User API

Qpformat supports several file formats (qpformat.file_formats.formats), which are divided into qpformat.file_formats.SingleData (the experimental data file format contains only one phase image) and qpformat.file_formats.SeriesData (the experimental data file format supports multiple phase images). From these base classes, all data file formats are derived. The idea is that experimental data is not loaded into memory until the get_qpimage method is called which returns a qpimage.QPImage object.

Basic Usage

The file format type is determined automatically by qpformat. If the file format is implemented in qpformat, experimental data can be loaded with the qpformat.load_data() method.

# Obtain a qpformat.file_formats.SingleData object
# (the data is not loaded into memory, only the meta data is read)
ds = qpformat.load_data(path="/path/to/SID PHA_xxx.tif")
# Get the quantitative phase data (a qpimage.QPImage is returned)
qpi = ds.get_qpimage()

SingleData

class qpformat.file_formats.SeriesData(path, meta_data={}, holo_kw={}, as_type='float32')

background_identifier = None

Unique string that identifies the background data that was set using set_bg.

identifier

Return a unique identifier for the given data set

get_identifier(idx)

Return an identifier for the data at index idx

get_name(idx)

Return name of data at index idx

get_qpimage(idx)

Return background-corrected QPImage of data at index idx

get_qpimage_raw(idx)

Return QPImage without background correction

get_time(idx)

Return time of data at index idx

saveh5(h5file)

Save the data set as an hdf5 file (QPImage format)

set_bg(dataset)

Set background data

Parameters:dataset (DataSet, qpimage.QPImage, or int) – If the len(dataset) matches len(self), then background correction is performed element-wise. Otherwise, len(dataset) must be one and is used for all data of self.

See also

get_qpimage()

obtain the background corrected QPImage

static verify(path)

Verify that path has this file format

Returns True if the file format matches. The implementation of this method should be fast and memory efficient, because e.g. the “GroupFolder” file format depends on it.

SeriesData

class qpformat.file_formats.SeriesData(path, meta_data={}, holo_kw={}, as_type='float32')

background_identifier = None

Unique string that identifies the background data that was set using set_bg.

identifier

Return a unique identifier for the given data set

get_identifier(idx)

Return an identifier for the data at index idx

get_name(idx)

Return name of data at index idx

get_qpimage(idx)

Return background-corrected QPImage of data at index idx

get_qpimage_raw(idx)

Return QPImage without background correction

get_time(idx)

Return time of data at index idx

saveh5(h5file)

Save the data set as an hdf5 file (QPImage format)

set_bg(dataset)

Set background data

Parameters:dataset (DataSet, qpimage.QPImage, or int) – If the len(dataset) matches len(self), then background correction is performed element-wise. Otherwise, len(dataset) must be one and is used for all data of self.

See also

get_qpimage()

obtain the background corrected QPImage

static verify(path)

Verify that path has this file format

Returns True if the file format matches. The implementation of this method should be fast and memory efficient, because e.g. the “GroupFolder” file format depends on it.

Constants

qpformat.file_formats.formats = [<class 'qpformat.file_formats.SeriesFolder'>, <class 'qpformat.file_formats.single_hdf5_qpimage.SingleHdf5Qpimage'>, <class 'qpformat.file_formats.single_tif_phasics.SingleTifPhasics'>, <class 'qpformat.file_formats.single_tif_holo.SingleTifHolo'>, <class 'qpformat.file_formats.single_npy_numpy.SingleNpyNumpy'>, <class 'qpformat.file_formats.series_hdf5_hyperspy.SeriesHdf5HyperSpy'>, <class 'qpformat.file_formats.series_hdf5_qpimage.SeriesHdf5Qpimage'>, <class 'qpformat.file_formats.series_zip_tif_phasics.SeriesZipTifPhasics'>, <class 'qpformat.file_formats.series_zip_tif_holo.SeriesZipTifHolo'>]

list() -> new empty list list(iterable) -> new list initialized from iterable’s items