def PandC_datasets_test():
"""Test if pDataset and cDataset work exactly the same"""
try:
from models.dataset import cDataset
from models.dataset import pDataset
except:
print("Test not run, could not import cDataset or pDataset")
return False
check = True
size = 5
for i in range(100):
n = random.randint(1, size)
m = random.randint(1, size)
cdset = cDataset(n, m)
pdset = pDataset(n, m)
for i in range(10):
x = np.random.rand(n)
y = np.random.rand(m)
cdset.add_xy(x, y)
pdset.add_xy(x, y)
checkpoint = cdset.size == pdset.size == i+1
if not checkpoint:
print('checkpoint 1')
check = check and checkpoint
for i in range(10):
assert tuple(pdset.get_x(i)) == tuple(pdset.get_x(i))
for i in range(100):
x = np.random.rand(n)
k = random.randint(1, size)
cdists, cnn_x = cdset.nn_x(x, k = k)
pdists, dnn_x = pdset.nn_x(x, k = k)
if sorted(cnn_x) != sorted(dnn_x):
print(n, m, k)
print(cnn_x, cdists)
print(dnn_x, pdists*pdists)
print('Error', x)
print('c++ ', sorted(cnn_x), cdset.get_x(cnn_x[0]), x - cdset.get_x(cnn_x[0]))
print('python', sorted(dnn_x), pdset.get_x(dnn_x[1]), x - pdset.get_x(dnn_x[1]))
pass
check = check and sorted(cnn_x) == sorted(dnn_x)
y = np.random.rand(m)
cnn_y = cdset.nn_y(y, k = k)[1]
dnn_y = pdset.nn_y(y, k = k)[1]
check = check and sorted(cnn_y) == sorted(dnn_y)
# for i in xrange(100):
# index = random.randint(0, cdset.size-1)
# check = check and np.allclose(cdset.get_x(index), pdset.get_x(index), rtol = 1e-10, atol = 1e-10)
# check = check and np.allclose(cdset.get_y(index), pdset.get_y(index), rtol = 1e-10, atol = 1e-10)
# check = check and np.allclose(cdset.get_x_padded(index), pdset.get_x_padded(index), rtol = 1e-10, atol = 1e-10)
return check
def PandC_datasets_test2():
"""Test if pDataset and cDataset work exactly the same, interweaving adding and nn request"""
try:
from models.dataset import cDataset
from models.dataset import pDataset
except:
print("Test not run, could not import cDataset or pDataset")
return False
check = True
for i in range(100):
n = random.randint(1, 20)
m = random.randint(1, 20)
n, m = 1, 1
cdset = cDataset(n, m)
pdset = pDataset(n, m)
for i in range(10):
for j in range(10):
x = np.random.rand(n)
y = np.random.rand(m)
cdset.add_xy(x, y)
pdset.add_xy(x, y)
check = check and cdset.size == pdset.size == 10*i+j+1
for j in range(3):
x = np.random.rand(n)
k = random.randint(1, 20)
cdists, cnn_x = cdset.nn_x(x, k = k)
pdists, dnn_x = pdset.nn_x(x, k = k)
if sorted(cnn_x) != sorted(dnn_x):
# print cnn_x, cdists
# print dnn_x, pdists
# print dnn_x, pdists*pdists
# print 'Error', x
# print 'c++ ', sorted(cnn_x), cdset.get_x(cnn_x[0])[0], x - cdset.get_x(cnn_x[0])[0]
# print 'python', sorted(dnn_x), pdset.get_x(dnn_x[0])[0], x - pdset.get_x(dnn_x[0])[0]
pass
check = check and sorted(cnn_x) == sorted(dnn_x)
y = np.random.rand(m)
cnn_y = cdset.nn_y(y, k = k)[1]
dnn_y = pdset.nn_y(y, k = k)[1]
if sorted(cnn_y) != sorted(dnn_y):
# print 'error'
# print cnn_y
# print dnn_y
pass
check = check and sorted(cnn_y) == sorted(dnn_y)
for i in range(100):
index = random.randint(0, cdset.size-1)
check = check and np.allclose(cdset.get_x(index), pdset.get_x(index), rtol = 1e-10, atol = 1e-10)
check = check and np.allclose(cdset.get_y(index), pdset.get_y(index), rtol = 1e-10, atol = 1e-10)
check = check and np.allclose(cdset.get_x_padded(index), pdset.get_x_padded(index), rtol = 1e-10, atol = 1e-10)
