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新建项目
Signed-off-by: aboutlong <aboutlong@qq.com>
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README.en.md
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# pyminer
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#### Description
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{**When you're done, you can delete the content in this README and update the file with details for others getting started with your repository**}
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#### Software Architecture
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Software architecture description
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#### Installation
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|
||||
1. xxxx
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2. xxxx
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3. xxxx
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#### Instructions
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1. xxxx
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2. xxxx
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3. xxxx
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#### Contribution
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1. Fork the repository
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2. Create Feat_xxx branch
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3. Commit your code
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||||
4. Create Pull Request
|
||||
|
||||
|
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#### Gitee Feature
|
||||
|
||||
1. You can use Readme\_XXX.md to support different languages, such as Readme\_en.md, Readme\_zh.md
|
||||
2. Gitee blog [blog.gitee.com](https://blog.gitee.com)
|
||||
3. Explore open source project [https://gitee.com/explore](https://gitee.com/explore)
|
||||
4. The most valuable open source project [GVP](https://gitee.com/gvp)
|
||||
5. The manual of Gitee [https://gitee.com/help](https://gitee.com/help)
|
||||
6. The most popular members [https://gitee.com/gitee-stars/](https://gitee.com/gitee-stars/)
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49
README.md
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README.md
@ -1,39 +1,20 @@
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# pyminer
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# PyMiner
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#### 介绍
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{**以下是码云平台说明，您可以替换此简介**
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码云是 OSCHINA 推出的基于 Git 的代码托管平台（同时支持 SVN）。专为开发者提供稳定、高效、安全的云端软件开发协作平台
|
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无论是个人、团队、或是企业，都能够用码云实现代码托管、项目管理、协作开发。企业项目请看 [https://gitee.com/enterprises](https://gitee.com/enterprises)}
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#### 描述
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PyMiner一款数据分析工具,目的是使pandas\sklearn的操作进行可视化，项目许可遵循MIT 开源协议。
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#### 软件架构
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软件架构说明
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#### 技术说明
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项目开发环境基于Window 10 X64，使用Python3.8+PyQt5.15+Pycharm进行技术开发。
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#### 安装
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1. 下载项目源码
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2. 安装python并打开命令行工具，使用python -m pip -r requirements.txt 导入python包
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3. 调用python 执行目录下pyminer.py，例如python安装在C盘根目录下，可以在cmd命令行中执行：C:\python\python.exe C:\PyMiner\pyminer.py
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4. 此外，你也可以使用pyinstaller进行编译后使用，编译语句：pyinstaller -i logo.ico -w pyminer.py
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#### 安装教程
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#### 联系我
|
||||
|
||||
1. xxxx
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2. xxxx
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3. xxxx
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#### 使用说明
|
||||
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||||
1. xxxx
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2. xxxx
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||||
3. xxxx
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||||
|
||||
#### 参与贡献
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||||
|
||||
1. Fork 本仓库
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||||
2. 新建 Feat_xxx 分支
|
||||
3. 提交代码
|
||||
4. 新建 Pull Request
|
||||
|
||||
|
||||
#### 码云特技
|
||||
|
||||
1. 使用 Readme\_XXX.md 来支持不同的语言，例如 Readme\_en.md, Readme\_zh.md
|
||||
2. 码云官方博客 [blog.gitee.com](https://blog.gitee.com)
|
||||
3. 你可以 [https://gitee.com/explore](https://gitee.com/explore) 这个地址来了解码云上的优秀开源项目
|
||||
4. [GVP](https://gitee.com/gvp) 全称是码云最有价值开源项目，是码云综合评定出的优秀开源项目
|
||||
5. 码云官方提供的使用手册 [https://gitee.com/help](https://gitee.com/help)
|
||||
6. 码云封面人物是一档用来展示码云会员风采的栏目 [https://gitee.com/gitee-stars/](https://gitee.com/gitee-stars/)
|
||||
1. QQ:454017698
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||||
2. 邮箱：aboutlong@qq.com
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0
__init__.py
Normal file
0
__init__.py
Normal file
20
class.csv
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20
class.csv
Normal file
@ -0,0 +1,20 @@
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Name,Sex,Age,Height,Weight
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Alfred,M,14,69,112.5
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Alice,F,13,56.5,84
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Barbara,F,13,65.3,98
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Carol,F,14,62.8,102.5
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Henry,M,14,63.5,102.5
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James,M,12,57.3,83
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Jane,F,12,59.8,84.5
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Janet,F,15,62.5,112.5
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Jeffrey,M,13,62.5,84
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John,M,12,59,99.5
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Joyce,F,11,51.3,50.5
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Judy,F,14,64.3,90
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Louise,F,12,56.3,77
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Mary,F,15,66.5,112
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Philip,M,16,72,150
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Robert,M,12,64.8,128
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Ronald,M,15,67,133
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Thomas,M,11,57.5,85
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William,M,15,66.5,112
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|
1697
pyminer.py
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1697
pyminer.py
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File diff suppressed because it is too large
Load Diff
0
pyminer/__init__.py
Normal file
0
pyminer/__init__.py
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BIN
pyminer/__pycache__/__init__.cpython-38.pyc
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BIN
pyminer/__pycache__/__init__.cpython-38.pyc
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Binary file not shown.
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pyminer/config/settings.json
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64
pyminer/config/settings.json
Normal file
@ -0,0 +1,64 @@
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{
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"lang": {
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"zh_cn": true,
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"English": false
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},
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"theme": [
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{
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"name": "default",
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"index":1,
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"detail": {
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"fontfamily": ["微软雅黑", "simhei"],
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"color":"",
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"font-size":14
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}
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},
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{
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"name": "dark",
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"index":2,
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"detail": {
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"fontfamily": ["微软雅黑", "simhei"]
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}
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},
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{
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"name": "fushion",
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"index":3,
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"detail": {
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"fontfamily": ["微软雅黑", "simhei"]
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}
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},
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{
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"name": "windows",
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"index":4,
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"detail": {
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"fontfamily": ["微软雅黑", "simhei"]
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}
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}
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],
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"core": {
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"version": "1.0_20200423",
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"website": "http://www.py2cn.com",
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"author":"lixianglong",
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"mail":"aboutlong@qq.com"
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},
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"table": {
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"alternatingrowcolors": false
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},
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"interpreter": [{
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"name":"python",
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"version":"3.8.2",
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"path":"c:/patata/python",
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"install_path":"c:/patata/python",
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"pip_index":1,
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"pip_install_option":"only_download",
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"is_default":true
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}],
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"project": [{
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"name":"demo",
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"location":"c:/patata/patata/workspace/demo",
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"description":""
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}],
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"character_set":"utf-8",
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"auto_start":false,
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"workspace":"c:/patata/patata/workspace"
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}
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BIN
pyminer/features/datasets/TitanicData.xls
Normal file
BIN
pyminer/features/datasets/TitanicData.xls
Normal file
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1036
pyminer/features/datasets/air_quality_no2.csv
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1036
pyminer/features/datasets/air_quality_no2.csv
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Load Diff
508
pyminer/features/datasets/boston_house_prices.csv
Normal file
508
pyminer/features/datasets/boston_house_prices.csv
Normal file
@ -0,0 +1,508 @@
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506,13,,,,,,,,,,,,
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"CRIM","ZN","INDUS","CHAS","NOX","RM","AGE","DIS","RAD","TAX","PTRATIO","B","LSTAT","MEDV"
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||||
0.00632,18,2.31,0,0.538,6.575,65.2,4.09,1,296,15.3,396.9,4.98,24
|
||||
0.02731,0,7.07,0,0.469,6.421,78.9,4.9671,2,242,17.8,396.9,9.14,21.6
|
||||
0.02729,0,7.07,0,0.469,7.185,61.1,4.9671,2,242,17.8,392.83,4.03,34.7
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||||
0.03237,0,2.18,0,0.458,6.998,45.8,6.0622,3,222,18.7,394.63,2.94,33.4
|
||||
0.06905,0,2.18,0,0.458,7.147,54.2,6.0622,3,222,18.7,396.9,5.33,36.2
|
||||
0.02985,0,2.18,0,0.458,6.43,58.7,6.0622,3,222,18.7,394.12,5.21,28.7
|
||||
0.08829,12.5,7.87,0,0.524,6.012,66.6,5.5605,5,311,15.2,395.6,12.43,22.9
|
||||
0.14455,12.5,7.87,0,0.524,6.172,96.1,5.9505,5,311,15.2,396.9,19.15,27.1
|
||||
0.21124,12.5,7.87,0,0.524,5.631,100,6.0821,5,311,15.2,386.63,29.93,16.5
|
||||
0.17004,12.5,7.87,0,0.524,6.004,85.9,6.5921,5,311,15.2,386.71,17.1,18.9
|
||||
0.22489,12.5,7.87,0,0.524,6.377,94.3,6.3467,5,311,15.2,392.52,20.45,15
|
||||
0.11747,12.5,7.87,0,0.524,6.009,82.9,6.2267,5,311,15.2,396.9,13.27,18.9
|
||||
0.09378,12.5,7.87,0,0.524,5.889,39,5.4509,5,311,15.2,390.5,15.71,21.7
|
||||
0.62976,0,8.14,0,0.538,5.949,61.8,4.7075,4,307,21,396.9,8.26,20.4
|
||||
0.63796,0,8.14,0,0.538,6.096,84.5,4.4619,4,307,21,380.02,10.26,18.2
|
||||
0.62739,0,8.14,0,0.538,5.834,56.5,4.4986,4,307,21,395.62,8.47,19.9
|
||||
1.05393,0,8.14,0,0.538,5.935,29.3,4.4986,4,307,21,386.85,6.58,23.1
|
||||
0.7842,0,8.14,0,0.538,5.99,81.7,4.2579,4,307,21,386.75,14.67,17.5
|
||||
0.80271,0,8.14,0,0.538,5.456,36.6,3.7965,4,307,21,288.99,11.69,20.2
|
||||
0.7258,0,8.14,0,0.538,5.727,69.5,3.7965,4,307,21,390.95,11.28,18.2
|
||||
1.25179,0,8.14,0,0.538,5.57,98.1,3.7979,4,307,21,376.57,21.02,13.6
|
||||
0.85204,0,8.14,0,0.538,5.965,89.2,4.0123,4,307,21,392.53,13.83,19.6
|
||||
1.23247,0,8.14,0,0.538,6.142,91.7,3.9769,4,307,21,396.9,18.72,15.2
|
||||
0.98843,0,8.14,0,0.538,5.813,100,4.0952,4,307,21,394.54,19.88,14.5
|
||||
0.75026,0,8.14,0,0.538,5.924,94.1,4.3996,4,307,21,394.33,16.3,15.6
|
||||
0.84054,0,8.14,0,0.538,5.599,85.7,4.4546,4,307,21,303.42,16.51,13.9
|
||||
0.67191,0,8.14,0,0.538,5.813,90.3,4.682,4,307,21,376.88,14.81,16.6
|
||||
0.95577,0,8.14,0,0.538,6.047,88.8,4.4534,4,307,21,306.38,17.28,14.8
|
||||
0.77299,0,8.14,0,0.538,6.495,94.4,4.4547,4,307,21,387.94,12.8,18.4
|
||||
1.00245,0,8.14,0,0.538,6.674,87.3,4.239,4,307,21,380.23,11.98,21
|
||||
1.13081,0,8.14,0,0.538,5.713,94.1,4.233,4,307,21,360.17,22.6,12.7
|
||||
1.35472,0,8.14,0,0.538,6.072,100,4.175,4,307,21,376.73,13.04,14.5
|
||||
1.38799,0,8.14,0,0.538,5.95,82,3.99,4,307,21,232.6,27.71,13.2
|
||||
1.15172,0,8.14,0,0.538,5.701,95,3.7872,4,307,21,358.77,18.35,13.1
|
||||
1.61282,0,8.14,0,0.538,6.096,96.9,3.7598,4,307,21,248.31,20.34,13.5
|
||||
0.06417,0,5.96,0,0.499,5.933,68.2,3.3603,5,279,19.2,396.9,9.68,18.9
|
||||
0.09744,0,5.96,0,0.499,5.841,61.4,3.3779,5,279,19.2,377.56,11.41,20
|
||||
0.08014,0,5.96,0,0.499,5.85,41.5,3.9342,5,279,19.2,396.9,8.77,21
|
||||
0.17505,0,5.96,0,0.499,5.966,30.2,3.8473,5,279,19.2,393.43,10.13,24.7
|
||||
0.02763,75,2.95,0,0.428,6.595,21.8,5.4011,3,252,18.3,395.63,4.32,30.8
|
||||
0.03359,75,2.95,0,0.428,7.024,15.8,5.4011,3,252,18.3,395.62,1.98,34.9
|
||||
0.12744,0,6.91,0,0.448,6.77,2.9,5.7209,3,233,17.9,385.41,4.84,26.6
|
||||
0.1415,0,6.91,0,0.448,6.169,6.6,5.7209,3,233,17.9,383.37,5.81,25.3
|
||||
0.15936,0,6.91,0,0.448,6.211,6.5,5.7209,3,233,17.9,394.46,7.44,24.7
|
||||
0.12269,0,6.91,0,0.448,6.069,40,5.7209,3,233,17.9,389.39,9.55,21.2
|
||||
0.17142,0,6.91,0,0.448,5.682,33.8,5.1004,3,233,17.9,396.9,10.21,19.3
|
||||
0.18836,0,6.91,0,0.448,5.786,33.3,5.1004,3,233,17.9,396.9,14.15,20
|
||||
0.22927,0,6.91,0,0.448,6.03,85.5,5.6894,3,233,17.9,392.74,18.8,16.6
|
||||
0.25387,0,6.91,0,0.448,5.399,95.3,5.87,3,233,17.9,396.9,30.81,14.4
|
||||
0.21977,0,6.91,0,0.448,5.602,62,6.0877,3,233,17.9,396.9,16.2,19.4
|
||||
0.08873,21,5.64,0,0.439,5.963,45.7,6.8147,4,243,16.8,395.56,13.45,19.7
|
||||
0.04337,21,5.64,0,0.439,6.115,63,6.8147,4,243,16.8,393.97,9.43,20.5
|
||||
0.0536,21,5.64,0,0.439,6.511,21.1,6.8147,4,243,16.8,396.9,5.28,25
|
||||
0.04981,21,5.64,0,0.439,5.998,21.4,6.8147,4,243,16.8,396.9,8.43,23.4
|
||||
0.0136,75,4,0,0.41,5.888,47.6,7.3197,3,469,21.1,396.9,14.8,18.9
|
||||
0.01311,90,1.22,0,0.403,7.249,21.9,8.6966,5,226,17.9,395.93,4.81,35.4
|
||||
0.02055,85,0.74,0,0.41,6.383,35.7,9.1876,2,313,17.3,396.9,5.77,24.7
|
||||
0.01432,100,1.32,0,0.411,6.816,40.5,8.3248,5,256,15.1,392.9,3.95,31.6
|
||||
0.15445,25,5.13,0,0.453,6.145,29.2,7.8148,8,284,19.7,390.68,6.86,23.3
|
||||
0.10328,25,5.13,0,0.453,5.927,47.2,6.932,8,284,19.7,396.9,9.22,19.6
|
||||
0.14932,25,5.13,0,0.453,5.741,66.2,7.2254,8,284,19.7,395.11,13.15,18.7
|
||||
0.17171,25,5.13,0,0.453,5.966,93.4,6.8185,8,284,19.7,378.08,14.44,16
|
||||
0.11027,25,5.13,0,0.453,6.456,67.8,7.2255,8,284,19.7,396.9,6.73,22.2
|
||||
0.1265,25,5.13,0,0.453,6.762,43.4,7.9809,8,284,19.7,395.58,9.5,25
|
||||
0.01951,17.5,1.38,0,0.4161,7.104,59.5,9.2229,3,216,18.6,393.24,8.05,33
|
||||
0.03584,80,3.37,0,0.398,6.29,17.8,6.6115,4,337,16.1,396.9,4.67,23.5
|
||||
0.04379,80,3.37,0,0.398,5.787,31.1,6.6115,4,337,16.1,396.9,10.24,19.4
|
||||
0.05789,12.5,6.07,0,0.409,5.878,21.4,6.498,4,345,18.9,396.21,8.1,22
|
||||
0.13554,12.5,6.07,0,0.409,5.594,36.8,6.498,4,345,18.9,396.9,13.09,17.4
|
||||
0.12816,12.5,6.07,0,0.409,5.885,33,6.498,4,345,18.9,396.9,8.79,20.9
|
||||
0.08826,0,10.81,0,0.413,6.417,6.6,5.2873,4,305,19.2,383.73,6.72,24.2
|
||||
0.15876,0,10.81,0,0.413,5.961,17.5,5.2873,4,305,19.2,376.94,9.88,21.7
|
||||
0.09164,0,10.81,0,0.413,6.065,7.8,5.2873,4,305,19.2,390.91,5.52,22.8
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5.66637,0,18.1,0,0.74,6.219,100,2.0048,24,666,20.2,395.69,16.59,18.4
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12.8023,0,18.1,0,0.74,5.854,96.6,1.8956,24,666,20.2,240.52,23.79,10.8
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9.92485,0,18.1,0,0.74,6.251,96.6,2.198,24,666,20.2,388.52,16.44,12.6
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7.52601,0,18.1,0,0.713,6.417,98.3,2.185,24,666,20.2,304.21,19.31,13
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6.71772,0,18.1,0,0.713,6.749,92.6,2.3236,24,666,20.2,0.32,17.44,13.4
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13.0751,0,18.1,0,0.58,5.713,56.7,2.8237,24,666,20.2,396.9,14.76,20.1
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4.34879,0,18.1,0,0.58,6.167,84,3.0334,24,666,20.2,396.9,16.29,19.9
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4.03841,0,18.1,0,0.532,6.229,90.7,3.0993,24,666,20.2,395.33,12.87,19.6
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3.56868,0,18.1,0,0.58,6.437,75,2.8965,24,666,20.2,393.37,14.36,23.2
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4.64689,0,18.1,0,0.614,6.98,67.6,2.5329,24,666,20.2,374.68,11.66,29.8
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8.05579,0,18.1,0,0.584,5.427,95.4,2.4298,24,666,20.2,352.58,18.14,13.8
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6.39312,0,18.1,0,0.584,6.162,97.4,2.206,24,666,20.2,302.76,24.1,13.3
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15.0234,0,18.1,0,0.614,5.304,97.3,2.1007,24,666,20.2,349.48,24.91,12
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10.233,0,18.1,0,0.614,6.185,96.7,2.1705,24,666,20.2,379.7,18.03,14.6
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14.3337,0,18.1,0,0.614,6.229,88,1.9512,24,666,20.2,383.32,13.11,21.4
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5.82401,0,18.1,0,0.532,6.242,64.7,3.4242,24,666,20.2,396.9,10.74,23
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5.73116,0,18.1,0,0.532,7.061,77,3.4106,24,666,20.2,395.28,7.01,25
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2.81838,0,18.1,0,0.532,5.762,40.3,4.0983,24,666,20.2,392.92,10.42,21.8
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2.37857,0,18.1,0,0.583,5.871,41.9,3.724,24,666,20.2,370.73,13.34,20.6
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3.67367,0,18.1,0,0.583,6.312,51.9,3.9917,24,666,20.2,388.62,10.58,21.2
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5.69175,0,18.1,0,0.583,6.114,79.8,3.5459,24,666,20.2,392.68,14.98,19.1
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4.83567,0,18.1,0,0.583,5.905,53.2,3.1523,24,666,20.2,388.22,11.45,20.6
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0.15086,0,27.74,0,0.609,5.454,92.7,1.8209,4,711,20.1,395.09,18.06,15.2
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0.18337,0,27.74,0,0.609,5.414,98.3,1.7554,4,711,20.1,344.05,23.97,7
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0.10574,0,27.74,0,0.609,5.983,98.8,1.8681,4,711,20.1,390.11,18.07,13.6
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0.11132,0,27.74,0,0.609,5.983,83.5,2.1099,4,711,20.1,396.9,13.35,20.1
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0.17331,0,9.69,0,0.585,5.707,54,2.3817,6,391,19.2,396.9,12.01,21.8
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0.27957,0,9.69,0,0.585,5.926,42.6,2.3817,6,391,19.2,396.9,13.59,24.5
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0.17899,0,9.69,0,0.585,5.67,28.8,2.7986,6,391,19.2,393.29,17.6,23.1
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0.2896,0,9.69,0,0.585,5.39,72.9,2.7986,6,391,19.2,396.9,21.14,19.7
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0.26838,0,9.69,0,0.585,5.794,70.6,2.8927,6,391,19.2,396.9,14.1,18.3
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0.23912,0,9.69,0,0.585,6.019,65.3,2.4091,6,391,19.2,396.9,12.92,21.2
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0.17783,0,9.69,0,0.585,5.569,73.5,2.3999,6,391,19.2,395.77,15.1,17.5
|
||||
0.22438,0,9.69,0,0.585,6.027,79.7,2.4982,6,391,19.2,396.9,14.33,16.8
|
||||
0.06263,0,11.93,0,0.573,6.593,69.1,2.4786,1,273,21,391.99,9.67,22.4
|
||||
0.04527,0,11.93,0,0.573,6.12,76.7,2.2875,1,273,21,396.9,9.08,20.6
|
||||
0.06076,0,11.93,0,0.573,6.976,91,2.1675,1,273,21,396.9,5.64,23.9
|
||||
0.10959,0,11.93,0,0.573,6.794,89.3,2.3889,1,273,21,393.45,6.48,22
|
||||
0.04741,0,11.93,0,0.573,6.03,80.8,2.505,1,273,21,396.9,7.88,11.9
|
||||
|
9569
pyminer/features/datasets/ccpp.csv
Normal file
9569
pyminer/features/datasets/ccpp.csv
Normal file
File diff suppressed because it is too large
Load Diff
20
pyminer/features/datasets/class.csv
Normal file
20
pyminer/features/datasets/class.csv
Normal file
@ -0,0 +1,20 @@
|
||||
Name,Sex,Age,Height,Weight
|
||||
Alfred,M,14,69,112.5
|
||||
Alice,F,13,56.5,84
|
||||
Barbara,F,13,65.3,98
|
||||
Carol,F,14,62.8,102.5
|
||||
Henry,M,14,63.5,102.5
|
||||
James,M,12,57.3,83
|
||||
Jane,F,12,59.8,84.5
|
||||
Janet,F,15,62.5,112.5
|
||||
Jeffrey,M,13,62.5,84
|
||||
John,M,12,59,99.5
|
||||
Joyce,F,11,51.3,50.5
|
||||
Judy,F,14,64.3,90
|
||||
Louise,F,12,56.3,77
|
||||
Mary,F,15,66.5,112
|
||||
Philip,M,16,72,150
|
||||
Robert,M,12,64.8,128
|
||||
Ronald,M,15,67,133
|
||||
Thomas,M,11,57.5,85
|
||||
William,M,15,66.5,112
|
||||
|
443
pyminer/features/datasets/diabetes.csv
Normal file
443
pyminer/features/datasets/diabetes.csv
Normal file
@ -0,0 +1,443 @@
|
||||
"","x.age","x.sex","x.bmi","x.map","x.tc","x.ldl","x.hdl","x.tch","x.ltg","x.glu","y","x2.age","x2.sex","x2.bmi","x2.map","x2.tc","x2.ldl","x2.hdl","x2.tch","x2.ltg","x2.glu","x2.age^2","x2.bmi^2","x2.map^2","x2.tc^2","x2.ldl^2","x2.hdl^2","x2.tch^2","x2.ltg^2","x2.glu^2","x2.age:sex","x2.age:bmi","x2.age:map","x2.age:tc","x2.age:ldl","x2.age:hdl","x2.age:tch","x2.age:ltg","x2.age:glu","x2.sex:bmi","x2.sex:map","x2.sex:tc","x2.sex:ldl","x2.sex:hdl","x2.sex:tch","x2.sex:ltg","x2.sex:glu","x2.bmi:map","x2.bmi:tc","x2.bmi:ldl","x2.bmi:hdl","x2.bmi:tch","x2.bmi:ltg","x2.bmi:glu","x2.map:tc","x2.map:ldl","x2.map:hdl","x2.map:tch","x2.map:ltg","x2.map:glu","x2.tc:ldl","x2.tc:hdl","x2.tc:tch","x2.tc:ltg","x2.tc:glu","x2.ldl:hdl","x2.ldl:tch","x2.ldl:ltg","x2.ldl:glu","x2.hdl:tch","x2.hdl:ltg","x2.hdl:glu","x2.tch:ltg","x2.tch:glu","x2.ltg:glu"
|
||||
"1",0.0380759064334241,0.0506801187398187,0.0616962065186885,0.0218723549949558,-0.0442234984244464,-0.0348207628376986,-0.0434008456520269,-0.00259226199818282,0.0199084208763183,-0.0176461251598052,151,0.038075906433423,0.0506801187398183,0.0616962065186835,0.0218723549949555,-0.044223498424446,-0.034820762837699,-0.0434008456520249,-0.00259226199818327,0.0199084208763174,-0.0176461251598038,-0.0148551624981244,0.0225045739060872,-0.0310446765097524,-0.00433111970083595,-0.0137399242523993,-0.00463142483760742,-0.0304484628906324,-0.0288162192140816,-0.027525561775169,0.0328649757889785,0.0405716740563147,0.00166064095920588,-0.0465532511209619,-0.0382447104337485,-0.0345115069409769,-0.012112260878828,0.0030648915648428,-0.0302775065790892,0.0621030122547407,0.0122820370761595,-0.0485722317941718,-0.0441240238028508,-0.030804298141063,-0.0195479919484543,0.0142268227669149,-0.0293859648154392,0.00900089875753169,-0.0717180777831974,-0.0603176794281382,-0.0413575386150322,-0.0240342003514448,0.00482619355389497,-0.0410278366900181,-0.0327209535943078,-0.0257474212008051,-0.0112074290959139,-0.0138251130574591,-0.0101938360524957,-0.0257784633196462,-0.00686896466070258,0.0398230898731766,-0.0193030537298928,-0.0428915071573702,0.000962970049780259,0.0423549303729145,-0.0220378304616975,-0.0311245646076788,-0.000922109490861135,0.0334936252426516,0.000852148707692385,0.0311502575998521,-0.0281911756717842,-0.0176581552772387,-0.0277936831188906
|
||||
"2",-0.00188201652779104,-0.044641636506989,-0.0514740612388061,-0.0263278347173518,-0.00844872411121698,-0.019163339748222,0.0744115640787594,-0.0394933828740919,-0.0683297436244215,-0.09220404962683,75,-0.0018820165277906,-0.0446416365069889,-0.0514740612388005,-0.0263278347173517,-0.00844872411121685,-0.0191633397482222,0.0744115640787573,-0.0394933828740933,-0.0683297436244167,-0.0922040496268239,-0.0412915429199698,0.00564277328458802,-0.0273076608989145,-0.0309389015906613,-0.024801031934002,0.0400365241171023,-0.00948548235226443,0.0371612444122533,0.0880219609141294,-0.00660999280061308,-0.00676480377922374,-0.0159342243474914,-0.0117287997176067,-0.00965554056350056,0.000699547688135526,-0.00836899629194366,-0.010201679519104,-0.0113801440047604,0.0445181908638052,0.0137392709649757,0.00622262123573813,0.0112617658501637,-0.0565675488119957,0.0224021267067543,0.0575880019287151,0.0784642524736441,0.0091148702261925,-0.00283553670771013,0.00870973138585412,-0.0671553343614269,0.0240456899327673,0.055299443996021,0.0806093115302844,-0.00703998031114477,0.00184624044138617,-0.0319794276664497,0.00987452004254188,0.0203696547240473,0.0313619644359448,-0.026235312318019,-0.0164622947980466,-0.0155012001908042,-0.0123430994788801,0.000932683142754431,-0.0212564242578439,-0.0115642515825463,0.0129733755090618,0.0237834359487639,-0.0238146612918248,-0.0945055990001922,-0.140377589448139,0.0252977154507378,0.0530335390342874,0.104013276820245
|
||||
"3",0.0852989062966783,0.0506801187398187,0.0444512133365941,-0.00567061055493425,-0.0455994512826475,-0.0341944659141195,-0.0323559322397657,-0.00259226199818282,0.00286377051894013,-0.0259303389894746,141,0.0852989062966755,0.0506801187398183,0.0444512133365907,-0.00567061055493434,-0.0455994512826472,-0.0341944659141199,-0.0323559322397641,-0.00259226199818327,0.00286377051894033,-0.0259303389894727,0.0916434391368713,-0.00417642140667041,-0.0388099037506294,-0.00258593662516533,-0.0143055610531069,-0.0148614559552319,-0.0304484628906324,-0.0348099250364741,-0.02243261233058,0.0840517453310858,0.0708891293159234,-0.0279128686509667,-0.0917442739094573,-0.0716415162895924,-0.060292091965198,-0.0147605279027446,-0.00776351737802842,-0.0646990886517641,0.0435615292401802,-0.0181579596887773,-0.0500315235509747,-0.0434530875260124,-0.0179545692956378,-0.0195479919484543,-0.00412168402876947,-0.0384231554244371,-0.0226918084269877,-0.0564432291255567,-0.0464818380292779,-0.0136167525311802,-0.0230540269980099,-0.0194513971846466,-0.0423606976975263,-0.0062598620995419,-0.0049233842767764,0.0120934524955339,-0.0122818753554297,-0.0203183065119236,-0.0149534837719668,-0.0065969775183954,0.0300168639783543,-0.0192411417603178,-0.0271777643267647,0.00987160659840789,0.033586964591413,-0.0220633407083399,-0.0180161690721766,0.00491345530064829,0.0329558783789466,0.0182807986260919,0.0327952439416963,-0.0273318270686805,-0.0172359590436968,-0.022303736816539
|
||||
"4",-0.0890629393522603,-0.044641636506989,-0.0115950145052127,-0.0366564467985606,0.0121905687618,0.0249905933641021,-0.0360375700438527,0.0343088588777263,0.0226920225667445,-0.0093619113301358,206,-0.0890629393522567,-0.0446416365069889,-0.0115950145052109,-0.0366564467985604,0.0121905687618,0.0249905933641022,-0.036037570043851,0.0343088588777268,0.0226920225667434,-0.00936191133013488,0.103640330128407,-0.0310170858965227,-0.0159874155608658,-0.0298483889804742,-0.0214340114197961,-0.0117828858431991,-0.0146503349268825,-0.0269850700933837,-0.0306820951728691,0.0766292448704794,0.0129034053949937,0.0562904031993087,-0.0342989420300201,-0.0571356258420052,0.0786805432124302,-0.0760817035889675,-0.0555091413398771,0.00337859344205518,0.00674978171260364,0.0237941847899894,-0.0130586592105299,-0.0304033769415045,0.0566194244221747,-0.050554601389262,-0.0287218500421114,-0.00113993714603886,-0.00929251860066593,-0.0153834200800705,-0.0193921008426697,0.0279274130698514,-0.0292499537273335,-0.0280603703457815,-0.0160690141522585,-0.0214874364356105,-0.0291135216326405,0.0354925517272733,-0.0397827563941866,-0.0385992764666214,-0.0109701271940759,-0.0242291836557686,-0.0122792654475566,-0.0140331587222177,-0.0186440420163486,-0.0188580962453177,-0.00987842467815741,-0.00998395136803574,-0.00337275550377794,-0.0191092831982032,0.0081586184143522,0.001897732335907,0.0215138965718504,-0.0120454909125379,-0.0248722039634121,-0.0250419366997782
|
||||
"5",0.00538306037424807,-0.044641636506989,-0.0363846922044735,0.0218723549949558,0.00393485161259318,0.0155961395104161,0.00814208360519211,-0.00259226199818282,-0.0319914449413559,-0.0466408735636482,135,0.00538306037424824,-0.0446416365069889,-0.0363846922044693,0.0218723549949555,0.00393485161259326,0.0155961395104161,0.00814208360519228,-0.00259226199818327,-0.0319914449413535,-0.0466408735636449,-0.0408265979088352,-0.0136807215116181,-0.0310446765097524,-0.0317282077228268,-0.026423638379566,-0.0268506699940182,-0.0304484628906324,-0.0191324512010173,-0.00122841851396909,-0.0135465959398708,-0.012917320905025,-0.0144024121450549,-0.0116206046380032,-0.00865024226348658,0.00498016942319217,-0.0102788452468857,-0.0165418441134961,-0.0208710561605729,0.0302274414552425,-0.0331836602184214,-0.00534614703202269,-0.0215384529432772,0.0113446351285065,-0.0140762373412539,0.0231308241409316,0.0346819481828185,-0.0334523098883672,-0.0154230196724137,-0.0255070025130311,0.0119441348323745,-0.0184594644037839,0.00340886358913354,0.0170453174759943,-0.00998370039399319,-0.00171492652414081,0.0119825520966184,-0.0138251130574591,-0.0356386917132688,-0.038658354238658,-0.0276482685680629,-0.0018670730978759,-0.0214699726650182,-0.0270791696150981,-0.0203958710907172,0.0123759490780511,-0.0240914053164124,-0.0268464903287977,-0.0296874121185648,0.030984139878695,0.0144891319598384,0.00538565902071688,-0.0255745143583194,-0.0161804684598421,0.00873519874707534
|
||||
"6",-0.0926954778032799,-0.044641636506989,-0.0406959404999971,-0.0194420933298793,-0.0689906498720667,-0.0792878444118122,0.0412768238419757,-0.076394503750001,-0.0411803851880079,-0.0963461565416647,97,-0.0926954778032761,-0.0446416365069889,-0.0406959404999925,-0.0194420933298793,-0.0689906498720663,-0.0792878444118129,0.0412768238419748,-0.0763945037500034,-0.0411803851880048,-0.0963461565416583,0.115709254854061,-0.00883701451738252,-0.0327918526382835,0.0352626532848092,0.0526602897013096,-0.00683040348906031,0.0482386066882214,-0.00874971436816851,0.0990402558415625,0.0800975464401083,0.0704832806311581,0.0234365272921502,0.118968539632341,0.143871818941206,-0.0851146968084602,0.143219933856352,0.0675437503935968,0.184368682719467,0.0343105127148318,0.00703599508163326,0.0627810438781243,0.0679972794388182,-0.0226114568417446,0.0588804907547624,0.0318440814819462,0.0824444619546283,-0.0020460266247006,0.0488321409952076,0.0580412283870737,-0.0190229455643413,0.0476394963881885,0.0146962189237323,0.0634061397807656,0.0171122203932631,0.0244459436516931,-0.00818834271747913,0.0195036026290302,-0.00200813816670592,0.0201031993883727,0.0483666130214823,-0.0654803859298034,0.0701909475338339,0.0350969956529422,0.130960089514876,-0.0612519836201182,0.0717191451133754,0.0560369456385581,0.149663022266507,-0.0278444433445282,-0.0180308996952476,-0.075512751835102,0.0339989574071917,0.126146572936409,0.0577886516871124
|
||||
"7",-0.0454724779400257,0.0506801187398187,-0.0471628129432825,-0.015999222636143,-0.040095639849843,-0.0248000120604336,0.000778807997017968,-0.0394933828740919,-0.0629129499162512,-0.0383566597339788,138,-0.0454724779400237,0.0506801187398183,-0.0471628129432773,-0.015999222636143,-0.0400956398498427,-0.0248000120604339,0.000778807997018393,-0.0394933828740933,-0.0629129499162468,-0.038356659733976,-0.00355896328393352,-0.000555516747579884,-0.034915156962169,-0.00924586588378609,-0.0215581881292861,-0.0276537752406353,-0.00948548235226443,0.0261833276710403,-0.0111624080757801,-0.0576962318624419,0.0362730290419516,-0.000704451656201736,0.0253000974725321,0.0132605929117162,0.00313535317765844,0.0288740424494596,0.0473851196310185,0.0237277847980145,-0.0549400992746722,-0.0295729584756286,-0.0441943565237631,-0.0333890433734355,0.0205946172406378,-0.0609606274618937,-0.0749300946794753,-0.0519789413379339,-0.00277122408144176,0.0288724121526246,0.0127443569951608,0.0177527104241745,0.0203124290242131,0.0431701364244515,0.0193800351460187,0.00200587439165389,-0.000501973631085994,0.00806298987555708,0.00105774957219044,0.00260767401849853,-0.00547638454684384,-0.0145357824803414,-0.00326458086090795,0.00619321255546504,0.0284218560046411,0.0177496311315475,0.00920754632743378,-0.00806639008277836,0.0184962813811995,0.00629765859172306,0.0308028704045102,0.0192673193195207,0.0132544356681896,0.0211369904048348,0.0112242142742037,0.0269860452317196
|
||||
"8",0.0635036755905609,0.0506801187398187,-0.00189470584028465,0.0666296740135272,0.0906198816792644,0.108914381123697,0.0228686348215404,0.0177033544835672,-0.0358167281015492,0.00306440941436832,63,0.063503675590559,0.0506801187398183,-0.00189470584028368,0.0666296740135265,0.090619881679264,0.108914381123697,0.0228686348215401,0.0177033544835672,-0.0358167281015465,0.00306440941436848,0.0323596759565468,-0.0329243817192768,0.0378838484243839,0.0840102000073463,0.125625877924697,-0.0212671763746795,-0.026308679687707,-0.0151270305437726,-0.0317861151815026,0.0604270824654978,-0.0113296706372693,0.0780014576430322,0.105847511499006,0.134778834229009,0.0377684499108324,0.0143441661593129,-0.0608516484595162,-0.0109091366589389,-0.00626870636145101,0.0617470318191818,0.0944383603725125,0.109855851731576,0.0462940749314882,0.00322895758393736,-0.0457611061886545,-0.00679298829294457,-0.0202018807551889,-0.016044265675543,-0.0175554889686951,0.0176050194475945,-0.0212629614379295,-0.0207620168025318,-0.0184530034614233,0.118493810482665,0.14900473668715,0.0396625246878983,0.0128960726037934,-0.0734466686429589,-0.013793009269941,0.110200069255674,0.0432031851891619,0.00655361798221895,-0.0924591966068138,-0.0101757543227696,0.0635673298752813,0.00684062113304919,-0.101758038137772,-0.00693925915749089,0.0389843873010683,0.0018680364634926,0.0155023250230582,-0.0395197366765709,-0.0174909084600868,-0.0230071720599637
|
||||
"9",0.0417084448844436,0.0506801187398187,0.0616962065186885,-0.0400993174922969,-0.0139525355440215,0.00620168565673016,-0.0286742944356786,-0.00259226199818282,-0.0149564750249113,0.0113486232440377,110,0.0417084448844424,0.0506801187398183,0.0616962065186835,-0.0400993174922966,-0.0139525355440213,0.00620168565673009,-0.0286742944356772,-0.00259226199818327,-0.0149564750249099,0.0113486232440374,-0.00955740877970156,0.0225045739060872,-0.0113889450537842,-0.029197952340987,-0.02910340608727,-0.0176085858067559,-0.0304484628906324,-0.0314822598293453,-0.0301016084619806,0.0368024195999099,0.0452819389982141,-0.0546172495122257,-0.0239773167807327,-0.00498275112545622,-0.0238825055141004,-0.0123159737268216,-0.0260602068112379,-0.00467875192937979,0.0621030122547407,-0.0562079556449483,-0.016467813144508,-0.000177697669931729,-0.0136713263471627,-0.0195479919484543,-0.0233051163436824,0.00224420231605329,-0.0666618676538972,-0.0310501731903485,-0.004585974560005,-0.0210215963106599,-0.0240342003514448,-0.0426061496455996,-0.00373573330031678,0.000235570550349741,-0.0145689047549187,0.031971169128181,-0.010352828227893,-0.00651104728694577,-0.0271820411765607,-0.0297268312321458,0.00626290299639631,-0.0206651170605431,-0.0200679791904862,-0.0198378491150454,0.00577460396386221,-0.0237087516167761,-0.0179023324561471,-0.0125852182626633,0.0327766294243783,0.0300641898908337,0.00660775972279424,-0.0264333748978242,-0.0191358420946353,-0.0241956939326532
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"439",-0.00551455497881059,0.0506801187398187,-0.0159062628007364,-0.067642283042187,0.0493412959332305,0.0791652772536912,-0.0286742944356786,0.0343088588777263,-0.0181182673078967,0.0444854785627154,104,-0.00551455497881003,0.0506801187398183,-0.0159062628007341,-0.0676422830421865,0.0493412959332303,0.0791652772536917,-0.0286742944356772,0.0343088588777268,-0.0181182673078952,0.044485478562713,-0.0408004038237007,-0.0292889198895316,0.0402498161020451,0.00243042138169551,0.0524061413111551,-0.0176085858067559,-0.0146503349268825,-0.0298674093899606,-0.00399942111500433,-0.0143843499421974,-0.00695730265080704,-0.00866796828965593,-0.0176292542943585,-0.0195769995572278,0.00764102981552017,-0.0140700036756498,-0.0108062422790129,-0.0207424612632487,-0.0213336613107814,-0.0866479524098851,0.0506596076684254,0.0779863785817488,-0.0136713263471627,0.0218646435649851,-0.0267087747335295,0.0383929647520448,0.00358841702916421,-0.0293956116253921,-0.0407397975497529,0.0287834179136977,-0.0324931279591703,-0.0159034873064022,-0.033083100722514,-0.0838857884437407,-0.125851717742157,0.0482168977112667,-0.0627607829756748,0.00751661291508638,-0.0790528269509603,0.026386037706581,-0.0338281009555992,0.00809094901417812,-0.0431756488733244,0.0323087759192345,-0.0395356426513504,0.0192211114883726,-0.0474436612832251,0.0613999396605777,0.0129033757657124,0.0321126151945183,-0.014761543982107,-0.0392774156650059,0.0114485697606271,-0.0368038269050855
|
||||
"440",0.0417084448844436,0.0506801187398187,-0.0159062628007364,0.0172818607481171,-0.0373437341334407,-0.0138398158977999,-0.0249926566315915,-0.0110795197996419,-0.0468794828442166,0.0154907301588724,132,0.0417084448844424,0.0506801187398183,-0.0159062628007341,0.0172818607481168,-0.0373437341334404,-0.0138398158978002,-0.0249926566315902,-0.0110795197996426,-0.0468794828442132,0.0154907301588718,-0.00955740877970156,-0.0292889198895316,-0.0341723374749933,-0.0122550274690348,-0.0271001809412452,-0.0200242753977713,-0.0288821735246703,-0.000999983324380843,-0.0285331990846363,0.0368024195999099,-0.022744257980958,-0.000855514177693004,-0.0439656047738701,-0.0225300903260483,-0.0203076897653082,-0.0199740678273224,-0.0541233725778817,-0.000817100426874716,-0.0213336613107814,0.00720870429468673,-0.0412757730101573,-0.0216476585287624,-0.00938808339868762,-0.0290728981165453,-0.0576701231716256,0.00676279762055223,-0.0231434854408504,0.000629135374416991,-0.0081638412170092,0.0274726856140709,-0.0166633874904058,-0.00581553232522462,-0.0234686036508157,-0.0257723799283846,-0.014361744577475,-0.000565316751817445,-0.0167382123766547,-0.0381141217915824,-0.0125027922731748,-0.021247182526425,0.0180420959197175,-0.0141111618220497,0.0122461024441367,-0.0291476443189945,0.0171168457867699,-0.0210467573796391,-0.00157338159148029,-0.0186897475903142,0.036581354456346,0.0468465169987158,0.00521922054414783,-0.0170854715135979,-0.0219317193745352,-0.0352224733896595
|
||||
"441",-0.0454724779400257,-0.044641636506989,0.0390621529671896,0.00121513083253827,0.0163184273364034,0.0152829910486266,-0.0286742944356786,0.0265596234937854,0.0445283740214053,-0.0259303389894746,220,-0.0454724779400237,-0.0446416365069889,0.0390621529671867,0.00121513083253812,0.0163184273364034,0.0152829910486266,-0.0286742944356772,0.0265596234937857,0.0445283740214029,-0.0259303389894727,-0.00355896328393352,-0.0107363422046209,-0.0393437631236063,-0.028186672760159,-0.0265501783688838,-0.0176085858067559,-0.0210172757495206,-0.00431861274675231,-0.02243261233058,0.0350096260349332,-0.0461328708783035,-0.0182885116490972,-0.0272574579735098,-0.0250012505550337,0.0343147904790452,-0.0361045825562791,-0.0555891765327752,0.0110973309477519,-0.0412263055875713,-0.013073832568394,-0.0169149152997835,-0.0212429554766696,0.0490736262065633,-0.0428941449391803,-0.0494278013821068,0.0147809007778977,-0.0167642952850973,0.00157492268601058,0.00013442003513615,-0.00649513382855557,0.00222027956916888,0.016096447996621,-0.0394475646740065,-0.0114134544110441,-0.00874449819743362,0.00760257625355246,-0.0119020301339451,-0.0187414775821822,-0.0185797208673875,-0.0250057427393442,-0.0129110554154276,-0.0137698982602856,-0.00921361306003149,-0.0257055087629693,0.000135131209179095,-0.0170781270770976,-0.000874841283209641,-0.0225891829165384,0.0170767590340322,-0.00847416401307057,0.0306482263908081,-0.00418567929051579,-0.0320973344508845,-0.043712353646299
|
||||
"442",-0.0454724779400257,-0.044641636506989,-0.0730303027164241,-0.081413765817132,0.0837401173882587,0.0278089295202079,0.17381578478911,-0.0394933828740919,-0.00421985970694603,0.00306440941436832,57,-0.0454724779400237,-0.0446416365069889,-0.0730303027164164,-0.0814137658171314,0.0837401173882584,0.027808929520208,0.173815784789105,-0.0394933828740933,-0.00421985970694538,0.00306440941436848,-0.00355896328393352,0.0447617216730217,0.0759698614127442,0.0670718718607615,-0.0194867007777123,0.341717273542819,-0.00948548235226443,-0.0346615890113986,-0.0317861151815026,0.0350096260349332,0.0609947990180281,0.066114976316801,-0.0900701461895112,-0.036958076638393,-0.180043840967989,0.0288740424494596,-0.00886772082623655,-0.0183737280361942,0.064933547161752,0.0673654780317152,-0.0799004314242591,-0.0330628541409727,-0.158435824722749,0.0224021267067543,-0.0032031123544662,-0.0130805655889913,0.0999571076204403,-0.145474656505948,-0.0577321839781554,-0.265542092646783,0.0427119944755386,-0.0154628270575754,-0.0229973646405775,-0.159005712277338,-0.0584903715430468,-0.282767701081251,0.0568972958844162,-0.0122535339530691,-0.0230066919223992,0.00421725318037418,0.318950834470234,-0.0786979677560232,-0.0318465185873455,-0.0106429155773642,0.114307586745747,-0.0407130974139457,-0.0184438959395085,-0.0122671537802096,-0.0975483290818771,0.00380211974804052,0.0259053117613143,-0.0239461018471299,-0.0209368047720145,-0.0210884856882758
|
||||
|
Can't render this file because it is too large.
|
BIN
pyminer/features/datasets/german.zip
Normal file
BIN
pyminer/features/datasets/german.zip
Normal file
Binary file not shown.
