def getWidthAt(x, imp):
ip = imp.getProcessor()
calibration = imp.getCalibration()
height = ip.getHeight()
lastValue = 0
numberOfTimesValueChanged = 0;
startY = 0;
endY = 0
xUnscaled = int(round(calibration.getRawX(x),0))
for i in range(0, height-1):
newValue = ip.get(xUnscaled, i)
if lastValue!=newValue:
if numberOfTimesValueChanged==0:
startY = i
numberOfTimesValueChanged = numberOfTimesValueChanged + 1
endY = i
lastValue = newValue;
calibration = imp.getCalibration()
yS = calibration.getY(startY)
yE = calibration.getY(endY)
IJ.makeLine(xUnscaled, startY, xUnscaled, endY)
IJ.run("Add Selection...")
return yE-yS
def duty_cycle(i, horizontal):
IJ.open(i)
IJ.run("Enhance Contrast...", "saturated=0.3 equalize")
IJ.run("Smooth", "")
'IJ.run("Anisotropic Diffusion 2D", "number=20 smoothings=1 keep=20 a1=0.50 a2=0.90 dt=20 edge=5") # use instead of smooth for better results, slower
imp = IJ.getImage()
ImageConverter(imp).convertToGray8()
file_base = str(imp.title) # convert name into string
file_base = file_base.split('.', 1)[0] # remove all characters including and after .
sample_id = file_base.split('_', 1)[0]
height = imp.height
width = imp.width
IJ.run(imp, "Set Scale...", "distance=5000 known=1 pixel=1 unit=cm")
IJ.setTool("line")
for scan in range(1, num_scans):
row_count = 0
data=[]
data2=[]
last = 0
filename = file_base + "_" + str(scan)
if not horizontal:
IJ.makeLine(0, scan*height/num_scans, width, scan*height/num_scans) # horizontal line to measure vertical grating profile
else:
IJ.makeLine(width*scan/num_scans, 9*height/10, width*scan/num_scans, 0) # vertical line to measure horizontal grating profile
IJ.run(imp, "Plot Profile", "")
imp_plot = IJ.getImage()
IJ.run(imp, "Find Peaks", setting) # nw07 params: min._peak_amplitude=60 min._peak_distance=0 min._value=100 max._value=0 exclude list
IJ.saveAs("Results", csvpath + filename + "_raw.csv")
imp_plot.close()
imp_plot = IJ.getImage()
IJ.saveAs("Png", csvpath + "Peaks in Plot of " + filename + ".png")
imp_plot.close()
IJ.selectWindow(filename + "_raw.csv")
IJ.run("Close")
with open(csvpath + filename + "_raw.csv", "rb") as fin, open(csvpath + filename + "_peaks.csv", "wb") as fout:
writer = csv.writer(fout)
for row in csv.reader(fin):
if not row[2] == '':
writer.writerow(row)
with open(csvpath + filename + "_peaks.csv", "rb") as File:
reader = csv.reader(File)
for row in reader:
row_count += 1
if row_count == 1:
continue
data.append(tuple(row)) # Append all non-header rows into a list of data as a tuple of cells
for row in sort_table(data, 2):
data2.append(tuple(row))
if len(data2) < 3:
IJ.log(filename + " no peaks detected, skipping...")
