Reverse Dependencies of h5py
The following projects have a declared dependency on h5py:
- splendaq — Generalized offline data acquisition with a focus on the Moku
- spokes — An End-to-End Simulation Facility for Spectroscopic Cosmological Surveys
- sprice — Consumer price data package for Saudi Arabia
- sprocket-vc — Voice conversion software
- sputummrcnn — Custom Mask RCNN
- spychhiker — Various python class for speech analysis and speech synthesis
- spyking-circus — Fast spike sorting by template matching
- srfnef — Scalable Reconstruction Framework -- Not Enough Functions
- srlife — Evaluate the structural life of a solar receiver
- ssm-analyze — Analysis GUI for scanning SQUID microscopy
- stactools-goes — stactools package for working with NOAA''s GOES data
- stactools-viirs — stactools package for VIIRS sensor data
- stagpy — Tool for StagYY output files processing
- stan-utility — Helper routines for pystan based off @betanalphas stan_utility
- star-persephone — Stellar model grid management and seismic rotational kernel computations.
- starcatalogquery — A package to establish an offline star catalog query database
- starepandas — STARE pandas extensions
- starttf — A tensorflow batteries included kit to write tensorflow networks from scratch or use existing ones.
- statmoments — Fast streaming single-pass univariate/bivariate statistics and t-test
- stats-can — Read StatsCan data into python, mostly pandas dataframes
- steam-sdk — Source code for APIs for STEAM tools.
- steinbock — A toolkit for processing multiplexed tissue images
- stempy — A package for the ingestion of 4D STEM data.
- stemtool — A single package for analyzing atomic resolution STEM, 4D-STEM and STEM-EELS datasets, along with basic STEM simulation functionality
- stereoAlign — A toolkit package of data integration
- stimpack — Precise and flexible generation of stimuli for neuroscience experiments.
- stio — IO for Stereo Cell
- stock-analysis-engine — Backtest 1000s of minute-by-minute trading algorithms. Automated pricing data ingestion from: IEX Cloud (https://iexcloud.io), Tradier (https://tradier.com) and FinViz. Datasets and trading performance automatically compressed and published to S3 for building AI training datasets for teaching DNNs how to trade. Runs on Kubernetes with Helm and docker-compose. >150 million trading history rows generated from +5000 algorithms
- StockerMake — Modular Neural Network Protyping for Stock Market Prediction
- Stoner — Library to help write data analysis tools for experimental condensed matter physics.
- stonesoup — A tracking and state estimation framework
- stos — Converting the American sign language into speech or text, and vice versa.
- strainge — Strain Genome Explorer: a tool suite for tracking and characterizing low-abundance strains.
- strainmap — no summary
- streaminghub-datamux — A library to stream data into real-time analytics pipelines
- streaminghub-pydfds — Parser for Data Flow Description Schema (DFDS) metadata
- stridespatial — STRIDE (Spatial TRanscrIptomics DEconvolution by topic modelling) is a cell-type deconvolution tool for spatial transcriptomics.
- structuremap — An open-source Python package of the AlphaPept ecosystem
- struphy — Multi-model plasma physics package
- stuned — Utility code from STAI (https://scalabletrustworthyai.github.io/)
- stxmalign — Pixel Alignment of STXM images.
- stxmnorm — Normalization techniques for STXM images.
- stxmproc — Pixel Alignment and Normalization of STXM images.
- subaligner — Automatically synchronize and translate subtitles, or create new ones by transcribing, using pre-trained DNNs, Forced Alignments and Transformers.
- SubBrainSegment — Package for subcortical brain segmentation
- subcellular-sprawl — Subcellular Patterning Ranked Analysis With Labels
- suite2p — Pipeline for calcium imaging
- suite2p-haisslab — Pipeline for calcium imaging
- sumo — Heavy weight plotting tools for ab initio solid-state calculations
- sumo-output-parsers — Fast and lightweight file parsers for SUMO(traffic simulator) output
- sumo2 — Heavy weight plotting tools for ab initio solid-state calculations
- suncasa — "SunCASA: CASA-based Python package for reducing, analyzing, and visualizing solar dynamic spectroscopic imaging data at radio wavelengths"
- sunpy — SunPy core package: Python for Solar Physics
- super-image — State-of-the-art image super resolution models for PyTorch.