151
pyminer/features/datasets/iris.csv
Normal file
151
pyminer/features/datasets/iris.csv
Normal file
@ -0,0 +1,151 @@
|
||||
sepal length,sepal width,petal length,petal width,iris
|
||||
5.1,3.5,1.4,0.2,Iris-setosa
|
||||
4.9,3.0,1.4,0.2,Iris-setosa
|
||||
4.7,3.2,1.3,0.2,Iris-setosa
|
||||
4.6,3.1,1.5,0.2,Iris-setosa
|
||||
5.0,3.6,1.4,0.2,Iris-setosa
|
||||
5.4,3.9,1.7,0.4,Iris-setosa
|
||||
4.6,3.4,1.4,0.3,Iris-setosa
|
||||
5.0,3.4,1.5,0.2,Iris-setosa
|
||||
4.4,2.9,1.4,0.2,Iris-setosa
|
||||
4.9,3.1,1.5,0.1,Iris-setosa
|
||||
5.4,3.7,1.5,0.2,Iris-setosa
|
||||
4.8,3.4,1.6,0.2,Iris-setosa
|
||||
4.8,3.0,1.4,0.1,Iris-setosa
|
||||
4.3,3.0,1.1,0.1,Iris-setosa
|
||||
5.8,4.0,1.2,0.2,Iris-setosa
|
||||
5.7,4.4,1.5,0.4,Iris-setosa
|
||||
5.4,3.9,1.3,0.4,Iris-setosa
|
||||
5.1,3.5,1.4,0.3,Iris-setosa
|
||||
5.7,3.8,1.7,0.3,Iris-setosa
|
||||
5.1,3.8,1.5,0.3,Iris-setosa
|
||||
5.4,3.4,1.7,0.2,Iris-setosa
|
||||
5.1,3.7,1.5,0.4,Iris-setosa
|
||||
4.6,3.6,1.0,0.2,Iris-setosa
|
||||
5.1,3.3,1.7,0.5,Iris-setosa
|
||||
4.8,3.4,1.9,0.2,Iris-setosa
|
||||
5.0,3.0,1.6,0.2,Iris-setosa
|
||||
5.0,3.4,1.6,0.4,Iris-setosa
|
||||
5.2,3.5,1.5,0.2,Iris-setosa
|
||||
5.2,3.4,1.4,0.2,Iris-setosa
|
||||
4.7,3.2,1.6,0.2,Iris-setosa
|
||||
4.8,3.1,1.6,0.2,Iris-setosa
|
||||
5.4,3.4,1.5,0.4,Iris-setosa
|
||||
5.2,4.1,1.5,0.1,Iris-setosa
|
||||
5.5,4.2,1.4,0.2,Iris-setosa
|
||||
4.9,3.1,1.5,0.1,Iris-setosa
|
||||
5.0,3.2,1.2,0.2,Iris-setosa
|
||||
5.5,3.5,1.3,0.2,Iris-setosa
|
||||
4.9,3.1,1.5,0.1,Iris-setosa
|
||||
4.4,3.0,1.3,0.2,Iris-setosa
|
||||
5.1,3.4,1.5,0.2,Iris-setosa
|
||||
5.0,3.5,1.3,0.3,Iris-setosa
|
||||
4.5,2.3,1.3,0.3,Iris-setosa
|
||||
4.4,3.2,1.3,0.2,Iris-setosa
|
||||
5.0,3.5,1.6,0.6,Iris-setosa
|
||||
5.1,3.8,1.9,0.4,Iris-setosa
|
||||
4.8,3.0,1.4,0.3,Iris-setosa
|
||||
5.1,3.8,1.6,0.2,Iris-setosa
|
||||
4.6,3.2,1.4,0.2,Iris-setosa
|
||||
5.3,3.7,1.5,0.2,Iris-setosa
|
||||
5.0,3.3,1.4,0.2,Iris-setosa
|
||||
7.0,3.2,4.7,1.4,Iris-versicolor
|
||||
6.4,3.2,4.5,1.5,Iris-versicolor
|
||||
6.9,3.1,4.9,1.5,Iris-versicolor
|
||||
5.5,2.3,4.0,1.3,Iris-versicolor
|
||||
6.5,2.8,4.6,1.5,Iris-versicolor
|
||||
5.7,2.8,4.5,1.3,Iris-versicolor
|
||||
6.3,3.3,4.7,1.6,Iris-versicolor
|
||||
4.9,2.4,3.3,1.0,Iris-versicolor
|
||||
6.6,2.9,4.6,1.3,Iris-versicolor
|
||||
5.2,2.7,3.9,1.4,Iris-versicolor
|
||||
5.0,2.0,3.5,1.0,Iris-versicolor
|
||||
5.9,3.0,4.2,1.5,Iris-versicolor
|
||||
6.0,2.2,4.0,1.0,Iris-versicolor
|
||||
6.1,2.9,4.7,1.4,Iris-versicolor
|
||||
5.6,2.9,3.6,1.3,Iris-versicolor
|
||||
6.7,3.1,4.4,1.4,Iris-versicolor
|
||||
5.6,3.0,4.5,1.5,Iris-versicolor
|
||||
5.8,2.7,4.1,1.0,Iris-versicolor
|
||||
6.2,2.2,4.5,1.5,Iris-versicolor
|
||||
5.6,2.5,3.9,1.1,Iris-versicolor
|
||||
5.9,3.2,4.8,1.8,Iris-versicolor
|
||||
6.1,2.8,4.0,1.3,Iris-versicolor
|
||||
6.3,2.5,4.9,1.5,Iris-versicolor
|
||||
6.1,2.8,4.7,1.2,Iris-versicolor
|
||||
6.4,2.9,4.3,1.3,Iris-versicolor
|
||||
6.6,3.0,4.4,1.4,Iris-versicolor
|
||||
6.8,2.8,4.8,1.4,Iris-versicolor
|
||||
6.7,3.0,5.0,1.7,Iris-versicolor
|
||||
6.0,2.9,4.5,1.5,Iris-versicolor
|
||||
5.7,2.6,3.5,1.0,Iris-versicolor
|
||||
5.5,2.4,3.8,1.1,Iris-versicolor
|
||||
5.5,2.4,3.7,1.0,Iris-versicolor
|
||||
5.8,2.7,3.9,1.2,Iris-versicolor
|
||||
6.0,2.7,5.1,1.6,Iris-versicolor
|
||||
5.4,3.0,4.5,1.5,Iris-versicolor
|
||||
6.0,3.4,4.5,1.6,Iris-versicolor
|
||||
6.7,3.1,4.7,1.5,Iris-versicolor
|
||||
6.3,2.3,4.4,1.3,Iris-versicolor
|
||||
5.6,3.0,4.1,1.3,Iris-versicolor
|
||||
5.5,2.5,4.0,1.3,Iris-versicolor
|
||||
5.5,2.6,4.4,1.2,Iris-versicolor
|
||||
6.1,3.0,4.6,1.4,Iris-versicolor
|
||||
5.8,2.6,4.0,1.2,Iris-versicolor
|
||||
5.0,2.3,3.3,1.0,Iris-versicolor
|
||||
5.6,2.7,4.2,1.3,Iris-versicolor
|
||||
5.7,3.0,4.2,1.2,Iris-versicolor
|
||||
5.7,2.9,4.2,1.3,Iris-versicolor
|
||||
6.2,2.9,4.3,1.3,Iris-versicolor
|
||||
5.1,2.5,3.0,1.1,Iris-versicolor
|
||||
5.7,2.8,4.1,1.3,Iris-versicolor
|
||||
6.3,3.3,6.0,2.5,Iris-virginica
|
||||
5.8,2.7,5.1,1.9,Iris-virginica
|
||||
7.1,3.0,5.9,2.1,Iris-virginica
|
||||
6.3,2.9,5.6,1.8,Iris-virginica
|
||||
6.5,3.0,5.8,2.2,Iris-virginica
|
||||
7.6,3.0,6.6,2.1,Iris-virginica
|
||||
4.9,2.5,4.5,1.7,Iris-virginica
|
||||
7.3,2.9,6.3,1.8,Iris-virginica
|
||||
6.7,2.5,5.8,1.8,Iris-virginica
|
||||
7.2,3.6,6.1,2.5,Iris-virginica
|
||||
6.5,3.2,5.1,2.0,Iris-virginica
|
||||
6.4,2.7,5.3,1.9,Iris-virginica
|
||||
6.8,3.0,5.5,2.1,Iris-virginica
|
||||
5.7,2.5,5.0,2.0,Iris-virginica
|
||||
5.8,2.8,5.1,2.4,Iris-virginica
|
||||
6.4,3.2,5.3,2.3,Iris-virginica
|
||||
6.5,3.0,5.5,1.8,Iris-virginica
|
||||
7.7,3.8,6.7,2.2,Iris-virginica
|
||||
7.7,2.6,6.9,2.3,Iris-virginica
|
||||
6.0,2.2,5.0,1.5,Iris-virginica
|
||||
6.9,3.2,5.7,2.3,Iris-virginica
|
||||
5.6,2.8,4.9,2.0,Iris-virginica
|
||||
7.7,2.8,6.7,2.0,Iris-virginica
|
||||
6.3,2.7,4.9,1.8,Iris-virginica
|
||||
6.7,3.3,5.7,2.1,Iris-virginica
|
||||
7.2,3.2,6.0,1.8,Iris-virginica
|
||||
6.2,2.8,4.8,1.8,Iris-virginica
|
||||
6.1,3.0,4.9,1.8,Iris-virginica
|
||||
6.4,2.8,5.6,2.1,Iris-virginica
|
||||
7.2,3.0,5.8,1.6,Iris-virginica
|
||||
7.4,2.8,6.1,1.9,Iris-virginica
|
||||
7.9,3.8,6.4,2.0,Iris-virginica
|
||||
6.4,2.8,5.6,2.2,Iris-virginica
|
||||
6.3,2.8,5.1,1.5,Iris-virginica
|
||||
6.1,2.6,5.6,1.4,Iris-virginica
|
||||
7.7,3.0,6.1,2.3,Iris-virginica
|
||||
6.3,3.4,5.6,2.4,Iris-virginica
|
||||
6.4,3.1,5.5,1.8,Iris-virginica
|
||||
6.0,3.0,4.8,1.8,Iris-virginica
|
||||
6.9,3.1,5.4,2.1,Iris-virginica
|
||||
6.7,3.1,5.6,2.4,Iris-virginica
|
||||
6.9,3.1,5.1,2.3,Iris-virginica
|
||||
5.8,2.7,5.1,1.9,Iris-virginica
|
||||
6.8,3.2,5.9,2.3,Iris-virginica
|
||||
6.7,3.3,5.7,2.5,Iris-virginica
|
||||
6.7,3.0,5.2,2.3,Iris-virginica
|
||||
6.3,2.5,5.0,1.9,Iris-virginica
|
||||
6.5,3.0,5.2,2.0,Iris-virginica
|
||||
6.2,3.4,5.4,2.3,Iris-virginica
|
||||
5.9,3.0,5.1,1.8,Iris-virginica
|
||||
|
6
pyminer/features/datasets/miss.csv
Normal file
6
pyminer/features/datasets/miss.csv
Normal file
@ -0,0 +1,6 @@
|
||||
name,English,Math,Chinese,Null
|
||||
Kite,92,69,,
|
||||
Lily,78,87,78,
|
||||
Hanmei,,91,96,
|
||||
Danny,23,,,
|
||||
Bob,82,90,75,
|
||||
|
33
pyminer/features/datasets/mtcars.csv
Normal file
33
pyminer/features/datasets/mtcars.csv
Normal file
@ -0,0 +1,33 @@
|
||||
"mpg","cyl","disp","hp","drat","wt","qsec","vs","am","gear","carb"
|
||||
21,6,160,110,3.9,2.62,16.46,0,1,4,4
|
||||
21,6,160,110,3.9,2.875,17.02,0,1,4,4
|
||||
22.8,4,108,93,3.85,2.32,18.61,1,1,4,1
|
||||
21.4,6,258,110,3.08,3.215,19.44,1,0,3,1
|
||||
18.7,8,360,175,3.15,3.44,17.02,0,0,3,2
|
||||
18.1,6,225,105,2.76,3.46,20.22,1,0,3,1
|
||||
14.3,8,360,245,3.21,3.57,15.84,0,0,3,4
|
||||
24.4,4,146.7,62,3.69,3.19,20,1,0,4,2
|
||||
22.8,4,140.8,95,3.92,3.15,22.9,1,0,4,2
|
||||
19.2,6,167.6,123,3.92,3.44,18.3,1,0,4,4
|
||||
17.8,6,167.6,123,3.92,3.44,18.9,1,0,4,4
|
||||
16.4,8,275.8,180,3.07,4.07,17.4,0,0,3,3
|
||||
17.3,8,275.8,180,3.07,3.73,17.6,0,0,3,3
|
||||
15.2,8,275.8,180,3.07,3.78,18,0,0,3,3
|
||||
10.4,8,472,205,2.93,5.25,17.98,0,0,3,4
|
||||
10.4,8,460,215,3,5.424,17.82,0,0,3,4
|
||||
14.7,8,440,230,3.23,5.345,17.42,0,0,3,4
|
||||
32.4,4,78.7,66,4.08,2.2,19.47,1,1,4,1
|
||||
30.4,4,75.7,52,4.93,1.615,18.52,1,1,4,2
|
||||
33.9,4,71.1,65,4.22,1.835,19.9,1,1,4,1
|
||||
21.5,4,120.1,97,3.7,2.465,20.01,1,0,3,1
|
||||
15.5,8,318,150,2.76,3.52,16.87,0,0,3,2
|
||||
15.2,8,304,150,3.15,3.435,17.3,0,0,3,2
|
||||
13.3,8,350,245,3.73,3.84,15.41,0,0,3,4
|
||||
19.2,8,400,175,3.08,3.845,17.05,0,0,3,2
|
||||
27.3,4,79,66,4.08,1.935,18.9,1,1,4,1
|
||||
26,4,120.3,91,4.43,2.14,16.7,0,1,5,2
|
||||
30.4,4,95.1,113,3.77,1.513,16.9,1,1,5,2
|
||||
15.8,8,351,264,4.22,3.17,14.5,0,1,5,4
|
||||
19.7,6,145,175,3.62,2.77,15.5,0,1,5,6
|
||||
15,8,301,335,3.54,3.57,14.6,0,1,5,8
|
||||
21.4,4,121,109,4.11,2.78,18.6,1,1,4,2
|
||||
|
8125
pyminer/features/datasets/mushrooms.csv
Normal file
8125
pyminer/features/datasets/mushrooms.csv
Normal file
File diff suppressed because it is too large
Load Diff
BIN
pyminer/features/datasets/sas/cars.sas7bdat
Normal file
BIN
pyminer/features/datasets/sas/cars.sas7bdat
Normal file
Binary file not shown.
BIN
pyminer/features/datasets/sas/class.sas7bdat
Normal file
BIN
pyminer/features/datasets/sas/class.sas7bdat
Normal file
Binary file not shown.
BIN
pyminer/features/datasets/spss/worldsales.sav
Normal file
BIN
pyminer/features/datasets/spss/worldsales.sav
Normal file
Binary file not shown.
30001
pyminer/features/datasets/uci.csv
Normal file
30001
pyminer/features/datasets/uci.csv
Normal file
File diff suppressed because it is too large
Load Diff
3
pyminer/features/datasets/v_concat_data/df1.csv
Normal file
3
pyminer/features/datasets/v_concat_data/df1.csv
Normal file
@ -0,0 +1,3 @@
|
||||
Index,Name,Sex,Age,Height,Weight
|
||||
0,Alfred,M,14,69.0,112.5
|
||||
1,Alice,F,13,56.5,84.0
|
||||
|
4
pyminer/features/datasets/v_concat_data/df2.csv
Normal file
4
pyminer/features/datasets/v_concat_data/df2.csv
Normal file
@ -0,0 +1,4 @@
|
||||
Index,Name,Sex,Age,Height,Weight
|
||||
2,Barbara,F,13,65.3,98.0
|
||||
3,Carol,F,14,62.8,102.5
|
||||
4,Henry,M,14,63.5,102.5
|
||||
|
5
pyminer/features/datasets/v_concat_data/df3.csv
Normal file
5
pyminer/features/datasets/v_concat_data/df3.csv
Normal file
@ -0,0 +1,5 @@
|
||||
Index,Name,Sex,Age,Height,Weight
|
||||
5,James,M,12,57.3,83.0
|
||||
6,Jane,F,12,59.8,84.5
|
||||
7,Janet,F,15,62.5,112.5
|
||||
8,Jeffrey,M,13,62.5,84.0
|
||||
|
BIN
pyminer/features/datasets/xlsx_files/header_0.xlsx
Normal file
BIN
pyminer/features/datasets/xlsx_files/header_0.xlsx
Normal file
Binary file not shown.
BIN
pyminer/features/datasets/xlsx_files/header_0_sheet.xls
Normal file
BIN
pyminer/features/datasets/xlsx_files/header_0_sheet.xls
Normal file
Binary file not shown.
BIN
pyminer/features/datasets/xlsx_files/header_0_sheet.xlsx
Normal file
BIN
pyminer/features/datasets/xlsx_files/header_0_sheet.xlsx
Normal file
Binary file not shown.
BIN
pyminer/features/datasets/xlsx_files/header_1_flags.xlsx
Normal file
BIN
pyminer/features/datasets/xlsx_files/header_1_flags.xlsx
Normal file
Binary file not shown.
BIN
pyminer/features/datasets/xlsx_files/header_1_no_flags.xlsx
Normal file
BIN
pyminer/features/datasets/xlsx_files/header_1_no_flags.xlsx
Normal file
Binary file not shown.
BIN
pyminer/features/datasets/xlsx_files/header_3.xlsx
Normal file
BIN
pyminer/features/datasets/xlsx_files/header_3.xlsx
Normal file
Binary file not shown.
BIN
pyminer/features/datasets/xlsx_files/round_floats.xlsx
Normal file
BIN
pyminer/features/datasets/xlsx_files/round_floats.xlsx
Normal file
Binary file not shown.
168
pyminer/features/evaluation/clustering.py
Normal file
168
pyminer/features/evaluation/clustering.py
Normal file
@ -0,0 +1,168 @@
|
||||
import warnings
|
||||
|
||||
import numpy as np
|
||||
from sklearn.metrics import silhouette_score, adjusted_mutual_info_score, silhouette_samples
|
||||
|
||||
from Orange.data import Table
|
||||
from Orange.evaluation.testing import Results, Validation
|
||||
from Orange.evaluation.scoring import Score
|
||||
|
||||
|
||||
__all__ = ['ClusteringEvaluation']
|
||||
|
||||
|
||||
class ClusteringResults(Results):
|
||||
def get_fold(self, fold):
|
||||
results = Results()
|
||||
results.data = self.data
|
||||
|
||||
if self.folds is None:
|
||||
raise ValueError("This 'Results' instance does not have folds.")
|
||||
|
||||
if self.models is not None:
|
||||
results.models = self.models[fold]
|
||||
|
||||
results.row_indices = self.row_indices
|
||||
results.actual = self.actual
|
||||
results.predicted = self.predicted[:, fold, :]
|
||||
results.domain = self.domain
|
||||
return results
|
||||
|
||||
|
||||
class ClusteringScore(Score):
|
||||
considers_actual = False
|
||||
|
||||
# pylint: disable=arguments-differ
|
||||
def from_predicted(self, results, score_function):
|
||||
# Clustering scores from labels
|
||||
if self.considers_actual:
|
||||
return np.fromiter(
|
||||
(score_function(results.actual.flatten(),
|
||||
predicted.flatten())
|
||||
for predicted in results.predicted),
|
||||
dtype=np.float64, count=len(results.predicted))
|
||||
# Clustering scores from data only
|
||||
else:
|
||||
return np.fromiter(
|
||||
(score_function(results.data.X, predicted.flatten())
|
||||
for predicted in results.predicted),
|
||||
dtype=np.float64, count=len(results.predicted))
|
||||
|
||||
|
||||
class Silhouette(ClusteringScore):
|
||||
separate_folds = True
|
||||
|
||||
def compute_score(self, results):
|
||||
return self.from_predicted(results, silhouette_score)
|
||||
|
||||
|
||||
class AdjustedMutualInfoScore(ClusteringScore):
|
||||
separate_folds = True
|
||||
considers_actual = True
|
||||
|
||||
def compute_score(self, results):
|
||||
return self.from_predicted(results, adjusted_mutual_info_score)
|
||||
|
||||
|
||||
# Class overrides fit and doesn't need to define the abstract get_indices
|
||||
# pylint: disable=abstract-method
|
||||
class ClusteringEvaluation(Validation):
|
||||
"""
|
||||
Clustering evaluation.
|
||||
|
||||
.. attribute:: k
|
||||
The number of runs.
|
||||
|
||||
"""
|
||||
def __init__(self, k=1, store_data=False, store_models=False):
|
||||
super().__init__(store_data=store_data, store_models=store_models)
|
||||
self.k = k
|
||||
|
||||
def __call__(self, data, learners, preprocessor=None, *, callback=None):
|
||||
res = ClusteringResults()
|
||||
res.data = data
|
||||
res.predicted = np.empty((len(learners), self.k, len(data)))
|
||||
res.folds = range(self.k)
|
||||
res.row_indices = np.arange(len(data))
|
||||
res.actual = data.Y.flatten() if hasattr(data, "Y") else None
|
||||
if self.store_models:
|
||||
res.models = np.tile(None, (self.k, len(learners)))
|
||||
|
||||
for k in range(self.k):
|
||||
for i, learner in enumerate(learners):
|
||||
model = learner.get_model(data)
|
||||
if self.store_models:
|
||||
res.models[k, i] = model
|
||||
res.predicted[i, k, :] = model.labels
|
||||
|
||||
return res
|
||||
|
||||
|
||||
def graph_silhouette(X, y, xlim=None, colors=None, figsize=None, filename=None):
|
||||
"""
|
||||
Silhouette plot.
|
||||
:param filename:
|
||||
Output file name.
|
||||
:param X Orange.data.Table or numpy.ndarray
|
||||
Data table.
|
||||
:param y Orange.data.Table or numpy.ndarray:
|
||||
Cluster labels (integers).
|
||||
:param colors list, optional (default = None):
|
||||
List of colors. If provided, it must equal the number of clusters.
|
||||
:param figsize tuple (float, float):
|
||||
Figure size (width, height) in inches.
|
||||
:param xlim tuple (float, float):
|
||||
Limit x-axis values.
|
||||
"""
|
||||
# If the module is not there, let the user install it
|
||||
# pylint: disable=import-error
|
||||
import matplotlib.pyplot as plt
|
||||
|
||||
if isinstance(X, Table):
|
||||
X = X.X
|
||||
if isinstance(y, Table):
|
||||
y = y.X
|
||||
y = y.ravel()
|
||||
|
||||
# Detect number of clusters and set colors
|
||||
N = len(set(y))
|
||||
if isinstance(colors, type(None)):
|
||||
colors = ["g" if i % 2 else "b" for i in range(N)]
|
||||
elif len(colors) != N:
|
||||
import sys
|
||||
sys.stderr.write("Number of colors does not match the number of clusters. \n")
|
||||
return
|
||||
|
||||
# Silhouette coefficients
|
||||
s = silhouette_samples(X, y)
|
||||
s = s[np.argsort(y)] # Sort by clusters
|
||||
parts = []
|
||||
# Within clusters sort by silhouette scores
|
||||
for label, (i, j) in enumerate([(sum(y == c1), sum(y == c1) + sum(y == c2))
|
||||
for c1, c2 in zip(range(-1, N-1), range(0, N))]):
|
||||
scores = sorted(s[i:j])
|
||||
parts.append((scores, label))
|
||||
|
||||
# Plot data
|
||||
if figsize:
|
||||
plt.figure(figsize=figsize)
|
||||
else:
|
||||
plt.figure()
|
||||
plt.title("Silhouette score")
|
||||
total = 0
|
||||
centers = []
|
||||
for i, (scores, label) in enumerate(parts):
|
||||
plt.barh(range(total, total + len(scores)),
|
||||
scores, color=colors[i], edgecolor=colors[i])
|
||||
centers.append(total+len(scores)/2)
|
||||
total += len(scores)
|
||||
if not isinstance(xlim, type(None)):
|
||||
plt.xlim(xlim)
|
||||
plt.yticks(centers)
|
||||
plt.gca().set_yticklabels(range(N))
|
||||
plt.ylabel("Cluster label")
|
||||
if filename:
|
||||
plt.savefig(filename)
|
||||
plt.close()
|
||||
else:
|
||||
plt.show()
|
||||
150
pyminer/features/evaluation/performance_curves.py
Normal file
150
pyminer/features/evaluation/performance_curves.py
Normal file
@ -0,0 +1,150 @@
|
||||
import numpy as np
|
||||
|
||||
|
||||
class Curves:
|
||||
# names of scores are standard acronyms, pylint: disable=invalid-name
|
||||
"""
|
||||
Computation of performance curves (ca, f1, precision, recall and the rest
|
||||
of the zoo) from test results.
|
||||
|
||||
The class works with binary classes. Attribute `probs` contains ordered
|
||||
probabilities and all curves represent performance statistics if an
|
||||
instance is classified as positive if it equals or exceeds the threshold
|
||||
in `probs`, that is, `sensitivity[i]` is the sensitivity of the classifier
|
||||
that classifies an instances as positive if the probability of being
|
||||
positive is at least `probs[i]`.
|
||||
|
||||
Class can be constructed by giving `probs` and `ytrue`, or from test
|
||||
results (see :obj:`Curves.from_results`). The latter removes instances
|
||||
with missing class values or predicted probabilities.
|
||||
|
||||
The class treats all results as obtained from a single run instead of
|
||||
computing separate curves and fancy averaging.
|
||||
|
||||
Arguments:
|
||||
probs (np.ndarray): vector of predicted probabilities
|
||||
ytrue (np.ndarray): corresponding true classes
|
||||
|
||||
Attributes:
|
||||
probs (np.ndarray): ordered vector of predicted probabilities
|
||||
ytrue (np.ndarray): corresponding true classes
|
||||
tot (int): total number of data instances
|
||||
p (int): number of real positive instances
|
||||
n (int): number of real negative instances
|
||||
tp (np.ndarray): number of true positives (property computed from `tn`)
|
||||
fp (np.ndarray): number of false positives (property computed from `tn`)
|
||||
tn (np.ndarray): number of true negatives (property computed from `tn`)
|
||||
fn (np.ndarray): number of false negatives (precomputed, not a property)
|
||||
"""
|
||||
def __init__(self, ytrue, probs):
|
||||
sortind = np.argsort(probs)
|
||||
self.probs = np.hstack((probs[sortind], [1]))
|
||||
self.ytrue = ytrue[sortind]
|
||||
self.fn = np.hstack(([0], np.cumsum(self.ytrue)))
|
||||
self.tot = len(probs)
|
||||
self.p = self.fn[-1]
|
||||
self.n = self.tot - self.p
|
||||
|
||||
@classmethod
|
||||
def from_results(cls, results, target_class=None, model_index=None):
|
||||
"""
|
||||
Construct an instance of `Curves` from test results.
|
||||
|
||||
Args:
|
||||
results (:obj:`Orange.evaluation.testing.Results`): test results
|
||||
target_class (int): target class index; if the class is binary,
|
||||
this defaults to `1`, otherwise it must be given
|
||||
model_index (int): model index; if there is only one model, this
|
||||
argument can be omitted
|
||||
|
||||
Returns:
|
||||
curves (:obj:`Curves`)
|
||||
"""
|
||||
if model_index is None:
|
||||
if results.probabilities.shape[0] != 1:
|
||||
raise ValueError("Argument 'model_index' is required when "
|
||||
"there are multiple models")
|
||||
model_index = 0
|
||||
if target_class is None:
|
||||
if results.probabilities.shape[2] != 2:
|
||||
raise ValueError("Argument 'target_class' is required when the "
|
||||
"class is not binary")
|
||||
target_class = 1
|
||||
actual = results.actual
|
||||
probs = results.probabilities[model_index, :, target_class]
|
||||
nans = np.isnan(actual) + np.isnan(probs)
|
||||
if nans.any():
|
||||
actual = actual[~nans]
|
||||
probs = probs[~nans]
|
||||
return cls(actual == target_class, probs)
|
||||
|
||||
@property
|
||||
def tn(self):
|
||||
return np.arange(self.tot + 1) - self.fn
|
||||
|
||||
@property
|
||||
def tp(self):
|
||||
return self.p - self.fn
|
||||
|
||||
@property
|
||||
def fp(self):
|
||||
return self.n - self.tn
|
||||
|
||||
def ca(self):
|
||||
"""Classification accuracy curve"""
|
||||
return (self.tp + self.tn) / self.tot
|
||||
|
||||
def f1(self):
|
||||
"""F1 curve"""
|
||||
return 2 * self.tp / (2 * self.tp + self.fp + self.fn)
|
||||
|
||||
def sensitivity(self):
|
||||
"""Sensitivity curve"""
|
||||
return self.tp / self.p
|
||||
|
||||
def specificity(self):
|
||||
"""Specificity curve"""
|
||||
return self.tn / self.n
|
||||
|
||||
def precision(self):
|
||||
"""
|
||||
Precision curve
|
||||
|
||||
The last element represents precision at threshold 1. Unless such
|
||||
a probability appears in the data, the precision at this point is
|
||||
undefined. To avoid this, we copy the previous value to the last.
|
||||
"""
|
||||
tp_fp = np.arange(self.tot, -1, -1)
|
||||
tp_fp[-1] = 1 # avoid division by zero
|
||||
prec = self.tp / tp_fp
|
||||
prec[-1] = prec[-2]
|
||||
return prec
|
||||
|
||||
def recall(self):
|
||||
"""Recall curve"""
|
||||
return self.sensitivity()
|
||||
|
||||
def ppv(self):
|
||||
"""PPV curve; see the comment at :obj:`precision`"""
|
||||
return self.precision()
|
||||
|
||||
def npv(self):
|
||||
"""
|
||||
NPV curve
|
||||
|
||||
The first value is undefined (no negative instances). To avoid this,
|
||||
we copy the second value into the first.
|
||||
"""
|
||||
tn_fn = np.arange(self.tot + 1)
|
||||
tn_fn[0] = 1 # avoid division by zero
|
||||
npv = self.tn / tn_fn
|
||||
npv[0] = npv[1]
|
||||
return npv
|
||||
|
||||
def fpr(self):
|
||||
"""FPR curve"""
|
||||
return self.fp / self.n
|
||||
|
||||
def tpr(self):
|
||||
"""TPR curve"""
|
||||
return self.sensitivity()
|
||||
654
pyminer/features/evaluation/scoring.py
Normal file
654
pyminer/features/evaluation/scoring.py
Normal file
@ -0,0 +1,654 @@
|
||||
"""
|
||||
Methods for scoring prediction results (CA, AUC, ...).
|
||||
|
||||
Examples
|
||||
--------
|
||||
>>> import Orange
|
||||
>>> data = Orange.data.Table('iris')
|
||||
>>> learner = Orange.classification.LogisticRegressionLearner()
|
||||
>>> results = Orange.evaluation.TestOnTrainingData(data, [learner])
|
||||
|
||||
"""
|
||||
|
||||
import math
|
||||
|
||||
import numpy as np
|
||||
import sklearn.metrics as skl_metrics
|
||||
from sklearn.metrics import confusion_matrix
|
||||
|
||||
from Orange.data import DiscreteVariable, ContinuousVariable
|
||||
from Orange.misc.wrapper_meta import WrapperMeta
|
||||
|
||||
__all__ = ["CA", "Precision", "Recall", "F1", "PrecisionRecallFSupport", "AUC",
|
||||
"MSE", "RMSE", "MAE", "R2", "compute_CD", "graph_ranks", "LogLoss"]
|
||||
|
||||
|
||||
class ScoreMetaType(WrapperMeta):
|
||||
"""
|
||||
Maintain a registry of non-abstract subclasses and assign the default
|
||||
value of `name`.
|
||||
|
||||
The existing meta class Registry cannot be used since a meta class cannot
|
||||
have multiple inherited __new__ methods."""
|
||||
def __new__(mcs, name, bases, dict_, **kwargs):
|
||||
cls = WrapperMeta.__new__(mcs, name, bases, dict_)
|
||||
# Essentially `if cls is not Score`, except that Score may not exist yet
|
||||
if hasattr(cls, "registry"):
|
||||
if not kwargs.get("abstract"):
|
||||
# Don't use inherited names, look into dict_
|
||||
cls.name = dict_.get("name", name)
|
||||
cls.registry[name] = cls
|
||||
else:
|
||||
cls.registry = {}
|
||||
return cls
|
||||
|
||||
def __init__(cls, *args, **_):
|
||||
WrapperMeta.__init__(cls, *args)
|
||||
|
||||
|
||||
class Score(metaclass=ScoreMetaType):
|
||||
"""
|
||||
${sklpar}
|
||||
Parameters
|
||||
----------
|
||||
results : Orange.evaluation.Results
|
||||
Stored predictions and actual data in model testing.
|
||||
"""
|
||||
__wraps__ = None
|
||||
|
||||
separate_folds = False
|
||||
is_scalar = True
|
||||
is_binary = False #: If true, compute_score accepts `target` and `average`
|
||||
#: If the class doesn't explicitly contain `abstract=True`, it is not
|
||||
#: abstract; essentially, this attribute is not inherited
|
||||
abstract = True
|
||||
class_types = ()
|
||||
name = None
|
||||
long_name = None #: A short user-readable name (e.g. a few words)
|
||||
|
||||
def __new__(cls, results=None, **kwargs):
|
||||
self = super().__new__(cls)
|
||||
if results is not None:
|
||||
self.__init__()
|
||||
return self(results, **kwargs)
|
||||
else:
|
||||
return self
|
||||
|
||||
def __call__(self, results, **kwargs):
|
||||
if self.separate_folds and results.score_by_folds and results.folds:
|
||||
scores = self.scores_by_folds(results, **kwargs)
|
||||
return self.average(scores)
|
||||
|
||||
return self.compute_score(results, **kwargs)
|
||||
|
||||
def average(self, scores):
|
||||
if self.is_scalar:
|
||||
return np.mean(scores, axis=0)
|
||||
return NotImplementedError
|
||||
|
||||
def scores_by_folds(self, results, **kwargs):
|
||||
nfolds = len(results.folds)
|
||||
nmodels = len(results.predicted)
|
||||
if self.is_scalar:
|
||||
scores = np.empty((nfolds, nmodels), dtype=np.float64)
|
||||
else:
|
||||
scores = [None] * nfolds
|
||||
for fold in range(nfolds):
|
||||
fold_results = results.get_fold(fold)
|
||||
scores[fold] = self.compute_score(fold_results, **kwargs)
|
||||
return scores
|
||||
|
||||
def compute_score(self, results):
|
||||
wraps = type(self).__wraps__ # self.__wraps__ is invisible
|
||||
if wraps:
|
||||
return self.from_predicted(results, wraps)
|
||||
else:
|
||||
return NotImplementedError
|
||||
|
||||
@staticmethod
|
||||
def from_predicted(results, score_function, **kwargs):
|
||||
return np.fromiter(
|
||||
(score_function(results.actual, predicted, **kwargs)
|
||||
for predicted in results.predicted),
|
||||
dtype=np.float64, count=len(results.predicted))
|
||||
|
||||
|
||||
class ClassificationScore(Score, abstract=True):
|
||||
class_types = (DiscreteVariable, )
|
||||
|
||||
|
||||
class RegressionScore(Score, abstract=True):
|
||||
class_types = (ContinuousVariable, )
|
||||
|
||||
|
||||
# pylint: disable=invalid-name
|
||||
class CA(ClassificationScore):
|
||||
__wraps__ = skl_metrics.accuracy_score
|
||||
long_name = "Classification accuracy"
|
||||
|
||||
|
||||
class PrecisionRecallFSupport(ClassificationScore):
|
||||
__wraps__ = skl_metrics.precision_recall_fscore_support
|
||||
is_scalar = False
|
||||
|
||||
|
||||
class TargetScore(ClassificationScore):
|
||||
"""
|
||||
Base class for scorers that need a target value (a "positive" class).
|
||||
|
||||
Parameters
|
||||
----------
|
||||
results : Orange.evaluation.Results
|
||||
Stored predictions and actual data in model testing.
|
||||
|
||||
target : int, optional (default=None)
|
||||
Target class value.
|
||||
When None:
|
||||
- if averaging is specified, use all classes and average results
|
||||
- if average is 'binary' and class variable has exactly 2 values,
|
||||
use the value '1' as the positive class
|
||||
|
||||
average: str, method for averaging (default='binary')
|
||||
Default requires a binary class or target to be set.
|
||||
Options: 'weighted', 'macro', 'micro', None
|
||||
|
||||
"""
|
||||
is_binary = True
|
||||
abstract = True
|
||||
__wraps__ = None # Subclasses should set the scoring function
|
||||
|
||||
def compute_score(self, results, target=None, average='binary'):
|
||||
if average == 'binary':
|
||||
if target is None:
|
||||
if len(results.domain.class_var.values) > 2:
|
||||
raise ValueError(
|
||||
"Multiclass data: specify target class or select "
|
||||
"averaging ('weighted', 'macro', 'micro')")
|
||||
target = 1 # Default: use 1 as "positive" class
|
||||
average = None
|
||||
labels = None if target is None else [target]
|
||||
return self.from_predicted(
|
||||
results, type(self).__wraps__, labels=labels, average=average)
|
||||
|
||||
|
||||
class Precision(TargetScore):
|
||||
__wraps__ = skl_metrics.precision_score
|
||||
|
||||
|
||||
class Recall(TargetScore):
|
||||
__wraps__ = skl_metrics.recall_score
|
||||
|
||||
|
||||
class F1(TargetScore):
|
||||
__wraps__ = skl_metrics.f1_score
|
||||
|
||||
|
||||
class AUC(ClassificationScore):
|
||||
"""
|
||||
${sklpar}
|
||||
|
||||
Parameters
|
||||
----------
|
||||
results : Orange.evaluation.Results
|
||||
Stored predictions and actual data in model testing.
|
||||
|
||||
target : int, optional (default=None)
|
||||
Value of class to report.
|
||||
"""
|
||||
__wraps__ = skl_metrics.roc_auc_score
|
||||
separate_folds = True
|
||||
is_binary = True
|
||||
long_name = "Area under ROC curve"
|
||||
|
||||
@staticmethod
|
||||
def calculate_weights(results):
|
||||
classes = np.unique(results.actual)
|
||||
class_cases = [sum(results.actual == class_)
|
||||
for class_ in classes]
|
||||
N = results.actual.shape[0]
|
||||
weights = np.array([c * (N - c) for c in class_cases])
|
||||
wsum = np.sum(weights)
|
||||
if wsum == 0:
|
||||
raise ValueError("Class variable has less than two values")
|
||||
else:
|
||||
return weights / wsum
|
||||
|
||||
@staticmethod
|
||||
def single_class_auc(results, target):
|
||||
y = np.array(results.actual == target, dtype=int)
|
||||
return np.fromiter(
|
||||
(skl_metrics.roc_auc_score(y, probabilities[:, int(target)])
|
||||
for probabilities in results.probabilities),
|
||||
dtype=np.float64, count=len(results.predicted))
|
||||
|
||||
def multi_class_auc(self, results):
|
||||
classes = np.unique(results.actual)
|
||||
weights = self.calculate_weights(results)
|
||||
auc_array = np.array([self.single_class_auc(results, class_)
|
||||
for class_ in classes])
|
||||
return np.sum(auc_array.T * weights, axis=1)
|
||||
|
||||
def compute_score(self, results, target=None, average=None):
|
||||
domain = results.domain
|
||||
n_classes = len(domain.class_var.values)
|
||||
|
||||
if n_classes < 2:
|
||||
raise ValueError("Class variable has less than two values")
|
||||
elif n_classes == 2:
|
||||
return self.single_class_auc(results, 1)
|
||||
else:
|
||||
if target is None:
|
||||
return self.multi_class_auc(results)
|
||||
else:
|
||||
return self.single_class_auc(results, target)
|
||||
|
||||
|
||||
class LogLoss(ClassificationScore):
|
||||
"""
|
||||
${sklpar}
|
||||
|
||||
Parameters
|
||||
----------
|
||||
results : Orange.evaluation.Results
|
||||
Stored predictions and actual data in model testing.
|
||||
|
||||
eps : float
|
||||
Log loss is undefined for p=0 or p=1, so probabilities are
|
||||
clipped to max(eps, min(1 - eps, p)).
|
||||
|
||||
normalize : bool, optional (default=True)
|
||||
If true, return the mean loss per sample.
|
||||
Otherwise, return the sum of the per-sample losses.
|
||||
|
||||
sample_weight : array-like of shape = [n_samples], optional
|
||||
Sample weights.
|
||||
|
||||
Examples
|
||||
--------
|
||||
>>> Orange.evaluation.LogLoss(results)
|
||||
array([ 0.3...])
|
||||
|
||||
"""
|
||||
__wraps__ = skl_metrics.log_loss
|
||||
|
||||
def compute_score(self, results, eps=1e-15, normalize=True,
|
||||
sample_weight=None):
|
||||
return np.fromiter(
|
||||
(skl_metrics.log_loss(results.actual,
|
||||
probabilities,
|
||||
eps=eps,
|
||||
normalize=normalize,
|
||||
sample_weight=sample_weight)
|
||||
for probabilities in results.probabilities),
|
||||
dtype=np.float64, count=len(results.probabilities))
|
||||
|
||||
|
||||
class Specificity(ClassificationScore):
|
||||
is_binary = True
|
||||
|
||||
@staticmethod
|
||||
def calculate_weights(results):
|
||||
classes, counts = np.unique(results.actual, return_counts=True)
|
||||
n = np.array(results.actual).shape[0]
|
||||
return counts / n, classes
|
||||
|
||||
@staticmethod
|
||||
def specificity(y_true, y_pred):
|
||||
tn, fp, _, _ = confusion_matrix(y_true, y_pred).ravel()
|
||||
return tn / (tn + fp)
|
||||
|
||||
def single_class_specificity(self, results, target):
|
||||
y_true = (np.array(results.actual) == target).astype(int)
|
||||
return np.fromiter(
|
||||
(self.specificity(y_true,
|
||||
np.array(predicted == target, dtype=int))
|
||||
for predicted in results.predicted),
|
||||
dtype=np.float64, count=len(results.predicted))
|
||||
|
||||
def multi_class_specificity(self, results):
|
||||
weights, classes = self.calculate_weights(results)
|
||||
scores = np.array([self.single_class_specificity(results, class_)
|
||||
for class_ in classes])
|
||||
return np.sum(scores.T * weights, axis=1)
|
||||
|
||||
def compute_score(self, results, target=None, average="binary"):
|
||||
domain = results.domain
|
||||
n_classes = len(domain.class_var.values)
|
||||
|
||||
if target is None:
|
||||
if average == "weighted":
|
||||
return self.multi_class_specificity(results)
|
||||
elif average == "binary": # average is binary
|
||||
if n_classes != 2:
|
||||
raise ValueError(
|
||||
"Binary averaging needs two classes in data: "
|
||||
"specify target class or use "
|
||||
"weighted averaging.")
|
||||
return self.single_class_specificity(results, 1)
|
||||
else:
|
||||
raise ValueError(
|
||||
"Wrong parameters: For averaging select one of the "
|
||||
"following values: ('weighted', 'binary')")
|
||||
elif target is not None:
|
||||
return self.single_class_specificity(results, target)
|
||||
|
||||
# Regression scores
|
||||
|
||||
|
||||
class MSE(RegressionScore):
|
||||
__wraps__ = skl_metrics.mean_squared_error
|
||||
long_name = "Mean square error"
|
||||
|
||||
|
||||
class RMSE(RegressionScore):
|
||||
long_name = "Root mean square error"
|
||||
|
||||
def compute_score(self, results):
|
||||
return np.sqrt(MSE(results))
|
||||
|
||||
|
||||
class MAE(RegressionScore):
|
||||
__wraps__ = skl_metrics.mean_absolute_error
|
||||
long_name = "Mean absolute error"
|
||||
|
||||
|
||||
# pylint: disable=invalid-name
|
||||
class R2(RegressionScore):
|
||||
__wraps__ = skl_metrics.r2_score
|
||||
long_name = "Coefficient of determination"
|
||||
|
||||
|
||||
class CVRMSE(RegressionScore):
|
||||
long_name = "Coefficient of variation of the RMSE"
|
||||
|
||||
def compute_score(self, results):
|
||||
mean = np.nanmean(results.actual)
|
||||
if mean < 1e-10:
|
||||
raise ValueError("Mean value is too small")
|
||||
return RMSE(results) / mean * 100
|
||||
|
||||
|
||||
# CD scores and plot
|
||||
|
||||
def compute_CD(avranks, n, alpha="0.05", test="nemenyi"):
|
||||
"""
|
||||
Returns critical difference for Nemenyi or Bonferroni-Dunn test
|
||||
according to given alpha (either alpha="0.05" or alpha="0.1") for average
|
||||
ranks and number of tested datasets N. Test can be either "nemenyi" for
|
||||
for Nemenyi two tailed test or "bonferroni-dunn" for Bonferroni-Dunn test.
|
||||
"""
|
||||
k = len(avranks)
|
||||
d = {("nemenyi", "0.05"): [0, 0, 1.959964, 2.343701, 2.569032, 2.727774,
|
||||
2.849705, 2.94832, 3.030879, 3.101730, 3.163684,
|
||||
3.218654, 3.268004, 3.312739, 3.353618, 3.39123,
|
||||
3.426041, 3.458425, 3.488685, 3.517073,
|
||||
3.543799],
|
||||
("nemenyi", "0.1"): [0, 0, 1.644854, 2.052293, 2.291341, 2.459516,
|
||||
2.588521, 2.692732, 2.779884, 2.854606, 2.919889,
|
||||
2.977768, 3.029694, 3.076733, 3.119693, 3.159199,
|
||||
3.195743, 3.229723, 3.261461, 3.291224, 3.319233],
|
||||
("bonferroni-dunn", "0.05"): [0, 0, 1.960, 2.241, 2.394, 2.498, 2.576,
|
||||
2.638, 2.690, 2.724, 2.773],
|
||||
("bonferroni-dunn", "0.1"): [0, 0, 1.645, 1.960, 2.128, 2.241, 2.326,
|
||||
2.394, 2.450, 2.498, 2.539]}
|
||||
q = d[(test, alpha)]
|
||||
cd = q[k] * (k * (k + 1) / (6.0 * n)) ** 0.5
|
||||
return cd
|
||||
|
||||
|
||||
def graph_ranks(avranks, names, cd=None, cdmethod=None, lowv=None, highv=None,
|
||||
width=6, textspace=1, reverse=False, filename=None, **kwargs):
|
||||
"""
|
||||
Draws a CD graph, which is used to display the differences in methods'
|
||||
performance. See Janez Demsar, Statistical Comparisons of Classifiers over
|
||||
Multiple Data Sets, 7(Jan):1--30, 2006.
|
||||
|
||||
Needs matplotlib to work.
|
||||
|
||||
The image is ploted on `plt` imported using
|
||||
`import matplotlib.pyplot as plt`.
|
||||
|
||||
Args:
|
||||
avranks (list of float): average ranks of methods.
|
||||
names (list of str): names of methods.
|
||||
cd (float): Critical difference used for statistically significance of
|
||||
difference between methods.
|
||||
cdmethod (int, optional): the method that is compared with other methods
|
||||
If omitted, show pairwise comparison of methods
|
||||
lowv (int, optional): the lowest shown rank
|
||||
highv (int, optional): the highest shown rank
|
||||
width (int, optional): default width in inches (default: 6)
|
||||
textspace (int, optional): space on figure sides (in inches) for the
|
||||
method names (default: 1)
|
||||
reverse (bool, optional): if set to `True`, the lowest rank is on the
|
||||
right (default: `False`)
|
||||
filename (str, optional): output file name (with extension). If not
|
||||
given, the function does not write a file.
|
||||
"""
|
||||
try:
|
||||
import matplotlib.pyplot as plt
|
||||
from matplotlib.backends.backend_agg import FigureCanvasAgg
|
||||
except ImportError:
|
||||
raise ImportError("Function graph_ranks requires matplotlib.")
|
||||
|
||||
width = float(width)
|
||||
textspace = float(textspace)
|
||||
|
||||
def nth(l, n):
|
||||
"""
|
||||
Returns only nth elemnt in a list.
|
||||
"""
|
||||
n = lloc(l, n)
|
||||
return [a[n] for a in l]
|
||||
|
||||
def lloc(l, n):
|
||||
"""
|
||||
List location in list of list structure.
|
||||
Enable the use of negative locations:
|
||||
-1 is the last element, -2 second last...
