Initial attempt at NumPy trapz() function - Issue #17939 (#18093)

ivy/functional/frontends/numpy/mathematical_functions/sums_products_differences.py

@@ -154,3 +154,8 @@ def ediff1d(ary, to_end=None, to_begin=None):
         to_end = ivy.array(to_end)
         diffs = ivy.concat((diffs, to_end))
     return diffs
+
+
+@to_ivy_arrays_and_back
+def trapz(y, x=None, dx=1.0, axis=-1):
+    return ivy.trapz(y, x=x, dx=dx, axis=axis)

ivy_tests/test_ivy/test_frontends/test_numpy/test_mathematical_functions/test_sums_products_differences.py

@@ -1,4 +1,5 @@
 # global
+import numpy as np
 from hypothesis import strategies as st, assume
 
 # local
@@ -365,3 +366,76 @@ def test_numpy_ediff1d(
         to_end=to_end,
         to_begin=to_begin,
     )
+
+
+# trapz
+@st.composite
+def _either_x_dx(draw):
+    rand = (draw(st.integers(min_value=0, max_value=1)),)
+    if rand == 0:
+        either_x_dx = draw(
+            helpers.dtype_and_values(
+                avaliable_dtypes=st.shared(
+                    helpers.get_dtypes("float"), key="trapz_dtype"
+                ),
+                min_value=-100,
+                max_value=100,
+                min_num_dims=1,
+                max_num_dims=3,
+                min_dim_size=1,
+                max_dim_size=3,
+            )
+        )
+        return rand, either_x_dx
+    else:
+        either_x_dx = draw(
+            st.floats(min_value=-10, max_value=10),
+        )
+        return rand, either_x_dx
+
+
+@handle_frontend_test(
+    fn_tree="numpy.trapz",
+    dtype_values_axis=helpers.dtype_values_axis(
+        available_dtypes=st.shared(helpers.get_dtypes("float"), key="trapz_dtype"),
+        min_value=-100,
+        max_value=100,
+        min_num_dims=1,
+        max_num_dims=3,
+        min_dim_size=1,
+        max_dim_size=3,
+        allow_neg_axes=True,
+        valid_axis=True,
+        force_int_axis=True,
+    ),
+    rand_either=_either_x_dx(),
+)
+def test_numpy_trapz(
+    dtype_values_axis,
+    rand_either,
+    fn_tree,
+    frontend,
+    test_flags,
+    on_device,
+):
+    input_dtype, y, axis = dtype_values_axis
+    rand, either_x_dx = rand_either
+    if rand == 0:
+        dtype_x, x = either_x_dx
+        x = np.asarray(x, dtype=dtype_x)
+        dx = None
+    else:
+        x = None
+        dx = either_x_dx
+    helpers.test_frontend_function(
+        input_dtypes=input_dtype,
+        frontend=frontend,
+        fn_tree=fn_tree,
+        test_flags=test_flags,
+        on_device=on_device,
+        y=np.asarray(y[0], dtype=input_dtype[0]),
+        x=x,
+        dx=dx,
+        axis=axis,
+    )
+