contour = ax1.contour(combined_theta, combined_r, combined_density, levels=[1.0], linewidths=1.5, colors=colors) contour_paths = contour.collections[0].get_paths() for path in contour_paths: vertices = path.vertices theta_vals = vertices[:, 0] r_vals = vertices[:, 1] mask = np.ones_like(combined_theta, dtype=bool) print(f"combined_theta: {combined_theta}") print(f"combined_r: {combined_r}") for i in range(len(combined_theta)): for j in range(len(combined_r[0])): # Assuming combined_r is 2D if np.any(np.isclose(combined_theta[i, j], theta_vals)) and np.any(np.isclose(combined_r[i, j], r_vals)): mask[i, j] = False remaining_theta = combined_theta[mask] remaining_r = combined_r[mask] print(f"Remaining theta_vals (after removing): {remaining_theta}") print(f"Remaining r_vals (after removing): {remaining_r}") ax1.fill(remaining_theta, remaining_r, color=colors, alpha=0.3, zorder=2) although the printed values are fine: combined_theta: [[ 1.57079633 1.57079633 1.57079633 ... 1.57079633 1.57079633 1.57079633] [ 1.55443387 1.55443387 1.55443387 ... 1.55443387 1.55443387 1.55443387] [ 1.53807141 1.53807141 1.53807141 ... 1.53807141 1.53807141 1.53807141] ... [-1.53807107 -1.53807107 -1.53807107 ... -1.53807107 -1.53807107 -1.53807107] [-1.55443353 -1.55443353 -1.55443353 ... -1.55443353 -1.55443353 -1.55443353] [-1.57079599 -1.57079599 -1.57079599 ... -1.57079599 -1.57079599 -1.57079599]] combined_r: [[1.18999999e+00 1.21394504e+00 1.23837191e+00 ... 2.40235105e+03 2.45069089e+03 2.50000342e+03] [1.18999999e+00 1.21394504e+00 1.23837191e+00 ... 2.40235105e+03 2.45069089e+03 2.50000342e+03] [1.18999999e+00 1.21394504e+00 1.23837191e+00 ... 2.40235105e+03 2.45069089e+03 2.50000342e+03] ... [1.18999999e+00 1.21394504e+00 1.23837191e+00 ... 2.40235105e+03 2.45069089e+03 2.50000342e+03] [1.18999999e+00 1.21394504e+00 1.23837191e+00 ... 2.40235105e+03 2.45069089e+03 2.50000342e+03] [1.18999999e+00 1.21394504e+00 1.23837191e+00 ... 2.40235105e+03 2.45069089e+03 2.50000342e+03]] Remaining theta_vals (after removing): [ 1.57079633 1.57079633 1.57079633 ... -1.57079599 -1.57079599 -1.57079599] Remaining r_vals (after removing): [1.18999999e+00 1.21394504e+00 1.23837191e+00 ... 2.40235105e+03 2.45069089e+03 2.50000342e+03] It is very confusing that why it is showing ax1.fill(remaining_theta, remaining_r, color=colors, alpha=0.3, zorder=2) IndexError: list index out of range Continue reading...