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 the column field

Parameters

column (str or Column) – column to be aggregated
n (int) – Number of ticks to output
running (bool) –
Aggregation will be calculated as sliding window. running and bucket_interval parameters determines when new buckets are created.
- running = True
  
  aggregation 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 = 0
    
    Left boundary of window will be bound to start time. For each tick aggregation will be calculated in [start_time; tick_t].
- running = False
  
  buckets 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). If bucket_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 = True
  
  bucket_end_condition is applied only to the group defined by group_by
- end_condition_per_group = False
  
  bucket_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. If Operation is used then GROUP_{i} column is added. Where i is index in group_by list. For example, if Operation is the only element in group_by list then GROUP_0 field will be added.
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