nested-loops

问题 i have read some topics on this, but i don't quite think it answers my question. if it does then please direct me to the correct topic and i will definitely look again. here is my problem: i want to write a for loop which will cycle through every possible combination of an array where the array is of length 'n'. that is, if n = 2 then my for loop would be do i1 = 1,2 do i2 = 1,2 ! do stuff here enddo enddo while if n = 3 then my array would look like do i1 = 1,3 do i2 = 1,3 do i3 = 1,3 ! do

问题 I have 2 .vcf files with genomic data and I want to remove lines in the 1st file that are also present in the second file. The code I have so far it seems to iterate only one time, removing the first hit and then stops the search. Any help would be very appreciated since I can not figure out where the problem is. Sorry for any mis-code... I opted for arrays of arrays instead of hashes because the initial order of the file must be maintained, and I think that this is better achieved with

问题 I have an array of object, within those objects is a name property. const objArr = [ { name: "Avram" }, { name: "Andy" } ]; I’m collecting an array of strings from an outside source containing names. const strArr = [ "Avram", "Andy", "Brandon" ]; If strArr contains a string that does not exist as a property name on an object in objArr , I need to create a new object and push it to objArr . For example: objArr.push( { name: "Brandon" } ); Obviously, I can use nested loops, but I’d like to

问题 I need to iterate thru a multi-feature SpatialPolygonsDataFrame (SPDF herein) and erase where each polygon intersects with SpatialLines contained in a list of single-feature SpatialLinesDataFrames (SLDF) and save the updated 'erased' SLDFs to a new list. If a line intersects with two different polygon features, I want two updated 'erased' SLDF to be created and added to the new SLDF list. In the sample I provide below, the SLDFs intersect with exactly one SPDF, except one of the SLDF

问题 I have two arrays A and B. A has multiple values (these values can be string or integer or float) and B has values 0 and 1. I need, for each unique value in A, the count of points that coincide with the 1s in B and the 0s in B. Both the counts need to be stored as separate variables. For example: A = [1, 1, 3, 2, 2, 1, 1, 3, 3] # input multivalue array; it has three unique values – 1,2,3 B = [0, 0, 0, 1, 1, 1, 0, 1, 0] # input binary array #Desired result: countA1_B1 = 1 #for unique value of

问题 I am trying to combine the third column of several data frames, which are called and renamed in a nested for loop, within the same looping process. # Sample Data ecvec_msa6_1998=matrix( round(rnorm(200, 5,15)), ncol=4) ecvec_msa6_1999=matrix( round(rnorm(200, 4,16)), ncol=4) ecvec_msa6_2000=matrix( round(rnorm(200, 3,17)), ncol=4) datasets=c("msa") num_industrys=c(6) years=c(1998, 1999, 2000) alist=list() for (d in 1:length(datasets)) { dataset=datasets[d] for (n in 1:length(num_industrys)){

问题 I try to create a list with nested foreach loop. First loop is looping some numbers, second loop is looping dates. I want to write one number to one date. So there is a another function to check that. But the result is numbers writes on dates multiple times. Out is something like that : number 5 is on 2013.01.15; number 5 is on 2013.01.16; number 5 is on 2013.01.17; number 6 is on 2013.01.15; number 6 is on 2013.01.17; The code : function create_event($numbers,$available_dates) { foreach(

问题 I am attempting to try and find if a string called "values" contains substrings from two different lists. This is my current code: for (i in 1:length(value)){ for (j in 1:length(city)){ if (str_detect(value[i],(city[j]))) == TRUE){ for (k in 1:length(school)){ if (str_detect(value[i],(school[j]))) == TRUE){ ........................................................... } } } } } city and school are separate vectors of different length, each containing string elements. city <- ("Madrid", "London"

问题 I want to calculate the complexity of this nested for loop: s = 0; for(i=1; i<=n; i*=2) for(j=1; j<=i; j*=2) s++; What strategy do I use to find the Big O complexity of this piece of code? 回答1: The outer loop marches through 1, 2, 4, 8, ... n , which takes O(lg n ) steps because you can only double one O(lg n ) times until you hit n . The inner loop does the same. It only goes up to i , but in the final iteration of the outer loop, i reaches its maximum value which is again n , so that's also

问题 I want to compute means with bootstrap confidence intervals for some subsets of a dataframe; the ultimate goal is to produce bar graphs of the means with bootstrap confidence intervals as the error bars. My data frame looks like this: ATG12 Norm ATG5 Norm ATG7 Norm Cancer Stage 5.55 4.99 8.99 IIA 4.87 5.77 8.88 IIA 5.98 7.88 8.34 IIC The subsets I'm interested in are every combination of Norm columns and cancer stage. I've managed to produce a table of means using: df.groupby('Cancer Stage')[