Regionalizing with clusterPy¶

Layer.cluster(*args, **kargs)¶

Layer.cluster contains a wide set of algorithms for clustering with spatial contiguity constraints. For literature reviews on constrained clustering, see [Murtagh1985], [Gordon1996], [Duque_Ramos_Surinach2007].

Below you will find links that take you to a detailed description of each algorithm.

The available algorithms are:

Arisel [Duque_Church2004], [Duque_Church_Middleton2011]:
- Arisel description.
- Using Arisel with clusterPy.
AZP [Openshaw_Rao1995]:
- AZP description.
- Using AZP with clusterPy.
AZP-Simulated Annealing [Openshaw_Rao1995].
- AZPSA description.
- Using AZPSA with clusterPy.
AZP-Tabu [Openshaw_Rao1995].
- AZP Tabu description.
- Using AZP Tabu with clusterPy.
AZP-R-Tabu [Openshaw_Rao1995].
- AZP Reactive Tabu description.
- Using AZP reactive Tabu with clusterPy.
Max-p-regions (Tabu) [Duque_Anselin_Rey2010].
- Max-p description.
- Using Max-p with clusterPy.
AMOEBA [Alstadt_Getis2006], [Duque_Alstadt_Velasquez_Franco_Betancourt2010].
- AMOEBA description.
- Using AMOEBA with clusterPy.
SOM [Kohonen1990].
- SOM description.
- Using SOM with clusterPy.
geoSOM [Bacao_Lobo_Painho2004].
- GeoSOM description.
- Using geoSOM with clusterPy.
Random

Parameters:	args (tuple) – Basic parameters. kargs (dictionary) – Optional parameter keywords.

The dataOperations dictionary used by ‘dissolveMap <dissolveMap>’ could be passed in order to specify which data should be calculated for the dissolved layer. The dataOperations dictionary must be:

>>> X = {}
>>> X[variableName1] = [function1, function2,....]
>>> X[variableName2] = [function1, function2,....]

Where functions are strings wich represents the name of the functions to be used on the given variableName. Functions could be,’sum’,’mean’,’min’, ‘max’,’meanDesv’,’stdDesv’,’med’, ‘mode’,’range’,’first’,’last’, ‘numberOfAreas. By deffault just ID variable is added to the dissolved map.

Examples

ARISEL

Arisel description:

Example 1

import clusterpy
instance = clusterpy.createGrid(10, 10)
instance.generateData("SAR", 'rook', 1, 0.9)
instance.exportArcData("testOutput/arisel_1_input")
instance.cluster('arisel', ['SAR1'], 15, dissolve=1)
instance.results[0].exportArcData("testOutput/arisel_1_solution")

Example 2

import clusterpy
instance = clusterpy.createGrid(10, 10)
instance.generateData("SAR", 'rook', 2, 0.9)
instance.exportArcData("testOutput/arisel_2_input")
instance.cluster('arisel', ['SAR1', 'SAR2'], 15, wType='queen', std=1, inits=3, convTabu=5, tabuLength=5, dissolve=1)
instance.results[0].exportArcData("testOutput/arisel_2_solution")

Example 3

import clusterpy
instance = clusterpy.createGrid(3, 3)
instance.generateData("SAR", 'rook', 2, 0.9)
instance.exportArcData("testOutput/arisel_3_input")
instance.cluster('arisel', ['SAR1', 'SAR2'], 3, wType='queen', std=1, inits=1, initialSolution=[0, 0, 1, 0, 1, 1, 2, 2, 2], convTabu=5, tabuLength=5, dissolve=1)
instance.results[0].exportArcData("testOutput/arisel_3_solution")

Example 4

import clusterpy
calif = clusterpy.importArcData("clusterpy/data_examples/CA_Polygons")
calif.fieldNames
dataOperations = {'POP1970':['sum', 'mean'], 'POP2001':['sum', 'mean']}
calif.exportArcData("testOutput/arisel_4_input")
calif.cluster('arisel', ['POP1970', 'POP2001'], 15, inits= 3, dissolve=1, dataOperations=dataOperations)
calif.results[0].exportArcData("testOutput/arisel_4_solution")

Example 5

import clusterpy
calif = clusterpy.importArcData("clusterpy/data_examples/CA_Polygons")
calif.fieldNames
calif.dataOperation("g70_01 = float(POP2001 - POP1970) / POP1970")
calif.exportArcData("testOutput/arisel_5_input")
calif.cluster('arisel', ['g70_01'], 15, inits= 4, dissolve=1)
calif.results[0].exportArcData("testOutput/arisel_5_solution")