return check
def PandC_datasets_test2():
"""Test if pDataset and cDataset work exactly the same, interweaving adding and nn request"""
try:
from models.dataset import cDataset
from models.dataset import pDataset
except:
print("Test not run, could not import cDataset or pDataset")
return False
check = True
for i in range(100):
n = random.randint(1, 20)
m = random.randint(1, 20)
n, m = 1, 1
cdset = cDataset(n, m)
pdset = pDataset(n, m)
for i in range(10):
for j in range(10):
x = np.random.rand(n)
y = np.random.rand(m)
cdset.add_xy(x, y)
pdset.add_xy(x, y)
check = check and cdset.size == pdset.size == 10 * i + j + 1
for j in range(3):
x = np.random.rand(n)
k = random.randint(1, 20)
cdists, cnn_x = cdset.nn_x(x, k=k)
pdists, dnn_x = pdset.nn_x(x, k=k)
if sorted(cnn_x) != sorted(dnn_x):
# print cnn_x, cdists
# print dnn_x, pdists
# print dnn_x, pdists*pdists
# print 'Error', x
# print 'c++ ', sorted(cnn_x), cdset.get_x(cnn_x[0])[0], x - cdset.get_x(cnn_x[0])[0]
# print 'python', sorted(dnn_x), pdset.get_x(dnn_x[0])[0], x - pdset.get_x(dnn_x[0])[0]
pass
check = check and sorted(cnn_x) == sorted(dnn_x)
y = np.random.rand(m)
cnn_y = cdset.nn_y(y, k=k)[1]
dnn_y = pdset.nn_y(y, k=k)[1]
if sorted(cnn_y) != sorted(dnn_y):
# print 'error'
# print cnn_y
# print dnn_y
pass
check = check and sorted(cnn_y) == sorted(dnn_y)
for i in range(100):
index = random.randint(0, cdset.size - 1)
check = check and np.allclose(
cdset.get_x(index), pdset.get_x(index), rtol=1e-10, atol=1e-10)
check = check and np.allclose(
cdset.get_y(index), pdset.get_y(index), rtol=1e-10, atol=1e-10)
check = check and np.allclose(cdset.get_x_padded(index),
pdset.get_x_padded(index),
rtol=1e-10,
atol=1e-10)
return check
def PandC_datasets_test():
"""Test if pDataset and cDataset work exactly the same"""
try:
from models.dataset import cDataset
from models.dataset import pDataset
except:
print("Test not run, could not import cDataset or pDataset")
return False
check = True
size = 5
for i in range(100):
n = random.randint(1, size)
m = random.randint(1, size)
cdset = cDataset(n, m)
pdset = pDataset(n, m)
for i in range(10):
x = np.random.rand(n)
y = np.random.rand(m)
cdset.add_xy(x, y)
pdset.add_xy(x, y)
checkpoint = cdset.size == pdset.size == i + 1
if not checkpoint:
print('checkpoint 1')
check = check and checkpoint
for i in range(10):
assert tuple(pdset.get_x(i)) == tuple(pdset.get_x(i))
for i in range(100):
x = np.random.rand(n)
k = random.randint(1, size)
cdists, cnn_x = cdset.nn_x(x, k=k)
pdists, dnn_x = pdset.nn_x(x, k=k)
if sorted(cnn_x) != sorted(dnn_x):
print(n, m, k)
print(cnn_x, cdists)
print(dnn_x, pdists * pdists)
print('Error', x)
print('c++ ', sorted(cnn_x), cdset.get_x(cnn_x[0]),
x - cdset.get_x(cnn_x[0]))
print('python', sorted(dnn_x), pdset.get_x(dnn_x[1]),
x - pdset.get_x(dnn_x[1]))
pass
check = check and sorted(cnn_x) == sorted(dnn_x)
y = np.random.rand(m)
cnn_y = cdset.nn_y(y, k=k)[1]
dnn_y = pdset.nn_y(y, k=k)[1]
check = check and sorted(cnn_y) == sorted(dnn_y)
# for i in xrange(100):
# index = random.randint(0, cdset.size-1)
# check = check and np.allclose(cdset.get_x(index), pdset.get_x(index), rtol = 1e-10, atol = 1e-10)
# check = check and np.allclose(cdset.get_y(index), pdset.get_y(index), rtol = 1e-10, atol = 1e-10)
# check = check and np.allclose(cdset.get_x_padded(index), pdset.get_x_padded(index), rtol = 1e-10, atol = 1e-10)
return check