ENH: new function nunique

docs/api-reference.md

@@ -12,6 +12,7 @@
     create_diagonal
     expand_dims
     kron
+    nunique
     setdiff1d
     sinc
 ```

pyproject.toml

@@ -299,6 +299,7 @@ messages_control.disable = [
     "line-too-long",
     "missing-module-docstring",
     "missing-function-docstring",
+    "too-many-lines",
     "wrong-import-position",
 ]
 

src/array_api_extra/__init__.py

@@ -7,6 +7,7 @@
     create_diagonal,
     expand_dims,
     kron,
+    nunique,
     pad,
     setdiff1d,
     sinc,
@@ -23,6 +24,7 @@
     "create_diagonal",
     "expand_dims",
     "kron",
+    "nunique",
     "pad",
     "setdiff1d",
     "sinc",

src/array_api_extra/_funcs.py

@@ -3,6 +3,7 @@
 # https://github.com/scikit-learn/scikit-learn/pull/27910#issuecomment-2568023972
 from __future__ import annotations
 
+import math
 import operator
 import warnings
 from collections.abc import Callable
@@ -25,6 +26,7 @@
     "create_diagonal",
     "expand_dims",
     "kron",
+    "nunique",
     "pad",
     "setdiff1d",
     "sinc",
@@ -638,6 +640,42 @@
     return at(padded, tuple(slices)).set(x)
 
 
+def nunique(x: Array, /, *, xp: ModuleType | None = None) -> Array:
+    """
+    Count the number of unique elements in an array.
+
+    Compatible with JAX and Dask, whose laziness would be otherwise
+    problematic.
+
+    Parameters
+    ----------
+    x : Array
+        Input array.
+    xp : array_namespace, optional
+        The standard-compatible namespace for `x`. Default: infer.
+
+    Returns
+    -------
+    array: 0-dimensional integer array
+        The number of unique elements in `x`. It can be lazy.
+    """
+    if xp is None:
+        xp = array_namespace(x)
+
+    if is_jax_array(x):
+        # size= is JAX-specific
+        # https://github.com/data-apis/array-api/issues/883
+        _, counts = xp.unique_counts(x, size=_compat.size(x))
+        return xp.astype(counts, xp.bool).sum()
+
+    _, counts = xp.unique_counts(x)
+    n = _compat.size(counts)
+    # FIXME https://github.com/data-apis/array-api-compat/pull/231
+    if n is None or math.isnan(n):  # e.g. Dask, ndonnx
+        return xp.astype(counts, xp.bool).sum()
+    return xp.asarray(n, device=_compat.device(x))
+
+
 class _AtOp(Enum):
     """Operations for use in `xpx.at`."""
 

tests/test_funcs.py

@@ -11,6 +11,7 @@
     create_diagonal,
     expand_dims,
     kron,
+    nunique,
     pad,
     setdiff1d,
     sinc,
@@ -448,3 +449,21 @@ def test_list_of_tuples_width(self, xp: ModuleType):
 
         padded = pad(a, [(1, 0), (0, 0)])
         assert padded.shape == (4, 4)
+
+
+class TestNUnique:
+    def test_simple(self, xp: ModuleType):
+        a = xp.asarray([[1, 1], [0, 2], [2, 2]])
+        xp_assert_equal(nunique(a), xp.asarray(3))
+
+    def test_empty(self, xp: ModuleType):
+        a = xp.asarray([])
+        xp_assert_equal(nunique(a), xp.asarray(0))
+
+    def test_device(self, xp: ModuleType, device: Device):
+        a = xp.asarray(0.0, device=device)
+        assert get_device(nunique(a)) == device
+
+    def test_xp(self, xp: ModuleType):
+        a = xp.asarray([[1, 1], [0, 2], [2, 2]])
+        xp_assert_equal(nunique(a, xp=xp), xp.asarray(3))