I'm currently working on a project where I try to optimize the way objects are assigned a spot in a stockroom. Where we want the most frequently bought products as close to the front as possible, with a decreasing order towards the back. I was thinking of somehow representing this using an array, where array[x] = 0 represents a wall, array[x] = 1 represents a path where one could walk, and array[x] = Object represents some item in a shelf. With properties such as distance from drop off point, etc.
Any one have any tips or things I should think about?
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So basically im doing this for my minecraft spigot plugin (java). I know there are already some land claim plugins but i would like to make my own.
For this claim plugin i'd like to know how to get if a point (minecraft block) is inside a region (rectangle). i know how to check if a point is inside a rectangle, the main problem is how to check as quickly as possible when there are like lets say 10.000 rectangles.
What would be the most efficient way to check 10.000 or even 100.000 without having to manually loop through all of them and check every single rectangle?
Is there a way to add a logical test when the rectangles get generated in a way that checks if they hold that point? In that case you could set a boolean to true if they contain that point when generated, and then when checking for that minecraft block the region (rectangle) replies with true or false.
This way you run the loops or checks when generating the rectangles, but when running the game the replies should happen very fast, just check if true or false for bool ContainsPoint.
If your rectangles are uniformly placed neighbors of each other in a big rectangle, then finding which rectangle contains point is easy:
width = (maxX-minX)/num_rectangles_x;
height = same but for y
idx = floor( (x - minX)/width );
idy = floor( (y - minY)/height );
id_square = idx + idy*num_rectangles_x;
If your rectangles are randomly placed, then you should use a spatial acceleration structure like octree. Then check if point is in root, then check if point is in one of its nodes, repeat until you find a leaf that includes the point. 10000 tests per 10milliseconds should be reachable on cpu. 1 million tests per 10ms should be ok for a gpu. But you may need to implement a sparse version of the octree and a space filling curve order for leaf nodes to have better caching, to reach those performance levels.
I had the idea of creating a fantasy city, and to avoid having the same house over and over, but not have to manually create hundreds of houses I was thinking on creating collections like "windows", "doors", "roofs", etc, and then create objects with vertex's assigned to specific groups with the same names ("windows" vertex groups, "doors" vertex groups, etc), and then have blender pick for each instance of a house a random window for each of the vertex in the group, same for doors, roofs, etc.
Is there a way of doing this? (couldn't find anything online), or do I need to create a custom addon? If so, any good reference or starting point where something close to this is done?
I've thought of particle systems, or child objects, but couldn't find a way to attach to the vertex a random part of the collection. Also thought of booleans, but it doesn't have an option to attach to specific vertex, nor to use collections. So I'm out of ideas of how to approach this.
What I have in mind:
Create basic shape, and assign vertex to the "windows" vertex group:
https://i.imgur.com/DAkgDR3.png
And then have random objects within the "Windows" collection attached to those vertex, as either a particle or modifier:
https://i.imgur.com/rl5BDQL.png
Thanks for any help :)
Ok, I've found a way of doing this.
I'm using 3 particle systems (doors, roofs and windows), each using vertex as emitters, and using vector groups to define where to display one of each the different options.
To avoid the particle emitter to put more than one object per vertex, I created a small script that counts the number of vertex of each vertex group and updates each of the particle system Emission number accordingly.
import bpy
o = bpy.data.objects["buildings"]
groups = ["windows", "doors", "roofs"]
for group in groups:
vid = o.vertex_groups.find(group)
vectors = [ v for v in o.data.vertices if vid in [ vg.group for vg in v.groups ] ]
bpy.data.particles[group].count = len(vectors)
I've used someone's code from stack overflow for counting the number of vectors in a vector group, but can't find again the link to the specific question, so if you see your code here, please do comment and I'll update my answer with the proper credit.
I am working on a vb.net auto-focus routine and have the image processing part worked out, basically I do some edge detection, convert to gray-scale and then measure the standard deviation to work out the most 'in focus' point of the image.
I have done this with a number of images, and it almost comes out as a normal distribution, now I want to start to integrate this with my microscope and a stepper motor.
The concept is that I would move through a lower and upper limit on the stepper motor, and measure the above through live-view, recording the values in a list. In my case the two things I want to record are the position, and the double standard deviation value.
I am wondering what the best way to record these are, should it be
recorded as a typed list, or a dictionary or another method?
Once I record all of these values, I would want to go through the values to conduct some simple analysis of them, so if that was the case
how would I then be able to determine the average, min, max etc?
My first attempt of storing the information was in a typed list, where I had essentially done the below;
Public ZPositions As New List(Of Zfocus)
Public Class Zfocus
Public Position As Integer
Public GreyStDev As Double
End Class
The second way was to use a dictionary;
Public ZPosition As New Dictionary(Of Integer, Double)
However in both cases, I am not sure how I can either pull out a single maximum position value (e.g. Position integer,) or from the dictionary the position value (integer) which (sort of) corrosponds to the best auto-focus position.