|
||||
"""
|
||||
if n < 0:
|
||||
return len(l[0]) + n
|
||||
else:
|
||||
return n
|
||||
|
||||
def mxrange(lr):
|
||||
"""
|
||||
Multiple xranges. Can be used to traverse matrices.
|
||||
This function is very slow due to unknown number of
|
||||
parameters.
|
||||
|
||||
>>> mxrange([3,5])
|
||||
[(0, 0), (0, 1), (0, 2), (1, 0), (1, 1), (1, 2)]
|
||||
|
||||
>>> mxrange([[3,5,1],[9,0,-3]])
|
||||
[(3, 9), (3, 6), (3, 3), (4, 9), (4, 6), (4, 3)]
|
||||
|
||||
"""
|
||||
if not len(lr):
|
||||
yield ()
|
||||
else:
|
||||
# it can work with single numbers
|
||||
index = lr[0]
|
||||
if isinstance(index, int):
|
||||
index = [index]
|
||||
for a in range(*index):
|
||||
for b in mxrange(lr[1:]):
|
||||
yield tuple([a] + list(b))
|
||||
|
||||
def print_figure(fig, *args, **kwargs):
|
||||
canvas = FigureCanvasAgg(fig)
|
||||
canvas.print_figure(*args, **kwargs)
|
||||
|
||||
sums = avranks
|
||||
|
||||
tempsort = sorted([(a, i) for i, a in enumerate(sums)], reverse=reverse)
|
||||
ssums = nth(tempsort, 0)
|
||||
sortidx = nth(tempsort, 1)
|
||||
nnames = [names[x] for x in sortidx]
|
||||
|
||||
if lowv is None:
|
||||
lowv = min(1, int(math.floor(min(ssums))))
|
||||
if highv is None:
|
||||
highv = max(len(avranks), int(math.ceil(max(ssums))))
|
||||
|
||||
cline = 0.4
|
||||
|
||||
k = len(sums)
|
||||
|
||||
lines = None
|
||||
|
||||
linesblank = 0
|
||||
scalewidth = width - 2 * textspace
|
||||
|
||||
def rankpos(rank):
|
||||
if not reverse:
|
||||
a = rank - lowv
|
||||
else:
|
||||
a = highv - rank
|
||||
return textspace + scalewidth / (highv - lowv) * a
|
||||
|
||||
distanceh = 0.25
|
||||
|
||||
if cd and cdmethod is None:
|
||||
# get pairs of non significant methods
|
||||
|
||||
def get_lines(sums, hsd):
|
||||
# get all pairs
|
||||
lsums = len(sums)
|
||||
allpairs = [(i, j) for i, j in mxrange([[lsums], [lsums]]) if j > i]
|
||||
# remove not significant
|
||||
notSig = [(i, j) for i, j in allpairs
|
||||
if abs(sums[i] - sums[j]) <= hsd]
|
||||
# keep only longest
|
||||
|
||||
def no_longer(ij_tuple, notSig):
|
||||
i, j = ij_tuple
|
||||
for i1, j1 in notSig:
|
||||
if (i1 <= i and j1 > j) or (i1 < i and j1 >= j):
|
||||
return False
|
||||
return True
|
||||
|
||||
longest = [(i, j) for i, j in notSig if no_longer((i, j), notSig)]
|
||||
|
||||
return longest
|
||||
|
||||
lines = get_lines(ssums, cd)
|
||||
linesblank = 0.2 + 0.2 + (len(lines) - 1) * 0.1
|
||||
|
||||
# add scale
|
||||
distanceh = 0.25
|
||||
cline += distanceh
|
||||
|
||||
# calculate height needed height of an image
|
||||
minnotsignificant = max(2 * 0.2, linesblank)
|
||||
height = cline + ((k + 1) / 2) * 0.2 + minnotsignificant
|
||||
|
||||
fig = plt.figure(figsize=(width, height))
|
||||
fig.set_facecolor('white')
|
||||
ax = fig.add_axes([0, 0, 1, 1]) # reverse y axis
|
||||
ax.set_axis_off()
|
||||
|
||||
hf = 1. / height # height factor
|
||||
wf = 1. / width
|
||||
|
||||
def hfl(l):
|
||||
return [a * hf for a in l]
|
||||
|
||||
def wfl(l):
|
||||
return [a * wf for a in l]
|
||||
|
||||
|
||||
# Upper left corner is (0,0).
|
||||
ax.plot([0, 1], [0, 1], c="w")
|
||||
ax.set_xlim(0, 1)
|
||||
ax.set_ylim(1, 0)
|
||||
|
||||
def line(l, color='k', **kwargs):
|
||||
"""
|
||||
Input is a list of pairs of points.
|
||||
"""
|
||||
ax.plot(wfl(nth(l, 0)), hfl(nth(l, 1)), color=color, **kwargs)
|
||||
|
||||
def text(x, y, s, *args, **kwargs):
|
||||
ax.text(wf * x, hf * y, s, *args, **kwargs)
|
||||
|
||||
line([(textspace, cline), (width - textspace, cline)], linewidth=0.7)
|
||||
|
||||
bigtick = 0.1
|
||||
smalltick = 0.05
|
||||
|
||||
tick = None
|
||||
for a in list(np.arange(lowv, highv, 0.5)) + [highv]:
|
||||
tick = smalltick
|
||||
if a == int(a):
|
||||
tick = bigtick
|
||||
line([(rankpos(a), cline - tick / 2),
|
||||
(rankpos(a), cline)],
|
||||
linewidth=0.7)
|
||||
|
||||
for a in range(lowv, highv + 1):
|
||||
text(rankpos(a), cline - tick / 2 - 0.05, str(a),
|
||||
ha="center", va="bottom")
|
||||
|
||||
k = len(ssums)
|
||||
|
||||
for i in range(math.ceil(k / 2)):
|
||||
chei = cline + minnotsignificant + i * 0.2
|
||||
line([(rankpos(ssums[i]), cline),
|
||||
(rankpos(ssums[i]), chei),
|
||||
(textspace - 0.1, chei)],
|
||||
linewidth=0.7)
|
||||
text(textspace - 0.2, chei, nnames[i], ha="right", va="center")
|
||||
|
||||
for i in range(math.ceil(k / 2), k):
|
||||
chei = cline + minnotsignificant + (k - i - 1) * 0.2
|
||||
line([(rankpos(ssums[i]), cline),
|
||||
(rankpos(ssums[i]), chei),
|
||||
(textspace + scalewidth + 0.1, chei)],
|
||||
linewidth=0.7)
|
||||
text(textspace + scalewidth + 0.2, chei, nnames[i],
|
||||
ha="left", va="center")
|
||||
|
||||
if cd and cdmethod is None:
|
||||
# upper scale
|
||||
if not reverse:
|
||||
begin, end = rankpos(lowv), rankpos(lowv + cd)
|
||||
else:
|
||||
begin, end = rankpos(highv), rankpos(highv - cd)
|
||||
|
||||
line([(begin, distanceh), (end, distanceh)], linewidth=0.7)
|
||||
line([(begin, distanceh + bigtick / 2),
|
||||
(begin, distanceh - bigtick / 2)],
|
||||
linewidth=0.7)
|
||||
line([(end, distanceh + bigtick / 2),
|
||||
(end, distanceh - bigtick / 2)],
|
||||
linewidth=0.7)
|
||||
text((begin + end) / 2, distanceh - 0.05, "CD",
|
||||
ha="center", va="bottom")
|
||||
|
||||
# no-significance lines
|
||||
def draw_lines(lines, side=0.05, height=0.1):
|
||||
start = cline + 0.2
|
||||
for l, r in lines:
|
||||
line([(rankpos(ssums[l]) - side, start),
|
||||
(rankpos(ssums[r]) + side, start)],
|
||||
linewidth=2.5)
|
||||
start += height
|
||||
|
||||
draw_lines(lines)
|
||||
|
||||
elif cd:
|
||||
begin = rankpos(avranks[cdmethod] - cd)
|
||||
end = rankpos(avranks[cdmethod] + cd)
|
||||
line([(begin, cline), (end, cline)],
|
||||
linewidth=2.5)
|
||||
line([(begin, cline + bigtick / 2),
|
||||
(begin, cline - bigtick / 2)],
|
||||
linewidth=2.5)
|
||||
line([(end, cline + bigtick / 2),
|
||||
(end, cline - bigtick / 2)],
|
||||
linewidth=2.5)
|
||||
|
||||
if filename:
|
||||
print_figure(fig, filename, **kwargs)
|
||||
825
pyminer/features/evaluation/testing.py
Normal file
825
pyminer/features/evaluation/testing.py
Normal file
@ -0,0 +1,825 @@
|
||||
# __new__ methods have different arguments
|
||||
# pylint: disable=arguments-differ
|
||||
from warnings import warn
|
||||
from collections import namedtuple
|
||||
from time import time
|
||||
|
||||
import numpy as np
|
||||
|
||||
import sklearn.model_selection as skl
|
||||
|
||||
from Orange.data import Table, Domain, ContinuousVariable, DiscreteVariable
|
||||
|
||||
__all__ = ["Results", "CrossValidation", "LeaveOneOut", "TestOnTrainingData",
|
||||
"ShuffleSplit", "TestOnTestData", "sample", "CrossValidationFeature"]
|
||||
|
||||
_MpResults = namedtuple('_MpResults', ('fold_i', 'learner_i', 'model',
|
||||
'failed', 'n_values', 'values',
|
||||
'probs', 'train_time', 'test_time'))
|
||||
|
||||
|
||||
def _identity(x):
|
||||
return x
|
||||
|
||||
|
||||
def _mp_worker(fold_i, train_data, test_data, learner_i, learner,
|
||||
store_models):
|
||||
predicted, probs, model, failed = None, None, None, False
|
||||
train_time, test_time = None, None
|
||||
try:
|
||||
if not train_data or not test_data:
|
||||
raise RuntimeError('Test fold is empty')
|
||||
# training
|
||||
t0 = time()
|
||||
model = learner(train_data)
|
||||
train_time = time() - t0
|
||||
t0 = time()
|
||||
# testing
|
||||
if train_data.domain.has_discrete_class:
|
||||
predicted, probs = model(test_data, model.ValueProbs)
|
||||
elif train_data.domain.has_continuous_class:
|
||||
predicted = model(test_data, model.Value)
|
||||
test_time = time() - t0
|
||||
# Different models can fail at any time raising any exception
|
||||
except Exception as ex: # pylint: disable=broad-except
|
||||
failed = ex
|
||||
return _MpResults(fold_i, learner_i, store_models and model,
|
||||
failed, len(test_data), predicted, probs,
|
||||
train_time, test_time)
|
||||
|
||||
|
||||
class Results:
|
||||
"""
|
||||
Class for storing predictions in model testing.
|
||||
|
||||
Attributes:
|
||||
data (Optional[Table]): Data used for testing.
|
||||
|
||||
models (Optional[List[Model]]): A list of induced models.
|
||||
|
||||
row_indices (np.ndarray): Indices of rows in `data` that were used in
|
||||
testing, stored as a numpy vector of length `nrows`.
|
||||
Values of `actual[i]`, `predicted[i]` and `probabilities[i]` refer
|
||||
to the target value of instance, that is, the i-th test instance
|
||||
is `data[row_indices[i]]`, its actual class is `actual[i]`, and
|
||||
the prediction by m-th method is `predicted[m, i]`.
|
||||
|
||||
nrows (int): The number of test instances (including duplicates);
|
||||
`nrows` equals the length of `row_indices` and `actual`, and the
|
||||
second dimension of `predicted` and `probabilities`.
|
||||
|
||||
actual (np.ndarray): true values of target variable in a vector of
|
||||
length `nrows`.
|
||||
|
||||
predicted (np.ndarray): predicted values of target variable in an array
|
||||
of shape (number-of-methods, `nrows`)
|
||||
|
||||
probabilities (Optional[np.ndarray]): predicted probabilities
|
||||
(for discrete target variables) in an array of shape
|
||||
(number-of-methods, `nrows`, number-of-classes)
|
||||
|
||||
folds (List[Slice or List[int]]): a list of indices (or slice objects)
|
||||
corresponding to testing data subsets, that is,
|
||||
`row_indices[folds[i]]` contains row indices used in fold i, so
|
||||
`data[row_indices[folds[i]]]` is the corresponding testing data
|
||||
|
||||
train_time (np.ndarray): training times of batches
|
||||
|
||||
test_time (np.ndarray): testing times of batches
|
||||
"""
|
||||
def __init__(self, data=None, *,
|
||||
nmethods=None, nrows=None, nclasses=None,
|
||||
domain=None,
|
||||
row_indices=None, folds=None, score_by_folds=True,
|
||||
learners=None, models=None, failed=None,
|
||||
actual=None, predicted=None, probabilities=None,
|
||||
store_data=None, store_models=None,
|
||||
train_time=None, test_time=None):
|
||||
"""
|
||||
Construct an instance.
|
||||
|
||||
The constructor stores the given data, and creates empty arrays
|
||||
`actual`, `predicted` and `probabilities` if ther are not given but
|
||||
sufficient data is provided to deduct their shapes.
|
||||
|
||||
The function
|
||||
|
||||
- set any attributes specified directly through arguments.
|
||||
- infers the number of methods, rows and classes from other data
|
||||
and/or check their overall consistency.
|
||||
- Prepare empty arrays `actual`, `predicted`, `probabilities` and
|
||||
`failed` if the are not given. If not enough data is available,
|
||||
the corresponding arrays are `None`.
|
||||
|
||||
Args:
|
||||
data (Orange.data.Table): stored data from which test was sampled
|
||||
nmethods (int): number of methods; can be inferred (or must match)
|
||||
the size of `learners`, `models`, `failed`, `predicted` and
|
||||
`probabilities`
|
||||
nrows (int): number of data instances; can be inferred (or must
|
||||
match) `data`, `row_indices`, `actual`, `predicted` and
|
||||
`probabilities`
|
||||
nclasses (int): number of class values (`None` if continuous); can
|
||||
be inferred (or must match) from `domain.class_var` or
|
||||
`probabilities`
|
||||
domain (Orange.data.Domain): data domain; can be inferred (or must)
|
||||
match `data.domain`
|
||||
row_indices (np.ndarray): see class documentation
|
||||
folds (np.ndarray): see class documentation
|
||||
score_by_folds (np.ndarray): see class documentation
|
||||
learners (np.ndarray): see class documentation
|
||||
models (np.ndarray): see class documentation
|
||||
failed (list of str): see class documentation
|
||||
actual (np.ndarray): see class documentation
|
||||
predicted (np.ndarray): see class documentation
|
||||
probabilities (np.ndarray): see class documentation
|
||||
store_data (bool): ignored; kept for backward compatibility
|
||||
store_models (bool): ignored; kept for backward compatibility
|
||||
"""
|
||||
|
||||
# Set given data directly from arguments
|
||||
self.data = data
|
||||
self.domain = domain
|
||||
|
||||
self.row_indices = row_indices
|
||||
self.folds = folds
|
||||
self.score_by_folds = score_by_folds
|
||||
|
||||
self.learners = learners
|
||||
self.models = models
|
||||
|
||||
self.actual = actual
|
||||
self.predicted = predicted
|
||||
self.probabilities = probabilities
|
||||
self.failed = failed
|
||||
|
||||
self.train_time = train_time
|
||||
self.test_time = test_time
|
||||
|
||||
# Guess the rest -- or check for ambguities
|
||||
def set_or_raise(value, exp_values, msg):
|
||||
for exp_value in exp_values:
|
||||
if exp_value is False:
|
||||
continue
|
||||
if value is None:
|
||||
value = exp_value
|
||||
elif value != exp_value:
|
||||
raise ValueError(msg)
|
||||
return value
|
||||
domain = self.domain = set_or_raise(
|
||||
domain, [data is not None and data.domain],
|
||||
"mismatching domain")
|
||||
self.nrows = nrows = set_or_raise(
|
||||
nrows, [actual is not None and len(actual),
|
||||
row_indices is not None and len(row_indices),
|
||||
predicted is not None and predicted.shape[1],
|
||||
probabilities is not None and probabilities.shape[1]],
|
||||
"mismatching number of rows")
|
||||
if domain is not None and domain.has_continuous_class:
|
||||
if nclasses is not None:
|
||||
raise ValueError(
|
||||
"regression results cannot have non-None 'nclasses'")
|
||||
if probabilities is not None:
|
||||
raise ValueError(
|
||||
"regression results cannot have 'probabilities'")
|
||||
nclasses = set_or_raise(
|
||||
nclasses, [domain is not None and domain.has_discrete_class and
|
||||
len(domain.class_var.values),
|
||||
probabilities is not None and probabilities.shape[2]],
|
||||
"mismatching number of class values")
|
||||
nmethods = set_or_raise(
|
||||
nmethods, [learners is not None and len(learners),
|
||||
models is not None and models.shape[1],
|
||||
failed is not None and len(failed),
|
||||
predicted is not None and predicted.shape[0],
|
||||
probabilities is not None and probabilities.shape[0]],
|
||||
"mismatching number of methods")
|
||||
|
||||
# Prepare empty arrays
|
||||
if actual is None \
|
||||
and nrows is not None:
|
||||
self.actual = np.empty(nrows)
|
||||
|
||||
if predicted is None \
|
||||
and nmethods is not None and nrows is not None:
|
||||
self.predicted = np.empty((nmethods, nrows))
|
||||
|
||||
if probabilities is None \
|
||||
and nmethods is not None and nrows is not None \
|
||||
and nclasses is not None:
|
||||
self.probabilities = \
|
||||
np.empty((nmethods, nrows, nclasses))
|
||||
|
||||
if failed is None \
|
||||
and nmethods is not None:
|
||||
self.failed = [False] * nmethods
|
||||
|
||||
def get_fold(self, fold):
|
||||
results = Results()
|
||||
results.data = self.data
|
||||
|
||||
if self.folds is None:
|
||||
raise ValueError("This 'Results' instance does not have folds.")
|
||||
|
||||
if self.models is not None:
|
||||
results.models = self.models[fold]
|
||||
|
||||
results.row_indices = self.row_indices[self.folds[fold]]
|
||||
results.actual = self.actual[self.folds[fold]]
|
||||
results.predicted = self.predicted[:, self.folds[fold]]
|
||||
results.domain = self.domain
|
||||
|
||||
if self.probabilities is not None:
|
||||
results.probabilities = self.probabilities[:, self.folds[fold]]
|
||||
|
||||
return results
|
||||
|
||||
def get_augmented_data(self, model_names,
|
||||
include_attrs=True, include_predictions=True,
|
||||
include_probabilities=True):
|
||||
"""
|
||||
Return the test data table augmented with meta attributes containing
|
||||
predictions, probabilities (if the task is classification) and fold
|
||||
indices.
|
||||
|
||||
Args:
|
||||
model_names (list of str): names of models
|
||||
include_attrs (bool):
|
||||
if set to `False`, original attributes are removed
|
||||
include_predictions (bool):
|
||||
if set to `False`, predictions are not added
|
||||
include_probabilities (bool):
|
||||
if set to `False`, probabilities are not added
|
||||
|
||||
Returns:
|
||||
augmented_data (Orange.data.Table):
|
||||
data augmented with predictions, probabilities and fold indices
|
||||
|
||||
"""
|
||||
assert self.predicted.shape[0] == len(model_names)
|
||||
|
||||
data = self.data[self.row_indices]
|
||||
class_var = data.domain.class_var
|
||||
classification = class_var and class_var.is_discrete
|
||||
|
||||
new_meta_attr = []
|
||||
new_meta_vals = np.empty((len(data), 0))
|
||||
|
||||
if classification:
|
||||
# predictions
|
||||
if include_predictions:
|
||||
new_meta_attr += (
|
||||
DiscreteVariable(name=name, values=class_var.values)
|
||||
for name in model_names)
|
||||
new_meta_vals = np.hstack((new_meta_vals, self.predicted.T))
|
||||
|
||||
# probabilities
|
||||
if include_probabilities:
|
||||
for name in model_names:
|
||||
new_meta_attr += (
|
||||
ContinuousVariable(name=f"{name} ({value})")
|
||||
for value in class_var.values)
|
||||
|
||||
for i in self.probabilities:
|
||||
new_meta_vals = np.hstack((new_meta_vals, i))
|
||||
|
||||
elif include_predictions:
|
||||
# regression
|
||||
new_meta_attr += (ContinuousVariable(name=name)
|
||||
for name in model_names)
|
||||
new_meta_vals = np.hstack((new_meta_vals, self.predicted.T))
|
||||
|
||||
# add fold info
|
||||
if self.folds is not None:
|
||||
new_meta_attr.append(
|
||||
DiscreteVariable(
|
||||
name="Fold",
|
||||
values=[str(i + 1) for i in range(len(self.folds))]))
|
||||
fold = np.empty((len(data), 1))
|
||||
for i, s in enumerate(self.folds):
|
||||
fold[s, 0] = i
|
||||
new_meta_vals = np.hstack((new_meta_vals, fold))
|
||||
|
||||
# append new columns to meta attributes
|
||||
new_meta_attr = list(data.domain.metas) + new_meta_attr
|
||||
new_meta_vals = np.hstack((data.metas, new_meta_vals))
|
||||
|
||||
attrs = data.domain.attributes if include_attrs else []
|
||||
domain = Domain(attrs, data.domain.class_vars, metas=new_meta_attr)
|
||||
predictions = data.transform(domain)
|
||||
predictions.metas = new_meta_vals
|
||||
predictions.name = data.name
|
||||
return predictions
|
||||
|
||||
def split_by_model(self):
|
||||
"""
|
||||
Split evaluation results by models.
|
||||
|
||||
The method generates instances of `Results` containing data for single
|
||||
models
|
||||
"""
|
||||
data = self.data
|
||||
nmethods = len(self.predicted)
|
||||
for i in range(nmethods):
|
||||
res = Results()
|
||||
res.data = data
|
||||
res.domain = self.domain
|
||||
res.learners = [self.learners[i]]
|
||||
res.row_indices = self.row_indices
|
||||
res.actual = self.actual
|
||||
res.folds = self.folds
|
||||
res.score_by_folds = self.score_by_folds
|
||||
res.test_time = self.test_time[i]
|
||||
res.train_time = self.train_time[i]
|
||||
|
||||
res.predicted = self.predicted[(i,), :]
|
||||
if getattr(self, "probabilities", None) is not None:
|
||||
res.probabilities = self.probabilities[(i,), :, :]
|
||||
|
||||
if self.models is not None:
|
||||
res.models = self.models[:, i:i + 1]
|
||||
|
||||
res.failed = [self.failed[i]]
|
||||
yield res
|
||||
|
||||
|
||||
class Validation:
|
||||
"""
|
||||
Base class for different testing schemata such as cross validation and
|
||||
testing on separate data set.
|
||||
|
||||
If `data` is some data table and `learners` is a list of learning
|
||||
algorithms. This will run 5-fold cross validation and store the results
|
||||
in `res`.
|
||||
|
||||
cv = CrossValidation(k=5)
|
||||
res = cv(data, learners)
|
||||
|
||||
If constructor was given data and learning algorithms (as in
|
||||
`res = CrossValidation(data, learners, k=5)`, it used to automagically
|
||||
call the instance after constructing it and return `Results` instead
|
||||
of an instance of `Validation`. This functionality
|
||||
is deprecated and will be removed in the future.
|
||||
|
||||
Attributes:
|
||||
store_data (bool): a flag defining whether the data is stored
|
||||
store_models (bool): a flag defining whether the models are stored
|
||||
"""
|
||||
score_by_folds = False
|
||||
|
||||
def __new__(cls,
|
||||
data=None, learners=None, preprocessor=None, test_data=None,
|
||||
*, callback=None, store_data=False, store_models=False,
|
||||
n_jobs=None, **kwargs):
|
||||
self = super().__new__(cls)
|
||||
|
||||
if (learners is None) != (data is None):
|
||||
raise ValueError(
|
||||
"learners and train_data must both be present or not")
|
||||
if learners is None:
|
||||
if preprocessor is not None:
|
||||
raise ValueError("preprocessor cannot be given if learners "
|
||||
"and train_data are omitted")
|
||||
if callback is not None:
|
||||
raise ValueError("callback cannot be given if learners "
|
||||
"and train_data are omitted")
|
||||
return self
|
||||
|
||||
warn("calling Validation's constructor with data and learners "
|
||||
"is deprecated;\nconstruct an instance and call it",
|
||||
DeprecationWarning, stacklevel=2)
|
||||
|
||||
# Explicitly call __init__ because Python won't
|
||||
self.__init__(store_data=store_data, store_models=store_models,
|
||||
**kwargs)
|
||||
if test_data is not None:
|
||||
test_data_kwargs = {"test_data": test_data}
|
||||
else:
|
||||
test_data_kwargs = {}
|
||||
return self(data, learners=learners, preprocessor=preprocessor,
|
||||
callback=callback, **test_data_kwargs)
|
||||
|
||||
# Note: this will be called only if __new__ doesn't have data and learners
|
||||
def __init__(self, *, store_data=False, store_models=False):
|
||||
self.store_data = store_data
|
||||
self.store_models = store_models
|
||||
|
||||
def fit(self, *args, **kwargs):
|
||||
warn("Validation.fit is deprecated; use the call operator",
|
||||
DeprecationWarning)
|
||||
return self(*args, **kwargs)
|
||||
|
||||
def __call__(self, data, learners, preprocessor=None, *, callback=None):
|
||||
"""
|
||||
Args:
|
||||
data (Orange.data.Table): data to be used (usually split) into
|
||||
training and testing
|
||||
learners (list of Orange.Learner): a list of learning algorithms
|
||||
preprocessor (Orange.preprocess.Preprocess): preprocessor applied
|
||||
on training data
|
||||
callback (Callable): a function called to notify about the progress
|
||||
|
||||
Returns:
|
||||
results (Result): results of testing
|
||||
"""
|
||||
if preprocessor is None:
|
||||
preprocessor = _identity
|
||||
if callback is None:
|
||||
callback = _identity
|
||||
indices = self.get_indices(data)
|
||||
folds, row_indices, actual = self.prepare_arrays(data, indices)
|
||||
|
||||
data_splits = (
|
||||
(fold_i, preprocessor(data[train_i]), data[test_i])
|
||||
for fold_i, (train_i, test_i) in enumerate(indices))
|
||||
args_iter = (
|
||||
(fold_i, data, test_data, learner_i, learner, self.store_models)
|
||||
for (fold_i, data, test_data) in data_splits
|
||||
for (learner_i, learner) in enumerate(learners))
|
||||
|
||||
part_results = []
|
||||
parts = np.linspace(.0, .99, len(learners) * len(indices) + 1)[1:]
|
||||
for progress, part in zip(parts, args_iter):
|
||||
part_results.append(_mp_worker(*(part + ())))
|
||||
callback(progress)
|
||||
callback(1)
|
||||
|
||||
results = Results(
|
||||
data=data if self.store_data else None,
|
||||
domain=data.domain,
|
||||
nrows=len(row_indices), learners=learners,
|
||||
row_indices=row_indices, folds=folds, actual=actual,
|
||||
score_by_folds=self.score_by_folds,
|
||||
train_time=np.zeros((len(learners),)),
|
||||
test_time=np.zeros((len(learners),)))
|
||||
|
||||
if self.store_models:
|
||||
results.models = np.tile(None, (len(indices), len(learners)))
|
||||
self._collect_part_results(results, part_results)
|
||||
return results
|
||||
|
||||
@classmethod
|
||||
def prepare_arrays(cls, data, indices):
|
||||
"""Prepare `folds`, `row_indices` and `actual`.
|
||||
|
||||
The method is used by `__call__`. While functional, it may be
|
||||
overriden in subclasses for speed-ups.
|
||||
|
||||
Args:
|
||||
data (Orange.data.Table): data use for testing
|
||||
indices (list of vectors):
|
||||
indices of data instances in each test sample
|
||||
|
||||
Returns:
|
||||
folds: (np.ndarray): see class documentation
|
||||
row_indices: (np.ndarray): see class documentation
|
||||
actual: (np.ndarray): see class documentation
|
||||
"""
|
||||
folds = []
|
||||
row_indices = []
|
||||
|
||||
ptr = 0
|
||||
for _, test in indices:
|
||||
folds.append(slice(ptr, ptr + len(test)))
|
||||
row_indices.append(test)
|
||||
ptr += len(test)
|
||||
|
||||
row_indices = np.concatenate(row_indices, axis=0)
|
||||
actual = data[row_indices].Y.ravel()
|
||||
return folds, row_indices, actual
|
||||
|
||||
@staticmethod
|
||||
def get_indices(data):
|
||||
"""
|
||||
Return a list of arrays of indices of test data instance
|
||||
|
||||
For example, in k-fold CV, the result is a list with `k` elements,
|
||||
each containing approximately `len(data) / k` nonoverlapping indices
|
||||
into `data`.
|
||||
|
||||
This method is abstract and must be implemented in derived classes
|
||||
unless they provide their own implementation of the `__call__`
|
||||
method.
|
||||
|
||||
Args:
|
||||
data (Orange.data.Table): test data
|
||||
|
||||
Returns:
|
||||
indices (list of np.ndarray):
|
||||
a list of arrays of indices into `data`
|
||||
"""
|
||||
raise NotImplementedError()
|
||||
|
||||
def _collect_part_results(self, results, part_results):
|
||||
part_results = sorted(part_results)
|
||||
|
||||
ptr, prev_fold_i, prev_n_values = 0, 0, 0
|
||||
for res in part_results:
|
||||
if res.fold_i != prev_fold_i:
|
||||
ptr += prev_n_values
|
||||
prev_fold_i = res.fold_i
|
||||
result_slice = slice(ptr, ptr + res.n_values)
|
||||
prev_n_values = res.n_values
|
||||
|
||||
if res.failed:
|
||||
results.failed[res.learner_i] = res.failed
|
||||
continue
|
||||
|
||||
if self.store_models:
|
||||
results.models[res.fold_i][res.learner_i] = res.model
|
||||
|
||||
results.predicted[res.learner_i][result_slice] = res.values
|
||||
results.train_time[res.learner_i] += res.train_time
|
||||
results.test_time[res.learner_i] += res.test_time
|
||||
if res.probs is not None:
|
||||
results.probabilities[res.learner_i][result_slice, :] = \
|
||||
res.probs
|
||||
|
||||
|
||||
class CrossValidation(Validation):
|
||||
"""
|
||||
K-fold cross validation
|
||||
|
||||
Attributes:
|
||||
k (int): number of folds (default: 10)
|
||||
random_state (int):
|
||||
seed for random number generator (default: 0). If set to `None`,
|
||||
a different seed is used each time
|
||||
stratified (bool):
|
||||
flag deciding whether to perform stratified cross-validation.
|
||||
If `True` but the class sizes don't allow it, it uses non-stratified
|
||||
validataion and adds a list `warning` with a warning message(s) to
|
||||
the `Result`.
|
||||
"""
|
||||
# TODO: list `warning` contains just repetitions of the same message
|
||||
# replace with a flag in `Results`?
|
||||
def __init__(self, k=10, stratified=True, random_state=0,
|
||||
store_data=False, store_models=False, warnings=None):
|
||||
super().__init__(store_data=store_data, store_models=store_models)
|
||||
self.k = k
|
||||
self.stratified = stratified
|
||||
self.random_state = random_state
|
||||
self.warnings = [] if warnings is None else warnings
|
||||
|
||||
def get_indices(self, data):
|
||||
if self.stratified and data.domain.has_discrete_class:
|
||||
try:
|
||||
splitter = skl.StratifiedKFold(
|
||||
self.k, shuffle=True, random_state=self.random_state
|
||||
)
|
||||
splitter.get_n_splits(data.X, data.Y)
|
||||
return list(splitter.split(data.X, data.Y))
|
||||
except ValueError:
|
||||
self.warnings.append("Using non-stratified sampling.")
|
||||
|
||||
splitter = skl.KFold(
|
||||
self.k, shuffle=True, random_state=self.random_state)
|
||||
splitter.get_n_splits(data)
|
||||
return list(splitter.split(data))
|
||||
|
||||
|
||||
class CrossValidationFeature(Validation):
|
||||
"""
|
||||
Cross validation with folds according to values of a feature.
|
||||
|
||||
Attributes:
|
||||
feature (Orange.data.Variable): the feature defining the folds
|
||||
"""
|
||||
def __init__(self, feature=None,
|
||||
store_data=False, store_models=False, warnings=None):
|
||||
super().__init__(store_data=store_data, store_models=store_models)
|
||||
self.feature = feature
|
||||
|
||||
def get_indices(self, data):
|
||||
data = data.transform(Domain([self.feature], None))
|
||||
values = data[:, self.feature].X
|
||||
indices = []
|
||||
for v in range(len(self.feature.values)):
|
||||
test_index = np.where(values == v)[0]
|
||||
train_index = np.where((values != v) & (~np.isnan(values)))[0]
|
||||
if test_index.size and train_index.size:
|
||||
indices.append((train_index, test_index))
|
||||
if not indices:
|
||||
raise ValueError(
|
||||
f"'{self.feature.name}' does not have at least two distinct "
|
||||
"values on the data")
|
||||
return indices
|
||||
|
||||
|
||||
class LeaveOneOut(Validation):
|
||||
"""Leave-one-out testing"""
|
||||
score_by_folds = False
|
||||
|
||||
def get_indices(self, data):
|
||||
splitter = skl.LeaveOneOut()
|
||||
splitter.get_n_splits(data)
|
||||
return list(splitter.split(data))
|
||||
|
||||
@staticmethod
|
||||
def prepare_arrays(data, indices):
|
||||
# sped up version of super().prepare_arrays(data)
|
||||
row_indices = np.arange(len(data))
|
||||
return row_indices, row_indices, data.Y.flatten()
|
||||
|
||||
|
||||
class ShuffleSplit(Validation):
|
||||
"""
|
||||
Test by repeated random sampling
|
||||
|
||||
Attributes:
|
||||
n_resamples (int): number of repetitions
|
||||
test_size (float, int, None):
|
||||
If float, should be between 0.0 and 1.0 and represent the proportion
|
||||
of the dataset to include in the test split. If int, represents the
|
||||
absolute number of test samples. If None, the value is set to the
|
||||
complement of the train size. By default, the value is set to 0.1.
|
||||
The default will change in version 0.21. It will remain 0.1 only
|
||||
if ``train_size`` is unspecified, otherwise it will complement
|
||||
the specified ``train_size``.
|
||||
(from documentation of scipy.sklearn.StratifiedShuffleSplit)
|
||||
|
||||
train_size : float, int, or None, default is None
|
||||
If float, should be between 0.0 and 1.0 and represent the
|
||||
proportion of the dataset to include in the train split. If
|
||||
int, represents the absolute number of train samples. If None,
|
||||
the value is automatically set to the complement of the test size.
|
||||
(from documentation of scipy.sklearn.StratifiedShuffleSplit)
|
||||
|
||||
stratified (bool):
|
||||
flag deciding whether to perform stratified cross-validation.
|
||||
|
||||
random_state (int):
|
||||
seed for random number generator (default: 0). If set to `None`,
|
||||
a different seed is used each time
|
||||
|
||||
"""
|
||||
def __init__(self, n_resamples=10, train_size=None, test_size=0.1,
|
||||
stratified=True, random_state=0,
|
||||
store_data=False, store_models=False):
|
||||
super().__init__(store_data=store_data, store_models=store_models)
|
||||
self.n_resamples = n_resamples
|
||||
self.train_size = train_size
|
||||
self.test_size = test_size
|
||||
self.stratified = stratified
|
||||
self.random_state = random_state
|
||||
|
||||
def get_indices(self, data):
|
||||
if self.stratified and data.domain.has_discrete_class:
|
||||
splitter = skl.StratifiedShuffleSplit(
|
||||
n_splits=self.n_resamples, train_size=self.train_size,
|
||||
test_size=self.test_size, random_state=self.random_state
|
||||
)
|
||||
splitter.get_n_splits(data.X, data.Y)
|
||||
return list(splitter.split(data.X, data.Y))
|
||||
|
||||
splitter = skl.ShuffleSplit(
|
||||
n_splits=self.n_resamples, train_size=self.train_size,
|
||||
test_size=self.test_size, random_state=self.random_state
|
||||
)
|
||||
splitter.get_n_splits(data)
|
||||
return list(splitter.split(data))
|
||||
|
||||
|
||||
class TestOnTestData(Validation):
|
||||
"""
|
||||
Test on separately provided test data
|
||||
|
||||
Note that the class has a different signature for `__call__`.
|
||||
"""
|
||||
# get_indices is not needed in this class, pylint: disable=abstract-method
|
||||
|
||||
def __new__(cls, data=None, test_data=None, learners=None,
|
||||
preprocessor=None, **kwargs):
|
||||
if "train_data" in kwargs:
|
||||
if data is None:
|
||||
data = kwargs.pop("train_data")
|
||||
else:
|
||||
raise ValueError(
|
||||
"argument 'data' is given twice (once as 'train_data')")
|
||||
return super().__new__(
|
||||
cls,
|
||||
data=data, learners=learners, preprocessor=preprocessor,
|
||||
test_data=test_data, **kwargs)
|
||||
|
||||
def __call__(self, data, test_data, learners, preprocessor=None,
|
||||
*, callback=None):
|
||||
"""
|
||||
Args:
|
||||
data (Orange.data.Table): training data
|
||||
test_data (Orange.data.Table): test_data
|
||||
learners (list of Orange.Learner): a list of learning algorithms
|
||||
preprocessor (Orange.preprocess.Preprocess): preprocessor applied
|
||||
on training data
|
||||
callback (Callable): a function called to notify about the progress
|
||||
|
||||
Returns:
|
||||
results (Result): results of testing
|
||||
"""
|
||||
if preprocessor is None:
|
||||
preprocessor = _identity
|
||||
if callback is None:
|
||||
callback = _identity
|
||||
|
||||
train_data = preprocessor(data)
|
||||
part_results = []
|
||||
for (learner_i, learner) in enumerate(learners):
|
||||
part_results.append(
|
||||
_mp_worker(0, train_data, test_data, learner_i, learner,
|
||||
self.store_models))
|
||||
callback((learner_i + 1) / len(learners))
|
||||
callback(1)
|
||||
|
||||
results = Results(
|
||||
data=test_data if self.store_data else None,
|
||||
domain=test_data.domain,
|
||||
nrows=len(test_data), learners=learners,
|
||||
row_indices=np.arange(len(test_data)),
|
||||
folds=(Ellipsis, ),
|
||||
actual=test_data.Y.ravel(),
|
||||
score_by_folds=self.score_by_folds,
|
||||
train_time=np.zeros((len(learners),)),
|
||||
test_time=np.zeros((len(learners),)))
|
||||
|
||||
if self.store_models:
|
||||
results.models = np.tile(None, (1, len(learners)))
|
||||
self._collect_part_results(results, part_results)
|
||||
return results
|
||||
|
||||
|
||||
class TestOnTrainingData(TestOnTestData):
|
||||
"""Test on training data"""
|
||||
# get_indices is not needed in this class, pylint: disable=abstract-method
|
||||
# signature is such as on the base class, pylint: disable=signature-differs
|
||||
def __new__(cls, data=None, learners=None, preprocessor=None, **kwargs):
|
||||
return super().__new__(
|
||||
cls,
|
||||
data, test_data=data, learners=learners, preprocessor=preprocessor,
|
||||
**kwargs)
|
||||
|
||||
def __call__(self, data, learners, preprocessor=None, *, callback=None,
|
||||
**kwargs):
|
||||
kwargs.setdefault("test_data", data)
|
||||
# if kwargs contains anything besides test_data, this will be detected
|
||||
# (and complained about) by super().__call__
|
||||
return super().__call__(
|
||||
data=data, learners=learners, preprocessor=preprocessor,
|
||||
callback=callback, **kwargs)
|
||||
|
||||
|
||||
def sample(table, n=0.7, stratified=False, replace=False,
|
||||
random_state=None):
|
||||
"""
|
||||
Samples data instances from a data table. Returns the sample and
|
||||
a dataset from input data table that are not in the sample. Also
|
||||
uses several sampling functions from
|
||||
`scikit-learn <http://scikit-learn.org>`_.
|
||||
|
||||
table : data table
|
||||
A data table from which to sample.
|
||||
|
||||
n : float, int (default = 0.7)
|
||||
If float, should be between 0.0 and 1.0 and represents
|
||||
the proportion of data instances in the resulting sample. If
|
||||
int, n is the number of data instances in the resulting sample.
|
||||
|
||||
stratified : bool, optional (default = False)
|
||||
If true, sampling will try to consider class values and
|
||||
match distribution of class values
|
||||
in train and test subsets.
|
||||
|
||||
replace : bool, optional (default = False)
|
||||
sample with replacement
|
||||
|
||||
random_state : int or RandomState
|
||||
Pseudo-random number generator state used for random sampling.
|
||||
"""
|
||||
|
||||
if isinstance(n, float):
|
||||
n = int(n * len(table))
|
||||
|
||||
if replace:
|
||||
if random_state is None:
|
||||
rgen = np.random
|
||||
else:
|
||||
rgen = np.random.mtrand.RandomState(random_state)
|
||||
a_sample = rgen.randint(0, len(table), n)
|
||||
o = np.ones(len(table))
|
||||
o[a_sample] = 0
|
||||
others = np.nonzero(o)[0]
|
||||
return table[a_sample], table[others]
|
||||
|
||||
n = len(table) - n
|
||||
if stratified and table.domain.has_discrete_class:
|
||||
test_size = max(len(table.domain.class_var.values), n)
|
||||
splitter = skl.StratifiedShuffleSplit(
|
||||
n_splits=1, test_size=test_size, train_size=len(table) - test_size,
|
||||
random_state=random_state)
|
||||
splitter.get_n_splits(table.X, table.Y)
|
||||
ind = splitter.split(table.X, table.Y)
|
||||
else:
|
||||
splitter = skl.ShuffleSplit(
|
||||
n_splits=1, test_size=n, random_state=random_state)
|
||||
splitter.get_n_splits(table)
|
||||
ind = splitter.split(table)
|
||||
ind = next(ind)
|
||||
return table[ind[0]], table[ind[1]]
|
||||
0
pyminer/features/evaluation/tests/__init__.py
Normal file
0
pyminer/features/evaluation/tests/__init__.py
Normal file
125
pyminer/features/evaluation/tests/test_performance_curves.py
Normal file
125
pyminer/features/evaluation/tests/test_performance_curves.py
Normal file
@ -0,0 +1,125 @@
|
||||
import unittest
|
||||
from unittest.mock import patch
|
||||
|
||||
import numpy as np
|
||||
|
||||
from Orange.evaluation.testing import Results
|
||||
from Orange.evaluation.performance_curves import Curves
|
||||
|
||||
|
||||
# Test data and sensitivity/specificity are taken from
|
||||
# Tom Fawcett: An introduction to ROC analysis, with one true positive instance
|
||||
# removed, so that the number of positive and negative does not match
|
||||
|
||||
class TestCurves(unittest.TestCase):
|
||||
def setUp(self):
|
||||
n, p = (0, 1)
|
||||
self.data = np.array([
|
||||
(p, .8), (n, .7), (p, .6), (p, .55), (p, .54), (n, .53),
|
||||
(n, .52), (p, .51), (n, .505), (p, .4), (n, .39), (p, .38),
|
||||
(n, .37), (n, .36), (n, .35), (p, .34), (n, .33), (p, .30), (n, .1)
|
||||
])
|
||||
|
||||
def test_curves(self):
|
||||
np.random.shuffle(self.data)
|
||||
ytrue, probs = self.data.T
|
||||
curves = Curves(ytrue, probs)
|
||||
|
||||
tn = np.array(
|
||||
[0, 1, 1, 2, 2, 3, 4, 5, 5, 6, 6, 7, 7, 8, 9, 9, 9, 9, 10, 10])
|
||||
np.testing.assert_equal(curves.tn, tn)
|
||||
np.testing.assert_equal(curves.fp, 10 - tn)
|
||||
np.testing.assert_almost_equal(curves.specificity(), tn / 10)
|
||||
|
||||
tp = np.array(
|
||||
[9, 9, 8, 8, 7, 7, 7, 7, 6, 6, 5, 5, 4, 4, 4, 3, 2, 1, 1, 0])
|
||||
np.testing.assert_equal(curves.tp, tp)
|
||||
np.testing.assert_equal(curves.fn, 9 - tp)
|
||||
np.testing.assert_almost_equal(curves.sensitivity(), tp / 9)
|
||||
|
||||
np.testing.assert_almost_equal(
|
||||
curves.ca(),
|
||||
np.array([9, 10, 9, 10, 9, 10, 11, 12, 11, 12, 11, 12, 11, 12,
|
||||
13, 12, 11, 10, 11, 10]) / 19)
|
||||
|
||||
precision = np.array(
|
||||
[9 / 19, 9 / 18, 8 / 17, 8 / 16, 7 / 15, 7 / 14, 7 / 13,
|
||||
7 / 12, 6 / 11, 6 / 10, 5 / 9, 5 / 8, 4 / 7, 4 / 6,
|
||||
4 / 5, 3 / 4, 2 / 3, 1 / 2, 1 / 1, 1])
|
||||
np.testing.assert_almost_equal(curves.precision(), precision)
|
||||
np.testing.assert_almost_equal(curves.recall(), tp / 9)
|
||||
|
||||
np.testing.assert_almost_equal(curves.ppv(), precision)
|
||||
np.testing.assert_almost_equal(
|
||||
curves.npv(),
|
||||
np.array([1, 1 / 1, 1 / 2, 2 / 3, 2 / 4, 3 / 5, 4 / 6, 5 / 7,
|
||||
5 / 8, 6 / 9, 6 / 10, 7 / 11, 7 / 12, 8 / 13, 9 / 14,
|
||||
9 / 15, 9 / 16, 9 / 17, 10 / 18, 10 / 19]))
|
||||
|
||||
np.testing.assert_almost_equal(curves.tpr(), tp / 9)
|
||||
np.testing.assert_almost_equal(curves.fpr(), (10 - tn) / 10)
|
||||
|
||||
@patch("Orange.evaluation.performance_curves.Curves.__init__",
|
||||
return_value=None)
|
||||
def test_curves_from_results(self, init):
|
||||
res = Results()
|
||||
ytrue, probs = self.data.T
|
||||
res.actual = ytrue.astype(float)
|
||||
res.probabilities = np.vstack((1 - probs, probs)).T.reshape(1, -1, 2)
|
||||
Curves.from_results(res)
|
||||
cytrue, cprobs = init.call_args[0]
|
||||
np.testing.assert_equal(cytrue, ytrue)
|
||||
np.testing.assert_equal(cprobs, probs)
|
||||
|
||||
Curves.from_results(res, target_class=0)
|
||||
cytrue, cprobs = init.call_args[0]
|
||||
np.testing.assert_equal(cytrue, 1 - ytrue)
|
||||
np.testing.assert_equal(cprobs, 1 - probs)
|
||||
|
||||
res.actual = ytrue.astype(float)
|
||||
res.probabilities = np.random.random((2, 19, 2))
|
||||
res.probabilities[1] = np.vstack((1 - probs, probs)).T
|
||||
|
||||
Curves.from_results(res, model_index=1)
|
||||
cytrue, cprobs = init.call_args[0]
|
||||
np.testing.assert_equal(cytrue, ytrue)
|
||||
np.testing.assert_equal(cprobs, probs)
|
||||
|
||||
self.assertRaises(ValueError, Curves.from_results, res)
|
||||
|
||||
ytrue[ytrue == 0] = 2 * (np.arange(10) % 2)
|
||||
res.actual = ytrue.astype(float)
|
||||
res.probabilities = np.random.random((2, 19, 3))
|
||||
res.probabilities[1] = np.vstack(
|
||||
((1 - probs) / 3, probs, (1 - probs) * 2 / 3)).T
|
||||
|
||||
Curves.from_results(res, model_index=1, target_class=1)
|
||||
cytrue, cprobs = init.call_args[0]
|
||||
np.testing.assert_equal(cytrue, ytrue == 1)
|
||||
np.testing.assert_equal(cprobs, probs)
|
||||
|
||||
Curves.from_results(res, model_index=1, target_class=0)
|
||||
cytrue, cprobs = init.call_args[0]
|
||||
np.testing.assert_equal(cytrue, ytrue == 0)
|
||||
np.testing.assert_equal(cprobs, (1 - probs) / 3)
|
||||
|
||||
Curves.from_results(res, model_index=1, target_class=2)
|
||||
cytrue, cprobs = init.call_args[0]
|
||||
np.testing.assert_equal(cytrue, ytrue == 2)
|
||||
np.testing.assert_equal(cprobs, (1 - probs) * 2 / 3)
|
||||
|
||||
self.assertRaises(ValueError, Curves.from_results, res, model_index=1)
|
||||
|
||||
@patch("Orange.evaluation.performance_curves.Curves.__init__",
|
||||
return_value=None)
|
||||
def test_curves_from_results_nans(self, init):
|
||||
res = Results()
|
||||
ytrue, probs = self.data.T
|
||||
ytrue[0] = np.nan
|
||||
probs[-1] = np.nan
|
||||
res.actual = ytrue.astype(float)
|
||||
res.probabilities = np.vstack((1 - probs, probs)).T.reshape(1, -1, 2)
|
||||
Curves.from_results(res)
|
||||
cytrue, cprobs = init.call_args[0]
|
||||
np.testing.assert_equal(cytrue, ytrue[1:-1])
|
||||
np.testing.assert_equal(cprobs, probs[1:-1])
|
||||
BIN
pyminer/features/extensions/__pycache__/plugins.cpython-38.pyc
Normal file
BIN
pyminer/features/extensions/__pycache__/plugins.cpython-38.pyc
Normal file
Binary file not shown.
