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I'm searching for algorithms to reduce the LOD of polylines, lines (looped or not) of nodes. In simple words, I want to take hi-resolution coastline data and be able to reduce its LOD hundred- or thousandfold to render it in small-scale.
I found polygon reduction algorithms (but they require triangles) and Laplacian smoothing, but that doesn't seem exactly what I need.
595
The simplest one is probably to just keep removing the point whose angle between neighboring points is closest to 180 degrees, until some threshold, or until you've reached a desired number of points.
The Ramer-Douglas–Peucker algorithm is an algorithm for reducing the number of points in a curve that is approximated by a series of points. It does so by "thinking" of a line between the first and last point in a set of points that form the curve. It checks which point in between is farthest away from this line.
I've modified the code in culebrón's answer, removing the need for the Vec2D/Line classes, instead handling the points as a list of tuples.
The code is slightly less tidy, but shorter, and a bit quicker (for 900 points, the original code took 2966ms, and this version takes 500ms - still a bit slower than I'd like, but an improvement)
def _vec2d_dist(p1, p2):
return (p1[0] - p2[0])**2 + (p1[1] - p2[1])**2
def _vec2d_sub(p1, p2):
return (p1[0]-p2[0], p1[1]-p2[1])
def _vec2d_mult(p1, p2):
return p1[0]*p2[0] + p1[1]*p2[1]
def ramerdouglas(line, dist):
"""Does Ramer-Douglas-Peucker simplification of a curve with `dist`
threshold.
`line` is a list-of-tuples, where each tuple is a 2D coordinate
Usage is like so:
>>> myline = [(0.0, 0.0), (1.0, 2.0), (2.0, 1.0)]
>>> simplified = ramerdouglas(myline, dist = 1.0)
"""
if len(line) < 3:
return line
(begin, end) = (line[0], line[-1]) if line[0] != line[-1] else (line[0], line[-2])
distSq = []
for curr in line[1:-1]:
tmp = (
_vec2d_dist(begin, curr) - _vec2d_mult(_vec2d_sub(end, begin), _vec2d_sub(curr, begin)) ** 2 / _vec2d_dist(begin, end))
distSq.append(tmp)
maxdist = max(distSq)
if maxdist < dist ** 2:
return [begin, end]
pos = distSq.index(maxdist)
return (ramerdouglas(line[:pos + 2], dist) +
ramerdouglas(line[pos + 1:], dist)[1:])
The solution that I've found and quite probably will use, is Ramer-Douglas-Peucker algorithm. It's used in PostGIS
I've published my own implementation in Python (site currently down, the following was pulled from archive.org)
#!/usr/bin/python
"""Ramer-Douglas-Peucker line simplification demo.
Dmitri Lebedev, [email protected]
http://ryba4.com/python/ramer-douglas-peucker
2010-04-17"""
def ramerdouglas(line, dist):
"""Does Ramer-Douglas-Peucker simplification of
a line with `dist` threshold.
`line` must be a list of Vec objects,
all of the same type (either 2d or 3d)."""
if len(line) < 3:
return line
begin, end = line[0], line[-1]
distSq = [begin.distSq(curr) -
((end - begin) * (curr - begin)) ** 2 /
begin.distSq(end) for curr in line[1:-1]]
maxdist = max(distSq)
if maxdist < dist ** 2:
return [begin, end]
pos = distSq.index(maxdist)
return (ramerdouglas(line[:pos + 2], dist) +
ramerdouglas(line[pos + 1:], dist)[1:])
class Line:
"""Polyline. Contains a list of points and outputs
a simplified version of itself."""
def __init__(self, points):
pointclass = points[0].__class__
for i in points[1:]:
if i.__class__ != pointclass:
raise TypeError("""All points in a Line
must have the same type""")
self.points = points
def simplify(self, dist):
if self.points[0] != self.points[-1]:
points = ramerdouglas(self.points, dist)
else:
points = ramerdouglas(
self.points[:-1], dist) + self.points[-1:]
return self.__class__(points)
def __repr__(self):
return '{0}{1}'.format(self.__class__.__name__,
tuple(self.points))
class Vec:
"""Generic vector class for n-dimensional vectors
for any natural n."""
