def test_yaxis_labels_with_axes(self):
import matplotlib.pyplot as plt
fig = plt.figure()
ax = fig.add_subplot(111)
ax.set_ylim(0, 3)
iplt.pcolor(self.cube, axes=ax, coords=('bar', 'str_coord'))
plt.close(fig)
self.assertPointsTickLabels('yaxis', ax)
def test_yaxis_labels_with_axes(self):
import matplotlib.pyplot as plt
fig = plt.figure()
ax = fig.add_subplot(111)
ax.set_ylim(0, 3)
iplt.pcolor(self.cube, axes=ax, coords=('bar', 'str_coord'))
plt.close(fig)
self.assertPointsTickLabels('yaxis', ax)
def pcolor(cube, *args, **kwargs):
"""
Draws a labelled pseudocolor plot based on the given Cube.
See :func:`iris.plot.pcolor` for details of valid keyword arguments.
"""
coords = kwargs.get('coords')
result = iplt.pcolor(cube, *args, **kwargs)
_label_with_bounds(cube, result, coords=coords)
return result
def hatch_cube(cube, axes=None, p=0.05, **kwArgs):
pD = dict(hatch='.', zorder=9, alpha=0.)
pD.update(kwArgs)
if axes is None:
axes = plt.gca()
lo0, la0 = cube.coord('longitude'), cube.coord('latitude')
cube_ = cube.copy(np.ma.masked_greater(cube.data, p))
if lo0.ndim == 1:
pch = iplt.pcolor(cube_, axes=axes, **pD)
else:
if hasattr(lo0, 'has_bounds') and lo0.has_bounds():
x, y = lo0.contiguous_bounds(), la0.contiguous_bounds()
else:
x, y = _2d_bounds(lo0.points, la0.points)
pch = axes.pcolor(x, y, cube_.data, transform=ccrs.PlateCarree(), **pD)
return pch
def fishcell(self,
levels=[
0, 0.3, 1.6, 3.4, 5.5, 8., 10.8, 13.9, 17.2, 20.8, 24.5,
28.5, 32.7
],
title=None):
proj = ccrs.PlateCarree()
cmap = plt.get_cmap('Spectral_r')
norm = BoundaryNorm(levels, ncolors=cmap.N, clip=True)
# --shp数据
shp_path = '/home/qxs/bma/shp/fish_shp/'
ax = self.map()
fishcell = geopandas.read_file(shp_path + 'FishCellALL.shp')
ax.add_geometries(fishcell.geometry,
crs=proj,
edgecolor='k',
facecolor='none',
zorder=9)
# --风速数据
wind = self.ds['ws']
new_lon = np.linspace(wind.lon[0] - 0.25, wind.lon[-1] - 0.25,
wind.lon.shape[0])
new_lat = np.linspace(wind.lat[0] - 0.25, wind.lat[-1] - 0.25,
wind.lat.shape[0])
wind = wind.interp(lat=new_lat, lon=new_lon)
wind_mask = wind.salem.roi(shape=fishcell).to_iris()
# --画图
im = iplt.pcolor(wind_mask, cmap=cmap, axes=ax, norm=norm)
# --画色标
cbr = plt.colorbar(im, fraction=0.06, pad=0.04, norm=norm)
cbr.set_ticks(levels)
# --标题
if self.ini_time != None and self.shift_hour != None:
fcst_time = self.ini_time.shift(
hours=self.shift_hour).format('YYYY-MM-DD HH:mm')
ini_time = self.ini_time.format('YYYY-MM-DD HH:mm')
title = '渔区风速图 \n 预报时间:{} UTC \n初始时间:{} UTC'.format(
fcst_time, ini_time)
ax.set_title(title, fontsize=18)
# --存图
plt.savefig(self.path + 'ws_fishcell_{}_{}.png'.format(
self.ini_time.format('YYYYMMDDHH'), str(self.shift_hour)))
# plt.show()
else:
ax.set_title(title, fontsize=18)
plt.show()
def add_cube(self, cube, kind='pcolormesh', **kwargs):
if self.symmetric_colorbar:
max_mag = max(abs(cube.data.min()), abs(cube.data.max()))
self.val_max_magnitude = max(max_mag, self.val_max_magnitude)
vmin = -self.val_max_magnitude
vmax = self.val_max_magnitude
kwargs.setdefault('vmin', vmin)
kwargs.setdefault('vmax', vmax)
kwargs.setdefault('zorder', 2)
if kind == 'pcolormesh':
p = iplt.pcolormesh(cube, axes=self.ax, **kwargs)
elif kind == 'pcolor':
p = iplt.pcolor(cube, axes=self.ax, **kwargs)
elif kind == 'contourf':
p = iplt.contourf(cube, axes=self.ax, **kwargs)
elif kind == 'contour':
p = iplt.contour(cube, axes=self.ax, **kwargs)
else:
raise RuntimeError('Unknown plot kind: {:}'.format(kind))
return p
def test_pcolor(self):
cube = self.cube[0, 0]
iplt.pcolor(cube)
self.check_graphic()
def test_xaxis_labels(self):
iplt.pcolor(self.cube, coords=('str_coord', 'bar'))
self.assertBoundsTickLabels('xaxis')
def test_pcolor(self):
cube = self.cube[0, 0]
iplt.pcolor(cube)
self.check_graphic()
def test_xaxis_labels(self):
iplt.pcolor(self.cube, coords=('str_coord', 'bar'))
self.assertBoundsTickLabels('xaxis')
def pcolor_mask_geoms(cube, geoms, transform):
path = Path.make_compound_path(*geos_to_path(geoms))
im = iplt.pcolor(cube)
im.set_clip_path(path, transform=transform)
def pcolor_mask_geoms(cube, geoms, transform):
path = Path.make_compound_path(*geos_to_path(geoms))
im = iplt.pcolor(cube)
im.set_clip_path(path, transform=transform)
# First plot the full map:
cube = iris.load_cube(
'/RESEARCH/paper_ocean_heat_carbon/data/newCO2_control_800/sst.nc')
cube = cube[0, :, :]
plt.figure(figsize=(12, 6))
ax1 = plt.axes(projection=ccrs.PlateCarree())
ax1.coastlines()
iplt.pcolor(cube)
'''
# Now plot just the required countries:
plt.figure(figsize=(12, 6))
ax2 = plt.axes(projection=ccrs.PlateCarree())
ax2.coastlines()
countries = [
'United States',
'United Kingdom',
'Saudi Arabia',
'South Africa',
'Nigeria']
geoms, transform = get_geometries(countries)
pcolor_mask_geoms(cube, geoms, transform(ax2))
'''
plt.show()
