Results 3201-3250 of 3594 (3502 ASCL, 92 submitted)
SURF reduces data from the SCUBA instrument from the James Clerk Maxwell Telescope. Facilities are provided for reducing all the SCUBA observing modes including jiggle, scan and photometry modes. SURF uses the Starlink environment (ascl:1110.012).
surfinBH predicts the final mass, spin and recoil velocity of the remnant of a binary black hole merger. Trained directly against numerical relativity simulations, these models are extremely accurate, reproducing the results of the simulations at the same level of accuracy as the simulations themselves. Fits such as these play a crucial role in waveform modeling and tests of general relativity with gravitational waves, performed by LIGO.
The Surprise is a measure for consistency between posterior distributions and operates in parameter space. It can be used to analyze either the compatibility of separately analyzed posteriors from two datasets, or the posteriors from a Bayesian update. The Surprise Calculator estimates relative entropy and Surprise between two samples, assuming they are Gaussian. The software requires the R package CompQuadForm to estimate the significance of the Surprise, and rpy2 to interface R with Python.
surrkick quickly and reliably extract recoils imparted to generic, precessing, black hole binaries. It uses a numerical-relativity surrogate model to obtain the gravitational waveform given a set of binary parameters, and from this waveform directly integrates the gravitational-wave linear momentum flux. This entirely bypasses the need of fitting formulae which are typically used to model black-hole recoils in astrophysical contexts.
SUSHI (Semi-blind Unmixing with Sparsity for hyperspectral images) performs non-stationary unmixing of hyperspectral images. The typical use case is to map the physical parameters such as temperature and redshift from a model with multiple components using data from hyperspectral images. Applying a spatial regularization provides more robust results on voxels with low signal to noise ratio. The code has been used on X-ray astronomy but the method can be applied to any integral field unit (IFU) data cubes.
Swarm-NG is a C++ library for the efficient direct integration of many n-body systems using highly-parallel Graphics Processing Units (GPU). Swarm-NG focuses on many few-body systems, e.g., thousands of systems with 3...15 bodies each, as is typical for the study of planetary systems; the code parallelizes the simulation, including both the numerical integration of the equations of motion and the evaluation of forces using NVIDIA's "Compute Unified Device Architecture" (CUDA) on the GPU. Swarm-NG includes optimized implementations of 4th order time-symmetrized Hermite integration and mixed variable symplectic integration as well as several sample codes for other algorithms to illustrate how non-CUDA-savvy users may themselves introduce customized integrators into the Swarm-NG framework. Applications of Swarm-NG include studying the late stages of planet formation, testing the stability of planetary systems and evaluating the goodness-of-fit between many planetary system models and observations of extrasolar planet host stars (e.g., radial velocity, astrometry, transit timing). While Swarm-NG focuses on the parallel integration of many planetary systems,the underlying integrators could be applied to a wide variety of problems that require repeatedly integrating a set of ordinary differential equations many times using different initial conditions and/or parameter values.
SWarp resamples and co-adds together FITS images using any arbitrary astrometric projection defined in the WCS standard. It operates on pre-reduced images and their weight-maps. Based on the astrometric and photometric calibrations derived at an earlier phase of the pipeline, SWarp re-maps ("warps") the pixels to a perfect projection system, and co-adds them in an optimum way, according to their relative weights. SWarp's astrometric engine is based on a customized version of Calabretta's WCSLib 2.6 and supports all of the projections defined in the 2000 version of the WCS proposal.
SWIFT follows the long-term dynamical evolution of a swarm of test particles in the solar system. The code efficiently and accurately handles close approaches between test particles and planets while retaining the powerful features of recently developed mixed variable symplectic integrators. Four integration techniques are included: Wisdom-Holman Mapping; Regularized Mixed Variable Symplectic (RMVS) method; fourth order T+U Symplectic (TU4) method; and Bulirsch-Stoer method. The package is designed so that the calls to each of these look identical so that it is trivial to replace one with another. Complex data manipulations and results can be analyzed with the graphics packace SwiftVis.
