def compute_flags(self, lswt, visible, nir, bt3, lower_bt, upper_bt,
sat_za, sun_za, rel_az, lwm, cmsk, height, width,
sattype):
self.check = QualityCheck(lswt, visible, nir, bt3, lower_bt, upper_bt,
sat_za, sun_za, rel_az, lwm, cmsk, height,
width, sattype)
return self.check.check_quality()
def setUp(self):
lswt = numpy.ones((4, 4)) * 293
visible = numpy.ones((4, 4)) * 3.0
nir = numpy.ones((4, 4)) * 0.25
bt3 = numpy.ones((4, 4)) * 294
lower_bt = numpy.ones((4, 4)) * 295
upper_bt = numpy.ones((4, 4)) * 294
sat_za = numpy.ones((4, 4)) * 20
sun_za = numpy.ones((4, 4)) * 40
rel_az = numpy.ones((4, 4)) * 100
lwm = numpy.ones((4, 4))
cmsk = numpy.zeros((4, 4))
self.check = QualityCheck(lswt, visible, nir, bt3, lower_bt, upper_bt,
sat_za, sun_za, rel_az, lwm, cmsk, 4, 4,
'AVHRR')
def test_spatial_stddev(self):
in_data = [[5, 2, 3, 1], [5, 2, 3, 1], [5, 2, 3, 1], [5, 2, 3, 1]]
in_data = numpy.array(in_data, dtype=numpy.float32)
in_data[0, 0:2] = numpy.nan
stdv = QualityCheck.spatial_stddev(in_data, 3)
testing.assert_allclose(
numpy.array([[numpy.nan, numpy.nan, numpy.nan, 0.99999994],
[numpy.nan, numpy.nan, numpy.nan, 0.99999994],
[1.5, 1.32287566, 0.8660254, 0.99999994],
[1.5, 1.32287566, 0.8660254, 0.99999994]]),
stdv.tolist())
class MonoWindowAlgo:
def __init__(self, a0, a1, needs_lut):
self.needs_lut = needs_lut
if not needs_lut:
self.a0 = a0
self.a1 = a1
else:
season = numpy.array(range(
0, 4), dtype=numpy.float64) # spring, summer, autumn, winter
height = numpy.array([400, 800, 1000]) # height in meter
zenith = numpy.array(range(
5, 56, 5), dtype=numpy.float64) # 5 - 55deg in 5deg steps
dimensions = [season, height, zenith]
mono_coeff = Mono()
values = numpy.array(mono_coeff.values, dtype=numpy.float64)
self.lut = LookupTable(values, dimensions, 2)
self.check = None
def get_season(self, start_date):
utils = Utils()
return utils.get_season(start_date)
def compute_lswt(self, data, season, height, zenith_data):
if not self.needs_lut:
return self.a0 * data + self.a1
else:
lswt = numpy.zeros(numpy.shape(data))
lswt[numpy.where(numpy.isnan(data))] = Float.NaN
season = season[numpy.where(~numpy.isnan(data))]
height = height[numpy.where(~numpy.isnan(data))]
zenith_data = zenith_data[numpy.where(~numpy.isnan(data))]
size = numpy.shape(season)
if size != (0, ):
if len(size) == 2:
(shape_x, shape_y) = size
result = self.lut.getValues([
season[::2, ::2], height[::2, ::2],
zenith_data[::2, ::2]
])
[a0, a1] = result
a0 = numpy.repeat(numpy.repeat(a0, 2, axis=0), 2, axis=1)
a1 = numpy.repeat(numpy.repeat(a1, 2, axis=0), 2, axis=1)
a0 = a0[:shape_x, :shape_y]
a1 = a1[:shape_x, :shape_y]
elif len(size) == 1:
(shape_x, ) = size
result = self.lut.getValues(
[season[::2], height[::2], zenith_data[::2]])
[a0, a1] = result
a0 = numpy.repeat(a0, 2)
a1 = numpy.repeat(a1, 2)
a0 = a0[:shape_x]
a1 = a1[:shape_x]
lswt[numpy.where(~numpy.isnan(
data))] = a0 * data[numpy.where(~numpy.isnan(data))] + a1
return lswt
def compute_flags(self, lswt, visible, nir, bt, sat_za, sun_za, rel_az,
lwm, cmsk, height, width, sattype):
self.check = QualityCheck(lswt, visible, nir, None, bt, None, sat_za,
sun_za, rel_az, lwm, cmsk, height, width,
sattype)
return self.check.check_quality()
def compute_quality_index(self, flags):
return self.check.get_quality_mask(flags)
class SplitWindowAlgo:
def __init__(self, a0, a1, a2, a3, needs_lut):
if needs_lut:
self.has_lut = True
season = numpy.array(range(
0, 4), dtype=numpy.float64) # spring, summer, autumn, winter
height = numpy.array([400, 800, 1000]) # height in meter
zenith = numpy.array(range(
5, 56, 5), dtype=numpy.float64) # 5 - 55deg in 5deg steps
dimensions = [season, height, zenith]
