| # cython: language_level=3 |
| # distutils: define_macros=CYTHON_TRACE_NOGIL=1 |
| |
| # Copyright 2023 Google Inc. All Rights Reserved. |
| # Copyright 2023 Behdad Esfahbod. All Rights Reserved. |
| # |
| # Licensed under the Apache License, Version 2.0 (the "License"); |
| # you may not use this file except in compliance with the License. |
| # You may obtain a copy of the License at |
| # |
| # http://www.apache.org/licenses/LICENSE-2.0 |
| # |
| # Unless required by applicable law or agreed to in writing, software |
| # distributed under the License is distributed on an "AS IS" BASIS, |
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
| # See the License for the specific language governing permissions and |
| # limitations under the License. |
| |
| try: |
| import cython |
| |
| COMPILED = cython.compiled |
| except (AttributeError, ImportError): |
| # if cython not installed, use mock module with no-op decorators and types |
| from fontTools.misc import cython |
| |
| COMPILED = False |
| |
| from fontTools.misc.bezierTools import splitCubicAtTC |
| from collections import namedtuple |
| import math |
| from typing import ( |
| List, |
| Tuple, |
| Union, |
| ) |
| |
| |
| __all__ = ["quadratic_to_curves"] |
| |
| |
| # Copied from cu2qu |
| @cython.cfunc |
| @cython.returns(cython.int) |
| @cython.locals( |
| tolerance=cython.double, |
| p0=cython.complex, |
| p1=cython.complex, |
| p2=cython.complex, |
| p3=cython.complex, |
| ) |
| @cython.locals(mid=cython.complex, deriv3=cython.complex) |
| def cubic_farthest_fit_inside(p0, p1, p2, p3, tolerance): |
| """Check if a cubic Bezier lies within a given distance of the origin. |
| |
| "Origin" means *the* origin (0,0), not the start of the curve. Note that no |
| checks are made on the start and end positions of the curve; this function |
| only checks the inside of the curve. |
| |
| Args: |
| p0 (complex): Start point of curve. |
| p1 (complex): First handle of curve. |
| p2 (complex): Second handle of curve. |
| p3 (complex): End point of curve. |
| tolerance (double): Distance from origin. |
| |
| Returns: |
| bool: True if the cubic Bezier ``p`` entirely lies within a distance |
| ``tolerance`` of the origin, False otherwise. |
| """ |
| # First check p2 then p1, as p2 has higher error early on. |
| if abs(p2) <= tolerance and abs(p1) <= tolerance: |
| return True |
| |
| # Split. |
| mid = (p0 + 3 * (p1 + p2) + p3) * 0.125 |
| if abs(mid) > tolerance: |
| return False |
| deriv3 = (p3 + p2 - p1 - p0) * 0.125 |
| return cubic_farthest_fit_inside( |
| p0, (p0 + p1) * 0.5, mid - deriv3, mid, tolerance |
| ) and cubic_farthest_fit_inside(mid, mid + deriv3, (p2 + p3) * 0.5, p3, tolerance) |
| |
| |
| @cython.locals( |
| p0=cython.complex, |
| p1=cython.complex, |
| p2=cython.complex, |
| p1_2_3=cython.complex, |
| ) |
| def elevate_quadratic(p0, p1, p2): |
| """Given a quadratic bezier curve, return its degree-elevated cubic.""" |
| |
| # https://pomax.github.io/bezierinfo/#reordering |
| p1_2_3 = p1 * (2 / 3) |
| return ( |
| p0, |
| (p0 * (1 / 3) + p1_2_3), |
| (p2 * (1 / 3) + p1_2_3), |
| p2, |
| ) |
| |
| |
| @cython.cfunc |
| @cython.locals( |
| start=cython.int, |
| n=cython.int, |
| k=cython.int, |
| prod_ratio=cython.double, |
| sum_ratio=cython.double, |
| ratio=cython.double, |
| t=cython.double, |
| p0=cython.complex, |
| p1=cython.complex, |
| p2=cython.complex, |
| p3=cython.complex, |
| ) |
| def merge_curves(curves, start, n): |
| """Give a cubic-Bezier spline, reconstruct one cubic-Bezier |
| that has the same endpoints and tangents and approxmates |
| the spline.""" |
| |
| # Reconstruct the t values of the cut segments |
| prod_ratio = 1.0 |
| sum_ratio = 1.0 |
| ts = [1] |
| for k in range(1, n): |
| ck = curves[start + k] |
| c_before = curves[start + k - 1] |
| |
| # |t_(k+1) - t_k| / |t_k - t_(k - 1)| = ratio |
| assert ck[0] == c_before[3] |
| ratio = abs(ck[1] - ck[0]) / abs(c_before[3] - c_before[2]) |