BIN
pyminer/features/extensions/package_manager/Icon.ico
Normal file
BIN
pyminer/features/extensions/package_manager/Icon.ico
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 164 KiB |
18
pyminer/features/extensions/package_manager/__init__.py
Normal file
18
pyminer/features/extensions/package_manager/__init__.py
Normal file
@ -0,0 +1,18 @@
|
||||
import os
|
||||
import sys
|
||||
|
||||
from .env_manager import *
|
||||
from .package_install import *
|
||||
from .package_remove import *
|
||||
from .package_update import *
|
||||
|
||||
# 获取项目相关目录添加到path中
|
||||
plugins_dir = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
|
||||
features_dir = os.path.dirname(plugins_dir)
|
||||
patata_dir = os.path.dirname(features_dir)
|
||||
ui_dir = patata_dir + '\\ui'
|
||||
# 把目录加入环境变量
|
||||
sys.path.insert(0, plugins_dir)
|
||||
sys.path.insert(0, patata_dir)
|
||||
sys.path.insert(0, features_dir)
|
||||
sys.path.insert(0, ui_dir)
|
||||
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
123
pyminer/features/extensions/package_manager/env_manager.py
Normal file
123
pyminer/features/extensions/package_manager/env_manager.py
Normal file
@ -0,0 +1,123 @@
|
||||
# -*- coding: utf-8 -*-
|
||||
|
||||
# Form implementation generated from reading ui file 'env_manager.ui'
|
||||
#
|
||||
# Created by: PyQt5 UI code generator 5.15.0
|
||||
#
|
||||
# WARNING: Any manual changes made to this file will be lost when pyuic5 is
|
||||
# run again. Do not edit this file unless you know what you are doing.
|
||||
|
||||
|
||||
from PyQt5 import QtCore, QtGui, QtWidgets
|
||||
|
||||
|
||||
class Ui_Form(object):
|
||||
def setupUi(self, Form):
|
||||
Form.setObjectName("Form")
|
||||
Form.resize(800, 500)
|
||||
self.horizontalLayout = QtWidgets.QHBoxLayout(Form)
|
||||
self.horizontalLayout.setObjectName("horizontalLayout")
|
||||
self.widget = QtWidgets.QWidget(Form)
|
||||
self.widget.setMaximumSize(QtCore.QSize(200, 16777215))
|
||||
self.widget.setObjectName("widget")
|
||||
self.horizontalLayout_3 = QtWidgets.QHBoxLayout(self.widget)
|
||||
self.horizontalLayout_3.setContentsMargins(0, 0, 0, 0)
|
||||
self.horizontalLayout_3.setObjectName("horizontalLayout_3")
|
||||
self.verticalLayout_2 = QtWidgets.QVBoxLayout()
|
||||
self.verticalLayout_2.setObjectName("verticalLayout_2")
|
||||
self.listWidget = QtWidgets.QListWidget(self.widget)
|
||||
self.listWidget.setObjectName("listWidget")
|
||||
item = QtWidgets.QListWidgetItem()
|
||||
self.listWidget.addItem(item)
|
||||
self.verticalLayout_2.addWidget(self.listWidget)
|
||||
self.horizontalLayout_2 = QtWidgets.QHBoxLayout()
|
||||
self.horizontalLayout_2.setObjectName("horizontalLayout_2")
|
||||
self.pushButton_new = QtWidgets.QPushButton(self.widget)
|
||||
self.pushButton_new.setObjectName("pushButton_new")
|
||||
self.horizontalLayout_2.addWidget(self.pushButton_new)
|
||||
self.pushButton_copy = QtWidgets.QPushButton(self.widget)
|
||||
self.pushButton_copy.setObjectName("pushButton_copy")
|
||||
self.horizontalLayout_2.addWidget(self.pushButton_copy)
|
||||
self.pushButton_from = QtWidgets.QPushButton(self.widget)
|
||||
self.pushButton_from.setObjectName("pushButton_from")
|
||||
self.horizontalLayout_2.addWidget(self.pushButton_from)
|
||||
self.pushButton_delete = QtWidgets.QPushButton(self.widget)
|
||||
self.pushButton_delete.setObjectName("pushButton_delete")
|
||||
self.horizontalLayout_2.addWidget(self.pushButton_delete)
|
||||
spacerItem = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum)
|
||||
self.horizontalLayout_2.addItem(spacerItem)
|
||||
self.verticalLayout_2.addLayout(self.horizontalLayout_2)
|
||||
self.horizontalLayout_3.addLayout(self.verticalLayout_2)
|
||||
self.horizontalLayout.addWidget(self.widget)
|
||||
self.stackedWidget = QtWidgets.QStackedWidget(Form)
|
||||
self.stackedWidget.setObjectName("stackedWidget")
|
||||
self.page_1 = QtWidgets.QWidget()
|
||||
self.page_1.setObjectName("page_1")
|
||||
self.horizontalLayout_5 = QtWidgets.QHBoxLayout(self.page_1)
|
||||
self.horizontalLayout_5.setContentsMargins(0, 0, 0, 0)
|
||||
self.horizontalLayout_5.setObjectName("horizontalLayout_5")
|
||||
self.verticalLayout_3 = QtWidgets.QVBoxLayout()
|
||||
self.verticalLayout_3.setObjectName("verticalLayout_3")
|
||||
self.horizontalLayout_4 = QtWidgets.QHBoxLayout()
|
||||
self.horizontalLayout_4.setObjectName("horizontalLayout_4")
|
||||
self.pushButton_install = QtWidgets.QPushButton(self.page_1)
|
||||
self.pushButton_install.setObjectName("pushButton_install")
|
||||
self.horizontalLayout_4.addWidget(self.pushButton_install)
|
||||
self.pushButton_import = QtWidgets.QPushButton(self.page_1)
|
||||
self.pushButton_import.setObjectName("pushButton_import")
|
||||
self.horizontalLayout_4.addWidget(self.pushButton_import)
|
||||
self.pushButton_export = QtWidgets.QPushButton(self.page_1)
|
||||
self.pushButton_export.setObjectName("pushButton_export")
|
||||
self.horizontalLayout_4.addWidget(self.pushButton_export)
|
||||
spacerItem1 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum)
|
||||
self.horizontalLayout_4.addItem(spacerItem1)
|
||||
self.lineEdit_find = QtWidgets.QLineEdit(self.page_1)
|
||||
self.lineEdit_find.setMinimumSize(QtCore.QSize(0, 25))
|
||||
self.lineEdit_find.setObjectName("lineEdit_find")
|
||||
self.horizontalLayout_4.addWidget(self.lineEdit_find)
|
||||
self.comboBox = QtWidgets.QComboBox(self.page_1)
|
||||
self.comboBox.setObjectName("comboBox")
|
||||
self.comboBox.addItem("")
|
||||
self.comboBox.addItem("")
|
||||
self.comboBox.addItem("")
|
||||
self.horizontalLayout_4.addWidget(self.comboBox)
|
||||
self.verticalLayout_3.addLayout(self.horizontalLayout_4)
|
||||
self.tableWidget = QtWidgets.QTableWidget(self.page_1)
|
||||
self.tableWidget.setObjectName("tableWidget")
|
||||
self.tableWidget.setColumnCount(0)
|
||||
self.tableWidget.setRowCount(0)
|
||||
self.verticalLayout_3.addWidget(self.tableWidget)
|
||||
self.horizontalLayout_5.addLayout(self.verticalLayout_3)
|
||||
self.stackedWidget.addWidget(self.page_1)
|
||||
self.page_2 = QtWidgets.QWidget()
|
||||
self.page_2.setObjectName("page_2")
|
||||
self.pushButton = QtWidgets.QPushButton(self.page_2)
|
||||
self.pushButton.setGeometry(QtCore.QRect(500, 250, 75, 23))
|
||||
self.pushButton.setObjectName("pushButton")
|
||||
self.stackedWidget.addWidget(self.page_2)
|
||||
self.horizontalLayout.addWidget(self.stackedWidget)
|
||||
|
||||
self.retranslateUi(Form)
|
||||
self.stackedWidget.setCurrentIndex(0)
|
||||
QtCore.QMetaObject.connectSlotsByName(Form)
|
||||
|
||||
def retranslateUi(self, Form):
|
||||
_translate = QtCore.QCoreApplication.translate
|
||||
Form.setWindowTitle(_translate("Form", "Python环境管理"))
|
||||
__sortingEnabled = self.listWidget.isSortingEnabled()
|
||||
self.listWidget.setSortingEnabled(False)
|
||||
item = self.listWidget.item(0)
|
||||
item.setText(_translate("Form", "默认环境"))
|
||||
self.listWidget.setSortingEnabled(__sortingEnabled)
|
||||
self.pushButton_new.setText(_translate("Form", "新建"))
|
||||
self.pushButton_copy.setText(_translate("Form", "复制"))
|
||||
self.pushButton_from.setText(_translate("Form", "导入"))
|
||||
self.pushButton_delete.setText(_translate("Form", "删除"))
|
||||
self.pushButton_install.setText(_translate("Form", "安装"))
|
||||
self.pushButton_import.setText(_translate("Form", "导入"))
|
||||
self.pushButton_export.setText(_translate("Form", "导出"))
|
||||
self.lineEdit_find.setPlaceholderText(_translate("Form", "请输入包名"))
|
||||
self.comboBox.setItemText(0, _translate("Form", "已安装"))
|
||||
self.comboBox.setItemText(1, _translate("Form", "可更新"))
|
||||
self.comboBox.setItemText(2, _translate("Form", "源"))
|
||||
self.pushButton.setText(_translate("Form", "PushButton"))
|
||||
218
pyminer/features/extensions/package_manager/env_manager.ui
Normal file
218
pyminer/features/extensions/package_manager/env_manager.ui
Normal file
@ -0,0 +1,218 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<ui version="4.0">
|
||||
<class>Form</class>
|
||||
<widget class="QWidget" name="Form">
|
||||
<property name="geometry">
|
||||
<rect>
|
||||
<x>0</x>
|
||||
<y>0</y>
|
||||
<width>800</width>
|
||||
<height>500</height>
|
||||
</rect>
|
||||
</property>
|
||||
<property name="windowTitle">
|
||||
<string>Python环境管理</string>
|
||||
</property>
|
||||
<layout class="QHBoxLayout" name="horizontalLayout">
|
||||
<item>
|
||||
<widget class="QWidget" name="widget" native="true">
|
||||
<property name="maximumSize">
|
||||
<size>
|
||||
<width>200</width>
|
||||
<height>16777215</height>
|
||||
</size>
|
||||
</property>
|
||||
<layout class="QHBoxLayout" name="horizontalLayout_3">
|
||||
<property name="leftMargin">
|
||||
<number>0</number>
|
||||
</property>
|
||||
<property name="topMargin">
|
||||
<number>0</number>
|
||||
</property>
|
||||
<property name="rightMargin">
|
||||
<number>0</number>
|
||||
</property>
|
||||
<property name="bottomMargin">
|
||||
<number>0</number>
|
||||
</property>
|
||||
<item>
|
||||
<layout class="QVBoxLayout" name="verticalLayout_2">
|
||||
<item>
|
||||
<widget class="QListWidget" name="listWidget">
|
||||
<item>
|
||||
<property name="text">
|
||||
<string>默认环境</string>
|
||||
</property>
|
||||
</item>
|
||||
</widget>
|
||||
</item>
|
||||
<item>
|
||||
<layout class="QHBoxLayout" name="horizontalLayout_2">
|
||||
<item>
|
||||
<widget class="QPushButton" name="pushButton_new">
|
||||
<property name="text">
|
||||
<string>新建</string>
|
||||
</property>
|
||||
</widget>
|
||||
</item>
|
||||
<item>
|
||||
<widget class="QPushButton" name="pushButton_copy">
|
||||
<property name="text">
|
||||
<string>复制</string>
|
||||
</property>
|
||||
</widget>
|
||||
</item>
|
||||
<item>
|
||||
<widget class="QPushButton" name="pushButton_from">
|
||||
<property name="text">
|
||||
<string>导入</string>
|
||||
</property>
|
||||
</widget>
|
||||
</item>
|
||||
<item>
|
||||
<widget class="QPushButton" name="pushButton_delete">
|
||||
<property name="text">
|
||||
<string>删除</string>
|
||||
</property>
|
||||
</widget>
|
||||
</item>
|
||||
<item>
|
||||
<spacer name="horizontalSpacer">
|
||||
<property name="orientation">
|
||||
<enum>Qt::Horizontal</enum>
|
||||
</property>
|
||||
<property name="sizeHint" stdset="0">
|
||||
<size>
|
||||
<width>40</width>
|
||||
<height>20</height>
|
||||
</size>
|
||||
</property>
|
||||
</spacer>
|
||||
</item>
|
||||
</layout>
|
||||
</item>
|
||||
</layout>
|
||||
</item>
|
||||
</layout>
|
||||
</widget>
|
||||
</item>
|
||||
<item>
|
||||
<widget class="QStackedWidget" name="stackedWidget">
|
||||
<property name="currentIndex">
|
||||
<number>0</number>
|
||||
</property>
|
||||
<widget class="QWidget" name="page_1">
|
||||
<layout class="QHBoxLayout" name="horizontalLayout_5">
|
||||
<property name="leftMargin">
|
||||
<number>0</number>
|
||||
</property>
|
||||
<property name="topMargin">
|
||||
<number>0</number>
|
||||
</property>
|
||||
<property name="rightMargin">
|
||||
<number>0</number>
|
||||
</property>
|
||||
<property name="bottomMargin">
|
||||
<number>0</number>
|
||||
</property>
|
||||
<item>
|
||||
<layout class="QVBoxLayout" name="verticalLayout_3">
|
||||
<item>
|
||||
<layout class="QHBoxLayout" name="horizontalLayout_4">
|
||||
<item>
|
||||
<widget class="QPushButton" name="pushButton_install">
|
||||
<property name="text">
|
||||
<string>安装</string>
|
||||
</property>
|
||||
</widget>
|
||||
</item>
|
||||
<item>
|
||||
<widget class="QPushButton" name="pushButton_import">
|
||||
<property name="text">
|
||||
<string>导入</string>
|
||||
</property>
|
||||
</widget>
|
||||
</item>
|
||||
<item>
|
||||
<widget class="QPushButton" name="pushButton_export">
|
||||
<property name="text">
|
||||
<string>导出</string>
|
||||
</property>
|
||||
</widget>
|
||||
</item>
|
||||
<item>
|
||||
<spacer name="horizontalSpacer_2">
|
||||
<property name="orientation">
|
||||
<enum>Qt::Horizontal</enum>
|
||||
</property>
|
||||
<property name="sizeHint" stdset="0">
|
||||
<size>
|
||||
<width>40</width>
|
||||
<height>20</height>
|
||||
</size>
|
||||
</property>
|
||||
</spacer>
|
||||
</item>
|
||||
<item>
|
||||
<widget class="QLineEdit" name="lineEdit_find">
|
||||
<property name="minimumSize">
|
||||
<size>
|
||||
<width>0</width>
|
||||
<height>25</height>
|
||||
</size>
|
||||
</property>
|
||||
<property name="placeholderText">
|
||||
<string>请输入包名</string>
|
||||
</property>
|
||||
</widget>
|
||||
</item>
|
||||
<item>
|
||||
<widget class="QComboBox" name="comboBox">
|
||||
<item>
|
||||
<property name="text">
|
||||
<string>已安装</string>
|
||||
</property>
|
||||
</item>
|
||||
<item>
|
||||
<property name="text">
|
||||
<string>可更新</string>
|
||||
</property>
|
||||
</item>
|
||||
<item>
|
||||
<property name="text">
|
||||
<string>源</string>
|
||||
</property>
|
||||
</item>
|
||||
</widget>
|
||||
</item>
|
||||
</layout>
|
||||
</item>
|
||||
<item>
|
||||
<widget class="QTableWidget" name="tableWidget"/>
|
||||
</item>
|
||||
</layout>
|
||||
</item>
|
||||
</layout>
|
||||
</widget>
|
||||
<widget class="QWidget" name="page_2">
|
||||
<widget class="QPushButton" name="pushButton">
|
||||
<property name="geometry">
|
||||
<rect>
|
||||
<x>500</x>
|
||||
<y>250</y>
|
||||
<width>75</width>
|
||||
<height>23</height>
|
||||
</rect>
|
||||
</property>
|
||||
<property name="text">
|
||||
<string>PushButton</string>
|
||||
</property>
|
||||
</widget>
|
||||
</widget>
|
||||
</widget>
|
||||
</item>
|
||||
</layout>
|
||||
</widget>
|
||||
<resources/>
|
||||
<connections/>
|
||||
</ui>
|
||||
155
pyminer/features/extensions/package_manager/package_install.py
Normal file
155
pyminer/features/extensions/package_manager/package_install.py
Normal file
@ -0,0 +1,155 @@
|
||||
# -*- coding: utf-8 -*-
|
||||
|
||||
# Form implementation generated from reading ui file 'package_install.ui'
|
||||
#
|
||||
# Created by: PyQt5 UI code generator 5.14.2
|
||||
#
|
||||
# WARNING! All changes made in this file will be lost!
|
||||
|
||||
|
||||
from PyQt5 import QtCore, QtGui, QtWidgets
|
||||
|
||||
|
||||
class Ui_Form(object):
|
||||
def setupUi(self, Form):
|
||||
Form.setObjectName("Form")
|
||||
Form.resize(800, 600)
|
||||
self.verticalLayout = QtWidgets.QVBoxLayout(Form)
|
||||
self.verticalLayout.setObjectName("verticalLayout")
|
||||
self.horizontalLayout_4 = QtWidgets.QHBoxLayout()
|
||||
self.horizontalLayout_4.setObjectName("horizontalLayout_4")
|
||||
self.formLayout = QtWidgets.QFormLayout()
|
||||
self.formLayout.setObjectName("formLayout")
|
||||
self.label_2 = QtWidgets.QLabel(Form)
|
||||
self.label_2.setObjectName("label_2")
|
||||
self.formLayout.setWidget(0, QtWidgets.QFormLayout.LabelRole, self.label_2)
|
||||
self.label = QtWidgets.QLabel(Form)
|
||||
self.label.setObjectName("label")
|
||||
self.formLayout.setWidget(1, QtWidgets.QFormLayout.LabelRole, self.label)
|
||||
self.horizontalLayout_3 = QtWidgets.QHBoxLayout()
|
||||
self.horizontalLayout_3.setObjectName("horizontalLayout_3")
|
||||
self.comboBox_source = QtWidgets.QComboBox(Form)
|
||||
self.comboBox_source.setEnabled(True)
|
||||
self.comboBox_source.setMinimumSize(QtCore.QSize(100, 0))
|
||||
self.comboBox_source.setMaximumSize(QtCore.QSize(100, 16777215))
|
||||
self.comboBox_source.setObjectName("comboBox_source")
|
||||
self.comboBox_source.addItem("")
|
||||
self.comboBox_source.addItem("")
|
||||
self.comboBox_source.addItem("")
|
||||
self.comboBox_source.addItem("")
|
||||
self.comboBox_source.addItem("")
|
||||
self.comboBox_source.addItem("")
|
||||
self.horizontalLayout_3.addWidget(self.comboBox_source)
|
||||
self.lineEdit_source = QtWidgets.QLineEdit(Form)
|
||||
self.lineEdit_source.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter)
|
||||
self.lineEdit_source.setReadOnly(True)
|
||||
self.lineEdit_source.setObjectName("lineEdit_source")
|
||||
self.horizontalLayout_3.addWidget(self.lineEdit_source)
|
||||
self.formLayout.setLayout(1, QtWidgets.QFormLayout.FieldRole, self.horizontalLayout_3)
|
||||
self.label_3 = QtWidgets.QLabel(Form)
|
||||
self.label_3.setObjectName("label_3")
|
||||
self.formLayout.setWidget(2, QtWidgets.QFormLayout.LabelRole, self.label_3)
|
||||
self.horizontalLayout = QtWidgets.QHBoxLayout()
|
||||
self.horizontalLayout.setObjectName("horizontalLayout")
|
||||
self.comboBox_dir = QtWidgets.QComboBox(Form)
|
||||
self.comboBox_dir.setMinimumSize(QtCore.QSize(100, 0))
|
||||
self.comboBox_dir.setMaximumSize(QtCore.QSize(100, 16777215))
|
||||
self.comboBox_dir.setObjectName("comboBox_dir")
|
||||
self.comboBox_dir.addItem("")
|
||||
self.comboBox_dir.addItem("")
|
||||
self.comboBox_dir.addItem("")
|
||||
self.comboBox_dir.addItem("")
|
||||
self.horizontalLayout.addWidget(self.comboBox_dir)
|
||||
self.lineEdit_dir = QtWidgets.QLineEdit(Form)
|
||||
self.lineEdit_dir.setReadOnly(True)
|
||||
self.lineEdit_dir.setObjectName("lineEdit_dir")
|
||||
self.horizontalLayout.addWidget(self.lineEdit_dir)
|
||||
self.toolButton = QtWidgets.QToolButton(Form)
|
||||
self.toolButton.setObjectName("toolButton")
|
||||
self.horizontalLayout.addWidget(self.toolButton)
|
||||
self.formLayout.setLayout(2, QtWidgets.QFormLayout.FieldRole, self.horizontalLayout)
|
||||
self.horizontalLayout_7 = QtWidgets.QHBoxLayout()
|
||||
self.horizontalLayout_7.setObjectName("horizontalLayout_7")
|
||||
self.lineEdit_name = QtWidgets.QLineEdit(Form)
|
||||
self.lineEdit_name.setText("")
|
||||
self.lineEdit_name.setObjectName("lineEdit_name")
|
||||
self.horizontalLayout_7.addWidget(self.lineEdit_name)
|
||||
self.checkBox_version = QtWidgets.QCheckBox(Form)
|
||||
self.checkBox_version.setObjectName("checkBox_version")
|
||||
self.horizontalLayout_7.addWidget(self.checkBox_version)
|
||||
self.comboBox_version = QtWidgets.QComboBox(Form)
|
||||
self.comboBox_version.setEnabled(True)
|
||||
self.comboBox_version.setMinimumSize(QtCore.QSize(0, 0))
|
||||
self.comboBox_version.setMaximumSize(QtCore.QSize(16777215, 16777215))
|
||||
self.comboBox_version.setEditable(False)
|
||||
self.comboBox_version.setObjectName("comboBox_version")
|
||||
self.comboBox_version.addItem("")
|
||||
self.horizontalLayout_7.addWidget(self.comboBox_version)
|
||||
self.formLayout.setLayout(0, QtWidgets.QFormLayout.FieldRole, self.horizontalLayout_7)
|
||||
self.horizontalLayout_4.addLayout(self.formLayout)
|
||||
self.verticalLayout.addLayout(self.horizontalLayout_4)
|
||||
self.groupBox = QtWidgets.QGroupBox(Form)
|
||||
self.groupBox.setObjectName("groupBox")
|
||||
self.horizontalLayout_5 = QtWidgets.QHBoxLayout(self.groupBox)
|
||||
self.horizontalLayout_5.setContentsMargins(0, 0, 0, 0)
|
||||
self.horizontalLayout_5.setObjectName("horizontalLayout_5")
|
||||
self.textEdit_desc = QtWidgets.QTextEdit(self.groupBox)
|
||||
self.textEdit_desc.setObjectName("textEdit_desc")
|
||||
self.horizontalLayout_5.addWidget(self.textEdit_desc)
|
||||
self.verticalLayout.addWidget(self.groupBox)
|
||||
self.groupBox_2 = QtWidgets.QGroupBox(Form)
|
||||
self.groupBox_2.setObjectName("groupBox_2")
|
||||
self.horizontalLayout_6 = QtWidgets.QHBoxLayout(self.groupBox_2)
|
||||
self.horizontalLayout_6.setContentsMargins(0, 0, 0, 0)
|
||||
self.horizontalLayout_6.setObjectName("horizontalLayout_6")
|
||||
self.textEdit_log = QtWidgets.QTextEdit(self.groupBox_2)
|
||||
self.textEdit_log.setObjectName("textEdit_log")
|
||||
self.horizontalLayout_6.addWidget(self.textEdit_log)
|
||||
self.verticalLayout.addWidget(self.groupBox_2)
|
||||
self.widget = QtWidgets.QWidget(Form)
|
||||
self.widget.setMaximumSize(QtCore.QSize(16777215, 50))
|
||||
self.widget.setObjectName("widget")
|
||||
self.verticalLayout_2 = QtWidgets.QVBoxLayout(self.widget)
|
||||
self.verticalLayout_2.setObjectName("verticalLayout_2")
|
||||
self.horizontalLayout_2 = QtWidgets.QHBoxLayout()
|
||||
self.horizontalLayout_2.setObjectName("horizontalLayout_2")
|
||||
spacerItem = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum)
|
||||
self.horizontalLayout_2.addItem(spacerItem)
|
||||
self.pushButton_ok = QtWidgets.QPushButton(self.widget)
|
||||
self.pushButton_ok.setObjectName("pushButton_ok")
|
||||
self.horizontalLayout_2.addWidget(self.pushButton_ok)
|
||||
self.pushButton_cancel = QtWidgets.QPushButton(self.widget)
|
||||
self.pushButton_cancel.setObjectName("pushButton_cancel")
|
||||
self.horizontalLayout_2.addWidget(self.pushButton_cancel)
|
||||
self.verticalLayout_2.addLayout(self.horizontalLayout_2)
|
||||
self.verticalLayout.addWidget(self.widget)
|
||||
|
||||
self.retranslateUi(Form)
|
||||
QtCore.QMetaObject.connectSlotsByName(Form)
|
||||
|
||||
def retranslateUi(self, Form):
|
||||
_translate = QtCore.QCoreApplication.translate
|
||||
Form.setWindowTitle(_translate("Form", "安装"))
|
||||
self.label_2.setText(_translate("Form", "包名:"))
|
||||
self.label.setText(_translate("Form", "下载源:"))
|
||||
self.comboBox_source.setItemText(0, _translate("Form", "腾讯(推荐)"))
|
||||
self.comboBox_source.setItemText(1, _translate("Form", "官方"))
|
||||
self.comboBox_source.setItemText(2, _translate("Form", "清华大学"))
|
||||
self.comboBox_source.setItemText(3, _translate("Form", "阿里"))
|
||||
self.comboBox_source.setItemText(4, _translate("Form", "豆瓣"))
|
||||
self.comboBox_source.setItemText(5, _translate("Form", "自定义"))
|
||||
self.lineEdit_source.setText(_translate("Form", "https://mirrors.cloud.tencent.com/pypi/simple"))
|
||||
self.lineEdit_source.setPlaceholderText(_translate("Form", "腾讯镜像源"))
|
||||
self.label_3.setText(_translate("Form", "安装选项:"))
|
||||
self.comboBox_dir.setItemText(0, _translate("Form", "默认位置"))
|
||||
self.comboBox_dir.setItemText(1, _translate("Form", "用户目录"))
|
||||
self.comboBox_dir.setItemText(2, _translate("Form", "仅下载"))
|
||||
self.comboBox_dir.setItemText(3, _translate("Form", "自定义"))
|
||||
self.lineEdit_dir.setPlaceholderText(_translate("Form", "默认"))
|
||||
self.toolButton.setText(_translate("Form", "..."))
|
||||
self.checkBox_version.setText(_translate("Form", "指定版本"))
|
||||
self.comboBox_version.setItemText(0, _translate("Form", "最新版本"))
|
||||
self.groupBox.setTitle(_translate("Form", "详情"))
|
||||
self.groupBox_2.setTitle(_translate("Form", "执行记录"))
|
||||
self.pushButton_ok.setText(_translate("Form", "确定"))
|
||||
self.pushButton_cancel.setText(_translate("Form", "取消"))
|
||||
312
pyminer/features/extensions/package_manager/package_install.ui
Normal file
312
pyminer/features/extensions/package_manager/package_install.ui
Normal file
@ -0,0 +1,312 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<ui version="4.0">
|
||||
<class>Form</class>
|
||||
<widget class="QWidget" name="Form">
|
||||
<property name="geometry">
|
||||
<rect>
|
||||
<x>0</x>
|
||||
<y>0</y>
|
||||
<width>800</width>
|
||||
<height>600</height>
|
||||
</rect>
|
||||
</property>
|
||||
<property name="windowTitle">
|
||||
<string>安装</string>
|
||||
</property>
|
||||
<layout class="QVBoxLayout" name="verticalLayout">
|
||||
<item>
|
||||
<layout class="QHBoxLayout" name="horizontalLayout_4">
|
||||
<item>
|
||||
<layout class="QFormLayout" name="formLayout">
|
||||
<item row="0" column="0">
|
||||
<widget class="QLabel" name="label_2">
|
||||
<property name="text">
|
||||
<string>包名:</string>
|
||||
</property>
|
||||
</widget>
|
||||
</item>
|
||||
<item row="1" column="0">
|
||||
<widget class="QLabel" name="label">
|
||||
<property name="text">
|
||||
<string>下载源:</string>
|
||||
</property>
|
||||
</widget>
|
||||
</item>
|
||||
<item row="1" column="1">
|
||||
<layout class="QHBoxLayout" name="horizontalLayout_3">
|
||||
<item>
|
||||
<widget class="QComboBox" name="comboBox_source">
|
||||
<property name="enabled">
|
||||
<bool>true</bool>
|
||||
</property>
|
||||
<property name="minimumSize">
|
||||
<size>
|
||||
<width>100</width>
|
||||
<height>0</height>
|
||||
</size>
|
||||
</property>
|
||||
<property name="maximumSize">
|
||||
<size>
|
||||
<width>100</width>
|
||||
<height>16777215</height>
|
||||
</size>
|
||||
</property>
|
||||
<item>
|
||||
<property name="text">
|
||||
<string>腾讯(推荐)</string>
|
||||
</property>
|
||||
</item>
|
||||
<item>
|
||||
<property name="text">
|
||||
<string>官方</string>
|
||||
</property>
|
||||
</item>
|
||||
<item>
|
||||
<property name="text">
|
||||
<string>清华大学</string>
|
||||
</property>
|
||||
</item>
|
||||
<item>
|
||||
<property name="text">
|
||||
<string>阿里</string>
|
||||
</property>
|
||||
</item>
|
||||
<item>
|
||||
<property name="text">
|
||||
<string>豆瓣</string>
|
||||
</property>
|
||||
</item>
|
||||
<item>
|
||||
<property name="text">
|
||||
<string>自定义</string>
|
||||
</property>
|
||||
</item>
|
||||
</widget>
|
||||
</item>
|
||||
<item>
|
||||
<widget class="QLineEdit" name="lineEdit_source">
|
||||
<property name="text">
|
||||
<string>https://mirrors.cloud.tencent.com/pypi/simple</string>
|
||||
</property>
|
||||
<property name="alignment">
|
||||
<set>Qt::AlignLeading|Qt::AlignLeft|Qt::AlignVCenter</set>
|
||||
</property>
|
||||
<property name="readOnly">
|
||||
<bool>true</bool>
|
||||
</property>
|
||||
<property name="placeholderText">
|
||||
<string>腾讯镜像源</string>
|
||||
</property>
|
||||
</widget>
|
||||
</item>
|
||||
</layout>
|
||||
</item>
|
||||
<item row="2" column="0">
|
||||
<widget class="QLabel" name="label_3">
|
||||
<property name="text">
|
||||
<string>安装选项:</string>
|
||||
</property>
|
||||
</widget>
|
||||
</item>
|
||||
<item row="2" column="1">
|
||||
<layout class="QHBoxLayout" name="horizontalLayout">
|
||||
<item>
|
||||
<widget class="QComboBox" name="comboBox_dir">
|
||||
<property name="minimumSize">
|
||||
<size>
|
||||
<width>100</width>
|
||||
<height>0</height>
|
||||
</size>
|
||||
</property>
|
||||
<property name="maximumSize">
|
||||
<size>
|
||||
<width>100</width>
|
||||
<height>16777215</height>
|
||||
</size>
|
||||
</property>
|
||||
<item>
|
||||
<property name="text">
|
||||
<string>默认位置</string>
|
||||
</property>
|
||||
</item>
|
||||
<item>
|
||||
<property name="text">
|
||||
<string>用户目录</string>
|
||||
</property>
|
||||
</item>
|
||||
<item>
|
||||
<property name="text">
|
||||
<string>仅下载</string>
|
||||
</property>
|
||||
</item>
|
||||
<item>
|
||||
<property name="text">
|
||||
<string>自定义</string>
|
||||
</property>
|
||||
</item>
|
||||
</widget>
|
||||
</item>
|
||||
<item>
|
||||
<widget class="QLineEdit" name="lineEdit_dir">
|
||||
<property name="readOnly">
|
||||
<bool>true</bool>
|
||||
</property>
|
||||
<property name="placeholderText">
|
||||
<string>默认</string>
|
||||
</property>
|
||||
</widget>
|
||||
</item>
|
||||
<item>
|
||||
<widget class="QToolButton" name="toolButton">
|
||||
<property name="text">
|
||||
<string>...</string>
|
||||
</property>
|
||||
</widget>
|
||||
</item>
|
||||
</layout>
|
||||
</item>
|
||||
<item row="0" column="1">
|
||||
<layout class="QHBoxLayout" name="horizontalLayout_7">
|
||||
<item>
|
||||
<widget class="QLineEdit" name="lineEdit_name">
|
||||
<property name="text">
|
||||
<string/>
|
||||
</property>
|
||||
</widget>
|
||||
</item>
|
||||
<item>
|
||||
<widget class="QCheckBox" name="checkBox_version">
|
||||
<property name="text">
|
||||
<string>指定版本</string>
|
||||
</property>
|
||||
</widget>
|
||||
</item>
|
||||
<item>
|
||||
<widget class="QComboBox" name="comboBox_version">
|
||||
<property name="enabled">
|
||||
<bool>true</bool>
|
||||
</property>
|
||||
<property name="minimumSize">
|
||||
<size>
|
||||
<width>0</width>
|
||||
<height>0</height>
|
||||
</size>
|
||||
</property>
|
||||
<property name="maximumSize">
|
||||
<size>
|
||||
<width>16777215</width>
|
||||
<height>16777215</height>
|
||||
</size>
|
||||
</property>
|
||||
<property name="editable">
|
||||
<bool>false</bool>
|
||||
</property>
|
||||
<item>
|
||||
<property name="text">
|
||||
<string>最新版本</string>
|
||||
</property>
|
||||
</item>
|
||||
</widget>
|
||||
</item>
|
||||
</layout>
|
||||
</item>
|
||||
</layout>
|
||||
</item>
|
||||
</layout>
|
||||
</item>
|
||||
<item>
|
||||
<widget class="QGroupBox" name="groupBox">
|
||||
<property name="title">
|
||||
<string>详情</string>
|
||||
</property>
|
||||
<layout class="QHBoxLayout" name="horizontalLayout_5">
|
||||
<property name="leftMargin">
|
||||
<number>0</number>
|
||||
</property>
|
||||
<property name="topMargin">
|
||||
<number>0</number>
|
||||
</property>
|
||||
<property name="rightMargin">
|
||||
<number>0</number>
|
||||
</property>
|
||||
<property name="bottomMargin">
|
||||
<number>0</number>
|
||||
</property>
|
||||
<item>
|
||||
<widget class="QTextEdit" name="textEdit_desc"/>
|
||||
</item>
|
||||
</layout>
|
||||
</widget>
|
||||
</item>
|
||||
<item>
|
||||
<widget class="QGroupBox" name="groupBox_2">
|
||||
<property name="title">
|
||||
<string>执行记录</string>
|
||||
</property>
|
||||
<layout class="QHBoxLayout" name="horizontalLayout_6">
|
||||
<property name="leftMargin">
|
||||
<number>0</number>
|
||||
</property>
|
||||
<property name="topMargin">
|
||||
<number>0</number>
|
||||
</property>
|
||||
<property name="rightMargin">
|
||||
<number>0</number>
|
||||
</property>
|
||||
<property name="bottomMargin">
|
||||
<number>0</number>
|
||||
</property>
|
||||
<item>
|
||||
<widget class="QTextEdit" name="textEdit_log"/>
|
||||
</item>
|
||||
</layout>
|
||||
</widget>
|
||||
</item>
|
||||
<item>
|
||||
<widget class="QWidget" name="widget" native="true">
|
||||
<property name="maximumSize">
|
||||
<size>
|
||||
<width>16777215</width>
|
||||
<height>50</height>
|
||||
</size>
|
||||
</property>
|
||||
<layout class="QVBoxLayout" name="verticalLayout_2">
|
||||
<item>
|
||||
<layout class="QHBoxLayout" name="horizontalLayout_2">
|
||||
<item>
|
||||
<spacer name="horizontalSpacer">
|
||||
<property name="orientation">
|
||||
<enum>Qt::Horizontal</enum>
|
||||
</property>
|
||||
<property name="sizeHint" stdset="0">
|
||||
<size>
|
||||
<width>40</width>
|
||||
<height>20</height>
|
||||
</size>
|
||||
</property>
|
||||
</spacer>
|
||||
</item>
|
||||
<item>
|
||||
<widget class="QPushButton" name="pushButton_ok">
|
||||
<property name="text">
|
||||
<string>确定</string>
|
||||
</property>
|
||||
</widget>
|
||||
</item>
|
||||
<item>
|
||||
<widget class="QPushButton" name="pushButton_cancel">
|
||||
<property name="text">
|
||||
<string>取消</string>
|
||||
</property>
|
||||
</widget>
|
||||
</item>
|
||||
</layout>
|
||||
</item>
|
||||
</layout>
|
||||
</widget>
|
||||
</item>
|
||||
</layout>
|
||||
</widget>
|
||||
<resources/>
|
||||
<connections/>
|
||||
</ui>
|
||||
947
pyminer/features/extensions/package_manager/package_manager.py
Normal file
947
pyminer/features/extensions/package_manager/package_manager.py
Normal file
@ -0,0 +1,947 @@
|
||||
import os
|
||||
import subprocess
|
||||
import sys
|
||||
import logging
|
||||
import webbrowser
|
||||
import time
|
||||
import numpy as np
|
||||
import pandas as pd
|
||||
# 导入PyQt5模块
|
||||
from PyQt5.Qt import *
|
||||
|
||||
from pyminer.share.threads import *
|
||||
from pyminer.features.extensions.package_manager.env_manager import Ui_Form as EnvManager_Ui_Form
|
||||
from pyminer.features.extensions.package_manager.package_install import Ui_Form as PackageInstall_Ui_Form
|
||||
from pyminer.features.extensions.package_manager.package_update import Ui_Form as PackageUpdate_Ui_Form
|
||||
from pyminer.features.extensions.package_manager.package_remove import Ui_Form as PackageRemove_Ui_Form
|
||||
from pyminer.features.extensions.package_manager.package_setting import Ui_Form as PackageSetting_Ui_Form
|
||||
from pyminer.ui.source.qss.qss_tools import QssTools
|
||||
|
||||
|
||||
|
||||
class PackageManagerForm(QWidget, EnvManager_Ui_Form):
|
||||
"""
|
||||
打开"包管理"窗口
|
||||
"""
|
||||
|
||||
def __init__(self, parent=None):
|
||||
super().__init__(parent)
|
||||
self.setupUi(self)
|
||||
self.center()
|
||||
self.source_index = "-i https://mirrors.cloud.tencent.com/pypi/simple" # 设置默认镜像源地址
|
||||
|
||||
self.widget.hide()
|
||||
self.package_filter_change()
|
||||
|
||||
ui_dir = os.path.dirname(os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__)))))+r'\ui'
|
||||
qss_path = ui_dir + "\\source\\qss\\patata.qss"
|
||||
QssTools.set_qss_to_obj(qss_path, self)
|
||||
|
||||
self.pushButton_install.clicked.connect(self.package_install_display)
|
||||
self.pushButton_import.clicked.connect(self.pip_requirements_import) # 从requirements.txt导入包
|
||||
self.pushButton_export.clicked.connect(self.pip_freeze_export) # 导出当前包到requirements.txt
|
||||
|
||||
self.lineEdit_find.textChanged.connect(self.pip_find)
|
||||
self.listWidget.currentRowChanged.connect(self.env_display)
|
||||
self.pushButton_new.clicked.connect(self.env_new)
|
||||
self.pushButton_delete.clicked.connect(self.env_delete)
|
||||
self.pushButton_copy.clicked.connect(self.env_copy)
|
||||
self.comboBox.currentIndexChanged.connect(self.package_filter_change) # 当下拉索引发生改变时发射信号触发绑定的事件
|
||||
|
||||
def keyPressEvent(self, e):
|
||||
"""
|
||||
按键盘Escape退出当前窗口
|
||||
@param e:
|
||||
"""
|
||||
if e.key() == Qt.Key_Escape:
|
||||
self.close()
|
||||
|
||||
def center(self):
|
||||
qr = self.frameGeometry()
|
||||
cp = QDesktopWidget().availableGeometry().center()
|
||||
qr.moveCenter(cp)
|
||||
self.move(qr.topLeft())
|
||||
|
||||
def package_filter_change(self):
|
||||
try:
|
||||
if self.comboBox.currentText() == "已安装":
|
||||
self.package_filter_default()
|
||||
elif self.comboBox.currentText() == "可更新":
|
||||
# self.package_filter_update()
|
||||
self.writing_thread = QtCore.QThread()
|
||||
self.package_filter_update.moveToThread(self.writing_thread)
|
||||
|
||||
|
||||
except:
|
||||
pass
|
||||
|
||||
def package_setting_display(self):
|
||||
"""
|
||||
显示"数据信息"窗口
|
||||
"""
|
||||
self.package_setting = PackageSettingForm()
|
||||
self.package_setting.show()
|
||||
|
||||
def env_manager_display(self):
|
||||
if self.action_env.isChecked():
|
||||
self.widget.show()
|
||||
else:
|
||||
self.widget.hide()
|
||||
|
||||
def env_delete(self):
|
||||
button = QMessageBox.Warning(self, "确认删除", "确认删除该虚拟环境吗？",
|
||||
QMessageBox.Ok | QMessageBox.Cancel, QMessageBox.Ok)
|
||||
if button == QMessageBox.Ok:
|
||||
print("确认")
|
||||
elif button == QMessageBox.Cancel:
|
||||
print("取消")
|
||||
else:
|
||||
return
|
||||
|
||||
def env_new(self):
|
||||
self.listWidget.addItem("test")
|
||||
|
||||
def env_copy(self):
|
||||
pass
|
||||
|
||||
def env_display(self, i):
|
||||
self.stackedWidget.setCurrentIndex(i)
|
||||
|
||||
def package_install_display(self):
|
||||
"""
|
||||
显示"数据信息"窗口
|
||||
"""
|
||||
self.package_install = PackageInstallForm()
|
||||
self.package_install.show()
|
||||
|
||||
def package_update_display(self):
|
||||
"""
|
||||
显示"数据信息"窗口
|
||||
"""
|
||||
self.package_update = PackageUpdateForm()
|
||||
self.package_update.show()
|
||||
|
||||
def package_remove_display(self):
|
||||
"""
|
||||
显示"数据信息"窗口
|
||||
"""
|
||||
self.package_remove = PackageRemoveForm()
|
||||
self.package_remove.show()
|
||||
|
||||
def pip_freeze_export(self):
|
||||
"""
|
||||
导出已安装的python包到requirements.txt文件中
|
||||
"""
|
||||
export_path = QFileDialog.getSaveFileName(self, "导出已安装模块为requirements.txt",
|
||||
os.path.join(os.path.expanduser('~'), "Desktop"),
|
||||
r"文本文件(*.txt)")
|
||||
|
||||
if export_path == "":
|
||||
logging.info("\n取消选择")
|
||||
return
|
||||
# cmd = "python -m pip freeze>" + export_path + "requirements.txt"
|
||||
print(export_path)
|
||||
# os.system(cmd)
|
||||
|
||||
def pip_requirements_import(self):
|
||||
"""
|
||||
导入requirements.txt文件并进行相关处理
|
||||
"""
|
||||
import_path = QFileDialog.getOpenFileName(self, '导入requirements.txt', '', "文本文件(*.txt)")
|
||||
|
||||
if import_path == "":
|
||||
logging.info("\n取消选择")
|
||||
return
|
||||
cmd = sys.executable + " -m pip install -r" + import_path[0]
|
||||
print(import_path)
|
||||
|
||||
def package_filter_default(self):
|
||||
"""
|
||||
pip环境管理页面初始化--默认筛选已安装的pip包
|
||||
"""
|
||||
# result = subprocess.check_output("python -m pip list", encoding="utf-8")
|
||||
pipe = subprocess.run(sys.executable + " -m pip list", shell=True, stdout=subprocess.PIPE,
|
||||
stderr=subprocess.PIPE,
|
||||
encoding="utf-8")
|
||||
if pipe.returncode == 0:
|
||||
result = pipe.stdout
|
||||
else:
|
||||
