test per assert

CHANGELOG.md

@@ -1,9 +1,9 @@
 # Changelog of galpynostatic
 
-## Unreleased
+## v0.3.2 (2024-01-30)
 
 - `base` and `utils` modules are now tested directly.
-- Better docs of `datasets` submodule and the three functions replaced in only one.
+- Better docs of `datasets` submodule and the three functions replaced in only one. For each assert now there is a test.
 
 
 ## v0.3.1 (2024-01-29)

pyproject.toml

@@ -15,7 +15,7 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "galpynostatic"
-version = "0.3.1"
+version = "0.3.2"
 authors = [{name = "Francisco Fernandez", email = "ffernandev@gmail.com"}]
 readme = "README.md"
 license = {file = "LICENSE"}

tests/test_datasets.py

@@ -25,64 +25,258 @@
 # =============================================================================
 
 
-def test_load_planar():
-    """Test the planar dataset."""
-    pla = galpynostatic.datasets.load_dataset(geometry="planar")
+# =============================================================================
+# planar geometry
+# =============================================================================
+
+
+def test_planar_dataset_type():
+    """Test the type of the planar dataset."""
+    assert isinstance(
+        galpynostatic.datasets.load_dataset(geometry="planar"), pd.DataFrame
+    )
+
+
+def test_planar_dataset_logell_min():
+    """Test minimum value of 'logell' in the planar dataset."""
+    assert galpynostatic.datasets.load_dataset(geometry="planar").l.min() == -4
+
+
+def test_planar_dataset_logell_max():
+    """Test maximum value of 'logell' in the planar dataset."""
+    np.testing.assert_almost_equal(
+        galpynostatic.datasets.load_dataset(geometry="planar").l.max(), 1.75, 6
+    )
+
+
+def test_planar_dataset_logell_mean():
+    """Test mean value of 'logell' in the planar dataset."""
+    np.testing.assert_almost_equal(
+        galpynostatic.datasets.load_dataset(geometry="planar").l.mean(),
+        -1.125,
+        6,
+    )
+
+
+def test_planar_dataset_logxi_min():
+    """Test minimum value of 'logxi' in the planar dataset."""
+    np.testing.assert_almost_equal(
+        galpynostatic.datasets.load_dataset(geometry="planar").xi.min(),
+        -3.2,
+        6,
+    )
+
+
+def test_planar_dataset_logxi_max():
+    """Test maximum value of 'logxi' in the planar dataset."""
+    np.testing.assert_almost_equal(
+        galpynostatic.datasets.load_dataset(geometry="planar").xi.max(), 2, 6
+    )
+
+
+def test_planar_dataset_logxi_mean():
+    """Test mean value of 'logxi' in the planar dataset."""
+    np.testing.assert_almost_equal(
+        galpynostatic.datasets.load_dataset(geometry="planar").xi.mean(),
+        -0.6,
+        6,
+    )
+
+
+def test_planar_dataset_xmax_min():
+    """Test minimum value of 'xmax' in the planar dataset."""
+    np.testing.assert_almost_equal(
+        galpynostatic.datasets.load_dataset(geometry="planar").xmax.min(),
+        0.0,
+        6,
+    )
+
+
+def test_planar_dataset_xmax_max():
+    """Test maximum value of 'xmax' in the planar dataset."""
+    np.testing.assert_almost_equal(
+        galpynostatic.datasets.load_dataset(geometry="planar").xmax.max(),
+        0.997055,
+        6,
+    )
+
+
+def test_planar_dataset_xmax_mean():
+    """Test mean value of 'xmax' in the planar dataset."""
+    np.testing.assert_almost_equal(
+        galpynostatic.datasets.load_dataset(geometry="planar").xmax.mean(),
