** Note from OHSU Fork
To install, clone the repo and run `pip3 install path/to/ashlar` while the
desired environment is active.
Requires python 3.7.5
**
ashlar [-h] [-o DIR] [-c [CHANNEL]]
[--output-channels [CHANNEL [CHANNEL ...]]] [-m SHIFT]
[--filter-sigma SIGMA] [-f FORMAT] [--pyramid]
[--tile-size PIXELS] [--ffp [FILE [FILE ...]]]
[--dfp [FILE [FILE ...]]] [--plates] [-q] [--version]
[FILE [FILE ...]]
Stitch and align one or more multi-series images
positional arguments:
FILE an image file to be processed (one file per cycle)
optional arguments:
-h, --help show this help message and exit
-o DIR, --output DIR write output image files to DIR; default is the
current directory
-c [CHANNEL], --align-channel [CHANNEL]
align images using channel number CHANNEL; numbering
starts at 0
--output-channels [CHANNEL [CHANNEL ...]]
output only channels listed in CHANNELS; numbering
starts at 0
-m SHIFT, --maximum-shift SHIFT
maximum allowed per-tile corrective shift in microns
--filter-sigma SIGMA width in pixels of Gaussian filter to apply to images
before alignment; default is 0 which disables
filtering
-f FORMAT, --filename-format FORMAT
use FORMAT to generate output filenames, with {cycle}
and {channel} as required placeholders for the cycle
and channel numbers; default is
cycle_{cycle}_channel_{channel}.tif
--pyramid write output as a single pyramidal TIFF
--tile-size PIXELS set tile width and height to PIXELS (pyramid output
only); default is 1024
--ffp [FILE [FILE ...]]
read flat field profile image from FILES; if specified
must be one common file for all cycles or one file for
each cycle
--dfp [FILE [FILE ...]]
read dark field profile image from FILES; if specified
must be one common file for all cycles or one file for
each cycle
--plates enable plate mode for HTS data
-q, --quiet suppress progress display
--version print version
On Linux, installation is fairly straightforward, but you must first install
your distribution's development package for libfftw3 and a JDK (any one of
versions 1.6, 1.7 or 1.8). You will also have to manually run pip install numpy
before pip install ashlar
due to a requirement of one of the required
packages.
On MacOS, obtaining and configuring the necessary native libraries can be a bit challenging. For users on those platforms, or for Linux users having trouble with the instructions above, the Anaconda Python distribution can simplify the process.
If you don't already have Anaconda, download it from https://www.anaconda.com/download/ and install. Then, run the following commands from a terminal:
conda install -q -y -c conda-forge pyfftw
pip install -q -U ashlar
The pyfftw dependency is not currently supported on Windows. We are currently
investigating a workaround. There is an experimental Docker image on DockerHub
at sorgerlab/ashlar
which should be suitable for many use cases.