apply | 易学教程

Javascript .apply() method equivalent in Java?

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问题 I want to create a class in Java from a classname and an variable number of arguments (i.e. an Object[] args with variable length). Is there any way to achieve that? Basically, the method would look like this in Javascript function createClass(classname, args) { protoObject = Object.create(window[classname].prototype); return window[classname].apply(protoObject,args) || protoObject; } // I want to be able to do this: var resultClass = createClass("someClass", someArrayOfArgs); A simpler

How to apply a function to each element of a vector in R

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问题 Let's say I want to multiply each even element of a vector by 2 and each odd element of a vector by 3. Here is some code that can do this: v <- 0:10 idx <- v %% 2 == 0 v[idx] <- v[idx] * 2 v[!idx] <- v[!idx] * 3 This would get difficult if I had more than two cases. It seems like the apply family of functions never deals with vectors so I don't know a better way to do this problem. Maybe using an apply function would work if I made transformations on the data, but it seems like that shouldn't

ES5-call,apply,bind的用法

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区别bind()与call()和apply()? 1. Function.prototype.bind(obj) : * 作用: 将函数内的this绑定为obj, 并将函数返回 2. 面试题: 区别bind()与call()和apply()? * 都能指定函数中的this * call()/apply()是立即调用函数 *bind()是将函数返回 <script type="text/javascript"> function fun(age) { this.name = 'kobe'; this.age = age; console.log('dddddddddddddd'); } var obj = {}; fun.bind(obj, 12)(); console.log(obj.name, obj.age); 来源： https://www.cnblogs.com/hack-ing/p/12005479.html

Is there a way to loop through a matrix/df in R to create an adjacency matrix?

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问题 I am trying to loop through 53 rows in a data.frame and create an adjacency matrix with the results. However, my efforts continue to be stalled by the fact that the loop will not run correctly. I have tried to create matches as well as applying numerous count() functions, without success. MRE: (In truth, the data is a lot larger so my unique search is actually 217k elements) df1<-data.frame(col1=c(12345,123456,1234567,12345678), col2=c(54321,54432,12345,76543), col3=c(11234,12234,1234567

Apply to list of vectors

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I have list of numerical vectors (with different sizes each) in R. Let's say the list has 10 elements. I would like to apply a function (something like max(x - K, 0) where K is a fixed constant) to each elements of each vector of the list, and get an output with exactly the same structure (thus a list of vectors). I tried sapply(data, function(x) max(x-K, 0)) but I get a vector of size 10. I don't know exactly what are its components by the way. I also tried max(data-K,0) directly, but I get an error message. Can anyone help me ? ## dummy data set.seed(1) ll <- as.list(data.frame(matrix(rnorm

Apply List of functions on List of columns based on different combinations

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问题 I have a dataframe df with three categorical variables cat1 , cat2 , cat3 and two continuous variables con1 , con2 . I would like to compute list of functions sd , mean on list of columns con1 , con2 based on different combinations of list of columns cat1 , cat2 , cat3 . I have done them explicitly subsetting all different combinations. # Random generation of values for categorical data set.seed(33) df <- data.frame(cat1 = sample( LETTERS[1:2], 100, replace=TRUE ), cat2 = sample( LETTERS[3:5]

Apply to list of vectors

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问题 I have list of numerical vectors (with different sizes each) in R. Let's say the list has 10 elements. I would like to apply a function (something like max(x - K, 0) where K is a fixed constant) to each elements of each vector of the list, and get an output with exactly the same structure (thus a list of vectors). I tried sapply(data, function(x) max(x-K, 0)) but I get a vector of size 10. I don't know exactly what are its components by the way. I also tried max(data-K,0) directly, but I get

How can I use spark_apply() to generate combinations using combn()

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问题 I would like to use spark to generate the output of the combn() function for a relatively large list of inputs (200 ish), and to varying values of m (2-5), however I am having trouble including this in spark_apply() . A mwe of my current approach (based on this): names_df <- data.frame(name = c("Alice", "Bob", "Cat"), types = c("Human", "Human", "Animal")) combn(names_df$name, 2) name_tbl <- sdf_copy_to(sc = sc, x = names_df, name = "name_table") name_tbl %>% select(name) %>% spark_apply

Apply vs For loop in R

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问题 I wrote the following code to scrap tendering information from a portal on daily basis. packages <- c('rvest', 'stringi', 'tidyverse','lubridate','dplyr') purrr::walk(packages, library, character.only = TRUE, warn.conflicts = FALSE) start_time <- proc.time() Main Page to scrap and get total no of records. data <- read_html('https://eprocure.gov.in/mmp/latestactivetenders') total_tenders_raw <- html_nodes(data,xpath = '//*[(@id = "table")]') All_tenders <- data.frame(html_table(total_tenders

How to apply patches on the top of a git tree preventing duplication?

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问题 I'm seeking advice for a problem that I thought to be simple, and it might be simple indeed by creating a small script, but I think there should already be a way to do that with git/quilt/stgit. I'm not exactly good at git and this is causing some issues to me. My problem: I've got a git tree (linux kernel) and a number of patches. What happens, such patches were intended for and older version of the kernel, and many of them have already been applied to my tree. The patches start with an