def test_getStat(self):
reference = Raster('../../examples/data.tif')
simulated = Raster('../../examples/data1.tif')
reference.resetMask([2])
simulated.resetMask([2])
eb = EBudget(reference, simulated)
stat = eb.getStat(nIter=3)
ans0 = {
'NoNo': 0.5,
'NoMed': (5.0 * 5 / 8 + 3.0 * 3 / 8) / 8,
'MedMed': 4.0 / 8,
'MedPer': 1.0,
'PerPer': 1.0
}
for k in stat[0].keys():
np.testing.assert_almost_equal(stat[0][k], ans0[k])
ans1 = {
'NoNo': 0.5,
'NoMed': (5.0 / 8 + 5.0 / 32 + 3.0 / 16 + 3.0 / 32) / 2,
'MedMed': 4.0 / 8,
'MedPer': 1.0,
'PerPer': 1.0
}
for k in stat[1].keys():
np.testing.assert_almost_equal(stat[0][k], ans1[k])
def test_getStat(self):
reference = Raster('../../examples/data.tif')
simulated = Raster('../../examples/data1.tif')
reference.resetMask([2])
simulated.resetMask([2])
eb = EBudget(reference, simulated)
stat = eb.getStat(nIter=3)
ans0 = {'NoNo': 0.5, 'NoMed': (5.0*5/8 + 3.0*3/8)/8, 'MedMed': 4.0/8, 'MedPer': 1.0, 'PerPer': 1.0}
for k in stat[0].keys():
np.testing.assert_almost_equal(stat[0][k],ans0[k])
ans1 = {'NoNo': 0.5, 'NoMed': (5.0/8+5.0/32 + 3.0/16 + 3.0/32)/2, 'MedMed': 4.0/8, 'MedPer': 1.0, 'PerPer': 1.0}
for k in stat[1].keys():
np.testing.assert_almost_equal(stat[0][k],ans1[k])
def test_Init(self):
Rj = {
1:
np.ma.array(
data=[[1.0, 1.0, 1.0, 1.0], [1.0, 1.0, 0.0, 0.0],
[0.0, 0.0, 0.0, 0.0], [0.0, 0.0, 0.0, 0.0]],
mask=[[False, False, False,
False], [False, False, False, False],
[False, False, False, False],
[False, False, False, False]],
),
2:
np.ma.array(
data=[[0.0, 0.0, 0.0, 0.0], [0.0, 0.0, 1.0, 1.0],
[1.0, 1.0, 1.0, 1.0], [0.0, 0.0, 0.0, 0.0]],
mask=[[False, False, False,
False], [False, False, False, False],
[False, False, False, False],
[False, False, False, False]],
),
3:
np.ma.array(
data=[[0.0, 0.0, 0.0, 0.0], [0.0, 0.0, 0.0, 0.0],
[0.0, 0.0, 0.0, 0.0], [1.0, 1.0, 1.0, 1.0]],
mask=[[False, False, False,
False], [False, False, False, False],
[False, False, False, False],
[False, False, False, False]],
)
}
eb = EBudget(self.reference, self.simulated)
np.testing.assert_equal(eb.Rj, Rj)
def test_weightedSum(self):
eb = EBudget(self.reference, self.simulated)
W = eb.W
S1 = weightedSum(eb.Sj[1], W)
S2 = weightedSum(eb.Sj[2], W)
S3 = weightedSum(eb.Sj[3], W)
self.assertEqual(S1, 5.0 / 16)
self.assertEqual(S2, 3.0 / 16)
self.assertEqual(S3, 8.0 / 16)
def test_Mask(self):
reference = Raster('../../examples/data.tif')
simulated = Raster('../../examples/data1.tif')
reference.resetMask([2])
simulated.resetMask([2])
eb = EBudget(reference, simulated)
W = eb.W
S1 = weightedSum(eb.Sj[1], W)
S3 = weightedSum(eb.Sj[3], W)
np.testing.assert_almost_equal(S1, 5.0 / 8)
np.testing.assert_almost_equal(S3, 3.0 / 8)
noNo = eb.NoNo()
np.testing.assert_almost_equal(noNo, 0.5)
noM = eb.NoMed()
np.testing.assert_almost_equal(noM, (5.0 * 5 / 8 + 3.0 * 3 / 8) / 8)
medM = eb.MedMed()
np.testing.assert_almost_equal(medM, 4.0 / 8)
