def test_plot_ppi(self):
ax, pm = vis.plot_ppi(self.img, re=6371000., ke=(4. / 3.))
ax, pm = vis.plot_ppi(self.img, self.r, self.az,
re=6371000., ke=(4. / 3.))
ax, pm = vis.plot_ppi(self.img, self.r, self.az, refrac=True,
re=6371000., ke=(4. / 3.))
ax, pm = vis.plot_ppi(self.img, self.r, self.az, refrac=True,
re=6371000., ke=(4. / 3.), ax=ax)
ax, pm = vis.plot_ppi(self.img, self.r, self.az, refrac=True,
re=6371000., ke=(4. / 3.), ax=212)
ax, pm = vis.plot_ppi(self.img, autoext=False)
vis.plot_ppi_crosshair(site=(0, 0), ranges=[2, 4, 8])
vis.plot_ppi_crosshair(site=(0, 0),
ranges=[2, 4, 8],
angles=[0, 45, 90, 180, 270],
line=dict(color='white',
linestyle='solid'))
ax, pm = vis.plot_ppi(self.img, site=(10., 45.), autoext=False,
proj=self.proj)
vis.plot_ppi_crosshair(site=(0, 0),
ranges=[2, 4, 8],
angles=[0, 45, 90, 180, 270],
proj=self.proj,
line=dict(color='white',
linestyle='solid'))
ax, pm = vis.plot_ppi(self.img, func='contour')
ax, pm = vis.plot_ppi(self.img, func='contourf')
def test_plot_cg_ppi(self):
cgax, pm = vis.plot_ppi(self.img, elev=2.0, cg=True)
cgax, pm = vis.plot_ppi(self.img, elev=2.0, cg=True, ax=cgax)
cgax, pm = vis.plot_ppi(self.img, elev=2.0, cg=True, ax=111)
cgax, pm = vis.plot_ppi(self.img, elev=2.0, cg=True, ax=121)
cgax, pm = vis.plot_ppi(self.img, autoext=False, cg=True)
cgax, pm = vis.plot_ppi(self.img, refrac=False, cg=True)
cgax, pm = vis.plot_ppi(self.img, func='contour', cg=True)
cgax, pm = vis.plot_ppi(self.img, func='contourf', cg=True)
def test_plot_cg_ppi(self):
cgax, pm = vis.plot_ppi(self.img, elev=2.0, cg=True)
cgax, pm = vis.plot_ppi(self.img, elev=2.0, cg=True, ax=cgax)
cgax, pm = vis.plot_ppi(self.img, elev=2.0, cg=True, ax=111)
cgax, pm = vis.plot_ppi(self.img, elev=2.0, cg=True, ax=121)
cgax, pm = vis.plot_ppi(self.img, autoext=False, cg=True)
cgax, pm = vis.plot_ppi(self.img, refrac=False, cg=True)
cgax, pm = vis.plot_ppi(self.img, func='contour', cg=True)
cgax, pm = vis.plot_ppi(self.img, func='contourf', cg=True)
def test_plot_cg_ppi(self):
cgax, pm = vis.plot_ppi(self.img, elev=2.0, cg=True)
cgax, pm = vis.plot_ppi(self.img, elev=2.0, cg=True, ax=cgax)
fig, ax = pl.subplots(2, 2)
self.assertRaises(TypeError,
lambda: vis.plot_ppi(self.img, elev=2.0,
cg=True, ax=ax[0, 0]))
cgax, pm = vis.plot_ppi(self.img, elev=2.0, cg=True, ax=111)
cgax, pm = vis.plot_ppi(self.img, elev=2.0, cg=True, ax=121)
cgax, pm = vis.plot_ppi(self.img, autoext=False, cg=True)
cgax, pm = vis.plot_ppi(self.img, refrac=False, cg=True)
cgax, pm = vis.plot_ppi(self.img, func='contour', cg=True)
cgax, pm = vis.plot_ppi(self.img, func='contourf', cg=True)
def test_plot_cg_ppi(self):
cgax, pm = vis.plot_ppi(self.img, elev=2.0, cg=True)
cgax, pm = vis.plot_ppi(self.img, elev=2.0, cg=True, ax=cgax)
fig, ax = pl.subplots(2, 2)
self.assertRaises(
TypeError,
lambda: vis.plot_ppi(self.img, elev=2.0, cg=True, ax=ax[0, 0]))
cgax, pm = vis.plot_ppi(self.img, elev=2.0, cg=True, ax=111)
cgax, pm = vis.plot_ppi(self.img, elev=2.0, cg=True, ax=121)
cgax, pm = vis.plot_ppi(self.img, autoext=False, cg=True)
cgax, pm = vis.plot_ppi(self.img, refrac=False, cg=True)
cgax, pm = vis.plot_ppi(self.img, func='contour', cg=True)
cgax, pm = vis.plot_ppi(self.img, func='contourf', cg=True)
def test_plot_ppi(self):
pl.figure()
proj = georef.create_osr("dwd-radolan")
ax, pm = vis.plot_ppi(self.img, re=6371000., ke=4./3.)
