"""Coupled multi-layer finite-difference solver. Each included copper layer is a 2D 5-point sheet with per-layer face conductance sigma_s = t/rho [S] (square cells: independent of h); via and plated-through-pad barrels add vertical conductances between the layers they span AND reach copper on. Per layer the barrel attaches to the cell under it, or to the nearest copper cell within the pad footprint (+1 cell) - fills joined by thermal-relief spokes still connect. A barrel passing a (wider) antipad still bridges the layers above/below it with the full barrel length. At freq > 0 the per-layer sheet conductances and the barrel walls get the 1D skin-effect correction (see skin.py; AC results are a rigorous lower bound - lateral redistribution is not modeled). Two contact models for the terminals (each terminal = merged parts): - "uniform" (default): a conductor pressed onto the contact area injects the current orthogonally with UNIFORM surface density: every contact cell sources (sinks) I/N. The in-plane current density ramps across the contact instead of being zero. The pure-Neumann system is grounded at one V- cell (that cell's sink share is exactly the flux that exits through the ground reference, so the solution equals the singular system's). R = ( - ) / I; because the injection and averaging weights coincide, sum(edge powers) = I^2 R holds exactly and remains the consistency check. - "equipotential": ideal bonded lug; contact cells are Dirichlet (V+ = 1 V, V- = 0). R from the exact discrete electrode flux. Touching terminals are rejected (a direct face would short the Dirichlet regions); with "uniform" contacts touching is physically fine. The two models bracket a real contact: R_equipotential <= R_real <= R_uniform. Missing neighbors give no matrix term = insulated boundary. Current density per layer comes from face currents (np.gradient across the NaN staircase boundary would pollute the field). Power density per layer distributes each in-plane edge's dissipation half to each endpoint cell. All reported fields are rescaled to the test current I_test. """ from __future__ import annotations import time from dataclasses import dataclass, field import numpy as np from scipy import sparse from scipy.sparse import csgraph from scipy.sparse import linalg as sla from . import config, skin from .errors import ConnectivityError, ElectrodeError, SolverError from .geometry import Problem from .raster import RasterStack, electrodes_touch @dataclass class SolveInfo: method: str # "spsolve" | "cg+jacobi" n_unknowns: int iterations: int | None = None residual: float | None = None @dataclass class Edges: a: np.ndarray # int64 flat cell ids b: np.ndarray w: np.ndarray # conductance [S] via_index: np.ndarray # int32; -1 = in-plane edge dead_barrels: int = 0 # barrels spanning >=2 layers that found # fill copper on fewer than 2 of them @dataclass class ViaReport: x_mm: float y_mm: float kind: str drill_mm: float current_a: float # max barrel-segment current @ I_test power_w: float # total barrel dissipation @ I_test @dataclass class Result: R_ohm: float i_test: float V: np.ndarray # (L, ny, nx) volts @ I_test, NaN off-copper Jmag: np.ndarray # (L, ny, nx) A/m^2 @ I_test Parea: np.ndarray # (L, ny, nx) W/m^2 @ I_test layer_names: list[str] P_total: float # I_test^2 * R P_layers: list[float] # in-plane dissipation per layer @ I_test P_vias: float # total barrel dissipation @ I_test power_balance_rel: float # |sum(edge powers) - I^2 R| / I^2 R via_reports: list[ViaReport] # sorted by current, descending I1_a: float # electrode currents (unit drive) I2_a: float mismatch_rel: float n_free: int solve_info: SolveInfo # per-part terminal currents @ I_test: [(label, amps), ...]; # computed flux for "equipotential", prescribed area share for "uniform" part_currents1: list = field(default_factory=list) part_currents2: list = field(default_factory=list) contact_model: str = "uniform" freq_hz: float = 0.0 skin_depth_um: float | None = None rs_ratios: list[float] = field(default_factory=list) # R_AC/R_DC per layer timings: dict = field(default_factory=dict) def _shifts2d(): return [ ((slice(None), slice(None, -1)), (slice(None), slice(1, None))), ((slice(None, -1), slice(None)), (slice(1, None), slice(None))), ] def _sigma_2d(stack: RasterStack, li: int, sigma_layer: float, sigma_buildup: float) -> np.ndarray | None: """Per-cell sheet conductance for one layer, or None if uniform.""" if stack.buildup is None or sigma_buildup <= 0 \ or not stack.buildup[li].any(): return None s = np.full(stack.shape2d, sigma_layer) s[stack.buildup[li]] += sigma_buildup return s def build_edges(stack: RasterStack, problem: Problem, sigmas: list[float], via_factor: float = 1.0, sigma_buildup: float = 0.0) -> Edges: """All copper-copper conductances: in-plane faces + via barrels. sigmas: effective (possibly AC) sheet conductance per layer; via_factor: R_AC/R_DC of the barrel wall; sigma_buildup: extra sheet conductance on solder-buildup cells. Faces between cells of unequal conductance use the harmonic mean (series half-cells), which reduces exactly to sigma for uniform regions.""" L, ny, nx = stack.masks.shape plane = ny * nx aa, bb, ww, vv = [], [], [], [] for li in range(L): m = stack.masks[li] sig = sigmas[li] scell = _sigma_2d(stack, li, sig, sigma_buildup) base = li * plane for src, dst in _shifts2d(): pair = m[src] & m[dst] ii, jj = np.nonzero(pair) if src[0] == slice(None): # horizontal: j, j+1 a = base + ii * nx + jj b = a + 1 else: # vertical: i, i+1 a = base + ii * nx + jj b = a + nx aa.append(a.astype(np.int64)) bb.append(b.astype(np.int64)) if scell is None: ww.append(np.full(len(a), sig)) else: s_a = scell[src][pair] s_b = scell[dst][pair] ww.append(2.0 * s_a * s_b / (s_a + s_b)) vv.append(np.full(len(a), -1, dtype=np.int32)) h = stack.h_nm dead_barrels = 0 for vi, via in enumerate(problem.vias): cell = stack.cell_of(via.x, via.y) if cell is None: continue i, j = cell span = [li for li, layer in enumerate(problem.layers) if via.spans(layer.z_nm)] # Connection cell per layer: the cell under the barrel, or the # nearest copper cell whose center lies within the pad footprint # (+1 cell of rasterization slop) - fills joined to the barrel by # thermal-relief spokes still connect, wider antipads do not (the # barrel then bridges the layers above/below as before). r_nm = max(via.pad_nm, via.drill_nm + 300_000) / 2.0 + h win = int(r_nm // h) + 1 i0, i1 = max(0, i - win), min(ny, i + win + 1) j0, j1 = max(0, j - win), min(nx, j + win + 1) xs = stack.x0_nm + (np.arange(j0, j1) + 0.5) * h - via.x ys = stack.y0_nm + (np.arange(i0, i1) + 0.5) * h - via.y d2 = ys[:, None] ** 2 + xs[None, :] ** 2 d2 = np.where(d2 <= r_nm * r_nm, d2, np.inf) present = [] # (layer, i, j) per layer for li in span: if stack.masks[li, i, j]: present.append((li, i, j)) continue dc = np.where(stack.masks[li, i0:i1, j0:j1], d2, np.inf) ci, cj = np.unravel_index(int(np.argmin(dc)), dc.shape) if np.isfinite(dc[ci, cj]): present.append((li, i0 + ci, j0 + cj)) if len(span) >= 2 and len(present) < 2: dead_barrels += 1 for (la, ia, ja), (lb, ib, jb) in zip(present[:-1], present[1:]): length = problem.layers[lb].z_nm - problem.layers[la].z_nm if length <= 0: continue r = via.barrel_resistance(length, problem.rho_ohm_m, problem.plating_nm) * via_factor aa.append(np.array([la * plane + ia * nx + ja], dtype=np.int64)) bb.append(np.array([lb * plane + ib * nx + jb], dtype=np.int64)) ww.append(np.array([1.0 / r])) vv.append(np.array([vi], dtype=np.int32)) if not aa: raise ConnectivityError("No copper found on the selected layers.") return Edges(a=np.concatenate(aa), b=np.concatenate(bb), w=np.concatenate(ww), via_index=np.concatenate(vv), dead_barrels=dead_barrels) def connected_restrict(stack: RasterStack, e1: np.ndarray, e2: np.ndarray, edges: Edges) -> tuple[bool, int]: """Keep only components (through-plane AND through-via) touching both terminals. Mutates stack.masks / e1 / e2. Returns (changed, n_components): whether anything was dropped (caller must rebuild edges) and how many disjoint copper groups survive.""" n = stack.masks.size graph = sparse.coo_matrix( (np.ones(len(edges.a)), (edges.a, edges.b)), shape=(n, n)) _, labels = csgraph.connected_components(graph, directed=False) labels3 = labels.reshape(stack.masks.shape) common = np.intersect1d(np.unique(labels3[e1]), np.unique(labels3[e2])) if len(common) == 0: raise ConnectivityError( "The two terminals are not connected by the selected fill " "layers (not even through vias). Check the layer selection and " "that the fills are up to date." ) keep = np.isin(labels3, common) & stack.masks changed = bool((stack.masks & ~keep).any()) stack.masks &= keep e1 &= keep e2 &= keep return changed, len(common) def _assemble(state: np.ndarray, edges: Edges, rhs_extra: np.ndarray | None): """Weighted-Laplacian assembly with Dirichlet elimination. state: 0 off, 1 free, 2 Dirichlet@1V, 3 Dirichlet@0V. rhs_extra: per-flat-cell current injection [A] added for free cells.""" n = state.size sa, sb = state[edges.a], state[edges.b] short = ((sa == 2) & (sb == 3)) | ((sa == 3) & (sb == 2)) if short.any(): n_via = int((edges.via_index[short] >= 0).sum()) raise ElectrodeError( f"The terminals are directly connected by {int(short.sum())} " f"conductance(s) ({n_via} via barrel(s)) without any free copper " f"in between - move the contacts apart." ) free = state == 1 n_free = int(free.sum()) if n_free == 0: raise ElectrodeError( "No free copper cells remain between the terminals - the " "contacts cover the whole fill at this grid resolution." ) idx = np.full(n, -1, dtype=np.int64) idx[free] = np.arange(n_free) diag = np.zeros(n_free) rhs = np.zeros(n_free) fa, fb = sa == 1, sb == 1 np.add.at(diag, idx[edges.a[fa]], edges.w[fa]) np.add.at(diag, idx[edges.b[fb]], edges.w[fb]) r1a = fa & (sb == 2) r1b = fb & (sa == 2) np.add.at(rhs, idx[edges.a[r1a]], edges.w[r1a]) np.add.at(rhs, idx[edges.b[r1b]], edges.w[r1b]) if rhs_extra is not None: rhs += rhs_extra[free] ff = fa & fb rows = np.concatenate([idx[edges.a[ff]], idx[edges.b[ff]], np.arange(n_free)]) cols = np.concatenate([idx[edges.b[ff]], idx[edges.a[ff]], np.arange(n_free)]) vals = np.concatenate([-edges.w[ff], -edges.w[ff], diag]) A = sparse.coo_matrix((vals, (rows, cols)), shape=(n_free, n_free)).tocsr() return A, rhs, idx def solve_system(A: sparse.csr_matrix, b: np.ndarray) -> tuple[np.ndarray, SolveInfo]: n = A.shape[0] if n <= config.SPSOLVE_MAX_UNKNOWNS: x = sla.spsolve(A.tocsc(), b) return x, SolveInfo(method="spsolve", n_unknowns=n) try: return _solve_amg(A, b) except ImportError: print("note: pyamg not installed - falling back to Jacobi-CG " "(much slower on large grids)") return _solve_cg_jacobi(A, b) def _solve_amg(A: sparse.csr_matrix, b: np.ndarray) -> tuple[np.ndarray, SolveInfo]: """CG preconditioned with smoothed-aggregation AMG: near-linear scaling on these 2D Laplacians and a fraction of spsolve's memory.""" import pyamg n = A.shape[0] ml = pyamg.smoothed_aggregation_solver(A.tocsr(), max_coarse=500) residuals: list[float] = [] x = ml.solve(b, tol=config.AMG_TOL, maxiter=300, accel="cg", residuals=residuals) res = float(np.linalg.norm(b - A @ x) / max(np.linalg.norm(b), 1e-300)) if not