def test_plot_barbs_from_u_v2():
bins = list(np.linspace(0, 1, 10))
xbins = list(pd.date_range(pd.to_datetime('2020-01-01'), pd.to_datetime('2020-01-02'), 12))
y_data = np.full([len(xbins), len(bins)], 1.0)
x_data = np.full([len(xbins), len(bins)], 2.0)
y_array = xr.DataArray(y_data, dims={'xbins': xbins, 'ybins': bins}, attrs={'units': 'm/s'})
x_array = xr.DataArray(x_data, dims={'xbins': xbins, 'ybins': bins}, attrs={'units': 'm/s'})
xbins = xr.DataArray(xbins, dims={'xbins': xbins})
ybins = xr.DataArray(bins, dims={'ybins': bins})
fake_obj = xr.Dataset({'xbins': xbins, 'ybins': ybins, 'ydata': y_array, 'xdata': x_array})
BarbDisplay = TimeSeriesDisplay(fake_obj)
BarbDisplay.plot_barbs_from_u_v(
'xdata',
'ydata',
None,
num_barbs_x=20,
num_barbs_y=20,
set_title='test plot',
cmap='jet',
)
fake_obj.close()
try:
return BarbDisplay.fig
finally:
matplotlib.pyplot.close(BarbDisplay.fig)
def test_plot_barbs_from_u_v():
sonde_ds = arm.read_netcdf(
sample_files.EXAMPLE_TWP_SONDE_WILDCARD)
BarbDisplay = TimeSeriesDisplay({'sonde_darwin': sonde_ds})
BarbDisplay.plot_barbs_from_u_v('u_wind', 'v_wind', '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)