Merge branch 'master' into fix-issue-10244

27 files changed, 0 insertions, 1372 deletions

diff --git a/numpy/tests/typing/fail/array_like.py b/numpy/tests/typing/fail/array_like.py
deleted file mode 100644
index a97e72dc7..000000000
--- a/numpy/tests/typing/fail/array_like.py
+++ /dev/null
@@ -1,16 +0,0 @@
-import numpy as np
-from numpy.typing import ArrayLike
-
-
-class A:
-    pass
-
-
-x1: ArrayLike = (i for i in range(10))  # E: Incompatible types in assignment
-x2: ArrayLike = A()  # E: Incompatible types in assignment
-x3: ArrayLike = {1: "foo", 2: "bar"}  # E: Incompatible types in assignment
-
-scalar = np.int64(1)
-scalar.__array__(dtype=np.float64)  # E: Unexpected keyword argument
-array = np.array([1])
-array.__array__(dtype=np.float64)  # E: Unexpected keyword argument
diff --git a/numpy/tests/typing/fail/fromnumeric.py b/numpy/tests/typing/fail/fromnumeric.py
deleted file mode 100644
index 66f8a89d0..000000000
--- a/numpy/tests/typing/fail/fromnumeric.py
+++ /dev/null
@@ -1,126 +0,0 @@
-"""Tests for :mod:`numpy.core.fromnumeric`."""
-
-import numpy as np
-
-A = np.array(True, ndmin=2, dtype=bool)
-A.setflags(write=False)
-
-a = np.bool_(True)
-
-np.take(a, None)  # E: No overload variant of "take" matches argument type
-np.take(a, axis=1.0)  # E: No overload variant of "take" matches argument type
-np.take(A, out=1)  # E: No overload variant of "take" matches argument type
-np.take(A, mode="bob")  # E: No overload variant of "take" matches argument type
-
-np.reshape(a, None)  # E: Argument 2 to "reshape" has incompatible type
-np.reshape(A, 1, order="bob")  # E: Argument "order" to "reshape" has incompatible type
-
-np.choose(a, None)  # E: No overload variant of "choose" matches argument type
-np.choose(a, out=1.0)  # E: No overload variant of "choose" matches argument type
-np.choose(A, mode="bob")  # E: No overload variant of "choose" matches argument type
-
-np.repeat(a, None)  # E: Argument 2 to "repeat" has incompatible type
-np.repeat(A, 1, axis=1.0)  # E: Argument "axis" to "repeat" has incompatible type
-
-np.swapaxes(A, None, 1)  # E: Argument 2 to "swapaxes" has incompatible type
-np.swapaxes(A, 1, [0])  # E: Argument 3 to "swapaxes" has incompatible type
-
-np.transpose(A, axes=1.0)  # E: Argument "axes" to "transpose" has incompatible type
-
-np.partition(a, None)  # E: Argument 2 to "partition" has incompatible type
-np.partition(
-    a, 0, axis="bob"  # E: Argument "axis" to "partition" has incompatible type
-)
-np.partition(
-    A, 0, kind="bob"  # E: Argument "kind" to "partition" has incompatible type
-)
-np.partition(
-    A, 0, order=range(5)  # E: Argument "order" to "partition" has incompatible type
-)
-
-np.argpartition(  # E: No overload variant of "argpartition" matches argument type
-    a, None
-)
-np.argpartition(  # E: No overload variant of "argpartition" matches argument type
-    a, 0, axis="bob"
-)
-np.argpartition(  # E: No overload variant of "argpartition" matches argument type
-    A, 0, kind="bob"
-)
-np.argpartition(
-    A, 0, order=range(5)  # E: Argument "order" to "argpartition" has incompatible type
-)
-
-np.sort(A, axis="bob")  # E: Argument "axis" to "sort" has incompatible type
-np.sort(A, kind="bob")  # E: Argument "kind" to "sort" has incompatible type
-np.sort(A, order=range(5))  # E: Argument "order" to "sort" has incompatible type
-
-np.argsort(A, axis="bob")  # E: Argument "axis" to "argsort" has incompatible type
-np.argsort(A, kind="bob")  # E: Argument "kind" to "argsort" has incompatible type
-np.argsort(A, order=range(5))  # E: Argument "order" to "argsort" has incompatible type
-
-np.argmax(A, axis="bob")  # E: No overload variant of "argmax" matches argument type
-np.argmax(A, kind="bob")  # E: No overload variant of "argmax" matches argument type
-
-np.argmin(A, axis="bob")  # E: No overload variant of "argmin" matches argument type
-np.argmin(A, kind="bob")  # E: No overload variant of "argmin" matches argument type
-
-np.searchsorted(  # E: No overload variant of "searchsorted" matches argument type
-    A[0], 0, side="bob"
-)
-np.searchsorted(  # E: No overload variant of "searchsorted" matches argument type
-    A[0], 0, sorter=1.0
-)
-
-np.resize(A, 1.0)  # E: Argument 2 to "resize" has incompatible type
-
-np.squeeze(A, 1.0)  # E: No overload variant of "squeeze" matches argument type
-
-np.diagonal(A, offset=None)  # E: Argument "offset" to "diagonal" has incompatible type
-np.diagonal(A, axis1="bob")  # E: Argument "axis1" to "diagonal" has incompatible type
-np.diagonal(A, axis2=[])  # E: Argument "axis2" to "diagonal" has incompatible type
-
-np.trace(A, offset=None)  # E: Argument "offset" to "trace" has incompatible type
-np.trace(A, axis1="bob")  # E: Argument "axis1" to "trace" has incompatible type
-np.trace(A, axis2=[])  # E: Argument "axis2" to "trace" has incompatible type
-
-np.ravel(a, order="bob")  # E: Argument "order" to "ravel" has incompatible type
-
-np.compress(
-    [True], A, axis=1.0  # E: Argument "axis" to "compress" has incompatible type
-)
-
-np.clip(a, 1, 2, out=1)  # E: No overload variant of "clip" matches argument type
-np.clip(1, None, None)  # E: No overload variant of "clip" matches argument type
-
-np.sum(a, axis=1.0)  # E: No overload variant of "sum" matches argument type
-np.sum(a, keepdims=1.0)  # E: No overload variant of "sum" matches argument type
-np.sum(a, initial=[1])  # E: No overload variant of "sum" matches argument type
-
-np.all(a, axis=1.0)  # E: No overload variant of "all" matches argument type
-np.all(a, keepdims=1.0)  # E: No overload variant of "all" matches argument type
-np.all(a, out=1.0)  # E: No overload variant of "all" matches argument type
-
-np.any(a, axis=1.0)  # E: No overload variant of "any" matches argument type
-np.any(a, keepdims=1.0)  # E: No overload variant of "any" matches argument type
-np.any(a, out=1.0)  # E: No overload variant of "any" matches argument type
-
-np.cumsum(a, axis=1.0)  # E: Argument "axis" to "cumsum" has incompatible type
-np.cumsum(a, dtype=1.0)  # E: Argument "dtype" to "cumsum" has incompatible type
-np.cumsum(a, out=1.0)  # E: Argument "out" to "cumsum" has incompatible type
-
-np.ptp(a, axis=1.0)  # E: No overload variant of "ptp" matches argument type
-np.ptp(a, keepdims=1.0)  # E: No overload variant of "ptp" matches argument type
-np.ptp(a, out=1.0)  # E: No overload variant of "ptp" matches argument type
-
-np.amax(a, axis=1.0)  # E: No overload variant of "amax" matches argument type
-np.amax(a, keepdims=1.0)  # E: No overload variant of "amax" matches argument type
-np.amax(a, out=1.0)  # E: No overload variant of "amax" matches argument type
-np.amax(a, initial=[1.0])  # E: No overload variant of "amax" matches argument type
-np.amax(a, where=[1.0])  # E: List item 0 has incompatible type
-
-np.amin(a, axis=1.0)  # E: No overload variant of "amin" matches argument type
-np.amin(a, keepdims=1.0)  # E: No overload variant of "amin" matches argument type
-np.amin(a, out=1.0)  # E: No overload variant of "amin" matches argument type
-np.amin(a, initial=[1.0])  # E: No overload variant of "amin" matches argument type
-np.amin(a, where=[1.0])  # E: List item 0 has incompatible type
diff --git a/numpy/tests/typing/fail/ndarray.py b/numpy/tests/typing/fail/ndarray.py
deleted file mode 100644
index 5a5130d40..000000000
--- a/numpy/tests/typing/fail/ndarray.py
+++ /dev/null
@@ -1,11 +0,0 @@
-import numpy as np
-
-# Ban setting dtype since mutating the type of the array in place
-# makes having ndarray be generic over dtype impossible. Generally
-# users should use `ndarray.view` in this situation anyway. See
-#
-# https://github.com/numpy/numpy-stubs/issues/7
-#
-# for more context.
