blob: e224b411d7219237ffc6b899559095029e2e635e [file] [log] [blame]
#!/usr/bin/python
"""Small functions to help with plots"""
from matplotlib import pyplot as plt
GOLDEN_RATIO = 1.618034
def normalize_title(title, opt_title):
"""
Return a string with that contains the title and opt_title if it's not the empty string
See test_normalize_title() for usage
"""
if opt_title is not "":
title = opt_title + " - " + title
return title
def set_lim(lim, get_lim, set_lim):
"""Set x or y limitis of the plot
lim can be a tuple containing the limits or the string "default"
or "range". "default" does nothing and uses matplotlib default.
"range" extends the current margin by 10%. This is useful since
the default xlim and ylim of the plots sometimes make it harder to
see data that is just in the margin.
"""
if lim == "default":
return
if lim == "range":
cur_lim = get_lim()
lim = (cur_lim[0] - 0.1 * (cur_lim[1] - cur_lim[0]),
cur_lim[1] + 0.1 * (cur_lim[1] - cur_lim[0]))
set_lim(lim[0], lim[1])
def set_xlim(ax, xlim):
"""Set the xlim of the plot
See set_lim() for the details
"""
set_lim(xlim, ax.get_xlim, ax.set_xlim)
def set_ylim(ax, ylim):
"""Set the ylim of the plot
See set_lim() for the details
"""
set_lim(ylim, ax.get_ylim, ax.set_ylim)
def pre_plot_setup(width=None, height=None, ncols=1):
"""initialize a figure
width and height are numbers. This function should be called
before any calls to plot()
"""
if height is None:
if width is None:
height = 6
width = 10
else:
height = width / GOLDEN_RATIO
else:
if width is None:
width = height * GOLDEN_RATIO
_, axis = plt.subplots(ncols=ncols, figsize=(width, height))
return axis
def post_plot_setup(ax, title="", xlabel=None, xlim="default", ylim="range"):
"""Set xlabel, title, xlim adn ylim of the plot
This has to be called after calls to .plot(). The default ylim is
to extend it by 10% because matplotlib default makes it hard
values that are close to the margins
"""
if xlabel is not None:
plt.xlabel(xlabel)
if title:
ax.set_title(title)
set_ylim(ax, ylim)
set_xlim(ax, xlim)
def plot_temperature(runs, width=None, height=None, ylim="range"):
"""Plot temperatures
runs is an array of Run() instances. Extract the control_temp
from the governor data and plot the temperatures reported by the
thermal framework. The governor doesn't track temperature when
it's off, so the thermal framework trace is more reliable.
"""
ax = pre_plot_setup(width, height)
for run in runs:
current_temp = run.thermal_governor.data_frame["current_temperature"]
delta_temp = run.thermal_governor.data_frame["delta_temperature"]
control_temp_series = (current_temp + delta_temp) / 1000
run.thermal.plot_temperature(control_temperature=control_temp_series,
ax=ax, legend_label=run.name)
post_plot_setup(ax, title="Temperature", ylim=ylim)
plt.legend(loc="best")
def plot_hist(data, title, bins, xlabel, xlim, ylim):
"""Plot a histogram"""
mean = data.mean()
std = data.std()
title += " (mean = {:.2f}, std = {:.2f})".format(mean, std)
ax = pre_plot_setup()
data.hist(ax=ax, bins=bins)
post_plot_setup(ax, title=title, xlabel=xlabel, xlim=xlim, ylim=ylim)
def plot_load(runs, map_label, width=None, height=None):
"""Make a multiplot of all the loads"""
axis = pre_plot_setup(width=width, height=height, ncols=len(runs))
for ax, run in zip(axis, runs):
run.in_power.plot_load(map_label, ax=ax)
title = normalize_title("Utilisation", run.name)
post_plot_setup(ax, title=title)