added tests for data.py

tests/test_data.py

@@ -2,184 +2,286 @@ import numpy as np
 import pytest
 import scipy.sparse as sp
 
-from quacc.data import ExtendedCollection
+from quacc.data import (
+    ExtendedCollection,
+    ExtendedData,
+    ExtendedLabels,
+    ExtendedPrev,
+    ExtensionPolicy,
+)
 
 
-class TestExtendedCollection:
+@pytest.mark.ext
+@pytest.mark.extpol
+class TestExtendedPolicy:
     @pytest.mark.parametrize(
-        "instances,result",
+        "extpol,nbcl,result",
         [
-            (
+            (ExtensionPolicy(), 2, np.array([0, 1, 2, 3])),
-                np.asarray(
+            (ExtensionPolicy(collapse_false=True), 2, np.array([0, 1, 2])),
-                    [[0, 0.3, 0.7], [1, 0.54, 0.46], [2, 0.28, 0.72], [3, 0.6, 0.4]]
+            (ExtensionPolicy(), 3, np.array([0, 1, 2, 3, 4, 5, 6, 7, 8])),
-                ),
+            (ExtensionPolicy(collapse_false=True), 3, np.array([0, 1, 2, 3])),
-                [np.asarray([1, 3]), np.asarray([0, 2])],
-            ),
-            (
-                sp.csr_matrix(
-                    [[0, 0.3, 0.7], [1, 0.54, 0.46], [2, 0.28, 0.72], [3, 0.6, 0.4]]
-                ),
-                [np.asarray([1, 3]), np.asarray([0, 2])],
-            ),
-            (
-                np.asarray([[0, 0.3, 0.7], [2, 0.28, 0.72]]),
-                [np.asarray([], dtype=int), np.asarray([0, 1])],
-            ),
-            (
-                sp.csr_matrix([[0, 0.3, 0.7], [2, 0.28, 0.72]]),
-                [np.asarray([], dtype=int), np.asarray([0, 1])],
-            ),
-            (
-                np.asarray([[1, 0.54, 0.46], [3, 0.6, 0.4]]),
-                [np.asarray([0, 1]), np.asarray([], dtype=int)],
-            ),
-            (
-                sp.csr_matrix([[1, 0.54, 0.46], [3, 0.6, 0.4]]),
-                [np.asarray([0, 1]), np.asarray([], dtype=int)],
-            ),
         ],
     )
-    def test__split_index_by_pred(self, instances, result):
+    def test_qclasses(self, extpol, nbcl, result):
-        ncl = 2
+        assert (result == extpol.qclasses(nbcl)).all()
-        assert all(
-            np.array_equal(a, b)
-            for (a, b) in zip(
-                ExtendedCollection._split_index_by_pred(ncl, instances),
-                result,
-            )
-        )
 
     @pytest.mark.parametrize(
-        "instances,s_inst,norms",
+        "extpol,nbcl,result",
         [
+            (ExtensionPolicy(), 2, np.array([0, 1, 2, 3])),
+            (ExtensionPolicy(collapse_false=True), 2, np.array([0, 1, 2, 3])),
+            (ExtensionPolicy(), 3, np.array([0, 1, 2, 3, 4, 5, 6, 7, 8])),
             (
-                np.asarray(
+                ExtensionPolicy(collapse_false=True),
-                    [[0, 0.3, 0.7], [1, 0.54, 0.46], [2, 0.28, 0.72], [3, 0.6, 0.4]]
+                3,
-                ),
+                np.array([0, 1, 2, 3, 4, 5, 6, 7, 8]),
-                [
-                    np.asarray([[1, 0.54, 0.46], [3, 0.6, 0.4]]),
-                    np.asarray([[0, 0.3, 0.7], [2, 0.28, 0.72]]),
-                ],
-                [0.5, 0.5],
-            ),
-            (
-                sp.csr_matrix(
-                    [[0, 0.3, 0.7], [1, 0.54, 0.46], [2, 0.28, 0.72], [3, 0.6, 0.4]]
-                ),
-                [
-                    sp.csr_matrix([[1, 0.54, 0.46], [3, 0.6, 0.4]]),
-                    sp.csr_matrix([[0, 0.3, 0.7], [2, 0.28, 0.72]]),
-                ],
-                [0.5, 0.5],
-            ),
-            (
-                np.asarray([[1, 0.54, 0.46], [3, 0.6, 0.4]]),
-                [
-                    np.asarray([[1, 0.54, 0.46], [3, 0.6, 0.4]]),
-                    np.asarray([], dtype=int),
-                ],
-                [1.0, 0.0],
-            ),
-            (
-                sp.csr_matrix([[1, 0.54, 0.46], [3, 0.6, 0.4]]),
-                [
