Releases: b1quint/samfp-tools
Releases · b1quint/samfp-tools
Fixed Travis CI and tools for repeat, oversample and cut cubes.
I finished to apply the changes that you asked. The scripts that you want to run after installing the package are:
- fp_repeat
- fp_oversample
- fp_cut
- fp_roc (repeat-oversample-cut)
You can use the install.me
or the reinstall.me
scripts for installation within an Anaconda environment.
If you have an error with MatPlotLib, try to do conda install python.app
and then add alias python="pythonw"
to your ~/.bashrc file. You may have this problem if you are using MacOs and Anaconda.
Type fp_xxx --help
for details about how to run each script.
Updates on 3D Tools
This new pre-release contains the following updates.
- Travis CI is implemented for Python 2.7, Python 3.5 and Python 3.6 (Linux only).
fp_repeat
was updated in order to save the history as cards within the header.fp_oversample
was updated in order to follow Philippe's suggestion. It seems to be working now. Asfp_repeat
the cards in the header are properly saved.- Python 2 and Python 3 compatibility was increased by changing some parts of the code.
Updated log/version systems.
Now every script that is part of the samfp tools will carry the version of the package itself. Before, they were carrying only their own versions and it was difficult to track/update.
Fixed small bug on io.py
Main methods working and some combine tools
0.0.0 - Starting from old version. Some features may not be working. My
idea is to implement each of the scripts as a bin to be installed
using setup.py and the entry_points keyword.
0.1.0 - xjoin was released again. It is working and installed using
entry_points.
0.2.0 - mkcube can now be called as script again and it is installed using
pip.
0.3.0 - phmxtractor can now be called as script again and it is installed
using pip.
0.4.0 - phmfit can now be called as script again and it is installed using
pip.
0.4.1 - phmfit now stores fit parameters in the header.
0.5.0 - phmapply back to work.
0.6.0 - Add tools to combine Bias and Flats.