lisa.analysis.pixel6.Pixel6Analysis#

Attributes#

Pixel6Analysis.EMETER_CHAN_NAMES = {'S2M_VDD_CPUCL2': 'CPU-Big', 'S2S_VDD_G3D': 'GPU', 'S3M_VDD_CPUCL1': 'CPU-Mid', 'S4M_VDD_CPUCL0': 'CPU-Little'}#

Pixel6Analysis.name = 'pixel6'#

Name of the analysis class.

Properties#

property Pixel6Analysis.logger#

Inherited property, see lisa.utils.Loggable.logger

Convenience short-hand for self.get_logger().

Methods#

Pixel6Analysis.df_power_meter(*, df_fmt=None)#

Called on Trace instances as trace.ana.pixel6.df_power_meter()

Get the power meter readings across the trace.

Returns:

A pandas.DataFrame with:

• A channel column (name of the power meter channel)

• A power column (average power usage in mW since the last measurement)

• A energy column (energy samples in mJ provided by the PMIC)

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

Parameters:

df_fmt (str or None) –

Format of dataframe to return. One of:

• "pandas": pandas.DataFrame

• "polars-lazyframe": polars.LazyFrame

Returns:

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

Required trace events:

• pixel6_emeter

Pixel6Analysis.plot_power_meter(channels: List[str] | None = None, metrics: List[str] | None = None, *, 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)#

metrics=['energy', 'power']

Called on Trace instances as trace.ana.pixel6.plot_power_meter()

Plot the power meter readings from various channels.

Parameters:

• channels (list(str)) – List of channels to plot

• metrics (list(str)) – List of metrics to plot. Can be: * "power": plot the power (mW) * "energy": plot the energy (mJ)

The channels needs to correspond to values in the channel column of df_power_meter().

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:

• pixel6_emeter

classmethod Pixel6Analysis.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 Pixel6Analysis.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 Pixel6Analysis.df_method(f, index=None)#

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

Dataframe function decorator.

classmethod Pixel6Analysis.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 Pixel6Analysis.get_analysis_classes()#

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

Pixel6Analysis.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 Pixel6Analysis.get_df_methods(*args, **kwargs)#

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

classmethod Pixel6Analysis.get_logger(suffix=None)#

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

Provides a logging.Logger named after cls.

classmethod Pixel6Analysis.get_plot_methods(*args, **kwargs)#

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

classmethod Pixel6Analysis.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 Pixel6Analysis.plot_method(f)#

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

Plot function decorator.

Pixel6Analysis.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.