Rewrite reclustering (#340)

This large commit is a rewrite of reclustering, along with a variety of related 
fixes and changes:

* Add a new `taxonomy` module which includes the `ContigTaxonomy` previously
  stored in vambtools. Also include new types `PredictedTaxonomy` and `Taxonomy`
  to more clearly encapsulate the difference between the output of taxometer
  and that of e.g. mmseqs.
* Rewrite reclustering, such that it uses the `Markers` object, and parsemarkers
  integrates with reclustering better.
  The new version is more readable and extendable, is statically analyzable,
  and should be less brittle.
  It does not rely on the shell. 
* Remove dependency on pandas

Note that the changes in this commit has not been properly tested. That is
because following this commit, we will do a more thorough performance testing
of Vamb before release v5, and I expect that this process will cause a series
of fixes anyway.

.github/workflows/cli_vamb.yml

@@ -28,7 +28,7 @@ jobs:
         cache-dependency-path: '**/pyproject.toml'
     - name: Download fixtures
       run: |
-        wget https://www.dropbox.com/scl/fi/xzc0tro7oe6tfm3igygpj/ci_data.zip\?rlkey\=xuv6b5eoynfryp4fba1kfp5jm\&st\=9oz24ych\&dl\=0 -O ci_data.zip
+        wget https://www.dropbox.com/scl/fi/xzc0tro7oe6tfm3igygpj/ci_data.zip\?rlkey\=xuv6b5eoynfryp4fba1kfp5jm\&st\=rjb1xccw\&dl\=0 -O ci_data.zip
         unzip -o ci_data.zip
     - name: Install dependencies
       run: |
@@ -61,6 +61,6 @@ jobs:
         cat outdir_taxometer/log.txt
     - name: Run k-means reclustering
       run: |
-        vamb recluster --outdir outdir_recluster --fasta catalogue_mock.fna.gz --abundance abundance_mock.npz --latent_path outdir_taxvamb/vaevae_latent.npz --clusters_path outdir_taxvamb/vaevae_clusters_split.tsv --hmmout_path markers_mock.hmmout --algorithm kmeans --minfasta 200000
+        vamb recluster --outdir outdir_recluster --fasta catalogue_mock.fna.gz --abundance abundance_mock.npz --latent_path outdir_taxvamb/vaevae_latent.npz --clusters_path outdir_taxvamb/vaevae_clusters_split.tsv --markers markers_mock.npz --algorithm kmeans --minfasta 200000
         ls -la outdir_recluster
         cat outdir_recluster/log.txt

pyproject.toml

@@ -8,7 +8,6 @@ dependencies = [
     "pycoverm == 0.6.0",
     "networkx == 3.2", # 3.3 drops Python 3.9 support
     "scikit-learn == 1.5.0",
-    "pandas == 2.2.0",
     "dadaptation == 3.2",
     "loguru == 0.7.2",
     "pyhmmer == 0.10.12",

