Search Results for "python data analysis"
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Showing 13 open source projects for "python data analysis"
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PAMGUARD
Detection Classification and Localisation of marine mammals
The PAMGUARD project develops software to help detect, locate and classify marine mammals using Passive Acoustic Monitoring. This project is being migrated to github at https://github.com/PAMGuard. Please go there for the latest updates. thank you sourceforge for hosting us for all these years. -
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GenoCline
GenoCline is a free Java software for genetic cline analysis
Identification of clines from allele frequency or genome-wide databases. Angular transformation. Sigmoid function. Parameterization of a cline: orientation, Pearson’s product-moment correlation coefficient, linear and sigmoid regression and coefficient of determination. Graphical representation of the cline. Confidence limits. Spatial autocorrelation. Moran's index. Isolation by distance. Exponential regression. Correlation Fst/Distance. Centroid method. Cline's expected vs. predicted... -
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Piko stats
Piko solar inverter data communicator and manager
Piko solar inverter interface. Get online real time data and status. Get also history data. Database management of data. Exports, graphs, ... Manage data and stats using a SQLite or MySQL database. Third party intergration. See the Wiki home page for more informations. -
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Hydroponic Automation Platform (HAPI)
Technologies for automating food production on various scales
The Hydroponic Automation Platform Initiative (HAPI) develops and provides hardware and software components for automating food production using hydroponic, aquaponics, and precision agriculture techniques. High-yield production in urban settings is one of the primary goals. Artifacts include hardware design (mainly Arduino-based), firmware, management software and reporting modules. -
Waitlist App and Paging SystemStreamline your customer flow with our SMS-powered waitlist, reservations, and queue management app for restaurants, health care providers, and many other businesses.
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phenotemp
phenological trends using NOAA AVHRR time series
Starting from GIMMS values as ascii data (each line will be treated as individual time series), the application can smooth the ts - values by applying different algorithm that are based on Fouriertransformation. Separation of seasonal figure as well as the detection of linear trends is possible. Possible breaks in longterm mean can be detected with a change-point analysis using CuSum algorithms. -
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u/sbmv2012
Taxonomy assignment of metazoans using a python based pipeline
The aim of this project is to create an automated pipeline for taxonomic assignment of DNA sequences obtained from environmental samples. We develop a series of python scripts to process the raw sequence data obtained from benthic environmental samples and to taxonomical assignment of these sequences and finally to integrate all data in a relational database. -
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BioMa is a specimen based Biodiversity database Manager. It is designed to store, organize, and manipulate biodiversity-related scientific data, either for the purposes of museums, scientific collections, or research projects.
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birdweights is a a package of scripts to analyze data from an automated system for the measurement of mass and identification of birds at perches.
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MBAS -- Macro-Biological Analysis System -- provides a set of interoperable tools for aid in the analysis of biological data. The backing database is currently PostgreSQL and the primary language is C, though some data entry tools are written in Java.
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geoscipy
Python-accessible toolkit for Geoscience & Remote Sensing Applications
GeoSciPy is a set of C and Python functions that provide an API for all aspects of Geoscience and Remote Sensing Applications. Functions include reading/writing of many data formats, images, vectors, ..., and processing of images, vectors, ... including map projections, ... The library is written C, using HDF5 as the file format for storage of all remotely-sensed data and ancillary data, as well as processed data. -
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Obs-dm aims to provide a robust and reliable way to collect, analyze, and share observational data. It is being designed for extendability into other areas such as fisheries and habitat science.
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