thoth-tech · CchristiNana · Dec 8, 2023 · Dec 8, 2023 · Dec 11, 2023 · Dec 12, 2023
diff --git a/astro.config.mjs b/astro.config.mjs
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@@ -17,6 +17,7 @@
     "@astrojs/netlify": "^3.0.0",
     "@astrojs/starlight": "^0.13.0",
     "astro": "^3.6.0",
+    "prettier": "^3.1.1",
     "sharp": "^0.32.3",
     "starlight": "^0.3.9",
     "starlight-blog": "^0.4.0"

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diff --git a/...kit/Documentation/API Expansion/Modules/Data Analytics/Background/Background.md b/...kit/Documentation/API Expansion/Modules/Data Analytics/Background/Background.md
@@ -0,0 +1,21 @@
+---
+title: Data Analytics Code Repositories
+---
+
+The code received for Trimester 1, 2022 was not pulled into the Thoth Tech repository at the
+completion of Trimester 3, 2021. All future links to Data Analytics code either within the Thoth
+Tech repository or in separated forked repositories will be located within this document.
+
+## Links to code
+
+Please add your fork to this list, labelled appropriately, if work is incomplete but ongoing at the
+end of the semester.
+
+- [End of 2021 Repository - Contains Broken/Missing Imports](https://bitbucket-students.deakin.edu.au/users/zbargiamidis/repos/splashkit2021t3/browse/coresdk/src/coresdk)
+- [T2 2021 Plan for Scope](https://bitbucket-students.deakin.edu.au/users/zbargiamidis/repos/splashkit2021t3/browse/T2%20Development%20Plan)
+- [T1 2022 Data Analytics Code Refactor data_analytics.cpp](https://github.com/lawrence0arabia/splashkit-core/tree/develop/coresdk/src/coresdk/data_analytics.cpp)
+- [T1 2022 Data Analytics Code Refactor data_analytics.h](https://github.com/lawrence0arabia/splashkit-core/tree/develop/coresdk/src/coresdk/data_analytics.h)
+- [T1 2022 Implementation of Test Showcase](https://github.com/lawrence0arabia/splashkit-core/tree/develop/coresdk/src/test/test_data_analytics.cpp)
+- [T1 2022 Implementation of Unit Tests](https://github.com/lawrence0arabia/splashkit-core/tree/develop/coresdk/src/test/unit_tests/unit_test_data_analytics.cpp)
+
+---
diff --git a/...umentation/API Expansion/Modules/Data Analytics/Background/Code Repositories.md b/...umentation/API Expansion/Modules/Data Analytics/Background/Code Repositories.md
@@ -0,0 +1,21 @@
+---
+title: Data Analytics Code Repositories
+---
+
+The code received for Trimester 1, 2022 was not pulled into the Thoth Tech repository at the
+completion of Trimester 3, 2021. All future links to Data Analytics code either within the Thoth
+Tech repository or in separated forked repositories will be located within this document.
+
+## Links to code
+
+Please add your fork to this list, labelled appropriately, if work is incomplete but ongoing at the
+end of the semester.
+
+- [End of 2021 Repository - Contains Broken/Missing Imports](https://bitbucket-students.deakin.edu.au/users/zbargiamidis/repos/splashkit2021t3/browse/coresdk/src/coresdk)
+- [T2 2021 Plan for Scope](https://bitbucket-students.deakin.edu.au/users/zbargiamidis/repos/splashkit2021t3/browse/T2%20Development%20Plan)
+- [T1 2022 Data Analytics Code Refactor data_analytics.cpp](https://github.com/lawrence0arabia/splashkit-core/tree/develop/coresdk/src/coresdk/data_analytics.cpp)
+- [T1 2022 Data Analytics Code Refactor data_analytics.h](https://github.com/lawrence0arabia/splashkit-core/tree/develop/coresdk/src/coresdk/data_analytics.h)
+- [T1 2022 Implementation of Test Showcase](https://github.com/lawrence0arabia/splashkit-core/tree/develop/coresdk/src/test/test_data_analytics.cpp)
+- [T1 2022 Implementation of Unit Tests](https://github.com/lawrence0arabia/splashkit-core/tree/develop/coresdk/src/test/unit_tests/unit_test_data_analytics.cpp)
+
+---
diff --git a/...splashkit/Documentation/API Expansion/Modules/Data Analytics/Background/Epic.md b/...splashkit/Documentation/API Expansion/Modules/Data Analytics/Background/Epic.md
@@ -0,0 +1,66 @@
+---
+title: Data Analytics Epic
+---
+
+## Background / Context
+
+SplashKit is a live product, which can be improved as per valid suggestions and observations. The
+addition of Data Analytics is one of the recognised areas for improvement.
+
+## Business Value
+
+The addition of Data Analytics into SplashKit enables more focused classes to be designed for data
+science students, rather than only using SplashKit for building games.
