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<p>Dimensionality reduction techniques are useful methods that allow us to gain crucial insights about the given dataset. Unfortunately, such methods become computationally intensive when dealing with large scale dataset. To deal with complexity issues, one possible approach is to implement algorithms in a distributed fashion. Ideally, users of LiberTEM can benefit from implementation of these algorithms that they can run through a simple pipeline called User-defined functions, which allow the users to run functions with their desired functionality without having to worry about parallelization, which is done under the hood by LiberTEM. Therefore, my project will be concerning both the distributed implementation of a dimensionality reduction method as well as improving on the User-defined functions framework.</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>
Pharo is a powerful object-oriented programming language widely used in research and industry, as seen here. The graph algorithms library in PharoAI is a crucial resource for developers who work with graph data structures. The current graph algorithms library in PharoAI needs a redesign of APIs and the addition of different algorithms in the library. The goal of this project is to redesign the graph algorithms library in PharoAI by 1. Redesigning the current API using the standard API Practices 2. Incorporating graPharo Layout Algorithms into PharoAI graph algorithms 3. I also plan to incorporate new graph algorithms and layout techniques and Data Structures to improve the library's performance and functionality of current algorithms.
<p>This project is aimed to provide a fixed point compiler backend for the <code>fixbv</code> type defined in <a href="http://dev.myhdl.org/meps/mep-111.html" target="_blank">MEP-111</a> of MyHDL project.</p> <p>When the project finishes, MyHDL should have a complete implementation of <code>fixbv</code> and its compiler backend with complete documentation, include tutorials and reference.</p>
My proposed project aims to enhance the Borg ecosystem by tackling three main areas: Filter option in diff and extract view in Vorta, implement live binary tests in Vorta, and bootstrap a Borgmatic restore from nothing. These improvements will help users more efficiently and effectively manage their backups, improve testing processes, and facilitate disaster recovery. Firstly, I will implement a search function that allows users to filter files by search string in Vorta's diff and extract view. I will also add the "Change" filter to the comparison view, which will filter only removed, added, and modified files. This task also includes adding syntax to allow advanced filtering and filter by size range as a stretch goal. These enhancements will help users easily find and manage their backup files. Secondly, I will improve BorgBackup testing by implementing live binary tests in Vorta. Currently Vorta contains stdout and stderr mock files for the Borg JSON output of various commands for testing purposes but there’s no actual running of the commands. Moreover, it only supports one mock file while Vorta supports multiple Borg versions where output syntax may vary. This project aims to improve Vorta Testing by implementing live binary tests that run on multiple actual Borg versions/binaries. I'll also integrate live binary tests with Vorta's CI/CD pipeline. Finally, I will implement bootstrap functionality in Borgmatic to restore backups from nothing, enabling users to easily recover their data in the event of a disaster. I will implement this feature by providing clear and comprehensive documentation, which will outline the steps required to perform a Borgmatic restore from scratch. This will significantly improve disaster recovery capabilities and reduce the risk of data loss.
