def ex_load_hdf5():
filename = "X:/gpm/level2/2A.GPM.Ku.V620160118.20160327-S004128-E011127.V04A.RT-H5"
# load rainbow file contents to dict
rbdict = read_generic_hdf5(filename)#, loaddata=False)
class DictEditor(HasTraits):
Object = Instance(object)
def __init__(self, obj, **traits):
super(DictEditor, self).__init__(**traits)
self.Object = obj
def trait_view(self, name=None, view_elements=None):
return View(
VGroup(
Item('Object',
label='Debug',
id='debug',
editor=ValueEditor(), # ValueEditor()
style='custom',
dock='horizontal',
show_label=False), ),
title='Dictionary Editor',
width=800,
height=600,
resizable=True)
def dic(my_data):
b = DictEditor(my_data)
b.configure_traits()
dic(rbdict)
class TestKNMIVolume(MeasuredDataVolume):
if has_data:
name = "hdf5/knmi_polar_volume.h5"
format = "ODIM"
volumes = 1
sweeps = 14
moments = ["DBZH"]
elevations = [
0.3,
0.4,
0.8,
1.1,
2.0,
3.0,
4.5,
6.0,
8.0,
10.0,
12.0,
15.0,
20.0,
25.0,
]
azimuths = [360] * sweeps
ranges = [320, 240, 240, 240, 240, 340, 340, 300, 300, 240, 240, 240, 240, 240]
data = io.read_generic_hdf5(util.get_wradlib_data_file(name))
dsdesc = "dataset{}"
mdesc = "data{}"
class TestGamicVolume(MeasuredDataVolume):
if has_data:
name = "hdf5/DWD-Vol-2_99999_20180601054047_00.h5"
format = "GAMIC"
volumes = 1
sweeps = 10
moments = [
"DBZH",
"DBZV",
"DBTH",
"DBTV",
"ZDR",
"VRADH",
"VRADV",
"WRADH",
"WRADV",
"PHIDP",
"KDP",
"RHOHV",
]
elevations = [28.0, 18.0, 14.0, 11.0, 8.2, 6.0, 4.5, 3.1, 1.7, 0.6]
azimuths = [361, 361, 361, 360, 361, 360, 360, 361, 360, 360]
ranges = [360, 500, 620, 800, 1050, 1400, 1000, 1000, 1000, 1000]
data = io.read_generic_hdf5(util.get_wradlib_data_file(name))
dsdesc = "scan{}"
mdesc = "moment_{}"
class TestGamicVolume(MeasuredDataVolume):
name = 'hdf5/DWD-Vol-2_99999_20180601054047_00.h5'
format = 'GAMIC'
volumes = 1
sweeps = 10
moments = [
'DBZH', 'DBZV', 'DBTH', 'DBTV', 'ZDR', 'VRADH', 'VRADV', 'WRADH',
'WRADV', 'PHIDP', 'KDP', 'RHOHV'
]
elevations = [28.0, 18.0, 14.0, 11.0, 8.2, 6.0, 4.5, 3.1, 1.7, 0.6]
azimuths = [361, 361, 361, 360, 361, 360, 360, 361, 360, 360]
ranges = [360, 500, 620, 800, 1050, 1400, 1000, 1000, 1000, 1000]
data = io.read_generic_hdf5(util.get_wradlib_data_file(name))
dsdesc = 'scan{}'
mdesc = 'moment_{}'
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 TestKNMIVolume(MeasuredDataVolume):
name = 'hdf5/knmi_polar_volume.h5'
format = 'ODIM'
volumes = 1
sweeps = 14
moments = ['DBZH']
elevations = [
0.3, 0.4, 0.8, 1.1, 2.0, 3.0, 4.5, 6.0, 8.0, 10.0, 12.0, 15.0, 20.0,
25.0
]
azimuths = [360] * sweeps
ranges = [
320, 240, 240, 240, 240, 340, 340, 300, 300, 240, 240, 240, 240, 240
]
data = io.read_generic_hdf5(util.get_wradlib_data_file(name))
dsdesc = 'dataset{}'
mdesc = 'data{}'
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 trait_view(self, name=None, view_elements=None):
return View(
VGroup(
Item('Object',
label='Debug',
id='debug',
editor=ValueEditor(), # ValueEditor()
style='custom',
dock='horizontal',
show_label=False), ),
title='Dictionary Editor',
width=800,
height=600,
resizable=True)
def dic(my_data):
b = DictEditor(my_data)
b.configure_traits()
dic(rbdict)
# =======================================================
if __name__ == '__main__':
# ex_load_hdf5()
filename = "X:/gpm/level2/2A.GPM.Ku.V620160118.20160327-S004128-E011127.V04A.RT-H5"
# load rainbow file contents to dict
out = read_generic_hdf5(filename)#, loaddata=False)
for key in out.keys():
print key