# TODO needs to be loaded from file!
values = numpy.tile([3.079654, 0.988938, 1.867209, -0.434251],
len(season) * len(zenith) * len(height))
self.lut = LookupTable(values, dimensions, 4)
else:
self.has_lut = False
self.a0 = a0
self.a1 = a1
self.a2 = a2
self.a3 = a3
self.check = None
def get_season(self, start_date):
utils = Utils()
return utils.get_season(start_date)
def compute_lswt_lut(self, lower_data, upper_data, zenith_data, season,
height):
lswt = numpy.zeros(numpy.shape(lower_data))
lswt[numpy.where(
numpy.logical_or(numpy.isnan(lower_data),
numpy.isnan(upper_data)))] = Float.NaN
season = season[numpy.where(
numpy.logical_and(~numpy.isnan(lower_data),
~numpy.isnan(upper_data)))]
zenith_data = zenith_data[numpy.where(
numpy.logical_and(~numpy.isnan(lower_data),
~numpy.isnan(upper_data)))]
height = height[numpy.where(
numpy.logical_and(~numpy.isnan(lower_data),
~numpy.isnan(upper_data)))]
size = numpy.shape(season)
if size != (0, ):
[self.a0, self.a1, self.a2,
self.a3] = self.lut.getValues([season, height, zenith_data])
lswt[numpy.where(
numpy.logical_and(
~numpy.isnan(lower_data),
~numpy.isnan(upper_data)))] = self.compute_lswt(
lower_data[numpy.where(
numpy.logical_and(~numpy.isnan(lower_data),
~numpy.isnan(upper_data)))],
upper_data[numpy.where(
numpy.logical_and(~numpy.isnan(lower_data),
~numpy.isnan(upper_data)))],
zenith_data)
return lswt
def compute_lswt(self, lower_data, upper_data, zenith_data):
lswt = self.a0 + self.a1 * lower_data + self.a2 * (lower_data - upper_data) + \
self.a3 * (1 - 1 / (numpy.cos(zenith_data * (numpy.math.pi / 180.0)))) * (lower_data - upper_data)
return lswt
def compute_flags(self, lswt, visible, nir, bt3, lower_bt, upper_bt,
sat_za, sun_za, rel_az, lwm, cmsk, height, width,
sattype):
self.check = QualityCheck(lswt, visible, nir, bt3, lower_bt, upper_bt,
sat_za, sun_za, rel_az, lwm, cmsk, height,
width, sattype)
return self.check.check_quality()
def compute_quality_index(self, flags):
return self.check.get_quality_mask(flags)
class TestLSWTQualityCheck(unittest.TestCase):
def setUp(self):
lswt = numpy.ones((4, 4)) * 293
visible = numpy.ones((4, 4)) * 3.0
nir = numpy.ones((4, 4)) * 0.25
bt3 = numpy.ones((4, 4)) * 294
lower_bt = numpy.ones((4, 4)) * 295
upper_bt = numpy.ones((4, 4)) * 294
sat_za = numpy.ones((4, 4)) * 20
sun_za = numpy.ones((4, 4)) * 40
rel_az = numpy.ones((4, 4)) * 100
lwm = numpy.ones((4, 4))
cmsk = numpy.zeros((4, 4))
self.check = QualityCheck(lswt, visible, nir, bt3, lower_bt, upper_bt,
sat_za, sun_za, rel_az, lwm, cmsk, 4, 4,
'AVHRR')
def test_spatial_stddev(self):
in_data = [[5, 2, 3, 1], [5, 2, 3, 1], [5, 2, 3, 1], [5, 2, 3, 1]]
in_data = numpy.array(in_data, dtype=numpy.float32)
in_data[0, 0:2] = numpy.nan
stdv = QualityCheck.spatial_stddev(in_data, 3)
testing.assert_allclose(
numpy.array([[numpy.nan, numpy.nan, numpy.nan, 0.99999994],
