def test_du_performance():
v = np.array([0.2, 0.5, 0.7, 0.4, 0.2])
r = np.array([0, 0, 0, 0, 0])
c = np.array([0, 2, 3, 4, 5])
data = csr_matrix((v, (r, c)), shape=(2, 6))
VL = np.array([[0.01, 0.02, 0.03, 0.015, 0.02, 0.03, 0.05, 0.007],
[0.02, 0.03, 0.05, 0.007, 0.01, 0.04, 0.01, 0.021],
[0.05, 0.07, 0.11, 0.101, 0.02, 0.01, 0.01, 0.003],
[0.02, 0.01, 0.01, 0.003, 0.02, 0.01, 0.01, 0.003],
[0.01, 0.04, 0.01, 0.021, 0.02, 0.01, 0.01, 0.003],
[0.03, 0.02, 0.02, 0.005, 0.05, 0.07, 0.11, 0.101]])
VV = VL.copy()
UL = np.array([[0.02, 0.01, 0.03, 0.04, 0.02, 0.01, 0.03, 0.04]])
UV = UL.copy()
b = datetime.now()
for i in xrange(1000):
xclimf.update(data, UV, VV, 0.01, 0.01)
time_vector = (datetime.now() - b).total_seconds()
b = datetime.now()
for i in xrange(1000):
looping_update.update(data, UL, VL, 0.01, 0.01)
time_looping = (datetime.now() - b).total_seconds()
print "looping", time_looping
print "vector", time_vector
assert time_looping > time_vector
def test_du_1():
v = np.array([0.2, 0.5])
r = np.array([0, 0])
c = np.array([0, 2])
data = csr_matrix((v, (r, c)), shape=(2, 6))
VL = np.array([[0.01, 0.02, 0.03, 0.015], [0.02, 0.03, 0.05, 0.007],
[0.05, 0.07, 0.11, 0.101]])
VV = VL.copy()
UL = np.array([[0.02, 0.01, 0.03, 0.04]])
UV = UL.copy()
looping_update.update(data, UL, VL, 0.01, 0.01)
xclimf.update(data, UV, VV, 0.01, 0.01)
print("UL", UL)
print("UV", UV)
print UL - UV
assert np.all(UL == UV)
def test_di_2():
v = np.array([0.2, 0.5, 0.7])
r = np.array([0, 0, 0])
c = np.array([0, 2, 3])
data = csr_matrix((v, (r, c)), shape=(2, 6))
VL = np.array([[0.01, 0.02, 0.03, 0.015], [0.02, 0.03, 0.05, 0.07],
[0.05, 0.07, 0.11, 0.101], [0.02, 0.01, 0.01, 0.03]])
VV = VL.copy()
UL = np.array([[0.02, 0.01, 0.03, 0.04]])
UV = UL.copy()
looping_update.update(data, UL, VL, 0.01, 0.01)
xclimf.update(data, UV, VV, 0.01, 0.01)
print("VL", VL)
print("VV", VV)
print VL - VV
assert np.all(VL == VV)