+
+## In Scope
+
+- SplashKit Core SDK (program code for the feature)
+- SplashKit.io (articles on usage of the feature)
+
+## Out of Scope
+
+- SplashKit Translator
+- SKM
+
+## What needs to happen
+
+- Review the code from previous trimesters to determine if any of the existing data frames code can
+  be reused
+- Re-create the expected functionality of data frames, including capabilities to perform the loading
+  of structured data, multiple data types, data modification and cleaning, standardisation,
+  transformation, feature selection, feature extraction, and descriptive statistics
+- Expand the functionality so that the user can visualise data with customizable parameters through
+  pie-charts, bar graphs, etc. (potentially through the existing SplashKit drawing modules)
+- Produce documentation for the usage of the module
+- Assess the potential for integration with the machine learning module
+
+## Assumptions / Dependencies
+
+- Everything is customizable by the user (for example, the colours in visualisations)
+- Previous contribution code is accessible and working
+
+## UX/UI Considerations
+
+N/A
+
+## Analytics Considerations
+
+None known
+
+## Regulation & Compliance Considerations
+
+N/A
+
+## Operations / Support / Training Considerations
+
+- Team members must become familiar with SplashKit, C++, Ninja and CMake
+- Advise teams 2 weeks in advance of planned release
+
+## Acceptance criteria
+
+- Successful addition of being able to load, record, analyse, and visualize the correct data that is
+  desired by the users
+- Functional and passing QA
+- Easy to use (user acceptance testing completed)
+- Documentation completed for design decisions and work
+- Documentation fits current expectations as set by SplashKit.io and stakeholders
diff --git a/...ansion/Modules/Data Analytics/Background/Software_Requirements_Specification.md b/...ansion/Modules/Data Analytics/Background/Software_Requirements_Specification.md
@@ -0,0 +1,55 @@
+---
+title: Software Requirement Specification (SRS) Document Template
+---
+
+## 1. Introduction
+
+The purpose of Data Analytics module is to allowing users to load datasets from various file
+formats, then perform data manipulations and visualization for the goal of extracting useful
+insights from the dataset.
+
+### 1.1 Purpose
+
+The purpose of Data Analytics module is that it is a tool that allows users to import, create data
+visualisations, and use pre-written algorithms to perform statistical analysis of the data, and
+pre-process data for use in a machine learning model.
+
+### 1.2 Intended Audience
+
+The intended audience is Data Analysts, Machine Learning Engineers, and developers.
+
+### 1.3 Intended Use
+
+The intended use of this module is to create data visualisations and preprocess the data to be used
+in a machine learning model.
+
+### 1.4 Scope
+
+- Create dataframes by importing datasets. Adding and removing rows/columns in a dataset.
+- Changing data inside a dataset.
+- Preprocessing functionality for cleaning and standardising the dataframe for the goal of making it
+  fit to be used in a machine learning model.
+- Create data visualisations like bar graphs, histograms.
+
+### 1.5 Definitions and Acronyms
+
+- Dataset: A collection of data in tabular form. Files ending in comma separated values (.csv), tab
+  separated values (.tbv), Excel (.xlsx), test (.txt) file extension.
+- Dataframe: Representation of dataset as an object in the program which allows users to use method
+  calls to perform actions on the dataset.
+- Standardising: the process of converting data to a common format to enable users to process and
+  analyse it
+
+## Overall Description
+
+### 2.1 User Needs
+
+### 2.2 Assumptions and Dependencies
+
+## System Features and Requirements
+
+### 3.1 Functional Requirements
+
+### 3.2 External Interface Requirements
+
+### 3.3 Nonfunctional Requirements
diff --git a/.../products/splashkit/Documentation/API Expansion/Modules/Data Analytics/Index.md b/.../products/splashkit/Documentation/API Expansion/Modules/Data Analytics/Index.md
@@ -0,0 +1,15 @@
+---
+title: Data Analytics Module Index
+---
+
+Here you will find all resources for the Data Analytics module within the SplashKit project. This
+documentation is not only for onboarding purposes, but it keeps all team members and leaders up to
+date on progress, issues faced and future scope.
+
+## Links to SplashKit Modules Documentation
+
+- [Background](Background/Index.md)
+- [Research & Findings](Research%20&%20Findings/Index.md)
+- [Testing](Testing/Index.md)
+
+---
diff --git a/...nsion/Modules/Data Analytics/Research & Findings/Code_Status_2022_Semester_1.md b/...nsion/Modules/Data Analytics/Research & Findings/Code_Status_2022_Semester_1.md
@@ -0,0 +1,78 @@
+---
+title: Semester 1 2022 Data Analytics Update
+---
+
+## State Of Code Received
+
+There were a few roadblocks that halted progress through the data analytics module. Despite bug
+fixes being listed as commits from the 2021 code file, it appeared to have never ran. Poor coding
+practices were found throughout, including the following:
+
+- portable_files_dialog.h library not recognised, which could not be resolved
+  - It was a very unneccessary addition as it only ran in one method and was not used for similar
+    things in other methods
+- splashkit.h was called inside SplashKit, which broke the code and is something you definitely
+  should not do
+- Most imports required for the code were missing
+- Data validation code was lengthy and did not work
+  - A lot of true/false statements were switched, meaning it would never give a proper result
+  - Swapped between using poorly written Regex and making their own methods to do the same thing,
+    both did not work properly
+- Display function used import that was Windows operating system only
+  - Means you could not run the Data Analytics module from Mac or Linux
+  - Also was poorly written and we never got it working
+- Dataframe code looked impressive but without display function working, was hard to see if it was
+  working properly
+  - Ran out of time to test each individual method
+- Poor coding practices within DataFrame object
+  - Methods to scale window for no reason
+  - Bad calculations (+1 and -1 in the same line is redundant)
+
+This meant that instead of starting with Instance Selection and Data Visualisation, all our efforts
+had to go into code quality assurance.
