我正在使用功能组图——散点图。图表上显示的图例（系列）会自动按照首次出现的值排序，因此它看起来像一个随机数（附图）。我想通过从小到大对值进行排序来自定义图例，但一无所获（案例：1 – 11）。有没有人有办法解决吗？
原始代码：
var target_image = ee.Image("users/noahdornier/clustering_indo_1000"),
world = ee.Image("users/noahdornier/WORLD_1000M"),
aoi =
/* color: #d63000 */
/* shown: false */
ee.Geometry.MultiPolygon(
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image = ee.Image("users/insgis/noah/moef_image_v1");
Map.addLayer(target_image);
Map.addLayer(world);
function generatesScatter(feature, xProperty, yProperty, series, title, hAxis_title, xAxis_title, hMinMax, vMinMax) {
var scatter_chart = ui.Chart.feature.groups(feature, xProperty, yProperty, series)
.setChartType('ScatterChart')
.setOptions({
title: title,
pointSize: 2,
dataOpacity: 0.4,
hAxis: {
viewWindow: {
min: hMinMax[0],
max: hMinMax[1],
},
'title': hAxis_title,
titleTextStyle: { italic: false, bold: true },
},
vAxis: {
viewWindow: {
min: vMinMax[0],
max: vMinMax[1],
},
'title': xAxis_title,
titleTextStyle: { italic: false, bold: true }
},
});
return scatter_chart
}
function stratifiedSampling(img_input, numPoints, classBand, classVal, pts, scale, region) {
// Sampling
var str_point = img_input.stratifiedSample({
numPoints: numPoints,
classBand: classBand,
// Class to be sampled
classValues: classVal,
// Points each class
classPoints: [pts, pts, pts, pts, pts, pts, pts, pts, pts, pts, pts],
scale: scale,
// region: region,
geometries: false
})
return str_point
}
// Class references
// Define a dictionary that maps the original values to new numeric values
var classDict = ee.Dictionary({
"Bush / Shrub": 1,
"Swamp Shrub": 2,
"Plantation Forest": 3,
"Primary Swamp Forest": 4,
"Secondary Swamp Forest": 5,
"Primary Mangrove Forest": 6,
"Dryland Agriculture": 7,
"Secondary Mangrove Forest": 8,
"Primary Dry Land Forest": 9,
"Secondary Dry Land Forest": 10,
"Shrub-Mixed Dryland Farm": 11
});
// List of class
var classList = classDict.keys()
// List of class values
// Using for remapping raster value from 0 to 10 --> 1 to 11
var valueList = classDict.values().sort()
// SEA
var SEA_select = world.select('VV_mean', 'VV_stdDev', 'VH_mean', 'VH_stdDev');
// K-Means Clustering
// Create training dataset.
var training = SEA_select.sample({
region: aoi,
scale: 1000,
numPixels: 10000
});
// Start unsupervised clusterering algorithm and train it.
var kmeans = ee.Clusterer.wekaKMeans(11).train(training);
// Cluster the input using the trained clusterer.
var result = SEA_select.cluster(kmeans);
// Remapping class raster
var cluster_image = result.select("cluster")
.remap([0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10], valueList)
.rename("cluster")
// Add SEA Band to image input
var cluster_concat = cluster_image.addBands(world)
// Cluster - Str sampling
var cluster_sample = stratifiedSampling(
cluster_concat, 1100, "cluster", valueList, 100, 1000, aoi
)
// Cluster - mean chart
var cluster_mean_chart = generatesScatter(
cluster_sample,
"VV_mean",
"VH_mean",
"cluster",
"VV Mean .vs VH Mean - Cluster Results",
"VV Mean",
"VH Mean",
[-22, -1.5],
[-30, -5]
)
print("Cluster Mean:",cluster_mean_chart)
解决方案：
很多时候我们会出现上面的问题，如果我们时需要按照图例的大小进行排序的话，我们就会遇到上面的问题，要更改默认行为，您必须跳过一些步骤才能以正确的排序顺序创建 Google Charts API 数据表。
修改后的代码：
// We create a list of rows for the data table
// Each row would contain 12 values, 1 X-axis valuie and 11 Y-axis series values
// Only 1 of the Y-axis series will be populated
var rows = valueList.map(function(cluster) {
var features = cluster_sample.filter(ee.Filter.eq('cluster', cluster))
return features.toList(100).map(function(f) {
var f = ee.Feature(f);
var cluster = f.get('cluster');
var vv = f.get('VV_mean');
var vh = f.get('VH_mean');
var empty = ee.List([{}, {}, {}, {}, {}, {}, {}, {}, {}, {}, {}])
var row = empty.set(ee.Number(cluster).subtract(1), {v: vh});
var fullrow = ee.List([{v: vv}]).cat(row)
return {c: fullrow}
})
}).flatten()
// Rows is server-side object created using EE API
// Convert it to cliend-side javascript object
rows.evaluate(function(rowsResult) {
print(rowsResult)
var dataTable = {
cols: [
{id: 'vv', label: 'vv', type: 'number'},
{id: 'vh1', label: '1', type: 'number'},
{id: 'vh2', label: '2', type: 'number'},
{id: 'vh3', label: '3', type: 'number'},
{id: 'vh4', label: '4', type: 'number'},
{id: 'vh5', label: '5', type: 'number'},
{id: 'vh6', label: '6', type: 'number'},
{id: 'vh7', label: '7', type: 'number'},
{id: 'vh8', label: '8', type: 'number'},
{id: 'vh9', label: '9', type: 'number'},
{id: 'vh10', label: '10', type: 'number'},
{id: 'vh11', label: '11', type: 'number'},
],
rows: rowsResult
};
var chart = ui.Chart(dataTable, 'ScatterChart')
.setOptions({
title: 'VV Mean .vs VH Mean - Cluster Results',
pointSize: 2,
dataOpacity: 0.4,
hAxis: {
viewWindow: {
min: -22,
max: -1.5,
},
'title': 'VV Mean',
titleTextStyle: { italic: false, bold: true },
},
vAxis: {
viewWindow: {
min: -30,
max: -5,
},
'title': 'VH Mean',
titleTextStyle: { italic: false, bold: true }
},
});
;
print(chart)
})修改后的图里结果：
这里面用到的函数：
ui.Chart(dataTable, chartType, options, view, downloadable)
A chart widget.
Arguments:
dataTable (List>|Object|String, optional):
A 2-D array of data or a Google Visualization DataTable literal. See: http://developers.google.com/chart/interactive/docs/reference#DataTable
chartType (String, optional):
The chart type; e.g ‘ScatterChart’,
‘LineChart’, and ‘ColumnChart’. For the complete list of charts, see: https://developers.google.com/chart/interactive/docs/gallery
options (Object, optional):
An object defining chart style options such as:
- title (string) The title of the chart.
- colors (Array) An array of colors used to draw the chart. Its format should follow the Google Visualization API’s options: https://developers.google.com/chart/interactive/docs/customizing_charts
view (Object, optional):
Sets a DataView initializer object, which acts as a filter over the underlying data. See: https://developers.google.com/chart/interactive/docs/reference#DataView
downloadable (Boolean, optional):
Whether the chart can be downloaded as CSV, SVG, and PNG. Defaults to true.
Returns: ui.Chart
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