otp.agg.high_tick#
- high_tick(column, n=1, running=False, bucket_interval=0, bucket_time='end', bucket_units='seconds', bucket_end_condition=None, end_condition_per_group=False, boundary_tick_bucket='new', group_by=None, keep_timestamp=True, selection='first', time_series_type='event_ts')#
Select
n
ticks with the highest values in thecolumn
field- Parameters
n (int) – Number of ticks to output
running (bool) –
Aggregation will be calculated as sliding window.
running
andbucket_interval
parameters determines when new buckets are created.running
= Trueaggregation will be calculated in a sliding window.
bucket_interval
= N (N > 0)Window size will be N. Output tick will be generated when tick “enter” window (arrival event) and when “exit” window (exit event)
bucket_interval
= 0Left boundary of window will be bound to start time. For each tick aggregation will be calculated in [start_time; tick_t].
running
= Falsebuckets partition the [query start time, query end time) interval into non-overlapping intervals of size
bucket_interval
(with the last interval possibly of a smaller size). Ifbucket_interval
is set to 0 a single bucket for the entire interval is created.
Default: False - create totally independent buckets. Number of buckets = (end - start) / bucket_interval’)
bucket_interval (int) – Determines the length of each bucket (units depends on
bucket_units
).bucket_time (Literal['start', 'end']) –
Control output timestamp.
start
the timestamp assigned to the bucket is the start time of the bucket.
end
the timestamp assigned to the bucket is the end time of the bucket.
bucket_units (Literal['seconds', 'ticks', 'days', 'months', 'flexible']) –
Set bucket interval units.
If set to flexible
bucket_end_criteria
must be set.bucket_end_condition (condition) – An expression that is evaluated on every tick. If it evaluates to “True”, then a new bucket is created. This parameter is only used if
bucket_units
is set to “flexible”end_condition_per_group (bool) –
Controls application of
bucket_end_condition
in groups.end_condition_per_group
= Truebucket_end_condition
is applied only to the group defined bygroup_by
end_condition_per_group
= Falsebucket_end_condition
applied across all groups
This parameter is only used if
bucket_units
is set to “flexible”boundary_tick_bucket (Literal['new', 'previous']) –
Controls boundary tick ownership.
previous
A tick on which
bucket_end_condition
evaluates to “true” belongs to the bucket being closed.new
tick belongs to the new bucket.
This parameter is only used if
bucket_units
is set to “flexible”group_by (list, str or expression) – When specified, each bucket is broken further into additional sub-buckets based on specified field values.
keep_timestamp (bool) – If True, timestamps of the output ticks are the same as timestamps of the original ticks. Otherwise, timestamps of the output ticks are determined by bucket_time, and original timestamps are put in the TICK_TIME field.
selection (Literal['first', 'last']) – Controls the selection of the respective beginning or trailing part of ticks.
time_series_type (Literal['event_ts', 'state_ts']) –
Controls initial value for each bucket
event_ts
only ticks from current bucket used for calculations
state_ts
if there is a tick in bucket with timestamp = bucket start
only ticks in bucket used for calculation max value
else
latest tick from previous bucket included in current bucket
Examples
>>> data = otp.Ticks(X=[1, 2, 3, 4], offset=[0, 1000, 1500, 3000]) >>> agg = otp.agg.high_tick('X', 2) >>> data = agg.apply(data) >>> otp.run(data) Time X 0 2003-12-01 00:00:01.500 3 1 2003-12-01 00:00:03.000 4
See also
HIGH_TICK OneTick event processor