Multiplying a 1D array with a scalar

Hello Everyone,
I'm trying to turn on a back-to-back thyristor by sending a current pulse outputed from the DAQ. The delay of this pulse would depend on the line current. I have a forumla that relates the line current and the delay and that includes fixed values for capacitance and inductance, however, the voltage would vary (some numeric constant).The forumla is as follows:
I = V(w*c-(1/w*L)(1-(2*alpha/pi)-(sin(2*alpha)/pi)); alpha is the delay in radians, w is the angular frequency 2*pi*60 rad/s, L and C are my inductor and capacitor value respectively, V is the varied voltage, and finally I is the current.
Since V is a constant which can be detected all the time from the DAQ, I thought about desiging an array for the other terms that just depends on alpha which vary from 0 to 90 degrees or 0 to pi/2 radians. I called (w*c-(1/w*L)(1-(2*alpha/pi)-(sin(2*alpha)/pi)) to be F which is an array to have the different values of F for alpha 0 to 90 degrees , after that I want to multiply this 1 D array with V (scalar) to get a current array. I used searh array to compare the whole current array with an element (which would extracted from my circuit and in labview would be tested as a constant). Using the same index for the found current, I want to extract an alpha value from an alpha array.
so basically, I want to multiply F by V to get I, then search through I and compare all the columns by a constant value, and then extract the value of alpha from the same index. I attached my vi, plz help
Attachments:
look_up_table_generation.vi ‏20 KB

Sure, here are the guts of the code. The loop on the left creates the lookup table.
entering a current level will calculate the fractional index, then return the corresponding value from the x array. The "current value" output is basically the "current level" input coerced to the valid y-range of the lookup table.
Note that threshold and interpolate do a linear interpolation only. It is also required that the function increases monotonically, if not there will be multiple solutions and it would need extra code to get them all.
Message Edited by altenbach on 02-25-2006 01:00 PM
LabVIEW Champion . Do more with less code and in less time .
Attachments:
lookup.png ‏12 KB

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A number of problems.
First, I bet you see a lot of "error at" messages, don't you? You create a 21x7 array, then go through the first array up to 21, going through the second one all the way to 21 as well.
your second for loop should go to flights[x].length, not flights.length. That will eliminate the need for ArrayIndexOutOfBounds checking, which should have been an indication that you were doing something wrong.
Second, when you get to flights[0][0] (the very first iteration of the inner loop) you are taking every element from the StringTokenizer and setting flights[0][0] to each, thereby overwriting the previous one. There will be nothing in the StringTokenizer left for any of the other (21x7)-1=146 array elements. At the end of all the loops, the very first element in the array (flights[0][0]) should contain the last token in the file.
At the end, you only print the first element (i=0, j=0, println(flight[ i][j])) which explains why you see the last element from the file.
I'm assuming you have a file with 21 lines, each of which has 7 items on the line. Here is some pseudo-code to help you out:
count the lines
reset the file
create a 2d array with the first dimension set to the number of lines.
int i = 0;
while (read a line) {
Tokenize the line;
count the tokens;
create an array whose size is the number of tokens;
stuff the tokens into the array;
set flights[i++] to this array;
}

