A programming challenge with Mathematica - input

I am interfacing an external program with Mathematica. I am creating an input file for the external program. Its about converting geometry data from a Mathematica generated graphics into a predefined format. Here is an example Geometry.
Figure 1
The geometry can be described in many ways in Mathematica. One laborious way is the following.
dat={{1.,-1.,0.},{0.,-1.,0.5},{0.,-1.,-0.5},{1.,-0.3333,0.},{0.,-0.3333,0.5},
{0.,-0.3333,-0.5},{1.,0.3333,0.},{0.,0.3333,0.5},{0.,0.3333,-0.5},{1.,1.,0.},
{0.,1.,0.5},{0.,1.,-0.5},{10.,-1.,0.},{10.,-0.3333,0.},{10.,0.3333,0.},{10.,1.,0.}};
Show[ListPointPlot3D[dat,PlotStyle->{{Red,PointSize[Large]}}],Graphics3D[{Opacity[.8],
Cyan,GraphicsComplex[dat,Polygon[{{1,2,5,4},{1,3,6,4},{2,3,6,5},{4,5,8,7},{4,6,9,7},
{5,6,9,8},{7,8,11,10},{7,9,12,10},{8,9,12,11},{1,2,3},{10,12,11},{1,4,14,13},
{4,7,15,14},{7,10,16,15}}]]}],AspectRatio->GoldenRatio]
This generates the required 3D geometry in GraphicsComplex format of MMA.
This geometry is described as the following input file for my external program.
# GEOMETRY
# x y z [m]
NODES 16
1. -1. 0.
0. -1. 0.5
0. -1. -0.5
1. -0.3333 0.
0. -0.3333 0.50. -0.3333 -0.5
1. 0.3333 0.
0. 0.3333 0.5
0. 0.3333 -0.5
1. 1. 0.
0. 1. 0.5
0. 1. -0.5
10. -1. 0.
10. -0.3333 0.
10. 0.3333 0.
10. 1. -0.
# type node_id1 node_id2 node_id3 node_id4 elem_id1 elem_id2 elem_id3 elem_id4
PANELS 14
1 1 4 5 2 4 2 10 0
1 2 5 6 3 1 5 3 10
1 3 6 4 1 2 6 10 0
1 4 7 8 5 7 5 1 0
1 5 8 9 6 4 8 6 2
1 6 9 7 4 5 9 3 0
1 7 10 11 8 8 4 11 0
1 8 11 12 9 7 9 5 11
1 9 12 10 7 8 6 11 0
2 1 2 3 1 2 3
2 10 12 11 9 8 7
10 4 1 13 14 1 3
10 7 4 14 15 4 6
10 10 7 15 16 7 9
# end of input file
Now the description I have from the documentation of this external program is pretty short. I am quoting it here.
First keyword NODES states total number of
nodes. After this line there should be no comment or empty lines. Next lines consist of
three values x, y and z node coordinates and number of lines must be the same as number
of nodes.
Next keyword is PANEL and states how many panels we have. After that we have lines
defining each panel. First integer defines panel type
ID 1 – quadrilateral panel - is defined by four nodes and four neighboring panels.
Neighboring panels are panels that share same sides (pair of nodes) and is needed for
velocity and pressure calculation (methods 1 and 2). Missing neighbors (for example for
panels near the trailing edge) are filled with value 0 (see Figure 1).
ID 2 – triangular panel – is defined by three nodes and three neighboring panels.
ID 10 – wake panel – is quadrilateral panel defined with four nodes and with two
(neighboring) panels which are located on the trailing edge (panels to which wake panel is
applying Kutta condition).
Panel types 1 and 2 must be defined before type 10 in input file.
Important to notice is the surface normal; order of nodes defining panels should be
counter clockwise. By the right-hand rule if fingers are bended to follow numbering,
thumb will show normal vector that should point “outwards” geometry.
Challenge!!
We are given with a 3D CAD model in a file called One.obj and it is exported fine in MMA.
cd = Import["One.obj"]
The output is a MMA Graphics3D object
Now I can get easily access the geometry data as MMA internally reads them.
{ver1, pol1} = cd[[1]][[2]] /. GraphicsComplex -> List;
MyPol = pol1 // First // First;
Graphics3D[GraphicsComplex[ver1,MyPol],Axes-> True]
How we can use the vertices and polygon information contained in ver1 and pol1 and write them in a text file as described in the input file example above. In this case we will only have ID2 type (triangular) panels.
Using the Mathematica triangulation how to find the surface area of this 3D object. Is there any inbuilt function that can compute surface area in MMA?
No need to create the wake panel or ID10 type elements right now. A input file with only triangular elements will be fine.
Sorry for such a long post but its a puzzle that I am trying to solve for a long time. Hope some of you expert may have the right insight to crack it.
BR

