hypercube | Graph visualization tool | Data Visualization library
kandi X-RAY | hypercube Summary
kandi X-RAY | hypercube Summary
Hypercube features a Qt based GUI tool for visualizing simple text based graph representations as SVG and EPS images as well as a Qt independent command line tool. Hypercube uses a simulated annealing algorithm to lay out the graph that can be easy parametrized to achieve the desired look. Main goals in development are portability and easy usage rather than high performance and complexity. The command line tool does not use any other libraries than the standard C++ library and the GUI tool uses "pure" Qt.
Support
Quality
Security
License
Reuse
Top functions reviewed by kandi - BETA
Currently covering the most popular Java, JavaScript and Python libraries. See a Sample of hypercube
hypercube Key Features
hypercube Examples and Code Snippets
Lines of Code : 17
License : No License
Copydef HypercubeEmbedding(M):
"""Map medium states isometrically onto a hypercube."""
dim = 0
tokmap = {}
for t in M.tokens():
if t not in tokmap:
tokmap[t] = tokmap[M.reverse(t)] = 1< def testHypercubeClosure(self):
TC = TransitiveClosure(self.cube)
for i in range(16):
self.assertEqual(TC[i],
{j for j in range(16) if i & j == i and i != j}) def PartialCubeLabeling(G):
"""Return vertex labels with Hamming distance = graph distance."""
return Medium.HypercubeEmbedding(MediumForPartialCube(G)) Community Discussions
Trending Discussions on hypercube
QUESTION
I am trying to subsample a data.frame in a way that the sample would have observations that capture as much variation as possible among a set of columns of the original data.frame.
An example with the mtcars dataset: I'd like to find 3 cars that are the most different from each other by mpg, vs and carb. Looking at the data visually, it would probably be Toyota Corolla (high mpg, vs 1, low carb), Cadillac Fleetwood (low mpg, vs 0, medium carb) and either Maserati Bora (low-med mpg, vs 0, high carb) or Ferrari Dino (medium mpg, vs 0, med-high carb):
ANSWER
Answered 2021-Mar-20 at 15:12I am not exactly sure if this is what you are looking for, but here it goes:
calculate a distance matrix, giving you information about how "far away" each car is from all other cars, based on all the attributes they have (the default for
dist()is eucledian, which you can change).Then take the rowsums or colsums (same thing) from that matrix, which just sums up for each car what the combined distance to all other cars is.
Then isolate those cars with the biggest distances (here, we want 3 cars)
Finally subset your dataframe to only include those cars:
QUESTION
I need to create a custom Monte Carlo integration function to adapt to custom multi-dimensional distribution objects using NumPy. I need it to integrate over the same values in each dimension. It works correctly for a single dimension, but underestimates in multiple dimensions, which gets worse with higher dimensions. I am using this paper (equation 5) as a guide. Is my equation of Volume * Mean Density incorrect? Is my sampling method incorrect? I'm really at a loss for what the error is.
...ANSWER
Answered 2021-Mar-01 at 16:44John, looks good overall but it looks to me that you're figuring the expected result incorrectly. I think the expected result should be (F(2) - F(-2)^3 where F is the Gaussian cdf for mean 0 and variance 1. For F(2) - F(-2), I get erf(sqrt(2)) which is approximately 0.9545, and then (F(2) - F(-2))^3 is 0.8696, which agrees pretty well with your results.
I don't know what mvn.cdf is supposed to return, but the concept of "cdf" is a little fishy in more than one dimension, so maybe you can steer away from that.
About multidimensional integration in general, you mention using Halton sequences. I think that's an interesting idea too. My experience with computing integrals is to use quadrature rules in 1 or 2 dimensions, low-discrepancy sequences in 3 to several (5? 7? I dunno), and MC in more than that. Oh, and also my advice is to work pretty hard for exact results before resorting to numerical approximations.
I would be interested to hear about what you're working on.
QUESTION
I want to generate a uniform random float number in the range of float numbers in the bash script. range e.g. [3.556,6.563]
basically, I am creating LSH(Latin hypercube sampling) function in bash. There I would like to generate an array as one can do with this python command line.
p = np.random.uniform(low=l_lim, high=u_lim, size=[n]).
sample code :
...ANSWER
Answered 2020-Dec-02 at 15:52Most common rand() implementations at least generate a number in the range [0...1), which is really all you need. You can scale a random number in one range to a number in another using the techniques outlined in the answers to this question, eg:
NewValue = (((OldValue - OldMin) * (NewMax - NewMin)) / (OldMax - OldMin)) + NewMin
For bash you have two choices: integer arithmetic or use a different tool.
Some of your choices for tools that support float arithmetic from the command-line include:
- a different shell (eg, zsh)
- perl:
my $x = $minimum + rand($maximum - $minimum); - ruby:
x = min + rand * (max-min) - awk:
awk -v min=3 -v max=17 'BEGIN{srand(); print min+rand()*int(1000*(max-min)+1)/1000}'
note: The original answer this was copied from is broken; the above is a slight modification to help correct the problem. - bc:
printf '%s\n' $(echo "scale=8; $RANDOM/32768" | bc )
... to name a few.
