semvec/pypi-packages huggingface dataset:
croppdf 0.1.1
A tool to crop white margins from PDF files
Requires Python: >=3.6

# Crop PDF

Automatically removes white margins from PDF files.

## Features

- Automatically detect and crop white margins from PDF files
- Process single or multi-page PDFs
- Option to export pages separately or as a single file
- Customizable margin settings
- Command-line interface for easy integration into workflows

## Installation

You can install PDF Margin Crop using pip:

```bash
pip install croppdf
```

## Usage

### Command Line Interface

After installation, you can use PDF Margin Crop from the command line:

```bash
croppdf input.pdf output.pdf [options]
```

Options:
- `-m MARGIN`, `--margin MARGIN`: Margin to leave around content (default: 0 pixels).
- `-s`, `--separate`: Export pages separately. The output filenames would look like output_page_1.pdf, output_page_2.pdf, etc.

Examples:

1. Crop a PDF with default settings:
   ```bash
   croppdf input.pdf output.pdf
   ```

2. Crop a PDF and add a 10-pixel margin:
   ```bash
   croppdf input.pdf output.pdf -m 10
   ```

3. Crop a PDF and export pages separately:
   ```bash
   croppdf input.pdf output.pdf -s
   ```

### Python API

You can also use PDF Margin Crop in your Python scripts:

```python
from croppdf import crop_pdf

# Crop a PDF
crop_pdf("input.pdf", "output.pdf", margin=10, separate_pages=False)
```

## Requirements

- Python 3.6+
- PyPDF2
- pdf2image
- numpy


## License

This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.

## Author

Yongyi Zang
diagram-eye 0.1.0
A library designed to generate and visualize eye diagrams for digital communication signals.
Requires Python: >=3.6

# diagram_eye

`diagram_eye` is a Python library designed to generate and visualize eye diagrams for digital communication signals. The library provides functions to create various types of filters, generate signals, and plot eye diagrams to analyze the quality of the signal transmission.

>>> It mainly comes with three functions. get_filter() , get_signal(),  drawFullEyeDiagram()

>>> get_filter(name,T,rolloff= None): 

    Generate a filter function.

    Parameters:
    name (str): The type of filter to generate ('rect', 'rc', 'rrc').
    T (float): Symbol period.
    rolloff (float, optional): Roll-off factor for 'rc' and 'rrc' filters.

    Returns:
    function: A function representing the specified filter.

    Available Filters:
    - 'rect': Rectangular filter.
    - 'rc': Raised cosine filter.
    - 'rrc': Root raised cosine filter.
    

>>>get_signal(data,g):


    Generate a signal by convolving the data with the provided filter.

    Parameters:
    data (array-like): Input binary data stream.
    g (function): Filter function.

    Returns:
    tuple:
        t (numpy.ndarray): Time vector.
        x (numpy.ndarray): Generated signal.

>>>def drawFullEyeDiagram(x):

    Generate and plot the eye diagram of the signal.

    Parameters:
    x (numpy.ndarray): Input signal.

    Returns:
    None. The function plots the eye diagram.




## Features

- Generate Rectangular, Raised Cosine, and Root Raised Cosine filters.
- Convolve input binary data streams with specified filters to create modulated signals.
- Visualize eye diagrams for analyzing signal integrity and performance.

## Sample usage:

  >>>import diagram_eye as eye
  >>>import numpy as np
  >>>Fs=10
  >>>T=1
  >>>N=10
  >>>b=np.random.randint(0,2,N)
  >>>data=2*b-1
  >>>t=np.arange(-3*T,3*T,1/Fs)
  >>>g=eye.get_filter('rc',T,rolloff=0.2)
  >>>t,x=eye.get_signal(data,g)
  >>>eye.drawFullEyeDiagram(x)

  

## Installation

You can install `diagram_eye` via pip:

```bash
pip install diagram_eye
uois-deu 0.1.0
A small utility made for UOIS to extract data from current database and creates demodata.
Requires Python: >=3.6

# uois_deu (database extraction utility)
## WARNING
Does not seem to be able to perform what it needs to through GQL, consider extracting data directly from database with this tool: https://github.com/KlementOndrej/uois_dataextraction
## Description
A small utility made for UOIS(https://github.com/hrbolek/_uois), extracts data from current database and creates demodata.

## How to run
Just run the main.py file.