-float_array = np.array([1.0])
-float_array.dtype = np.bool_  # E: Property "dtype" defined in "ndarray" is read-only
diff --git a/numpy/tests/typing/fail/numerictypes.py b/numpy/tests/typing/fail/numerictypes.py
deleted file mode 100644
index dd03eacc1..000000000
--- a/numpy/tests/typing/fail/numerictypes.py
+++ /dev/null
@@ -1,13 +0,0 @@
-import numpy as np
-
-# Techincally this works, but probably shouldn't. See
-#
-# https://github.com/numpy/numpy/issues/16366
-#
-np.maximum_sctype(1)  # E: incompatible type "int"
-
-np.issubsctype(1, np.int64)  # E: incompatible type "int"
-
-np.issubdtype(1, np.int64)  # E: incompatible type "int"
-
-np.find_common_type(np.int64, np.int64)  # E: incompatible type "Type[int64]"
diff --git a/numpy/tests/typing/fail/scalars.py b/numpy/tests/typing/fail/scalars.py
deleted file mode 100644
index 5d7221895..000000000
--- a/numpy/tests/typing/fail/scalars.py
+++ /dev/null
@@ -1,81 +0,0 @@
-import numpy as np
-
-# Construction
-
-np.float32(3j)  # E: incompatible type
-
-# Technically the following examples are valid NumPy code. But they
-# are not considered a best practice, and people who wish to use the
-# stubs should instead do
-#
-# np.array([1.0, 0.0, 0.0], dtype=np.float32)
-# np.array([], dtype=np.complex64)
-#
-# See e.g. the discussion on the mailing list
-#
-# https://mail.python.org/pipermail/numpy-discussion/2020-April/080566.html
-#
-# and the issue
-#
-# https://github.com/numpy/numpy-stubs/issues/41
-#
-# for more context.
-np.float32([1.0, 0.0, 0.0])  # E: incompatible type
-np.complex64([])  # E: incompatible type
-
-np.complex64(1, 2)  # E: Too many arguments
-# TODO: protocols (can't check for non-existent protocols w/ __getattr__)
-
-np.datetime64(0)  # E: non-matching overload
-
-dt_64 = np.datetime64(0, "D")
-td_64 = np.timedelta64(1, "h")
-
-dt_64 + dt_64  # E: Unsupported operand types
-
-td_64 - dt_64  # E: Unsupported operand types
-td_64 / dt_64  # E: No overload
-td_64 % 1  # E: Unsupported operand types
-td_64 % dt_64  # E: Unsupported operand types
-
-
-class A:
-    def __float__(self):
-        return 1.0
-
-
-np.int8(A())  # E: incompatible type
-np.int16(A())  # E: incompatible type
-np.int32(A())  # E: incompatible type
-np.int64(A())  # E: incompatible type
-np.uint8(A())  # E: incompatible type
-np.uint16(A())  # E: incompatible type
-np.uint32(A())  # E: incompatible type
-np.uint64(A())  # E: incompatible type
-
-np.void("test")  # E: incompatible type
-
-np.generic(1)  # E: Cannot instantiate abstract class
-np.number(1)  # E: Cannot instantiate abstract class
-np.integer(1)  # E: Cannot instantiate abstract class
-np.signedinteger(1)  # E: Cannot instantiate abstract class
-np.unsignedinteger(1)  # E: Cannot instantiate abstract class
-np.inexact(1)  # E: Cannot instantiate abstract class
-np.floating(1)  # E: Cannot instantiate abstract class
-np.complexfloating(1)  # E: Cannot instantiate abstract class
-np.character("test")  # E: Cannot instantiate abstract class
-np.flexible(b"test")  # E: Cannot instantiate abstract class
-
-np.float64(value=0.0)  # E: Unexpected keyword argument
-np.int64(value=0)  # E: Unexpected keyword argument
-np.uint64(value=0)  # E: Unexpected keyword argument
-np.complex128(value=0.0j)  # E: Unexpected keyword argument
-np.str_(value='bob')  # E: No overload variant
-np.bytes_(value=b'test')  # E: No overload variant
-np.void(value=b'test')  # E: Unexpected keyword argument
-np.bool_(value=True)  # E: Unexpected keyword argument
-np.datetime64(value="2019")  # E: No overload variant
-np.timedelta64(value=0)  # E: Unexpected keyword argument
-
-np.bytes_(b"hello", encoding='utf-8')  # E: No overload variant
-np.str_("hello", encoding='utf-8')  # E: No overload variant
diff --git a/numpy/tests/typing/fail/simple.py b/numpy/tests/typing/fail/simple.py
deleted file mode 100644
index b5e9d1b13..000000000
--- a/numpy/tests/typing/fail/simple.py
+++ /dev/null
@@ -1,10 +0,0 @@
-"""Simple expression that should fail with mypy."""
-
-import numpy as np
-
-# Array creation routines checks
-np.zeros("test")  # E: incompatible type
-np.zeros()  # E: Too few arguments
-
-np.ones("test")  # E: incompatible type
-np.ones()  # E: Too few arguments
diff --git a/numpy/tests/typing/fail/ufuncs.py b/numpy/tests/typing/fail/ufuncs.py
deleted file mode 100644
index 4da9d08ba..000000000
--- a/numpy/tests/typing/fail/ufuncs.py
+++ /dev/null
@@ -1,7 +0,0 @@
-import numpy as np
-
-np.sin.nin + "foo"  # E: Unsupported operand types
-np.sin(1, foo="bar")  # E: Unexpected keyword argument
-np.sin(1, extobj=["foo", "foo", "foo"])  # E: incompatible type
-
-np.abs(None)  # E: incompatible type
diff --git a/numpy/tests/typing/fail/warnings_and_errors.py b/numpy/tests/typing/fail/warnings_and_errors.py
deleted file mode 100644
index 7390cc45f..000000000
--- a/numpy/tests/typing/fail/warnings_and_errors.py
+++ /dev/null
@@ -1,7 +0,0 @@
-import numpy as np
-
-np.AxisError(1.0)  # E: Argument 1 to "AxisError" has incompatible type
-np.AxisError(1, ndim=2.0)  # E: Argument "ndim" to "AxisError" has incompatible type
-np.AxisError(
-    2, msg_prefix=404  # E: Argument "msg_prefix" to "AxisError" has incompatible type
-)
diff --git a/numpy/tests/typing/mypy.ini b/numpy/tests/typing/mypy.ini
deleted file mode 100644
index 91d93588a..000000000
--- a/numpy/tests/typing/mypy.ini
+++ /dev/null
@@ -1,8 +0,0 @@
-[mypy]
-mypy_path = ../../..
