ee.Array.erfInv

On an element-wise basis, computes the inverse error function of the input.

UsageReturns
Array.erfInv()Array
ArgumentTypeDetails
this: inputArrayThe input array.

Examples

Code Editor (JavaScript)

print(ee.Array([-0.99]).erfInv());  // [-1.82]
print(ee.Array([0]).erfInv());  // [0]
print(ee.Array([0.99]).erfInv());  // [1.82]

var start = -0.99;
var end = 0.99;
var points = ee.Array(ee.List.sequence(start, end, null, 50));
var values = points.erfInv();

// Plot erfInv() defined above.
var chart = ui.Chart.array.values(values, 0, points)
    .setOptions({
      viewWindow: {min: start, max: end},
      hAxis: {
        title: 'x',
        viewWindowMode: 'maximized',
        ticks: [
          {v: -1},
          {v: 0},
          {v: 1}]
      },
      vAxis: {
        title: 'erfInv(x)',
        ticks: [
          {v: -2},
          {v: 0},
          {v: 2}]
      },
      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

display(ee.Array([-0.99]).erfInv())  # [-1.82]
display(ee.Array([0]).erfInv())  # [0]
display(ee.Array([0.99]).erfInv())  # [1.82]

start = -0.99
end = 0.99
points = ee.Array(ee.List.sequence(start, end, None, 50))
values = points.erfInv()

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

# Plot erfInv() defined above.
alt.Chart(df).mark_line().encode(
    x=alt.X('x', axis=alt.Axis(values=[-1, 0, 1])),
    y=alt.Y('erfInv(x)', axis=alt.Axis(values=[-2, 0, 2]))
)