aicsimageio 3.0.7

Python library for reading and writing image data with special handlers for bio-formats from Allen Institute for Cell Science.

AICSImageIO

A Python library for reading and writing image data with specific support for handling bio-formats.

---

Features

• Supports reading metadata and imaging data from file path or buffered bytes for:
  • CZI
  • OME-TIFF
  • TIFF
  • Any additional format supported by imageio
• Supports writing metadata and imaging data for:
  • OME-TIFF
  • TIFF
  • Any additional format supported by imageio

Disclaimer:

This package is under heavy revision in preparation for version 3.0.0 release. The quick start below is representative of how to interact with the package under 3.0.0 and not under the current stable release.

Quick Start

from aicsimageio import AICSImage, imread

# For numpy array of image data
im = imread("/path/to/your/file_or_buffer.ome.tiff")

# For AICSImage object that
with AICSImage("/path/to/your/file_or_buffer.ome.tiff") as im:
    # use im object

# To specify a known dimension order
with AICSImage("/path/to/your/file_or_buffer.ome.tiff", known_dims="SYX") as im:
    # use im object

# if you instantiate an AICSImage:
im = AICSImage("/path/to/your/file_or_buffer.ome.tiff")
# you should close it when done:
im.close()

# Image data is stored in `data` attribute
im.data  # returns the image data numpy array

# Image dimension sizes can be obtained via properties:
im.size_z  # returns the size of the Z dimension. X,Y,Z,C,T, and S supported.

# Image dimensions can also be obtained as a tuple in two ways:
im.size("ZYX")  # returns a tuple containing the Z, Y, and X sizes only
im.get_image_data(out_orientation="ZYX").shape  # returns same as above

# Image metadata is stored in `metadata` attribute
im.metadata  # returns whichever metadata parser best suits the file format

# Subsets or transposes of the image data can be requested:
im.get_image_data(out_orientation="ZYX")  # returns a 3d data block containing only the ZYX dimensions

Notes

• Image data numpy arrays are always returned as six dimensional in dimension order STCZYX or Scene, Time, Channel, Z, Y, and X.
• Each file format may use a different metadata parser it is dependent on the reader's implementation.

Installation

Stable Release: pip install aicsimageio
Development Head: pip install git+https://github.com/AllenCellModeling/aicsimageio.git

Documentation

For full package documentation please visit allencellmodeling.github.io/aicsimageio.

Development

See CONTRIBUTING.md for information related to developing the code.

Free software: BSD-3-Clause