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The main purpose of this project is to build a C++ library that allows efficient computation of sparse matrices stored in different formats such as COO, CSR, DIA etc. The library would be able to generate code that unifies different formats and generate optimized loops to aid in computation. The library will implement 6 level formats which can be used to represent any of the common tensor storage formats. The library will also implement a code generation algorithm that will allow efficient computations between disparate formats at compile time, thereby improving performance.

<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>This project covers the development of a Tango Control’s Device Server(s) for the purpose of reading and configuring biometric signal sensors.</p> <ul> <li>Phase I of the project consists of selecting which biometrics are to be measured. Eg: Pulsioximetry, Accelerometry, etc. The next step would be to survey the commercial sensors available, and select one, or more, according to criteria like: Budget, Programming libraries available, Documentation, Signal Preprocessing capability, etc. Multi-sensor devices should be preferred over several single-sensor devices.</li> <li>Phase II consists of writing the Device Servers for the chosen devices, in Python, with abstraction and decoupling in mind. It would also entail looking into the possibility of interfacing these device servers to the existing Habitat Monitor and Health Monitor GUI.</li> <li>Phase III covers improving the signal quality and, if time allows, performing some signal analysis. This phase is slightly flexible in that if sufficient preprocessing on the signals is done by the chosen devices themselves, more work can be done on the GUI and interfacing.</li> </ul> <p>The project is part of the current studies on the simulation of an Astronaut’s Health Monitor system.</p>

The goal of this project is to integrate pitch-correction into Blender's video sequence editor (VSE). While the editor supports retiming video and audio through the retiming keys, one particular feature that is missing for audio clips is being to preserve the original pitch of the audio when it is sped up or slowed down. So, this project will add a "Pitch Correction" toggle option to the audio strips in the editor, allowing the audio to retain its natural tonal quality if retimed.

Eye-tracking devices are widely used in neuroscience research. Studies of visual perception and attention in particular are increasingly integrating eye-tracking and EEG/MEG devices, in order to gain a better understanding of these processes and their neural correlates. However, the Python community has yet to coalesce around a well-supported package for analyzing eye-tracking signals. This project proposes to integrate support for reading, visualizing, and analyzing eye-tracking signals in MNE-Python. By incorporating the ability to analyze eye-tracking data into MNE-Python, researchers would be able to analyze both neural and eye movement data within the same software environment, making MNE-Python more versatile and useful for a wider range of research questions. Finally, MNE-Python has a large community of developers and users, making it likely that eye-tracking integration will prove useful for many in the scientific Python community. This project will focus on building a robust I/O routine for eye-tracking data and developing functions for preprocessing, visualization, and analytical routines that are commonly required in eye-tracking research. This includes the ability to interpolate eye-position data during blinks, produce heatmap plots of eye-position across trials, and estimate the deconvolved pupil response.

<p>Improve the sculpting tools by adding a silhouette brush and other minor improvements to the toolset. Giving the sculptor the freedom to add and subtract new geometry contrary to just shaping the existing.</p>

Flamenco, whose target audience is small studios of artists and Blender users, could benefit by adding features that enhance the user-friendliness and speed up the workflow. The main features to be implemented for this project are: 1) a configuration editor page with simple form inputs that lets users visualize, edit, and save the settings directly to/from the YAML file 2) a mass deletion function for unneeded/unwanted render jobs and 3) UI-related bug fixes to improve the overall user experience.

The main objective of this project is to update the existing UI system without impacting the current functionality, while also creating tests for each new change to ensure reliability. The project will focus on several key areas including Layout Management, Creating Scrollbar as an individual element, Completing Tree UI implementation, Spin Box Implementation, and Improving the Border Implementation. Additionally, the project will include fixing multiple UI elements such as ComboBox, TabUI, Filedialog, and Tree UI. Furthermore, the project will involve exploring a new framework with the existing UI element, which will enable selecting them together. Overall, the project aims to enhance the UI system while ensuring that it remains stable and reliable.

<p>I have started doing the initial work on the EOS Adobe XD plugin and I found the community extremely supportive. For the summer, my goal would be to increase the capabilities of the Adobe XD plugin, and develop the Angular package for EOS. This might touch the sister packages for React library and the original NPM package and I would ensure there are no frictions during development and we are on the same page while moving forward.</p>

<p>EOS User Story provides an interface to the users to share how they are using the product and relate to other users’ stories and vote them up. It helps users tell developers how they are using the products and request new features, report bugs, etc. The project aims to enhance the user experience by introducing new features and improve on the existing ones. These features include providing users the functionality of sharing stories with a single click, providing request templates for products, personalized email notifications, priority labels for stories, priority based sorting of stories, and a feature for users to mention other users in the comments section.</p>

<p>The aim of the project is to develop a <strong>language independent</strong> analyzing routine that will find all <strong>documentation strings</strong> in a file, parse them into <strong>specific groups</strong> and checks them against a <strong>specified documentation style</strong> given by the user. The functionality can be extended to providing a patch that <strong>re-formats</strong> the documentation correctly and checks for <strong>grammatical errors</strong> and performs other <strong>aesthetical fixes</strong>.</p>

The study of complex networks involves analyzing the structure and dynamics of the networks and their emergent properties, such as resilience, robustness, and efficiency. The significance of complex networks in real life demands us to have tools to analyze the properties and dynamics of the network. Through this project, I would like to introduce a complex network library on top of the existing PharoAI graph library by implementing various measures, metrics, and algorithms for fundamental network quantities.

