def testWitnessStream():
from WitnessFiltration import WitnessStream
from WeakWitnessFiltration import WeakWitnessStream
# mean = [0, 0]
# cov = [[1, 0], [0, 1]]
# matrixofpoints_inR2 = np.random.multivariate_normal(mean, cov, 100)
# p = pc.PointCloud(matrixofpoints_inR2)
filename = '/Users/naheed/PycharmProjects/PersistenceHomology/data/eight.mat'
p = pc.MatlabPointCloud(filename, 'point_cloud')
p.compute_distancematrix()
# Create Selector
pointcloud_sel = sel.PointCloudSelector(p, 100, "RandomSelector")
R = float(pointcloud_sel.get_maxdistance_landmarktoPointcloud()) / 2
# R = 0
print 'R = ', R
numdivision = 5
maxdim = 3
# ws = WitnessStream(landmarkselector=pointcloud_sel, maxdistance=R, numdivision=numdivision, maxdimension=maxdim)
ws = WeakWitnessStream(mu=2,
landmarkselector=pointcloud_sel,
maxdistance=R,
numdivision=numdivision,
maxdimension=maxdim)
ws.construct
print ws
print "Total number of Simplices in the Filtration: ", len(ws)
def testRandomSelector():
# Create PointCloud
matrixofpoints_inR2 = []
mean = [0, 0]
cov = [[1, 0], [0, 1]]
matrixofpoints_inR2 = np.random.multivariate_normal(mean, cov, 100)
p = pc.PointCloud(matrixofpoints_inR2)
# Create Selector
s = sel.PointCloudSelector(p, 5, "RandomSelector")
print s.getLandmarkPoints().points
print s.getdistance_subsetstoPointcloud()
def comparebars():
maxdim = 2
filename = '/Users/naheed/PycharmProjects/PersistenceHomology/data/eight.mat'
p = pc.MatlabPointCloud(filename, 'point_cloud')
print p.dimension, p.size
p.compute_distancematrix()
print p.getdistance(0, 1)
from src.RipsFiltration import BruteForceRips
rf = BruteForceRips(p, 100, maxdim, 0.01)
rf.construct()
from src.ComputeInterval import IntervalComputation
ci = IntervalComputation(rf)
ci.compute_intervals(maxdim)
print ci.betti_intervals
from src.WeakWitnessFiltration import WeakWitnessStream
filename = '/Users/naheed/PycharmProjects/PersistenceHomology/data/eight.mat'
p2 = pc.MatlabPointCloud(filename, 'point_cloud')
print p2.dimension, p2.size
p2.compute_distancematrix()
pointcloud_sel = sel.PointCloudSelector(p2, 200, "MaxminSelector")
pointcloud_sel.select()
R = 0.01
print "R= ", R
ws = WeakWitnessStream(mu=1,
landmarkselector=pointcloud_sel,
maxdistance=R,
numdivision=100,
maxdimension=maxdim)
ws.construct()
ci2 = IntervalComputation(ws)
ci2.compute_intervals(maxdim)
# print len(ci2.betti_intervals), len(ci.betti_intervals)
from src.Intervalviz import PersistenceViz
pv = PersistenceViz(ci.betti_intervals, replace_Inf=rf.maxfiltration_val)
pv.qual_compare_barcodes(ci2.betti_intervals, R)
def testWitnessStreamPH():
from WitnessFiltration import WitnessStream
from src.WeakWitnessFiltration import WeakWitnessStream
from src.ComputeInterval import IntervalComputation
# mean = [0, 0]
# cov = [[1, 0], [0, 1]]
# matrixofpoints_inR2 = np.random.multivariate_normal(mean, cov, 100)
# p = pc.PointCloud(matrixofpoints_inR2)
filename = '/Users/naheed/PycharmProjects/PersistenceHomology/data/eight.mat'
p = pc.MatlabPointCloud(filename, 'point_cloud')
p.compute_distancematrix()
# Create Selector
# pointcloud_sel = sel.PointCloudSelector(p, 10, "RandomSelector")
pointcloud_sel = sel.PointCloudSelector(p, 50, "MaxminSelector")
# Measuring system time elapsed since the epoch (UTC time-zone)
start_time = time()
pointcloud_sel.select()
elapsed_time = time() - start_time
R = float(pointcloud_sel.get_maxdistance_landmarktoPointcloud()) / 3
# R = 0
print 'R = ', R
numdivision = 10
maxdim = 2
# ws = WitnessStream(landmarkselector=pointcloud_sel, maxdistance=R, numdivision=numdivision, maxdimension=maxdim)
ws = WeakWitnessStream(mu=2,
landmarkselector=pointcloud_sel,
maxdistance=R,
numdivision=numdivision,
maxdimension=maxdim)
ws.construct()
print "Total number of Simplices in the Filtration: ", len(ws)
ci = IntervalComputation(ws)
ci.compute_intervals(
maxdim
) # I should check everything is ok in this function since the deg for simplices can have real value now.
ci.print_BettiNumbers()
def testWitnessStreamPerCom():
from WitnessFiltration import WitnessStream
from src.WeakWitnessFiltration import WeakWitnessStream
from src.AbsoluteCohomologyOptimized import *
from src.ComputeInterval import IntervalComputation
# mean = [0, 0]
# cov = [[1, 0], [0, 1]]
# matrixofpoints_inR2 = np.random.multivariate_normal(mean, cov, 100)
# p = pc.PointCloud(matrixofpoints_inR2)
filename = '/Users/naheed/PycharmProjects/PersistenceHomology/data/eight.mat'
h = hpy() # guppy heap object
p = pc.MatlabPointCloud(filename, 'point_cloud')
p.compute_distancematrix()
# Create Selector
# pointcloud_sel = sel.PointCloudSelector(p, 10, "RandomSelector")
pointcloud_sel = sel.PointCloudSelector(p, 500, "MaxminSelector")
# Measuring system time elapsed since the epoch (UTC time-zone)
start_time = time()
pointcloud_sel.select()
elapsed_time = time() - start_time
R = float(pointcloud_sel.get_maxdistance_landmarktoPointcloud())
# R = 0
print 'R = ', R
numdivision = 10
maxdim = 2
# ws = WitnessStream(landmarkselector=pointcloud_sel, maxdistance=R, numdivision=numdivision, maxdimension=maxdim)
ws = WeakWitnessStream(mu=2,
landmarkselector=pointcloud_sel,
maxdistance=R,
numdivision=numdivision,
maxdimension=maxdim)
ws.construct()
print "Total number of Simplices in the Filtration: ", len(ws)
print "After ws.construct():\n", h.heap().size
start_time = time()
cohom = FiltrationArrayCohomologyComputer(filtr=ws,
maxdim=maxdim,
maxfilter=R)
total_mem_consumed = h.heap().size
cohom.compute()
total_mem_consumed = h.heap().size - total_mem_consumed
elapsed_time = time() - start_time
print "time: ", elapsed_time
print "After cohomology:\n", total_mem_consumed
start_time = time()
ci = IntervalComputation(ws)
total_mem_consumed = h.heap().size
ci.compute_intervals(
maxdim
) # I should check everything is ok in this function since the deg for simplices can have real value now.
total_mem_consumed = h.heap().size - total_mem_consumed
ci.print_BettiNumbers()
elapsed_time = time() - start_time
print "time: ", elapsed_time
print "After Homology:\n", total_mem_consumed
