MJD = windows.time.mjd """ Display the status of the reduction so far """ statusString = "\r%s MJD: %5.7f Frame: [%d/%d]"%(timeLeftString, MJD, trueFrameNumber, frameRange) sys.stdout.write(statusString) sys.stdout.flush() for windowIndex, w in enumerate(windows): image = w._data allWindows[windowIndex].setData(image) if arg.preview: fullFrame = numpy.zeros((fullFrameysize, fullFramexsize)) for w in allWindows: boostedImage = ultracamutils.percentiles(w.data, 20, 99) xll = w.xll/w.xbin - xmin xsize = w.nx yll = w.yll/w.ybin - ymin ysize = w.ny fullFrame[yll:yll+ysize, xll:xll+xsize] = fullFrame[yll:yll+ysize, xll:xll+xsize] + boostedImage matplotlib.pyplot.imshow(fullFrame, cmap='gray_r') for a in apertures: (x, y) = a.position matplotlib.pyplot.gca().add_artist(matplotlib.pyplot.Circle((x,y), a.radius, color='green', fill=False, linewidth=1.0)) matplotlib.pyplot.gca().add_artist(matplotlib.pyplot.Circle((x,y), a.skyInnerRadius, color='blue', fill=False, linewidth=1.0)) matplotlib.pyplot.gca().add_artist(matplotlib.pyplot.Circle((x,y), a.skyOuterRadius, color='blue', fill=False, linewidth=1.0))
sys.stdout.write(statusString) sys.stdout.flush() windows = ccdFrame[0] for windowIndex, w in enumerate(windows): image = w._data allWindows[windowIndex].setData(image) if arg.preview: ppgplot.pgslct(bitmapView['pgplotHandle']) ppgplot.pgbbuf() fullFrame = numpy.zeros((fullFrameysize, fullFramexsize)) for w in allWindows: if (arg.stack): boostedImage = ultracamutils.percentiles(w.stackedData, 20, 99) else: boostedImage = ultracamutils.percentiles(w.data, 20, 99) xll = w.xll/w.xbin - xmin xsize = w.nx yll = w.yll/w.ybin - ymin ysize = w.ny fullFrame[yll:yll+ysize, xll:xll+xsize] = fullFrame[yll:yll+ysize, xll:xll+xsize] + boostedImage rows, cols = numpy.shape(fullFrame) # Draw the grayscale bitmap ppgplot.pggray(fullFrame, 0, cols-1 , 0, rows-1 , 0, 255, pgPlotTransform) # Draw the full reference aperture list ppgplot.pgsci(3)
xll = frameInfo.getWindow(j).xll yll = frameInfo.getWindow(j).yll xsize = frameInfo.getWindow(j).xsize ysize = frameInfo.getWindow(j).ysize #print "windowImage.shape:", windowImage.shape #print "assembledChannelFrame.shape:", assembledChannelFrame.shape leftPixel = xll-1 rightPixel = xll-1+xsize bottomPixel = yll-1 topPixel = yll-1+ysize #print "leftPixel", leftPixel #print "rightPixel", rightPixel #print "bottomPixel", bottomPixel #print "topPixel", topPixel assembledChannelFrame[leftPixel:rightPixel, bottomPixel:topPixel] = assembledChannelFrame[leftPixel:rightPixel, bottomPixel:topPixel] + ultracamutils.percentiles(windowImage, 20, 98) #stackedFrame[xll:xll+xsize, yll:yll+ysize] = stackedFrame[xll:xll+xsize, yll:yll+ysize] + windowImage for o in newObjectsinWindow: (windowX, windowY) = ( o['y'], o['x'] ) (absoluteX, absoluteY) = (windowX + xll - 1, windowY + yll - 1) o['absX'] = absoluteX o['absY'] = absoluteY newObjects.append(o) if len(newObjects)>0: updateCatalog(wholeFrame['MJD'], frameIndex, newObjects) frameData.setObjectCount(channel, len(newObjects)) allObjects[channel] = masterObjectList
ccdFrame = rdat()
frameWindows = ccdFrame[0]
for windowIndex, w in enumerate(frameWindows):
image = w._data
allWindows[windowIndex].addData(image)
# Reconstruct a full frame from the windows
if (arg.keyimages):
stackedFigure = matplotlib.pyplot.figure(figsize=(10, 10))
matplotlib.pyplot.title("Initial 10 frame stacked image")
boostedFullFrame = numpy.zeros((fullFrameysize, fullFramexsize))
fullFrame = numpy.zeros((fullFrameysize, fullFramexsize))
for w in allWindows:
boostedImage = ultracamutils.percentiles(w.stackedData, 10, 99.8)
