = snmm.getArray(self.obsMagADUHandle)
         obsMagADUErr = snmm.getArray(self.obsMagADUErrHandle)
 
         obsFlag = snmm.getArray(self.obsFlagHandle)
-        bad, = np.where(obsMagADUErr <= 0.0)
+
+        bad, = np.where(~np.isfinite(obsMagADU))
+        obsFlag[bad] |= obsFlagDict['BAD_MAG']
+        if bad.size > 0:
+            self.fgcmLog.info('Flagging %d observations with bad magnitudes.' %
+                              (bad.size))
+
+        bad, = np.where((np.nan_to_num(obsMagADUErr) <= 0.0) | ~np.isfinite(obsMagADUErr))
         obsFlag[bad] |= obsFlagDict['BAD_ERROR']
         if (bad.size > 0):
             self.fgcmLog.info('Flagging %d observations with bad errors.' %
@@ -661,7 +671,15 @@ def loadStars(self, fgcmPars,
 
         bad,=np.where(obsFlag != 0)
         tempSecZenith[bad] = 1.0  # filler here, but these stars aren't used
-        snmm.getArray(self.obsSecZenithHandle)[:] = tempSecZenith
+        obsSecZenith = snmm.getArray(self.obsSecZenithHandle)
+        obsSecZenith[:] = tempSecZenith
+
+        # Check the airmass range
+        if ((np.min(obsSecZenith) < self.secZenithRange[0]) |
+            (np.max(obsSecZenith) > self.secZenithRange[1])):
+            raise ValueError("Input stars have a secZenith that is out of range of LUT."
+                             "Observed range is %.2f to %.2f, and LUT goes from %.2f to %.2f" % (np.min(obsSecZenith), np.max(obsSecZenith), self.secZenithRange[0], self.secZenithRange[1]))
+
         if not self.quietMode:
             self.fgcmLog.info('Computed secZenith in %.1f seconds.' %
                               (time.time() - startTime))

fgcm/fgcmSuperStarFlat.py

@@ -173,7 +173,7 @@ def computeSuperStarFlats(self, doPlots=True, doNotUseSubCCD=False, onlyObsErr=F
             # And for signaling here, we're going to set to a large value
             superStarOffset[~gd] = 100.0
 
-            # And the central parameter should be in flux or mag space depending
+            # And the central parameter should be in flux space
             self.fgcmPars.parSuperStarFlat[:, :, :, 0] = 10.**(superStarOffset / (-2.5))
 
         else:

fgcm/fgcmUtilities.py

@@ -20,10 +20,11 @@ def _pickle_method(m):
                'BAD_QUANTITY': 2**6}
 
 # Dictionary of observation flags
-obsFlagDict = {'NO_EXPOSURE':2**0,
-               'BAD_ERROR':2**1,
-               'SUPERSTAR_OUTLIER':2**2,
-               'NO_ZEROPOINT': 2**4}
+obsFlagDict = {'NO_EXPOSURE': 2**0,
+               'BAD_ERROR': 2**1,
+               'SUPERSTAR_OUTLIER': 2**2,
+               'NO_ZEROPOINT': 2**4,
+               'BAD_MAG': 2**5}
 
 # Dictionary of exposure flags
 expFlagDict = {'TOO_FEW_STARS':2**0,