medP = eb.MedPer()
np.testing.assert_almost_equal(medP, 1.0)
def test_coarse(self):
reference = Raster('../../examples/data.tif')
simulated = Raster('../../examples/data1.tif')
reference.resetMask([2])
simulated.resetMask([2])
eb = EBudget(reference, simulated)
eb.coarse(2)
# W
answer = np.array([[1.0, 0.25], [0.5, 0.25]])
np.testing.assert_array_equal(eb.W, answer)
# Rj
answer1 = np.array([[1.0, 1.0], [0, 0]])
answer3 = np.array([[0, 0], [1.0, 1.0]])
ans = {1: answer1, 3: answer3}
np.testing.assert_equal(eb.Rj, ans)
# Sj
answer1 = np.array([[3.0/4, 0.0], [1.0, 0]])
answer3 = np.array([[1.0/4, 1.0], [0, 1.0]])
ans = {1: answer1, 3: answer3}
np.testing.assert_equal(eb.Sj, ans)
eb.coarse(2)
# W
answer = np.array([[0.5]])
np.testing.assert_array_equal(eb.W, answer)
# Rj
answer1 = np.array([[(1+1.0/4)/2]])
answer3 = np.array([[(1.0/2 + 1.0/4)/2]])
ans = {1: answer1, 3: answer3}
np.testing.assert_equal(eb.Rj, ans)
# Sj
answer1 = np.array([[(3.0/4 + 0.5)/2]])
answer3 = np.array([[(1.0/4 + 1.0/4 + 1.0/4 )/2]])
ans = {1: answer1, 3: answer3}
np.testing.assert_equal(eb.Sj, ans)
def test_coarse(self):
reference = Raster('../../examples/data.tif')
simulated = Raster('../../examples/data1.tif')
reference.resetMask([2])
simulated.resetMask([2])
eb = EBudget(reference, simulated)
eb.coarse(2)
# W
answer = np.array([[1.0, 0.25], [0.5, 0.25]])
np.testing.assert_array_equal(eb.W, answer)
# Rj
answer1 = np.array([[1.0, 1.0], [0, 0]])
answer3 = np.array([[0, 0], [1.0, 1.0]])
ans = {1: answer1, 3: answer3}
np.testing.assert_equal(eb.Rj, ans)
# Sj
answer1 = np.array([[3.0 / 4, 0.0], [1.0, 0]])
answer3 = np.array([[1.0 / 4, 1.0], [0, 1.0]])
ans = {1: answer1, 3: answer3}
np.testing.assert_equal(eb.Sj, ans)
eb.coarse(2)
# W
answer = np.array([[0.5]])
np.testing.assert_array_equal(eb.W, answer)
# Rj
answer1 = np.array([[(1 + 1.0 / 4) / 2]])
answer3 = np.array([[(1.0 / 2 + 1.0 / 4) / 2]])
ans = {1: answer1, 3: answer3}
np.testing.assert_equal(eb.Rj, ans)
# Sj
answer1 = np.array([[(3.0 / 4 + 0.5) / 2]])
answer3 = np.array([[(1.0 / 4 + 1.0 / 4 + 1.0 / 4) / 2]])
ans = {1: answer1, 3: answer3}
np.testing.assert_equal(eb.Sj, ans)
def test_MedPer(self):
eb = EBudget(self.reference, self.simulated)
medP = eb.MedPer()
answer = min(6.0 / 16, 5.0 / 16) + min(6.0 / 16, 3.0 / 16) + min(
4.0 / 16, 8.0 / 16)
np.testing.assert_almost_equal(medP, answer)
def test_MedMed(self):
eb = EBudget(self.reference, self.simulated)
medM = eb.MedMed()
answer = 5.0 / 16
np.testing.assert_almost_equal(medM, answer)
def test_NoMed(self):
eb = EBudget(self.reference, self.simulated)
noM = eb.NoMed()
answer = (6.0 * 5 / 16 + 6.0 * 3 / 16 + 4.0 * 8 / 16) / 16
np.testing.assert_almost_equal(noM, answer)
def test_NoNo(self):
eb = EBudget(self.reference, self.simulated)
noNo = eb.NoNo()
answer = 1.0 / 3
np.testing.assert_almost_equal(noNo, answer)