QUESTION
- OS Platform: Linux Centos 7.6
- Distribution: Intel Xeon Gold 6152 (22x3.70 GHz);
- GPU Model: NVIDIA Tesla V100 32 GB;
- Number of nodes/CPU/Cores/GPU: 26/52/1144/104;
- TensorFlow installed from (source or binary): official webpage
- TensorFlow version (use command below): 2.1.0
- Python version: 3.6.8
Description of issue:
While I was implementing my proposed method, using the second style of implementation (see below), I realized that the performance of the algorithm is indeed strange. To be more precise, the accuracy decreases and loss value increases while the number of epochs increases.
So I narrow down the problem and finally, I decided to modify some codes from TensorFlow official page to check what is happening. As it is explained in TF v2 official webpage there are two styles of implementation which I have adopted as follows.
I have modified the code provided in "getting started of TF v2" the link below:
as follows:
...ANSWER
Answered 2020-Jul-14 at 16:27As it is pointed in the comment I made mistake in using the evaluation metrics. I should have used BinaryAccuracy.
Moreover, it is better to edit the call in the advance version as follows:
QUESTION
I have a script that download a playlist of video info as json file.
Yesterday I get video description with \n newline characters, but today those newlines are now just a space and the extracted description is truncated . I remember no change to my code and no update to youtube-dl.
Did youtube change something? Or did I make a mistake somewhere?
Python 3.8.1, youtube-dl 2020.6.16.1
Here's the code that currently extract video description with no newlines.
...ANSWER
Answered 2020-Jul-09 at 07:47This is an issue with youtube-dl that seems to have started today. It is most likely related to changes on Youtube's side.
QUESTION
I am working on hyper-cubes. I am currently using networX in python. I read that networkX is a very good library for working on graphs. My problem is that
1) I want to construct the all perfect matchings of hypercube Q4 and Q5.
2) Then i want to verify that all perfect matchings always extends to Hamiltonian cycle of Hypercube?
P.S : its already proven all perfect matchings in hyper-cubes always extends to Hamiltonian Cycle in hyper-cubes.
I want to verify both these task by a computer program.
I am new to python. I write a code for constructing hyper-cube.
...ANSWER
Answered 2019-Jul-30 at 01:171) I want to construct the all perfect matchings of hypercube Q4 and Q5.
I don't know of any library for finding all perfect matchings of a graph directly. However, this github repository "contains functions to enumerate all perfect and maximum matchings in bipartited graph." Since all perfect matchings are maximum matchings, you can use this to get all maximum matchings and throw out those that are not perfect. Below is some code to do this in python 2.7.
QUESTION
My thoughts so far were:
Types
a hypercube is a (discrete) function from one or more Dimensions to some value. I wanted to use Enumeration types for the Dimensions and ended up with this typeclass:
class (Eq a, Ord a, Show a, Enum a, Bounded a) => Dimension a
which allowed me to use this
...ANSWER
Answered 2020-May-18 at 15:03Dunno what the Eq and Ord constraints are, but I'd replace Enum and Bounded by Finite. For example:
QUESTION
I need to write a python function that returns a list or tuple of coordinates for a unit hypercube, (square/box/tesseract etc.) based on starting coordinates that will be placed in the top left. I have a vector class that takes a list of any length, which I use for different unrelated parts of the project. The order of the points doesn't really matter, only that the starting position is the 'lowest point', ie [x, y, z ...] and that no other point is [x-1, y] or something like that. It needs to work for any number of dimensions, and each side is one unit long.
For a square, it would look like this:
...ANSWER
Answered 2020-Apr-21 at 20:24The itertools function combinations_with_replacement can give you all the needed combinations of "add 1" or "add nothing" for each axis in your cube.
So, supposing your Vector class supports Vector addition:
QUESTION
I have the following header file
possion_surface_reconstructor.h
...ANSWER
Answered 2020-Jan-23 at 23:58The #include directive essentially performs text-level copy and paste of the contents of the specified file at the point where the #include appears. Your header MyMiscellany.h contains definitions for a bunch of static member variables:
QUESTION
I'm trying to generate an optimized LHS (Latin Hypercube Sampling) design in R, with sample size N = 400 and d = 7 variables, but it's taking forever. My pc is an HP Z820 workstation with 12 cores, 32 Mb RAM, Windows 7 64 bit, and I'm running Microsoft R Open which is a multicore version of R. The code has been running for half an hour, but I still don't see any results:
...ANSWER
Answered 2017-Mar-24 at 18:19Just a little code to check performance.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install hypercube
Linux packages
Support
Reuse Trending Solutions
Find, review, and download reusable Libraries, Code Snippets, Cloud APIs from over 650 million Knowledge Items
Find more librariesStay Updated
Subscribe to our newsletter for trending solutions and developer bootcamps
Share this Page
