Search Results for "function list"

This package provides guaranteed methods for finding roots of functions, i.e. solutions to the equation f(x) == 0 for a function f. To do so, it uses methods from interval analysis, using interval arithmetic from the IntervalArithmetic.jl package by the same authors. The basic function is roots. A standard Julia function and an interval is provided and the roots function return a list of intervals containing all roots of the function located in the starting interval.

NCDatasets allows one to read and create netCDF files. NetCDF data set and attribute list behave like Julia dictionaries and variables like Julia arrays. This package implements the CommonDataModel.jl interface, which means that the datasets can be accessed in the same way as GRIB files opened with GRIBDatasets.jl.

Visualize the distribution of code coverage in your project. This helps to identify code areas with high and low coverage. Useful when you have a large project with lots of files and packages. This 2D image-hash of your project should be more representative than a single number. For each module, the node representing the greatest version (i.e., the version chosen by Go's minimal version selection algorithm) is colored green. Other nodes, which aren't in the final build list, are colored grey...

gusty allows you to control your Airflow DAGs, Task Groups, and Tasks with greater ease. gusty manages collections of tasks, represented as any number of YAML, Python, SQL, Jupyter Notebook, or R Markdown files. A directory of task files is instantly rendered into a DAG by passing a file path to gusty's create_dag function. gusty also manages dependencies (within one DAG) and external dependencies (dependencies on tasks in other DAGs) for each task file you define. All you have to do is provide a list of dependencies or external_dependencies inside of a task file, and gusty will automatically set each task's dependencies and create external task sensors for any external dependencies listed. gusty works with both Airflow 1.x and Airflow 2.x, and has even more features, all of which aim to make the creation, management, and iteration of DAGs more fluid, so that you can intuitively design your DAG and build your tasks.

pandas-profiling generates profile reports from a pandas DataFrame. The pandas df.describe() function is handy yet a little basic for exploratory data analysis. pandas-profiling extends pandas DataFrame with df.profile_report(), which automatically generates a standardized univariate and multivariate report for data understanding. High correlation warnings, based on different correlation metrics (Spearman, Pearson, Kendall, Cramér’s V, Phik).

React lets you use whatever style of data management you want, including mutation. However, if you can use immutable data in performance-critical parts of your application it's easy to implement a fast shouldComponentUpdate() method to significantly speed up your app. Dealing with immutable data in JavaScript is more difficult than in languages designed for it, like Clojure. However, we've provided a simple immutability helper, update(), that makes dealing with this type of data much easier,...

This package has been merged into the Julia standard library. As such, you probably just want to using REPL.TerminalMenus and skip the Installation instructions. The RadioMenu allows the user to select one option from the list. The request function displays the interactive menu and returns the index of the selected choice. If a user presses 'q' or ctrl-c, request will return a -1.

Paralline executes a python function (or lambda function) or a script over each line of huge text files, in parallel processes and aggregates the result to a list.

A small utility for visualizing graphics of the wide math function list. Based on Glade/GTK+ toolkit so integrates into GNOME flawlessly. Uses mathGl library for drawing purposes, see http://mathgl.sourceforge.net/