SWIFT runs cosmological simulations on peta-scale machines for solving gravity and SPH. It uses the Fast Multipole Method (FMM) to calculate gravitational forces between nearby particles, combining these with long-range forces provided by a mesh that captures both the periodic nature of the calculation and the expansion of the simulated universe. SWIFT currently uses a single fixed but time-variable softening length for all the particles. Many useful external potentials are also available, such as galaxy haloes or stratified boxes that are used in idealised problems. SWIFT implements a standard LCDM cosmology background expansion and solves the equations in a comoving frame; equations of state of dark-energy evolve with scale-factor. The structure of the code allows implementation for modified-gravity solvers or self-interacting dark matter schemes to be implemented. Many hydrodynamics schemes are implemented in SWIFT and the software allows users to add their own.
Swiftbat retrieves, analyzes, and displays data from NASA's Swift spacecraft, especially data from the Swift Burst Alert Telescope (BAT). All BAT data are available from the Swift data archive; however, a few routines in this library use data access methods not available to the general public and thus are useful only to Swift team members. The package also installs a command-line program 'swinfo' that provides Swift Information such as what the MET (onboard-clock) time is, where Swift was pointing, and whether a specific source was above the horizon and/or in the field of view.
Swiftest is a software package designed to model the long-term dynamics of system of bodies in orbit around a dominant central body, such a planetary system around a star, or a satellite system around a planet. The main body of the program is written in Modern Fortran, taking advantage of the object-oriented capabilities included with Fortran 2003 and the parallel capabilities included with Fortran 2008 and Fortran 2018. Swiftest also includes a Python package that allows the user to quickly generate input, run simulations, and process output from the simulations. Swiftest uses a NetCDF output file format which makes data analysis with the Swiftest Python package a streamlined and flexible process for the user. Building off a strong legacy, including its predecessors Swifter and Swift, Swiftest takes the next step in modeling the dynamics of planetary systems by improving the performance and ease of use of software, and by introducing a new collisional fragmentation model. Currently, Swiftest includes the four main symplectic integrators included in its predecessors: WHM, RMVS, HELIO, and SyMBA. In addition, Swiftest also contains the Fraggle model for generating products of collisional fragmentation.
SWIFTGalaxy provides a software abstraction of simulated galaxies produced by the SWIFT smoothed particle hydrodynamics code. It extends the SWIFTSimIO module and is tailored to analyses of particles belonging to individual simulated galaxies. It inherits from and extends the functionality of the SWIFTDataset. It understands the output of halo finders and therefore which particles belong to a galaxy, and its integrated properties. The particles occupy a coordinate frame that is enforced to be consistent, such that particles loaded on-the-fly will match e.g. rotations and translations of particles already in memory. Intuitive masking of particle datasets is also enabled. Finally, some utilities to make working in cylindrical and spherical coordinate systems more convenient are also provided.
SwiftVis is a tool originally developed as part of a rewrite of Swift (ascl:1303.001) to be used for analysis and plotting of simulations performed with Swift and Swifter. The extensibility built into the design has allowed us to make SwiftVis a general purpose analysis and plotting package customized to be usable by the planetary science community at large. SwiftVis is written in Java and has been tested on Windows, Linux, and Mac platforms. Its graphical interface allows users to do complex analysis and plotting without having to write custom code.
SWIGLAL, a wrapper for and component of the LALSuite (ascl:2012.021) gravitational wave detection and analysis libraries, which are primarily written in C, makes LALSuite routines directly accessible to Python and Octave scripts.
SWOC (Spectral Wavelength Optimization Code) determines the wavelength ranges that provide the optimal amount of information to achieve the required science goals for a spectroscopic study. It computes a figure-of-merit for different spectral configurations using a user-defined list of spectral features, and, utilizing a set of flux-calibrated spectra, determines the spectral regions showing the largest differences among the spectra.
Swordfish studies the information yield of counting experiments. It implements at its core a rather general version of a Poisson point process with background uncertainties described by a Gaussian random field, and provides easy access to its information geometrical properties. Based on this information, a number of common and less common tasks can be performed. Swordfish allows quick and accurate forecasts of experimental sensitivities without time-intensive Monte Carlos, mock data generation and likelihood maximization. It can:
- calculate the expected upper limit or discovery reach of an instrument;
- derive expected confidence contours for parameter reconstruction;
- visualize confidence contours as well as the underlying information metric field;
- calculate the information flux, an effective signal-to-noise ratio that accounts for background systematics and component degeneracies; and
- calculate the Euclideanized signal which approximately maps the signal to a new vector which can be used to calculate the Euclidean distance between points.
