ee.Array.erfInv
On an element-wise basis, computes the inverse error function of the input.
Usage | Returns |
---|
Array.erfInv() | Array |
Argument | Type | Details |
---|
this: input | Array | The input array. |
Examples
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
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]))
)
Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License, and code samples are licensed under the Apache 2.0 License. For details, see the Google Developers Site Policies. Java is a registered trademark of Oracle and/or its affiliates.
Last updated 2023-10-06 UTC.
[null,null,["Last updated 2023-10-06 UTC."],[[["`erfInv()` calculates the inverse error function of an input array element-by-element."],["It accepts an `ee.Array` as input and returns a new `ee.Array` with the calculated values."],["The function is useful for statistical analysis and probability calculations involving the normal distribution."],["Examples demonstrate usage and visualization of the function in both JavaScript and Python environments within Google Earth Engine."]]],[]]