def _create_increment_one_axis(self, plot, start, number, orientation,
ticks=None):
"""Create axis with ticks at a distance of one units.
Parameters
----------
plot : Plot
plot where the axis will be attached
start : float
position of first tick
number : int
number of ticks
orientation: ['top', 'bottom', 'left', 'right']
position of axis on the plot
ticks : list of strings
string to be displayed for each tick
"""
ids = start + np.arange(0, number)
if ticks is None:
ticks = [str(idx) for idx in np.arange(0, number)]
axis = LabelAxis(
plot,
orientation = orientation,
positions = ids,
labels = ticks,
label_rotation = 0
)
# use a FixedScale tick generator with a resolution of 1
axis.tick_generator = ScalesTickGenerator(scale=FixedScale(1.))
return axis
def _create_probability_axis(self, plot):
"""Create plot axis for probability values."""
prob_axis = LabelAxis(plot,
orientation='left',
positions=[0.5, 0.5 + np.sqrt(0.25) / 2., 1.0],
labels=['0', '0.25', '1'])
prob_axis.tick_generator = ScalesTickGenerator(scale=FixedScale(0.001))
return prob_axis
def _create_probability_axis(self, plot):
"""Create plot axis for probability values."""
prob_axis = LabelAxis(
plot,
orientation='left',
positions=[0.5, 0.5 + np.sqrt(0.25) / 2., 1.0],
labels=['0', '0.25', '1']
)
prob_axis.tick_generator = ScalesTickGenerator(scale=FixedScale(0.001))
return prob_axis
def _create_increment_one_axis(self,
plot,
start,
number,
orientation,
ticks=None):
"""Create axis with ticks at a distance of one units.
Parameters
----------
plot : Plot
plot where the axis will be attached
start : float
position of first tick
number : int
number of ticks
orientation: ['top', 'bottom', 'left', 'right']
position of axis on the plot
ticks : list of strings
string to be displayed for each tick
"""
ids = start + np.arange(0, number)
if ticks is None:
ticks = [str(idx) for idx in np.arange(0, number)]
axis = LabelAxis(plot,
orientation=orientation,
positions=ids,
labels=ticks,
label_rotation=0)
# use a FixedScale tick generator with a resolution of 1
axis.tick_generator = ScalesTickGenerator(scale=FixedScale(1.))
return axis
def _theta_plot_default(self):
"""Create plot of theta parameters."""
# We plot both the thetas and the samples from the posterior; if the
# latter are not defined, the corresponding ArrayPlotData names
# should be set to an empty list, so that they are not displayed
theta = self.model.theta
theta_len = theta.shape[0]
# create the plot data
if not self.theta_plot_data:
self.theta_plot_data = ArrayPlotData()
self._update_plot_data()
# create the plot
theta_plot = Plot(self.theta_plot_data)
for idx in range(theta_len):
# candle plot summarizing samples over the posterior
theta_plot.candle_plot((_w_idx('index', idx),
_w_idx('min', idx),
_w_idx('barmin', idx),
_w_idx('avg', idx),
_w_idx('barmax', idx),
_w_idx('max', idx)),
color = get_annotator_color(idx),
bar_line_color = "black",
stem_color = "blue",
center_color = "red",
center_width = 2)
# plot of raw samples
theta_plot.plot((_w_idx('ysamples', idx),
_w_idx('xsamples', idx)),
type='scatter',
color='black',
marker='dot',
line_width=0.5,
marker_size=1)
# plot current parameters
theta_plot.plot((_w_idx('y', idx), _w_idx('x', idx)),
type='scatter',
color=get_annotator_color(idx),
marker='plus',
marker_size=8,
line_width=2)
# adjust axis bounds
theta_plot.range2d = self._compute_range2d()
# remove horizontal grid and axis
theta_plot.underlays = [theta_plot.x_grid, theta_plot.y_axis]
# create new horizontal axis
label_list = [str(i) for i in range(theta_len)]
label_axis = LabelAxis(
theta_plot,
orientation = 'bottom',
positions = range(1, theta_len+1),
labels = label_list,
label_rotation = 0
)
# use a FixedScale tick generator with a resolution of 1
label_axis.tick_generator = ScalesTickGenerator(scale=FixedScale(1.))
theta_plot.index_axis = label_axis
theta_plot.underlays.append(label_axis)
theta_plot.padding = 25
theta_plot.padding_left = 40
theta_plot.aspect_ratio = 1.0
container = VPlotContainer()
container.add(theta_plot)
container.bgcolor = 0xFFFFFF
self.decorate_plot(container, theta)
self._set_title(theta_plot)
return container
def _theta_plot_default(self):
"""Create plot of theta parameters."""
# We plot both the thetas and the samples from the posterior; if the
# latter are not defined, the corresponding ArrayPlotData names
# should be set to an empty list, so that they are not displayed
theta = self.model.theta
theta_len = theta.shape[0]
# create the plot data
if not self.theta_plot_data:
self.theta_plot_data = ArrayPlotData()
self._update_plot_data()
# create the plot
theta_plot = Plot(self.theta_plot_data)
for idx in range(theta_len):
# candle plot summarizing samples over the posterior
theta_plot.candle_plot((_w_idx('index', idx),
_w_idx('min', idx),
_w_idx('barmin', idx),
_w_idx('avg', idx),
_w_idx('barmax', idx),
_w_idx('max', idx)),
color = get_annotator_color(idx),
bar_line_color = "black",
stem_color = "blue",
center_color = "red",
center_width = 2)
# plot of raw samples
theta_plot.plot((_w_idx('ysamples', idx),
_w_idx('xsamples', idx)),
type='scatter',
color='black',
marker='dot',
line_width=0.5,
marker_size=1)
# plot current parameters
theta_plot.plot((_w_idx('y', idx), _w_idx('x', idx)),
type='scatter',
color=get_annotator_color(idx),
marker='plus',
marker_size=8,
line_width=2)
# adjust axis bounds
theta_plot.range2d = self._compute_range2d()
# remove horizontal grid and axis
theta_plot.underlays = [theta_plot.x_grid, theta_plot.y_axis]
# create new horizontal axis
label_list = [str(i) for i in range(theta_len)]
label_axis = LabelAxis(
theta_plot,
orientation = 'bottom',
positions = list(range(1, theta_len+1)),
labels = label_list,
label_rotation = 0
)
# use a FixedScale tick generator with a resolution of 1
label_axis.tick_generator = ScalesTickGenerator(scale=FixedScale(1.))
theta_plot.index_axis = label_axis
theta_plot.underlays.append(label_axis)
theta_plot.padding = 25
theta_plot.padding_left = 40
theta_plot.aspect_ratio = 1.0
container = VPlotContainer()
container.add(theta_plot)
container.bgcolor = 0xFFFFFF
self.decorate_plot(container, theta)
self._set_title(theta_plot)
return container
def test_label_axis(self):
axis = LabelAxis()
with warnings.catch_warnings(record=True) as w:
axis.positions = np.arange(10)
self.assertEqual(w, [])