Split contacts and fragments tests

tests/contacts_tests/test_contacts.py

@@ -7,7 +7,7 @@
 import numpy as np
 import dask.dataframe as dd
 
-from spoc import contacts, fragments
+from spoc import contacts
 
 # pytlint: disable=unused-import
 from ..fixtures.symmetry import (
@@ -16,16 +16,16 @@
 )
 
 
-@pytest.fixture
-def triplet_expander():
-    """expander for triplets"""
-    return fragments.FragmentExpander(number_fragments=3, contains_metadata=False)
+# @pytest.fixture
+# def triplet_expander():
+#     """expander for triplets"""
+#     return fragments.FragmentExpander(number_fragments=3, contains_metadata=False)
 
 
-@pytest.fixture
-def triplet_expander_labelled():
-    """expander for triplets"""
-    return fragments.FragmentExpander(number_fragments=3, contains_metadata=True)
+# @pytest.fixture
+# def triplet_expander_labelled():
+#     """expander for triplets"""
+#     return fragments.FragmentExpander(number_fragments=3, contains_metadata=True)
 
 
 @pytest.fixture
@@ -90,157 +90,6 @@ def unlabelled_df():
     )
 
 
-@pytest.fixture
-def labelled_fragments(labelled_df):
-    """labelled fragments"""
-    return fragments.Fragments(labelled_df)
-
-
-@pytest.fixture
-def labelled_fragments_dask(labelled_df):
-    """labelled fragments from a dask dataframe"""
-    return fragments.Fragments(dd.from_pandas(labelled_df, npartitions=1))
-
-
-@pytest.fixture
-def unlabelled_fragments(unlabelled_df):
-    """unlabelled fragments"""
-    return fragments.Fragments(unlabelled_df)
-
-
-@pytest.fixture
-def unlabelled_fragments_dask(unlabelled_df):
-    """unlabelled fragments from a dask dataframe"""
-    return fragments.Fragments(dd.from_pandas(unlabelled_df, npartitions=1))
-
-
-@pytest.mark.parametrize(
-    "fragments, expander",
-    [
-        ("labelled_fragments", "triplet_expander_labelled"),
-        ("labelled_fragments_dask", "triplet_expander_labelled"),
-        ("unlabelled_fragments", "triplet_expander"),
-        ("unlabelled_fragments_dask", "triplet_expander"),
-    ],
-)
-def test_expander_drops_reads_w_too_little_fragments(expander, fragments, request):
-    """Tests whether expander drops reads with too little fragments"""
-    triplet_expander = request.getfixturevalue(expander)
-    result = triplet_expander.expand(request.getfixturevalue(fragments)).data
-    if isinstance(result, dd.DataFrame):
-        result = result.compute()
-    assert len(set(result.read_name)) == 1
-    assert result.read_name[0] == "dummy"
-
-
-@pytest.mark.parametrize(
-    "fragments, expander",
-    [
-        ("labelled_fragments", "triplet_expander_labelled"),
-        ("labelled_fragments_dask", "triplet_expander_labelled"),
-        ("unlabelled_fragments", "triplet_expander"),
-        ("unlabelled_fragments_dask", "triplet_expander"),
-    ],
-)
-def test_expander_returns_correct_number_of_contacts(expander, fragments, request):
-    """Tests whether expander returns correct number of contacts"""
-    triplet_expander = request.getfixturevalue(expander)
-    result = triplet_expander.expand(request.getfixturevalue(fragments)).data
-    assert len(result) == 4
-
-
-@pytest.mark.parametrize("fragments", ["labelled_fragments", "labelled_fragments_dask"])
-def test_expander_returns_correct_contacts_labelled(
-    triplet_expander_labelled, fragments, request
-):
-    """Tests whether expander returns correct contacts for labelled fragments"""
-    df = request.getfixturevalue(fragments)
-    result = triplet_expander_labelled.expand(df).data
-    if isinstance(result, dd.DataFrame):
-        result = result.compute()
-    assert np.array_equal(result["start_1"].values, np.array([1, 1, 1, 2]))
