def test_simple_layout():
"""Test metpy's simple layout for station plots."""
fig = plt.figure(figsize=(9, 9))
# testing data
x = np.array([1, 5])
y = np.array([2, 4])
data = {
'air_temperature': np.array([32., 212.]) * units.degF,
'dew_point_temperature': np.array([28., 80.]) * units.degF,
'air_pressure_at_sea_level': np.array([29.92, 28.00]) * units.inHg,
'eastward_wind': np.array([2, 0]) * units.knots,
'northward_wind': np.array([0, 5]) * units.knots,
'cloud_coverage': [3, 8],
'present_weather': [65, 75],
'unused': [1, 2]
}
# Make the plot
sp = StationPlot(fig.add_subplot(1, 1, 1), x, y, fontsize=12)
simple_layout.plot(sp, data)
sp.ax.set_xlim(0, 6)
sp.ax.set_ylim(0, 6)
return fig
def test_simple_layout():
"""Test metpy's simple layout for station plots."""
fig = plt.figure(figsize=(9, 9))
# testing data
x = np.array([1, 5])
y = np.array([2, 4])
data = dict()
data["air_temperature"] = np.array([32.0, 212.0]) * units.degF
data["dew_point_temperature"] = np.array([28.0, 80.0]) * units.degF
data["air_pressure_at_sea_level"] = np.array([29.92, 28.00]) * units.inHg
data["eastward_wind"] = np.array([2, 0]) * units.knots
data["northward_wind"] = np.array([0, 5]) * units.knots
data["cloud_coverage"] = [3, 8]
data["present_weather"] = [65, 75]
data["unused"] = [1, 2]
# Make the plot
sp = StationPlot(fig.add_subplot(1, 1, 1), x, y, fontsize=12)
simple_layout.plot(sp, data)
sp.ax.set_xlim(0, 6)
sp.ax.set_ylim(0, 6)
return fig
def test_simple_layout():
"""Test metpy's simple layout for station plots."""
fig = plt.figure(figsize=(9, 9))
# testing data
x = np.array([1, 5])
y = np.array([2, 4])
data = {'air_temperature': np.array([32., 212.]) * units.degF,
'dew_point_temperature': np.array([28., 80.]) * units.degF,
'air_pressure_at_sea_level': np.array([29.92, 28.00]) * units.inHg,
'eastward_wind': np.array([2, 0]) * units.knots,
'northward_wind': np.array([0, 5]) * units.knots, 'cloud_coverage': [3, 8],
'present_weather': [65, 75], 'unused': [1, 2]}
# Make the plot
sp = StationPlot(fig.add_subplot(1, 1, 1), x, y, fontsize=12)
simple_layout.plot(sp, data)
sp.ax.set_xlim(0, 6)
sp.ax.set_ylim(0, 6)
return fig
#
# Here's the actual station plot
#
# Start the station plot by specifying the axes to draw on, as well as the
# lon/lat of the stations (with transform). We also the fontsize to 12 pt.
stationplot = StationPlot(ax,
data['longitude'],
data['latitude'],
transform=ccrs.PlateCarree(),
fontsize=12)
# The layout knows where everything should go, and things are standardized using
# the names of variables. So the layout pulls arrays out of `data` and plots them
# using `stationplot`.
simple_layout.plot(stationplot, data)
plt.show()
###########################################
# or instead, a custom layout can be used:
# Just winds, temps, and dewpoint, with colors. Dewpoint and temp will be plotted
# out to Farenheit tenths. Extra data will be ignored
custom_layout = StationPlotLayout()
custom_layout.add_barb('eastward_wind', 'northward_wind', units='knots')
custom_layout.add_value('NW',
'air_temperature',
fmt='.1f',
units='degF',
color='darkred')
# Set plot bounds
ax.set_extent((-118, -73, 23, 50))
#
# Here's the actual station plot
#
# Start the station plot by specifying the axes to draw on, as well as the
# lon/lat of the stations (with transform). We also the fontsize to 12 pt.
stationplot = StationPlot(ax, data['longitude'], data['latitude'],
transform=ccrs.PlateCarree(), fontsize=12)