Q1 and Q2 are easy enough that you could drop the "challenge" labels in your question. Q3 could use some clarification.
Q1
edges = cd[[1, 2, 1]];
polygons = cd[[1, 2, 2, 1, 1, 1]];
Update Q1
The main problem is to find the neighbor of each polygon. The following does this:
(* Split every triangle in 3 edges, with nodes in each edge sorted *)
triangleEdges = (Sort /# Subsets[#, {2}]) & /# polygons;
(* Generate a list of edges *)
singleEdges = Union[Flatten[triangleEdges, 1]];
(* Define a function which, given an edge (node number list), returns the bordering *)
(* triangle numbers. It's done by working through each of the triangles' edges *)
ClearAll[edgesNeighbors]
edgesNeighbors[_] = {};
MapIndexed[(
edgesNeighbors[#1[[1]]] = Flatten[{edgesNeighbors[#1[[1]]], #2[[1]]}];
edgesNeighbors[#1[[2]]] = Flatten[{edgesNeighbors[#1[[2]]], #2[[1]]}];
edgesNeighbors[#1[[3]]] = Flatten[{edgesNeighbors[#1[[3]]], #2[[1]]}];
) &, triangleEdges
];
(* Build a triangle relation table. Each '1' indicates a triangle relation *)
relations = ConstantArray[0, {triangleEdges // Length, triangleEdges // Length}];
Scan[
(n = edgesNeighbors[##];
If[Length[n] == 2,
{n1, n2} = n;
relations[[n1, n2]] = 1; relations[[n2, n1]] = 1];
) &, singleEdges
]
MatrixPlot[relations]
(* Build a neighborhood list *)
triangleNeigbours =
Table[Flatten[Position[relations[[i]], 1]], {i,triangleEdges // Length}];
(* Test: Which triangles border on triangle number 1? *)
triangleNeigbours[[1]]
(* ==> {32, 61, 83} *)
(* Check this *)
polygons[[{1, 32, 61, 83}]]
(* ==> {{1, 2, 3}, {3, 2, 52}, {1, 3, 50}, {19, 2, 1}} *)
(* Indeed, they all share an edge with #1 *)
You can use the low level output functions described here to output these. I'll leave the details to you (that's my challenge to you).
Q2
The area of the wing is the summed area of the individual polygons. The individual areas can be calculated as follows:
ClearAll[polygonArea];
polygonArea[pts_List] :=
Module[{dtpts = Append[pts, pts[[1]]]},
If[Length[pts] < 3,
0,
1/2 Sum[Det[{dtpts[[i]], dtpts[[i + 1]]}], {i, 1, Length[dtpts] - 1}]
]
]
based on this Mathworld page.
The area is signed BTW, so you may want to use Abs.
CORRECTION
The above area function is only usable for general polygons in 2D. For the area of a triangle in 3D the following can be used:
ClearAll[polygonArea];
polygonArea[pts_List?(Length[#] == 3 &)] :=
Norm[Cross[pts[[2]] - pts[[1]], pts[[3]] - pts[[1]]]]/2

