Skip to main content

latent_experiments

Python package for running experiments on latent spaces of neural networks

Installation

pip install latent-experiments

Usage

import latent_experiments as le


# Run experiments on a simple dataset
outcome_diff_df = run_latent_experiments(
    data,
    columns_to_match=columns_to_match,
    outcome_var=outcome_var,
    match_threshold=0.8,
)

Metadata

Release files for latent-experiments 0.0.7

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for latent-experiments 0.0.7
File Size Uploaded Provenance
latent_experiments-0.0.7.tar.gz 3.3 kB Without provenance Details

Built distribution (wheel)

Table of built distributions (wheels) for latent-experiments 0.0.7
File Interpreter ABI Platform
latent_experiments-0.0.7-py3-none-any.whl Python 3 none any Details

Total release size: 6.8 kB

Release files / latent_experiments-0.0.7.tar.gz

Download URL latent_experiments-0.0.7.tar.gz
Size 3.3 kB
Tags Source
SHA-256 checksum
How to use checksums
1f559e397725fa57ce14b3bcc5ba2c95ab3e466e50acf951b151a6577b07b15c
BLAKE2b-256 checksum
How to use checksums
5688ee256415f8ffe2ce80846e7b297fdf265cd6f3dc7e0a27842b233bc6f3f5
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/5.0.0 CPython/3.9.18

Release files / latent_experiments-0.0.7-py3-none-any.whl

Download URL latent_experiments-0.0.7-py3-none-any.whl
Size 3.6 kB
Tags Python 3
SHA-256 checksum
How to use checksums
8c2e36eaf420a02bb4d4261fcd4abf8d9fbd481d478316103bb3742ebf2971b6
BLAKE2b-256 checksum
How to use checksums
a7f4532861557a11de5e80018ee1c42b6bb3b1af1c792dea310bf70c9d5befb2
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/5.0.0 CPython/3.9.18

Security for latent-experiments 0.0.7

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

No provenance found

None of the files in this release were uploaded with provenance metadata.

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

To learn more about protecting yourself from malicious actors, visit our package security documentation.

Release history Release notifications | RSS feed

This release

0.0.7 This release

2 release files No provenance

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page