def getParticleContrastFromMrc(mrcfile):
apDisplay.printMsg("Particle contrast determination is experimental")
if not os.path.isfile(mrcfile):
apDisplay.printWarning(
"Could not determine particle contrast, mrc file not found")
return None
rawimage = mrc.read(mrcfile)
boxSize = min(rawimage.shape) - 1
innerNoise = boxSize / 2 / 20 #one-twentieth the box radius
particleRadius = boxSize / 2 / 3 + 1 #one-third the box radius
outerLimit = boxSize / 2 * 0.9 # 90% of the box radius
radialData, densityData = ctftools.rotationalAverage(rawimage, full=True)
# find indices for radial values
innerNoiseIndex = numpy.searchsorted(radialData, innerNoise)
partRadIndex = numpy.searchsorted(radialData, particleRadius)
outerLimitIndex = numpy.searchsorted(radialData, outerLimit)
maxDiam = radialData[-1]
innerVal = numpy.median(densityData[innerNoiseIndex:partRadIndex])
outerVal = numpy.median(densityData[outerLimitIndex:])
#print innerMean, outerMean, mrcfile
if debug is True:
print "%d:%d and %d:%d" % (innerNoiseIndex, partRadIndex,
outerLimitIndex, densityData.shape[0])
print "inner density %.1f <> outer density %.1f" % (innerVal, outerVal)
from matplotlib import pyplot
pyplot.plot(radialData, densityData, 'ko-')
pyplot.xlabel('Pixel Radius')
pyplot.ylabel('Density')
xmin, xmax, ymin, ymax = pyplot.axis()
pyplot.axhline(y=innerVal,
xmin=innerNoise / xmax,
xmax=particleRadius / xmax,
linewidth=2,
color="blue",
linestyle='-')
#pyplot.axhline(y=innerVal, xmax=particleRadius, linewidth=2, color="cyan", linestyle='-')
#print innerVal, radialData[1], particleRadius
pyplot.axhline(y=outerVal,
xmin=outerLimit / xmax,
xmax=maxDiam / xmax,
linewidth=2,
color="orange",
linestyle='-')
#pyplot.axhline(y=outerVal, xmax=maxDiam, linewidth=2, color="orange", linestyle='-')
#print outerVal, outerLimit, maxDiam
pyplot.grid(True)
pyplot.show()
if innerVal > outerVal:
apDisplay.printMsg(
"Contrast determined as WHITE particles on black background")
return "whiteOnBlack"
else:
apDisplay.printMsg(
"Contrast determined as BLACK particles on white background")
print "BLACK on white", mrcfile
return "blackOnWhite"
def from2Dinto1D(self, fftarray):
if self.params['astig'] is False and self.ellipseParams is None:
### simple case: do a rotational average
pixelrdata, PSDarray = ctftools.rotationalAverage(fftarray, self.params['ringwidth'], full=False)
return self.removeBlackCenter(pixelrdata*self.freq, PSDarray)
if self.ellipseParams is None:
### hard case: find ellipse and do a elliptical average
blurArray = copy.deepcopy(fftarray)
for blurIter in range(2):
### each time the image is blurred more
blurArray = self.rotationBlur(blurArray, angle=1, numIter=3)
self.findEllipseEdge(blurArray)
if self.ellipseParams is None:
apDisplay.printWarning("Failed to find ellipse, continuing with no astig")
pixelrdata, PSDarray = ctftools.rotationalAverage(fftarray, self.params['ringwidth'], full=False)
return self.removeBlackCenter(pixelrdata*self.freq, PSDarray)
ellipratio = self.ellipseParams['a']/self.ellipseParams['b']
ellipangle = math.degrees(self.ellipseParams['alpha'])
pixelrdata, PSDarray = ctftools.ellipticalAverage(fftarray, ellipratio, ellipangle,
self.params['ringwidth'], full=False)
return self.removeBlackCenter(pixelrdata*self.freq, PSDarray)
def getParticleContrastFromMrc(mrcfile):
apDisplay.printMsg("Particle contrast determination is experimental")
if not os.path.isfile(mrcfile):
apDisplay.printWarning("Could not determine particle contrast, mrc file not found")
return None
rawimage = mrc.read(mrcfile)
boxSize = min(rawimage.shape)-1
innerNoise = boxSize/2/20 #one-twentieth the box radius
particleRadius = boxSize/2/3 + 1 #one-third the box radius
outerLimit = boxSize/2 * 0.9 # 90% of the box radius
radialData, densityData = ctftools.rotationalAverage(rawimage, full=True)
# find indices for radial values
innerNoiseIndex = numpy.searchsorted(radialData, innerNoise)
partRadIndex = numpy.searchsorted(radialData, particleRadius)
outerLimitIndex = numpy.searchsorted(radialData, outerLimit)
maxDiam = radialData[-1]
innerVal = numpy.median(densityData[innerNoiseIndex:partRadIndex])
outerVal = numpy.median(densityData[outerLimitIndex:])
#print innerMean, outerMean, mrcfile
if debug is True:
print "%d:%d and %d:%d"%(innerNoiseIndex, partRadIndex, outerLimitIndex, densityData.shape[0])
print "inner density %.1f <> outer density %.1f"%(innerVal, outerVal)
from matplotlib import pyplot
pyplot.plot(radialData, densityData, 'ko-')
pyplot.xlabel('Pixel Radius')
pyplot.ylabel('Density')
xmin, xmax, ymin, ymax = pyplot.axis()
pyplot.axhline(y=innerVal, xmin=innerNoise/xmax, xmax=particleRadius/xmax, linewidth=2, color="blue", linestyle='-')
#pyplot.axhline(y=innerVal, xmax=particleRadius, linewidth=2, color="cyan", linestyle='-')
#print innerVal, radialData[1], particleRadius
pyplot.axhline(y=outerVal, xmin=outerLimit/xmax, xmax=maxDiam/xmax, linewidth=2, color="orange", linestyle='-')
#pyplot.axhline(y=outerVal, xmax=maxDiam, linewidth=2, color="orange", linestyle='-')
#print outerVal, outerLimit, maxDiam
pyplot.grid(True)
pyplot.show()
if innerVal > outerVal:
apDisplay.printMsg("Contrast determined as WHITE particles on black background")
return "whiteOnBlack"
else:
apDisplay.printMsg("Contrast determined as BLACK particles on white background")
print "BLACK on white", mrcfile
return "blackOnWhite"
