def make_plot(
plot_lists,
use_median=False,
plot_width=None,
plot_height=None,
title=None,
):
"""
plot_lists is a list of lists.
Each outer list represents different y-axis attributes.
Each inner list represents different experiments to run, within that y-axis
attribute.
Each plot is an AttrDict which should have the elements used below.
"""
x_axis = [(subplot['plot_key'], subplot['means']) for plot_list in plot_lists for subplot in plot_list if subplot['x_key']]
plot_lists = [[subplot for subplot in plot_list] for plot_list in plot_lists if not plot_list[0]['x_key']]
xlabel = x_axis[0][0] if len(x_axis) else 'iteration'
p25, p50, p75 = [], [], []
num_y_axes = len(plot_lists)
fig = tools.make_subplots(rows=num_y_axes, cols=1, print_grid=False)
fig['layout'].update(
width=plot_width,
height=plot_height,
title=title,
)
for y_idx, plot_list in enumerate(plot_lists):
for idx, plt in enumerate(plot_list):
color = core.color_defaults[idx % len(core.color_defaults)]
if use_median:
p25.append(np.mean(plt.percentile25))
p50.append(np.mean(plt.percentile50))
p75.append(np.mean(plt.percentile75))
if x_axis:
x = list(x_axis[idx][1])
else:
x = list(range(len(plt.percentile50)))
y = list(plt.percentile50)
y_upper = list(plt.percentile75)
y_lower = list(plt.percentile25)
else:
if x_axis:
x = list(x_axis[idx][1])
else:
x = list(range(len(plt.means)))
y = list(plt.means)
y_upper = list(plt.means + plt.stds)
y_lower = list(plt.means - plt.stds)
errors = go.Scatter(
x=x + x[::-1],
y=y_upper + y_lower[::-1],
fill='tozerox',
fillcolor=core.hex_to_rgb(color, 0.2),
line=go.scatter.Line(color=core.hex_to_rgb(color, 0)),
showlegend=False,
legendgroup=plt.legend,
hoverinfo='none',
)
values = go.Scatter(
x=x,
y=y,
name=plt.legend,
legendgroup=plt.legend,
line=dict(color=core.hex_to_rgb(color)),
hoverlabel=dict(namelength=-1),
hoverinfo='all',
)
# plotly is 1-indexed like matplotlib for subplots
y_idx_plotly = y_idx + 1
fig.append_trace(values, y_idx_plotly, 1)
fig.append_trace(errors, y_idx_plotly, 1)
title = plt.plot_key
if len(title) > 30:
title_parts = title.split('/')
title = "<br />/".join(
title_parts[:-1]
+ [r"<b>{}</b>".format(t) for t in title_parts[-1:]]
)
fig['layout']['yaxis{}'.format(y_idx_plotly)].update(
title=title,
)
fig['layout']['xaxis{}'.format(y_idx_plotly)].update(
title=xlabel,
)
fig_div = po.plot(fig, output_type='div', include_plotlyjs=False)
if "footnote" in plot_list[0]:
footnote = "<br />".join([
r"<span><b>%s</b></span>: <span>%s</span>" % (
plt.legend, plt.footnote)
for plt in plot_list
])
return r"%s<div>%s</div>" % (fig_div, footnote)
else:
return fig_div
def make_plot(plot_list,
use_median=False,
plot_width=None,
plot_height=None,
title=None):
data = []
p25, p50, p75 = [], [], []
for idx, plt in enumerate(plot_list):
color = core.color_defaults[idx % len(core.color_defaults)]
if use_median:
p25.append(np.mean(plt.percentile25))
p50.append(np.mean(plt.percentile50))
p75.append(np.mean(plt.percentile75))
x = list(range(len(plt.percentile50)))
y = list(plt.percentile50)
y_upper = list(plt.percentile75)
y_lower = list(plt.percentile25)
else:
x = list(range(len(plt.means)))
y = list(plt.means)
y_upper = list(plt.means + plt.stds)
y_lower = list(plt.means - plt.stds)
data.append(
go.Scatter(x=x + x[::-1],
y=y_upper + y_lower[::-1],
fill='tozerox',
fillcolor=core.hex_to_rgb(color, 0.2),
line=go.Line(color='transparent'),
showlegend=False,
legendgroup=plt.legend,
hoverinfo='none'))
data.append(
go.Scatter(
x=x,
y=y,
name=plt.legend,
legendgroup=plt.legend,
line=dict(color=core.hex_to_rgb(color)),
))
p25str = '['
p50str = '['
p75str = '['
for p25e, p50e, p75e in zip(p25, p50, p75):
p25str += (str(p25e) + ',')
p50str += (str(p50e) + ',')
p75str += (str(p75e) + ',')
p25str += ']'
p50str += ']'
p75str += ']'
print(p25str)
print(p50str)
print(p75str)
layout = go.Layout(
legend=dict(
x=1,
y=1,
# xanchor="left",
# yanchor="bottom",
),
