semvec/pypi-packages huggingface dataset:
hypersindy 0.0.4
HyperSINDy, a package to discover RDEs from time series data.
Requires Python: >=3.7

# HyperSINDy
This repository is the official implementation of HyperSINDy, first introduced in [HyperSINDy: Deep Generative Modeling of Nonlinear Stochastic Governing Equations](). 


## Requirements
All the requirements are contained in the environment.yml file\\
To install the requirements, run:
```
conda env create -f environment.yml
```

Then, activate the conda environment:
```
conda activate hypersindy
```

Or, with some conda environment that can run Python 3.9, you can manually install
the dependencies:
```
conda install scipy seaborn tensorboard matplotlib scikit-learn pandas jupyterlab pip
pip3 install pysindy torch==1.12.0 torchvision
```

## Installation
After installing dependencies, you can install hypersindy:
```
pip3 install hypersindy
```

## Example use case
See example.py as well.
``
python3

from hypersindy.library import Library
from hypersindy.net import Net
from hypersindy.trainer import Trainer
from hypersindy.dataset import SyntheticDataset
from hypersindy.utils import set_random_seed

set_random_seed(0)
device = 2
x_dim = 3
z_dim = 6
data_path = 'x_train.npy'

library = Library(x_dim)
net = Net(library, z_dim).to(device)
dataset = SyntheticDataset(library, fpath=data_path)
trainer = Trainer(net, library, "runs/1", "runs/1.pt", device=device)
trainer.train(dataset)

equations
results
``

Results can be viewed in tensorboard.
``
tensorboard --logdir="runs"
``

## Paper
To reproduce results from the paper, go to the paper folder and view the README there.
``
cd paper
``
ip2domains 0.1.2
Scans IP addresses and finds domains
Requires Python: >=3.11,<4.0

# ip2domains

Scans IP addresses and finds domains. Domain names are extracted from SSL certificates. This method does not guarantee 100% finding of all domains. You can also use the method of obtaining a domain name through a reverse DNS lookup, but 99% of domains do not contain a PTR record.

The reason for developing this tool was that many Internet services provide unreliable results:

![image](https://github.com/s3rgeym/ip2domains/assets/12753171/d0f5728c-c9ff-480f-b830-13595b386c06)

Installation:

```bash
pip install ip2domains
```

Usage:

```bash
# help
$ ip2domains -h

# Scan domains
# KLM is sucks. Don't use these f*gots. Give me back my money, assholes!
$ echo 171.21.120.0/22 | ip2domains --no-banner

# List unique domains
$ echo 171.21.120.0/22 | ip2domains --no-banner | jq -r '.domains[]' | sort | uniq

# Remember that not all domains listed in the certificate actually use this IP
$ dig +short af-klm.com
171.21.122.81

$ dig +short bluebiz.com
52.166.78.97
```