lisa.analysis.latency.LatencyAnalysis#

class lisa.analysis.latency.LatencyAnalysis(trace, proxy=None)[source]#

Bases: TraceAnalysisBase

Support for plotting Latency Analysis data

Parameters:

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

Attributes

LATENCY_THRESHOLD_COLOR

LATENCY_THRESHOLD_ZONE_COLOR

name

Name of the analysis class.

Properties

logger inherited

Convenience short-hand for self.get_logger().

Methods

df_activations()

DataFrame of a task’s activations.

df_latency_preemption()

DataFrame of a task’s preemption latencies.

df_latency_wakeup()

DataFrame of a task’s wakeup latencies.

df_runtimes()

DataFrame of task’s runtime each time the task blocks.

plot_activations()

Plot the df_activations() of a task.

plot_latencies()

Plot the latencies of a task over time.

plot_latencies_cdf()

Plot the latencies Cumulative Distribution Function of a task.

plot_latencies_histogram()

Plot the latencies histogram of a task.

plot_latency_bands()

Draw the task wakeup/preemption latencies as colored bands.

plot_runtimes()

Plot the lisa.analysis.latency.LatencyAnalysis.df_runtimes() of a task.

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#

LatencyAnalysis.LATENCY_THRESHOLD_COLOR = '#f781bf'#
LatencyAnalysis.LATENCY_THRESHOLD_ZONE_COLOR = '#4daf4a'#
LatencyAnalysis.name = 'latency'#

Name of the analysis class.

Properties#

property LatencyAnalysis.logger#

Inherited property, see lisa.utils.Loggable.logger

Convenience short-hand for self.get_logger().

Methods#

LatencyAnalysis.df_activations(task, *, df_fmt=None)[source]#

Called on Trace instances as trace.ana.latency.df_activations()

DataFrame of a task’s activations

Parameters:

task (int or str or tuple(int, str)) – The task’s name or PID

Returns:

a pandas.DataFrame with:

  • An activation_interval column (the time since the last activation).

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:

  • sched_switch

  • sched_wakeup

  • one group of: task_rename

  • optional: sched_wakeup_new

LatencyAnalysis.df_latency_preemption(task, *, df_fmt=None)[source]#

Called on Trace instances as trace.ana.latency.df_latency_preemption()

DataFrame of a task’s preemption latencies

Parameters:

task (int or str or tuple(int, str)) – The task’s name or PID

Returns:

a pandas.DataFrame with:

  • A preempt_latency column (the preemption latency at that timestamp)

  • A cpu column (the CPU where the event took place)

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:

  • sched_switch

  • sched_wakeup

  • one group of: task_rename

  • optional: sched_wakeup_new

LatencyAnalysis.df_latency_wakeup(task, *, df_fmt=None)[source]#

Called on Trace instances as trace.ana.latency.df_latency_wakeup()

DataFrame of a task’s wakeup latencies

Parameters:

task (int or str or tuple(int, str)) – The task’s name or PID

Returns:

a pandas.DataFrame with:

  • A wakeup_latency column (the wakeup latency at that timestamp)

  • A cpu column (the CPU where the event took place)

  • A target_cpu column (the CPU where the task has been scheduled)

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:

  • sched_switch

  • sched_wakeup

  • one group of: task_rename

  • optional: sched_wakeup_new

LatencyAnalysis.df_runtimes(task, *, df_fmt=None)[source]#

Called on Trace instances as trace.ana.latency.df_runtimes()

DataFrame of task’s runtime each time the task blocks

Parameters:

task (int or str or tuple(int, str)) – The task’s name or PID

Returns:

a pandas.DataFrame with:

  • The times where the task stopped running as an index

  • A curr_state column (the current task state, see lisa.analysis.tasks.TaskState)

  • A running_time column (the cumulated running time since the last activation).

