Metadata-Version: 2.1
Name: xtiff
Version: 0.1.2
Summary: A tiny Python 3 library for writing multi-channel TIFF stacks
Home-page: https://github.com/BodenmillerGroup/xtiff
Author: Jonas Windhager
Author-email: jonas.windhager@uzh.ch
License: MIT
Project-URL: Source, https://github.com/BodenmillerGroup/xtiff
Project-URL: Tracker, https://github.com/BodenmillerGroup/xtiff/issues
Description: # xtiff
        
        A tiny Python 3 library for writing multi-channel TIFF stacks.
        
        The aim of this library is to provide an easy way to write multi-channel image stacks for external visualization and
        analysis. It acts as an interface to the popular [tifffile](https://www.lfd.uci.edu/~gohlke/) package and supports
        [xarray](http://xarray.pydata.org) DataArrays as well as [numpy](https://www.numpy.org)-compatible data structures.
        
        To maximize compatibility with third-party software, the images are written in standard-compliant fashion, with minimal
        metadata and in TZCYX channel order. In particular, a minimal subset of the OME-TIFF standard is supported, enabling the
        naming of channels.
        
        ## Installation
        
        Install from pypi:
        
        `pip install xtiff`
        
        
        ## Usage
        
        The package provides one single function:
        
        ```python3
        to_tiff(img, file, image_name=None, channel_names=None, image_date=None,
                write_mode=WriteMode.OME_TIFF, big_tiff=None, big_tiff_size_threshold=4294967246, 
                byte_order=None, compression_type=None, compression_level=0, pixel_size=None,
                pixel_depth=None, ome_schema_version=OMESchemaVersion.OME201606v2)
        ```
        
        Documentation of the function parameters is available via Python's internal help system: `help(xtiff.to_tiff)`
        
        ## FAQ
        
        _Why should I care about TIFF? I use Zarr/NetCDF/whatever._
        
        That's good! TIFF is an old and complex file format, has many disadvantages and is impractical for storing large images.
        However, it also remains one of the most widely used scientific image formats and is (at least partially) supported by
        many popular tools, such as ImageJ. With xtiff, you can continue to store your images in your favorite file format,
        while having the opportunity to easily convert them to a format that can be read by (almost) any tool if needed.
        
        _Why can't I use the tifffile package directly?_
        
        Of course you can! Christoph Gohlke's [tifffile](https://www.lfd.uci.edu/~gohlke/) package provides a very powerful and
        feature-complete interface for writing TIFF files and is the backend for xtiff. Essentially, the xtiff package is just a
        wrapper for tifffile. While you can in principle write any image directly with tifffile, in many cases, the flexibility
        of the TIFF format can be daunting. The xtiff package reduces the configuration burden and metadata to an essential
        minimum.
        
        ## Change log
        
        2019-12-12 v0.1.0 - Initial release
        
        ## License
        
        This project is licensed under the [MIT license](https://github.com/BodenmillerGroup/xtiff/blob/master/LICENSE.txt).
Keywords: xarray ome tiff
Platform: UNKNOWN
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Requires-Python: >=3
Description-Content-Type: text/markdown