continue
else:
peaks = len(data2)
last = data2[0]
last = last[2]
row_count = 0
diff = 0
colG = []
blank = ""
duty = zip(*data2)
for row in data2:
row_count += 1
if row_count == 1:
continue
else:
print row[2]
print last
diff = float(row[2]) - float(last)
colG.append(diff)
last = row[2]
a, b = colG[::2], colG[1::2]
avga = sum(a)/len(a)
avgb = sum(b)/len(b)
a_len_dev = len(a) - 1
b_len_dev = len(b) - 1
if b_len_dev > 1:
a_stdev = sqrt(sum((x - avga)**2 for x in a) / a_len_dev)
b_stdev = sqrt(sum((x - avgb)**2 for x in b) / b_len_dev)
else:
a_stdev = 1
b_stdev = 1
duty_cyc = avga/(avga+avgb)
perc = duty_cyc*100
invperc = 100 - perc
inv_duty = 1 - duty_cyc
duty_max = max(duty_cyc, inv_duty)
duty_min = min(duty_cyc, inv_duty)
percs = round(perc)
percs = int(percs)
percs = str(percs)
invpercs = round(invperc)
invpercs = int(invpercs)
invpercs = str(invpercs)
colG.insert(0, blank)
a.insert(0, blank)
b.insert(0, blank)
b.insert(1, blank)
i = 0
while i < len(a):
i += 2
a.insert(i, blank)
i = 1
while i < len(b):
i += 2
b.insert(i, blank)
duty.append(colG)
duty.append(a)
duty.append(b)
duty = zip(*duty)
result = [sample_id, file_base, scan, duty_cyc, inv_duty, a_stdev, b_stdev, peaks, duty_max, duty_min]
header = ["X0", "Y0", "X1", "Y1", "X2", "Y2", "diff", "a", "b"]
results.append(result)
with open(csvpath + filename + "_duty.csv", 'wb') as myfile:
wr = csv.writer(myfile, delimiter=',', quotechar='|', quoting=csv.QUOTE_MINIMAL)
wr.writerow(header)
wr.writerows(duty)
print(filename + " duty cycle is " + percs + "/" + invpercs + "%.")
IJ.log(filename + " duty cycle is " + percs + "/" + invpercs + "% (" + str(peaks) + " peaks found)")
with open(csvpath + "results.csv", 'wb') as myfile:
wr = csv.writer(myfile, delimiter=',', quotechar='|', quoting=csv.QUOTE_MINIMAL)
wr.writerows(results) # Write the result data from all images into a single csv file
IJ.log("Results for " + path.basename(stackpath) + ":")
IJ.log("Average intensity: " + str(average(means)))
IJ.log("Standard deviation: " + str(stdev(means)))
# now, use the subtracted image to output the flat field image and plot
# get the plot out of the way to bring back the stack
WM.putBehind()
#average all frames
IJ.run("Z Project...", "projection=[Average Intensity]")
# plot the diagonal profile
imp = IJ.getImage()
IJ.run("Line Width...", "line=3")
IJ.makeLine(0, 0, imp.width, imp.height)
IJ.run("Plot Profile")
# bring back the projection, run Measure to get max and min
WM.putBehind()
IJ.run("Measure") #this method reports the actual max and min, not averaged across 3 px...
rt = ResultsTable.getResultsTable()
max = rt.getValue("Max", 0)
min = rt.getValue("Min", 0)
rolloff = (min*1.0/max)*100
IJ.run("Fire")
IJ.log("Percent illumination roll-off: " + str(rolloff))
# close the annoying results window
IJ.run("Colors...","foreground=cyan background=cyan selection=yellow")
colDim = theImage.getWidth() / (xtiles)
rowDim = theImage.getHeight() / (ytiles)
rowStarts = range(rowDim,theImage.getHeight()-xtiles,rowDim)
colStarts = range(colDim,theImage.getWidth()-ytiles,colDim)
rowCenters = list(rowStarts)
rowCenters.insert(0,0)
colCenters = list(colStarts)
colCenters.insert(0,0)
for i in range(0,len(rowCenters)):
rowCenters[i] = rowCenters[i] + rowDim - rowDim/8
for i in range(0,len(colCenters)):
colCenters[i] = colCenters[i] + colDim/2
for i in rowStarts:
IJ.makeLine(0,i,theImage.getWidth(),i)
IJ.run("Draw","stack")
for i in colStarts:
IJ.makeLine(i,0,i,theImage.getHeight())
IJ.run("Draw","stack")
numSlices = theImage.getNSlices() * theImage.getNChannels() * theImage.getNFrames()
for zslice in range(1,numSlices+1):
theImage.setSliceWithoutUpdate(zslice)
ip = theImage.getProcessor()
ip.setColor(255*255)
for i in range(0,len(colCenters)):
for j in range(0,len(rowCenters)):
theString = str(int(j*xtiles+i+1))
ip.drawString(theString,int(colCenters[i]),int(rowCenters[j]))
theImage.updateAndDraw()
def makeLine(x1, y1, x2, y2):
IJ.makeLine(x1, y1, x2, y2)
def batch_open_images(pathImage, file_typeImage, name_filterImage=None):
if isinstance(pathImage, File):
pathImage = pathImage.getAbsolutePath()
def check_filter(string):
'''This function is used to check for a given filter.
