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ee.Array.erfcInv
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。
按元素计算输入的逆互补误差函数。
示例
代码编辑器 (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 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([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]))
)
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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\u003eerfcInv()\u003c/code\u003e calculates the inverse complementary error function of an input array, element-by-element.\u003c/p\u003e\n"],["\u003cp\u003eThe function accepts an array as input and returns an array of the same size with the calculated values.\u003c/p\u003e\n"],["\u003cp\u003eIt's used for statistical computations, particularly in areas like probability and signal processing where the error function is relevant.\u003c/p\u003e\n"],["\u003cp\u003eThe \u003ccode\u003eerfcInv()\u003c/code\u003e function provides the inverse mapping of the complementary error function, allowing you to find the input value corresponding to a given probability.\u003c/p\u003e\n"]]],[],null,["# ee.Array.erfcInv\n\nOn an element-wise basis, computes the inverse complementary error function of the input.\n\n\u003cbr /\u003e\n\n| Usage | Returns |\n|-------------------|---------|\n| Array.erfcInv`()` | 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([0.1]).erfcInv()); // [1.163]\nprint(ee.Array([1]).erfcInv()); // [0]\nprint(ee.Array([1.9]).erfcInv()); // [-1.163]\n\nvar start = 0.001;\nvar end = 1.999;\nvar points = ee.Array(ee.List.sequence(start, end, null, 50));\nvar values = points.erfcInv();\n\n// Plot erfcInv() 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: 0},\n {v: 1},\n {v: 2}]\n },\n vAxis: {\n title: 'erfcInv(x)',\n ticks: [\n {v: -3},\n {v: 0},\n {v: 3}]\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([0.1]).erfcInv()) # [1.163]\ndisplay(ee.Array([1]).erfcInv()) # [0]\ndisplay(ee.Array([1.9]).erfcInv()) # [-1.163]\n\nstart = 0.001\nend = 1.999\npoints = ee.Array(ee.List.sequence(start, end, None, 50))\nvalues = points.erfcInv()\n\ndf = pd.DataFrame({'x': points.getInfo(), 'erfcInv(x)': values.getInfo()})\n\n# Plot erfcInv() defined above.\nalt.Chart(df).mark_line().encode(\n x=alt.X('x', axis=alt.Axis(values=[0, 1, 2])),\n y=alt.Y('erfcInv(x)', axis=alt.Axis(values=[-3, 0, 3]))\n)\n```"]]
