for filename, row, row_value in all_ydata:
table.set(filename, row, row_value)
uiservice.show("MergedFiles_%s" % data_identifier, table)
log("Retrieving statistics for merged Y-data...")
list_of_rows = defaultdict(list)
for data in all_ydata:
list_of_rows[data[1]].append(data[2])
row_stats = {}
for row_key, row_values in list_of_rows.iteritems():
row_stats[row_key] = (mean(row_values), stdev(row_values), len(row_values))
table = newtable(xcolumn_header, xvalues)
for key, value in row_stats.iteritems():
table.set("Mean", int(key), value[0])
table.set("StdDev", int(key), value[1])
table.set("N", int(key), value[2])
uiservice.show("Stats_%s" % data_identifier, table)
plot = Plot("Mean Sholl Plot [%s]" % ycolumn_header, xcolumn_header, "N. of intersections")
plot.setLegend("Mean"+ u'\u00B1' +"SD", Plot.LEGEND_TRANSPARENT + Plot.AUTO_POSITION)
plot.setColor("cyan", "blue")
plot.addPoints(table.get(0), table.get(1), table.get(2), Plot.CONNECTED_CIRCLES, data_identifier)
plot.show()
log("Parsing concluded.")
main()
row=[ str(p[i]) for p in profiles ]
row=",".join(row)
f.write(row+"\n")
# Generate a plot
if doPlot:
from ij.gui import Plot
from java.awt import Color
p = Plot('Profiles','Channel #','Intensity')
p.setSize(640,480)
maxP = len(profiles)
maxV = 0
for iprofile,profile in enumerate(profiles):
h = 0.66-(float(iprofile)/maxP)
if h<0:
h=h+1
p.setColor(Color.getHSBColor( h,.8,1))
p.addPoints(range(len(profile)),profile,p.LINE)
maxV_=max(profile)
if maxV < maxV_:
maxV = maxV_
p.setLimits(0,len(profile)-1,0,maxV*1.2)
p.setLegend("\n".join(names),p.TOP_LEFT|p.LEGEND_TRANSPARENT)
p.show()
# Save the plot as PNG
if doSavePlot:
imp = p.getImagePlus()
IJ.saveAs(imp,'PNG',file.absolutePath + "_compensationPlot.png")