def to_serializable(self):
"""
Exports intervals and length of `ArrayInterval` to a serializable object.
Intervals are exported as `self._intervals_to_str` to be human readable.
Allows easy export of `ArrayIntervals`, e.g. into .json format.
>>> from IPython.lib.pretty import pprint
>>> from paderbox.array.interval.core import ArrayInterval
>>> ai = ArrayInterval.from_str('1:4, 5:20, 21:25', shape=50)
>>> ai
ArrayInterval("1:4, 5:20, 21:25", shape=(50,))
>>> ai.to_serializable()
('1:4, 5:20, 21:25', (50,))
"""
intervals = self.normalized_intervals
if self.inverse_mode:
intervals = cy_invert_intervals(intervals, self.shape[-1])
return intervals_to_str(intervals), self.shape
def test_cy_invert_intervals():
assert cy_invert_intervals(((1, 2), (3, 4)), 5) == ((0, 1), (2, 3), (4, 5))
assert cy_invert_intervals(((0, 3), (4, 5)), 5) == ((3, 4), )
assert cy_invert_intervals(((0, 3), (4, 5)), 6) == ((3, 4), (5, 6))
assert cy_invert_intervals(((1, 3), (4, 5)), 5) == ((0, 1), (3, 4))
assert cy_invert_intervals((), 10) == ((0, 10), )
def __setitem__(self, item, value):
"""
>>> ai = zeros(50)
>>> ai[10:15] = 1
>>> ai
ArrayInterval("10:15", shape=(50,))
>>> ai[5:10] = 1
>>> ai
ArrayInterval("5:15", shape=(50,))
>>> ai[1:4] = 1
>>> ai
ArrayInterval("1:4, 5:15", shape=(50,))
>>> ai[15:20] = 1
>>> ai
ArrayInterval("1:4, 5:20", shape=(50,))
>>> ai[21:25] = 1
>>> ai
ArrayInterval("1:4, 5:20, 21:25", shape=(50,))
>>> ai[10:15] = 1
>>> ai
ArrayInterval("1:4, 5:20, 21:25", shape=(50,))
>>> ai[0:50] = 1
>>> ai[0:0] = 1
>>> ai
ArrayInterval("0:50", shape=(50,))
>>> ai[3:6]
array([ True, True, True])
>>> ai[3:6] = np.array([ True, False, True])
>>> ai
ArrayInterval("0:4, 5:50", shape=(50,))
>>> ai[10:13] = np.array([ False, True, False])
>>> ai
ArrayInterval("0:4, 5:10, 11:12, 13:50", shape=(50,))
>>> ai = zeros(50)
>>> ai[:] = 1
>>> ai[10:40] = 0
>>> ai
ArrayInterval("0:10, 40:50", shape=(50,))
>>> ai = zeros(50)
>>> ai2 = zeros(10)
>>> ai2[5:10] = 1
>>> ai[10:20] = ai2
>>> ai
ArrayInterval("15:20", shape=(50,))
>>> ai2 = zeros(20)
>>> ai2[0:10] = 1
>>> ai2[15:20] = 1
>>> ai[10:30] = ai2
>>> ai
ArrayInterval("10:20, 25:30", shape=(50,))
>>> ai[40:60] = ai2
Traceback (most recent call last):
...
ValueError: Could not broadcast input with length 20 into shape 10
>>> ai[-20:] = ai2
>>> ai
ArrayInterval("10:20, 25:40, 45:50", shape=(50,))
>>> ai = zeros(20)
>>> ai[:10] = ones(10)
>>> ai
ArrayInterval("0:10", shape=(20,))
>>> ai = ones(20)
>>> ai[:10] = zeros(10)
>>> ai
ArrayInterval("0:10", shape=(20,), inverse_mode=True)
"""
if not isinstance(item, slice):
raise NotImplementedError(
f'{self.__class__.__name__}.__setitem__ only supports slices '
f'for indexing, not {item!r}')
start, stop = cy_parse_item(item, self.shape)
if np.isscalar(value):
if value not in (0, 1):
# Numpy interprets values as boolean even if they are larger
# than 1. We don't do that here because using other values than
# boolean (or 0, 1) often indicates a bug or a wrong assumption
# by the user.
raise ValueError(
f'{self.__class__.__name__} only supports assigning '
f'boolean (or 0 or 1) scalar values, not {value!r}')
value = bool(value)
if self.inverse_mode:
value = not value
if value:
self.intervals = self.intervals + ((start, stop), )
else:
self.intervals = cy_non_intersection((start, stop),
self.intervals)
elif isinstance(value, (tuple, list, np.ndarray, ArrayInterval)):
if not isinstance(value, ArrayInterval):
# Inverse mode has to be the same as self.inverse_mode to have
# matching intervals. The value is inverted in
# ArrayInterval.__init__ if inverse_mode=True
value = ArrayInterval(value, inverse_mode=self.inverse_mode)
if len(value) != stop - start:
raise ValueError(
f'Could not broadcast input with length {len(value)} into '
f'shape {stop - start}')
value_intervals = value.intervals
if value.inverse_mode != self.inverse_mode:
value_intervals = cy_invert_intervals(value_intervals,
value.shape[-1])
intervals = cy_non_intersection((start, stop), self.intervals)
self.intervals = intervals + tuple([(s + start, e + start)
for s, e in value_intervals])
else:
raise NotImplementedError(
f'{self.__class__.__name__}.__setitem__ not implemented for '
f'type {type(value)} of {value!r}')