-
-[mypy-numpy]
-ignore_errors = True
-
-[mypy-numpy.*]
-ignore_errors = True
diff --git a/numpy/tests/typing/pass/array_like.py b/numpy/tests/typing/pass/array_like.py
deleted file mode 100644
index 6b823ca7e..000000000
--- a/numpy/tests/typing/pass/array_like.py
+++ /dev/null
@@ -1,39 +0,0 @@
-from typing import Any, List, Optional
-
-import numpy as np
-from numpy.typing import ArrayLike, DtypeLike, _SupportsArray
-
-x1: ArrayLike = True
-x2: ArrayLike = 5
-x3: ArrayLike = 1.0
-x4: ArrayLike = 1 + 1j
-x5: ArrayLike = np.int8(1)
-x6: ArrayLike = np.float64(1)
-x7: ArrayLike = np.complex128(1)
-x8: ArrayLike = np.array([1, 2, 3])
-x9: ArrayLike = [1, 2, 3]
-x10: ArrayLike = (1, 2, 3)
-x11: ArrayLike = "foo"
-x12: ArrayLike = memoryview(b'foo')
-
-
-class A:
-    def __array__(self, dtype: DtypeLike = None) -> np.ndarray:
-        return np.array([1, 2, 3])
-
-
-x13: ArrayLike = A()
-
-scalar: _SupportsArray = np.int64(1)
-scalar.__array__(np.float64)
-array: _SupportsArray = np.array(1)
-array.__array__(np.float64)
-
-a: _SupportsArray = A()
-a.__array__(np.int64)
-a.__array__(dtype=np.int64)
-
-# Escape hatch for when you mean to make something like an object
-# array.
-object_array_scalar: Any = (i for i in range(10))
-np.array(object_array_scalar)
diff --git a/numpy/tests/typing/pass/dtype.py b/numpy/tests/typing/pass/dtype.py
deleted file mode 100644
index f954fdd44..000000000
--- a/numpy/tests/typing/pass/dtype.py
+++ /dev/null
@@ -1,3 +0,0 @@
-import numpy as np
-
-np.dtype(dtype=np.int64)
diff --git a/numpy/tests/typing/pass/fromnumeric.py b/numpy/tests/typing/pass/fromnumeric.py
deleted file mode 100644
index d9dd45c54..000000000
--- a/numpy/tests/typing/pass/fromnumeric.py
+++ /dev/null
@@ -1,185 +0,0 @@
-"""Tests for :mod:`numpy.core.fromnumeric`."""
-
-import numpy as np
-
-A = np.array(True, ndmin=2, dtype=bool)
-B = np.array(1.0, ndmin=2, dtype=np.float32)
-A.setflags(write=False)
-B.setflags(write=False)
-
-a = np.bool_(True)
-b = np.float32(1.0)
-c = 1.0
-
-np.take(a, 0)
-np.take(b, 0)
-np.take(c, 0)
-np.take(A, 0)
-np.take(B, 0)
-np.take(A, [0])
-np.take(B, [0])
-
-np.reshape(a, 1)
-np.reshape(b, 1)
-np.reshape(c, 1)
-np.reshape(A, 1)
-np.reshape(B, 1)
-
-np.choose(a, [True, True])
-np.choose(A, [1.0, 1.0])
-
-np.repeat(a, 1)
-np.repeat(b, 1)
-np.repeat(c, 1)
-np.repeat(A, 1)
-np.repeat(B, 1)
-
-np.swapaxes(A, 0, 0)
-np.swapaxes(B, 0, 0)
-
-np.transpose(a)
-np.transpose(b)
-np.transpose(c)
-np.transpose(A)
-np.transpose(B)
-
-np.partition(a, 0, axis=None)
-np.partition(b, 0, axis=None)
-np.partition(c, 0, axis=None)
-np.partition(A, 0)
-np.partition(B, 0)
-
-np.argpartition(a, 0)
-np.argpartition(b, 0)
-np.argpartition(c, 0)
-np.argpartition(A, 0)
-np.argpartition(B, 0)
-
-np.sort(A, 0)
-np.sort(B, 0)
-
-np.argsort(A, 0)
-np.argsort(B, 0)
-
-np.argmax(A)
-np.argmax(B)
-np.argmax(A, axis=0)
-np.argmax(B, axis=0)
-
-np.argmin(A)
-np.argmin(B)
-np.argmin(A, axis=0)
-np.argmin(B, axis=0)
-
-np.searchsorted(A[0], 0)
-np.searchsorted(B[0], 0)
-np.searchsorted(A[0], [0])
-np.searchsorted(B[0], [0])
-
-np.resize(a, (5, 5))
-np.resize(b, (5, 5))
-np.resize(c, (5, 5))
-np.resize(A, (5, 5))
-np.resize(B, (5, 5))
-
-np.squeeze(a)
-np.squeeze(b)
-np.squeeze(c)
-np.squeeze(A)
-np.squeeze(B)
-
-np.diagonal(A)
-np.diagonal(B)
-
-np.trace(A)
-np.trace(B)
-
-np.ravel(a)
-np.ravel(b)
-np.ravel(c)
-np.ravel(A)
-np.ravel(B)
-
-np.nonzero(A)
-np.nonzero(B)
-
-np.shape(a)
-np.shape(b)
-np.shape(c)
-np.shape(A)
-np.shape(B)
-
-np.compress([True], a)
-np.compress([True], b)
-np.compress([True], c)
-np.compress([True], A)
-np.compress([True], B)
-
-np.clip(a, 0, 1.0)
-np.clip(b, -1, 1)
-np.clip(a, 0, None)
-np.clip(b, None, 1)
-np.clip(c, 0, 1)
-np.clip(A, 0, 1)
-np.clip(B, 0, 1)
-np.clip(B, [0, 1], [1, 2])
-
-np.sum(a)
-np.sum(b)
-np.sum(c)
-np.sum(A)
-np.sum(B)
-np.sum(A, axis=0)
-np.sum(B, axis=0)
-
-np.all(a)
-np.all(b)
-np.all(c)
-np.all(A)
-np.all(B)
-np.all(A, axis=0)
-np.all(B, axis=0)
-np.all(A, keepdims=True)
-np.all(B, keepdims=True)
-
-np.any(a)
-np.any(b)
-np.any(c)
-np.any(A)
-np.any(B)
-np.any(A, axis=0)
-np.any(B, axis=0)
-np.any(A, keepdims=True)
-np.any(B, keepdims=True)
-
-np.cumsum(a)
-np.cumsum(b)
-np.cumsum(c)
-np.cumsum(A)
-np.cumsum(B)
-
-np.ptp(b)
-np.ptp(c)
-np.ptp(B)
-np.ptp(B, axis=0)
-np.ptp(B, keepdims=True)
-
-np.amax(a)
-np.amax(b)
-np.amax(c)
-np.amax(A)
-np.amax(B)
-np.amax(A, axis=0)
-np.amax(B, axis=0)
-np.amax(A, keepdims=True)
-np.amax(B, keepdims=True)
-
-np.amin(a)
-np.amin(b)
-np.amin(c)
-np.amin(A)
-np.amin(B)
-np.amin(A, axis=0)
-np.amin(B, axis=0)
-np.amin(A, keepdims=True)
-np.amin(B, keepdims=True)
diff --git a/numpy/tests/typing/pass/ndarray_conversion.py b/numpy/tests/typing/pass/ndarray_conversion.py
deleted file mode 100644
index 303cf53e4..000000000
--- a/numpy/tests/typing/pass/ndarray_conversion.py
+++ /dev/null
@@ -1,94 +0,0 @@
-import os
-import tempfile
-
-import numpy as np
-
-nd = np.array([[1, 2], [3, 4]])
-scalar_array = np.array(1)
-
-# item
-scalar_array.item()
-nd.item(1)
-nd.item(0, 1)
-nd.item((0, 1))
-
-# tolist is pretty simple
-
-# itemset
-scalar_array.itemset(3)
-nd.itemset(3, 0)
-nd.itemset((0, 0), 3)
-
-# tobytes
-nd.tobytes()
-nd.tobytes("C")
-nd.tobytes(None)
-
-# tofile
-if os.name != "nt":
-    with tempfile.NamedTemporaryFile(suffix=".txt") as tmp:
