# Chu-Liu-Edmonds Algorithm from TurpoParser.
This package wraps the Chu-Liu-Edmonds maximum spanning algorithm from
TurboParser for use within Python.
The original package was made by https://github.com/andersjo/dependency_decoding .
## Documentation
The package provides a function `chu_liu_edmonds`, which accepts an _N×N_ score
matrix as argument, where _N_ is the sentence length including the artificial
root node, which has index 0. The _(i,j)_-th cell is the score for the edge _j→i_.
In other words, a row gives the scores for the different heads of a dependent.
A `np.nan` cell value informs the algorithm to skip the edge.
Example usage:
```python
import numpy as np
from ufal.chu_liu_edmonds import chu_liu_edmonds
np.random.seed(42)
score_matrix = np.random.rand(3, 3)
heads, tree_score = chu_liu_edmonds(score_matrix)
print(heads, tree_score)
```
## Install
Binary wheels of the package are provided, just run
```
pip install ufal.chu_liu_edmonds
```
## Updating the Cython-generated Module
To update the Cython-generated module, run
```
cython --module-name ufal.chu_liu_edmonds._chu_liu_edmonds chu_liu_edmonds.pyx -o chu_liu_edmonds.cpp
```
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