import matplotlib.pyplot as plt
from utils.archiver import *
from utils.plotting import cdf_points
import tri_mesh_viewer as tmv
if __name__ == "__main__":
(_,file_base) = sys.argv
(nodes,faces) = read_ctri(file_base + ".mesh")
print "Number of nodes:",len(nodes)
print "Number of faces:",len(faces)
D = Unarchiver(file_base + ".data")
(N,A) = D.basis.shape
plt.figure()
plt.suptitle("Value -> Flow");
for a in xrange(A):
plt.subplot(2,2,a+1);
tmv.plot_vertices(nodes,faces,D.basis[:,a],
cmap=plt.get_cmap('jet'))
plt.figure()
plt.suptitle("Flow -> Value");
for a in xrange(A):
plt.subplot(2,2,a+1);
tmv.plot_vertices(nodes,faces,D.ibasis[:,a],
cmap=plt.get_cmap('jet'))
plt.show()
if __name__ == "__main__":
(_,filename) = sys.argv
(nodes,faces) = read_ctri(filename + ".mesh")
sol = Unarchiver(filename + '.sol')
V = nodes.shape[0]
assert 0 == sol.p.size % V
A = sol.p.size / V
P = np.reshape(sol.p,(V,A),order='F')
residual = sol.res
assert V == residual.size
plt.figure()
plt.title("Residual l2-norm: " + str(np.linalg.norm(residual)))
tmv.plot_vertices(nodes,faces,residual)
plt.figure()
plt.title("Agg flow")
agg_flow = np.sum(P[:,1:],axis=1)
tmv.plot_vertices(nodes,faces,agg_flow)
plt.clim([0,np.max(agg_flow)])
plt.figure()
assert A <= 4
for i in xrange(A):
plt.subplot(2,2,(i+1))
plt.title("Component " + str(i))
tmv.plot_vertices(nodes,faces,P[:,i])
plt.figure()
print "Number of faces:",len(faces)
sol = Unarchiver(file_base + ".data")
ref_P = sol.ref_P
ref_D = sol.ref_D
P = sol.P
D = sol.D
(N,A) = P.shape
#######################################
# Value
plt.figure()
plt.suptitle("Value information")
plt.subplot(2,2,1)
plt.title("Ref. value")
tmv.plot_vertices(nodes,faces,ref_P[:,0])
plt.subplot(2,2,2)
plt.title("Approx. value")
tmv.plot_vertices(nodes,faces,P[:,0])
plt.subplot(2,2,3)
plt.title("Difference")
tmv.plot_vertices(nodes,faces,P[:,0] - ref_P[:,0])
plt.subplot(2,2,4)
plt.title("Bellman res")
tmv.plot_vertices(nodes,faces,sol.res)
#######################################
# Flow
sol = Unarchiver(file_base + ".sol")
N = nodes.shape[0]
assert 0 == sol.p1.size % N
A = sol.p1.size / N
# RHS information
if False:
Q = sol.Q
assert((N,A) == Q.shape)
plt.figure()
plt.suptitle('Projected Q')
for a in range(A):
plt.subplot(2,2,a+1)
tmv.plot_vertices(nodes,faces,Q[:,a])
# Before and after primal/dual info
if True:
P1 = np.reshape(sol.p1,(N,A),order='F')
D1 = np.reshape(sol.d1,(N,A),order='F')
P2 = np.reshape(sol.p2,(N,A),order='F')
D2 = np.reshape(sol.d2,(N,A),order='F')
for (X,name) in [(P1,"Primal 1"),(D1,"Dual 1"),
(P2,"Primal 2"),(D2,"Dual 2")]:
plt.figure()
plt.suptitle(name)
assert A == 3
for a in xrange(A):
plt.subplot(2,2,a+1)
if a > 0:
if __name__ == "__main__":
(_,file_base) = sys.argv
(nodes,faces) = read_ctri(file_base + ".mesh")
print "Number of nodes:",len(nodes)
print "Number of faces:",len(faces)
sol = Unarchiver(file_base + ".data")
plt.figure()
plt.suptitle("Reference solve")
