semvec/pypi-packages huggingface dataset:
laura 0.0.2
**laura**: Local Auto-Regressive Average
Requires Python: >=3.6.0

# **laura**: Local Auto-Regressive Average

This repository contains the source code for the **L**ocal
**AU**to-**R**egressive **A**verage (LAURA) inverse solution as described by de
Peralta Menendez et al. (2001, 2004). The code is based on
[mne-python](https://mne.tools/), a powerful EEG library for
[python](https://python.org/).

Personally, I think this linear inverse solution finds the neural sources
underlying M/EEG measurements with great success and is a valuable option among
other inverse solutions such as *minimum norm estimates* and *(e)LORETA*.

# Dependencies
* [mne](https://mne.tools/stable/index.html)
* [scipy](https://scipy.org/)
* [numpy](https://numpy.org/)  

That's it!
<br/>

# Installation from PyPi
Use [pip](https://pip.pypa.io/en/stable/) to install laura and all its
dependencies from [PyPi](https://pypi.org/project/laura/):

```
pip install laura
```

<br/>

# Quick Start
The following code demonstrates how to use this package:

```
from laura import compute_laura

stc = compute_laura(evoked, forward)
stc.plot()
```
, where evoked is an instance of **mne.Evoked** and forward is an instance of
**mne.Forward**. For further explanation on mne and its objects please refer to
the [mne website](https://mne.tools/).

For a more comprehensive tutorial hop over to [this notebook!](tutorials/tutorial_1.ipynb)

# Feedback
Please leave your feedback and bug reports at lukas_hecker@web.de.

<br/>

# References
Please cite the authors of the LAURA inverse solution appropriately:

[1] Menendez, R. G. D. P., Andino, S. G., Lantz, G., Michel, C. M., &
    Landis, T. (2001). Noninvasive localization of electromagnetic epileptic
    activity. I. Method descriptions and simulations. Brain topography, 14(2),
    131-137.

[2] de Peralta Menendez, R. G., Murray, M. M., Michel, C. M., Martuzzi, R.,
& Andino, S. L. G. (2004). Electrical neuroimaging based on biophysical
constraints. Neuroimage, 21(2), 527-539.

<br/>

I would be happy if you would cite this package, too:

```
LAURA was calculated using the laura python package available at https://github.com/LukeTheHecker/laura.
```

# Limitations
The current implementation is limited to:

* fixed dipole orientations
* time-domain EEG data
  
Feel free to modify the code and start a pull request!

# Troubleshooting
* Having problems with the installation? Check the [package requirements](requirements.txt).
dnaseq-genbit 0.0.1
Computationally operate on DNA and RNA sequences
Requires Python: >=3.8

# GenBit

Operate on DNA/RNA genetic sequences using a computer, the same way protein biosynthesis would happen within a cell. For instance, a given DNA sequence can be converted into an RNA sequence, and then an amino acid sequence. The full name of the protein then generated can also be found. You can also find the complentary genetic sequence, of the non-coding strand involved.

## Coming Soon

- The ability to randomly mutate sequences
- Randomly generate sequences
- Finding the non-chemical name of the protein, and its functionality
- Building a system of proteins that can work together (protein simulations)

## Usage

Install the package with `pip install dnaseq-genbit`. Now, it can be imported with `import genbit`, and you now have access to all the methods in GenBit. Sequences are represented by strings, and it is these strings that are operated on.

### Example

```python
import genbit

aa_seq = 'VLSPADKTNVKAAWGKVGAHAGEYGAEALERMFLSFPTTKTYFPHFDLSHGSAQVKGHGKKVADALTNAVAHVDDMPNALSALSDLHAHKLRVDPVNFKLLSHCLLVTLAAHLPAEFTPAVHASLDKFLASVSTVLTSKYRXXVLSPADKTNVKAAWGKVGAHAGEYGAEALERMFLSFPTTKTYFPHFDLSHGSAQVKGHGKKVADALTNAVAHVDDMPNALSALSDLHAHKLRVDPVNFKLLSHCLLVTLAAHLPAEFTPAVHASLDKFLASVSTVLTSKYRXXVHFTAEEKAAVTSLWSKMNVEEAGGEALGRLLVVYPWTQRFFDSFGNLSSPSAILGNPKVKAHGKKVLTSFGDAIKNMDNLKPAFAKLSELHCDKLHVDPENFKLLGNVMVIILATHFGKEFTPEVQAAWQKLVSAVAIALAHKYXXVHFTAEEKAAVTSLWSKMNVEEAGGEALGRLLVVYPWTQRFFDSFGNLSSPSAILGNPKVKAHGKKVLTSFGDAIKNMDNLKPAFAKLSELHCDKLHVDPENFKLLGNVMVIILATHFGKEFTPEVQAAWQKLVSAVAIALAHKYXX'  # Amino Acid Sequence

rna_seq = genbit.amino_to_rna(aa_seq)  # RNA Sequence
words_amino_seq = genbit.chemical_name_amino_chain(aa_seq)  # Chemical Name of Amino Acid Sequence
dna_seq = genbit.chemical_name_to_dna(words_amino_seq)  # DNA Sequence
codon_dna_seq = genbit.codons(dna_seq)  # Codon Sequence
```
py-deployer 1.7.5
Lightweight package to execute zero-downtime deployment on Linux servers
Requires Python: >=3.6
Keywords: deployment python releases git zero-downtime ssh

# Py Deployer

Py Deployer is a lightweight package to execute zero-downtime deployment on **Linux servers**.

```bash
pydeploy -s prod
```

## ✨ Features

- Cross-technology deployments
- Simple configuration
- Zero downtime deployments
- Multiple environment management
- Release version management
- Use SSH protocol

#### ⚠ This package does not currently support after-deployment scripts

## 1️⃣ Installation

```bash
sudo pip3 install py-deployer
```

## 2️⃣ Configuration

Create the file `deploy/config.yaml` inside your project as following:

```yaml
# Example of file: ./deploy/config.yaml

deploy:
  # Shared files and folders (between releases)
  shared: [.env]

  # All available servers (SSH configuration)
  servers:
    dev:
      hostname: '10.56.12.0'
      port: 22
      user: 'dev_username'
      password: ~ # Ignore that if you use SSH keys
      deploy_path: '/server/application/path'
      stage: 'develop'
      branch: 'dev'
      identity_file: ~  # Ignore that if it stay in the default folder (~/.ssh)
      repository: ~     # Ignore that if you run pydeploy from a git project directory
      max_releases: 3
    # ...
    prod:
      hostname: '10.56.11.0'
      port: 22
      user: 'prod_username'
      password: ~ # Ignore that if you use SSH keys
      deploy_path: '/server/application/path'
      stage: 'production'
      branch: 'master'
      identity_file: ~  # Ignore that if it stay in the default folder (~/.ssh)
      repository: ~     # Ignore that if you run pydeploy from a git project directory
      max_releases: 3


```

## 3️⃣ Deployment

Deploy your application by running:

```bash
pydeploy -s <dev|stag|prod|...>
```

## Links

- [PyPi](https://pypi.org/project/py-deployer/)