mvpa2.testing.datasets.Event

class mvpa2.testing.datasets.Event(**kwargs)

Simple class to define properties of an event.

The class is basically a dictionary. Any properties can be passed as keyword arguments to the constructor, e.g.:

>>> ev = Event(onset=12, duration=2.45)

Conventions for keys:

onset

The onset of the event in some unit.

duration

The duration of the event in the same unit as onset.

label

E.g. the condition this event is part of.

chunk

Group this event is part of (if any), e.g. experimental run.

features

Any amount of additional features of the event. This might include things like physiological measures, stimulus intensity. Must be a mutable sequence (e.g. list), if present.

Methods

as_descrete_time(dt[, storeoffset, offsetattr])	Convert onset and duration information into descrete timepoints.
clear(() -> None.  Remove all items from D.)
copy(() -> a shallow copy of D)
fromkeys(...)	v defaults to None.
get((k[,d]) -> D[k] if k in D, ...)
has_key((k) -> True if D has a key k, else False)
items(() -> list of D’s (key, value) pairs, ...)
iteritems(() -> an iterator over the (key, ...)
iterkeys(() -> an iterator over the keys of D)
itervalues(...)
keys(() -> list of D’s keys)
pop((k[,d]) -> v, ...)	If key is not found, d is returned if given, otherwise KeyError is raised
popitem(() -> (k, v), ...)	2-tuple; but raise KeyError if D is empty.
setdefault((k[,d]) -> D.get(k,d), ...)
update(([E, ...)	If E present and has a .keys() method, does: for k in E: D[k] = E[k]
values(() -> list of D’s values)
viewitems(...)
viewkeys(...)
viewvalues(...)

Parameters:

**kwargs : dict

All keys to describe the Event to initialize its dict.

Methods

as_descrete_time(dt[, storeoffset, offsetattr])	Convert onset and duration information into descrete timepoints.
clear(() -> None.  Remove all items from D.)
copy(() -> a shallow copy of D)
fromkeys(...)	v defaults to None.
get((k[,d]) -> D[k] if k in D, ...)
has_key((k) -> True if D has a key k, else False)
items(() -> list of D’s (key, value) pairs, ...)
iteritems(() -> an iterator over the (key, ...)
iterkeys(() -> an iterator over the keys of D)
itervalues(...)
keys(() -> list of D’s keys)
pop((k[,d]) -> v, ...)	If key is not found, d is returned if given, otherwise KeyError is raised
popitem(() -> (k, v), ...)	2-tuple; but raise KeyError if D is empty.
setdefault((k[,d]) -> D.get(k,d), ...)
update(([E, ...)	If E present and has a .keys() method, does: for k in E: D[k] = E[k]
values(() -> list of D’s values)
viewitems(...)
viewkeys(...)
viewvalues(...)

as_descrete_time(dt, storeoffset=False, offsetattr='offset')

Convert onset and duration information into descrete timepoints.

Parameters:

dt : float

Temporal distance between two timepoints in the same unit as onset and duration.

storeoffset : bool

If True, the temporal offset between original onset and descretized onset is stored as an additional item.

offsetattr : str

The name of the attribute that is used to store the computed offset in case the storeoffset is enabled.

Returns:

A copy of the original Event with onset and optionally duration

replaced by their corresponding descrete timepoint. The new onset will

correspond to the timepoint just before or exactly at the original

onset. The new duration will be the number of timepoints covering the

event from the computed onset timepoint till the timepoint exactly at

the end, or just after the event.

Note again, that the new values are expressed as #timepoint and not

in their original unit!