def test_inverted_poly_simple_hole(self):
proj = ccrs.NorthPolarStereo()
poly = sgeom.Polygon([(0, 0), (-90, 0), (-180, 0), (-270, 0)],
[[(0, -30), (90, -30), (180, -30), (270, -30)]])
multi_polygon = proj.project_geometry(poly)
# Check the structure
self.assertEqual(len(multi_polygon), 1)
self.assertEqual(len(multi_polygon[0].interiors), 1)
# Check the rough shape
polygon = multi_polygon[0]
self._assert_bounds(polygon.bounds, -2.4e7, -2.4e7, 2.4e7, 2.4e7, 1e6)
self._assert_bounds(polygon.interiors[0].bounds, -1.2e7, -1.2e7, 1.2e7,
1.2e7, 1e6)
def test_quiver_regrid():
x = np.arange(-60, 42.5, 2.5)
y = np.arange(30, 72.5, 2.5)
x2d, y2d = np.meshgrid(x, y)
u = np.cos(np.deg2rad(y2d))
v = np.cos(2. * np.deg2rad(x2d))
mag = (u**2 + v**2)**.5
plot_extent = [-60, 40, 30, 70]
plt.figure(figsize=(6, 3))
ax = plt.axes(projection=ccrs.NorthPolarStereo())
ax.set_extent(plot_extent, crs=ccrs.PlateCarree())
ax.coastlines()
ax.quiver(x, y, u, v, mag, transform=ccrs.PlateCarree(), regrid_shape=30)
def make_plot(srcCoord, srcData, dstCoord, dstData, month=1):
it = month-1
fig = plt.figure( figsize=(20,8) )
gs = gridspec.GridSpec(2, 2, height_ratios=(30,1))
ax1 = fig.add_subplot(gs[0], projection=ccrs.NorthPolarStereo())
ax1.set_extent([-180,180,40,90], ccrs.PlateCarree())
pcm = ax1.pcolormesh(srcCoord[0], srcCoord[1], srcData, cmap = 'gist_ncar',
transform=ccrs.PlateCarree(), vmin = 0, vmax = 6)
ax1.add_feature(cfeature.COASTLINE)
ax1.set_title('PIOMAS Mask - Original')
ax2 = fig.add_subplot(gs[1], projection=ccrs.NorthPolarStereo())
ax2.set_extent([-180,180,40,90], ccrs.PlateCarree())
ax2.pcolormesh(dstCoord[0], dstCoord[1], dstData, cmap = 'gist_ncar',
transform=ccrs.PlateCarree(), vmin = 0, vmax = 6)
ax2.add_feature(cfeature.COASTLINE)
ax2.set_title('Regridded')
plt.show()
def multi_polar_axis(ncols,
nrows,
Nplots=None,
sizefcter=1,
extent=None,
central_longitude=-45):
if not Nplots:
Nplots = ncols * nrows
# Create a grid of plots
f, (axes) = plt.subplots(
ncols=ncols,
nrows=nrows,
subplot_kw={
'projection':
ccrs.NorthPolarStereo(central_longitude=central_longitude)
})
f.set_size_inches(ncols * 1.5 * sizefcter, nrows * 2 * sizefcter)
axes = axes.reshape(-1)
for (i, ax) in enumerate(axes):
axes[i].coastlines(linewidth=0.2, color='black', resolution='50m')
axes[i].gridlines(crs=ccrs.PlateCarree(),
linestyle='--',
linewidth=0.20,
color='grey')
#ax.set_extent([0, 359.9, 57, 90], crs=ccrs.PlateCarree())
# Full NSIDC extent
if not extent:
axes[i].set_extent(
[-3850000 * 0.9, 3725000 * 0.8, -5325000 * 0.7, 5850000 * 0.9],
crs=ccrs.NorthPolarStereo(central_longitude=central_longitude))
else: # Set Regional extent
axes[i].set_extent(
extent,
crs=ccrs.NorthPolarStereo(central_longitude=central_longitude))
if i >= Nplots - 1:
f.delaxes(axes[i])
return (f, axes)
def set_up_subplot(fig,subplot=111):
crs_np = ccrs.NorthPolarStereo(central_longitude=-45)
ax = fig.add_subplot(subplot,projection=crs_np)
xll, yll = crs_np.transform_point(279.26,33.92, ccrs.Geodetic())
xur, yur = crs_np.transform_point(102.34,31.37, ccrs.Geodetic())
ax.set_extent([xll,xur,yll,yur],crs=crs_np)
ax.add_feature(cfeature.OCEAN,facecolor='c', zorder=1)
ax.add_feature(cfeature.LAND,facecolor='0.3', zorder=3)
ax.add_feature(cfeature.LAKES,facecolor='c',linestyle='-', edgecolor='k',zorder=3)
ax.coastlines(resolution='110m',linewidth=1,color='k',zorder=3)
return ax
def test_fetch_img_reprojected_twoparts(self):
source = ogc.WMTSRasterSource(self.URI, self.layer_name)
extent = [-10, 12, 48, 50]
images = source.fetch_raster(ccrs.NorthPolarStereo(), extent, (30, 30))
