semvec/pypi-packages huggingface dataset:
cfanalysis 0.1.13
Library to perform Combinatorial Fusion Analysis

A Combinatorial Fusion Analysis (CFA) to enhance Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) performance of ML models. CFA models show superior performance compared to most of the individual ML models. The CFA model architecture and the performance of CFA models on TDC and other internal datasets is presented on the GitHub repo. Significant enhancement suggests that CFA is a viable tool for improving ADMET ML model performance, offering promise for faster and more cost-effective drug development pipelines. Refer to the GitHub repository for example usage: https://github.com/mquazi/cfanalysis 
    
 
Link to the manuscript: Enhancing ADMET Property Models Performance through Combinatorial Fusion Analysis: https://chemrxiv.org/doi/full/10.26434/chemrxiv-2023-dh70x 
    
Note: Previously, the GitHub repository was hosted at github.com/FLIDM/CFA4DD, which is no longer active.
vyas-group-scripts 1.5.1
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Requires Python: >=3.9

# vyas_group_scripts

vyas_group_scripts is a python package meant to hold tools built in aiding the Shubham Vyas Research lab in completing repetitive tasks. Most use cases will involve installing the package as a tool through uv of pipx and using the command line tools.

## Installation and Updating

To install the command line tools using uv use the command below:

```bash
uv tool install vyas_group_scripts
```

to update the package using uv use the command below:
```bash
uv tool install vyas_group_scripts --upgrade
```

alternatively you can use pipx. To install using pipx run the command below:
```bash
pipx install vyas_group_scripts
```

To update the package using pipx use the following command:
 ```bash
pipx upgrade vyas_group_scripts
```

## Further Setup

Once installed run the command `pyvgs_test` in the terminal and enter the newly created "vgs_tests" directory for further set up instructions
and test files. It will have a document that walks you through the rest of the set up and exposes you to the core functionality.

In order for pygab and pyrab to correctly format batch files they need to know your account number. They read this account number from an environment variable `ACTNUM`. Ensure that you have set this environment variable.

There are other optional environment variables you can set below are their names, defaults, and what they change

- `DEFAULT_DFT_TIME`, 00:59:00,The default dft job time in a batch file.
- `DEFAULT_DFT_PROCESSORS`, 36, The default number of processors a DFT job will use

## Available Commands
All commands with a * next to their name have a help flag that can be accessed by passing the `-h` flag. This is not placed here to keep documentation succinct.
### pygab *

python generate all batch. This generates a batch file for all gjf, inp, and xyz files that match a pattern (match all by default).

### pyrab *

python run all batch. This runs all batch files in a directory that match a pattern (match all by default) and have a matching input file.

### pysqm

prints the queue for the just the user's jobs


### pysff *

python sort from folders. Copies input, output, and batch files from dft jobs in to organized directories.

### pyaif

apply in folders. applies a list of commands in all subfolders. If a command includes space it must be in quotes.