Fileshack is an open source web application for hosting a web file storage, focusing on providing a repository for exchanging documents in groups of small number of people. It has a simple interface and an open permission model, anyone who knows the access code can download, upload and delete files, or opt-in to receive notifications.
ccplot is an open source command-line application for producing two-dimensinal plots of profile, layer and earth view data from CloudSat, CALIPSO and Aqua satellites.
django-attach is a django admin plugin for attaching files to model instances with multiple file selection support. Its main feature is a custom admin inline form. Requires a modern browser supporting HTML5 and XMLHttpRequest2, but falls back to the plain django inline form when these are not available.
PictureSlider allows you to create an unobtrusive and easy-to-control picture preview box, controlled by two arrows on the sides, or by keyboard. Optional caption is displayed in a panel at the bottom of the box.
wstcp is a node.js client and server implementation of TCP forwarding over WebSocket. wstcp supports local and remote port forwarding, similar to OpenSSH.
Convert Metek MRR-2 micro rain radar data files to NetCDF. mrr2c is an open source program which converts Metek Micro Rain Radar 2 (MRR-2) data to NetCDF. RAW, PRO and AVE files are supported.
cl2nc is a command-line Python program for converting Vaisala CL51 and CL31 dat files to NetCDF.
Convert Sigma Space Micro Pulse Lidar (MPL) data files to NetCDF. mpl2nc is a Python program for converting binary MPL files to NetCDF4. The converted variables closely follow those in the binary files.
ALCF is an open source command line tool for processing of automatic lidar and ceilometer (ALC) data and intercomparison with atmospheric models such as general circulation models (GCMs), numerical weather prediction models (NWP) and reanalyses with a lidar simulator using the COPS instrument simulator framework. ALCs are vertically pointing atmospheric lidars, measuring cloud and aerosol backscatter. The primary focus of ALCF are atmospheric studies of cloud using ALC observations and model cloud validation.
ccbrowse is an open source web application for browsing data from atmospheric profilers. It is comprised of a web application and a backend for importing various types of product files.
ds-format is an open source program, a Python package and a storage format which provides an interface for reading and writing NetCDF files, as well as its own optional data file format. The data format and interface are a simpler alternative to other more complex interfaces and formats, while supporting most of the same essential functions.
Scientific time library for Python
Command-line program for converting native radiosonde data to NetCDF and calculation of derived quantities, supporting InterMet Systems (iMet) and Windsond radiosondes.
PST is a format for structured text modelled after Bourne shell expressions and JSON. PST supports strings, numbers (integers and floating-point), boolean, missing values (none), arrays, objects (key-value pairs), single-character flags, and string flags. Relative to JSON, PST is simpler, while supporting many of its features. PST aims to be a unified human and machine-readable format for command line argument passing, standard input/output and config file formatting which is easier to read and write than JSON. PST is smilar to YAML, but simpler, supporing one-line expressions, and is more consistent with conventions on GNU systems.
Create bunyan streams from JSON configuration.
RTC performs cluster analysis using trees. A tree approximates the probability density function from which data has been drawn. A set of such trees is inferred using a Metropolis-Hastings sampler, and returned as a partitioning of the parameter space into rectangular segments.
The tree clustering library performs clustering of elements using trees. Elements are defined by a set of numerical (metric) parameters. A tree approximates the probability density function from which elements have been drawn by partitioning the parameter space hierarchically into a number of rectangular segments, on which the probability density function is assumed to have a uniform distribution. Clustering trees are generated using a Metropolis-Hastings sampler.