class baseband_tasks.integration.Integrate(ih, step=None, phase=None, *, start=0, average=True, samples_per_frame=1, dtype=None)[source] [edit on github]

Bases: baseband_tasks.base.BaseTaskBase

Integrate a stream stepwise.

ihtask or baseband stream reader

Input data stream, with time as the first axis.

stepint or Quantity, optional

Interval over which to integrate. For time invervals, should have units of time. For phase intervals, units should be consistent with what the phase callable returns. If no phase callable is passed in, then if step is integer, it is taken to be a number of samples in the underlying stream that should be integrated over, and if step is omitted, integration is over all samples.


Should return full pulse phase (i.e., including cycle count) for given input times (passed in as ‘~astropy.time.Time’). The output should be compatible with step, i.e., generally an Quantity with angular units.

startTime or int, optional

Time or offset at which to start the integration. If an offset or if step is integer, the actual start time will the underlying sample time nearest to the requested one. Default: 0 (start of stream).

averagebool, optional

Whether the output should be the average of all entries that contributed to it, or rather the sum, in a structured array that holds both 'data' and 'count' items.

samples_per_frameint, optional

Number of samples to process in one go. This can be used to optimize the process. With many samples per bin, the default of 1 should be OK.

dtypedtype, optional

Output dtype. Generally, the default of the dtype of the underlying stream is good enough, but can be used to increase precision. Note that if average=True, it is the user’s responsibilty to pass in a structured dtype.


If there are not many samples per bin, either set samples_per_frame to a larger number or ensure that samples_per_frame of the underlying stream is not small (larger than, say, 20). If both are small, there will be a relatively large overhead in calculating phases.

Since time or phase bins are typically not an integer multiple of the underlying bin spacing, the integrated samples will generally not contain the same number of samples. The actual number of samples is counted, and for average=True, the sums have been divided by these counts, with bins with no points set to NaN. For average=False, the arrays returned by read are structured arrays with data and count fields.

Attributes Summary


Start time of the output, left edge of the first sample.


Time at the end of the output, just after the last sample.

Attributes Documentation


Start time of the output, left edge of the first sample.

See also time and stop_time.


Time at the end of the output, just after the last sample.

See also start_time and time.