test/data/marker.fna

@@ -0,0 +1,2 @@
+>abc
+GTGGTGAGTGCTTGGACGTGTGTGGTGATGCTCATGGTGTCTTCCCCCCTTCCCCGTGTTGTTACCACCCACTCTACCCGCTCACACTTTCGAATACAAGGGTATTTTTCGAAATGGAAAAGCTGTCGAGCACTCACATGTTCGACAGCTTCATATGTCCTTGAACTACGTAACTTTTTCCTTACAATCAGCGCAAAGTCCAAAGATTTCGGCCTCGTGACTACTGAGAGCAAAGCCGTTTTTAGTGGCAATTTCCTGTGCCCATGTCTCTACTGGACCGCCATCGATTTCGACTGTGTGACCGCAATTGGTGCAGACCAAGTGATGGTGGTGTCCCTCGTCGTGGCATTGGCGGTACAGAGTTTCTCCACCTGTGACGGTAAGTACGTCGACTGCCCTGATGTCCGCGAGGGATTGGAGGGTTCGGTAGACGGTTGTGAGGCCGACGTTGTGTTCCCTGGTGGATAGCTCGTGATGGATTTCTTTGGCGGAAGCGAAGTTATCGATTTCCTCAAGAACGTCAATTACGGCTTTTCGCTGTCTGGTGCTTCGCACTCCCAGCTTCGGGGCAGAGCCTTGGCTGATGCGATTGATACCCACCGTTGATCCTCCTCAATGACACAAAATGTACTTCGATAGTCTACCCAGATGTGTCAACCCCTGCGTTTAGTGCCAGGAGAAGTATGTCGAGGACGAGTGGTTCGGCAAGTGAATAAGTCATTTGCCGGCCTTGACGTTCTGCGTCGACGATACCTGCAGTTTTAAGGACTTTGAGGTGTTGGCTCACTAGTGGTTGCGAACTTTTTACTAGCTTGACCAATTCGTGGACGTAGTGGGGCCTTTCGTTGAGGGCGAGGATGATTTCGATTCTTAAGGGGGAATCTAGTGCCCTAATCAGCAGGCTGATCGCTTTGATGTTTTTTGCTGTTGCAAGTTTCTGAAGCTCAGCTGATGCTGTGGATTCGGACTCTTCTGCAGGGGTGACGAAATTCCGATTTGAGTGTTGAGCCACGGGGAAGTCCTTCCGTCCTTAGGCTAGGTCTGGAATGGATCTAGCACGCTTGCTATTTTACCTTCTATATAAACCTTTTATGAGGGAAATGAAAAAATAGTTATTAGAACTAGTTTACATCGCGAAGGCCGCAAAATGACGGGGTCAGCGGAAGCAACATCGTTAGTTGGGCTAGGATTGGTTGGGTATGTCCTAAAAGGGACGGTTATTTTTTCATTCGACGTGGAGGAGAGCATCCGACGTGGCTCAGCAATCGATCATCGACACCGTGGTTAACCTGTGTAAACGACGTGGACTGGTGTACCCCTGTGGTGAGATCTACGGCGGTACCCGCTCTGCGTGGGACTACGGCCCGCTGGGTGTGGAGCTGAAGGAAAACATCAAGCGCCAGTGGTGGCGTTCTATGGTTACTTCCCGCCCAGATGTTGTGGGTGTTGATACTTCTGTCATCCTTCCTCGCCAGGTGTGGGTAACTTCCGGCCACGTTGAGGTCTTCACTGACCCACTGGTTGAGTCTTTGAACACCCACAAGCGTTACCGTGCGGACCACCTGCTGGAGCAGTACGAAGAGAAGCATGGTCACCCACCTGTAAACGGCTTGGCTGACATCAACGATCCAGAGACCGGCCAGCCAGGTAACTGGACTGAGCCTAAGGCGTTCTCTGGTCTTCTGAAGACTTTCTTGGGACCTGTGGACGACGAAGAGGGTCTGCACTACCTGCGCCCTGAAACTGCTCAGGGTATCTTCGTGAACTTCAAGAACGTGATGAACACTTCACGCATGAAGCCACCTTTCGGTATCGCGAACATCGGTAAGTCTTTCCGTAACGAGATCACCCCAGGTAACTTCATTTTCCGTACTCGTGAGTTCGAGCAGATGGAGATGGAGTTCTTCGTCAAGCCTGGTGAGGACGAAGAGTGGCACCAGCACTGGATTGATACTCGCCTGCAGTGGTACATCAACCTGGGCATTAAGCCTGAGAACCTGCGTCTGTACGAGCACCCTCAGGAGAAGCTGTCTCACTACTCCAAGCGCACTGTTGATATTGAGTACGCATTCAACTTTGCTAACACCAAGTGGGGCGAGTTAGAGGGTATCGCGAACCGTACTGATTACGATCTTCGCGTGCACTCTGAGGGCTCTGGTGAGGACCTGTCATTCTTCGATCAGGAGACCAATGAGCGTTGGATTCCTTTCGTAATCGAGCCTGCTGCAGGTCTTGGTCGCGCAATGATGATGTTCCTGATGGATGCTTATCACGAGGACGAGGCACCAAACTCAAAGGGTGGCGTCGATAAGCGTGTTGTTCTGAAGCTTGACCGTCGCCTTGCGCCGGTTAAGGTTGCGGTCTTGCCGCTGTCAAAGAAGGACACTTTGACGCCTTTGGCGGAAAAGCTCGCAGCAGAGCTGCGTGAATTCTGGAACGTTGATTACGACACTTCAGGTGCGATTGGTCGCCGTTACCGTCGTCAGGACGAGATCGGTACTCCATTCTGCGTCACCGTTGACTTTGATTCTCTCGAGGACAACGCTGTGACCGTGCGTGAGCGCGACACCATGGAGCAGGTTCGTGTTCCACTTGATGAGCTGCAGGGTTACTTGGCTCAGCGCCTCATCGGCTGCTAAACGGCAACCAATAGAGCGATAATTCGCTAAGACGAATGTAATCGCAGCAACATATAGCACCGGCTTAACAGGCCGGTGCTATTCTGTTCGCATGACTTCGAAGGATCTGATTGTGACCTCCTATACGTCTTGGGGCAAGCGTTTCAAGAATGACGGGAAGCTTTTTATTAACCTACTTCGCAGCACCACTGATAGTGCTGATGAAAAGGTTTTAGCCACTTTCGGTGAAGTTCCCAGCAAATCATTTGAAACCACCGCAACGGTTGATGAGCAGCAGTGGGAACTGTCCTTCAATATTGATGGAACGGCAACTGCCAAGCTTCCTGATGGTCGTGTGTTCAGCGCGAATGCAGGTGAGAAGACCTTTACCAAGTCCAAGCGGATTGAAATCGACATGGACGGCACCGCGATGGCTGCTGTTAATGAAGATAAAAACAATTGGATTATCGACGATTCTGAAGAGAATAAAGTCGCTCAGTTTACCGGTATGAACAACGGTGTGCGTCGCGCGATTGTGGAGTTTGAGCCTGACGTAGAAGTCACCCAGGAGCAGGAAATTTTCTTGTCGTGGGTTGCTCGGAAAACTCTGGAATCCCGCATGTTGGGCTCCAGTTGGGGACTGACTCTGTTTTTGATCATTTTGACGCCAATCATTATTTTTCTCACTTTCAGCTAAAAGGACCATGCAATGGTAGACGCTCAGCGCCCCAAAGCAGGCATCTTCGGTAGCCACACAGAAGAAACATGGGTGTGGCTCGGTAATGAACTTTTCGACGAGTCCGGCGAGGTCATCGCCGACGTTCGCTCCGACGTCCTCTACGTGGATCGCGAACGACTACTCATCGAATCCACCCCCGGCACCATGCGTTTTCGTTGCCGCGCAACACTGTCCGGGGGTGAGGTCTATACAATGACTCAGAATTCTTTCACTGTGGGGGATCTCACTGCGGTGTGCGGGCGCCGGACGTATTCGCTAAAAAGGGTGTCGCCGTGGCGTAAAGAACGCCTGATCACCAACAATGGGGTGGAAGTGGCGCGACTTCGCCCGATGACCAGCGGTAAAGTCGAATTCATTGTGGGCACCGCGGACAGCGAGGCGTTGCCGTTCGTCGACGCAGTATTTTTGAGCTGGGCGTGCGTCCTGGTGGATTCGGCCGTGCGCCGGCCGAAAATTTAAAAGCTTTTTGCTTATCGACGCACCCCTCCACCTGTTTTTTGTAGCCGGGGGATCATTTCCTTTGAAGGATCCAATCTCCGCACTTAGTTTCCTTCGGTGTGAAGGAAAGAGTTCCGTAAAGACCTCTATCTCATTTAAAGAAGTGGAGGATTAGGGTCGTTGACTCGCCTTCGGCACTAATTTGAGCCAAGTTCAAGTTTGCTGCCATCCCAGGTGACCGAAAATGTCCTATGCGAGGTCTCTTCGGTCACTTGGTTTTGCTCGTTTCAGGCTAGAAGCGGCCTCCGCGGAACCCTCCTCCGCCACCGCCACCACCGCTGAAGCCGCCACCGCCTCCACCGAAGCCTCCACCGAAACCGCCACCGCGGCCGCTGTTGAGAATCGAGTTGATCACCATGCCGGTGACAATCGCACCGGTGGTTCCGCCACCGGAATTGTGGCGATTGTTGTAGGTGGTGATGTCGTTTTGTGCTGACTTGCTGGCGCGTTGGGCTGCGACTGCTGCTTGACGTCCGTAATCAATTCCTGCACGGGTGTCGCGGGTGCGGTTTTGTTGTGCCATGGCGTACAGTTTTTGTGCGTTGGCCAGGTGGGTGCGGGCTTCGGATTTTACGATGCGACCGCGGGTGGAGATGAGGTCTTCGGCCTTTTGGATTTGGCTTCTTGCAGATTGCAGCTGTTGGTCGAATACGCGTAGCTGGCGGGCTTGATCAGCTGCGGTGGCGCGAAGTGTGTCAAGTTGAGTGTCGAGGGCGGAGTCGACATCGACAAGTTCTGTGTAGGTTCCGAGCGGATCCTTTTCGGCGTCTGCTGATGCGGTGGTTAGTGCTGCGCTGGCTGCGCGGACAGCATCGTCGAGGGAGGCCCAGTCGGCACGGGCACCGTCGGCTCCTGCGCTTTGTTTGAGTTGGCCGGCTTCGTTGATTTCGTCTGAGATTTCTTGAATCAGATCGGCAACGTTTGCTTTGGCTGTGGAGATGTTTTCATCGGCATGCTCGACGCCCTCGAGGAGTTTGTCTGCGGTAGTGATGGCGTGCTCGATGTGACGGATCGCGTCGATAAGCCCGCCCTGCTCGCCTGCGGGCATGGACTCTATCTTGTACGCCTGTGGCAGGACTTCTTCTGCTTCGTCGAGCGAAGCGCTGGCGAGGTCGACGTTGTCGTCGATGCTTTCAAGGACCTCTGCTGAGTAGCGAGCGCGCAGGCCAGCGAGTGTTTCTTGAGCCTTGGGGAGGCGGGTGCGCAGGTCGACGGATTTTTGGGTGAGAGCATCCAATTTGCTGCCCGCGTTGATCAGCAGGTTGCGCATATCGGCAAAGTTTTGGGCCTCGGCGTCGAGGGCATCGTCGGCTTGGCCACAGGATGAAATGATTTCTACCAGCATGGATCGACGTTCGGCTTCGGATTCTGGGATAGAATCGTTGAGGCGCTGCTGAATCTCAAAGGCTTTTTGCAGGGTGCCGGTGGAGTGGTTCATGGCGCGGTTGAAGCTGCGGGTGCGCTCTGGTCCGAACTCGGAGGTAGCGATAGCGAGCTCTTCTTTTCCGCGACGGATGGAGTCATCAGTGGAGGTGAGCTCTTCTTGGGCAAGGTGTTCGAGAGTTTCCATGGGAAGCTGCATGAGGCGGTTGGTATCGCGAGGGTCGATCTCACGTGCATCTTCCAAGGTTGCAGCACTTGTTTTCTTCTTGCGGCTGCGGGAATAGGCCCAAATTCCGCCACCAGCGGCCACTGTGCCAACGCCCGCAGCAGCCAACCAAGCGCCGGAAGATCCAGAAGAGCCTGAGGTTCCTGAGGCACCAGAACTAGAACCAACTGATTCTGCCAGCGCTAGTGCGGAGCCTGCCCAATCTTCTTGGGAAAGCGCCTGGAAAGCAGCGTTGTTGGCGGCGTCGAGTTCAGCGTCGGTCCATTGAGTACCACCTTGGATGCCGTACTGCCGTTCCTCGGGAGCGAGTGCATAAACCAAGACGTTTCCGCCGCCGTTGGCTTGGAGTGCTTGCTGCGTCCACGTTTCAGGGTCAACTCCGTCGAAAGAGCTTAGGAAAACAACGAAAATAACCTTTTGTTCAGATGCCTTTACATCATCGATGGCAGCCTGAATGTTGGTGATATCGGACGAGGAAATCTGGCCGGTGTAGTCAGTGACATTGTCTTGGTAAAATTCTGGTGATTCAGCCAAGACATATGTTTCTGTGGCTTCTGCAGTGTGAGCAGTAAAAAATGGTCCACTGATAAGGAGCGCGCCAGCTCCAATTGCCACAGTGACCGATACACGGCGGACGTTTTCCCGAAGATGCACCAAACTAAAGTTCATGGTCCCCACCTTAGACGAGTCCAGCTGGCACACTAGTTAACGTGAGAAGATTTTTAGCCAAGAGTTTACTCTTAACCGCAGTAGCGCAACCAGCCCTGAGGGTGGTCGCGTATTCGATGCTCAGAACGCCTAATAATCGGCACAAAATTGATTCAATTTTGGTGTTGGGCACAGCTCAATATGATGGGGTTCCATCGAGGCAGTTTGCTGCTCGTTTGAGGCATGCCGCGAAGCTGTGGCGTCTTCATGAAATCCAGCATGTATATACTGTCGGCGGAAAACTTCCTGGTGATCGTTTCACCGAAGCAGAAGTCGCGCGGGAGTATTTGATCAAAGAGGGCGTGGATCCGGATCTGATTTTTGTCTCTGCAGTTGGCAATGACACTGTCTCCTCCTATGAGGCGCTTGATCCGGAAAAGCTTGGTCGGGTGCTGATTGTTACTGATCCGAACCATTCGTATCGGGCGGTGCGCATCGCGCGACGCATGGGCTTTGACGCGAAACCTTCCCCGACAACCTATAGTCCCGCGAAGTTTCCGTCGATAGTTTATTTTCTGACCTTGTCCCATGAGTGGGGCGGGGTAGTGGTACAGGACGTGTCGTGGCTCTTGGGCGAACGGGTGGCCGATAAGGTGGAAGCATCTTTGCGAACTATCCAAGGCCTGCTGCGCCCTTCGAGGCGTGCGCGCCATGAGCAACTTCGGAGGCTGAAAAAGTAGATGTACCCCTATTCCGACGCAGACGCTTTTCGACGCCACCCTGAGCGCGCCAAGTCCAGCCAACTGCGCACCAGCGCCGTAGACACCCGCAGCGCGTTCGCCCGCGACCGGGCTCGCGTGCTGCATTCTGCTGCTCTTCGACGCCTCGCGGATAAAACCCAAGTGGTTGGCCCCAATGATGGTGATACTCCGCGCACCCGGCTGACGCACTCTTTGGAAGTAGCTCAAATTGCACGGGGAATCGGAGCTGGACTGGATTTGGATCCTGATCTGTGCGATCTGGCAGGGCTGTGCCATGACATTGGGCATCCGCCGTATGGACACAACGGTGAAAACGCGTTGAATGAAGTTGCTGCGGCCTGTGGAGGATTTGAGGGCAACGCCCAAACCTTGCGTATTCTCACGCGGCTGGAGCCAAAAATTGTCTCTGATGAGGGGGAGAGCTTTGGGCTGAACTTGTCGCGGGCTGCTCTTGATGCTGCATGTAAGTATCCGTGGGCTAAAACAAATGCGGATGGCAGTGTCAATAAGAAATACAGTGCTTATGATGAGGACGCAGAAATTCTTGCTTGGATCAGGCAAGGCCATGAAGACCTCAGACCACCAATCGAAGCTCAGGTCATGGACTTTTCCGATGATATTGCCTACTCAGTACACGATGTAGAAGACGGCATTGTTTCCGGTCGCATCGATTTGAAAGTGCTGTGGGACCTGGTGGAATTAGCAGCACTGGCGGACAAAGGCGCAGCAGCTTTCGGAGGCTCGCCTGCAGAACTCATCGAGGGCGCAGCCTCGTTGCGGGAGCTTCCTGTGGTAGCGGCCGCTGCAGATTTTGATTTCTCACTGCGTTCCTACGCTGCGCTGAAGGCCATGACCTCAGAACTAGTGGGAAGATACGTTGGCTCTACCATCGAGTCAACAAAGAAAACACACGCCGGCATTGATGTGGGACGCATGCACGGCGATTTGATCATTCCAGAAACAGCGGCCAGTGAAGTAAAACTGCTCAAAACGTTAGCGGTTCTCTATGTGATGGATGACCCAGGGCACCTTGCGCGCCAAAACAGGCAACGGGATCGTATCTTCCGGGTTTTTGACTACCTGGTGCTGGGGGCTCCGGGATCGTTGGATCCGATGTATCGCCAGTGGTTTATTGAAGCGGATTCAGAATCGGAACAGATCCGTGTGATTGTTGATCAGATTGCGTCGATGACGGAGTCTCGTCTGGAACGCCTTGCCCGGAATGCTGCTGACATCTCAGGATTCTTGGGATAGTTGGTTAGAGCAGCAGCGATTTTTAGTAAGGCCAATAACATGTTTTGGCTTAAACCTGTGTCGTGTCAGATGGTGGCGAAGTAGAGTTCGCAAAGCTAGCGAACATGAATTCGTGTTCAGGAACTTAACAGGGATCAAACAGAGAACAGAGAACAGATCACGCTGCCCAAAAATCGCACTTTTAAGGTTTGTGGGCGTCTGTGTGTGGTTTGCCGCTGTAAAGTATCACCACGTTATGCGCCCTGGTGTGATCAAGCGTTCGTTCTGGGTCGAAACCCCAAAAGTCACAATTCCCCAGAAGCGGGTCAAACCCATTTAGCTTATTGCTTACATATCGAGGGTTTAGAAAAGTGATTTGTCGGATCAGTCGGTTTCTGCCAAGTAAATAGAACTTTATAAATTTTGTGGCTCTCAAATCTTAGGCCACGGCTTCCGATTTGAACCGGAGGTTCAAAAGGCTTATATAGACAAGATTCTGCATCGTCTCACGAGCCCCTCATTGCCTGACACGGTCAATCGTGTGGGAGGTACCAATCCGTGAGATTTCTGCCAACGAGCGATTCATTGGCCCCGCTGCAGAGCTGGCAGAACACGGACATAACCCAAATAATCTGAGGTCTGCCGTTTGCAGCAGCATTAGCGTTTGATGTGGAAGGTGATGCAGAGGCTGTTGATCTGCAAGCGCGTCTTTCCCAAGCACGGGGGAACCCTGAAGCATCGGATGCTCTAGTTGCTGAGCTGACTGGTGTTACTGCTAATCATCCGTTGGTCAGTGCTTGTCTGAAGTTTCCGCTCAATCCTAAGCTTCTCAAGATTTCGTAAAAAAGCTGCCAACTACCGTAAAACCGCACTACTAGAGGAGTGCGTTTTTCGTTCCTGAACACATTGCGTGCTGCAACTTAATTATGGTCCTCCCAGCTCAGTGTGCTGTGTGGATTGTTTATTCTCGTCCATTAAGTGATCGAGAAAAAGTTGTTGTAAAGTCATGCGCATGTGTGGAATTGTTGGATATATTGGCCAGGCGGGCGACTCCCGTGATTACTTTGCGCTTGACGTCGTTTTAGAAGGACTGCGCCGACTTGAATACCGCGGTTATGATTCCGCAGGTGTAGCTGTTCATGCGAACGGTGAAATCAGCTACCGAAAGAAGGCTGGAAAGGTAGCTGCGCTGGACGCTGAGATCGCTCGCGCTCCTTTGGCGGATTCCATTTTGGCTATTGGTCACACCCGGTGGGCAACTCACGGTGGACCAACCGATGCAAATGCACACCCCCATGTTGTTGATGGCGGCAAGTTAGCTGTCGTACACAACGGTATTATTGAAAACTTTGCAGAGCTGCGCGCAGAGCTTTCAGCTAAGGGCTACAACTTTGTTTCCGTTACTGACACTGAAGTTGCCGCCACATTGCTGGCAGAAATCTACAACACCCAGGCTAATGGCGATCTGACCAAGGCTATGCAGCTTACTGGTCAGCGTCTTGAGGGTGCGTTCACCCTGCTGGCTATCCATGCTGATCATGATGATCGTATTGTTGCAGCGCGCCGTAACTCTCCTTTGGTTATTGGCTTGGGTGAAGGCGAAAACTTCCTCGGCTCTGACGTTTCTGGCTTCATCGATTACACCCGCAAGGCTGTTGAGATGGGCAACGATCAGATTGTGACCATCACTGCGAACGACTACCAGATCACCAACTTCGATGGTTCTGAGGCAACCGGAAAACCTTTCGACGTGGAGTGGGATGCGGCTGCTGCTGAAAAGGGTGGCTTTGATTCCTTCATGGATAAGGAAATCCACGACCAGCCAGCTGCAGTGCGTGACACCCTCCTCGGACGTTTAGATGAGGATGGCAAGCTGGTCCTTGATGAGCTTCGT