-    assert np.array_equal(result["end_1"].values, np.array([4, 4, 4, 5]))
-    assert np.array_equal(result["start_2"].values, np.array([2, 2, 3, 3]))
-    assert np.array_equal(result["end_2"].values, np.array([5, 5, 6, 6]))
-    assert np.array_equal(result["start_3"].values, np.array([3, 4, 4, 4]))
-    assert np.array_equal(result["end_3"].values, np.array([6, 7, 7, 7]))
-    assert np.array_equal(
-        result["metadata_1"].values,
-        np.array(["SisterA", "SisterA", "SisterA", "SisterB"]),
-    )
-    assert np.array_equal(
-        result["metadata_2"].values,
-        np.array(["SisterB", "SisterB", "SisterA", "SisterA"]),
-    )
-    assert np.array_equal(
-        result["metadata_3"].values,
-        np.array(["SisterA", "SisterB", "SisterB", "SisterB"]),
-    )
-
-
-@pytest.mark.parametrize(
-    "fragments", ["unlabelled_fragments", "unlabelled_fragments_dask"]
-)
-def test_expander_returns_correct_contacts_unlabelled(
-    triplet_expander, fragments, request
-):
-    """Tests whether expander returns correct contacts for unlabelled fragments"""
-    df = request.getfixturevalue(fragments)
-    result = triplet_expander.expand(df).data
-    if isinstance(result, dd.DataFrame):
-        result = result.compute()
-    assert np.array_equal(result["start_1"].values, np.array([1, 1, 1, 2]))
-    assert np.array_equal(result["end_1"].values, np.array([4, 4, 4, 5]))
-    assert np.array_equal(result["start_2"].values, np.array([2, 2, 3, 3]))
-    assert np.array_equal(result["end_2"].values, np.array([5, 5, 6, 6]))
-    assert np.array_equal(result["start_3"].values, np.array([3, 4, 4, 4]))
-    assert np.array_equal(result["end_3"].values, np.array([6, 7, 7, 7]))
-    assert "metadata_1" not in result.columns
-
-
-def test_contacts_constructor_rejects_wrong_df(bad_df):
-    """Tests whether contacts constructor rejects wrong df"""
-    with pytest.raises(pa.errors.SchemaError):
-        contacts.Contacts(bad_df, number_fragments=3)
-
-
-def test_merge_works_for_good_pandas_df(
-    triplet_expander, contact_manipulator, labelled_fragments
-):
-    """Tests whether merge works for good pandas df"""
-    contacts = triplet_expander.expand(labelled_fragments)
-    result = contact_manipulator.merge_contacts([contacts, contacts]).data
-    assert result.shape[0] == 8
-    assert result.shape[1] == contacts.data.shape[1]
-
-
-def test_merge_works_for_good_dask_df(
-    triplet_expander, contact_manipulator, labelled_fragments
-):
-    """Tests whether merge works for good dask df"""
-    cont = triplet_expander.expand(labelled_fragments)
-    contacts_dask = contacts.Contacts(
-        dd.from_pandas(cont.data, npartitions=1), number_fragments=3
-    )
-    result = contact_manipulator.merge_contacts(
-        [contacts_dask, contacts_dask]
-    ).data.compute()
-    assert result.shape[0] == 8
-    assert result.shape[1] == cont.data.shape[1]
-
-
-def test_merge_fails_for_pandas_dask_mixed(
-    triplet_expander, contact_manipulator, labelled_fragments
-):
-    """Tests whether merge fails for pandas dask mixed"""
-    with pytest.raises(ValueError):
-        contacts_pandas = triplet_expander.expand(labelled_fragments)
-        contacts_dask = contacts.Contacts(
-            dd.from_pandas(contacts_pandas.data, npartitions=1), number_fragments=3
-        )
-        contact_manipulator.merge_contacts([contacts_pandas, contacts_dask])
-
-
 def test_subset_metadata_fails_if_not_labelled(unlabelled_contacts_2d):
     """Tests whether subset fails if the datafrane is not laelled"""
     contact_manipulator = contacts.ContactManipulator()