width=plot_width,
height=plot_height,
title=title,
)
fig = go.Figure(data=data, layout=layout)
fig_div = po.plot(fig, output_type='div', include_plotlyjs=False)
if "footnote" in plot_list[0]:
footnote = "<br />".join([
r"<span><b>%s</b></span>: <span>%s</span>" %
(plt.legend, plt.footnote) for plt in plot_list
])
return r"%s<div>%s</div>" % (fig_div, footnote)
else:
return fig_div
def make_plot(plot_list, title=None):
data = []
for idx, plt in enumerate(plot_list):
color = core.color_defaults[idx % len(core.color_defaults)]
x = list(plt.xs)
if plt.display_mode in ["mean_std", "mean_se"]:
y = list(plt.means)
if plt.display_mode == "mean_std":
y_upper = list(plt.means + plt.stds)
y_lower = list(plt.means - plt.stds)
elif plt.display_mode == "mean_se":
y_upper = list(plt.means + plt.ses)
y_lower = list(plt.means - plt.ses)
else:
raise NotImplementedError
data.append(
go.Scatter(x=x + x[::-1],
y=y_upper + y_lower[::-1],
fill='tozerox',
fillcolor=core.hex_to_rgb(color, 0.2),
line=go.Line(color='transparent'),
showlegend=False,
legendgroup=plt.legend,
hoverinfo='none'))
data.append(
go.Scatter(
x=x,
y=y,
name=plt.legend,
legendgroup=plt.legend,
line=dict(color=core.hex_to_rgb(color)),
))
elif plt.display_mode == "individual":
for idx, y in enumerate(plt.ys):
data.append(
go.Scatter(
x=x,
y=y,
name=plt.legend,
legendgroup=plt.legend,
line=dict(color=core.hex_to_rgb(color)),
showlegend=idx == 0,
))
else:
raise NotImplementedError
layout = go.Layout(
legend=dict(
x=1,
y=1,
),
title=title,
)
fig = go.Figure(data=data, layout=layout)
fig_div = po.plot(fig, output_type='div', include_plotlyjs=False)
if "footnote" in plot_list[0]:
footnote = "<br />".join([
r"<span><b>%s</b></span>: <span>%s</span>" %
(plt.legend, plt.footnote) for plt in plot_list
])
return r"%s<div>%s</div>" % (fig_div, footnote)
else:
return fig_div
def make_plot(plot_list,
use_median=False,
use_five_numbers=False,
plot_width=None,
plot_height=None,
title=None,
xlim=None,
ylim=None):
data = []
p25, p50, p75 = [], [], []
p0, p100 = [], []
for idx, plt in enumerate(plot_list):
color = core.color_defaults[idx % len(core.color_defaults)]
if use_median:
p25.append(np.mean(plt.percentile25))
p50.append(np.mean(plt.percentile50))
p75.append(np.mean(plt.percentile75))
x = list(range(len(plt.percentile50)))
y = list(plt.percentile50)
y_upper = list(plt.percentile75)
y_lower = list(plt.percentile25)
y_extras = []
elif use_five_numbers:
p0.append(np.mean(plt.percentile0))
p25.append(np.mean(plt.percentile25))
p50.append(np.mean(plt.percentile50))
print('>>> mean: {}'.format(plt.mean))
p75.append(np.mean(plt.percentile75))
p100.append(np.mean(plt.percentile100))
x = list(range(len(plt.percentile50)))
y = list(plt.percentile50)
y_upper = list(plt.percentile75)
y_lower = list(plt.percentile25)
y_extras = [
list(ys) for ys in [plt.percentile0, plt.percentile100]
]
else:
x = list(range(len(plt.means)))
y = list(plt.means)
y_upper = list(plt.means + plt.stds)
y_lower = list(plt.means - plt.stds)
y_extras = []
if hasattr(plt, "custom_x"):
x = list(plt.custom_x)
data.append(
go.Scatter(x=x + x[::-1],
y=y_upper + y_lower[::-1],
fill='tozerox',
fillcolor=core.hex_to_rgb(color, 0.2),
line=go.Line(color='hsva(0,0,0,0)'),
showlegend=False,
legendgroup=plt.legend,
hoverinfo='none'))
data.append(
go.Scatter(
x=x,
y=y,
name=plt.legend,
legendgroup=plt.legend,
line=dict(color=core.hex_to_rgb(color)),
))
for y_extra in y_extras:
data.append(
go.Scatter(
x=x,
y=y_extra,
showlegend=False,
legendgroup=plt.legend,
line=dict(color=core.hex_to_rgb(color), dash='dot')
# choices: solid, dot, dash, longdash, dashdot, longdashdot
))
def numeric_list_to_string(numbers):
s = '['
for num in numbers:
s += (str(num) + ',')
s += ']'
return s
print(numeric_list_to_string(p25))
print(numeric_list_to_string(p50))
print(numeric_list_to_string(p75))
layout = go.Layout(
legend=dict(
x=1,
