Overloaded Operators

Let’s see how to use overloaded operators in eemont!

Before anything, let’s import our modules and authenticate in Google Earth Engine:

import ee, eemont

ee.Authenticate()
ee.Initialize()

Now, we are ready to go!

Overview

The eemont package extends the ee.Image and ee.Number classes with the binary and unary operators (including rich comparisons).

ee.Image

Binary Operators

The following table shows the list of binary operators that are overloaded:

Binary operators.

Operation	GEE Python method	Overloaded Operator
Addition	Image1.add(Image2)	Image1 + Image2
Subtraction	Image1.subtract(Image2)	Image1 - Image2
Multiplication	Image1.multiply(Image2)	Image1 * Image2
Division	Image1.divide(Image2)	Image1 / Image2
Floor Division	Image1.divide(Image2).floor()	Image1 // Image2
Modulo	Image1.mod(Image2)	Image1 % Image2
Power	Image1.pow(Image2)	Image1 ** Image2
Left Shift	Image1.leftShift(Image2)	Image1 << Image2
Right Shift	Image1.rightShift(Image2)	Image1 >> Image2
And	Image1.And(Image2)	Image1 & Image2
Or	Image1.Or(Image2)	Image1 | Image2

Rich Comparisons

The following table shows the list of rich comparisons that are overloaded:

Rich comparisons.

Operation	GEE Python method	Overloaded Operator
Lower Than	Image1.lt(Image2)	Image1 < Image2
Lower Than or Equal	Image1.lte(Image2)	Image1 <= Image2
Equal	Image1.eq(Image2)	Image1 == Image2
Not Equal	Image1.neq(Image2)	Image1 != Image2
Greater Than	Image1.gt(Image2)	Image1 > Image2
Greater Than or Equal	Image1.gte(Image2)	Image1 >= Image2
Equal	Image1.eq(Image2)	Image1 == Image2

Unary Operators

The following table shows the list of unary operators that are overloaded:

Unary operators.

Operation	GEE Python method	Overloaded Operator
Negation	Image.multiply(-1)	-Image
Invert	Image.Not()	~ Image

ee.Number

Binary Operators

The following table shows the list of binary operators that are overloaded:

Binary operators.

Operation	GEE Python method	Overloaded Operator
Addition	Number1.add(Number2)	Number1 + Number2
Subtraction	Number1.subtract(Number2)	Number1 - Number2
Multiplication	Number1.multiply(Number2)	Number1 * Number2
Division	Number1.divide(Number2)	Image1 / Image2
Floor Division	Number1.divide(Number2).floor()	Number1 // Number2
Modulo	Number1.mod(Number2)	Number1 % Number2
Power	Number1.pow(Number2)	Number1 ** Number2
Left Shift	Number1.leftShift(Number2)	Number1 << Number2
Right Shift	Number1.rightShift(Number2)	Number1 >> Number2
And	Number1.And(Number2)	Number1 & Number2
Or	Number1.Or(Number2)	Number1 | Number2

Rich Comparisons

The following table shows the list of rich comparisons that are overloaded:

Rich comparisons.

Operation	GEE Python method	Overloaded Operator
Lower Than	Number1.lt(Number2)	Number1 < Number2
Lower Than or Equal	Number1.lte(Number2)	Number1 <= Number2
Equal	Number1.eq(Number2)	Number1 == Number2
Not Equal	Number1.neq(Number2)	Number1 != Number2
Greater Than	Number1.gt(Number2)	Number1 > Number2
Greater Than or Equal	Number1.gte(Number2)	Number1 >= Number2
Equal	Number1.eq(Number2)	Number1 == Number2

Unary Operators

The following table shows the list of unary operators that are overloaded:

Unary operators.

Operation	GEE Python method	Overloaded Operator
Negation	Number.multiply(-1)	-Number
Invert	Number.Not()	~ Number

ee.List

Binary Operators

The following table shows the list of binary operators that are overloaded:

Binary operators.

Operation	GEE Python method	Overloaded Operator
Concatenation	List1.cat(List2)	List1 + List2
Repeat	ee.List.repeat(List,Value)	List * Value

Usage

Overloaded operators can be used on any ee.Image or ee.Number object. Let’s see how to compute the EVI using overloaded operators!

Let’s take the Sentinel-2 SR image collection as example (remember to scale your image or image collection!):

point = ee.Geometry.Point([-76.0269,2.92846])
S2 = (ee.ImageCollection('COPERNICUS/S2_SR')
   .filterBounds(point)
   .sort('CLOUDY_PIXEL_PERCENTAGE')
   .first()
   .maskClouds()
   .scale())

Now, let’s take apart the bands that we need (it is not necessary, but it’s easier to use N instead of S2.select('B8')):

N = S2.select('B8')
R = S2.select('B4')
B = S2.select('B2')

And finally, let’s compute the EVI using overloaded operators:

EVI = 2.5 * (N - R) / (N + 6.0 * R - 7.5 * B + 1.0)

Let’s see another example, but using rich comparisons. We are going to compute a snow cover mask!

First, compute the NDSI:

S2 = S2.index('NDSI')

And now, let’s take apart the bands that we need:

NDSI = S2.select('NDSI')
N = S2.select('B8')
G = S2.select('B3')

Finally, compute the snow cover mask (Hall et al., 2001):

snowPixels = (NDSI > 0.4) & (N >= 0.1) & (G > 0.11)

And update the mask (if required):

S2 = S2.updateMask(snowPixels)

Masking Clouds and Shadows Spectral Indices Computation