# Check for 2 results in this case.
assert len(images) == 2
im1, im2 = images
# Check image arrays is as expected (more or less).
assert np.array(im1.image).shape == (42, 42, 4)
assert np.array(im2.image).shape == (42, 42, 4)
# When reprojected, extent is exactly what you asked for.
assert im1.extent == extent
assert im2.extent == extent
def test_streamplot():
x = np.arange(-60, 42.5, 2.5)
y = np.arange(30, 72.5, 2.5)
x2d, y2d = np.meshgrid(x, y)
u = np.cos(np.deg2rad(y2d))
v = np.cos(2. * np.deg2rad(x2d))
mag = (u**2 + v**2)**.5
plot_extent = [-60, 40, 30, 70]
plt.figure(figsize=(6, 3))
ax = plt.axes(projection=ccrs.NorthPolarStereo())
ax.set_extent(plot_extent, crs=ccrs.PlateCarree())
ax.coastlines()
ax.streamplot(x, y, u, v, transform=ccrs.PlateCarree(),
density=(1.5, 2), color=mag, linewidth=2*mag)
def plot(lat, lon, Z, date, time, intfactor, maxtec, aacgm, plottype, extent):
tecmap = plt.figure(figsize=(11, 8))
if plottype == 'Northern Hemisphere':
map_proj = ccrs.NorthPolarStereo()
elif plottype == 'Southern Hemisphere':
map_proj = ccrs.SouthPolarStereo()
elif plottype == 'Global':
map_proj = ccrs.PlateCarree()
if aacgm:
ax = tecmap.add_subplot(projection='aacgmv2', map_projection=map_proj)
ax.overaly_coast_lakes(coords="aacgmv2", plot_date=date)
if map_proj == ccrs.PlateCarree():
mesh = ax.pcolor(lon,
lat,
Z,
cmap='jet',
vmax=maxtec,
transform=ccrs.PlateCarree())
else:
mesh = ax.scatter(lon,
lat,
c=Z,
cmap='jet',
vmax=maxtec,
transform=ccrs.PlateCarree())
else:
#usepcolormesh in
ax = plt.axes(projection=map_proj)
ax.add_feature(cfeature.COASTLINE)
ax.add_feature(cfeature.LAKES)
mesh = ax.pcolormesh(lon,
lat,
Z,
cmap='jet',
vmax=maxtec,
transform=ccrs.PlateCarree())
ax.set_extent(extent, ccrs.PlateCarree())
clrbar = plt.colorbar(mesh, shrink=0.5)
clrbar.set_label('Total Electron Content (TECU)')
ax.gridlines(linewidth=0.5)
plt.title('Total Electron Content for ' + str(date.month) + '/' +
str(date.day) + '/' + str(date.year) + ' at ' + str(time.hour) +
':' + ('%02d' % time.minute) + ' UT')
st.pyplot(tecmap)
def test_barbs_regrid():
x = np.arange(-60, 42.5, 2.5)
y = np.arange(30, 72.5, 2.5)
x2d, y2d = np.meshgrid(x, y)
u = 40 * np.cos(np.deg2rad(y2d))
v = 40 * np.cos(2. * np.deg2rad(x2d))
mag = (u**2 + v**2)**.5
plot_extent = [-60, 40, 30, 70]
fig = plt.figure(figsize=(6, 3))
ax = fig.add_subplot(projection=ccrs.NorthPolarStereo())
ax.set_extent(plot_extent, crs=ccrs.PlateCarree())
ax.coastlines()
ax.barbs(x, y, u, v, mag, transform=ccrs.PlateCarree(),
length=4, linewidth=.4, regrid_shape=20)
return fig
def lookup_projection(projection_code):
"""Get a Cartopy projection based on a short abbreviation."""
