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Data visualization is crucial for effective communication of complex information. Chart libraries simplify chart creation with customizable templates, helping users create visually appealing and informative charts effortlessly. The goal of this project is to add missing statistical charts to Roassal3, Pharo's agile visualization engine. These charts would enable researchers, individuals and businesses to focus more on analyzing data and less on how to build a data visualization.

<p>The current shader framework for fury is based on VTK and lacks documentation to get started which can be overwhelming for new users . The objective of this project is to enable users to be easily able to understand and use the shader framework to render stunning visual representations of data. The project involves programming vertex and fragment shaders to generate effects for more immersive visualization .</p>

<p>Bringing the functionality of Pandas to Pharo</p>

The goal of the proposal is to implement bindings for C++ based Elastica++ to the python based PyElastica, to achieve speedups. It covers selecting a suitable C++ build system and setting up the compilation architecture, writing binding code using pybind11 or alternative methods, benchmarking against existing Python implementations, expanding unit tests, polishing documentation and typestubs, and updating the CI pipeline for building and testing on multiple Python versions.

<p>4D STEM data in datasets can be stored with different shapes as different representations may be possible depending on the application. For example, data is sometimes stored with a 3D shape as some software for crystallography expects data stored in 3D and currently, LiberTEM’s GUI is limited to 4D datasets. Some datasets with synchronisation/acquisition problems also require specifying the offset. The proposed project aims to enhance LiberTEM’s data pipeline by supporting reshaping of datasets in the GUI which would provide its users with more flexibility to load and perform analyses of multidimensional data.</p>

<p>This will be a continuation of the previous summer’s <strong>Outliner Improvements</strong> project. With selection now syncing between the outliner and other editors, other improvements can be made to the outliner to increase usability. These include changes to the context menu, a connection with the properties editor tabs, manual object sorting, and increased control over selection and activation of data types.</p>

This proposal aims to develop an information theoretic approach to filter out artificial information from real information in geospatial datasets. The project will use the bitinformation framework to distinguish between real and false information, where real information is defined as the mutual information between adjacent bits. The proposed algorithm will filter out artificial information, which is a consequence of prior compression, from real information, which reflects the underlying signal. The project will involve a theoretical review, test case generation, algorithm development, evaluation, and integration into xbitinfo, a software package that implements the bitinformation framework. The resulting artificial information filter will provide a valuable tool for users who may not have access to high-precision/uncompressed data, and it will enhance the accuracy and reliability of geospatial data analysis. As a participant in the Google Summer of Code, I am excited about the opportunity to work on this project and contribute to the development of an open-source software tool that will benefit the scientific community.

The objective of this project is to enhance the distributed rendering and task execution capabilities within Blender through several key improvements. Firstly, we introduce the ability to pause jobs and submit them in a paused state, providing users with increased control over their rendering workflow and resource allocation. This feature will be particularly advantageous during peak usage periods or when prioritizing specific tasks. Furthermore, we address the challenge of distributed rendering of single images by adopting a sample-based rendering approach. This method ensures more efficient utilization of computational resources across nodes, minimizing memory usage and avoiding artifacts caused by boundary dependencies.

This project aims to enhance the FURY documentation experience by making it more reliable, accessible, and visually engaging for both users and developers. Currently, the documentation build process generates multiple warnings, some tutorials fail to produce static images consistently, animated tutorials are not natively supported, and parts of the website layout can be improved for better usability. To address these issues, I plan to streamline the documentation build pipeline by resolving existing warnings and improving the reliability of tutorial image generation. I will also introduce native GIF support to enable animated tutorials and interactive visual examples. In addition, I will redesign key parts of the documentation website’s UI/UX to improve readability, navigation, and overall user experience. The key deliverables of this project include a clean and warning-free documentation build process, robust static image generation for tutorials, native support for GIF-based animated examples, and a refreshed documentation interface that makes FURY easier to learn, explore, and contribute to.

<h5>coala website and coala-html</h5> <p><em>coala-html</em> is a console application used to display results from coala-json as an interactive web page. Prototype is available at <a href="https://github.com/coala-analyzer/coala-html/tree/tushar-rishav" target="_blank">Github</a>.</p> <p><em>coala website</em> a main website for coala with coala demo integrated. It’d be written from scratch with improved UI and features.</p> <p>Proposed features are:</p> <ul> <li>coala-html<ul> <li>Improve UI for Logs and Results by implementing Material Design.</li> <li>Implement better search feature. Create a Fuzzy Search module.</li> <li>Add UnitTest</li> </ul> </li> <li>coala-website<ul> <li>Implement a demo of coala within coala website allowing users to run coala on their code snippet from within their web browser.</li> <li>Available at <a href="https://gitlab.com/coala/website" target="_blank">Gitlab</a></li> </ul> </li> </ul>

<p>The Project aims to improve the output of the cve-bin-tool. Currently, we are having a very basic console logging and output. I'll add colourized output and logging to improve readability. CVE Binary tool provides us with an option to generate CSV, JSON output but both are not easily human-readable formats. So, I'll add a feature to generate single page HTML Reports which will be human-readable and will provide the user with much additional information like Total Scanned Files, Total Products with known vulnerability and severity analysis for each product. The report will also have a feature to search for data easily and due to the single page nature, it can be shared easily. Mostly, my work is related to OutputEngine but there are other smaller issues that needs to be solved.</p>

This project aims at bridging the gap between popular DataFrames and the Pharo DataFrame. This can be done by adding more functionality to the Pharo DataFrame. The DataFrame API in Pharo will be improved by fixing existing features and adding new ones. This project also aims to make the Pharo AI DataFrame Inspector interactive. This will be achieved by enabling users to perform operations such as editing, searching, sorting, etc., directly from within the DataFrame Inspector itself.

