diff --git a/.gitlab-ci.yml b/.gitlab-ci.yml
index 0c12a21cc6e40f8f77cfe4986e55a1da6ba8f767..15b69a405625d367bee895ae1ff039fc2dd585ce 100644
--- a/.gitlab-ci.yml
+++ b/.gitlab-ci.yml
@@ -1,13 +1,19 @@
image: python:3
+before_script:
+ - pip install doxec numpy
+ - python3 setup.py install
+
stages:
- test
+unittest:
+ stage: test
+ script:
+ - python3 setup.py test
README:
stage: test
script:
- - pip install doxec numpy
- - python3 setup.py install
- doxec README.md
diff --git a/setup.py b/setup.py
index c9e35cb987db74638dcc5e873612976b0b26c1dc..0a9ca87b2dc206922100d7c636c5015d2c5c2e08 100644
--- a/setup.py
+++ b/setup.py
@@ -11,5 +11,6 @@ module1 = Extension('sortednp', language='c++',
setup (name = 'sortednp',
version = '0.0.0',
install_requires=['numpy'],
+ test_suite='tests',
description = 'Merge and intersect sorted numpy arrays.',
ext_modules = [module1])
diff --git a/sortednpmodule.c b/sortednpmodule.c
index 13401a490668063d5c07159bf96b152976ed9eec..7dac6f1b8e03f6850e33402b5dab952d5fd16f3f 100644
--- a/sortednpmodule.c
+++ b/sortednpmodule.c
@@ -5,8 +5,9 @@
static PyObject * sortednp_intersect(PyObject *self, PyObject *args) {
PyObject *a, *b;
- if (!PyArg_ParseTuple(args, "OO", &a, &b))
- return NULL;
+
+ if (!PyArg_ParseTuple(args, "O!O!", &PyArray_Type, &a, &PyArray_Type, &b))
+ return NULL;
a = PyArray_FROM_OF(a, NPY_ARRAY_CARRAY_RO);
b = PyArray_FROM_OF(b, NPY_ARRAY_CARRAY_RO);
@@ -19,6 +20,7 @@ static PyObject * sortednp_intersect(PyObject *self, PyObject *args) {
int nd_b = PyArray_NDIM(b);
if (PyArray_NDIM(a) != 1 || PyArray_NDIM(b) != 1) {
+ PyErr_SetString(PyExc_ValueError, "Arguments can not be multi-dimensional.");
return NULL;
}
@@ -70,8 +72,8 @@ static PyObject * sortednp_intersect(PyObject *self, PyObject *args) {
static PyObject * sortednp_merge(PyObject *self, PyObject *args) {
PyObject *a, *b;
- if (!PyArg_ParseTuple(args, "OO", &a, &b))
- return NULL;
+ if (!PyArg_ParseTuple(args, "O!O!", &PyArray_Type, &a, &PyArray_Type, &b))
+ return NULL;
a = PyArray_FROM_OF(a, NPY_ARRAY_CARRAY_RO);
b = PyArray_FROM_OF(b, NPY_ARRAY_CARRAY_RO);
@@ -84,6 +86,7 @@ static PyObject * sortednp_merge(PyObject *self, PyObject *args) {
int nd_b = PyArray_NDIM(b);
if (PyArray_NDIM(a) != 1 || PyArray_NDIM(b) != 1) {
+ PyErr_SetString(PyExc_ValueError, "Arguments can not be multi-dimensional.");
return NULL;
}
diff --git a/tests/__init__.py b/tests/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/tests/test_intersect.py b/tests/test_intersect.py
new file mode 100644
index 0000000000000000000000000000000000000000..ae704899d1b6fb3b5f5623c30d1d01812ac83013
--- /dev/null
+++ b/tests/test_intersect.py
@@ -0,0 +1,237 @@
+
+from abc import ABCMeta, abstractmethod
+import unittest
+import numpy as np
+
+import sortednp as snp
+
+class IntersectBase(metaclass=ABCMeta):
+ """
+ Define general test cases for the intersect method. Sub-classes need to
+ implement have to overwrite the dtype method.
+ """
+
+ @abstractmethod
+ def get_dtype(self):
+ """
+ Returns the numpy data type, which should be used for all tests.
+ """
+ pass
+
+ def test_simple_middle(self):
+ """
+ Check that intersect returns only element, which are present in both
+ non-empty input arrays. The common elements are neither at the
+ beginning nor at the end of the arrays.