def __eq__(self, obj):
"""Equality check."""
if self.__class__ == obj.__class__:
return self.coords == obj.coords
return False
def __repr__(self):
"""String representation. The string is executable as Python
code and makes the same vector."""
return '{0}{1}'.format(self.__class__.__name__, self.coords)
def __add__(self, obj):
"""Add a vector."""
if not isinstance(obj, self.__class__):
raise TypeError
return self.__class__(*map(sum, zip(self.coords, obj.coords)))
def __neg__(self):
"""Reverse the vector."""
return self.__class__(*[-i for i in self.coords])
def __sub__(self, obj):
"""Substract object from self."""
if not isinstance(obj, self.__class__):
raise TypeError
return self + (- obj)
def __mul__(self, obj):
"""If obj is scalar, scales the vector.
If obj is vector returns the scalar product."""
if isinstance(obj, self.__class__):
return sum([a * b for (a, b) in zip(self.coords, obj.coords)])
return self.__class__(*[i * obj for i in self.coords])
def dist(self, obj = None):
"""Distance to another object. Leave obj empty to get
the length of vector from point 0."""
return self.distSq(obj) ** 0.5
def distSq(self, obj = None):
""" Square of distance. Use this method to save
calculations if you don't need to calculte an extra square root."""
if obj is None:
obj = self.__class__(*[0]*len(self.coords))
elif not isinstance(obj, self.__class__):
raise TypeError('Parameter must be of the same class')
# simple memoization to save extra calculations
if obj.coords not in self.distSqMem:
self.distSqMem[obj.coords] = sum([(s - o) ** 2 for (s, o) in
zip(self.coords, obj.coords)])
return self.distSqMem[obj.coords]
class Vec3D(Vec):
"""3D vector"""
def __init__(self, x, y, z):
self.coords = x, y, z
self.distSqMem = {}
class Vec2D(Vec):
"""2D vector"""
def __init__(self, x, y):
self.coords = x, y
self.distSqMem = {}
if __name__ == '__main__':
coast = Line([
Vec2D( 6.247872 , 11.316756 ),
Vec2D( 6.338566 , 11.316756 ),
Vec2D( 6.633323 , 11.205644 ),
Vec2D( 6.724018 , 11.205644 ),
Vec2D( 6.792039 , 11.205644 ),
Vec2D( 7.154817 , 11.372311 ),
Vec2D( 7.313532 , 11.400089 ),
Vec2D( 7.381553 , 11.344533 ),
Vec2D( 7.336206 , 11.288978 ),
Vec2D( 7.200164 , 11.288978 ),
Vec2D( 7.154817 , 11.261200 ),
Vec2D( 7.132143 , 11.233422 ),
Vec2D( 7.154817 , 11.150089 ),
Vec2D( 7.268185 , 11.177867 ),
Vec2D( 7.313532 , 11.122311 ),
Vec2D( 7.404227 , 11.150089 ),
Vec2D( 7.472248 , 11.094533 ),
