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ee.Array.erfc
使用集合让一切井井有条
根据您的偏好保存内容并对其进行分类。
按元素计算输入的互补误差函数。
示例
代码编辑器 (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 设置
如需了解 Python API 和如何使用 geemap 进行交互式开发，请参阅
Python 环境页面。
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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最后更新时间 (UTC)：2025-07-26。
[null,null,["最后更新时间 (UTC)：2025-07-26。"],[[["\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```"]]