-        nd.tofile(tmp.name)
-        nd.tofile(tmp.name, "")
-        nd.tofile(tmp.name, sep="")
-
-        nd.tofile(tmp.name, "", "%s")
-        nd.tofile(tmp.name, format="%s")
-
-        nd.tofile(tmp)
-
-# dump is pretty simple
-# dumps is pretty simple
-
-# astype
-nd.astype("float")
-nd.astype(float)
-
-nd.astype(float, "K")
-nd.astype(float, order="K")
-
-nd.astype(float, "K", "unsafe")
-nd.astype(float, casting="unsafe")
-
-nd.astype(float, "K", "unsafe", True)
-nd.astype(float, subok=True)
-
-nd.astype(float, "K", "unsafe", True, True)
-nd.astype(float, copy=True)
-
-# byteswap
-nd.byteswap()
-nd.byteswap(True)
-
-# copy
-nd.copy()
-nd.copy("C")
-
-# view
-nd.view()
-nd.view(np.int64)
-nd.view(dtype=np.int64)
-nd.view(np.int64, np.matrix)
-nd.view(type=np.matrix)
-
-# getfield
-complex_array = np.array([[1 + 1j, 0], [0, 1 - 1j]], dtype=np.complex128)
-
-complex_array.getfield("float")
-complex_array.getfield(float)
-
-complex_array.getfield("float", 8)
-complex_array.getfield(float, offset=8)
-
-# setflags
-nd.setflags()
-
-nd.setflags(True)
-nd.setflags(write=True)
-
-nd.setflags(True, True)
-nd.setflags(write=True, align=True)
-
-nd.setflags(True, True, False)
-nd.setflags(write=True, align=True, uic=False)
-
-# fill is pretty simple
diff --git a/numpy/tests/typing/pass/ndarray_shape_manipulation.py b/numpy/tests/typing/pass/ndarray_shape_manipulation.py
deleted file mode 100644
index 0ca3dff39..000000000
--- a/numpy/tests/typing/pass/ndarray_shape_manipulation.py
+++ /dev/null
@@ -1,47 +0,0 @@
-import numpy as np
-
-nd1 = np.array([[1, 2], [3, 4]])
-
-# reshape
-nd1.reshape(4)
-nd1.reshape(2, 2)
-nd1.reshape((2, 2))
-
-nd1.reshape((2, 2), order="C")
-nd1.reshape(4, order="C")
-
-# resize
-nd1.resize()
-nd1.resize(4)
-nd1.resize(2, 2)
-nd1.resize((2, 2))
-
-nd1.resize((2, 2), refcheck=True)
-nd1.resize(4, refcheck=True)
-
-nd2 = np.array([[1, 2], [3, 4]])
-
-# transpose
-nd2.transpose()
-nd2.transpose(1, 0)
-nd2.transpose((1, 0))
-
-# swapaxes
-nd2.swapaxes(0, 1)
-
-# flatten
-nd2.flatten()
-nd2.flatten("C")
-
-# ravel
-nd2.ravel()
-nd2.ravel("C")
-
-# squeeze
-nd2.squeeze()
-
-nd3 = np.array([[1, 2]])
-nd3.squeeze(0)
-
-nd4 = np.array([[[1, 2]]])
-nd4.squeeze((0, 1))
diff --git a/numpy/tests/typing/pass/numerictypes.py b/numpy/tests/typing/pass/numerictypes.py
deleted file mode 100644
index 4f205cabc..000000000
--- a/numpy/tests/typing/pass/numerictypes.py
+++ /dev/null
@@ -1,29 +0,0 @@
-import numpy as np
-
-np.maximum_sctype("S8")
-np.maximum_sctype(object)
-
-np.issctype(object)
-np.issctype("S8")
-
-np.obj2sctype(list)
-np.obj2sctype(list, default=None)
-np.obj2sctype(list, default=np.string_)
-
-np.issubclass_(np.int32, int)
-np.issubclass_(np.float64, float)
-np.issubclass_(np.float64, (int, float))
-
-np.issubsctype("int64", int)
-np.issubsctype(np.array([1]), np.array([1]))
-
-np.issubdtype("S1", np.string_)
-np.issubdtype(np.float64, np.float32)
-
-np.sctype2char("S1")
-np.sctype2char(list)
-
-np.find_common_type([], [np.int64, np.float32, complex])
-np.find_common_type((), (np.int64, np.float32, complex))
-np.find_common_type([np.int64, np.float32], [])
-np.find_common_type([np.float32], [np.int64, np.float64])
diff --git a/numpy/tests/typing/pass/scalars.py b/numpy/tests/typing/pass/scalars.py
deleted file mode 100644
index 1c7ace282..000000000
--- a/numpy/tests/typing/pass/scalars.py
+++ /dev/null
@@ -1,98 +0,0 @@
-import numpy as np
-
-
-# Construction
-class C:
-    def __complex__(self):
-        return 3j
-
-
-class B:
-    def __int__(self):
-        return 4
-
-
-class A:
-    def __float__(self):
-        return 4.0
-
-
-np.complex64(3j)
-np.complex64(C())
-np.complex128(3j)
-np.complex128(C())
-np.complex128(None)
-
-np.int8(4)
-np.int16(3.4)
-np.int32(4)
-np.int64(-1)
-np.uint8(B())
-np.uint32()
-
-np.float16(A())
-np.float32(16)
-np.float64(3.0)
-np.float64(None)
-
-np.bytes_(b"hello")
-np.bytes_("hello", 'utf-8')
-np.bytes_("hello", encoding='utf-8')
-np.str_("hello")
-np.str_(b"hello", 'utf-8')
-np.str_(b"hello", encoding='utf-8')
-
-# Protocols
-float(np.int8(4))
-int(np.int16(5))
-np.int8(np.float32(6))
-
-# TODO(alan): test after https://github.com/python/typeshed/pull/2004
-# complex(np.int32(8))
-
-abs(np.int8(4))
-
-# Array-ish semantics
-np.int8().real
-np.int16().imag
-np.int32().data
-np.int64().flags
-
-np.uint8().itemsize * 2
-np.uint16().ndim + 1
-np.uint32().strides
-np.uint64().shape
-
-# Time structures
-np.datetime64()
-np.datetime64(0, "D")
-np.datetime64("2019")
-np.datetime64("2019", "D")
-np.datetime64(None)
-np.datetime64(None, "D")
-
-np.timedelta64()
-np.timedelta64(0)
-np.timedelta64(0, "D")
-np.timedelta64(None)
-np.timedelta64(None, "D")
-
-dt_64 = np.datetime64(0, "D")
-td_64 = np.timedelta64(1, "h")
-
-dt_64 + td_64
-dt_64 - dt_64
-dt_64 - td_64
-
-td_64 + td_64
-td_64 - td_64
-td_64 / 1.0
-td_64 / td_64
-td_64 % td_64
-
-np.void(1)
-np.void(np.int64(1))
-np.void(True)
-np.void(np.bool_(True))
-np.void(b"test")
-np.void(np.bytes_("test"))
diff --git a/numpy/tests/typing/pass/simple.py b/numpy/tests/typing/pass/simple.py
deleted file mode 100644
index e0157ab81..000000000
--- a/numpy/tests/typing/pass/simple.py
+++ /dev/null
@@ -1,176 +0,0 @@
-"""Simple expression that should pass with mypy."""
