snnlab.viz.layouts

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Deterministic geometry helpers with no plotting-backend dependency.

The signatures, defaults, fields, docstrings and implementation excerpts below are generated from the Python source. Annotations are shown as declared; unannotated means the source supplies no type annotation. These pages document callable surfaces, including legacy support utilities, without promising backend support for every declaration.

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def grid_layout(count: int, *, columns: int, x_range: tuple[float, float]=(0.0, 1.0), y_range: tuple[float, float]=(0.0, 1.0)) -> np.ndarray

Return a NumPy array of shape (count, 2) containing regular grid coordinates within x_range and y_range. columns determines the number of columns; the row count is rounded up to fit count. A zero count returns an empty (0, 2) array. Negative counts and non-positive column counts raise ValueError.

Return annotation: np.ndarray.

Return expressions (branch-dependent; names refer to the linked implementation):

np.empty((0, 2), dtype=float)

np.c_[x.ravel()[:count], y.ravel()[:count]]

Explicit exceptions in this implementation; called helpers may raise additional errors:

def grid_layout(
    count: int,
    *,
    columns: int,
    x_range: tuple[float, float] = (0.0, 1.0),
    y_range: tuple[float, float] = (0.0, 1.0),
) -> np.ndarray:
    if count < 0:
        raise ValueError("count must be non-negative")
    if columns <= 0:
        raise ValueError("columns must be positive")
    if count == 0:
        return np.empty((0, 2), dtype=float)
    rows = int(np.ceil(count / columns))
    x, y = np.meshgrid(
        np.linspace(*x_range, columns), np.linspace(*y_range, rows)
    )
    return np.c_[x.ravel()[:count], y.ravel()[:count]]