AZP

AZP description

Example 1

import clusterpy
instance = clusterpy.createGrid(10, 10)
instance.generateData("SAR", 'rook', 2, 0.9)
instance.exportArcData("testOutput/azp_1_input")
instance.cluster('azp', ['SAR1'], 15, dissolve=1)
instance.results[0].exportArcData("testOutput/azp_1_solution")

Example 2

import clusterpy
instance = clusterpy.createGrid(10, 10)
instance.generateData("SAR", 'rook', 2, 0.9)
instance.exportArcData("testOutput/azp_2_input")
instance.cluster('azp', ['SAR1', 'SAR2'], 15, wType='queen', std=1, dissolve=1)
instance.results[0].exportArcData("testOutput/azp_2_solution")

Example 3

import clusterpy
instance = clusterpy.createGrid(3, 3)
instance.generateData("SAR", 'rook', 2, 0.9)
instance.exportArcData("testOutput/azp_3_input")
instance.cluster('azp', ['SAR1', 'SAR2'], 3, wType='queen', std=1, initialSolution=[0, 0, 1, 0, 1, 1, 2, 2, 2], dissolve=1)
instance.results[0].exportArcData("testOutput/azp_3_solution")

Example 4

import clusterpy
calif = clusterpy.importArcData("clusterpy/data_examples/CA_Polygons")
calif.fieldNames
dataOperations = {'POP1970':['sum', 'mean'], 'POP2001':['sum', 'mean']}
calif.exportArcData("testOutput/azp_4_input")
calif.cluster('azp', ['POP1970', 'POP2001'], 15, dissolve=1, dataOperations=dataOperations)
calif.results[0].exportArcData("testOutput/azp_4_solution")

Example 5

import clusterpy
calif = clusterpy.importArcData("clusterpy/data_examples/CA_Polygons")
calif.fieldNames
calif.dataOperation("g70_01 = float(POP2001 - POP1970) / POP1970")
calif.exportArcData("testOutput/azp_5_input")
calif.cluster('azp', ['g70_01'], 15, dissolve=1)
calif.results[0].exportArcData("testOutput/azp_5_solution")

AZP Simulated Annealing

AZP Simulated Annealing description

Example 1

import clusterpy
instance = clusterpy.createGrid(10, 10)
instance.generateData("SAR", 'rook', 2, 0.9)
instance.exportArcData("testOutput/azpSA_1_input")
instance.cluster('azpSa', ['SAR1'], 15, dissolve=1)
instance.results[0].exportArcData("testOutput/azpSA_1_solution")

Example 2

import clusterpy
instance = clusterpy.createGrid(10, 10)
instance.generateData("SAR", 'rook', 2, 0.9)
instance.exportArcData("testOutput/azpSA_2_input")
instance.cluster('azpSa', ['SAR1', 'SAR2'], 15, wType='queen', std=1, maxit=2, dissolve=1)
instance.results[0].exportArcData("testOutput/azpSA_2_solution")

Example 3

import clusterpy
instance = clusterpy.createGrid(3, 3)
instance.generateData("SAR", 'rook', 2, 0.9)
instance.exportArcData("testOutput/azpSA_3_input")
instance.cluster('azpSa', ['SAR1', 'SAR2'], 3, wType='queen', std=1, initialSolution=[0, 0, 1, 0, 1, 1, 2, 2, 2], maxit=2, dissolve=1)
instance.results[0].exportArcData("testOutput/azpSA_3_solution")

Example 4

import clusterpy
calif = clusterpy.importArcData("clusterpy/data_examples/CA_Polygons")
calif.fieldNames
dataOperations = {'POP1970':['sum', 'mean'], 'POP2001':['sum', 'mean']}
calif.exportArcData("testOutput/azpSA_4_input")
calif.cluster('azpSa', ['POP1970', 'POP2001'], 15, dissolve=1, dataOperations=dataOperations)
calif.results[0].exportArcData("testOutput/azpSA_4_solution")

Example 5

import clusterpy
calif = clusterpy.importArcData("clusterpy/data_examples/CA_Polygons")
calif.fieldNames
calif.dataOperation("g70_01 = float(POP2001 - POP1970) / POP1970")
calif.exportArcData("testOutput/azpSA_5_input")
calif.cluster('azpSa', ['g70_01'], 15, dissolve=1)
calif.results[0].exportArcData("testOutput/azpSA_5_solution")

AZP Tabu

AZP tabu description

Example 1

import clusterpy
instance = clusterpy.createGrid(10, 10)
instance.generateData("SAR", 'rook', 1, 0.9)
instance.exportArcData("testOutput/azpTabu_1_input")
instance.cluster('azpTabu', ['SAR1'], 15, dissolve=1)
instance.results[0].exportArcData("testOutput/azpTabu_1_solution")

