semvec/pypi-packages huggingface dataset:
DLSim 0.2.12
DLSim is an open-source, cross-platform, lightweight, and fast Python traffic assignment tool adopted and modified from ASU TransAI Lab

"Dynamic Traffic Simulation Package with Multi-Resolution Modelling" (DLSim-MRM) is an open source, high-fidelity multi-resolution (i.e., macroscopic, mesoscopic, and microscopic simulation) traffic simulation package which users jointly apply varying temporal and spatial resolutions to solve a single question or set of questions that mirror the physical world with complex intersections. Users can perform traffic assignments and feed results from one model to another while maintaining consistency between the model assumptions. DLSim-MRM typically takes the following steps for simulation based on [General Modeling Network Specification (GMNS)](https://github.com/zephyr-data-specs/GMNS) format:

1. Use demand forecasting models to determine overall trip patterns in a regional network, including trip generation, trip distribution, mode split, and initial O-D matrices.
2. Use mesoscopic simulation-based dynamic traffic assignment (DTA) to realistically assign traffic to the network by accounting for strategic traveler behavior.
3. Use microscopic analysis of traffic at the corridor level or subnetwork level.

DLSim-MRM uses 3 open-source packages; [OSM2GMNS](https://github.com/asu-trans-ai-lab/OSM2GMNS), [Path4GMNS](https://github.com/asu-trans-ai-lab/Path4GMNS) and [Vol2Timing](https://github.com/asu-trans-ai-lab/Vol2Timing) with the additional developments along the multi-resolution modelling and dyanmic traffic simulation.

-OSM2GMNS can help users easily convert networks from OpenStreetMap to .csv files with standard GMNS format for visualization, traffic simulation and planning purpose.

-Path4GMNS is an open-source AMS library for efficiently macroscopic and mesoscopic traffic assignment based on General Modeling Network Specification (GMNS) format.

-Vol2Timing is a python tool aims to offer a light-weight computational engine to generate optimize signal control timing data, and analyze the effectiveness of signal control strategies.

## Installation:

DLSim has been published on [PyPI](https://pypi.org/project/dlsim/), and can be installed by using package manager [pip](https://pip.pypa.io/en/stable/) to install DLSim.

```
pip install DLSim
```

If you need a specific version of DLSim, say, 0.2.1,

```
$ pip install dlsim==0.2.11
```

## Usage

Find the shortest path (based on distance) and output it in the format of a sequence of node/link IDs.

```
from DLSim import DLSim

# load the DLSim class
DL = DLSim()

# check the working directory
DL.check_working_directory()

# check all the required files exist
DL.check_DLSim_input_files()

# load and update settings
DL.DLSim_settings

# perform kernel network assignment simulation
DL.perform_kernel_network_assignment_simulation()



```

## Contributing

Pull requests are welcome. For major changes, please [open an issue](https://github.com/asu-trans-ai-lab/DLSim-MRM) first to discuss what you would like to change.

## License

[License](https://github.com/asu-trans-ai-lab/DLSim)
RandomCarrot 1.0
RandomCarrot is a module for Python that can generate random numbers, letters or something else.

# RandomCarrot (Carrot)

Carrot is a module for Python also know as RandomCarrot.

## Installation

Use the package manager [pip](https://pip.pypa.io/en/stable/) to install Carrot.

```bash
pip install RandomCarrot
```

## Usage

Importing is very easy in Carrot. All you need to do is type: 
 ```Python
import carrot
```
To display random numbers type:
 ```Python
carrot.randomnumber()
```
To display random letters:
 ```Python
carrot.randomletters()
```
You can adjust length for letters by typing: 
```Python
carrot(length=)
```
To display both numbers and letters:
 ```Python
carrot.both()
``` 
(again you can adjust length by typing the same text like in letters)

## Developer Usage

If you want to use developer commands, feel free to use them! Everyone can use them, even if you just want to see how do they work.
If you want to try using ``carrot.randomnumber()`` like a developer, here is the code:
 ```Python
carrot.random_number_generator()
```
If you want to try using ``carrot.randomletter()`` like a developer, here is the code:
 ```Python
carrot.random_letters_generator()
```
And if you want to use ``carrot.both`` like a developer, here is the command:
 ```Python
carrot.both_numbers_letters_generator()
```
Use them knowing these commands can work not as they used to. Happy coding!
## License

[MIT](https://choosealicense.com/licenses/mit/)
animatebar 1.0
A Python package to generate animated bar plots with Plotly


# animatebar
The animate_bar function generates an animated bar plot using Plotly, displaying changes in bar heights over time. It takes in data representing the initial and final heights of the bars, along with the duration of the animation. The function creates an interactive plot where users can see the bars gradually transition from their initial heights to their final heights, providing a visually appealing way to visualize changes in data over time.



## version
1.0
## Authors

- [@RANJIT_MAITY](https://www.linkedin.com/in/ranjit-maity-75204a131/)


## Reales Date 
 16-03-2024
 
 


## Badges

[![MIT License](https://img.shields.io/apm/l/atomic-design-ui.svg?)](https://github.com/tterb/atomic-design-ui/blob/master/LICENSEs)
[![GPLv3 License](https://img.shields.io/badge/License-GPL%20v3-yellow.svg)](https://opensource.org/licenses/)
[![AGPL License](https://img.shields.io/badge/license-AGPL-blue.svg)](http://www.gnu.org/licenses/agpl-3.0)


##  About Author
I Am Ranjit From INDIA, a Certified Data scientist , Data Engineer by professional  with hands-on experience of more than 2Years ,on ML> NLP> Data mining > Neural Networks > ModeL Deployment>ETL.
 Give me raw data and I'll return you insights, problems to be rectified and enhancements to achieve the target. I am always on the lookout for new projects to work And 
Am Always Happy â˜» To Play With Data


##  Links

[![linkedin](https://img.shields.io/badge/linkedin-0A66C2?style=for-the-badge&logo=linkedin&logoColor=white)](https://www.linkedin.com/in/ranjit-maity-75204a131/)
[![twitter](https://img.shields.io/badge/twitter-1DA1F2?style=for-the-badge&logo=twitter&logoColor=white)](https://twitter.com/ranjitmaity95)