Package: pacfish
PACFISHIn this repository we develop the photoacoustic converter for information sharing (PACFISH).
It is a tool that enables the conversion of vendor-specific
proprietary data formats into the IPASC data format,
which is an HDF5 container that has a defined
structure for the meta data that are given with the binary data.
A list of meta data information was suggested by the International
Photoacoustic Standardisation Consortium (IPASC)
in early 2020. You can find this list using the following link:https://www.ipasc.science/documents/20210916_IPASC_Format_V2.pdfPACFISH serves three purposes: (1) it helps vendors to integrate the IPASC data format
export into their standard software; (2) it assists scientists to read and write data in
the consensus HDF5 format; and (3) it helps the PA community to create custom adapters
that convert proprietary file formats into the consensus HDF5 format.Please help IPASC by reporting any missing parameters, bugs, or issues.
We are also looking forward to any contributions in form of adapters that
can convert a priprietary format into the IPASC format.
If you are a member of the research community, a photoacoustic vendor, or
interested to contribute or in the project in general because of any other
reasons, please contact the leadership team of the Data Acquisition and
Management Theme of IPASC.These are currently: Janek Gröhl, Lina Hacker, and Ben Cox.Software ArchitecturePACFISH is divided into the API, core, quality control, and iohandler modules.
The API package (pacfish.apiyellow module) can be used to facilitate the
integration of conversion adapters to convert from arbitrary file formats
into the IPASC data format. To create a conversion adapter,
a Python representation of (1) the binary data, (2) the acquisition metadata
dictionary, and (3) the device metadata dictionary need to be implemented.The core classes (pacfish.coregreen module) represent the metadata and
data structure in Python. Each metadatum is described with specific device
tags defining the name, data type, necessity and SI unit (if applicable),
and setting a value constraint. Basic metadata constraints have been
implemented to avoid accidental typos within the values field (e.g. only
positive numbers larger than zero are applicable for acquisition wavelengths).
If the value is not within the constraints aTypeErroris raised.
Metadatum-specific functions enable easy addition of the values for the
specific metadata field.The quality control functionalities (pacfish.qualitycontrolblue module) ensure
the correctness of the conversion into the IPASC format: acompleteness checkertests that all metadata are being called and aconsistency checkerensures
that all metadata are within their constraints. An automatically-generated
output report gives a human-readable summary of the quality control checks and
ensures that the likelihood of conversion mistakes are minimized. For control of
theDevice Metadata, the detector and illuminator positions can be represented
in a 3D coordinate system as visual control.Finally, the I/O functionality (pacfish.iohandlerred module) enables reading
and writing of IPASC-formatted data files.Examples and use casesPlease look in theexamplesfolder for
detailed and functional examples how to use the
PACFISH API. We have examples for bothPythonandMATLAB.Use case: using the tool to read and write HDF5 filesimport pacfish as pf

# Loading data from the hard drive
pa_data = pf.load_data("path/to/hdf5file.hdf5")
numpy_array = pa_data.binary_time_series_data

# Writing of data to hard drive
pf.write_data("path/to/new/file.hdf5", pa_data)Use case: Implement a conversion adapterimpot pacfish as pf

class DeviceSpecificAdapter(pf.BaseAdapter):

    def generate_binary_data(self) -> np.ndarray:
        # IMPLEMENTATION HERE
        pass

    def generate_device_meta_data(self) -> dict:
        # IMPLEMENTATION HERE
        pass

    def set_metadata_value(self, metadata_tag: MetaDatum) -> object:
        # IMPLEMENTATION HERE
        pass