-                    sp.csr_matrix([[1, 0.54, 0.46], [3, 0.6, 0.4]]),
-                    sp.csr_matrix([], dtype=int),
-                ],
-                [1.0, 0.0],
-            ),
-            (
-                np.asarray([[0, 0.3, 0.7], [2, 0.28, 0.72]]),
-                [
-                    np.asarray([], dtype=int),
-                    np.asarray([[0, 0.3, 0.7], [2, 0.28, 0.72]]),
-                ],
-                [0.0, 1.0],
-            ),
-            (
-                sp.csr_matrix([[0, 0.3, 0.7], [2, 0.28, 0.72]]),
-                [
-                    sp.csr_matrix([], dtype=int),
-                    sp.csr_matrix([[0, 0.3, 0.7], [2, 0.28, 0.72]]),
-                ],
-                [0.0, 1.0],
             ),
         ],
     )
-    def test_split_inst_by_pred(self, instances, s_inst, norms):
+    def test_eclasses(self, extpol, nbcl, result):
-        ncl = 2
+        assert (result == extpol.eclasses(nbcl)).all()
-        _s_inst, _norms = ExtendedCollection.split_inst_by_pred(ncl, instances)
-        if isinstance(s_inst, np.ndarray):
-            assert all(np.array_equal(a, b) for (a, b) in zip(_s_inst, s_inst))
-        if isinstance(s_inst, sp.csr_matrix):
-            assert all((a != b).nnz == 0 for (a, b) in zip(_s_inst, s_inst))
-        assert all(a == b for (a, b) in zip(_norms, norms))
 
     @pytest.mark.parametrize(
-        "instances,labels,inst0,lbl0,inst1,lbl1",
+        "extpol,nbcl,result",
         [
             (
-                np.asarray(
+                ExtensionPolicy(),
-                    [[0, 0.3, 0.7], [1, 0.54, 0.46], [2, 0.28, 0.72], [3, 0.6, 0.4]]
+                2,
+                (
+                    np.array([0, 0, 1, 1]),
+                    np.array([0, 1, 0, 1]),
                 ),
-                np.asarray([3, 0, 1, 2]),
-                np.asarray([[1, 0.54, 0.46], [3, 0.6, 0.4]]),
-                np.asarray([0, 1]),
-                np.asarray([[0, 0.3, 0.7], [2, 0.28, 0.72]]),
-                np.asarray([1, 0]),
             ),
             (
-                sp.csr_matrix(
+                ExtensionPolicy(collapse_false=True),
-                    [[0, 0.3, 0.7], [1, 0.54, 0.46], [2, 0.28, 0.72], [3, 0.6, 0.4]]
+                2,
+                (
+                    np.array([0, 1, 0]),
+                    np.array([0, 1, 1]),
                 ),
-                np.asarray([3, 0, 1, 2]),
-                sp.csr_matrix([[1, 0.54, 0.46], [3, 0.6, 0.4]]),
-                np.asarray([0, 1]),
-                sp.csr_matrix([[0, 0.3, 0.7], [2, 0.28, 0.72]]),
-                np.asarray([1, 0]),
             ),
             (
-                np.asarray([[0, 0.3, 0.7], [2, 0.28, 0.72]]),
+                ExtensionPolicy(),
-                np.asarray([3, 1]),
+                3,
-                np.asarray([], dtype=int),
+                (
-                np.asarray([], dtype=int),
+                    np.array([0, 0, 0, 1, 1, 1, 2, 2, 2]),
-                np.asarray([[0, 0.3, 0.7], [2, 0.28, 0.72]]),
+                    np.array([0, 1, 2, 0, 1, 2, 0, 1, 2]),
-                np.asarray([1, 0]),
+                ),
             ),
             (
-                sp.csr_matrix([[0, 0.3, 0.7], [2, 0.28, 0.72]]),
+                ExtensionPolicy(collapse_false=True),
-                np.asarray([3, 1]),
+                3,
-                sp.csr_matrix(np.empty((0, 0), dtype=int)),
-                np.asarray([], dtype=int),
-                sp.csr_matrix([[0, 0.3, 0.7], [2, 0.28, 0.72]]),
-                np.asarray([1, 0]),
-            ),
                 (
-                np.asarray([[1, 0.54, 0.46], [3, 0.6, 0.4]]),
+                    np.array([0, 1, 2, 0]),
-                np.asarray([0, 2]),
+                    np.array([0, 1, 2, 1]),
-                np.asarray([[1, 0.54, 0.46], [3, 0.6, 0.4]]),
-                np.asarray([0, 1]),