ax, pm = vis.plot_ppi(self.img, autoext=False)
vis.plot_ppi_crosshair(site=(0, 0),
ranges=[2, 4, 8],
angles=[0, 45, 90, 180, 270],
line=dict(color='white',
linestyle='solid'))
pl.figure()
ax, pm = vis.plot_ppi(self.img, site=(10., 45.), autoext=False, proj=proj)
vis.plot_ppi_crosshair(site=(0, 0),
ranges=[2, 4, 8],
angles=[0, 45, 90, 180, 270],
proj=proj,
line=dict(color='white',
linestyle='solid'))
def test_plot_ppi(self):
ax, pm = vis.plot_ppi(self.img, re=6371000., ke=(4. / 3.))
ax, pm = vis.plot_ppi(self.img, autoext=False)
vis.plot_ppi_crosshair(site=(0, 0),
ranges=[2, 4, 8],
angles=[0, 45, 90, 180, 270],
line=dict(color='white', linestyle='solid'))
ax, pm = vis.plot_ppi(self.img,
site=(10., 45.),
autoext=False,
proj=self.proj)
vis.plot_ppi_crosshair(site=(0, 0),
ranges=[2, 4, 8],
angles=[0, 45, 90, 180, 270],
proj=self.proj,
line=dict(color='white', linestyle='solid'))
ax, pm = vis.plot_ppi(self.img, func='contour')
ax, pm = vis.plot_ppi(self.img, func='contourf')
def test_plot_ppi_cartopy(self):
if cartopy:
site = (7, 45, 0.)
map_proj = cartopy.crs.Mercator(central_longitude=site[1])
ax, pm = vis.plot_ppi(self.img, self.r, self.az, proj=map_proj)
self.assertIsInstance(ax, cartopy.mpl.geoaxes.GeoAxes)
fig = pl.figure(figsize=(10, 10))
ax = fig.add_subplot(111, projection=map_proj)
self.da_ppi.wradlib.plot_ppi(ax=ax)
ax.gridlines(draw_labels=True)
def test_plot_ppi_cartopy(self):
if cartopy:
site = (7, 45, 0.)
map_proj = cartopy.crs.Mercator(central_longitude=site[1])
ax, pm = vis.plot_ppi(self.img, self.r, self.az, proj=map_proj)
self.assertIsInstance(ax, cartopy.mpl.geoaxes.GeoAxes)
fig = pl.figure(figsize=(10, 10))
ax = fig.add_subplot(111, projection=map_proj)
self.da_ppi.wradlib.plot_ppi(ax=ax)
ax.gridlines(draw_labels=True)
def test_plot_ppi(self):
pl.figure()
proj = georef.create_osr("dwd-radolan")
ax, pm = vis.plot_ppi(self.img, re=6371000., ke=4. / 3.)
