def test_histogram_errors():
files = sample_files.EXAMPLE_MET1
obj = arm.read_netcdf(files)
histdisplay = HistogramDisplay(obj)
histdisplay.axes = None
with np.testing.assert_raises(RuntimeError):
histdisplay.set_yrng([0, 10])
with np.testing.assert_raises(RuntimeError):
histdisplay.set_xrng([-40, 40])
histdisplay.fig = None
histdisplay.plot_stacked_bar_graph('temp_mean', bins=np.arange(-40, 40, 5))
histdisplay.set_yrng([0, 0])
assert histdisplay.yrng[0][1] == 1.
assert histdisplay.fig is not None
assert histdisplay.axes is not None
with np.testing.assert_raises(AttributeError):
HistogramDisplay([])
histdisplay.axes = None
histdisplay.fig = None
histdisplay.plot_stairstep_graph('temp_mean', bins=np.arange(-40, 40, 5))
assert histdisplay.fig is not None
assert histdisplay.axes is not None
sigma = 10
mu = 50
bins = np.linspace(0, 100, 50)
ydata = 1 / (sigma * np.sqrt(2 * np.pi)) * np.exp(-(bins - mu)**2 /
(2 * sigma**2))
y_array = xr.DataArray(ydata, dims={'bins': bins})
bins = xr.DataArray(bins, dims={'bins': bins})
my_fake_ds = xr.Dataset({'bins': bins, 'ydata': y_array})
histdisplay = HistogramDisplay(my_fake_ds)
histdisplay.axes = None
histdisplay.fig = None
histdisplay.plot_size_distribution('ydata',
'bins',
set_title='Fake distribution.')
assert histdisplay.fig is not None
assert histdisplay.axes is not None
sonde_ds = arm.read_netcdf(sample_files.EXAMPLE_SONDE1)
histdisplay = HistogramDisplay({'sgpsondewnpnC1.b1': sonde_ds})
histdisplay.axes = None
histdisplay.fig = None
histdisplay.plot_heatmap('tdry',
'alt',
x_bins=np.arange(-60, 10, 1),
y_bins=np.linspace(0, 10000., 50),
cmap='coolwarm')
assert histdisplay.fig is not None
assert histdisplay.axes is not None
matplotlib.pyplot.close(fig=histdisplay.fig)
def test_size_distribution():
sigma = 10
mu = 50
bins = np.linspace(0, 100, 50)
ydata = 1 / (sigma * np.sqrt(2 * np.pi)) * np.exp(-(bins - mu)**2 / (2 * sigma**2))
y_array = xr.DataArray(ydata, dims={'bins': bins})
bins = xr.DataArray(bins, dims={'bins': bins})
my_fake_ds = xr.Dataset({'bins': bins, 'ydata': y_array})
histdisplay = HistogramDisplay(my_fake_ds)
histdisplay.plot_size_distribution('ydata', 'bins', set_title='Fake distribution.')
return histdisplay.fig
def test_size_distribution():
sigma = 10
mu = 50
bins = np.linspace(0, 100, 50)
ydata = 1 / (sigma * np.sqrt(2 * np.pi)) * np.exp(-((bins - mu) ** 2) / (2 * sigma**2))
y_array = xr.DataArray(ydata, dims={'time': bins})
bins = xr.DataArray(bins, dims={'time': bins})
my_fake_ds = xr.Dataset({'time': bins, 'ydata': y_array})
histdisplay = HistogramDisplay(my_fake_ds)
histdisplay.plot_size_distribution('ydata', 'time', set_title='Fake distribution.')
try:
return histdisplay.fig
finally:
matplotlib.pyplot.close(histdisplay.fig)