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This package provides a Python library for building and analyzing recommender systems that deal with explicit rating data. It was designed with the following purposes in mind:
Provide tools to handle downloaded or user-provided datasets.
Provide ready-to-use prediction algorithms and similarity measures.
Provide a base for creating custom algorithms.
Provide tools to evaluate, analyse and compare algorithm performance.
Provide documentation with precise details regarding library algorithms.
This package implements sparse arrays of arbitrary dimension on top of numpy and scipy.sparse. Sparse array is a matrix in which most of the elements are zero. python-sparse generalizes the scipy.sparse.coo_matrix and scipy.sparse.dok_matrix layouts, but extends beyond just rows and columns to an arbitrary number of dimensions. Additionally, this project maintains compatibility with the numpy.ndarray interface rather than the numpy.matrix interface used in scipy.sparse. These differences make this project useful in certain situations where scipy.sparse matrices are not well suited, but it should not be considered a full replacement. It lacks layouts that are not easily generalized like compressed sparse row/column(CSR/CSC) and depends on scipy.sparse for some computations.
PyQtGraph is a Pure-python graphics library for PyQt5, PyQt6, PySide2 and PySide6. It is intended for use in mathematics, scientific or engineering applications.
Pyzo is a Python IDE focused on interactivity and introspection,which makes it very suitable for scientific computing. Its practical design is aimed at simplicity and efficiency.
It consists of two main components, the editor and the shell, and uses a set of pluggable tools to help the programmer in various ways. Some example tools are source structure, project manager, interactive help, workspace...
Plotnine is a Python implementation of the Grammar of Graphics. It is a powerful graphics concept for creating plots and visualizations in a structured and declarative manner. It is inspired by the R package ggplot2 and aims to provide a similar API and functionality in Python.
python-pydicom is a Python library for reading and writing DICOM medical imaging data. It can read, modify and write DICOM data.
Scikit-opt (or sko) is a Python module implementing swarm intelligence algorithms: genetic algorithm, particle swarm optimization, simulated annealing, ant colony algorithm, immune algorithm, artificial fish swarm algorithm.
Dask is a flexible parallel computing library for analytics. It consists of two components: dynamic task scheduling optimized for computation, and large data collections like parallel arrays, dataframes, and lists that extend common interfaces like NumPy, Pandas, or Python iterators to larger-than-memory or distributed environments. These parallel collections run on top of the dynamic task schedulers.
This package implements a functionality to solve automatic numerical differentiation problems in one or more variables. Finite differences are used in an adaptive manner, coupled with a Richardson extrapolation methodology to provide a maximally accurate result. The user can configure many options like; changing the order of the method or the extrapolation, even allowing the user to specify whether complex-step, central, forward or backward differences are used.
This package lets you generate a multiscale, chunked, multi-dimensional spatial image data structure that can serialized to OME-NGFF. Each scale is a scientific Python Xarray spatial-image Dataset, organized into nodes of an Xarray Datatree.
A Snakemake executor plugin for running SLURM jobs.
flox mainly provides strategies for fast GroupBy reductions with dask.array. It uses the MapReduce paradigm (or a "tree reduction") to run the GroupBy operation in a parallel-native way totally avoiding a sort or shuffle operation. flox can use either dask or cubed as its backend.
This package provides a Python interface for the SCS (Splitting conic solver) library.
A Snakemake executor plugin for running srun jobs inside of SLURM jobs (meant for internal use by python-snakemake-executor-plugin-slurm).
Numpoly is a generic library for creating, manipulating and evaluating arrays of polynomials based on numpy.ndarray objects.
This package provides an extremely lightweight compatibility layer between dataframe libraries.
full API support: cuDF, Modin, pandas, Polars, PyArrow
lazy-only support: Dask, DuckDB, Ibis, PySpark, SQLFrame
iminuit is a Jupyter-friendly Python interface for the Minuit2 C++ library maintained by CERN's ROOT team.
Minuit was designed to optimize statistical cost functions, for maximum-likelihood and least-squares fits. It provides the best-fit parameters and error estimates from likelihood profile analysis.
Optionally, Iminuit supports SciPy minimizers as alternatives to Minuit's MIGRAD algorithm and Numba accelerated functions.
Vaex is a high performance Python library for lazy Out-of-Core DataFrames (similar to Pandas), to visualize and explore big tabular datasets. This package provides the core modules of Vaex.
Often when we want to label multiple points on a graph the text will start heavily overlapping with both other labels and data points. This can be a major problem requiring manual solution. However this can be largely automated by smart placing of the labels (difficult) or iterative adjustment of their positions to minimize overlaps (relatively easy). This library implements the latter option to help with matplotlib graphs.
Polars is a DataFrame library for manipulating structured data.
This package provides tools to easily search and download French data from INSEE and IGN APIs. This data includes more than 150 000 macroeconomic series, a dozen datasets of local french data, numerous sources available on insee.fr, geographical limits of administrative areas taken from IGN as well as key metadata and SIRENE database containing data on all French compagnies.
Einops provides a set of tensor operations for NumPy and multiple deep learning frameworks.
This package provides a Python library for calculating Evapotranspiration using various standard methods.
PyMCubes is an implementation of the marching cubes algorithm to extract iso-surfaces from volumetric data. The volumetric data can be given as a three-dimensional NumPy array or as a Python function f(x, y, z).