Related

No of Passes in a Bubble Sort

For the list of items in an array i.e. {23 , 12, 8, 15, 21}; the number of passes I could see is only 3 contrary to (n-1) passes for n elements. I also see that the (n-1) passes for n elements is also the worst case where all the elements are in descending order. So I have got 2 conclusions and I request you to let me know if my understanding is right wrt the conclusions.
Conclusion 1
(n-1) passes for n elements can occur in the following scenarios:
all elements in the array are in descending order which is the worst case
when it is not the best case(no of passes is 1 for a sorted array)
Conclusion 2
(n-1) passes for n elements is more like a theoretical concept and may not hold true in all cases as in this example {23 , 12, 8, 15, 21}. Here the number of passes are (n-2).
In a classic, one-directional bubble sort, no element is moved more than one position to the “left” (to a smaller index) in a pass. Therefore you must make n-1 passes when (and only when) the smallest element is in the largest position. Example:
12 15 21 23 8 // initial array
12 15 21 8 23 // after pass 1
12 15 8 21 23 // after pass 2
12 8 15 21 23 // after pass 3
8 12 15 21 23 // after pass 4
Let's define L(i) as the number of elements to the left of element i that are larger than element i.
The array is sorted when L(i) = 0 for all i.
A bubble sort pass decreases every non-zero L(i) by one.
Therefore the number of passes required is max(L(0), L(1), ..., L(n-1)). In your example:
23 12 8 15 21 // elements
0 1 2 1 1 // L(i) for each element
The max L(i) is L(2): the element at index 2 is 8 and there are two elements left of 8 that are larger than 8.
The bubble sort process for your example is
23 12 8 15 21 // initial array
12 8 15 21 23 // after pass 1
8 12 15 21 23 // after pass 2
which takes max(L(i)) = L(2) = 2 passes.
For a detailed analysis of bubble sort, see The Art of Computer Programming Volume 3: Sorting and Searching section 5.2.2. In the book, what I called the L(i) function is called the “inversion table” of the array.
re: Conclusion 1
all elements in the array are in descending order which is the worst case
Yep, this is when you'll have to do all (n-1) "passes".
when it is not the best case (no of passes is 1 for a sorted array)
No. When you don't have the best-case, you'll have more than 1 passes. So long as it's not fully sorted, you'll need less than (n-1) passes. So it's somewhere in between
re: Conclusion 2
There's nothing theoretical about it at all. You provide an example of a middle-ground case (not fully reversed, but not fully sorted either), and you end up needing a middle-ground number of passes through it. What's theoretical about it?

Efficiently plot coordinate set to numpy (bitmap) array excluding offscreen coordinates

This question follows from Efficiently plot set of {coordinate+value}s to (numpy array) bitmap
A solution for plotting from x, y, color lists to a bitmap is given:
bitmap = np.zeros((10, 10, 3))
s_x = (0,1,2) ## tuple
s_y = (1,2,3) ## tuple
pixal_val = np.array([[0,0,1],[1,0,0],[0,1,0]]) ## np
bitmap[s_x, s_y] = pixal_val
plt.imshow(bitmap)
But how to handle the case where some (x,y) pairs lie outside the bitmap?
Efficiency is paramount.
If I could map offscreen coords to the first row/col of the bitmap (-42, 7) -> (0, 7), (15, -6) -> (15, 0), I could simply black out the first row&col with bitmap[:,0,:] = 0; bitmap[0,:,:] = 0.
Is this doable?
Is there a smarter way?
Are you expecting offscreen coords? if so don't worry otherwise I was just wondering if it was using a non-traditional coordinate system - where the zero may be in the center of the image for whatever reason
Anyway, after my revelation that you can use numpy arrays to store the coordinates, mapping outliers to the first row/col is pretty straightforward, simply using: s_x[s_x < 0] = 0, however, i believe the most efficient way to use logic to find the index of the pixels you want to use so only they are allocated - see below:
bitmap = np.zeros((15, 16, 3))
## generate data
s_x = np.array([a for a in range(-3,22)], dtype=int)
s_y = np.array([a for a in range(-4,21)], dtype=int)
np.random.shuffle(s_x)
np.random.shuffle(s_y)
print(s_x)
print(s_y)
pixel_val = np.random.rand(25,3)
## generate is done
use = np.logical_and(np.logical_and(s_x >= 0, s_x < bitmap.shape[1]), np.logical_and(s_y >= 0, s_y < bitmap.shape[0]))
bitmap[s_y[use], s_x[use]] = pixel_val[use]
plt.imshow(bitmap)
output:
coordinates:
[ 8 3 21 9 -2 -3 5 14 -1 18 13 16 0 11 7 1 2 12 15 6 19 10 4 17 20]
[ 8 14 1 9 2 4 7 15 3 -3 19 16 6 -1 0 17 5 13 -2 20 -4 11 10 12 18]
image:
I ran a test where it had to allocate 3145728 (four times the size of the bitmap you gave in your other question), around half of which were outside the image and on average it took around 140ms, whereas remapping the outliers and then setting the first row/col to zero took 200ms for the same task

How to plot a linegraph in SPSS with respect to the data?

