SciPy is an open-source scientific computing library for the Python programming language. Since its initial release in 2001, SciPy has become a de facto standard for leveraging scientific algorithms in Python, with over 600 unique code contributors, thousands of dependent packages, over 100,000 dependent repositories and millions of downloads per year. In this work, we provide an overview of the capabilities and development practices of SciPy 1.0 and highlight some recent technical developments.

Array programming provides a powerful, compact and expressive syntax for accessing, manipulating and operating on data in vectors, matrices and higher-dimensional arrays. NumPy is the primary array programming library for the Python language. It has an essential role in research analysis pipelines in fields as diverse as physics, chemistry, astronomy, geoscience, biology, psychology, materials science, engineering, finance and economics. For example, in astronomy, NumPy was an important part of the software stack used in the discovery of gravitational waves1 and in the first imaging of a black hole2. Here we review how a few fundamental array concepts lead to a simple and powerful programming paradigm for organizing, exploring and analysing scientific data. NumPy is the foundation upon which the scientific Python ecosystem is constructed. It is so pervasive that several projects, targeting audiences with specialized needs, have developed their own NumPy-like interfaces and array objects. Owing to its central position in the ecosystem, NumPy increasingly acts as an interoperability layer between such array computation libraries and, together with its application programming interface (API), provides a flexible framework to support the next decade of scientific and industrial analysis.

We present Thermobar, a new open-source Python3 package for calculating pressures, temperatures, and melt compositions from mineral and mineral-melt equilibrium. Thermobar allows users to perform calculations with >100 popular parametrizations involving liquid, olivine-liquid, olivine-spinel, pyroxene only, pyroxene-liquid, two pyroxene, feldspar-liquid, two feldspar, amphibole only, amphibole-liquid, and garnet equilibria. Thermobar is the first open-source tool which can match up all possible pairs of phases from a given region, and apply various equilibrium tests to identify pairs from which to calculate pressures and temperatures (e.g. pyroxene-liquid, two pyroxene, feldspar-liquid, two feldspar, amphibole-liquid). Thermobar also contains functions allowing users to propagate analytical errors using Monte-Carlo methods, convert pressures to depths using different crustal density profiles, plot mineral classification and mineral-melt equilibrium diagrams, calculate liquid viscosities, and convert between oxygen fugacity values, buffer positions and Fe speciation in a silicate melt. Thermobar can be downloaded using pip and extensive documentation is available at https://thermobar.readthedocs.io/.

In human visual processing, information from the visual field passes through numerous transformations before perceptual attributes such as colour are derived. The sequence of transforms involved in constructing perceptions of colour can be approximated by colour appearance models such as the CIE (2002) colour appearance model, abbreviated as CIECAM02. In this study, we test the plausibility of CIECAM02 as a model of colour processing by looking for evidence of its cortical entrainment. The CIECAM02 model predicts that colour is split in to two opposing chromatic components, red-green and cyan-yellow (termed CIECAM02-a and CIECAM02-b respectively), and an achromatic component (termed CIECAM02-A). Entrainment of cortical activity to the outputs of these components was estimated using measurements of electro- and magnetoencephalographic (EMEG) activity, recorded while healthy subjects watched videos of dots changing colour. We find entrainment to chromatic component CIECAM02-a at approximately 35 ms latency bilaterally in occipital lobe regions, and entrainment to achromatic component CIECAM02-A at approximately 75 ms latency, also bilaterally in occipital regions. For comparison, transforms from a less physiologically plausible model (CIELAB) were also tested, with no significant entrainment found.

We present Thermobar, a new open-source Python3 package for calculating pressures, temperatures, and melt compositions from mineral and mineral-melt equilibrium. Thermobar allows users to perform calculations with >100 popular parametrizations involving liquid, olivine-liquid, olivine-spinel, pyroxene only, pyroxene-liquid, two pyroxene, feldspar-liquid, two feldspar, amphibole only, amphibole-liquid, and garnet equilibria. Thermobar is the first open-source tool which can match up all possible pairs of phases from a given region, and apply various equilibrium tests to identify pairs from which to calculate pressures and temperatures (e.g., pyroxene-liquid, two pyroxene, feldspar-liquid, two feldspar, amphibole-liquid). Thermobar also contains functions allowing users to propagate analytical errors using Monte-Carlo methods, convert pressures to depths using different crustal density profiles, plot mineral classification and mineral-melt equilibrium diagrams, calculate liquid viscosities, and convert between oxygen fugacity values, buffer positions and Fe speciation in a silicate melt. Thermobar can be downloaded using pip and extensive documentation is available athttps://thermobar.readthedocs.io/