<p>This project aims at adding some missing functionalities in Pharo DataFrame. Implementing the missing features and functionality of Pandas DataFrame in the Pharo DataFrame namely, Addition of the dtype object and Addition of the DataFrame slicing feature. Add examples of applying the DataFrame and its new features to real problems of Data Science by using samples and Datasets into the official Pharo documentation .</p>
<p>Refactoring tools help pharo developers to perform a number of predefined refactorings in automated fashion. However, besides the options provided by Pharo, there is still some missing refactoring options and a list of open issues.</p> <p>The goal of this project is to improve the Pharo’s refactoring support by</p> <ul> <li>Adding three missing refactoring options: inline method, inline variable and find and replace duplicate code.</li> <li>Improving the usability of refactoring tools by adding: preview dialogs and shortcuts for a number of refactoring options, such as: extract method, extract temp, inline method.</li> <li>Improving the extract method refactoring option: checking for duplicated instances of the refactored code and letting the user specify arguments.</li> </ul>
Modernize fs_filepicker: The fs_filepicker is a GUI used for selecting files in the msui_settings.json configuration file. Currently, the GUI only offers a basic set of navigation elements for selecting a file and returns the fs URL for accessing it. The goal of this project is to modernize the GUI using the Pyfilesystem module to make it more user-friendly and efficient. Pyfilesystem is a Python module used for accessing different types of file systems. It provides a common API for working with various file systems, such as local, remote, and cloud-based storage systems. The Pyfilesystem module is easy to use and has many features that can be used to improve the functionality of the fs_filepicker. View Layout and Restoring:: The mscolab project is a collaborative software platform that enables multiple users to work together on a shared project in real-time. The project is written in Python and uses the PyQT GUI library for the user interface. Currently, the PyQT Gui of the MSS client can handle different views by one flight path. However, once a new flight path is loaded and activated, all views change to this flight path. This is inconvenient for users who want to work on multiple flight paths simultaneously. Additionally, the view configuration consists of many windows with a complex set of configuration options that are tedious to re-create after shutting down the application. This proposal aims to improve the mscolab user interface by adding the ability to store and restore the view configuration of multiple windows for the user. Additionally, the proposal seeks to add a layout option for any participant on the same flight path, as well as the ability for the creator of an operation to set the layout of all participants.
<p>Tern currently does not list the metadata of packages installed by different package managers. This project aims to enable this functionality in Tern. Also to increase the current test coverage of Tern by writing more Unit Tests.</p>
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.
<p>Currently, EOS delivers icons via a set of well-documented methods, which chiefly include EOS-Icons Package, CDN, or direct download of icons in SVG/PNG formats. This project will be based on developing an npm package that can deliver EOS Icons to its users as an independent component library and create a unified central system that will enable EOS to deliver its icons to various frameworks (e.g. React, Vue and Angular) independently. This npm package will be as lightweight as possible in order to reduce the load put on the browser (using the tree shaking approach), which will result in providing a much smoother workflow to the users. Creating a package of EOS Icons for React, Vue, and Angular frameworks will go a long way in having a more consistent user experience as well as boost capability to accommodate users who migrate from one framework to another.</p>
The EGI-MFF reader in MNE-Python uses an old internal parser that’s pretty hard to maintain and often runs into timing drifts or memory issues. My plan for GSoC is to completely modernize this by switching the backend over to the 'mffpy' library. I’m going to build a wrapper that keeps everything backward-compatible while fixing those annoying 1-sample errors and array mismatches that have been blocking users for years. By the end of the summer, I’ll have delivered a refactored read_raw_egi module that supports O(1) memory mapping, so researchers can stream huge files without crashing. I'm also making sure we get proper support for PNS channel mapping and automated bad-channel detection. Most importantly, I’ll be building a solid regression test suite to make sure the event timing stays microsecond-accurate, which is crucial for the neuroscience work this library supports.
<p>This project's objective is to provide an additional backend for the <strong>visualization of two-dimensional data</strong> (channels x time) based on <strong>PyQt</strong>. It is supposed to offer <strong>high performance</strong> for visualizing data and thus facilitating signal inspection.</p> <p>First of all the most suitable PyQt-based backend will be determined regarding performance and compatibility under the specific conditions of <a href="https://mne.tools/stable/index.html" target="_blank">MNE-Python</a>. The chosen backend will then be used to create an implementation with equivalent features to the <a href="https://mne.tools/stable/generated/mne.io.Raw.html#mne.io.Raw.plot" target="_blank">original matplotlib-version</a>. Finally the foundation for an integration of the new implementation alongside the original will be laid.</p>
<p>Currently dateparser supports parsing in some languages and the data used for conversion has been contributed by the community. However the languages supported by dateparser is merely a fraction of the languages used across the world. Also the languages are used differently on the basis of the territory they are used in and thus parsing dates in a language also varies according to the territory. The complete information for parsing dates taking in account both language and territory can be obtained by using locales. Currently dateparser lacks a mechanism of defining and working with locales. This project aims to extend support for all locales in Unicode Common Locale Data Repository(CLDR) which is a standard repository of locale specific data.</p>
During my project, I will successfully implement a module for Correlation-Tensor Magnetic Resonance Imaging (CT-MRI) in DIPY, which provides advanced diffusion acquisition techniques for characterizing healthy and pathological brain alterations. This implementation is significant because DIPY previously provided limited modules to process this type of diffusion MRI data. By expanding DIPY's capabilities, researchers and clinicians can now gain unique insights into tissue microstructure, making DIPY a more complete and useful tool for a wider range of MRI data users.
