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README
LGPL-3.0

简介

数据工作流设计器,这个软件的设计目标是实现工作流驱动数据的ETL,集成panda的数据处理能力,实现高效的交互式数据可视化以及能固定输出论文级别的图片,软件主要分三大块:work flow、data、chart,三大板块的关系如下图所示:

about-data-work-flow

软件的设计初衷:

在数据处理过程往往有很多重复性的工作,尤其针对科研实验数据,有可能要面对n组数据,每组数据的清洗抽取方式基本是一样的,因此我希望一个数据处理软件应该是带有工作流功能的,当然python是很容易实现上述功能,但要求有一定的开发基础且要熟悉一些库才能得心应手

另外通过python进行数据处理过程,很多功能是隐藏的,panda有那么多种数据清洗方法,除非你把整个文档浏览一遍,否则你很难想起他们,因此一个交互式的数据清洗工具是很有必要的,把功能通过GUI明确的展现给用户,这样数据处理过程不需要长时间的翻阅文档

最后也是我用matlab和python这类数据处理工具最头疼的一点,就是数据可视化,虽然matlab和python能做出很漂亮的图,但细微的调节非常令人抓狂,例如要调整一个文本的位置,交互式的设计你只需要拖动一下鼠标,但在脚本语言里你要指定它的坐标,如果图片非常大,渲染时间比较久,那么移动一个文本到你想要的地方是一件令人非常抓狂的事情,而且matlab或者matplotlib的数据可视化函数有多有细,每次操作都要查阅半天文档,这是另人非常苦恼的事情。

本软件的设计就是为了解决上面遇到的这三个问题,因此软件会分为三大板块:工作流解决固定流程问题,数据处理板块会把pandas的功能进行集成,chart板块能实现交互式的数据可视化,且能生成论文级别的图片

软件界面截图:

更新于2022年9月

编译

编译前请确保已经拉取了第三方库,由于使用的是git submodule方式管理大部分第三方库,因此需要执行:

git submodule update --init --recursive

把所有第三方库拉取

bin目录

DA项目编译好的二进制文件统一生成到bin_qt$$[QT_VERSION]{msvc/mingw}{debug/release}{/_64}目录下,如:使用qt5.14.2, msvc版本debug模式64位编译,将生成bin_qt5.14.2_msvc_debug_64文件夹,common.pri文件定义了DA项目的目录内容:

# DA_BIN_DIR为生成的bin文件夹 ./bin_qt$$[QT_VERSION]_{msvc/mingw}_{debug/release}{/_64}
# DA_SRC_DIR为源代码路径:./src
DA_3RD_PARTY_DIR = $${DA_SRC_DIR}/3rdparty # 第三方库路径
BIN_APP_BUILD_DIR = $${DA_BIN_DIR}/build_apps # 生成的app路径
BIN_LIB_BUILD_DIR = $${DA_BIN_DIR}/build_libs # 生成的lib路径
BIN_TEST_BUILD_DIR = $${DA_BIN_DIR}/build_tst # 生成的测试程序路径
BIN_PLUGIN_BUILD_DIR = $${DA_BIN_DIR}/build_plugins # 生成的plugin路径
BIN_PLUGIN_DIR = $${DA_BIN_DIR}/plugins #插件的路径
BIN_TEST_DIR = $${DA_BIN_DIR}/tst #测试程序路径

bin_xx目录下的build_libs将是构建的库所在目录,也是第三方库需要放置的目录,下面先讲如何编译第三方库

第三方库编译

首先需要编译第三方库,第三方库位于src/3rdparty, 第三方库使用git submodule形式进行管理,因此第三方库需要在根目录下(存在.gitmodules的目录)执行下面语句对第三方库进行拉取

git submodule update --init --recursive

用Qt Creator 打开src/3rdparty/3rdparty.pro对第三方库进行编译

编译完第三方库后,需要手动把第三方库编译的结果(.a/.lib文件)移动到bin_xx/build_libs文件夹下,把编译的*.dll文件移动到bin_xx目录下

qwt和Qt-Advanced-Docking-System的编译结果是在build文件夹下,SARibbon会在本程序目录下建立一个bin_xx目录,在查找生成的lib时需要注意,ctk会自动把生成的dll和lib转移到对应的文件夹,无需手动移动

需要编译的第三方库如下:

SARibbon

用qt creator 打开./src/3rdparty/SARibbon/SARibbon.pro进行编译

编译完成后会把./src/3rdparty/SARibbon/bin_xx目录下的*.lib / *.a文件拷贝到bin_xx目录下的build_libs文件夹下,把dll文件拷贝到bin_xx目录下

Qt-Advanced-Docking-System

用qt creator 打开./src/3rdparty/Qt-Advanced-Docking-System/ads.pro进行编译

编译完成后的二进制文件会在./src/build-3rdparty-Desktop_Qtxx下的Qt-Advanced-Docking-System里,用户根据自己定义的情况查找,找到其lib文件夹下的lib文件和dll文件复制到build_libs文件夹和bin_xx目录下

ctk

本程序使用的ctk是简化版ctk,仅抽取了使用到的几个类,因此称为liteCtk

用qt creator 打开./src/3rdparty/ctk/ctk.pro进行编译

此库已经自动配置编译lib和dll的位置,无需手动移动

qwt

在build目录下找到qwt编译好的dll和lib文件,把lib文件拷贝到bin_xx目录下的build_libs文件夹下,把dll文件拷贝到bin_xx目录下

python环境配置

DA依赖python环境:

  • 至少是python3.7
  • python环境需要安装pandas库

把安装好pandas库的python环境整体拷贝到bin_xx目录下,并重命名为Python,DA默认的python搜索路径就是程序运行目录下的Python文件夹,另外需要把./src/PyScripts文件夹拷贝到bin_xx目录下,这是DA的固定脚本内容

如果遇到如下错误,说明你缺少Python环境设置的环节,请确保已经配置好Python环境

你要保证bin_xx目录下有Python环境,如下图所示

Python目录内部如下图所示

如果用其他版本的Python,也需要配置./src/python_lib.pri文件

把DA_PYTHON设置为对应的python版本:

如python3.7则设置为:

DA_PYTHON = python37

编译程序

用Qt Creator 打开./src/DataWorkFlow.pro进行编译,编译过程会自动把文件编译到bin_xx目录下

程序框架

1.插件与接口

2.可缩放图元模块

3.工作流模块

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简介

以Qt(C++)和python混合编写的数据处理软件,以工作流为基础,实现数据的导入、清洗、分析、绘图、导出等功能,内部主要对pandas进行了封装,实现pandas内置函数的大部分功能,以不懂python得人也可以非常方便的使用pandas功能,同时利用Qt自身绘图能力实现数据的绘图(暂时不上用matplotlib而是用C++的QCustomerPlot) 展开 收起
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