Vec2D( 7.767005 , 10.900089 ),
Vec2D( 7.758951 , 10.864989 ),
Vec2D( 7.752684 , 10.837656 ),
Vec2D( 7.426900 , 10.927867 ),
Vec2D( 6.519955 , 10.927867 ),
Vec2D( 6.429261 , 10.900089 ),
Vec2D( 6.315893 , 10.955644 ),
Vec2D( 6.270545 , 10.955644 ),
Vec2D( 6.247872 , 10.927867 ),
Vec2D( 6.111830 , 11.011200 ),
Vec2D( 6.066483 , 11.066756 ),
Vec2D( 5.862420 , 11.038978 ),
Vec2D( 5.817073 , 10.955644 ),
Vec2D( 5.771726 , 10.900089 ),
Vec2D( 5.862420 , 10.761200 ),
Vec2D( 5.975788 , 10.733422 ),
Vec2D( 6.157177 , 10.566756 ),
Vec2D( 6.247872 , 10.511200 ),
Vec2D( 6.293219 , 10.427867 ),
Vec2D( 6.315893 , 10.233422 ),
Vec2D( 6.315893 , 10.177867 ),
Vec2D( 6.542629 , 9.844533 ),
Vec2D( 6.587976 , 9.761200 ),
Vec2D( 6.610650 , 9.288978 ),
Vec2D( 6.542629 , 9.066756 ),
Vec2D( 6.565303 , 8.900089 ),
Vec2D( 6.519955 , 8.816756 ),
Vec2D( 6.542629 , 8.761200 ),
Vec2D( 6.565303 , 8.733422 ),
Vec2D( 6.429261 , 8.427867 ),
Vec2D( 6.474608 , 8.316756 ),
Vec2D( 6.724018 , 8.288978 ),
Vec2D( 6.882733 , 8.538978 ),
Vec2D( 6.973428 , 8.594533 ),
Vec2D( 6.996101 , 8.622311 ),
Vec2D( 7.200164 , 8.650089 ),
Vec2D( 7.290859 , 8.650089 ),
Vec2D( 7.426900 , 8.483422 ),
Vec2D( 7.404227 , 8.455644 ),
Vec2D( 7.245511 , 8.511200 ),
Vec2D( 6.996101 , 8.427867 ),
Vec2D( 7.041449 , 8.372311 ),
Vec2D( 7.154817 , 8.455644 ),
Vec2D( 7.200164 , 8.455644 ),
Vec2D( 7.245511 , 8.455644 ),
Vec2D( 7.381553 , 8.316756 ),
Vec2D( 7.381553 , 8.261200 ),
Vec2D( 7.404227 , 8.233422 ),
Vec2D( 7.494921 , 8.205644 ),
Vec2D( 7.767005 , 8.288978 ),
Vec2D( 7.948394 , 8.233422 ),
Vec2D( 8.016415 , 8.261200 ),
Vec2D( 8.197804 , 8.094533 ),
Vec2D( 8.084435 , 7.816756 ),
Vec2D( 8.152456 , 7.733422 ),
Vec2D( 8.175130 , 7.650089 ),
Vec2D( 8.175130 , 7.511200 ),
Vec2D( 8.311172 , 7.427867 ),
Vec2D( 8.311172 , 7.372311 ),
Vec2D( 8.651276 , 7.372311 ),
Vec2D( 8.923360 , 7.316756 ),
Vec2D( 8.900686 , 7.261200 ),
Vec2D( 8.809991 , 7.261200 ),
Vec2D( 8.472735 , 7.171122 ),
Vec2D( 8.333845 , 7.038978 ),
Vec2D( 8.282022 , 6.981100 ),
Vec2D( 8.254778 , 6.848911 ),
Vec2D( 8.265824 , 6.816756 ),
Vec2D( 8.239206 , 6.711211 ),
Vec2D( 8.219743 , 6.612067 ),
Vec2D( 8.130227 , 6.433044 ),
Vec2D( 8.084435 , 6.316756 ),
Vec2D( 8.107109 , 6.288978 ),
Vec2D( 7.948394 , 6.177867 ),
Vec2D( 7.925720 , 5.983422 ),
Vec2D( 7.857699 , 5.816756 ),
Vec2D( 7.835026 , 5.788978 ),
Vec2D( 7.857699 , 5.511200 ),
Vec2D( 7.812352 , 5.400089 ),
