Comments (3)
Ah I see that domains have been removed for some reason on master (making this somewhat moot).
Searching around I couldn't seem to find a reason for this. Could someone provide a reference or reason?
from traces.
Hi, thanks for opening the issue. We removed domains because people were finding them confusing, and we were finding that they were rarely used. It didn't seem like the minimal value they were adding was worth the confusion in explaining them. Would you mind sharing a more complete use case of how you are using domains and why they are useful? (and perhaps how ugly it would be without them)
from traces.
@stringertheory I am developing a library py-stl for working within Metric Temporal Logic and Signal Temporal Logic.
These are often used to determine if a time series signal meets some specification (for filtering perhaps). For example, one may write G[0, 10]((x > 0) -> F[0, 1](y < -1))
which translates to:
Between time 0 and 10, if x is greater than zero, then within the next 1 time steps y will be less than negative one.
My library would take the two signals x(t)
and y(t)
and evaluate the above formula. The problem is if x
and y
are defined on different domains, then the result may not be well defined.
For example, if x.domain = (0, 10)
, but y.domain = (0, 4)
, then the above formula is only defined if for all t > 4, x(t) = False.
It's worth noting that I made the design decision to make x
and y
different TimeSeries
objects since it means I can often compress x > 0
and y < -1
quite abit using the compact
method. This makes evaluation much more efficent, particularly if one is interested in at what time points a particular formula is True
(similar to doing a sliding window and evaluating the formula on the window).
from traces.
Related Issues (20)
- pd.NaT creates unexpected behavior in TimeSeries
- tests fail because of something with config
- TimeSeries._get_linear_interpolate() explicitly casts int to float HOT 2
- Result of to_bool is missing default value assignment HOT 2
- Merge fails with TypeError HOT 2
- will it work for multivariate time series prediction both regression and classification HOT 1
- Where is the folder called "data" containing the 40 times series ? HOT 1
- [... list of forty traces.TimeSeries ...] is not functioning. HOT 2
- Incorrect handling of Numpy array passed as times of measurements HOT 1
- No longer maintained? HOT 5
- `max` for distribution with `start` and `end` gives wrong result HOT 1
- add documentation for TimeSeries.plot
- add documentation for EventSeries
- Documentation failing HOT 1
- bool(trace) should handle default values
- use a specific value for the default when not given (e.g. NotGiven) to differentiate a default=None with a default not given HOT 2
- add default in __str__ when default is given
- support __abs__ on traces
- support all mathematical magic methods including __r*__ and __pos__/__neg__
- adding a constant to a trace fails
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from traces.