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)