causal-learn VS directory-structure

Compare causal-learn vs directory-structure and see what are their differences.

causal-learn

Causal Discovery in Python. It also includes (conditional) independence tests and score functions. (by py-why)
causal causal-discovery causal-inference Causality Python Graph Structure tetrad continous time-series hidden-causal confounder
Source Code
causal-learn.readthedocs.io
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directory-structure

:package: Print a directory tree structure in your Python code. (by gabrielstork)
Directory Structure Tree Emoji Folder File
Source Code
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causal-learn directory-structure
1 2
982 51
5.2% -
7.9 0.0
12 days ago over 2 years ago
Python Python
MIT License MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

causal-learn

Posts with mentions or reviews of causal-learn. We have used some of these posts to build our list of alternatives and similar projects.

directory-structure

Posts with mentions or reviews of directory-structure. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing causal-learn and directory-structure you can also consider the following projects:

dowhy - DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.

br4nch - br4nch - Data Structure Tree Builder for Python.

dodiscover - [Experimental] Global causal discovery algorithms

sections - Easy Python tree data structures

tfcausalimpact - Python Causal Impact Implementation Based on Google's R Package. Built using TensorFlow Probability.

Duplicate-Image-Finder - difPy - Python package for finding duplicate or similar images within folders

output-files - Output a tree of files and directories by providing an object. Especially useful for testing with real files.

looper - A resource list for causality in statistics, data science and physics

Structure_threader - A wrapper program to parallelize and automate runs of "Structure", "fastStructure" and "MavericK".

HumesGuillotine - Hume's Guillotine: Beheading the social pseudo-sciences with the Algorithmic Information Criterion for CAUSAL model selection.

Voila - Voila is a domain-specific language launched through CLI tool for operating with files and directories in massive amounts in a fast & reliable way.

causal-learn vs dowhy directory-structure vs br4nch causal-learn vs dodiscover directory-structure vs sections causal-learn vs tfcausalimpact directory-structure vs Duplicate-Image-Finder causal-learn vs sections directory-structure vs output-files causal-learn vs looper directory-structure vs Structure_threader causal-learn vs HumesGuillotine directory-structure vs Voila