Merge pull request #14 from jung235/feat/version

feat: update version 0.0.3

README.md

@@ -35,7 +35,7 @@ If properly installed, you can run:
 
 ```console
 $ pydiffuser --version
-pydiffuser, version 0.0.2
+pydiffuser, version 0.0.3
 ```
 
 ## Quickstart

docs/features/configs/config.json

@@ -1,6 +1,6 @@
 {
     "model_alias": "abp",
-    "pydiffuser_version": "0.0.2",
+    "pydiffuser_version": "0.0.3",
     "realization": 10,
     "length": 1000,
     "dimension": 2,

pydiffuser/_version.py

@@ -1 +1 @@
-__version__ = "0.0.2"
+__version__ = "0.0.3"

tests/utils/test_jitted.py

@@ -8,7 +8,12 @@
 from scipy.stats import expon, norm, pareto
 
 import pydiffuser as pyd
-from pydiffuser.utils.jitted import get_noise, normalize
+from pydiffuser.utils.jitted import (
+    get_noise,
+    normalize,
+    polar_to_cartesian,
+    spherical_to_cartesian,
+)
 
 
 def test_normalize():
@@ -23,6 +28,32 @@ def test_normalize():
     assert jnp.all(normed_arr == expected_arr)
 
 
+@pytest.mark.parametrize(
+    "r, phi",
+    [
+        (1, [jnp.pi / 6, jnp.pi / 4, jnp.pi / 3, jnp.pi / 2, jnp.pi]),
+        (2, [jnp.pi / 6, jnp.pi / 4, jnp.pi / 3, jnp.pi / 2, jnp.pi]),
+    ],
+)
+def test_polar_to_cartesian(r, phi):
+    phi = jnp.array(phi)
+    x1, x2 = polar_to_cartesian(r, phi)
+    assert jnp.all(x1 == r * jnp.cos(phi))
+    assert jnp.all(x2 == r * jnp.sin(phi))
+
+
+def test_spherical_to_cartesian():
+    r = 1
+    theta = rand(50) * jnp.pi
+    phi = rand(50) * 2 * jnp.pi
+    x1, x2, x3 = spherical_to_cartesian(
+        r=r, theta=theta.reshape(5, 10), phi=phi.reshape(5, 10)
+    )
+    assert x1.shape == (5, 10)
+    assert x2.shape == (5, 10)
+    assert x3.shape == (5, 10)
+
+
 @pytest.mark.parametrize(
     "generator",
     [