Vec2D( 7.812352 , 5.344533 ),
Vec2D( 7.812352 , 5.177867 ),
Vec2D( 8.084435 , 4.733422 ),
Vec2D( 8.107109 , 4.622311 ),
Vec2D( 7.857699 , 4.344533 ),
Vec2D( 7.630963 , 4.261200 ),
Vec2D( 7.540268 , 4.177867 ),
Vec2D( 7.494921 , 4.150089 ),
Vec2D( 7.449574 , 4.150089 ),
Vec2D( 7.404227 , 4.150089 ),
Vec2D( 7.336206 , 4.094533 ),
Vec2D( 7.313532 , 4.066756 ),
Vec2D( 7.041449 , 4.011200 ),
Vec2D( 6.905407 , 3.955644 ),
Vec2D( 6.950754 , 3.900089 ),
Vec2D( 7.200164 , 3.927867 ),
Vec2D( 7.630963 , 3.872311 ),
Vec2D( 7.721657 , 3.872311 ),
Vec2D( 7.948394 , 3.788978 ),
Vec2D( 7.993741 , 3.705644 ),
Vec2D( 7.971067 , 3.677867 ),
Vec2D( 7.925720 , 3.622311 ),
Vec2D( 8.175130 , 3.705644 ),
Vec2D( 8.401866 , 3.650089 ),
Vec2D( 8.492561 , 3.650089 ),
Vec2D( 8.605929 , 3.538978 ),
Vec2D( 8.651276 , 3.566756 ),
Vec2D( 8.855339 , 3.372311 ),
Vec2D( 8.900686 , 3.316756 ),
Vec2D( 8.900686 , 3.150089 ),
Vec2D( 8.787318 , 2.900089 ),
Vec2D( 8.787318 , 2.844533 ),
Vec2D( 8.946033 , 2.816756 ),
Vec2D( 8.991380 , 2.788978 ),
Vec2D( 9.014054 , 2.705644 ),
Vec2D( 8.886928 , 2.524989 ),
Vec2D( 8.832665 , 2.538978 ),
Vec2D( 8.809991 , 2.455644 ),
Vec2D( 8.923360 , 2.538978 ),
Vec2D( 9.014054 , 2.400089 ),
Vec2D( 9.308811 , 2.288978 ),
Vec2D( 9.399506 , 2.261200 ),
Vec2D( 9.512874 , 2.122311 ),
Vec2D( 9.535548 , 1.983422 ),
Vec2D( 9.512874 , 1.955644 ),
Vec2D( 9.467527 , 1.816756 ),
Vec2D( 9.036728 , 1.816756 ),
Vec2D( 8.991380 , 1.927867 ),
Vec2D( 8.946033 , 1.955644 ),
Vec2D( 8.900686 , 1.983422 ),
Vec2D( 8.946033 , 2.122311 ),
Vec2D( 8.968707 , 2.150089 ),
Vec2D( 9.195443 , 1.927867 ),
Vec2D( 9.354158 , 1.955644 ),
Vec2D( 9.376832 , 2.038978 ),
Vec2D( 9.376832 , 2.094533 ),
Vec2D( 9.240790 , 2.205644 ),
Vec2D( 9.195443 , 2.205644 ),
Vec2D( 9.263464 , 2.150089 ),
Vec2D( 9.240790 , 2.122311 ),
Vec2D( 9.195443 , 2.122311 ),
Vec2D( 9.104749 , 2.122311 ),
Vec2D( 8.900686 , 2.316756 ),
Vec2D( 8.787318 , 2.344533 ),
Vec2D( 8.696623 , 2.372311 ),
Vec2D( 8.651276 , 2.427867 ),
Vec2D( 8.719297 , 2.455644 ),
Vec2D( 8.787318 , 2.650089 ),
Vec2D( 8.832665 , 2.705644 ),
Vec2D( 8.605929 , 2.677867 ),
Vec2D( 8.537908 , 2.788978 ),
Vec2D( 8.333845 , 2.788978 ),
Vec2D( 7.925720 , 2.316756 ),
Vec2D( 7.925720 , 2.261200 ),
Vec2D( 7.903046 , 2.233422 ),
Vec2D( 7.857699 , 2.233422 ),
Vec2D( 7.857699 , 2.177867 ),
Vec2D( 7.789678 , 1.983422 ),
Vec2D( 7.812352 , 1.788978 ),
Vec2D( 7.948394 , 1.538978 ),