Example 2

import clusterpy
instance = clusterpy.createGrid(10, 10)
instance.generateData("SAR", 'rook', 2, 0.9)
instance.exportArcData("testOutput/azpTabu_2_input")
instance.cluster('azpTabu', ['SAR1', 'SAR2'], 15, wType='queen', std=1, convTabu=5, tabuLength=5, dissolve=1)
instance.results[0].exportArcData("testOutput/azpTabu_2_solution")

Example 3

import clusterpy
instance = clusterpy.createGrid(3, 3)
instance.generateData("SAR", 'rook', 2, 0.9)
instance.exportArcData("testOutput/azpTabu_3_input")
instance.cluster('azpTabu', ['SAR1', 'SAR2'], 3, wType='queen', std=1, initialSolution=[0, 0, 1, 0, 1, 1, 2, 2, 2], convTabu=5, tabuLength=5, dissolve=1)
instance.results[0].exportArcData("testOutput/azpTabu_3_solution")

Example 4

import clusterpy
calif = clusterpy.importArcData("clusterpy/data_examples/CA_Polygons")
calif.fieldNames
dataOperations = {'POP1970':['sum', 'mean'], 'POP2001':['sum', 'mean']}
calif.exportArcData("testOutput/azpTabu_4_input")
calif.cluster('azpTabu', ['POP1970', 'POP2001'], 15, dissolve=1, dataOperations=dataOperations)
calif.results[0].exportArcData("testOutput/azpTabu_4_solution")

Example 5

import clusterpy
calif = clusterpy.importArcData("clusterpy/data_examples/CA_Polygons")
calif.fieldNames
calif.dataOperation("g70_01 = float(POP2001 - POP1970) / POP1970")
calif.exportArcData("testOutput/azpTabu_5_input")
calif.cluster('azpTabu', ['g70_01'], 15, dissolve=1)
calif.results[0].exportArcData("testOutput/azpTabu_5_solution")

AZP Reactive Tabu

AZP reactive tabu description

Example 1

import clusterpy
instance = clusterpy.createGrid(10, 10)
instance.generateData("SAR", 'rook', 1, 0.9)
instance.exportArcData("testOutput/azpRTabu_1_input")
instance.cluster('azpRTabu', ['SAR1'], 15, dissolve=1)
instance.results[0].exportArcData("testOutput/azpRTabu_1_solution")

Example 2

import clusterpy
instance = clusterpy.createGrid(10, 10)
instance.generateData("SAR", 'rook', 2, 0.9)
instance.exportArcData("testOutput/azpRTabu_2_input")
instance.cluster('azpRTabu', ['SAR1', 'SAR2'], 15, wType='queen', std=1, convTabu=5, dissolve=1)
instance.results[0].exportArcData("testOutput/azpRTabu_2_solution")

Example 3

import clusterpy
instance = clusterpy.createGrid(3, 3)
instance.generateData("SAR", 'rook', 2, 0.9)
instance.exportArcData("testOutput/azpRTabu_3_input")
instance.cluster('azpRTabu', ['SAR1', 'SAR2'], 3, wType='queen', std=1, initialSolution=[0, 0, 1, 0, 1, 1, 2, 2, 2], convTabu=5, dissolve=1)
instance.results[0].exportArcData("testOutput/azpRTabu_3_solution")

Example 4

import clusterpy
calif = clusterpy.importArcData("clusterpy/data_examples/CA_Polygons")
calif.fieldNames
dataOperations = {'POP1970':['sum', 'mean'], 'POP2001':['sum', 'mean']}
calif.exportArcData("testOutput/azpRTabu_4_input")
calif.cluster('azpRTabu', ['POP1970', 'POP2001'], 15, dissolve=1, dataOperations=dataOperations)
calif.results[0].exportArcData("testOutput/azpRTabu_4_solution")

Example 5

import clusterpy
calif = clusterpy.importArcData("clusterpy/data_examples/CA_Polygons")
calif.fieldNames
calif.dataOperation("g70_01 = float(POP2001 - POP1970) / POP1970")
calif.exportArcData("testOutput/azpRTabu_5_input")
calif.cluster('azpRTabu', ['g70_01'], 15, dissolve=1)
calif.results[0].exportArcData("testOutput/azpRTabu_5_solution")

MAX-P

Max-p region description

Example 1

import clusterpy
instance = clusterpy.createGrid(10, 10)
instance.generateData("SAR", 'rook', 1, 0.9)
instance.generateData('Uniform', 'rook', 1, 10, 15)
instance.exportArcData("testOutput/maxpTabu_1_input")
instance.cluster('maxpTabu', ['SAR1', 'Uniform2'], threshold=130, dissolve=1)
instance.results[0].exportArcData("testOutput/maxpTabu_1_solution")

