"""Depth-2 twin of the nested shear preset (opt-in twin_shear_n128).

Same two L0->L1 boxes as shear_nested, no L2. Four fresh cases: U128, U256
(finest control = 2N), constant R128 depth 2, projected R128 depth 2; same
wave, phase, Re100/U=0.03, initialization, times, eps(root N), limits, floors.

Twin vs nested measures the effect of adding this nested L2 refinement.
Removing L2 also changes the finest spacing and refined volume, so the
contrast does not isolate abstract depth. Physics is the unchanged depth-2,
2N-control shear_wave.assess; shear_nested.py stays byte-identical.
"""

import numpy as np

import shear_nested as nested

ROOT_N = nested.ROOT_N
DEPTH = 2
FINEST_FACTOR = 2
REFINEMENTS = [nested.REFINEMENTS[0]]  # L0 -> L1 only, root coordinates
CASES = ((100, ROOT_N, 1, "constant"), (100, FINEST_FACTOR * ROOT_N, 1, "constant"),
         (100, ROOT_N, DEPTH, "constant"), (100, ROOT_N, DEPTH, "projected_linear"))
ROOT_STEPS = 16 * ROOT_N
LEAVES = [7936, 33792]
HOPS = [ROOT_STEPS * 2**level for level in range(DEPTH)]  # [2048, 4096]
WORK = sum(c * h for c, h in zip(LEAVES, HOPS))           # 154664960 per refined case
NU = nested.NU[:DEPTH]
TAU = nested.TAU[:DEPTH]


def leaf_masks():
    """Independent numpy leaf masks (root complement, full L1 boxes)."""
    child = np.zeros((ROOT_N, ROOT_N), bool)
    for x0, y0, x1, y1 in REFINEMENTS[0]:
        child[y0:y1, x0:x1] = True
    return [~child, np.kron(child, np.ones((2, 2), bool))]