-import operator
-
-import numpy as np
-from typing import Iterable  # noqa: F401
-
-# Basic checks
-array = np.array([1, 2])
-
-
-def ndarray_func(x):
-    # type: (np.ndarray) -> np.ndarray
-    return x
-
-
-ndarray_func(np.array([1, 2]))
-array == 1
-array.dtype == float
-
-# Array creation routines checks
-ndarray_func(np.zeros([1, 2]))
-ndarray_func(np.ones([1, 2]))
-ndarray_func(np.empty([1, 2]))
-
-ndarray_func(np.zeros_like(array))
-ndarray_func(np.ones_like(array))
-ndarray_func(np.empty_like(array))
-
-# Dtype construction
-np.dtype(float)
-np.dtype(np.float64)
-np.dtype(None)
-np.dtype("float64")
-np.dtype(np.dtype(float))
-np.dtype(("U", 10))
-np.dtype((np.int32, (2, 2)))
-# Define the arguments on the previous line to prevent bidirectional
-# type inference in mypy from broadening the types.
-two_tuples_dtype = [("R", "u1"), ("G", "u1"), ("B", "u1")]
-np.dtype(two_tuples_dtype)
-
-three_tuples_dtype = [("R", "u1", 2)]
-np.dtype(three_tuples_dtype)
-
-mixed_tuples_dtype = [("R", "u1"), ("G", np.unicode_, 1)]
-np.dtype(mixed_tuples_dtype)
-
-shape_tuple_dtype = [("R", "u1", (2, 2))]
-np.dtype(shape_tuple_dtype)
-
-shape_like_dtype = [("R", "u1", (2, 2)), ("G", np.unicode_, 1)]
-np.dtype(shape_like_dtype)
-
-object_dtype = [("field1", object)]
-np.dtype(object_dtype)
-
-np.dtype({"col1": ("U10", 0), "col2": ("float32", 10)})
-np.dtype((np.int32, {"real": (np.int16, 0), "imag": (np.int16, 2)}))
-np.dtype((np.int32, (np.int8, 4)))
-
-# Dtype comparision
-np.dtype(float) == float
-np.dtype(float) != np.float64
-np.dtype(float) < None
-np.dtype(float) <= "float64"
-np.dtype(float) > np.dtype(float)
-np.dtype(float) >= np.dtype(("U", 10))
-
-# Iteration and indexing
-def iterable_func(x):
-    # type: (Iterable) -> Iterable
-    return x
-
-
-iterable_func(array)
-[element for element in array]
-iter(array)
-zip(array, array)
-array[1]
-array[:]
-array[...]
-array[:] = 0
-
-array_2d = np.ones((3, 3))
-array_2d[:2, :2]
-array_2d[..., 0]
-array_2d[:2, :2] = 0
-
-# Other special methods
-len(array)
-str(array)
-array_scalar = np.array(1)
-int(array_scalar)
-float(array_scalar)
-# currently does not work due to https://github.com/python/typeshed/issues/1904
-# complex(array_scalar)
-bytes(array_scalar)
-operator.index(array_scalar)
-bool(array_scalar)
-
-# comparisons
-array < 1
-array <= 1
-array == 1
-array != 1
-array > 1
-array >= 1
-1 < array
-1 <= array
-1 == array
-1 != array
-1 > array
-1 >= array
-
-# binary arithmetic
-array + 1
-1 + array
-array += 1
-
-array - 1
-1 - array
-array -= 1
-
-array * 1
-1 * array
-array *= 1
-
-nonzero_array = np.array([1, 2])
-array / 1
-1 / nonzero_array
-float_array = np.array([1.0, 2.0])
-float_array /= 1
-
-array // 1
-1 // nonzero_array
-array //= 1
-
-array % 1
-1 % nonzero_array
-array %= 1
-
-divmod(array, 1)
-divmod(1, nonzero_array)
-
-array ** 1
-1 ** array
-array **= 1
-
-array << 1
-1 << array
-array <<= 1
-
-array >> 1
-1 >> array
-array >>= 1
-
-array & 1
-1 & array
-array &= 1
-
-array ^ 1
-1 ^ array
-array ^= 1
-
-array | 1
-1 | array
-array |= 1
-
-# unary arithmetic
--array
-+array
-abs(array)
-~array
-
-# Other methods
-np.array([1, 2]).transpose()
diff --git a/numpy/tests/typing/pass/simple_py3.py b/numpy/tests/typing/pass/simple_py3.py
deleted file mode 100644
index c05a1ce61..000000000
--- a/numpy/tests/typing/pass/simple_py3.py
+++ /dev/null
@@ -1,6 +0,0 @@
-import numpy as np
-
-array = np.array([1, 2])
-
-# The @ operator is not in python 2
-array @ array
diff --git a/numpy/tests/typing/pass/ufuncs.py b/numpy/tests/typing/pass/ufuncs.py
deleted file mode 100644
index 82172952a..000000000
--- a/numpy/tests/typing/pass/ufuncs.py
+++ /dev/null
@@ -1,13 +0,0 @@
-import numpy as np
-
-np.sin(1)
-np.sin([1, 2, 3])
-np.sin(1, out=np.empty(1))
-np.matmul(np.ones((2, 2, 2)), np.ones((2, 2, 2)), axes=[(0, 1), (0, 1), (0, 1)])
-np.sin(1, signature="D")
-np.sin(1, extobj=[16, 1, lambda: None])
-np.sin(1) + np.sin(1)
-np.sin.types[0]
-np.sin.__name__
-
-np.abs(np.array([1]))
diff --git a/numpy/tests/typing/pass/warnings_and_errors.py b/numpy/tests/typing/pass/warnings_and_errors.py
deleted file mode 100644
index 5b6ec2626..000000000
--- a/numpy/tests/typing/pass/warnings_and_errors.py
+++ /dev/null
@@ -1,7 +0,0 @@
-import numpy as np
-
-np.AxisError(1)
-np.AxisError(1, ndim=2)
-np.AxisError(1, ndim=None)
-np.AxisError(1, ndim=2, msg_prefix="error")
-np.AxisError(1, ndim=2, msg_prefix=None)
diff --git a/numpy/tests/typing/reveal/constants.py b/numpy/tests/typing/reveal/constants.py
deleted file mode 100644
index 8e00810bd..000000000
--- a/numpy/tests/typing/reveal/constants.py
+++ /dev/null
@@ -1,44 +0,0 @@
-import numpy as np
-
-reveal_type(np.Inf)  # E: float
-reveal_type(np.Infinity)  # E: float
-reveal_type(np.NAN)  # E: float
-reveal_type(np.NINF)  # E: float
-reveal_type(np.NZERO)  # E: float
-reveal_type(np.NaN)  # E: float
-reveal_type(np.PINF)  # E: float
-reveal_type(np.PZERO)  # E: float
-reveal_type(np.e)  # E: float
-reveal_type(np.euler_gamma)  # E: float
-reveal_type(np.inf)  # E: float
-reveal_type(np.infty)  # E: float
-reveal_type(np.nan)  # E: float
-reveal_type(np.pi)  # E: float
-
-reveal_type(np.ALLOW_THREADS)  # E: int
-reveal_type(np.BUFSIZE)  # E: int
-reveal_type(np.CLIP)  # E: int
-reveal_type(np.ERR_CALL)  # E: int
-reveal_type(np.ERR_DEFAULT)  # E: int
-reveal_type(np.ERR_IGNORE)  # E: int
-reveal_type(np.ERR_LOG)  # E: int
-reveal_type(np.ERR_PRINT)  # E: int
-reveal_type(np.ERR_RAISE)  # E: int
-reveal_type(np.ERR_WARN)  # E: int
-reveal_type(np.FLOATING_POINT_SUPPORT)  # E: int
-reveal_type(np.FPE_DIVIDEBYZERO)  # E: int
-reveal_type(np.FPE_INVALID)  # E: int
-reveal_type(np.FPE_OVERFLOW)  # E: int
-reveal_type(np.FPE_UNDERFLOW)  # E: int
-reveal_type(np.MAXDIMS)  # E: int
-reveal_type(np.MAY_SHARE_BOUNDS)  # E: int
-reveal_type(np.MAY_SHARE_EXACT)  # E: int
-reveal_type(np.RAISE)  # E: int
-reveal_type(np.SHIFT_DIVIDEBYZERO)  # E: int
-reveal_type(np.SHIFT_INVALID)  # E: int
-reveal_type(np.SHIFT_OVERFLOW)  # E: int
-reveal_type(np.SHIFT_UNDERFLOW)  # E: int
-reveal_type(np.UFUNC_BUFSIZE_DEFAULT)  # E: int
-reveal_type(np.WRAP)  # E: int
-reveal_type(np.little_endian)  # E: int
-reveal_type(np.tracemalloc_domain)  # E: int
diff --git a/numpy/tests/typing/reveal/fromnumeric.py b/numpy/tests/typing/reveal/fromnumeric.py
deleted file mode 100644
index f5feb3f5f..000000000
--- a/numpy/tests/typing/reveal/fromnumeric.py
+++ /dev/null
@@ -1,205 +0,0 @@
-"""Tests for :mod:`numpy.core.fromnumeric`."""
