Fish (friendly interactive shell) is a shell focused on interactive use, discoverability, and friendliness. Fish has very user-friendly and powerful tab-completion, including descriptions of every completion, completion of strings with wildcards, and many completions for specific commands. It also has extensive and discoverable help. A special help command gives access to all the fish documentation in your web browser. Other features include smart terminal handling based on terminfo, an easy to search history, and syntax highlighting.

Proposes non-parametric estimates of the Fisher information measure and the Shannon entropy power. More theoretical and implementation details can be found in Guignard et al. <doi:10.3389/feart.2020.00255>. A python version of this work is available on github and PyPi ('FiShPy').

This package provides raw and curated data on the codes, classification and conservation status of freshwater fishes in British Columbia. Marine fishes will be added in a future release.

Base maps are transformed to focus on a specific location using an azimuthal logarithmic distance transformation.

Fits models to catch and effort data. Single-species models are 1) delta log-normal, 2) Tweedie, or 3) Poisson-gamma (G)LMs.

An interface to the Fish Tree of Life API to download taxonomies, phylogenies, fossil calibrations, and diversification rate information for ray-finned fishes.

This package provides a bundle of analytics tools for fisheries scientists. A shiny R App is included for a no-code solution for retrieval, analysis, and visualization.

The fishpond package contains methods for differential transcript and gene expression analysis of RNA-seq data using inferential replicates for uncertainty of abundance quantification, as generated by Gibbs sampling or bootstrap sampling. Also the package contains a number of utilities for working with Salmon and Alevin quantification files.

The Food and Agriculture Organization of the United Nations (FAO) FishStat database is the leading source of global fishery and aquaculture statistics and provides unique information for sector analysis and monitoring. This package provides the global production data from all fisheries and aquaculture in R format, ready for analysis.

This package provides a collection of four datasets based around the population dynamics of migratory fish. Datasets contain both basic size information on a per fish basis, as well as otolith data that contains a per day record of fish growth history. All data in this package was collected by the author, from 2015-2016, in the Wellington region of New Zealand.

The FisherEM algorithm, proposed by Bouveyron & Brunet (2012) <doi:10.1007/s11222-011-9249-9>, is an efficient method for the clustering of high-dimensional data. FisherEM models and clusters the data in a discriminative and low-dimensional latent subspace. It also provides a low-dimensional representation of the clustered data. A sparse version of Fisher-EM algorithm is also provided.

Implementation of color palettes based on fish species.

FISHalyseR provides functionality to process and analyse digital cell culture images, in particular to quantify FISH probes within nuclei. Furthermore, it extract the spatial location of each nucleus as well as each probe enabling spatial co-localisation analysis.

Fit growth models to otoliths and/or tagging data, using the RTMB package and maximum likelihood. The otoliths (or similar measurements of age) provide direct observed coordinates of age and length. The tagging data provide information about the observed length at release and length at recapture at a later time, where the age at release is unknown and estimated as a vector of parameters. The growth models provided by this package can be fitted to otoliths only, tagging data only, or a combination of the two. Growth variability can be modelled as constant or increasing with length.

This package provides functions for applying a wide range of fisheries stock assessment methods.

Documentation at https://melpa.org/#/fish-mode

This package provides syntax highlighting and indentation functions for Fish shell scripts.

Dataset of 302 measurements of 11 fish species to accompany the manuscript "Length-weight relationships of six freshwater fish species from lake Kirkkojarvi, Finland".

fish-foreign-env wraps bash script execution in a way that environment variables that are exported or modified get imported back into fish.

This package provides an alternative to facilitate the construction of a phylogeny for fish species from a list of species or a community matrix using as a backbone the phylogenetic tree proposed by Rabosky et al. (2018) <doi:10.1038/s41586-018-0273-1>.

Documentation at https://melpa.org/#/fish-completion

This package provides completion for the Fish shell to pcomplete (used by shell and Eshell). You can set it up globally with:

(when (and (executable-find "fish")
           (require 'fish-completion nil t))
  (global-fish-completion-mode))

Alternatively, you can call the fish-completion-mode manually or in shell/Eshell mode hook.

The package emacs-bash-completion is an optional dependency: if available, fish-completion-complete can be configured to fall back on bash to further try completing. See fish-completion-fallback-on-bash-p.

Populate rich completions using fish and remove the default bash based completer.

The proximate composition analysis is the quantification of main components that constitutes nutritional profile of any food and food products including fish, shellfish, fish feed and their ingredients. Understanding this composition is essential for evaluating their nutritional value and for making informed dietary choices. The primary components typically analyzed include; moisture/ water in foods, crude protein, crude fat/ lipid, total ash, fiber and carbohydrates AOAC(2005,ISBN:0-935584-77-3). In case of fish, shellfish and its products, the proximate composition consists of four primary constituents - water, protein, fat, and ash (mostly minerals). Fish exhibit significant variation in their chemical makeup based on age, sex, environment, and season, both within the same species and between individual fish. There is minimal fluctuation in the content of ash and protein. The lipid concentration varies remarkably and is inversely correlated with the water content. In case of fish, carbohydrates are present in minor quantity so that are quantified by subtracting total of other components from 100 to get percentage of carbohydrates.