Example 2

import clusterpy
instance = clusterpy.createGrid(10, 10)
instance.generateData("SAR", 'rook', 1, 0.9)
instance.generateData('Uniform', 'rook', 1, 10, 15)
instance.exportArcData("testOutput/maxpTabu_2_input")
instance.cluster('maxpTabu', ['SAR1', 'Uniform2'], threshold=130, wType='queen', maxit=3, tabuLength=5, dissolve=1)
instance.results[0].exportArcData("testOutput/maxpTabu_2_solution")

Example 3

import clusterpy
calif = clusterpy.importArcData("clusterpy/data_examples/CA_Polygons")
calif.fieldNames
dataOperations = {'POP1970':['sum', 'mean'], 'POP2001':['sum', 'mean']}
calif.exportArcData("testOutput/maxpTabu_3_input")
calif.cluster('maxpTabu', ['POP1970', 'POP2001'], threshold=100000, dissolve=1, dataOperations=dataOperations)
calif.results[0].exportArcData("testOutput/maxpTabu_3_solution")

Example 4

import clusterpy
calif = clusterpy.importArcData("clusterpy/data_examples/CA_Polygons")
calif.fieldNames
calif.dataOperation("g70_01 = float(POP2001 - POP1970) / POP1970")
calif.exportArcData("testOutput/maxpTabu_4_input")
calif.cluster('maxpTabu', ['g70_01', 'POP2001'], threshold=100000, dissolve=1,std=1)
calif.results[0].exportArcData("testOutput/maxpTabu_4_solution")

AMOEBA

AMOEBA description

Example 1

import clusterpy
instance = clusterpy.createGrid(33, 33)
instance.generateData("Spots", 'rook', 1, 2, 0.7, 0.99)
instance.cluster('amoeba', ['Spots1'],significance=0.01)
instance.exportArcData("testOutput/amoeba_1_solution")

Example 2:

import clusterpy
instance = clusterpy.createGrid(25, 25)
instance.generateData("Spots", 'rook', 1, 2, 0.7, 0.99)
instance.cluster('amoeba', ['Spots1'],wType="queen",significance=0.01)
instance.exportArcData("testOutput/amoeba_2_solution")

Example 3

import clusterpy
calif = clusterpy.importArcData("clusterpy/data_examples/CA_Polygons")
calif.dataOperation("g70_01 = float(POP2001 - POP1970) / POP1970")
calif.cluster('amoeba', ['g70_01'],significance=0.01)
calif.exportArcData("testOutput/amoeba_3_solution")

Self Organizing Maps (SOM)

SOM description

Example 1

import clusterpy
instance = clusterpy.createGrid(33, 33)
instance.generateData("SAR", "rook", 1, 0.9)
instance.cluster("som", ["SAR1"], nRows=2,nCols=2)
instance.exportArcData("testOutput/som_1_dataLayer")

Example 2

import clusterpy
instance = clusterpy.createGrid(33,33)
instance.generateData("SAR",'rook',1,0.9)
instance.generateData("SAR",'rook',1,0.9)
instance.cluster('som',['SAR1','SAR2'],nRows=2,nCols=2,alphaType='quadratic', fileName="testOutput/NeuronsLayer")
instance.exportArcData("testOutput/som_2_dataLayer")

Example 3

import clusterpy
calif = clusterpy.importArcData("clusterpy/data_examples/CA_Polygons")
calif.dataOperation("g70_01 = float(POP2001 - POP1970) / POP1970")
calif.cluster('som',['g70_01'],nRows=2,nCols=2,alphaType='linear')
calif.exportArcData("testOutput/som_3_solution")

Geo Self Organizing Maps (geoSOM)

GeoSOM description

Example 1

import clusterpy
instance = clusterpy.createGrid(33, 33)
instance.generateData("SAR", "rook", 1, 0.9)
instance.cluster("geoSom", ["SAR1"], nRows=3,nCols=3)
instance.exportArcData("testOutput/geoSom_1_dataLayer")

Example 2

import clusterpy
instance = clusterpy.createGrid(33,33)
instance.generateData("SAR",'rook',1,0.9)
instance.generateData("SAR",'rook',1,0.9)
instance.cluster('geoSom',['SAR1','SAR2'],nRows=3,nCols=3,alphaType='quadratic', fileName="testOutput/NeuronsLayer")
instance.exportArcData("testOutput/geoSom_2_dataLayer")

Example 3

import clusterpy
calif = clusterpy.importArcData("clusterpy/data_examples/CA_Polygons")
calif.dataOperation("g70_01 = float(POP2001 - POP1970) / POP1970")
calif.cluster('geoSom',['g70_01'],nRows=3,nCols=3,alphaType='linear')
calif.exportArcData("testOutput/geoSom_3_solution")

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