EcoPy provides tools for ecological data analyses. In general, it focuses on multivariate data analysis, which can be useful in any field, but with particular attention to those methods widely used in ecology. The homepage, with full documentation and examples, can be found here
Install via 'pip install ecopy'
- Ported to Python 3.11-3.14
- Removed dependency of C++ compiler
- EcoPy 0.2.0 is a compatibility-focused revival release. Further numerical and methodological auditing is ongoing.
- Fixed compatibility problems in functions cca(), simper(), and transform()
- Added Ochiai's binary coefficient to distance() function
- Added bioenv() function
- More Python 3.x compatibility
- Fix typos in code and examples on readthedocs. Thorough code check
EcoPy is distributed under the MIT license
0.2.0
- Modernized for current Python 3 and NumPy, SciPy, pandas, and matplotlib.
- Tested with Python 3.14.
- The isotonic-regression implementation now has a pure-Python/NumPy fallback, so installation does not require a C/C++ compiler.
- The original Cython implementation is retained as optional development code.
- Updated legacy Python 2/early Python 3 APIs and numerical compatibility issues.
- This release is intended as a compatibility-focused revival of EcoPy; further numerical and methodological auditing will continue in subsequent releases.
Transforming a site x species matrix, dividing by site totals:
import ecopy as ep
varespec = ep.load_data('varespec')
newMat = ep.transform(varespec, method='total', axis=1)
Calculating Bray-Curtis dissimilarities on the new matrix:
brayMat = ep.distance(newMat, method='bray')
PCA on US Arrests data:
USArrests = ep.load_data('USArrests')
prcomp = ep.pca(USArrests, scale = True)
prcomp.biplot(type = 'distance')
prcomp.biplot(type = 'correlation')
Full online documentation is a work in progress
- MINIMUM SPANNING TREE
- PROCRUSTES ROTATION
- LINEAR/SURFACE ENVIRONMENTAL FITTING
- MAXENT WRAPPER
- MANY MANY OTHER THINGS