-                np.asarray([], dtype=int),
-                np.asarray([], dtype=int),
                 ),
-            (
-                sp.csr_matrix([[1, 0.54, 0.46], [3, 0.6, 0.4]]),
-                np.asarray([0, 2]),
-                sp.csr_matrix([[1, 0.54, 0.46], [3, 0.6, 0.4]]),
-                np.asarray([0, 1]),
-                sp.csr_matrix(np.empty((0, 0), dtype=int)),
-                np.asarray([], dtype=int),
             ),
         ],
     )
-    def test_split_by_pred(self, instances, labels, inst0, lbl0, inst1, lbl1):
+    def test_matrix_idx(self, extpol, nbcl, result):
-        ec = ExtendedCollection(instances, labels, classes=range(0, 4))
+        _midx = extpol.matrix_idx(nbcl)
-        [ec0, ec1] = ec.split_by_pred()
+        assert len(_midx) == len(result)
-        if isinstance(instances, np.ndarray):
+        assert all((idx == r).all() for idx, r in zip(_midx, result))
-            assert np.array_equal(ec0.X, inst0)
+
-            assert np.array_equal(ec1.X, inst1)
+    @pytest.mark.parametrize(
-        if isinstance(instances, sp.csr_matrix):
+        "extpol,nbcl,true,pred,result",
-            assert (ec0.X != inst0).nnz == 0
+        [
-            assert (ec1.X != inst1).nnz == 0
+            (
-        assert np.array_equal(ec0.y, lbl0)
+                ExtensionPolicy(),
-        assert np.array_equal(ec1.y, lbl1)
+                2,
+                np.array([1, 0, 1, 1, 0, 0]),
+                np.array([1, 0, 0, 1, 1, 0]),
+                np.array([3, 0, 2, 3, 1, 0]),
+            ),
+            (
+                ExtensionPolicy(collapse_false=True),
+                2,
+                np.array([1, 0, 1, 1, 0, 0]),
+                np.array([1, 0, 0, 1, 1, 0]),
+                np.array([1, 0, 2, 1, 2, 0]),
+            ),
+            (
+                ExtensionPolicy(),
+                3,
+                np.array([1, 2, 0, 1, 0, 2, 0, 1, 2]),
+                np.array([1, 0, 0, 0, 1, 1, 2, 2, 2]),
+                np.array([4, 6, 0, 3, 1, 7, 2, 5, 8]),
+            ),
+            (
+                ExtensionPolicy(collapse_false=True),
+                3,
+                np.array([1, 2, 0, 1, 0, 2, 0, 1, 2]),
+                np.array([1, 0, 0, 0, 1, 1, 2, 2, 2]),
+                np.array([1, 3, 0, 3, 3, 3, 3, 3, 2]),
+            ),
+        ],
+    )
+    def test_ext_lbl(self, extpol, nbcl, true, pred, result):
+        vfun = extpol.ext_lbl(nbcl)
+        assert (vfun(true, pred) == result).all()
+
+
+@pytest.mark.ext
+@pytest.mark.extd
+class TestExtendedData:
+    @pytest.mark.parametrize(
+        "pred_proba,result",
+        [
+            (
+                np.array([[0.3, 0.7], [0.54, 0.46], [0.28, 0.72], [0.6, 0.4]]),
+                [np.array([1, 3]), np.array([0, 2])],
+            ),
+            (
+                np.array([[0.3, 0.7], [0.28, 0.72]]),
+                [np.array([]), np.array([0, 1])],
+            ),
+            (
+                np.array([[0.54, 0.46], [0.6, 0.4]]),
+                [np.array([0, 1]), np.array([])],
+            ),
+            (
+                np.array(
+                    [
+                        [0.25, 0.4, 0.35],
+                        [0.24, 0.3, 0.46],
+                        [0.61, 0.28, 0.11],
+                        [0.4, 0.1, 0.5],
+                    ]
+                ),
+                [np.array([2]), np.array([0]), np.array([1, 3])],
+            ),
+        ],
+    )
+    def test__split_index_by_pred(self, monkeypatch, pred_proba, result):
+        def mockinit(self, pred_proba):
+            self.pred_proba_ = pred_proba
+
+        monkeypatch.setattr(ExtendedData, "__init__", mockinit)
+        ed = ExtendedData(pred_proba)
+        _split_index = ed._ExtendedData__split_index_by_pred()
+        assert len(_split_index) == len(result)
+        assert all((a == b).all() for (a, b) in zip(_split_index, result))
+
+