It is possible to use a single string or a list/tuple of strings as filter.
This function can access the variables of the surrounding function.
:param string: The filename to perform the filtering on.
'''
if name_filterImage:
# The first branch is used if name_filter is a list or a tuple.
if isinstance(name_filterImage, (list, tuple)):
for name_filter_ in name_filterImage:
if name_filter_ in string:
# Exit the function with True.
return True
else:
# Next iteration of the for loop.
continue
# The second branch is used if name_filter is a string.
elif isinstance(name_filterImage, string):
if name_filterImage in string:
return True
else:
return False
return False
else:
# Accept all files if name_filter is None.
return True
def check_type(string):
'''This function is used to check the file type.
It is possible to use a single string or a list/tuple of strings as filter.
This function can access the variables of the surrounding function.
:param string: The filename to perform the check on.
'''
if file_typeImage:
# The first branch is used if file_type is a list or a tuple.
if isinstance(file_typeImage, (list, tuple)):
for file_type_ in file_typeImage:
if string.endswith(file_type_):
# Exit the function with True.
return True
else:
# Next iteration of the for loop.
continue
# The second branch is used if file_type is a string.
elif isinstance(file_typeImage, string):
if string.endswith(file_typeImage):
return True
else:
return False
return False
# Accept all files if file_type is None.
else:
return True
# We collect all files to open in a list.
path_to_Image = []
# Replacing some abbreviations (e.g. $HOME on Linux).
path = os.path.expanduser(pathImage)
path = os.path.expandvars(pathImage)
# If we don't want a recursive search, we can use os.listdir().
for directory, dir_names, file_names in os.walk(pathImage):
# We are only interested in files.
for file_name in file_names:
# The list contains only the file names.
# The full path needs to be reconstructed.
full_path = os.path.join(directory, file_name)
# Both checks are performed to filter the files.
if check_type(file_name):
if check_filter(file_name) is False:
# Add the file to the list of images to open.
path_to_Image.append([
full_path,
os.path.basename(os.path.splitext(full_path)[0])
])
Images = []
for img_path, file_name in path_to_Image:
imp = IJ.openImage(img_path)
maskimage = ops.run("create.img", imp)
cursor = maskimage.localizingCursor()
imp.show()
IJ.run("Select None")
overlay = imp.getOverlay()
if overlay == None:
overlay = Overlay()
imp.setOverlay(overlay)
else:
overlay.clear()
imp.updateAndDraw()
impY = imp.getHeight()
impX = imp.getWidth()
print(impY, impX)
rm = RoiManager.getInstance()
if not rm:
rm = RoiManager()
rm.runCommand("reset")
WaitForUserDialog("Select the landmark and the second point").show()
rm.runCommand("Add")
roi_points = rm.getRoisAsArray()
for Roi in roi_points:
xpoints = Roi.getPolygon().xpoints
ypoints = Roi.getPolygon().ypoints
print(xpoints, ypoints)
print('Start Landmark', xpoints[0], ypoints[0])
fixedpointX = xpoints[0]
fixedpointY = ypoints[0]
print('End Landmark', xpoints[1], ypoints[1])
IJ.makeLine(xpoints[0], ypoints[0], xpoints[1], ypoints[1])
