def testLargeArrayConversionCython(self):
""" Test that we don't get segmentation fault: 11 on large (1MM points) arrays using Cython """
# London bounding box
N = 51.691874116909894
E = 0.3340155643740321
S = 51.28676016315085
W = -0.5103750689005356
num_coords = 1000000
lon_ls = np.random.uniform(W, E, [num_coords])
lat_ls = np.random.uniform(S, N, [num_coords])
cconvert_bng(lon_ls, lat_ls)
def testLargeArrayConversionCython(self):
""" Test that we don't get segmentation fault: 11 on large (1MM points) arrays using Cython """
# London bounding box
N = 51.691874116909894
E = 0.3340155643740321
S = 51.28676016315085
W = -0.5103750689005356
num_coords = 1000000
lon_ls = np.random.uniform(W, E, [num_coords])
lat_ls = np.random.uniform(S, N, [num_coords])
cconvert_bng(lon_ls, lat_ls)
def testCythonConvertLonLat(self):
""" Test Cythonised multithreaded lon, lat --> BNG function """
expected = ([516274.46000000002, 398915.554], [173141.101, 521544.09000000003])
result = cconvert_bng(np.array([-0.32824866, -2.0183041005533306]), np.array([51.44533267, 54.589097162646141]))
# dump array result into list
a, b = list(result[0]), list(result[1])
self.assertEqual(expected, (a, b))
def testCythonConvertList(self):
""" Test Cythonised multithreaded lon, lat --> BNG function with lists """
expected = (np.array([516274.460,
398915.542]), np.array([173141.098, 521544.088]))
result = cconvert_bng([-0.32824866, -2.0183041005533306],
[51.44533267, 54.589097162646141])
self.assertEqual(expected[0][0], result[0][0])
def testCythonConvertLonLat(self):
""" Test Cythonised multithreaded lon, lat --> BNG function """
expected = ([516274.46000000002,
398915.554], [173141.101, 521544.09000000003])
result = cconvert_bng(np.array([-0.32824866, -2.0183041005533306]),
np.array([51.44533267, 54.589097162646141]))
# dump array result into list
a, b = list(result[0]), list(result[1])
self.assertEqual(expected, (a, b))
def testCythonConsistency(self):
""" Ensure Ctypes and Cython give same results """
# London bounding box
N = 51.691874116909894
E = 0.3340155643740321
S = 51.28676016315085
W = -0.5103750689005356
num_coords = 100
rand = randrange(0, 100)
lon_ls = np.random.uniform(W, E, [num_coords])
lat_ls = np.random.uniform(S, N, [num_coords])
# result is a list, so convert to an array. Ugh.
res_ctypes = np.array(convert_bng(lon_ls, lat_ls)[0][rand])
res_cython = cconvert_bng(lon_ls, lat_ls)[0][rand]
self.assertEqual(res_ctypes, res_cython)
def testCythonConsistency(self):
""" Ensure Ctypes and Cython give same results """
# London bounding box
N = 51.691874116909894
E = 0.3340155643740321
S = 51.28676016315085
W = -0.5103750689005356
num_coords = 100
rand = randrange(0, 100)
lon_ls = np.random.uniform(W, E, [num_coords])
lat_ls = np.random.uniform(S, N, [num_coords])
# result is a list, so convert to an array. Ugh.
res_ctypes = np.array(convert_bng(lon_ls, lat_ls)[0][rand])
res_cython = cconvert_bng(lon_ls, lat_ls)[0][rand]
self.assertEqual(res_ctypes, res_cython)
def testCythonConvertList(self):
""" Test Cythonised multithreaded lon, lat --> BNG function with lists """
expected = (np.array([516274.460, 398915.542]), np.array([173141.098, 521544.088]))
result = cconvert_bng([-0.32824866, -2.0183041005533306], [51.44533267, 54.589097162646141])
self.assertEqual(expected[0][0], result[0][0])
