add minimum in mathematical function

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

@@ -0,0 +1,24 @@
+import ivy
+
+#minimum
+
+def minimum(
+    x1,
+    x2,
+    /,
+    out=None,
+    *,
+    where=True,
+    casting="same_kind",
+    order="K",
+    dtype=None,
+    subok=True
+):
+    if dtype:
+        x1 = ivy.astype(ivy.array(x1), ivy.as_ivy_dtype(dtype))
+        x2 = ivy.astype(ivy.array(x2), ivy.as_ivy_dtype(dtype))
+    ret = ivy.minimum(x1, x2, out=out)
+    if ivy.is_array(where):
+        ret = ivy.where(where, ret, ivy.default(out, ivy.zeros_like(ret)), out=out)
+    return ret
+

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

@@ -0,0 +1,62 @@
+# global
+import numpy as np
+from hypothesis import given, strategies as st
+
+# local
+import ivy_tests.test_ivy.helpers as helpers
+import ivy.functional.backends.numpy as ivy_np
+import ivy_tests.test_ivy.test_frontends.test_numpy.helpers as np_frontend_helpers
+from ivy_tests.test_ivy.helpers import handle_cmd_line_args
+
+
+# minimum
+@handle_cmd_line_args
+@given(
+    dtype_and_x=helpers.dtype_and_values(
+        available_dtypes=ivy_np.valid_float_dtypes,num_arrays=2
+    ),
+    dtype=st.sampled_from(ivy_np.valid_float_dtypes + (None,)),
+    where=np_frontend_helpers.where(),
+    as_variable=helpers.array_bools(),
+    num_positional_args=helpers.num_positional_args(
+        fn_name="ivy.functional.frontends.numpy.minimum"
+    ),
+    native_array=helpers.array_bools(),
+)
+def test_numpy_minimum(
+        dtype_and_x,
+        dtype,
+        where,
+        as_variable,
+        with_out,
+        num_positional_args,
+        native_array,
+        fw,
+):
+    input_dtype, x = dtype_and_x
+    where = np_frontend_helpers.handle_where_and_array_bools(
+        where=where,
+        input_dtype=input_dtype,
+        as_variable=as_variable,
+        native_array=native_array,
+
+    )
+    np_frontend_helpers.test_frontend_function(
+        input_dtypes=input_dtype,
+        as_variable_flags=as_variable,
+        with_out=with_out,
+        num_positional_args=num_positional_args,
+        native_array_flags=native_array,
+        fw=fw,
+        frontend="numpy",
+        fn_tree="minimum",
+        x1=np.asarray(x[0], dtype=input_dtype[0]),
+        x2=np.asarray(x[1], dtype=input_dtype[1]),
+        out=None,
+        where=where,
+        casting="same_kind",
+        order="k",
+        dtype=dtype,
+        subok=True,
+        test_values=False,
+    )