import numpy as np
from scipy import stats
import matplotlib
import matplotlib.pylab as plt
from pylab import *
from pyutils import readfile, column
if (len(sys.argv) > 1):
dir = sys.argv[1]
else:
print "Need 1 arguments: directory"
x, nx = readfile(dir + "/xgrid.dat")
y, ny = readfile(dir + "/ygrid.dat")
x = column(x, 0)
y = column(y, 0)
fig = plt.figure(figsize=(4, 4))
ax = fig.add_axes([0.05, 0.05, 0.9, 0.9])
ax.set_xticks(x)
ax.set_yticks(y)
ax.set_xticklabels([])
ax.set_yticklabels([])
grid(True)
ticklines = ax.get_xticklines()
ticklines.extend(ax.get_yticklines())
gridlines = ax.get_xgridlines()
gridlines.extend(ax.get_ygridlines())
ticklabels = ax.get_xticklabels()
ticklabels.extend(ax.get_yticklabels())
import matplotlib.pyplot as plt
import matplotlib.tri as tri
from matplotlib.lines import Line2D
import numpy as np
import math
from pyutils import readfile, column, checkPtInside
def trArea(x, y):
return (abs(x[0] * (y[1] - y[2]) + x[1] * (y[2] - y[0]) + x[2] *
(y[0] - y[1])) / 2.0)
xyc, nl = readfile('data/cali.dat')
xc = np.array(column(xyc, 0))
yc = np.array(column(xyc, 1))
xy, nl = readfile('data/cali_cvt_4096.dat')
x = np.array(column(xy, 0))
y = np.array(column(xy, 1))
# Create the Triangulation; no triangles so Delaunay triangulation created.
triang = tri.Triangulation(x, y)
# Mask off unwanted triangles.
xmid = x[triang.triangles].mean(axis=1)
ymid = y[triang.triangles].mean(axis=1)
mask = checkPtInside(xc, yc, xmid, ymid)
triang.set_mask(mask)
nreal = sys.argv[3]
if ( rtype == "anlKLevec2D" ) | ( rtype == "anlKLevec2Du" ):
ctype = sys.argv[2]
clen = sys.argv[3]
if ( rtype == "numKLevec2D" ) | (rtype == "numKLevec2Du" ) :
clen = sys.argv[2]
nreal = sys.argv[3]
if rtype == "samples":
fname = "cvspl_"+clen+"_512/samples_"+clen+"_512.dat"
print "Processing file ",fname
din,nliles=readfile(fname);
# Plot samples
fs1=18
lw1=2
xp=column(din,0);
fig = plt.figure(figsize=(4,4))
ax = fig.add_axes([0.19, 0.13, 0.76, 0.82])
for i in range(1,Npl+1):
plt.plot(xp,column(din,i),linewidth=lw1)
plt.xlabel('$x$',fontsize=fs1)
plt.ylabel(r'$F(x,\theta)$',fontsize=fs1)
ax.set_ylim([-4*sigma,4*sigma])
ax.set_yticks([-4*sigma,-2*sigma,0,2*sigma,4*sigma])
plt.savefig("rf1D_"+clen+".pdf")
if rtype == "pltKLeig1D":
#parameters
lw1 = 2
fs1 = 18
clrs = ['b','g','r']
