lisa.analysis.thermal.ThermalAnalysis#

class lisa.analysis.thermal.ThermalAnalysis(trace, proxy=None)[source]#

Bases: TraceAnalysisBase

Support for plotting Thermal Analysis data

Parameters:

trace (lisa.trace.Trace) – input Trace object

Attributes

name

Name of the analysis class.

Properties

cpufreq_cdevs

Get cpufreq cooling devices that appear in the trace.

devfreq_cdevs

Get devfreq cooling devices that appear in the trace.

thermal_zones

Get thermal zone ids that appear in the trace.

logger inherited

Convenience short-hand for self.get_logger().

Methods

df_cpufreq_cooling_state()

Get cpufreq cooling device states.

df_devfreq_cooling_state()

Get devfreq cooling device states.

df_thermal_zones_temperature()

Get the temperature of the thermal zones.

plot_cpu_cooling_states()

Plot the state evolution of a cpufreq cooling device.

plot_dev_freq_cooling_states()

Plot the state evolution of a devfreq cooling device.

plot_thermal_zone_temperature()

Plot temperature of thermal zones (all by default).

cache() inherited

Decorator to enable caching of the output of dataframe getter function in the trace cache.

call_on_trace() inherited

Call a method of a subclass on a given trace.

df_method() inherited

Dataframe function decorator.

get_all_events() inherited

Returns the set of all events used by any of the methods.

get_analysis_classes() inherited

get_default_plot_path() inherited

Return the default path to use to save plots for the analysis.

get_df_methods() inherited

get_logger() inherited

Provides a logging.Logger named after cls.

get_plot_methods() inherited

log_locals() inherited

Debugging aid: log the local variables of the calling function.

plot_method() inherited

Plot function decorator.

save_plot() inherited

Save a holoviews element or matplotlib.figure.Figure as an image file.

Attributes#

ThermalAnalysis.name = 'thermal'#

Name of the analysis class.

Properties#

property ThermalAnalysis.cpufreq_cdevs[source]#

Get cpufreq cooling devices that appear in the trace

Required trace events:

  • thermal_power_cpu_limit

property ThermalAnalysis.devfreq_cdevs[source]#

Get devfreq cooling devices that appear in the trace

Required trace events:

  • thermal_power_devfreq_limit

property ThermalAnalysis.thermal_zones[source]#

Get thermal zone ids that appear in the trace

Required trace events:

  • thermal_temperature

property ThermalAnalysis.logger#

Inherited property, see lisa.utils.Loggable.logger

Convenience short-hand for self.get_logger().

Methods#

ThermalAnalysis.df_cpufreq_cooling_state(cpus=None, *, df_fmt=None)[source]#

Called on Trace instances as trace.ana.thermal.df_cpufreq_cooling_state()

Get cpufreq cooling device states

Parameters:

cpus (list(int)) – The CPUs to consider (all by default)

Returns:

a pandas.DataFrame with:

  • An cpus column (The CPUs affected by the cooling device)

  • A freq column (The frequency limit)

  • A cdev_state column (The cooling device state index)

Added by lisa.analysis.base.TraceAnalysisBase.df_method():

Parameters:

df_fmt (str or None) –

Format of dataframe to return. One of:

Returns:

The return type is determined by the dataframe format chosen for the trace object.

Required trace events:

  • thermal_power_cpu_limit

ThermalAnalysis.df_devfreq_cooling_state(devices=None, *, df_fmt=None)[source]#

Called on Trace instances as trace.ana.thermal.df_devfreq_cooling_state()

Get devfreq cooling device states

Parameters:

devices – The devfreq devices to consider (all by default)

Returns:

a pandas.DataFrame with:

  • An cpus column (The CPUs affected by the cooling device)

  • A freq column (The frequency limit)

  • A cdev_state column (The cooling device state index)

Added by lisa.analysis.base.TraceAnalysisBase.df_method():

Parameters:

df_fmt (str or None) –

Format of dataframe to return. One of:

Returns:

The return type is determined by the dataframe format chosen for the trace object.

Required trace events:

  • thermal_power_devfreq_limit

ThermalAnalysis.df_thermal_zones_temperature(*, df_fmt=None)[source]#

Called on Trace instances as trace.ana.thermal.df_thermal_zones_temperature()

Get the temperature of the thermal zones

Returns:

a pandas.DataFrame with:

  • An id column (The thermal zone ID)

  • A thermal_zone column (The thermal zone name)

  • A temp column (The reported temperature)

Added by lisa.analysis.base.TraceAnalysisBase.df_method():

Parameters:

df_fmt (str or None) –

Format of dataframe to return. One of:

Returns:

The return type is determined by the dataframe format chosen for the trace object.

