def plot_rectangles(ax, single_example, plot_seq_width=1, offset=0, how='bar',
**plot_kwargs):
"""
Parameters
----------
ax : matplotlib axes
single_example : numpy.ndarray
A single example from within the batch.
i.e. single_output = batch[seq_i]
Shape = (3, n_outputs)
plot_seq_width : int or float, optional
The width of a sequence plotted on the X-axis.
Multiply `left` and `right` values by `plot_seq_width` before plotting.
offset : float, optional
Shift rectangles left or right by `offset` where one complete sequence
is of length `plot_seq_width`. i.e. to move rectangles half a plot
width right, set `offset` to `plot_seq_width / 2.0`.
how : {'bar', 'line'}
**plot_kwargs : key word arguments to send to `ax.bar()`. For example:
alpha : float, optional
[0, 1]. Transparency for the rectangles.
color
"""
# sanity check
for obj in [plot_seq_width, offset]:
if not isinstance(obj, (int, float)):
raise ValueError("Incorrect input: {}".format(obj))
assert single_example.shape[0] == 3
n_outputs = single_example.shape[1]
colors = get_colors(n_outputs)
for output_i in range(n_outputs):
single_rect = single_example[:, output_i]
# left
left = (single_rect[0] * plot_seq_width) + offset
right = (single_rect[1] * plot_seq_width) + offset
# width
if single_rect[0] > 0 and single_rect[1] > 0:
width = (single_rect[1] - single_rect[0]) * plot_seq_width
else:
width = 0
height = single_rect[2]
color = colors[output_i]
plot_kwargs.setdefault('color', color)
if how == 'bar':
plot_kwargs.setdefault('edgecolor', plot_kwargs['color'])
plot_kwargs.setdefault('linewidth', 0)
ax.bar(left, height, width, **plot_kwargs)
elif how == 'line':
ax.plot([left, left, right, right],
[0, height, height, 0],
**plot_kwargs)
else:
raise ValueError("'how' is not recognised.")
def _plot_validation_scores_for_source_and_fold(self, ax, source_id, fold,
show_axes_labels,
show_scales):
fields = ['iteration'] + ['scores.' + metric_name for metric_name in
self.validation_metric_names]
monary = Monary(host=self.mongo_host)
result = monary.query(
db=self.mongo_db,
coll='validation_scores',
query={
'experiment_id': self.experiment_id,
'source_id': source_id,
'fold': fold
},
fields=fields,
types=['int32'] + ['float32'] * len(self.validation_metric_names)
)
index = result[0]
data = {metric_name: result[i+1] for i, metric_name in
enumerate(self.validation_metric_names)}
df = pd.DataFrame(data, index=index)
df = df.sort_index()
df = self._downsample(df)
# Create multiple independent axes. Adapted from Joe Kington's answer:
# http://stackoverflow.com/a/7734614
# Colours
n = len(self.validation_metric_names)
colors = get_colors(n)
# Twin the x-axis to make independent y-axes.
axes = [ax]
for metric_name in self.validation_metric_names[1:]:
axes.append(ax.twinx())
SEP = 0.2
if show_scales:
for i, axis in enumerate(axes):
axis.yaxis.tick_right()
if i != 0:
# To make the border of the right-most axis visible,
# we need to turn the frame on. This hides the other plots,
# however, so we need to turn its fill off.
axis.set_frame_on(True)
axis.patch.set_visible(False)
# Move the last y-axes spines over to the right.
axis.spines['right'].set_position(
('axes', 1 + (SEP * i)))
else:
for axis in axes:
axis.tick_params(labelright=False, labelleft=False)
axis.yaxis.set_ticks_position('none')
axis.spines['right'].set_visible(False)
for axis in axes:
for spine in ['top', 'left', 'bottom']:
axis.spines[spine].set_visible(False)
axis.xaxis.set_ticks_position('none')
lines = []
for i, (axis, metric_name, color) in enumerate(
zip(axes, self.validation_metric_names, colors)):
axis.tick_params(axis='y', colors=color, direction='out')
label = metric_name.replace("regression.", "")
label = label.replace("classification_", "")
label = label.replace("_", " ")
label = label.replace(".", " ")
label = label.replace(" ", "\n")
line, = axis.plot(
df.index, df[metric_name].values, color=color, label=label)
if show_axes_labels and show_scales:
axis.set_ylabel(
label, color=color, rotation=0, fontsize=8, va='bottom')
if i == 0:
coords = (1.05, 1.1)
else:
coords = (1.05 + (SEP * i), 1.1)
axis.yaxis.set_label_coords(*coords)
lines.append(line)
self._last_iteration_processed['validation'] = index[-1]
return lines
def _plot_validation_scores_for_source_and_fold(self, ax, source_id, fold,
show_axes_labels,
show_scales):
fields = ['iteration'] + [
'scores.' + metric_name
for metric_name in self.validation_metric_names
]
monary = Monary(host=self.mongo_host)
result = monary.query(db=self.mongo_db,
coll='validation_scores',
query={
'experiment_id': self.experiment_id,
'source_id': source_id,
'fold': fold
},
fields=fields,
types=['int32'] +
['float32'] * len(self.validation_metric_names))
index = result[0]
data = {
metric_name: result[i + 1]
for i, metric_name in enumerate(self.validation_metric_names)
}
df = pd.DataFrame(data, index=index)
df = df.sort_index()
df = self._downsample(df)
# Create multiple independent axes. Adapted from Joe Kington's answer:
# http://stackoverflow.com/a/7734614
# Colours
n = len(self.validation_metric_names)
colors = get_colors(n)
