def PlotFirstField(filename, variable = "Marine Air Temperature", vmin = None,vmax = None, field = 0):
'''
Plot the first field of the data in the netcdf file
- i.e. a map of the humidities in the first month
uses iris
:param cube cube: the input cube
:returns: None
'''
import matplotlib.pyplot as plt
import iris.quickplot as qplt
import cartopy.crs as ccrs
import iris
cube = iris.load_cube(filename, variable)
plt.clf()
ax = plt.axes(projection=ccrs.Robinson())
ax.gridlines() #draw_labels=True)
ax.coastlines()
qplt.pcolor(cube[field], cmap=plt.cm.PiYG,vmin=vmin,vmax=vmax)
plt.show()
return # PlotFirstField
def test_orography(self):
qplt.contourf(self.cube)
iplt.orography_at_points(self.cube)
iplt.points(self.cube)
self.check_graphic()
coords = ['altitude', 'grid_longitude']
qplt.contourf(self.cube, coords=coords)
iplt.orography_at_points(self.cube, coords=coords)
iplt.points(self.cube, coords=coords)
self.check_graphic()
# TODO: Test bounds once they are supported.
with self.assertRaises(NotImplementedError):
qplt.pcolor(self.cube)
iplt.orography_at_bounds(self.cube)
iplt.outline(self.cube)
self.check_graphic()
def test_orography(self):
qplt.contourf(self.cube)
iplt.orography_at_points(self.cube)
iplt.points(self.cube)
self.check_graphic()
coords = ['altitude', 'grid_longitude']
qplt.contourf(self.cube, coords=coords)
iplt.orography_at_points(self.cube, coords=coords)
iplt.points(self.cube, coords=coords)
self.check_graphic()
# TODO: Test bounds once they are supported.
with self.assertRaises(NotImplementedError):
qplt.pcolor(self.cube)
iplt.orography_at_bounds(self.cube)
iplt.outline(self.cube)
self.check_graphic()
def test_osgb_to_latlon(self):
path = tests.get_data_path(
('NIMROD', 'uk2km', 'WO0000000003452',
'201007020900_u1096_ng_ey00_visibility0180_screen_2km'))
src = iris.load_cube(path)[0]
src.data = src.data.astype(np.float32)
grid = Cube(np.empty((73, 96)))
cs = GeogCS(6370000)
lat = DimCoord(np.linspace(46, 65, 73), 'latitude', units='degrees',
coord_system=cs)
lon = DimCoord(np.linspace(-14, 8, 96), 'longitude', units='degrees',
coord_system=cs)
grid.add_dim_coord(lat, 0)
grid.add_dim_coord(lon, 1)
result = regrid(src, grid)
qplt.pcolor(result, antialiased=False)
qplt.plt.gca().coastlines()
self.check_graphic()
def test_osgb_to_latlon(self):
path = tests.get_data_path(
('NIMROD', 'uk2km', 'WO0000000003452',
'201007020900_u1096_ng_ey00_visibility0180_screen_2km'))
src = iris.load_cube(path)[0]
src.data = src.data.astype(np.float32)
grid = Cube(np.empty((73, 96)))
cs = GeogCS(6370000)
lat = DimCoord(np.linspace(46, 65, 73), 'latitude', units='degrees',
coord_system=cs)
lon = DimCoord(np.linspace(-14, 8, 96), 'longitude', units='degrees',
coord_system=cs)
grid.add_dim_coord(lat, 0)
grid.add_dim_coord(lon, 1)
result = regrid(src, grid)
qplt.pcolor(result, antialiased=False)
qplt.plt.gca().coastlines()
self.check_graphic()
def main():
# Parameters to compare between forecasts
path = datadir + 'deterministic/'
filename = 'rp_physics.nc'
name = 'Temperature [K]'
pressure = 500
lead_time = 7*24
cs = iris.Constraint(
name=name, pressure=pressure, forecast_period=lead_time)
# Load full precision reference forecast
cube = iris.load_cube(path + filename, cs)
# Calculate the errors with each different precision used as the `truth`
diffs = CubeList()
for pseudo_truth in cube.slices_over('precision'):
# Add the precision of the `truth` cube as another coordinate
p = pseudo_truth.coord('precision').points[0]
p = AuxCoord(p, long_name='reference_precision')
# Calculate the errors
diff = rms_diff(cube, pseudo_truth)
diff.add_aux_coord(p)
# Store the errors in the cubelist
diffs.append(diff)
# Combine all the errors into a single cube with dimensions of
# precision vs reference_precision
diffs = diffs.merge_cube()
# Plot the errors
qplt.pcolor(diffs, vmin=0, cmap='cubehelix_r')
precisions = cube.coord('precision').points
plt.xticks(precisions)
plt.yticks(precisions)
plt.show()
return
def test_pcolor(self):
qplt.pcolor(self._small())
self.check_graphic()
def _check(self, cube):
qplt.contourf(cube)
self.check_graphic()
qplt.pcolor(cube)
self.check_graphic()
def test_bounds(self):
cube = simple_cube()
qplt.pcolor(cube)
self.check_graphic()
def test_xaxis_labels(self):
qplt.pcolor(self.cube, coords=("str_coord", "bar"))
self.assertBoundsTickLabels("xaxis")
def test_pcolor(self):
qplt.pcolor(self._small())
self.check_graphic()
def test_xaxis_labels(self):
qplt.pcolor(self.cube, coords=('str_coord', 'bar'))
self.assertBoundsTickLabels('xaxis')
def _regrid(self, method):
regridder = Regridder(self.src, self.grid, method, 'mask')
result = regridder(self.src)
qplt.pcolor(result, antialiased=False)
qplt.plt.gca().coastlines()
def test_xaxis_labels(self):
qplt.pcolor(self.cube, coords=('str_coord', 'bar'))
self.assertBoundsTickLabels('xaxis')
def test_bounds(self):
cube = simple_cube()
qplt.pcolor(cube)
self.check_graphic()
def test_xaxis_labels(self):
qplt.pcolor(self.cube, coords=("str_coord", "bar"))
self.assertBoundsTickLabels("xaxis")
def _check(self, cube):
qplt.contourf(cube)
self.check_graphic()
qplt.pcolor(cube)
self.check_graphic()
def _regrid(self, method):
regridder = Regridder(self.src, self.grid, method, 'mask')
result = regridder(self.src)
qplt.pcolor(result, antialiased=False)
qplt.plt.gca().coastlines()
