Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

upgrading to 0.1.7 #212

Merged
merged 1 commit into from
Oct 7, 2024
Merged

upgrading to 0.1.7 #212

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
2 changes: 1 addition & 1 deletion CHANGELOG.md
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -1,6 +1,6 @@
# Change Log

## Version 0.1.7-dev
## Version 0.1.7 (10/7/2024)

### Added
- Formally adopted the NumPy + Numba solution in the ordinal mapper. This significantly accelerated the algorithm ([#209](https://github.com/qiyunzhu/woltka/pull/209)).
Expand Down
17 changes: 3 additions & 14 deletions doc/install.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -51,17 +51,6 @@ python setup.py install

Type `woltka` to check if installation is successful, in which case command-line help information will be displayed on the screen.

## Acceleration

Woltka has a [Numba](https://numba.pydata.org/)-accelerated version (the [numba](https://github.com/qiyunzhu/woltka/tree/numba) branch) in parallel to the main branch. In this version, the "coord-match" algorithm for functional analysis (see [details](ordinal.md)) is significantly faster and consumes less memory. To use this feature, install Woltka using the following commands instead:

```bash
conda install -c conda-forge numba biom-format
pip install git+https://github.com/qiyunzhu/woltka.git@numba
```

[**Note**] This feature only accelerates read-gene matching. It does not help with the analysis of microbiome structure.

## Upgrade

If you installed Woltka using Conda, do:
Expand Down Expand Up @@ -101,10 +90,10 @@ conda env remove -n woltka
If in the future some dependencies have changes that are not compatible with the current release of Woltka, the following "safe" commands can be used to install the current versions of dependencies.

```bash
conda create -n woltka python=3.12.2
conda create -n woltka python=3.12.7
conda activate woltka
conda install -c conda-forge biom-format=2.1.15
conda install -c bioconda woltka=0.1.6
conda install -c conda-forge numba=0.60.0 biom-format=2.1.16
conda install -c bioconda woltka=0.1.7
```

## Test
Expand Down
3 changes: 1 addition & 2 deletions doc/perform.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -52,8 +52,7 @@ _Functional analysis_
Simple read-gene matching | 4:08:53 | 7.745 GB
Simple read-gene matching, reporting RPK | 4:16:31 | 11.99 GB
Functional profiling at UniRef entry, then GO process | 4:24:49 | 14.92 GB
_Experimental_
Simple read-gene matching, with Numba [acceleration](install.md#acceleration) | 1:55:40 | 5.066 GB
Simple read-gene matching, with Numba acceleration (default since v0.1.7) | 1:55:40 | 5.066 GB


## Tips for efficient computing
Expand Down
2 changes: 1 addition & 1 deletion woltka/__init__.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -10,7 +10,7 @@

__name__ = 'woltka'
__description__ = 'versatile meta-omic data classifier'
__version__ = '0.1.6'
__version__ = '0.1.7'
__license__ = 'BSD-3-Clause'
__author__ = 'Qiyun Zhu'
__email__ = 'qiyunzhu@gmail.com'
Expand Down