Vec2D( 7.971067 , 1.511200 ),
Vec2D( 8.129783 , 1.511200 ),
Vec2D( 8.243151 , 1.594533 ),
Vec2D( 8.333845 , 1.594533 ),
Vec2D( 8.424540 , 1.622311 ),
Vec2D( 8.515234 , 1.566756 ),
Vec2D( 8.673950 , 1.400089 ),
Vec2D( 8.771174 , 1.291756 ),
Vec2D( 8.828938 , 1.119878 ),
Vec2D( 8.762504 , 0.972544 ),
Vec2D( 9.238614 , 0.759633 ),
Vec2D( 9.492323 , 0.627022 ),
Vec2D( 9.820891 , 0.644711 ),
Vec2D( 10.376567 , 0.800622 ),
Vec2D( 10.651961 , 1.085978 ),
Vec2D( 10.762173 , 1.132022 ),
Vec2D( 10.943045 , 1.095989 ),
Vec2D( 11.256739 , 0.999878 ),
Vec2D( 11.576074 , 0.761611 ),
Vec2D( 11.768247 , 0.425211 ),
Vec2D( 11.960165 , 0.074778 ),
Vec2D( 11.953907 , 0.000000 ),
Vec2D( 11.629411 , 0.258767 ),
Vec2D( 11.229920 , 0.582278 ),
Vec2D( 11.001633 , 0.564300 ),
Vec2D( 10.868476 , 0.447478 ),
Vec2D( 10.633849 , 0.541833 ),
Vec2D( 10.513370 , 0.672133 ),
Vec2D( 11.188700 , 0.820078 ),
Vec2D( 11.194014 , 0.859656 ),
Vec2D( 11.118212 , 0.905822 ),
Vec2D( 10.874860 , 0.930311 ),
Vec2D( 10.427319 , 0.716522 ),
Vec2D( 10.023620 , 0.374211 ),
Vec2D( 9.434614 , 0.360144 ),
Vec2D( 8.455131 , 0.859544 ),
Vec2D( 8.180481 , 0.920500 ),
Vec2D( 7.902529 , 1.115078 ),
Vec2D( 7.823108 , 1.269800 ),
Vec2D( 7.830482 , 1.403778 ),
Vec2D( 7.791937 , 1.496744 ),
Vec2D( 7.767005 , 1.538978 ),
Vec2D( 7.676310 , 1.622311 ),
Vec2D( 7.653637 , 1.650089 ),
Vec2D( 7.585616 , 1.955644 ),
Vec2D( 7.562942 , 1.983422 ),
Vec2D( 7.562942 , 2.233422 ),
Vec2D( 7.608289 , 2.400089 ),
Vec2D( 7.630963 , 2.427867 ),
Vec2D( 7.608289 , 2.538978 ),
Vec2D( 7.585616 , 2.566756 ),
Vec2D( 7.653637 , 2.705644 ),
Vec2D( 7.630963 , 2.816756 ),
Vec2D( 7.336206 , 3.011200 ),
Vec2D( 7.290859 , 3.011200 ),
Vec2D( 7.245511 , 3.011200 ),
Vec2D( 7.041449 , 2.955644 ),
Vec2D( 6.928081 , 2.816756 ),
Vec2D( 6.928081 , 2.733422 ),
Vec2D( 6.905407 , 2.622311 ),
Vec2D( 6.860060 , 2.677867 ),
Vec2D( 6.814712 , 2.677867 ),
Vec2D( 6.678671 , 2.677867 ),
Vec2D( 6.678671 , 2.733422 ),
Vec2D( 6.769365 , 2.733422 ),
Vec2D( 6.814712 , 2.733422 ),
Vec2D( 6.792039 , 2.788978 ),
Vec2D( 6.293219 , 3.066756 ),
Vec2D( 6.225198 , 3.122311 ),
Vec2D( 6.202525 , 3.233422 ),
Vec2D( 6.134504 , 3.344533 ),
Vec2D( 5.907767 , 3.261200 ),
Vec2D( 5.862420 , 3.288978 ),
Vec2D( 6.043809 , 3.427867 ),
Vec2D( 6.021136 , 3.483422 ),
Vec2D( 5.975788 , 3.483422 ),
Vec2D( 5.930441 , 3.511200 ),
Vec2D( 5.953115 , 3.566756 ),
Vec2D( 5.975788 , 3.594533 ),
Vec2D( 5.749052 , 3.788978 ),
