| from shinka.edit import apply_diff_patch |
|
|
|
|
| patch_str_1 = """ |
| <<<<<<< SEARCH |
| import numpy as np |
| |
| |
| def construct_packing(): |
| ======= |
| import numpy as np |
| |
| # Optional LP solver for radii (used if SciPy is available) |
| try: |
| from scipy.optimize import linprog |
| except Exception: |
| linprog = None |
| |
| |
| def construct_packing(): |
| >>>>>>> REPLACE |
| </DIFF> |
| |
| |
| <NAME>dist_matrix_precompute_for_radii</NAME> |
| <DESCRIPTION>Speed up the radii computation by precomputing the pairwise distance matrix once and reusing it in both the LP (when available) and the fallback loop. This reduces repeated distance calculations (norms) for the same center pairs and improves runtime reliability without changing the outcome for a fixed set of centers.</DESCRIPTION> |
| <DIFF> |
| <<<<<<< SEARCH |
| # Compute maximum valid radii for this configuration |
| radii = compute_max_radii(centers) |
| return centers, radii |
| ======= |
| # Compute maximum valid radii for this configuration |
| radii = compute_max_radii(centers) |
| return centers, radii |
| >>>>>>> REPLACE |
| """ |
|
|
|
|
| patch_str_2 = ''' |
| <<<<<<< SEARCH |
| def compute_max_radii(centers): |
| """ |
| Compute the maximum possible radii for each circle position |
| such that they don't overlap and stay within the unit square. |
| |
| Args: |
| centers: np.array of shape (n, 2) with (x, y) coordinates |
| |
| Returns: |
| np.array of shape (n) with radius of each circle |
| """ |
| n = centers.shape[0] |
| radii = np.ones(n) |
| |
| # First, limit by distance to square borders |
| for i in range(n): |
| x, y = centers[i] |
| # Distance to borders |
| radii[i] = min(x, y, 1 - x, 1 - y) |
| |
| # Then, limit by distance to other circles |
| # Each pair of circles with centers at distance d can have |
| # sum of radii at most d to avoid overlap |
| for i in range(n): |
| for j in range(i + 1, n): |
| dist = np.sqrt(np.sum((centers[i] - centers[j]) ** 2)) |
| |
| # If current radii would cause overlap |
| if radii[i] + radii[j] > dist: |
| # Scale both radii proportionally |
| scale = dist / (radii[i] + radii[j]) |
| radii[i] *= scale |
| radii[j] *= scale |
| |
| return radii |
| ======= |
| def compute_max_radii(centers, tol=1e-9, max_iter=1000): |
| """ |
| Compute the maximum possible radii for each circle position |
| such that they don't overlap and stay within the unit square. |
| |
| Args: |
| centers: np.array of shape (n, 2) |
| |
| Returns: |
| np.array of shape (n,) with radius of each circle |
| """ |
| n = centers.shape[0] |
| # Precompute pairwise distances |
| dists = np.linalg.norm(centers[:, None, :] - centers[None, :, :], axis=2) |
| |
| # Boundary distance constraints |
| border_dist = np.minimum.reduce([centers[:, 0], centers[:, 1], 1 - centers[:, 0], 1 - centers[:, 1]]) |
| |
| # Initial guess for radii (some slack inside borders) |
| x0 = np.clip(border_dist * 0.9, 0.0, border_dist) |
| |
| radii = None |
| # Try to solve a global max-sum-radii problem using SciPy (SLSQP) |
| try: |
| from scipy.optimize import minimize |
| bounds = [(0.0, bd) for bd in border_dist] |
| |
| def objective(r): |
| return -np.sum(r) |
| |
| constraints = [] |
| for i in range(n): |
| for j in range(i + 1, n): |
| d = dists[i, j] |
| constraints.append({'type': 'ineq', |
| 'fun': lambda r, i=i, j=j, d=d: d - (r[i] + r[j])}) |
| |
| res = minimize(objective, x0, bounds=bounds, constraints=constraints, |
| method='SLSQP', options={'ftol': 1e-9, 'maxiter': max_iter}) |
| if res.success: |
| radii = np.clip(res.x, 0.0, border_dist) |
| except Exception: |
| radii = None |
| |
| if radii is not None: |
| return radii |
| |
| # Fallback simple relaxation if SciPy not available or failed |
| radii = np.ones(n) |
| for i in range(n): |
| x, y = centers[i] |
| radii[i] = min(x, y, 1 - x, 1 - y) |
| |
| for i in range(n): |
| for j in range(i + 1, n): |
| dist = np.linalg.norm(centers[i] - centers[j]) |
| if radii[i] + radii[j] > dist: |
| scale = dist / (radii[i] + radii[j]) |
| radii[i] *= scale |
| radii[j] *= scale |
| |
| return radii |
| >>>>>>> REPLACE |
| ''' |
|
|
|
|
| def test_edit(): |
| result = apply_diff_patch( |
| original_path="tests/circle.py", |
| patch_str=patch_str_1, |
| patch_dir=None, |
| ) |
| updated_str, num_applied, output_path, error, patch_txt, diff_path = result |
| print(error) |
| assert num_applied == 2 |
| assert output_path is None |
| assert error is None |
|
|
|
|
| def test_edit_2(): |
| result = apply_diff_patch( |
| original_path="tests/circle.py", |
| patch_str=patch_str_2, |
| patch_dir=None, |
| ) |
| updated_str, num_applied, output_path, error, patch_txt, diff_path = result |
| print(error) |
| assert num_applied == 1 |
| assert output_path is None |
| assert error is None |
|
|