result = pipe.stderr
|
||||
|
||||
self.tableWidget.setEditTriggers(QAbstractItemView.NoEditTriggers) # 将表格变为禁止编辑
|
||||
self.tableWidget.setColumnCount(6) # 设置列数
|
||||
self.tableWidget.setRowCount(len(result.splitlines()) - 2) # 设置行数
|
||||
self.tableWidget.setSelectionBehavior(QAbstractItemView.SelectRows) # 整行选中
|
||||
self.tableWidget.setHorizontalHeaderLabels(['包名', '当前版本', ' 最新版本', '类型', '', '']) # 设置表头
|
||||
# self.tableWidget.horizontalHeader().setSectionResizeMode(6, QHeaderView.Stretch) # 设置第五列宽度自动调整，充满屏幕
|
||||
self.tableWidget.horizontalHeader().setStretchLastSection(True) # 设置最后一列拉伸至最大
|
||||
self.tableWidget.sortItems(0, Qt.AscendingOrder)
|
||||
self.tableWidget.setColumnHidden(3, False) # 将第4列隐藏
|
||||
self.tableWidget.setColumnHidden(4, False) # 将第5列隐藏
|
||||
self.tableWidget.setColumnWidth(0, 150) # 设置第1列宽度
|
||||
self.tableWidget.setColumnWidth(1, 150) # 设置第1列宽度
|
||||
self.tableWidget.setColumnWidth(2, 150) # 设置第1列宽度
|
||||
self.tableWidget.setColumnWidth(3, 150) # 设置第5列宽度
|
||||
self.tableWidget.setColumnWidth(4, 150) # 设置第5列宽度
|
||||
self.tableWidget.setShowGrid(True)
|
||||
|
||||
font = QFont('微软雅黑', 20)
|
||||
font.setBold(True) # 设置字体加粗
|
||||
self.tableWidget.horizontalHeader().setFont(font) # 设置表头字体
|
||||
self.tableWidget.horizontalHeader().setFixedHeight(30) # 设置表头高度
|
||||
stylesheet = "::section{Background-color:rgb(242,242,242);border-radius:5px;border-width: 1px;border-style: " \
|
||||
"outset;border-color: white;font: bold 12px;} "
|
||||
self.tableWidget.horizontalHeader().setStyleSheet(stylesheet)
|
||||
|
||||
x = 0 # 当前行数
|
||||
for line in result.splitlines(): # 逐行读取pip 清单
|
||||
x += 1
|
||||
package = line.split()[0]
|
||||
version = line.split()[1]
|
||||
|
||||
btn_update = QtWidgets.QPushButton("更新")
|
||||
btn_update.setMaximumWidth(40)
|
||||
btn_update.setStyleSheet('QPushButton{margin:3px}')
|
||||
btn_remove = QtWidgets.QPushButton("卸载")
|
||||
btn_remove.setMaximumWidth(40)
|
||||
btn_remove.setStyleSheet('QPushButton{margin:3px}')
|
||||
|
||||
btn_update.clicked.connect(self.btn_pip_update)
|
||||
btn_remove.clicked.connect(self.btn_pip_remove)
|
||||
|
||||
# 逐行写入pip数据到页面
|
||||
if 3 <= x <= len(result.splitlines()): # 从第3行开始识别
|
||||
y = 0 # 列
|
||||
while y <= 5:
|
||||
if y == 0:
|
||||
name = QTableWidgetItem(package)
|
||||
name.setTextAlignment(Qt.AlignCenter)
|
||||
self.tableWidget.setItem(x - 3, y, name)
|
||||
elif y == 1:
|
||||
ver = QTableWidgetItem(version)
|
||||
ver.setTextAlignment(Qt.AlignCenter)
|
||||
self.tableWidget.setItem(x - 3, y, ver)
|
||||
elif y == 4:
|
||||
self.tableWidget.setCellWidget(x - 3, y, btn_update)
|
||||
elif y == 5:
|
||||
self.tableWidget.setCellWidget(x - 3, y, btn_remove)
|
||||
|
||||
y += 1
|
||||
|
||||
def package_filter_update(self):
|
||||
"""
|
||||
pip环境管理页面--筛选可更新的pip包
|
||||
"""
|
||||
print("开始检查更新")
|
||||
cmd = sys.executable + " -m pip list -o" + " " + self.source_index
|
||||
# result = subprocess.check_output(cmd, encoding="utf-8")
|
||||
pipe = subprocess.run(cmd.strip(), shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE,
|
||||
encoding="utf-8")
|
||||
if pipe.returncode == 0:
|
||||
result = pipe.stdout
|
||||
else:
|
||||
result = pipe.stderr
|
||||
|
||||
self.tableWidget.setEditTriggers(QAbstractItemView.NoEditTriggers) # 将表格变为禁止编辑
|
||||
self.tableWidget.setColumnCount(6) # 设置列数
|
||||
self.tableWidget.setRowCount(len(result.splitlines()) - 2) # 设置行数
|
||||
self.tableWidget.setSelectionBehavior(QAbstractItemView.SelectRows) # 整行选中
|
||||
self.tableWidget.setHorizontalHeaderLabels(['包名', '当前版本', ' 最新版本', '类型', '', '']) # 设置表头
|
||||
# self.tableWidget.horizontalHeader().setSectionResizeMode(5, QHeaderView.Stretch) # 设置第五列宽度自动调整，充满屏幕
|
||||
self.tableWidget.horizontalHeader().setStretchLastSection(True) # 设置最后一列拉伸至最大
|
||||
self.tableWidget.sortItems(0, Qt.AscendingOrder)
|
||||
self.tableWidget.setColumnHidden(3, False) # 将第4列隐藏
|
||||
self.tableWidget.setColumnHidden(4, False) # 将第5列隐藏
|
||||
self.tableWidget.setColumnWidth(0, 150) # 设置第1列宽度
|
||||
self.tableWidget.setColumnWidth(1, 150) # 设置第1列宽度
|
||||
self.tableWidget.setColumnWidth(2, 150) # 设置第1列宽度
|
||||
self.tableWidget.setColumnWidth(3, 150) # 设置第5列宽度
|
||||
self.tableWidget.setColumnWidth(4, 150) # 设置第5列宽度
|
||||
self.tableWidget.setShowGrid(True)
|
||||
|
||||
font = QFont('微软雅黑', 20)
|
||||
font.setBold(True) # 设置字体加粗
|
||||
self.tableWidget.horizontalHeader().setFont(font) # 设置表头字体
|
||||
self.tableWidget.horizontalHeader().setFixedHeight(30) # 设置表头高度
|
||||
stylesheet = "::section{Background-color:rgb(242,242,242);border-radius:5px;border-width: 1px;border-style: " \
|
||||
"outset;border-color: white;font: bold 12px;} "
|
||||
self.tableWidget.horizontalHeader().setStyleSheet(stylesheet)
|
||||
|
||||
x = 0 # 当前行数
|
||||
for line in result.splitlines(): # 逐行读取pip 清单
|
||||
x += 1
|
||||
package = line.split()[0]
|
||||
version = line.split()[1]
|
||||
latest = line.split()[2]
|
||||
type = line.split()[3]
|
||||
|
||||
btn_update = QtWidgets.QPushButton("更新")
|
||||
btn_update.setMaximumWidth(40)
|
||||
btn_update.setStyleSheet('QPushButton{margin:3px}')
|
||||
btn_remove = QtWidgets.QPushButton("卸载")
|
||||
btn_remove.setMaximumWidth(40)
|
||||
btn_remove.setStyleSheet('QPushButton{margin:3px}')
|
||||
|
||||
btn_update.clicked.connect(self.btn_pip_update)
|
||||
btn_remove.clicked.connect(self.btn_pip_remove)
|
||||
|
||||
# 逐行写入pip数据到页面
|
||||
if 3 <= x <= len(result.splitlines()): # 从第3行开始识别
|
||||
y = 0 # 列
|
||||
while y <= 5:
|
||||
if y == 0:
|
||||
name = QTableWidgetItem(package)
|
||||
name.setTextAlignment(Qt.AlignCenter)
|
||||
self.tableWidget.setItem(x - 3, y, name)
|
||||
elif y == 1:
|
||||
ver = QTableWidgetItem(version)
|
||||
ver.setTextAlignment(Qt.AlignCenter)
|
||||
self.tableWidget.setItem(x - 3, y, ver)
|
||||
elif y == 2:
|
||||
ver = QTableWidgetItem(latest)
|
||||
ver.setTextAlignment(Qt.AlignCenter)
|
||||
self.tableWidget.setItem(x - 3, y, ver)
|
||||
elif y == 3:
|
||||
ver = QTableWidgetItem(type)
|
||||
ver.setTextAlignment(Qt.AlignCenter)
|
||||
self.tableWidget.setItem(x - 3, y, ver)
|
||||
elif y == 4:
|
||||
self.tableWidget.setCellWidget(x - 3, y, btn_update)
|
||||
elif y == 5:
|
||||
self.tableWidget.setCellWidget(x - 3, y, btn_remove)
|
||||
|
||||
y += 1
|
||||
|
||||
def btn_pip_remove(self):
|
||||
"""
|
||||
调用pip卸载包
|
||||
"""
|
||||
print("调用pip卸载包")
|
||||
row = self.tableWidget.currentRow()
|
||||
package = self.tableWidget.item(row, 0).text()
|
||||
package_remove_form = PackageRemoveForm()
|
||||
package_remove_form.set_package_name(package)
|
||||
package_remove_form.exec_()
|
||||
|
||||
def btn_pip_update(self):
|
||||
"""
|
||||
调用pip升级包
|
||||
"""
|
||||
print("调用pip升级包")
|
||||
row = self.tableWidget.currentRow()
|
||||
package = self.tableWidget.item(row, 0).text()
|
||||
package_update_form = PackageUpdateForm()
|
||||
package_update_form.set_package_name(package)
|
||||
package_update_form.exec_()
|
||||
|
||||
def pip_find(self):
|
||||
"""
|
||||
查找指定包
|
||||
"""
|
||||
text = self.lineEdit_find.text().strip() # 查找内容
|
||||
items = self.tableWidget.findItems(text, Qt.MatchContains)
|
||||
rows = self.tableWidget.rowCount() # 获取表格行数
|
||||
i = 0
|
||||
# 隐藏所有列
|
||||
while i < rows:
|
||||
self.tableWidget.setRowHidden(i, True)
|
||||
i += 1
|
||||
m = 0
|
||||
while m < len(items):
|
||||
try:
|
||||
item = items[m].row()
|
||||
self.tableWidget.setRowHidden(item, False)
|
||||
except:
|
||||
pass
|
||||
m += 1
|
||||
|
||||
def pip_update_check(self):
|
||||
cmd = sys.executable + " -m pip list -o "
|
||||
|
||||
|
||||
class PackageInstallForm(QWidget, PackageInstall_Ui_Form):
|
||||
"""
|
||||
打开"使用pip安装python包"窗口
|
||||
"""
|
||||
|
||||
def __init__(self, parent=None):
|
||||
super().__init__(parent)
|
||||
self.setupUi(self)
|
||||
self.center()
|
||||
self.pip_init()
|
||||
self.source_index = "-i https://mirrors.cloud.tencent.com/pypi/simple"
|
||||
|
||||
self.comboBox_source.currentIndexChanged.connect(self.source_change)
|
||||
self.comboBox_dir.currentIndexChanged.connect(self.dir_change)
|
||||
self.pushButton_ok.clicked.connect(self.package_install)
|
||||
self.pushButton_cancel.clicked.connect(self.close)
|
||||
self.checkBox_version.stateChanged.connect(self.version_change)
|
||||
|
||||
filter_delay = DelayedExecutionTimer(self.lineEdit_name)
|
||||
self.lineEdit_name.textChanged.connect(filter_delay.trigger)
|
||||
filter_delay.triggered[str].connect(self.set_package_info)
|
||||
|
||||
def keyPressEvent(self, e):
|
||||
"""
|
||||
按键盘Escape退出当前窗口
|
||||
@param e:
|
||||
"""
|
||||
if e.key() == Qt.Key_Escape:
|
||||
self.close()
|
||||
|
||||
def center(self):
|
||||
"""
|
||||
设置窗口居中
|
||||
"""
|
||||
screen = QDesktopWidget().screenGeometry()
|
||||
size = self.geometry()
|
||||
self.move((screen.width() - size.width()) / 2,
|
||||
(screen.height() - size.height()) / 2)
|
||||
|
||||
def pip_init(self):
|
||||
python_path = sys.executable
|
||||
package_path = os.path.split(python_path)[0] + r"Lib\site-packages"
|
||||
self.lineEdit_dir.setStyleSheet("background-color:rgb(208, 207, 209);")
|
||||
self.lineEdit_dir.setReadOnly(True)
|
||||
self.lineEdit_dir.setText(package_path)
|
||||
self.lineEdit_source.setStyleSheet("background-color:rgb(208, 207, 209);")
|
||||
self.lineEdit_source.setReadOnly(True)
|
||||
|
||||
def dir_change(self):
|
||||
import sys
|
||||
python_path = sys.executable
|
||||
if self.comboBox_dir.currentText() == "默认位置":
|
||||
self.lineEdit_dir.setReadOnly(True)
|
||||
self.lineEdit_dir.setStyleSheet("background-color:rgb(208, 207, 209);")
|
||||
package_path = os.path.split(python_path)[0] + r"Lib\site-packages"
|
||||
self.lineEdit_dir.setText(package_path)
|
||||
elif self.comboBox_dir.currentText() == "用户目录":
|
||||
self.lineEdit_dir.setReadOnly(True)
|
||||
self.lineEdit_dir.setStyleSheet("background-color:rgb(208, 207, 209);")
|
||||
for i in sys.path:
|
||||
if i.find("Users") >= 0 and i.find("site-packages") >= 0:
|
||||
self.lineEdit_dir.setText(i)
|
||||
elif self.comboBox_dir.currentText() == "自定义":
|
||||
self.lineEdit_dir.setReadOnly(False)
|
||||
self.lineEdit_dir.setStyleSheet("background-color:rgb(110, 190, 10);")
|
||||
self.lineEdit_dir.setText("")
|
||||
self.lineEdit_dir.setPlaceholderText("请选择python包安装目录")
|
||||
elif self.comboBox_dir.currentText() == "仅下载":
|
||||
self.lineEdit_dir.setReadOnly(False)
|
||||
self.lineEdit_dir.setStyleSheet("background-color:rgb(110, 190, 10);")
|
||||
self.lineEdit_dir.setText("")
|
||||
self.lineEdit_dir.setPlaceholderText("请选择下载目录")
|
||||
|
||||
def source_change(self):
|
||||
if self.comboBox_source.currentText() == "腾讯(推荐)":
|
||||
self.lineEdit_source.setReadOnly(True)
|
||||
self.lineEdit_source.setStyleSheet("background-color:rgb(208, 207, 209);")
|
||||
self.lineEdit_source.setText("https://mirrors.cloud.tencent.com/pypi/simple")
|
||||
elif self.comboBox_source.currentText() == "官方":
|
||||
self.lineEdit_source.setReadOnly(True)
|
||||
self.lineEdit_source.setStyleSheet("background-color:rgb(208, 207, 209);")
|
||||
self.lineEdit_source.setText("https://pypi.org/")
|
||||
elif self.comboBox_source.currentText() == "华为":
|
||||
self.lineEdit_source.setReadOnly(True)
|
||||
self.lineEdit_source.setStyleSheet("background-color:rgb(208, 207, 209);")
|
||||
self.lineEdit_source.setText("https://mirrors.huaweicloud.com/repository/pypi/simple")
|
||||
elif self.comboBox_source.currentText() == "清华大学":
|
||||
self.lineEdit_source.setReadOnly(True)
|
||||
self.lineEdit_source.setStyleSheet("background-color:rgb(208, 207, 209);")
|
||||
self.lineEdit_source.setText("https://pypi.tuna.tsinghua.edu.cn/simple")
|
||||
elif self.comboBox_source.currentText() == "阿里":
|
||||
self.lineEdit_source.setReadOnly(True)
|
||||
self.lineEdit_source.setStyleSheet("background-color:rgb(208, 207, 209);")
|
||||
self.lineEdit_source.setText("https://mirrors.aliyun.com/pypi/simple")
|
||||
elif self.comboBox_source.currentText() == "豆瓣":
|
||||
self.lineEdit_source.setReadOnly(True)
|
||||
self.lineEdit_source.setStyleSheet("background-color:rgb(208, 207, 209);")
|
||||
self.lineEdit_source.setText("http://pypi.douban.com/simple")
|
||||
elif self.comboBox_source.currentText() == "自定义":
|
||||
self.lineEdit_source.setReadOnly(False)
|
||||
self.lineEdit_source.setStyleSheet("background-color:rgb(110, 190, 10);")
|
||||
self.lineEdit_source.setText("")
|
||||
self.lineEdit_source.setPlaceholderText("请输入镜像源地址")
|
||||
|
||||
def version_change(self):
|
||||
if self.checkBox_version.checkState() == 2:
|
||||
self.comboBox_version.setEnabled(True)
|
||||
self.comboBox_version.setEditable(True)
|
||||
self.comboBox_version.setItemText(0, "")
|
||||
self.comboBox_version.lineEdit().setPlaceholderText("填写需要安装的版本号")
|
||||
else:
|
||||
self.comboBox_version.setEnabled(False)
|
||||
|
||||
def package_install(self):
|
||||
"""
|
||||
调用系统命令，使用pip安装python包
|
||||
"""
|
||||
if len(self.lineEdit_name.text().strip()) > 0:
|
||||
package_name = self.lineEdit_name.text().strip()
|
||||
else:
|
||||
QMessageBox.warning(self, '注意', '包名为空！', QMessageBox.Yes)
|
||||
|
||||
if self.checkBox_version.isChecked():
|
||||
if len(self.comboBox_version.currentText().strip()) > 0:
|
||||
version = "==" + self.comboBox_version.currentText().strip()
|
||||
else:
|
||||
version = ""
|
||||
else:
|
||||
version = ""
|
||||
|
||||
if self.comboBox_dir.currentText() == "默认位置":
|
||||
target = ""
|
||||
elif self.comboBox_dir.currentText() == "安装到用户目录":
|
||||
target = "--user"
|
||||
print("安装到用户目录")
|
||||
elif self.comboBox_dir.currentText() == "指定安装位置":
|
||||
target = "--target = " + self.lineEdit_dir.text()
|
||||
elif self.comboBox_dir.currentText() == "仅下载":
|
||||
print("仅下载")
|
||||
|
||||
if self.comboBox_source.currentText() == "腾讯(推荐)":
|
||||
self.source_index = "-i https://mirrors.cloud.tencent.com/pypi/simple"
|
||||
elif self.comboBox_source.currentText() == "官方":
|
||||
self.source_index = ""
|
||||
elif self.comboBox_source.currentText() == "华为":
|
||||
self.source_index = "-i https://mirrors.huaweicloud.com/repository/pypi/simple"
|
||||
elif self.comboBox_source.currentText() == "清华大学":
|
||||
self.source_index = "-i https://pypi.tuna.tsinghua.edu.cn/simple"
|
||||
elif self.comboBox_source.currentText() == "阿里":
|
||||
self.source_index = "-i https://mirrors.aliyun.com/pypi/simple"
|
||||
elif self.comboBox_source.currentText() == "豆瓣":
|
||||
self.source_index = "-i http://pypi.douban.com/simple"
|
||||
elif self.comboBox_source.currentText() == "自定义" and self.lineEdit_source.text() == "":
|
||||
self.source_index = "-i http://pypi.douban.com/simple"
|
||||
QMessageBox.warning(self, '注意', '镜像源地址为空！', QMessageBox.Yes)
|
||||
|
||||
self.th = threads.ThreadPipInstall(package_name=package_name, target_path=target,
|
||||
source_index=self.source_index, version=version)
|
||||
self.th.finishSignal.connect(self.button_finish)
|
||||
self.th.start()
|
||||
|
||||
def button_finish(self, result):
|
||||
print("信号接收成功")
|
||||
self.textEdit_log.moveCursor(QtGui.QTextCursor.End) # 鼠标移动到文本末尾
|
||||
self.textEdit_log.insertPlainText(result) # 插入执行结果
|
||||
# self.textEdit_log.setText(result)
|
||||
|
||||
def set_package_info(self):
|
||||
"""
|
||||
从pypi获取包的信息
|
||||
"""
|
||||
if len(self.lineEdit_name.text().strip()) > 0:
|
||||
self.textEdit_desc.setText("正在加载...")
|
||||
package_name = self.lineEdit_name.text()
|
||||
cmd = sys.executable + " -m pip search " + package_name
|
||||
# result = subprocess.check_output(cmd_info,encoding="utf-8")
|
||||
pipe = subprocess.run(cmd, shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE,
|
||||
encoding="utf-8")
|
||||
if pipe.returncode == 0:
|
||||
result = pipe.stdout
|
||||
else:
|
||||
result = pipe.stderr
|
||||
self.textEdit_desc.setText(result)
|
||||
else:
|
||||
self.textEdit_desc.setText("")
|
||||
|
||||
|
||||
class PackageUpdateForm(QWidget, PackageUpdate_Ui_Form):
|
||||
"""
|
||||
打开"使用pip更新python包"窗口
|
||||
"""
|
||||
|
||||
def __init__(self, parent=None):
|
||||
super().__init__(parent)
|
||||
self.setupUi(self)
|
||||
self.center()
|
||||
self.pip_init()
|
||||
self.source_index = "-i https://mirrors.cloud.tencent.com/pypi/simple"
|
||||
|
||||
# self.lineEdit_dir.setHidden(True) #隐藏安装目录
|
||||
|
||||
self.comboBox_source.currentIndexChanged.connect(self.source_change)
|
||||
self.comboBox_dir.currentIndexChanged.connect(self.dir_change)
|
||||
self.pushButton_ok.clicked.connect(self.package_update)
|
||||
self.pushButton_cancel.clicked.connect(self.close)
|
||||
self.checkBox_version.stateChanged.connect(self.version_change)
|
||||
|
||||
filter_delay = DelayedExecutionTimer(self.lineEdit_name)
|
||||
self.lineEdit_name.textChanged.connect(filter_delay.trigger)
|
||||
filter_delay.triggered[str].connect(self.set_package_info)
|
||||
|
||||
def keyPressEvent(self, e):
|
||||
"""
|
||||
按键盘Escape退出当前窗口
|
||||
@param e:
|
||||
"""
|
||||
if e.key() == Qt.Key_Escape:
|
||||
self.close()
|
||||
|
||||
def center(self):
|
||||
"""
|
||||
设置窗口居中
|
||||
"""
|
||||
screen = QDesktopWidget().screenGeometry()
|
||||
size = self.geometry()
|
||||
self.move((screen.width() - size.width()) / 2,
|
||||
(screen.height() - size.height()) / 2)
|
||||
|
||||
def pip_init(self):
|
||||
python_path = sys.executable
|
||||
package_path = os.path.split(python_path)[0] + r"Lib\site-packages"
|
||||
self.lineEdit_dir.setStyleSheet("background-color:rgb(208, 207, 209);")
|
||||
self.lineEdit_dir.setReadOnly(True)
|
||||
self.lineEdit_dir.setText(package_path)
|
||||
self.lineEdit_source.setStyleSheet("background-color:rgb(208, 207, 209);")
|
||||
self.lineEdit_source.setReadOnly(True)
|
||||
|
||||
def dir_change(self):
|
||||
import sys
|
||||
python_path = sys.executable
|
||||
if self.comboBox_dir.currentText() == "默认位置":
|
||||
self.lineEdit_dir.setReadOnly(True)
|
||||
self.lineEdit_dir.setStyleSheet("background-color:rgb(208, 207, 209);")
|
||||
package_path = os.path.split(python_path)[0] + r"Lib\site-packages"
|
||||
self.lineEdit_dir.setText(package_path)
|
||||
elif self.comboBox_dir.currentText() == "用户目录":
|
||||
self.lineEdit_dir.setReadOnly(True)
|
||||
self.lineEdit_dir.setStyleSheet("background-color:rgb(208, 207, 209);")
|
||||
for i in sys.path:
|
||||
if i.find("Users") >= 0 and i.find("site-packages") >= 0:
|
||||
self.lineEdit_dir.setText(i)
|
||||
elif self.comboBox_dir.currentText() == "自定义":
|
||||
self.lineEdit_dir.setReadOnly(False)
|
||||
self.lineEdit_dir.setStyleSheet("background-color:rgb(110, 190, 10);")
|
||||
self.lineEdit_dir.setText("")
|
||||
self.lineEdit_dir.setPlaceholderText("请选择python包安装目录")
|
||||
elif self.comboBox_dir.currentText() == "仅下载":
|
||||
self.lineEdit_dir.setReadOnly(False)
|
||||
self.lineEdit_dir.setStyleSheet("background-color:rgb(110, 190, 10);")
|
||||
self.lineEdit_dir.setText("")
|
||||
self.lineEdit_dir.setPlaceholderText("请选择下载目录")
|
||||
|
||||
def source_change(self):
|
||||
if self.comboBox_source.currentText() == "腾讯(推荐)":
|
||||
self.lineEdit_source.setReadOnly(True)
|
||||
self.lineEdit_source.setStyleSheet("background-color:rgb(208, 207, 209);")
|
||||
self.lineEdit_source.setText("https://mirrors.cloud.tencent.com/pypi/simple")
|
||||
elif self.comboBox_source.currentText() == "官方":
|
||||
self.lineEdit_source.setReadOnly(True)
|
||||
self.lineEdit_source.setStyleSheet("background-color:rgb(208, 207, 209);")
|
||||
self.lineEdit_source.setText("https://pypi.org/")
|
||||
elif self.comboBox_source.currentText() == "华为":
|
||||
self.lineEdit_source.setReadOnly(True)
|
||||
self.lineEdit_source.setStyleSheet("background-color:rgb(208, 207, 209);")
|
||||
self.lineEdit_source.setText("https://mirrors.huaweicloud.com/repository/pypi/simple")
|
||||
elif self.comboBox_source.currentText() == "清华大学":
|
||||
self.lineEdit_source.setReadOnly(True)
|
||||
self.lineEdit_source.setStyleSheet("background-color:rgb(208, 207, 209);")
|
||||
self.lineEdit_source.setText("https://pypi.tuna.tsinghua.edu.cn/simple")
|
||||
elif self.comboBox_source.currentText() == "阿里":
|
||||
self.lineEdit_source.setReadOnly(True)
|
||||
self.lineEdit_source.setStyleSheet("background-color:rgb(208, 207, 209);")
|
||||
self.lineEdit_source.setText("https://mirrors.aliyun.com/pypi/simple")
|
||||
elif self.comboBox_source.currentText() == "豆瓣":
|
||||
self.lineEdit_source.setReadOnly(True)
|
||||
self.lineEdit_source.setStyleSheet("background-color:rgb(208, 207, 209);")
|
||||
self.lineEdit_source.setText("http://pypi.douban.com/simple")
|
||||
elif self.comboBox_source.currentText() == "自定义":
|
||||
self.lineEdit_source.setReadOnly(False)
|
||||
self.lineEdit_source.setStyleSheet("background-color:rgb(110, 190, 10);")
|
||||
self.lineEdit_source.setText("")
|
||||
self.lineEdit_source.setPlaceholderText("请输入镜像源地址")
|
||||
|
||||
def version_change(self):
|
||||
if self.checkBox_version.checkState() == 2:
|
||||
self.comboBox_version.setEnabled(True)
|
||||
self.comboBox_version.setEditable(True)
|
||||
self.comboBox_version.setItemText(0, "")
|
||||
self.comboBox_version.lineEdit().setPlaceholderText("填写需要安装的版本号")
|
||||
else:
|
||||
self.comboBox_version.setEnabled(False)
|
||||
|
||||
def package_update(self):
|
||||
"""
|
||||
调用系统命令，使用pip安装python包
|
||||
"""
|
||||
if len(self.lineEdit_name.text().strip()) > 0:
|
||||
package_name = self.lineEdit_name.text().strip()
|
||||
else:
|
||||
QMessageBox.warning(self, '注意', '包名为空！', QMessageBox.Yes)
|
||||
|
||||
if self.checkBox_version.isChecked():
|
||||
if len(self.comboBox_version.currentText().strip()) > 0:
|
||||
version = "==" + self.comboBox_version.currentText().strip()
|
||||
else:
|
||||
version = ""
|
||||
else:
|
||||
version = ""
|
||||
|
||||
if self.comboBox_dir.currentText() == "默认位置":
|
||||
target = ""
|
||||
elif self.comboBox_dir.currentText() == "安装到用户目录":
|
||||
target = "--user"
|
||||
print("安装到用户目录")
|
||||
elif self.comboBox_dir.currentText() == "指定安装位置":
|
||||
target = "--target = " + self.lineEdit_dir.text()
|
||||
elif self.comboBox_dir.currentText() == "仅下载":
|
||||
print("仅下载")
|
||||
|
||||
if self.comboBox_source.currentText() == "腾讯(推荐)":
|
||||
self.source_index = "-i https://mirrors.cloud.tencent.com/pypi/simple"
|
||||
elif self.comboBox_source.currentText() == "官方":
|
||||
self.source_index = ""
|
||||
elif self.comboBox_source.currentText() == "华为":
|
||||
self.source_index = "-i https://mirrors.huaweicloud.com/repository/pypi/simple"
|
||||
elif self.comboBox_source.currentText() == "清华大学":
|
||||
self.source_index = "-i https://pypi.tuna.tsinghua.edu.cn/simple"
|
||||
elif self.comboBox_source.currentText() == "阿里":
|
||||
self.source_index = "-i https://mirrors.aliyun.com/pypi/simple"
|
||||
elif self.comboBox_source.currentText() == "豆瓣":
|
||||
self.source_index = "-i http://pypi.douban.com/simple"
|
||||
elif self.comboBox_source.currentText() == "自定义" and self.lineEdit_source.text() == "":
|
||||
self.source_index = "-i http://pypi.douban.com/simple"
|
||||
QMessageBox.warning(self, '注意', '镜像源地址为空！', QMessageBox.Yes)
|
||||
cmd = sys.executable + " -m pip install --upgrade " + self.source_index + " " + target + " " + package_name + version
|
||||
self.textEdit_log.setPlainText("") # 清空当前日志
|
||||
self.textEdit_log.insertPlainText("正在执行{0}".format(cmd) + '\n')
|
||||
|
||||
# result = subprocess.check_output(cmd.strip(), encoding="utf-8")
|
||||
pipe = subprocess.run(cmd.strip(), shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE,
|
||||
encoding="utf-8")
|
||||
if pipe.returncode == 0:
|
||||
result = pipe.stdout
|
||||
else:
|
||||
result = pipe.stderr
|
||||
|
||||
self.textEdit_log.insertPlainText(result)
|
||||
|
||||
def set_cmd(self, str):
|
||||
self.textEdit_log.setText("当前命令为：{0}".format(str))
|
||||
self.package_update()
|
||||
|
||||
def set_package_name(self, str):
|
||||
self.lineEdit_name.setText(str)
|
||||
|
||||
def set_package_info(self):
|
||||
if len(self.lineEdit_name.text().strip()) > 0:
|
||||
self.textEdit_desc.setText("正在加载...")
|
||||
package_name = self.lineEdit_name.text()
|
||||
cmd = sys.executable + " -m pip show " + package_name
|
||||
# result = subprocess.check_output(cmd_info, encoding="utf-8")
|
||||
pipe = subprocess.run(cmd.strip(), shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE,
|
||||
encoding="utf-8")
|
||||
if pipe.returncode == 0:
|
||||
result = pipe.stdout
|
||||
else:
|
||||
result = pipe.stderr
|
||||
|
||||
self.textEdit_desc.setText(result)
|
||||
else:
|
||||
self.textEdit_desc.setText("")
|
||||
|
||||
|
||||
class PackageRemoveForm(QWidget, PackageRemove_Ui_Form):
|
||||
"""
|
||||
打开"使用pip卸载python包"窗口
|
||||
"""
|
||||
|
||||
def __init__(self, parent=None):
|
||||
super().__init__(parent)
|
||||
self.setupUi(self)
|
||||
self.center()
|
||||
|
||||
self.toolButton_open.clicked.connect(self.open_package_path)
|
||||
self.pushButton_ok.clicked.connect(self.package_remove)
|
||||
|
||||
filter_delay = DelayedExecutionTimer(self.lineEdit_name)
|
||||
self.lineEdit_name.textChanged.connect(filter_delay.trigger)
|
||||
filter_delay.triggered[str].connect(self.set_package_info)
|
||||
|
||||
# self.pip_init()
|
||||
|
||||
# self.lineEdit_dir.setHidden(True) #隐藏安装目录
|
||||
|
||||
# self.comboBox_source.currentIndexChanged.connect(self.source_change)
|
||||
# self.comboBox_dir.currentIndexChanged.connect(self.dir_change)
|
||||
|
||||
# self.pushButton_cancel.clicked.connect(self.close)
|
||||
# self.checkBox_version.stateChanged.connect(self.version_change)
|
||||
|
||||
def keyPressEvent(self, e):
|
||||
"""
|
||||
按键盘Escape退出当前窗口
|
||||
@param e:
|
||||
"""
|
||||
if e.key() == Qt.Key_Escape:
|
||||
self.close()
|
||||
|
||||
def center(self):
|
||||
"""
|
||||
设置窗口居中
|
||||
"""
|
||||
screen = QDesktopWidget().screenGeometry()
|
||||
size = self.geometry()
|
||||
self.move((screen.width() - size.width()) / 2,
|
||||
(screen.height() - size.height()) / 2)
|
||||
|
||||
def open_package_path(self):
|
||||
"""
|
||||
打开python包的安装路径
|
||||
"""
|
||||
import win32api
|
||||
path = self.lineEdit_dir.text()
|
||||
try:
|
||||
win32api.ShellExecute(0, 'open', path, '', '', 1)
|
||||
except IOError:
|
||||
print("error")
|
||||
|
||||
def pip_init(self):
|
||||
python_path = sys.executable
|
||||
package_path = os.path.split(python_path)[0] + r"Lib\site-packages"
|
||||
self.lineEdit_dir.setStyleSheet("background-color:rgb(208, 207, 209);")
|
||||
self.lineEdit_dir.setReadOnly(True)
|
||||
self.lineEdit_dir.setText(package_path)
|
||||
self.lineEdit_source.setStyleSheet("background-color:rgb(208, 207, 209);")
|
||||
self.lineEdit_source.setReadOnly(True)
|
||||
|
||||
def package_remove(self):
|
||||
"""
|
||||
调用系统命令，使用pip卸载python包
|
||||
"""
|
||||
if len(self.lineEdit_name.text().strip()) > 0:
|
||||
self.textEdit_desc.setText("正在加载...")
|
||||
package_name = self.lineEdit_name.text()
|
||||
cmd = sys.executable + " -m pip uninstall " + package_name
|
||||
# result = subprocess.check_output(cmd_info, encoding="utf-8")
|
||||
pipe = subprocess.run(cmd.strip(), shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE,
|
||||
encoding="utf-8")
|
||||
if pipe.returncode == 0:
|
||||
result = pipe.stdout
|
||||
else:
|
||||
result = pipe.stderr
|
||||
|
||||
self.textEdit_desc.setText(result)
|
||||
else:
|
||||
self.textEdit_desc.setText("")
|
||||
|
||||
def set_cmd(self, str):
|
||||
self.textEdit_log.setText("当前命令为：{0}".format(str))
|
||||
|
||||
def set_package_name(self, str):
|
||||
self.lineEdit_name.setText(str)
|
||||
|
||||
def set_package_info(self):
|
||||
if len(self.lineEdit_name.text().strip()) > 0:
|
||||
self.textEdit_desc.setText("正在加载...")
|
||||
package_name = self.lineEdit_name.text()
|
||||
cmd = sys.executable + " -m pip show " + package_name
|
||||
# result = subprocess.check_output(cmd_info, encoding="utf-8")
|
||||
pipe = subprocess.run(cmd.strip(), shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE,
|
||||
encoding="utf-8")
|
||||
if pipe.returncode == 0:
|
||||
result = pipe.stdout
|
||||
for line in result.splitlines():
|
||||
if line.find("Location") >= 0:
|
||||
self.lineEdit_dir.setText(line[10:])
|
||||
else:
|
||||
result = pipe.stderr
|
||||
|
||||
self.textEdit_desc.setText(result)
|
||||
else:
|
||||
self.textEdit_desc.setText("")
|
||||
|
||||
|
||||
class PackageSettingForm(QWidget, PackageSetting_Ui_Form):
|
||||
"""
|
||||
打开"使用pip卸载python包"窗口
|
||||
"""
|
||||
|
||||
def __init__(self, parent=None):
|
||||
super().__init__(parent)
|
||||
self.setupUi(self)
|
||||
self.center()
|
||||
|
||||
def keyPressEvent(self, e):
|
||||
"""
|
||||
按键盘Escape退出当前窗口
|
||||
@param e:
|
||||
"""
|
||||
if e.key() == Qt.Key_Escape:
|
||||
self.close()
|
||||
|
||||
def center(self):
|
||||
"""
|
||||
设置窗口居中
|
||||
"""
|
||||
screen = QDesktopWidget().screenGeometry()
|
||||
size = self.geometry()
|
||||
self.move((screen.width() - size.width()) / 2,
|
||||
(screen.height() - size.height()) / 2)
|
||||
|
||||
|
||||
class DelayedExecutionTimer(QObject): # source: https://wiki.qt.io/Delay_action_to_wait_for_user_interaction
|
||||
"""
|
||||
延迟执行筛选
|
||||
"""
|
||||
triggered = pyqtSignal(str)
|
||||
|
||||
def __init__(self, parent):
|
||||
super(DelayedExecutionTimer, self).__init__(parent)
|
||||
# The minimum delay is the time the class will wait after being triggered before emitting the triggered() signal
|
||||
# (if there is no key press for this time: trigger)
|
||||
self.minimumDelay = 500
|
||||
self.minimumTimer = QTimer(self)
|
||||
self.minimumTimer.timeout.connect(self.timeout)
|
||||
|
||||
def timeout(self):
|
||||
self.minimumTimer.stop()
|
||||
self.triggered.emit(self.string)
|
||||
|
||||
def trigger(self, string):
|
||||
self.string = string
|
||||
self.minimumTimer.stop()
|
||||
self.minimumTimer.start(self.minimumDelay)
|
||||
|
||||
|
||||
class database_pip_manage(QObject):
|
||||
def __init__(self, parent=None):
|
||||
super().__init__(parent)
|
||||
|
||||
def db_pip_update_insert(self):
|
||||
from PyQt5 import QtSql
|
||||
from PyQt5.QtSql import QSqlQuery
|
||||
|
||||
database = QtSql.QSqlDatabase.addDatabase('QSQLITE')
|
||||
database.setDatabaseName('patata.db')
|
||||
|
||||
if database.open():
|
||||
print("OK")
|
||||
else:
|
||||
print("连接数据库失败！")
|
||||
|
||||
insert_sql = 'insert into pip_install_info values (?,?,?)'
|
||||
query = QSqlQuery()
|
||||
query.prepare(insert_sql)
|
||||
query.addBindValue(4)
|
||||
query.addBindValue('test3')
|
||||
query.addBindValue(1)
|
||||
if not query.exec_():
|
||||
print(query.lastError())
|
||||
else:
|
||||
print('inserted')
|
||||
|
||||
|
||||
|
||||
def button_finish(self, msg):
|
||||
print(msg)
|
||||
|
||||
|
||||
|
||||
# ====================================窗体测试程序============================
|
||||
if __name__ == '__main__':
|
||||
app = QApplication(sys.argv)
|
||||
form = PackageManagerForm()
|
||||
form.show()
|
||||
sys.exit(app.exec_())
|
||||
@ -0,0 +1,95 @@
|
||||
# -*- coding: utf-8 -*-
|
||||
|
||||
# Form implementation generated from reading ui file 'package_remove.ui'
|
||||
#
|
||||
# Created by: PyQt5 UI code generator 5.14.1
|
||||
#
|
||||
# WARNING! All changes made in this file will be lost!
|
||||
|
||||
|
||||
from PyQt5 import QtCore, QtGui, QtWidgets
|
||||
|
||||
|
||||
class Ui_Form(object):
|
||||
def setupUi(self, Form):
|
||||
Form.setObjectName("Form")
|
||||
Form.resize(800, 600)
|
||||
self.verticalLayout = QtWidgets.QVBoxLayout(Form)
|
||||
self.verticalLayout.setObjectName("verticalLayout")
|
||||
self.horizontalLayout_4 = QtWidgets.QHBoxLayout()
|
||||
self.horizontalLayout_4.setObjectName("horizontalLayout_4")
|
||||
self.formLayout = QtWidgets.QFormLayout()
|
||||
self.formLayout.setObjectName("formLayout")
|
||||
self.label_2 = QtWidgets.QLabel(Form)
|
||||
self.label_2.setObjectName("label_2")
|
||||
self.formLayout.setWidget(0, QtWidgets.QFormLayout.LabelRole, self.label_2)
|
||||
self.lineEdit_name = QtWidgets.QLineEdit(Form)
|
||||
self.lineEdit_name.setText("")
|
||||
self.lineEdit_name.setObjectName("lineEdit_name")
|
||||
self.formLayout.setWidget(0, QtWidgets.QFormLayout.FieldRole, self.lineEdit_name)
|
||||
self.label_3 = QtWidgets.QLabel(Form)
|
||||
self.label_3.setObjectName("label_3")
|
||||
self.formLayout.setWidget(1, QtWidgets.QFormLayout.LabelRole, self.label_3)
|
||||
self.horizontalLayout = QtWidgets.QHBoxLayout()
|
||||
self.horizontalLayout.setObjectName("horizontalLayout")
|
||||
self.lineEdit_dir = QtWidgets.QLineEdit(Form)
|
||||
self.lineEdit_dir.setReadOnly(True)
|
||||
self.lineEdit_dir.setObjectName("lineEdit_dir")
|
||||
self.horizontalLayout.addWidget(self.lineEdit_dir)
|
||||
self.toolButton_open = QtWidgets.QToolButton(Form)
|
||||
self.toolButton_open.setMinimumSize(QtCore.QSize(0, 22))
|
||||
self.toolButton_open.setObjectName("toolButton_open")
|
||||
self.horizontalLayout.addWidget(self.toolButton_open)
|
||||
self.formLayout.setLayout(1, QtWidgets.QFormLayout.FieldRole, self.horizontalLayout)
|
||||
self.horizontalLayout_4.addLayout(self.formLayout)
|
||||
self.verticalLayout.addLayout(self.horizontalLayout_4)
|
||||
self.groupBox = QtWidgets.QGroupBox(Form)
|
||||
self.groupBox.setObjectName("groupBox")
|
||||
self.horizontalLayout_5 = QtWidgets.QHBoxLayout(self.groupBox)
|
||||
self.horizontalLayout_5.setContentsMargins(0, 0, 0, 0)
|
||||
self.horizontalLayout_5.setObjectName("horizontalLayout_5")
|
||||
self.textEdit_desc = QtWidgets.QTextEdit(self.groupBox)
|
||||
self.textEdit_desc.setObjectName("textEdit_desc")
|
||||
self.horizontalLayout_5.addWidget(self.textEdit_desc)
|
||||
self.verticalLayout.addWidget(self.groupBox)
|
||||
self.groupBox_2 = QtWidgets.QGroupBox(Form)
|
||||
self.groupBox_2.setObjectName("groupBox_2")
|
||||
self.horizontalLayout_6 = QtWidgets.QHBoxLayout(self.groupBox_2)
|
||||
self.horizontalLayout_6.setContentsMargins(0, 0, 0, 0)
|
||||
self.horizontalLayout_6.setObjectName("horizontalLayout_6")
|
||||
self.textEdit_log = QtWidgets.QTextEdit(self.groupBox_2)
|
||||
self.textEdit_log.setObjectName("textEdit_log")
|
||||
self.horizontalLayout_6.addWidget(self.textEdit_log)
|
||||
self.verticalLayout.addWidget(self.groupBox_2)
|
||||
self.widget = QtWidgets.QWidget(Form)
|
||||
self.widget.setMaximumSize(QtCore.QSize(16777215, 50))
|
||||
self.widget.setObjectName("widget")
|
||||
self.verticalLayout_2 = QtWidgets.QVBoxLayout(self.widget)
|
||||
self.verticalLayout_2.setObjectName("verticalLayout_2")
|
||||
self.horizontalLayout_2 = QtWidgets.QHBoxLayout()
|
||||
self.horizontalLayout_2.setObjectName("horizontalLayout_2")
|
||||
spacerItem = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum)
|
||||
self.horizontalLayout_2.addItem(spacerItem)
|
||||
self.pushButton_ok = QtWidgets.QPushButton(self.widget)
|
||||
self.pushButton_ok.setObjectName("pushButton_ok")
|
||||
self.horizontalLayout_2.addWidget(self.pushButton_ok)
|
||||
self.pushButton_cancel = QtWidgets.QPushButton(self.widget)
|
||||
self.pushButton_cancel.setObjectName("pushButton_cancel")
|
||||
self.horizontalLayout_2.addWidget(self.pushButton_cancel)
|
||||
self.verticalLayout_2.addLayout(self.horizontalLayout_2)
|
||||
self.verticalLayout.addWidget(self.widget)
|
||||
|
||||
self.retranslateUi(Form)
|
||||
QtCore.QMetaObject.connectSlotsByName(Form)
|
||||
|
||||
def retranslateUi(self, Form):
|
||||
_translate = QtCore.QCoreApplication.translate
|
||||
Form.setWindowTitle(_translate("Form", "卸载"))
|
||||
self.label_2.setText(_translate("Form", "包名:"))
|
||||
self.label_3.setText(_translate("Form", "当前安装位置:"))
|
||||
self.lineEdit_dir.setPlaceholderText(_translate("Form", "默认"))
|
||||
self.toolButton_open.setText(_translate("Form", "打开"))
|
||||
self.groupBox.setTitle(_translate("Form", "详情"))
|
||||
self.groupBox_2.setTitle(_translate("Form", "执行记录"))
|
||||
self.pushButton_ok.setText(_translate("Form", "确定"))
|
||||
self.pushButton_cancel.setText(_translate("Form", "取消"))
|
||||
168
pyminer/features/extensions/package_manager/package_remove.ui
Normal file
168
pyminer/features/extensions/package_manager/package_remove.ui
Normal file
@ -0,0 +1,168 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<ui version="4.0">