Required trace events:

  • thermal_temperature

ThermalAnalysis.plot_cpu_cooling_states(cpu: CPU, *, filepath=None, output='holoviews', img_format=None, always_save=False, backend=None, _compat_render=False, link_dataframes=None, cursor_delta=None, width=None, height=None, rc_params=None, axis=None, interactive=None, colors: Sequence[str] = None, linestyles: Sequence[str] = None, markers: Sequence[str] = None, **kwargs)[source]#

Called on Trace instances as trace.ana.thermal.plot_cpu_cooling_states()

Plot the state evolution of a cpufreq cooling device

Parameters:

cpu (int) – The CPU. Whole clusters can be controlled as a single cooling device, they will be plotted as long this CPU belongs to the cluster.

Added by lisa.analysis.base.AnalysisHelpers.plot_method():

Returns:

The return type is determined by the output parameter.

Parameters:

  • backend (str or None) –

    Holoviews plot library backend to use:

    • bokeh: good support for interactive plots

    • matplotlib: sometimes better static image output, but unpredictable results that more often than not require a fair amount of hacks to get something good.

    • plotly: not supported by LISA but technically available. Since it’s very similar to bokeh feature-wise, bokeh should be preferred.

    Note

    In a notebook, the way to choose which backend should be used to display plots is typically selected with e.g. holoviews.extension('bokeh') at the beginning of the notebook. The backend parameter is more intended for expert use where an object of the given library is required, without depending on the environment.

  • link_dataframes (list(pandas.DataFrame) or None) – Gated by output="ui". List of dataframes to display under the figure, which is dynamically linked with it: clicking on the plot will scroll in the dataframes and vice versa.

  • filepath (str or None) – Path of the file to save the figure in. If None, no file is saved.

  • always_save (bool) – When True, the plot is always saved even if no filepath has explicitly been set. In that case, a default path will be used.

  • img_format (str) – The image format to generate. Defaults to using filepath to guess the type, or “png” if no filepath is given. html and rst are supported in addition to matplotlib image formats.

  • output (str or None) –

    Change the return value of the method:

    • None: Equivalent to holoviews for now. In the future, this will be either holoviews or ui if used in an interactive jupyter notebook.

    • holoviews: a bare holoviews element.

    • render: a backend-specific object, such as matplotlib.figure.Figure if backend='matplotlib'

    • html: HTML document

    • rst: a snippet of reStructuredText

    • ui: Pseudo holoviews figure, enriched with extra controls.

      Note

      No assumption must be made on the return type other than that it can be displayed in a notebook cell output (and with IPython.display.display()). The public API holoviews is implemented in a best-effort approach, so that .options() and .opts() will work, but compositions using e.g. x * y will not work if x is a holoviews element.

      In the midterm, the output type will be changed so that it is a real holoviews object, rather than some sort of proxy.

  • colors (list(str) or None) –

    List of color names to use for the plots.

    Deprecated since version 2.0: This parameter is deprecated, use holoviews APIs to set matplotlib options.

  • linestyles (list(str) or None) –

    List of linestyle to use for the plots.

    Deprecated since version 2.0: This parameter is deprecated, use holoviews APIs to set matplotlib options.

  • markers (list(str) or None) –

    List of marker to use for the plots.

    Deprecated since version 2.0: This parameter is deprecated, use holoviews APIs to set matplotlib options.

  • axis (matplotlib.axes.Axes or numpy.ndarray(matplotlib.axes.Axes) or None) –

    instance of matplotlib.axes.Axes to plot into. If None, a new figure and axis are created and returned.

    Deprecated since version 2.0: This parameter is deprecated, use holoviews APIs to compose plot elements: http://holoviews.org/user_guide/Composing_Elements.html

  • rc_params (dict(str, object) or None) –

    Matplotlib rc params dictionary overlaid on existing settings.

    Deprecated since version 2.0: This parameter is deprecated, use holoviews APIs to set matplotlib options.

  • _compat_render (bool) – Internal parameter not to be used. This enables the compatibility mode where render=True by default when matplotlib is the current holoviews backend.

Required trace events:

  • thermal_power_cpu_limit

ThermalAnalysis.plot_dev_freq_cooling_states(device: str, *, filepath=None, output='holoviews', img_format=None, always_save=False, backend=None, _compat_render=False, link_dataframes=None, cursor_delta=None, width=None, height=None, rc_params=None, axis=None, interactive=None, colors: Sequence[str] = None, linestyles: Sequence[str] = None, markers: Sequence[str] = None, **kwargs)[source]#

Called on Trace instances as trace.ana.thermal.plot_dev_freq_cooling_states()

Plot the state evolution of a devfreq cooling device

Parameters:

device (str) – The devfreq devices to consider

Added by lisa.analysis.base.AnalysisHelpers.plot_method():

Returns:

The return type is determined by the output parameter.

