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author | Matti Picus <matti.picus@gmail.com> | 2020-06-09 08:25:36 +0300 |
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committer | GitHub <noreply@github.com> | 2020-06-09 08:25:36 +0300 |
commit | e73c8e5479297f235b37fba91d6d0e8464be66a6 (patch) | |
tree | 713099e98dbc7f9c3d0d87564faac52e2046b463 /numpy/tests/typing/reveal/fromnumeric.py | |
parent | d647ef2d98852e322d487d6045d5860223dcda79 (diff) | |
parent | 2e238e411a4875d470a40cd0c351056ca30882ed (diff) | |
download | numpy-e73c8e5479297f235b37fba91d6d0e8464be66a6.tar.gz |
Merge pull request #16515 from person142/add-type-stubs
ENH: add type stubs from numpy-stubs
Diffstat (limited to 'numpy/tests/typing/reveal/fromnumeric.py')
-rw-r--r-- | numpy/tests/typing/reveal/fromnumeric.py | 135 |
1 files changed, 135 insertions, 0 deletions
diff --git a/numpy/tests/typing/reveal/fromnumeric.py b/numpy/tests/typing/reveal/fromnumeric.py new file mode 100644 index 000000000..7d79d5fa9 --- /dev/null +++ b/numpy/tests/typing/reveal/fromnumeric.py @@ -0,0 +1,135 @@ +"""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 |