add bincount function (#796)

* add bincount function

Author: KsanaKozlova

dpnp/dpnp_iface_statistics.py

@@ -51,6 +51,7 @@
     'amax',
     'amin',
     'average',
+    'bincount',
     'correlate',
     'cov',
     'max',
@@ -169,6 +170,28 @@ def average(x1, axis=None, weights=None, returned=False):
     return call_origin(numpy.average, x1, axis, weights, returned)
 
 
+def bincount(x1, weights=None, minlength=0):
+    """
+    Count number of occurrences of each value in array of non-negative ints.
+
+    For full documentation refer to :obj:`numpy.bincount`.
+
+    See Also
+    --------
+    :obj:`dpnp.unique` : Find the unique elements of an array.
+
+    Examples
+    --------
+    >>> import dpnp as np
+    >>> res = np.bincount(np.arange(5))
+    >>> print(res)
+    [1, 1, 1, 1, 1]
+
+    """
+
+    return call_origin(numpy.bincount, x1, weights=weights, minlength=minlength)
+
+
 def correlate(x1, x2, mode='valid'):
     """
     Cross-correlation of two 1-dimensional sequences.

tests/test_statistics.py

@@ -72,3 +72,42 @@ def test_nanvar(array):
     expected = numpy.nanvar(a, axis=None, ddof=0)
     result = dpnp.nanvar(ia, axis=None, ddof=0)
     numpy.testing.assert_array_equal(expected, result)
+
+
+class TestBincount:
+
+    @pytest.mark.parametrize("array",
+                             [[1, 2, 3],
+                              [1, 2, 2, 1, 2, 4],
+                              [2, 2, 2, 2]],
+                             ids=['[1, 2, 3]',
+                                  '[1, 2, 2, 1, 2, 4]',
+                                  '[2, 2, 2, 2]'])
+    @pytest.mark.parametrize("minlength",
+                             [0, 1, 3, 5],
+                             ids=['0', '1', '3', '5'])
+    def test_bincount_minlength(self, array, minlength):
+        np_a = numpy.array(array)
+        dpnp_a = dpnp.array(array)
+
+        expected = numpy.bincount(np_a, minlength=minlength)
+        result = dpnp.bincount(dpnp_a, minlength=minlength)
+        numpy.testing.assert_array_equal(expected, result)
+
+    @pytest.mark.parametrize("array",
+                             [[1, 2, 2, 1, 2, 4]],
+                             ids=['[1, 2, 2, 1, 2, 4]'])
+    @pytest.mark.parametrize("weights",
+                             [None,
+                              [0.3, 0.5, 0.2, 0.7, 1., -0.6],
+                              [2, 2, 2, 2, 2, 2]],
+                             ids=['None',
+                                  '[0.3, 0.5, 0.2, 0.7, 1., -0.6]',
+                                  '[2, 2, 2, 2, 2, 2]'])
+    def test_bincount_weights(self, array, weights):
+        np_a = numpy.array(array)
+        dpnp_a = dpnp.array(array)
+
+        expected = numpy.bincount(np_a, weights=weights)
+        result = dpnp.bincount(dpnp_a, weights=weights)
+        numpy.testing.assert_array_equal(expected, result)