plt.subplot(2,3,1)
plt.title("Value")
tmv.plot_vertices(nodes,faces, sol.primal[:,0])
plt.subplot(2,3,2)
plt.title("Policy")
tmv.plot_vertices(nodes,faces,
np.argmax(sol.primal[:,1:],axis=1))
plt.subplot(2,3,3)
plt.title("Min Flow Slack")
tmv.plot_vertices(nodes,faces, np.min(sol.dual[:,1:],axis=1))
plt.subplot(2,3,4)
plt.title('Residual')
tmv.plot_vertices(nodes,faces,sol.residual)
print "Number of nodes:",len(nodes)
print "Number of faces:",len(faces)
sol = Unarchiver(file_base + ".data")
l1 = sol.data[:,:,0]
l2 = sol.data[:,:,1]
linf = sol.data[:,:,2]
############
plt.figure()
plt.suptitle("Residual change")
for (i,name) in enumerate(["l1","l2","linf"]):
plt.subplot(2,2,i+1)
Z = np.min(sol.data[:,:,i],axis=1)
plt.title(name)
tmv.plot_vertices(nodes,faces,Z,cmap=plt.get_cmap('jet'))
############
plt.figure()
plt.suptitle("Minimizing bandwidth")
for (i,name) in enumerate(["l1","l2","linf"]):
plt.subplot(2,2,i+1)
Z = sol.bandwidths[np.argmin(sol.data[:,:,i],axis=1)]
Z = np.log(Z)
plt.title(name)
tmv.plot_vertices(nodes,faces,Z,cmap=plt.get_cmap('jet'))
############
plt.figure()
plt.suptitle('Residuals')
plt.subplot(2,2,1)
import numpy as np
import matplotlib.pyplot as plt
from utils.archiver import *
from scipy.stats import pearsonr
import tri_mesh_viewer as tmv
(nodes,faces) = read_shewchuk("/home/epz/data/minop/sensitivity")
unarch = Unarchiver("/home/epz/data/minop/sensitivity.exp_res")
(N,D) = nodes.shape
assert(N == unarch.twiddle.size)
plt.subplot(1,2,1)
tmv.plot_vertices(nodes,faces,unarch.twiddle)
J = unarch.jitter
R = unarch.noise
P = np.zeros(N)
for i in xrange(N):
(r,p) = pearsonr(J[i,:],R[i,:])
if(p < 0.01):
P[i] = r
plt.subplot(1,2,2)
tmv.plot_vertices(nodes,faces,P)
plt.show()
group = np.argmax(np.abs(basis),1)
idx = np.argsort(group)
residual = np.array(residual).T
jitter = np.array(jitter).T
np.savez("tmp.npz",
residual=residual,
jitter=jitter)
Cor1 = np.cov(residual[idx,:])
Cor2 = np.cov(residual[idx,:]*jitter[idx,:])
cmap = plt.get_cmap('jet')
(nodes,faces) = read_shewchuk(base_file)
for (i,c) in enumerate([Cor1,Cor2]):
plt.figure(1);
plt.subplot(1,2,i+1)
tmv.plot_vertices(nodes,faces,np.diag(c),
cmap=cmap,interp='nearest');
plt.colorbar()
plt.figure(2);
plt.subplot(1,2,i+1)
plt.imshow(c,
cmap=cmap,interpolation='nearest');
plt.colorbar()
plt.show()
if __name__ == "__main__":
(_,file_base) = sys.argv
sol = Unarchiver(file_base + ".data")
(nodes,faces) = read_ctri(file_base + ".mesh")
R = sol.residuals
(N,I) = R.shape
for i in xrange(0,I):
plt.figure()
plt.suptitle("Iter " + str(i))
plt.subplot(2,3,1)
plt.title("Value")
tmv.plot_vertices(nodes,faces, sol.primals[:,0,i])
plt.subplot(2,3,2)
plt.title("Policy")
tmv.plot_vertices(nodes,faces,
sol.policies[:,i])
plt.subplot(2,3,3)
plt.title("Min Flow Slack")
tmv.plot_vertices(nodes,faces, sol.min_duals[:,i])
plt.subplot(2,3,4)
plt.title('Residual')
tmv.plot_vertices(nodes,faces,sol.residuals[:,i])
