1 files changed, 0 insertions, 176 deletions
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()