+ """
+ a = np.array([2, 3, 6, 7, 9], dtype=self.get_dtype())
+ b = np.array([1, 3, 7, 8, 10], dtype=self.get_dtype())
+
+ i = snp.intersect(a, b)
+
+ self.assertEqual(list(i), [3, 7])
+ self.assertEqual(i.dtype, self.get_dtype())
+
+ def test_simple_end_single(self):
+ """
+ Check that intersect returns only element, which are present in both
+ non-empty input arrays. One common element is at the end of one array.
+ """
+ a = np.array([2, 3, 6, 7, 9], dtype=self.get_dtype())
+ b = np.array([1, 3, 7, 9, 10], dtype=self.get_dtype())
+
+ i = snp.intersect(a, b)
+
+ self.assertEqual(list(i), [3, 7, 9])
+ self.assertEqual(i.dtype, self.get_dtype())
+
+
+ def test_simple_end_both(self):
+ """
+ Check that intersect returns only element, which are present in both
+ non-empty input arrays. One common element is at the end of both
+ arrays.
+ """
+ a = np.array([2, 3, 6, 7, 9], dtype=self.get_dtype())
+ b = np.array([1, 3, 7, 9], dtype=self.get_dtype())
+
+ i = snp.intersect(a, b)
+
+ self.assertEqual(list(i), [3, 7, 9])
+ self.assertEqual(i.dtype, self.get_dtype())
+
+ def test_simple_begining_single(self):
+ """
+ Check that intersect returns only element, which are present in both
+ non-empty input arrays. One common element is at the begining of one array.
+ """
+ a = np.array([2, 3, 6, 7, 8], dtype=self.get_dtype())
+ b = np.array([1, 2, 3, 7, 9, 10], dtype=self.get_dtype())
+
+ i = snp.intersect(a, b)
+
+ self.assertEqual(list(i), [2, 3, 7])
+ self.assertEqual(i.dtype, self.get_dtype())
+
+ def test_simple_begining_both(self):
+ """
+ Check that intersect returns only element, which are present in both
+ non-empty input arrays. One common element is at the end of both
+ arrays.
+ """
+ a = np.array([2, 3, 6, 7, 8], dtype=self.get_dtype())
+ b = np.array([2, 3, 7, 9, 10], dtype=self.get_dtype())
+
+ i = snp.intersect(a, b)
+
+ self.assertEqual(list(i), [2, 3, 7])
+ self.assertEqual(i.dtype, self.get_dtype())
+
+ def test_empty_intersect(self):
+ """
+ Check that intersect returns an empty array, if the non-empty inputs
+ do not have any elements in common.
+ """
+ a = np.array([1, 3, 5, 10], dtype=self.get_dtype())
+ b = np.array([2, 4, 7, 8, 20], dtype=self.get_dtype())
+
+ i = snp.intersect(a, b)
+
+ self.assertEqual(list(i), [])
+ self.assertEqual(len(i), 0)
+ self.assertEqual(i.dtype, self.get_dtype())
+
+ def test_empty_input_single(self):
+ """
+ Check that intersect returns an empty array, if one of the input arrays
+ is empty.
+ """
+ a = np.array([], dtype=self.get_dtype())
+ b = np.array([2, 4, 7, 8, 20], dtype=self.get_dtype())
+
+ i = snp.intersect(a, b)
+ self.assertEqual(list(i), [])
+ self.assertEqual(len(i), 0)
+ self.assertEqual(i.dtype, self.get_dtype())
+
+ i = snp.intersect(b, a)
+ self.assertEqual(list(i), [])
+ self.assertEqual(len(i), 0)
+ self.assertEqual(i.dtype, self.get_dtype())
+
+ def test_empty_input_both(self):
+ """
+ Check that intersect returns an empty array, both input arrays are
+ empty.
+ """
+ a = np.array([], dtype=self.get_dtype())
+ b = np.array([], dtype=self.get_dtype())
+
+ i = snp.intersect(a, b)
+ self.assertEqual(list(i), [])
+ self.assertEqual(len(i), 0)
+ self.assertEqual(i.dtype, self.get_dtype())
+
+ def test_contained(self):
+ """
+ Check that intersect returns the common elements, if one array is
+ contained in the other.
+ """
+ a = np.array([1, 2, 3, 4, 5, 6, 7, 8], dtype=self.get_dtype())
+ b = np.array([4, 5, 7], dtype=self.get_dtype())
+
+ i = snp.intersect(a, b)
+ self.assertEqual(list(i), [4, 5, 7])
+ self.assertEqual(i.dtype, self.get_dtype())
+
+ i = snp.intersect(b, a)
+ self.assertEqual(list(i), [4, 5, 7])
+ self.assertEqual(i.dtype, self.get_dtype())
+
+ def test_identical(self):
+ """
+ Check that intersect returns a copy, if the same array is passed in
+ twice.