|
||||
<class>Form</class>
|
||||
<widget class="QWidget" name="Form">
|
||||
<property name="geometry">
|
||||
<rect>
|
||||
<x>0</x>
|
||||
<y>0</y>
|
||||
<width>800</width>
|
||||
<height>600</height>
|
||||
</rect>
|
||||
</property>
|
||||
<property name="windowTitle">
|
||||
<string>卸载</string>
|
||||
</property>
|
||||
<layout class="QVBoxLayout" name="verticalLayout">
|
||||
<item>
|
||||
<layout class="QHBoxLayout" name="horizontalLayout_4">
|
||||
<item>
|
||||
<layout class="QFormLayout" name="formLayout">
|
||||
<item row="0" column="0">
|
||||
<widget class="QLabel" name="label_2">
|
||||
<property name="text">
|
||||
<string>包名:</string>
|
||||
</property>
|
||||
</widget>
|
||||
</item>
|
||||
<item row="0" column="1">
|
||||
<widget class="QLineEdit" name="lineEdit_name">
|
||||
<property name="text">
|
||||
<string/>
|
||||
</property>
|
||||
</widget>
|
||||
</item>
|
||||
<item row="1" column="0">
|
||||
<widget class="QLabel" name="label_3">
|
||||
<property name="text">
|
||||
<string>当前安装位置:</string>
|
||||
</property>
|
||||
</widget>
|
||||
</item>
|
||||
<item row="1" column="1">
|
||||
<layout class="QHBoxLayout" name="horizontalLayout">
|
||||
<item>
|
||||
<widget class="QLineEdit" name="lineEdit_dir">
|
||||
<property name="readOnly">
|
||||
<bool>true</bool>
|
||||
</property>
|
||||
<property name="placeholderText">
|
||||
<string>默认</string>
|
||||
</property>
|
||||
</widget>
|
||||
</item>
|
||||
<item>
|
||||
<widget class="QToolButton" name="toolButton_open">
|
||||
<property name="minimumSize">
|
||||
<size>
|
||||
<width>0</width>
|
||||
<height>22</height>
|
||||
</size>
|
||||
</property>
|
||||
<property name="text">
|
||||
<string>打开</string>
|
||||
</property>
|
||||
</widget>
|
||||
</item>
|
||||
</layout>
|
||||
</item>
|
||||
</layout>
|
||||
</item>
|
||||
</layout>
|
||||
</item>
|
||||
<item>
|
||||
<widget class="QGroupBox" name="groupBox">
|
||||
<property name="title">
|
||||
<string>详情</string>
|
||||
</property>
|
||||
<layout class="QHBoxLayout" name="horizontalLayout_5">
|
||||
<property name="leftMargin">
|
||||
<number>0</number>
|
||||
</property>
|
||||
<property name="topMargin">
|
||||
<number>0</number>
|
||||
</property>
|
||||
<property name="rightMargin">
|
||||
<number>0</number>
|
||||
</property>
|
||||
<property name="bottomMargin">
|
||||
<number>0</number>
|
||||
</property>
|
||||
<item>
|
||||
<widget class="QTextEdit" name="textEdit_desc"/>
|
||||
</item>
|
||||
</layout>
|
||||
</widget>
|
||||
</item>
|
||||
<item>
|
||||
<widget class="QGroupBox" name="groupBox_2">
|
||||
<property name="title">
|
||||
<string>执行记录</string>
|
||||
</property>
|
||||
<layout class="QHBoxLayout" name="horizontalLayout_6">
|
||||
<property name="leftMargin">
|
||||
<number>0</number>
|
||||
</property>
|
||||
<property name="topMargin">
|
||||
<number>0</number>
|
||||
</property>
|
||||
<property name="rightMargin">
|
||||
<number>0</number>
|
||||
</property>
|
||||
<property name="bottomMargin">
|
||||
<number>0</number>
|
||||
</property>
|
||||
<item>
|
||||
<widget class="QTextEdit" name="textEdit_log"/>
|
||||
</item>
|
||||
</layout>
|
||||
</widget>
|
||||
</item>
|
||||
<item>
|
||||
<widget class="QWidget" name="widget" native="true">
|
||||
<property name="maximumSize">
|
||||
<size>
|
||||
<width>16777215</width>
|
||||
<height>50</height>
|
||||
</size>
|
||||
</property>
|
||||
<layout class="QVBoxLayout" name="verticalLayout_2">
|
||||
<item>
|
||||
<layout class="QHBoxLayout" name="horizontalLayout_2">
|
||||
<item>
|
||||
<spacer name="horizontalSpacer">
|
||||
<property name="orientation">
|
||||
<enum>Qt::Horizontal</enum>
|
||||
</property>
|
||||
<property name="sizeHint" stdset="0">
|
||||
<size>
|
||||
<width>40</width>
|
||||
<height>20</height>
|
||||
</size>
|
||||
</property>
|
||||
</spacer>
|
||||
</item>
|
||||
<item>
|
||||
<widget class="QPushButton" name="pushButton_ok">
|
||||
<property name="text">
|
||||
<string>确定</string>
|
||||
</property>
|
||||
</widget>
|
||||
</item>
|
||||
<item>
|
||||
<widget class="QPushButton" name="pushButton_cancel">
|
||||
<property name="text">
|
||||
<string>取消</string>
|
||||
</property>
|
||||
</widget>
|
||||
</item>
|
||||
</layout>
|
||||
</item>
|
||||
</layout>
|
||||
</widget>
|
||||
</item>
|
||||
</layout>
|
||||
</widget>
|
||||
<resources/>
|
||||
<connections/>
|
||||
</ui>
|
||||
178
pyminer/features/extensions/package_manager/package_setting.py
Normal file
178
pyminer/features/extensions/package_manager/package_setting.py
Normal file
@ -0,0 +1,178 @@
|
||||
# -*- coding: utf-8 -*-
|
||||
|
||||
# Form implementation generated from reading ui file 'package_setting.ui'
|
||||
#
|
||||
# Created by: PyQt5 UI code generator 5.14.1
|
||||
#
|
||||
# WARNING! All changes made in this file will be lost!
|
||||
|
||||
|
||||
from PyQt5 import QtCore, QtGui, QtWidgets
|
||||
|
||||
|
||||
class Ui_Form(object):
|
||||
def setupUi(self, Form):
|
||||
Form.setObjectName("Form")
|
||||
Form.resize(600, 400)
|
||||
self.verticalLayout = QtWidgets.QVBoxLayout(Form)
|
||||
self.verticalLayout.setObjectName("verticalLayout")
|
||||
self.splitter = QtWidgets.QSplitter(Form)
|
||||
self.splitter.setOrientation(QtCore.Qt.Horizontal)
|
||||
self.splitter.setObjectName("splitter")
|
||||
self.widget_2 = QtWidgets.QWidget(self.splitter)
|
||||
self.widget_2.setMaximumSize(QtCore.QSize(120, 16777215))
|
||||
self.widget_2.setObjectName("widget_2")
|
||||
self.verticalLayout_2 = QtWidgets.QVBoxLayout(self.widget_2)
|
||||
self.verticalLayout_2.setContentsMargins(0, 0, 0, 0)
|
||||
self.verticalLayout_2.setObjectName("verticalLayout_2")
|
||||
self.listWidget = QtWidgets.QListWidget(self.widget_2)
|
||||
sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Preferred)
|
||||
sizePolicy.setHorizontalStretch(0)
|
||||
sizePolicy.setVerticalStretch(0)
|
||||
sizePolicy.setHeightForWidth(self.listWidget.sizePolicy().hasHeightForWidth())
|
||||
self.listWidget.setSizePolicy(sizePolicy)
|
||||
self.listWidget.setObjectName("listWidget")
|
||||
item = QtWidgets.QListWidgetItem()
|
||||
self.listWidget.addItem(item)
|
||||
item = QtWidgets.QListWidgetItem()
|
||||
self.listWidget.addItem(item)
|
||||
self.verticalLayout_2.addWidget(self.listWidget)
|
||||
self.stackedWidget = QtWidgets.QStackedWidget(self.splitter)
|
||||
self.stackedWidget.setObjectName("stackedWidget")
|
||||
self.page = QtWidgets.QWidget()
|
||||
self.page.setObjectName("page")
|
||||
self.verticalLayout_3 = QtWidgets.QVBoxLayout(self.page)
|
||||
self.verticalLayout_3.setObjectName("verticalLayout_3")
|
||||
self.horizontalLayout_2 = QtWidgets.QHBoxLayout()
|
||||
self.horizontalLayout_2.setObjectName("horizontalLayout_2")
|
||||
self.label = QtWidgets.QLabel(self.page)
|
||||
self.label.setObjectName("label")
|
||||
self.horizontalLayout_2.addWidget(self.label)
|
||||
self.comboBox_source = QtWidgets.QComboBox(self.page)
|
||||
self.comboBox_source.setEnabled(True)
|
||||
self.comboBox_source.setMinimumSize(QtCore.QSize(100, 0))
|
||||
self.comboBox_source.setMaximumSize(QtCore.QSize(100, 16777215))
|
||||
self.comboBox_source.setObjectName("comboBox_source")
|
||||
self.comboBox_source.addItem("")
|
||||
self.comboBox_source.addItem("")
|
||||
self.comboBox_source.addItem("")
|
||||
self.comboBox_source.addItem("")
|
||||
self.comboBox_source.addItem("")
|
||||
self.comboBox_source.addItem("")
|
||||
self.horizontalLayout_2.addWidget(self.comboBox_source)
|
||||
self.lineEdit_source = QtWidgets.QLineEdit(self.page)
|
||||
self.lineEdit_source.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter)
|
||||
self.lineEdit_source.setReadOnly(True)
|
||||
self.lineEdit_source.setObjectName("lineEdit_source")
|
||||
self.horizontalLayout_2.addWidget(self.lineEdit_source)
|
||||
self.verticalLayout_3.addLayout(self.horizontalLayout_2)
|
||||
self.horizontalLayout_3 = QtWidgets.QHBoxLayout()
|
||||
self.horizontalLayout_3.setObjectName("horizontalLayout_3")
|
||||
self.label_3 = QtWidgets.QLabel(self.page)
|
||||
self.label_3.setObjectName("label_3")
|
||||
self.horizontalLayout_3.addWidget(self.label_3)
|
||||
self.comboBox_dir = QtWidgets.QComboBox(self.page)
|
||||
self.comboBox_dir.setMinimumSize(QtCore.QSize(100, 0))
|
||||
self.comboBox_dir.setMaximumSize(QtCore.QSize(100, 16777215))
|
||||
self.comboBox_dir.setObjectName("comboBox_dir")
|
||||
self.comboBox_dir.addItem("")
|
||||
self.comboBox_dir.addItem("")
|
||||
self.comboBox_dir.addItem("")
|
||||
self.comboBox_dir.addItem("")
|
||||
self.horizontalLayout_3.addWidget(self.comboBox_dir)
|
||||
self.lineEdit_dir = QtWidgets.QLineEdit(self.page)
|
||||
self.lineEdit_dir.setReadOnly(True)
|
||||
self.lineEdit_dir.setObjectName("lineEdit_dir")
|
||||
self.horizontalLayout_3.addWidget(self.lineEdit_dir)
|
||||
self.toolButton = QtWidgets.QToolButton(self.page)
|
||||
self.toolButton.setObjectName("toolButton")
|
||||
self.horizontalLayout_3.addWidget(self.toolButton)
|
||||
self.verticalLayout_3.addLayout(self.horizontalLayout_3)
|
||||
self.horizontalLayout_4 = QtWidgets.QHBoxLayout()
|
||||
self.horizontalLayout_4.setObjectName("horizontalLayout_4")
|
||||
self.label_4 = QtWidgets.QLabel(self.page)
|
||||
self.label_4.setObjectName("label_4")
|
||||
self.horizontalLayout_4.addWidget(self.label_4)
|
||||
self.comboBox_dir_2 = QtWidgets.QComboBox(self.page)
|
||||
self.comboBox_dir_2.setMinimumSize(QtCore.QSize(100, 0))
|
||||
self.comboBox_dir_2.setMaximumSize(QtCore.QSize(100, 16777215))
|
||||
self.comboBox_dir_2.setObjectName("comboBox_dir_2")
|
||||
self.comboBox_dir_2.addItem("")
|
||||
self.comboBox_dir_2.addItem("")
|
||||
self.comboBox_dir_2.addItem("")
|
||||
self.comboBox_dir_2.addItem("")
|
||||
self.horizontalLayout_4.addWidget(self.comboBox_dir_2)
|
||||
self.lineEdit_dir_2 = QtWidgets.QLineEdit(self.page)
|
||||
self.lineEdit_dir_2.setReadOnly(True)
|
||||
self.lineEdit_dir_2.setObjectName("lineEdit_dir_2")
|
||||
self.horizontalLayout_4.addWidget(self.lineEdit_dir_2)
|
||||
self.toolButton_2 = QtWidgets.QToolButton(self.page)
|
||||
self.toolButton_2.setObjectName("toolButton_2")
|
||||
self.horizontalLayout_4.addWidget(self.toolButton_2)
|
||||
self.verticalLayout_3.addLayout(self.horizontalLayout_4)
|
||||
spacerItem = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding)
|
||||
self.verticalLayout_3.addItem(spacerItem)
|
||||
self.stackedWidget.addWidget(self.page)
|
||||
self.page_2 = QtWidgets.QWidget()
|
||||
self.page_2.setObjectName("page_2")
|
||||
self.stackedWidget.addWidget(self.page_2)
|
||||
self.verticalLayout.addWidget(self.splitter)
|
||||
self.widget = QtWidgets.QWidget(Form)
|
||||
self.widget.setMinimumSize(QtCore.QSize(0, 50))
|
||||
self.widget.setMaximumSize(QtCore.QSize(16777215, 50))
|
||||
self.widget.setObjectName("widget")
|
||||
self.horizontalLayout = QtWidgets.QHBoxLayout(self.widget)
|
||||
self.horizontalLayout.setContentsMargins(0, 0, 0, 0)
|
||||
self.horizontalLayout.setObjectName("horizontalLayout")
|
||||
self.pushButton = QtWidgets.QPushButton(self.widget)
|
||||
self.pushButton.setObjectName("pushButton")
|
||||
self.horizontalLayout.addWidget(self.pushButton)
|
||||
spacerItem1 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum)
|
||||
self.horizontalLayout.addItem(spacerItem1)
|
||||
self.pushButton_2 = QtWidgets.QPushButton(self.widget)
|
||||
self.pushButton_2.setObjectName("pushButton_2")
|
||||
self.horizontalLayout.addWidget(self.pushButton_2)
|
||||
self.pushButton_3 = QtWidgets.QPushButton(self.widget)
|
||||
self.pushButton_3.setObjectName("pushButton_3")
|
||||
self.horizontalLayout.addWidget(self.pushButton_3)
|
||||
self.verticalLayout.addWidget(self.widget)
|
||||
|
||||
self.retranslateUi(Form)
|
||||
QtCore.QMetaObject.connectSlotsByName(Form)
|
||||
|
||||
def retranslateUi(self, Form):
|
||||
_translate = QtCore.QCoreApplication.translate
|
||||
Form.setWindowTitle(_translate("Form", "设置"))
|
||||
__sortingEnabled = self.listWidget.isSortingEnabled()
|
||||
self.listWidget.setSortingEnabled(False)
|
||||
item = self.listWidget.item(0)
|
||||
item.setText(_translate("Form", "常规"))
|
||||
item = self.listWidget.item(1)
|
||||
item.setText(_translate("Form", "环境"))
|
||||
self.listWidget.setSortingEnabled(__sortingEnabled)
|
||||
self.label.setText(_translate("Form", "下 载 源:"))
|
||||
self.comboBox_source.setItemText(0, _translate("Form", "腾讯(推荐)"))
|
||||
self.comboBox_source.setItemText(1, _translate("Form", "官方"))
|
||||
self.comboBox_source.setItemText(2, _translate("Form", "清华大学"))
|
||||
self.comboBox_source.setItemText(3, _translate("Form", "阿里"))
|
||||
self.comboBox_source.setItemText(4, _translate("Form", "豆瓣"))
|
||||
self.comboBox_source.setItemText(5, _translate("Form", "自定义"))
|
||||
self.lineEdit_source.setText(_translate("Form", "https://mirrors.cloud.tencent.com/pypi/simple"))
|
||||
self.lineEdit_source.setPlaceholderText(_translate("Form", "腾讯镜像源"))
|
||||
self.label_3.setText(_translate("Form", "安装选项:"))
|
||||
self.comboBox_dir.setItemText(0, _translate("Form", "默认位置"))
|
||||
self.comboBox_dir.setItemText(1, _translate("Form", "用户目录"))
|
||||
self.comboBox_dir.setItemText(2, _translate("Form", "仅下载"))
|
||||
self.comboBox_dir.setItemText(3, _translate("Form", "自定义"))
|
||||
self.lineEdit_dir.setPlaceholderText(_translate("Form", "默认"))
|
||||
self.toolButton.setText(_translate("Form", "..."))
|
||||
self.label_4.setText(_translate("Form", "默认路径:"))
|
||||
self.comboBox_dir_2.setItemText(0, _translate("Form", "默认位置"))
|
||||
self.comboBox_dir_2.setItemText(1, _translate("Form", "用户目录"))
|
||||
self.comboBox_dir_2.setItemText(2, _translate("Form", "仅下载"))
|
||||
self.comboBox_dir_2.setItemText(3, _translate("Form", "自定义"))
|
||||
self.lineEdit_dir_2.setPlaceholderText(_translate("Form", "默认"))
|
||||
self.toolButton_2.setText(_translate("Form", "..."))
|
||||
self.pushButton.setText(_translate("Form", "帮助"))
|
||||
self.pushButton_2.setText(_translate("Form", "确定"))
|
||||
self.pushButton_3.setText(_translate("Form", "取消"))
|
||||
445
pyminer/features/extensions/package_manager/package_setting.ui
Normal file
445
pyminer/features/extensions/package_manager/package_setting.ui
Normal file
@ -0,0 +1,445 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<ui version="4.0">
|
||||
<class>Form</class>
|
||||
<widget class="QWidget" name="Form">
|
||||
<property name="geometry">
|
||||
<rect>
|
||||
<x>0</x>
|
||||
<y>0</y>
|
||||
<width>600</width>
|
||||
<height>400</height>
|
||||
</rect>
|
||||
</property>
|
||||
<property name="windowTitle">
|
||||
<string>设置</string>
|
||||
</property>
|
||||
<layout class="QVBoxLayout" name="verticalLayout">
|
||||
<item>
|
||||
<widget class="QSplitter" name="splitter">
|
||||
<property name="orientation">
|
||||
<enum>Qt::Horizontal</enum>
|
||||
</property>
|
||||
<widget class="QWidget" name="widget_2" native="true">
|
||||
<property name="maximumSize">
|
||||
<size>
|
||||
<width>120</width>
|
||||
<height>16777215</height>
|
||||
</size>
|
||||
</property>
|
||||
<layout class="QVBoxLayout" name="verticalLayout_2">
|
||||
<property name="leftMargin">
|
||||
<number>0</number>
|
||||
</property>
|
||||
<property name="topMargin">
|
||||
<number>0</number>
|
||||
</property>
|
||||
<property name="rightMargin">
|
||||
<number>0</number>
|
||||
</property>
|
||||
<property name="bottomMargin">
|
||||
<number>0</number>
|
||||
</property>
|
||||
<item>
|
||||
<widget class="QListWidget" name="listWidget">
|
||||
<property name="sizePolicy">
|
||||
<sizepolicy hsizetype="Preferred" vsizetype="Preferred">
|
||||
<horstretch>0</horstretch>
|
||||
<verstretch>0</verstretch>
|
||||
</sizepolicy>
|
||||
</property>
|
||||
<item>
|
||||
<property name="text">
|
||||
<string>常规</string>
|
||||
</property>
|
||||
</item>
|
||||
<item>
|
||||
<property name="text">
|
||||
<string>解释器</string>
|
||||
</property>
|
||||
</item>
|
||||
</widget>
|
||||
</item>
|
||||
</layout>
|
||||
</widget>
|
||||
<widget class="QStackedWidget" name="stackedWidget">
|
||||
<property name="currentIndex">
|
||||
<number>0</number>
|
||||
</property>
|
||||
<widget class="QWidget" name="page">
|
||||
<layout class="QVBoxLayout" name="verticalLayout_3">
|
||||
<property name="leftMargin">
|
||||
<number>0</number>
|
||||
</property>
|
||||
<property name="topMargin">
|
||||
<number>0</number>
|
||||
</property>
|
||||
<property name="rightMargin">
|
||||
<number>0</number>
|
||||
</property>
|
||||
<property name="bottomMargin">
|
||||
<number>0</number>
|
||||
</property>
|
||||
<item>
|
||||
<layout class="QHBoxLayout" name="horizontalLayout_2">
|
||||
<item>
|
||||
<widget class="QLabel" name="label">
|
||||
<property name="text">
|
||||
<string>下 载 源:</string>
|
||||
</property>
|
||||
</widget>
|
||||
</item>
|
||||
<item>
|
||||
<widget class="QComboBox" name="comboBox_source">
|
||||
<property name="enabled">
|
||||
<bool>true</bool>
|
||||
</property>
|
||||
<property name="minimumSize">
|
||||
<size>
|
||||
<width>100</width>
|
||||
<height>0</height>
|
||||
</size>
|
||||
</property>
|
||||
<property name="maximumSize">
|
||||
<size>
|
||||
<width>100</width>
|
||||
<height>16777215</height>
|
||||
</size>
|
||||
</property>
|
||||
<item>
|
||||
<property name="text">
|
||||
<string>腾讯(推荐)</string>
|
||||
</property>
|
||||
</item>
|
||||
<item>
|
||||
<property name="text">
|
||||
<string>官方</string>
|
||||
</property>
|
||||
</item>
|
||||
<item>
|
||||
<property name="text">
|
||||
<string>清华大学</string>
|
||||
</property>
|
||||
</item>
|
||||
<item>
|
||||
<property name="text">
|
||||
<string>阿里</string>
|
||||
</property>
|
||||
</item>
|
||||
<item>
|
||||
<property name="text">
|
||||
<string>豆瓣</string>
|
||||
</property>
|
||||
</item>
|
||||
<item>
|
||||
<property name="text">
|
||||
<string>自定义</string>
|
||||
</property>
|
||||
</item>
|
||||
</widget>
|
||||
</item>
|
||||
<item>
|
||||
<widget class="QLineEdit" name="lineEdit_source">
|
||||
<property name="text">
|
||||
<string>https://mirrors.cloud.tencent.com/pypi/simple</string>
|
||||
</property>
|
||||
<property name="alignment">
|
||||
<set>Qt::AlignLeading|Qt::AlignLeft|Qt::AlignVCenter</set>
|
||||
</property>
|
||||
<property name="readOnly">
|
||||
<bool>true</bool>
|
||||
</property>
|
||||
<property name="placeholderText">
|
||||
<string>腾讯镜像源</string>
|
||||
</property>
|
||||
</widget>
|
||||
</item>
|
||||
</layout>
|
||||
</item>
|
||||
<item>
|
||||
<layout class="QHBoxLayout" name="horizontalLayout_3">
|
||||
<item>
|
||||
<widget class="QLabel" name="label_3">
|
||||
<property name="text">
|
||||
<string>安装选项:</string>
|
||||
</property>
|
||||
</widget>
|
||||
</item>
|
||||
<item>
|
||||
<widget class="QComboBox" name="comboBox_dir">
|
||||
<property name="minimumSize">
|
||||
<size>
|
||||
<width>100</width>
|
||||
<height>0</height>
|
||||
</size>
|
||||
</property>
|
||||
<property name="maximumSize">
|
||||
<size>
|
||||
<width>100</width>
|
||||
<height>16777215</height>
|
||||
</size>
|
||||
</property>
|
||||
<item>
|
||||
<property name="text">
|
||||
<string>默认位置</string>
|
||||
</property>
|
||||
</item>
|
||||
<item>
|
||||
<property name="text">
|
||||
<string>用户目录</string>
|
||||
</property>
|
||||
</item>
|
||||
<item>
|
||||
<property name="text">
|
||||
<string>仅下载</string>
|
||||
</property>
|
||||
</item>
|
||||
<item>
|
||||
<property name="text">
|
||||
<string>自定义</string>
|
||||
</property>
|
||||
</item>
|
||||
</widget>
|
||||
</item>
|
||||
<item>
|
||||
<widget class="QLineEdit" name="lineEdit_dir">
|
||||
<property name="readOnly">
|
||||
<bool>true</bool>
|
||||
</property>
|
||||
<property name="placeholderText">
|
||||
<string>默认</string>
|
||||
</property>
|
||||
</widget>
|
||||
</item>
|
||||
<item>
|
||||
<widget class="QToolButton" name="toolButton">
|
||||
<property name="text">
|
||||
<string>...</string>
|
||||
</property>
|
||||
</widget>
|
||||
</item>
|
||||
</layout>
|
||||
</item>
|
||||
<item>
|
||||
<layout class="QHBoxLayout" name="horizontalLayout_4">
|
||||
<item>
|
||||
<widget class="QLabel" name="label_4">
|
||||
<property name="text">
|
||||
<string>默认路径:</string>
|
||||
</property>
|
||||
</widget>
|
||||
</item>
|
||||
<item>
|
||||
<widget class="QComboBox" name="comboBox_dir_2">
|
||||
<property name="minimumSize">
|
||||
<size>
|
||||
<width>100</width>
|
||||
<height>0</height>
|
||||
</size>
|
||||
</property>
|
||||
<property name="maximumSize">
|
||||
<size>
|
||||
<width>100</width>
|
||||
<height>16777215</height>
|
||||
</size>
|
||||
</property>
|
||||
<item>
|
||||
<property name="text">
|
||||
<string>默认位置</string>
|
||||
</property>
|
||||
</item>
|
||||
<item>
|
||||
<property name="text">
|
||||
<string>用户目录</string>
|
||||
</property>
|
||||
</item>
|
||||
<item>
|
||||
<property name="text">
|
||||
<string>仅下载</string>
|
||||
</property>
|
||||
</item>
|
||||
<item>
|
||||
<property name="text">
|
||||
<string>自定义</string>
|
||||
</property>
|
||||
</item>
|
||||
</widget>
|
||||
</item>
|
||||
<item>
|
||||
<widget class="QLineEdit" name="lineEdit_dir_2">
|
||||
<property name="readOnly">
|
||||
<bool>true</bool>
|
||||
</property>
|
||||
<property name="placeholderText">
|
||||
<string>默认</string>
|
||||
</property>
|
||||
</widget>
|
||||
</item>
|
||||
<item>
|
||||
<widget class="QToolButton" name="toolButton_2">
|
||||
<property name="text">
|
||||
<string>...</string>
|
||||
</property>
|
||||
</widget>
|
||||
</item>
|
||||
</layout>
|
||||
</item>
|
||||
<item>
|
||||
<spacer name="verticalSpacer">
|
||||
<property name="orientation">
|
||||
<enum>Qt::Vertical</enum>
|
||||
</property>
|
||||
<property name="sizeHint" stdset="0">
|
||||
<size>
|
||||
<width>20</width>
|
||||
<height>40</height>
|
||||
</size>
|
||||
</property>
|
||||
</spacer>
|
||||
</item>
|
||||
</layout>
|
||||
</widget>
|
||||
<widget class="QWidget" name="page_2">
|
||||
<layout class="QHBoxLayout" name="horizontalLayout_5">
|
||||
<property name="leftMargin">
|
||||
<number>0</number>
|
||||
</property>
|
||||
<property name="topMargin">
|
||||
<number>0</number>
|
||||
</property>
|
||||
<property name="rightMargin">
|
||||
<number>0</number>
|
||||
</property>
|
||||
<property name="bottomMargin">
|
||||
<number>0</number>
|
||||
</property>
|
||||
<item>
|
||||
<widget class="QTableWidget" name="tableWidget">
|
||||
<column>
|
||||
<property name="text">
|
||||
<string>名称</string>
|
||||
</property>
|
||||
</column>
|
||||
<column>
|
||||
<property name="text">
|
||||
<string>路径</string>
|
||||
</property>
|
||||
</column>
|
||||
<column>
|
||||
<property name="text">
|
||||
<string>是否默认</string>
|
||||
</property>
|
||||
</column>
|
||||
</widget>
|
||||
</item>
|
||||
<item>
|
||||
<layout class="QVBoxLayout" name="verticalLayout_4">
|
||||
<item>
|
||||
<widget class="QPushButton" name="pushButton_browser">
|
||||
<property name="text">
|
||||
<string>浏览</string>
|
||||
</property>
|
||||
</widget>
|
||||
</item>
|
||||
<item>
|
||||
<widget class="QPushButton" name="pushButton_default">
|
||||
<property name="text">
|
||||
<string>设为默认</string>
|
||||
</property>
|
||||
</widget>
|
||||
</item>
|
||||
<item>
|
||||
<widget class="QPushButton" name="pushButton_delete">
|
||||
<property name="text">
|
||||
<string>删除</string>
|
||||
</property>
|
||||
</widget>
|
||||
</item>
|
||||
<item>
|
||||
<spacer name="verticalSpacer_2">
|
||||
<property name="orientation">
|
||||
<enum>Qt::Vertical</enum>
|
||||
</property>
|
||||
<property name="sizeHint" stdset="0">
|
||||
<size>
|
||||
<width>20</width>
|
||||
<height>40</height>
|
||||
</size>
|
||||
</property>
|
||||
</spacer>
|
||||
</item>
|
||||
</layout>
|
||||
</item>
|
||||
</layout>
|
||||
</widget>
|
||||
</widget>
|
||||
</widget>
|
||||
</item>
|
||||
<item>
|
||||
<widget class="QWidget" name="widget" native="true">
|
||||
<property name="minimumSize">
|
||||
<size>
|
||||
<width>0</width>
|
||||
<height>50</height>
|
||||
</size>
|
||||
</property>
|
||||
<property name="maximumSize">
|
||||
<size>
|
||||
<width>16777215</width>
|
||||
<height>50</height>
|
||||
</size>
|
||||
</property>
|
||||
<layout class="QHBoxLayout" name="horizontalLayout">
|
||||
<property name="leftMargin">
|
||||
<number>0</number>
|
||||
</property>
|
||||
<property name="topMargin">
|
||||
<number>0</number>
|
||||
</property>
|
||||
<property name="rightMargin">
|
||||
<number>0</number>
|
||||
</property>
|
||||
<property name="bottomMargin">
|
||||
<number>0</number>
|
||||
</property>
|
||||
<item>
|
||||
<widget class="QPushButton" name="pushButton_help">
|
||||
<property name="text">
|
||||
<string>帮助</string>
|
||||
</property>
|
||||
</widget>
|
||||
</item>
|
||||
<item>
|
||||
<spacer name="horizontalSpacer">
|
||||
<property name="orientation">
|
||||
<enum>Qt::Horizontal</enum>
|
||||
</property>
|
||||
<property name="sizeHint" stdset="0">
|
||||
<size>
|
||||
<width>40</width>
|
||||
<height>20</height>
|
||||
</size>
|
||||
</property>
|
||||
</spacer>
|
||||
</item>
|
||||
<item>
|
||||
<widget class="QPushButton" name="pushButton_ok">
|
||||
<property name="text">
|
||||
<string>确定</string>
|
||||
</property>
|
||||
</widget>
|
||||
</item>
|
||||
<item>
|
||||
<widget class="QPushButton" name="pushButton_cancel">
|
||||
<property name="text">
|
||||
<string>取消</string>
|
||||
</property>
|
||||
</widget>
|
||||
</item>
|
||||
</layout>
|
||||
</widget>
|
||||
</item>
|
||||
</layout>
|
||||
</widget>
|
||||
<resources/>
|
||||
<connections/>
|
||||
</ui>
|
||||
151
pyminer/features/extensions/package_manager/package_update.py
Normal file
151
pyminer/features/extensions/package_manager/package_update.py
Normal file
@ -0,0 +1,151 @@
|
||||
# -*- coding: utf-8 -*-
|
||||
|
||||
# Form implementation generated from reading ui file 'package_update.ui'
|
||||
#
|
||||
# Created by: PyQt5 UI code generator 5.14.1
|
||||
#
|
||||
# WARNING! All changes made in this file will be lost!
|
||||
|
||||
|
||||
from PyQt5 import QtCore, QtGui, QtWidgets
|
||||
|
||||
|
||||
class Ui_Form(object):
|
||||
def setupUi(self, Form):
|
||||
Form.setObjectName("Form")
|
||||
Form.resize(800, 600)
|
||||
self.verticalLayout = QtWidgets.QVBoxLayout(Form)
|
||||
self.verticalLayout.setObjectName("verticalLayout")
|
||||
self.horizontalLayout_4 = QtWidgets.QHBoxLayout()
|
||||
self.horizontalLayout_4.setObjectName("horizontalLayout_4")
|
||||
self.formLayout = QtWidgets.QFormLayout()
|
||||
self.formLayout.setObjectName("formLayout")
|
||||
self.label_2 = QtWidgets.QLabel(Form)
|
||||
self.label_2.setObjectName("label_2")
|
||||
self.formLayout.setWidget(0, QtWidgets.QFormLayout.LabelRole, self.label_2)
|
||||
self.lineEdit_name = QtWidgets.QLineEdit(Form)
|
||||
self.lineEdit_name.setText("")
|
||||
self.lineEdit_name.setObjectName("lineEdit_name")
|
||||
self.formLayout.setWidget(0, QtWidgets.QFormLayout.FieldRole, self.lineEdit_name)
|
||||
self.checkBox_version = QtWidgets.QCheckBox(Form)
|
||||
self.checkBox_version.setObjectName("checkBox_version")
|
||||
self.formLayout.setWidget(1, QtWidgets.QFormLayout.LabelRole, self.checkBox_version)
|
||||
self.comboBox_version = QtWidgets.QComboBox(Form)
|
||||
self.comboBox_version.setEnabled(False)
|
||||
self.comboBox_version.setMinimumSize(QtCore.QSize(0, 0))
|
||||
self.comboBox_version.setMaximumSize(QtCore.QSize(16777215, 16777215))
|
||||
self.comboBox_version.setObjectName("comboBox_version")
|
||||
self.comboBox_version.addItem("")
|
||||
self.formLayout.setWidget(1, QtWidgets.QFormLayout.FieldRole, self.comboBox_version)
|
||||
self.label = QtWidgets.QLabel(Form)
|
||||
self.label.setObjectName("label")
|
||||
self.formLayout.setWidget(2, QtWidgets.QFormLayout.LabelRole, self.label)
|
||||
self.horizontalLayout_3 = QtWidgets.QHBoxLayout()
|
||||
self.horizontalLayout_3.setObjectName("horizontalLayout_3")
|
||||
self.comboBox_source = QtWidgets.QComboBox(Form)
|
||||
self.comboBox_source.setEnabled(True)
|
||||
self.comboBox_source.setMinimumSize(QtCore.QSize(100, 0))
|
||||
self.comboBox_source.setMaximumSize(QtCore.QSize(100, 16777215))
|
||||
self.comboBox_source.setObjectName("comboBox_source")
|
||||
self.comboBox_source.addItem("")
|
||||
self.comboBox_source.addItem("")
|
||||
self.comboBox_source.addItem("")
|
||||
self.comboBox_source.addItem("")
|
||||
self.comboBox_source.addItem("")
|
||||
self.comboBox_source.addItem("")
|
||||
self.horizontalLayout_3.addWidget(self.comboBox_source)
|
||||
self.lineEdit_source = QtWidgets.QLineEdit(Form)
|
||||
self.lineEdit_source.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter)
|
||||
self.lineEdit_source.setReadOnly(True)
|
||||
self.lineEdit_source.setObjectName("lineEdit_source")
|
||||
self.horizontalLayout_3.addWidget(self.lineEdit_source)
|
||||
self.formLayout.setLayout(2, QtWidgets.QFormLayout.FieldRole, self.horizontalLayout_3)
|
||||
self.label_3 = QtWidgets.QLabel(Form)
|
||||
self.label_3.setObjectName("label_3")
|
||||
self.formLayout.setWidget(3, QtWidgets.QFormLayout.LabelRole, self.label_3)
|
||||
self.horizontalLayout = QtWidgets.QHBoxLayout()
|
||||
self.horizontalLayout.setObjectName("horizontalLayout")
|
||||
self.comboBox_dir = QtWidgets.QComboBox(Form)
|
||||
self.comboBox_dir.setMinimumSize(QtCore.QSize(100, 0))
|
||||
self.comboBox_dir.setMaximumSize(QtCore.QSize(100, 16777215))
|
||||
self.comboBox_dir.setObjectName("comboBox_dir")
|
||||
self.comboBox_dir.addItem("")
|
||||
self.comboBox_dir.addItem("")
|
||||
self.comboBox_dir.addItem("")
|
||||
self.comboBox_dir.addItem("")
|
||||
self.horizontalLayout.addWidget(self.comboBox_dir)
|
||||
self.lineEdit_dir = QtWidgets.QLineEdit(Form)
|
||||
self.lineEdit_dir.setReadOnly(True)
|
||||
self.lineEdit_dir.setObjectName("lineEdit_dir")
|
||||
self.horizontalLayout.addWidget(self.lineEdit_dir)
|
||||
self.toolButton = QtWidgets.QToolButton(Form)
|
||||
self.toolButton.setObjectName("toolButton")
|
||||
self.horizontalLayout.addWidget(self.toolButton)
|
||||
self.formLayout.setLayout(3, QtWidgets.QFormLayout.FieldRole, self.horizontalLayout)
|
||||
self.horizontalLayout_4.addLayout(self.formLayout)
|
||||
self.verticalLayout.addLayout(self.horizontalLayout_4)
|
||||
self.groupBox = QtWidgets.QGroupBox(Form)
|
||||
self.groupBox.setObjectName("groupBox")
|
||||
self.horizontalLayout_5 = QtWidgets.QHBoxLayout(self.groupBox)
|
||||
self.horizontalLayout_5.setContentsMargins(0, 0, 0, 0)
|
||||
self.horizontalLayout_5.setObjectName("horizontalLayout_5")
|
||||
self.textEdit_desc = QtWidgets.QTextEdit(self.groupBox)
|
||||
self.textEdit_desc.setObjectName("textEdit_desc")
|
||||
self.horizontalLayout_5.addWidget(self.textEdit_desc)
|
||||
self.verticalLayout.addWidget(self.groupBox)
|
||||
self.groupBox_2 = QtWidgets.QGroupBox(Form)
|
||||
self.groupBox_2.setObjectName("groupBox_2")
|
||||
self.horizontalLayout_6 = QtWidgets.QHBoxLayout(self.groupBox_2)
|
||||
self.horizontalLayout_6.setContentsMargins(0, 0, 0, 0)
|
||||
self.horizontalLayout_6.setObjectName("horizontalLayout_6")
|
||||
self.textEdit_log = QtWidgets.QTextEdit(self.groupBox_2)
|
||||
self.textEdit_log.setObjectName("textEdit_log")
|
||||
self.horizontalLayout_6.addWidget(self.textEdit_log)
|
||||
self.verticalLayout.addWidget(self.groupBox_2)
|
||||
self.widget = QtWidgets.QWidget(Form)
|
||||
self.widget.setMaximumSize(QtCore.QSize(16777215, 50))
|
||||
self.widget.setObjectName("widget")
|
||||
self.verticalLayout_2 = QtWidgets.QVBoxLayout(self.widget)
|
||||
self.verticalLayout_2.setObjectName("verticalLayout_2")
|
||||
self.horizontalLayout_2 = QtWidgets.QHBoxLayout()
|
||||
self.horizontalLayout_2.setObjectName("horizontalLayout_2")
|
||||
spacerItem = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum)
|
||||
self.horizontalLayout_2.addItem(spacerItem)
|
||||
self.pushButton_ok = QtWidgets.QPushButton(self.widget)
|
||||
self.pushButton_ok.setObjectName("pushButton_ok")
|
||||
self.horizontalLayout_2.addWidget(self.pushButton_ok)
|
||||
self.pushButton_cancel = QtWidgets.QPushButton(self.widget)
|
||||
self.pushButton_cancel.setObjectName("pushButton_cancel")
|
||||
self.horizontalLayout_2.addWidget(self.pushButton_cancel)
|
||||
self.verticalLayout_2.addLayout(self.horizontalLayout_2)
|
||||
self.verticalLayout.addWidget(self.widget)
|
||||
|
||||
self.retranslateUi(Form)
|
||||
QtCore.QMetaObject.connectSlotsByName(Form)
|
||||
|
||||
def retranslateUi(self, Form):
|
||||
_translate = QtCore.QCoreApplication.translate
|
||||
Form.setWindowTitle(_translate("Form", "更新"))
|
||||
self.label_2.setText(_translate("Form", "包名:"))
|
||||
self.checkBox_version.setText(_translate("Form", "指定版本"))
|
||||
self.comboBox_version.setItemText(0, _translate("Form", "最新版本"))
|
||||
self.label.setText(_translate("Form", "下载源:"))
|
||||
self.comboBox_source.setItemText(0, _translate("Form", "腾讯(推荐)"))
|
||||
self.comboBox_source.setItemText(1, _translate("Form", "官方"))
|
||||
self.comboBox_source.setItemText(2, _translate("Form", "清华大学"))
|
||||
self.comboBox_source.setItemText(3, _translate("Form", "阿里"))
|
||||
self.comboBox_source.setItemText(4, _translate("Form", "豆瓣"))
|
||||
self.comboBox_source.setItemText(5, _translate("Form", "自定义"))
|
||||
self.lineEdit_source.setText(_translate("Form", "https://mirrors.cloud.tencent.com/pypi/simple"))
|
||||
self.lineEdit_source.setPlaceholderText(_translate("Form", "腾讯镜像源"))
|
||||
self.label_3.setText(_translate("Form", "安装选项:"))
|
||||
self.comboBox_dir.setItemText(0, _translate("Form", "默认位置"))
|
||||
self.comboBox_dir.setItemText(1, _translate("Form", "用户目录"))
|
||||
self.comboBox_dir.setItemText(2, _translate("Form", "仅下载"))
|
||||
self.comboBox_dir.setItemText(3, _translate("Form", "自定义"))
|
||||
self.lineEdit_dir.setPlaceholderText(_translate("Form", "默认"))
|
||||
self.toolButton.setText(_translate("Form", "..."))
|
||||
self.groupBox.setTitle(_translate("Form", "详情"))
|
||||
self.groupBox_2.setTitle(_translate("Form", "执行记录"))
|
||||
self.pushButton_ok.setText(_translate("Form", "确定"))
|
||||
self.pushButton_cancel.setText(_translate("Form", "取消"))
|
||||
305
pyminer/features/extensions/package_manager/package_update.ui
Normal file
305
pyminer/features/extensions/package_manager/package_update.ui
Normal file
@ -0,0 +1,305 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<ui version="4.0">
|
||||
<class>Form</class>
|
||||
<widget class="QWidget" name="Form">
|
||||
<property name="geometry">
|
||||
<rect>
|
||||
<x>0</x>
|
||||
<y>0</y>
|
||||
<width>800</width>
|
||||
<height>600</height>
|
||||
</rect>
|
||||
</property>
|
||||
<property name="windowTitle">
|
||||
<string>更新</string>
|
||||
</property>
|
||||
<layout class="QVBoxLayout" name="verticalLayout">
|
||||
<item>
|
||||
<layout class="QHBoxLayout" name="horizontalLayout_4">
|
||||
<item>
|
||||
<layout class="QFormLayout" name="formLayout">
|
||||
<item row="0" column="0">
|
||||
<widget class="QLabel" name="label_2">
|
||||
<property name="text">
|
||||
<string>包名:</string>
|
||||
</property>
|
||||
</widget>
|
||||
</item>
|
||||
<item row="0" column="1">
|
||||
<widget class="QLineEdit" name="lineEdit_name">
|
||||
<property name="text">
|
||||
<string/>
|
||||
</property>
|
||||
</widget>
|
||||
</item>
|
||||
<item row="1" column="0">
|
||||
<widget class="QCheckBox" name="checkBox_version">
|
||||
<property name="text">
|
||||
<string>指定版本</string>
|
||||
</property>
|
||||
</widget>
|
||||
</item>
|
||||
<item row="1" column="1">
|
||||
<widget class="QComboBox" name="comboBox_version">
|
||||
<property name="enabled">
|
||||
<bool>false</bool>
|
||||
</property>
|
||||
<property name="minimumSize">
|
||||
<size>
|
||||
<width>0</width>
|
||||
<height>0</height>
|
||||
</size>
|
||||
</property>
|
||||
<property name="maximumSize">
|
||||
<size>
|
||||
<width>16777215</width>
|
||||
<height>16777215</height>
|
||||
</size>
|
||||
</property>
|
||||
<item>
|
||||
<property name="text">
|
||||
<string>最新版本</string>
|
||||
</property>
|
||||
</item>
|
||||
</widget>
|
||||
</item>
|
||||
<item row="2" column="0">
|
||||
<widget class="QLabel" name="label">
|
||||
<property name="text">
|
||||
<string>下载源:</string>
|
||||
</property>
|
||||
</widget>
|
||||
</item>
|
||||
<item row="2" column="1">
|
||||
<layout class="QHBoxLayout" name="horizontalLayout_3">
|
||||
<item>
|
||||
<widget class="QComboBox" name="comboBox_source">
|
||||
<property name="enabled">
|
||||
<bool>true</bool>
|
||||
</property>
|
||||
<property name="minimumSize">
|
||||
<size>
|
||||
<width>100</width>
|
||||
<height>0</height>
|
||||
</size>
|
||||
</property>
|
||||
<property name="maximumSize">
|
||||
<size>
|
||||
<width>100</width>
|
||||
<height>16777215</height>
|
||||
</size>
|
||||
</property>
|
||||
<item>
|
||||
<property name="text">
|
||||
<string>腾讯(推荐)</string>
|
||||
</property>
|
||||
</item>
|
||||
<item>
|
||||
<property name="text">
|
||||
<string>官方</string>
|
||||
</property>
|
||||
</item>
|
||||
<item>
|
||||
<property name="text">
|
||||
<string>清华大学</string>
|
||||
</property>
|
||||
</item>
|
||||
<item>
|
||||
<property name="text">
|
||||
<string>阿里</string>
|
||||
</property>
|
||||
</item>
|
||||
<item>
|
||||
<property name="text">
|
||||
<string>豆瓣</string>
|
||||
</property>
|
||||
</item>
|
||||
<item>
|
||||
<property name="text">
|
||||
<string>自定义</string>
|
||||
</property>
|
||||
</item>
|
||||
</widget>
|
||||
</item>
|
||||
<item>
|
||||
<widget class="QLineEdit" name="lineEdit_source">
|
||||
<property name="text">
|
||||
<string>https://mirrors.cloud.tencent.com/pypi/simple</string>
|
||||
</property>
|
||||
<property name="alignment">
|
||||
<set>Qt::AlignLeading|Qt::AlignLeft|Qt::AlignVCenter</set>
|
||||
</property>
|
||||
<property name="readOnly">
|
||||
<bool>true</bool>
|
||||
</property>
|
||||
<property name="placeholderText">
|
||||
<string>腾讯镜像源</string>
|
||||
</property>
|
||||
</widget>
|
||||
</item>
|
||||
</layout>
|
||||
</item>
|
||||
<item row="3" column="0">
|
||||
<widget class="QLabel" name="label_3">
|
||||
<property name="text">
|
||||
<string>安装选项:</string>
|
||||
</property>
|
||||
</widget>
|
||||
</item>
|
||||
<item row="3" column="1">
|
||||
<layout class="QHBoxLayout" name="horizontalLayout">
|
||||
<item>
|
||||
<widget class="QComboBox" name="comboBox_dir">
|
||||
<property name="minimumSize">
|
||||
<size>
|
||||
<width>100</width>
|
||||
<height>0</height>
|
||||
</size>
|
||||
</property>
|
||||
<property name="maximumSize">
|
||||
<size>
|
||||
<width>100</width>
|
||||
<height>16777215</height>
|
||||
</size>
|
||||
</property>
|
||||
<item>
|
||||
<property name="text">
|
||||
<string>默认位置</string>
|
||||
</property>
|
||||
</item>
|
||||
<item>
|
||||
<property name="text">
|
||||
<string>用户目录</string>
|
||||
</property>
|
||||
</item>
|
||||
<item>
|
||||
<property name="text">
|
||||
<string>仅下载</string>
|
||||
</property>
|
||||
</item>
|
||||
<item>
|
||||
<property name="text">
|
||||
<string>自定义</string>
|
||||
</property>
|
||||
</item>
|
||||
</widget>
|
||||
</item>
|
||||
<item>
|
||||
<widget class="QLineEdit" name="lineEdit_dir">
|
||||
<property name="readOnly">
|
||||
<bool>true</bool>
|
||||
</property>
|
||||
<property name="placeholderText">
|
||||
<string>默认</string>
|
||||
</property>
|
||||
</widget>
|
||||
</item>
|
||||
<item>
|
||||
<widget class="QToolButton" name="toolButton">
|
||||
<property name="text">
|
||||
<string>...</string>
|
||||
</property>
|
||||
</widget>
|
||||
</item>
|
||||
</layout>
|
||||
</item>
|
||||
</layout>
|
||||
</item>
|
||||
</layout>
|
||||
</item>
|
||||
<item>
|
||||
<widget class="QGroupBox" name="groupBox">
|
||||
<property name="title">
|
||||
<string>详情</string>
|
||||
</property>
|
||||
<layout class="QHBoxLayout" name="horizontalLayout_5">
|
||||
<property name="leftMargin">
|
||||
<number>0</number>
|
||||
</property>
|
||||
<property name="topMargin">
|
||||
<number>0</number>
|
||||
</property>
|
||||
<property name="rightMargin">
|
||||
<number>0</number>
|
||||
</property>
|
||||
<property name="bottomMargin">
|
||||
<number>0</number>
|
||||
</property>
|
||||
<item>
|
||||
<widget class="QTextEdit" name="textEdit_desc"/>
|
||||
</item>
|
||||
</layout>
|
||||
</widget>
|
||||
</item>
|
||||
<item>
|
||||
<widget class="QGroupBox" name="groupBox_2">
|
||||
<property name="title">
|
||||
<string>执行记录</string>
|
||||
</property>
|
||||
<layout class="QHBoxLayout" name="horizontalLayout_6">
|
||||
<property name="leftMargin">
|
||||
<number>0</number>
|
||||
</property>
|
||||
<property name="topMargin">
|
||||
<number>0</number>
|
||||
</property>
|
||||
<property name="rightMargin">
|
||||
<number>0</number>
|
||||
</property>
|
||||
<property name="bottomMargin">
|
||||
<number>0</number>
|
||||
</property>
|
||||
<item>
|
||||
<widget class="QTextEdit" name="textEdit_log"/>
|
||||
</item>
|
||||
</layout>
|
||||
</widget>
|
||||
</item>
|
||||
<item>
|
||||
<widget class="QWidget" name="widget" native="true">
|
||||
<property name="maximumSize">
|
||||
<size>
|
||||
<width>16777215</width>
|
||||
<height>50</height>
|
||||
</size>
|
||||
</property>
|
||||
<layout class="QVBoxLayout" name="verticalLayout_2">
|
||||
<item>
|
||||
<layout class="QHBoxLayout" name="horizontalLayout_2">
|
||||
<item>
|
||||
<spacer name="horizontalSpacer">
|
||||
<property name="orientation">
|
||||
<enum>Qt::Horizontal</enum>
|
||||
</property>
|
||||
<property name="sizeHint" stdset="0">
|
||||
<size>
|
||||
<width>40</width>
|
||||
<height>20</height>
|
||||
</size>
|
||||
</property>
|
||||
</spacer>
|
||||
</item>
|
||||
<item>
|
||||
<widget class="QPushButton" name="pushButton_ok">
|
||||
<property name="text">
|
||||
<string>确定</string>
|
||||
</property>
|
||||
</widget>
|
||||
</item>
|
||||
<item>
|
||||
<widget class="QPushButton" name="pushButton_cancel">
|
||||
<property name="text">
|
||||
<string>取消</string>
|
||||
</property>
|
||||
</widget>
|
||||
</item>
|
||||
</layout>
|
||||
</item>
|
||||
</layout>
|
||||
</widget>
|
||||
</item>
|
||||
</layout>
|
||||
</widget>
|
||||
<resources/>
|
||||
<connections/>
|
||||
</ui>
|
||||
0
pyminer/features/flow/flowchart.py
Normal file
0
pyminer/features/flow/flowchart.py
Normal file
0
pyminer/features/flow/pyflow.py
Normal file
0
pyminer/features/flow/pyflow.py
Normal file
251
pyminer/features/flow/pyppl_flowchart.py
Normal file
251
pyminer/features/flow/pyppl_flowchart.py
Normal file
@ -0,0 +1,251 @@
|
||||
"""Flowchart generator for PyPPL."""
