PYME.contrib.gohlke.tifffile module

Read and write image data from and to TIFF files.

Image and meta-data can be read from TIFF, BigTIFF, OME-TIFF, STK, LSM, NIH, and FluoView files. Only a subset of the TIFF specification is supported, mainly uncompressed and losslessly compressed 2**(0 to 6) bit integer, 16, 32 and 64-bit float, grayscale and RGB(A) images, which are commonly used in bio-scientific imaging. Specifically, reading JPEG or CCITT compressed image data is not implemented. Only primary info records are read for STK, FluoView, and NIH image formats.

TIFF, the Tagged Image File Format, is under the control of Adobe Systems. BigTIFF allows for files greater than 4 GB. STK, LSM, FluoView, and OME-TIFF are custom extensions defined by MetaMorph, Carl Zeiss MicroImaging, Olympus, and the Open Microscopy Environment consortium respectively.

The API is not stable yet and might change between revisions. Tested on little-endian platforms only.

For command line usage run python tifffile.py --help

Authors

Christoph Gohlke, Laboratory for Fluorescence Dynamics, University of California, Irvine

Version

2012.04.21

Requirements

Acknowledgements

  • Egor Zindy, University of Manchester, for cz_lsm_scan_info specifics.

  • Wim Lewis, for a bug fix and some read_cz_lsm functions.

References

  1. TIFF 6.0 Specification and Supplements. Adobe Systems Incorporated. http://partners.adobe.com/public/developer/tiff/

  2. TIFF File Format FAQ. http://www.awaresystems.be/imaging/tiff/faq.html

  3. MetaMorph Stack (STK) Image File Format. http://support.meta.moleculardevices.com/docs/t10243.pdf

  4. File Format Description - LSM 5xx Release 2.0. http://ibb.gsf.de/homepage/karsten.rodenacker/IDL/Lsmfile.doc

  5. BioFormats. http://www.loci.wisc.edu/ome/formats.html

  6. The OME-TIFF format. http://www.openmicroscopy.org/site/support/file-formats/ome-tiff

Examples

>>> data = numpy.random.rand(301, 219)
>>> imsave('temp.tif', data)
>>> image = imread('temp.tif')
>>> assert numpy.all(image == data)

>>> tif = TIFFfile('test.tif')
>>> images = tif.asarray()
>>> image0 = tif[0].asarray()
>>> for page in tif:
...     for tag in page.tags.values():
...         t = tag.name, tag.value
...     image = page.asarray()
...     if page.is_rgb: pass
...     if page.is_palette:
...         t = page.color_map
...     if page.is_stk:
...         t = page.mm_uic_tags.number_planes
...     if page.is_lsm:
...         t = page.cz_lsm_info
>>> tif.close()
class PYME.contrib.gohlke.tifffile.TIFFfile(filename)

Bases: object

Read image and meta-data from TIFF, STK, LSM, and FluoView files.

TIFFfile instances must be closed using the close method.

Attributes
pageslist

All TIFFpages in file.

serieslist of Records(shape, dtype, axes, TIFFpages)

TIFF pages with compatible shapes and types.

All attributes are read-only.

Initialize instance from file.

asarray(key=None, series=None)

Return image data of multiple TIFF pages as numpy array.

By default the first image series is returned.

close()

Close open file handle(s).

fstat

Lazy object attribute whose value is computed on first access.

is_bigtiff

Lazy object attribute whose value is computed on first access.

is_fluoview

Lazy object attribute whose value is computed on first access.

is_lsm

Lazy object attribute whose value is computed on first access.

is_nih

Lazy object attribute whose value is computed on first access.

is_ome

Lazy object attribute whose value is computed on first access.

is_palette

Lazy object attribute whose value is computed on first access.

is_rgb

Lazy object attribute whose value is computed on first access.

is_stk

Lazy object attribute whose value is computed on first access.

series

Lazy object attribute whose value is computed on first access.

PYME.contrib.gohlke.tifffile.imread(filename, *args, **kwargs)

Return image data from TIFF file as numpy array.

The first image series is returned if no arguments are provided.

PYME.contrib.gohlke.tifffile.imsave(filename, data, photometric=None, planarconfig=None, resolution=None, description=None, software='tifffile.py', byteorder=None, bigtiff=False)

Write image data to TIFF file.

Image data are written uncompressed in one stripe per plane. Dimensions larger than 2 or 3 (depending on photometric mode and planar configuration) are flattened and saved as separate pages.

PYME.contrib.gohlke.tifffile.imshow(data, title=None, vmin=0, vmax=None, cmap=None, bitspersample=None, photometric='rgb', interpolation='nearest', dpi=96, figure=None, subplot=111, maxdim=4096, **kwargs)

Plot n-dimensional images using matplotlib.pyplot.

Return figure, subplot and plot axis. Requires pyplot already imported from matplotlib import pyplot.