def test_rescale_max():
a = np.arange(0, 11)
# Max & first element has no effect
assert max(rescale_max(a, to=(0, 5))) == 5
assert max(rescale_max(a, to=(4, 5))) == 5
# Expanded & first elements have no effect
assert max(rescale_max(a, to=(0, 5), _from=(0, 3))) > 5
assert max(rescale_max(a, to=(2, 5), _from=(2, 3))) > 5
# branches #
assert rescale_max(2, _from=(0, 10)) == 0.2
def test_rescale_max():
a = np.arange(0, 11)
# Max & first element has no effect
assert max(rescale_max(a, to=(0, 5))) == 5
assert max(rescale_max(a, to=(4, 5))) == 5
# Expanded & first elements have no effect
assert max(rescale_max(a, to=(0, 5), _from=(0, 3))) > 5
assert max(rescale_max(a, to=(2, 5), _from=(2, 3))) > 5
# branches #
assert rescale_max(2, _from=(0, 10)) == 0.2
# Maintains the same index
s = pd.Series([1, 2, 3], index=[3, 2, 1])
result = rescale_max(s)
assert s.index.equals(result.index)
x = [-5, -4, -3, -2, -1, 0]
result = rescale_max(x)
assert result == approx([0, 0.2, 0.4, 0.6, 0.8, 1.0])
result = rescale_max(x, to=(0, 5))
assert result == approx([0, 1, 2, 3, 4, 5])
def test_rescale_max():
a = np.arange(0, 11)
# Max & first element has no effect
assert max(rescale_max(a, to=(0, 5))) == 5
assert max(rescale_max(a, to=(4, 5))) == 5
# Expanded & first elements have no effect
assert max(rescale_max(a, to=(0, 5), _from=(0, 3))) > 5
assert max(rescale_max(a, to=(2, 5), _from=(2, 3))) > 5
# branches #
assert rescale_max(2, _from=(0, 10)) == 0.2
# Maintains the same index
s = pd.Series([1, 2, 3], index=[3, 2, 1])
result = rescale_max(s)
assert s.index.equals(result.index)