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Merged
merged 5 commits into from
Nov 15, 2024
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DOC: Use new Model API in README #94

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7b86ed7
ENH: add jc distance app
rmcar17 Nov 15, 2024
e3bd16e
Merge branch 'iqtree:main' into main
rmcar17 Nov 15, 2024
dfc3ca2
ENH: allow `Model` to be imported from top level for easy Model const…
rmcar17 Nov 15, 2024
aad6e49
DOC: utilise new `Model` api in readme
rmcar17 Nov 15, 2024
45f9fe9
Merge branch 'iqtree:main' into readme
rmcar17 Nov 15, 2024
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8 changes: 4 additions & 4 deletions README.md
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Original file line number Diff line number Diff line change
Expand Up @@ -21,15 +21,15 @@ This project is still in early development, if you encounter any problems or hav

```python
from piqtree2 import build_tree
from piqtree2.model import DnaModel, Model
from piqtree2.model import Model
from cogent3 import load_aligned_seqs # Included with piqtree2!

# Load Sequences
aln = load_aligned_seqs("tests/data/example.fasta", moltype="dna")
aln = aln.take_seqs(["Human", "Chimpanzee", "Rhesus", "Mouse"])

# Reconstruct a phylogenetic tree with IQ-TREE!
tree = build_tree(aln, Model(DnaModel.JC), rand_seed=1) # Optionally specify a random seed.
tree = build_tree(aln, Model("JC"), rand_seed=1) # Optionally specify a random seed.

print("Tree topology:", tree) # A cogent3 tree object
print("Log-likelihood:", tree.params["lnL"])
Expand All @@ -43,7 +43,7 @@ print("Log-likelihood:", tree.params["lnL"])

```python
from piqtree2 import fit_tree
from piqtree2.model import DnaModel, Model
from piqtree2.model import Model
from cogent3 import load_aligned_seqs, make_tree # Included with piqtree2!

# Load Sequences
Expand All @@ -54,7 +54,7 @@ aln = aln.take_seqs(["Human", "Chimpanzee", "Rhesus", "Mouse"])
tree = make_tree("(Human, Chimpanzee, (Rhesus, Mouse));")

# Fit branch lengths with IQ-TREE!
tree = fit_tree(aln, tree, Model(DnaModel.JC), rand_seed=1) # Optionally specify a random seed.
tree = fit_tree(aln, tree, Model("JC"), rand_seed=1) # Optionally specify a random seed.

print("Tree with branch lengths:", tree) # A cogent3 tree object
print("Log-likelihood:", tree.params["lnL"])
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