Metadata-Version: 2.4
Name: tklds
Version: 0.0.7
Summary: Tenokonda Low Discrepancy Sequences
Author: tenokonda
Author-email: Ilya Manyakin <ilya@tenokonda.com>, Andres Oliva Denis <andres@tenokonda.com>, Gregory Kell <gregory@tenokonda.com>, Adrien Papaioannou <adrien@tenokonda.com>
License: BSD 3-Clause License
        
        Copyright (c) 2024, TENOKONDA LTD
        
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Project-URL: Homepage, https://github.com/tenokonda/tklds
Project-URL: Issues, https://github.com/tenokonda/tklds/issues
Classifier: Programming Language :: Python :: 3.10
Classifier: Operating System :: OS Independent
Requires-Python: >=3.10
Description-Content-Type: text/x-rst
License-File: LICENSE
Requires-Dist: numpy>=1.23.5
Requires-Dist: pandas>=1.5.3
Requires-Dist: scipy>=1.8.1
Requires-Dist: sympy>=1.12
Requires-Dist: tqdm>=4.65.0
Dynamic: author
Dynamic: license-file

tklds
=================

The repository accompanies the paper:

*On the generation of direction numbers for Sobol Sequences and the application to Quasi Monte Carlo Methods (insert link here)*

The set of direction numbers :code:`tkrg-a-ap5` satisfying property A for all 50,000 dimensions and A' for five adjacent
dimensions can be found in :code:`tklds/direction_numbers/tkrgsobol_a_ap5_50000`

Installing
==========

Install the requirements using :code:`python -m pip install -r requirements.txt`

Install the project by calling :code:`python -m pip install .` from the current folder.

Quickstart
===========

To generate uniform floating point values in the range [0,1] use the following snippet:

>>> from tklds.interface.generators import generate_lds_rvs
>>> u = generate_lds_rvs(sequence_name='tkrg-a-ap5', n=1024, d=5, skip=0)

Here we generate a total of :code:`n=1024` points with each point having :code:`d=5` dimensions using the
sequence generated by the :code:`sequence_name=tkrg-a-ap5` direction numbers, without skipping the first point (:code:`skip=0`).