- superMatch — Local Feature Extractors and Matchers Network Library for PyTorch
- supernnova — framework for Bayesian, Neural Network based supernova light-curve classification
- superscreen — SuperScreen: simulate Meissner screening in 2D superconducting devices.
- supplychainmodelhelper — A package to help with your supply chain model
- SurfaceTopography — Read and analyze surface topographies
- surfinBH — Surrogate Final BH properties.
- swdl — Soccerwatch Data Library
- sweep — SWeeP is a tool for representing large biological sequences datasets in compact vectors
- swiftest — no summary
- swiftgalaxy — Code abstraction of objects (galaxies) in simulations.
- swiftsimio — SWIFTsim (swift.dur.ac.uk) i/o routines for python.
- swmfpy — A collection of tools for the Space Weather Modelling Framework
- swmmtonetcdf — A tool to write SWMM output to netcdf
- swmr-tools — Python iterator for safely monitoring NeXus files
- sxdm — Tools for analyzing Scanning X-ray Diffraction Microscopy data
- sxs — Interface to data produced by the Simulating eXtreme Spacetimes collaboration
- symclosestwannier — A Python library for Symmetry-Adapted Closest Wannier (SymCW) Tight-Binding model based on Plane-Wave DFT calculation.
- syml-ultralytics — SyML Ultralytics YOLOv8 for SOTA object detection, multi-object tracking, instance segmentation, pose estimation and image classification.
- Sympathy — Sympathy for Data is a visual data analysis and processing platform based on Python.
- sympde — Symbolic calculus for partial differential equations (and variational forms)
- synaptogram — Module for helping assess synapse counts
- synbols — Synbols: Probing Learning Algorithms with Synthetic Datasets
- syne-tune — Distributed Hyperparameter Optimization on SageMaker
- synth-data-metrics — Synthetic Data Metrics is a Python library for evaluating synthetic data quality across a wide range of data types (image, tabular, time series, language) and approaches to evaluation.
- synthetic-data-metrics — Synthetic Data Metrics is a Python library for evaluating synthetic data quality across a wide range of data types (image, tabular, time series, language) and approaches to evaluation.
- tabcorr — Tabulated Correlation Functions
- tables-io — Input/output and conversion functions for tabular data
- tablite — multiprocessing enabled out-of-memory data analysis library for tabular data.
- tamaas — no summary
- tangelo-gc — Tangelo is an open-source Python package maintained by Good Chemistry Company, focusing on the development of quantum chemistry simulation workflows on quantum computers. It was developed as an engine to accelerate research, and leverages other popular frameworks to harness the innovation in our field.
- tank-lab-to-nwb — NWB conversion scripts and tutorials.
- tapr — TAbular PRogramming in Python
- tart — Transient Array Radio Telescope Imaging and Operation Library
- tart2ms — Convert TART observation data to Measurement Sets
- taskchain — Utility for running data and ML pipelines
- tatau — no summary
- taurex — TauREx 3 retrieval framework
- tbmodels — A tool for reading, creating and modifying tight-binding models.
- TCFile — Python package for handling TCF data. It works with Tomcube data
- tcs-pythonwhat — Submission correctness tests for Python
- tcsa — temporalis segmentation pipeline to assess CSA of temporalis muscle
- tdgl — pyTDGL: Time-dependent Ginzburg-Landau in Python.
- tdr-convert — tdr-convert: tdr file converter
- TDY-PKG — its an implimentation of TF-2 , Detectron and yolov5
- TDY-PKG-saquibquddus — its an implimentation of TF-2 , Detectron and yolov5
- teili — This toolbox was developed to provide computational neuroscientists and neuromorphic engineers with a playground for implementing neural algorithms which are simulated using Brian 2.