Hi all,
Above you'll see a line-graph plotted with SPSS. I want to improve this line-graph according to its data. Meaning that some elements are not presented correctly:
(1) I deliberately adjusted the scaling on the Y-axis from -1 to 10, in order to notice the breaks (i.e. missing values) in the line graph. Otherwise you'll not notice the breaks, as it will overlap with the bottom-line of the graph. Is it possible to notice the breaks, but with a scaling of 0 to 10 (in SPSS)? > SOLVED
(2) On the X-axis, point 14 and 15 are missing, hence the break. However, the line graph shows an upward trend just after point 13, and a downward trend just before point 16. Is it possible to adjust the line-graph (in SPSS), which would delete these described (interpolation) trends?
GGRAPH
/GRAPHDATASET NAME="graphdataset" VARIABLES=Time_Period_Hours
MEAN(MT)[name="MEAN_MT"] MISSING=VARIABLEWISE REPORTMISSING=NO
/GRAPHSPEC SOURCE=INLINE.
BEGIN GPL
SOURCE: s=userSource(id("graphdataset"))
DATA: Time_Period_Hours=col(source(s), name("Time_Period_Hours"), unit.category())
DATA: MEAN_MT=col(source(s), name("MEAN_MT"))
GUIDE: axis(dim(2), delta(1))
SCALE: linear(dim(2), min(-0.5), max(9))
ELEMENT: line(position(Time_Period_Hours*MEAN_MT))
ELEMENT: point(position(Time_Period_Hours*MEAN_MT), color(color.black),
size(size."3px"))
END GPL.
Here is an example, for the line element you need to specify the option missing.gap() - I thought just deleting missing.wings() from the default code would work but maybe it is an internal default. You may want to consider changing Time_Period_Hours to a scale variable and doing the aggregation outside of GGRAPH. Also making the Y axis scale in your example go all the way up to 9 seems a bit superfluous.
DATA LIST FREE / Time_Period_Hours MT.
BEGIN DATA
1 1
2 0
3 0
4 0
5 1
6 0
7 0
8 0
9 0
10 0
11 .
12 0
13 0
14 .
15 .
16 1
17 0
18 0
19 0
20 .
21 0
END DATA.
FORMATS Time_Period_Hours MT (F2.0).
GGRAPH
/GRAPHDATASET NAME="graphdataset" VARIABLES=Time_Period_Hours
MEAN(MT)[name="MEAN_MT"] MISSING=VARIABLEWISE REPORTMISSING=NO
/GRAPHSPEC SOURCE=INLINE.
BEGIN GPL
SOURCE: s=userSource(id("graphdataset"))
DATA: Time_Period_Hours=col(source(s), name("Time_Period_Hours"), unit.category())
DATA: MEAN_MT=col(source(s), name("MEAN_MT"))
GUIDE: axis(dim(2), delta(1))
SCALE: linear(dim(2), min(-0.5), max(9))
ELEMENT: line(position(Time_Period_Hours*MEAN_MT), missing.gap())
ELEMENT: point(position(Time_Period_Hours*MEAN_MT), color(color.black),
size(size."3px"))
END GPL.

