semvec/pypi-packages huggingface dataset:
paperplots 0.2.0
Camera ready machine learning plots with a Tensorboard-like API
License: MIT

# paperplots
Camera ready machine learning plots with a Tensorboard-like API

Ever felt like the tensorboard summary writer can do a bit more than just letting you monitor your training logs? Wouldn't it be nice if you could also directly get pretty paper-ready versions of your tensorboard logs? Paperplots does just this! 

- Record scalars in the exact same way as you do with [tensorboard summarywriter](https://pytorch.org/docs/stable/tensorboard.html) 
- Save your training data in easy to access pickle files
- Plot runs, whole experiments, and even compare different experiments
- Automatically calculate simple convenience transforms such as rolling averages and shaded error regions

[**Documentation**](Docs.md)

# Examples

## Writing Logs
```
writer = Writer(logdir=f'runs/algo', run_name=f'run1')

for i in range(iter):
	writer.add_scalar("loss", loss_value, i, ylabel="loss", xlabel="num iter", name="algo loss")

writer.close()

```

## Plotting Written Logs
```
plotter = Plotter(logdir='runs')

# Plotting runs
plotter.plot_run(run_name="algo/run1")

# Compare two runs
plotter.plot_run(run_name=["algo/run0", "algo/run1"])

# Plot an average over all runs in the experiment
plotter.plot_experiment(exp_name="algo")

# Compare two experiments
plotter.plot_experiment(exp_name=["algo1", "algo2"])
```

![Plots](test_plots/plots.png)
noaa-wildfires 0.0.5
Download wildfires data from NOAA satellites
License: MIT

### Other resources

* Docs: [palewi.re/docs/noaa-wildfires/](https://palewi.re/docs/noaa-wildfires/)
* Issues: [github.com/datadesk/noaa-wildfires/issues](https://github.com/datadesk/noaa-wildfires/issues)
* Packaging: [pypi.python.org/pypi/noaa-wildfires](https://pypi.python.org/pypi/noaa-wildfires)
* Testing: [github.com/datadesk/noaa-wildfires/actions](https://github.com/datadesk/noaa-wildfires/actions)
py-raytrace 0.5.2
A simple ray tracing application
License: MIT


# Raytrace

Py-Raytrace is a simple ray tracing application that creates realistic images by simulating the behavior of light rays in a virtual scene.

## Installation

You can install Raytrace using `pip`:

```bash
pip install py-raytrace
Usage
After installation, you can run Py-Raytrace from the command line:
```
```bash
ray
```

or

```bash
raytrace
```

or
```bash
py-raytrace
``` 

This command will launch the ray tracing process and generate a rendered image based on the provided scene and camera parameters.

## Configuration

Raytrace allows you to configure the scene and camera parameters in the raytrace.py script. You can customize the positions and properties of spheres, lighting, and the floor to create different scenes.

Additionally, the script provides a graphical interface using matplotlib with sliders to adjust the camera angles interactively.

## Dependencies

Py-Raytrace depends on the following Python packages:

```bash
numpy
Pillow (PIL)
tqdm
matplotlib
```
These dependencies will be automatically installed when you install Py-Raytrace using pip.


## License

This project is licensed under the MIT License - see the LICENSE file for details.

## Author

Pranav A: [Github](https://github.com/pranavnasrani/)