def plot_histograms(
self,
keys: Sequence[str],
ax: Optional[plt.Axes] = None,
*,
labels: Optional[Sequence[str]] = None,
) -> plt.Axes:
"""Plots integrated histograms of metric values corresponding to keys
Args:
keys: List of metric keys for which an integrated histogram should be plot
ax: The axis to plot on. If None, we generate one.
Returns:
The axis that was plotted on.
Raises:
ValueError if the metric values are not single floats.
"""
show_plot = not ax
if not ax:
fig, ax = plt.subplots(1, 1)
if isinstance(keys, str):
keys = [keys]
if not labels:
labels = keys
colors = ['b', 'r', 'k', 'g', 'c', 'm']
for key, label, color in zip(keys, labels, cycle(colors)):
metrics = self[key]
if not all(len(k) == 1 for k in metrics.values()):
raise ValueError(
'Histograms are only supported if all values in a metric '
+ 'are single metric values.'
+ f'{key} has metric values {metrics.values()}'
)
vis.integrated_histogram(
[self.value_to_float(v) for v in metrics.values()],
ax,
label=label,
color=color,
title=key.replace('_', ' ').title(),
)
if show_plot:
fig.show()
return ax
def test_multiple_plots():
_, ax = plt.subplots(1, 1)
n = 53
data = np.random.random_sample((2, n))
integrated_histogram(
data[0],
ax,
color='r',
label='data_1',
median_line=False,
mean_line=True,
mean_label='mean_1',
)
integrated_histogram(data[1],
ax,
color='k',
label='data_2',
median_label='median_2')
assert ax.get_title() == 'N=53'
for line in ax.get_lines():
assert line.get_color() in ['r', 'k']
assert line.get_label() in ['data_1', 'data_2', 'mean_1', 'median_2']
def test_integrated_histogram(data):
ax = integrated_histogram(
data,
title='Test Plot',
axis_label='Y Axis Label',
color='r',
label='line label',
cdf_on_x=True,
show_zero=True,
)
assert ax.get_title() == 'Test Plot'
assert ax.get_ylabel() == 'Y Axis Label'
assert len(ax.get_lines()) == 2
for line in ax.get_lines():
assert line.get_color() == 'r'