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[FEATURE][processing] New algorithm for topological coloring of polygons
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nyalldawson committed Feb 22, 2017
2 parents bde4ff9 + 74abd5b commit 18b9f40
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14 changes: 14 additions & 0 deletions python/plugins/processing/algs/help/qgis.yaml
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Expand Up @@ -544,6 +544,19 @@ qgis:symmetricaldifference: >
qgis:texttofloat: >
This algorithm modifies the type of a given attribute in a vector layer, converting a text attribute containing numeric strings into a numeric attribute.

qgis:topologicalcoloring: >
This algorithm assigns a color index to polygon features in such a way that no adjacent polygons share the same color index, whilst minimizing the number of colors required.

An optional minimum distance between features assigned the same color can be set to prevent nearby (but non-touching) features from being assigned equal colors.

The algorithm allows choice of method to use when assigning colors. The default method attempts to assign colors so that the count of features assigned to each individual color index is balanced.

The 'by assigned area' mode instead assigns colors so that the total area of features assigned to each color is balanced. This mode can be useful to help avoid large features resulting in one of the colors appearing more dominant on a colored map.

The 'by distance between colors' mode will assign colors in order to maximize the distance between features of the same color. This mode helps to create a more uniform distribution of colors across a map.

A minimum number of colors can be specified if desired. The color index is saved to a new attribute named color_id.

qgis:translate: >
This algorithm moves the geometries within a layer, by offsetting them with a specified x and y displacement.

Expand Down Expand Up @@ -595,3 +608,4 @@ qgis:fixgeometries: >
This algorithm attempts to create a valid representation of a given invalid geometry without losing any of the input vertices. Already-valid geometries are returned without further intervention. Always outputs multi-geometry layer.

NOTE: M values will be dropped from the output.

4 changes: 3 additions & 1 deletion python/plugins/processing/algs/qgis/
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Expand Up @@ -186,6 +186,7 @@
from .FixGeometry import FixGeometry
from .ExecuteSQL import ExecuteSQL
from .FindProjection import FindProjection
from .TopoColors import TopoColor

pluginPath = os.path.normpath(os.path.join(
os.path.split(os.path.dirname(__file__))[0], os.pardir))
Expand Down Expand Up @@ -255,7 +256,8 @@ def __init__(self):
ShortestPathPointToPoint(), ShortestPathPointToLayer(),
ShortestPathLayerToPoint(), ServiceAreaFromPoint(),
ServiceAreaFromLayer(), TruncateTable(), Polygonize(),
FixGeometry(), ExecuteSQL(), FindProjection()
FixGeometry(), ExecuteSQL(), FindProjection(),

if hasPlotly:
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274 changes: 274 additions & 0 deletions python/plugins/processing/algs/qgis/
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# -*- coding: utf-8 -*-

Date : February 2017
Copyright : (C) 2017 by Nyall Dawson
Email : nyall dot dawson at gmail dot com
* *
* This program 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 2 of the License, or *
* (at your option) any later version. *
* *

__author__ = 'Nyall Dawson'
__date__ = 'February 2017'
__copyright__ = '(C) 2017, Nyall Dawson'

# This will get replaced with a git SHA1 when you do a git archive323

__revision__ = '$Format:%H$'

import os
import operator
import sys

from collections import defaultdict, deque

from qgis.core import (QgsField,

from qgis.PyQt.QtCore import (QVariant)

from processing.core.GeoAlgorithm import GeoAlgorithm
from processing.core.parameters import (ParameterVector,
from processing.core.outputs import OutputVector
from import dataobjects, vector

pluginPath = os.path.split(os.path.split(os.path.dirname(__file__))[0])[0]

class TopoColor(GeoAlgorithm):

def defineCharacteristics(self):, self.i18n_name = self.trAlgorithm('Topological coloring'), self.i18n_group = self.trAlgorithm('Cartographic tools')
self.tags ='topocolor,colors,graph,adjacent,assign')

self.addParameter(ParameterVector(self.INPUT_LAYER,'Input layer'), [dataobjects.TYPE_VECTOR_POLYGON]))
self.addParameter(ParameterNumber(self.MIN_COLORS,'Minimum number of colors'), 1, 1000, 4))
self.addParameter(ParameterNumber(self.MIN_DISTANCE,'Minimum distance between features'), 0.0, 999999999.0, 0.0))
balance_by = ['By feature count'),'By assigned area'),'By distance between colors')]
self.BALANCE,'Balance color assignment'),
balance_by, default=0))

self.addOutput(OutputVector(self.OUTPUT_LAYER,'Colored'), datatype=[dataobjects.TYPE_VECTOR_POLYGON]))

def processAlgorithm(self, feedback):
layer = dataobjects.getObjectFromUri(
min_colors = self.getParameterValue(self.MIN_COLORS)
balance_by = self.getParameterValue(self.BALANCE)
min_distance = self.getParameterValue(self.MIN_DISTANCE)

fields = layer.fields()
fields.append(QgsField('color_id', QVariant.Int))

writer = self.getOutputFromName(

features = { f for f in vector.features(layer)}

topology, id_graph = self.compute_graph(features, feedback, min_distance=min_distance)
feature_colors = ColoringAlgorithm.balanced(features,

max_colors = max(feature_colors.values())
feedback.pushInfo('{} colors required').format(max_colors))

total = 20.0 / len(features)
current = 0
for feature_id, input_feature in features.items():
output_feature = input_feature
attributes = input_feature.attributes()
if feature_id in feature_colors:

current += 1
feedback.setProgress(80 + int(current * total))

del writer

def compute_graph(features, feedback, create_id_graph=False, min_distance=0):
""" compute topology from a layer/field """
s = Graph(sort_graph=False)
id_graph = None
if create_id_graph:
id_graph = Graph(sort_graph=True)

