def test_proj4_to_osr(self):
srs = georef.proj4_to_osr('+proj=lcc +lat_1=46.8 +lat_0=46.8 +lon_0=0 '
'+k_0=0.99987742 +x_0=600000 +y_0=2200000 '
'+a=6378249.2 +b=6356515 '
'+towgs84=-168,-60,320,0,0,0,0 '
'+pm=paris +units=m +no_defs')
p4 = srs.ExportToProj4()
srs2 = osr.SpatialReference()
srs2.ImportFromProj4(p4)
self.assertTrue(srs.IsSame(srs2))
self.assertRaises(ValueError,
lambda: georef.proj4_to_osr("+proj=lcc1"))
def test_proj4_to_osr(self):
srs = georef.proj4_to_osr('+proj=lcc +lat_1=46.8 +lat_0=46.8 +lon_0=0 '
'+k_0=0.99987742 +x_0=600000 +y_0=2200000 '
'+a=6378249.2 +b=6356515 '
'+towgs84=-168,-60,320,0,0,0,0 '
'+pm=paris +units=m +no_defs')
p4 = srs.ExportToProj4()
srs2 = osr.SpatialReference()
srs2.ImportFromProj4(p4)
self.assertTrue(srs.IsSame(srs2))
self.assertRaises(ValueError,
lambda: georef.proj4_to_osr("+proj=lcc1"))
def test_proj4_to_osr(self):
projstr = ('+proj=tmerc +lat_0=0 +lon_0=9 +k=1 '
'+x_0=3500000 +y_0=0 +ellps=bessel '
'+towgs84=598.1,73.7,418.2,0.202,0.045,-2.455,6.7 '
'+units=m +no_defs')
srs = georef.proj4_to_osr(projstr)
p4 = srs.ExportToProj4()
srs2 = osr.SpatialReference()
srs2.ImportFromProj4(p4)
self.assertTrue(srs.IsSame(srs2))
with self.assertRaises(ValueError):
georef.proj4_to_osr("+proj=lcc1")
def test_get_radolan_grid_equality(self):
# create radolan projection osr object
scale = (1. + np.sin(np.radians(60.))) / (1. + np.sin(np.radians(90.)))
dwd_string = ('+proj=stere +lat_0=90 +lat_ts=90 +lon_0=10 '
'+k={0:10.8f} +x_0=0 +y_0=0 +a=6370040 +b=6370040 '
'+to_meter=1000 +no_defs'.format(scale))
proj_stereo = georef.proj4_to_osr(dwd_string)
# create wgs84 projection osr object
proj_wgs = osr.SpatialReference()
proj_wgs.ImportFromEPSG(4326)
# transform radolan polar stereographic projection to wgs84 and wgs84
# to polar stereographic
# using osr transformation routines
radolan_grid_ll = georef.reproject(self.radolan_grid_xy,
projection_source=proj_stereo,
projection_target=proj_wgs)
radolan_grid_xy = georef.reproject(self.radolan_grid_ll,
projection_source=proj_wgs,
projection_target=proj_stereo)
# check source and target arrays for equality
self.assertTrue(np.allclose(radolan_grid_ll, self.radolan_grid_ll))
self.assertTrue(np.allclose(radolan_grid_xy, self.radolan_grid_xy))
def test_get_radolan_grid_equality(self):
# create radolan projection osr object
scale = (1. + np.sin(np.radians(60.))) / (1. + np.sin(np.radians(90.)))