ax, pm = vis.plot_ppi(self.img, autoext=False)
vis.plot_ppi_crosshair(site=(0, 0),
ranges=[2, 4, 8],
angles=[0, 45, 90, 180, 270],
line=dict(color='white', linestyle='solid'))
pl.figure()
ax, pm = vis.plot_ppi(self.img,
site=(10., 45.),
autoext=False,
proj=proj)
vis.plot_ppi_crosshair(site=(0, 0),
ranges=[2, 4, 8],
angles=[0, 45, 90, 180, 270],
proj=proj,
line=dict(color='white', linestyle='solid'))
def test_plot_ppi_cartopy(self):
if cartopy:
if (LooseVersion(cartopy.__version__) < LooseVersion("0.18.0")) and (
LooseVersion(mpl.__version__) >= LooseVersion("3.3.0")
):
pytest.skip("fails for cartopy < 0.18.0 and matplotlib >= 3.3.0")
site = (7, 45, 0.0)
map_proj = cartopy.crs.Mercator(central_longitude=site[1])
ax, pm = vis.plot_ppi(self.img, self.r, self.az, proj=map_proj)
assert isinstance(ax, cartopy.mpl.geoaxes.GeoAxes)
fig = pl.figure(figsize=(10, 10))
ax = fig.add_subplot(111, projection=map_proj)
self.da_ppi.wradlib.plot_ppi(ax=ax)
ax.gridlines(draw_labels=True)
def test_plot_cg_ppi(self):
cgax, pm = vis.plot_ppi(self.img, elev=2.0, cg=True)
cgax, pm = vis.plot_ppi(self.img, autoext=False, cg=True)
cgax, pm = vis.plot_ppi(self.img, refrac=False, cg=True)
cgax, pm = vis.plot_ppi(self.img, func='contour', cg=True)
cgax, pm = vis.plot_ppi(self.img, func='contourf', cg=True)
with self.assertWarns(UserWarning):
cgax, pm = vis.plot_ppi(self.img, func='contourf',
proj=self.proj, cg=True)
def test_plot_cg_ppi(self):
cgax, pm = vis.plot_ppi(self.img, elev=2.0, cg=True)
cgax, pm = vis.plot_ppi(self.img, autoext=False, cg=True)
cgax, pm = vis.plot_ppi(self.img, refrac=False, cg=True)
cgax, pm = vis.plot_ppi(self.img, func='contour', cg=True)
cgax, pm = vis.plot_ppi(self.img, func='contourf', cg=True)
with self.assertWarns(UserWarning):
cgax, pm = vis.plot_ppi(self.img,
func='contourf',
proj=self.proj,
cg=True)
def ex_clutter_gabella():
# load the example data
import numpy as np
# Todo: link right data set
testdata = np.loadtxt(os.path.dirname(__file__) + '/' + 'data/polar_dBZ_fbg.gz')
# calculate the clutter map
clmap = clutter.filter_gabella(testdata,
wsize=5,
thrsnorain=0.,
tr1=6.,
n_p=8,
tr2=1.3)
# visualize the result
ax, pm = vis.plot_ppi(clmap)
ax.set_title('cluttermap')
pl.show()
def ex_clutter_gabella():
# load the example data
import numpy as np
# Todo: link right data set
testdata = np.loadtxt(
os.path.dirname(__file__) + '/' + 'data/polar_dBZ_fbg.gz')
# calculate the clutter map
clmap = clutter.filter_gabella(testdata,
wsize=5,
thrsnorain=0.,
tr1=6.,
n_p=8,
tr2=1.3)
# visualize the result
ax, pm = vis.plot_ppi(clmap)
ax.set_title('cluttermap')
pl.show()
def ex_clutter_cloud():
# read the radar volume scan
path = os.path.dirname(__file__) + '/'
pvol = io.read_OPERA_hdf5(path + 'data/20130429043000.rad.bewid.pvol.dbzh.scan1.hdf')
# Count the number of dataset
ntilt = 1
for i in range(100):
try:
pvol["dataset%d/what" % ntilt]
ntilt += 1
except Exception:
ntilt -= 1
break
# Construct radar values
nrays = int(pvol["dataset1/where"]["nrays"])
nbins = int(pvol["dataset1/where"]["nbins"])
val = np.empty((ntilt, nrays, nbins))
for t in range(ntilt):
val[t, ...] = pvol["dataset%d/data1/data" % (t + 1)]
gain = float(pvol["dataset1/data1/what"]["gain"])
offset = float(pvol["dataset1/data1/what"]["offset"])
val = val * gain + offset
# Construct radar coordinates
rscale = int(pvol["dataset1/where"]["rscale"])
coord = np.empty((ntilt, nrays, nbins, 3))
for t in range(ntilt):
elangle = pvol["dataset%d/where" % (t + 1)]["elangle"]
coord[t, ...] = georef.sweep_centroids(nrays, rscale, nbins, elangle)
ascale = math.pi / nrays
sitecoords = (pvol["where"]["lon"], pvol["where"]["lat"], pvol["where"]["height"])
proj_radar = georef.create_osr("aeqd", lat_0=pvol["where"]["lat"], lon_0=pvol["where"]["lon"])
coord[..., 0], coord[..., 1], coord[..., 2] = georef.polar2lonlatalt_n(coord[..., 0], np.degrees(coord[..., 1]),
coord[..., 2], sitecoords, re=6370040.,
ke=4. / 3.)