SWOT (Super W Of Theta) computes two-point statistics for very large data sets, based on “divide and conquer” algorithms, mainly, but not limited to data storage in binary trees, approximation at large scale, parellelization (open MPI), and bootstrap and jackknife resampling methods “on the fly”. It currently supports projected and 3D galaxy auto and cross correlations, galaxy-galaxy lensing, and weighted histograms.
swyft implements Truncated Marginal Neural Radio Estimation (TMNRE), a Bayesian parameter inference technique for complex simulation data. The code improves performance by estimating low-dimensional marginal posteriors rather than the joint posteriors of distributions, while also targeting simulations to targets of observational interest via an indicator function. The use of local amortization permits statistical checks, enabling validation of parameters that cannot be performed using sampling-based methods. swyft is also based on stochastic simulations, mapping parameters to observational data, and incorporates a simulator manager.
The ROSAT X-Ray Background Tool (sxrbg) calculates the average X-ray background count rate and statistical uncertainty in each of the six standard bands of the ROSAT All-Sky Survey (RASS) diffuse background maps (R1, R2, R4, R5, R6, R7) for a specified astronomical position and a search region consisting of either a circle with a specified radius or an annulus with specified inner and outer radii centered on the position. The values returned by the tool are in units of 10^-6 counts/second/arcminute^2. sxrbg can also create a count-rate-based spectrum file which can be used with XSpec (ascl:9910.005) to calculate fluxes and offers support for counts statistics (cstat), an alternative method for generating a background spectrum. HEASoft (ascl:1408.004) is a prerequisite for building. The code is in the public domain.
SYGMA (Stellar Yields for Galactic Modeling Applications) follows the ejecta of simple stellar populations as a function of time to model the enrichment and feedback from simple stellar populations. It is the basic building block of the galaxy code One-zone Model for the Evolution of GAlaxies (OMEGA, ascl:1806.018) and is part of the NuGrid Python Chemical Evolution Environment (NuPyCEE, ascl:1610.015). Stellar yields of AGB and massive stars are calculated with the same nuclear physics and are provided by the NuGrid collaboration.
symbolic_pofk provides simple Python functions and a Fortran90 routine for precise symbolic emulations of the linear and non-linear matter power spectra and for the conversion σ 8 ↔ A s as a function of cosmology. These can be easily copied, pasted, and modified to other languages. Outside of a tested k range, the fit includes baryons by default; however, this can be switched off.
The Python package sympy2c allows creation and compilation of fast C/C++ based extension modules from symbolic representations. It can create fast code for the solution of high dimensional ODEs, or numerical evaluation of integrals where sympy fails to compute an anti-derivative. Based on the symbolic formulation of a stiff ODE, sympy2c analyzes sparsity patterns in the Jacobian matrix of the ODE, and generates loop-less fast code by unrolling loops in the internally used LU factorization algorithm and by avoiding unnecessary computations involving known zeros.
SYN++ is a standalone SN spectrum synthesis program. It is a rewrite of the original SYNOW (ascl:1010.055) code in modern C++. It offers further enhancements, a new structured input control file format, and the atomic data files have been repackaged and are more complete than those of SYNOW.
SYNAPPS is a spectrum fitter embedding a highly parameterized synthetic SN spectrum calculation within a parallel asynchronous optimizer. This open-source code is aimed primarily at the problem of systematically interpreting large sets of SN spectroscopy data.
The synchrofit (synchrotron fitter) package implements a reduced dimensionality parameterisation of standard synchrotron spectrum models, and provides fitting routines applicable for active galactic nuclei and supernova remnants. The Python code includes the Jaffe-Parola model (JP), Kardashev-Pacholczyk model (KP), and continuous injection models (CI/KGJP) for both constant or Maxwell-Boltzmann magnetic field distributions. An adaptive maximum likelihood algorithm is invoked to fit these models to multi-frequency radio observations; the adaptive mesh is customisable for either optimal precision or computational efficiency. Functions are additionally provided to plot the fitted spectral model with its confidence interval, and to derive the spectral age of the synchrotron emitting particles.