| |
| prod_ratio *= ratio |
| sum_ratio += prod_ratio |
| ts.append(sum_ratio) |
| |
| # (t(n) - t(n - 1)) / (t_(1) - t(0)) = prod_ratio |
| |
| ts = [t / sum_ratio for t in ts[:-1]] |
| |
| p0 = curves[start][0] |
| p1 = curves[start][1] |
| p2 = curves[start + n - 1][2] |
| p3 = curves[start + n - 1][3] |
| |
| # Build the curve by scaling the control-points. |
| p1 = p0 + (p1 - p0) / (ts[0] if ts else 1) |
| p2 = p3 + (p2 - p3) / ((1 - ts[-1]) if ts else 1) |
| |
| curve = (p0, p1, p2, p3) |
| |
| return curve, ts |
| |
| |
| @cython.locals( |
| count=cython.int, |
| num_offcurves=cython.int, |
| i=cython.int, |
| off1=cython.complex, |
| off2=cython.complex, |
| on=cython.complex, |
| ) |
| def add_implicit_on_curves(p): |
| q = list(p) |
| count = 0 |
| num_offcurves = len(p) - 2 |
| for i in range(1, num_offcurves): |
| off1 = p[i] |
| off2 = p[i + 1] |
| on = off1 + (off2 - off1) * 0.5 |
| q.insert(i + 1 + count, on) |
| count += 1 |
| return q |
| |
| |
| Point = Union[Tuple[float, float], complex] |
| |
| |
| @cython.locals( |
| cost=cython.int, |
| is_complex=cython.int, |
| ) |
| def quadratic_to_curves( |
| quads: List[List[Point]], |
| max_err: float = 0.5, |
| all_cubic: bool = False, |
| ) -> List[Tuple[Point, ...]]: |
| """Converts a connecting list of quadratic splines to a list of quadratic |
| and cubic curves. |
| |
| A quadratic spline is specified as a list of points. Either each point is |
| a 2-tuple of X,Y coordinates, or each point is a complex number with |
| real/imaginary components representing X,Y coordinates. |
| |
| The first and last points are on-curve points and the rest are off-curve |
| points, with an implied on-curve point in the middle between every two |
| consequtive off-curve points. |
| |
| Returns: |
| The output is a list of tuples of points. Points are represented |
| in the same format as the input, either as 2-tuples or complex numbers. |
| |
| Each tuple is either of length three, for a quadratic curve, or four, |
| for a cubic curve. Each curve's last point is the same as the next |
| curve's first point. |
| |
| Args: |
| quads: quadratic splines |
| |
| max_err: absolute error tolerance; defaults to 0.5 |
| |
| all_cubic: if True, only cubic curves are generated; defaults to False |
| """ |
| is_complex = type(quads[0][0]) is complex |
| if not is_complex: |
| quads = [[complex(x, y) for (x, y) in p] for p in quads] |
| |
| q = [quads[0][0]] |
| costs = [1] |
| cost = 1 |
| for p in quads: |
| assert q[-1] == p[0] |
| for i in range(len(p) - 2): |
| cost += 1 |
| costs.append(cost) |
| costs.append(cost) |
| qq = add_implicit_on_curves(p)[1:] |
| costs.pop() |
| q.extend(qq) |
| cost += 1 |
| costs.append(cost) |
| |
| curves = spline_to_curves(q, costs, max_err, all_cubic) |
| |
| if not is_complex: |
| curves = [tuple((c.real, c.imag) for c in curve) for curve in curves] |
| return curves |
| |
| |
| Solution = namedtuple("Solution", ["num_points", "error", "start_index", "is_cubic"]) |
| |
| |
| @cython.locals( |
| i=cython.int, |
| j=cython.int, |
| k=cython.int, |
| start=cython.int, |
| i_sol_count=cython.int, |
| j_sol_count=cython.int, |
| this_sol_count=cython.int, |
| tolerance=cython.double, |
| err=cython.double, |
| error=cython.double, |
| i_sol_error=cython.double, |
| j_sol_error=cython.double, |
| all_cubic=cython.int, |
| is_cubic=cython.int, |
| count=cython.int, |
| p0=cython.complex, |
| p1=cython.complex, |
| p2=cython.complex, |
| p3=cython.complex, |
| v=cython.complex, |
| u=cython.complex, |
| ) |
| def spline_to_curves(q, costs, tolerance=0.5, all_cubic=False): |
| """ |
| q: quadratic spline with alternating on-curve / off-curve points. |
| |
| costs: cumulative list of encoding cost of q in terms of number of |
| points that need to be encoded. Implied on-curve points do not |
| contribute to the cost. If all points need to be encoded, then |
| costs will be range(1, len(q)+1). |