# skip features without geometry
features_with_geometry = {f_id: f for (f_id, f) in features.items() if f.hasGeometry()}

total = 70.0 / len(features_with_geometry)
index = QgsSpatialIndex()

i = 0
for feature_id, f in features_with_geometry.items():
g = f.geometry()
if min_distance > 0:
g = g.buffer(min_distance, 5)

engine = QgsGeometry.createGeometryEngine(g.geometry())

feature_bounds = g.boundingBox()
# grow bounds a little so we get touching features
feature_bounds.grow(feature_bounds.width() * 0.01)
intersections = index.intersects(feature_bounds)
for l2 in intersections:
f2 = features_with_geometry[l2]
if engine.intersects(f2.geometry().geometry()):
if id_graph:

i += 1
feedback.setProgress(int(i * total))

for feature_id, f in features_with_geometry.items():
if not feature_id in s.node_edge:
s.add_edge(feature_id, None)

return s, id_graph

class ColoringAlgorithm:

def balanced(features, graph, feedback, balance=0, min_colors=4):
feature_colors = {}
# start with minimum number of colors in pool
color_pool = set(range(1, min_colors + 1))

# calculate count of neighbours
neighbour_count = defaultdict(int)
for feature_id, neighbours in graph.node_edge.items():
neighbour_count[feature_id] += len(neighbours)

# sort features by neighbour count - we want to handle those with more neighbours first
sorted_by_count = [feature_id for feature_id in sorted(neighbour_count.items(),
# counts for each color already assigned
color_counts = defaultdict(int)
color_areas = defaultdict(float)
for c in color_pool:
color_counts[c] = 0
color_areas[c] = 0

total = 10.0 / len(sorted_by_count)
i = 0

for (feature_id, n) in sorted_by_count:
# first work out which already assigned colors are adjacent to this feature
adjacent_colors = set()
for neighbour in graph.node_edge[feature_id]:
if neighbour in feature_colors:

# from the existing colors, work out which are available (ie non-adjacent)
available_colors = color_pool.difference(adjacent_colors)

feature_color = -1
if len(available_colors) == 0:
# no existing colors available for this feature, so add new color to pool and repeat
min_colors += 1
return ColoringAlgorithm.balanced(features, graph, feedback, balance, min_colors)
if balance == 0:
# choose least used available color
counts = [(c, v) for c, v in color_counts.items() if c in available_colors]
feature_color = sorted(counts, key=operator.itemgetter(1))[0][0]
color_counts[feature_color] += 1
elif balance == 1:
areas = [(c, v) for c, v in color_areas.items() if c in available_colors]
feature_color = sorted(areas, key=operator.itemgetter(1))[0][0]
color_areas[feature_color] += features[feature_id].geometry().area()
elif balance == 2:
min_distances = {c: sys.float_info.max for c in available_colors}
this_feature_centroid = QgsPointV2(features[feature_id].geometry().centroid().geometry())

# find features for all available colors
other_features = {f_id: c for (f_id, c) in feature_colors.items() if c in available_colors}

# loop through these, and calculate the minimum distance from this feature to the nearest
# feature with each assigned color
for other_feature_id, c in other_features.items():
other_geometry = features[other_feature_id].geometry()
other_centroid = QgsPointV2(other_geometry.centroid().geometry())

distance = this_feature_centroid.distanceSquared(other_centroid)
if distance < min_distances[c]:
min_distances[c] = distance

# choose color such that minimum distance is maximised! ie we want MAXIMAL separation between
# features with the same color
feature_color = sorted(min_distances, key=min_distances.__getitem__, reverse=True)[0]

feature_colors[feature_id] = feature_color

i += 1
feedback.setProgress(70 + int(i * total))

return feature_colors

class Graph:

def __init__(self, sort_graph=True):
self.sort_graph = sort_graph
self.node_edge = {}

def add_edge(self, i, j):
ij = [i, j]
if self.sort_graph:
(i, j) = ij
if i in self.node_edge:
self.node_edge[i] = {j}

def make_full(self):
g = Graph(sort_graph=False)
for k in self.node_edge.keys():
for v in self.node_edge[k]:
g.add_edge(v, k)
g.add_edge(k, v)
return g
41 changes: 41 additions & 0 deletions python/plugins/processing/tests/testdata/custom/adjacent_polys.gfs
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