向量元素两两相乘 (VectorInteractionBatchOp)

Java 类名：com.alibaba.alink.operator.batch.dataproc.vector.VectorInteractionBatchOp
Python 类名：VectorInteractionBatchOp

功能介绍

对两个vector 中的元素两两相乘，并组成一个新的向量。
输入的两个向量长度分别为m和n，生成的向量长度为m*n

参数说明

备注：选择列的数目必须为两列

代码示例

Python 代码

from pyalink.alink import *
import pandas as pd
useLocalEnv(1)
df = pd.DataFrame([
    ["$8$1:3,2:4,4:7", "$8$1:3,2:4,4:7"],
    ["$8$0:3,5:5", "$8$1:2,2:4,4:7"],
    ["$8$2:4,4:5", "$5$1:3,2:3,4:7"]
])
data = BatchOperator.fromDataframe(df, schemaStr="vec1 string, vec2 string")
vecInter = VectorInteractionBatchOp().setSelectedCols(["vec1","vec2"]).setOutputCol("vec_product")
vecInter.linkFrom(data).print()

Java 代码

import org.apache.flink.types.Row;
import com.alibaba.alink.operator.batch.BatchOperator;
import com.alibaba.alink.operator.batch.dataproc.vector.VectorInteractionBatchOp;
import com.alibaba.alink.operator.batch.source.MemSourceBatchOp;
import org.junit.Test;
import java.util.Arrays;
import java.util.List;
public class VectorInteractionBatchOpTest {
    @Test
    public void testVectorInteractionBatchOp() throws Exception {
        List <Row> df = Arrays.asList(
            Row.of("$8$1:3,2:4,4:7", "$8$1:3,2:4,4:7"),
            Row.of("$8$0:3,5:5", "$8$1:2,2:4,4:7"),
            Row.of("$8$2:4,4:5", "$5$1:3,2:3,4:7")
        );
        BatchOperator <?> data = new MemSourceBatchOp(df, "vec1 string, vec2 string");
        BatchOperator <?> vecInter = new VectorInteractionBatchOp().setSelectedCols("vec1", "vec2").setOutputCol(
            "vec_product");
        vecInter.linkFrom(data).print();
    }
}

运行结果