import cartopy.crs as ccrs
projections = {
'lcc':
ccrs.LambertConformal(central_latitude=40,
central_longitude=-100,
standard_parallels=[30, 60]),
'ps':
ccrs.NorthPolarStereo(central_longitude=-100),
'mer':
ccrs.Mercator()
}
return projections[projection_code]
def test_inverted_poly_clipped_hole(self):
proj = ccrs.NorthPolarStereo()
poly = sgeom.Polygon([(0, 0), (-90, 0), (-180, 0),
(-270, 0)], [[(-135, -60), (-45, -60), (45, -60),
(135, -60)]])
multi_polygon = proj.project_geometry(poly)
# Check the structure
assert len(multi_polygon) == 1
assert len(multi_polygon[0].interiors) == 1
# Check the rough shape
polygon = multi_polygon[0]
self._assert_bounds(polygon.bounds, -5.0e7, -5.0e7, 5.0e7, 5.0e7, 1e6)
self._assert_bounds(polygon.interiors[0].bounds, -1.2e7, -1.2e7, 1.2e7,
1.2e7, 1e6)
assert abs(polygon.area - 7.30e15) < 1e13
def test_inverted_poly_removed_hole(self):
proj = ccrs.NorthPolarStereo(globe=ccrs.Globe(ellipse='WGS84'))
poly = sgeom.Polygon([(0, 0), (-90, 0), (-180, 0),
(-270, 0)], [[(-135, -75), (-45, -75), (45, -75),
(135, -75)]])
multi_polygon = proj.project_geometry(poly)
# Check the structure
self.assertEqual(len(multi_polygon), 1)
self.assertEqual(len(multi_polygon[0].interiors), 1)
# Check the rough shape
polygon = multi_polygon[0]
self._assert_bounds(polygon.bounds, -5.0e7, -5.0e7, 5.0e7, 5.0e7, 1e6)
self._assert_bounds(polygon.interiors[0].bounds, -1.2e7, -1.2e7, 1.2e7,
1.2e7, 1e6)
self.assertAlmostEqual(polygon.area, 7.34e15, delta=1e13)
def make_graph(Dataset, Name, filename, central):
lats = nc.variables['lat'][:]
lons = nc.variables['lon'][:]
avg, lons = add_cyclic_point(Dataset, coord=lons)
fig = figure()
ax = axes(projection=ccrs.NorthPolarStereo(central_longitude=central))
cs = contourf(lons,
lats,
avg,
cmap='nipy_spectral',
alpha=0.8,
transform=ccrs.PlateCarree())
ax.coastlines()
colorbar(orientation='horizontal')
plot()
savefig("NorthPolarStereo/" + str(Name) + ".png")
def test_inverted_poly_clipped_hole(self):
proj = ccrs.NorthPolarStereo()
poly = Polygon([(0, 0), (90, 0), (180, 0), (270, 0)], [[(135, -60),
(45, -60),
(-45, -60),
(-135, -60)]])
multi_polygon = proj.project_geometry(poly)
# Check the structure
self.assertEqual(len(multi_polygon), 1)
self.assertEqual(len(multi_polygon[0].interiors), 1)
# Check the rough shape
polygon = multi_polygon[0]
self._assert_bounds(polygon.bounds, -5.0e7, -5.0e7, 5.0e7, 5.0e7, 1e6)
self._assert_bounds(polygon.interiors[0].bounds, -1.2e7, -1.2e7, 1.2e7,
1.2e7, 1e6)
self.assertAlmostEqual(polygon.area, 7.30e15, delta=1e13)
def test_quiver_regrid_with_extent():
x = np.arange(-60, 42.5, 2.5)
y = np.arange(30, 72.5, 2.5)
