Could you explain to me what is a VGroup and how is it useful, please? I tried looking for it, but obviously to no avail, not much documentation there is. Thanks in advance.
It is basically a group of VMobjects. So say you have some equation consisting of multiple seperate Texmobjects. Then you want to move the entire thing. It would make sense to VGroup all the parts, so let entire_eq = VGroup (eq_part1, eq_part2, eq_part3) and then you would just have to move this entire_eq. This also applies for changing the colors, scaling and so fort.
This works for any kinds of VMobject.
Related
I am quite new to Julia so I maybe missed the proper documentation.
Is it possible to define a PDESystem in ModelingToolKit with symbolic BCs and Domain for arbitrary geometry?
For instance, if I want to solve the 2D Navier-Stokes equations with a PINN in the following period-hill shape with a curved ground:
How can I defined a no-slip boundary condition on the ground and how can I limit my y-axis to range from y/H = ground(x) to y/H=3 ?
Thanks in advance!
That just doesn't exist right now. The PDESystem parts are still under very active development.
I'm trying to think of the best way to conduct some sort of analysis between two 3D models of the same object.
The first scan is of the original item and the second scan is after it has been put under some load x.
An example would be trying to find the difference between two types of metal.
I would like to be able to scan the initial metal cylinder, apply a measured load, scan it again, and then finally apply some sort of algorithm to compare the difference.
Is it possible to do this efficiently (maybe using Mablab) over say 50 - 100 items for an object around 5inch^3?
I am assuming I will need to work out some sort of utility function as the total mass should be the same?
Would machine learning be beneficial in this case?
Any suggestions or direction would be amazing.
Thank you :)
EDIT: The scan files are coming through as '.stl'
I'm teaching myself swift while recuperating from back surgery and everyone's help has been awesome while I'm learning swift. I apologize if this seems super simple but I figure it might help the next guy.
I've read the Apple Documentation on fixed joints and was struggling to get this to work.
You will notice that the joint is present but doesn't lock the two together.
This seems like a simple fix (and is) but hopefully this will help someone.
When you are adding your joint the documentation shows:
joint(withBodyA:bodyB:anchor:)
For this to work you need to make sure you enter in your sprite to be joined as the "withBodyA" body.
My "bad" joint:
let jointFixed = SKPhysicsJointFixed.jointWithBodyA(zombie1.physicsBody!, bodyB: zombie2.physicsBody!, anchor: z1.position)
self.physicsWorld.addJoint(jointFixed)
The fix is to make sure the sprite you are joining to is the first variable:
let jointFixed = SKPhysicsJointFixed.jointWithBodyA(zombie2.physicsBody!, bodyB: zombie1.physicsBody!, anchor: z1.position)
self.physicsWorld.addJoint(jointFixed)
As always, triple reading the documentation is the key.
This is an idea I got in to my mind,
All the display devices(screens which have pixels etc...) have an upper bound for the amount of various images they can generate.
as an example 1024*728 - 32 bit pixel display can only show (2^32)^(1024*768) etc... number of identical frames without duplicating any scene(view).
funny thing is, It's like we could pre generate all the films all the windows we have ever seen in our lives through screens etc...
the question here is can anybody use this abstract idea to create something useful? :D
You're talking of a number about
(2^32)^(1024*768) ~~ ((2^4)^8)^(10^6) ~~ 10^8^(10^6) ~ 10^8000000.
The number of atoms in universe is about
10^80 // http://en.wikipedia.org/wiki/Observable_universe#Matter_content
I think that there is no way we could pre-generate all the screens in our life.
Let me formulate another question. From a number this big, what can we do to reduce it? How to aggregate similar pictures in order to reduce the complexity?
Another nice question is: what kind of data structure we need to store all this information? Suppose we reduce the number of similar images to 10^10. What kind of structure can handle so many different kinds of pictures in an efficient way?
So given some extra information about the scenes you could generate you might be able to pull apart the scenes that no-one has ever seen.
So if you could take all the pictures out on the internet and the statistics about what was popular or viewed a lot then compute your all possible screens you could pull apart that was not viewed much.
With some basic rules about complexity of the image you might be able to come up with images that have not been seen before. Think 80% flesh tones might produce something coupled with a variance to show range might render people naked. :-)
Of course the computation of such an idea is vastly outside our potential. 2^32^(1024*768) is in the superexponential range which is outside the bounds of reality. I tried to compute it in ruby, and it just died. It would have been fun if it had actually worked. :-)
my Application is given a list of Geocorrdinates and now I have to determine which of those Coordinates are inside a defined Area. For example the Search would definiton would be: Show me all Areas where 100 Coordinates are in an Area of 1km^2. So I have to find out which of these coordinates are together in Areas of 1km^2 and more than 100.
But that seems to be a hard Job for my understanding of geocoordinates and I hope someone can help me with that.
The Latitude coordinates are consistent and Distance between two degrees is 111km. For example the Distance between N50,985° and N50,995° is 1,11km. The Distance between 2 Longtitude Coordinates is not so easy and depends on the Latitude coordinate.
But to be honest, I really don't know how to start.
Does someone have an Idea and can help me?
Thank you
twickl
what you need is a geospatial database, I'd recommend PostgreSQL with PostGIS. It provides the function you need to calculate this kind of stuff. Also search for good tutorials about it. An example is a radius search like "give me all McDonalds in a radius of 10km where I live"
If the problem with having a database is simply that you don't want to host it (or pay for someone to host it) then I recommend Fusion Tables.
I don't know if it supports exactly the functionality you are looking for, however I suppose you could select a random point and do a count of everything within range of that point.
I think that what you are talking could be quite a cpu intensive task (depending on how accurate you want it to be). Not something I would personally try and unload onto a portable device.