1 performance r distance matrix euclidean-distance
下面的循环时间过lonng运行(2分钟/迭代)的tumor_signals是大小950000x422的normal_signals是大小950000x772如何加快它的任何想法?
for(i in 1:ncol(tumor_signals)){
x <- as.vector(tumor_signals[,i])
print("Assigned x")
y <- t((t(normal_signals) - x)^2)
print("assigned y")
y <- t(sqrt(colSums(y)))
print("done")
#all_distance <- cbind(all_distance,matrix(distance))
print(i)
}
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您的代码中存在错误 - 您无需进行转置normal_signals.据我所知,您要计算,对于所有i = 1,2,...422,和j=1,2,...,772之间的欧氏距离tumor_signals[,i]和normal_signals[,j].您可能希望将结果放在422 x 772矩阵中.rdist()包fields中有一个功能可以为您完成此操作:
require(fields)
result <- rdist(t(tumor_signals), t(normal_signals))
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顺便提一下,谷歌搜索[R Euclidean distance]会很容易找到这个包.