def bokeh_quantiles(ticks,
avgs,
quantiles,
color='#000055',
alpha=1.0,
**kwargs):
plotting.line(ticks,
avgs,
color=color,
line_alpha=alpha,
title_text_font_size='6pt',
**kwargs)
plotting.hold(True)
if quantiles is not None:
print(quantiles)
x_std = list(ticks) + list(reversed(ticks))
y_std = ([q_min for q_min, q_max in quantiles] +
list(reversed([q_max for q_min, q_max in quantiles])))
plotting.patch(x_std,
y_std,
fill_color=color,
fill_alpha=alpha * 0.25,
line_color=None)
plotting.grid().grid_line_color = 'white'
plotting_axis()
plotting.hold(False)
def coverage(
s_channels,
threshold,
s_vectors=(),
title="no title",
swap_xy=True,
x_range=None,
y_range=None,
color=C_COLOR,
c_alpha=1.0,
alpha=0.5,
**kwargs
):
x_range, y_range = ranges(s_channels, x_range=x_range, y_range=y_range)
try:
xv, yv = zip(*(s[:2] for s in s_vectors))
except ValueError:
xv, yv = [], []
if swap_xy:
x_range, y_range = y_range, x_range
xv, yv = yv, xv
plotting.circle(
xv,
yv,
radius=threshold,
x_range=x_range,
y_range=y_range,
fill_color=hexa(color, 0.35),
fill_alpha=c_alpha,
line_color=None,
title=title,
**kwargs
)
plotting.hold(True)
union = shapely.ops.unary_union([shapely.geometry.Point(*sv_i).buffer(threshold) for sv_i in s_vectors])
boundary = union.boundary
if isinstance(boundary, shapely.geometry.LineString):
boundary = [boundary]
for b in boundary:
x, y = b.xy
x, y = list(x), list(y)
if swap_xy:
x, y = y, x
plotting.patch(x, y, fill_color=None, line_color=hexa(color, 0.75))
plotting.hold(True)
plotting_axis()
plotting.hold(False)
def bokeh_quantiles(ticks, avgs, quantiles, color="#000055", alpha=1.0, **kwargs):
plotting.line(ticks, avgs, color=color, line_alpha=alpha, title_text_font_size="6pt", **kwargs)
plotting.hold(True)
if quantiles is not None:
print(quantiles)
x_std = list(ticks) + list(reversed(ticks))
y_std = [q_min for q_min, q_max in quantiles] + list(reversed([q_max for q_min, q_max in quantiles]))
plotting.patch(x_std, y_std, fill_color=color, fill_alpha=alpha * 0.25, line_color=None)
plotting.grid().grid_line_color = "white"
plotting_axis()
plotting.hold(False)
def coverage(s_channels,
threshold,
s_vectors=(),
title='no title',
swap_xy=True,
x_range=None,
y_range=None,
color=C_COLOR,
c_alpha=1.0,
alpha=0.5,
**kwargs):
x_range, y_range = ranges(s_channels, x_range=x_range, y_range=y_range)
try:
xv, yv = zip(*(s[:2] for s in s_vectors))
except ValueError:
xv, yv = [], []
if swap_xy:
x_range, y_range = y_range, x_range
xv, yv = yv, xv
plotting.circle(xv,
yv,
radius=threshold,
x_range=x_range,
y_range=y_range,
fill_color=hexa(color, 0.35),
fill_alpha=c_alpha,
line_color=None,
title=title,
**kwargs)
plotting.hold(True)
union = shapely.ops.unary_union([
shapely.geometry.Point(*sv_i).buffer(threshold) for sv_i in s_vectors
])
boundary = union.boundary
if isinstance(boundary, shapely.geometry.LineString):
boundary = [boundary]
for b in boundary:
x, y = b.xy
x, y = list(x), list(y)
if swap_xy:
x, y = y, x
plotting.patch(x, y, fill_color=None, line_color=hexa(color, 0.75))
plotting.hold(True)
plotting_axis()
plotting.hold(False)
def perf_astd(ticks,
avgs,
astds,
color=BLUE,
alpha=1.0,
sem=1.0,
plot_width=1000,
plot_height=500,
**kwargs):
plotting.line(ticks,
avgs,
color=color,
line_alpha=alpha,
title_text_font_size='6pt',
plot_width=plot_width,
plot_height=plot_height,
**kwargs)
plotting.hold(True)
if astds is not None:
