semvec/pypi-packages huggingface dataset:
spatial-eggplant 0.2.3
Landmark-based transfer of spatial transcriptomics data
Requires Python: >=3.7

# eggplant - effortless generic GP landmark transfer

[![codecov](https://codecov.io/gh/almaan/eggplant/branch/publish/graph/badge.svg?token=NFJWGVK56D)](https://codecov.io/gh/almaan/eggplant)
[![Documentation Status](https://readthedocs.org/projects/spatial-eggplant/badge/?version=latest)](https://spatial-eggplant.readthedocs.io/en/latest/?badge=latest)


eggplant is a tool that transfers information from multiple different spatial
transcriptomics data sets to a single reference representing a common
coordinate framework (CCF).

The package is compatible with `scanpy` and its derivatives as well as with
`anndata`.

We refer to the
[Documentation](https://spatial-eggplant.readthedocs.io/en/latest/eggplant.html#)
for more information about installation and examples of use. You can also visit
the [github](https://github.com/almaan/eggplant) page to find instructions on
how to access example data sets and the associated manuscript.
cherrypy-jinja2 2.2
CherryPy tool to render output through Jinja2 templates

CherryPy-Jinja2
===============

CherryPy-Jinja2 is a simple CherryPy Tool to render output via Jinja2 templates.

Import `cherrypy_jinja2` to make the tool available in CherryPy's default toolbox.

Set `tools.jinja2.search_path` to a directory containing Jinja2 template files,
then attach the tool to exposed methods:

    class Root:
        @cherrypy.expose
        @cherrypy.tools.jinja2(template="index.html")
        def index(self):
            return {'message': "Hello"}
RTK-ODM-GPS 1.0.0
RTK calibrate GPS
Requires Python: >=3.6

### RTK校准GPS 使用说明

---

##### 1、运行环境（链接中含安装方法）

- [Ubuntu](https://releases.ubuntu.com/18.04/) >= 18.04
- [Python3](https://www.digitalocean.com/community/tutorials/ubuntu-18-04-python-3-zh) >= 3.6.9
- [Docker](https://docs.docker.com/engine/install/ubuntu/) >= 20.10.16
- [g++](https://www.cnblogs.com/dragonsuc/p/4342472.html) >= 7.5.0
- [OpenSfM](https://opensfm.org/docs/building.html)

##### 2、安装脚本程序

```
sudo pip3 install rtk_odm_gps
sudo pip3 install -r requirements.txt
```

##### 3、运行脚本程序

```
python3 ODM_SfM.py
--rtk=./RTK # RTK图像的目录，尚不支持子目录搜索
--gps=./GPS # RPS图像的目录，尚不支持子目录搜索
--dst=./out # 工作目录，存放输出的结果
--log=log.txt # 将屏幕输出保存到{dst}/log.txt
--cpu=3 # 最大并行计算/并发数；范围[1,cpu内核数]
--type=sift # 特征提取的类型；默认SIFT
--min=4000 # 每张图像特征点数的下限；默认4000
--quality=0.5 # 每张图像的特征粒度，越大特征越多约细致；默认0.5，范围(0,1]
```

> - 更多参数项目，详见：`python3 ODM_SfM.py --help`
>
> - 若`--log`功能失效，可尝试手动重定向，即在上述命令后添加`>> log.txt 2>&1`。例如：
>   - `python3 ODM_SfM.py --gps=GPS --rtk=RTK --dst=out >> out/log.txt 2>&1`
>
> - 首次运行程序时，docker会自动下载odm的镜像：需要联网，耗时较长。
>
> - 程序运行过程中需要sudo权限，会提示输入sudo密码。