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Genentech · Jun 6, 2024 · 1670b5a · 1670b5a
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diff --git a/docs/beignet.special.md b/docs/beignet.special.md
@@ -1,7 +1,12 @@
 # beignet.special
 
-::: beignet.special.dawson_integral_f
+## Error and Related Functions
+
 ::: beignet.special.error_erf
 ::: beignet.special.error_erfc
 ::: beignet.special.error_erfi
+
+## Dawson and Fresnel Integrals
+
+::: beignet.special.dawson_integral_f
 ::: beignet.special.faddeeva_w
diff --git a/tests/beignet/special/test__dawson_integral_f.py b/tests/beignet/special/test__dawson_integral_f.py
@@ -0,0 +1,55 @@
+import beignet.special
+import hypothesis
+import hypothesis.strategies
+import scipy
+import torch
+
+
+@hypothesis.strategies.composite
+def _strategy(function):
+    x, y = torch.meshgrid(
+        torch.linspace(
+            function(
+                hypothesis.strategies.floats(
+                    min_value=-10,
+                    max_value=-10,
+                ),
+            ),
+            function(
+                hypothesis.strategies.floats(
+                    min_value=10,
+                    max_value=10,
+                ),
+            ),
+            steps=128,
+            dtype=torch.float64,
+        ),
+        torch.linspace(
+            function(
+                hypothesis.strategies.floats(
+                    min_value=-10,
+                    max_value=-10,
+                ),
+            ),
+            function(
+                hypothesis.strategies.floats(
+                    min_value=10,
+                    max_value=10,
+                ),
+            ),
+            steps=128,
+            dtype=torch.float64,
+        ),
+        indexing="xy",
+    )
+
+    input = x + 1.0j * y
+
+    return input, scipy.special.dawsn(input)
+
+
+@hypothesis.given(_strategy())
+def test_dawson_integral_f(data):
+    input, output = data
+
+    torch.testing.assert_close(beignet.special.dawson_integral_f(input), output)
diff --git a/tests/beignet/special/test__erf.py → tests/beignet/special/test__error_erf.py b/tests/beignet/special/test__erf.py → tests/beignet/special/test__error_erf.py
@@ -21,12 +21,7 @@ def _strategy(function):
                     max_value=10,
                 ),
             ),
-            steps=function(
-                hypothesis.strategies.integers(
-                    min_value=128,
-                    max_value=512,
-                ),
-            ),
+            steps=128,
             dtype=torch.float64,
         ),
         torch.linspace(
@@ -42,12 +37,7 @@ def _strategy(function):
                     max_value=10,
                 ),
             ),
-            function(
-                hypothesis.strategies.integers(
-                    min_value=128,
-                    max_value=512,
-                ),
-            ),
+            steps=128,
             dtype=torch.float64,
         ),
         indexing="xy",
@@ -59,7 +49,7 @@ def _strategy(function):
 
 
 @hypothesis.given(_strategy())
-def test_erf(data):
+def test_error_erf(data):
     input, output = data
 
     torch.testing.assert_close(beignet.special.error_erf(input), output)
diff --git a/tests/beignet/special/test__erfc.py → tests/beignet/special/test__error_erfc.py b/tests/beignet/special/test__erfc.py → tests/beignet/special/test__error_erfc.py
@@ -21,12 +21,7 @@ def _strategy(function):
                     max_value=10,
                 ),
             ),
-            steps=function(
-                hypothesis.strategies.integers(
-                    min_value=128,
-                    max_value=512,
-                ),
-            ),
+            steps=128,
             dtype=torch.float64,
         ),
         torch.linspace(
@@ -42,12 +37,7 @@ def _strategy(function):
                     max_value=10,
                 ),
             ),
-            function(
-                hypothesis.strategies.integers(
-                    min_value=128,
-                    max_value=512,
-                ),
-            ),
+            steps=128,
             dtype=torch.float64,
         ),
         indexing="xy",
@@ -59,7 +49,7 @@ def _strategy(function):
 
 
 @hypothesis.given(_strategy())
-def test_erfc(data):
+def test_error_erfc(data):
     input, output = data
 
     torch.testing.assert_close(beignet.special.error_erfc(input), output)
diff --git a/tests/beignet/special/test__error_erfi.py b/tests/beignet/special/test__error_erfi.py
@@ -0,0 +1,55 @@
+import beignet.special
+import hypothesis
+import hypothesis.strategies
+import scipy
+import torch
+
+
+@hypothesis.strategies.composite
+def _strategy(function):
+    x, y = torch.meshgrid(
+        torch.linspace(
+            function(
+                hypothesis.strategies.floats(
+                    min_value=-10,
+                    max_value=-10,
+                ),
+            ),
+            function(
+                hypothesis.strategies.floats(
+                    min_value=10,
+                    max_value=10,
+                ),
+            ),
+            steps=128,
+            dtype=torch.float64,
+        ),
+        torch.linspace(
+            function(
+                hypothesis.strategies.floats(
+                    min_value=-10,
+                    max_value=-10,
+                ),
+            ),
+            function(
+                hypothesis.strategies.floats(
+                    min_value=10,
+                    max_value=10,
+                ),
+            ),
+            steps=128,
+            dtype=torch.float64,
+        ),
+        indexing="xy",
+    )
+
+    input = x + 1.0j * y
+
+    return input, scipy.special.erfi(input)
+
+
+@hypothesis.given(_strategy())
+def test_error_erfi(data):
+    input, output = data
+
+    torch.testing.assert_close(beignet.special.error_erfi(input), output)
diff --git a/tests/beignet/special/test__faddeeva_w.py b/tests/beignet/special/test__faddeeva_w.py
@@ -21,12 +21,7 @@ def _strategy(function):
                     max_value=10,
                 ),
             ),
-            steps=function(
-                hypothesis.strategies.integers(
-                    min_value=128,
-                    max_value=512,
-                ),
-            ),
+            steps=128,
             dtype=torch.float64,
         ),
         torch.linspace(
@@ -42,12 +37,7 @@ def _strategy(function):
                     max_value=10,
                 ),
             ),
-            function(
-                hypothesis.strategies.integers(
-                    min_value=128,
-                    max_value=512,
-                ),
-            ),
+            steps=128,
             dtype=torch.float64,
         ),
         indexing="xy",