coord = georef.reproject(coord, projection_target=proj_radar)
# Construct collocated satellite data
sat_gdal = io.read_safnwc(path + 'data/SAFNWC_MSG3_CT___201304290415_BEL_________.h5')
val_sat = georef.read_gdal_values(sat_gdal)
coord_sat = georef.read_gdal_coordinates(sat_gdal)
proj_sat = georef.read_gdal_projection(sat_gdal)
coord_sat = georef.reproject(coord_sat, projection_source=proj_sat, projection_target=proj_radar)
coord_radar = coord
interp = ipol.Nearest(coord_sat[..., 0:2].reshape(-1, 2), coord_radar[..., 0:2].reshape(-1, 2))
val_sat = interp(val_sat.ravel()).reshape(val.shape)
# Estimate localisation errors
timelag = 9 * 60
wind = 10
error = np.absolute(timelag) * wind
# Identify clutter based on collocated cloudtype
clutter = cl.filter_cloudtype(val[0, ...], val_sat[0, ...], scale=rscale, smoothing=error)
# visualize the result
plt.figure()
vis.plot_ppi(clutter)
plt.suptitle('clutter')
plt.savefig('clutter_cloud_example_1.png')
plt.figure()
vis.plot_ppi(val_sat[0, ...])
plt.suptitle('satellite')
plt.savefig('clutter_cloud_example_2.png')
plt.show()
def test_plot_ppi(self):
ax, pm = vis.plot_ppi(self.img, re=6371000.0, ke=(4.0 / 3.0))
ax, pm = vis.plot_ppi(self.img, self.r, self.az, re=6371000.0, ke=(4.0 / 3.0))
ax, pm = vis.plot_ppi(
self.img, self.r, self.az, re=6371000.0, ke=(4.0 / 3.0), ax=ax
)
ax, pm = vis.plot_ppi(
self.img, self.r, self.az, re=6371000.0, ke=(4.0 / 3.0), ax=212
)
ax, pm = vis.plot_ppi(self.img)
vis.plot_ppi_crosshair(site=(0, 0, 0), ranges=[2, 4, 8])
vis.plot_ppi_crosshair(
site=(0, 0, 0),
ranges=[2, 4, 8],
angles=[0, 45, 90, 180, 270],
line=dict(color="white", linestyle="solid"),
)
ax, pm = vis.plot_ppi(self.img, self.r, site=(10.0, 45.0, 0.0), proj=self.proj)
vis.plot_ppi_crosshair(
site=(10.0, 45.0, 0.0),
ranges=[2, 4, 8],
angles=[0, 45, 90, 180, 270],
proj=self.proj,
line=dict(color="white", linestyle="solid"),
)
ax, pm = vis.plot_ppi(self.img, func="contour")
ax, pm = vis.plot_ppi(self.img, func="contourf")
ax, pm = vis.plot_ppi(self.img, self.r, self.az, proj=self.proj, site=(0, 0, 0))
with pytest.warns(UserWarning):
ax, pm = vis.plot_ppi(self.img, site=(10.0, 45.0, 0.0), proj=self.proj)
with pytest.warns(UserWarning):
ax, pm = vis.plot_ppi(self.img, proj=None, site=(0, 0, 0))
with pytest.raises(TypeError):
ax, pm = vis.plot_ppi(self.img, proj=self.proj)
with pytest.raises(ValueError):
ax, pm = vis.plot_ppi(self.img, site=(0, 0), proj=self.proj)
with pytest.raises(ValueError):
vis.plot_ppi_crosshair(site=(0, 0), ranges=[2, 4, 8])
def test_plot_cg_ppi(self):
cgax, pm = vis.plot_ppi(self.img, elev=2.0, proj="cg")