+        0.515846,
+        6,
+    )
+
+
+# =============================================================================
+# cylindrical geometry
+# =============================================================================
+
+
+def test_cylindrical_dataset_type():
+    """Test the type of the cylindrical dataset."""
+    assert isinstance(
+        galpynostatic.datasets.load_dataset(geometry="cylindrical"),
+        pd.DataFrame,
+    )
+
+
+def test_cylindrical_dataset_logell_min():
+    """Test minimum value of 'logell' in the cylindrical dataset."""
+    assert (
+        galpynostatic.datasets.load_dataset(geometry="cylindrical").l.min()
+        == -4
+    )
+
+
+def test_cylindrical_dataset_logell_max():
+    """Test maximum value of 'logell' in the cylindrical dataset."""
+    np.testing.assert_almost_equal(
+        galpynostatic.datasets.load_dataset(geometry="cylindrical").l.max(),
+        1.75,
+        6,
+    )
+
+
+def test_cylindrical_dataset_logell_mean():
+    """Test mean value of 'logell' in the cylindrical dataset."""
+    np.testing.assert_almost_equal(
+        galpynostatic.datasets.load_dataset(geometry="cylindrical").l.mean(),
+        -1.125,
+        6,
+    )
+
+
+def test_cylindrical_dataset_logxi_min():
+    """Test minimum value of 'logxi' in the cylindrical dataset."""
+    np.testing.assert_almost_equal(
+        galpynostatic.datasets.load_dataset(geometry="cylindrical").xi.min(),
+        -3.4,
+        6,
+    )
+
+
+def test_cylindrical_dataset_logxi_max():
+    """Test maximum value of 'logxi' in the cylindrical dataset."""
+    np.testing.assert_almost_equal(
+        galpynostatic.datasets.load_dataset(geometry="cylindrical").xi.max(),
+        2,
+        6,
+    )
+
+
+def test_cylindrical_dataset_logxi_mean():
+    """Test mean value of 'logxi' in the cylindrical dataset."""
+    np.testing.assert_almost_equal(
+        galpynostatic.datasets.load_dataset(geometry="cylindrical").xi.mean(),
+        -0.7,
+        6,
+    )
+
+
+def test_cylindrical_dataset_xmax_min():
+    """Test minimum value of 'xmax' in the cylindrical dataset."""
+    np.testing.assert_almost_equal(
+        galpynostatic.datasets.load_dataset(geometry="cylindrical").xmax.min(),
+        0.0,
+        6,
+    )
+
+
+def test_cylindrical_dataset_xmax_max():
+    """Test maximum value of 'xmax' in the cylindrical dataset."""
+    np.testing.assert_almost_equal(
+        galpynostatic.datasets.load_dataset(geometry="cylindrical").xmax.max(),
+        0.997055,
+        6,
+    )
+
+
+def test_cylindrical_dataset_xmax_mean():
+    """Test mean value of 'xmax' in the cylindrical dataset."""
+    np.testing.assert_almost_equal(
+        galpynostatic.datasets.load_dataset(
+            geometry="cylindrical"
+        ).xmax.mean(),
+        0.516647,
+        6,
+    )
+
+
+# =============================================================================
+# spherical geometry
+# =============================================================================
+
+
+def test_spherical_dataset_type():
+    """Test the type of the spherical dataset."""
+    assert isinstance(galpynostatic.datasets.load_dataset(), pd.DataFrame)
+
+
+def test_spherical_dataset_logell_min():
+    """Test minimum value of 'logell' in the spherical dataset."""
+    assert galpynostatic.datasets.load_dataset().l.min() == -4
 