y=1,
# xanchor="left",
# yanchor="bottom",
),
width=plot_width,
height=plot_height,
title=title,
xaxis=go.XAxis(range=xlim),
yaxis=go.YAxis(range=ylim),
)
fig = go.Figure(data=data, layout=layout)
fig_div = po.plot(fig, output_type='div', include_plotlyjs=False)
if "footnote" in plot_list[0]:
footnote = "<br />".join([
r"<span><b>%s</b></span>: <span>%s</span>" %
(plt.legend, plt.footnote) for plt in plot_list
])
return r"%s<div>%s</div>" % (fig_div, footnote)
else:
return fig_div
def make_plot(plot_list, title=None):
data = []
for idx, plt in enumerate(plot_list):
color = core.color_defaults[idx % len(core.color_defaults)]
x = list(plt.xs)
if plt.display_mode in ["mean_std", "mean_se"]:
y = list(plt.means)
if plt.display_mode == "mean_std":
y_upper = list(plt.means + plt.stds)
y_lower = list(plt.means - plt.stds)
elif plt.display_mode == "mean_se":
y_upper = list(plt.means + plt.ses)
y_lower = list(plt.means - plt.ses)
else:
raise NotImplementedError
data.append(go.Scatter(
x=x + x[::-1],
y=y_upper + y_lower[::-1],
fill='tozerox',
fillcolor=core.hex_to_rgb(color, 0.2),
line=go.Line(color='transparent'),
showlegend=False,
legendgroup=plt.legend,
hoverinfo='none'
))
data.append(go.Scatter(
x=x,
y=y,
name=plt.legend,
legendgroup=plt.legend,
line=dict(color=core.hex_to_rgb(color)),
))
elif plt.display_mode == "individual":
for idx, y in enumerate(plt.ys):
data.append(go.Scatter(
x=x,
y=y,
name=plt.legend,
legendgroup=plt.legend,
line=dict(color=core.hex_to_rgb(color)),
showlegend=idx == 0,
))
else:
raise NotImplementedError
layout = go.Layout(
legend=dict(
x=1,
y=1,
),
title=title,
)
fig = go.Figure(data=data, layout=layout)
fig_div = po.plot(fig, output_type='div', include_plotlyjs=False)
if "footnote" in plot_list[0]:
footnote = "<br />".join([
r"<span><b>%s</b></span>: <span>%s</span>" % (
plt.legend, plt.footnote)
for plt in plot_list
])
return r"%s<div>%s</div>" % (fig_div, footnote)
else:
return fig_div
def make_plot(
plot_lists,
use_median=False,
plot_width=None,
plot_height=None,
title=None,
):
"""
plot_lists is a list of lists.
Each outer list represents different y-axis attributes.
Each inner list represents different experiments to run, within that y-axis
attribute.
Each plot is an AttrDict which should have the elements used below.
"""
p25, p50, p75 = [], [], []
num_y_axes = len(plot_lists)
fig = tools.make_subplots(rows=1, cols=1, print_grid=False)
fig['layout'].update(
width=plot_width,
height=plot_height,
title=title,
)
i = 0
for y_idx, plot_list in enumerate(plot_lists):
for idx, plt in enumerate(plot_list):
color = core.color_defaults[i % len(core.color_defaults)]
i += 1
if use_median:
p25.append(np.mean(plt.percentile25))
p50.append(np.mean(plt.percentile50))
p75.append(np.mean(plt.percentile75))
x = list(range(len(plt.percentile50)))
y = list(plt.percentile50)
y_upper = list(plt.percentile75)
y_lower = list(plt.percentile25)
else:
x = list(range(len(plt.means)))
y = list(plt.means)
y_upper = list(plt.means + plt.stds)
y_lower = list(plt.means - plt.stds)
errors = go.Scatter(
x=x + x[::-1],
y=y_upper + y_lower[::-1],
fill='tozerox',
fillcolor=core.hex_to_rgb(color, 0.2),
line=go.Line(color=core.hex_to_rgb(color, 0)),
showlegend=False,
legendgroup=plt.legend,
hoverinfo='none'
)
values = go.Scatter(
x=x,
y=y,
name=plt.plot_key,
legendgroup=plt.legend,
line=dict(color=core.hex_to_rgb(color)),
)
# plotly is 1-indexed like matplotlib for subplots
y_idx_plotly = 1
fig.append_trace(values, y_idx_plotly, 1)
fig.append_trace(errors, y_idx_plotly, 1)
fig['layout']['yaxis{}'.format(y_idx_plotly)].update(
title=plt.plot_key,
)
fig_div = po.plot(fig, output_type='div', include_plotlyjs=False)
if "footnote" in plot_list[0]:
footnote = "<br />".join([
r"<span><b>%s</b></span>: <span>%s</span>" % (
plt.legend, plt.footnote)
for plt in plot_list
])
return r"%s<div>%s</div>" % (fig_div, footnote)
else:
return fig_div
