lisa.analysis.notebook.NotebookAnalysis#
- class lisa.analysis.notebook.NotebookAnalysis(*args, **kwargs)[source]#
Bases:
TraceAnalysisBaseSupport for custom Notebook-defined plots
This analysis provides a proxy object that can be used to turn any plot method defined in a notebook into a proper analysis plot method:
import holoviews as hv from lisa.trace import Trace trace = Trace('trace.dat', events=['sched_switch']) # Define a plot method in any cell: # The first parameter will be the trace, other parameters are free-form def plot_foo(trace, y): print(f'Plotting horizontal line at level: {y}') return hv.HLine(y).options(color='red') # The plot function becomes available on the "notebook.custom" proxy # object. trace.ana.notebook.custom.plot_foo(0.5)
Attributes
Name of the analysis class.
Properties
loggerinheritedConvenience short-hand for
self.get_logger().Methods
Provide a dataframe with an
infocolumn containing the textual human-readable representation of the events fields.Plot a signal represented by the filtered values of a field of an event.
cache()inheritedDecorator to enable caching of the output of dataframe getter function in the trace cache.
call_on_trace()inheritedCall a method of a subclass on a given trace.
df_method()inheritedDataframe function decorator.
get_all_events()inheritedReturns the set of all events used by any of the methods.
get_analysis_classes()inheritedget_default_plot_path()inheritedReturn the default path to use to save plots for the analysis.
get_df_methods()inheritedget_logger()inheritedProvides a
logging.Loggernamed aftercls.get_plot_methods()inheritedlog_locals()inheritedDebugging aid: log the local variables of the calling function.
plot_method()inheritedPlot function decorator.
save_plot()inheritedSave a holoviews element or
matplotlib.figure.Figureas an image file.
Attributes#
- NotebookAnalysis.name = 'notebook'#
Name of the analysis class.
Properties#
- property NotebookAnalysis.logger#
Inherited property, see
lisa.utils.Loggable.loggerConvenience short-hand for
self.get_logger().
Methods#
- NotebookAnalysis.__getattr__(attr)[source]#
Called on
Traceinstances astrace.ana.notebook.__getattr__()
- NotebookAnalysis.df_all_events(events=None, *, field_sep=' ', fields_as_cols=None, event_as_col=True, error='raise', df_fmt=None)[source]#
Called on
Traceinstances astrace.ana.notebook.df_all_events()Provide a dataframe with an
infocolumn containing the textual human-readable representation of the events fields.- Parameters:
List of events to include. If
None, all parsed events will be used.Note
Since events can be parsed on-demand, passing
Nonemight result in different results depending on what was done with the object. For reproducible behaviour, pass an explicit list of events.field_sep (str) – String to use to separate fields.
fields_as_cols (list(str) or None) – List of fields to keep as separate columns rather than merged in the
infocolumn. IfNone, will default to a fixed set of columns.event_as_col (bool) – If
True, the event name is split in its own column.error (str) – Can be one of: *
raise: any error while parsing an event will be raised. *log: the error will be logged at error level. *ignore: the error is simply ignored.
- NotebookAnalysis.plot_event_field(event: str, field: str, filter_columns=None, filter_f=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)[source]#
event=cpu_frequency, field=state, filter_columns={'cpu_id': 0}
Called on
Traceinstances astrace.ana.notebook.plot_event_field()Plot a signal represented by the filtered values of a field of an event.
- Parameters:
event (str) – FTrace event name of interest.
field (str) – Name of the field of
event.filter_columns (dict or None) – Pre-filter the dataframe using
lisa.datautils.df_filter(). Also, a signal will be inferred from the column names being used and will be passed tolisa.trace.TraceBase.df_event().filter_f (collections.abc.Callable) – Function used to filter the dataframe of the event. The function must take a dataframe as only parameter and return a filtered dataframe. It is applied after
filter_columnsfilter.
Added by
lisa.analysis.base.AnalysisHelpers.plot_method():- Returns:
The return type is determined by the
outputparameter.- Parameters:
backend (str or None) –
Holoviews plot library backend to use:
bokeh: good support for interactive plotsmatplotlib: 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. Thebackendparameter 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 nofilepathhas 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 toholoviewsfor now. In the future, this will be eitherholoviewsoruiif used in an interactive jupyter notebook.holoviews: a bare holoviews element.render: a backend-specific object, such asmatplotlib.figure.Figureifbackend='matplotlib'html: HTML documentrst: a snippet of reStructuredTextui: 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 * ywill not work ifxis 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.
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.
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.Axesto 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=Trueby default when matplotlib is the current holoviews backend.
- classmethod NotebookAnalysis.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 NotebookAnalysis.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 NotebookAnalysis.df_method(f, index=None)#
Inherited method, see
lisa.analysis.base.TraceAnalysisBase.df_method()Dataframe function decorator.
- classmethod NotebookAnalysis.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 NotebookAnalysis.get_analysis_classes()#
Inherited method, see
lisa.analysis.base.TraceAnalysisBase.get_analysis_classes()
- NotebookAnalysis.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 NotebookAnalysis.get_df_methods(*args, **kwargs)#
Inherited method, see
lisa.analysis.base.TraceAnalysisBase.get_df_methods()
- classmethod NotebookAnalysis.get_logger(suffix=None)#
Inherited method, see
lisa.utils.Loggable.get_logger()Provides a
logging.Loggernamed aftercls.
- classmethod NotebookAnalysis.get_plot_methods(*args, **kwargs)#
Inherited method, see
lisa.analysis.base.AnalysisHelpers.get_plot_methods()
- classmethod NotebookAnalysis.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 NotebookAnalysis.plot_method(f)#
Inherited method, see
lisa.analysis.base.AnalysisHelpers.plot_method()Plot function decorator.
- NotebookAnalysis.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.Figureas an image file.