SYNMAG is a tool for producing synthetic aperture magnitudes to enable fast matched photometry at the catalog level without reprocessing imaging data. Aperture magnitudes are the most widely tabulated flux measurements in survey catalogs; obtaining reliable, matched photometry for galaxies imaged by different observatories represents a key challenge in the era of wide-field surveys spanning more than several hundred square degrees. Methods such as flux fitting, profile fitting, and PSF homogenization followed by matched-aperture photometry are all computationally expensive. An alternative solution called "synthetic aperture photometry" exploits galaxy profile fits in one band to efficiently model the observed, point-spread-function-convolved light profile in other bands and predict the flux in arbitrarily sized apertures.
SYNOW is a highly parameterized spectrum synthesis code used primarily for direct (empirical) analysis of SN spectra. The code is based on simple assumptions : spherical symmetry; homologous expansion; a sharp photosphere that emits a blackbody continuous spectrum; and line formation by resonance scattering, treated in the Sobolev approximation. Synow does not do continuum transport, it does not solve rate equations, and it does not calculate ionization ratios. Its main function is to take line multiple scattering into account so that it can be used in an empirical spirit to make line identifications and estimate the velocity at the photosphere (or pseudo-photosphere) and the velocity interval within which each ion is detected. these quantities provide constraints on the composition structure of the ejected matter.
Synphot simulates photometric data and spectra, observed or otherwise. It can incorporate the user's filters, spectra, and data, and use of a pre-defined standard star (Vega), bandpass, or extinction law. synphot can also construct complicated composite spectra using different models, simulate observations, and compute photometric properties such as count rate, effective wavelength, and effective stimulus. It can manipulate a spectrum by, for example, applying redshift, or normalize it to a given flux value in a given bandpass. Synphot can also sample a spectrum at given wavelengths, plot a quick-view of a spectrum, and perform repetitive operations such as simulating the observations of multiple type of sources through multiple bandpasses. Synphot understands Astropy (ascl:1304.002) models and units and is an Astropy affiliated package. Support for HST and JWST is available through the extension stsynphot (ascl:2010.003).
Synspec is a user-oriented package written in FORTRAN for modeling stellar atmospheres and for stellar spectroscopic diagnostics. It assumes an existing model atmosphere, calculated previously with Tlusty or taken from the literature (for instance, from the Kurucz grid of models). The opacity sources (continua, atomic and molecular lines) are fully specified by the user. An arbitrary stellar rotation and instrumental profile can be applied to the synthetic spectrum.
Synth3 is a non-magnetic spectrum synthesis code. It works with model atmospheres in Kurucz format and VALD Sf line lists and features element stratification, molecular equilibrium and individual microturbulence for each line. Disk integration can be done with s3di which is included in the archive. Synth3 computes spectra emergent from the stellar atmospheres with a depth-dependent chemical composition if depth-dependent abundance is provided in the input model atmosphere file.
Synthetic LISA simulates the LISA science process at the level of scientific and technical requirements. The code generates synthetic time series of the LISA fundamental noises, as filtered through all the TDI observables, and provides a streamlined module to compute the TDI responses to gravitational waves, according to a full model of TDI, including the motion of the LISA array, and the temporal and directional dependence of the armlengths.
Synthetic Population of Interstellar Objects generates a synthetic population of interstellar objects (orbits and sizes) in arbitrary volume of space around the Sun. The only necessary assumption is that the population of ISOs in the interstellar space (far from any massive body) is homogeneous and isotropic. The assumed distribution of interstellar velocities of ISOs has to be provided as an input. This distribution can be defined analytically, but also in a discrete form. The algorithm, based on the multivariate inverse transform sampling method, is implemented in Python.
The Feed Forward Neural Network SYSNet models the relationship between the imaging maps, such as stellar density and the observed galaxy density field, in order to mitigate the systematic effects and to make a robust galaxy clustering measurements. The cost function is Mean Squared Error and a L2 regularization term, and the optimization algorithm is Adaptive Moment (ADAM).
Systemic Console is a tool for advanced analysis of exoplanetary data. It comprises a graphical tool for fitting radial velocity and transits datasets and a library of routines for non-interactive calculations. Among its features are interactive plotting of RV curves and transits, combined fitting of RV and transit timing (primary and secondary), interactive periodograms and FAP estimation, and bootstrap and MCMC error estimation. The console package includes public radial velocity and transit data.
