Search Results for "spectral"

The hsdar package contains classes and functions to manage, analyse and simulate hyperspectral data. These might be either spectrometer measurements or hyperspectral images through the interface of rgdal.

...Besides the search utility by the Raman band positions, which was proven to be priceless in the interpretation of Raman spectra, the RDSS software gives the user the ability to display and inspect the Raman spectra quickly and very efficiently. Users can zoom into the Raman spectrum, shift in any direction the wavenumber and the intensity axes, and if any part of the spectral display is clicked, that region will be highlighted and the specific wavenumber returned. A photo for every sample entry stored in the database is also available.

Spectral Python (SPy) is a python package for reading, viewing, manipulating, and classifying hyperspectral image (HSI) data. SPy includes functions for clustering, dimensionality reduction, supervised classification, and more.

A lightweight hyperspectral imaging library that provides developers with spectral algorithms for the Python programming language. New for v0.14.x: a scikit-learn bridge (alpha and partial). The functions and classes are organized by topics: * abundance maps: FCLS, NNLS, UCLS * classification: AbundanceClassification, NormXCorr, KMeans SAM, SID, SVC * detection: ACE, CEM, GLRT, MatchedFilter, OSP * distance: chebychev, NormXCorr, SAM, SID * endmembers extraction: ATGP, FIPPI, NFINDR, PPI * material count: HfcVd, HySime * noise: Savitzky Golay, MNF, whiten * sigproc: bilateral * sklearn: HyperEstimatorCrossVal, HyperSVC and others * spectro: convex hull quotient, features extraction (tetracorder style), USGS06 lib interface * util: load_ENVI_file, load_ENVI_spec_lib, corr, cov and others The library do an extensive use of the numpy numeric library and can achieve good speed. ...

A computer program for a fast and accurate determination of Sb/(Sb+As) content ratio in the tetrahedrite-tennantite and bournonite-seligmannite solid solution series by at least one spectral parameter (band position or relative intensity) of their Raman spectra.

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.