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pykdtree is a kd-tree implementation for fast nearest neighbour search in Python.
xarray-dataclasses is a Python package that makes it easy to create xarray's DataArray and Datase objects that are "typed" (i.e. fixed dimensions, data type, coordinates, attributes, and name) using the Python's dataclass.
This package provides a simplified scipy.signal.spectral module to do spectral analysis in Python.
Scikit-Optimize, or skopt, is a simple and efficient library to minimize (very) expensive and noisy black-box functions. It implements several methods for sequential model-based optimization. skopt aims to be accessible and easy to use in many contexts.
This package implements a functionality to tell whether two images look nearly identical. The image hash algorithms (average, perceptual, difference, wavelet) analyse the image structure on luminance (without color information). The color hash algorithm analyses the color distribution and black & gray fractions (without position information).
Features:
average hashing
perceptual hashing
difference hashing
wavelet hashing
HSV color hashing (colorhash)
crop-resistant hashing
pyfma provides an implementation of fused multiply-add which computes (x*y) + z with a single rounding. This is useful for dot products, matrix multiplications, polynomial evaluations (e.g., with Horner's rule), Newton's method for evaluating functions, convolutions, artificial neural networks etc.
This package provides Python bindings for the Boost::Histogram library, one of the fastest libraries for histogramming.
fgivenx is a Python package for plotting posteriors of functions. It is currently used in astronomy, but will be of use to any scientists performing Bayesian analyses which have predictive posteriors that are functions.
This package allows one to plot a predictive posterior of a function, dependent on sampled parameters. It assumes one has a Bayesian posterior Post(theta|D,M) described by a set of posterior samples theta_i~Post. If there is a function parameterised by theta y=f(x;theta), then this script will produce a contour plot of the conditional posterior P(y|x,D,M) in the (x,y) plane.
The osfclient is a python library and a command-line client for up- and downloading files to and from Open Science Framework projects. The OSF is an open source project which facilitates the open collaboration of researchers on the web, by sharing data and other research outputs.
Numpoly is a generic library for creating, manipulating and evaluating arrays of polynomials based on numpy.ndarray objects.
The SciPy library is one of the core packages that make up the SciPy stack. It provides many user-friendly and efficient numerical routines such as routines for numerical integration and optimization.
Modin uses Ray or Dask to provide an effortless way to speed up your pandas notebooks, scripts, and libraries. Unlike other distributed DataFrame libraries, Modin provides seamless integration and compatibility with existing pandas code.
This package provides a Python library for calculating Evapotranspiration using various standard methods.
python-pandera provides a flexible and expressive API for performing data validation on dataframe-like objects to make data processing pipelines more readable and robust. Dataframes contain information that python-pandera explicitly validates at runtime. This is useful in production-critical data pipelines or reproducible research settings. With python-pandera, you can:
Define a schema once and use it to validate different dataframe types.
Check the types and properties of columns.
Perform more complex statistical validation like hypothesis testing.
Seamlessly integrate with existing data pipelines via function decorators.
Define dataframe models with the class-based API with pydantic-style syntax.
Synthesize data from schema objects for property-based testing.
Lazily validate dataframes so that all validation rules are executed.
Integrate with a rich ecosystem of tools like
python-pydantic,python-fastapiandpython-mypy.
xarray-dataclass is a Python package that makes it easy to create xarray's DataArray and Dataset objects that are "typed" (i.e. fixed dimensions, data type, coordinates, attributes, and name) using the Python's dataclass. It's a successor of not maintained https://github.com/astropenguin/xarray-dataclasses.
This package provides optimized tools for group-indexing operations: aggregated sum and more.
SALib provides tools for global sensitivity analysis. It contains Sobol', Morris, FAST, DGSM, PAWN, HDMR, Moment Independent and fractional factorial methods.
openPMD is an open meta-data schema that provides meaning and self-description for data sets in science and engineering. See the openPMD standard for details of this schema.
This library provides a reference API for openPMD data handling. Since openPMD is a schema (or markup) on top of portable, hierarchical file formats, this library implements various backends such as HDF5, ADIOS2 and JSON. Writing & reading through those backends and their associated files are supported for serial and MPI-parallel workflows.
Trimesh is a pure Python library for loading and using triangular meshes with an emphasis on watertight surfaces. The goal of the library is to provide a full featured and well tested Trimesh object which allows for easy manipulation and analysis, in the style of the Polygon object in the Shapely library.
This package provides a stable interface for interactions between Snakemake and its executor plugins.
The fast-histogram mini-package aims to provide simple and fast histogram functions for regular bins that don't compromise on performance. It doesn't do anything complicated - it just implements a simple histogram algorithm in C and keeps it simple. The aim is to have functions that are fast but also robust and reliable. The result is a 1D histogram function here that is 7-15x faster than numpy.histogram, and a 2D histogram function that is 20-25x faster than numpy.histogram2d.
This package implements a functionality to work with Nested sampling, a popular numerical method for Bayesian computation, which simultaneously generates samples from the posterior distribution and an estimate of the Bayesian evidence for a given likelihood and prior. nestcheck provides Python utilities for analysing samples produced by nested sampling, and estimating uncertainties on nested sampling calculations (which have different statistical properties to calculations using other numerical methods).
This package provides a Python wrapper around Fabio Crameri's perceptually uniform colormaps for scientific data visualization.
Pandas 0.23 added a simple API for registering accessors with Pandas objects. Pandas-flavor extends Pandas' extension API by
adding support for registering methods as well
making each of these functions backwards compatible with older versions of Pandas