-    assert isinstance(pla, pd.DataFrame)
 
-    assert pla.l.min() == -4
-    np.testing.assert_almost_equal(pla.l.max(), 1.75, 6)
-    np.testing.assert_almost_equal(pla.l.mean(), -1.125, 6)
+def test_spherical_dataset_logell_max():
+    """Test maximum value of 'logell' in the spherical dataset."""
+    np.testing.assert_almost_equal(
+        galpynostatic.datasets.load_dataset().l.max(), 1.75, 6
+    )
 
-    np.testing.assert_almost_equal(pla.xi.min(), -3.2, 6)
-    np.testing.assert_almost_equal(pla.xi.max(), 2, 6)
-    np.testing.assert_almost_equal(pla.xi.mean(), -0.6, 6)
 
-    np.testing.assert_almost_equal(pla.xmax.min(), 0.0, 6)
-    np.testing.assert_almost_equal(pla.xmax.max(), 0.997055, 6)
-    np.testing.assert_almost_equal(pla.xmax.mean(), 0.515846, 6)
+def test_spherical_dataset_logell_mean():
+    """Test mean value of 'logell' in the spherical dataset."""
+    np.testing.assert_almost_equal(
+        galpynostatic.datasets.load_dataset().l.mean(), -1.125, 6
+    )
 
 
-def test_load_cylindrical():
-    """Test the cylindrical dataset."""
-    cyl = galpynostatic.datasets.load_dataset(geometry="cylindrical")
+def test_spherical_dataset_logxi_min():
+    """Test minimum value of 'logxi' in the spherical dataset."""
+    np.testing.assert_almost_equal(
+        galpynostatic.datasets.load_dataset().xi.min(), -3.5, 6
+    )
 
-    assert isinstance(cyl, pd.DataFrame)
 
-    assert cyl.l.min() == -4
-    np.testing.assert_almost_equal(cyl.l.max(), 1.75, 6)
-    np.testing.assert_almost_equal(cyl.l.mean(), -1.125, 6)
+def test_spherical_dataset_logxi_max():
+    """Test maximum value of 'logxi' in the spherical dataset."""
+    np.testing.assert_almost_equal(
+        galpynostatic.datasets.load_dataset().xi.max(), 2, 6
+    )
 
-    np.testing.assert_almost_equal(cyl.xi.min(), -3.4, 6)
-    np.testing.assert_almost_equal(cyl.xi.max(), 2, 6)
-    np.testing.assert_almost_equal(cyl.xi.mean(), -0.7, 6)
 
-    np.testing.assert_almost_equal(cyl.xmax.min(), 0.0, 6)
-    np.testing.assert_almost_equal(cyl.xmax.max(), 0.997055, 6)
-    np.testing.assert_almost_equal(cyl.xmax.mean(), 0.516647, 6)
+def test_spherical_dataset_logxi_mean():
+    """Test mean value of 'logxi' in the spherical dataset."""
+    np.testing.assert_almost_equal(
+        galpynostatic.datasets.load_dataset().xi.mean(), -0.75, 6
+    )
 
 
-def test_load_spherical():
-    """Test the spherical dataset."""
-    sph = galpynostatic.datasets.load_dataset()
+def test_spherical_dataset_xmax_min():
+    """Test minimum value of 'xmax' in the spherical dataset."""
+    np.testing.assert_almost_equal(
+        galpynostatic.datasets.load_dataset().xmax.min(), 0.0, 6
+    )
 
-    assert isinstance(sph, pd.DataFrame)
 
-    assert sph.l.min() == -4
-    np.testing.assert_almost_equal(sph.l.max(), 1.75, 6)
-    np.testing.assert_almost_equal(sph.l.mean(), -1.125, 6)
+def test_spherical_dataset_xmax_max():
+    """Test maximum value of 'xmax' in the spherical dataset."""
+    np.testing.assert_almost_equal(
+        galpynostatic.datasets.load_dataset().xmax.max(), 0.99706, 6
+    )
 
-    np.testing.assert_almost_equal(sph.xi.min(), -3.5, 6)
-    np.testing.assert_almost_equal(sph.xi.max(), 2, 6)
-    np.testing.assert_almost_equal(sph.xi.mean(), -0.75, 6)
 
-    np.testing.assert_almost_equal(sph.xmax.min(), 0.0, 6)
-    np.testing.assert_almost_equal(sph.xmax.max(), 0.99706, 6)
-    np.testing.assert_almost_equal(sph.xmax.mean(), 0.518575, 6)
+def test_spherical_dataset_xmax_mean():
+    """Test mean value of 'xmax' in the spherical dataset."""
+    np.testing.assert_almost_equal(
+        galpynostatic.datasets.load_dataset().xmax.mean(), 0.518575, 6
+    )
 
 
-def test_raise():
+def test_value_error():
     """Test the raise of the ValueError."""
     with pytest.raises(ValueError):
         galpynostatic.datasets.load_dataset(geometry="plane")