Search Results for "python time series analysis"

This package is a VLF receiver for monitoring VLF transmitter signals for evidence of transients indicating ionospheric disturbances, usually caused by x-ray bursts from the sun. It takes sample pairs from dual-channel sound cards and spectrally processes them to Stokes parameters. Data are plotted as time series and in scatter plots.

CAIRO for AERMOD v1.1 by MSc Dominik Subotić Simplified training software Avaliable: www.sourceforge.net/projects/cairo-for-aermod/ QGIS plugin: CAIROforAERMOD (Coming 2025.) Tutorial: https://www.youtube.com/watch?v=DZnsJuu1zLc AERMAP, AERMOD and AERPLOT analysis tool and input file compiler. Features: Automatic input by copying coordinates (Google Maps or text) and automatic conversion to UTM. Sources are automatically visualised in Google Earth. Input is done through user...

* Please check latest update on https://github.com/igps-ftk/iGPS A tool written in Interactive Data Language (IDL), for processing and analyzing daily continuous GPS position time series. It can read time series in various formats, detect outliers, remove abnormal observation spans, find jumps, extract common-mode components(CMC), etc.

Geophysical Library is a C++-library to handle geophysical data. At the moment the focus is on magnetotelluric and seismic data. It also includes a genetic algorithm for data inversion, signal processing and statistics routines.

Along with calculating basic statistics and quality parameters such as mean and variance, the soft-ware is capable of importing and visualizing different standard time series formats, determining and removing jumps and outliers, and makes numerical and publication quality graphical outputs. Bivariate statistical analysis (including correlation coefficient and linear regression) and time series analysis (including auto and cross-spectral analysis, wavelet power spectrum, spectrogram and periodicities) form the main analysis features of the software.

This project provides a Fortran90 library and a python module for singular spectrum analyses such as PCA/EOF or MSSA. It is intended for people interested, for example, in analysing climate or financial variability.

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. Phenological events such as start-of-season, day-of-max/day-of-min, end-of-season can be determined via threshold-based algorithms or via analysis of max. increase of NDVI during green-up. ...

Tidal Analysis Program in PYthon (TAPPY) uses the least squares optimization function from scipy to perform a harmonic analysis (calculate amplitude and phases of a set of sine waves) of a hourly time series of water level values.

Meteorologists use the FPA to create a series of weather charts, known as depictions, that show weather fields over a sequence of times. The weather fields can contain grid point data or sets of areas, lines or scattered points. The weather depictions are not just graphical displays, but windows into an object database. By connecting processes to the database, forecast offices can automatically generate forecast products or run local models, while spending more of their time on weather analysis, diagnosis and prognosis.

To develop a software package for time series manipulation and cycles analysis. Cycles means repeated occurrences at nearly equal time intervals in any time series data. See http://www.cyclesresearchinstitute.org/ for a site about cycles.