image = w.stackedData
xll = w.xll/w.xbin - xmin
xsize = w.nx
yll = w.yll/w.ybin - ymin
ysize = w.ny
boostedFullFrame[yll:yll+ysize, xll:xll+xsize] = fullFrame[yll:yll+ysize, xll:xll+xsize] + boostedImage
fullFrame[yll:yll+ysize, xll:xll+xsize] = fullFrame[yll:yll+ysize, xll:xll+xsize] + image
bkg_sigma = 1.48 * mad(image)
sources = daofind(image, fwhm=4.0, threshold=3*bkg_sigma)
w.setSourcesAvoidBorders(sources)
# Get the source list from this image
# Combine the sources from all of the windows
tmpFilename = ultracamutils.createFITS(trueFrameNumber, j, channel, windowImage) catFilename = ultracamutils.runSex(tmpFilename) newObjectsinWindow = ultracamutils.readSexObjects(catFilename) newObjectsinWindow = ultracamutils.rejectBadObjects(newObjectsinWindow) if config.KEEP_TMP_FILES!="1": ultracamutils.removeTMPFile(tmpFilename) ultracamutils.removeTMPFile(catFilename) xll = frameInfo.getWindow(j).xll yll = frameInfo.getWindow(j).yll xsize = frameInfo.getWindow(j).xsize ysize = frameInfo.getWindow(j).ysize assembledChannelFrame[xll:xll+xsize, yll:yll+ysize] = assembledChannelFrame[xll:xll+xsize, yll:yll+ysize] + ultracamutils.percentiles(windowImage, 20, 98) assembledChannelFrameUnequalised[xll:xll+xsize, yll:yll+ysize] = assembledChannelFrameUnequalised[xll:xll+xsize, yll:yll+ysize] + windowImage #stackedFrame[xll:xll+xsize, yll:yll+ysize] = stackedFrame[xll:xll+xsize, yll:yll+ysize] + windowImage for o in newObjectsinWindow: (windowX, windowY) = ( o['y'], o['x'] ) (absoluteX, absoluteY) = (windowX + xll - 1, windowY + yll - 1) o['absX'] = absoluteX o['absY'] = absoluteY newObjects.append(o) if len(newObjects)>0: updateCatalog(wholeFrame['MJD'], frameIndex, newObjects) allObjects[channel] = masterObjectList channelTempCatalogs[channel] = prevCatalog
yll = w.yll/w.ybin - ymin sources = w.getSources() newSources = [(x + xll, y + yll, flux) for (x, y, flux) in sources] allSources+=newSources sourceMap.updateMap(allSources) print allSources sortedSources = sorted(allSources, key= lambda tup: tup[2], reverse=True) for s in sortedSources: print s[2]," : ", s[0], s[1] if arg.preview: fullFrame = numpy.zeros((fullFrameysize, fullFramexsize)) for w in allWindows: if (arg.stack): boostedImage = ultracamutils.percentiles(w.stackedData, 20, 99) else: boostedImage = ultracamutils.percentiles(w.data, 20, 99) xll = w.xll/w.xbin - xmin xsize = w.nx yll = w.yll/w.ybin - ymin ysize = w.ny fullFrame[yll:yll+ysize, xll:xll+xsize] = fullFrame[yll:yll+ysize, xll:xll+xsize] + boostedImage matplotlib.pyplot.imshow(fullFrame, cmap='gray') for s in allSources: (x, y) = s matplotlib.pyplot.gca().add_artist(matplotlib.pyplot.Circle((x,y), 15, color='green', fill=False, linewidth=2.0))
imageData = hdulist[0].data
hdulist.close()
if arg.testimage:
imageData = matplotlib.pyplot.imread("/Users/rashley/code/utils/lena.png")
print imageData
maximumValue = numpy.max(imageData)
minimumValue = numpy.min(imageData)
fullRange = maximumValue - minimumValue
imageData = imageData/ fullRange * 255.0
print imageData
originalFigure = matplotlib.pyplot.figure(figsize=(10, 10))
matplotlib.pyplot.title("Original image")
boostedImageData = ultracamutils.percentiles(imageData, 10, 99.8)
imagePlot = matplotlib.pyplot.imshow(boostedImageData, cmap='gray')
#matplotlib.pyplot.gca().invert_yaxis()
matplotlib.pyplot.show(block=False)
freqData = fftpack.fft2(imageData)
transformFigure = matplotlib.pyplot.figure(figsize=(10, 10))
matplotlib.pyplot.title("FFT image")
magnitudes = numpy.absolute(freqData)
"""print freqData
print magnitudes
maximumValue = numpy.max(magnitudes)