FEAT: expm1 ufunc implementation

quaddtype/numpy_quaddtype/src/ops.hpp

@@ -124,6 +124,12 @@ quad_exp2(const Sleef_quad *op)
     return Sleef_exp2q1_u10(*op);
 }
 
+static inline Sleef_quad
+quad_expm1(const Sleef_quad *op)
+{
+    return Sleef_expm1q1_u10(*op);
+}
+
 static inline Sleef_quad
 quad_sin(const Sleef_quad *op)
 {
@@ -308,6 +314,12 @@ ld_exp2(const long double *op)
     return exp2l(*op);
 }
 
+static inline long double
+ld_expm1(const long double *op)
+{
+    return expm1l(*op);
+}
+
 static inline long double
 ld_sin(const long double *op)
 {

quaddtype/numpy_quaddtype/src/umath/unary_ops.cpp

@@ -203,6 +203,9 @@ init_quad_unary_ops(PyObject *numpy)
     if (create_quad_unary_ufunc<quad_exp2, ld_exp2>(numpy, "exp2") < 0) {
         return -1;
     }
+    if (create_quad_unary_ufunc<quad_expm1, ld_expm1>(numpy, "expm1") < 0) {
+        return -1;
+    }
     if (create_quad_unary_ufunc<quad_sin, ld_sin>(numpy, "sin") < 0) {
         return -1;
     }

quaddtype/release_tracker.md

@@ -34,7 +34,7 @@
 | log           | ✅    | ✅                                                                   |
 | log2          | ✅    | ✅                                                                   |
 | log10         | ✅    | ✅                                                                   |
-| expm1         |       |                                                                      |
+| expm1         | ✅    | ✅                                                                   |
 | log1p         | ✅    | ✅                                                                   |
 | sqrt          | ✅    | ✅                                                                   |
 | square        | ✅    | ✅                                                                   |

quaddtype/tests/test_quaddtype.py

@@ -429,6 +429,75 @@ def test_log1p(val):
             quad_result), f"Zero sign mismatch for {op}({val})"
 
 
+@pytest.mark.parametrize("val", [
+    # Cases close to 0 (where expm1 is most accurate and important)
+    "0.0", "-0.0",
+    "1e-10", "-1e-10", "1e-15", "-1e-15", "1e-20", "-1e-20",
+    "1e-100", "-1e-100", "1e-300", "-1e-300",
+    # Small values
+    "0.001", "-0.001", "0.01", "-0.01", "0.1", "-0.1",
+    # Moderate values
+    "0.5", "-0.5", "1.0", "-1.0", "2.0", "-2.0",
+    # Larger values
+    "5.0", "-5.0", "10.0", "-10.0", "20.0", "-20.0",
+    # Values that test exp behavior
+    "50.0", "-50.0", "100.0", "-100.0",
+    # Large positive values (exp(x) grows rapidly)
+    "200.0", "500.0", "700.0",
+    # Large negative values (should approach -1)
+    "-200.0", "-500.0", "-700.0", "-1000.0",
+    # Special values
+    "inf",   # Should give inf
+    "-inf",  # Should give -1
+    "nan", "-nan"
+])
+def test_expm1(val):
+    """Comprehensive test for expm1 function: exp(x) - 1
+
+    This function provides greater precision than exp(x) - 1 for small values of x.
+    """
+    quad_val = QuadPrecision(val)
+    float_val = float(val)
+
+    quad_result = np.expm1(quad_val)
+    float_result = np.expm1(float_val)
+
+    # Handle NaN cases
+    if np.isnan(float_result):
+        assert np.isnan(
+            float(quad_result)), f"Expected NaN for expm1({val}), got {float(quad_result)}"
+        return
+
+    # Handle infinity cases
+    if np.isinf(float_result):
+        assert np.isinf(
+            float(quad_result)), f"Expected inf for expm1({val}), got {float(quad_result)}"
+        assert np.sign(float_result) == np.sign(
+            float(quad_result)), f"Infinity sign mismatch for expm1({val})"
+        return
+
+    # For finite results
+    # expm1 is designed for high accuracy near 0, so use tight tolerances for small inputs
+    if abs(float(val)) < 1e-10:
+        rtol = 1e-15
+        atol = 1e-20
+    elif abs(float_result) < 1:
+        rtol = 1e-14
+        atol = 1e-15
+    else:
+        # For larger results, use relative tolerance
+        rtol = 1e-14
+        atol = 1e-15
+
+    np.testing.assert_allclose(float(quad_result), float_result, rtol=rtol, atol=atol,
+                               err_msg=f"Value mismatch for expm1({val})")
+
+    # Check sign for zero results
+    if float_result == 0.0:
+        assert np.signbit(float_result) == np.signbit(
+            quad_result), f"Zero sign mismatch for expm1({val})"
+
+
 @pytest.mark.parametrize("x", [
     # Regular values
     "0.0", "1.0", "2.0", "-1.0", "-2.0", "0.5", "-0.5",