Skip to main content

The DAG adaptation of the Onion method

Project description

DaOsim

The DAG adaptation of the Onion method

Example Usage

import pandas as pd

from daosim import er_dag            # generates a Erdos-Renyi directed acyclic graph
from daosim import sf_out            # rewires a DAG to have scale-free out degree
from daosim import randomize_graph   # randomly shuffles the order of the variables
from daosim import corr              # samples a correlation matrix 
from daosim import simulate          # simulates a dataset
from daosim import standardize       # standardizes a dataset

p = 10    # number of variables
ad = 4    # average degree
n = 100   # number of samples

g = er_dag(p, ad=ad)
g = sf_out(g)
g = randomize_graph(g)

R, B, O = corr(g)
X = simulate(B, O, n)
X = standardize(X)

cols = [f"X{i + 1}" for i in range(p)]
df = pd.DataFrame(X, columns=cols)

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

daosim-0.0.5.tar.gz (4.4 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

daosim-0.0.5-py3-none-any.whl (5.0 kB view details)

Uploaded Python 3

File details

Details for the file daosim-0.0.5.tar.gz.

File metadata

  • Download URL: daosim-0.0.5.tar.gz
  • Upload date:
  • Size: 4.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.11.12

File hashes

Hashes for daosim-0.0.5.tar.gz
Algorithm Hash digest
SHA256 d5752c9fbc4189aab8f8231c52640951f6648067bae0f92edf0dfb1064eeabe3
MD5 c1406dad0365b57c3b599a8100e222ca
BLAKE2b-256 9651f8951884b22a1a448a63e42b6f9d8fe5d6f3bce9718c195f019f60dad3a1

See more details on using hashes here.

File details

Details for the file daosim-0.0.5-py3-none-any.whl.

File metadata

  • Download URL: daosim-0.0.5-py3-none-any.whl
  • Upload date:
  • Size: 5.0 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.11.12

File hashes

Hashes for daosim-0.0.5-py3-none-any.whl
Algorithm Hash digest
SHA256 254576fe6b2c3b9a058d46a9777a819ac95299bab4e5f1b76d5e6e3e13689e95
MD5 33f100ff02ffab22a878ba61c3742c32
BLAKE2b-256 e7519916cb765a4818e38cf1bc0be90ea2f550afbc4ba3e4afc7da07df452f11

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page