-
-import numpy as np
-
-A = np.array(True, ndmin=2, dtype=bool)
-B = np.array(1.0, ndmin=2, dtype=np.float32)
-A.setflags(write=False)
-B.setflags(write=False)
-
-a = np.bool_(True)
-b = np.float32(1.0)
-c = 1.0
-
-reveal_type(np.take(a, 0))  # E: numpy.bool_
-reveal_type(np.take(b, 0))  # E: numpy.float32
-reveal_type(
-    np.take(c, 0)  # E: Union[numpy.generic, datetime.datetime, datetime.timedelta]
-)
-reveal_type(
-    np.take(A, 0)  # E: Union[numpy.generic, datetime.datetime, datetime.timedelta]
-)
-reveal_type(
-    np.take(B, 0)  # E: Union[numpy.generic, datetime.datetime, datetime.timedelta]
-)
-reveal_type(
-    np.take(  # E: Union[Union[numpy.generic, datetime.datetime, datetime.timedelta], numpy.ndarray]
-        A, [0]
-    )
-)
-reveal_type(
-    np.take(  # E: Union[Union[numpy.generic, datetime.datetime, datetime.timedelta], numpy.ndarray]
-        B, [0]
-    )
-)
-
-reveal_type(np.reshape(a, 1))  # E: numpy.ndarray
-reveal_type(np.reshape(b, 1))  # E: numpy.ndarray
-reveal_type(np.reshape(c, 1))  # E: numpy.ndarray
-reveal_type(np.reshape(A, 1))  # E: numpy.ndarray
-reveal_type(np.reshape(B, 1))  # E: numpy.ndarray
-
-reveal_type(np.choose(a, [True, True]))  # E: numpy.bool_
-reveal_type(np.choose(A, [True, True]))  # E: numpy.ndarray
-
-reveal_type(np.repeat(a, 1))  # E: numpy.ndarray
-reveal_type(np.repeat(b, 1))  # E: numpy.ndarray
-reveal_type(np.repeat(c, 1))  # E: numpy.ndarray
-reveal_type(np.repeat(A, 1))  # E: numpy.ndarray
-reveal_type(np.repeat(B, 1))  # E: numpy.ndarray
-
-# TODO: Add tests for np.put()
-
-reveal_type(np.swapaxes(A, 0, 0))  # E: numpy.ndarray
-reveal_type(np.swapaxes(B, 0, 0))  # E: numpy.ndarray
-
-reveal_type(np.transpose(a))  # E: numpy.ndarray
-reveal_type(np.transpose(b))  # E: numpy.ndarray
-reveal_type(np.transpose(c))  # E: numpy.ndarray
-reveal_type(np.transpose(A))  # E: numpy.ndarray
-reveal_type(np.transpose(B))  # E: numpy.ndarray
-
-reveal_type(np.partition(a, 0, axis=None))  # E: numpy.ndarray
-reveal_type(np.partition(b, 0, axis=None))  # E: numpy.ndarray
-reveal_type(np.partition(c, 0, axis=None))  # E: numpy.ndarray
-reveal_type(np.partition(A, 0))  # E: numpy.ndarray
-reveal_type(np.partition(B, 0))  # E: numpy.ndarray
-
-reveal_type(np.argpartition(a, 0))  # E: numpy.integer
-reveal_type(np.argpartition(b, 0))  # E: numpy.integer
-reveal_type(np.argpartition(c, 0))  # E: numpy.ndarray
-reveal_type(np.argpartition(A, 0))  # E: numpy.ndarray
-reveal_type(np.argpartition(B, 0))  # E: numpy.ndarray
-
-reveal_type(np.sort(A, 0))  # E: numpy.ndarray
-reveal_type(np.sort(B, 0))  # E: numpy.ndarray
-
-reveal_type(np.argsort(A, 0))  # E: numpy.ndarray
-reveal_type(np.argsort(B, 0))  # E: numpy.ndarray
-
-reveal_type(np.argmax(A))  # E: numpy.integer
-reveal_type(np.argmax(B))  # E: numpy.integer
-reveal_type(np.argmax(A, axis=0))  # E: Union[numpy.integer, numpy.ndarray]
-reveal_type(np.argmax(B, axis=0))  # E: Union[numpy.integer, numpy.ndarray]
-
-reveal_type(np.argmin(A))  # E: numpy.integer
-reveal_type(np.argmin(B))  # E: numpy.integer
-reveal_type(np.argmin(A, axis=0))  # E: Union[numpy.integer, numpy.ndarray]
-reveal_type(np.argmin(B, axis=0))  # E: Union[numpy.integer, numpy.ndarray]
-
-reveal_type(np.searchsorted(A[0], 0))  # E: numpy.integer
-reveal_type(np.searchsorted(B[0], 0))  # E: numpy.integer
-reveal_type(np.searchsorted(A[0], [0]))  # E: numpy.ndarray
-reveal_type(np.searchsorted(B[0], [0]))  # E: numpy.ndarray
-
-reveal_type(np.resize(a, (5, 5)))  # E: numpy.ndarray
-reveal_type(np.resize(b, (5, 5)))  # E: numpy.ndarray
-reveal_type(np.resize(c, (5, 5)))  # E: numpy.ndarray
-reveal_type(np.resize(A, (5, 5)))  # E: numpy.ndarray
-reveal_type(np.resize(B, (5, 5)))  # E: numpy.ndarray
-
-reveal_type(np.squeeze(a))  # E: numpy.bool_
-reveal_type(np.squeeze(b))  # E: numpy.float32
-reveal_type(np.squeeze(c))  # E: numpy.ndarray
-reveal_type(np.squeeze(A))  # E: numpy.ndarray
-reveal_type(np.squeeze(B))  # E: numpy.ndarray
-
-reveal_type(np.diagonal(A))  # E: numpy.ndarray
-reveal_type(np.diagonal(B))  # E: numpy.ndarray
-
-reveal_type(np.trace(A))  # E: Union[numpy.number, numpy.ndarray]
-reveal_type(np.trace(B))  # E: Union[numpy.number, numpy.ndarray]
-
-reveal_type(np.ravel(a))  # E: numpy.ndarray
-reveal_type(np.ravel(b))  # E: numpy.ndarray
-reveal_type(np.ravel(c))  # E: numpy.ndarray
-reveal_type(np.ravel(A))  # E: numpy.ndarray
-reveal_type(np.ravel(B))  # E: numpy.ndarray
-
-reveal_type(np.nonzero(a))  # E: tuple[numpy.ndarray]
-reveal_type(np.nonzero(b))  # E: tuple[numpy.ndarray]
-reveal_type(np.nonzero(c))  # E: tuple[numpy.ndarray]
-reveal_type(np.nonzero(A))  # E: tuple[numpy.ndarray]
-reveal_type(np.nonzero(B))  # E: tuple[numpy.ndarray]
-
-reveal_type(np.shape(a))  # E: tuple[builtins.int]
-reveal_type(np.shape(b))  # E: tuple[builtins.int]
-reveal_type(np.shape(c))  # E: tuple[builtins.int]
-reveal_type(np.shape(A))  # E: tuple[builtins.int]
