Constructors of waveband objects for commonly used biological spectral weighting functions (BSWFs) and for different wavebands describing named ranges of wavelengths in the ultraviolet (UV), visible (VIS) and infrared (IR) regions of the electromagnetic spectrum. Part of the r4photobiology suite, Aphalo P. J. (2015) <doi:10.19232/uv4pb.2015.1.14>.
Like Iterator::take_while, but calls the predicate on a peeked value. This allows you to use Iterator::by_ref and Iterator::take_while together, and still get the first value for which the take_while predicate returned false after dropping the by_ref.
This library enables path variables in networking routes when using Hunchenissr for Common Lisp. If a part of the path (between two slashes) starts with a question mark (?), that symbol (without question mark) will be bound to whatever value was in the same place in the URL (as a string).
Selenium implements the W3C WebDriver protocol to automate popular browsers. It aims to mimic the behaviour of a real user as it interacts with the application's HTML. It's primarily intended for web application testing, but any web-based task can be automated. This package provides the Ruby bindings of Selenium.
This crate defines an unsafe marker trait, StableDeref, for container types which deref to a fixed address which is valid even when the containing type is moved. For example, Box, Vec, Rc, Arc and String implement this trait. Additionally, it defines CloneStableDeref for types like Rc where clones deref to the same address.
This package provides raw data objects to be used for blood cell proportion estimation in minfi and similar packages. The FlowSorted.Blood.EPIC object is based in samples assayed by Brock Christensen and colleagues; for details see Salas et al. 2018. https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE110554.
This package provides a splittable PRNG functions like a PRNG that can be used as a stream of random values; it can also be split to produce a second, independent stream of random values.
This library implements a splittable pseudo-random number generator that sacrifices cryptographic-quality randomness in favor of performance.
Allows you to retrieve information from the Google Knowledge Graph API <https://www.google.com/intl/bn/insidesearch/features/search/knowledge.html> and process it in R in various forms. The Knowledge Graph Search API lets you find entities in the Google Knowledge Graph'. The API uses standard schema.org types and is compliant with the JSON-LD specification.
This package implements methods for calibrating an aggregated functional data model using wavelets or splines. Each aggregated curve is modeled as a linear combination of component functions and known weights. The component functions are estimated using wavelets or splines. The package is based on dos Santos Sousa (2024) <doi:10.1515/mcma-2023-2016> and Saraiva and Dias (2009) <doi:10.47749/T/UNICAMP.2009.471073>.
The iterator APIs in the Rust standard library do not allow elements to be yielded which borrow from the iterator itself. That means, for example, that the std::io::Lines iterator must allocate a new String for each line rather than reusing an internal buffer. The StreamingIterator trait instead provides access to elements being iterated over only by reference rather than by value.
Perform interactive occupation coding during interviews as described in Peycheva, D., Sakshaug, J., Calderwood, L. (2021) <doi:10.2478/jos-2021-0042> and Schierholz, M., Gensicke, M., Tschersich, N., Kreuter, F. (2018) <doi:10.1111/rssa.12297>. Generate suggestions for occupational categories based on free text input, with pre-trained machine learning models in German and a ready-to-use shiny application provided for quick and easy data collection.
This package implements the "Smith-Pittman" community detection algorithm for network analysis using igraph objects. This algorithm combines node degree and betweenness centrality measures to identify communities within networks, with a gradient evident in social partitioning. The package provides functions for community detection, visualization, and analysis of the resulting community structure. Methods are based on results from Smith, Pittman and Xu (2024) <doi:10.48550/arXiv.2411.01394>.
Allows users to input their data, segmentation and function used for the segmentation (and additional arguments) and the package calculates the influence of the data on the changepoint locations, see Wilms et al. (2022) <doi:10.1080/10618600.2021.2000873>. Currently this can only be used with the changepoint package functions to identify changes, but we plan to extend this. There are options for different types of graphics to assess the influence.
This package provides functions for the hyperbolic and related distributions. Density, distribution and quantile functions and random number generation are provided for the hyperbolic distribution, the generalized hyperbolic distribution, the generalized inverse Gaussian distribution and the skew-Laplace distribution. Additional functionality is provided for the hyperbolic distribution, normal inverse Gaussian distribution and generalized inverse Gaussian distribution, including fitting of these distributions to data. Linear models with hyperbolic errors may be fitted using hyperblmFit.