Vec2D( 5.703705 , 3.788978 ),
Vec2D( 5.635684 , 3.788978 ),
Vec2D( 5.703705 , 3.844533 ),
Vec2D( 5.703705 , 4.011200 ),
Vec2D( 5.499642 , 4.011200 ),
Vec2D( 5.862420 , 4.372311 ),
Vec2D( 5.975788 , 4.427867 ),
Vec2D( 6.021136 , 4.427867 ),
Vec2D( 6.089156 , 4.538978 ),
Vec2D( 6.111830 , 4.566756 ),
Vec2D( 6.089156 , 4.650089 ),
Vec2D( 5.998462 , 4.650089 ),
Vec2D( 5.817073 , 4.788978 ),
Vec2D( 5.771726 , 4.816756 ),
Vec2D( 5.681031 , 4.816756 ),
Vec2D( 5.749052 , 4.927867 ),
Vec2D( 5.749052 , 5.038978 ),
Vec2D( 5.839747 , 5.177867 ),
Vec2D( 5.998462 , 5.233422 ),
Vec2D( 6.225198 , 5.233422 ),
Vec2D( 6.270545 , 5.233422 ),
Vec2D( 6.383914 , 5.288978 ),
Vec2D( 6.406587 , 5.372311 ),
Vec2D( 6.429261 , 5.400089 ),
Vec2D( 6.587976 , 5.483422 ),
Vec2D( 6.670626 , 5.490000 ),
Vec2D( 6.700845 , 5.564100 ),
Vec2D( 6.860060 , 5.927867 ),
Vec2D( 6.860060 , 6.038978 ),
Vec2D( 6.950754 , 6.205644 ),
Vec2D( 6.973428 , 6.316756 ),
Vec2D( 7.041449 , 6.344533 ),
Vec2D( 7.064122 , 6.455644 ),
Vec2D( 7.116072 , 6.541989 ),
Vec2D( 7.114313 , 6.603667 ),
Vec2D( 7.025305 , 6.741422 ),
Vec2D( 6.736924 , 6.701367 ),
Vec2D( 6.641658 , 6.741467 ),
Vec2D( 6.500574 , 6.761389 ),
Vec2D( 6.435410 , 6.733422 ),
Vec2D( 6.224291 , 6.728556 ),
Vec2D( 6.191759 , 6.738989 ),
Vec2D( 6.099124 , 6.755000 ),
Vec2D( 6.041805 , 6.749733 ),
Vec2D( 6.001672 , 6.742967 ),
Vec2D( 5.905382 , 6.718300 ),
Vec2D( 5.817073 , 6.677867 ),
Vec2D( 5.611713 , 6.686622 ),
Vec2D( 5.401366 , 6.864333 ),
Vec2D( 5.386274 , 6.927867 ),
Vec2D( 5.356608 , 6.981811 ),
Vec2D( 5.404095 , 7.111822 ),
Vec2D( 5.561958 , 7.216133 ),
Vec2D( 5.660643 , 7.244722 ),
Vec2D( 5.366149 , 7.489478 ),
Vec2D( 5.340927 , 7.511200 ),
Vec2D( 5.114998 , 7.592867 ),
Vec2D( 4.870667 , 7.692033 ),
Vec2D( 4.746560 , 7.781856 ),
Vec2D( 4.708060 , 7.760867 ),
Vec2D( 4.692225 , 7.802500 ),
Vec2D( 4.607090 , 7.849044 ),
Vec2D( 4.481324 , 7.879711 ),
Vec2D( 4.340031 , 8.093378 ),
Vec2D( 4.181171 , 8.158044 ),
Vec2D( 4.116415 , 8.200800 ),
Vec2D( 4.081135 , 8.195278 ),
Vec2D( 4.090912 , 8.272500 ),
Vec2D( 4.032232 , 8.378311 ),
Vec2D( 3.779566 , 8.791278 ),
Vec2D( 3.769654 , 8.849022 ),
Vec2D( 3.598177 , 8.955178 ),
Vec2D( 3.576828 , 9.059633 ),
Vec2D( 3.527037 , 9.066756 ),
Vec2D( 3.498069 , 9.082022 ),
Vec2D( 3.541865 , 9.174211 ),
Vec2D( 3.542409 , 9.234411 ),
Vec2D( 3.576275 , 9.262711 ),
Vec2D( 3.582279 , 9.287744 ),
Vec2D( 3.390995 , 9.316756 ),
