HDF5RawHeader

class baseband_tasks.io.hdf5.header.HDF5RawHeader(*, verify=True, mutable=True, **kwargs)

Bases: baseband_tasks.io.hdf5.header.HDF5Header

Attributes Summary

dtype
encoded_dtype	The numpy dtype in which the data are stored.
frequency
polarization
sample_rate
sample_shape
samples_per_frame
shape
sideband
time

Methods Summary

clear()
copy()
fromfile(fh[, verify])	Create a header from a yaml-encoded 'header' extension.
fromkeys(iterable[, value])	Create a new dictionary with keys from iterable and values set to value.
fromvalues(template[, whole, verify])	Initialise a header from a template and/or values.
get(key[, default])	Return the value for key if key is in the dictionary, else default.
items()
keys()
pop(k[,d])	If key is not found, d is returned if given, otherwise KeyError is raised
popitem()	2-tuple; but raise KeyError if D is empty.
setdefault(key[, default])	Insert key with a value of default if key is not in the dictionary.
tofile(fh)	Write the header as a yaml-encoded 'header' extension.
update(*[, verify])	Update the header with new values.
values()
verify()

Attributes Documentation

dtype

encoded_dtype

The numpy dtype in which the data are stored.

This is generally the same as the actual dtype in which data are produced, except that it can have lower number of bits. Furthermore, the DTYPE_C4 dtype can be used for complex data using half-precision floats (‘<f2’) for the real and imaginary parts.

Can be set using a dtype or a string (with ‘c4’ representing the above half-precision complex numbers). Will set dtype as well (with half precision changed to single precision, i.e., ‘f2’ to ‘f4’ and ‘c4’ to ‘c4’).

frequency

polarization

sample_rate

sample_shape

samples_per_frame

shape

sideband

time

Methods Documentation

clear() → None.  Remove all items from D.

copy() → a shallow copy of D

classmethod fromfile(fh, verify=True)

Create a header from a yaml-encoded ‘header’ extension.

fromkeys(iterable, value=None, /)

Create a new dictionary with keys from iterable and values set to value.

classmethod fromvalues(template, whole=None, verify=True, **kwargs)

Initialise a header from a template and/or values.

Parameters

templateheader or stream template, optional

Must have attributes that define a header (‘sample_shape’, ‘samples_per_frame’, ‘sample_rate’, ‘time’, and either ‘dtype’ or ‘bps’ and ‘complex_data’).

wholebool, optional

If True, assume a header for the complete stream is wanted, and use ‘start_time’ for the ‘time’ and the total number of samples for ‘samples_per_frame’. Default: True if the template has both ‘start_time’ and ‘shape’ (i.e., for streams).

verifybool, optional

Whether to do basic verification. Default: True.

**kwargs

Any additional values. These will override values inferred from the template.

get(key, default=None, /)

Return the value for key if key is in the dictionary, else default.

items() → a set-like object providing a view on D's items

keys() → a set-like object providing a view on D's keys

pop(k[, d]) → v, remove specified key and return the corresponding value.

If key is not found, d is returned if given, otherwise KeyError is raised

popitem() → (k, v), remove and return some (key, value) pair as a

2-tuple; but raise KeyError if D is empty.

setdefault(key, default=None, /)

Insert key with a value of default if key is not in the dictionary.

Return the value for key if key is in the dictionary, else default.

tofile(fh)

Write the header as a yaml-encoded ‘header’ extension.

update(*, verify=True, **kwargs)

Update the header with new values.

Here, any keywords matching properties are processed as well, in the order set by the class (in _properties), and after all other keywords have been processed.

Parameters

verifybool, optional

If True (default), verify integrity after updating.

**kwargs

Arguments used to set keywords and properties.

values() → an object providing a view on D's values

verify()