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Feat/sequence scatter #3785
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Feat/sequence scatter #3785
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- classification background for training process 1 - neighborhood relationship for training process 2
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let TRAINING_PROCESS_ID = 1; // 1 for code search process, 2 for image classification process | ||
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let original_data, training_info, task_type, scope; |
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2种任务的效果都蛮好的,建议拆分成2个demo。
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/* | ||
create data for sequence-scatter | ||
*/ |
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数据处理的逻辑可以内置在packages/vchart-extension/src/charts/sequence-scatter/utils中,导出使用即可。
input:task_type -> output: chartData
y0: pos[1], | ||
x1: original_data[epoch].projection[neighbor][0], | ||
y1: original_data[epoch].projection[neighbor][1], | ||
type:0, |
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type如果没有特殊意义,建议配置成字符串,'intra_similarity' / 'inter_similarity'之类的,语义化,比较好理解
type:0, | ||
color: label_color_dict[label_text[label_index[id]]] | ||
}); | ||
edgeId++; |
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edgeId同上
Helper functions for preprocessing original data | ||
*/ | ||
function transformEdges(specData, pointX, pointY) { | ||
const endpoints: any[] = []; |
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这个类型也是,有对应的定义IterationEdgesData[],尽量避免用any
/* | ||
Helper functions for preprocessing original data | ||
*/ | ||
function transformEdges(specData, pointX, pointY) { |
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类型定义可以补充下
🤔 This is a ...
🔗 Related issue link
close #3574
🔗 Related PR link
🐞 Bugserver case id
💡 Background and solution
Plot the data under different numbers of iterations.
Plot the relationships between samples.
Plot the clustering boundaries of different categories.
📝 Changelog
☑️ Self-Check before Merge
🚀 Summary
copilot:summary
🔍 Walkthrough
copilot:walkthrough