fonttools/Lib/cu2qu/__init__.py
2016-07-28 17:10:49 -07:00

245 lines
7.5 KiB
Python

# Copyright 2015 Google Inc. 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.
from __future__ import print_function, division, absolute_import
__all__ = ['curve_to_quadratic', 'curves_to_quadratic']
MAX_N = 100
class Cu2QuError(Exception):
pass
class ApproxNotFoundError(Cu2QuError):
def __init__(self, curve):
message = "no approximation found: %s" % curve
super(Cu2QuError, self).__init__(message)
self.curve = curve
def dot(v1, v2):
"""Return the dot product of two vectors."""
return (v1 * v2.conjugate()).real
def calc_cubic_points(a, b, c, d):
_1 = d
_2 = (c / 3.0) + d
_3 = (b + c) / 3.0 + _2
_4 = a + d + c + b
return _1, _2, _3, _4
def calc_cubic_parameters(p0, p1, p2, p3):
c = (p1 - p0) * 3.0
b = (p2 - p1) * 3.0 - c
d = p0
a = p3 - d - c - b
return a, b, c, d
def split_cubic_into_n(p0, p1, p2, p3, n):
# Hand-coded special-cases
if n == 2:
return split_cubic_into_two(p0, p1, p2, p3)
if n == 3:
return split_cubic_into_three(p0, p1, p2, p3)
a, b, c, d = calc_cubic_parameters(p0, p1, p2, p3)
segments = []
dt = 1 / n
delta_2 = dt * dt
delta_3 = dt * delta_2
for i in range(n):
t1 = i * dt
t1_2 = t1 * t1
t1_3 = t1 * t1_2
# calc new a, b, c and d
a1 = a * delta_3
b1 = (3*a*t1 + b) * delta_2
c1 = (2*b*t1 + c + 3*a*t1_2) * dt
d1 = a*t1_3 + b*t1_2 + c*t1 + d
segments.append(calc_cubic_points(a1, b1, c1, d1))
return segments
def split_cubic_into_two(p0, p1, p2, p3):
mid = (p0 + 3 * (p1 + p2) + p3) * .125
deriv3 = (p3 + p2 - p1 - p0) * .125
return ((p0, (p0 + p1) * .5, mid - deriv3, mid),
(mid, mid + deriv3, (p2 + p3) * .5, p3))
def split_cubic_into_three(p0, p1, p2, p3, _27=1/27):
# we define 1/27 as a keyword argument so that it will be evaluated only
# once but still in the scope of this function
mid1 = (8*p0 + 12*p1 + 6*p2 + p3) * _27
deriv1 = (p3 + 3*p2 - 4*p0) * _27
mid2 = (p0 + 6*p1 + 12*p2 + 8*p3) * _27
deriv2 = (4*p3 - 3*p1 - p0) * _27
return ((p0, (2*p0 + p1) / 3, mid1 - deriv1, mid1),
(mid1, mid1 + deriv1, mid2 - deriv2, mid2),
(mid2, mid2 + deriv2, (p2 + 2*p3) / 3, p3))
def cubic_approx_control(p, t):
"""Approximate a cubic bezier curve with a quadratic one.
Returns the candidate control point."""
p1 = p[0] + (p[1] - p[0]) * 1.5
p2 = p[3] + (p[2] - p[3]) * 1.5
return p1 + (p2 - p1) * t
def calc_intersect(a, b, c, d):
"""Calculate the intersection of ab and cd, given a, b, c, d."""
ab = b - a
cd = d - c
p = ab * 1j
try:
h = dot(p, a - c) / dot(p, cd)
except ZeroDivisionError:
return None
return c + cd * h
def cubic_farthest_fit_inside(p0, p1, p2, p3, tolerance):
"""Returns True if the cubic Bezier p entirely lies within a distance
tolerance of origin, False otherwise. Assumes that p0 and p3 do fit
within tolerance of origin, and just checks the inside of the curve."""
# 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) * .125
if abs(mid) > tolerance:
return False
deriv3 = (p3 + p2 - p1 - p0) * .125
return (cubic_farthest_fit_inside(p0, (p0+p1)*.5, mid-deriv3, mid, tolerance) and
cubic_farthest_fit_inside(mid, mid+deriv3, (p2+p3)*.5, p3, tolerance))
def cubic_farthest_fit(p0, p1, p2, p3, tolerance):
"""Returns True if the cubic Bezier p entirely lies within a distance
tolerance of origin, False otherwise."""
# First check p3 then p0, as p3 has higher error early on.
if abs(p3) > tolerance or abs(p0) > tolerance:
return False
return cubic_farthest_fit_inside(p0, p1, p2, p3, tolerance)
def cubic_approx_spline(cubic, n, tolerance, _2_3=2/3):
"""Approximate a cubic bezier curve with a spline of n quadratics.
Returns None if no quadratic approximation is found which lies entirely
within a distance `tolerance` from the original curve.
"""
# we define 2/3 as a keyword argument so that it will be evaluated only
# once but still in the scope of this function
if n == 1:
# Try the uniq quadratic approximating cubic that maintains
# endpoint tangents.
q1 = calc_intersect(*cubic)
if q1 is None:
return None
c0 = cubic[0]
c3 = cubic[3]
c1 = c0 + (q1 - c0) * _2_3
c2 = c3 + (q1 - c3) * _2_3
if not cubic_farthest_fit_inside(0,
c1 - cubic[1],
c2 - cubic[2],
0, tolerance):
return None
return c0, q1, c3
spline = []
# calculate the spline of quadratics
segments = split_cubic_into_n(cubic[0], cubic[1], cubic[2], cubic[3], n)
for i in range(len(segments)):
spline.append(cubic_approx_control(segments[i], i / (n - 1)))
# determine whether the spline is within the tolerance error
q2 = cubic[0]
n_1 = n - 1
for i in range(n):
if i < n_1:
q0, q1, q2 = q2, spline[i], (spline[i] + spline[i + 1]) * .5
else:
q0, q1, q2 = q2, spline[-1], cubic[3]
c0, c1, c2, c3 = segments[i]
if not cubic_farthest_fit(q0 - c0,
q0 + (q1 - q0) * _2_3 - c1,
q2 + (q1 - q2) * _2_3 - c2,
q2 - c3,
tolerance):
return None
spline.insert(0, cubic[0])
spline.append(cubic[3])
return spline
def curve_to_quadratic(curve, max_err):
"""Return a quadratic spline approximating this cubic bezier.
Raise 'ApproxNotFoundError' if no suitable approximation can be found
with the given parameters.
"""
curve = [complex(*p) for p in curve]
for n in range(1, MAX_N + 1):
spline = cubic_approx_spline(curve, n, max_err)
if spline is not None:
# done. go home
return [(s.real, s.imag) for s in spline]
raise ApproxNotFoundError(curve)
def curves_to_quadratic(curves, max_errors):
"""Return quadratic splines approximating these cubic beziers.
Raise 'ApproxNotFoundError' if no suitable approximation can be found
for all curves with the given parameters.
"""
curves = [[complex(*p) for p in curve] for curve in curves]
assert len(max_errors) == len(curves)
for n in range(1, MAX_N + 1):
splines = []
for c, e in zip(curves, max_errors):
spline = cubic_approx_spline(c, n, e)
if spline is None:
break
splines.append(spline)
else:
# done. go home
return [[(s.real, s.imag) for s in spline] for spline in splines]
raise ApproxNotFoundError(curves)