blob: c9ce93ae329b119e5026cadd3a22543b1d3ebf27 [file] [log] [blame]
#cython: language_level=3
#distutils: define_macros=CYTHON_TRACE_NOGIL=1
# 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.
try:
import cython
except ImportError:
# if cython not installed, use mock module with no-op decorators and types
from fontTools.misc import cython
import math
from .errors import Error as Cu2QuError, ApproxNotFoundError
__all__ = ['curve_to_quadratic', 'curves_to_quadratic']
MAX_N = 100
NAN = float("NaN")
if cython.compiled:
# Yep, I'm compiled.
COMPILED = True
else:
# Just a lowly interpreted script.
COMPILED = False
@cython.cfunc
@cython.inline
@cython.returns(cython.double)
@cython.locals(v1=cython.complex, v2=cython.complex)
def dot(v1, v2):
"""Return the dot product of two vectors.
Args:
v1 (complex): First vector.
v2 (complex): Second vector.
Returns:
double: Dot product.
"""
return (v1 * v2.conjugate()).real
@cython.cfunc
@cython.inline
@cython.locals(a=cython.complex, b=cython.complex, c=cython.complex, d=cython.complex)
@cython.locals(_1=cython.complex, _2=cython.complex, _3=cython.complex, _4=cython.complex)
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
@cython.cfunc
@cython.inline
@cython.locals(p0=cython.complex, p1=cython.complex, p2=cython.complex, p3=cython.complex)
@cython.locals(a=cython.complex, b=cython.complex, c=cython.complex, d=cython.complex)
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
@cython.cfunc
@cython.locals(p0=cython.complex, p1=cython.complex, p2=cython.complex, p3=cython.complex)
def split_cubic_into_n_iter(p0, p1, p2, p3, n):
"""Split a cubic Bezier into n equal parts.
Splits the curve into `n` equal parts by curve time.
(t=0..1/n, t=1/n..2/n, ...)
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.
Returns:
An iterator yielding the control points (four complex values) of the
subcurves.
"""
# Hand-coded special-cases
if n == 2:
return iter(split_cubic_into_two(p0, p1, p2, p3))
if n == 3:
return iter(split_cubic_into_three(p0, p1, p2, p3))
if n == 4:
a, b = split_cubic_into_two(p0, p1, p2, p3)
return iter(split_cubic_into_two(*a) + split_cubic_into_two(*b))
if n == 6:
a, b = split_cubic_into_two(p0, p1, p2, p3)
return iter(split_cubic_into_three(*a) + split_cubic_into_three(*b))
return _split_cubic_into_n_gen(p0,p1,p2,p3,n)
@cython.locals(p0=cython.complex, p1=cython.complex, p2=cython.complex, p3=cython.complex, n=cython.int)
@cython.locals(a=cython.complex, b=cython.complex, c=cython.complex, d=cython.complex)
@cython.locals(dt=cython.double, delta_2=cython.double, delta_3=cython.double, i=cython.int)
@cython.locals(a1=cython.complex, b1=cython.complex, c1=cython.complex, d1=cython.complex)
def _split_cubic_into_n_gen(p0, p1, p2, p3, n):
a, b, c, d = calc_cubic_parameters(p0, p1, p2, p3)
dt = 1 / n
delta_2 = dt * dt
delta_3 = dt * delta_2
for i in range(n):
t1 = i * dt
t1_2 = t1 * t1
# 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*t1_2 + b*t1_2 + c*t1 + d
yield calc_cubic_points(a1, b1, c1, d1)
@cython.locals(p0=cython.complex, p1=cython.complex, p2=cython.complex, p3=cython.complex)
@cython.locals(mid=cython.complex, deriv3=cython.complex)
def split_cubic_into_two(p0, p1, p2, p3):
"""Split a cubic Bezier into two equal parts.
Splits the curve into two equal parts at t = 0.5
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.
Returns:
tuple: Two cubic Beziers (each expressed as a tuple of four complex
values).
"""
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))
@cython.locals(p0=cython.complex, p1=cython.complex, p2=cython.complex, p3=cython.complex, _27=cython.double)
@cython.locals(mid1=cython.complex, deriv1=cython.complex, mid2=cython.complex, deriv2=cython.complex)
def split_cubic_into_three(p0, p1, p2, p3, _27=1/27):
"""Split a cubic Bezier into three equal parts.
