Nanodot spacing analysis

nanodots.py

import httplib, urllib, marshal
from math import floor

def getVal(table, i):
    x = table.getValue('X', i)
    y = table.getValue('Y', i)
    return [x, y]

def draw_triangles(imp, triangles):
    ip = imp.getProcessor()
    for tri in triangles:
    	ip.drawLine(int(tri[0]),
                    int(tri[1]),
                    int(tri[2]),
                    int(tri[3]))

# Use a remote server for calculating Delaunay triangulation
def delaunay(coords):
    headers = {"Content-type": "application/x-www-form-urlencoded", "Accept": "text/plain"}
    params = urllib.urlencode({'data': coords, 'json': 0})

    host = "groveslab.cchem.berkeley.edu:3000"
#    host = "localhost:3000"
    conn = httplib.HTTPConnection(host)
    print "connected"

    conn.request("POST", "/programming/delaunay", params, headers)
    r = conn.getresponse()

    # print r1.status, r1.reason
    result = r.read()
    ls = result.split("\n")
    vs = [map(float,l.split(",")) for l in ls]

    conn.close()
    return vs



# imp is a thresholded image (binary image).
def find_dots(imp):
    IJ.run(imp, "Set Measurements...", "  centroid redirect=None decimal=2")
    IJ.run(imp, "Analyze Particles...", "size=20-Infinity circularity=0.00-1.00 show=Ellipses display clear")

    # Get a Results table. This content can be shown from Window -> Results
    table = ResultsTable.getResultsTable()

    # Get the number of rows.
    n = table.getCounter()

    # Call getVal to get every (x,y) coordinate.
    return [getVal(table, i) for i in range(0, n)]


def main():
#    path = "/Volumes/Macintosh HD/Dropbox/Groves Lab Data/SEM/130712 EML/20 80k.tiff"
    imp = IJ.getImage()
    th_imp = threshold(imp)
    coords = find_dots(th_imp)
    imp_ps = IJ.getImage()
    triangles = delaunay(coords)
    # print triangles
    draw_triangles(imp_ps,triangles)

    # Show an original image and a thresholded image.
    imp_ps.repaintWindow()
    # th_imp.show()
    print "Done"



def threshold(imp):
    imp2 = imp.duplicate()
    ip2 = imp2.getProcessor()
    IJ.run(imp2, "Auto Threshold", "method=RenyiEntropy white")
    IJ.run(imp2, "Convert to Mask", "")
    return imp2

main()