Auto-indexing is slow for arrays with 1 dimensions

Hi,
I was looking at the performance of operations on all individual elements in 3D arrays, especially the difference between auto-indexing (left image) and manual-indexing (right image, calling "Index array" and "Replace array subset" in the innermost loop). I'm a bit puzzled by the results and post it here for discussion and hopefully somebody's benefit in the future.
Left: auto-indexing; right: manual-indexing
In the tests I added a different random number to all individual elements in a 3D array. I found that auto-indexing is 1.2 to 1.5 times slower than manual-indexing. I also found that the performance of auto-indexing is much more dependent on the size the dimensions: an array with 1000x200x40 elements is 20% slower than an array with 1000x40x200 elements. For manual-indexing there is hardly any difference. The detailed results can be found at the end of this post.
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Fake-auto-indexing
Second, I looked if Locality of reference (how the 3D array is stored in memory and how efficiently you can iterate over that) may be an issue. Auto-indexing loops over pages-rows-columns (i.e. pages in the outer for-loop, rows in the middle for-loop, columns in the inner for-loop). This can't be changed for auto-indexing, but I did change it for manual and fake-indexing. The performance of manual-indexing is now similar to auto-indexing, except for two cases that I can't explain. Fake-auto-indexing performs way worse in all cases.
It seems that the performance problem with auto-indexing is due to inefficient data organization.
Other tests
I did the same tests for 1D and 2D arrays. For 1D arrays the three methods perform identical. For 2D arrays auto-indexing is 15% slower than manual-indexing, while fake-auto-indexing is 8% slower than manual-indexing. I find it interesting that auto-indexing is the slowest of the three methods.
Finally, I tested the performance of operating on entire columns (instead of every single element) of a 3D array. In all cases it is a lot faster than iterating over individual elements. Auto-indexing is more than 1.8 to 3.4 times slower than manual-indexing, while fake-auto-indexing is about 1.5 to 2.7 times slower. Because of the number of iterations that has to be done, the effect of the size of the column is important: an array with 1000x200x40 elements is in all cases much slower than an array with 1000x40x200 elements.
Discussion & conclusions
In all the cases I tested, auto-indexing is significantly slower than manual-indexing. Because auto-indexing is the standard way of indexing arrays in LabView I expected the method to be highly optimized. Judging by the tests I did, that is not the case. I find this puzzling.
Does anybody know any best practices when it comes to working with >1D arrays? It seems there is a lack of documentation about the performance, surprising given the significant differences I found.
It is of course possible that I made mistakes. I tried to keep the code as straightforward as possible to minimize that risk. Still, I hope somebody can double-check the work I did.
Results
I ran the tests on a computer with a i5-4570 @ 3.20 GHz processor (4 cores, but only 1 is used), 8 GB RAM running Windows 7 64-bit and LabView 2013 32-bit. The tests were averaged 10 times. The results are in milliseconds.
3D-arrays, iterate pages-rows-columns
pages x rows x cols : auto    manual fake
   40 x 200 x 1000 : 268.9   202.0   268.8
   40 x 1000 x 200 : 276.9   204.1   263.8
200 x   40 x 1000 : 264.6   202.8   260.6
200 x 1000 x   40 : 306.9   205.0   300.0
1000 x   40 x 200 : 253.7   203.1   259.3
1000 x 200 x   40 : 307.2   206.2   288.5
100 x 100 x 100 : 36.2    25.7    33.9
3D-arrays, iterate columns-rows-pages
pages x rows x cols : manual fake
   40 x 200 x 1000 : 277.6   457
   40 x 1000 x 200 : 291.6   461.5
200 x   40 x 1000 : 277.4   431.9
200 x 1000 x   40 : 452.5   572.1
1000 x   40 x 200 : 298.1   460.4
1000 x 200 x   40 : 460.5   583.8
100 x 100 x 100 : 31.7    51.9
2D-arrays, iterate rows-columns
rows x cols : auto     manual   fake
200 x 20000 : 123.5    106.1    113.2
20000 x   200 : 119.5    106.1    115.0
10000 x 10000 : 3080.25 2659.65 2835.1
1D-arrays, iterate over columns
cols   : auto manual fake
500000 : 11.5 11.8    11.6
3D-arrays, iterate pages-rows, operate on columns
pages x rows x cols : auto    manual fake
   40 x 200 x 1000 : 83.9   23.3     62.9
   40 x 1000 x 200 : 89.6   31.9     69.0
200 x   40 x 1000 : 74.3   27.6     62.2
200 x 1000 x   40 : 135.6   76.2    107.1
1000 x   40 x 200 : 75.3   31.2     68.6
1000 x 200 x   40 : 133.6   71.7    108.7
100 x 100 x 100 : 13.0    5.4      9.9
VI's
I attached the VI's I used for testing. "ND_add_random_number.vi" (where N is 1, 2 or 3) is where all the action happens, taking a selector with a method and an array with the N dimensions as input. It returns the result and time in milliseconds. Using "ND_add_random_number_automated_test.vi" I run this for a few different situations (auto/manual/fake-indexing, interchanging the dimensions). The VI's starting with "3D_locality_" are used for the locality tests. The VI's starting with "3D_norows_" are used for the iterations over pages and columns only.
Attachments:
3D_arrays_2.zip ‏222 KB

Robert,
the copy-thing is not specific for auto-indexing. It is common for all tunnels. A tunnel is first of all a unique data space.
This sounds hard, but there is an optimization in the compiler trying to reduce the number of copies the VI will create. This optimization is called "in-placeness".
The in-placeness algorithm checks, if the wire passing data to the is connected to anything else ("branch"). If there is no other connection then the tunnel, chance is high that the tunnel won't create an additional copy.
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You can do a small test to elaborate on this: Simply wire "0" (or anything less than the array sizy of the input array) to the 'N' terminal.......
Norbert
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TEST11.vi ‏13 KB

Chuck,
0. Do not post VIs with infinite loops! Change the True constant to a control. One of the regular participants on these Forums has commented that using the Abort button to stop a VI is like using a tree to stop a car. It works, but may have undesired consequences!
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TEST11.2.vi ‏11 KB

I have read 118 files (from a directory) each with 2088 data and put them into a 2 D array with 2cols and 246384row, I want to have aeach file on a separate columns with 2088 rows

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Hiya,
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S.
// it takes almost no time to rate an answer
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read_files_updated.vi ‏81 KB
Num_Lines_in_File.vi ‏62 KB

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An inefficient way to create the array is to use the build array and a shift register as shown below. It's more effecient in terms of memory management to create the array and then use the replace array subset as shown in the other image. Of course, if you don't need the array inside the loop, just wire the value out of the while loop and on the exit tunnel, right click and select 'Enable Indexing'.
Message Edited by Dennis Knutson on 07-03-2007 10:25 PM
Message Edited by Dennis Knutson on 07-03-2007 10:26 PM
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Message Edited by GerdW on 05-21-2010 10:01 PM
Best regards,
GerdW
CLAD, using 2009SP1 + LV2011SP1 + LV2014SP1 on WinXP+Win7+cRIO
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Thanks very much,
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Is there any way to get around this?What about creating a class that aggregatesseveral
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KajUnfortunately, many of the methods in the List
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Kaj

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Apparently I must specify the dimension of my array
So I have done like that :
Object[][] data;
data = new Object[3] [3];
And that work!
But the problem is when I need to add extra elements to my array.
If I write :
data[4][1] = "123";
I have the error message :
java.lang.ArrayIndexOutOfBoundsException
So, how can I defined a array with variables dimensions OR how can I add a dimension to a array?

if you have:
Object[][] data;
data = new Object[3] [3];you end yo getting ArrayIndexOutOfBoundException if you try to point to some other Indexes. You can increase the size by doing new:
Object[][] data;
data = new Object[4] [3];and then copy the old Arrays to this one... this is heavy.
Other thing to consider then is using some other datastructure, such as Vector, which grows along you add elements to it.
P_trg

Multiplying a 1D array with a scalar

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