ee.Array.erfcInv

  • erfcInv() calculates the inverse complementary error function of an input array, element-by-element.

  • The function accepts an array as input and returns an array of the same size with the calculated values.

  • It's used for statistical computations, particularly in areas like probability and signal processing where the error function is relevant.

  • The erfcInv() function provides the inverse mapping of the complementary error function, allowing you to find the input value corresponding to a given probability.

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

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

Examples

Code Editor (JavaScript)

print(ee.Array([0.1]).erfcInv());  // [1.163]
print(ee.Array([1]).erfcInv());  // [0]
print(ee.Array([1.9]).erfcInv());  // [-1.163]

var start = 0.001;
var end = 1.999;
var points = ee.Array(ee.List.sequence(start, end, null, 50));
var values = points.erfcInv();

// Plot erfcInv() defined above.
var chart = ui.Chart.array.values(values, 0, points)
    .setOptions({
      viewWindow: {min: start, max: end},
      hAxis: {
        title: 'x',
        viewWindowMode: 'maximized',
        ticks: [
          {v: 0},
          {v: 1},
          {v: 2}]
      },
      vAxis: {
        title: 'erfcInv(x)',
        ticks: [
          {v: -3},
          {v: 0},
          {v: 3}]
      },
      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([0.1]).erfcInv())  # [1.163]
display(ee.Array([1]).erfcInv())  # [0]
display(ee.Array([1.9]).erfcInv())  # [-1.163]

start = 0.001
end = 1.999
points = ee.Array(ee.List.sequence(start, end, None, 50))
values = points.erfcInv()

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

# Plot erfcInv() defined above.
alt.Chart(df).mark_line().encode(
    x=alt.X('x', axis=alt.Axis(values=[0, 1, 2])),
    y=alt.Y('erfcInv(x)', axis=alt.Axis(values=[-3, 0, 3]))
)