|
||||
from pathlib import Path
|
||||
from copy import deepcopy
|
||||
from graphviz import Digraph # pylint: disable=import-error
|
||||
from pyppl.plugin import hookimpl
|
||||
from pyppl.logger import logger
|
||||
|
||||
__version__ = "0.1.3"
|
||||
|
||||
THEMES = dict(
|
||||
default = dict(
|
||||
base = dict(
|
||||
shape = 'box',
|
||||
style = 'rounded,filled',
|
||||
fillcolor = '#ffffff',
|
||||
color = '#000000',
|
||||
fontcolor = '#000000',
|
||||
),
|
||||
start = dict(
|
||||
style = 'filled',
|
||||
color = '#259229', # green
|
||||
),
|
||||
end = dict(
|
||||
style = 'filled',
|
||||
color = '#d63125', # red
|
||||
),
|
||||
procset = dict(
|
||||
style = 'filled',
|
||||
color = '#eeeeee', # almost white
|
||||
),
|
||||
edge = dict(),
|
||||
edge_hidden = dict(style = 'dashed'),
|
||||
),
|
||||
|
||||
dark = dict(
|
||||
base = dict(
|
||||
shape = 'box',
|
||||
style = 'rounded,filled',
|
||||
fillcolor = '#555555',
|
||||
color = '#ffffff',
|
||||
fontcolor = '#ffffff',
|
||||
),
|
||||
start = dict(
|
||||
style = 'filled',
|
||||
color = '#59b95d', # green
|
||||
penwidth = 2,
|
||||
),
|
||||
end = dict(
|
||||
style = 'filled',
|
||||
color = '#ea7d75', # red
|
||||
penwidth = 2,
|
||||
),
|
||||
procset = dict(
|
||||
style = 'filled',
|
||||
color = '#eeeeee', # almost white
|
||||
),
|
||||
edge = dict(),
|
||||
edge_hidden = dict(style = 'dashed'),
|
||||
)
|
||||
)
|
||||
|
||||
ROOTGROUP = '__ROOT__'
|
||||
|
||||
class Flowchart:
|
||||
"""@API
|
||||
Draw flowchart for pipelines
|
||||
"""
|
||||
|
||||
def __init__(self, fcfile, dotfile):
|
||||
"""@API
|
||||
The flowchart constructor
|
||||
@params:
|
||||
fcfile (file): The flowchart file.
|
||||
dotfile (file): The dot file.
|
||||
"""
|
||||
self.fcfile = Path(fcfile)
|
||||
self.dotfile = Path(dotfile)
|
||||
fmt = self.fcfile.suffix
|
||||
fmt = 'svg' if not fmt else fmt[1:]
|
||||
self.graph = Digraph('PyPPL', format = fmt)
|
||||
self.theme = THEMES['default']
|
||||
self.nodes = {}
|
||||
self.starts = []
|
||||
self.ends = []
|
||||
self.links = []
|
||||
|
||||
def set_theme(self, theme, base = 'default'):
|
||||
"""@API
|
||||
Set the theme to be used
|
||||
@params:
|
||||
theme (str|dict): The theme, could be the key of Flowchart.
|
||||
- THEMES or a dict of a theme definition.
|
||||
base (str): The base theme to be based on you pass custom theme
|
||||
"""
|
||||
if isinstance(theme, dict):
|
||||
self.theme = deepcopy(THEMES[base])
|
||||
for key, val in self.theme.items():
|
||||
val.update(theme.get(key, {}))
|
||||
elif not theme:
|
||||
self.theme = THEMES[base]
|
||||
else:
|
||||
self.theme = THEMES[theme]
|
||||
|
||||
def add_node(self, node, role = None):
|
||||
"""@API
|
||||
Add a node to the chart
|
||||
@params:
|
||||
node (Proc): The process node
|
||||
role (str): Is it a starting node, an ending node or None. Default: `None`.
|
||||
"""
|
||||
if role == 'start' and node not in self.starts:
|
||||
self.starts.append(node)
|
||||
if role == 'end' and node not in self.ends:
|
||||
self.ends.append(node)
|
||||
gname = node.procset or ROOTGROUP
|
||||
if gname not in self.nodes:
|
||||
self.nodes[gname] = []
|
||||
if node not in self.nodes[gname]:
|
||||
self.nodes[gname].append(node)
|
||||
|
||||
def add_link(self, node1, node2, has_hidden = False):
|
||||
"""@API
|
||||
Add a link to the chart
|
||||
@params:
|
||||
node1 (Proc): The first process node.
|
||||
node2 (Proc): The second process node.
|
||||
has_hidden (bool): Whether there are processes hidden along the link
|
||||
"""
|
||||
if not has_hidden and (node1, node2, True) in self.links:
|
||||
self.links.remove((node1, node2, True))
|
||||
|
||||
if has_hidden and (node1, node2, False) in self.links:
|
||||
return
|
||||
|
||||
if (node1, node2, has_hidden) not in self.links:
|
||||
self.links.append((node1, node2, has_hidden))
|
||||
|
||||
def _assemble(self):
|
||||
"""
|
||||
Assemble the graph for printing and rendering
|
||||
"""
|
||||
# nodes
|
||||
for group, nodes in self.nodes.items():
|
||||
graph = self.graph if group == ROOTGROUP else Digraph("cluster_%s" % group)
|
||||
for node in nodes:
|
||||
# copy the theme
|
||||
theme = deepcopy(self.theme['base'])
|
||||
if node in self.starts:
|
||||
theme.update(self.theme['start'])
|
||||
if node in self.ends:
|
||||
theme.update(self.theme['end'])
|
||||
if node.desc != 'No description.':
|
||||
theme['tooltip'] = node.desc
|
||||
graph.node(node.shortname, **{k:str(v) for k, v in theme.items()})
|
||||
if group != ROOTGROUP:
|
||||
graph.attr(label = group, **{k:str(v) for k,v in self.theme['procset'].items()})
|
||||
self.graph.subgraph(graph)
|
||||
|
||||
# edges
|
||||
for node1, node2, has_hidden in self.links:
|
||||
self.graph.edge(
|
||||
node1.shortname,
|
||||
node2.shortname,
|
||||
**{k:str(v) for k,v in self.theme[
|
||||
'edge_hidden' if has_hidden else 'edge'].items()})
|
||||
|
||||
def generate(self):
|
||||
"""@API
|
||||
Generate the dot file and graph file.
|
||||
"""
|
||||
self._assemble()
|
||||
self.graph.save(self.dotfile)
|
||||
self.graph.render(self.fcfile.parent.joinpath(self.fcfile.stem), cleanup = True)
|
||||
|
||||
def _get_mate(proc):
|
||||
nextprocs = proc.nexts
|
||||
ret = []
|
||||
for nproc in nextprocs:
|
||||
if nproc.config.flowchart_hide:
|
||||
ret.extend([(np[0], True) for np in _get_mate(nproc)])
|
||||
else:
|
||||
ret.append((nproc, False))
|
||||
return ret
|
||||
|
||||
def flowchart(ppl, fcfile = None, dotfile = None):
|
||||
"""
|
||||
Generate graph in dot language and visualize it.
|
||||
@params:
|
||||
dotfile (file): Where to same the dot graph.
|
||||
- Default: `None` (`path.splitext(sys.argv[0])[0] + ".pyppl.dot"`)
|
||||
fcfile (file): The flowchart file.
|
||||
- Default: `None` (`path.splitext(sys.argv[0])[0] + ".pyppl.svg"`)
|
||||
- For example: run `python pipeline.py` will save it to `pipeline.pyppl.svg`
|
||||
@returns:
|
||||
(PyPPL): The pipeline object itself.
|
||||
"""
|
||||
fcfile = fcfile or Path('.').joinpath('%s.pyppl.svg' % ppl.name)
|
||||
fcfile = Path(fcfile)
|
||||
dotfile = dotfile if dotfile else Path(fcfile).with_suffix('.dot')
|
||||
dotfile = Path(dotfile)
|
||||
|
||||
fchart = Flowchart(fcfile = fcfile, dotfile = dotfile)
|
||||
fchart.set_theme(ppl.procs[0].config.flowchart_theme)
|
||||
|
||||
for start in ppl.starts:
|
||||
if start.config.flowchart_hide:
|
||||
raise ValueError('Cannot hide start process: %s' % start.name)
|
||||
fchart.add_node(start, 'start')
|
||||
for end in ppl.ends:
|
||||
if end.config.flowchart_hide:
|
||||
raise ValueError('Cannot hide end process: %s' % end.name)
|
||||
fchart.add_node(end, 'end')
|
||||
|
||||
for proc in ppl.procs:
|
||||
if proc.config.flowchart_hide:
|
||||
if len(proc.depends) > 1 and len(proc.nexts) > 1:
|
||||
raise ValueError('Cannot hide processes [%s] with multiple \
|
||||
dependenders and multiple dependendees.' % proc.name)
|
||||
continue # pragma: no cover (wired this is not reported)
|
||||
fchart.add_node(proc)
|
||||
if not proc.nexts:
|
||||
continue
|
||||
|
||||
for mproc, has_hidden in _get_mate(proc):
|
||||
fchart.add_link(proc, mproc, has_hidden)
|
||||
|
||||
fchart.generate()
|
||||
logger.fchart('Flowchart file saved to: %s', fchart.fcfile)
|
||||
logger.fchart('DOT file saved to: %s', fchart.dotfile)
|
||||
return ppl
|
||||
|
||||
@hookimpl
|
||||
def setup(config):
|
||||
"""Add default config"""
|
||||
config.config.flowchart_theme = None
|
||||
|
||||
@hookimpl
|
||||
def logger_init(logger):
|
||||
"""Add log level"""
|
||||
logger.add_level('fchart')
|
||||
|
||||
@hookimpl
|
||||
def proc_init(proc):
|
||||
"""Add config for process"""
|
||||
proc.add_config('flowchart_hide', default = False,
|
||||
converter = bool, runtime = 'ignore')
|
||||
|
||||
@hookimpl
|
||||
def pyppl_init(ppl):
|
||||
"""Initiate pipeline"""
|
||||
ppl.add_method(flowchart, require = 'start')
|
||||
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pyminer/features/modelling/__pycache__/__init__.cpython-37.pyc
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pyminer/features/modelling/__pycache__/__init__.cpython-38.pyc
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pyminer/features/modelling/__pycache__/__init__.cpython-38.pyc
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pyminer/features/modelling/__pycache__/base.cpython-38.pyc
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pyminer/features/modelling/__pycache__/base.cpython-38.pyc
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377
pyminer/features/modelling/base.py
Normal file
377
pyminer/features/modelling/base.py
Normal file
@ -0,0 +1,377 @@
|
||||
# coding=utf-8
|
||||
import os
|
||||
import sys
|
||||
import logging
|
||||
import webbrowser
|
||||
import time
|
||||
import graphviz
|
||||
import numpy as np
|
||||
import pandas as pd
|
||||
import pydotplus
|
||||
from sklearn import tree
|
||||
# from IPython.display import Image
|
||||
from sklearn.datasets import load_wine
|
||||
from sklearn.model_selection import train_test_split
|
||||
from sklearn.preprocessing import StandardScaler # 数据标准化
|
||||
|
||||
# 导入PyQt5模块
|
||||
from PyQt5.QtCore import Qt, pyqtSignal
|
||||
from PyQt5.QtGui import QCursor, QIcon, QPixmap
|
||||
from PyQt5 import QtWidgets, QtCore
|
||||
from PyQt5.QtWidgets import QWidget, QDesktopWidget, QApplication, QDialog, QMessageBox, QTableWidgetItem
|
||||
|
||||
# 导入模型相关操作模块
|
||||
from pyminer.ui.model.model_woe_result import Ui_Form as ModelWoeIVResult_Ui_Form
|
||||
from pyminer.ui.model.model_woe import Ui_Form as ModelWoe_Ui_Form
|
||||
from pyminer.ui.model.model_frame import Ui_Form as ModelFrame_Ui_Form
|
||||
from pyminer.ui.model.model_tree import Ui_Form as ModelTree_Ui_Form
|
||||
|
||||
# 定义日志输出格式
|
||||
logging.basicConfig(format="%(asctime)s %(name)s:%(levelname)s:%(message)s", datefmt="%Y-%m-%d %H:%M:%S",
|
||||
level=logging.INFO)
|
||||
|
||||
|
||||
class ModelFrameForm(QWidget):
|
||||
"""
|
||||
"新建窗口"
|
||||
"""
|
||||
|
||||
def __init__(self, parent=None):
|
||||
super().__init__(parent)
|
||||
self.__ui = ModelFrame_Ui_Form()
|
||||
self.__ui.setupUi(self)
|
||||
self.center()
|
||||
|
||||
def keyPressEvent(self, e):
|
||||
"""
|
||||
按键盘Escape退出当前窗口
|
||||
@param e:
|
||||
"""
|
||||
if e.key() == Qt.Key_Escape:
|
||||
self.close()
|
||||
|
||||
def center(self):
|
||||
screen = QDesktopWidget().screenGeometry()
|
||||
size = self.geometry()
|
||||
self.move(int((screen.width() - size.width()) / 2), int((screen.height() - size.height()) / 2))
|
||||
|
||||
|
||||
class ModelFrameForm(QWidget, ModelFrame_Ui_Form):
|
||||
"""
|
||||
打开"关于"窗口
|
||||
"""
|
||||
|
||||
def __init__(self, parent=None):
|
||||
super().__init__(parent)
|
||||
self.setupUi(self)
|
||||
self.center()
|
||||
|
||||
def keyPressEvent(self, e):
|
||||
"""
|
||||
按键盘Escape退出当前窗口
|
||||
@param e:
|
||||
"""
|
||||
if e.key() == Qt.Key_Escape:
|
||||
self.close()
|
||||
|
||||
def center(self):
|
||||
screen = QDesktopWidget().screenGeometry()
|
||||
size = self.geometry()
|
||||
self.move(int((screen.width() - size.width()) / 2), int((screen.height() - size.height()) / 2))
|
||||
|
||||
|
||||
class ModelTreeForm(QDialog, ModelTree_Ui_Form):
|
||||
"""
|
||||
打开"模型-决策树"窗口
|
||||
"""
|
||||
signal_output = pyqtSignal(str, str) # 自定义信号，用于传递输出结果的名称、路径
|
||||
|
||||
def __init__(self, parent=None):
|
||||
super().__init__(parent)
|
||||
self.setupUi(self)
|
||||
self.center()
|
||||
self.current_dataset = pd.DataFrame()
|
||||
self.current_dataset_columns = []
|
||||
self.tree_count = 0
|
||||
|
||||
self.lineEdit_result_path.setText(output_dir)
|
||||
self.pushButton_dependent_add.clicked.connect(self.dependent_add)
|
||||
self.pushButton_dependent_del.clicked.connect(self.dependent_del)
|
||||
|
||||
self.pushButton_independent_add.clicked.connect(self.independent_add)
|
||||
self.pushButton_independent_up.clicked.connect(self.independent_up)
|
||||
self.pushButton_independent_down.clicked.connect(self.independent_down)
|
||||
self.pushButton_independent_del.clicked.connect(self.independent_del)
|
||||
|
||||
self.pushButton_ok.clicked.connect(self.model_tree)
|
||||
self.pushButton_cancel.clicked.connect(self.close)
|
||||
self.pushButton_help.clicked.connect(self.get_help)
|
||||
|
||||
def keyPressEvent(self, e):
|
||||
"""
|
||||
按键盘Escape退出当前窗口
|
||||
@param e:
|
||||
"""
|
||||
if e.key() == Qt.Key_Escape:
|
||||
self.close()
|
||||
|
||||
def center(self):
|
||||
screen = QDesktopWidget().screenGeometry()
|
||||
size = self.geometry()
|
||||
self.move(int((screen.width() - size.width()) / 2), int((screen.height() - size.height()) / 2))
|
||||
|
||||
# ================================自定义槽函数=========================
|
||||
def get_help(self):
|
||||
"""
|
||||
打开帮助页面
|
||||
"""
|
||||
try:
|
||||
webbrowser.get('chrome').open_new_tab("http://www.py2cn.com")
|
||||
except Exception as e:
|
||||
webbrowser.open_new_tab("http://www.py2cn.com")
|
||||
|
||||
def model_tree(self):
|
||||
self.tree_count += 1 # 用户生成决策树名称，根据第几次调用决策树进行命名
|
||||
result_name = "tree_" + str(self.tree_count)
|
||||
result_png = result_name + '.png'
|
||||
result_png_path = output_dir + '\\' + result_png
|
||||
print('result_name', result_name)
|
||||
print('result_png_path', result_png_path)
|
||||
|
||||
if len(self.lineEdit_result_path.text().strip()) == 0:
|
||||
QMessageBox.information(self, "注意", "决策树路径不能为空", QMessageBox.Yes | QMessageBox.No, QMessageBox.Yes)
|
||||
return
|
||||
|
||||
result_path = self.lineEdit_result_path.text() + r'/' + result_name + '.html'
|
||||
print(result_path)
|
||||
|
||||
# 可视化决策树
|
||||
data = self.current_dataset
|
||||
# 获取已选变量
|
||||
var_list = []
|
||||
count = self.listWidget_independent.count()
|
||||
for i in range(count):
|
||||
var_list.append(self.listWidget_independent.item(i).text())
|
||||
|
||||
data_x = data[var_list]
|
||||
print(data_x)
|
||||
data_y = data[self.listWidget_dependent.item(0).text()]
|
||||
|
||||
# 获取用户设置的参数
|
||||
train_size = self.doubleSpinBox_train_size.value()
|
||||
random_state = self.lineEdit_random_state.value()
|
||||
min_samples_leaf = self.spinBox_min_samples_leaf.value()
|
||||
max_depth = self.spinBox_max_depth.value()
|
||||
criterion = self.comboBox_criterion.currentText().lower()
|
||||
min_samples_split = self.spinBox_min_samples_split.value()
|
||||
train_X, test_X, train_y, test_y = train_test_split(data_x
|
||||
, data_y
|
||||
, train_size=train_size
|
||||
, random_state=random_state)
|
||||
|
||||
model_tree = tree.DecisionTreeClassifier(criterion=criterion # gini或者entropy,前者是基尼系数，后者是信息熵。
|
||||
, splitter="best"
|
||||
# best or random 前者是在所有特征中找最好的切分点 后者是在部分特征中，默认的”best”适合样本量不大的时候，而如果样本数据量非常大，此时决策树构建推荐”random” 。
|
||||
, max_features=None # None（所有），log2，sqrt，N 特征小于50的时候一般使用所有的
|
||||
, min_samples_leaf=min_samples_leaf # 最小叶子节点数
|
||||
, max_depth=max_depth
|
||||
# int or None, optional (default=None) 设置决策随机森林中的决策树的最大深度，深度越大，越容易过拟合，推荐树的深度为：5-20之间。
|
||||
, min_samples_split=min_samples_split
|
||||
# 设置结点的最小样本数量，当样本数量可能小于此值时，结点将不会在划分。
|
||||
, max_leaf_nodes=None # 通过限制最大叶子节点数，可以防止过拟合，默认是"None”，即不限制最大的叶子节点数。
|
||||
)
|
||||
model_tree = model_tree.fit(train_X, train_y)
|
||||
|
||||
score = model_tree.score(test_X, test_y) # 返回预测的准确度accuracy
|
||||
print(score)
|
||||
# feature_name = ["酒精", "苹果酸", "灰", "灰的碱性", "镁", "总酚", "类黄酮", "非黄烷类酚类", "花青素", "颜色强度", "色调", "od280/od315稀疏葡萄酒",
|
||||
# "脯氨酸"]
|
||||
print("开始执行决策树")
|
||||
dot_tree = tree.export_graphviz(model_tree
|
||||
, out_file=None
|
||||
# , feature_names=feature_name
|
||||
# , class_names=["琴酒", "雪莉", "贝尔莫得"]
|
||||
, filled=True # 填充颜色
|
||||
, rounded=True # 画出的方块无棱角
|
||||
, special_characters=True
|
||||
)
|
||||
|
||||
os.environ["PATH"] += root_dir + r'\features\plugins\graphviz-2.38\release\bin'
|
||||
graph = pydotplus.graph_from_dot_data(dot_tree)
|
||||
# img = Image(graph.create_png())
|
||||
graph.write_png(result_png_path)
|
||||
print("图片已生成！")
|
||||
|
||||
html = """
|
||||
<!DOCTYPE html>
|
||||
<html lang="en">
|
||||
<head>
|
||||
<meta charset="UTF-8">
|
||||
<meta name="viewport" content="width=device-width, initial-scale=1.0">
|
||||
<title>结果</title>
|
||||
</head>
|
||||
<body>
|
||||
<img border="0" src=" """ + result_png_path + """ " alt="决策树结果" >
|
||||
</body>
|
||||
</html>
|
||||
"""
|
||||
with open(result_path, 'w') as f:
|
||||
f.write(html)
|
||||
print("写入完成")
|
||||
f.close()
|
||||
print("开始发射信号")
|
||||
self.signal_result.emit(result_name, result_path) # 发射信号
|
||||
self.close()
|
||||
|
||||
def dependent_add(self):
|
||||
items = self.listWidget_var.selectedItems()
|
||||
for item in items:
|
||||
self.listWidget_dependent.addItem(item.text())
|
||||
|
||||
def dependent_del(self):
|
||||
items = self.listWidget_dependent.selectedItems()
|
||||
for item in items:
|
||||
row = self.listWidget_dependent.row(item)
|
||||
self.listWidget_dependent.removeItemWidget(self.listWidget_dependent.takeItem(row))
|
||||
|
||||
def independent_add(self):
|
||||
items = self.listWidget_var.selectedItems()
|
||||
for item in items:
|
||||
self.listWidget_independent.addItem(item.text())
|
||||
|
||||
def independent_up(self):
|
||||
var_list = []
|
||||
# 获取listwidget中条目数
|
||||
count = self.listWidget_independent.count()
|
||||
for i in range(count):
|
||||
var_list.append(self.listWidget_independent.item(i).text())
|
||||
row = self.listWidget_independent.currentRow()
|
||||
print("row:", row)
|
||||
temp = var_list[row]
|
||||
var_list[row] = var_list[row - 1]
|
||||
var_list[row - 1] = temp
|
||||
# 清空当前listWidget
|
||||
self.listWidget_independent.clear()
|
||||
# 重新添加新项
|
||||
self.listWidget_independent.addItems(var_list)
|
||||
|
||||
def independent_down(self):
|
||||
var_list = []
|
||||
# 获取listwidget中条目数
|
||||
count = self.listWidget_independent.count()
|
||||
for i in range(count):
|
||||
var_list.append(self.listWidget_independent.item(i).text())
|
||||
row = self.listWidget_independent.currentRow()
|
||||
print("row:", row)
|
||||
temp = var_list[row]
|
||||
var_list[row] = var_list[row + 1]
|
||||
var_list[row + 1] = temp
|
||||
# 清空当前listWidget
|
||||
self.listWidget_independent.clear()
|
||||
# 重新添加新项
|
||||
self.listWidget_independent.addItems(var_list)
|
||||
|
||||
def independent_del(self):
|
||||
items = self.listWidget_independent.selectedItems()
|
||||
for item in items:
|
||||
row = self.listWidget_independent.row(item)
|
||||
self.listWidget_independent.removeItemWidget(self.listWidget_independent.takeItem(row))
|
||||
|
||||
|
||||
class ModelWoeForm(QDialog, ModelWoe_Ui_Form):
|
||||
"""
|
||||
打开"模型-WOE/IV"窗口
|
||||
"""
|
||||
|
||||
def __init__(self, parent=None):
|
||||
super().__init__(parent)
|
||||
self.setupUi(self)
|
||||
self.center()
|
||||
|
||||
self.current_dataset = pd.DataFrame()
|
||||
self.all_dataset = ''
|
||||
self.current_dataset_name = ''
|
||||
self.current_dataset_columns = ''
|
||||
self.current_dataset_path = '' # 当前数据对应路径
|
||||
|
||||
self.pushButton_next.clicked.connect(self.calc_woe)
|
||||
self.toolButton_output_path.triggered.connect(self.slot_change_output_path)
|
||||
|
||||
def keyPressEvent(self, e):
|
||||
"""
|
||||
按键盘Escape退出当前窗口
|
||||
@param e:
|
||||
"""
|
||||
if e.key() == Qt.Key_Escape:
|
||||
self.close()
|
||||
|
||||
def center(self):
|
||||
screen = QDesktopWidget().screenGeometry()
|
||||
size = self.geometry()
|
||||
self.move(int((screen.width() - size.width()) / 2), int((screen.height() - size.height()) / 2))
|
||||
|
||||
def slot_change_output_path(self):
|
||||
directory = QtWidgets.QFileDialog.getExistingDirectory(self, "选择输出文件位置", output_dir)
|
||||
self.lineEdit_output_path.setText(directory)
|
||||
|
||||
def calc_woe(self):
|
||||
if os.path.isfile(output_dir + r"\features_detail.csv"):
|
||||
feature_detail = pd.read_csv(output_dir + r"\features_detail.csv")
|
||||
else:
|
||||
feature_detail = calc_woe_iv.woe(self.current_dataset)
|
||||
self.flush_preview(feature_detail)
|
||||
|
||||
def flush_preview(self, dataset):
|
||||
if any(dataset):
|
||||
input_table_rows = dataset.head(100).shape[0]
|
||||
input_table_colunms = dataset.shape[1]
|
||||
input_table_header = dataset.columns.values.tolist()
|
||||
self.tableWidget_dataset.setColumnCount(input_table_colunms)
|
||||
self.tableWidget_dataset.setRowCount(input_table_rows)
|
||||
self.tableWidget_dataset.setHorizontalHeaderLabels(input_table_header)
|
||||
|
||||
# 数据预览窗口
|
||||
for i in range(input_table_rows):
|
||||
input_table_rows_values = dataset.iloc[[i]]
|
||||
input_table_rows_values_array = np.array(input_table_rows_values)
|
||||
input_table_rows_values_list = input_table_rows_values_array.tolist()[0]
|
||||
for j in range(input_table_colunms):
|
||||
input_table_items_list = input_table_rows_values_list[j]
|
||||
|
||||
input_table_items = str(input_table_items_list)
|
||||
newItem = QTableWidgetItem(input_table_items)
|
||||
newItem.setTextAlignment(Qt.AlignHCenter | Qt.AlignVCenter)
|
||||
self.tableWidget_dataset.setItem(i, j, newItem)
|
||||
|
||||
|
||||
class ModelWoeResultForm(QWidget):
|
||||
"""
|
||||
打开"关于"窗口
|
||||
"""
|
||||
|
||||
def __init__(self, parent=None):
|
||||
super().__init__(parent)
|
||||
self.__ui = ModelWoeIVResult_Ui_Form()
|
||||
self.__ui.setupUi(self)
|
||||
self.center()
|
||||
|
||||
def keyPressEvent(self, e):
|
||||
"""
|
||||
按键盘Escape退出当前窗口
|
||||
@param e:
|
||||
"""
|
||||
if e.key() == Qt.Key_Escape:
|
||||
self.close()
|
||||
|
||||
def center(self):
|
||||
screen = QDesktopWidget().screenGeometry()
|
||||
size = self.geometry()
|
||||
self.move(int((screen.width() - size.width()) / 2), int((screen.height() - size.height()) / 2))
|
||||
|
||||
|
||||
# ====================================窗体测试程序============================
|
||||
if __name__ == '__main__':
|
||||
app = QApplication(sys.argv)
|
||||
form = ModelFrameForm()
|
||||
form.show()
|
||||
sys.exit(app.exec_())
|
||||
74
pyminer/features/modelling/calc_woe_iv.py
Normal file
74
pyminer/features/modelling/calc_woe_iv.py
Normal file
@ -0,0 +1,74 @@
|
||||
# -*- coding:utf-8 -*-
|
||||
__author__ = 'boredbird'
|
||||
import os
|
||||
import numpy as np
|
||||
import pandas as pd
|
||||
|
||||
import logging
|
||||
|
||||
parent_dir = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
|
||||
root_dir = os.path.dirname(parent_dir)
|
||||
output_dir = root_dir + r'\output'
|
||||
features_dir = root_dir + r'\features'
|
||||
modelling_dir = root_dir + r'\features\modelling'
|
||||
|
||||
import woe.feature_process as fp
|
||||
import woe.GridSearch as gs
|
||||
|
||||
logging.basicConfig(format="%(asctime)s %(name)s:%(levelname)s:%(message)s", datefmt="%Y-%m-%d %H:%M:%S", level=logging.INFO)
|
||||
|
||||
def config(data_path):
|
||||
data=data_path
|
||||
var_name=[]
|
||||
var_dtype=[]
|
||||
is_tobe_bin=[]
|
||||
is_candidate=[]
|
||||
is_modelfeature=[]
|
||||
for i in data.columns:
|
||||
var_name.append(i)
|
||||
#变量类型
|
||||
var_dtype.append(str(data[i].dtypes))
|
||||
#是否分箱
|
||||
if i.lower() in ['y', 'target']:
|
||||
tobe_bin = 0
|
||||
elif i.lower() in ['id', 'userid', 'user_id', 'order_no', 'order_id']:
|
||||
tobe_bin = 0
|
||||
elif str(data[i].dtypes)=="object":
|
||||
tobe_bin = 0
|
||||
else:
|
||||
tobe_bin=1
|
||||
is_tobe_bin.append(tobe_bin)
|
||||
#是否候选变量
|
||||
if i.lower() in ['y', 'target']:
|
||||
candidate = 0
|
||||
elif i.lower() in ['id', 'userid', 'user_id', 'order_no', 'order_id']:
|
||||
candidate = 0
|
||||
else:
|
||||
candidate=1
|
||||
is_candidate.append(candidate)
|
||||
#是否模型特征
|
||||
if i.lower() in ['y', 'target']:
|
||||
modelfeature = 0
|
||||
elif i.lower() in ['id', 'userid', 'user_id', 'order_no', 'order_id']:
|
||||
modelfeature = 0
|
||||
else:
|
||||
modelfeature=1
|
||||
is_modelfeature.append(modelfeature)
|
||||
|
||||
df = pd.DataFrame({"var_name": var_name, 'var_dtype': var_dtype, 'is_tobe_bin': is_tobe_bin, 'is_candidate': is_candidate,'is_modelfeature': is_modelfeature})
|
||||
logging.info("配置文件修改完成")
|
||||
print(df)
|
||||
return df
|
||||
|
||||
|
||||
def woe(data_path):
|
||||
config_path = config(data_path)
|
||||
data_path = data_path
|
||||
feature_detail_path = output_dir+'\\features_detail.csv'
|
||||
rst_pkl_path = output_dir+'\\woe_rule.pkl'
|
||||
# train Weight of Evidence rule
|
||||
feature_detail,rst = fp.process_train_woe(infile_path=data_path
|
||||
,outfile_path=feature_detail_path
|
||||
,config_path=config_path)
|
||||
return feature_detail
|
||||
logging.info("WOE和IV计算完成")
|
||||
22
pyminer/features/modelling/classification/__init__.py
Normal file
22
pyminer/features/modelling/classification/__init__.py
Normal file
@ -0,0 +1,22 @@
|
||||
# Pull members from modules to Orange.classification namespace
|
||||
# pylint: disable=wildcard-import
|
||||
|
||||
from .base_classification import (ModelClassification as Model,
|
||||
LearnerClassification as Learner,
|
||||
SklModelClassification as SklModel,
|
||||
SklLearnerClassification as SklLearner)
|
||||
from .knn import *
|
||||
from .logistic_regression import *
|
||||
from .majority import *
|
||||
from .naive_bayes import *
|
||||
from .random_forest import *
|
||||
from .softmax_regression import *
|
||||
from .svm import *
|
||||
from .tree import *
|
||||
from .simple_tree import *
|
||||
from .simple_random_forest import *
|
||||
from .elliptic_envelope import *
|
||||
from .rules import *
|
||||
from .sgd import *
|
||||
from .neural_network import *
|
||||
from .calibration import *
|
||||
191
pyminer/features/modelling/classification/tests/test_base.py
Normal file
191
pyminer/features/modelling/classification/tests/test_base.py
Normal file
@ -0,0 +1,191 @@
|
||||
import os
|
||||
from tempfile import TemporaryDirectory
|
||||
import unittest
|
||||
|
||||
import numpy as np
|
||||
|
||||
from Orange.data import Table, DiscreteVariable, Domain
|
||||
from Orange.classification import LogisticRegressionLearner, TreeLearner
|
||||
|
||||
|
||||
class TestModelMapping(unittest.TestCase):
|
||||
@classmethod
|
||||
def setUpClass(cls):
|
||||
cls.iris = iris = Table("iris")
|
||||
with TemporaryDirectory() as tempdir:
|
||||
tables = []
|
||||
x = np.vstack((iris.X[:50], iris.X[100:]))
|
||||
y = np.hstack((iris.Y[:50], iris.Y[100:]))
|
||||
for i, data in enumerate([iris[50:],
|
||||
Table.from_numpy(iris.domain, x, y),
|
||||
iris[:100]]):
|
||||
|
||||
name = os.path.join(tempdir, f"no{i}.tab")
|
||||
data.save(name)
|
||||
tables.append(Table(name))
|
||||
cls.iris0, cls.iris1, cls.iris2 = tables
|
||||
|
||||
def test_larger_model(self):
|
||||
# Train on all data, test on subset of values
|
||||
# Probabilities should stay the same, but normalized
|
||||
# Class predictions for existing classes should stay the same
|
||||
def normalized(a):
|
||||
n = np.sum(a, axis=1)
|
||||
n[n == 0] = 1.0 / a.shape[1]
|
||||
a[n == 0] = 1
|
||||
return a / n[:, None]
|
||||
|
||||
for lrn in [TreeLearner, LogisticRegressionLearner]: # skl and non-skl
|
||||
model = lrn()(self.iris)
|
||||
val, prob = model(self.iris, model.ValueProbs)
|
||||
|
||||
val0, prob0 = model(self.iris0, model.ValueProbs)
|
||||
vale = val[50:]
|
||||
probe = normalized(prob[50:, 1:])
|
||||
# No effect on class predictions
|
||||
np.testing.assert_array_equal(
|
||||
val0[vale != 0],
|
||||
vale[vale != 0] - 1)
|
||||
# Classes that to not exist are replaced with the most probable;
|
||||
# don't use argmax because of possible ties
|
||||
np.testing.assert_array_equal(
|
||||
probe[vale == 0, val0[vale == 0].astype(int)],
|
||||
np.max(probe[vale == 0], axis=1))
|
||||
# Probabilities are not affected (but normalized)
|
||||
np.testing.assert_almost_equal(prob0, probe)
|
||||
|
||||
# Same as above for other two classes ...
|
||||
val1, prob1 = model(self.iris1, model.ValueProbs)
|
||||
vale = np.hstack((val[:50], val[100:])).astype(float)
|
||||
no1 = vale != 1
|
||||
vale[vale == 2] -= 1
|
||||
probe = np.vstack((prob[:50], prob[100:]))
|
||||
probe = normalized(np.hstack((probe[:, :1], probe[:, 2:])))
|
||||
np.testing.assert_array_equal(
|
||||
val1[no1],
|
||||
vale[no1])
|
||||
np.testing.assert_array_equal(
|
||||
probe[~no1, val1[~no1].astype(int)],
|
||||
np.max(probe[~no1], axis=1))
|
||||
np.testing.assert_almost_equal(prob1, probe)
|
||||
|
||||
val2, prob2 = model(self.iris2, model.ValueProbs)
|
||||
vale = val[:100]
|
||||
probe = normalized(prob[:100, :2])
|
||||
np.testing.assert_array_equal(
|
||||
val2[vale != 2],
|
||||
vale[vale != 2])
|
||||
np.testing.assert_array_equal(
|
||||
probe[vale != 2, val2[vale != 2].astype(int)],
|
||||
np.max(probe[vale != 2], axis=1))
|
||||
np.testing.assert_almost_equal(prob2, probe)
|
||||
|
||||
def test_smaller_model(self):
|
||||
for lrn in [LogisticRegressionLearner, TreeLearner]: # skl and non-skl
|
||||
model = lrn()(self.iris0)
|
||||
val0, prob0 = model(self.iris0, model.ValueProbs)
|
||||
val, prob = model(self.iris, model.ValueProbs)
|
||||
# Model can't predict class 0 in whole data
|
||||
np.testing.assert_array_equal(val0, val[50:] - 1)
|
||||
np.testing.assert_almost_equal(prob0, prob[50:, 1:])
|
||||
# First 50 instances in whole data can be assigned anything 1 or 2
|
||||
# and should not be nan
|
||||
self.assertTrue(np.all((val[:50] == 1) + (val[:50] == 2)))
|
||||
np.testing.assert_almost_equal(np.sum(prob, axis=1), 1)
|
||||
np.testing.assert_almost_equal(prob[:, 0], 0)
|
||||
|
||||
model = lrn()(self.iris1)
|
||||
val, prob = model(self.iris, model.ValueProbs)
|
||||
val1, prob1 = model(self.iris1, model.ValueProbs)
|
||||
np.testing.assert_array_equal(val1[:50], val[:50])
|
||||
np.testing.assert_array_equal(val1[50:], val[100:] - 1)
|
||||
np.testing.assert_almost_equal(prob1[:50, 0], prob[:50, 0])
|
||||
np.testing.assert_almost_equal(prob1[:50, 1], prob[:50, 2])
|
||||
np.testing.assert_almost_equal(prob1[50:, 0], prob[100:, 0])
|
||||
np.testing.assert_almost_equal(prob1[50:, 1], prob[100:, 2])
|
||||
self.assertTrue(np.all((val[50:100] == 0) + (val[50:100] == 2)))
|
||||
np.testing.assert_almost_equal(np.sum(prob, axis=1), 1)
|
||||
np.testing.assert_almost_equal(prob[:, 1], 0)
|
||||
|
||||
model = lrn()(self.iris2)
|
||||
val, prob = model(self.iris, model.ValueProbs)
|
||||
val2, prob2 = model(self.iris2, model.ValueProbs)
|
||||
np.testing.assert_array_equal(val2, val[:100])
|
||||
np.testing.assert_almost_equal(prob2, prob[:100, :2])
|
||||
self.assertTrue(np.all((val[100:] == 0) + (val[100:] == 1)))
|
||||
self.assertTrue(np.all(val[:50] < 2)) # also tests it's not nan
|
||||
np.testing.assert_almost_equal(np.sum(prob, axis=1), 1)
|
||||
np.testing.assert_almost_equal(prob[:, 2], 0)
|
||||
|
||||
def test_model_different(self):
|
||||
def test_val_prob(val, prob):
|
||||
np.testing.assert_almost_equal(np.sum(prob, axis=1), 1)
|
||||
np.testing.assert_array_equal(
|
||||
np.choose(val.astype(int), (prob[:, 0], prob[:, 1])),
|
||||
np.max(prob, axis=1))
|
||||
|
||||
for lrn in [LogisticRegressionLearner, TreeLearner]: # skl and non-skl
|
||||
model0 = lrn()(self.iris0)
|
||||
valp0 = model0(self.iris0)
|
||||
model1 = lrn()(self.iris1)
|
||||
valp1 = model1(self.iris1)
|
||||
model2 = lrn()(self.iris2)
|
||||
valp2 = model2(self.iris2)
|
||||
|
||||
val1, prob1 = model0(self.iris1, model0.ValueProbs)
|
||||
np.testing.assert_array_equal(val1[valp0 == 1], 1)
|
||||
np.testing.assert_array_equal(prob1[valp0 == 1, 0], 0)
|
||||
np.testing.assert_array_equal(prob1[valp0 == 1, 1], 1)
|
||||
test_val_prob(val1, prob1)
|
||||
|
||||
val2, prob2 = model0(self.iris2, model0.ValueProbs)
|
||||
np.testing.assert_array_equal(val2[valp0 == 1], 1)
|
||||
np.testing.assert_array_equal(prob2[valp0 == 1, 0], 0)
|
||||
np.testing.assert_array_equal(prob2[valp0 == 1, 1], 1)
|
||||
np.testing.assert_almost_equal(np.sum(prob2, axis=1), 1)
|
||||
test_val_prob(val2, prob2)
|
||||
|
||||
val0, prob0 = model1(self.iris0, model1.ValueProbs)
|
||||
np.testing.assert_array_equal(val0[valp1 == 1], 1)
|
||||
np.testing.assert_array_equal(prob0[valp1 == 1, 0], 0)
|
||||
np.testing.assert_array_equal(prob0[valp1 == 1, 1], 1)
|
||||
np.testing.assert_almost_equal(np.sum(prob0, axis=1), 1)
|
||||
test_val_prob(val0, prob0)
|
||||
|
||||
val2, prob2 = model1(self.iris2, model1.ValueProbs)
|
||||
np.testing.assert_array_equal(val2[valp1 == 0], 0)
|
||||
np.testing.assert_array_equal(prob2[valp1 == 0, 0], 1)
|
||||
np.testing.assert_array_equal(prob2[valp1 == 0, 1], 0)
|
||||
np.testing.assert_almost_equal(np.sum(prob2, axis=1), 1)
|
||||
test_val_prob(val2, prob2)
|
||||
|
||||
val0, prob0 = model2(self.iris0, model2.ValueProbs)
|
||||
np.testing.assert_array_equal(val0[valp2 == 1], 0)
|
||||
np.testing.assert_array_equal(prob0[valp2 == 1, 0], 1)
|
||||
np.testing.assert_array_equal(prob0[valp2 == 1, 1], 0)
|
||||
np.testing.assert_almost_equal(np.sum(prob0, axis=1), 1)
|
||||
test_val_prob(val0, prob0)
|
||||
|
||||
val1, prob1 = model2(self.iris1, model2.ValueProbs)
|
||||
np.testing.assert_array_equal(val1[valp2 == 0], 0)
|
||||
np.testing.assert_array_equal(prob1[valp2 == 0, 0], 1)
|
||||
np.testing.assert_array_equal(prob1[valp2 == 0, 1], 0)
|
||||
np.testing.assert_almost_equal(np.sum(prob1, axis=1), 1)
|
||||
test_val_prob(val1, prob1)
|
||||
|
||||
def test_no_common_values(self):
|
||||
abc = DiscreteVariable("iris", values=list("abc"))
|
||||
iris_abc = Table.from_numpy(
|
||||
Domain(self.iris.domain.attributes, abc),
|
||||
self.iris.X, self.iris.Y)
|
||||
for lrn in [LogisticRegressionLearner,
|
||||
TreeLearner]: # skl and non-skl
|
||||
model = lrn()(self.iris)
|
||||
val, prob = model(iris_abc, model.ValueProbs)
|
||||
self.assertTrue(np.all(val >= 0))
|
||||
self.assertTrue(np.all(val <= 2))
|
||||
np.testing.assert_array_equal(prob, 1 / 3)
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
unittest.main()
|
||||
@ -0,0 +1,203 @@
|
||||
import unittest
|
||||
from unittest.mock import Mock, patch
|
||||
|
||||
import numpy as np
|
||||
|
||||
from Orange.base import Model
|
||||
from Orange.classification.calibration import \
|
||||
ThresholdLearner, ThresholdClassifier, \
|
||||
CalibratedLearner, CalibratedClassifier
|
||||
from Orange.data import Table
|
||||
|
||||
|
||||
class TestThresholdClassifier(unittest.TestCase):
|
||||
def setUp(self):
|
||||
probs1 = np.array([0.3, 0.5, 0.2, 0.8, 0.9, 0]).reshape(-1, 1)
|
||||
self.probs = np.hstack((1 - probs1, probs1))
|
||||
base_model = Mock(return_value=self.probs)
|
||||
base_model.domain.class_var.is_discrete = True
|
||||
base_model.domain.class_var.values = ["a", "b"]
|
||||
self.model = ThresholdClassifier(base_model, 0.5)
|
||||
self.data = Mock()
|
||||
|
||||
def test_threshold(self):
|
||||
vals = self.model(self.data)
|
||||
np.testing.assert_equal(vals, [0, 1, 0, 1, 1, 0])
|
||||
|
||||
self.model.threshold = 0.8
|
||||
vals = self.model(self.data)
|
||||
np.testing.assert_equal(vals, [0, 0, 0, 1, 1, 0])
|
||||
|
||||
self.model.threshold = 0
|
||||
vals = self.model(self.data)
|
||||
np.testing.assert_equal(vals, [1] * 6)
|
||||
|
||||
def test_return_types(self):
|
||||
vals = self.model(self.data, ret=Model.Value)
|
||||
np.testing.assert_equal(vals, [0, 1, 0, 1, 1, 0])
|
||||
|
||||
vals = self.model(self.data)
|
||||
np.testing.assert_equal(vals, [0, 1, 0, 1, 1, 0])
|
||||
|
||||
probs = self.model(self.data, ret=Model.Probs)
|
||||
np.testing.assert_equal(probs, self.probs)
|
||||
|
||||
vals, probs = self.model(self.data, ret=Model.ValueProbs)
|
||||
np.testing.assert_equal(vals, [0, 1, 0, 1, 1, 0])
|
||||
np.testing.assert_equal(probs, self.probs)
|
||||
|
||||
def test_nans(self):
|
||||
self.probs[1, :] = np.nan
|
||||
vals, probs = self.model(self.data, ret=Model.ValueProbs)
|
||||
np.testing.assert_equal(vals, [0, np.nan, 0, 1, 1, 0])
|
||||
np.testing.assert_equal(probs, self.probs)
|
||||
|
||||
def test_non_binary_base(self):
|
||||
base_model = Mock()
|
||||
base_model.domain.class_var.is_discrete = True
|
||||
base_model.domain.class_var.values = ["a"]
|
||||
self.assertRaises(ValueError, ThresholdClassifier, base_model, 0.5)
|
||||
|
||||
base_model.domain.class_var.values = ["a", "b", "c"]
|
||||
self.assertRaises(ValueError, ThresholdClassifier, base_model, 0.5)
|
||||
|
||||
base_model.domain.class_var = Mock()
|
||||
base_model.domain.class_var.is_discrete = False
|
||||
self.assertRaises(ValueError, ThresholdClassifier, base_model, 0.5)
|
||||
|
||||
|
||||
class TestThresholdLearner(unittest.TestCase):
|
||||
@patch("Orange.evaluation.performance_curves.Curves.from_results")
|
||||
@patch("Orange.classification.calibration.TestOnTrainingData")
|
||||
def test_fit_storage(self, test_on_training, curves_from_results):
|
||||
curves_from_results.return_value = curves = Mock()
|
||||
curves.probs = np.array([0.1, 0.15, 0.3, 0.45, 0.6, 0.8])
|
||||
curves.ca = lambda: np.array([0.1, 0.7, 0.4, 0.4, 0.3, 0.1])
|
||||
curves.f1 = lambda: np.array([0.1, 0.2, 0.4, 0.4, 0.3, 0.1])
|
||||
model = Mock()
|
||||
model.domain.class_var.is_discrete = True
|
||||
model.domain.class_var.values = ("a", "b")
|
||||
data = Table("heart_disease")
|
||||
learner = Mock()
|
||||
test_on_training.return_value = res = Mock()
|
||||
res.models = np.array([[model]])
|
||||
test_on_training.return_value = res
|
||||
|
||||
thresh_learner = ThresholdLearner(
|
||||
base_learner=learner,
|
||||
threshold_criterion=ThresholdLearner.OptimizeCA)
|
||||
thresh_model = thresh_learner(data)
|
||||
self.assertEqual(thresh_model.threshold, 0.15)
|
||||
args, kwargs = test_on_training.call_args
|
||||
self.assertEqual(len(args), 2)
|
||||
self.assertIs(args[0], data)
|
||||
self.assertIs(args[1][0], learner)
|
||||
self.assertEqual(len(args[1]), 1)
|
||||
self.assertEqual(kwargs, {"store_models": 1})
|
||||
|
||||
thresh_learner = ThresholdLearner(
|
||||
base_learner=learner,
|
||||
threshold_criterion=ThresholdLearner.OptimizeF1)
|
||||
thresh_model = thresh_learner(data)
|
||||
self.assertEqual(thresh_model.threshold, 0.45)
|
||||
|
||||
def test_non_binary_class(self):
|
||||
thresh_learner = ThresholdLearner(
|
||||
base_learner=Mock(),
|
||||
threshold_criterion=ThresholdLearner.OptimizeF1)
|
||||
|
||||
data = Mock()
|
||||
data.domain.class_var.is_discrete = True
|
||||
data.domain.class_var.values = ["a"]
|
||||
self.assertRaises(ValueError, thresh_learner.fit_storage, data)
|
||||
|
||||
data.domain.class_var.values = ["a", "b", "c"]
|
||||
self.assertRaises(ValueError, thresh_learner.fit_storage, data)
|
||||
|
||||
data.domain.class_var = Mock()
|
||||
data.domain.class_var.is_discrete = False
|
||||
self.assertRaises(ValueError, thresh_learner.fit_storage, data)
|
||||
|
||||
|
||||
class TestCalibratedClassifier(unittest.TestCase):
|
||||
def setUp(self):
|
||||
probs1 = np.array([0.3, 0.5, 0.2, 0.8, 0.9, 0]).reshape(-1, 1)
|
||||
self.probs = np.hstack((1 - probs1, probs1))
|
||||
base_model = Mock(return_value=self.probs)
|
||||
base_model.domain.class_var.is_discrete = True
|
||||
base_model.domain.class_var.values = ["a", "b"]
|
||||
self.model = CalibratedClassifier(base_model, None)
|
||||
self.data = Mock()
|
||||
|
||||
def test_call(self):
|
||||
calprobs = np.arange(self.probs.size).reshape(self.probs.shape)
|
||||
calprobs = calprobs / np.sum(calprobs, axis=1)[:, None]
|
||||
calprobs[-1] = [0.7, 0.3]
|
||||
self.model.calibrated_probs = Mock(return_value=calprobs)
|
||||
|
||||
probs = self.model(self.data, ret=Model.Probs)
|
||||
self.model.calibrated_probs.assert_called_with(self.probs)
|
||||
np.testing.assert_almost_equal(probs, calprobs)
|
||||
|
||||
vals = self.model(self.data, ret=Model.Value)
|
||||
np.testing.assert_almost_equal(vals, [1, 1, 1, 1, 1, 0])
|
||||
|
||||
vals, probs = self.model(self.data, ret=Model.ValueProbs)
|
||||
np.testing.assert_almost_equal(probs, calprobs)
|
||||
np.testing.assert_almost_equal(vals, [1, 1, 1, 1, 1, 0])
|
||||
|
||||
def test_calibrated_probs(self):
|
||||
self.model.calibrators = None
|
||||
calprobs = self.model.calibrated_probs(self.probs)
|
||||
np.testing.assert_equal(calprobs, self.probs)
|
||||
self.assertIsNot(calprobs, self.probs)
|
||||
|
||||
calibrator = Mock()
|
||||
calibrator.predict = lambda x: x**2
|
||||
self.model.calibrators = [calibrator] * 2
|
||||
calprobs = self.model.calibrated_probs(self.probs)
|
||||
expprobs = self.probs ** 2 / np.sum(self.probs ** 2, axis=1)[:, None]
|
||||
np.testing.assert_almost_equal(calprobs, expprobs)
|
||||
|
||||
self.probs[1] = 0
|
||||
self.probs[2] = np.nan
|
||||
expprobs[1] = 0.5
|
||||
expprobs[2] = np.nan
|
||||
calprobs = self.model.calibrated_probs(self.probs)
|
||||
np.testing.assert_almost_equal(calprobs, expprobs)
|
||||
|
||||
|
||||
class TestCalibratedLearner(unittest.TestCase):
|
||||
@patch("Orange.classification.calibration._SigmoidCalibration.fit")
|
||||
@patch("Orange.classification.calibration.TestOnTrainingData")
|
||||
def test_fit_storage(self, test_on_training, sigmoid_fit):
|
||||
data = Table("heart_disease")
|
||||
learner = Mock()
|
||||
|
||||
model = Mock()
|
||||
model.domain.class_var.is_discrete = True
|
||||
model.domain.class_var.values = ("a", "b")
|
||||
|
||||
test_on_training.return_value = res = Mock()
|
||||
res.models = np.array([[model]])
|
||||
res.probabilities = np.arange(20, dtype=float).reshape(1, 5, 4)
|
||||
test_on_training.return_value = res
|
||||
|
||||
sigmoid_fit.return_value = Mock()
|
||||
|
||||
cal_learner = CalibratedLearner(
|
||||
base_learner=learner, calibration_method=CalibratedLearner.Sigmoid)
|
||||
cal_model = cal_learner(data)
|
||||
|
||||
self.assertIs(cal_model.base_model, model)
|
||||
self.assertEqual(cal_model.calibrators, [sigmoid_fit.return_value] * 4)
|
||||
args, kwargs = test_on_training.call_args
|
||||
self.assertEqual(len(args), 2)
|
||||
self.assertIs(args[0], data)
|
||||
self.assertIs(args[1][0], learner)
|
||||
self.assertEqual(len(args[1]), 1)
|
||||
self.assertEqual(kwargs, {"store_models": 1})
|
||||
|
||||
for call, cls_probs in zip(sigmoid_fit.call_args_list,
|
||||
res.probabilities[0].T):
|
||||
np.testing.assert_equal(call[0][0], cls_probs)
|
||||
7
pyminer/features/modelling/clustering/__init__.py
Normal file
7
pyminer/features/modelling/clustering/__init__.py
Normal file
@ -0,0 +1,7 @@
|
||||
# The package is pulling names from modules with defined __all__
|
||||
# pylint: disable=wildcard-import
|
||||
|
||||
from .dbscan import *
|
||||
from .hierarchical import *
|
||||
from .kmeans import *
|
||||
from .louvain import *
|
||||
16
pyminer/features/modelling/regression/__init__.py
Normal file
16
pyminer/features/modelling/regression/__init__.py
Normal file
@ -0,0 +1,16 @@
|
||||
# Pull members from modules to Orange.regression namespace
|
||||
# pylint: disable=wildcard-import
|
||||
|
||||
from .base_regression import (ModelRegression as Model,
|
||||
LearnerRegression as Learner,
|
||||
SklModelRegression as SklModel,
|
||||
SklLearnerRegression as SklLearner)
|
||||
from .linear import *
|
||||
from .mean import *
|
||||
from .knn import *
|
||||
from .simple_random_forest import *
|
||||
from .svm import *
|
||||
from .random_forest import *
|
||||
from .tree import *
|
||||
from .neural_network import *
|
||||
from ..classification.simple_tree import *
|
||||
0
pyminer/features/modelling/test_model.py
Normal file
0
pyminer/features/modelling/test_model.py
Normal file
BIN
pyminer/features/preprocess/__pycache__/__init__.cpython-38.pyc
Normal file
BIN
pyminer/features/preprocess/__pycache__/__init__.cpython-38.pyc
Normal file
Binary file not shown.