Parameters:

  • backend (str or None) –

    Holoviews plot library backend to use:

    • bokeh: good support for interactive plots

    • matplotlib: sometimes better static image output, but unpredictable results that more often than not require a fair amount of hacks to get something good.

    • plotly: not supported by LISA but technically available. Since it’s very similar to bokeh feature-wise, bokeh should be preferred.

    Note

    In a notebook, the way to choose which backend should be used to display plots is typically selected with e.g. holoviews.extension('bokeh') at the beginning of the notebook. The backend parameter is more intended for expert use where an object of the given library is required, without depending on the environment.

  • link_dataframes (list(pandas.DataFrame) or None) – Gated by output="ui". List of dataframes to display under the figure, which is dynamically linked with it: clicking on the plot will scroll in the dataframes and vice versa.

  • filepath (str or None) – Path of the file to save the figure in. If None, no file is saved.

  • always_save (bool) – When True, the plot is always saved even if no filepath has explicitly been set. In that case, a default path will be used.

  • img_format (str) – The image format to generate. Defaults to using filepath to guess the type, or “png” if no filepath is given. html and rst are supported in addition to matplotlib image formats.

  • output (str or None) –

    Change the return value of the method:

    • None: Equivalent to holoviews for now. In the future, this will be either holoviews or ui if used in an interactive jupyter notebook.

    • holoviews: a bare holoviews element.

    • render: a backend-specific object, such as matplotlib.figure.Figure if backend='matplotlib'

    • html: HTML document

    • rst: a snippet of reStructuredText

    • ui: Pseudo holoviews figure, enriched with extra controls.

      Note

      No assumption must be made on the return type other than that it can be displayed in a notebook cell output (and with IPython.display.display()). The public API holoviews is implemented in a best-effort approach, so that .options() and .opts() will work, but compositions using e.g. x * y will not work if x is a holoviews element.

      In the midterm, the output type will be changed so that it is a real holoviews object, rather than some sort of proxy.

  • colors (list(str) or None) –

    List of color names to use for the plots.

    Deprecated since version 2.0: This parameter is deprecated, use holoviews APIs to set matplotlib options.

  • linestyles (list(str) or None) –

    List of linestyle to use for the plots.

    Deprecated since version 2.0: This parameter is deprecated, use holoviews APIs to set matplotlib options.

  • markers (list(str) or None) –

    List of marker to use for the plots.

    Deprecated since version 2.0: This parameter is deprecated, use holoviews APIs to set matplotlib options.

  • axis (matplotlib.axes.Axes or numpy.ndarray(matplotlib.axes.Axes) or None) –

    instance of matplotlib.axes.Axes to plot into. If None, a new figure and axis are created and returned.

    Deprecated since version 2.0: This parameter is deprecated, use holoviews APIs to compose plot elements: http://holoviews.org/user_guide/Composing_Elements.html

  • rc_params (dict(str, object) or None) –

    Matplotlib rc params dictionary overlaid on existing settings.

    Deprecated since version 2.0: This parameter is deprecated, use holoviews APIs to set matplotlib options.

  • _compat_render (bool) – Internal parameter not to be used. This enables the compatibility mode where render=True by default when matplotlib is the current holoviews backend.

ThermalAnalysis.plot_thermal_zone_temperature(thermal_zone_id: int, *, filepath=None, output='holoviews', img_format=None, always_save=False, backend=None, _compat_render=False, link_dataframes=None, cursor_delta=None, width=None, height=None, rc_params=None, axis=None, interactive=None, colors: Sequence[str] = None, linestyles: Sequence[str] = None, markers: Sequence[str] = None, **kwargs)[source]#

Called on Trace instances as trace.ana.thermal.plot_thermal_zone_temperature()

Plot temperature of thermal zones (all by default)

Parameters:

thermal_zone_id (int) – ID of the zone

Added by lisa.analysis.base.AnalysisHelpers.plot_method():

Returns:

The return type is determined by the output parameter.

Parameters:

  • backend (str or None) –

    Holoviews plot library backend to use:

    • bokeh: good support for interactive plots

    • matplotlib: sometimes better static image output, but unpredictable results that more often than not require a fair amount of hacks to get something good.

    • plotly: not supported by LISA but technically available. Since it’s very similar to bokeh feature-wise, bokeh should be preferred.

    Note

    In a notebook, the way to choose which backend should be used to display plots is typically selected with e.g. holoviews.extension('bokeh') at the beginning of the notebook. The backend parameter is more intended for expert use where an object of the given library is required, without depending on the environment.

  • link_dataframes (list(pandas.DataFrame) or None) – Gated by output="ui". List of dataframes to display under the figure, which is dynamically linked with it: clicking on the plot will scroll in the dataframes and vice versa.

