kmeans_common.py File Reference

Namespaces
	kmeans_common

Functions
def	kmeans_common.get_common_int_coords_2 (x, y, z)
def	kmeans_common.get_common_int_coords (x, y, z)
def	kmeans_common.load_centroid (fn, ncluster)
def	kmeans_common.load_centroid_xyz (fn, ncluster)

Variables
float	kmeans_common.cutoff = 1.6
	kmeans_common.restype = sys.argv[1]
	kmeans_common.ncluster = int(sys.argv[2])
string	kmeans_common.inpfile = "./split/" + restype + ".dat"
	kmeans_common.inp = open(inpfile,'r')
	kmeans_common.lines = inp.readlines()
	kmeans_common.skip = int(len(lines)/10000)
list	kmeans_common.colorlist = ['r', 'b', 'g', 'y', 'c', 'm', 'k', 'w', 'r']
list	kmeans_common.marklist = ['o', '^', '+', '>', (5,2), (5,0)]
list	kmeans_common.xyzlist = []
list	kmeans_common.bblist = []
	kmeans_common.dats = line.split()
	kmeans_common.dis = float(dats[0])
	kmeans_common.ang = float(dats[1])
	kmeans_common.dih = float(dats[2])
	kmeans_common.psi = float(dats[3])
	kmeans_common.phi = float(dats[4])
	kmeans_common.x = dis*sin(ang)*cos(dih)
	kmeans_common.y = dis*sin(ang)*sin(dih)
	kmeans_common.z = dis*cos(ang)
	kmeans_common.data = vstack(xyzlist)
	cluster, find the centroid More...
	kmeans_common.save_data = data
string	kmeans_common.fn = "refine/" + restype + ".xyz"
def	kmeans_common.centroids = load_centroid_xyz(fn, ncluster)
	kmeans_common._
	kmeans_common.idx
	assign More...
	kmeans_common.dist
	kmeans_common.nd = len(data)
	kmeans_common.savend = nd
	kmeans_common.fig = plt.figure()
	kmeans_common.ax = fig.add_subplot(111, projection='3d')
float	kmeans_common.R = 2.0
list	kmeans_common.c = colorlist[i]
string	kmeans_common.m = '.'
	kmeans_common.flag = i
	kmeans_common.xs = save_data[flag, 0]
	kmeans_common.ys = save_data[flag, 1]
	kmeans_common.zs = save_data[flag, 2]
	kmeans_common.n = len(xs)
	kmeans_common.s
	kmeans_common.marker
	kmeans_common.r = sqrt(x*x+y*y+z*z)
	kmeans_common.t = arccos(z/r)
	kmeans_common.p = arctan2(y,x)
	kmeans_common.u
	kmeans_common.v
	kmeans_common.color