def test_single_boxcar(target_point, tmpfile, source_data_function):
'''Smooth a single point'''
import iris.quickplot as qplt, matplotlib.pyplot as plt
from gridsmoother import GridSmoother
import os
#lat,lon = target_point
dlat = 180. / 1#CUBE_SHAPE[0]
dlon = 360. / 1#CUBE_SHAPE[1]
print "point lat = %s, lon = %s" % target_point
assert int(target_point[0] / dlat) - target_point[0] / dlat < SMALL_NUMBER
assert int(target_point[1] / dlon) - target_point[1] / dlon < SMALL_NUMBER
print "dlat = %s, dlon = %s" % (dlat, dlon)
#centre = (lat,lon)#(dlat / 2., dlon / 2.)
source_cube = gen_or_load_2D(tmpfile , [source_data_function], ["unsmoothed data"], {"GS_centre_lat":target_point[0], 'GS_centre_lon':target_point[1]},nlat=180, nlon=360)[0]
lat_width = 6.
lon_width = 18.
print "box car parameters: lat_width %s, lon_width %s" % (lat_width, lon_width)
gs = GridSmoother()
filename= "boxcar_%s_x_%s.json.gz" % (lon_width,lat_width)
if os.path.exists(filename):
gs.load(filename)
else:
gs.build_boxcar_lat_lon(source_cube, lat_width, lon_width)
gs.save(filename)
smoothed_cube = gs.smooth_2d_cube(source_cube)
if PLOT:
import cartopy.crs as ccrs
fig = plt.figure()
subpl = fig.add_subplot(111, projection=ccrs.PlateCarree())
qplt.pcolormesh(smoothed_cube, cmap='Reds')
qplt.outline(smoothed_cube)
# subpl.add_artist(plt.Circle(target_point, smoothing_width, edgecolor='blue', facecolor='none', transform=ccrs.PlateCarree()))
for i, lat in enumerate(smoothed_cube.coord('latitude').points):
for j, lon in enumerate(smoothed_cube.coord('longitude').points):
if smoothed_cube.data[i, j] > 0:
plt.text(lon, lat, smoothed_cube.data[i, j] ** -1, transform=ccrs.PlateCarree(), ha='center', va='center')
qplt.plt.gca().coastlines()
qplt.show()
def test_xaxis_labels(self):
qplt.outline(self.cube, coords=('str_coord', 'bar'))
self.assertBoundsTickLabels('xaxis')
def test_xaxis_labels(self):
qplt.outline(self.cube, coords=("str_coord", "bar"))
self.assertBoundsTickLabels("xaxis")
def test_single_point(target_point, tmpfile, source_data_function, num_expected_distinct_values=2):
'''Smooth a single point'''
import iris.quickplot as qplt, matplotlib.pyplot as plt
from gridsmoother import GridSmoother
import os
#lat,lon = target_point
dlat = 180. / CUBE_SHAPE[0]
dlon = 360. / CUBE_SHAPE[1]
print "point lat = %s, lon = %s" % target_point
assert int(target_point[0] / dlat) - target_point[0] / dlat < SMALL_NUMBER
assert int(target_point[1] / dlon) - target_point[1] / dlon < SMALL_NUMBER
print "dlat = %s, dlon = %s" % (dlat, dlon)
#centre = (lat,lon)#(dlat / 2., dlon / 2.)
source_cube = gen_or_load_2D(tmpfile , [source_data_function], ["unsmoothed data"], {"GS_centre_lat":target_point[0], 'GS_centre_lon':target_point[1]})[0]
for smoothing_width in np.arange(2.0, 5, 0.5) * dlat:
print "smoothing_width: ", smoothing_width
gs = GridSmoother()
filename = 'smoothing_%s.json.gz' % smoothing_width
smoothing_function = lambda s: (s <= smoothing_width) * 1.0
if os.path.exists(filename):
gs.load(filename)
else:
gs.build(source_cube, smoothing_function)
gs.save('smoothing_%s.json.gz' % smoothing_width)
smoothed_cube = gs.smooth_2d_cube(source_cube)
assert np.isclose(smoothed_cube.data.sum(), source_cube.data.sum(), atol=SMALL_NUMBER)
#will fail for smoothing functions other than a hard cut off:
if num_expected_distinct_values is not None:
assert len(set(smoothed_cube.data.ravel().tolist())) == num_expected_distinct_values
for i, j in zip(*np.where(smoothed_cube.data > 0.0)):
assert smoothing_function(angular_separation(source_cube.coord('latitude').points[i],
source_cube.coord('longitude').points[j],
*target_point)
) > 0.
for i, j in zip(*np.where(smoothed_cube.data == 0.0)):
assert smoothing_function(angular_separation(source_cube.coord('latitude').points[i],
source_cube.coord('longitude').points[j],
*target_point)
) == 0.