[numpy.nan, numpy.nan, numpy.nan, 0.99999994],
[1.5, 1.32287566, 0.8660254, 0.99999994],
[1.5, 1.32287566, 0.8660254, 0.99999994]]),
stdv.tolist())
def test_get_quality_flag_Q8(self):
# 0: 0000 0000 0000
flag = numpy.ones(1) * 0
result = self.check.get_quality_mask(flag)
self.assertEqual(8, result[0], 'Quality level should be 8 for 0')
def test_get_quality_flag_Q7(self):
# 1024: 0100 0000 0000
flag = numpy.ones(1) * 1024
result = self.check.get_quality_mask(flag)
self.assertEqual(7, result[0], 'Quality level should be 7 for 1024')
def test_get_quality_flag_Q6(self):
# 512: 0010 0000 0000
flag = numpy.ones(1) * 512
result = self.check.get_quality_mask(flag)
self.assertEqual(6, result[0], 'Quality level should be 6 for 512')
def test_get_quality_flag_Q5(self):
# 2048: 1000 0000 0000
flag = numpy.ones(1) * 2048
result = self.check.get_quality_mask(flag)
self.assertEqual(5, result[0], 'Quality level should be 5 for 2048')
def test_get_quality_flag_Q4(self):
# 3072: 1100 0000 0000
flag = numpy.ones(1) * 3072
result = self.check.get_quality_mask(flag)
self.assertEqual(4, result[0], 'Quality level should be 4 for 3072')
def test_get_quality_flag_Q3(self):
# 2560: 1010 0000 0000
flag = numpy.ones(1) * 2560
result = self.check.get_quality_mask(flag)
self.assertEqual(3, result[0], 'Quality level should be 3 for 2560')
def test_get_quality_flag_Q2(self):
# 1536: 0110 0000 0000
# 3584: 1110 0000 0000
for i in [1536, 3584]:
flag = numpy.ones(1) * i
result = self.check.get_quality_mask(flag)
self.assertEqual(2, result[0],
'Quality level should be 2 for ' + str(i))
def test_get_quality_flag_Q1(self):
# 256: 0001 0000 0000
# 768: 0011 0000 0000
# 1280: 0101 0000 0000
# 1792: 0111 0000 0000
# 2304: 1001 0000 0000
# 2816: 1011 0000 0000
# 3328: 1101 0000 0000
# 3840: 1111 0000 0000
for i in [256, 768, 1280, 1792, 2304, 2816, 3328, 3840]:
flag = numpy.ones(1) * i
result = self.check.get_quality_mask(flag)
self.assertEqual(1, result[0],
'Quality level should be 1 for ' + str(i))
# 3584: 1110 0000 0000
# 0: 0000 0000 0000
# 4095: 1111 1111 1111
for i in [3584, 0, 4095]:
flag = numpy.ones(1) * i
result = self.check.get_quality_mask(flag)
self.assertNotEqual(1, result[0],
'Quality level should NOT be 1 for ' + str(i))
def test_get_quality_flag_Q0(self):
# 255: 00000 1111 1111
# everything below should be quality level 0
for i in range(1, 256):
flag = numpy.ones(1) * i
result = self.check.get_quality_mask(flag)
self.assertEqual(0, result[0],
'Quality level should be 0 for ' + str(i))
# 3855: 1111 0000 1111 -> also Q0
# 257: 0001 0000 0001
flag = numpy.ones(1) * 3855
result = self.check.get_quality_mask(flag)
self.assertEqual(0, result[0], 'Quality level should be 0 for 3855')
# 256: 0001 0000 0000 -> not Q0
flag = numpy.ones(1) * 256
result = self.check.get_quality_mask(flag)
self.assertNotEqual(0, result[0],
'Quality level should NOT be 0 for 256')