mapu 0.1.0

A native Python port of the R vegan package for community ecology.

mapu

A native Python implementation of the classic R package vegan for community ecology.

This package aims to provide ecologists and data scientists using Python with rapid, pure-Python ports of popular vegan functions, including diversity indices, distance matrices (vegdist), ordination techniques, and multivariate statistical tests.

Installation

You can install mapu using pip:

pip install mapu

Or using uv for ultra-fast dependency resolution and installation:

uv pip install mapu

Development Installation

To install from source for development using uv:

git clone https://github.com/pedropablosilvaa/mapu.git
cd mapu
uv venv
source .venv/bin/activate  # On Unix/macOS
uv pip install -e ".[dev]"

Features

The library currently supports a wide array of functions mirroring R vegan:

• Diversity Analysis: diversity (Shannon, Simpson, etc.), fisher_alpha, specnumber, renyi, tsallis, rarefaction functions (rarefy, rrarefy), and species accumulation curves.
• Distance Matrices: vegdist (Bray-Curtis, Jaccard, Euclidean, Manhattan, Gower, etc.), designdist.
• Ordination: Unconstrained (PCoA/cmdscale, PCA, NMDS/metaMDS, isomap) and Constrained (rda, cca, capscale).
• Data Transformation: decostand, wisconsin.
• Statistical Tests: adonis (PERMANOVA), anosim, mantel, mrpp, simper, betadisper.
• Clustering: spantree, cascadeKM, cophenetic.

Example Usage

import numpy as np
import pandas as pd
from mapu import vegdist, metaMDS, diversity

# Create a mock species abundance matrix (sites x species)
np.random.seed(42)
community_data = pd.DataFrame(np.random.poisson(lam=2, size=(10, 20)))

# Calculate Bray-Curtis distance
bray_dist = vegdist(community_data, method="bray")

# Perform Non-metric Multidimensional Scaling (NMDS)
nmds_result = metaMDS(community_data, distance="bray", k=2)
print("Stress:", nmds_result.stress)

# Calculate Shannon diversity
shannon_h = diversity(community_data, index="shannon")
print("Shannon Diversity:\\n", shannon_h)

License

This project is licensed under the MIT License - see the LICENSE file for details.