cgax, pm = vis.plot_ppi(self.img, elev=2.0, proj="cg", site=(0, 0, 0))
cgax, pm = vis.plot_ppi(self.img, elev=2.0, proj="cg", ax=cgax)
fig, ax = pl.subplots(2, 2)
with pytest.raises(TypeError):
vis.plot_ppi(self.img, elev=2.0, proj="cg", ax=ax[0, 0])
cgax, pm = vis.plot_ppi(self.img, elev=2.0, proj="cg", ax=111)
cgax, pm = vis.plot_ppi(self.img, elev=2.0, proj="cg", ax=121)
cgax, pm = vis.plot_ppi(self.img, proj="cg")
cgax, pm = vis.plot_ppi(self.img, func="contour", proj="cg")
cgax, pm = vis.plot_ppi(self.img, func="contourf", proj="cg")
cgax, pm = vis.plot_ppi(self.img, func="contourf", proj="cg")
def test_plot_cg_ppi_py3k(self):
with self.assertWarns(UserWarning):
cgax, pm = vis.plot_ppi(self.img,
func='contourf',
proj=self.proj,
cg=True)
def test_plot_cg_ppi(self):
# DeprecationTests
with self.assertWarns(DeprecationWarning):
cgax, pm = vis.plot_ppi(self.img, autoext=True, cg=True)
with self.assertWarns(DeprecationWarning):
cgax, pm = vis.plot_ppi(self.img, autoext=False, cg=True)
with self.assertWarns(DeprecationWarning):
cgax, pm = vis.plot_ppi(self.img, refrac=True, cg=True)
with self.assertWarns(DeprecationWarning):
cgax, pm = vis.plot_ppi(self.img, refrac=False, cg=True)
cgax, pm = vis.plot_ppi(self.img, elev=2.0, cg=True)
cgax, pm = vis.plot_ppi(self.img,
elev=2.0,
cg=True,
proj=self.proj,
site=(0, 0, 0))
cgax, pm = vis.plot_ppi(self.img, elev=2.0, proj='cg')
cgax, pm = vis.plot_ppi(self.img, elev=2.0, cg=True, ax=cgax)
fig, ax = pl.subplots(2, 2)
self.assertRaises(
TypeError,
lambda: vis.plot_ppi(self.img, elev=2.0, cg=True, ax=ax[0, 0]))
cgax, pm = vis.plot_ppi(self.img, elev=2.0, cg=True, ax=111)
cgax, pm = vis.plot_ppi(self.img, elev=2.0, cg=True, ax=121)
cgax, pm = vis.plot_ppi(self.img, cg=True)
cgax, pm = vis.plot_ppi(self.img, func='contour', cg=True)
cgax, pm = vis.plot_ppi(self.img, func='contourf', cg=True)
cgax, pm = vis.plot_ppi(self.img, func='contourf', cg=True)
with self.assertWarns(DeprecationWarning):
cgax, pm = vis.plot_ppi(self.img,
func='contourf',
proj=self.proj,
site=(0, 0, 0),
cg=True)
def test_plot_ppi(self):
# DeprecationTests
with self.assertWarns(DeprecationWarning):
ax, pm = vis.plot_ppi(self.img, autoext=True)
with self.assertWarns(DeprecationWarning):
ax, pm = vis.plot_ppi(self.img, autoext=False)
with self.assertWarns(DeprecationWarning):
ax, pm = vis.plot_ppi(self.img, refrac=True)
with self.assertWarns(DeprecationWarning):
ax, pm = vis.plot_ppi(self.img, refrac=False)
ax, pm = vis.plot_ppi(self.img, re=6371000., ke=(4. / 3.))
ax, pm = vis.plot_ppi(self.img, self.r, self.az,
re=6371000., ke=(4. / 3.))