# The layout knows where everything should go, and things are standardized using
# the names of variables. So the layout pulls arrays out of `data` and plots them
# using `stationplot`.
simple_layout.plot(stationplot, data)
plt.show()
###########################################
# or instead, a custom layout can be used:
# Just winds, temps, and dewpoint, with colors. Dewpoint and temp will be plotted
# out to Farenheit tenths. Extra data will be ignored
custom_layout = StationPlotLayout()
custom_layout.add_barb('eastward_wind', 'northward_wind', units='knots')
custom_layout.add_value('NW', 'air_temperature', fmt='.1f', units='degF', color='darkred')
custom_layout.add_value('SW', 'dew_point_temperature', fmt='.1f', units='degF',
color='darkgreen')
# Also, we'll add a field that we don't have in our dataset. This will be ignored
def plot_the_ppi(radar, ex, have_obs, sfc_data,
d, rname, gatefilter=None, moment='reflectivity', vmin=-8,
vmax=64, cmap=pyart.graph.cm_colorblind.HomeyerRainbow, sweep=0,
form='.png', dirr='./', latest=False):
homes = str(Path.home())
mybb = {'north': ex[3], 'south': ex[2], 'east': ex[0], 'west': ex[1]}
figme = plt.figure(figsize=[15, 11])
proj = ccrs.PlateCarree()
mydisplay = pyart.graph.RadarMapDisplayCartopy(radar)
mydisplay.plot_ppi_map(moment, sweep=sweep,
cmap=cmap,
embelish=False, vmin=vmin, vmax=vmax,
min_lat=mybb['south'], max_lat=mybb['north'],
min_lon=mybb['west'], max_lon=mybb['east'],
projection=proj,
gatefilter=gatefilter)
ax = plt.gca()
ax.set_extent(ex)
lat_lines = np.arange(np.around(ex[2], decimals=1),
ex[3]+.4, .4)
lon_lines = np.arange(np.around(ex[0], decimals=1),
ex[1]+.5, .5)
# Create a feature for States/Admin 1 regions at 1:50m from Natural Earth
states_provinces = cfeature.NaturalEarthFeature(
category='cultural',
name='admin_1_states_provinces_lines',
scale='10m',
facecolor='none')
ax.add_feature(states_provinces, edgecolor='gray')
request = cimgt.StamenTerrain()
if True: # len(request.imgs) > 0:
ax.add_image(request, 10, zorder=0)
plt.xticks(fontsize=15)
plt.yticks(fontsize=15)
ax.set_xticks(lon_lines, crs=ccrs.PlateCarree())
ax.set_yticks(lat_lines, crs=ccrs.PlateCarree())
lon_formatter = LongitudeFormatter(zero_direction_label=True)
lat_formatter = LatitudeFormatter()
ax.xaxis.set_major_formatter(lon_formatter)
ax.yaxis.set_major_formatter(lat_formatter)
_ = ax.gridlines(crs=ccrs.PlateCarree(), draw_labels=False,
linewidth=2, color='gray', alpha=0.5, linestyle='--',
xlocs=lon_lines, ylocs=lat_lines)
scale_bar_left(plt.gca(), linewidth=10, fs=15, col='Black', length=40)
if have_obs:
stationplot = StationPlot(ax, sfc_data['longitude'], sfc_data['latitude'],
transform=ccrs.PlateCarree(),
fontsize=12)
simple_layout.plot(stationplot, sfc_data)
sites = argonne_df()
plot_points_from_df(sites, sym='k*')
plot_text(sites, dx=0.02, dy=-0.02, tcol='k', fontsize=15)
plot_text(pyart_df(), tcol='k', fontsize=10)
mydisplay.cbs[0].ax.tick_params(labelsize=15)
nice_string = radar.fields[moment]['standard_name'].replace('_', ' ')
unts = ' (' + radar.fields[moment]['units'] + ')'
mydisplay.cbs[0].set_label(label=nice_string+unts, fontsize=15)
logo = plt.imread(homes + '/unfunded_projects/nerve/nerve/argonne_logo.png')
#ax.figure.figimage(logo, -89, 42.7, alpha=.15, zorder=1)
this_thing = figme.figimage(logo, 550,820)
this_thing.set_zorder(10)
ax.set_aspect(1.1)
#plt.tight_layout()
plt.savefig(dirr + rname + '_' + d + '_' + moment + form, bbox_inches='tight')
if latest:
plt.savefig(dirr+'/'+rname+'_'+moment+'_latest'+form, bbox_inches='tight')
