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fastplotlib-0.1.0a9
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مشاهده بیشترتوضیحات
A fast plotting library built using the pygfx render engine
| ویژگی | مقدار |
|---|---|
| سیستم عامل | - |
| نام فایل | fastplotlib-0.1.0a9 |
| نام | fastplotlib |
| نسخه کتابخانه | 0.1.0a9 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | Kushal Kolar |
| ایمیل نویسنده | - |
| آدرس صفحه اصلی | https://github.com/kushalkolar/fastplotlib |
| آدرس اینترنتی | https://pypi.org/project/fastplotlib/ |
| مجوز | Apache 2.0 |
# fastplotlib
[](https://badge.fury.io/py/fastplotlib)
[](https://fastplotlib.readthedocs.io/en/latest/?badge=latest)
[](https://gitter.im/fastplotlib/community?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge)
[**Installation**](https://github.com/kushalkolar/fastplotlib#installation) | [**GPU Drivers**](https://github.com/kushalkolar/fastplotlib#install-vulkan-drivers) | [**Examples**](https://github.com/kushalkolar/fastplotlib#examples)
A fast plotting library built using the [`pygfx`](https://github.com/pygfx/pygfx) render engine utilizing [Vulkan](https://en.wikipedia.org/wiki/Vulkan) via WGPU, so it is very fast! `fastplotlib` is focussed on very fast interactive plotting in the notebook using an expressive API. It also works within desktop applications using `glfw` or `Qt`.
`fastplotlib` is currently in the **early alpha stage with breaking changes every ~week**, but you're welcome to try it out or contribute! See our [Roadmap for 2023](https://github.com/kushalkolar/fastplotlib/issues/55).
**Documentation**: http://fastplotlib.readthedocs.io/
The docs are not entirely thorough, we recommend the example notebooks to get started.
Questions, ideas? Post an issue or [chat on gitter](https://gitter.im/fastplotlib/community?utm_source=share-link&utm_medium=link&utm_campaign=share-link).
# Examples
**See the examples directory. Start out with `simple.ipynb`.**
### Neuroscience usecase demonstrating some of fastplotlib's capabilities
https://user-images.githubusercontent.com/9403332/210304485-e554b648-50b4-4243-b292-a9ed30514a2d.mp4
### Simple image plot
```python
from fastplotlib import Plot
import numpy as np
plot = Plot()
data = np.random.rand(512, 512)
plot.add_image(data=data)
plot.show()
```
### Fast image updates
```python
from fastplotlib import Plot
import numpy as np
plot = Plot()
data = np.random.rand(512, 512)
image = plot.image(data=data)
def update_data():
new_data = np.random.rand(512, 512)
image.data = new_data
plot.add_animations(update_data)
plot.show()
```
### Interactivity
This is all in the notebook and non-blocking!
### Image widget
Interactive visualization of large imaging datasets in the notebook.
# Installation
Install using `pip`.
```bash
pip install fastplotlib
```
**Installing `simplejpeg` is recommended for faster plotting in notebooks using remote frame buffer. You will need C compilers to install it:**
```bash
pip install simplejpeg
```
Clone or download the repo to try the examples
```bash
# clone the repo
git clone https://github.com/kushalkolar/fastplotlib.git
# cd into examples and launch jupyter lab
cd fastplotlib/examples
jupyter lab
```
**Note:** `fastplotlib` and `pygfx` are fast evolving projects, the version available through pip might be outdated, you will need to follow the "For Development" instructions below if you want the latest features. You can find the release history on pypi here: https://pypi.org/project/fastplotlib/#history
### For Development
```bash
git clone https://github.com/kushalkolar/fastplotlib.git
cd fastplotlib
pip install -r requirements.txt
pip install -e .
# try the examples
cd examples
jupyter lab
```
## Install Vulkan drivers
You will need a GPU that supports Vulkan (integrated GPUs in CPUs are usually fine). Generally if your GPU is from 2017 or later it should support Vulkan.
For more information see: https://wgpu-py.readthedocs.io/en/stable/start.html#platform-requirements
### Windows:
Vulkan should be installed by default on Windows 11, but you will need to install your GPU manufacturer's driver package (Nvidia or AMD). If you have an integrated GPU within your CPU, you might still need to install a driver package too, check your CPU manufacturer's info. We recommend installing C compilers so that you can install `simplejpeg` which improves remote frame buffer performance in notebooks.
### Linux:
Debian based distros:
```bash
sudo apt install mesa-vulkan-drivers
# for better performance with the remote frame buffer install libjpeg-turbo
sudo apt install libjpeg-turbo
```
For other distros install the appropriate vulkan driver package, and optionally the corresponding `libjpeg-turbo` package for better remote-frame-buffer performance in jupyter notebooks.
### Mac OSX:
As far as I know, WGPU uses Metal instead of Vulkan on Mac. I think you will need at least Mac OSX 10.13.
# Gallery
### Extremely fast image updates, 5 x 5 gridplot
https://www.youtube.com/embed/-_0Gp_EqepI
### Very fast image updates with some synced controllers
https://user-images.githubusercontent.com/9403332/165678225-dcf3b401-86a5-4df5-a9e5-dc65bdb0443a.mp4
### 4x Grid of Scatter plots, 1.2 million points each
[https://user-images.githubusercontent.com/9403332/165677576-a0aa2d0f-a201-4e0e-91bd-aed800f775ee.mp4](https://www.youtube.com/watch?v=j_gwi-Wf1Ao)
### Lineplot
https://user-images.githubusercontent.com/9403332/165678270-aea65a83-6cc1-4edc-981c-4857eaf293c7.mp4
نیازمندی
| مقدار | نام |
|---|---|
| - | numpy |
| >=0.1.10 | pygfx |
| - | jupyterlab |
| - | jupyter-rfb |
زبان مورد نیاز
| مقدار | نام |
|---|---|
| >=3.8 | Python |
نحوه نصب
نصب پکیج whl fastplotlib-0.1.0a9:
pip install fastplotlib-0.1.0a9.whl
نصب پکیج tar.gz fastplotlib-0.1.0a9:
pip install fastplotlib-0.1.0a9.tar.gz