SZpack is a numerical library which allows fast and precise computation of the Sunyaev-Zeldovich (SZ) signal for hot, moving clusters of galaxies. Both explicit numerical integration as well as approximate representation of the SZ signals can be obtained. Variations of the electron temperature and bulk velocity along the line-of-sight can be included. SZpack allows very fast and precise (<~0.001% at frequencies h nu <~ 30kT_g and electron temperature kTe ~ 75 keV) computation and its accuracy practically eliminates uncertainties related to more expensive numerical evaluation of the Boltzmann collision term. It furthermore cleanly separates kinematic corrections from scattering physics, effects that previously have not been clarified.
The T-Matrix package includes codes to compute electromagnetic scattering by homogeneous, rotationally symmetric nonspherical particles in fixed and random orientations, randomly oriented two-sphere clusters with touching or separated components, and multi-sphere clusters in fixed and random orientations. All codes are written in Fortran-77. LAPACK-based, extended-precision, Gauss-elimination- and NAG-based, and superposition codes are available, as are double-precision superposition, parallelized double-precision, double-precision Lorenz-Mie codes, and codes for the computation of the coefficients for the generalized Chebyshev shape.
T-PHOT extracts accurate photometry from low-resolution images of extragalactic fields, where the blending of sources can be a serious problem for accurate and unbiased measurement of fluxes and colors. It gathers data from a high-resolution image of a region of the sky and uses the source positions and morphologies to obtain priors for the photometric analysis of the lower resolution image of the same field. T-PHOT handles different types of datasets as input priors, including a list of objects that will be used to obtain cutouts from the real high-resolution image, a set of analytical models (as .fits stamps), and a list of unresolved, point-like sources, useful for example for far-infrared wavelength domains. T-PHOT yields accurate estimations of fluxes within the intrinsic uncertainties of the method when systematic errors are taken into account (which can be done using a flagging code given in the output), and handles multiwavelength optical to far-infrared image photometry. T-PHOT was developed as part of the ASTRODEEP project (www.astrodeep.eu).
T-RECS produces radio sources catalogs with user-defined frequencies, area and depth. It models two main populations of radio galaxies, Active Galactic Nuclei (AGNs) and Star-Forming Galaxies (SFGs), and corresponding sub-populations. T-RECS is not computationally demanding and can be run multiple times, using the same catalog inputs, to project the simulated sky onto different fields.
This IDL code returns the dust temperature of a galaxy from its redshift, SFR and stellar mass; it can also predict the observed monochromatic fluxes of the galaxy. These monochromatic fluxes correspond to those of a DH SED template with the appropriate dust temperature and the appropriate normalization. Dust temperatures and fluxes predictions are only valid and provided in the redshift, stellar mass, SSFR and wavelength ranges 0 < z < 2.5, Mstar> 10^10 Msun, 10^-11 < SSFR[yr-1]< 10^-7 and 30um < lambda_rest < 2mm.
TA-DA is a pre-compiled IDL widget-based application which greatly simplifies and improves the analysis of stellar photometric data in comparison with theoretical models and allows the derivation of stellar parameters from multi-band photometry. It is flexible and can address a number of problems, from the interpolation of stellar models or sets of stellar physical parameters in general to the computation of synthetic photometry in arbitrary filters or units. It also analyzes observed color-magnitude diagrams and allows a Bayesian derivation of stellar parameters (and extinction) based on multi-band data.
TAC-maker allows for rapid and interactive calculation of synthetic planet transits by numerical computations of the integrals, allowing the use of an arbitrary limb-darkening law of the host star. This advantage together with the practically arbitrary precision of the calculations makes the code a valuable tool for the continuously increasing photometric precision of ground-based and space observations.
TACHE (TensoriAl Classification of Hydrodynamic Elements) performs classification of the eigenvalues of either the tidal tensor or the velocity shear tensor at the point of a smoothed particle. This provides local information as to how matter is collapsing or flowing, respectively, in particular what stable manifold is being produced. The code reads in smoothed particle hydrodynamics (SPH) snapshot files in sphNG format and computes neighbor lists for SPH data and either the (symmetric) velocity shear tensor or tidal tensor and their eigenvalues/eigenvectors. It classifies fluid elements by number of "positive" eigenvalues and permits decomposition of snapshots into classified components; it also includes several Python plotting scripts.