+ """
+ a = np.array([3, 4, 6, 8], dtype=self.get_dtype())
+
+ i = snp.intersect(a, a)
+ self.assertEqual(list(i), [3, 4, 6, 8])
+ self.assertEqual(list(a), [3, 4, 6, 8])
+ self.assertEqual(i.dtype, self.get_dtype())
+
+ i[0] = 1
+ self.assertEqual(list(a), [3, 4, 6, 8])
+
+ def test_separated(self):
+ """
+ Check that intersect returns an empty array, if all elements are
+ greater than all elements in the other.
+ """
+ a = np.array([1, 2, 3], dtype=self.get_dtype())
+ b = np.array([4, 6, 8], dtype=self.get_dtype())
+
+ i = snp.intersect(a, b)
+ self.assertEqual(list(i), [])
+ self.assertEqual(len(i), 0)
+ self.assertEqual(i.dtype, self.get_dtype())
+
+ def test_duplicates_same(self):
+ """
+ Check that duplicates in the same array are dropped if not present in
+ the other array.
+ """
+ a = np.array([1, 2, 2, 3], dtype=self.get_dtype())
+ b = np.array([1, 6, 8], dtype=self.get_dtype())
+
+ i = snp.intersect(a, b)
+ self.assertEqual(list(i), [1])
+ self.assertEqual(i.dtype, self.get_dtype())
+
+ a = np.array([1, 2, 2, 3], dtype=self.get_dtype())
+ b = np.array([1, 2, 4, 6, 8], dtype=self.get_dtype())
+
+ i = snp.intersect(a, b)
+ self.assertEqual(list(i), [1, 2])
+ self.assertEqual(i.dtype, self.get_dtype())
+
+
+ def test_duplicates_both(self):
+ """
+ Check that duplicates in the same array are kept if they are also
+ duplicated in the other array.
+ """
+ a = np.array([1, 2, 2, 3], dtype=self.get_dtype())
+ b = np.array([2, 2, 4, 6, 8], dtype=self.get_dtype())
+
+ i = snp.intersect(a, b)
+ self.assertEqual(list(i), [2, 2])
+ self.assertEqual(i.dtype, self.get_dtype())
+
+ def test_raise_multi_dim(self):
+ """
+ Check that passing in a multi dimensional array raises an exception.
+ """
+ a = np.zeros((10, 2), dtype=self.get_dtype())
+ b = np.array([2, 3, 5, 6], dtype=self.get_dtype())
+
+ self.assertRaises(ValueError, snp.intersect, a, b)
+ self.assertRaises(ValueError, snp.intersect, b, a)
+ self.assertRaises(ValueError, snp.intersect, a, a)
+
+ def test_raise_non_array(self):
+ """
+ Check that passing in a non-numpy-array raises an exception.
+ """
+ b = np.array([2, 3, 5, 6], dtype=self.get_dtype())
+
+ self.assertRaises(TypeError, snp.intersect, 3, b)
+ self.assertRaises(TypeError, snp.intersect, b, 2)
+ self.assertRaises(TypeError, snp.intersect, 3, "a")
+
+
+class IntersectTestCase_Double(IntersectBase, unittest.TestCase):
+ def get_dtype(self):
+ return 'float'
+
+
diff --git a/tests/test_merge.py b/tests/test_merge.py
new file mode 100644
index 0000000000000000000000000000000000000000..83725dabf255fdc6d78e54901797e86fd0fb3406
--- /dev/null
+++ b/tests/test_merge.py
@@ -0,0 +1,156 @@
+
+from abc import ABCMeta, abstractmethod
+import unittest
+import numpy as np
+
+import sortednp as snp
+
+class MergeBase(metaclass=ABCMeta):
+ """
+ Define general test cases for the merge method. Sub-classes need to
+ implement have to overwrite the dtype method.
+ """
+
+ @abstractmethod
+ def get_dtype(self):
+ """
+ Returns the numpy data type, which should be used for all tests.
+ """
+ pass
+
+
+ def test_simple(self):
+ """
+ Check that merging two non-empty arrays returns the union of the two
+ arrays.
+ """
+ a = np.array([1, 3, 7], dtype=self.get_dtype())
+ b = np.array([2, 5, 6], dtype=self.get_dtype())
+
+ m = snp.merge(a, b)
+ self.assertEqual(list(m), [1, 2, 3, 5, 6, 7])
+ self.assertEqual(m.dtype, self.get_dtype())
+
+ def test_separated(self):
+ """
+ Check that merging two non-empty arrays returns the union of the two
+ arrays if all element in on array are greater than all elements in the
+ other. This tests the copy parts of the implementation.