Splits the curve into three equal parts at t = 1/3 and t = 2/3
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.
Returns:
tuple: Three cubic Beziers (each expressed as a tuple of four complex
values).
"""
# 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) / 3.0, mid1 - deriv1, mid1),
(mid1, mid1 + deriv1, mid2 - deriv2, mid2),
(mid2, mid2 + deriv2, (p2 + 2*p3) / 3.0, p3))
@cython.returns(cython.complex)
@cython.locals(t=cython.double, p0=cython.complex, p1=cython.complex, p2=cython.complex, p3=cython.complex)
@cython.locals(_p1=cython.complex, _p2=cython.complex)
def cubic_approx_control(t, p0, p1, p2, p3):
"""Approximate a cubic Bezier using a quadratic one.
Args:
t (double): Position of control point.
p0 (complex): Start point of curve.
p1 (complex): First handle of curve.
p2 (complex): Second handle of curve.
p3 (complex): End point of curve.
Returns:
complex: Location of candidate control point on quadratic curve.
"""
_p1 = p0 + (p1 - p0) * 1.5
_p2 = p3 + (p2 - p3) * 1.5
return _p1 + (_p2 - _p1) * t
@cython.returns(cython.complex)
@cython.locals(a=cython.complex, b=cython.complex, c=cython.complex, d=cython.complex)
@cython.locals(ab=cython.complex, cd=cython.complex, p=cython.complex, h=cython.double)
def calc_intersect(a, b, c, d):
"""Calculate the intersection of two lines.
Args:
a (complex): Start point of first line.
b (complex): End point of first line.
c (complex): Start point of second line.
d (complex): End point of second line.
Returns:
complex: Location of intersection if one present, ``complex(NaN,NaN)``
if no intersection was found.
"""
ab = b - a
cd = d - c
p = ab * 1j
try:
h = dot(p, a - c) / dot(p, cd)
except ZeroDivisionError:
return complex(NAN, NAN)
return c + cd * h
@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) * .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))
@cython.cfunc
@cython.locals(tolerance=cython.double, _2_3=cython.double)
@cython.locals(q1=cython.complex, c0=cython.complex, c1=cython.complex, c2=cython.complex, c3=cython.complex)
def cubic_approx_quadratic(cubic, tolerance, _2_3=2/3):
"""Approximate a cubic Bezier with a single quadratic within a given tolerance.
Args:
cubic (sequence): Four complex numbers representing control points of
the cubic Bezier curve.
tolerance (double): Permitted deviation from the original curve.
Returns:
Three complex numbers representing control points of the quadratic
curve if it fits within the given tolerance, or ``None`` if no suitable
curve could be calculated.
"""
# we define 2/3 as a keyword argument so that it will be evaluated only
# once but still in the scope of this function
q1 = calc_intersect(*cubic)
if math.isnan(q1.imag):
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
@cython.cfunc
@cython.locals(n=cython.int, tolerance=cython.double, _2_3=cython.double)
@cython.locals(i=cython.int)
@cython.locals(c0=cython.complex, c1=cython.complex, c2=cython.complex, c3=cython.complex)
@cython.locals(q0=cython.complex, q1=cython.complex, next_q1=cython.complex, q2=cython.complex, d1=cython.complex)
def cubic_approx_spline(cubic, n, tolerance, _2_3=2/3):
"""Approximate a cubic Bezier curve with a spline of n quadratics.
Args:
cubic (sequence): Four complex numbers representing control points of
the cubic Bezier curve.
n (int): Number of quadratic Bezier curves in the spline.
tolerance (double): Permitted deviation from the original curve.
Returns:
A list of ``n+2`` complex numbers, representing control points of the
quadratic spline if it fits within the given tolerance, or ``None`` if
no suitable spline could be calculated.
