To transpose an array, NumPy just swaps the shape and stride information for each axis. Here are the strides: >>> arr.strides (64, 32, 8) >>> arr.transpose(1, 0, 2).strides (32, 64, 8) Notice that the transpose operation swapped the strides for axis 0 and axis 1. The lengths of these axes were also swapped (both lengths … Read more
awk ‘ { for (i=1; i<=NF; i++) { a[NR,i] = $i } } NF>p { p = NF } END { for(j=1; j<=p; j++) { str=a[1,j] for(i=2; i<=NR; i++){ str=str” “a[i,j]; } print str } }’ file output $ more file 0 1 2 3 4 5 6 7 8 9 10 11 $ ./shell.sh … Read more
output = array[0].map((_, colIndex) => array.map(row => row[colIndex])); map calls a provided callback function once for each element in an array, in order, and constructs a new array from the results. callback is invoked only for indexes of the array which have assigned values; it is not invoked for indexes which have been deleted or … Read more
It’s working exactly as it’s supposed to. The transpose of a 1D array is still a 1D array! (If you’re used to matlab, it fundamentally doesn’t have a concept of a 1D array. Matlab’s “1D” arrays are 2D.) If you want to turn your 1D vector into a 2D array and then transpose it, just … Read more
2016 update: Here’s a snazzier Ecmascript 6 version: zip= rows=>rows[0].map((_,c)=>rows.map(row=>row[c])) Illustration equiv. to Python{zip(*args)}: > zip([[‘row0col0’, ‘row0col1’, ‘row0col2’], [‘row1col0’, ‘row1col1’, ‘row1col2’]]); [[“row0col0″,”row1col0”], [“row0col1″,”row1col1”], [“row0col2″,”row1col2”]] (and FizzyTea points out that ES6 has variadic argument syntax, so the following function definition will act like python, but see below for disclaimer… this will not be its own inverse … Read more
Python 3: # short circuits at shortest nested list if table is jagged: list(map(list, zip(*l))) # discards no data if jagged and fills short nested lists with None list(map(list, itertools.zip_longest(*l, fillvalue=None))) Python 2: map(list, zip(*l)) [[1, 4, 7], [2, 5, 8], [3, 6, 9]] Explanation: There are two things we need to know to understand … Read more
zip is its own inverse! Provided you use the special * operator. >>> zip(*[(‘a’, 1), (‘b’, 2), (‘c’, 3), (‘d’, 4)]) [(‘a’, ‘b’, ‘c’, ‘d’), (1, 2, 3, 4)] The way this works is by calling zip with the arguments: zip((‘a’, 1), (‘b’, 2), (‘c’, 3), (‘d’, 4)) … except the arguments are passed to … Read more