x2d, y2d = np.meshgrid(x, y)
u = np.cos(np.deg2rad(y2d))
v = np.cos(2. * np.deg2rad(x2d))
mag = (u**2 + v**2)**.5
plot_extent = [-60, 40, 30, 70]
target_extent = [-3e6, 2e6, -6e6, -2.5e6]
fig = plt.figure(figsize=(6, 3))
ax = fig.add_subplot(projection=ccrs.NorthPolarStereo())
ax.set_extent(plot_extent, crs=ccrs.PlateCarree())
ax.coastlines()
ax.quiver(x, y, u, v, mag, transform=ccrs.PlateCarree(),
regrid_shape=10, target_extent=target_extent)
return fig
def test_barbs_regrid_with_extent():
x = np.arange(-60, 42.5, 2.5)
y = np.arange(30, 72.5, 2.5)
x2d, y2d = np.meshgrid(x, y)
u = 40 * np.cos(np.deg2rad(y2d))
v = 40 * np.cos(2. * np.deg2rad(x2d))
mag = (u**2 + v**2)**.5
plot_extent = [-60, 40, 30, 70]
target_extent = [-3e6, 2e6, -6e6, -2.5e6]
plt.figure(figsize=(6, 3))
ax = plt.axes(projection=ccrs.NorthPolarStereo())
ax.set_extent(plot_extent, crs=ccrs.PlateCarree())
ax.coastlines()
ax.barbs(x, y, u, v, mag, transform=ccrs.PlateCarree(),
length=4, linewidth=.25, regrid_shape=10,
target_extent=target_extent)
def test_multiple_projections():
projections = [
ccrs.PlateCarree(),
ccrs.Robinson(),
ccrs.RotatedPole(pole_latitude=45, pole_longitude=180),
ccrs.OSGB(approx=True),
ccrs.TransverseMercator(approx=True),
ccrs.Mercator(globe=ccrs.Globe(semimajor_axis=math.degrees(1)),
min_latitude=-85.,
max_latitude=85.),
ccrs.LambertCylindrical(),
ccrs.Miller(),
ccrs.Gnomonic(),
ccrs.Stereographic(),
ccrs.NorthPolarStereo(),
ccrs.SouthPolarStereo(),
ccrs.Orthographic(),
ccrs.Mollweide(),
ccrs.InterruptedGoodeHomolosine(emphasis='land'),
ccrs.EckertI(),
ccrs.EckertII(),
ccrs.EckertIII(),
ccrs.EckertIV(),
ccrs.EckertV(),
ccrs.EckertVI(),
]
rows = np.ceil(len(projections) / 5).astype(int)
fig = plt.figure(figsize=(10, 2 * rows))
for i, prj in enumerate(projections, 1):
ax = fig.add_subplot(rows, 5, i, projection=prj)
ax.set_global()
ax.coastlines(resolution="110m")
plt.plot(-0.08, 51.53, 'o', transform=ccrs.PlateCarree())
plt.plot([-0.08, 132], [51.53, 43.17],
color='red',
transform=ccrs.PlateCarree())
plt.plot([-0.08, 132], [51.53, 43.17],
color='blue',
transform=ccrs.Geodetic())
def test_multiple_projections():
projections = [
ccrs.PlateCarree(),
ccrs.Robinson(),
ccrs.RotatedPole(pole_latitude=45, pole_longitude=180),
ccrs.OSGB(),
ccrs.TransverseMercator(),
ccrs.Mercator(globe=ccrs.Globe(semimajor_axis=math.degrees(1)),
min_latitude=-85.,
max_latitude=85.),
ccrs.LambertCylindrical(),
ccrs.Miller(),
ccrs.Gnomonic(),
ccrs.Stereographic(),
ccrs.NorthPolarStereo(),
ccrs.SouthPolarStereo(),
ccrs.Orthographic(),
ccrs.Mollweide(),
ccrs.InterruptedGoodeHomolosine(),
]
if ccrs.PROJ4_VERSION < (5, 0, 0):
