CARET is able to analyze data recorded for several minutes. When analyzing large data with CARET, both memory and time consumed for analysis will be critical issue.
In order not to load unnecessary data, CARET has
LTTngEventFilter to exclude selected data from loading data.
LTTngEventFilter has the following methods.
init_pass_filter method, events recorded by runtime tracepoints are not loaded onto memory.
duration_filter method, you can crop data with targeting time range of recorded data.
LttngEventFilter.duration_filter(duration_s: float, offset_s: float)
duration_filter method has following two arguments.
duration_sis duration of target time range
offset_sis point of target time range
strip_filter method, you can crop data with targeting time range of recorded data as well as
strip_filter has different arguments from
LttngEventFilter.strip_filter(lsplit_s: Optional[float], rsplit_s: Optional[float])
strip_filter method has following two optional arguments. If you omit either or both of them, default value '0' is given to the optional argument.
lstrip_sis start time of cropping range
rstrip_sis end point of cropping range
A sample code, where
duration_filter is used, is given as below.
from caret_analyze import Lttng, LttngEventFilter lttng = Lttng('/path/to/ctf', event_filters=[ LttngEventFilter.duration_filter(10, 5) ]) # Filtering for 10 from 5 seconds
If you want to add another filter, append it to