cr2/plot_utils.py - platform/external/trappy - Gitiles

 #!/usr/bin/python
 # $Copyright:
 # ----------------------------------------------------------------
 # This confidential and proprietary software may be used only as
 # authorised by a licensing agreement from ARM Limited
 #  (C) COPYRIGHT 2015 ARM Limited
 #       ALL RIGHTS RESERVED
 # The entire notice above must be reproduced on all authorised
 # copies and copies may only be made to the extent permitted
 # by a licensing agreement from ARM Limited.
 # ----------------------------------------------------------------
 # File:        plot_utils.py
 # ----------------------------------------------------------------
 # $
 #
 """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, nrows=1):
     """initialize a figure

     width and height are the height and width of each row of plots.
     For 1x1 plots, that's the height and width of the plot.  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

     height *= nrows

     _, axis = plt.subplots(ncols=ncols, nrows=nrows, figsize=(width, height))

     # Needed for multirow blots to not overlap with each other
     plt.tight_layout(h_pad=3.5)

     return axis

 def post_plot_setup(ax, title="", xlabel=None, ylabel=None, xlim="default",
                     ylim="range"):
     """Set xlabel, ylabel title, xlim and 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:
         ax.set_xlabel(xlabel)

     if ylabel is not None:
         ax.set_ylabel(ylabel)

     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_series = (current_temp + delta_temp) / 1000

         try:
             run.thermal.plot_temperature(control_temperature=control_series,
                                          ax=ax, legend_label=run.name)
         except ValueError:
             run.thermal_governor.plot_temperature(ax=ax, legend_label=run.name)

     post_plot_setup(ax, title="Temperature", ylim=ylim)
     plt.legend(loc="best")

 def plot_hist(data, ax, title, bins, xlabel, xlim, ylim):
     """Plot a histogram"""

     mean = data.mean()
     std = data.std()
     title += " (mean = {:.2f}, std = {:.2f})".format(mean, std)

     data.hist(ax=ax, bins=bins)
     post_plot_setup(ax, title=title, xlabel=xlabel, ylabel="count", xlim=xlim,
                     ylim=ylim)

 def plot_load(runs, map_label, width=None, height=None):
     """Make a multiplot of all the loads"""
     num_runs = len(runs)
     axis = pre_plot_setup(width=width, height=height, ncols=num_runs)

     if num_runs == 1:
         axis = [axis]

     for ax, run in zip(axis, runs):
         run.plot_load(map_label, title=run.name, ax=ax)

 def plot_allfreqs(runs, map_label, width=None, height=None):
     """Make a multicolumn plots of the allfreqs plots of each run"""
     num_runs = len(runs)
     axis = pre_plot_setup(width=width, height=height, nrows=len(map_label),
                           ncols=num_runs)

     if num_runs == 1:
         axis = [axis]
     else:
         axis = zip(*axis)

     for ax, run in zip(axis, runs):
         run.plot_allfreqs(map_label, ax=ax)

 def plot_controller(runs, width=None, height=None):
     """Make a multicolumn plot of the pid controller of each run"""
     num_runs = len(runs)
     axis = pre_plot_setup(width=width, height=height, ncols=num_runs)

     if num_runs == 1:
         axis = [axis]

     for ax, run in zip(axis, runs):
         run.pid_controller.plot_controller(title=run.name, ax=ax)

 def plot_input_power(runs, actor_order, width=None, height=None):
     """Make a multicolumn plot of the input power of each run"""
     num_runs = len(runs)
     axis = pre_plot_setup(width=width, height=height, ncols=num_runs)

     if num_runs == 1:
         axis = [axis]

     for ax, run in zip(axis, runs):
         run.thermal_governor.plot_input_power(actor_order, title=run.name, ax=ax)

 def plot_output_power(runs, actor_order, width=None, height=None):
     """Make a multicolumn plot of the output power of each run"""
     num_runs = len(runs)
     axis = pre_plot_setup(width=width, height=height, ncols=num_runs)

     if num_runs == 1:
         axis = [axis]

     for ax, run in zip(axis, runs):
         run.thermal_governor.plot_output_power(actor_order, title=run.name, ax=ax)

 def plot_freq_hists(runs, map_label):
     """Plot frequency histograms of multiple runs"""
     num_runs = len(runs)
     nrows = 2 * len(map_label)
     axis = pre_plot_setup(ncols=num_runs, nrows=nrows)

     if num_runs == 1:
         axis = [axis]
     else:
         axis = zip(*axis)

     for ax, run in zip(axis, runs):
         run.plot_freq_hists(map_label, ax=ax)

 def plot_temperature_hist(runs):
     """Plot temperature histograms for all the runs"""
     num_runs = 0
     for run in runs:
         if len(run.thermal.data_frame):
             num_runs += 1

     if num_runs == 0:
         return

     axis = pre_plot_setup(ncols=num_runs)

     if num_runs == 1:
         axis = [axis]