Vec2D( 3.209606 , 9.344533 ),
Vec2D( 3.100836 , 9.367511 ),
Vec2D( 2.957466 , 9.370756 ),
Vec2D( 2.870844 , 9.366222 ),
Vec2D( 2.777211 , 9.285222 ),
Vec2D( 2.744851 , 9.285900 ),
Vec2D( 2.775397 , 9.294867 ),
Vec2D( 2.832661 , 9.341156 ),
Vec2D( 2.868114 , 9.373300 ),
Vec2D( 2.869502 , 9.400089 ),
Vec2D( 2.794434 , 9.420178 ),
Vec2D( 2.714423 , 9.440078 ),
Vec2D( 2.641124 , 9.441944 ),
Vec2D( 2.572096 , 9.428378 ),
Vec2D( 2.548379 , 9.418600 ),
Vec2D( 2.573130 , 9.388211 ),
Vec2D( 2.563126 , 9.333567 ),
Vec2D( 2.535855 , 9.320067 ),
Vec2D( 2.517670 , 9.282778 ),
Vec2D( 2.479488 , 9.260278 ),
Vec2D( 2.483125 , 9.239067 ),
Vec2D( 2.464034 , 9.224278 ),
Vec2D( 2.468586 , 9.180556 ),
Vec2D( 2.443129 , 9.168989 ),
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Vec2D( 2.444897 , 9.109600 ),
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Vec2D( 2.444897 , 9.080389 ),
Vec2D( 2.447808 , 9.045822 ),
Vec2D( 2.424536 , 9.024011 ),
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Vec2D( 2.442457 , 8.957422 ),
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Vec2D( 2.413136 , 8.853411 ),
Vec2D( 2.410805 , 8.836944 ),
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Vec2D( 2.386608 , 8.776044 ),
Vec2D( 2.398706 , 8.757278 ),
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Vec2D( 2.365195 , 8.790533 ),
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Vec2D( 2.332091 , 8.946244 ),
Vec2D( 2.340091 , 8.927722 ),
Vec2D( 2.332091 , 8.912289 ),
Vec2D( 2.316093 , 8.904067 ),
Vec2D( 2.311730 , 8.874744 ),
Vec2D( 2.288975 , 8.861244 ),
Vec2D( 2.247727 , 8.856233 ),
Vec2D( 2.233180 , 8.861889 ),
Vec2D( 2.209436 , 8.859233 ),
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Vec2D( 2.265911 , 8.873200 ),
Vec2D( 2.277548 , 8.869600 ),
Vec2D( 2.290635 , 8.873711 ),
Vec2D( 2.299360 , 8.904578 ),
Vec2D( 2.268088 , 8.909622 ),
Vec2D( 2.247727 , 8.925256 ),
Vec2D( 2.225734 , 8.920756 ),
Vec2D( 2.208747 , 8.909622 ),
Vec2D( 2.203768 , 8.921811 ),
Vec2D( 2.214352 , 8.931822 ),
Vec2D( 2.197138 , 8.933811 ),
Vec2D( 2.148725 , 8.907478 ),
Vec2D( 2.134577 , 8.904844 ),
Vec2D( 2.113354 , 8.917222 ),
Vec2D( 2.095107 , 8.918800 ),
Vec2D( 2.079961 , 8.912944 ),
Vec2D( 2.060761 , 8.913356 ),
Vec2D( 2.034577 , 8.902656 ),
Vec2D( 1.983589 , 8.895400 ),
Vec2D( 2.033997 , 8.913356 ),
Vec2D( 2.062502 , 8.918700 ),
Vec2D( 2.092758 , 8.929811 ),