# Produce the same sized image for old proj, to avoid having to replace
# the image. If this figure is regenerated for both old and new proj,
# then drop this condition.
rows = 5
else:
rows = np.ceil(len(projections) / 5)
fig = plt.figure(figsize=(10, 2 * rows))
for i, prj in enumerate(projections, 1):
ax = fig.add_subplot(rows, 5, i, projection=prj)
ax.set_global()
ax.coastlines()
plt.plot(-0.08, 51.53, 'o', transform=ccrs.PlateCarree())
plt.plot([-0.08, 132], [51.53, 43.17],
color='red',
transform=ccrs.PlateCarree())
plt.plot([-0.08, 132], [51.53, 43.17],
color='blue',
transform=ccrs.Geodetic())
def plot(reference, test, diff, metrics_dict, parameter):
# Create figure, projection
fig = plt.figure(figsize=[8.5, 11.0])
# Create projection
print parameter.var_region
if parameter.var_region.find('N') !=-1:
pole = 'N'
proj = ccrs.NorthPolarStereo(central_longitude=0)
elif parameter.var_region.find('S') !=-1:
pole = 'S'
proj = ccrs.SouthPolarStereo(central_longitude=0)
# First two panels
min1 = metrics_dict['test']['min']
mean1 = metrics_dict['test']['mean']
max1 = metrics_dict['test']['max']
if test.count() >1:
plot_panel(0, fig, proj, pole, test, parameter.contour_levels, 'viridis', (parameter.test_name,parameter.test_title,test.units),stats=(max1,mean1,min1))
min2 = metrics_dict['ref']['min']
mean2 = metrics_dict['ref']['mean']
max2 = metrics_dict['ref']['max']
if reference.count() >1:
plot_panel(1, fig, proj, pole, reference, parameter.contour_levels, 'viridis', (parameter.reference_name,parameter.reference_title,reference.units),stats=(max2,mean2,min2))
# Third panel
min3 = metrics_dict['diff']['min']
mean3 = metrics_dict['diff']['mean']
max3 = metrics_dict['diff']['max']
r = metrics_dict['misc']['rmse']
c = metrics_dict['misc']['corr']
if diff.count() >1:
plot_panel(2, fig, proj, pole, diff, parameter.diff_levels, 'RdBu_r', (None,parameter.diff_title,None), stats=(max3,mean3,min3,r,c))
# Figure title
fig.suptitle(parameter.main_title, x=0.5, y=0.97, fontsize=18)
# Save figure
for f in parameter.output_format:
f = f.lower().split('.')[-1]
fnm = os.path.join(get_output_dir('7', parameter), parameter.output_file)
plt.savefig(fnm + '.' + f)
print('Plot saved in: ' + fnm + '.' + f)
def plot_contour(lons,
lats,
data,
levels=[.15],
colors=['purple'],
lw=[1.],
labels=['Variable'],
outname='test.png'):
# create the figure panel
fig = plt.figure(figsize=(10, 10), facecolor='w')
# create the map using the cartopy NorthPoleStereo
# +proj=stere +a=6378273 +b=6356889.44891 +lat_0=90 +lat_ts=70 +lon_0=-45"
globe = cartopy.crs.Globe(semimajor_axis=6378273,
semiminor_axis=6356889.44891)
ax1 = plt.subplot(1,
1,
1,
projection=ccrs.NorthPolarStereo(central_longitude=-45,
true_scale_latitude=70,
globe=globe))
ax1.set_extent([15, -180, 72, 62], crs=ccrs.PlateCarree())
# add coastlines, gridlines, make sure the projection is maximised inside the plot, and fill in the land with colour
ax1.coastlines(
resolution='110m', zorder=3
) # zorder=3 makes sure that no other plots overlay the coastlines
ax1.gridlines()
ax1.add_feature(cartopy.feature.LAND,
zorder=1,
facecolor=cartopy.feature.COLORS['land_alt1'])
# plot sea ice field
for i in range(len(levels)):
cs = plt.contour(lons,
lats,
data[i],
levels=[levels[i]],