ax, pm = vis.plot_ppi(self.img, self.r, self.az,
re=6371000., ke=(4. / 3.), ax=ax)
ax, pm = vis.plot_ppi(self.img, self.r, self.az,
re=6371000., ke=(4. / 3.), ax=212)
ax, pm = vis.plot_ppi(self.img)
vis.plot_ppi_crosshair(site=(0, 0), ranges=[2, 4, 8])
vis.plot_ppi_crosshair(site=(0, 0),
ranges=[2, 4, 8],
angles=[0, 45, 90, 180, 270],
line=dict(color='white',
linestyle='solid'))
ax, pm = vis.plot_ppi(self.img, site=(10., 45., 0.),
proj=self.proj)
vis.plot_ppi_crosshair(site=(0, 0),
ranges=[2, 4, 8],
angles=[0, 45, 90, 180, 270],
proj=self.proj,
line=dict(color='white',
linestyle='solid'))
ax, pm = vis.plot_ppi(self.img, func='contour')
ax, pm = vis.plot_ppi(self.img, func='contourf')
with self.assertRaises(TypeError):
ax, pm = vis.plot_ppi(self.img, proj=self.proj)
with self.assertWarns(UserWarning):
ax, pm = vis.plot_ppi(self.img, proj=None,
site=(0, 0, 0))
with self.assertWarns(UserWarning):
ax, pm = vis.plot_ppi(self.img, proj=None,
site=(0, 0))
ax, pm = vis.plot_ppi(self.img, self.r, self.az, proj=self.proj,
site=(0, 0, 0))
def test_plot_cg_ppi(self):
cgax, pm = vis.plot_ppi(self.img, elev=2.0, proj='cg')
cgax, pm = vis.plot_ppi(self.img, elev=2.0, proj='cg', site=(0, 0, 0))
cgax, pm = vis.plot_ppi(self.img, elev=2.0, proj='cg', ax=cgax)
fig, ax = pl.subplots(2, 2)
with self.assertRaises(TypeError):
vis.plot_ppi(self.img, elev=2.0, proj='cg', ax=ax[0, 0])
cgax, pm = vis.plot_ppi(self.img, elev=2.0, proj='cg', ax=111)
cgax, pm = vis.plot_ppi(self.img, elev=2.0, proj='cg', ax=121)
cgax, pm = vis.plot_ppi(self.img, proj='cg')
cgax, pm = vis.plot_ppi(self.img, func='contour', proj='cg')
cgax, pm = vis.plot_ppi(self.img, func='contourf', proj='cg')
cgax, pm = vis.plot_ppi(self.img, func='contourf', proj='cg')
def ex_clutter_cloud():
# read the radar volume scan
path = os.path.dirname(__file__) + '/'
pvol = io.read_OPERA_hdf5(
path + 'data/20130429043000.rad.bewid.pvol.dbzh.scan1.hdf')
# Count the number of dataset
ntilt = 1
for i in range(100):
try:
pvol["dataset%d/what" % ntilt]
ntilt += 1
except Exception:
ntilt -= 1
break
# Construct radar values
nrays = int(pvol["dataset1/where"]["nrays"])
nbins = int(pvol["dataset1/where"]["nbins"])
val = np.empty((ntilt, nrays, nbins))
for t in range(ntilt):
val[t, ...] = pvol["dataset%d/data1/data" % (t + 1)]
gain = float(pvol["dataset1/data1/what"]["gain"])
offset = float(pvol["dataset1/data1/what"]["offset"])
val = val * gain + offset
# Construct radar coordinates
rscale = int(pvol["dataset1/where"]["rscale"])
coord = np.empty((ntilt, nrays, nbins, 3))
for t in range(ntilt):
elangle = pvol["dataset%d/where" % (t + 1)]["elangle"]
coord[t, ...] = georef.sweep_centroids(nrays, rscale, nbins, elangle)
ascale = math.pi / nrays
sitecoords = (pvol["where"]["lon"], pvol["where"]["lat"],
pvol["where"]["height"])
proj_radar = georef.create_osr("aeqd",
lat_0=pvol["where"]["lat"],
lon_0=pvol["where"]["lon"])
coord[..., 0], coord[..., 1], coord[..., 2] = georef.polar2lonlatalt_n(
coord[..., 0],
np.degrees(coord[..., 1]),
coord[..., 2],
sitecoords,
re=6370040.,
ke=4. / 3.)
coord = georef.reproject(coord, projection_target=proj_radar)
# Construct collocated satellite data
sat_gdal = io.read_safnwc(
path + 'data/SAFNWC_MSG3_CT___201304290415_BEL_________.h5')
val_sat = georef.read_gdal_values(sat_gdal)
coord_sat = georef.read_gdal_coordinates(sat_gdal)
proj_sat = georef.read_gdal_projection(sat_gdal)
coord_sat = georef.reproject(coord_sat,
projection_source=proj_sat,
projection_target=proj_radar)
coord_radar = coord
interp = ipol.Nearest(coord_sat[..., 0:2].reshape(-1, 2),
coord_radar[..., 0:2].reshape(-1, 2))
val_sat = interp(val_sat.ravel()).reshape(val.shape)
# Estimate localisation errors
timelag = 9 * 60
wind = 10
error = np.absolute(timelag) * wind
# Identify clutter based on collocated cloudtype
clutter = cl.filter_cloudtype(val[0, ...],
val_sat[0, ...],
scale=rscale,
smoothing=error)
# visualize the result
plt.figure()
vis.plot_ppi(clutter)
plt.suptitle('clutter')
plt.savefig('clutter_cloud_example_1.png')
plt.figure()
vis.plot_ppi(val_sat[0, ...])
