auromat 1.0.8

Description:

auromat 1.0.8

Installation under Linux
The following assumes Ubuntu, but should be similar for other distributions.
Before installing auromat, some system libraries have to be installed.
sudo apt-get install libraw-dev liblensfun-dev libgeos-dev
If you want to use THEMIS data or export in CDF format you have to
install NASA’s CDF library:
wget http://cdaweb.gsfc.nasa.gov/pub/software/cdf/dist/cdf35_0_2/linux/cdf35_0-dist-cdf.tar.gz
tar xf cdf35_0-dist-cdf.tar.gz
cd cdf35_0-dist
make OS=linux ENV=gnu all
sudo make INSTALLDIR=/usr/local/cdf install
cd ..
Also, for using the CDF library in Python we need the spacepy library.
As this is not yet released on PyPI, you have to install it manually using:
sudo apt-get install libhdf5-serial-dev
pip install --user numpy python-dateutil
pip install --user git+http://git.code.sf.net/p/spacepy/code
If you want to export in netCDF format:
sudo apt-get install libnetcdf-dev libhdf5-serial-dev
If you want to draw any kind of geographic maps, install the basemap library with:
pip install --user --allow-external basemap --allow-unverified basemap basemap
Now, install auromat with:
pip install --user auromat[cdf,netcdf]
Support for CDF or netCDF can be left out using auromat[cdf] or auromat[netcdf], respectively.
The command-line tools are installed in ~/.local/bin. For convenience you should add this folder
to your PATH if that is not the case already:
export PATH=$HOME/.local/bin:$PATH


Installation under Mac OS X
First, install Homebrew if you don’t have it yet:
ruby -e "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/master/install)"
brew update
Then, install Python 3 with Homebrew:
brew install python3
If you want to use THEMIS data or export in CDF format you have to
install NASA’s CDF library:
curl -O http://cdaweb.gsfc.nasa.gov/pub/software/cdf/dist/cdf35_0_2/linux/cdf35_0-dist-cdf.tar.gz
tar xf cdf35_0-dist-cdf.tar.gz
cd cdf35_0-dist
make OS=macosx ENV=gnu all
sudo make INSTALLDIR=/Applications/cdf install
cd ..
Also, for using the CDF library in Python we need the spacepy library.
As this is not yet released on PyPI, you have to install it manually using:
pip3 install numpy python-dateutil
pip3 install git+http://git.code.sf.net/p/spacepy/code
If you want to export in netCDF format:
brew tap homebrew/science
brew install netcdf hdf5
If you want to draw any kind of geographic maps, install the basemap library with:
brew install geos
pip3 install --allow-external basemap --allow-unverified basemap basemap
Now, install auromat with:
sudo pip3 install auromat[cdf,netcdf]
Support for CDF or netCDF can be left out using auromat[cdf] or auromat[netcdf], respectively.


Installation under Windows
If you need to use THEMIS data or export in CDF format, then you need to use
Python 2.7 for 32 bit. The Python library that is used for handling CDF files
(SpacePy) is currently only available for Python 2.6 and 2.7 for 32 bit.
For Python 3.3 and lower, you have to install the package manager pip,
see http://pip.readthedocs.org/en/latest/installing.html for instructions.
Some required Python packages (as of late 2014) don’t offer Windows binary
wheels on PyPI yet. Therefore, you have to install them manually:
Please install numpy, scipy, numexpr, scikit-image, astropy, and pyephem from
http://www.lfd.uci.edu/~gohlke/pythonlibs/.
If you want to draw any kind of geographic maps, please install the basemap library from:
http://www.lfd.uci.edu/~gohlke/pythonlibs/#basemap
If you want to use THEMIS data or export in CDF format you have to
install NASA’s CDF library (32 bit version), see http://cdf.gsfc.nasa.gov for details.
Also, for using the CDF library in Python you need the SpacePy library.
You can download an installer from
http://sourceforge.net/projects/spacepy/files/spacepy
If you want to export in netCDF format please install the netCDF4 library from:
http://www.lfd.uci.edu/~gohlke/pythonlibs/#netcdf4
Now, install auromat with:
pip install --user auromat[cdf,netcdf]
Support for CDF or netCDF can be left out using auromat[cdf] or auromat[netcdf], respectively.


Advanced functionality
The following software can be installed if you want to georeference images yourself
and not use the available data providers. Note that the complete workflow is not as
straight-forward for certain data sources, e.g. to correctly georeference ISS images
you have to consider inaccurate camera timestamps and possibly create missing lens distortion
profiles.
If you want to determine astrometric solutions yourself using the auromat.solving package,
you need to install astrometry.net, see http://astrometry.net/use.html. Make sure the
bin/ folder is in your PATH so that auromat can find it.
If you want to automatically mask the starfield of an image using the auromat.solving.masking
module, please install on Ubuntu:
sudo apt-get install libopencv-imgproc-dev python-opencv
on Mac OS X, please follow
http://jjyap.wordpress.com/2014/05/24/installing-opencv-2-4-9-on-mac-osx-with-python-support/
on Windows, install from http://www.lfd.uci.edu/~gohlke/pythonlibs/#opencv
If you want to correct lens distortion in an image with the lensfun database
using EXIF data extracted from the image, please install on Ubuntu:
sudo apt-get install libimage-exiftool-perl
on Mac OS X:
brew install exiftool
on Windows, extract the zip archive from http://www.sno.phy.queensu.ca/~phil/exiftool/
into a folder and put it in your PATH so that auromat can find exiftool.