On an element-wise basis, computes the inverse complementary error function of the input.
Usage | Returns | Array.erfcInv() | Array |
Argument | Type | Details | this: input | Array | The 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]))
)