def run_tests(test_cases, test_sizes, n_iter):
for case in test_cases:
print("Curve type:", case)
print("{: <15}| {: <15}| {: <15}| {: <15}".format("Size", "Energy", "Error", "Time(seconds)"))
for size in test_sizes:
n = size # number of points in domain
t = np.linspace(0., 1., n)
gamma_sol = ex.gamma_example(case)[0](t)
q = ex.curve_example("circle", t)[0][0]
inter_func1 = scipy.interpolate.CubicSpline(t, q)
p = inter_func1(gamma_sol)
elapsed = np.inf
energy = 0
tg = 0
gammay = 0
for i in range(n_iter):
start = time.time()
energy, p_new, q_new, tg, gammay = shapedist.find_shapedist(p, q, 'ud', t1=t, t2=t)
end = time.time()
if start-end <np.inf:
elapsed = end-start
error = shapedist.find_error(tg, gammay, ex.gamma_example("bumpy")[0](tg))
print("{: <15}| {: <15}| {: <15}| {: <15}".format(str(size), "%0.10f" % energy, "%0.10f" % error,
"%0.10f" % elapsed))
def calc(filename):
readFile = open(filename, "r")
text = readFile.read()
readFile.close()
text = text.split("\n")
f = open(filename.split("_")[len(filename.split("_"))-1] + "_raw.txt", "w")
for i in text:
x = i.split(" ")
m = int(x[1])
curve_type = str(x[0])
print(m)
t = np.linspace(0., 1., m)
# t = np.random.rand(m)
#
# t[0] = 0
# t[t.size - 1] = 1
# t.sort()
q = ex.curve_example('bumps', t)[0][1]
x_function = CubicSpline(t, q)
test = ex.gamma_example(curve_type)[0](t)
#
# test = np.zeros(m)
#
# i = 1
# while i < m:
# test[i] = np.random.random_sample()
# i = i + 1
# test.sort()
# test[m-1] = 1
# test[0] = 0
p = x_function(test)
# p = np.array(np.sin(t))
# q = np.array(np.exp(t)-1)
num = int(np.log2(m) - 4)
domain_x, gammax, val = elastic_linear_uniform.find_gamma(np.array([t, p]), np.array([t, q]), 6, 4, num)
error = elastic_linear_uniform.find_error(domain_x, ex.gamma_example(curve_type)[0](domain_x), gammax)
print(error)
# plt.plot(domain_x, gammax, "-r")
# plt.show()
f.write("Minimum Energy: " + str(val) + " Error: " + str(error) + "\n\n\n")
for j in range(3):
cProfile.runctx("elastic_linear_uniform.find_gamma(np.array([t, p]), np.array([t, q]), 6, 4, num)", globals(),
locals(), filename="statsfile")
stream = StringIO()
stats = pstats.Stats('statsfile', stream=stream).sort_stats("cumulative")
stats.print_stats()
f.write(stream.getvalue())
f.close()
def calc(filename):
readFile = open(filename, "r")
text = readFile.read()
readFile.close()
text = text.split("\n")
f = open(
filename.split("_")[len(filename.split("_")) - 1] + "_raw.txt", "w")
for i in text:
x = i.split(" ")
m = int(x[1])
curve_type = str(x[0])
print(m)
t = np.linspace(0., 1., m)
# t = np.random.rand(m)
#
# t[0] = 0
# t[t.size - 1] = 1
# t.sort()
q = ex.curve_example('bumps', t)[0][0]
x_function = InterpolatedUnivariateSpline(t, q)
test = ex.gamma_example(curve_type)[0](t)
#
# test = np.zeros(m)
#
# i = 1
# while i < m:
# test[i] = np.random.random_sample()
# i = i + 1
# test.sort()
# test[m-1] = 1
# test[0] = 0
p = x_function(test)
# p = np.array(np.sin(t))
# q = np.array(np.exp(t)-1)
num = int(np.log2(m) - 4)
domain_x, gammax, val = elastic_linear_old.find_gamma(
np.array([t, p]), np.array([t, q]), 6, 12, num)
error = elastic_linear_old.find_error(
domain_x,
ex.gamma_example(curve_type)[0](domain_x), gammax)
def run_tests(ndim, test_cases, curve_name, test_sizes, n_iter, shape_reps,
mode):
mode = mode + "d"
for shape_rep in shape_reps:
for case in test_cases:
eprint(curve_name.upper() + " curve, " + case.upper() +
" gamma, in {} dimensions with ".format(str(ndim)) +
shape_rep.__name__ + " representation")
