# BEGIN OF LICENSE NOTE
# This file is part of Pyoints.
# Copyright (c) 2018, Sebastian Lamprecht, Trier University,
# lamprecht@uni-trier.de
#
# Pyoints is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# Pyoints is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with Pyoints. If not, see <https://www.gnu.org/licenses/>.
# END OF LICENSE NOTE
"""Data structures to handle multi-dimensional point data.
"""
import numpy as np
from .indexkd import IndexKD
from .extent import Extent
from . import (
assertion,
transformation,
)
from .misc import print_rounded
[docs]class Coords(np.ndarray, object):
"""Class to represent coordinates. It provides a spatial index to
conveniently optimize spatial neighborhood queries. The spatial index is
calculated on demand only and deleted, if coordinates have been changed.
Parameters
----------
coords : array_like(Number)
Represents `n` data points of `k` dimensions in a Cartesian coordinate
system. Any desired shape of at least length two is allowed to enable
the representation point, voxel or raster data. The last shape element
always represents the coordinate dimension.
Attributes
----------
dim : positive int
Number of coordinate dimensions.
flattened : array_like(Number, shape=(n, k))
List representation of the coordinates.
Examples
--------
Create some 2D points.
>>> coords = Coords([(0, 1), (2, 1), (2, 3), (0, -1)])
>>> print_rounded(coords)
[[ 0 1]
[ 2 1]
[ 2 3]
[ 0 -1]]
Get Extent.
>>> print_rounded(coords.extent())
[ 0 -1 2 3]
>>> print_rounded(coords.extent(dim=1))
[0 2]
Use IndexKD, which updates automatically, if a coordinate has changed.
>>> coords.indexKD().ball([0, 0], 2)
[0, 3]
>>> coords[1, 0] = -1
>>> coords.indexKD().ball([0, 0], 2)
[0, 1, 3]
"""
def __new__(cls, coords):
return assertion.ensure_numarray(coords).view(cls)
def __setitem__(self, key, value):
np.ndarray.__setitem__(self, key, value)
self._clear_cache()
def __iter__(self):
return iter(self.view(np.ndarray))
def _clear_cache(self):
if hasattr(self, '_indices'):
del self._indices
if hasattr(self, '_extents'):
del self._extents
@property
def dim(self):
return self.shape[-1]
@property
def flattened(self):
if len(self.shape) == 2:
return self
else:
s = (np.product(self.shape[:self.dim]), self.dim)
return self.reshape(s)
[docs] def indexKD(self, dim=None):
"""Get a spatial index of the coordinates.
Parameters
----------
dim : optional, positive int
Desired dimension of the spatial index. If None, the all coordinate
dimensions are used.
Returns
-------
IndexKD
Spatial index of the coordinates of desired dimension.
Notes
-----
The spatial indices are generated on demand and are cached
automatically. Setting new coordinates clears the cache.
See Also
--------
poynts.IndexKD
Examples
--------
>>> coords = Coords([(2, 3, 1), (3, 2, 3), (0, 1, 0), (9, 5, 4)])
>>> print_rounded(coords.indexKD().dim)
3
>>> print_rounded(coords.indexKD(dim=2).dim)
2
"""
if dim is None:
dim = self.dim
elif not (isinstance(dim, int) and dim > 0 and dim <= self.dim):
m = "'dim' needs to be an integer in range [1, %i]" % self.dim
raise ValueError(m)
# use cache for performance reasons
if not hasattr(self, '_indices'):
self._indices = {}
indexKD = self._indices.get(dim)
if indexKD is None:
indexKD = IndexKD(self.flattened[:, :dim], copy=False)
self._indices[dim] = indexKD
return indexKD
[docs] def extent(self, dim=None):
"""Provides the spatial extent of the coordinates.
Parameters
----------
dim : optional, positive int
Define how many coordinate dimensions to use. If None, all
dimensions are used.
Returns
-------
extent : Extent
Spatial extent of the coordinates.
Notes
-----
The extents are calculated on demand and are cached automatically.
Setting new coordinates clears the cache.
See Also
--------
Extent
Examples
--------
>>> coords = Coords([(2, 3), (3, 2), (0, 1), (-1, 2.2), (9, 5)])
>>> print_rounded(coords.extent())
[-1. 1. 9. 5.]
>>> print_rounded(coords.extent(dim=1))
[-1. 9.]
>>> print_rounded(coords.indexKD().ball([0, 0], 2))
[2]
"""
if dim is None:
dim = self.dim
elif not (isinstance(dim, int) and dim > 0 and dim <= self.dim):
m = "'dim' needs to be an integer in range [1, %i]" % self.dim
raise ValueError(m)
# use cache for performance reasons
if not hasattr(self, '_extents'):
self._extents = {}
ext = self._extents.get(dim)
if ext is None:
ext = Extent(self.flattened[:, :dim])
self._extents[dim] = ext
return ext