gui = GenericDialog("Rotation Angle")
gui.addNumericField("Choose Angle", 15, 0)
gui.showDialog()
if gui.wasOKed():
rotateangle = gui.getNextNumber()
IJ.run("Rotate...", "angle=" + str(int(float(rotateangle))))
rm.runCommand("reset")
overlay = imp.getOverlay()
rm.runCommand("Add")
roi_points = rm.getRoisAsArray()
for Roi in roi_points:
xpoints = Roi.getPolygon().xpoints
ypoints = Roi.getPolygon().ypoints
print(xpoints, ypoints)
print('Rotated Start Landmark', xpoints[0], ypoints[0])
print('Rotated End Landmark', xpoints[1], ypoints[1])
slope = (ypoints[1] - ypoints[0]) / (xpoints[1] - xpoints[0] + 1.0E-20)
intercept = fixedpointY - slope * fixedpointX
print(fixedpointX, fixedpointY)
print('Slope', slope, 'Intercept', intercept)
XwY0 = -intercept / slope
YxwY0 = slope * XwY0 + intercept
XwYmax = (impY - intercept) / slope
YxwYmax = slope * XwYmax + intercept
YwX0 = intercept
XywX0 = (YwX0 - intercept) / slope
YwXmax = impX * slope + intercept
XxwXmax = (YwXmax - intercept) / slope
rm.runCommand("reset")
if XwY0 > 0:
lineROIA = Line(fixedpointX, fixedpointY, XwY0, YxwY0)
lineROIB = Line(fixedpointX, fixedpointY, XwYmax, YxwYmax)
overlay.add(lineROIA)
overlay.add(lineROIB)
if XwY0 < 0:
lineROIA = Line(fixedpointX, fixedpointY, XywX0, YwX0)
lineROIB = Line(fixedpointX, fixedpointY, XxwXmax, YwXmax)
overlay.add(lineROIA)
overlay.add(lineROIB)
while cursor.hasNext():
cursor.fwd()
X = cursor.getDoublePosition(0)
Y = cursor.getDoublePosition(1)
if abs(Y - slope * X - intercept) <= 4:
cursor.get().set(0)
else:
cursor.get().set(1)
labeling = ops.labeling().cca(maskimage,
StructuringElement.EIGHT_CONNECTED)
# get the index image (each object will have a unique gray level)
labelingIndex = labeling.getIndexImg()
dataImg = ds.create(labelingIndex)
location = ls.resolve(
str(savedir) + '/' + file_name + '.' + file_type_image)
dio.save(dataImg, location)
imp.close()
from ij import IJ
from ij.plugin.frame import RoiManager
RM = RoiManager()
rm = RM.getRoiManager()
with open(
"C:/Users/emlh1n13/Downloads/Coronary Sinus/Case2_View2_F15/ROIs.csv",
"r") as roiFile:
next(roiFile) # skip header
for line in roiFile:
elements = line.rstrip().split(',')
x, y, w, h = elements[4], elements[5], elements[6], elements[7]
x1 = int(x)
y1 = int(y)
x2 = x1 + int(w)
y2 = y1 + int(h)
roi = IJ.makeLine(x1, y1, x2, y2)
rm.addRoi(roi)
gd.addCheckbox("First segment is injury?",injuryfirst)
gd.showDialog()
if (gd.wasOKed()):
roi = theImage.getRoi()
if roi is None:
IJ.error("No ROI selected")
else:
polygon = roi.getFloatPolygon()
# if len(polygon.xpoints) % 2 == 0 and is_monotonic_increasing(polygon.ypoints):
if is_monotonic_increasing(polygon.ypoints):
xset = average(polygon.xpoints)
IJ.setForegroundColor(255,255,0)
IJ.run("Draw","stack")
IJ.makeLine(xset,0,xset,theImage.getHeight())
IJ.setForegroundColor(0,255,255)
IJ.run("Draw","stack")
injuryfirst = gd.getNextBoolean()
if injuryfirst:
countidx = range(0,len(polygon.xpoints)-1,2)
else:
countidx = range(1,len(polygon.xpoints)-1,2)
injuryLength = 0.0
for idx in countidx:
injuryLength = injuryLength + (polygon.ypoints[idx+1]-polygon.ypoints[idx])
totalLength = polygon.ypoints[-1]-polygon.ypoints[0]
injuryRatio = injuryLength / totalLength
