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Seven functions to simplify or linearize a path of
LatLon
points.
Each of the simplify functions is based on a different
algorithm and produces different simplified results in (very) different
run times for the same path of LatLon
points.
Function simplify1 eliminates points based on edge lengths shorter than a given tolerance.
The functions simplifyRDP and simplifyRDPm use the original, respectively modified Ramer-Douglas-Peucker (RDP) algorithm, iteratively finding the point farthest from each path edge. The difference is that function simplifyRDP exhaustively searches the most distant point in each iteration, while modified simplifyRDPm stops at the first point exceeding the distance tolerance.
Function simplifyRW use the Reumann-Witkam method, sliding a "pipe" over each path edge, removing all subsequent points within, closer than the pipe radius up to the first point outside the pipe.
Functions simplifyVW and simplifyVWm are based on the original, respectively modified Visvalingam-Whyatt (VW) method using the area of the triangle formed by three neigboring points. Function simplifyVW removes only a single point per iteration, while modified simplifyVWm eliminates in each iteration all points with a triangular area not exceeding the tolerance.
Functions simplifyRDP, simplifyRDPm and simplifyRW provide keyword argument shortest to
select the computation of the distance between a point and a path edge.
If True
, use the shortest distance to the path edge or path
end points, if False
use the perpendicular distance to the
extended path edge line.
Keyword argument radius
of all fuctions is set to
the mean earth radius in meter. Other units can be choosen, provided
that the radius and tolerance are always specified in the same units.
Use keyword argument indices
=True
in
any function to return a list of simplified point indices instead
of the simplified points. The first and last index are always the first
and last original index.
Finally, any additional keyword arguments options
to all functions are passed thru to function equirectangular_ to specify the distance
approximation.
To process NumPy
arrays containing rows of lat-,
longitude and possibly other values, use class Numpy2LatLon to wrap the NumPy
array into
on-the-fly-LatLon points. Pass the Numpy2LatLon instance to any simplify function
and the returned result will be a NumPy
array containing the
simplified subset, a partial copy of the original NumPy
array. Use keyword argument
indices
=True
to return a list of array
row indices inlieu of the simplified array subset.
See:
Version: 19.05.08
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Variables | |
__all__ = _ALL_LAZY.simplify
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Function Details |
Basic simplification of a path of Eliminates any points closer together than the given distance tolerance.
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Ramer-Douglas-Peucker (RDP) simplification of a path of
Eliminates any points too close together or closer to an edge than the given distance tolerance. This RDP method exhaustively searches for the point with the largest distance, resulting in worst-case complexity O(n**2) where n is the number of points.
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Modified Ramer-Douglas-Peucker (RDPm) simplification of a path of
Eliminates any points too close together or closer to an edge than the given distance tolerance. This RDP method stops at the first point farther than the given distance tolerance, significantly reducing the run time (but producing results different from the original RDP method).
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Reumann-Witkam (RW) simplification of a path of Eliminates any points too close together or within the given pipe tolerance along an edge.
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Visvalingam-Whyatt (VW) simplification of a path of
Eliminates any points too close together or with a triangular area not exceeding the given area tolerance (squared). This VW method exhaustively searches for the single point with the smallest triangular area, resulting in worst-case complexity O(n**2) where n is the number of points.
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Modified Visvalingam-Whyatt (VWm) simplification of a path of
Eliminates any points too close together or with a triangular area not exceeding the given area tolerance (squared). This VW method removes all points with a triangular area below the tolerance each iteration, significantly reducing the run time (but producing results different from the original VW method).
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