Deterministic sampling via orthogonal inverse transform of low-discrepancy Fibonacci grids.
Project description
Deterministic Gaussian Sampling
Deterministic sampling via orthogonal inverse transform of low-discrepancy Fibonacci grids.
Installation
Install via pip:
pip install deterministic-gaussian-sampling-fibonacci
or directly from GitHub:
pip install git+https://github.com/KIT-ISAS/deterministic_gaussian_sampling_fibonacci.git
Usage example
from deterministic_gaussian_sampling_fibonacci import sample_gaussian_fibonacci
import numpy as np
# sample_gaussian_fibonacci(mean, covariance_matrix, sample_count, sample_type)
samples = sample_gaussian_fibonacci([1, 1], np.eye(2), 100, "Fibonacci")
from deterministic_gaussian_sampling_fibonacci import get_uniform_grid
# get_uniform_grid(dimension, sample_count, grid_type)
grid = get_uniform_grid(2, 100, "Fibonacci")
Maximum supported sample counts by dimension and type
| dim | ClassicalFrolov | ImprovedFrolov | Fibonacci | Galois |
|---|---|---|---|---|
| 2 | 100003 | 100003 | 99997 | - |
| 3 | 99997 | 100007 | 99995 | - |
| 4 | 100009 | 99965 | 99997 | - |
| 5 | 100217 | 100017 | 99989 | 105021 |
| 6 | 5987 | 99969 | 100005 | 104997 |
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