test/test_parsemarkers.py

@@ -0,0 +1,37 @@
+import unittest
+import vamb
+import testtools
+from pathlib import Path
+import tempfile
+import shutil
+import io
+
+
+class TestParseMarkers(unittest.TestCase):
+    def test_instantiate(self):
+        tmp = tempfile.mkdtemp()
+        tmp_path = Path(tmp)
+        shutil.rmtree(tmp)
+        markers = vamb.parsemarkers.Markers.from_files(
+            Path(testtools.DATADIR).joinpath("marker.fna"),
+            Path(testtools.PARENTDIR).joinpath("vamb").joinpath("marker.hmm"),
+            ["abc"],
+            tmp_path,
+            4,
+            None,
+        )
+        self.assertIsNotNone(markers.markers[0])
+        self.assertEqual(len(markers.markers), 1)
+        self.assertEqual(set(markers.markers[0]), {39})
+        self.assertEqual(
+            markers.refhash, vamb.vambtools.RefHasher.hash_refnames(["abc"])
+        )
+
+        buf = io.StringIO()
+        markers.save(buf)
+        buf.seek(0)
+
+        markers2 = vamb.parsemarkers.Markers.load(buf, markers.refhash)
+        self.assertEqual(len(markers.markers), len(markers2.markers))
+        self.assertEqual(set(markers.markers[0]), set(markers2.markers[0]))
+        self.assertEqual(markers.marker_names, markers2.marker_names)

test/test_reclustering.py

@@ -1,8 +1,5 @@
 import unittest
 
-# Invariants:
-# It produces disjoint clusters, a subset of the input points
-
 # For CAMI dataset, compute comp, abundance, taxonomy, markers
 # Subset to e.g. 5 genera plus a few unclassified contigs
 
@@ -22,3 +19,8 @@ class TestKmeansReclustering(unittest.TestCase):
     # Create latent
 
     # Initial clustering
+
+
+class TestDBScanReclustering(unittest.TestCase):
+    # It produces disjoint clusters, a subset of the input points
+    pass

test/test_semisupervised_encode.py

@@ -31,14 +31,14 @@ def make_random_annotation(self):
         phylum = np.random.choice(self.phyla, 1)[0]
         clas = np.random.choice(self.classes[phylum], 1)[0]
         if np.random.random() <= 0.2:
-            return vamb.vambtools.ContigTaxonomy.from_semicolon_sep(
+            return vamb.taxonomy.ContigTaxonomy.from_semicolon_sep(
                 ";".join([self.domain])
             )
         if 0.2 < np.random.random() <= 0.5:
-            return vamb.vambtools.ContigTaxonomy.from_semicolon_sep(
+            return vamb.taxonomy.ContigTaxonomy.from_semicolon_sep(
                 ";".join([self.domain, phylum])
             )
-        return vamb.vambtools.ContigTaxonomy.from_semicolon_sep(
+        return vamb.taxonomy.ContigTaxonomy.from_semicolon_sep(
             ";".join([self.domain, phylum, clas])
         )
 

vamb/__init__.py

@@ -16,6 +16,7 @@
 from . import parsebam
 from . import parsecontigs
 from . import parsemarkers
+from . import taxonomy
 from . import cluster
 from . import encode
 from . import aamb_encode
@@ -35,6 +36,7 @@
     "parsebam",
     "parsecontigs",
     "parsemarkers",
+    "taxonomy",
     "cluster",
     "encode",
     "aamb_encode",