-reveal_type(np.shape(B))  # E: tuple[builtins.int]
-
-reveal_type(np.compress([True], a))  # E: numpy.ndarray
-reveal_type(np.compress([True], b))  # E: numpy.ndarray
-reveal_type(np.compress([True], c))  # E: numpy.ndarray
-reveal_type(np.compress([True], A))  # E: numpy.ndarray
-reveal_type(np.compress([True], B))  # E: numpy.ndarray
-
-reveal_type(np.clip(a, 0, 1.0))  # E: numpy.number
-reveal_type(np.clip(b, -1, 1))  # E: numpy.float32
-reveal_type(np.clip(c, 0, 1))  # E: numpy.number
-reveal_type(np.clip(A, 0, 1))  # E: Union[numpy.number, numpy.ndarray]
-reveal_type(np.clip(B, 0, 1))  # E: Union[numpy.number, numpy.ndarray]
-
-reveal_type(np.sum(a))  # E: numpy.number
-reveal_type(np.sum(b))  # E: numpy.float32
-reveal_type(np.sum(c))  # E: numpy.number
-reveal_type(np.sum(A))  # E: numpy.number
-reveal_type(np.sum(B))  # E: numpy.number
-reveal_type(np.sum(A, axis=0))  # E: Union[numpy.number, numpy.ndarray]
-reveal_type(np.sum(B, axis=0))  # E: Union[numpy.number, numpy.ndarray]
-
-reveal_type(np.all(a))  # E: numpy.bool_
-reveal_type(np.all(b))  # E: numpy.bool_
-reveal_type(np.all(c))  # E: numpy.bool_
-reveal_type(np.all(A))  # E: numpy.bool_
-reveal_type(np.all(B))  # E: numpy.bool_
-reveal_type(np.all(A, axis=0))  # E: Union[numpy.bool_, numpy.ndarray]
-reveal_type(np.all(B, axis=0))  # E: Union[numpy.bool_, numpy.ndarray]
-reveal_type(np.all(A, keepdims=True))  # E: Union[numpy.bool_, numpy.ndarray]
-reveal_type(np.all(B, keepdims=True))  # E: Union[numpy.bool_, numpy.ndarray]
-
-reveal_type(np.any(a))  # E: numpy.bool_
-reveal_type(np.any(b))  # E: numpy.bool_
-reveal_type(np.any(c))  # E: numpy.bool_
-reveal_type(np.any(A))  # E: numpy.bool_
-reveal_type(np.any(B))  # E: numpy.bool_
-reveal_type(np.any(A, axis=0))  # E: Union[numpy.bool_, numpy.ndarray]
-reveal_type(np.any(B, axis=0))  # E: Union[numpy.bool_, numpy.ndarray]
-reveal_type(np.any(A, keepdims=True))  # E: Union[numpy.bool_, numpy.ndarray]
-reveal_type(np.any(B, keepdims=True))  # E: Union[numpy.bool_, numpy.ndarray]
-
-reveal_type(np.cumsum(a))  # E: numpy.ndarray
-reveal_type(np.cumsum(b))  # E: numpy.ndarray
-reveal_type(np.cumsum(c))  # E: numpy.ndarray
-reveal_type(np.cumsum(A))  # E: numpy.ndarray
-reveal_type(np.cumsum(B))  # E: numpy.ndarray
-
-reveal_type(np.ptp(a))  # E: numpy.number
-reveal_type(np.ptp(b))  # E: numpy.float32
-reveal_type(np.ptp(c))  # E: numpy.number
-reveal_type(np.ptp(A))  # E: numpy.number
-reveal_type(np.ptp(B))  # E: numpy.number
-reveal_type(np.ptp(A, axis=0))  # E: Union[numpy.number, numpy.ndarray]
-reveal_type(np.ptp(B, axis=0))  # E: Union[numpy.number, numpy.ndarray]
-reveal_type(np.ptp(A, keepdims=True))  # E: Union[numpy.number, numpy.ndarray]
-reveal_type(np.ptp(B, keepdims=True))  # E: Union[numpy.number, numpy.ndarray]
-
-reveal_type(np.amax(a))  # E: numpy.number
-reveal_type(np.amax(b))  # E: numpy.float32
-reveal_type(np.amax(c))  # E: numpy.number
-reveal_type(np.amax(A))  # E: numpy.number
-reveal_type(np.amax(B))  # E: numpy.number
-reveal_type(np.amax(A, axis=0))  # E: Union[numpy.number, numpy.ndarray]
-reveal_type(np.amax(B, axis=0))  # E: Union[numpy.number, numpy.ndarray]
-reveal_type(np.amax(A, keepdims=True))  # E: Union[numpy.number, numpy.ndarray]
-reveal_type(np.amax(B, keepdims=True))  # E: Union[numpy.number, numpy.ndarray]
-
-reveal_type(np.amin(a))  # E: numpy.number
-reveal_type(np.amin(b))  # E: numpy.float32
-reveal_type(np.amin(c))  # E: numpy.number
-reveal_type(np.amin(A))  # E: numpy.number
-reveal_type(np.amin(B))  # E: numpy.number
-reveal_type(np.amin(A, axis=0))  # E: Union[numpy.number, numpy.ndarray]
-reveal_type(np.amin(B, axis=0))  # E: Union[numpy.number, numpy.ndarray]
-reveal_type(np.amin(A, keepdims=True))  # E: Union[numpy.number, numpy.ndarray]
-reveal_type(np.amin(B, keepdims=True))  # E: Union[numpy.number, numpy.ndarray]
diff --git a/numpy/tests/typing/reveal/ndarray_conversion.py b/numpy/tests/typing/reveal/ndarray_conversion.py
deleted file mode 100644
index 411adcf63..000000000
--- a/numpy/tests/typing/reveal/ndarray_conversion.py
+++ /dev/null
@@ -1,54 +0,0 @@
-import numpy as np
-
-nd = np.array([[1, 2], [3, 4]])
-
-# item
-reveal_type(nd.item())  # E: Any
-reveal_type(nd.item(1))  # E: Any
-reveal_type(nd.item(0, 1))  # E: Any
-reveal_type(nd.item((0, 1)))  # E: Any
-
-# tolist
-reveal_type(nd.tolist())  # E: builtins.list[Any]
-
-# itemset does not return a value
-# tostring is pretty simple
-# tobytes is pretty simple
-# tofile does not return a value
-# dump does not return a value
-# dumps is pretty simple
-
-# astype
-reveal_type(nd.astype("float"))  # E: numpy.ndarray
-reveal_type(nd.astype(float))  # E: numpy.ndarray
-reveal_type(nd.astype(float, "K"))  # E: numpy.ndarray
-reveal_type(nd.astype(float, "K", "unsafe"))  # E: numpy.ndarray
-reveal_type(nd.astype(float, "K", "unsafe", True))  # E: numpy.ndarray
