Merge pull request #29 from mmschlk/development

Add additional Tests

docs/requirements.txt

@@ -57,6 +57,7 @@ nbsphinx==0.9.3
 networkx==3.1
 numpy==1.26.1
 packaging==23.2
+pandas==2.1.4
 pandoc==2.3
 pandocfilters==1.5.0
 pathspec==0.11.2

shapiq/__init__.py

@@ -28,6 +28,7 @@
     get_parent_array,
     powerset,
     split_subsets_budget,
+    safe_isinstance,
 )
 
 from .datasets import load_bike
@@ -53,6 +54,7 @@
     "split_subsets_budget",
     "get_conditional_sample_weights",
     "get_parent_array",
+    "safe_isinstance",
     # datasets
     "load_bike",
 ]

shapiq/datasets/_all.py

@@ -1,3 +1,4 @@
+"""This module contains functions to load datasets."""
 import os
 import pandas as pd
 
@@ -32,7 +33,3 @@ def load_bike() -> pd.DataFrame:
     data.columns = list(map(str.title, data.columns))
 
     return data
-
-
-if __name__ == "__main__":
-    print(load_bike())

shapiq/plot/_config.py

@@ -10,13 +10,3 @@
     "BLUE",
     "NEUTRAL",
 ]
-
-
-if __name__ == "__main__":
-    red = [round(c * 255, 0) for c in RED.rgb]
-    blue = [round(c * 255, 0) for c in BLUE.rgb]
-    neutral = [round(c * 255, 0) for c in NEUTRAL.rgb]
-
-    print("RED", red)
-    print("BLUE", blue)
-    print("NEUTRAL", neutral)

shapiq/plot/network.py

@@ -131,9 +131,9 @@ def _add_legend_to_axis(axis: plt.Axes) -> None:
 
 def network_plot(
     *,
-    interaction_values: InteractionValues,
     first_order_values: np.ndarray[float],
     second_order_values: np.ndarray[float],
+    interaction_values: InteractionValues = None,
     feature_names: Optional[list[Any]] = None,
     feature_image_patches: Optional[dict[int, Image.Image]] = None,
     feature_image_patches_size: Optional[Union[float, dict[int, float]]] = 0.2,

shapiq/utils/__init__.py

@@ -2,13 +2,17 @@
 
 from .sets import get_explicit_subsets, pair_subset_sizes, powerset, split_subsets_budget
 from .tree import get_conditional_sample_weights, get_parent_array
+from .modules import safe_isinstance
 
 __all__ = [
+    # sets
     "powerset",
     "pair_subset_sizes",
     "split_subsets_budget",
     "get_explicit_subsets",
-    # trees
+    # tree
     "get_parent_array",
     "get_conditional_sample_weights",
+    # modules
+    "safe_isinstance",
 ]

tests/test_integration_import_all.py

@@ -12,6 +12,7 @@
 import games as games
 import utils as utils
 import plot as plot
+import datasets as datasets
 
 
 @pytest.mark.parametrize(
@@ -23,6 +24,7 @@
         games,
         utils,
         plot,
+        datasets,
     ],
 )
 def test_import_package(package):
@@ -39,6 +41,7 @@ def test_import_package(package):
         games,
         utils,
         plot,
+        datasets,
     ],
 )
 def test_import_submodules(package):

tests/tests_datasets/test_bike.py

@@ -0,0 +1,11 @@
+"""This test module contains the tests for the bike dataset."""
+
+import pytest
+
+from shapiq import load_bike
+
+
+def test_load_bike():
+    data = load_bike()
+    # test if data is a pandas dataframe
+    assert isinstance(data, type(data))

tests/tests_plots/test_network_plot.py

@@ -0,0 +1,68 @@
+"""This module contains all tests for the network plots."""
+import numpy as np
+import matplotlib.pyplot as plt
+from PIL import Image
+
+from shapiq.plot import network_plot
+
+
+def test_network_plot():
+    """Tests whether the network plot can be created."""
+
+    first_order_values = np.asarray([0.1, -0.2, 0.3, 0.4, 0.5, 0.6])
+    second_order_values = np.random.rand(6, 6) - 0.5
+
+    fig, axes = network_plot(
+        first_order_values=first_order_values,
+        second_order_values=second_order_values,
+    )
+    assert fig is not None
+    assert axes is not None
+    plt.close(fig)
+
+    fig, axes = network_plot(
+        first_order_values=first_order_values[0:4],
+        second_order_values=second_order_values[0:4, 0:4],
+        feature_names=["a", "b", "c", "d"],
+    )
+    assert fig is not None
+    assert axes is not None
+    plt.close(fig)
+
+
+def test_network_plot_with_image():
+    first_order_values = np.asarray([0.1, -0.2, 0.3, 0.4, 0.5, 0.6])
+    second_order_values = np.random.rand(6, 6) - 0.5
+    n_features = len(first_order_values)
+
+    # create dummyimage
+    image = np.random.rand(100, 100, 3)
+    image = (image * 255).astype(np.uint8)
+    image = Image.fromarray(image)
+
+    feature_image_patches: dict[int, Image.Image] = {}
+    feature_image_patches_size: dict[int, float] = {}
+    for feature_idx in range(n_features):
+        feature_image_patches[feature_idx] = image
+        feature_image_patches_size[feature_idx] = 0.1
+
+    fig, axes = network_plot(
+        first_order_values=first_order_values,
+        second_order_values=second_order_values,
+        center_image=image,
+        feature_image_patches=feature_image_patches,
+    )
+    assert fig is not None
+    assert axes is not None
+    plt.close(fig)
+
+    fig, axes = network_plot(
+        first_order_values=first_order_values,
+        second_order_values=second_order_values,
+        center_image=image,
+        feature_image_patches=feature_image_patches,
+        feature_image_patches_size=feature_image_patches_size,
+    )
+    assert fig is not None
+    assert axes is not None
+    plt.close(fig)

tests/tests_utils/test_utils_modules.py

@@ -0,0 +1,21 @@
+"""This test module contains tests for utils.modules."""
+import pytest
+
+from shapiq.utils import safe_isinstance
+from sklearn.tree import DecisionTreeRegressor
+
+
+def test_safe_isinstance():
+    model = DecisionTreeRegressor()
+
+    assert safe_isinstance(model, "sklearn.tree.DecisionTreeRegressor")
+    assert safe_isinstance(
+        model, ["sklearn.tree.DecisionTreeClassifier", "sklearn.tree.DecisionTreeRegressor"]
+    )
+    assert safe_isinstance(model, ("sklearn.tree.DecisionTreeRegressor",))
+    with pytest.raises(ValueError):
+        safe_isinstance(model, "DecisionTreeRegressor")
+    with pytest.raises(ValueError):
+        safe_isinstance(model, None)
+    assert not safe_isinstance(model, "my.made.up.module")
+    assert not safe_isinstance(model, ["sklearn.ensemble.DecisionTreeRegressor"])