<p>Pharo and Smalltalk in general always encouraged a good quality of code [Kent Beck “Smalltalk with style”; Refectoring Browser; SmallLint; CriticBrowser]. Nonetheless there are still many features lacking from the quality-assistance in Pharo.</p>
<p>Implementing an optional language detection with two built-in supported language detection libraries and reimplementing <code>search_dates</code> for better results and improving the previously buggy <code>search_dates</code>.</p>
<p>Provides a single clean interface to the different representations of 3D rotations (matrices, Euler angles, quaternions). Also supports many useful algorithms such as SLERP, uniform random sampling, and solutions to Wahba's problem</p>
<p>The project is a demo for the Hydra draft proposed by the W3C. It aims to build a smart client and server that is able to exchange information in an efficient manner over a RESTful API using a Hydra based vocabulary. A smart client is able to communicate with the server even without previously knowing the supported methods of the server. This is made possible using Hydra's API documentation method. Hydra is a push towards the idea of semantic web and it's potential as a mean of communication is demonstrated in this project. This project lays the foundation for a larger project that showcases Hydra's full potential.</p>
This project aims to utilize LLMs to make the library more accessible to the community. There will be a Discord, GitHub and X (previously Twitter) Integration. By reducing the barrier of entry, we aim to bring more people into using scientific visualization libraries.
<p>The aim of this project will be to provide a replacement of the existing blender based simulations with the unity game engine.</p>
In Blender, geometry nodes provide the user with a visual scripting interface to manipulate 3D geometry, allowing the creation of custom modifiers and procedural tools. In most cases, the input of geometry nodes is the source geometry to which the geometry node is attached. File import nodes would allow more source data to be fed into geometry nodes, expanding the use case for geometry nodes. Currently, Blender has source nodes for primitive shapes, allowing the user to inject more geometric data into the geometry nodes graph. The user can inject data into the geometry node graph with dedicated file import nodes. Dynamically loading file formats like STL, OBJ, Alembic, and CSV with a geometry node would simplify everyday data visualization tasks. Also, it would reduce memory consumption on disks because the data would not have to be stored in a .blend file. As part of this year's Google Summer of Code, I'll be aiming to deliver the following 1) Multiple file import nodes for STL, OBJ, Alembic, PLY, and CSV formats 2) Refactoring for existing bf_io_* projects to expose Mesh loading functions 3) New importer project for CSV import support 4) Technical and user documentation Integrated tests
<p>About the project. The idea is to stabilize the project in python 3, perform unit tests (to test the migration to python3), add continuous integration (run the tests in each commit) and automated deployment (to assemble the packages and upload them to PyPi automatically). They are all things that would facilitate the development and installation of the project.</p>
<p>The project consists of implementing in Scipy an interior-point method for nonlinear problems. The main goal is to implement a constrained optimization algorithm able to deal with a large (and possibly sparse) problems for which the constrained optimization methods currently implemented in Scipy (namely SLSQP and COBYLA) are largely inappro- priate to deal with. Implement benchmark problems and integrate quasi-Newton (namely BFGS, SR1 and L-BFGS) and finite differences (using graph coloring schemes to deal with sparse structures) approximations to the method are also part of the project.</p>