colors=colors[i],
linewidths=lw[i],
transform=ccrs.PlateCarree())
cs.collections[0].set_label(labels[i])
ax1.legend(loc='upper right')
plt.savefig(outname, bbox_inches='tight')
plt.close()
def plot_transect_map(lon_start,
lat_start,
lon_end,
lat_end,
mesh,
npoints=30,
view='w',
stock_img=False):
# plt.figure(figsize=(10,10))
lonlat = transect_get_lonlat(lon_start,
lat_start,
lon_end,
lat_end,
npoints=npoints)
nodes = transect_get_nodes(lonlat, mesh)
dist = transect_get_distance(lonlat)
if view == 'w':
ax = plt.subplot(111, projection=ccrs.Mercator(central_longitude=0))
ax.set_extent([180, -180, -80, 90], crs=ccrs.PlateCarree())
elif view == 'np':
ax = plt.subplot(111,
projection=ccrs.NorthPolarStereo(central_longitude=0))
ax.set_extent([180, -180, 60, 90], crs=ccrs.PlateCarree())
elif view == 'sp':
ax = plt.subplot(111,
projection=ccrs.SouthPolarStereo(central_longitude=0))
ax.set_extent([180, -180, -90, -50], crs=ccrs.PlateCarree())
else:
raise ValueError(
'The "{}" is not recognized as valid view option.'.format(view))
ax.scatter(lonlat[:, 0],
lonlat[:, 1],
s=30,
c='b',
transform=ccrs.PlateCarree())
ax.scatter(mesh.x2[nodes],
mesh.y2[nodes],
s=30,
c='r',
transform=ccrs.PlateCarree())
if stock_img == True:
ax.stock_img()
ax.coastlines(resolution='50m')
return ax
def plot_ToE(z, zlat, zlon, title, outname, llim, ulim, by, clabel):
fig = plt.figure(figsize=(6, 6), dpi=300)
# some plot parameters
levs = np.arange(llim, ulim + by, by)
cticks = np.arange(llim, ulim + by, by)
# set up map
prj = ccrs.NorthPolarStereo()
ax = fig.add_axes([0.05, 0.05, 0.9, 0.90],
projection=prj) # left, bottom, width, height
ax.coastlines()
# has to be done before data to plot added for use_as_clip_path to work
llon = -180
ulon = 180
llat = 20
ulat = 90
ax.set_extent([llon, ulon, llat, ulat], ccrs.PlateCarree())
theta = np.linspace(0, 2 * np.pi, 100)
center, radius = [0.5, 0.5], 0.5
verts = np.vstack([np.sin(theta), np.cos(theta)]).T
circle = mpath.Path(verts * radius + center)
ax.set_boundary(circle, transform=ax.transAxes, use_as_clip_path=True)
# add data
# add cyclic point to wrap around in longitude (cartopy function); outputs as np array
#cyclic_z, cyclic_lon = add_cyclic_point(z, coord=z['lon'])
cyclic_z, cyclic_lon = add_cyclic_point(z, coord=zlon)
cplot = ax.contourf(cyclic_lon,
zlat,
cyclic_z,
transform=ccrs.PlateCarree(),
extend='both',
levels=levs,
cmap=cm.afmhot)
plt.title(title, fontsize=18)
# colorbar
cbar = plt.colorbar(cplot, orientation='vertical', ticks=cticks)
cbar.set_label(clabel, size=12)
cbar.ax.tick_params(labelsize=12)
plt.savefig(outname)
plt.close()
def plot_single_lat_lon(z, zlat, zlon, title, outname, lim, by, cbarlim, cbarby, clabel, zsig=0, colorscale='BlueRed'):
fig = plt.figure(figsize=(6, 6), dpi=300)
# some plot parameters
levs = np.arange(-lim,lim+by,by)
cbarticks = np.arange(-cbarlim,cbarlim+cbarby,cbarby)
cols = color_defs.custom(colorscale)
# set up map
prj = ccrs.NorthPolarStereo()
ax = fig.add_axes([0.05, 0.05, 0.9, 0.90], projection=prj) # left, bottom, width, height
ax.coastlines()
# has to be done before data to plot added for use_as_clip_path to work
llon=-180
ulon=180
llat=20
ulat=90
ax.set_extent([llon, ulon, llat, ulat], ccrs.PlateCarree())
theta = np.linspace(0, 2*np.pi, 100)
