testing

docs/source/api/extend.rst

@@ -0,0 +1,7 @@
+``skcriteria.extend`` module
+==============================
+
+.. automodule:: skcriteria.extend
+   :members:
+   :undoc-members:
+   :show-inheritance:

tests/test_extend.py

@@ -0,0 +1,173 @@
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+# License: BSD-3 (https://tldrlegal.com/license/bsd-3-clause-license-(revised))
+# Copyright (c) 2016-2021, Cabral, Juan; Luczywo, Nadia
+# Copyright (c) 2022, 2023, QuatroPe
+# All rights reserved.
+
+# =============================================================================
+# DOCS
+# =============================================================================
+
+"""test for skcriteria.extend
+
+"""
+
+
+# =============================================================================
+# IMPORTS
+# =============================================================================
+
+import numpy as np
+
+import pytest
+
+from skcriteria import extend as ext, pipeline
+
+
+# =============================================================================
+# RANDOM TEST
+# =============================================================================
+
+
+def test_mkagg(decision_matrix):
+    dm = decision_matrix(seed=42, min_alternatives=10)
+    values = np.arange(len(dm)) + 1
+    np.random.shuffle(values)
+
+    @ext.mkagg
+    def MyAgg(**kwargs):
+        return values, {}
+
+    dec = MyAgg()
+
+    assert repr(dec) == "<MyAgg []>"
+
+    rank = dec.evaluate(dm)
+
+    assert rank.method == "MyAgg"
+    np.testing.assert_array_equal(rank.alternatives, dm.alternatives)
+    np.testing.assert_array_equal(rank.values, values)
+    assert rank.extra_ == {}
+
+
+def test_mktransformer(decision_matrix):
+    dm = decision_matrix(seed=42, min_alternatives=10)
+
+    @ext.mktransformer
+    def MyTransformer(matrix, weights, hparams, **kwargs):
+        kwargs.update(matrix=matrix + 1, weights=weights + 1)
+        return kwargs
+
+    dec = MyTransformer()
+
+    assert repr(dec) == "<MyTransformer []>"
+
+    dmt = dec.transform(dm)
+
+    np.testing.assert_array_equal(dmt.matrix, dm.matrix + 1)
+    np.testing.assert_array_equal(dmt.weights, dm.weights + 1)
+
+
+def test_mkagg_CapWords():
+    with pytest.warns(ext.NonStandardNameWarning):
+
+        @ext.mkagg
+        def agg(**kwargs):
+            pass
+
+
+def test_mktransformer_CapWords():
+    with pytest.warns(ext.NonStandardNameWarning):
+
+        @ext.mktransformer
+        def transformer(**kwargs):
+            pass
+
+
+def test_mkagg_invalid_parameter():
+    with pytest.raises(TypeError):
+
+        @ext.mkagg
+        def Agg(foo):
+            pass
+
+
+def test_mktransformer_invalid_parameter():
+    with pytest.raises(TypeError):
+
+        @ext.mktransformer
+        def Transformer(foo):
+            pass
+
+
+def test_mkagg_missing_parameter():
+    with pytest.raises(TypeError):
+
+        @ext.mkagg
+        def Agg(matrix, objectives, weights, dtypes, criteria):
+            pass
+
+
+def test_mktransformer_missing_parameter():
+    with pytest.raises(TypeError):
+
+        @ext.mktransformer
+        def Transformer(matrix, objectives, weights, dtypes, criteria):
+            pass
+
+
+def test_mkagg_invalid_argument():
+    @ext.mkagg
+    def Agg(**kwargs):
+        pass
+
+    with pytest.raises(TypeError):
+        Agg(x=1)
+
+
+def test_mktransformer_invalid_argument():
+    @ext.mktransformer
+    def Transformer(**kwargs):
+        pass
+
+    with pytest.raises(TypeError):
+        Transformer(x=1)
+
+
+def test_mkagg_in_pipeline(decision_matrix):
+    dm = decision_matrix(seed=42, min_alternatives=10)
+
+    # TRANSFORMER =============================================================
+
+    @ext.mktransformer
+    def MyTransformer(matrix, weights, hparams, **kwargs):
+        kwargs.update(matrix=matrix + 1, weights=weights + 1)
+        return kwargs
+
+    # AGG =====================================================================
+    values = np.arange(len(dm)) + 1
+    np.random.shuffle(values)
+
+    @ext.mkagg
+    def MyAgg(**kwargs):
+        return values, {}
+
+    # PIPE ====================================================================
+    pipe = pipeline.mkpipe(MyTransformer(), MyAgg())
+
+    assert repr(pipe) == (
+        "<SKCPipeline "
+        "[steps=[('mytransformer', <MyTransformer []>), "
+        "('myagg', <MyAgg []>)]]>"
+    )
+
+    rank = pipe.evaluate(dm)
+    assert rank.method == "MyAgg"
+    np.testing.assert_array_equal(rank.alternatives, dm.alternatives)
+    np.testing.assert_array_equal(rank.values, values)
+    assert rank.extra_ == {}
+
+    dmt = pipe.transform(dm)
+    np.testing.assert_array_equal(dmt.matrix, dm.matrix + 1)
+    np.testing.assert_array_equal(dmt.weights, dm.weights + 1)