     for ax, run in zip(axis, runs):
         run.thermal.plot_temperature_hist(ax, run.name)
	#!/usr/bin/python
	# $Copyright:
	# ----------------------------------------------------------------
	# This confidential and proprietary software may be used only as
	# authorised by a licensing agreement from ARM Limited
	# (C) COPYRIGHT 2015 ARM Limited
	# ALL RIGHTS RESERVED
	# The entire notice above must be reproduced on all authorised
	# copies and copies may only be made to the extent permitted
	# by a licensing agreement from ARM Limited.
	# ----------------------------------------------------------------
	# File: plot_utils.py
	# ----------------------------------------------------------------
	# $
	#
	"""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, nrows=1):
	"""initialize a figure

	width and height are the height and width of each row of plots.
	For 1x1 plots, that's the height and width of the plot. 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

	height *= nrows

	_, axis = plt.subplots(ncols=ncols, nrows=nrows, figsize=(width, height))

	# Needed for multirow blots to not overlap with each other
	plt.tight_layout(h_pad=3.5)

	return axis

	def post_plot_setup(ax, title="", xlabel=None, ylabel=None, xlim="default",
	ylim="range"):
	"""Set xlabel, ylabel title, xlim and 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:
	ax.set_xlabel(xlabel)

	if ylabel is not None:
	ax.set_ylabel(ylabel)

	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_series = (current_temp + delta_temp) / 1000

	try:
	run.thermal.plot_temperature(control_temperature=control_series,
	ax=ax, legend_label=run.name)
	except ValueError:
	run.thermal_governor.plot_temperature(ax=ax, legend_label=run.name)

	post_plot_setup(ax, title="Temperature", ylim=ylim)
	plt.legend(loc="best")

	def plot_hist(data, ax, title, bins, xlabel, xlim, ylim):
	"""Plot a histogram"""

	mean = data.mean()
	std = data.std()
	title += " (mean = {:.2f}, std = {:.2f})".format(mean, std)

	data.hist(ax=ax, bins=bins)
	post_plot_setup(ax, title=title, xlabel=xlabel, ylabel="count", xlim=xlim,
	ylim=ylim)

	def plot_load(runs, map_label, width=None, height=None):
	"""Make a multiplot of all the loads"""
	num_runs = len(runs)
	axis = pre_plot_setup(width=width, height=height, ncols=num_runs)

	if num_runs == 1:
	axis = [axis]

	for ax, run in zip(axis, runs):
	run.plot_load(map_label, title=run.name, ax=ax)

	def plot_allfreqs(runs, map_label, width=None, height=None):
	"""Make a multicolumn plots of the allfreqs plots of each run"""
	num_runs = len(runs)
	axis = pre_plot_setup(width=width, height=height, nrows=len(map_label),
	ncols=num_runs)

	if num_runs == 1:
	axis = [axis]
	else:
	axis = zip(*axis)

	for ax, run in zip(axis, runs):
	run.plot_allfreqs(map_label, ax=ax)

	def plot_controller(runs, width=None, height=None):
	"""Make a multicolumn plot of the pid controller of each run"""
	num_runs = len(runs)
	axis = pre_plot_setup(width=width, height=height, ncols=num_runs)

	if num_runs == 1:
	axis = [axis]

	for ax, run in zip(axis, runs):
	run.pid_controller.plot_controller(title=run.name, ax=ax)

	def plot_input_power(runs, actor_order, width=None, height=None):
	"""Make a multicolumn plot of the input power of each run"""
	num_runs = len(runs)
	axis = pre_plot_setup(width=width, height=height, ncols=num_runs)

	if num_runs == 1:
	axis = [axis]

	for ax, run in zip(axis, runs):
	run.thermal_governor.plot_input_power(actor_order, title=run.name, ax=ax)

	def plot_output_power(runs, actor_order, width=None, height=None):
	"""Make a multicolumn plot of the output power of each run"""
	num_runs = len(runs)
	axis = pre_plot_setup(width=width, height=height, ncols=num_runs)

	if num_runs == 1:
	axis = [axis]

	for ax, run in zip(axis, runs):
	run.thermal_governor.plot_output_power(actor_order, title=run.name, ax=ax)

	def plot_freq_hists(runs, map_label):
	"""Plot frequency histograms of multiple runs"""
	num_runs = len(runs)
	nrows = 2 * len(map_label)
	axis = pre_plot_setup(ncols=num_runs, nrows=nrows)

	if num_runs == 1:
	axis = [axis]
	else:
	axis = zip(*axis)

	for ax, run in zip(axis, runs):
	run.plot_freq_hists(map_label, ax=ax)

	def plot_temperature_hist(runs):
	"""Plot temperature histograms for all the runs"""
	num_runs = 0
	for run in runs:
	if len(run.thermal.data_frame):
	num_runs += 1

	if num_runs == 0:
	return

	axis = pre_plot_setup(ncols=num_runs)

	if num_runs == 1:
	axis = [axis]

	for ax, run in zip(axis, runs):
	run.thermal.plot_temperature_hist(ax, run.name)