BIN
pyminer/features/preprocess/__pycache__/impute.cpython-38.pyc
Normal file
BIN
pyminer/features/preprocess/__pycache__/impute.cpython-38.pyc
Normal file
Binary file not shown.
BIN
pyminer/features/preprocess/__pycache__/modify.cpython-38.pyc
Normal file
BIN
pyminer/features/preprocess/__pycache__/modify.cpython-38.pyc
Normal file
Binary file not shown.
Binary file not shown.
12
pyminer/features/preprocess/datasets.py
Normal file
12
pyminer/features/preprocess/datasets.py
Normal file
@ -0,0 +1,12 @@
|
||||
import pandas as pd
|
||||
import os
|
||||
path=os.path.abspath(__file__)
|
||||
dirname=os.path.dirname(os.path.abspath(__file__))
|
||||
|
||||
ccpp=pd.read_csv(dirname+"\\datasets\\ccpp.csv")
|
||||
class_sas=pd.read_csv(dirname+"\\datasets\\class.csv")
|
||||
diabetes=pd.read_csv(dirname+"\\datasets\\diabetes.csv")
|
||||
iris=pd.read_csv(dirname+"\\datasets\\iris.csv")
|
||||
mtcars=pd.read_csv(dirname+"\\datasets\\mtcars.csv")
|
||||
mushrooms=pd.read_csv(dirname+"\\datasets\\mushrooms.csv")
|
||||
uci=pd.read_csv(dirname+"\\datasets\\uci.csv")
|
||||
0
pyminer/features/preprocess/impute.py
Normal file
0
pyminer/features/preprocess/impute.py
Normal file
65
pyminer/features/preprocess/normalize.py
Normal file
65
pyminer/features/preprocess/normalize.py
Normal file
@ -0,0 +1,65 @@
|
||||
import numpy as np
|
||||
|
||||
from Orange.data import Domain
|
||||
from Orange.statistics import distribution
|
||||
from Orange.util import Reprable
|
||||
from .preprocess import Normalize
|
||||
from .transformation import Normalizer as Norm
|
||||
__all__ = ["Normalizer"]
|
||||
|
||||
|
||||
class Normalizer(Reprable):
|
||||
def __init__(self,
|
||||
zero_based=True,
|
||||
norm_type=Normalize.NormalizeBySD,
|
||||
transform_class=False,
|
||||
center=True,
|
||||
normalize_datetime=False):
|
||||
self.zero_based = zero_based
|
||||
self.norm_type = norm_type
|
||||
self.transform_class = transform_class
|
||||
self.center = center
|
||||
self.normalize_datetime = normalize_datetime
|
||||
|
||||
def __call__(self, data):
|
||||
dists = distribution.get_distributions(data)
|
||||
new_attrs = [self.normalize(dists[i], var) for
|
||||
(i, var) in enumerate(data.domain.attributes)]
|
||||
|
||||
new_class_vars = data.domain.class_vars
|
||||
if self.transform_class:
|
||||
attr_len = len(data.domain.attributes)
|
||||
new_class_vars = [self.normalize(dists[i + attr_len], var) for
|
||||
(i, var) in enumerate(data.domain.class_vars)]
|
||||
|
||||
domain = Domain(new_attrs, new_class_vars, data.domain.metas)
|
||||
return data.transform(domain)
|
||||
|
||||
def normalize(self, dist, var):
|
||||
if not var.is_continuous or (var.is_time and not self.normalize_datetime):
|
||||
return var
|
||||
elif self.norm_type == Normalize.NormalizeBySD:
|
||||
return self.normalize_by_sd(dist, var)
|
||||
elif self.norm_type == Normalize.NormalizeBySpan:
|
||||
return self.normalize_by_span(dist, var)
|
||||
|
||||
def normalize_by_sd(self, dist, var):
|
||||
avg, sd = (dist.mean(), dist.standard_deviation()) if dist.size else (0, 1)
|
||||
if sd == 0:
|
||||
sd = 1
|
||||
if self.center:
|
||||
compute_val = Norm(var, avg, 1 / sd)
|
||||
else:
|
||||
compute_val = Norm(var, 0, 1 / sd)
|
||||
return var.copy(compute_value=compute_val)
|
||||
|
||||
def normalize_by_span(self, dist, var):
|
||||
dma, dmi = (dist.max(), dist.min()) if dist.shape[1] else (np.nan, np.nan)
|
||||
diff = dma - dmi
|
||||
if diff < 1e-15:
|
||||
diff = 1
|
||||
if self.zero_based:
|
||||
compute_val = Norm(var, dmi, 1 / diff)
|
||||
else:
|
||||
compute_val = Norm(var, (dma + dmi) / 2, 2 / diff)
|
||||
return var.copy(compute_value=compute_val)
|
||||
2637
pyminer/features/preprocess/preprocess.py
Normal file
2637
pyminer/features/preprocess/preprocess.py
Normal file
File diff suppressed because it is too large
Load Diff
267
pyminer/features/preprocess/remove.py
Normal file
267
pyminer/features/preprocess/remove.py
Normal file
@ -0,0 +1,267 @@
|
||||
from collections import namedtuple
|
||||
|
||||
import numpy as np
|
||||
|
||||
from Orange.data import Domain, DiscreteVariable, Table
|
||||
from Orange.preprocess.transformation import Lookup
|
||||
from Orange.statistics.util import nanunique
|
||||
from .preprocess import Preprocess
|
||||
|
||||
__all__ = ["Remove"]
|
||||
|
||||
|
||||
class Remove(Preprocess):
|
||||
"""
|
||||
Construct a preprocessor for removing constant features/classes
|
||||
and unused values.
|
||||
Given a data table, preprocessor returns a new table and a list of
|
||||
results. In the new table, the constant features/classes and unused
|
||||
values are removed. The list of results consists of two dictionaries.
|
||||
The first one contains numbers of 'removed', 'reduced' and 'sorted'
|
||||
features. The second one contains numbers of 'removed', 'reduced'
|
||||
and 'sorted' features.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
attr_flags : int (default: 0)
|
||||
If SortValues, values of discrete attributes are sorted.
|
||||
If RemoveConstant, unused attributes are removed.
|
||||
If RemoveUnusedValues, unused values are removed from discrete
|
||||
attributes.
|
||||
It is possible to merge operations in one by summing several types.
|
||||
|
||||
class_flags: int (default: 0)
|
||||
If SortValues, values of discrete class attributes are sorted.
|
||||
If RemoveConstant, unused class attributes are removed.
|
||||
If RemoveUnusedValues, unused values are removed from discrete
|
||||
class attributes.
|
||||
It is possible to merge operations in one by summing several types.
|
||||
|
||||
Examples
|
||||
--------
|
||||
>>> from Orange.data import Table
|
||||
>>> from Orange.preprocess import Remove
|
||||
>>> data = Table("zoo")[:10]
|
||||
>>> flags = sum([Remove.SortValues, Remove.RemoveConstant, Remove.RemoveUnusedValues])
|
||||
>>> remover = Remove(attr_flags=flags, class_flags=flags)
|
||||
>>> new_data = remover(data)
|
||||
>>> attr_results, class_results = remover.attr_results, remover.class_results
|
||||
"""
|
||||
|
||||
SortValues, RemoveConstant, RemoveUnusedValues = 1, 2, 4
|
||||
|
||||
def __init__(self, attr_flags=0, class_flags=0, meta_flags=0):
|
||||
self.attr_flags = attr_flags
|
||||
self.class_flags = class_flags
|
||||
self.meta_flags = meta_flags
|
||||
self.attr_results = None
|
||||
self.class_results = None
|
||||
self.meta_results = None
|
||||
|
||||
def __call__(self, data):
|
||||
"""
|
||||
Removes unused features or classes from the given data. Returns a new
|
||||
data table.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
data : Orange.data.Table
|
||||
A data table to remove features or classes from.
|
||||
|
||||
Returns
|
||||
-------
|
||||
data : Orange.data.Table
|
||||
New data table.
|
||||
"""
|
||||
if data is None:
|
||||
return None
|
||||
|
||||
domain = data.domain
|
||||
attrs_state = [purge_var_M(var, data, self.attr_flags)
|
||||
for var in domain.attributes]
|
||||
class_state = [purge_var_M(var, data, self.class_flags)
|
||||
for var in domain.class_vars]
|
||||
metas_state = [purge_var_M(var, data, self.meta_flags)
|
||||
for var in domain.metas]
|
||||
|
||||
att_vars, self.attr_results = self.get_vars_and_results(attrs_state)
|
||||
cls_vars, self.class_results = self.get_vars_and_results(class_state)
|
||||
meta_vars, self.meta_results = self.get_vars_and_results(metas_state)
|
||||
|
||||
domain = Domain(att_vars, cls_vars, meta_vars)
|
||||
return data.transform(domain)
|
||||
|
||||
def get_vars_and_results(self, state):
|
||||
removed, reduced, sorted = 0, 0, 0
|
||||
vars = []
|
||||
for st in state:
|
||||
removed += is_removed(st)
|
||||
reduced += not is_removed(st) and is_reduced(st)
|
||||
sorted += not is_removed(st) and is_sorted(st)
|
||||
if not is_removed(st):
|
||||
vars.append(merge_transforms(st).var)
|
||||
res = {'removed': removed, 'reduced': reduced, 'sorted': sorted}
|
||||
return vars, res
|
||||
|
||||
|
||||
# Define a simple Purge expression 'language'.
|
||||
#: A input variable (leaf expression).
|
||||
Var = namedtuple("Var", ["var"])
|
||||
#: Removed variable (can only ever be present as a root node).
|
||||
Removed = namedtuple("Removed", ["sub", "var"])
|
||||
#: A reduced variable
|
||||
Reduced = namedtuple("Reduced", ["sub", "var"])
|
||||
#: A sorted variable
|
||||
Sorted = namedtuple("Sorted", ["sub", "var"])
|
||||
#: A general (lookup) transformed variable.
|
||||
#: (this node is returned as a result of `merge` which joins consecutive
|
||||
#: Removed/Reduced nodes into a single Transformed node)
|
||||
Transformed = namedtuple("Transformed", ["sub", "var"])
|
||||
|
||||
|
||||
def is_var(exp):
|
||||
"""Is `exp` a `Var` node."""
|
||||
return isinstance(exp, Var)
|
||||
|
||||
|
||||
def is_removed(exp):
|
||||
"""Is `exp` a `Removed` node."""
|
||||
return isinstance(exp, Removed)
|
||||
|
||||
|
||||
def _contains(exp, cls):
|
||||
"""Does `node` contain a sub node of type `cls`"""
|
||||
if isinstance(exp, cls):
|
||||
return True
|
||||
elif isinstance(exp, Var):
|
||||
return False
|
||||
else:
|
||||
return _contains(exp.sub, cls)
|
||||
|
||||
|
||||
def is_reduced(exp):
|
||||
"""Does `exp` contain a `Reduced` node."""
|
||||
return _contains(exp, Reduced)
|
||||
|
||||
|
||||
def is_sorted(exp):
|
||||
"""Does `exp` contain a `Reduced` node."""
|
||||
return _contains(exp, Sorted)
|
||||
|
||||
|
||||
def merge_transforms(exp):
|
||||
"""
|
||||
Merge consecutive Removed, Reduced or Transformed nodes.
|
||||
|
||||
.. note:: Removed nodes are returned unchanged.
|
||||
|
||||
"""
|
||||
if isinstance(exp, (Var, Removed)):
|
||||
return exp
|
||||
elif isinstance(exp, (Reduced, Sorted, Transformed)):
|
||||
prev = merge_transforms(exp.sub)
|
||||
if isinstance(prev, (Reduced, Sorted, Transformed)):
|
||||
B = exp.var.compute_value
|
||||
assert isinstance(B, Lookup)
|
||||
A = B.variable.compute_value
|
||||
assert isinstance(A, Lookup)
|
||||
|
||||
new_var = DiscreteVariable(
|
||||
exp.var.name,
|
||||
values=exp.var.values,
|
||||
ordered=exp.var.ordered,
|
||||
compute_value=merge_lookup(A, B),
|
||||
sparse=exp.var.sparse,
|
||||
)
|
||||
assert isinstance(prev.sub, Var)
|
||||
return Transformed(prev.sub, new_var)
|
||||
else:
|
||||
assert prev is exp.sub
|
||||
return exp
|
||||
else:
|
||||
raise TypeError
|
||||
|
||||
|
||||
def purge_var_M(var, data, flags):
|
||||
state = Var(var)
|
||||
if flags & Remove.RemoveConstant:
|
||||
var = remove_constant(state.var, data)
|
||||
if var is None:
|
||||
return Removed(state, state.var)
|
||||
|
||||
if state.var.is_discrete:
|
||||
if flags & Remove.RemoveUnusedValues:
|
||||
newattr = remove_unused_values(state.var, data)
|
||||
|
||||
if newattr is not state.var:
|
||||
state = Reduced(state, newattr)
|
||||
|
||||
if flags & Remove.RemoveConstant and len(state.var.values) < 2:
|
||||
return Removed(state, state.var)
|
||||
|
||||
if flags & Remove.SortValues:
|
||||
newattr = sort_var_values(state.var)
|
||||
if newattr is not state.var:
|
||||
state = Sorted(state, newattr)
|
||||
|
||||
return state
|
||||
|
||||
|
||||
def has_at_least_two_values(data, var):
|
||||
((dist, unknowns),) = data._compute_distributions([var])
|
||||
# TODO this check is suboptimal for sparse since get_column_view
|
||||
# densifies the data. Should be irrelevant after Pandas.
|
||||
_, sparse = data.get_column_view(var)
|
||||
if var.is_continuous:
|
||||
dist = dist[1, :]
|
||||
min_size = 0 if sparse and unknowns else 1
|
||||
return np.sum(dist > 0.0) > min_size
|
||||
|
||||
|
||||
def remove_constant(var, data):
|
||||
if var.is_continuous:
|
||||
if not has_at_least_two_values(data, var):
|
||||
return None
|
||||
else:
|
||||
return var
|
||||
elif var.is_discrete:
|
||||
if len(var.values) < 2:
|
||||
return None
|
||||
else:
|
||||
return var
|
||||
else:
|
||||
return var
|
||||
|
||||
|
||||
def remove_unused_values(var, data):
|
||||
unique = nanunique(data.get_column_view(var)[0].astype(float)).astype(int)
|
||||
if len(unique) == len(var.values):
|
||||
return var
|
||||
used_values = [var.values[i] for i in unique]
|
||||
return DiscreteVariable(var.name, values=used_values, sparse=var.sparse)
|
||||
|
||||
|
||||
def sort_var_values(var):
|
||||
newvalues = list(sorted(var.values))
|
||||
|
||||
if newvalues == list(var.values):
|
||||
return var
|
||||
|
||||
translation_table = np.array(
|
||||
[float(newvalues.index(value)) for value in var.values]
|
||||
)
|
||||
|
||||
return DiscreteVariable(var.name, values=newvalues,
|
||||
compute_value=Lookup(var, translation_table),
|
||||
sparse=var.sparse)
|
||||
|
||||
|
||||
def merge_lookup(A, B):
|
||||
"""
|
||||
Merge two consecutive Lookup transforms into one.
|
||||
"""
|
||||
lookup_table = np.array(A.lookup_table)
|
||||
mask = np.isfinite(lookup_table)
|
||||
indices = np.array(lookup_table[mask], dtype=int)
|
||||
lookup_table[mask] = B.lookup_table[indices]
|
||||
return Lookup(A.variable, lookup_table)
|
||||
0
pyminer/features/preprocess/sample.py
Normal file
0
pyminer/features/preprocess/sample.py
Normal file
649
pyminer/features/preprocess/test_preprocess.py
Normal file
649
pyminer/features/preprocess/test_preprocess.py
Normal file
@ -0,0 +1,649 @@
|
||||
"""
|
||||
Preprocess
|
||||
----------
|
||||
|
||||
"""
|
||||
import numpy as np
|
||||
import bottleneck as bn
|
||||
import scipy.sparse as sp
|
||||
from sklearn.impute import SimpleImputer
|
||||
|
||||
import Orange.data
|
||||
from Orange.data.filter import HasClass
|
||||
from Orange.statistics import distribution
|
||||
from Orange.util import Reprable, Enum, deprecated
|
||||
from . import impute, discretize, transformation
|
||||
|
||||
__all__ = ["Continuize", "Discretize", "Impute", "RemoveNaNRows",
|
||||
"SklImpute", "Normalize", "Randomize", "Preprocess",
|
||||
"RemoveConstant", "RemoveNaNClasses", "RemoveNaNColumns",
|
||||
"ProjectPCA", "ProjectCUR", "Scale", "RemoveSparse",
|
||||
"AdaptiveNormalize"]
|
||||
|
||||
|
||||
class Preprocess(Reprable):
|
||||
"""
|
||||
A generic preprocessor base class.
|
||||
|
||||
Methods
|
||||
-------
|
||||
__call__(data: Table) -> Table
|
||||
Return preprocessed data.
|
||||
"""
|
||||
def __call__(self, data):
|
||||
raise NotImplementedError("Subclasses need to implement __call__")
|
||||
|
||||
|
||||
class Continuize(Preprocess):
|
||||
MultinomialTreatment = Enum(
|
||||
"Continuize",
|
||||
("Indicators", "FirstAsBase", "FrequentAsBase", "Remove",
|
||||
"RemoveMultinomial", "ReportError", "AsOrdinal", "AsNormalizedOrdinal",
|
||||
"Leave"),
|
||||
qualname="Continuize.MultinomialTreatment")
|
||||
(Indicators, FirstAsBase, FrequentAsBase, Remove, RemoveMultinomial,
|
||||
ReportError, AsOrdinal, AsNormalizedOrdinal, Leave) = MultinomialTreatment
|
||||
|
||||
def __init__(self, zero_based=True,
|
||||
multinomial_treatment=Indicators):
|
||||
self.zero_based = zero_based
|
||||
self.multinomial_treatment = multinomial_treatment
|
||||
|
||||
def __call__(self, data):
|
||||
from . import continuize
|
||||
|
||||
continuizer = continuize.DomainContinuizer(
|
||||
zero_based=self.zero_based,
|
||||
multinomial_treatment=self.multinomial_treatment)
|
||||
domain = continuizer(data)
|
||||
return data.transform(domain)
|
||||
|
||||
|
||||
class Discretize(Preprocess):
|
||||
"""
|
||||
Construct a discretizer, a preprocessor for discretization of
|
||||
continuous features.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
method : discretization method (default: Orange.preprocess.discretize.Discretization)
|
||||
|
||||
remove_const : bool (default=True)
|
||||
Determines whether the features with constant values are removed
|
||||
during discretization.
|
||||
"""
|
||||
|
||||
def __init__(self, method=None, remove_const=True,
|
||||
discretize_classes=False, discretize_metas=False):
|
||||
self.method = method
|
||||
self.remove_const = remove_const
|
||||
self.discretize_classes = discretize_classes
|
||||
self.discretize_metas = discretize_metas
|
||||
|
||||
def __call__(self, data):
|
||||
"""
|
||||
Compute and apply discretization of the given data. Returns a new
|
||||
data table.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
data : Orange.data.Table
|
||||
A data table to be discretized.
|
||||
"""
|
||||
|
||||
def transform(var):
|
||||
if var.is_continuous:
|
||||
new_var = method(data, var)
|
||||
if new_var is not None and \
|
||||
(len(new_var.values) >= 2 or not self.remove_const):
|
||||
return new_var
|
||||
else:
|
||||
return None
|
||||
else:
|
||||
return var
|
||||
|
||||
def discretized(vars_, do_discretize):
|
||||
if do_discretize:
|
||||
vars_ = (transform(var) for var in vars_)
|
||||
vars_ = [var for var in vars_ if var is not None]
|
||||
return vars_
|
||||
|
||||
method = self.method or discretize.EqualFreq()
|
||||
domain = Orange.data.Domain(
|
||||
discretized(data.domain.attributes, True),
|
||||
discretized(data.domain.class_vars, self.discretize_classes),
|
||||
discretized(data.domain.metas, self.discretize_metas))
|
||||
return data.transform(domain)
|
||||
|
||||
|
||||
class Impute(Preprocess):
|
||||
"""
|
||||
Construct a imputer, a preprocessor for imputation of missing values in
|
||||
the data table.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
method : imputation method (default: Orange.preprocess.impute.Average())
|
||||
"""
|
||||
|
||||
def __init__(self, method=Orange.preprocess.impute.Average()):
|
||||
self.method = method
|
||||
|
||||
def __call__(self, data):
|
||||
"""
|
||||
Apply an imputation method to the given dataset. Returns a new
|
||||
data table with missing values replaced by their imputations.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
data : Orange.data.Table
|
||||
An input data table.
|
||||
"""
|
||||
|
||||
method = self.method or impute.Average()
|
||||
newattrs = [method(data, var) for var in data.domain.attributes]
|
||||
domain = Orange.data.Domain(
|
||||
newattrs, data.domain.class_vars, data.domain.metas)
|
||||
return data.transform(domain)
|
||||
|
||||
|
||||
class SklImpute(Preprocess):
|
||||
__wraps__ = SimpleImputer
|
||||
|
||||
def __init__(self, strategy='mean'):
|
||||
self.strategy = strategy
|
||||
|
||||
def __call__(self, data):
|
||||
from Orange.data.sql.table import SqlTable
|
||||
if isinstance(data, SqlTable):
|
||||
return Impute()(data)
|
||||
imputer = SimpleImputer(strategy=self.strategy)
|
||||
X = imputer.fit_transform(data.X)
|
||||
# Create new variables with appropriate `compute_value`, but
|
||||
# drop the ones which do not have valid `imputer.statistics_`
|
||||
# (i.e. all NaN columns). `sklearn.preprocessing.Imputer` already
|
||||
# drops them from the transformed X.
|
||||
features = [impute.Average()(data, var, value)
|
||||
for var, value in zip(data.domain.attributes,
|
||||
imputer.statistics_)
|
||||
if not np.isnan(value)]
|
||||
assert X.shape[1] == len(features)
|
||||
domain = Orange.data.Domain(features, data.domain.class_vars,
|
||||
data.domain.metas)
|
||||
new_data = data.transform(domain)
|
||||
new_data.X = X
|
||||
return new_data
|
||||
|
||||
|
||||
class RemoveConstant(Preprocess):
|
||||
"""
|
||||
Construct a preprocessor that removes features with constant values
|
||||
from the dataset.
|
||||
"""
|
||||
|
||||
def __call__(self, data):
|
||||
"""
|
||||
Remove columns with constant values from the dataset and return
|
||||
the resulting data table.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
data : an input dataset
|
||||
"""
|
||||
|
||||
oks = np.logical_and(~bn.allnan(data.X, axis=0),
|
||||
bn.nanmin(data.X, axis=0) != bn.nanmax(data.X, axis=0))
|
||||
atts = [data.domain.attributes[i] for i, ok in enumerate(oks) if ok]
|
||||
domain = Orange.data.Domain(atts, data.domain.class_vars,
|
||||
data.domain.metas)
|
||||
return data.transform(domain)
|
||||
|
||||
|
||||
class RemoveNaNRows(Preprocess):
|
||||
_reprable_module = True
|
||||
|
||||
def __call__(self, data):
|
||||
mask = np.isnan(data.X)
|
||||
mask = np.any(mask, axis=1)
|
||||
return data[~mask]
|
||||
|
||||
|
||||
class RemoveNaNColumns(Preprocess):
|
||||
"""
|
||||
Remove features from the data domain if they contain
|
||||
`threshold` or more unknown values.
|
||||
|
||||
`threshold` can be an integer or a float in the range (0, 1) representing
|
||||
the fraction of the data size. When not provided, columns with only missing
|
||||
values are removed (default).
|
||||
"""
|
||||
def __init__(self, threshold=None):
|
||||
self.threshold = threshold
|
||||
|
||||
def __call__(self, data, threshold=None):
|
||||
# missing entries in sparse data are treated as zeros so we skip removing NaNs
|
||||
if sp.issparse(data.X):
|
||||
return data
|
||||
|
||||
if threshold is None:
|
||||
threshold = data.X.shape[0] if self.threshold is None else \
|
||||
self.threshold
|
||||
if isinstance(threshold, float):
|
||||
threshold = threshold * data.X.shape[0]
|
||||
nans = np.sum(np.isnan(data.X), axis=0)
|
||||
att = [a for a, n in zip(data.domain.attributes, nans) if n < threshold]
|
||||
domain = Orange.data.Domain(att, data.domain.class_vars,
|
||||
data.domain.metas)
|
||||
return data.transform(domain)
|
||||
|
||||
|
||||
@deprecated("Orange.data.filter.HasClas")
|
||||
class RemoveNaNClasses(Preprocess):
|
||||
"""
|
||||
Construct preprocessor that removes examples with missing class
|
||||
from the dataset.
|
||||
"""
|
||||
|
||||
def __call__(self, data):
|
||||
"""
|
||||
Remove rows that contain NaN in any class variable from the dataset
|
||||
and return the resulting data table.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
data : an input dataset
|
||||
|
||||
Returns
|
||||
-------
|
||||
data : dataset without rows with missing classes
|
||||
"""
|
||||
return HasClass()(data)
|
||||
|
||||
|
||||
class Normalize(Preprocess):
|
||||
"""
|
||||
Construct a preprocessor for normalization of features.
|
||||
Given a data table, preprocessor returns a new table in
|
||||
which the continuous attributes are normalized.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
zero_based : bool (default=True)
|
||||
Only used when `norm_type=NormalizeBySpan`.
|
||||
|
||||
Determines the value used as the “low” value of the variable.
|
||||
It determines the interval for normalized continuous variables
|
||||
(either [-1, 1] or [0, 1]).
|
||||
|
||||
norm_type : NormTypes (default: Normalize.NormalizeBySD)
|
||||
Normalization type. If Normalize.NormalizeBySD, the values are
|
||||
replaced with standardized values by subtracting the average
|
||||
value and dividing by the standard deviation.
|
||||
Attribute zero_based has no effect on this standardization.
|
||||
|
||||
If Normalize.NormalizeBySpan, the values are replaced with
|
||||
normalized values by subtracting min value of the data and
|
||||
dividing by span (max - min).
|
||||
|
||||
transform_class : bool (default=False)
|
||||
If True the class is normalized as well.
|
||||
|
||||
center : bool (default=True)
|
||||
Only used when `norm_type=NormalizeBySD`.
|
||||
|
||||
Whether or not to center the data so it has mean zero.
|
||||
|
||||
normalize_datetime : bool (default=False)
|
||||
|
||||
|
||||
Examples
|
||||
--------
|
||||
>>> from Orange.data import Table
|
||||
>>> from Orange.preprocess import Normalize
|
||||
>>> data = Table("iris")
|
||||
>>> normalizer = Normalize(norm_type=Normalize.NormalizeBySpan)
|
||||
>>> normalized_data = normalizer(data)
|
||||
"""
|
||||
Type = Enum("Normalize", ("NormalizeBySpan", "NormalizeBySD"),
|
||||
qualname="Normalize.Type")
|
||||
NormalizeBySpan, NormalizeBySD = Type
|
||||
|
||||
def __init__(self,
|
||||
zero_based=True,
|
||||
norm_type=NormalizeBySD,
|
||||
transform_class=False,
|
||||
center=True,
|
||||
normalize_datetime=False):
|
||||
self.zero_based = zero_based
|
||||
self.norm_type = norm_type
|
||||
self.transform_class = transform_class
|
||||
self.center = center
|
||||
self.normalize_datetime = normalize_datetime
|
||||
|
||||
def __call__(self, data):
|
||||
"""
|
||||
Compute and apply normalization of the given data. Returns a new
|
||||
data table.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
data : Orange.data.Table
|
||||
A data table to be normalized.
|
||||
|
||||
Returns
|
||||
-------
|
||||
data : Orange.data.Table
|
||||
Normalized data table.
|
||||
"""
|
||||
from . import normalize
|
||||
|
||||
if all(a.attributes.get('skip-normalization', False)
|
||||
for a in data.domain.attributes if a.is_continuous):
|
||||
# Skip normalization for datasets where all features are marked as already normalized.
|
||||
# Required for SVMs (with normalizer as their default preprocessor) on sparse data to
|
||||
# retain sparse structure. Normalizing sparse data would otherwise result in a dense
|
||||
# matrix, which requires too much memory. For example, this is used for Bag of Words
|
||||
# models where normalization is not really needed.
|
||||
return data
|
||||
|
||||
normalizer = normalize.Normalizer(
|
||||
zero_based=self.zero_based,
|
||||
norm_type=self.norm_type,
|
||||
transform_class=self.transform_class,
|
||||
center=self.center,
|
||||
normalize_datetime=self.normalize_datetime
|
||||
)
|
||||
return normalizer(data)
|
||||
|
||||
|
||||
class Randomize(Preprocess):
|
||||
"""
|
||||
Construct a preprocessor for randomization of classes,
|
||||
attributes and/or metas.
|
||||
Given a data table, preprocessor returns a new table in
|
||||
which the data is shuffled.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
|
||||
rand_type : RandTypes (default: Randomize.RandomizeClasses)
|
||||
Randomization type. If Randomize.RandomizeClasses, classes
|
||||
are shuffled.
|
||||
If Randomize.RandomizeAttributes, attributes are shuffled.
|
||||
If Randomize.RandomizeMetas, metas are shuffled.
|
||||
|
||||
rand_seed : int (optional)
|
||||
Random seed
|
||||
|
||||
Examples
|
||||
--------
|
||||
>>> from Orange.data import Table
|
||||
>>> from Orange.preprocess import Randomize
|
||||
>>> data = Table("iris")
|
||||
>>> randomizer = Randomize(Randomize.RandomizeClasses)
|
||||
>>> randomized_data = randomizer(data)
|
||||
"""
|
||||
Type = Enum("Randomize",
|
||||
dict(RandomizeClasses=1,
|
||||
RandomizeAttributes=2,
|
||||
RandomizeMetas=4),
|
||||
type=int,
|
||||
qualname="Randomize.Type")
|
||||
RandomizeClasses, RandomizeAttributes, RandomizeMetas = Type
|
||||
|
||||
def __init__(self, rand_type=RandomizeClasses, rand_seed=None):
|
||||
self.rand_type = rand_type
|
||||
self.rand_seed = rand_seed
|
||||
|
||||
def __call__(self, data):
|
||||
"""
|
||||
Apply randomization of the given data. Returns a new
|
||||
data table.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
data : Orange.data.Table
|
||||
A data table to be randomized.
|
||||
|
||||
Returns
|
||||
-------
|
||||
data : Orange.data.Table
|
||||
Randomized data table.
|
||||
"""
|
||||
new_data = data.copy()
|
||||
rstate = np.random.RandomState(self.rand_seed)
|
||||
# ensure the same seed is not used to shuffle X and Y at the same time
|
||||
r1, r2, r3 = rstate.randint(0, 2 ** 32 - 1, size=3, dtype=np.int64)
|
||||
if self.rand_type & Randomize.RandomizeClasses:
|
||||
new_data.Y = self.randomize(new_data.Y, r1)
|
||||
if self.rand_type & Randomize.RandomizeAttributes:
|
||||
new_data.X = self.randomize(new_data.X, r2)
|
||||
if self.rand_type & Randomize.RandomizeMetas:
|
||||
new_data.metas = self.randomize(new_data.metas, r3)
|
||||
return new_data
|
||||
|
||||
@staticmethod
|
||||
def randomize(table, rand_state=None):
|
||||
rstate = np.random.RandomState(rand_state)
|
||||
if sp.issparse(table):
|
||||
table = table.tocsc() # type: sp.spmatrix
|
||||
for i in range(table.shape[1]):
|
||||
permutation = rstate.permutation(table.shape[0])
|
||||
col_indices = \
|
||||
table.indices[table.indptr[i]: table.indptr[i + 1]]
|
||||
col_indices[:] = permutation[col_indices]
|
||||
elif len(table.shape) > 1:
|
||||
for i in range(table.shape[1]):
|
||||
rstate.shuffle(table[:, i])
|
||||
else:
|
||||
rstate.shuffle(table)
|
||||
return table
|
||||
|
||||
|
||||
class ProjectPCA(Preprocess):
|
||||
|
||||
def __init__(self, n_components=None):
|
||||
self.n_components = n_components
|
||||
|
||||
def __call__(self, data):
|
||||
pca = Orange.projection.PCA(n_components=self.n_components)(data)
|
||||
return pca(data)
|
||||
|
||||
|
||||
class ProjectCUR(Preprocess):
|
||||
|
||||
def __init__(self, rank=3, max_error=1):
|
||||
self.rank = rank
|
||||
self.max_error = max_error
|
||||
|
||||
def __call__(self, data):
|
||||
rank = min(self.rank, min(data.X.shape)-1)
|
||||
cur = Orange.projection.CUR(
|
||||
rank=rank, max_error=self.max_error,
|
||||
compute_U=False,
|
||||
)(data)
|
||||
return cur(data)
|
||||
|
||||
|
||||
class Scale(Preprocess):
|
||||
"""
|
||||
Scale data preprocessor. Scales data so that its distribution remains
|
||||
the same but its location on the axis changes.
|
||||
"""
|
||||
class _MethodEnum(Enum):
|
||||
def __call__(self, *args, **kwargs):
|
||||
return getattr(Scale, '_' + self.name)(*args, **kwargs)
|
||||
|
||||
CenteringType = _MethodEnum("Scale", ("NoCentering", "Mean", "Median"),
|
||||
qualname="Scale.CenteringType")
|
||||
ScalingType = _MethodEnum("Scale", ("NoScaling", "Std", "Span"),
|
||||
qualname="Scale.ScalingType")
|
||||
NoCentering, Mean, Median = CenteringType
|
||||
NoScaling, Std, Span = ScalingType
|
||||
|
||||
@staticmethod
|
||||
def _Mean(dist):
|
||||
values, counts = np.array(dist)
|
||||
return np.average(values, weights=counts)
|
||||
|
||||
@staticmethod
|
||||
def _Median(dist):
|
||||
values, counts = np.array(dist)
|
||||
cumdist = np.cumsum(counts)
|
||||
if cumdist[-1] > 0:
|
||||
cumdist /= cumdist[-1]
|
||||
return np.interp(.5, cumdist, values)
|
||||
|
||||
@staticmethod
|
||||
def _Std(dist):
|
||||
values, counts = np.array(dist)
|
||||
mean = np.average(values, weights=counts)
|
||||
diff = values - mean
|
||||
return np.sqrt(np.average(diff ** 2, weights=counts))
|
||||
|
||||
@staticmethod
|
||||
def _Span(dist):
|
||||
values = np.array(dist[0])
|
||||
return np.max(values) - np.min(values)
|
||||
|
||||
def __init__(self, center=Mean, scale=Std):
|
||||
self.center = center
|
||||
self.scale = scale
|
||||
|
||||
def __call__(self, data):
|
||||
if self.center is None and self.scale is None:
|
||||
return data
|
||||
|
||||
def transform(var):
|
||||
dist = distribution.get_distribution(data, var)
|
||||
if self.center != self.NoCentering:
|
||||
c = self.center(dist)
|
||||
dist[0, :] -= c
|
||||
else:
|
||||
c = 0
|
||||
|
||||
if self.scale != self.NoScaling:
|
||||
s = self.scale(dist)
|
||||
if s < 1e-15:
|
||||
s = 1
|
||||
else:
|
||||
s = 1
|
||||
factor = 1 / s
|
||||
transformed_var = var.copy(
|
||||
compute_value=transformation.Normalizer(var, c, factor))
|
||||
return transformed_var
|
||||
|
||||
newvars = []
|
||||
for var in data.domain.attributes:
|
||||
if var.is_continuous:
|
||||
newvars.append(transform(var))
|
||||
else:
|
||||
newvars.append(var)
|
||||
domain = Orange.data.Domain(newvars, data.domain.class_vars,
|
||||
data.domain.metas)
|
||||
return data.transform(domain)
|
||||
|
||||
|
||||
class PreprocessorList(Preprocess):
|
||||
"""
|
||||
Store a list of preprocessors and on call apply them to the dataset.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
preprocessors : list
|
||||
A list of preprocessors.
|
||||
"""
|
||||
|
||||
def __init__(self, preprocessors=()):
|
||||
self.preprocessors = list(preprocessors)
|
||||
|
||||
def __call__(self, data):
|
||||
"""
|
||||
Applies a list of preprocessors to the dataset.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
data : an input data table
|
||||
"""
|
||||
|
||||
for pp in self.preprocessors:
|
||||
data = pp(data)
|
||||
return data
|
||||
|
||||
class RemoveSparse(Preprocess):
|
||||
"""
|
||||
Remove sparse features. Sparseness is determined according to
|
||||
user-defined treshold.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
threshold : float
|
||||
Minimal proportion of non-zero entries of a feature
|
||||
"""
|
||||
|
||||
def __init__(self, threshold=0.05):
|
||||
self.threshold = threshold
|
||||
|
||||
def __call__(self, data):
|
||||
if sp.issparse(data.X):
|
||||
data_csc = sp.csc_matrix(data.X)
|
||||
h, w = data_csc.shape
|
||||
sparsness = [data_csc[:, i].count_nonzero() / h for i in range(w)]
|
||||
else:
|
||||
sparsness = np.count_nonzero(data.X, axis=0) / data.X.shape[0]
|
||||
att = [a for a, s in zip(data.domain.attributes, sparsness) if s >= self.threshold]
|
||||
domain = Orange.data.Domain(att, data.domain.class_vars,
|
||||
data.domain.metas)
|
||||
return data.transform(domain)
|
||||
|
||||
|
||||
class AdaptiveNormalize(Preprocess):
|
||||
"""
|
||||
Construct a preprocessors that normalizes or merely scales the data.
|
||||
If the input is sparse, data is only scaled, to avoid turning it to
|
||||
dense. Parameters are diveded to those passed to Normalize or Scale
|
||||
class. Scaling takes only scale parameter.
|
||||
If the user wants to have more options with scaling,
|
||||
they should use the preprocessing widget.
|
||||
For more details, check Scale and Normalize widget.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
|
||||
zero_based : bool (default=True)
|
||||
passed to Normalize
|
||||
|
||||
norm_type : NormTypes (default: Normalize.NormalizeBySD)
|
||||
passed to Normalize
|
||||
|
||||
transform_class : bool (default=False)
|
||||
passed to Normalize
|
||||
|
||||
center : bool(default=True)
|
||||
passed to Normalize
|
||||
|
||||
normalize_datetime : bool (default=False)
|
||||
passed to Normalize
|
||||
|
||||
scale : ScaleTypes (default: Scale.Span)
|
||||
passed to Scale
|
||||
"""
|
||||
|
||||
def __init__(self,
|
||||
zero_based=True,
|
||||
norm_type=Normalize.NormalizeBySD,
|
||||
transform_class=False,
|
||||
normalize_datetime=False,
|
||||
center=True,
|
||||
scale=Scale.Span):
|
||||
self.normalize_pps = Normalize(zero_based,
|
||||
norm_type,
|
||||
transform_class,
|
||||
center,
|
||||
normalize_datetime)
|
||||
self.scale_pps = Scale(center=Scale.NoCentering, scale=scale)
|
||||
|
||||
def __call__(self, data):
|
||||
if sp.issparse(data.X):
|
||||
return self.scale_pps(data)
|
||||
return self.normalize_pps(data)
|
||||
0
pyminer/features/preprocess/tests/__init__.py
Normal file
0
pyminer/features/preprocess/tests/__init__.py
Normal file
Some files were not shown because too many files have changed in this diff Show More
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Reference in New Issue
Block a user