# Twin the x-axis to make independent y-axes.
axes = [ax]
for metric_name in self.validation_metric_names[1:]:
axes.append(ax.twinx())
SEP = 0.2
if show_scales:
for i, axis in enumerate(axes):
axis.yaxis.tick_right()
if i != 0:
# To make the border of the right-most axis visible,
# we need to turn the frame on. This hides the other plots,
# however, so we need to turn its fill off.
axis.set_frame_on(True)
axis.patch.set_visible(False)
# Move the last y-axes spines over to the right.
axis.spines['right'].set_position(('axes', 1 + (SEP * i)))
else:
for axis in axes:
axis.tick_params(labelright=False, labelleft=False)
axis.yaxis.set_ticks_position('none')
axis.spines['right'].set_visible(False)
for axis in axes:
for spine in ['top', 'left', 'bottom']:
axis.spines[spine].set_visible(False)
axis.xaxis.set_ticks_position('none')
lines = []
for i, (axis, metric_name, color) in enumerate(
zip(axes, self.validation_metric_names, colors)):
axis.tick_params(axis='y', colors=color, direction='out')
label = metric_name.replace("regression.", "")
label = label.replace("classification_", "")
label = label.replace("_", " ")
label = label.replace(".", " ")
label = label.replace(" ", "\n")
line, = axis.plot(df.index,
df[metric_name].values,
color=color,
label=label)
if show_axes_labels and show_scales:
axis.set_ylabel(label,
color=color,
rotation=0,
fontsize=8,
va='bottom')
if i == 0:
coords = (1.05, 1.1)
else:
coords = (1.05 + (SEP * i), 1.1)
axis.yaxis.set_label_coords(*coords)
lines.append(line)
self._last_iteration_processed['validation'] = index[-1]
return lines
def plot_rectangles(ax,
single_example,
plot_seq_width=1,
offset=0,
how='bar',
**plot_kwargs):
"""
Parameters
----------
ax : matplotlib axes
single_example : numpy.ndarray
A single example from within the batch.
i.e. single_output = batch[seq_i]
Shape = (3, n_outputs)
plot_seq_width : int or float, optional
The width of a sequence plotted on the X-axis.
Multiply `left` and `right` values by `plot_seq_width` before plotting.
offset : float, optional
Shift rectangles left or right by `offset` where one complete sequence
is of length `plot_seq_width`. i.e. to move rectangles half a plot
width right, set `offset` to `plot_seq_width / 2.0`.
how : {'bar', 'line'}
**plot_kwargs : key word arguments to send to `ax.bar()`. For example:
alpha : float, optional
[0, 1]. Transparency for the rectangles.
color
"""
# sanity check
for obj in [plot_seq_width, offset]:
if not isinstance(obj, (int, float)):
raise ValueError("Incorrect input: {}".format(obj))
assert single_example.shape[0] == 3
n_outputs = single_example.shape[1]
colors = get_colors(n_outputs)
for output_i in range(n_outputs):
single_rect = single_example[:, output_i]
# left
left = (single_rect[0] * plot_seq_width) + offset
right = (single_rect[1] * plot_seq_width) + offset
# width
if single_rect[0] > 0 and single_rect[1] > 0:
width = (single_rect[1] - single_rect[0]) * plot_seq_width
else:
width = 0
height = single_rect[2]
color = colors[output_i]
plot_kwargs.setdefault('color', color)
if how == 'bar':
plot_kwargs.setdefault('edgecolor', plot_kwargs['color'])
plot_kwargs.setdefault('linewidth', 0)
ax.bar(left, height, width, **plot_kwargs)
elif how == 'line':
ax.plot([left, left, right, right], [0, height, height, 0],
**plot_kwargs)
else:
raise ValueError("'how' is not recognised.")