center, radius = [0.5, 0.5], 0.5
verts = np.vstack([np.sin(theta), np.cos(theta)]).T
circle = mpath.Path(verts * radius + center)
ax.set_boundary(circle, transform=ax.transAxes, use_as_clip_path=True)
# add data
# add cyclic point to wrap around in longitude (cartopy function); outputs as np array
# if using pyplot: ibase,ilon = user_addcyclic(z,np.array(lon))
cyclic_z, cyclic_lon = add_cyclic_point(z, coord=zlon)
cplot = ax.contourf(cyclic_lon, zlat, cyclic_z, transform=ccrs.PlateCarree(), extend='both', levels=levs, cmap=cols)
plt.title(title, fontsize=18)
# shade OUT non-significance
if type(zsig) is int: # default, no significance shown
zsig = np.zeros([len(zlat),len(zlon)])
cyclic_zsig, cyclic_tlon = add_cyclic_point(zsig, coord=zlon)
cplot_t = ax.contourf(cyclic_lon, zlat, cyclic_zsig, transform=ccrs.PlateCarree(),levels=[-1,0,1],hatches=[None,'..'],colors='none')
# colorbar
cbar=plt.colorbar(cplot, orientation='vertical', ticks=cbarticks)
cbar.set_label(clabel, size=14)
cbar.ax.tick_params(labelsize=14)
plt.savefig(outname)
plt.close()
def test_cartopy_projection(self):
cube = iris.load_cube(
tests.get_data_path(('PP', 'aPPglob1', 'global.pp')))
projections = {}
projections['RotatedPole'] = ccrs.RotatedPole(pole_longitude=177.5,
pole_latitude=37.5)
projections['Robinson'] = ccrs.Robinson()
projections['PlateCarree'] = ccrs.PlateCarree()
projections['NorthPolarStereo'] = ccrs.NorthPolarStereo()
projections['Orthographic'] = ccrs.Orthographic(central_longitude=-90,
central_latitude=45)
projections[
'InterruptedGoodeHomolosine'] = ccrs.InterruptedGoodeHomolosine()
projections['LambertCylindrical'] = ccrs.LambertCylindrical()
# Set up figure
fig = plt.figure(figsize=(10, 10))
gs = matplotlib.gridspec.GridSpec(nrows=3,
ncols=3,
hspace=1.5,
wspace=0.5)
for subplot_spec, (name, target_proj) in itertools.izip(
gs, projections.iteritems()):
# Set up axes and title
ax = plt.subplot(subplot_spec,
frameon=False,
projection=target_proj)
ax.set_title(name)
# Transform cube to target projection
new_cube, extent = iris.analysis.cartography.project(cube,
target_proj,
nx=150,
ny=150)
# Plot
plt.pcolor(
new_cube.coord('projection_x_coordinate').points,
new_cube.coord('projection_y_coordinate').points,
new_cube.data)
# Add coastlines
ax.coastlines()
# Tighten up layout
gs.tight_layout(plt.gcf())
# Verify resulting plot
self.check_graphic(tol=6e-4)
def sample_data(shape=(20, 30)):
"""
Returns ``(x, y, u, v, crs)`` of some vector data
computed mathematically. The returned CRS will be a North Polar
Stereographic projection, meaning that the vectors will be unevenly
spaced in a PlateCarree projection.
"""
crs = ccrs.NorthPolarStereo()
scale = 1e7
x = np.linspace(-scale, scale, shape[1])
y = np.linspace(-scale, scale, shape[0])
x2d, y2d = np.meshgrid(x, y)
u = 10 * np.cos(2 * x2d / scale + 3 * y2d / scale)
v = 20 * np.cos(6 * x2d / scale)
return x, y, u, v, crs
def test_cursor_values():
ax = plt.axes(projection=ccrs.NorthPolarStereo())
x, y = np.array([-969100.]), np.array([-4457000.])
r = ax.format_coord(x, y)
assert_equal(r.encode('ascii', 'ignore'),
'-9.691e+05, -4.457e+06 (50.716617N, 12.267069W)')
ax = plt.axes(projection=ccrs.PlateCarree())
x, y = np.array([-181.5]), np.array([50.])
