def test_barb_sounding_plot():
sonde_ds = arm.read_netcdf(sample_files.EXAMPLE_TWP_SONDE_WILDCARD)
BarbDisplay = TimeSeriesDisplay({'sonde_darwin': sonde_ds})
BarbDisplay.plot_time_height_xsection_from_1d_data('rh',
'pres',
cmap='coolwarm_r',
vmin=0,
vmax=100,
num_time_periods=25)
BarbDisplay.plot_barbs_from_spd_dir('deg', 'wspd', 'pres', num_barbs_x=20)
sonde_ds.close()
return BarbDisplay.fig
def test_errors():
files = sample_files.EXAMPLE_MET_WILDCARD
obj = arm.read_netcdf(files)
display = TimeSeriesDisplay(obj)
display.axes = None
with np.testing.assert_raises(RuntimeError):
display.day_night_background()
display = TimeSeriesDisplay({'met': obj, 'met2': obj})
with np.testing.assert_raises(ValueError):
display.plot('temp_mean')
with np.testing.assert_raises(ValueError):
display.qc_flag_block_plot('qc_temp_mean')
with np.testing.assert_raises(ValueError):
display.plot_barbs_from_spd_dir('wdir_vec_mean', 'wspd_vec_mean')
with np.testing.assert_raises(ValueError):
display.plot_barbs_from_u_v('wdir_vec_mean', 'wspd_vec_mean')
del obj.attrs['_file_dates']
data = np.empty(len(obj['time'])) * np.nan
lat = obj['lat'].values
lon = obj['lon'].values
obj['lat'].values = data
obj['lon'].values = data
display = TimeSeriesDisplay(obj)
display.plot('temp_mean')
display.set_yrng([0, 0])
with np.testing.assert_warns(RuntimeWarning):
display.day_night_background()
obj['lat'].values = lat
with np.testing.assert_warns(RuntimeWarning):
display.day_night_background()
obj['lon'].values = lon * 100.
with np.testing.assert_warns(RuntimeWarning):
display.day_night_background()
obj['lat'].values = lat * 100.
with np.testing.assert_warns(RuntimeWarning):
display.day_night_background()
obj.close()
# Test some of the other errors
obj = arm.read_netcdf(files)
del obj['temp_mean'].attrs['units']
display = TimeSeriesDisplay(obj)
display.axes = None
with np.testing.assert_raises(RuntimeError):
display.set_yrng([0, 10])
with np.testing.assert_raises(RuntimeError):
display.set_xrng([0, 10])
display.fig = None
display.plot('temp_mean', add_nan=True)
assert display.fig is not None
assert display.axes is not None
with np.testing.assert_raises(AttributeError):
display = TimeSeriesDisplay([])
fig, ax = matplotlib.pyplot.subplots()
display = TimeSeriesDisplay(obj)
display.add_subplots((2, 2), figsize=(15, 10))
display.assign_to_figure_axis(fig, ax)
assert display.fig is not None
assert display.axes is not None
obj = arm.read_netcdf(files)
display = TimeSeriesDisplay(obj)
obj.clean.cleanup()
display.axes = None
display.fig = None
display.qc_flag_block_plot('atmos_pressure')
assert display.fig is not None
assert display.axes is not None
matplotlib.pyplot.close(fig=display.fig)
# Add second plot of Ozone. Use variable long name for plot axes title
# and add background color to indicate when sun is shining and solar noon.
var_name = 'ozone'
my_disp.plot(
var_name,
dsname='ozone',
subplot_index=(1, ),
set_title=f"NOAA GML {location} {ozone_obj[var_name].attrs['long_name']}",
day_night_background=True)
# Add a wind barb plot from Met datastream. Because the wind speeds are low modify
# the barb thresholds. Currently there is no legend for barbs, that is something
# that will be added in the future.
axes = my_disp.plot_barbs_from_spd_dir(
'wind_direction',
'wind_speed',
dsname='met',
subplot_index=(2, ),
set_title=f"NOAA GML {location} Wind Barbs",
day_night_background=True,
barb_increments={
'half': 1,
'full': 2,
'flag': 3
})
axes.set_ylim(0, 2)
plt.subplots_adjust(hspace=0.4)
plt.show()