Understanding The Modulus Operator %

I understand the Modulus operator in terms of the following expression:
7 % 5
This would return 2 due to the fact that 5 goes into 7 once and then gives the 2 that is left over, however my confusion comes when you reverse this statement to read:
5 % 7
This gives me the value of 5 which confuses me slightly. Although the whole of 7 doesn't go into 5, part of it does so why is there either no remainder or a remainder of positive or negative 2?
If it is calculating the value of 5 based on the fact that 7 doesn't go into 5 at all why is the remainder then not 7 instead of 5?
I feel like there is something I'm missing here in my understanding of the modulus operator.
(This explanation is only for positive numbers since it depends on the language otherwise)
Definition
The Modulus is the remainder of the euclidean division of one number by another. % is called the modulo operation.
For instance, 9 divided by 4 equals 2 but it remains 1. Here, 9 / 4 = 2 and 9 % 4 = 1.
In your example: 5 divided by 7 gives 0 but it remains 5 (5 % 7 == 5).
Calculation
The modulo operation can be calculated using this equation:
a % b = a - floor(a / b) * b
floor(a / b) represents the number of times you can divide a by b
floor(a / b) * b is the amount that was successfully shared entirely
The total (a) minus what was shared equals the remainder of the division
Applied to the last example, this gives:
5 % 7 = 5 - floor(5 / 7) * 7 = 5
Modular Arithmetic
That said, your intuition was that it could be -2 and not 5. Actually, in modular arithmetic, -2 = 5 (mod 7) because it exists k in Z such that 7k - 2 = 5.
You may not have learned modular arithmetic, but you have probably used angles and know that -90° is the same as 270° because it is modulo 360. It's similar, it wraps! So take a circle, and say that its perimeter is 7. Then you read where is 5. And if you try with 10, it should be at 3 because 10 % 7 is 3.
Two Steps Solution.
Some of the answers here are complicated for me to understand. I will try to add one more answer in an attempt to simplify the way how to look at this.
Short Answer:
Example 1:
7 % 5 = 2
Each person should get one pizza slice.
Divide 7 slices on 5 people and every one of the 5 people will get one pizza slice and we will end up with 2 slices (remaining). 7 % 5 equals 2 is because 7 is larger than 5.
Example 2:
5 % 7 = 5
Each person should get one pizza slice
It gives 5 because 5 is less than 7. So by definition, you cannot divide whole 5items on 7 people. So the division doesn't take place at all and you end up with the same amount you started with which is 5.
Programmatic Answer:
The process is basically to ask two questions:
Example A: (7 % 5)
(Q.1) What number to multiply 5 in order to get 7?
Two Conditions: Multiplier starts from `0`. Output result should not exceed `7`.
Let's try:
Multiplier is zero 0 so, 0 x 5 = 0
Still, we are short so we add one (+1) to multiplier.
1 so, 1 x 5 = 5
We did not get 7 yet, so we add one (+1).
2 so, 2 x 5 = 10
Now we exceeded 7. So 2 is not the correct multiplier.
Let's go back one step (where we used 1) and hold in mind the result which is5. Number 5 is the key here.
(Q.2) How much do we need to add to the 5 (the number we just got from step 1) to get 7?
We deduct the two numbers: 7-5 = 2.
So the answer for: 7 % 5 is 2;
Example B: (5 % 7)
1- What number we use to multiply 7 in order to get 5?
Two Conditions: Multiplier starts from `0`. Output result and should not exceed `5`.
Let's try:
0 so, 0 x 7 = 0
We did not get 5 yet, let's try a higher number.
1 so, 1 x 7 = 7
Oh no, we exceeded 5, let's get back to the previous step where we used 0 and got the result 0.
2- How much we need to add to 0 (the number we just got from step 1) in order to reach the value of the number on the left 5?
