init commit; data shapes mostly defined. some tests and sketched documentation in README. core algorithm TODO next

test/galeshapley_test.py

@@ -0,0 +1,96 @@
+import rich
+import polars as pl
+import polars.selectors as pls
+import numpy as np
+
+rng = np.random.default_rng()
+
+from polars.testing import assert_frame_equal
+
+import pytest
+from hypothesis import given, strategies as st
+
+
+@st.composite
+def rankings(draw, names=["a", "b", "c"], choices=["A", "B", "C"]):
+    h = pl.DataFrame({"": choices})
+    r = pl.DataFrame(
+        {n: draw(st.just(rng.permutation(len(choices)) + 1)) for n in names}
+    )  # should add None option in generation of valid rankings
+    return pl.concat([h, r], how="horizontal")
+
+
+@st.composite
+def preferences(draw, names=["a", "b", "c"], choices=["A", "B", "C"]):
+    p = pl.DataFrame(
+        {
+            n: draw(st.just(rng.choice(choices, size=len(choices), replace=False)))
+            for n in names
+        }
+    )
+    return p
+
+
+import carousel as crsl
+
+p = pl.DataFrame({"a": ["A", "C", "B"], "b": ["B", "A", "C"], "c": ["C", "B", "A"]})
+r = pl.DataFrame({"": ["A", "B", "C"], "a": [1, 3, 2], "b": [2, 1, 3], "c": [3, 2, 1]})
+
+
+def test_invalid_pref():
+    pp = pl.DataFrame(
+        {"a": ["A", "A", "B"], "b": ["B", "A", "C"], "c": ["C", "B", "A"]}
+    )
+    assert crsl.check_valid_pref(pp) is False
+
+
+def test_pref_to_rank():
+    rr = crsl.pref_to_rank(p)
+    rich.print(p, rr, r)
+    assert_frame_equal(crsl.pref_to_rank(p), r, check_dtypes=False)
+
+
+def test_invalid_rank():
+    rr = pl.DataFrame(
+        {"": ["A", "B", "C"], "a": [1, 1, 2], "b": [2, 1, 3], "c": [3, 2, 1]}
+    )
+    assert crsl.check_valid_pref(rr) is False
+
+
+def test_rank_to_pref():
+    assert_frame_equal(crsl.rank_to_pref(r), p, check_dtypes=False)
+
+
+@given(rankings())
+def test_valid_rank(R):
+    assert crsl.check_valid_rank(R)
+
+
+@given(rankings())
+def test_ranks_tofrom_prefs(R):
+    assert_frame_equal(crsl.pref_to_rank(crsl.rank_to_pref(R)), R, check_dtypes=False)
+
+
+@given(preferences())
+def test_valid_pref(P):
+    assert crsl.check_valid_pref(P)
+
+
+@given(preferences())
+def test_prefs_tofrom_ranks(P):
+    assert_frame_equal(crsl.rank_to_pref(crsl.pref_to_rank(P)), P, check_dtypes=False)
+
+
+def test_eg3_unstable():
+    applicant_rankings = pl.DataFrame({"": ["A", "B", "C", "D"], "a": [1, 2, 3, 4], "b": [1, 4, 3, 2], "c": [2, 1, 3, 4], "d": [4, 2, 3, 1]})
+    reviewer_rankings = pl.DataFrame({"": ["a", "b", "c", "d"], "A": [3, 4, 2, 1], "B": [3, 1, 4, 2], "C": [2, 3, 4, 1], "D": [3, 2, 1, 4] })
+    match = pl.DataFrame({"A" : ["a"], "B": ["b"], "C": ["c"], "D": ["d"]})
+    
+    assert crsl.check_unstable(match, applicant_rankings, reviewer_rankings)
+
+def test_eg3_isstable():
+    applicant_rankings = pl.DataFrame({"": ["A", "B", "C", "D"], "a": [1, 2, 3, 4], "b": [1, 4, 3, 2], "c": [2, 1, 3, 4], "d": [4, 2, 3, 1]})
+    reviewer_rankings = pl.DataFrame({"": ["a", "b", "c", "d"], "A": [3, 4, 2, 1], "B": [3, 1, 4, 2], "C": [2, 3, 4, 1], "D": [3, 2, 1, 4] })
+    match = pl.DataFrame({"A" : ["c"], "B": ["d"], "C": ["a"], "D": ["b"]})
+    
+    assert crsl.check_stable(match, applicant_rankings, reviewer_rankings)