eprint("{: <15}| {: <15}| {: <15}| {: <15}| {: <15}".format(
"Size", "Coarsened Size", "Energy", "Error", "Time(seconds)"))
for size in test_sizes:
n = size # number of points in domain
t = np.linspace(0., 1., n)
gamma_sol = ex.gamma_example(case)[0](t)
if curve_name == "rand":
q = np.random.rand(n, ndim)
else:
if ndim > 2:
raise RuntimeWarning(
"There are no synthetic curves larger than 2 dimensions currently implemented"
)
q = ex.curve_example(curve_name, t)[0][:ndim].T
p = np.zeros(q.shape)
for d in range(ndim):
inter_func = scipy.interpolate.CubicSpline(t, q[:, d])
p[:, d] = inter_func(gamma_sol)
elapsed = np.inf
energy = 0
tg = 0
gammay = 0
for i in range(n_iter):
start = time.time()
energy, p_new, q_new, tg, gammay = shapedist.find_shapedist(
p, q, mode, t1=t, t2=t, shape_rep=shape_rep)
end = time.time()
if start - end < elapsed:
elapsed = end - start
error = shapedist.find_error(tg, gammay,
ex.gamma_example(case)[0](tg))
eprint("{: <15}| {: <15}| {: <15}| {: <15}| {: <15}".format(
str(size), str(tg.shape[0]), "%0.10f" % energy,
"%0.10f" % error, "%0.10f" % elapsed))
eprint("-" * 81)
path_nodes[i][j][0] = k
path_nodes[i][j][1] = l
l = l + 1
k = k + 1
min_energy_values[i][j] = minimum
j = j + 1
i = i + 1
m = 256
n = 256
t = np.linspace(0., 1., m)
p = [0, 0]
q = ex.curve_example('bumps', t)[0]
x_function = InterpolatedUnivariateSpline(t, q[0])
y_function = InterpolatedUnivariateSpline(t, q[1])
test = ex.gamma_example("sine")[0](t)
test1 = ex.gamma_example("sine")[0](t)
#
# test = np.zeros(m)
#
# i = 1
# while i < m:
# test[i] = np.random.random_sample()
# i = i + 1
# test.sort()
# test[m-1] = 1
print("Loading.....")
import sys
import matplotlib.pyplot as plt
import scipy.interpolate
import shapedist
from testing import examples as ex
import numpy as np
import cProfile
import pstats
from io import StringIO
# One example shapdist compuation for gamma
n = 4096 # number of points in domain
t = np.linspace(0., 1., n)
q = ex.curve_example('limacon', t)[0]
p = np.zeros(q.shape)
x_function = scipy.interpolate.CubicSpline(t, q[0])
y_function = scipy.interpolate.CubicSpline(t, q[1])
test = ex.gamma_example("bumpy")[0]
# test1 = ex.gamma_example("sine")[0](t)
p[0] = x_function(test(t))
p[1] = y_function(test(t))
p = p.T
q = q.T
# q = ex.curve_example("circle", t)[0].T
# p = ex.curve_example("ellipse", t)[0].T
def calc(filename):
readFile = open(filename, "r")
text = readFile.read()
readFile.close()
text = text.split("\n")
f = open("errors.csv", "a")
f.write("\n")
for i in text:
x = i.split(" ")
m = int(x[1])
curve_type = str(x[0])
print(m)
t = np.linspace(0., 1., m)
# t = np.random.rand(m)
#
# t[0] = 0
# t[t.size - 1] = 1
# t.sort()
q = ex.curve_example('bumps', t)[0][0]
x_function = InterpolatedUnivariateSpline(t, q)
test = ex.gamma_example(curve_type)[0](t)
#
# test = np.zeros(m)
#
# i = 1
# while i < m:
# test[i] = np.random.random_sample()
# i = i + 1
# test.sort()
# test[m-1] = 1
# test[0] = 0
p = x_function(test)
# p = np.array(np.sin(t))
# q = np.array(np.exp(t)-1)
f.write(str(m) + ",")
i = 9
while i <= 9:
x = int(np.log2(t.size) - 4)
domain_x, gammax, val = find_gamma(np.array([t, p]),
np.array([t, q]), 6, 8, x)
error = find_error(domain_x,
ex.gamma_example(curve_type)[0](domain_x),
gammax)
f.write(str(error) + ",")
i = i + 1
print(error, x)
plt.plot(domain_x,
gammax - ex.gamma_example(curve_type)[0](domain_x), "-b")
plt.plot(domain_x, gammax, ".-b")
plt.plot(domain_x, ex.gamma_example(curve_type)[0](domain_x), "-r")
plt.show()
f.write("\n")
f.close()