Vec2D( 2.148090 , 8.928756 ),
Vec2D( 2.168397 , 8.937878 ),
Vec2D( 2.146421 , 8.965533 ),
Vec2D( 2.182173 , 8.943933 ),
Vec2D( 2.201537 , 8.951311 ),
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Vec2D( 2.284939 , 8.925767 ),
Vec2D( 2.306887 , 8.926022 ),
Vec2D( 2.311086 , 8.936356 ),
Vec2D( 2.296312 , 8.952489 ),
Vec2D( 2.317254 , 8.981122 ),
Vec2D( 2.334939 , 9.003844 ),
Vec2D( 2.374500 , 9.014044 ),
Vec2D( 2.386136 , 9.034778 ),
Vec2D( 2.401962 , 9.044656 ),
Vec2D( 2.418723 , 9.044889 ),
Vec2D( 2.426287 , 9.054878 ),
Vec2D( 2.411739 , 9.063522 ),
Vec2D( 2.426867 , 9.099311 ),
Vec2D( 2.398362 , 9.125233 ),
Vec2D( 2.373339 , 9.121944 ),
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Vec2D( 2.425860 , 9.192778 ),
Vec2D( 2.423783 , 9.231400 ),
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Vec2D( 2.449495 , 9.245489 ),
Vec2D( 2.457676 , 9.289856 ),
Vec2D( 2.481311 , 9.298211 ),
Vec2D( 2.488585 , 9.334211 ),
Vec2D( 2.520255 , 9.353822 ),
Vec2D( 2.520400 , 9.369944 ),
Vec2D( 2.494960 , 9.432511 ),
Vec2D( 2.463671 , 9.469200 ),
Vec2D( 2.406950 , 9.500578 ),
Vec2D( 2.240907 , 9.536433 ),
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Vec2D( 2.031530 , 9.607422 ),
Vec2D( 1.932328 , 9.658044 ),
Vec2D( 1.835167 , 9.695656 ),
Vec2D( 1.746196 , 9.760744 ),
Vec2D( 1.667446 , 9.789667 ),
Vec2D( 1.575400 , 9.797622 ),
Vec2D( 1.562104 , 9.828722 ),
Vec2D( 1.531422 , 9.846800 ),
Vec2D( 1.415859 , 9.888744 ),
Vec2D( 1.315206 , 9.942167 ),
Vec2D( 1.175573 , 10.083667 ),
Vec2D( 1.147394 , 10.090267 ),
Vec2D( 1.118064 , 10.086567 ),
Vec2D( 0.990883 , 9.998400 ),
Vec2D( 0.778930 , 9.990856 ),
Vec2D( 0.592924 , 10.033144 ),
Vec2D( 0.507490 , 10.125422 ),
Vec2D( 0.419562 , 10.320811 ),
Vec2D( 0.375403 , 10.344533 ),
Vec2D( 0.276464 , 10.431189 ),
Vec2D( 0.220170 , 10.534911 ),
Vec2D( 0.181271 , 10.571000 ),
Vec2D( 0.153745 , 10.620156 ),
Vec2D( 0.114973 , 10.653889 ),
Vec2D( 0.103274 , 10.707756 ),
Vec2D( 0.097914 , 10.761511 ),
Vec2D( 0.076256 , 10.811522 ),
Vec2D( 0.061935 , 10.867833 ),
Vec2D( 0.000000 , 10.960167 )
])
distances = (0, .05, .1, .25) # threshold sizes in kilometres
import csv
for d in distances:
simple = coast.simplify(d) if d > 0 else coast
with open('poly-{0}.csv'.format(d), 'w') as output_doc:
writer = csv.writer(output_doc, dialect='excel')
for pt in simple.points:
writer.writerow(pt.coords)
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