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:

  • sched_switch

  • sched_wakeup

  • one group of: task_rename

  • optional: sched_wakeup_new

LatencyAnalysis.plot_activations(task: TaskID, *, 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]#

task=big_0-0

Called on Trace instances as trace.ana.latency.plot_activations()

Plot the df_activations() of a task

Parameters:

task (int or str or tuple(int, str)) – The task’s name or PID

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:

  • sched_switch

  • sched_wakeup

  • one group of: task_rename

  • optional: sched_wakeup_new

LatencyAnalysis.plot_latencies(task: TaskID, wakeup: bool = True, preempt: bool = True, threshold_ms: float = 1, *, 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]#

preempt=True, task=big_0-0, threshold_ms=1, wakeup=True

Called on Trace instances as trace.ana.latency.plot_latencies()

Plot the latencies of a task over time

Parameters:

  • task (int or str or tuple(int, str)) – The task’s name or PID

  • wakeup (bool) – Whether to plot wakeup latencies

  • preempt (bool) – Whether to plot preemption latencies

  • threshold_ms (int or float) – The latency threshold to plot

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:

  • sched_switch

  • sched_wakeup

  • one group of: task_rename

  • optional: sched_wakeup_new

LatencyAnalysis.plot_latencies_cdf(task: TaskID, wakeup: bool = True, preempt: bool = True, threshold_ms: float = 1, *, 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]#

preempt=True, task=big_0-0, threshold_ms=1, wakeup=True

Called on Trace instances as trace.ana.latency.plot_latencies_cdf()

Plot the latencies Cumulative Distribution Function of a task

Parameters:

  • task (int or str or tuple(int, str)) – The task’s name or PID

  • wakeup (bool) – Whether to plot wakeup latencies

  • preempt (bool) – Whether to plot preemption latencies

  • threshold_ms (int or float) – The latency threshold to plot

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:

  • sched_switch

  • sched_wakeup

  • one group of: task_rename

  • optional: sched_wakeup_new

LatencyAnalysis.plot_latencies_histogram(task: TaskID, wakeup: bool = True, preempt: bool = True, threshold_ms: float = 1, bins: int = 64, *, 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]#

bins=64, preempt=True, task=big_0-0, threshold_ms=1, wakeup=True

Called on Trace instances as trace.ana.latency.plot_latencies_histogram()

Plot the latencies histogram of a task

Parameters:

  • task (int or str or tuple(int, str)) – The task’s name or PID

  • wakeup (bool) – Whether to plot wakeup latencies

  • preempt (bool) – Whether to plot preemption latencies

  • threshold_ms (int or float) – The latency threshold to plot

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:

  • sched_switch

  • sched_wakeup

  • one group of: task_rename

  • optional: sched_wakeup_new

LatencyAnalysis.plot_latency_bands(task: TaskID, *, 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]#

task=big_0-0

Called on Trace instances as trace.ana.latency.plot_latency_bands()

Draw the task wakeup/preemption latencies as colored bands

Parameters:

task (int or str or tuple(int, str)) – The task’s name or PID

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:

  • sched_switch

  • sched_wakeup

  • one group of: task_rename

  • optional: sched_wakeup_new

LatencyAnalysis.plot_runtimes(task: TaskID, *, 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]#

task=big_0-0

Called on Trace instances as trace.ana.latency.plot_runtimes()

Plot the lisa.analysis.latency.LatencyAnalysis.df_runtimes() of a task

Parameters:

task (int or str or tuple(int, str)) – The task’s name or PID

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:

  • sched_switch

  • sched_wakeup

  • one group of: task_rename

  • optional: sched_wakeup_new

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

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

Dataframe function decorator.

classmethod LatencyAnalysis.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 LatencyAnalysis.get_analysis_classes()#

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

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

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

classmethod LatencyAnalysis.get_logger(suffix=None)#

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

Provides a logging.Logger named after cls.

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

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

classmethod LatencyAnalysis.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 LatencyAnalysis.plot_method(f)#

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

Plot function decorator.

LatencyAnalysis.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.