The Third added bonus, is to be able to pull out any postions above a
specific value, which may corrospond to having some focus information
within them for focus stacking?
Many thanks
Big thanks to jmcilhinney, this solved my issue and works a treat!
Went with a strongly typed list (the ZFocus list) and then I could do the below;
MaxPosition = ZPositions.First(Function(zp1) zp1.GreyStDev = ZPositions.Max(Function(zp2) zp2.GreyStDev))
This allowed be to set up an auto-focus routine which loops through a number of images (as a test), stores the position (e.g. image number in this case) and the intensity edge information, and at the end then pull out the strongest intensity information which forms the best auto-focus point in my case
I am running a wavelet transform (cmor) to estimate damping and frequencies that exists in a signal.cmor has 2 parameters that I can change them to get more accurate results. center frequency(Fc) and bandwidth frequency(Fb). If I construct a signal with few freqs and damping then I can measure the error of my estimation(fig 2). but in actual case I have a signal and I don't know its freqs and dampings so I can't measure the error.so a friend in here suggested me to reconstruct the signal and find error by measuring the difference between the original and reconstructed signal e(t)=|x(t)−x^(t)|.
so my question is:
Does anyone know a better function to find the error between reconstructed and original signal,rather than e(t)=|x(t)−x^(t)|.
can I use GA to search for Fb and Fc? or do you know a better search method?
Hope this picture shows what I mean, the actual case is last one. others are for explanations
Thanks in advance
You say you don't know the error until after running the wavelet transform, but that's fine. You just run a wavelet transform for every individual the GA produces. Those individuals with lower errors are considered fitter and survive with greater probability. This may be very slow, but conceptually at least, that's the idea.
Let's define a Chromosome datatype containing an encoded pair of values, one for the frequency and another for the damping parameter. Don't worry too much about how their encoded for now, just assume it's an array of two doubles if you like. All that's important is that you have a way to get the values out of the chromosome. For now, I'll just refer to them by name, but you could represent them in binary, as an array of doubles, etc. The other member of the Chromosome type is a double storing its fitness.
We can obviously generate random frequency and damping values, so let's create say 100 random Chromosomes. We don't know how to set their fitness yet, but that's fine. Just set it to zero at first. To set the real fitness value, we're going to have to run the wavelet transform once for each of our 100 parameter settings.
for Chromosome chr in population
chr.fitness = run_wavelet_transform(chr.frequency, chr.damping)
end
Now we have 100 possible wavelet transforms, each with a computed error, stored in our set called population. What's left is to select fitter members of the population, breed them, and allow the fitter members of the population and offspring to survive into the next generation.
while not done
offspring = new_population()
while count(offspring) < N
parent1, parent2 = select_parents(population)
child1, child2 = do_crossover(parent1, parent2)
mutate(child1)
mutate(child2)
child1.fitness = run_wavelet_transform(child1.frequency, child1.damping)
child2.fitness = run_wavelet_transform(child2.frequency, child2.damping)
offspring.add(child1)
offspring.add(child2)
end while
population = merge(population, offspring)
end while
There are a bunch of different ways to do the individual steps like select_parents, do_crossover, mutate, and merge here, but the basic structure of the GA stays pretty much the same. You just have to run a brand new wavelet decomposition for every new offspring.
I am writing a game, which need a map, and I want to store the map. The first thing I can think of, is using a 2D-array. But the problem is what data should I store in the 2D-array. The player can tap different place to have different reaction. So, I am thinking store a 2D-array with objects, when player click some position, and I find it in the array, and use the object in that array to execute a cmd. But I have a concern that storing lots of object may use lots of memory. So, I am think storing char/int only. But it seems that not enough for me. I want to store the data like that:
{
Type:1
Color:Green
}
No matter what color is, if they are all type 1, the have same reactions in logic, but the visual effect is based on the color. So, it is not easy to store using a prue char/int data, unless I make something like this:
1-5 --> all type 1. 1=color green ,
2=color red, 3 = color yellow.... ...
6-10 --> all type 2. 2 = color green,
2 = color red ... ...
So, do you have any ideas on how to minimize the ram use, but also easy for me to read... ...thx
Go ahead and store a bunch of objects in the array, but with these two refinements:
Store a pointer to the object, not the object itself. (Objective C may handle this for you automatically; I don't know.)
Remember that a pointer to a single object can appear in more than one position in the array. All squares that share the same color and behavior can share an object.
It would also help if you did the math on the size of the array and the number of distinct squares so we can know exactly how much RAM you are talking about.