FuzzyMSLarge

Récapitulatif

Defines a fuzzy membership through a function based on the mean and standard deviation, with the larger values having a membership closer to 1.

Discussion

The tool that uses the FuzzyMSLarge object: Fuzzy Membership.

There are two equations for the MS Large function, depending on the product of a * m.

• If x > a * m:

  u(x) = 1 - (b * s) / (x - (a * m) + (b * s))

  • where:

    m = the mean

    s = the standard deviation

    a = a multiplier of the mean

    b = a multiplier of the standard deviation

    The a and b multipliers are input parameters.

• If x <= a * m:

  u(x) = 0

The MSLarge function is useful when the large input values have a higher membership.

The input values can be either integer or floating point positive values.

The result can be similar to the Large fuzzy membership function, depending on how the multipliers of the mean and standard deviation are defined.

Syntaxe

FuzzyMSLarge (meanMultiplier, STDMultiplier)

Paramètre	Explication	Type de données
meanMultiplier	The multiplier for the mean of the input values in the MSLarge function equation. (La valeur par défaut est 1)	Double
STDMultiplier	The multiplier for the standard deviation of the input values in the MSLarge function equation. (La valeur par défaut est 1)	Double

Propriétés

Propriété	Explication	Type de données
meanMultiplier (Lecture et écriture)	The multiplier for the mean of the input values in the membership function equation.	Double
STDMultiplier (Lecture et écriture)	The multiplier for the standard deviation of the input values in the membership function equation.	Double

Exemple de code

FuzzyMSLarge example 1 (Python window)

Demonstrates how to create a FuzzyMSLarge class and use it in the FuzzyMembership tool within the Python window.

import arcpy
from arcpy.sa import *
from arcpy import env
env.workspace = "c:/sapyexamples/data"
outFzyMember = FuzzyMembership("as_std", FuzzyMSLarge(1, 1.8))
outFzyMember.save("c:/sapyexamples/fzymslrg")

FuzzyMSLarge example 2 (stand-alone script)

Performs a FuzzyMembership using the FuzzyMSLarge class.

# Name: FuzzyMSLarge_Ex_02.py
# Description: Scales input raster data into values ranging from zero to one
#     indicating the strength of a membership in a set. 
# Requirements: Spatial Analyst Extension

# Import system modules
import arcpy
from arcpy import env
from arcpy.sa import *

# Set environment settings
env.workspace = "C:/sapyexamples/data"

# Set local variables
inRaster = "as_std"

# Create the FuzzyMSLarge algorithm object
meanMultiply = 1.5
stdMultiply = 2.2
myFuzzyAlgorithm = FuzzyMSLarge(meanMultiply, stdMultiply)

# Check out the ArcGIS Spatial Analyst extension license
arcpy.CheckOutExtension("Spatial")

# Execute FuzzyMembership
outFuzzyMember = FuzzyMembership(inRaster, myFuzzyAlgorithm)

# Save the output
outFuzzyMember.save("c:/sapyexamples/fzymslrg2")