Filter

A 2-input mask gate: keep each data value whose aligned mask value is nonzero (zero or NaN drops, any other value keeps). The mask is an ordinary stream built from upstream comparison or logic ops. No Python predicate or callback - the gate logic runs entirely in C++ for batch, lazy, and graph regimes.

Gate rule: mask == 0 or isnan(mask) drops the aligned data value; any other mask value (positive, negative, non-NaN) keeps it. A NaN data value passes through unmodified when its aligned mask is nonzero.

Example

Keep the positive values by building a mask with GreaterThan.

import numpy as np
from screamer import Filter, GreaterThan

x = np.array([5.0, -2.0, 8.0, -1.0, 3.0])
mask = GreaterThan()(x, np.zeros_like(x))
survivors, idx = Filter()(x, mask)
print(survivors)

[5. 8. 3.]

Three regimes, byte-identical results

Batch (arrays or Streams)::

survivors, idx = Filter()(data_array, mask_array)

Lazy (iterators of (value, index) pairs)::

for val, idx in Filter()(iter(data_events), iter(mask_events)):
    ...

Graph (Node inputs inside a Pipeline)::

d, m = Input("d"), Input("m")
pipe = Pipeline(inputs=[d, m], outputs=[Filter()(d, m)])
survivors, idx = pipe(data_array, mask_array)