Plot
LatencyStackedBar
#
Class that provides latency stacked bar data.
to_dataframe(xaxis_type='system_time')
#
Get latency stacked bar data in pandas DataFrame format.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
xaxis_type |
str
|
X axis value's type , by default 'system_time'. |
'system_time'
|
Returns:
Type | Description |
---|---|
DataFrame
|
Latency dataframe. |
to_stacked_bar_data(xaxis_type='system_time')
#
Get stacked bar dict and columns.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
xaxis_type |
str
|
X axis value's type , by default 'system_time'. |
'system_time'
|
Returns:
Type | Description |
---|---|
(dict[str, list[int]], list[str])
|
Stacked bar dict. Columns (not include 'start time'). |
Plot
#
Facade class for plot.
create_callback_scheduling_plot(target_objects, lstrip_s=0, rstrip_s=0)
staticmethod
#
Get CallbackSchedulingPlot instance.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
target_objects |
CallbackGroupTypes
|
CallbackGroupTypes = (Application | Executor | Path | Node | CallbackGroup | Sequence[CallbackGroup]) Instances that are the sources of the plotting. |
required |
lstrip_s |
float
|
Start time of cropping range, 0 by default. |
0
|
rstrip_s |
float
|
End point of cropping range, 0 by default. |
0
|
Returns:
Type | Description |
---|---|
CallbackSchedulingPlot
|
|
create_frequency_histogram_plot(*target_objects)
staticmethod
#
Get frequency histogram plot instance.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
*target_objects |
CallbackBase | Communication | Publisher | Subscription
|
Instances that are the sources of the plotting. This also accepts multiple inputs by unpacking. |
()
|
Returns:
Type | Description |
---|---|
PlotBase
|
|
create_frequency_timeseries_plot(*target_objects)
staticmethod
#
Get frequency timeseries plot instance.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
*target_objects |
CallbackBase | Communication | Publisher | Subscription
|
Instances that are the sources of the plotting. This also accepts multiple inputs by unpacking. |
()
|
Returns:
Type | Description |
---|---|
PlotBase
|
|
create_latency_histogram_plot(*target_objects)
staticmethod
#
Get latency histogram plot instance.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
*target_objects |
CallbackBase | Communication
|
Instances that are the sources of the plotting. This also accepts multiple inputs by unpacking. |
()
|
Returns:
Type | Description |
---|---|
PlotBase
|
|
create_latency_timeseries_plot(*target_objects)
staticmethod
#
Get latency timeseries plot instance.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
*target_objects |
CallbackBase | Communication
|
Instances that are the sources of the plotting. This also accepts multiple inputs by unpacking. |
()
|
Returns:
Type | Description |
---|---|
PlotBase
|
|
create_message_flow_plot(target_path, granularity=None, treat_drop_as_delay=False, lstrip_s=0, rstrip_s=0)
staticmethod
#
Get MessageFlowPlot instance.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
target_path |
Path
|
Target path to be plotted. |
required |
granularity |
str | None
|
Granularity of chain with two value; [raw/node], None by default. |
None
|
treat_drop_as_delay |
bool
|
If there is a drop, the flow is drawn by connecting it to the next one, False by default. |
False
|
lstrip_s |
float
|
Start time of cropping range, 0 by default. |
0
|
rstrip_s |
float
|
End point of cropping range, 0 by default. |
0
|
Returns:
Type | Description |
---|---|
MessageFlowPlot
|
|
create_period_histogram_plot(*target_objects)
staticmethod
#
Get period histogram plot instance.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
*target_objects |
CallbackBase | Communication | Publisher | Subscription
|
Instances that are the sources of the plotting. This also accepts multiple inputs by unpacking. |
()
|
Returns:
Type | Description |
---|---|
PlotBase
|
|
create_period_timeseries_plot(*target_objects)
staticmethod
#
Get period timeseries plot instance.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
*target_objects |
CallbackBase | Communication | Publisher | Subscription
|
Instances that are the sources of the plotting. This also accepts multiple inputs by unpacking. |
()
|
Returns:
Type | Description |
---|---|
PlotBase
|
|
create_response_time_histogram_plot(*target_objects, case='all')
staticmethod
#
Get response time histogram plot instance.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
*target_objects |
Path
|
Instances that are the sources of the plotting. This also accepts multiple inputs by unpacking. |
()
|
case |
str
|
Response time calculation method, all by default. supported case: [all/best/worst/worst-with-external-latency]. |
'all'
|
Returns:
Type | Description |
---|---|
PlotBase
|
|
create_response_time_stacked_bar_plot(target_object, metrics='latency', case='all')
staticmethod
#
Get StackedBarPlot instance.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
target_object |
Path
|
Target path |
required |
metrics |
str
|
Metrics for stacked bar graph. supported metrics: [latency] |
'latency'
|
case |
str
|
Response time calculation method, all by default. supported case: [all/best/worst/worst-with-external-latency]. |
'all'
|
Returns:
Type | Description |
---|---|
StackedBarPlot
|
|
create_response_time_timeseries_plot(*target_objects, case='all')
staticmethod
#
Get response time timeseries plot instance.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
*target_objects |
Path
|
Instances that are the sources of the plotting. This also accepts multiple inputs by unpacking. |
()
|
case |
str
|
Response time calculation method, all by default. supported case: [all/best/worst/worst-with-external-latency]. |
'all'
|
Returns:
Type | Description |
---|---|
PlotBase
|
|
PlotBase
#
Plot base class.
figure(xaxis_type, ywheel_zoom, full_legends)
abstractmethod
#
Get bokeh.plotting.Figure object.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
xaxis_type |
str | None
|
Type of time for timestamp. |
required |
ywheel_zoom |
bool | None
|
If True, the drawn graph can be expanded in the y-axis direction. |
required |
full_legends |
bool | None
|
If True, all legends are drawn even if the number of legends exceeds the threshold. |
required |
Returns:
Type | Description |
---|---|
Figure
|
|
save(export_path, title='', xaxis_type=None, ywheel_zoom=None, full_legends=None)
#
Export a graph using the bokeh library.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
export_path |
str
|
The graph will be saved as a file. |
required |
title |
str
|
Title of the graph, by default ''. |
''
|
xaxis_type |
str
|
Type of x-axis of the graph to be plotted. "system_time", "index", or "sim_time" can be specified. |
None
|
ywheel_zoom |
bool
|
If True, the drawn graph can be expanded in the y-axis direction by the mouse wheel. |
None
|
full_legends |
bool
|
If True, all legends are drawn even if the number of legends exceeds the threshold. |
None
|
Raises:
Type | Description |
---|---|
UnsupportedTypeError
|
Argument xaxis_type is not "system_time", "index", or "sim_time". |
show(xaxis_type=None, ywheel_zoom=None, full_legends=None)
#
Draw a graph using the bokeh library.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
xaxis_type |
str
|
Type of x-axis of the graph to be plotted. "system_time", "index", or "sim_time" can be specified. |
None
|
ywheel_zoom |
bool
|
If True, the drawn graph can be expanded in the y-axis direction by the mouse wheel. |
None
|
full_legends |
bool
|
If True, all legends are drawn even if the number of legends exceeds the threshold. |
None
|
Raises:
Type | Description |
---|---|
UnsupportedTypeError
|
Argument xaxis_type is not "system_time", "index", or "sim_time". |
to_dataframe(xaxis_type)
abstractmethod
#
Get data in pandas DataFrame format.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
xaxis_type |
str
|
Type of time for timestamp. |
required |
Returns:
Type | Description |
---|---|
DataFrame
|
|