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ORPA-pyOpenRPA/Resources/WPy64-3720/python-3.7.2.amd64/Lib/site-packages/dask/array/tests/test_percentiles.py

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import pytest
pytest.importorskip('numpy')
import numpy as np
import dask.array as da
from dask.array.utils import assert_eq, same_keys
def test_percentile():
d = da.ones((16,), chunks=(4,))
assert_eq(da.percentile(d, [0, 50, 100]),
np.array([1, 1, 1], dtype=d.dtype))
x = np.array([0, 0, 5, 5, 5, 5, 20, 20])
d = da.from_array(x, chunks=(3,))
result = da.percentile(d, [0, 50, 100])
assert_eq(da.percentile(d, [0, 50, 100]),
np.array([0, 5, 20], dtype=result.dtype))
assert same_keys(da.percentile(d, [0, 50, 100]),
da.percentile(d, [0, 50, 100]))
assert not same_keys(da.percentile(d, [0, 50, 100]),
da.percentile(d, [0, 50]))
x = np.array(['a', 'a', 'd', 'd', 'd', 'e'])
d = da.from_array(x, chunks=(3,))
assert_eq(da.percentile(d, [0, 50, 100]),
np.array(['a', 'd', 'e'], dtype=x.dtype))
@pytest.mark.skip
def test_percentile_with_categoricals():
try:
import pandas as pd
except ImportError:
return
x0 = pd.Categorical(['Alice', 'Bob', 'Charlie', 'Dennis', 'Alice', 'Alice'])
x1 = pd.Categorical(['Alice', 'Bob', 'Charlie', 'Dennis', 'Alice', 'Alice'])
dsk = {('x', 0): x0, ('x', 1): x1}
x = da.Array(dsk, 'x', chunks=((6, 6),))
p = da.percentile(x, [50])
assert (p.compute().categories == x0.categories).all()
assert (p.compute().codes == [0]).all()
assert same_keys(da.percentile(x, [50]),
da.percentile(x, [50]))
def test_percentiles_with_empty_arrays():
x = da.ones(10, chunks=((5, 0, 5),))
assert_eq(da.percentile(x, [10, 50, 90]), np.array([1, 1, 1], dtype=x.dtype))
@pytest.mark.parametrize('q', [5, 5.0, np.int64(5), np.float64(5)])
def test_percentiles_with_scaler_percentile(q):
# Regression test to ensure da.percentile works with scalar percentiles
# See #3020
d = da.ones((16,), chunks=(4,))
assert_eq(da.percentile(d, q), np.array([1], dtype=d.dtype))
def test_unknown_chunk_sizes():
x = da.random.random(1000, chunks=(100,))
x._chunks = ((np.nan,) * 10,)
result = da.percentile(x, 50).compute()
assert 0.1 < result < 0.9
a, b = da.percentile(x, [40, 60]).compute()
assert 0.1 < a < 0.9
assert 0.1 < b < 0.9
assert a < b