def test_plot_bar_and_class_map(pytestconfig):
m = class_map(30, 10, 20, 8)
fig, ax = plt.subplots(1, 2)
data = init_class_data(m,
ax=ax[0],
colorbar_settings={
'ax': ax,
'location': 'bottom'
})
plot_class_map(data=data, ax=ax[0])
bar(data=data, ax=ax[1])
def test_no_args():
# Custom errors as not required if data keyword argument given.
with pytest.raises(TypeError) as e:
bar()
assert "bar() missing 1 required positional argument: 'class_map'" == str(
e.value)
with pytest.raises(TypeError) as e:
plot_class_map()
assert "plot_class_map() missing 1 required positional argument: 'class_map'" == str(
e.value)
class_map = c(t, x, y, n) # 3D array of classifications (t, y, x) #%% # Next, we shall import :func:`mcalf.visualisation.bar`. from mcalf.visualisation import bar #%% # We can now simply plot the 3D array. # By default, the first dimension of a 3D array will be averaged to # produce a time average, selecting the most common classification # at each (x, y) coordinate. # This means the percentage abundances will correspond to the # most common classification at each coordinate. bar(class_map) #%% # Instead, the percentage abundances can be determined for the whole # 3D array of classifications by setting ``reduce=True``. # This skips the averaging process. bar(class_map, reduce=False) #%% # Alternatively, a 2D array can be passed to the function. # If a 2D array is passed, no averaging is needed, and # the ``reduce`` parameter is ignored. #%% # A narrower range of classifications to be plotted can be
colorbar_settings={
'ax': fig.axes,
'label': 'classification',
})
#%%
# The function :func:`mcalf.visualisation.init_class_data`` is
# intended to be an internal function for generating data that
# is common to multiple plotting functions. However, it may be
# used externally if necessary.
from mcalf.visualisation import init_class_data, bar
fig, ax = plt.subplots(1, 2, constrained_layout=True)
data = init_class_data(class_map, resolution=(0.25, 0.25), ax=ax[1])
bar(data=data, ax=ax[0])
plot_class_map(data=data, ax=ax[1], show_colorbar=False)
#%%
# The following example should be equivalent to the example above,
fig, ax = plt.subplots(1, 2, constrained_layout=True)
bar(class_map, ax=ax[0])
plot_class_map(class_map,
ax=ax[1],
show_colorbar=False,
resolution=(0.25, 0.25))
def test_bar_allbad(pytestconfig):
m = class_map(30, 10, 20, 8)
m[:] = -1
bar(m)
def test_bar_reduce(pytestconfig):
m = class_map(30, 10, 20, 8)
bar(m, reduce=False)
def test_bar_range(pytestconfig):
m = class_map(30, 10, 20, 8)
bar(m, vmin=2, vmax=4)
def test_bar(pytestconfig):
m = class_map(30, 10, 20, 8)
bar(m)