| """ |
| |
| assert len(q) >= 3, "quadratic spline requires at least 3 points" |
| |
| # Elevate quadratic segments to cubic |
| elevated_quadratics = [ |
| elevate_quadratic(*q[i : i + 3]) for i in range(0, len(q) - 2, 2) |
| ] |
| |
| # Find sharp corners; they have to be oncurves for sure. |
| forced = set() |
| for i in range(1, len(elevated_quadratics)): |
| p0 = elevated_quadratics[i - 1][2] |
| p1 = elevated_quadratics[i][0] |
| p2 = elevated_quadratics[i][1] |
| if abs(p1 - p0) + abs(p2 - p1) > tolerance + abs(p2 - p0): |
| forced.add(i) |
| |
| # Dynamic-Programming to find the solution with fewest number of |
| # cubic curves, and within those the one with smallest error. |
| sols = [Solution(0, 0, 0, False)] |
| impossible = Solution(len(elevated_quadratics) * 3 + 1, 0, 1, False) |
| start = 0 |
| for i in range(1, len(elevated_quadratics) + 1): |
| best_sol = impossible |
| for j in range(start, i): |
| j_sol_count, j_sol_error = sols[j].num_points, sols[j].error |
| |
| if not all_cubic: |
| # Solution with quadratics between j:i |
| this_count = costs[2 * i - 1] - costs[2 * j] + 1 |
| i_sol_count = j_sol_count + this_count |
| i_sol_error = j_sol_error |
| i_sol = Solution(i_sol_count, i_sol_error, i - j, False) |
| if i_sol < best_sol: |
| best_sol = i_sol |
| |
| if this_count <= 3: |
| # Can't get any better than this in the path below |
| continue |
| |
| # Fit elevated_quadratics[j:i] into one cubic |
| try: |
| curve, ts = merge_curves(elevated_quadratics, j, i - j) |
| except ZeroDivisionError: |
| continue |
| |
| # Now reconstruct the segments from the fitted curve |
| reconstructed_iter = splitCubicAtTC(*curve, *ts) |
| reconstructed = [] |
| |
| # Knot errors |
| error = 0 |
| for k, reconst in enumerate(reconstructed_iter): |
| orig = elevated_quadratics[j + k] |
| err = abs(reconst[3] - orig[3]) |
| error = max(error, err) |
| if error > tolerance: |
| break |
| reconstructed.append(reconst) |
| if error > tolerance: |
| # Not feasible |
| continue |
| |
| # Interior errors |
| for k, reconst in enumerate(reconstructed): |
| orig = elevated_quadratics[j + k] |
| p0, p1, p2, p3 = tuple(v - u for v, u in zip(reconst, orig)) |
| |
| if not cubic_farthest_fit_inside(p0, p1, p2, p3, tolerance): |
| error = tolerance + 1 |
| break |
| if error > tolerance: |
| # Not feasible |
| continue |
| |
| # Save best solution |
| i_sol_count = j_sol_count + 3 |
| i_sol_error = max(j_sol_error, error) |
| i_sol = Solution(i_sol_count, i_sol_error, i - j, True) |
| if i_sol < best_sol: |
| best_sol = i_sol |
| |
| if i_sol_count == 3: |
| # Can't get any better than this |
| break |
| |
| sols.append(best_sol) |
| if i in forced: |
| start = i |
| |
| # Reconstruct solution |
| splits = [] |
| cubic = [] |
| i = len(sols) - 1 |
| while i: |
| count, is_cubic = sols[i].start_index, sols[i].is_cubic |
| splits.append(i) |
| cubic.append(is_cubic) |
| i -= count |
| curves = [] |
| j = 0 |
| for i, is_cubic in reversed(list(zip(splits, cubic))): |
| if is_cubic: |
| curves.append(merge_curves(elevated_quadratics, j, i - j)[0]) |
| else: |
| for k in range(j, i): |
| curves.append(q[k * 2 : k * 2 + 3]) |
| j = i |
| |
| return curves |
| |
| |
| def main(): |
| from fontTools.cu2qu.benchmark import generate_curve |
| from fontTools.cu2qu import curve_to_quadratic |
| |
| tolerance = 0.05 |
| reconstruct_tolerance = tolerance * 1 |
| curve = generate_curve() |
| quadratics = curve_to_quadratic(curve, tolerance) |
| print( |
| "cu2qu tolerance %g. qu2cu tolerance %g." % (tolerance, reconstruct_tolerance) |
| ) |
| print("One random cubic turned into %d quadratics." % len(quadratics)) |
| curves = quadratic_to_curves([quadratics], reconstruct_tolerance) |
| print("Those quadratics turned back into %d cubics. " % len(curves)) |
| print("Original curve:", curve) |
| print("Reconstructed curve(s):", curves) |
| |
| |
| if __name__ == "__main__": |
| main() |