<p>The Aim of this Project is to create and implement an algorithm that figures out the right indentation for as many programming languages as possible. The implementation must be configurable for different projects and must address features like indents based on <code>keywords</code>, <code>Hanging Indents</code> and creating new lines when the length of the line is too long .</p>

The aim of this project is to extend LPython's OOP capabilities to enable the porting of CPython modules. The proposal is divided into three main parts: improving the utility of classes in LPython using general imports and dunder methods, porting CPython's re and json modules and addressing some miscellaneous goals like adding advanced data structures and improving string attributes.

<p>The main goal of the proposed project is to create the frontend part of a JPEG encoder which will be implemented in MyHDL. The frontend part consists of the color-space converter, the 2D DCT, the top-level FSM, and the input buffer. Based on a reference design, the final implementation in MyHDL will provide a more modular and scalable design. Throughout the project, will be developed all the required unit tests to prove the correct functionality of each block of the frontend part of the encoder while keeping in mind not only to verify the correct behavior of the design but also to produce synthesizable VHDL/Verilog code. The ideal goal would be to create a fully working JPEG encoder by combining the frontend and the backend part of the encoder written in MyHDL and implement the converted code in a FPGA board in order to measure some metrics like resource utilization and performance.</p>

<p>For the project I propose working on creating a base class for the equations of motion generators in the physics module of the sympy library and add a Newton-Euler equation of motion generator. The benefits of creating a base class for equations of motion generators would include ease of adding additional equations of motion generators and making the code more compact and so speed enhancements and bug fixes will affect all generators simultaneously rather than having to be implemented on a per generator basis. In addition to this work I would also be working on increasing the speed/efficiency of the existing python code for the equations of motion generators since I will already be digging into their base functionality.</p>

<p>When astronauts travels to Mars, or even other planets, they will be exposed to a number of hazards e.g. radiation, microbes in the spacecraft, planetary surface toxic dust. This project mainly revolves around configuring biometric signal sensors.</p> <p>The project has an initial phase of surveying the commercial sensors available, and selecting one, or many, after extensive research. The sensors are selected such that they read the biometrics like Heart Rate, Accelerometer data, Respiration rate, body temperature, Pulsioximetry data,Respiratory Volume, ECG, etc.</p> <p>The second phase involves developing the Device Server itself in Tango, for these selected sensors. This project is part of the current studies on the simulation of Astronaut’s Health Monitor Systems.</p>

MNE-Python’s documentation is extensive but primarily static, requiring local installation for users to explore data. This project aims to integrate JupyterLite into the sphinx-gallery build, enabling a "Try in Browser" feature for core tutorials. Key challenges include managing large neuroimaging datasets in a WebAssembly environment and maintaining 3D interactivity (PyVista/Trame). I will deliver a production-ready CI/CD pipeline for JupyterLite builds, a prioritized set of interactive lightweight examples, and a library of ipywidgets for real-time parameter tuning (e.g., filtering, scaling) directly in the documentation.

<p>The proposed project is to create a set of Python based tools for easier and efficient creation of Hypermedia driven REST-APIs.</p> <p>The other part is an application that simulates the movements of a flock of drones that have as objective to detect the presence of fires or abnormal heat spots in a given geographical area using an infrared sensors to demonstrate the capabilities of Hydrus and the Hydra Draft.</p>

<ul> <li>Improving Guillotina API by making it more compliant to JSON-LD.</li> <li>Implementing WebSocket endpoint for all the API functionalities </li> <li>JSON validation for all the payloads by well-defined JSON schemas.</li> <li>Updating swagger documentation.</li> <li>Versioning of API by adding a version number to the endpoint URLs.</li> <li>And writing kubernetes configurations along with helm charts for Guillotina.</li> </ul>

Increase in amount of recording sensors in EEG, MEG and iEEG has brought about a need in new approaches for analysis of the data. Such approaches include source separation and decoding. This project is aimed at (1) implementing a supervised source separation technique called generalised eigendecomposition (GED) with accompanying visualisations, (2) refactoring, modernising and enhancing the implementation of decoding classes already implemented in MNE-Python.

<p>pip does not resolve dependencies correctly when there are conflicting requirements. The lack of dependency resolution has caused hard-to-diagnose bugs/failures due to the installation of incompatible packages. The lack of proper dependency resolution is also a blocker for various other features - adding an upgrade-all functionality to pip and properly determining build-time dependencies for packages are two such features.</p> <p>This project would resolve this issue by implementing a backtracking dependency resolver in pip; refactoring a critical component of pip's codebase in the process.</p>

<p>The GTK client (Tryton) already has CSV Import/Export feature. This project would implement the same feature in web client (SAO) keeping the behavior similar.</p>