Closes #3823 flatten function to match numpy

ServerModules.cfg

@@ -3,6 +3,7 @@
 
 ArgSortMsg
 ArraySetopsMsg
+AryUtil
 BroadcastMsg
 CastMsg
 ConcatenateMsg

arkouda/numpy/_manipulation_functions.py

@@ -81,8 +81,8 @@ def flip(
 
     elif isinstance(x, Strings):
         rep_msg = generic_msg(
-                cmd="flipString", args={"objType": x.objType, "obj": x.entry,  "size": x.size}
-            )
+            cmd="flipString", args={"objType": x.objType, "obj": x.entry, "size": x.size}
+        )
         return Strings.from_return_msg(cast(str, rep_msg))
     else:
         raise TypeError("flip only accepts type pdarray, Strings, or Categorical.")

arkouda/pdarrayclass.py

@@ -533,8 +533,7 @@ def _binop(self, other: pdarray, op: str) -> pdarray:
             except ValueError:
                 raise ValueError(f"shape mismatch {self.shape} {other.shape}")
             repMsg = generic_msg(
-                cmd=f"binopvv<{self.dtype},{other.dtype},{x1.ndim}>",
-                args={"op": op, "a": x1, "b": x2}
+                cmd=f"binopvv<{self.dtype},{other.dtype},{x1.ndim}>", args={"op": op, "a": x1, "b": x2}
             )
             if tmp_x1:
                 del x1
@@ -791,7 +790,7 @@ def opeq(self, other, op):
                 raise ValueError(f"shape mismatch {self.shape} {other.shape}")
             generic_msg(
                 cmd=f"opeqvv<{self.dtype},{other.dtype},{self.ndim}>",
-                args={"op": op, "a": self, "b": other}
+                args={"op": op, "a": self, "b": other},
             )
             return self
         # pdarray binop scalar
@@ -1769,6 +1768,21 @@ def reshape(self, *shape):
             ),
         )
 
+    def flatten(self):
+        """
+        Return a copy of the array collapsed into one dimension.
+
+        Returns
+        -------
+        A copy of the input array, flattened to one dimension.
+        """
+        return create_pdarray(
+            generic_msg(
+                cmd=f"flatten<{self.dtype.name},{self.ndim}>",
+                args={"a": self},
+            )
+        )
+
     def to_ndarray(self) -> np.ndarray:
         """
         Convert the array to a np.ndarray, transferring array data from the

arkouda/strings.py

@@ -2082,6 +2082,21 @@ def _get_grouping_keys(self) -> List[Strings]:
         """
         return [self]
 
+    def flatten(self):
+        """
+        Return a copy of the array collapsed into one dimension.
+
+        Returns
+        -------
+        A copy of the input array, flattened to one dimension.
+
+        Note
+        ----
+        As multidimensional Strings are currently supported,
+        flatten on a Strings object will always return itself.
+        """
+        return self
+
     def to_ndarray(self) -> np.ndarray:
         """
         Convert the array to a np.ndarray, transferring array data from the

src/AryUtil.chpl

@@ -944,6 +944,7 @@ module AryUtil
     /*
       flatten a multi-dimensional array into a 1D array
     */
+    @arkouda.registerCommand
     proc flatten(const ref a: [?d] ?t): [] t throws
       where a.rank > 1
     {
@@ -1003,6 +1004,12 @@ module AryUtil
       return flat;
     }
 
+    proc flatten(const ref a: [?d] ?t): [] t throws
+      where a.rank == 1
+    {
+      return a;
+    }
+
     // helper for computing an array element's index from its order
     record orderer {
       param rank: int;

tests/pdarrayclass_test.py

@@ -1,7 +1,8 @@
+import numpy as np
 import pytest
 
 import arkouda as ak
-import numpy as np
+from arkouda.testing import assert_equal as ak_assert_equal
 
 
 class TestPdarrayClass:
@@ -21,7 +22,20 @@ def test_shape(self):
 
     @pytest.mark.skip_if_max_rank_less_than(2)
     def test_shape_multidim(self):
-        a = ak.arange(4).reshape((2,2))
-        np_a = np.arange(4).reshape((2,2))
+        a = ak.arange(4).reshape((2, 2))
+        np_a = np.arange(4).reshape((2, 2))
         assert isinstance(a.shape, tuple)
         assert a.shape == np_a.shape
+
+    @pytest.mark.parametrize("size", pytest.prob_size)
+    def test_flatten(self, size):
+        a = ak.arange(size)
+        ak_assert_equal(a.flatten(), a)
+
+    @pytest.mark.skip_if_max_rank_less_than(3)
+    @pytest.mark.parametrize("size", pytest.prob_size)
+    def test_flatten(self, size):
+        size = size - (size % 4)
+        a = ak.arange(size)
+        b = a.reshape((2, 2, size / 4))
+        ak_assert_equal(b.flatten(), a)

tests/string_test.py

@@ -6,6 +6,7 @@
 import pytest
 
 import arkouda as ak
+from arkouda.testing import assert_equal as ak_assert_equal
 
 ak.verbose = False
 N = 100
@@ -910,3 +911,10 @@ def test_in1d(self, size):
         for word in more_words:
             inds |= strings == word
         assert (inds == matches).all()
+
+    @pytest.mark.parametrize("size", pytest.prob_size)
+    def test_flatten(self, size):
+        base_words, _ = self.base_words(size)
+        strings = self.get_strings(size, base_words)
+
+        ak_assert_equal(strings.flatten(), strings)