<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><code>clusterpy</code> is a Python module which offers various clustering algorithms. The goal of this project is to make these algorithms easily usable together with <code>PySAL</code> and <code>geopandas</code>. Besides that a key requirement is Python-3 compatibility which <code>clusterpy</code> currently does not offer. Once these goals are attained, additional clustering algorithms can be implemented.</p>

This project aims to port the remaining tree elements to the new object-oriented design of the Outliner codebase. The project will involve creating new subclasses, modifying existing code, thoroughly testing changes, and documenting the modifications made. The deliverables for this project include a detailed report and updated code of new AbstractTreeElement sub-classes representing the remaining tree elements. The project will contribute to the ongoing development efforts of the Outliner by providing a necessary refactoring that will make future development work easier and more efficient, and the Outliner module's documentation will be improved.

<p>Blender has had a cloth simulator for quite a while now. It is based on a system that now needs major changes. A lot of research has been done in adaptive cloth simulation (which is the next big step towards being able to do realistic cloth simulation in reasonable computation time). By introducing adaptive cloth simulation into Blender, we can decrease the computation time per frame, thereby leading to a better quality of simulation in the same amount of time. Furthermore, it would then be possible to build really powerful cloth production pipelines. The current cloth production pipeline is slow and requires a lot of user interaction (for example, for adding the correct level of topology and redefining the stitches each time the topology changes). With the introduction of adaptive cloth simulation, the algorithm can automatically determine the necessary topology to get the correct collisions and realistic folds and wrinkles. Additionally, this project would act as the base for future improvements, such as adding contact friction and dynamic tearing of cloth.</p>

<p>This project aims to add enhancements to Scrapy's Feed Exporter components. These enhancements consists of item filters, feed post-processing and batch delivery triggers. Currently there are no convenient ways to filter items before they can be exported. Item filter feature will provide such ways and interface. A Feed post-processing enhancement will enable plugins such as compression, minifying, beautifier, etc. which can then be added to the Feed exporting workflow. Batch creation was a recently introduced feature but was limited to only item count constraints. Batch Deliver triggers will be able to make the constraints flexible and give more control to user to create batches.</p>

The idea here is to provide both runtime support (preferably using the SymEngine library to provide the computation, as it is fast and robust) and compile time support (in ASR) to implement Symbolic Algorithms in LPython. The runtime operation could use the SymEngine library for LLVM, C and C++ backends. For Python backend, we can simply use SymPy itself. The algorithms would be implemented in the ASR code, which would make them independent of any specific frontend. Any frontend that uses the ASR code could then make use of the symbolic algorithms without having to reimplement them. LPython, in this case, would not implement the symbolic algorithms themselves, but would instead parse the syntax used by the SymPy library, which already has a rich set of symbolic algorithms, and use the ASR representation of these expressions to perform various operations. This would allow LPython to have powerful symbolic manipulation capabilities without having to reinvent the wheel.

<p>The aim of this project is to improve data visualization in MNE when working in the Jupyter Notebook. This will be achieved by implementing a package for interactive 3D visualization of human brain activity inside the notebooks. A working alternative to mayavi and PySurfer built on top of ipyvolume and ipywidgets will be developed. Ultimately, I will add ipyvolume as a backend to the MNE package. Export of data visualization to a variety of file formats will be added.</p>

<p>Peragro-at has a plug-in system that searches for an appropriate plug-in that can analyze or transcode a given file. One of my major work this summer is to implement a plug-in that can extract audio features such as mood, gender, genre, tempo, global key etc. My other part of work will focus on improving the modules by fixing numerous bugs and dockerizing the project.</p>

<p>This is a proposal to rework and fix WebOb's handling of HTTP <code>Accept</code>, <code>Accept-Language</code>, and (if necessary) <code>Accept-Charset</code> and <code>Accept-Encoding</code> headers; check that this handling is well-tested and conforms to relevant RFCs where appropriate; and if possible, help fix a longstanding, related issue in Pyramid of unpredictable <code>Accept</code> handling during view lookup.</p>

<p>For a long time, the modifier system was the main way to procedurally generate and modify 3D data in Blender. While modifiers can be stacked to produce a large variety of results it has limited control over the flow of data. The Geometry Nodes system, introduced in version 2.92 of Blender allows the user to go way beyond these limitations by building complex processing graphs with an advanced attribute system that allows storing data into geometry to be available for later nodes in the graph to operate on. At the time of writing, only a small set of basic functionality is available as nodes. This project will port a selection of functionality from the old modifier system to the new nodes system, taking into account the atomic design, the attributes system, and the variety of geometry types it operates on.</p>

The proposal aims to enhance the Pwndbg tool by adding support for jemalloc Heap Inspection and loading Linux Kernel Symbols. The problem being addressed is the no support for jemalloc in Pwndbg and the lack of a convenient method to load kernel symbols into GDB for debugging. To solve this, the project will involve deep diving into jemalloc's memory allocation mechanisms, implementing jemalloc-specific heap inspection commands, and developing a kallsyms command to fetch and load kernel symbols into GDB. The deliverables include developed parsers and data extraction functions for jemalloc, implementation of jemalloc-specific heap inspection commands, a kallsyms command for GDB symbol loading, comprehensive tests for validation, and documentation for these commands in Pwndbg's documentation.