Stack

class baseband.tasks.Stack(ih, n_phase, phase, *, start=0, average=True, samples_per_frame=1, dtype=None)[source] [edit on github]

Bases: baseband_tasks.base.BaseTaskBase

Create a stream of pulse profiles.

Parameters
ihtask or baseband stream reader

Input data stream, with time as the first axis.

n_phaseint

Number of bins per pulse period.

phasecallable

Should return pulse phases for given input time(s), passed in as an ‘~astropy.time.Time’ object. The output should be an array of float, and has to include the cycle count.

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 pulse profile 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 sample times to process in one go. This can be used to optimize the process, though with many samples per pulse period the default of 1 should be fine.

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.

See also

Fold

to calculate pulse profiles integrated over a given amount of time.

Notes

One can follow this with a Integrate task to average over multiple pulses.

If there are only few input samples per cycle, one can avoid a large overhead in calculating phases by ensuring samples_per_frame of the underlying stream is not too small (larger than, say, 20).

Since 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

closed

complex_data

dtype

Data type of the output.

meta

ndim

Number of dimensions of the output.

offset

sample_rate

Number of complete samples per second.

sample_shape

Shape of a complete sample.

samples_per_frame

Number of samples per frame of data.

shape

Shape of the output.

size

Number of component samples in the output.

start_time

Start time of the output.

stop_time

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

time

Time of the sample pointer's current offset in the output.

Methods Summary

close()

Close task.

read([count, out])

Read a number of complete samples.

seek(offset[, whence])

Change the sample pointer position.

tell([unit])

Current offset in the file.

Attributes Documentation

closed = False
complex_data
dtype

Data type of the output.

meta
ndim

Number of dimensions of the output.

offset = 0
sample_rate

Number of complete samples per second.

sample_shape

Shape of a complete sample.

samples_per_frame

Number of samples per frame of data.

For compatibility with file readers, to help indicate what a nominal chunk of data is.

shape

Shape of the output.

size

Number of component samples in the output.

start_time

Start time of the output.

See also time and stop_time.

stop_time

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

See also start_time and time.

time

Time of the sample pointer’s current offset in the output.

See also start_time and stop_time.

Methods Documentation

close() [edit on github]

Close task.

Note that this does not explicitly close the underlying source; instead, it just deletes the reference to it.

read(count=None, out=None) [edit on github]

Read a number of complete samples.

Parameters
countint or None, optional

Number of complete samples to read. If None (default) or negative, the number of samples left. Ignored if out is given.

outNone or array, optional

Array to store the samples in. If given, count will be inferred from the first dimension; the remaining dimensions should equal sample_shape.

Returns
outndarray of float or complex

The first dimension is sample-time, and the remaining ones are as given by sample_shape.

seek(offset, whence=0) [edit on github]

Change the sample pointer position.

This works like a normal filehandle seek, but the offset is in samples (or a relative or absolute time).

Parameters
offsetint, Quantity, or Time

Offset to move to. Can be an (integer) number of samples, an offset in time units, or an absolute time. For the latter two, the pointer will be moved to the nearest integer sample.

whence{0, 1, 2, ‘start’, ‘current’, or ‘end’}, optional

Like regular seek, the offset is taken to be from the start if whence=0 (default), from the current position if 1, and from the end if 2. One can alternativey use ‘start’, ‘current’, or ‘end’ for 0, 1, or 2, respectively. Ignored if offset is a time.

tell(unit=None) [edit on github]

Current offset in the file.

Parameters
unitUnit or str, optional

Time unit the offset should be returned in. By default, no unit is used, i.e., an integer enumerating samples is returned. For the special string ‘time’, the absolute time is calculated.

Returns
offsetint, Quantity, or Time

Offset in current file (or time at current position).