cr2/thermal.py

#!/usr/bin/python
"""Process the output of the power allocator trace in the current
directory's trace.dat"""

import os
import re
from matplotlib import pyplot as plt

from base import Base
from plot_utils import normalize_title, pre_plot_setup, post_plot_setup, plot_hist

class Thermal(Base):
    """Process the thermal framework data in a ftrace dump"""
    def __init__(self, path=None):
        super(Thermal, self).__init__(
            basepath=path,
            unique_word="thermal_temperature:",
        )

    def plot_temperature(self, control_temperature=None, title="", width=None,
                         height=None, ylim="range", ax=None, legend_label=""):
        """Plot the temperature.

        If control_temp is a pd.Series() representing the (possible)
        variation of control_temp during the run, draw it using a
        dashed yellow line.  Otherwise, only the temperature is
        plotted.

        """
        title = normalize_title("Temperature", title)

        setup_plot = False
        if not ax:
            ax = pre_plot_setup(width, height)
            setup_plot = True

        temp_label = normalize_title("Temperature", legend_label)
        (self.data_frame["temp"] / 1000).plot(ax=ax, label=temp_label)
        if control_temperature is not None:
            ct_label = normalize_title("Control", legend_label)
            control_temperature.plot(ax=ax, color="y", linestyle="--",
                           label=ct_label)

        if setup_plot:
            post_plot_setup(ax, title=title, ylim=ylim)
            plt.legend()

    def plot_temperature_hist(self, ax, title):
        """Plot a temperature histogram"""

        temps = self.data_frame["temp"] / 1000
        title = normalize_title("Temperature", title)
        xlim = (0, temps.max())

        plot_hist(temps, ax, title, 30, "Temperature", xlim, "default")

class ThermalGovernor(Base):
    """Process the power allocator data in a ftrace dump"""
    def __init__(self, path=None):
        super(ThermalGovernor, self).__init__(
            basepath=path,
            unique_word="thermal_power_allocator:",
        )

    def plot_input_power(self, actor_order, title="", width=None, height=None, ax=None):
        """Plot input power

        actor_order is an array with the order in which the actors were registered.
        """

        dfr = self.data_frame
        in_cols = [s for s in dfr.columns if re.match("req_power[0-9]+", s)]

        plot_dfr = dfr[in_cols]
        # Rename the columns from "req_power0" to "A15" or whatever is
        # in actor_order.  Note that we can do it just with an
        # assignment because the columns are already sorted (i.e.:
        # req_power0, req_power1...)
        plot_dfr.columns = actor_order

        title = normalize_title("Input Power", title)

        if not ax:
            ax = pre_plot_setup(width, height)

        plot_dfr.plot(ax=ax)
        post_plot_setup(ax, title=title)

    def plot_output_power(self, actor_order, title="", width=None, height=None, ax=None):
        """Plot output power

        actor_order is an array with the order in which the actors were registered.
        """

        out_cols = [s for s in self.data_frame.columns
                    if re.match("granted_power[0-9]+", s)]

        # See the note in plot_input_power()
        plot_dfr = self.data_frame[out_cols]
        plot_dfr.columns = actor_order

        title = normalize_title("Output Power", title)

        if not ax:
            ax = pre_plot_setup(width, height)

        plot_dfr.plot(ax=ax)
        post_plot_setup(ax, title=title)

    def plot_inout_power(self, title="", width=None, height=None):
        """Make multiple plots showing input and output power for each actor"""
        dfr = self.data_frame

        actors = []
        for col in dfr.columns:
                match = re.match("P(.*)_in", col)
                if match and col != "Ptot_in":
                    actors.append(match.group(1))

        for actor in actors:
            cols = ["P" + actor + "_in", "P" + actor + "_out"]
            this_title = normalize_title(actor, title)
            dfr[cols].plot(title=this_title)