5.6 KiB
5.6 KiB
SolarLytics Requirements
Functional Requirements
UML Diagram
Main diagram describing the process of the complete project:
The individual processing steps of the different datasets are shown here in more detail:
Non-functional Requirements
Must Have
- Compatibility: The workflow must run on Windows and Mac OS. It should be easy to deploy and run in different environments.
- Documentation: The documentation is for users and developers and must be available, including metadata, license information, a read-me file, and citation as well as contributing guidelines.
- Reproducibility: The workflow must be reproducible.
- Testability: The code must be well tested, with unit and integration tests in place.
Should Have
- Performance: The workflow should able to process the datasets in a reasonable time.
- Maintainability: The code should be well modularized and organized, following the standard template and PEP 8 guidelines. It should be refactured regularily.
- Easy-to-Use: The workflow should provide a easy user experience
Could Have
- Accessibility: The documentation could be translated to German.
- Presentation: The workflow could have a visual support in the form of graphics.
Won't Have
- Add-ons: Function for other countries.
Component Analysis
| Abstract Workflow Node (Operation) | Input(s) | Output(s) | Implementation |
|---|---|---|---|
| photovoltaic data processing | |||
| load and clean photovoltaics data | original dataset (.csv) from destatis | dataframe (.csv) | CLI tool built on pandas |
| trim photovoltaic | dataframe (.csv) | dataframe(.csv) | CLI tool built on pandas |
| collapse columns photovoltaic | dataframe (.csv) | dataframe (.csv) | CLI tool built on pandas |
| sunshine duration data processing | |||
| load sunshine duration data | DWD Website | sunshine duration data (.txt), one file for each month | CLI tool built on requests, os, bs4 and urllib |
| merge series | 12 sunshine duration datasets (.txt) | processed dataframe (.csv) | CLI tool built on pandas |
| collapse columns sunshine duration | dataframe (.csv) | dataframe (.csv) | CLI tool built on pandas |
| trim sunshine duration | dataframe (.csv) | dataframe (.csv) | CLI tool built on pandas |
| solarparc data processing | |||
| load solarparc data and border data | OverpassAPI | .gpkg file (solarparc / border) | CLI http request over OverpassAPI, osmium, geopandas, shapely |
| calculate area | .gpkg file | .txt with report | CLI tool built on geopandas |
| analysis | |||
| calculate theoretical energy | calculate area (.txt) & sunshine duration dataframe (.csv) | dataframe (.csv) | CLI tool built on pandas |
| collapse columns theoretical energy | dataframe (.csv) | dataframe (.csv) | CLI tool built on pandas |
| trim theoreticalenergy | dataframe (.csv) | energy differnce dataframe (.csv) | CLI tool built in pandas |
| calculate difference | theoritcal energy (.csv) & photovoltaic energy (.csv) | dataframe .csv | CLI tool built on pandas |
| plot energy difference | ernergy difference (.csv) | diagram over years (.png) | CLI tool built on matplotlib and pandas |
| plot yearly energy change | dataframe (.csv) | diagram over years (.png) | CLI tool built on matplotlib and pandas |
| plot solarparc map | .gpkg file (solarparc / border) | plot of germany (.png) | CLI tool built on matplotlib and geopandas |
| plot yearly change sunshine | dataframe (.csv) | diagram over years (.png) | CLI tool built on matplotlib and pandas |
| plot yearly change photovoltaic | dataframe (.csv) | diagram over years (.png) | CLI tool built on matplotlib and pandas |
| plot monthly change potovoltaic | dataframe (.csv) | diagram over months (.png) | CLI tool built on matplotlib and pandas |
| generate report | mutiple inputs (.txt, .png) | slides (.md) | built on markdown |