dwd_string = ('+proj=stere +lat_0=90 +lat_ts=90 +lon_0=10 '
'+k={0:10.8f} +x_0=0 +y_0=0 +a=6370040 +b=6370040 '
'+to_meter=1000 +no_defs'.format(scale))
proj_stereo = georef.proj4_to_osr(dwd_string)
# create wgs84 projection osr object
proj_wgs = osr.SpatialReference()
proj_wgs.ImportFromEPSG(4326)
# transform radolan polar stereographic projection to wgs84 and wgs84
# to polar stereographic
# using osr transformation routines
radolan_grid_ll = georef.reproject(self.radolan_grid_xy,
projection_source=proj_stereo,
projection_target=proj_wgs)
radolan_grid_xy = georef.reproject(self.radolan_grid_ll,
projection_source=proj_wgs,
projection_target=proj_stereo)
# check source and target arrays for equality
self.assertTrue(np.allclose(radolan_grid_ll, self.radolan_grid_ll))
self.assertTrue(np.allclose(radolan_grid_xy, self.radolan_grid_xy))
radolan_grid_xy = georef.get_radolan_grid(900, 900)
radolan_grid_ll = georef.get_radolan_grid(900, 900, wgs84=True)
# check source and target arrays for equality
self.assertTrue(np.allclose(radolan_grid_ll, self.radolan_grid_ll))
self.assertTrue(np.allclose(radolan_grid_xy, self.radolan_grid_xy))
def setUp(self):
f = 'gpm/2A-CS-151E24S154E30S.GPM.Ku.V7-20170308.20141206-S095002-E095137.004383.V05A.HDF5' # noqa
gpm_file = util.get_wradlib_data_file(f)
pr_data = read_generic_hdf5(gpm_file)
pr_lon = pr_data['NS/Longitude']['data']
pr_lat = pr_data['NS/Latitude']['data']
zenith = pr_data['NS/PRE/localZenithAngle']['data']
wgs84 = georef.get_default_projection()
a = wgs84.GetSemiMajor()
b = wgs84.GetSemiMinor()
rad = georef.proj4_to_osr(
('+proj=aeqd +lon_0={lon:f} ' +
'+lat_0={lat:f} +a={a:f} +b={b:f}' + '').format(lon=pr_lon[68, 0],
lat=pr_lat[68, 0],
a=a,
b=b))
pr_x, pr_y = georef.reproject(pr_lon,
pr_lat,
projection_source=wgs84,
projection_target=rad)
self.re = georef.get_earth_radius(pr_lat[68, 0], wgs84) * 4. / 3.
self.pr_xy = np.dstack((pr_x, pr_y))
self.alpha = zenith
self.zt = 407000.
self.dr = 125.
self.bw_pr = 0.71
self.nbin = 176
self.nray = pr_lon.shape[1]
self.pr_out = np.array([[[[-58533.78453556, 124660.60390174],
[-58501.33048429, 124677.58873852]],
[[-53702.13393133, 127251.83656509],
[-53670.98686161, 127268.11882882]]],
[[[-56444.00788528, 120205.5374491],
[-56411.55421163, 120222.52300741]],
[[-51612.2360682, 122796.78620764],
[-51581.08938314, 122813.06920719]]]])
self.r_out = np.array(
[0., 125., 250., 375., 500., 625., 750., 875., 1000., 1125.])
self.z_out = np.array([
0., 119.51255112, 239.02510224, 358.53765337, 478.05020449,
597.56275561, 717.07530673, 836.58785786, 956.10040898,
1075.6129601
])
def setUp(self):
f = 'gpm/2A-CS-151E24S154E30S.GPM.Ku.V7-20170308.20141206-S095002-E095137.004383.V05A.HDF5' # noqa
gpm_file = util.get_wradlib_data_file(f)
pr_data = read_generic_hdf5(gpm_file)
pr_lon = pr_data['NS/Longitude']['data']
pr_lat = pr_data['NS/Latitude']['data']
zenith = pr_data['NS/PRE/localZenithAngle']['data']
wgs84 = georef.get_default_projection()
a = wgs84.GetSemiMajor()
b = wgs84.GetSemiMinor()
rad = georef.proj4_to_osr(('+proj=aeqd +lon_0={lon:f} ' +
'+lat_0={lat:f} +a={a:f} +b={b:f}' +
'').format(lon=pr_lon[68, 0],
lat=pr_lat[68, 0],
a=a, b=b))
pr_x, pr_y = georef.reproject(pr_lon, pr_lat,
projection_source=wgs84,
projection_target=rad)
self.re = georef.get_earth_radius(pr_lat[68, 0], wgs84) * 4. / 3.
self.pr_xy = np.dstack((pr_x, pr_y))
self.alpha = zenith
self.zt = 407000.
self.dr = 125.
self.bw_pr = 0.71
self.nbin = 176
self.nray = pr_lon.shape[1]
self.pr_out = np.array([[[[-58533.78453556, 124660.60390174],
[-58501.33048429, 124677.58873852]],
[[-53702.13393133, 127251.83656509],
[-53670.98686161, 127268.11882882]]],
[[[-56444.00788528, 120205.5374491],
[-56411.55421163, 120222.52300741]],
[[-51612.2360682, 122796.78620764],
[-51581.08938314, 122813.06920719]]]])
self.r_out = np.array([0., 125., 250., 375., 500., 625., 750., 875.,
1000., 1125.])
