Michael, This is great. I wish I had seen this earlier. I did not know about the subscr function, but I had basically gotten to the same point by writing an equivalent custom calc function.
I understand that using a calc function in a table formula is inefficient, since it is executed for every table cell. But for small tables, I think the combination of table formulas and calc functions is extremely powerful. Here are two examples of mine: 1. I wrote a custom calc function called tailsInARow that uses the calc random function to simulate a coin toss and return the number of tails in a row. I used this function to fill a 20x20 table of values. I then used the calc histogram function in a table formula to read the table values, histogram the number of tails in a row, then write the histogram to a new table. 2. I calculated a rotation matrix as a succession of individual rotations about x, y, and z axes. I then wrote the resulting matrix to a table. I then wrote a table function to read the matrix, take the inverse, and write the result to a new table. I think calc is well suited for small problems like this for which I want to have a record of what I did later. But I am always looking for better approaches, if you have any to suggest. Steven On May 21, 2014, at 3:29 AM, Michael Brand <michael.ch.br...@gmail.com> wrote: > Hi Steven > >> Steven Adrian <sadr...@acumeniacal.com> writes: >>> #+TBLFM: @1$1..@1$10=index(10) >>> >>> But the formula above just puts the whole vector in each cell. Can anyone >>> tell me how to put the vector values in individual cells? > > The vector elements can be accessed with Calc subscr() and Org "field > coordinates": > http://orgmode.org/manual/References.html > > | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | > #+TBLFM: @1$1..@1$10 = subscr(index(10), $#) > > In a TBLFM I would not use Calc vector functions like index() but a > calculation of $#, here simply f(x) = x: > > | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | > #+TBLFM: @1$1..@1$10 = $# > > Or is there an interesting Calc vector function that is not easy to > mimic? > > Michael >
