Adds setup.py

.gitignore

@@ -1,7 +1,9 @@
-*.pyc
+build/
 .vscode
 .idea/
 
+*.pyc
+*.so
 *.c
 
-*.so
+yoshi_seals.egg-info/

setup.py

@@ -0,0 +1,35 @@
+import setuptools
+import os
+
+__name = "yoshi_seals"
+
+__version_sufix = os.environ.get('VERSION_SUFIX')
+if not __version_sufix:
+    __version_sufix = "dev"
+
+__version = f"2.0.{__version_sufix}"
+
+with open("README.md", "r") as fh:
+    long_description = fh.read()
+
+setuptools.setup(
+    name=__name,
+    version=__version,
+    author="Vitor Hideyoshi",
+    author_email="vitor.h.n.batista@gmail.com",
+    description="Numeric Calculus python module in the topic of Linear Algebra",
+    long_description=long_description,
+    long_description_content_type="text/markdown",
+    url="https://github.com/HideyoshiNakazone/Seals-NumericCalculus.git",
+    packages=setuptools.find_packages(),
+    classifiers=[
+        "Programming Language :: Python :: 3",
+        "License :: OSI Approved :: GNU General Public License v2 (GPLv2)",
+        "Operating System :: OS Independent"
+    ],
+    python_requires='>=3.6',
+    install_requires=[
+        'numpy',
+        'pandas',
+    ],
+)

test/test_process.py

@@ -54,13 +54,13 @@ class TestProcess(unittest.TestCase):
             ps.vstack(a, b)
 
     def test_gauss(self):
-        a = np.array(([4., 3.], [3., 2.]))
+        a = np.array(([4., 10., 8.], [10., 26., 26], [8., 26., 61.]))
-        b = np.array(([1.], [1.]))
+        b = np.array(([44.], [128.], [214.]))
 
         matrix = ps.gauss(a, b)
-        expected_matrix = np.array([[1.], [-1.]])
+        expected_matrix = np.array([[-8.], [6.], [2.]])
 
-        npt.assert_array_equal(matrix, expected_matrix)
+        npt.assert_almost_equal(matrix, expected_matrix)
 
     def test_cholesky(self):
         a = np.array(([4., 10., 8.], [10., 26., 26], [8., 26., 61.]))
@@ -72,19 +72,19 @@ class TestProcess(unittest.TestCase):
         npt.assert_almost_equal(matrix, expected_matrix)
 
     def test_decomposition(self):
-        a = np.array(([4., 3.], [3., 2.]))
+        a = np.array(([4., 10., 8.], [10., 26., 26], [8., 26., 61.]))
-        b = np.array(([1.], [1.]))
+        b = np.array(([44.], [128.], [214.]))
 
         matrix = ps.decomposition(a, b)
-        expected_matrix = np.array([[1.], [-1.]])
+        expected_matrix = np.array([[-8.], [6.], [2.]])
 
-        npt.assert_array_equal(matrix, expected_matrix)
+        npt.assert_almost_equal(matrix, expected_matrix)
 
     def test_cramer(self):
-        a = np.array(([4., 3.], [3., 2.]))
+        a = np.array(([4., 10., 8.], [10., 26., 26], [8., 26., 61.]))
-        b = np.array(([1.], [1.]))
+        b = np.array(([44.], [128.], [214.]))
 
         matrix = ps.cramer(a, b)
-        expected_matrix = np.array([[1.], [-1.]])
+        expected_matrix = np.array([[-8.], [6.], [2.]])
 
-        npt.assert_array_equal(matrix, expected_matrix)
+        npt.assert_almost_equal(matrix, expected_matrix)