np.isfinite(res) or res > 1e-6: raise SolverError( f"AMG-CG did not converge (residual {res:.2e}). Try a " f"different grid size, or force the direct solver by raising " f"SPSOLVE_MAX_UNKNOWNS in config.py." ) return x, SolveInfo(method="amg+cg", n_unknowns=n, iterations=max(len(residuals) - 1, 0), residual=res) def _solve_cg_jacobi(A: sparse.csr_matrix, b: np.ndarray) -> tuple[np.ndarray, SolveInfo]: # The matrix is SPD, so CG is guaranteed to converge. Jacobi is the # only preconditioner in scipy that keeps the preconditioned operator # SPD without a factorization that can break down at this scale. n = A.shape[0] d = A.diagonal() M = sla.LinearOperator((n, n), lambda v: v / d) iters = 0 def count(_): nonlocal iters iters += 1 try: x, code = sla.cg(A, b, M=M, rtol=config.CG_TOL, maxiter=config.CG_MAXITER, callback=count) except TypeError: # scipy < 1.12 uses tol= x, code = sla.cg(A, b, M=M, tol=config.CG_TOL, maxiter=config.CG_MAXITER, callback=count) if code != 0: raise SolverError( f"CG did not converge in {config.CG_MAXITER} iterations " f"(code {code}). Try a coarser grid or raise CG_MAXITER." ) res = float(np.linalg.norm(b - A @ x) / np.linalg.norm(b)) return x, SolveInfo(method="cg+jacobi", n_unknowns=n, iterations=iters, residual=res) def _face_current_density(V2: np.ndarray, mask2: np.ndarray, sigma: float, h_m: float, t_m: float, sig2d: np.ndarray | None = None, rho: float | None = None) -> np.ndarray: """|J| (A/m^2) for one layer from face currents; V2 in volts. With a per-cell conductance map (buildup), face currents use the harmonic mean and J is referenced to the conductance-equivalent copper thickness t_eq = sigma_cell * rho (equals the geometric t for plain DC copper).""" ny, nx = mask2.shape face_x = mask2[:, :-1] & mask2[:, 1:] face_y = mask2[:-1, :] & mask2[1:, :] if sig2d is None: wx = wy = sigma teq = np.full((ny, nx), t_m) else: wx = 2.0 * sig2d[:, :-1] * sig2d[:, 1:] / (sig2d[:, :-1] + sig2d[:, 1:]) wy = 2.0 * sig2d[:-1, :] * sig2d[1:, :] / (sig2d[:-1, :] + sig2d[1:, :]) teq = sig2d * rho with np.errstate(invalid="ignore"): Ix = np.where(face_x, (V2[:, :-1] - V2[:, 1:]) * wx, 0.0) Iy = np.where(face_y, (V2[:-1, :] - V2[1:, :]) * wy, 0.0) IxP = np.zeros((ny, nx + 1)) IxP[:, 1:nx] = Ix IyP = np.zeros((ny + 1, nx)) IyP[1:ny, :] = Iy Jx = 0.5 * (IxP[:, :-1] + IxP[:, 1:]) Jy = 0.5 * (IyP[:-1, :] + IyP[1:, :]) Jmag = np.hypot(Jx, Jy) / (h_m * teq) Jmag[~mask2] = np.nan return Jmag def _solve_equipotential(stack, e1, e2, edges): """Dirichlet terminals at 1 V / 0 V. Returns (Vflat_unit, R, I1, I2, mismatch, volts_per_amp, info). Fields at 1 V drive; scale by i_test * R to get volts at I_test.""" if (layer := electrodes_touch(stack, e1, e2)) is not None: raise ElectrodeError( f"The terminals touch on {layer}. With the equipotential " f"contact model at least one cell of copper must separate " f"them; the uniform-injection model allows touching contacts." ) state = np.zeros(stack.masks.size, dtype=np.uint8) state[stack.masks.ravel()] = 1 state[e1.ravel()] = 2 state[e2.ravel()] = 3 A, rhs, idx = _assemble(state, edges, None) x, info = solve_system(A, rhs) Vflat = np.zeros(state.size) Vflat[state == 2] = 1.0 Vflat[state == 1] = x Ie = edges.w * (Vflat[edges.a] - Vflat[edges.b]) sa, sb = state[edges.a], state[edges.b] I1 = float(Ie[sa == 2].sum() - Ie[sb == 2].sum()) I2 = float(Ie[sb == 3].sum() - Ie[sa == 3].sum()) mismatch = abs(I1 - I2) / max(abs(I1), abs(I2), 1e-300) R = 1.0 / (0.5 * (I1 + I2)) return Vflat, R, I1, I2, mismatch, R, info def _solve_uniform(stack, e1, e2, edges): """Uniform orthogonal injection: every contact cell sources (sinks) 1 A / N. Grounded at one V- cell. Returns like _solve_equipotential; fields are at 1 A drive, so volts_per_amp = 1.""" n = stack.masks.size e1f, e2f = e1.ravel(), e2.ravel() n1, n2 = int(e1f.sum()), int(e2f.sum()) inj = np.zeros(n) inj[e1f] = 1.0 / n1 inj[e2f] = -1.0 / n2 state = np.zeros(n, dtype=np.uint8) state[stack.masks.ravel()] = 1 ground = int(np.flatnonzero(e2f)[0]) state[ground] = 3 # single Dirichlet 0 V reference; # its sink share is exactly the flux that exits through the reference, # so the grounded solution equals the pure-Neumann one A, rhs, idx = _assemble(state, edges, inj) x, info = solve_system(A, rhs) Vflat = np.zeros(n) Vflat[state == 1] = x v_plus = float(Vflat[e1f].mean()) v_minus = float(Vflat[e2f].mean()) R = (v_plus - v_minus) / 1.0 Vflat = Vflat - v_minus # display reference: = 0 # quality: KCL residual of the solved system res = info.residual if res is None: res = float(np.linalg.norm(A @ x - rhs) / max(np.linalg.norm(rhs), 1e-300)) return Vflat, R, 1.0, 1.0, res, 1.0, info def _part_currents(parts, Ie, edges, e_flat, scale, i_test, contact_model, n_terminal_cells): """Current through each contact part @ I_test. Equipotential: exact discrete flux out of the part's cells (same-terminal internal edges carry zero, opposite-terminal edges are forbidden). Uniform: the injection is prescribed, so a part carries exactly its cell share.""" out = [] for label, mask3 in parts: pf = mask3.ravel() & e_flat n = int(pf.sum()) if contact_model == "uniform": amps = i_test * n / max(n_terminal_cells, 1) else: ina = pf[edges.a] inb = pf[edges.b] amps = abs(float(Ie[ina].sum() - Ie[inb].sum())) * scale out.append((label, amps)) return out def run_solve(problem: Problem, stack: RasterStack, e1: np.ndarray, e2: np.ndarray, i_test: float, freq_hz: float = 0.0, contact_model: str | None = None, parts1: list | None = None, parts2: list | None = None) -> Result: timings = {} L, ny, nx = stack.masks.shape h_m = stack.h_nm * 1e-9 if contact_model is None: contact_model = config.CONTACT_MODEL # effective (AC) sheet conductances and barrel factor sigmas = [ 1.0 / skin.sheet_resistance_ac( problem.layers[li].thickness_nm * 1e-9, freq_hz, problem.rho_ohm_m, config.SKIN_SIDES) for li in range(L) ] rs_ratios = [ skin.resistance_factor(problem.layers[li].thickness_nm * 1e-9, freq_hz, problem.rho_ohm_m, config.SKIN_SIDES) for li in range(L) ] via_factor = skin.resistance_factor(problem.plating_nm * 1e-9, freq_hz, problem.rho_ohm_m, sides=2) sigma_buildup = 0.0 if problem.buildups and stack.buildup is not None \ and stack.buildup.any(): sigma_buildup = 1.0 / skin.sheet_resistance_ac( problem.solder_thickness_nm * 1e-9, freq_hz, problem.solder_rho_ohm_m, config.SKIN_SIDES) if problem.extra_cu_nm > 0: sigma_buildup += 1.0 / skin.sheet_resistance_ac( problem.extra_cu_nm * 1e-9, freq_hz, problem.rho_ohm_m, config.SKIN_SIDES) eq_um = sigma_buildup * problem.rho_ohm_m * 1e6 print(f"solder buildup: {problem.solder_thickness_nm / 1000:.0f} um " f"solder + {problem.extra_cu_nm / 1000:.0f} um Cu on " f"{int(stack.buildup.sum())} cells " f"(= {eq_um:.1f} um equivalent copper)") if freq_hz > 0: depth = skin.skin_depth_m(freq_hz, problem.rho_ohm_m) print(f"AC @ {freq_hz:g} Hz: skin depth {depth * 1e6:.0f} um, " f"per-layer Rs ratio " f"{', '.join(f'{r:.2f}' for r in rs_ratios)}, " f"via factor {via_factor:.2f}") t0 = time.perf_counter() edges = build_edges(stack, problem, sigmas, via_factor, sigma_buildup) changed, n_groups = connected_restrict(stack, e1, e2, edges) if changed: edges = build_edges(stack, problem, sigmas, via_factor, sigma_buildup) if edges.dead_barrels: print(f"warning: {edges.dead_barrels} via/pad barrel(s) found fill " f"copper on fewer than 2 layers and carry no current (pad " f"copper is not modeled; a finer grid may pick up thermal " f"spokes)") if n_groups > 1 and contact_model != "equipotential": raise ConnectivityError( f"The selected fills form {n_groups} disconnected copper groups " f"that each touch both terminals. The uniform-injection contact " f"model cannot determine the current split between disconnected " f"sheets - switch to the equipotential contact model (bonded " f"lug), or include the layers/vias that join them." ) if stack.buildup is not None: stack.buildup &= stack.masks for label, m in (parts1 or []) + (parts2 or []): had = bool(m.any()) m &= stack.masks # follow the component restriction if had and not m.any(): print(f"warning: contact part '{label}' only touches copper " f"that is not connected to both terminals - it carries " f"no current") timings["edges_s"] = time.perf_counter() - t0 t0 = time.perf_counter() if contact_model == "equipotential": Vflat, R, I1, I2, mismatch, volts_per_amp, info = \ _solve_equipotential(stack, e1, e2, edges) else: Vflat, R, I1, I2, mismatch, volts_per_amp, info = \ _solve_uniform(stack, e1, e2, edges) timings["solve_s"] = time.perf_counter() - t0 t0 = time.perf_counter() s = i_test * volts_per_amp # unit-drive volts -> volts @ I_test # per-edge power @ I_test; distribute in-plane power to endpoint cells Pe = edges.w * ((Vflat[edges.a] - Vflat[edges.b]) * s) ** 2 inplane = edges.via_index < 0 Pflat = np.zeros(Vflat.size) np.add.at(Pflat, edges.a[inplane], 0.5 * Pe[inplane]) np.add.at(Pflat, edges.b[inplane], 0.5 * Pe[inplane]) Parea = Pflat.reshape(L, ny, nx) / (h_m * h_m) Parea[~stack.masks] = np.nan plane = ny * nx P_layers = [float(Pflat[li * plane:(li + 1) * plane].sum()) for li in range(L)] P_vias = float(Pe[~inplane].sum()) P_total = i_test ** 2 * R balance = abs((sum(P_layers) + P_vias) - P_total) / max(P_total, 1e-300) if not np.isfinite(balance) or balance > 1e-3: raise SolverError( f"Inconsistent solve: R = {R:.6g} ohm with power-balance error " f"{balance:.2e} (sum of edge powers vs I^2*R). The result is " f"not trustworthy - try the equipotential contact model or a " f"different grid size." ) # via reports: max segment current + total power per via Ie = edges.w * (Vflat[edges.a] - Vflat[edges.b]) # amps at unit drive via_reports = [] if problem.vias: vidx = edges.via_index for vi in np.unique(vidx[vidx >= 0]): sel = vidx == vi via = problem.vias[vi] via_reports.append(ViaReport( x_mm=via.x * 1e-6, y_mm=via.y * 1e-6, kind=via.kind, drill_mm=via.drill_nm * 1e-6, current_a=float(np.abs(Ie[sel]).max()) * s, power_w=float(Pe[sel].sum()), )) via_reports.sort(key=lambda v: v.current_a, reverse=True) # per-injection-area currents part_currents1 = _part_currents( parts1 or [], Ie, edges, e1.ravel(), s, i_test, contact_model, int(e1.sum())) part_currents2 = _part_currents( parts2 or [], Ie, edges, e2.ravel(), s, i_test, contact_model, int(e2.sum())) # embedded potential + per-layer current density @ I_test V3 = np.full((L, ny, nx), np.nan) V3[stack.masks] = Vflat.reshape(L, ny, nx)[stack.masks] * s J3 = np.stack([ _face_current_density( np.nan_to_num(V3[li]), stack.masks[li], sigmas[li], h_m, problem.layers[li].thickness_nm * 1e-9, sig2d=_sigma_2d(stack, li, sigmas[li], sigma_buildup), rho=problem.rho_ohm_m) for li in range(L) ]) timings["postprocess_s"] = time.perf_counter() - t0 return Result( R_ohm=R, i_test=i_test, V=V3, Jmag=J3, Parea=Parea, layer_names=list(stack.layer_names), P_total=P_total, P_layers=P_layers, P_vias=P_vias, power_balance_rel=balance, via_reports=via_reports, I1_a=I1, I2_a=I2, mismatch_rel=mismatch, n_free=info.n_unknowns, solve_info=info, part_currents1=part_currents1, part_currents2=part_currents2, contact_model=contact_model, freq_hz=freq_hz, skin_depth_um=(skin.skin_depth_m(freq_hz, problem.rho_ohm_m) * 1e6 if freq_hz > 0 else None), rs_ratios=rs_ratios, timings=timings, )