pyuff_ustb.objects.BeamformedData

pyuff_ustb.objects.BeamformedData#

class pyuff_ustb.objects.BeamformedData(_reader: Reader | str | None = None, **kwargs)[source]#

Bases: Uff

Uff class to hold beamformed data.

BeamformedData contains beamformed ultrasound data, i.e. a spacial map. Data is stored in the property data with dimensions: [pixel-dimension x channel-dimension x wave-dimension x frame-dimension].

Original authors:

Alfonso Rodriguez-Molares (alfonso.r.molares@ntnu.no)
Ole Marius Hoel Rindal (olemarius@olemarius.net)

__init__(_reader: Reader | str | None = None, **kwargs)#

Methods

`__init__`([_reader])
`copy`()	Return a (deep) copy of the Uff object.
`read`(name)	Read an Uff object from the file.
`write`(filepath, location[, overwrite, ...])	Write the Uff to a file.

Attributes

`N_channels`	Number of channels
`N_frames`	Number of frames
`N_pixels`	Number of pixels
`N_waves`	Number of waves (transmit events)
`author`	Contact of the authors
`data`	Data [pixel x channel x wave x frame]
`frame_rate`	Framerate for Video or GIF file to be saved [fps]
`info`	Other information
`modulation_frequency`	Modulation frequency in [Hz]
`name`	Name of the dataset
`phantom`	PHANTOM object
`probe`	PROBE object
`pulse`	PULSE object
`reference`	Reference to the publication where it was used/acquired
`sampling_frequency`	Sampling frequency in the depth direction in [Hz]
`scan`	SCAN object or array of SCAN objects
`sequence`	Array of WAVE objects
`version`	Version of the dataset

property scan: Scan#: SCAN object or array of SCAN objects

property data: ndarray#: Data [pixel x channel x wave x frame]

property phantom: Phantom#: PHANTOM object

property sequence: Wave | List[Wave]#: Array of WAVE objects

property probe: Probe#: PROBE object

property pulse: Pulse#: PULSE object

property sampling_frequency: float#: Sampling frequency in the depth direction in [Hz]

property modulation_frequency: float#: Modulation frequency in [Hz]

property frame_rate: int#: Framerate for Video or GIF file to be saved [fps]

property N_pixels: int#: Number of pixels

property N_channels: int#: Number of channels

property author: str | None#: Contact of the authors

copy() → Uff#

Return a (deep) copy of the Uff object.

In addition to the _reader, all compulsory and optional fields are copied (deeply) iff they are loaded/cached. This means that if a field has not been read from the file, it will not be copied. This is to avoid unintended eager loading of data.

See Uff.__deepcopy__() for implementation details.

Returns:: A deep copy of this object.
Return type:: Uff

property info: str | None#: Other information

property name: str | None#: Name of the dataset

read(name: str) → Uff#

Read an Uff object from the file. A Reader must be provided in order to read.

>> uff = Uff(“/path/to/some/file.uff”) >> scan = uff.read(“scan”)

property reference: str | None#: Reference to the publication where it was used/acquired

property version: str | None#: Version of the dataset

write(filepath: str, location: str | Tuple[str, ...] | List[str], overwrite: bool = False, ignore_missing_compulsory_fields: bool = False)#

Write the Uff to a file.

Parameters:

filepath (Union[str, h5py.File]) – The filepath (or h5py.File) to write to.
location (Union[str, Tuple[str, ...], List[str]]) – The location in the h5 file to write to. Can be a tuple/list of strings representing a path into the h5 file, or a string with the path separated by slashes.
overwrite (bool) – Whether to overwrite the location if it already exists. If the location already exists and overwrite=False, a ValueError is raised. overwrite=False by default.
ignore_missing_compulsory_fields (bool) – Whether to ignore missing compulsory fields. If a compulsory field is not set then usually a ValueError is raised. Setting ignore_missing_compulsory_fields=True will ignore this error and write the object anyway. ignore_missing_compulsory_fields=False by default.

Examples

We can write an object to a file like this:

>>> import pyuff_ustb as pyuff
>>> point = pyuff.Point(distance=0.0, azimuth=0.0, elevation=0.0)
>>> point.write("my_point.uff", "point")

If we try to write an object to the same location, we get an error:

>>> point.write("my_point.uff", "point")
Traceback (most recent call last):
    ...
ValueError: Location 'point' already exists in the file 'my_point.uff'. Use overwrite=True to overwrite it.

We can choose to overwrite the location by passing overwrite=True:

>>> point.write("my_point.uff", "point", overwrite=True)

We can also write the object to another arbitrary location if we want:

>>> point.write("my_point.uff", "sub_directory/point")

Compulsory fields may not be None when writing an object to an UFF file (unless ignore_missing_compulsory_fields=True).

>>> point.distance = None
>>> point.write("my_point.uff", "point2")
Traceback (most recent call last):
    ...
ValueError: The compulsory field 'distance' is set to None. Compulsory fields
may not be None when writing an object to an UFF file. To ignore this error and write
the object anyway, set ignore_missing_compulsory_fields=True.

Note that even though the previous step failed, the file was still partially written to (we don’t rollback changes when writing fails), so we will have to pass overwrite=True to write the object again.

>>> point.write(
...     "my_point.uff",
...     "point2",
...     overwrite=True,
...     ignore_missing_compulsory_fields=True,
... )

After running these steps, the file will contain the following fields:

>>> uff = pyuff.Uff("my_point.uff")
>>> uff
Uff(point=Point(<...>), point2=Point(<...>), sub_directory=<...>)

property N_waves: int#: Number of waves (transmit events)

property N_frames: int#: Number of frames

pyuff_ustb.objects.BeamformedData

Contents

pyuff_ustb.objects.BeamformedData#