tests/fixtures/symmetry.py

@@ -1,4 +1,5 @@
 """Fixtures for testing symmetry.py"""
+# pylint: disable=redefined-outer-name
 import pytest
 import pandas as pd
 import dask.dataframe as dd

tests/fragments_tests/test_fragments.py

@@ -0,0 +1,197 @@
+"""Tests for the fragments module."""
+
+# pylint: disable=redefined-outer-name
+import pytest
+import pandas as pd
+import numpy as np
+import dask.dataframe as dd
+
+from spoc import fragments
+
+# pytlint: disable=unused-import
+from ..fixtures.symmetry import (
+    unlabelled_contacts_2d,
+    labelled_binary_contacts_2d_sorted,
+)
+
+
+@pytest.fixture
+def triplet_expander():
+    """expander for triplets"""
+    return fragments.FragmentExpander(number_fragments=3, contains_metadata=False)
+
+
+@pytest.fixture
+def triplet_expander_labelled():
+    """expander for triplets"""
+    return fragments.FragmentExpander(number_fragments=3, contains_metadata=True)
+
+
+@pytest.fixture
+def contact_manipulator():
+    """manipulator for triplest"""
+    return contacts.ContactManipulator()
+
+
+@pytest.fixture
+def bad_df():
+    """bad df for testing"""
+    return pd.DataFrame({"be": ["bop"]})
+
+
+@pytest.fixture
+def labelled_df():
+    """Dataframe representing a labelled fragment file"""
+    return pd.DataFrame(
+        {
+            "chrom": ["chr1"] * 6,
+            "start": [1, 2, 3, 4, 5, 6],
+            "end": [4, 5, 6, 7, 8, 9],
+            "strand": [True] * 6,
+            "read_name": ["dummy"] * 4 + ["dummy2"] * 2,
+            "read_start": [1, 2, 3, 4, 5, 6],
+            "read_end": [4, 5, 6, 7, 8, 9],
+            "read_length": [1] * 6,
+            "mapping_quality": [1, 2, 3, 4, 5, 6],
+            "align_score": [1, 2, 3, 4, 5, 6],
+            "align_base_qscore": [1, 2, 3, 4, 5, 6],
+            "pass_filter": [True] * 6,
+            "metadata": [
+                "SisterA",
+                "SisterB",
+                "SisterA",
+                "SisterB",
+                "SisterA",
+                "SisterB",
+            ],
+        }
+    )
+
+
+@pytest.fixture
+def unlabelled_df():
+    """Dataframe representing an unlabelled fragment file"""
+    return pd.DataFrame(
+        {
+            "chrom": ["chr1"] * 6,
+            "start": [1, 2, 3, 4, 5, 6],
+            "end": [4, 5, 6, 7, 8, 9],
+            "strand": [True] * 6,
+            "read_name": ["dummy"] * 4 + ["dummy2"] * 2,
+            "read_start": [1, 2, 3, 4, 5, 6],
+            "read_end": [4, 5, 6, 7, 8, 9],
+            "read_length": [1] * 6,
+            "mapping_quality": [1, 2, 3, 4, 5, 6],
+            "align_score": [1, 2, 3, 4, 5, 6],
+            "align_base_qscore": [1, 2, 3, 4, 5, 6],
+            "pass_filter": [True] * 6,
+        }
+    )
+
+
+@pytest.fixture
+def labelled_fragments(labelled_df):
+    """labelled fragments"""
+    return fragments.Fragments(labelled_df)
+
+
+@pytest.fixture
+def labelled_fragments_dask(labelled_df):
+    """labelled fragments from a dask dataframe"""
+    return fragments.Fragments(dd.from_pandas(labelled_df, npartitions=1))
+
+
+@pytest.fixture
+def unlabelled_fragments(unlabelled_df):
+    """unlabelled fragments"""
+    return fragments.Fragments(unlabelled_df)
+
+
+@pytest.fixture
+def unlabelled_fragments_dask(unlabelled_df):
+    """unlabelled fragments from a dask dataframe"""
+    return fragments.Fragments(dd.from_pandas(unlabelled_df, npartitions=1))
+
+
+@pytest.mark.parametrize(
+    "fragments, expander",
+    [
+        ("labelled_fragments", "triplet_expander_labelled"),
