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# Hamamatsu

Reader for spectroscopy data saved in `.img` (ITEX) files from the HPD-TA (High Performance Digital Temporal Analyzer) or HiPic (High Performance image control) softwares from Hamamatsu, e.g. for images from streak cameras or high performance CCD cameras.

If LumiSpy is installed, `LumiTransientSpectrum` will be used as the `signal_type`, which is intended for streak camera images with both wavelength and time axes.

Note

Currently, reading files containing multiple channels or multiple images per channel is not implemented.

## API functions

rsciio.hamamatsu.file_reader(filename, lazy=False, use_uniform_signal_axes=False, **kwds)

  Read Hamamatsu’s `.img` file, e.g. for streak camera images. In case LumiSpy is installed, the signal type is automatically set to `LumiTransientSpectrum`.

  Parameters:
    filename `python:str`, `pathlib.Path`

      Filename of the file to read or corresponding pathlib.Path.

    lazy bool, default=False

      Whether to open the file lazily or not. The file will stay open until closed in `compute()` or closed manually. `get_file_handle()` can be used to access the file handler and close it manually.

    use_uniform_signal_axes bool, default=False

      Can be specified to choose between non-uniform or uniform signal axis. If `True`, the `scale` attribute is calculated from the average delta along the signal axis and a warning is raised in case the delta varies by more than 1 percent.

    **kwds `python:dict`, optional

      Extra keyword argument will be ignored.

  Returns:
    `python:list` of `python:dict`

      List of dictionaries containing the following fields:

      - ‘data’ – multidimensional `numpy.ndarray` or `dask.array.Array`

      - ‘axes’ – list of dictionaries describing the axes containing the fields ‘name’, ‘units’, ‘index_in_array’, and either ‘size’, ‘offset’, and ‘scale’ or a numpy array ‘axis’ containing the full axes vector

      - ‘metadata’ – dictionary containing the parsed metadata

      - ‘original_metadata’ – dictionary containing the full metadata tree from the input file

      When the file contains several datasets, each dataset will be loaded as separate dictionary.