UNIFORM
Uniform Quasirandom Datasets

UNIFORM is a dataset directory which contains points generated as part of an M-dimensional uniform random process.

The datasets are distinguished by the values of the following parameters:

• M, the spatial dimension;
• N, the number of points to generate;
• SEED, is the initial value of the seed;

Licensing:

The computer code and data files described and made available on this web page are distributed under the GNU LGPL license.

Related Data and Programs:

PLOT_POINTS, a FORTRAN90 program which can plot two dimensional datasets, making Encapsulated PostScript images.

SEQUENCE_STREAK_DISPLAY, a MATLAB program which can make a streak plot of a (one-dimensional) sequence.

TABLE, a file format which is used to store the datasets.

TABLE_TOP, a FORTRAN90 program which can be used to analyze datasets of any dimension, by creating images of pairwise coordinates.

UNIFORM, a C++ library which computes elements of a uniform pseudorandom sequence.

UNIFORM_DATASET, a C++ program which generates a dataset of uniform pseudorandom values and writes them to a file.

Example dataset:

A typical (but small) dataset of 10 points in 2 dimensions looks like this:

  0.218418  0.956318
  0.829509  0.561695
  0.415307  0.066119
  0.257578  0.109957
  0.043829  0.633966
  0.061727  0.449539
  0.401306  0.754673
  0.797287  0.001838
  0.897504  0.350752
  0.094545  0.013617
      

Reference:

1. Paul Bratley, Bennett Fox, Linus Schrage,
   A Guide to Simulation,
   Springer Verlag, pages 201-202, 1983.
2. Bennett Fox,
   Algorithm 647: Implementation and Relative Efficiency of Quasirandom Sequence Generators,
   ACM Transactions on Mathematical Software,
   Volume 12, Number 4, pages 362-376, 1986.
3. Donald Knuth,
   The Art of Computer Programming,
   Volume 2: Seminumerical Algorithms,
   Addison Wesley, 1969.

Datasets:

Datasets in M = 1 dimensions include:

• uniform_01_00010.txt, M = 1, N = 10, SEED = 123456789;
• uniform_01_00100.txt, M = 1, N = 100, SEED = 123456789;
• uniform_01_00100.png, a PNG image of the dataset, created by SEQUENCE_STREAK_DISPLAY.
• uniform_01_01000.txt, M = 1, N = 1000, SEED = 123456789;
• uniform_01_10000.txt, M = 1, N = 10000, SEED = 123456789;

Datasets in M = 2 dimensions include:

• uniform_02_00010.txt, M = 2, N = 10, SEED = 123456789;
• uniform_02_00010.png, a PNG image of the dataset;
• uniform_02_00100.txt, M = 2, N = 100, SEED = 123456789;
• uniform_02_00100.png, a PNG image of the dataset;
• uniform_02_01000.txt, M = 2, N = 1000, SEED = 123456789;
• uniform_02_01000.png, a PNG image of the dataset;
• uniform_02_10000.txt, M = 2, N = 10000, SEED = 123456789;

Datasets in M = 6 dimensions include:

• uniform_06_00001.txt, M = 6, N = 1, SEED = 123456789;
• uniform_06_00013.txt, M = 6, N = 13, SEED = 123456789;
• uniform_06_00097.txt, M = 6, N = 97, SEED = 123456789;
• uniform_06_00545.txt, M = 6, N = 545, SEED = 123456789;
• uniform_06_02561.txt, M = 6, N = 2561, SEED = 123456789;
• uniform_06_10625.txt, M = 6, N = 10625, SEED = 123456789;

Datasets in M = 7 dimensions include:

• uniform_07_00010.txt, M = 7, N = 10, SEED = 123456789;
• uniform_07_00100.txt, M = 7, N = 100, SEED = 123456789;
• uniform_07_01000.txt, M = 7, N = 1000, SEED = 123456789;
• uniform_07_10000.txt, M = 7, N = 10000, SEED = 123456789;

Datasets in M = 10 dimensions include:

• uniform_10_00001.txt, M = 10, N = 1, SEED = 123456789;
• uniform_10_00021.txt, M = 10, N = 21, SEED = 123456789;
• uniform_10_00241.txt, M = 10, N = 241, SEED = 123456789;
• uniform_106_02001.txt, M = 10, N = 2001, SEED = 123456789;
• uniform_10_13441.txt, M = 10, N = 13441, SEED = 123456789;
• uniform_10_77505.txt, M = 10, N = 77505, SEED = 123456789;

Datasets in M = 16 dimensions include:

• uniform_16_00010.txt, M = 16, N = 10, SEED = 123456789;
• uniform_16_00100.txt, M = 16, N = 100, SEED = 123456789;
• uniform_16_01000.txt, M = 16, N = 1000, SEED = 123456789;
• uniform_16_10000.txt, M = 16, N = 10000, SEED = 123456789;

You can go up one level to the DATASETS directory.