r = ax.format_coord(x, y)
assert_equal(r.encode('ascii', 'ignore'),
'-181.5, 50 (50.000000N, 178.500000E)')
ax = plt.axes(projection=ccrs.Robinson())
x, y = np.array([16060595.2]), np.array([2363093.4])
r = ax.format_coord(x, y)
assert_equal(r.encode('ascii', 'ignore'),
'1.606e+07, 2.363e+06 (22.095524N, 173.709136E)')
def test_barbs_1d_transformed():
x = np.array([20., 30., -17., 15.])
y = np.array([-1., 35., 11., 40.])
u = np.array([23., -18., 2., -11.])
v = np.array([5., -4., 19., 11.])
plot_extent = [-20, 31, -5, 45]
plt.figure(figsize=(6, 5))
ax = plt.axes(projection=ccrs.NorthPolarStereo())
ax.set_extent(plot_extent, crs=ccrs.PlateCarree())
ax.coastlines()
ax.barbs(x,
y,
u,
v,
transform=ccrs.PlateCarree(),
length=8,
linewidth=1,
color='#7f7f7f')
def test_barbs():
x = np.arange(-60, 45, 5)
y = np.arange(30, 75, 5)
x2d, y2d = np.meshgrid(x, y)
u = 40 * np.cos(np.deg2rad(y2d))
v = 40 * np.cos(2. * np.deg2rad(x2d))
plot_extent = [-60, 40, 30, 70]
plt.figure(figsize=(6, 6))
# plot on native projection
ax = plt.subplot(211, projection=ccrs.PlateCarree())
ax.set_extent(plot_extent, crs=ccrs.PlateCarree())
ax.coastlines(resolution="110m")
ax.barbs(x, y, u, v, length=4, linewidth=.25)
# plot on a different projection
ax = plt.subplot(212, projection=ccrs.NorthPolarStereo())
ax.set_extent(plot_extent, crs=ccrs.PlateCarree())
ax.coastlines(resolution="110m")
ax.barbs(x, y, u, v, transform=ccrs.PlateCarree(), length=4, linewidth=.25)
def test_cursor_values():
ax = plt.axes(projection=ccrs.NorthPolarStereo())
x, y = np.array([-969100., -4457000.])
r = ax.format_coord(x, y)
assert (r.encode('ascii', 'ignore') ==
b'-9.691e+05, -4.457e+06 (50.716617N, 12.267069W)')
ax = plt.axes(projection=ccrs.PlateCarree())
x, y = np.array([-181.5, 50.])
r = ax.format_coord(x, y)
assert (r.encode('ascii', 'ignore') ==
b'-181.5, 50 (50.000000N, 178.500000E)')
ax = plt.axes(projection=ccrs.Robinson())
x, y = np.array([16060595.2, 2363093.4])
r = ax.format_coord(x, y)
assert re.search(b'1.606e\\+07, 2.363e\\+06 '
b'\\(22.09[0-9]{4}N, 173.70[0-9]{4}E\\)',
r.encode('ascii', 'ignore'))
def test_quiver_plate_carree():
x = np.arange(-60, 42.5, 2.5)
y = np.arange(30, 72.5, 2.5)
x2d, y2d = np.meshgrid(x, y)
u = np.cos(np.deg2rad(y2d))
v = np.cos(2. * np.deg2rad(x2d))
mag = (u**2 + v**2)**.5
plot_extent = [-60, 40, 30, 70]
plt.figure(figsize=(6, 6))
# plot on native projection
ax = plt.subplot(211, projection=ccrs.PlateCarree())
ax.set_extent(plot_extent, crs=ccrs.PlateCarree())
ax.coastlines(resolution="110m")
ax.quiver(x, y, u, v, mag)
# plot on a different projection
ax = plt.subplot(212, projection=ccrs.NorthPolarStereo())
ax.set_extent(plot_extent, crs=ccrs.PlateCarree())
ax.coastlines()
ax.quiver(x, y, u, v, mag, transform=ccrs.PlateCarree())
