ImageD11 is a python code for identifying individual grains in spotty area detector X-ray diffraction images.
Version 2.0.2, Jon Wright, wright@esrf.fr
This is the source code for ImageD11. Probably you wanted a compiled version.
If your pip is up-to-date, you can try to install it like this:
```
python -m pip install --upgrade pip setuptools
python -m pip install ImageD11
```
If you want to use an existing numpy installation add a `--no-build-isolation` flag.
To get all the possible dependencies too, you can try:
`python -m pip install ImageD11[full]`
Some (dated) documentation is here: https://imaged11.readthedocs.io/
If you are at ESRF on an old linux computer you can try "module load fable".
To use from git, try this:
- Download and install python 3.8+, perhaps from www.python.org but probably from conda.
- Preload binary packages from conda (or your system package manager):
numpy, scipy, matplotlib, h5py, pillow, pycifrw, xfab, pyqt, pillow, silx[full] etc
- `pip install git+https://github.com/FABLE-3DXRD/ImageD11.git`
If you want to work with the sources then you can try like this:
```
$ python -m pip install --upgrade pip
$ git clone https://github.com/FABLE-3DXRD/ImageD11.git && cd ImageD11
$ python -m pip install --editable .
```
If you want multiple binaries in your home (on recent pythons) you can do and get the compiled code
for each platform in .so files that are labelled by platform. This is potentially useful for a
heterogenous cluster (like at ESRF):
```
# on ppc64le:
python3 -m pip install dist/ImageD11-1.9.8-cp38-cp38-linux_ppc64le.whl --user --ignore-installed
# on x86_64:
python3 -m pip install dist/ImageD11-1.9.8-cp38-cp38-linux_x86_64.whl --user --ignore-installed
# etc
# ~/.local/lib/python3.8/site-packages/ImageD11 % ls *.so
_cImageD11.cpython-38-powerpc64le-linux-gnu.so _cImageD11.cpython-38-x86_64-linux-gnu.so
```
After it is installed, you should find a script ImageD11_gui.py, somewhere in your path.
Until 2017 this code was mostly developed on sourceforge at http://sourceforge.net/projects/fable/
It is now developed at http://github.com/FABLE-3DXRD/ImageD11
Bug reports are always welcome!
Good luck!
## CI Status
[![Flake, Build and PyTest](https://github.com/FABLE-3DXRD/ImageD11/actions/workflows/build_flake_pytest_ubuntu2004.yml/badge.svg)](https://github.com/FABLE-3DXRD/ImageD11/actions/workflows/build_flake_pytest_ubuntu2004.yml)
<!--
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Linux: [![CircleCI](https://circleci.com/gh/jonwright/ImageD11.svg?style=svg)](https://circleci.com/gh/jonwright/ImageD11)
Macos + Linux [![Build Status](https://travis-ci.com/jonwright/ImageD11.svg?branch=master)](https://travis-ci.com/jonwright/ImageD11)
-->
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"description": "\n\nImageD11 is a python code for identifying individual grains in spotty area detector X-ray diffraction images.\n\nVersion 2.0.2, Jon Wright, wright@esrf.fr\n\nThis is the source code for ImageD11. Probably you wanted a compiled version.\n\nIf your pip is up-to-date, you can try to install it like this:\n```\n python -m pip install --upgrade pip setuptools\n python -m pip install ImageD11\n```\nIf you want to use an existing numpy installation add a `--no-build-isolation` flag.\n\nTo get all the possible dependencies too, you can try:\n `python -m pip install ImageD11[full]`\n\nSome (dated) documentation is here: https://imaged11.readthedocs.io/\n\nIf you are at ESRF on an old linux computer you can try \"module load fable\". \n\nTo use from git, try this:\n\n - Download and install python 3.8+, perhaps from www.python.org but probably from conda.\n - Preload binary packages from conda (or your system package manager): \n numpy, scipy, matplotlib, h5py, pillow, pycifrw, xfab, pyqt, pillow, silx[full] etc\n - `pip install git+https://github.com/FABLE-3DXRD/ImageD11.git`\n \nIf you want to work with the sources then you can try like this:\n ```\n $ python -m pip install --upgrade pip\n $ git clone https://github.com/FABLE-3DXRD/ImageD11.git && cd ImageD11\n $ python -m pip install --editable .\n ```\n\nIf you want multiple binaries in your home (on recent pythons) you can do and get the compiled code\nfor each platform in .so files that are labelled by platform. This is potentially useful for a\nheterogenous cluster (like at ESRF): \n```\n # on ppc64le:\n python3 -m pip install dist/ImageD11-1.9.8-cp38-cp38-linux_ppc64le.whl --user --ignore-installed\n # on x86_64:\n python3 -m pip install dist/ImageD11-1.9.8-cp38-cp38-linux_x86_64.whl --user --ignore-installed\n # etc\n # ~/.local/lib/python3.8/site-packages/ImageD11 % ls *.so\n _cImageD11.cpython-38-powerpc64le-linux-gnu.so _cImageD11.cpython-38-x86_64-linux-gnu.so\n```\n\nAfter it is installed, you should find a script ImageD11_gui.py, somewhere in your path.\n\nUntil 2017 this code was mostly developed on sourceforge at http://sourceforge.net/projects/fable/ \n\nIt is now developed at http://github.com/FABLE-3DXRD/ImageD11 \n\nBug reports are always welcome!\n\nGood luck!\n\n## CI Status\n\n[![Flake, Build and PyTest](https://github.com/FABLE-3DXRD/ImageD11/actions/workflows/build_flake_pytest_ubuntu2004.yml/badge.svg)](https://github.com/FABLE-3DXRD/ImageD11/actions/workflows/build_flake_pytest_ubuntu2004.yml)\n\n<!--\n\nWindows: [![Build status](https://ci.appveyor.com/api/projects/status/4pdlvsj2grtk0hel?svg=true)](https://ci.appveyor.com/project/jonwright/imaged11)\n\nLinux: [![CircleCI](https://circleci.com/gh/jonwright/ImageD11.svg?style=svg)](https://circleci.com/gh/jonwright/ImageD11)\n\nMacos + Linux [![Build Status](https://travis-ci.com/jonwright/ImageD11.svg?branch=master)](https://travis-ci.com/jonwright/ImageD11)\n\n-->\n",
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