ee.Array.exp

AI-generated Key Takeaways

• The exp() method computes Euler's number e raised to the power of each element in an input array.

• The exp() method returns an Array.

• The input to the exp() method must be an Array.

On an element-wise basis, computes the Euler's number e raised to the power of the input.

Usage	Returns
Array.exp()	Array

Argument	Type	Details
this: input	Array	The input array.

Examples

Code Editor (JavaScript)

var empty = ee.Array([], ee.PixelType.int8());
print(empty.exp());  // []

// [Math.pow(Math.E, -1), 1, Math.E, 7.389]
print(ee.Array([-1, 0, 1, 2]).exp());

var start = -5;
var end = 2;
var points = ee.Array(ee.List.sequence(start, end, null, 50));
var values = points.exp();

// Plot exp() defined above.
var chart = ui.Chart.array.values(values, 0, points)
    .setOptions({
      viewWindow: {min: start, max: end},
      hAxis: {
        title: 'x',
        viewWindowMode: 'maximized',
      },
      vAxis: {
        title: 'exp(x)',
      },
      lineWidth: 1,
      pointSize: 0,
    });
print(chart);

Python setup

See the Python Environment page for information on the Python API and using geemap for interactive development.

import ee
import geemap.core as geemap

Colab (Python)

import altair as alt
import pandas as pd

empty = ee.Array([], ee.PixelType.int8())
display(empty.exp())  # []

# [pow(math.e, -1), 1, math.e, 7.389]
display(ee.Array([-1, 0, 1, 2]).exp())

start = -5
end = 2
points = ee.Array(ee.List.sequence(start, end, None, 50))
values = points.exp()

df = pd.DataFrame({'x': points.getInfo(), 'exp(x)': values.getInfo()})

# Plot exp() defined above.
alt.Chart(df).mark_line().encode(
    x=alt.X('x'),
    y=alt.Y('exp(x)')
)