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ee.Array.erfc
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On an element-wise basis, computes the complementary error function of the input.
Usage | Returns | Array.erfc() | Array |
Argument | Type | Details | this: input | Array | The input array. |
Examples
Code Editor (JavaScript)
print(ee.Array([-6]).erfc()); // [2]
print(ee.Array([0]).erfc()); // [1]
print(ee.Array([28]).erfc()); // [0]
var start = -3;
var end = 3;
var points = ee.Array(ee.List.sequence(start, end, null, 50));
var values = points.erfc();
// Plot erfc() defined above.
var chart = ui.Chart.array.values(values, 0, points)
.setOptions({
viewWindow: {min: start, max: end},
hAxis: {
title: 'x',
viewWindowMode: 'maximized',
ticks: [
{v: start},
{v: 0},
{v: end}]
},
vAxis: {
title: 'erfc(x)',
ticks: [
{v: 0},
{v: 1},
{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([-6]).erfc()) # [2]
display(ee.Array([0]).erfc()) # [1]
display(ee.Array([28]).erfc()) # [0]
start = -3
end = 3
points = ee.Array(ee.List.sequence(start, end, None, 50))
values = points.erfc()
df = pd.DataFrame({'x': points.getInfo(), 'erfc(x)': values.getInfo()})
# Plot erfc() defined above.
alt.Chart(df).mark_line().encode(
x=alt.X('x', axis=alt.Axis(values=[start, 0, end])),
y=alt.Y('erfc(x)', axis=alt.Axis(values=[0, 1, 2]))
)
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Last updated 2023-10-06 UTC.
[null,null,["Last updated 2023-10-06 UTC."],[[["\u003cp\u003e\u003ccode\u003eArray.erfc()\u003c/code\u003e calculates the complementary error function for each element in an input array.\u003c/p\u003e\n"],["\u003cp\u003eThe function returns a new array with the calculated complementary error function values.\u003c/p\u003e\n"],["\u003cp\u003eIt operates on an element-by-element basis, applying the erfc function to each value in the input array.\u003c/p\u003e\n"],["\u003cp\u003eUsage examples are provided in both JavaScript and Python to demonstrate the function's application.\u003c/p\u003e\n"]]],["The `erfc()` method computes the complementary error function for each element in an input array. It's applied using `Array.erfc()` and returns a new array. Input values of -6, 0, and 28 yield results of 2, 1, and 0 respectively. The examples demonstrate creating a sequence of values, applying `erfc()`, and then plotting the resulting function graphically in both JavaScript and Python.\n"],null,["# ee.Array.erfc\n\nOn an element-wise basis, computes the complementary error function of the input.\n\n\u003cbr /\u003e\n\n| Usage | Returns |\n|----------------|---------|\n| Array.erfc`()` | Array |\n\n| Argument | Type | Details |\n|---------------|-------|------------------|\n| this: `input` | Array | The input array. |\n\nExamples\n--------\n\n### Code Editor (JavaScript)\n\n```javascript\nprint(ee.Array([-6]).erfc()); // [2]\nprint(ee.Array([0]).erfc()); // [1]\nprint(ee.Array([28]).erfc()); // [0]\n\nvar start = -3;\nvar end = 3;\nvar points = ee.Array(ee.List.sequence(start, end, null, 50));\nvar values = points.erfc();\n\n// Plot erfc() defined above.\nvar chart = ui.Chart.array.values(values, 0, points)\n .setOptions({\n viewWindow: {min: start, max: end},\n hAxis: {\n title: 'x',\n viewWindowMode: 'maximized',\n ticks: [\n {v: start},\n {v: 0},\n {v: end}]\n },\n vAxis: {\n title: 'erfc(x)',\n ticks: [\n {v: 0},\n {v: 1},\n {v: 2}]\n },\n lineWidth: 1,\n pointSize: 0,\n });\nprint(chart);\n```\nPython setup\n\nSee the [Python Environment](/earth-engine/guides/python_install) page for information on the Python API and using\n`geemap` for interactive development. \n\n```python\nimport ee\nimport geemap.core as geemap\n```\n\n### Colab (Python)\n\n```python\nimport altair as alt\nimport pandas as pd\n\ndisplay(ee.Array([-6]).erfc()) # [2]\ndisplay(ee.Array([0]).erfc()) # [1]\ndisplay(ee.Array([28]).erfc()) # [0]\n\nstart = -3\nend = 3\npoints = ee.Array(ee.List.sequence(start, end, None, 50))\nvalues = points.erfc()\n\ndf = pd.DataFrame({'x': points.getInfo(), 'erfc(x)': values.getInfo()})\n\n# Plot erfc() defined above.\nalt.Chart(df).mark_line().encode(\n x=alt.X('x', axis=alt.Axis(values=[start, 0, end])),\n y=alt.Y('erfc(x)', axis=alt.Axis(values=[0, 1, 2]))\n)\n```"]]