pyuff_ustb.objects.SectorScan

class pyuff_ustb.objects.SectorScan(_reader: Reader | str | None = None, **kwargs)

Bases: Scan

Uff class to define a sector scan.

SectorScan contains the position of the azimuth and depth axis from an origin. The origin may be a single point or a list of points with the same length as the azimuth_axis. In the case of multiple origins, each origin represents the apex of a single azimuth direction/column of the scan.

Original authors:

• Alfonso Rodriguez-Molares <alfonso.r.molares@ntnu.no>

• Anders E. Vrålstad <anders.e.vralstad@ntnu.no>

• Stefano Fiorentini <stefano.fiorentini@ntnu.no>

__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_azimuth_axis	Number of pixels in azimuth_axis
N_depth_axis	Number of pixels in depth_axis
N_origins	Number of scanline origins
author	Contact of the authors
azimuth_axis	Vector containing the azimuth coordinates [rad]
depth_axis	Vector containing the distance coordinates [m]
depth_step	Step size along the depth axis [m]
info	Other information
name	Name of the dataset
origin	Vector of UFF.POINT objects
reference	Reference to the publication where it was used/acquired
reference_distance	Distance used for the calculation of the phase term [m]
version	Version of the dataset
x	Vector containing the x coordinates of each pixel in [m]
xyz	Vector containing the [x, y, z] coordinates of each pixel in [m]
y	Vector containing the y coordinates of each pixel in [m]
z	Vector containing the z coordinates of each pixel in [m]

property azimuth_axis: ndarray

Vector containing the azimuth coordinates [rad]

property depth_axis: ndarray

Vector containing the distance coordinates [m]

property origin: Point | List[Point]

Vector of UFF.POINT objects

property N_azimuth_axis: int

Number of pixels in azimuth_axis

property N_depth_axis: int

Number of pixels in depth_axis

property N_origins: int

Number of scanline origins

property depth_step: float

Step size along the depth axis [m]

property reference_distance

Distance used for the calculation of the phase term [m]

property x: ndarray

Vector containing the x coordinates of each pixel in [m]

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 xyz: ndarray

Vector containing the [x, y, z] coordinates of each pixel in [m]

property y: ndarray

Vector containing the y coordinates of each pixel in [m]

property z: ndarray

Vector containing the z coordinates of each pixel in [m]