+
+## Changes Made To Code
+
+The T3 2021 code required a full rewrite. Imports were fixed by removing and adding required ones
+Data validation functions have been rewritten to run. They will need to be re-worked into more
+robust objects.
+
+Dataframes code is not currently included in
+[T1 2022 repository](https://github.com/lawrence0arabia/splashkit-core/tree/develop/coresdk/src/coresdk/data_analytics.cpp)
+as it does not compile or run. You can find the dataframes code in the
+[T3 2021 repository](https://bitbucket-students.deakin.edu.au/users/zbargiamidis/repos/splashkit2021t3/browse),
+data_analytics.cpp from line 369 on.
+
+## Issues To Be Resolved
+
+- Review on whether string recognition is required.
+  - If yes, create dynamic objects for each item to be recognised
+    - Regex also needs to be improved
+    - Actioning this is not urgent, but course of action is
+  - If no, remove altogether, along with tests
+- Clean up Dataframes code line by line
+  - Superfluous code present, needs to be simplified
+    - Issues identified include:
+      - Reliance on Windows exclusive console functions, display function is littered with them.
+        STD_OUTPUT_HANDLE, GetConsoleScreenBufferInfo, hConsole, etc are all exclusive to windows,
+        need to make multi-platform. Would recommend trying to get it running on a Windows device
+        first just to make sure it does work before removing windows stuff. (It seems to be using
+        the windows exclusive functions to check the console window width before printing so it can
+        format the dataframe correctly. This feature is a nice-to-have, but Mac and Linux support
+        are MUST HAVES)
+      - Variable arrays, array size must be known at compile time in C++. This only seems to be an
+        issue for a couple of the insert functions in the dataframe code, so it is recommended to
+        comment them out for now and try get it working without them.
+      - Needs more comments and general simplification -- too hard to understand what the code is
+        doing.
+      - Code does not compile or run on Mac or Linux.
+  - Research Pandas Dataframes and review our current setup
+  - Add basic functions required for simple implementation
+- Create new display function
+  - Needs to work on all systems
+- Test Dataframe code
+  - As we do not think it has ever compiled or run, we need to determine that all functions and
+    objects work properly.
+    - If they do not: either refactor or begin to re-write code based on
+      [Scope documents](../Scope/Index.md).
+  - Tests will have to be created as none currently exist for the dataframes.
diff --git a/...sion/Modules/Data Analytics/Research & Findings/Data_Analytics_Scope_T1_2022.md b/...sion/Modules/Data Analytics/Research & Findings/Data_Analytics_Scope_T1_2022.md
@@ -0,0 +1,54 @@
+---
+title: Scope for Data Analytics Module
+---
+
+The scope for the data analytics module depends on the finalisation of reviews for the code.
+
+## Previous Scope
+
+### Completed
+
+These are things that were listed as completed, some of these things seem like they were never done
+but ticked off.
+
+- Functions to read in structural dataset
+  - Column by column indicated by the programmer/computer scientist
+  - Row by row indicated by the programmer/computer scientist
+- Data management design for the analysed datasets
+  - Dataframe
+- Data pre-processing capabilities
+  - Reading data from files
+  - Data cleaning
+
+### To Do
+
+#### 2022
+
+- Data pre-processing capabilities
+  - Instance selection
+  - Data standardization
+  - Data transformation
+  - Feature extraction and selection
+  - Create MATLAB-like clear data input space, load data, visualisation, statistics, plots, subplots
+
+#### Ongoing
+
+- 1 year: across two trimesters for data visualisation plotting framework – data distribution and
+  central tendencies – functions for plotting 2D plots and axes formatting.
+- 1.5 years: Incorporate with SplashKit - API - Input developed functions for handling inputs and
+  interactions esp. for window applications
+- 2 years: Incorporate with Machine Learning module
+- 2.5 years: Data visualisation
+
+## New Scope
+
+### If dataframes can be salvaged
+
+- Begin ensuring the completed work is there. If not, create cards in Trello for things to be
+  re-done.
+- Create Objects for data Validation, or remove and rebuild at correct stage in former scope.
+
+### If dataframes can not be salvaged
+
+- Begin the whole module again.
+- Estimate new times for completion based on skill level and research.