-reveal_type(nd.astype(float, "K", "unsafe", True, True))  # E: numpy.ndarray
-
-# byteswap
-reveal_type(nd.byteswap())  # E: numpy.ndarray
-reveal_type(nd.byteswap(True))  # E: numpy.ndarray
-
-# copy
-reveal_type(nd.copy())  # E: numpy.ndarray
-reveal_type(nd.copy("C"))  # E: numpy.ndarray
-
-# view
-class SubArray(np.ndarray):
-    pass
-
-
-reveal_type(nd.view())  # E: numpy.ndarray
-reveal_type(nd.view(np.int64))  # E: numpy.ndarray
-# replace `Any` with `numpy.matrix` when `matrix` will be added to stubs
-reveal_type(nd.view(np.int64, np.matrix))  # E: Any
-reveal_type(nd.view(np.int64, SubArray))  # E: SubArray
-
-# getfield
-reveal_type(nd.getfield("float"))  # E: numpy.ndarray
-reveal_type(nd.getfield(float))  # E: numpy.ndarray
-reveal_type(nd.getfield(float, 8))  # E: numpy.ndarray
-
-# setflags does not return a value
-# fill does not return a value
diff --git a/numpy/tests/typing/reveal/ndarray_shape_manipulation.py b/numpy/tests/typing/reveal/ndarray_shape_manipulation.py
deleted file mode 100644
index a44e1cfa1..000000000
--- a/numpy/tests/typing/reveal/ndarray_shape_manipulation.py
+++ /dev/null
@@ -1,35 +0,0 @@
-import numpy as np
-
-nd = np.array([[1, 2], [3, 4]])
-
-# reshape
-reveal_type(nd.reshape())  # E: numpy.ndarray
-reveal_type(nd.reshape(4))  # E: numpy.ndarray
-reveal_type(nd.reshape(2, 2))  # E: numpy.ndarray
-reveal_type(nd.reshape((2, 2)))  # E: numpy.ndarray
-
-reveal_type(nd.reshape((2, 2), order="C"))  # E: numpy.ndarray
-reveal_type(nd.reshape(4, order="C"))  # E: numpy.ndarray
-
-# resize does not return a value
-
-# transpose
-reveal_type(nd.transpose())  # E: numpy.ndarray
-reveal_type(nd.transpose(1, 0))  # E: numpy.ndarray
-reveal_type(nd.transpose((1, 0)))  # E: numpy.ndarray
-
-# swapaxes
-reveal_type(nd.swapaxes(0, 1))  # E: numpy.ndarray
-
-# flatten
-reveal_type(nd.flatten())  # E: numpy.ndarray
-reveal_type(nd.flatten("C"))  # E: numpy.ndarray
-
-# ravel
-reveal_type(nd.ravel())  # E: numpy.ndarray
-reveal_type(nd.ravel("C"))  # E: numpy.ndarray
-
-# squeeze
-reveal_type(nd.squeeze())  # E: numpy.ndarray
-reveal_type(nd.squeeze(0))  # E: numpy.ndarray
-reveal_type(nd.squeeze((0, 2)))  # E: numpy.ndarray
diff --git a/numpy/tests/typing/reveal/numerictypes.py b/numpy/tests/typing/reveal/numerictypes.py
deleted file mode 100644
index e026158cd..000000000
--- a/numpy/tests/typing/reveal/numerictypes.py
+++ /dev/null
@@ -1,18 +0,0 @@
-import numpy as np
-
-reveal_type(np.issctype(np.generic))  # E: bool
-reveal_type(np.issctype("foo"))  # E: bool
-
-reveal_type(np.obj2sctype("S8"))  # E: Union[numpy.generic, None]
-reveal_type(np.obj2sctype("S8", default=None))  # E: Union[numpy.generic, None]
-reveal_type(
-    np.obj2sctype("foo", default=int)  # E: Union[numpy.generic, Type[builtins.int*]]
-)
-
-reveal_type(np.issubclass_(np.float64, float))  # E: bool
-reveal_type(np.issubclass_(np.float64, (int, float)))  # E: bool
-
-reveal_type(np.sctype2char("S8"))  # E: str
-reveal_type(np.sctype2char(list))  # E: str
-
-reveal_type(np.find_common_type([np.int64], [np.int64]))  # E: numpy.dtype
diff --git a/numpy/tests/typing/reveal/scalars.py b/numpy/tests/typing/reveal/scalars.py
deleted file mode 100644
index 8a9555fc3..000000000
--- a/numpy/tests/typing/reveal/scalars.py
+++ /dev/null
@@ -1,30 +0,0 @@
-import numpy as np
-
-x = np.complex64(3 + 2j)
-
-reveal_type(x.real)  # E: numpy.float32
-reveal_type(x.imag)  # E: numpy.float32
-
-reveal_type(x.real.real)  # E: numpy.float32
-reveal_type(x.real.imag)  # E: numpy.float32
-
-reveal_type(x.itemsize)  # E: int
-reveal_type(x.shape)  # E: tuple[builtins.int]
-reveal_type(x.strides)  # E: tuple[builtins.int]
-
-# Time structures
-dt = np.datetime64(0, "D")
-td = np.timedelta64(0, "D")
-
-reveal_type(dt + td)  # E: numpy.datetime64
-reveal_type(dt + 1)  # E: numpy.datetime64
-reveal_type(dt - dt)  # E: numpy.timedelta64
-reveal_type(dt - 1)  # E: numpy.timedelta64
-
-reveal_type(td + td)  # E: numpy.timedelta64
-reveal_type(td + 1)  # E: numpy.timedelta64
-reveal_type(td - td)  # E: numpy.timedelta64
-reveal_type(td - 1)  # E: numpy.timedelta64
-reveal_type(td / 1.0)  # E: numpy.timedelta64
-reveal_type(td / td)  # E: float
-reveal_type(td % td)  # E: numpy.timedelta64
diff --git a/numpy/tests/typing/reveal/warnings_and_errors.py b/numpy/tests/typing/reveal/warnings_and_errors.py
deleted file mode 100644
index c428deb7a..000000000
--- a/numpy/tests/typing/reveal/warnings_and_errors.py
+++ /dev/null
@@ -1,10 +0,0 @@
-from typing import Type
-
-import numpy as np
-
-reveal_type(np.ModuleDeprecationWarning())  # E: numpy.ModuleDeprecationWarning
-reveal_type(np.VisibleDeprecationWarning())  # E: numpy.VisibleDeprecationWarning
-reveal_type(np.ComplexWarning())  # E: numpy.ComplexWarning
-reveal_type(np.RankWarning())  # E: numpy.RankWarning
-reveal_type(np.TooHardError())  # E: numpy.TooHardError
-reveal_type(np.AxisError(1))  # E: numpy.AxisError