It's clear that the number is 5. 5-0 = 5
5 % 7 = 5
Hope that helps.
As others have pointed out modulus is based on remainder system.
I think an easier way to think about modulus is what remains after a dividend (number to be divided) has been fully divided by a divisor. So if we think about 5%7, when you divide 5 by 7, 7 can go into 5 only 0 times and when you subtract 0 (7*0) from 5 (just like we learnt back in elementary school), then the remainder would be 5 ( the mod). See the illustration below.
0
______
7) 5
__-0____
5
With the same logic, -5 mod 7 will be -5 ( only 0 7s can go in -5 and -5-0*7 = -5). With the same token -5 mod -7 will also be -5.
A few more interesting cases:
5 mod (-3) = 2 i.e. 5 - (-3*-1)
(-5) mod (-3) = -2 i.e. -5 - (-3*1) = -5+3
It's just about the remainders. Let me show you how
10 % 5=0
9 % 5=4 (because the remainder of 9 when divided by 5 is 4)
8 % 5=3
7 % 5=2
6 % 5=1
5 % 5=0 (because it is fully divisible by 5)
Now we should remember one thing, mod means remainder so
4 % 5=4
but why 4?
because 5 X 0 = 0
so 0 is the nearest multiple which is less than 4
hence 4-0=4
modulus is remainders system.
So 7 % 5 = 2.
5 % 7 = 5
3 % 7 = 3
2 % 7 = 2
1 % 7 = 1
When used inside a function to determine the array index. Is it safe programming ? That is a different question. I guess.
Step 1 : 5/7 = 0.71
Step 2 : Take the left side of the decimal , so we take 0 from 0.71 and multiply by 7
0*7 = 0;
Step # : 5-0 = 5 ; Therefore , 5%7 =5
Modulus operator gives you the result in 'reduced residue system'. For example for mod 5 there are 5 integers counted: 0,1,2,3,4. In fact 19=12=5=-2=-9 (mod 7). The main difference that the answer is given by programming languages by 'reduced residue system'.
lets put it in this way:
actually Modulus operator does the same division but it does not care about the answer , it DOES CARE ABOUT reminder for example if you divide 7 to 5 ,
so , lets me take you through a simple example:
think 5 is a block, then for example we going to have 3 blocks in 15 (WITH Nothing Left) , but when that loginc comes to this kinda numbers {1,3,5,7,9,11,...} , here is where the Modulus comes out , so take that logic that i said before and apply it for 7 , so the answer gonna be that we have 1 block of 5 in 7 => with 2 reminds in our hand! that is the modulus!!!
but you were asking about 5 % 7 , right ?
so take the logic that i said , how many 7 blocks do we have in 5 ???? 0
so the modulus returns 0...
that's it ...
A novel way to find out the remainder is given below
Statement : Remainder is always constant
ex : 26 divided by 7 gives R : 5
This can be found out easily by finding the number that completely divides 26 which is closer to the
divisor and taking the difference of the both
13 is the next number after 7 that completely divides 26 because after 7 comes 8, 9, 10, 11, 12 where none of them divides 26 completely and give remainder 0.
So 13 is the closest number to 7 which divides to give remainder 0.
Now take the difference (13 ~ 7) = 5 which is the temainder.
Note: for this to work divisor should be reduced to its simplest form ex: if 14 is the divisor, 7 has to be chosen to find the closest number dividing the dividend.
As you say, the % sign is used to take the modulus (division remainder).
In w3schools' JavaScript Arithmetic page we can read in the Remainder section what I think to be a great explanation
In arithmetic, the division of two integers produces a quotient and a
remainder.
In mathematics, the result of a modulo operation is the
remainder of an arithmetic division.
So, in your specific case, when you try to divide 7 bananas into a group of 5 bananas, you're able to create 1 group of 5 (quotient) and you'll be left with 2 bananas (remainder).
If 5 bananas into a group of 7, you won't be able to and so you're left with again the 5 bananas (remainder).