x_std = list(ticks) + list(reversed(ticks))
y_std = ([
a - s_min / math.sqrt(sem)
for a, (s_min, s_max) in zip(avgs, astds)
] + list(
reversed([
a + s_max / math.sqrt(sem)
for a, (s_min, s_max) in zip(avgs, astds)
])))
plotting.patch(x_std,
y_std,
fill_color=color,
fill_alpha=alpha * 0.25,
line_color=None)
plotting.grid().grid_line_color = 'white'
plotting_axis()
plotting.hold(False)
def perf_astd(ticks, avgs, astds, color=BLUE, alpha=1.0, sem=1.0, plot_width=1000, plot_height=500, **kwargs):
plotting.line(
ticks,
avgs,
color=color,
line_alpha=alpha,
title_text_font_size="6pt",
plot_width=plot_width,
plot_height=plot_height,
**kwargs
)
plotting.hold(True)
if astds is not None:
x_std = list(ticks) + list(reversed(ticks))
y_std = [a - s_min / math.sqrt(sem) for a, (s_min, s_max) in zip(avgs, astds)] + list(
reversed([a + s_max / math.sqrt(sem) for a, (s_min, s_max) in zip(avgs, astds)])
)
plotting.patch(x_std, y_std, fill_color=color, fill_alpha=alpha * 0.25, line_color=None)
plotting.grid().grid_line_color = "white"
plotting_axis()
plotting.hold(False)
def adapt_graphs(ex_cfg, explorations, s_vectors, weight_history, mesh=None, title="no title"):
s_channels = ex_cfg.s_channels
tally_dict = {}
for exploration, feedback in explorations:
key = exploration["from"] + "_" + exploration["uuid"][:8]
tally_dict.setdefault(key, 0)
tally_dict[key] += 1
print(tally_dict)
if ex_cfg.div_algorithm == "hyperball":
coverage(s_channels, ex_cfg.threshold, s_vectors=s_vectors, title=title)
else:
assert ex_cfg.div_algorithm == "grid"
if mesh is not None:
mesh(mesh, title=title)
hold(True)
spread(s_channels, s_vectors=s_vectors, e_radius=1.25, e_alpha=0.75, grid=False)
# interest measure
colors = [BLUE, PINK, GREEN]
weight_lists = zip(*weight_history["data"])
for i, weights in enumerate(weight_lists):
perf_std(
range(len(weights)),
weights,
[0.0 for _ in weights],
legend=weight_history["ex_names"][i] + " ex_{}".format(i),
color=colors[i],
alpha=0.5,
x_range=(0, len(weights)),
plot_width=1000,
plot_height=300,
title="diversity: {}".format(title),
)
hold(True)
hold(False)
# # usage with sliding window
window = 100.0
uuid_history = tuple(e[0]["uuids"] for e in explorations)
assert len(weight_lists) == 2
for i, weights in enumerate(weight_lists):
ex_uuid = weight_history["ex_uuids"][0]
ex_name = weight_history["ex_names"][0]
usage = [t_usage(window, t, ex_uuid, uuid_history) for t in range(len(uuid_history))]
x_p = tuple(range(1, len(usage) + 1)) + (len(usage), 0)
y_p = tuple(usage) + (i, i)
plotting.patch(
x_p,
y_p,
fill_color=colors[i],
fill_alpha=0.5,
line_color=None,
plot_width=1000,
plot_height=300,
title="usage: {}".format(title),
y_range=(0.0, 1.0),
x_range=(0, len(usage)),
)
hold(True)
perf_std(
range(len(usage)),
usage,
[0.0 for _ in usage],
color="black",
alpha=0.05,
plot_width=1000,
plot_height=300,
title="usage: {}".format(title),
y_range=(0.0, 1.0),
)
hold(True)
hold(False)
# print('{} {:.3f}'.format(env_name, np.average(errors)))
return tally_dict
# Define Bollinger Bands.
upperband = np.random.random_integers(100, 150, size=100)
lowerband = upperband - 100
x_data = np.arange(1, 101)
# Bollinger shading glyph:
band_x = np.append(x_data, x_data[::-1])
band_y = np.append(lowerband, upperband[::-1])
pl.patch(band_x, band_y, color='#7570B3', fill_alpha=0.2)
pl.show()
# In[27]:
import bokeh
for ele in dir(bokeh):
if 'version' in ele:
print ele