+@pytest.mark.ext
+@pytest.mark.extl
+class TestExtendedLabels:
+    @pytest.mark.parametrize(
+        "true,pred,nbcl,extpol,result",
+        [
+            (
+                np.array([1, 0, 0, 1, 1]),
+                np.array([1, 1, 0, 0, 1]),
+                2,
+                ExtensionPolicy(),
+                np.array([3, 1, 0, 2, 3]),
+            ),
+            (
+                np.array([1, 0, 0, 1, 1]),
+                np.array([1, 1, 0, 0, 1]),
+                2,
+                ExtensionPolicy(collapse_false=True),
+                np.array([1, 2, 0, 2, 1]),
+            ),
+        ],
+    )
+    def test_y(self, true, pred, nbcl, extpol, result):
+        el = ExtendedLabels(true, pred, nbcl, extpol)
+        assert (el.y == result).all()
+
+
+@pytest.mark.ext
+@pytest.mark.extp
+class TestExtendedPrev:
+    @pytest.mark.parametrize(
+        "flat,nbcl,extpol,q_classes,result",
+        [
+            (
+                np.array([0.2, 0, 0.8, 0]),
+                2,
+                ExtensionPolicy(),
+                [0, 1, 2, 3],
+                np.array([0.2, 0, 0.8, 0]),
+            ),
+            (
+                np.array([0.2, 0.8]),
+                2,
+                ExtensionPolicy(),
+                [0, 3],
+                np.array([0.2, 0, 0, 0.8]),
+            ),
+            (
+                np.array([0.2, 0.8]),
+                2,
+                ExtensionPolicy(collapse_false=True),
+                [0, 2],
+                np.array([0.2, 0, 0.8]),
+            ),
+            (
+                np.array([0.1, 0.1, 0.6, 0.2]),
+                3,
+                ExtensionPolicy(),
+                [0, 1, 3, 5],
+                np.array([0.1, 0.1, 0, 0.6, 0, 0.2, 0, 0, 0]),
+            ),
+            (
+                np.array([0.1, 0.1, 0.6]),
+                3,
+                ExtensionPolicy(collapse_false=True),
+                [0, 1, 2],
+                np.array([0.1, 0.1, 0.6, 0]),
+            ),
+        ],
+    )
+    def test__check_q_classes(self, monkeypatch, flat, nbcl, extpol, q_classes, result):
+        def mockinit(self, flat, nbcl, extpol):
+            self.flat = flat
+            self.nbcl = nbcl
+            self.extpol = extpol
+
+        monkeypatch.setattr(ExtendedPrev, "__init__", mockinit)
+        ep = ExtendedPrev(flat, nbcl, extpol)
+        ep._ExtendedPrev__check_q_classes(q_classes)
+        assert (ep.flat == result).all()
+
+    @pytest.mark.parametrize(
+        "flat,nbcl,extpol,result",
+        [
+            (
+                np.array([0.05, 0.1, 0.6, 0.25]),
+                2,
+                ExtensionPolicy(),
+                np.array([[0.05, 0.1], [0.6, 0.25]]),
+            ),
+            (
+                np.array([0.05, 0.1, 0.85]),
+                2,
+                ExtensionPolicy(collapse_false=True),
+                np.array([[0.05, 0.85], [0, 0.1]]),
+            ),
+            (
+                np.array([0.05, 0.1, 0.2, 0.15, 0.04, 0.06, 0.15, 0.14, 0.1]),
+                3,
+                ExtensionPolicy(),
+                np.array([[0.05, 0.1, 0.2], [0.15, 0.04, 0.06], [0.15, 0.14, 0.1]]),
+            ),
+            (
+                np.array([0.05, 0.2, 0.65, 0.1]),
+                3,
+                ExtensionPolicy(collapse_false=True),
+                np.array([[0.05, 0.1, 0], [0, 0.2, 0], [0, 0, 0.65]]),
+            ),
+        ],
+    )
+    def test__build_matrix(self, monkeypatch, flat, nbcl, extpol, result):
+        def mockinit(self, flat, nbcl, extpol):
+            self.flat = flat
+            self.nbcl = nbcl
+            self.extpol = extpol
+
+        monkeypatch.setattr(ExtendedPrev, "__init__", mockinit)
+        ep = ExtendedPrev(flat, nbcl, extpol)
+        _matrix = ep._ExtendedPrev__build_matrix()
+        assert _matrix.shape == result.shape
+        assert (_matrix == result).all()