self.z_out = np.array([0., 119.51255112, 239.02510224, 358.53765337,
478.05020449, 597.56275561, 717.07530673,
836.58785786, 956.10040898, 1075.6129601])
class TestSatellite:
f = "gpm/2A-CS-151E24S154E30S.GPM.Ku.V7-20170308.20141206-S095002-E095137.004383.V05A.HDF5" # noqa
gpm_file = util.get_wradlib_data_file(f)
pr_data = wradlib.io.read_generic_hdf5(gpm_file)
pr_lon = pr_data["NS/Longitude"]["data"]
pr_lat = pr_data["NS/Latitude"]["data"]
zenith = pr_data["NS/PRE/localZenithAngle"]["data"]
wgs84 = georef.get_default_projection()
a = wgs84.GetSemiMajor()
b = wgs84.GetSemiMinor()
rad = georef.proj4_to_osr(
("+proj=aeqd +lon_0={lon:f} " + "+lat_0={lat:f} +a={a:f} +b={b:f}" + "").format(
lon=pr_lon[68, 0], lat=pr_lat[68, 0], a=a, b=b
)
)
pr_x, pr_y = georef.reproject(
pr_lon, pr_lat, projection_source=wgs84, projection_target=rad
)
re = georef.get_earth_radius(pr_lat[68, 0], wgs84) * 4.0 / 3.0
pr_xy = np.dstack((pr_x, pr_y))
alpha = zenith
zt = 407000.0
dr = 125.0
bw_pr = 0.71
nbin = 176
nray = pr_lon.shape[1]
pr_out = np.array(
[
[
[
[-58533.78453556, 124660.60390174],
[-58501.33048429, 124677.58873852],
],
[
[-53702.13393133, 127251.83656509],
[-53670.98686161, 127268.11882882],
],
],
[
[
[-56444.00788528, 120205.5374491],
[-56411.55421163, 120222.52300741],
],
[
[-51612.2360682, 122796.78620764],
[-51581.08938314, 122813.06920719],
],
],
]
)
r_out = np.array(
[0.0, 125.0, 250.0, 375.0, 500.0, 625.0, 750.0, 875.0, 1000.0, 1125.0]
)
z_out = np.array(
[
0.0,
119.51255112,
239.02510224,
358.53765337,
478.05020449,
597.56275561,
717.07530673,
836.58785786,
956.10040898,
1075.6129601,
]
)
def test_correct_parallax(self):
xy, r, z = georef.correct_parallax(self.pr_xy, self.nbin, self.dr, self.alpha)
pr_out = np.array(
[
[
[
[-16582.50734831, 35678.47219358],
[-16547.94607589, 35696.40777009],
],
[
[-11742.02016667, 38252.32622057],
[-11708.84553319, 38269.52268457],
],
],
[
[
[-14508.62005182, 31215.98689653],
[-14474.05905935, 31233.92329553],
],
[
[-9667.99183645, 33789.86576047],
[-9634.81750708, 33807.06305397],
],
],
]
)
r_out = np.array(
[0.0, 125.0, 250.0, 375.0, 500.0, 625.0, 750.0, 875.0, 1000.0, 1125.0]
)
z_out = np.array(
[
0.0,
118.78164113,
237.56328225,
356.34492338,
475.1265645,
593.90820563,
712.68984675,
831.47148788,
950.25312901,
1069.03477013,
]
)
np.testing.assert_allclose(xy[60:62, 0:2, 0:2, :], pr_out, rtol=1e-12)
np.testing.assert_allclose(r[0:10], r_out, rtol=1e-12)
np.testing.assert_allclose(z[0, 0, 0:10], z_out, rtol=1e-10)
def test_dist_from_orbit(self):
beta = abs(-17.04 + np.arange(self.nray) * self.bw_pr)
xy, r, z = georef.correct_parallax(self.pr_xy, self.nbin, self.dr, self.alpha)
dists = georef.dist_from_orbit(self.zt, self.alpha, beta, r, re=self.re)
bd = np.array(
[
426553.58667772,
426553.50342119,
426553.49658156,
426553.51025979,
426553.43461609,
426553.42515894,
426553.46559985,
426553.37020786,
426553.44407286,
426553.42173696,
]
)
sd = np.array(
[
426553.58667772,
424895.63462839,
423322.25176564,
421825.47714885,
420405.9414294,
419062.44208923,
417796.86827302,
416606.91482435,
415490.82582636,
414444.11587979,
]
)
np.testing.assert_allclose(dists[0:10, 0, 0], bd, rtol=1e-12)
np.testing.assert_allclose(dists[0, 0:10, 0], sd, rtol=1e-12)
