imp.setRoi(roi)
# Now, iterate each peak, defining a small interval centered at each peak,
# and measure the sum of total pixel intensity,
# and display the results in an ImageJ ResultTable.
table = ResultsTable()
for peak in peaks:
# Read peak coordinates into an array of integers
peak.localize(p)
# Define limits of the interval around the peak:
# (sigmaSmaller is half the radius of the embryo)
minC = [p[i] - sigmaSmaller for i in range(img.numDimensions())]
maxC = [p[i] + sigmaSmaller for i in range(img.numDimensions())]
# View the interval around the peak, as a flat iterable (like an array)
fov = Views.flatIterable(Views.interval(img, minC, maxC))
# Compute sum of pixel intensity values of the interval
# (The t is the Type that mediates access to the pixels, via its get* methods)
s = sum(t.getInteger() for t in fov)
# Add to results table
table.incrementCounter()
table.addValue("x", p[0])
table.addValue("y", p[1])
table.addValue("sum", s)
table.show("Embryo intensities at peaks")
from operator import add
import csv
# The minumum and maximum coordinates, for each image dimension,
imp.setRoi(roi)
# Now, iterate each peak, defining a small interval centered at each peak,
# and measure the sum of total pixel intensity,
# and display the results in an ImageJ ResultTable.
table = ResultsTable()
for peak in peaks:
# Read peak coordinates into an array of integers
peak.localize(p)
# Define limits of the interval around the peak:
# (sigmaSmaller is half the radius of the embryo)
minC = [int(p[i] - sigmaSmaller) for i in xrange(img.numDimensions())]
maxC = [int(p[i] + sigmaSmaller) for i in xrange(img.numDimensions())]
# View the interval around the peak, as a flat iterable (like an array)
square = Views.flatIterable(Views.zeroMin(Views.interval(img, minC, maxC)))
s1 = sum(t.getInteger() for t in square)
area1 = Intervals.numElements(square)
# Use a sphere instead
radius = sqrt(area1 / pi) # same area for both
print sigmaSmaller, radius
circle = Masks.toIterableRegion(GeomMasks.closedSphere(p, radius))
s2 = sum(t.getInteger() for t in Regions.sample(circle, imgE))
area2 = Intervals.numElements(circle)
print area1, area2
# Compute sum of pixel intensity values of the interval
# (The t is the Type that mediates access to the pixels, via its get* methods)
# Add to results table
