matrix

问题 How can I delete one or more rows and/or columns from an array? 回答1: Working with: julia> array = [1 2 3 4; 5 6 7 8; 9 10 11 12; 13 14 15 16] 4×4 Array{Int64,2}: 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 To delete a single row (here row 2): julia> newarray = array[1:end .!= 2, :] 3×4 Array{Int64,2}: 1 2 3 4 9 10 11 12 13 14 15 16 To delete a single column (here column 3): julia> newarray = array[:, 1:end .!= 3] 4×3 Array{Int64,2}: 1 2 4 5 6 8 9 10 12 13 14 16 To delete a single row and a single

问题 How can I delete one or more rows and/or columns from an array? 回答1: Working with: julia> array = [1 2 3 4; 5 6 7 8; 9 10 11 12; 13 14 15 16] 4×4 Array{Int64,2}: 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 To delete a single row (here row 2): julia> newarray = array[1:end .!= 2, :] 3×4 Array{Int64,2}: 1 2 3 4 9 10 11 12 13 14 15 16 To delete a single column (here column 3): julia> newarray = array[:, 1:end .!= 3] 4×3 Array{Int64,2}: 1 2 4 5 6 8 9 10 12 13 14 16 To delete a single row and a single

问题 How can I delete one or more rows and/or columns from an array? 回答1: Working with: julia> array = [1 2 3 4; 5 6 7 8; 9 10 11 12; 13 14 15 16] 4×4 Array{Int64,2}: 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 To delete a single row (here row 2): julia> newarray = array[1:end .!= 2, :] 3×4 Array{Int64,2}: 1 2 3 4 9 10 11 12 13 14 15 16 To delete a single column (here column 3): julia> newarray = array[:, 1:end .!= 3] 4×3 Array{Int64,2}: 1 2 4 5 6 8 9 10 12 13 14 16 To delete a single row and a single

问题 I'd like to split the diamonds data frame into a list of 5 dataframe, group by cut . This instruction got me started. https://dplyr.tidyverse.org/reference/group_split.html diamonds_g <- diamonds%>% group_split(cut)%>% setNames(unique(diamonds$cut)) My desired output is a list of 5 nested lists. Each nested list contains one data frame and one matrix, such that: View(diamonds_g[[1]]) factors <- diamonds_g[[1]][2:4] mat <- diamonds_g[[1]][6:10] So each of the nested list (or each cut )

问题 I have a texture of size 800x600. How do I scale it on a webgl <canvas> at another size and keep the original aspect ratio? Assuming that the drawing buffer and the canvas have the same dimensions. 回答1: Given the WebGL only cares about clipsapce coordinates you can just draw a 2 unit quad (-1 to +1) and scale it by the aspect of the canvas vs the aspect of the image. In other words const canvasAspect = canvas.clientWidth / canvas.clientHeight; const imageAspect = image.width / image.height;

问题 I have a texture of size 800x600. How do I scale it on a webgl <canvas> at another size and keep the original aspect ratio? Assuming that the drawing buffer and the canvas have the same dimensions. 回答1: Given the WebGL only cares about clipsapce coordinates you can just draw a 2 unit quad (-1 to +1) and scale it by the aspect of the canvas vs the aspect of the image. In other words const canvasAspect = canvas.clientWidth / canvas.clientHeight; const imageAspect = image.width / image.height;

问题 I have a texture of size 800x600. How do I scale it on a webgl <canvas> at another size and keep the original aspect ratio? Assuming that the drawing buffer and the canvas have the same dimensions. 回答1: Given the WebGL only cares about clipsapce coordinates you can just draw a 2 unit quad (-1 to +1) and scale it by the aspect of the canvas vs the aspect of the image. In other words const canvasAspect = canvas.clientWidth / canvas.clientHeight; const imageAspect = image.width / image.height;

问题 For example, I have a dataset like this test = spark.createDataFrame([ (0, 1, 5, "2018-06-03", "Region A"), (1, 1, 2, "2018-06-04", "Region B"), (2, 2, 1, "2018-06-03", "Region B"), (3, 3, 1, "2018-06-01", "Region A"), (3, 1, 3, "2018-06-05", "Region A"), ])\ .toDF("orderid", "customerid", "price", "transactiondate", "location") test.show() and I can obtain the customer-region order count matrix by overall_stat = test.groupBy("customerid").agg(count("orderid"))\ .withColumnRenamed("count

问题 For example, I have a dataset like this test = spark.createDataFrame([ (0, 1, 5, "2018-06-03", "Region A"), (1, 1, 2, "2018-06-04", "Region B"), (2, 2, 1, "2018-06-03", "Region B"), (3, 3, 1, "2018-06-01", "Region A"), (3, 1, 3, "2018-06-05", "Region A"), ])\ .toDF("orderid", "customerid", "price", "transactiondate", "location") test.show() and I can obtain the customer-region order count matrix by overall_stat = test.groupBy("customerid").agg(count("orderid"))\ .withColumnRenamed("count

问题 I have 22 matrices having equal number of rows (i.e. 691) and different number of columns (i.e. 22-25). I have to add the values corresponding to same row, same column in each of the matrices resulting in one single matrix of the dimension 691*25. fullanno1 has 691 rows & 25 columns: >colnames(fullanno1) [1] "coding-notMod3" "coding-synonymous" "coding-synonymous-near-splice" [4] "intergenic" "intron" "missense" [7] "missense-near-splice" "near-gene-3" "near-gene-5" [10] "splice-3" "splice-5"