Scalarfirst

Scalarfirst is a software library and framework for efficient handling of scalar fields on multi-dimensional grids. It provides data structures for scalar fields, interpolation and differentiation utilities, and algorithms for filtering, sampling, and analysis. The project aims for performance and scalability to support large datasets in scientific computing and computer graphics.

The core data model centers on scalar fields defined over grids. Key abstractions include ScalarField, Grid, and FieldDescriptor, describing storage, topology, and coordinates. Implementations support dense and sparse layouts and interoperate with common array backends. A C++ core with language bindings (notably Python) uses templates and lightweight polymorphism to balance flexibility and speed.

Performance features include memory layouts optimized for vectorization, multi-threading, and optional GPU acceleration. Core operations cover gradient, divergence, Laplacian, interpolation, resampling, convolution, and thresholding, along with basic I/O and metadata utilities to support pipelines.

Use cases span computational physics, climate modeling, geoscience, medical imaging, and visualization workflows where scalar fields model quantities such as temperature or pressure.

Scalarfirst is an open-source project developed by a community of contributors. It is distributed to serve as a modular foundation for integration into simulation and analysis tools.

See also: scalar field, grid topology, numerical differentiation, data parallelism.