Simsam: Simplex Sampling Methods
This small package implements methods for sampling from a unit simplex, a problem that often crops up in a data analysis context.
Usage
There is only a single sampling strategy that results in uniform samples from the unit simplex:
from simsam import kraemer_sampling
# Sample 1,000 points from the 10-dimensional unit simplex.
dim = 10
N = 1000
samples = kraemer_sampling(dim, N)
For comparison purposes, there is also a naive sampling procedure, which does not result in uniform samples.
from simsam import naive_sampling
# Sample 1,000 points from the 10-dimensional unit simplex. Notice that
# the samples will be biased.
dim = 10
N = 1000
samples = naive_sampling(dim, N)
Metadata
Release files for simsam 0.1.3
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| Simsam-0.1.3.tar.gz | 3.4 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| Simsam-0.1.3-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 7.5 kB
Release files / Simsam-0.1.3.tar.gz
| Download URL | Simsam-0.1.3.tar.gz |
|---|---|
| Size | 3.4 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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| Uploaded via |
poetry/1.1.4 CPython/3.9.6 Darwin/19.6.0
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Release files / Simsam-0.1.3-py3-none-any.whl
| Download URL | Simsam-0.1.3-py3-none-any.whl |
|---|---|
| Size | 4.1 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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No |
| Uploaded via |
poetry/1.1.4 CPython/3.9.6 Darwin/19.6.0
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