+        ("labelled_fragments_dask", "triplet_expander_labelled"),
+        ("unlabelled_fragments", "triplet_expander"),
+        ("unlabelled_fragments_dask", "triplet_expander"),
+    ],
+)
+def test_expander_drops_reads_w_too_little_fragments(expander, fragments, request):
+    """Tests whether expander drops reads with too little fragments"""
+    triplet_expander = request.getfixturevalue(expander)
+    result = triplet_expander.expand(request.getfixturevalue(fragments)).data
+    if isinstance(result, dd.DataFrame):
+        result = result.compute()
+    assert len(set(result.read_name)) == 1
+    assert result.read_name[0] == "dummy"
+
+
+@pytest.mark.parametrize(
+    "fragments, expander",
+    [
+        ("labelled_fragments", "triplet_expander_labelled"),
+        ("labelled_fragments_dask", "triplet_expander_labelled"),
+        ("unlabelled_fragments", "triplet_expander"),
+        ("unlabelled_fragments_dask", "triplet_expander"),
+    ],
+)
+def test_expander_returns_correct_number_of_contacts(expander, fragments, request):
+    """Tests whether expander returns correct number of contacts"""
+    triplet_expander = request.getfixturevalue(expander)
+    result = triplet_expander.expand(request.getfixturevalue(fragments)).data
+    assert len(result) == 4
+
+
+@pytest.mark.parametrize("fragments", ["labelled_fragments", "labelled_fragments_dask"])
+def test_expander_returns_correct_contacts_labelled(
+    triplet_expander_labelled, fragments, request
+):
+    """Tests whether expander returns correct contacts for labelled fragments"""
+    df = request.getfixturevalue(fragments)
+    result = triplet_expander_labelled.expand(df).data
+    if isinstance(result, dd.DataFrame):
+        result = result.compute()
+    assert np.array_equal(result["start_1"].values, np.array([1, 1, 1, 2]))
+    assert np.array_equal(result["end_1"].values, np.array([4, 4, 4, 5]))
+    assert np.array_equal(result["start_2"].values, np.array([2, 2, 3, 3]))
+    assert np.array_equal(result["end_2"].values, np.array([5, 5, 6, 6]))
+    assert np.array_equal(result["start_3"].values, np.array([3, 4, 4, 4]))
+    assert np.array_equal(result["end_3"].values, np.array([6, 7, 7, 7]))
+    assert np.array_equal(
+        result["metadata_1"].values,
+        np.array(["SisterA", "SisterA", "SisterA", "SisterB"]),
+    )
+    assert np.array_equal(
+        result["metadata_2"].values,
+        np.array(["SisterB", "SisterB", "SisterA", "SisterA"]),
+    )
+    assert np.array_equal(
+        result["metadata_3"].values,
+        np.array(["SisterA", "SisterB", "SisterB", "SisterB"]),
+    )
+
+
+@pytest.mark.parametrize(
+    "fragments", ["unlabelled_fragments", "unlabelled_fragments_dask"]
+)
+def test_expander_returns_correct_contacts_unlabelled(
+    triplet_expander, fragments, request
+):
+    """Tests whether expander returns correct contacts for unlabelled fragments"""
+    df = request.getfixturevalue(fragments)
+    result = triplet_expander.expand(df).data
+    if isinstance(result, dd.DataFrame):
+        result = result.compute()
+    assert np.array_equal(result["start_1"].values, np.array([1, 1, 1, 2]))
+    assert np.array_equal(result["end_1"].values, np.array([4, 4, 4, 5]))
+    assert np.array_equal(result["start_2"].values, np.array([2, 2, 3, 3]))
+    assert np.array_equal(result["end_2"].values, np.array([5, 5, 6, 6]))
+    assert np.array_equal(result["start_3"].values, np.array([3, 4, 4, 4]))
+    assert np.array_equal(result["end_3"].values, np.array([6, 7, 7, 7]))
+    assert "metadata_1" not in result.columns