def test_different_parameters():
np.random.seed(3)
params_x = ['x0', 'x1', 'x2', 'x3', 'x4']
params_y = ['x0', 'x1', 'x2']
fig, axes = make_1d_axes(params_x)
ns = NestedSamples(root='./tests/example_data/pc')
ns.plot_1d(axes)
fig, axes = make_2d_axes(params_y)
ns.plot_2d(axes)
fig, axes = make_2d_axes(params_x)
ns.plot_2d(axes)
fig, axes = make_2d_axes([params_x, params_y])
ns.plot_2d(axes)
plt.close('all')
def test_masking():
pc = NestedSamples(root="./tests/example_data/pc")
mask = pc['x0'] > 0
plot_types = ['kde', 'hist']
if 'fastkde' in sys.modules:
plot_types += ['fastkde']
for ptype in plot_types:
fig, axes = make_1d_axes(['x0', 'x1', 'x2'])
pc[mask].plot_1d(axes=axes, plot_type=ptype)
for ptype in plot_types + ['scatter']:
fig, axes = make_2d_axes(['x0', 'x1', 'x2'], upper=False)
pc[mask].plot_2d(axes=axes, types=dict(lower=ptype, diagonal='hist'))
def test_plot_2d_colours():
np.random.seed(3)
gd = MCMCSamples(root="./tests/example_data/gd")
gd.drop(columns='x3', inplace=True)
pc = NestedSamples(root="./tests/example_data/pc")
pc.drop(columns='x4', inplace=True)
mn = NestedSamples(root="./tests/example_data/mn")
mn.drop(columns='x2', inplace=True)
plot_types = ['kde', 'hist']
if 'fastkde' in sys.modules:
plot_types += ['fastkde']
for types in plot_types:
fig = plt.figure()
fig, axes = make_2d_axes(['x0', 'x1', 'x2', 'x3', 'x4'], fig=fig)
types = {'diagonal': types, 'lower': types, 'upper': 'scatter'}
gd.plot_2d(axes, types=types, label="gd")
pc.plot_2d(axes, types=types, label="pc")
mn.plot_2d(axes, types=types, label="mn")
gd_colors = []
pc_colors = []
mn_colors = []
for y, rows in axes.iterrows():
for x, ax in rows.iteritems():
handles, labels = ax.get_legend_handles_labels()
for handle, label in zip(handles, labels):
if isinstance(handle, Rectangle):
color = to_hex(handle.get_facecolor())
else:
color = handle.get_color()
if label == 'gd':
gd_colors.append(color)
elif label == 'pc':
pc_colors.append(color)
elif label == 'mn':
mn_colors.append(color)
assert(len(set(gd_colors)) == 1)
assert(len(set(mn_colors)) == 1)
assert(len(set(pc_colors)) == 1)
plt.close("all")
def test_plot_2d_legend():
np.random.seed(3)
ns = NestedSamples(root='./tests/example_data/pc')
mc = MCMCSamples(root='./tests/example_data/gd')
params = ['x0', 'x1', 'x2', 'x3']
# Test label kwarg for kde
fig, axes = make_2d_axes(params, upper=False)
ns.plot_2d(axes, label='l1', types=dict(diagonal='kde', lower='kde'))
mc.plot_2d(axes, label='l2', types=dict(diagonal='kde', lower='kde'))
for y, row in axes.iterrows():
for x, ax in row.iteritems():
if ax is not None:
handles, labels = ax.get_legend_handles_labels()
assert(labels == ['l1', 'l2'])
if x == y:
assert(all([isinstance(h, Line2D) for h in handles]))
else:
assert(all([isinstance(h, Rectangle) for h in handles]))
plt.close('all')
# Test label kwarg for hist and scatter
fig, axes = make_2d_axes(params, lower=False)
ns.plot_2d(axes, label='l1', types=dict(diagonal='hist', upper='scatter'))
mc.plot_2d(axes, label='l2', types=dict(diagonal='hist', upper='scatter'))
for y, row in axes.iterrows():
for x, ax in row.iteritems():
if ax is not None:
handles, labels = ax.get_legend_handles_labels()
assert(labels == ['l1', 'l2'])
if x == y:
assert(all([isinstance(h, Rectangle) for h in handles]))
else:
assert(all([isinstance(h, Line2D)
for h in handles]))
plt.close('all')
# test default labelling
fig, axes = make_2d_axes(params, upper=False)
ns.plot_2d(axes)
mc.plot_2d(axes)
for y, row in axes.iterrows():
for x, ax in row.iteritems():
if ax is not None:
handles, labels = ax.get_legend_handles_labels()
assert(labels == ['pc', 'gd'])
plt.close('all')
# Test label kwarg to constructors
ns = NestedSamples(root='./tests/example_data/pc', label='l1')
mc = MCMCSamples(root='./tests/example_data/gd', label='l2')
params = ['x0', 'x1', 'x2', 'x3']
fig, axes = make_2d_axes(params, upper=False)
ns.plot_2d(axes)
mc.plot_2d(axes)
for y, row in axes.iterrows():
for x, ax in row.iteritems():
if ax is not None:
handles, labels = ax.get_legend_handles_labels()
assert(labels == ['l1', 'l2'])
plt.close('all')
mcmc.plot_2d([['omegabh2', 'omegach2', 'H0'], ['logA', 'ns']])
#| Rectangle plots are pretty flexible with what they can do:
mcmc.plot_2d([['omegabh2', 'omegach2', 'H0'], ['H0', 'omegach2']])
#| ## Changing the appearance
#|
#| Anesthetic tries to follow matplotlib conventions as much as possible, so
#| most changes to the appearance should be relatively straight forward.
#| Here are some examples:
#|
#| * figure size:
fig = plt.figure(figsize=(5, 5))
fig, axes = make_2d_axes(['omegabh2', 'omegach2', 'H0'], fig=fig, tex=mcmc.tex)
mcmc.plot_2d(axes)
#| * legends:
fig, axes = make_2d_axes(['omegabh2', 'omegach2', 'H0'], tex=mcmc.tex)
mcmc.plot_2d(axes, label='Posterior')
axes.iloc[-1, 0].legend(bbox_to_anchor=(len(axes), len(axes)),
loc='upper left')
#| * unfilled contours & modifying individual axes:
fig, axes = make_2d_axes(['omegabh2', 'omegach2', 'H0'], tex=mcmc.tex)
mcmc.plot_2d(axes.iloc[0:1, :],
types=dict(upper='kde', lower='kde', diagonal='kde'),
fc=None)
