def getXY(image):
image.setC(2)
pp = ProfilePlot(image).getPlot()
pw = PlotWindow(image, pp)
x, y = pw.getXValues(), pw.getYValues()
# convert to java double for use in CurveFitter() class
xd = [Double(i) for i in x]
yd = [Double(i) for i in y]
return xd, yd
def get_profile(imp, roi, rm):
'''
Iteratively get the profile of each roi in a list from give img.
returns ProfilePlots.
'''
i = rm.getCount()
rm.add(roi, i)
roi.setName("{0}_{1}".format(imp.getTitle(), i))
rm.select(imp, i)
pp = ProfilePlot(imp)
return pp.getProfile()
def get_profile(imp, roi, rm):
'''
Gets the profile plot of a roi from a given img.
returns a list containing the measured intensities on each pixel.
'''
from ij.gui import ProfilePlot
i = rm.getCount()
rm.add(roi, i)
roi.setName("{0}_{1}".format(imp.getTitle(), i))
rm.select(imp, i)
pp = ProfilePlot(imp)
return pp.getProfile()
def saveProfile(nch,
top,
bottom,
staining,
genotype,
staining_dir,
image_name,
cd=min_cd,
cd_no=0,
all_slices=False):
if all_slices == True:
temp_imp = IJ.getImage()
top = temp_imp.NSlices
bottom = 1
for j in range(bottom, top + 1):
imp1 = IJ.getImage()
imp1.setC(nch)
imp1.setZ(j)
pp1 = ProfilePlot(imp1)
s = "profile" + str(j)
exec(s + " = pp1.getProfile()")
file_name = image_name[:(
image_name.rfind('.tif'))] + "_" + staining + ".csv"
file_save = staining_dir + file_name
if cd == 1:
with open(file_save, "w") as text_file:
text_file.write("cd,cd_type,x,value")
# text_file.close()
with open(file_save, "a") as text_file:
for j in range(len(eval("profile" + str(top)))):
# print([profile1[j], profile2[j] ], max([profile1[j], profile2[j] ]))
x = list()
for k in range(bottom, top + 1):
x.append(eval("profile" + str(k) + "[j]"))
#print(x)
if intensity_to_process == "max":
text_file.write("\n" + str(cd) + "," + str(cd_no) + "," +
str(j) + "," + str(max(x)))
#print(len(x))
else:
#print(int(len(x)))
total = 0
for element in x:
total = total + eval(element)
text_file.write("\n" + str(cd) + "," + str(cd_no) + "," +
str(j) + "," + str(total / len(x)))
def fit_gauss(lroi, imp, p, peak_id, id_, type_, rm):
lroi.setName("{}_{}_{}".format(str(id_), peak_id, type_))
imp.setRoi(lroi)
rm.addRoi(lroi)
prof = ProfilePlot(imp)
y = prof.getProfile()
x = xrange(len(y))
fitter = CurveFitter(x, y)
fitter.doFit(CurveFitter.GAUSSIAN)
param_values = fitter.getParams()
std = param_values[3]
fwhm = 2.3548 * std
r2 = fitter.getFitGoodness()
y_ = [fitter.f(x_) for x_ in x]
area_profile = sum(y) - len(y) *min(y)
area_gauss = sum(y_) - len(y_)*min(y_)
output = {}
output["x_pos"] = p.x
output["y_pos"] = p.y
output["fwhm"] = fwhm
output["fwhm_nm"] = pixel_size_nm * fwhm
output["r2_GoF"] = r2
output["id"] = id_
output["peak_id"] = peak_id
output["type"] = type_
# yai, excel maagic :-)
output["avg_fwhm"] = '=AVERAGEIFS(F:F,B:B,B{},F:F,"<>"&"")'.format(id_+2)
output["area_profile"] = area_profile
output["area_gauss"] = area_gauss
if peak_id == DEBUG:
plot = Plot("ROI peak {} type {}".format(peak_id, type_), "X (gray)", "Y (fit window)")
plot.setLineWidth(2)
plot.setColor(Color.RED)
plot.addPoints(x, y, Plot.LINE)
plot.setColor(Color.BLUE)
plot.addPoints(x, y_, Plot.LINE)
plot.show()
return output
# using a default generic RealType converter via t.setReal(t.getRealDouble())
compute(op).into(blurred, None, FloatType(), None)
# Show the blurred image with the same LUT as the original
imp2 = IL.wrap(blurred, "integral image radius 5 blur")
imp2.getProcessor().setLut(imp.getProcessor().getLut())
imp2.show()
# Compare with Gaussian blur
from ij import ImagePlus
from ij.plugin.filter import GaussianBlur
from ij.gui import Line, ProfilePlot
# Gaussian of the original image
imp_gauss = ImagePlus(imp.getTitle() + " Gauss",
imp.getProcessor().duplicate())
GaussianBlur().blurGaussian(imp_gauss.getProcessor(), radius)
imp_gauss.show()
# Plot values from a diagonal from bottom left to top right
line = Line(imp.getWidth() - 1, 0, 0, imp.getHeight() - 1)
imp_gauss.setRoi(line)
pp1 = ProfilePlot(imp_gauss)
plot = pp1.getPlot()
imp2.setRoi(line)
pp2 = ProfilePlot(imp2)
profile2 = pp2.getProfile() # double[]
plot.setColor("red")
plot.add("line", range(len(profile2)), profile2)
plot.show()