Hash function to iterate through a matrix

Given a NxN matrix and a (row,column) position, what is a method to select a different position in a random (or pseudo-random) order, trying to avoid collisions as much as possible?
For example: consider a 5x5 matrix and start from (1,2)
0 0 0 0 0
0 0 X 0 0
0 0 0 0 0
0 0 0 0 0
0 0 0 0 0
I'm looking for a method like
(x,y) hash (x,y);
to jump to a different position in the matrix, avoiding collisions as much as possible
(do not care how to return two different values, it doesn't matter, just think of an array).
Of course, I can simply use
row = rand()%N;
column = rand()%N;
but it's not that good to avoid collisions.
I thought I could apply twice a simple hash method for both row and column and use the results as new coordinates, but I'm not sure this is a good solution.
Any ideas?
Can you determine the order of the walk before you start iterating? If your matrices are large, this approach isn't space-efficient, but it is straightforward and collision-free. I would do something like:
Generate an array of all of the coordinates. Remove the starting position from the list.
Shuffle the list (there's sample code for a Fisher-Yates shuffle here)
Use the shuffled list for your walk order.
Edit 2 & 3: A modular approach: Given s array elements, choose a prime p of form 2+3*n, p>s. For i=1 to p, use cells (iii)%p when that value is in range 1...s-1. (For row-length r, cell #c subscripts are c%r, c/r.)
Effectively, this method uses H(i) = (iii) mod p as a hash function. The reference shows that as i ranges from 1 to p, H(i) takes on each of the values from 0 to p-1, exactly one time each.
For example, with s=25 and p=29 or 47, this uses cells in following order:
p=29: 1 8 6 9 13 24 19 4 14 17 22 18 11 7 12 3 15 10 5 16 20 23 2 21 0
p=47: 1 8 17 14 24 13 15 18 7 4 10 2 6 21 3 22 9 12 11 23 5 19 16 20 0
according to bc code like
s=25;p=29;for(i=1;i<=p;++i){t=(i^3)%p; if(t<s){print " ",t}}
The text above shows the suggestion I made in Edit 2 of my answer. The text below shows my first answer.
Edit 0: (This is the suggestion to which Seamus's comment applied): A simple method to go through a vector in a "random appearing" way is to repeatedly add d (d>1) to an index. This will access all elements if d and s are coprime (where s=vector length). Note, my example below is in terms of a vector; you could do the same thing independently on the other axis of your matrix, with a different delta for it, except a problem mentioned below would occur. Note, "coprime" means that gcd(d,s)=1. If s is variable, you'd need gcd() code.
Example: Say s is 10. gcd(s,x) is 1 for x in {1,3,7,9} and is not 1 for x in {2,4,5,6,8,10}. Suppose we choose d=7, and start with i=0. i will take on values 0, 7, 14, 21, 28, 35, 42, 49, 56, 63, 70, which modulo 10 is 0, 7, 4, 1, 8, 5, 2, 9, 6, 3, 0.
Edit 1 & 3: Unfortunately this will have a problem in the two-axis case; for example, if you use d=7 for x axis, and e=3 for y-axis, while the first 21 hits will be distinct, it will then continue repeating the same 21 hits. To address this, treat the whole matrix as a vector, use d with gcd(d,s)=1, and convert cell numbers to subscripts as above.
If you just want to iterate through the matrix, what is wrong with row++; if (row == N) {row = 0; column++}?
If you iterate through the row and the column independently, and each cycles back to the beginning after N steps, then the (row, column) pair will interate through only N of the N^2 cells of the matrix.
If you want to iterate through all of the cells of the matrix in pseudo-random order, you could look at questions here on random permutations.
This is a companion answer to address a question about my previous answer: How to find an appropriate prime p >= s (where s = the number of matrix elements) to use in the hash function H(i) = (i*i*i) mod p.
We need to find a prime of form 3n+2, where n is any odd integer such that 3*n+2 >= s. Note that n odd gives 3n+2 = 3(2k+1)+2 = 6k+5 where k need not be odd. In the example code below, p = 5+6*(s/6); initializes p to be a number of form 6k+5, and p += 6; maintains p in this form.
The code below shows that half-a-dozen lines of code are enough for the calculation. Timings are shown after the code, which is reasonably fast: 12 us at s=half a million, 200 us at s=half a billion, where us denotes microseconds.
// timing how long to find primes of form 2+3*n by division
// jiw 20 Sep 2011
#include <stdlib.h>
#include <stdio.h>
#include <sys/time.h>
double ttime(double base) {
struct timeval tod;
gettimeofday(&tod, NULL);
return tod.tv_sec + tod.tv_usec/1e6 - base;
}
int main(int argc, char *argv[]) {
int d, s, p, par=0;
double t0=ttime(0);
++par; s=5000; if (argc > par) s = atoi(argv[par]);
p = 5+6*(s/6);
while (1) {
for (d=3; d*d<p; d+=2)
if (p%d==0) break;
if (d*d >= p) break;
p += 6;
}
printf ("p = %d after %.6f seconds\n", p, ttime(t0));
return 0;
}
Timing results on 2.5GHz Athlon 5200+:
qili ~/px > for i in 0 00 000 0000 00000 000000; do ./divide-timing 500$i; done
p = 5003 after 0.000008 seconds
p = 50021 after 0.000010 seconds
p = 500009 after 0.000012 seconds
p = 5000081 after 0.000031 seconds
p = 50000021 after 0.000072 seconds
p = 500000003 after 0.000200 seconds
qili ~/px > factor 5003 50021 500009 5000081 50000021 500000003
5003: 5003
50021: 50021
500009: 500009
5000081: 5000081
50000021: 50000021
500000003: 500000003
Update 1 Of course, timing is not determinate (ie, can vary substantially depending on the value of s, other processes on machine, etc); for example:
qili ~/px > time for i in 000 004 010 058 070 094 100 118 184; do ./divide-timing 500000$i; done
p = 500000003 after 0.000201 seconds
p = 500000009 after 0.000201 seconds
p = 500000057 after 0.000235 seconds
p = 500000069 after 0.000394 seconds
p = 500000093 after 0.000200 seconds
p = 500000099 after 0.000201 seconds
p = 500000117 after 0.000201 seconds
p = 500000183 after 0.000211 seconds
p = 500000201 after 0.000223 seconds
real 0m0.011s
user 0m0.002s
sys 0m0.004s
Consider using a double hash function to get a better distribution inside the matrix,
but given that you cannot avoid colisions, what I suggest is to use an array of sentinels
and mark the positions you visit, this way you are sure you get to visit a cell once.