+ """
+ a = np.array([1, 3, 7], dtype=self.get_dtype())
+ b = np.array([9, 10, 16], dtype=self.get_dtype())
+
+ m = snp.merge(a, b)
+ self.assertEqual(list(m), [1, 3, 7, 9, 10, 16])
+ self.assertEqual(m.dtype, self.get_dtype())
+
+ def test_empty_single(self):
+ """
+ Check that merging two arrays returns a copy of the first one if
+ the other is empty.
+ """
+ a = np.array([1, 3, 7], dtype=self.get_dtype())
+ b = np.array([], dtype=self.get_dtype())
+
+ m = snp.merge(a, b)
+ self.assertEqual(list(m), [1, 3, 7])
+ self.assertEqual(list(a), [1, 3, 7])
+ self.assertEqual(m.dtype, self.get_dtype())
+ m[0] = 0
+ self.assertEqual(list(a), [1, 3, 7])
+
+ m = snp.merge(b, a)
+ self.assertEqual(list(m), [1, 3, 7])
+ self.assertEqual(list(a), [1, 3, 7])
+ self.assertEqual(m.dtype, self.get_dtype())
+ m[0] = 0
+ self.assertEqual(list(a), [1, 3, 7])
+
+
+ def test_empty_both(self):
+ """
+ Check that merging two empty arrays returns an empty array.
+ """
+ a = np.array([], dtype=self.get_dtype())
+ b = np.array([], dtype=self.get_dtype())
+
+ m = snp.merge(a, b)
+ self.assertEqual(list(m), [])
+ self.assertEqual(len(m), 0)
+ self.assertEqual(m.dtype, self.get_dtype())
+
+
+ def test_identical(self):
+ """
+ Check that merging two identical arrays returns each element twice.
+ """
+ a = np.array([1, 3, 7], dtype=self.get_dtype())
+
+ m = snp.merge(a, a)
+ self.assertEqual(list(m), [1, 1, 3, 3, 7, 7])
+ self.assertEqual(m.dtype, self.get_dtype())
+
+
+ def test_duplicates_same(self):
+ """
+ Check that duplications in a single array are passed to the result.
+ """
+ a = np.array([1, 3, 3, 7], dtype=self.get_dtype())
+ b = np.array([2, 5, 6], dtype=self.get_dtype())
+
+ m = snp.merge(a, b)
+ self.assertEqual(list(m), [1, 2, 3, 3, 5, 6, 7])
+ self.assertEqual(m.dtype, self.get_dtype())
+
+ def test_duplicates_other(self):
+ """
+ Check that duplications in the other array are passed to the result.
+ """
+ a = np.array([1, 3, 7], dtype=self.get_dtype())
+ b = np.array([2, 3, 5, 6], dtype=self.get_dtype())
+
+ m = snp.merge(a, b)
+ self.assertEqual(list(m), [1, 2, 3, 3, 5, 6, 7])
+ self.assertEqual(m.dtype, self.get_dtype())
+
+ def test_duplicates_both(self):
+ """
+ Check that duplications in a single and the other array are both passed to
+ the result.
+ """
+ a = np.array([1, 3, 3, 7], dtype=self.get_dtype())
+ b = np.array([2, 3, 5, 6], dtype=self.get_dtype())
+
+ m = snp.merge(a, b)
+ self.assertEqual(list(m), [1, 2, 3, 3, 3, 5, 6, 7])
+ self.assertEqual(m.dtype, self.get_dtype())
+
+
+ def test_raise_multi_dim(self):
+ """
+ Check that passing in a multi dimensional array raises an exception.
+ """
+ a = np.zeros((10, 2), dtype=self.get_dtype())
+ b = np.array([2, 3, 5, 6], dtype=self.get_dtype())
+
+ self.assertRaises(ValueError, snp.merge, a, b)
+ self.assertRaises(ValueError, snp.merge, b, a)
+ self.assertRaises(ValueError, snp.merge, a, a)
+
+ def test_raise_non_array(self):
+ """
+ Check that passing in a non-numpy-array raises an exception.
+ """
+ b = np.array([2, 3, 5, 6], dtype=self.get_dtype())
+
+ self.assertRaises(TypeError, snp.merge, 3, b)
+ self.assertRaises(TypeError, snp.merge, b, 2)
+ self.assertRaises(TypeError, snp.merge, 3, "a")
+
+
+class MergeTestCase_Double(MergeBase, unittest.TestCase):
+ def get_dtype(self):
+ return 'float'
+
+
+