"""
# 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:
return cubic_approx_quadratic(cubic, tolerance)
cubics = split_cubic_into_n_iter(cubic[0], cubic[1], cubic[2], cubic[3], n)
# calculate the spline of quadratics and check errors at the same time.
next_cubic = next(cubics)
next_q1 = cubic_approx_control(0, *next_cubic)
q2 = cubic[0]
d1 = 0j
spline = [cubic[0], next_q1]
for i in range(1, n+1):
# Current cubic to convert
c0, c1, c2, c3 = next_cubic
# Current quadratic approximation of current cubic
q0 = q2
q1 = next_q1
if i < n:
next_cubic = next(cubics)
next_q1 = cubic_approx_control(i / (n-1), *next_cubic)
spline.append(next_q1)
q2 = (q1 + next_q1) * .5
else:
q2 = c3
# End-point deltas
d0 = d1
d1 = q2 - c3
if (abs(d1) > tolerance or
not cubic_farthest_fit_inside(d0,
q0 + (q1 - q0) * _2_3 - c1,
q2 + (q1 - q2) * _2_3 - c2,
d1,
tolerance)):
return None
spline.append(cubic[3])
return spline
@cython.locals(max_err=cython.double)
@cython.locals(n=cython.int)
def curve_to_quadratic(curve, max_err):
"""Approximate a cubic Bezier curve with a spline of n quadratics.
Args:
cubic (sequence): Four 2D tuples representing control points of
the cubic Bezier curve.
max_err (double): Permitted deviation from the original curve.
Returns:
A list of 2D tuples, representing control points of the quadratic
spline if it fits within the given tolerance, or ``None`` if no
suitable spline could be calculated.
"""
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)
@cython.locals(l=cython.int, last_i=cython.int, i=cython.int)
def curves_to_quadratic(curves, max_errors):
"""Return quadratic Bezier splines approximating the input cubic Beziers.
Args:
curves: A sequence of *n* curves, each curve being a sequence of four
2D tuples.
max_errors: A sequence of *n* floats representing the maximum permissible
deviation from each of the cubic Bezier curves.
Example::
>>> curves_to_quadratic( [
... [ (50,50), (100,100), (150,100), (200,50) ],
... [ (75,50), (120,100), (150,75), (200,60) ]
... ], [1,1] )
[[(50.0, 50.0), (75.0, 75.0), (125.0, 91.66666666666666), (175.0, 75.0), (200.0, 50.0)], [(75.0, 50.0), (97.5, 75.0), (135.41666666666666, 82.08333333333333), (175.0, 67.5), (200.0, 60.0)]]
The returned splines have "implied oncurve points" suitable for use in
TrueType ``glif`` outlines - i.e. in the first spline returned above,
the first quadratic segment runs from (50,50) to
( (75 + 125)/2 , (120 + 91.666..)/2 ) = (100, 83.333...).
Returns:
A list of splines, each spline being a list of 2D tuples.
Raises:
fontTools.cu2qu.Errors.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)
l = len(curves)
splines = [None] * l
last_i = i = 0
n = 1
while True:
spline = cubic_approx_spline(curves[i], n, max_errors[i])
if spline is None:
if n == MAX_N:
break
n += 1
last_i = i
continue
splines[i] = spline
i = (i + 1) % l
if i == last_i:
# done. go home
return [[(s.real, s.imag) for s in spline] for spline in splines]
raise ApproxNotFoundError(curves)
if __name__ == '__main__':
import random
import timeit
MAX_ERR = 5
def generate_curve():
return [
tuple(float(random.randint(0, 2048)) for coord in range(2))
for point in range(4)]
def setup_curve_to_quadratic():
return generate_curve(), MAX_ERR
def setup_curves_to_quadratic():
num_curves = 3
return (
[generate_curve() for curve in range(num_curves)],
[MAX_ERR] * num_curves)
def run_benchmark(
benchmark_module, module, function, setup_suffix='', repeat=5, number=1000):
setup_func = 'setup_' + function
if setup_suffix:
print('%s with %s:' % (function, setup_suffix), end='')
setup_func += '_' + setup_suffix
else:
print('%s:' % function, end='')
def wrapper(function, setup_func):
function = globals()[function]
setup_func = globals()[setup_func]
def wrapped():
return function(*setup_func())
return wrapped
results = timeit.repeat(wrapper(function, setup_func), repeat=repeat, number=number)
print('\t%5.1fus' % (min(results) * 1000000. / number))
def main():
run_benchmark('cu2qu.benchmark', 'cu2qu', 'curve_to_quadratic')
run_benchmark('cu2qu.benchmark', 'cu2qu', 'curves_to_quadratic')
random.seed(1)
main()