plt.suptitle('satellite')
plt.savefig('clutter_cloud_example_2.png')
plt.show()
def test_plot_cg_ppi_py3k(self):
with self.assertWarns(UserWarning):
cgax, pm = vis.plot_ppi(self.img, func='contourf',
proj=self.proj, cg=True)
def test_plot_ppi(self):
ax, pm = vis.plot_ppi(self.img, re=6371000., ke=(4. / 3.))
ax, pm = vis.plot_ppi(self.img,
self.r,
self.az,
re=6371000.,
ke=(4. / 3.))
ax, pm = vis.plot_ppi(self.img,
self.r,
self.az,
re=6371000.,
ke=(4. / 3.),
ax=ax)
ax, pm = vis.plot_ppi(self.img,
self.r,
self.az,
re=6371000.,
ke=(4. / 3.),
ax=212)
ax, pm = vis.plot_ppi(self.img)
vis.plot_ppi_crosshair(site=(0, 0, 0), ranges=[2, 4, 8])
vis.plot_ppi_crosshair(site=(0, 0, 0),
ranges=[2, 4, 8],
angles=[0, 45, 90, 180, 270],
line=dict(color='white', linestyle='solid'))
ax, pm = vis.plot_ppi(self.img,
self.r,
site=(10., 45., 0.),
proj=self.proj)
vis.plot_ppi_crosshair(site=(10., 45., 0.),
ranges=[2, 4, 8],
angles=[0, 45, 90, 180, 270],
proj=self.proj,
line=dict(color='white', linestyle='solid'))
ax, pm = vis.plot_ppi(self.img, func='contour')
ax, pm = vis.plot_ppi(self.img, func='contourf')
ax, pm = vis.plot_ppi(self.img,
self.r,
self.az,
proj=self.proj,
site=(0, 0, 0))
with self.assertWarns(UserWarning):
ax, pm = vis.plot_ppi(self.img,
site=(10., 45., 0.),
proj=self.proj)
with self.assertWarns(UserWarning):
ax, pm = vis.plot_ppi(self.img, proj=None, site=(0, 0, 0))
with self.assertRaises(TypeError):
ax, pm = vis.plot_ppi(self.img, proj=self.proj)
with self.assertRaises(ValueError):
ax, pm = vis.plot_ppi(self.img, site=(0, 0), proj=self.proj)
with self.assertRaises(ValueError):
vis.plot_ppi_crosshair(site=(0, 0), ranges=[2, 4, 8])
def test_plot_cg_ppi(self):
# DeprecationTests
with self.assertWarns(DeprecationWarning):
cgax, pm = vis.plot_ppi(self.img, autoext=True, cg=True)
with self.assertWarns(DeprecationWarning):
cgax, pm = vis.plot_ppi(self.img, autoext=False, cg=True)
with self.assertWarns(DeprecationWarning):
cgax, pm = vis.plot_ppi(self.img, refrac=True, cg=True)
with self.assertWarns(DeprecationWarning):
cgax, pm = vis.plot_ppi(self.img, refrac=False, cg=True)
cgax, pm = vis.plot_ppi(self.img, elev=2.0, cg=True)
cgax, pm = vis.plot_ppi(self.img, elev=2.0, cg=True, proj=self.proj,
site=(0, 0, 0))
cgax, pm = vis.plot_ppi(self.img, elev=2.0, proj='cg')
cgax, pm = vis.plot_ppi(self.img, elev=2.0, cg=True, ax=cgax)
fig, ax = pl.subplots(2, 2)
self.assertRaises(TypeError,
lambda: vis.plot_ppi(self.img, elev=2.0,
cg=True, ax=ax[0, 0]))
cgax, pm = vis.plot_ppi(self.img, elev=2.0, cg=True, ax=111)
cgax, pm = vis.plot_ppi(self.img, elev=2.0, cg=True, ax=121)
cgax, pm = vis.plot_ppi(self.img, cg=True)
cgax, pm = vis.plot_ppi(self.img, func='contour', cg=True)
cgax, pm = vis.plot_ppi(self.img, func='contourf', cg=True)
cgax, pm = vis.plot_ppi(self.img, func='contourf', cg=True)
with self.assertWarns(DeprecationWarning):
cgax, pm = vis.plot_ppi(self.img, func='contourf',
proj=self.proj, site=(0, 0, 0),
cg=True)