The Project Revenue Tryton module computes revenue and cost per task and project. The revenue uses the list price of the product. If the product's unit of measure is time based, the revenue is computed as the product of the price and the hours of effort otherwise the price is considered as fixed. The cost is computed by summing the cost of all the linked time sheets and the linked purchase lines.
This package provides a refactoring tool based on the Emacs Semantic parser framework. For C and C++ it supports operations such as:
Generating class implementations
Generating function prototypes
Converting functions to function pointers
Moving semantic units
etc...
For Lisp dialects like Clojure, ELisp, and Scheme, it supports operations such as:
Formatting the whole buffer
Converting sexpressions to one or multiple lines
etc...
This package provides utilities for implementing and composing tracing subscribers.
Tracing is a framework for instrumenting Rust programs to collect scoped, structured, and async-aware diagnostics. The Subscriber trait represents the functionality necessary to collect this trace data. This crate contains tools for composing subscribers out of smaller units of behaviour, and batteries-included implementations of common subscriber functionality.
Tracing-subscriber is intended for use by both Subscriber authors and application authors using tracing to instrument their applications.
This package provides utilities for implementing and composing tracing subscribers.
Tracing is a framework for instrumenting Rust programs to collect scoped, structured, and async-aware diagnostics. The Subscriber trait represents the functionality necessary to collect this trace data. This crate contains tools for composing subscribers out of smaller units of behaviour, and batteries-included implementations of common subscriber functionality.
Tracing-subscriber is intended for use by both Subscriber authors and application authors using tracing to instrument their applications.
This module reads a file backwards line by line. It is simple to use, memory efficient and fast. It supports both an object and a tied handle interface.
It is intended for processing log and other similar text files which typically have their newest entries appended to them. By default files are assumed to be plain text and have a line ending appropriate to the OS. But you can set the input record separator string on a per file basis.
It computes full conformal, split conformal and multi split conformal prediction regions when the response has functional nature. Moreover, the package also contain a plot function to visualize the output of the split conformal. To guarantee consistency, the package structure mimics the univariate conformalInference package of professor Ryan Tibshirani. The main references for the code are: Diquigiovanni, Fontana, and Vantini (2021) <arXiv:2102.06746>, Diquigiovanni, Fontana, and Vantini (2021) <arXiv:2106.01792>, Solari, and Djordjilovic (2021) <arXiv:2103.00627>.
Production efficiency and economic efficiency are crucial concepts in agriculture/horticulture for sustainable and profitable practices. It helps to determine the optimal use of resources to maximize outputs and profitability. Production efficiency focuses on the optimal use of resources to produce goods, while economic efficiency ensures these goods are produced and allocated in a way that maximizes economic welfare. Production efficiency and economic efficiency are calculated with the help of the formula given by (Kumar et al., 2017) <doi:10.21921/jas.v4i04.10202>.
This package provides a Python package of Roman Datamodels for the calibration pipelines started with the JWST calibration pipelines. The goal for the JWST pipelines was motivated primarily by the need to support FITS data files, specifically with isolating the details of where metadata and data were located in the FITS file from the representation of the same items within the Python code. That is not a concern for Roman since FITS format data files will not be used by the Roman calibration pipelines.
Estimate and return the needed parameters for visualizations designed for OpenBudgets.eu <http://openbudgets.eu/> datasets. Calculate descriptive statistical measures in budget data of municipalities across Europe, according to the OpenBudgets.eu data model. There are functions for measuring central tendency and dispersion of amount variables along with their distributions and correlations and the frequencies of categorical variables for a given dataset. Also, can be used generally to other datasets, to extract visualization parameters, convert them to JSON format and use them as input in a different graphical interface.
Includes functions for calculating basic indices of macrozoobenthos for water quality and is designed to provide researchers and environmental professionals with a comprehensive tool for evaluating the ecological health of aquatic ecosystems.The package is based on the following references: Paisley, M. F., Trigg, D. J. and Walley, W. J. (2014)<doi:10.1002/rra.2686>. Arslan, N., Salur, A., Kalyoncu, H. et al.(2016) <doi:10.1515/biolog-2016-0005>. Hilsenhoff W.L. (1987). Hilsenhoff. W.L. (1988) Barbour, M.T., Gerritsen, J., Snyder, B.D., and Stribling, J.B. (1999).