  • filepath (str or None) – Path of the file to save the figure in. If None, no file is saved.

  • always_save (bool) – When True, the plot is always saved even if no filepath has explicitly been set. In that case, a default path will be used.

  • img_format (str) – The image format to generate. Defaults to using filepath to guess the type, or “png” if no filepath is given. html and rst are supported in addition to matplotlib image formats.

  • output (str or None) –

    Change the return value of the method:

    • None: Equivalent to holoviews for now. In the future, this will be either holoviews or ui if used in an interactive jupyter notebook.

    • holoviews: a bare holoviews element.

    • render: a backend-specific object, such as matplotlib.figure.Figure if backend='matplotlib'

    • html: HTML document

    • rst: a snippet of reStructuredText

    • ui: Pseudo holoviews figure, enriched with extra controls.

      Note

      No assumption must be made on the return type other than that it can be displayed in a notebook cell output (and with IPython.display.display()). The public API holoviews is implemented in a best-effort approach, so that .options() and .opts() will work, but compositions using e.g. x * y will not work if x is a holoviews element.

      In the midterm, the output type will be changed so that it is a real holoviews object, rather than some sort of proxy.

  • colors (list(str) or None) –

    List of color names to use for the plots.

    Deprecated since version 2.0: This parameter is deprecated, use holoviews APIs to set matplotlib options.

  • linestyles (list(str) or None) –

    List of linestyle to use for the plots.

    Deprecated since version 2.0: This parameter is deprecated, use holoviews APIs to set matplotlib options.

  • markers (list(str) or None) –

    List of marker to use for the plots.

    Deprecated since version 2.0: This parameter is deprecated, use holoviews APIs to set matplotlib options.

  • axis (matplotlib.axes.Axes or numpy.ndarray(matplotlib.axes.Axes) or None) –

    instance of matplotlib.axes.Axes to plot into. If None, a new figure and axis are created and returned.

    Deprecated since version 2.0: This parameter is deprecated, use holoviews APIs to compose plot elements: http://holoviews.org/user_guide/Composing_Elements.html

  • rc_params (dict(str, object) or None) –

    Matplotlib rc params dictionary overlaid on existing settings.

    Deprecated since version 2.0: This parameter is deprecated, use holoviews APIs to set matplotlib options.

  • _compat_render (bool) – Internal parameter not to be used. This enables the compatibility mode where render=True by default when matplotlib is the current holoviews backend.

Required trace events:

  • thermal_temperature

classmethod ThermalAnalysis.cache(f, fmt='parquet', ignored_params=None)#

Inherited method, see lisa.analysis.base.TraceAnalysisBase.cache()

Decorator to enable caching of the output of dataframe getter function in the trace cache.

classmethod ThermalAnalysis.call_on_trace(meth, trace, meth_kwargs)#

Inherited method, see lisa.analysis.base.TraceAnalysisBase.call_on_trace()

Call a method of a subclass on a given trace.

classmethod ThermalAnalysis.df_method(f, index=None)#

Inherited method, see lisa.analysis.base.TraceAnalysisBase.df_method()

Dataframe function decorator.

classmethod ThermalAnalysis.get_all_events()#

Inherited method, see lisa.analysis.base.TraceAnalysisBase.get_all_events()

Returns the set of all events used by any of the methods.

classmethod ThermalAnalysis.get_analysis_classes()#

Inherited method, see lisa.analysis.base.TraceAnalysisBase.get_analysis_classes()

ThermalAnalysis.get_default_plot_path(**kwargs)#

Inherited method, see lisa.analysis.base.TraceAnalysisBase.get_default_plot_path()

Return the default path to use to save plots for the analysis.

classmethod ThermalAnalysis.get_df_methods(*args, **kwargs)#

Inherited method, see lisa.analysis.base.TraceAnalysisBase.get_df_methods()

classmethod ThermalAnalysis.get_logger(suffix=None)#

Inherited method, see lisa.utils.Loggable.get_logger()

Provides a logging.Logger named after cls.

classmethod ThermalAnalysis.get_plot_methods(*args, **kwargs)#

Inherited method, see lisa.analysis.base.AnalysisHelpers.get_plot_methods()

classmethod ThermalAnalysis.log_locals(var_names=None, level='debug')#

Inherited method, see lisa.utils.Loggable.log_locals()

Debugging aid: log the local variables of the calling function.

classmethod ThermalAnalysis.plot_method(f)#

Inherited method, see lisa.analysis.base.AnalysisHelpers.plot_method()

Plot function decorator.

ThermalAnalysis.save_plot(figure, filepath=None, img_format=None, backend=None)#

Inherited method, see lisa.analysis.base.AnalysisHelpers.save_plot()

Save a holoviews element or matplotlib.figure.Figure as an image file.