The Action Computation Tool (TACT) tests methods for estimating actions, angles and frequencies of orbits in both axisymmetric and triaxial potentials, including general spherical potentials, analytic potentials (Isochrone and Harmonic oscillator), axisymmetric Stackel fudge, average generating function from orbit (AvGF), and others. It is written in C++; code is provided to compile the routines into a Python library. TM (ascl:1512.014) and LAPACK are required to access some features.
TailZ estimates redshift distributions of photometric samples of galaxies selected photometrically given a subsample with measured spectroscopic redshifts. The approach uses a non-parametric Voronoi tessellation density estimator to interpolate the galaxy distribution in the redshift and photometric color space. The Voronoi tessellation estimator performs well at reconstructing the tails of the redshift distribution of individual galaxies and gives unbiased estimates of the first and second moments.
This Python package allows the user to setup and run an agent-based simulation of a SETI survey. The package allows the creation of a population of observing and transmitting civilisations. Each transmitter and observer conducts their activities according to an input strategy. The success of observers and transmitters can then be recorded, and multiple simulations can be run for Monte Carlo Realisation.
This package is therefore a flexible framework in which to simulate and test different SETI strategies, both as an Observer and as a Transmitter. It is primarily designed with radio SETI in mind, but is sufficiently flexible to simulate all forms of electromagnetic SETI, and potentially neutrino and gravitational wave SETI.
TALYS simulates nuclear reactions which involve neutrons, gamma-rays, protons, deuterons, tritons, helions and alpha-particles, in the 1 keV-200MeV energy range. A suite of nuclear reaction models has been implemented into a single code system, enabling one to evaluate basically all nuclear reactions beyond the resonance range. In particular, TALYS estimates the Maxwellian-averaged reaction rates that are of astrophysical relevance. This enables reaction rates to be calculated with increased accuracy and reliability and the approximations of previous codes to be investigated. The TALYS predictions for the thermonuclear rates of relevance to astrophysics are detailed and compared with those derived by widely-used codes for the same nuclear ingredients. TALYS predictions may differ significantly from those of previous codes, in particular for nuclei for which no or little nuclear data is available. The pre-equilibrium process is shown to influence the astrophysics rates of exotic neutron-rich nuclei significantly. The TALYS code provides a tool to estimate all nuclear reaction rates of relevance to astrophysics with improved accuracy and reliability.
TAME measures the equivalent width (EWs) in high-resolution spectra. Written by IDL, TAME provides the EWs of spectral lines by profile fitting in an automatic or interactive mode and is reliable for measuring EWs in a spectrum with a spectral resolution of R ≳ 20000. It offers an interactive mode for more flexible measurement of the EW and a fully automatic mode that can simultaneously measure the EWs for a large set of lines.
Tangos builds databases (along the lines of Eagle or MultiDark) for cosmological and zoom simulations. Its modular system generates and queries databases. It is designed to store and manage results from a user's own analysis code, provides web and python interfaces, and allows users to construct science-focused queries, including across entire merger trees, without requiring knowledge of SQL. Tangos manages the process of populating the database with science data, including auto-parallelizing the analysis. It can be customized to work with multiple python modules such as pynbody (ascl:1305.002) or yt (ascl:1011.022) to process raw simulation data; it defaults to using SQLite, but allows use of other databases as the underlying store through the use of SQLAlchemy.
Tangra performs scientific grade data reduction of GPS time-tagged video observations, including reduction of stellar occultation light curves and astrometry of close flybys of Near Earth Objects. It offers Dark and Flat frame image correction, PSF and aperture photometry, multiple methods for deriving a background as well as extensibility via add-ins. Tangra is actively developed for Windows and the current version of the software supports UCAC2, UCAC3, UCAC4, NOMAD, PPMXL and Gaia DR2 star catalogues for astrometry. The software can perform motion-fitting for fast objects and derive a mini-normal astrometric positions. The supported video file formats are AVI, SER, ADV and AAV. Tangra can be also used with observations recorded as a sequence of FITS files. There are also versions for Linux and OS-X with more limited functionality.
tapify implements a suite of multitaper spectral estimation techniques for analyzing time series data. It supports analysis of both evenly and unevenly sampled time series data. The multitaper statistic tackles the problems of bias and consistency, which makes it an improvement over the classical periodogram for evenly sampled data and the Lomb-Scargle periodogram for uneven sampling. In basic statistical terms, this estimator provides a confident look at the properties of a time series in the frequency or Fourier domain.
Would you like to view a random code?