if PLOT:
import cartopy.crs as ccrs
fig = plt.figure()
subpl = fig.add_subplot(111, projection=ccrs.PlateCarree())
qplt.pcolormesh(smoothed_cube, cmap='Reds')
qplt.outline(smoothed_cube)
subpl.add_artist(plt.Circle(target_point, smoothing_width, edgecolor='blue', facecolor='none', transform=ccrs.PlateCarree()))
for i, lat in enumerate(smoothed_cube.coord('latitude').points):
for j, lon in enumerate(smoothed_cube.coord('longitude').points):
if smoothed_cube.data[i, j] > 0:
plt.text(lon, lat, smoothed_cube.data[i, j] ** -1, transform=ccrs.PlateCarree(), ha='center', va='center')
qplt.plt.gca().coastlines()
qplt.show()
def plot_driftMap(um, glm, ifs, ship_data):
import iris.plot as iplt
import iris.quickplot as qplt
import iris.analysis.cartography
import cartopy.crs as ccrs
import cartopy
import matplotlib.path as mpath
from matplotlib.patches import Polygon
###################################
## PLOT MAP
###################################
print('******')
print('')
print('Plotting cartopy map:')
print('')
##################################################
##################################################
#### CARTOPY
##################################################
##################################################
SMALL_SIZE = 12
MED_SIZE = 14
LARGE_SIZE = 16
plt.rc('font', size=MED_SIZE)
plt.rc('axes', titlesize=MED_SIZE)
plt.rc('axes', labelsize=MED_SIZE)
plt.rc('xtick', labelsize=MED_SIZE)
plt.rc('ytick', labelsize=MED_SIZE)
plt.rc('legend', fontsize=MED_SIZE)
# plt.rc('figure',titlesize=LARGE_SIZE)
#################################################################
## create figure and axes instances
#################################################################
plt.figure(figsize=(5, 6)) #, dpi=300)
# ax = plt.axes(projection=ccrs.Orthographic(30, 70)) # NP Stereo
ax = plt.axes(projection=ccrs.NorthPolarStereo(central_longitude=30))
### set size
ax.set_extent([20, 50, 88.35, 89.95], crs=ccrs.PlateCarree()) ### SWATH
### DON'T USE: PLATECARREE, NORTHPOLARSTEREO (on it's own), LAMBERT
#################################################################
## add geographic features/guides for reference
#################################################################
ax.add_feature(cartopy.feature.OCEAN, color='lightcyan', zorder=0)
ax.add_feature(cartopy.feature.LAND,
color='lightgrey',
zorder=0,
edgecolor='black')
ax.add_feature(cartopy.feature.COASTLINE)
ax.gridlines(color='black', linestyle='--')
#################################################################
## plot UM data
################################################################
# iplt.pcolormesh(um[diag][290:370,150:230])
#################################################################
## plot UM nest
#################################################################
### draw outline of grid
# qplt.outline(um[0][0,:,:]) ### original swath
# qplt.outline(cube[diag][hour,386:479,211:305]) ### redesigned swath (>13th)
# qplt.outline(cube[hour,471:495,240:264]) ### 12-13th Aug swath
# qplt.outline(cube[diag][hour,386:495,211:305]) ### misc
# qplt.outline(cube[diag][290:370,150:230])
### Plot um grid centres
# plt.plot(um[0].dim_coords[2], um[0].dim_coords[1], '.',
# color = 'k', linewidth = 2,
# transform = ccrs.PlateCarree(), label = 'Whole',
# )
###---------------------------------------------------------------------------------
### Plot um grid centres
###---------------------------------------------------------------------------------
# plt.scatter(um[0].dim_coords[2], um[0].dim_coords[1], s = 9, c = 'steelblue')#,
# label = 'UM_RA2M/CASIM-100',
# alpha = 0.8,
# edgecolor = 'midnightblue'
# # transform = ccrs.PlateCarree()
# )
# qplt.scatter(um[0].dim_coords[2], um[0].dim_coords[1], s = 9, c = 'steelblue')
qplt.outline(um[2][0, 300:, 100:400], color='steelblue')
# qplt.outline(glm[1][0,:,:],
# color = 'lightgrey')
###---------------------------------------------------------------------------------
### Plot ifs grid centres
###---------------------------------------------------------------------------------
plt.scatter(
ifs['lons'][:],
ifs['lats'][:],
s=120,
c='gold',
label='IFS_midpoints',
marker='x',
# alpha = 0.5,
linewidth=3,
edgecolor='saddlebrown',
transform=ccrs.PlateCarree())
#################################################################
## plot ship track
#################################################################
### DEFINE DRIFT + IN_ICE PERIODS
drift_index = iceDrift(ship_data)
inIce_index = inIce(ship_data)
trackShip_index = trackShip(ship_data)
### Plot full track as line plot
# plt.plot(ship_data.values[:,6], ship_data.values[:,7], '--',
# color = 'pink', linewidth = 2,
# transform = ccrs.PlateCarree(), label = 'Whole',
# )
# plt.plot(ship_data.values[inIce_index,6], ship_data.values[inIce_index,7],
# color = 'palevioletred', linewidth = 3,
# transform = ccrs.PlateCarree(), label = 'In Ice',
# )
# plt.plot(ship_data.values[inIce_index[0],6], ship_data.values[inIce_index[0],7],
# 'k^', markerfacecolor = 'palevioletred', linewidth = 3,
# transform = ccrs.PlateCarree(),
# )
# plt.plot(ship_data.values[inIce_index[-1],6], ship_data.values[inIce_index[-1],7],
# 'kv', markerfacecolor = 'palevioletred', linewidth = 3,
# transform = ccrs.PlateCarree(),
# )
plt.plot(
ship_data.values[drift_index, 6],
ship_data.values[drift_index, 7],
color='firebrick',
linewidth=3,
transform=ccrs.PlateCarree(),
label='AO2018 drift',
)
plt.title('Grid setup')
plt.legend(bbox_to_anchor=(-0.05, 0.835, 1., .102), loc=4, ncol=1)
print('******')
print('')
print('Finished plotting cartopy map! :)')
print('')
plt.savefig('../FIGS/Drift_UM_IFS_grids_v4.png', dpi=300)
# plt.show()
plt.close()