seismogram files in the WAV(audio) format. The data are squeezed to
audible frequencies.
ObsPy is an open-source project dedicated to provide a Python framework
for processing seismological data. It provides parsers for common
file formats and seismological signal processing routines which allow
the manipulation of seismological time series (see Beyreuther et. al.
2010). The goal of the ObsPy project is to facilitate rapid application
development for seismology.
WWW: http://www.obspy.org/
scientific data in the free, portable HDF5 format.
Besides providing a simple tool for batch visualization as PNG images,
h5utils also includes programs to convert HDF5 datasets into the formats
required by other free visualization software (e.g. plain text, Vis5d,
and VTK).
WWW: http://ab-initio.mit.edu/wiki/index.php/H5utils
PR: ports/155482
Submitted by: Klaus Aehlig <aehlig at linta.de>
for ObsPy. It includes UTCDateTime, Stats, Stream and Trace
classes and methods for reading seismograms.
ObsPy is an open-source project dedicated to provide a Python
framework for processing seismological data. It provides
parsers for common file formats and seismological signal
processing routines which allow the manipulation of
seismological time series (see Beyreuther et. al. 2010).
The goal of the ObsPy project is to facilitate rapid application
development for seismology.
WWW: http://www.obspy.org/
for seismology. Capabilities include filtering, triggering,
rotation, instrument correction and coordinate transformations.
ObsPy is an open-source project dedicated to provide a Python
framework for processing seismological data. It provides parsers
for common file formats and seismological signal processing
routines which allow the manipulation of seismological time
series (see Beyreuther et. al. 2010). The goal of the ObsPy
project is to facilitate rapid application development for seismology.
WWW: http://www.obspy.org/
for ObsPy. It includes UTCDateTime, Stats, Stream and Trace
classes and methods for reading seismograms.
ObsPy is an open-source project dedicated to provide a Python
framework for processing seismological data. It provides
parsers for common file formats and seismological signal
processing routines which allow the manipulation of
seismological time series (see Beyreuther et. al. 2010).
The goal of the ObsPy project is to facilitate rapid application
development for seismology.
WWW: http://www.obspy.org/
BUFR is approved by WMO (World Meteorological Organization) as the standard
universal exchange format for meteorological observations, gradually
replacing a lot of older alphanumeric data formats.
This module provides methods for decoding and encoding BUFR messages, and
for displaying information in BUFR B and D tables and in BUFR flag and code
tables.
Installing this module also installs some programs: bufrread.pl,
bufrresolve.pl, bufrencode.pl, bufr_reencode.pl and bufralter.pl. See
https://wiki.met.no/bufr.pm/start for examples of use. For the majority of
potential users of Geo::BUFR I would expect these programs to be all that
you will need Geo::BUFR for.
WWW: http://search.cpan.org/dist/Geo-BUFR/
applications. The package includes: Bayes Regression (univariate or
multivariate dep var), Bayes Seemingly Unrelated Regression (SUR), Binary and
Ordinal Probit, Multinomial Logit (MNL) and Multinomial Probit (MNP),
Multivariate Probit, Negative Binomial (Poisson) Regression, Multivariate
Mixtures of Normals (including clustering), Dirichlet Process Prior Density
Estimation with normal base, Hierarchical Linear Models with normal prior and
covariates, Hierarchical Linear Models with a mixture of normals prior and
covariates, Hierarchical Multinomial Logits with a mixture of normals prior
and covariates, Hierarchical Multinomial Logits with a Dirichlet Process
prior and covariates, Hierarchical Negative Binomial Regression Models,
Bayesian analysis of choice-based conjoint data, Bayesian treatment of linear
instrumental variables models, and Analysis of Multivariate Ordinal survey
data with scale usage heterogeneity (as in Rossi et al, JASA (01)).
WWW: http://www.perossi.org/home/bsm-1
to the R users. It has grown and I think it can be of interest for
the users wanting to implement their own training algorithms as well as
for those others whose needs lye only in the "user space".
WWW: http://rwiki.sciviews.org/doku.php?id=packages:cran:amore
switch some dependencies from science/hdf5 to science/hdf5-18.
As a side note: I think that all ports depending on science/hdf5
could be switched to science/hdf5-18, by defining H5_USE_16_API
when necessary, and then science/hdf5 could be deprecated.
PR: ports/154736
Changes:
- Eliminate expectation and use of leading scale factor in the "have"
unit of udunits2(1).
- Add verification of commit status to "make ftp".
- Add dependency of documentation on version.
- Add "force" flag to tagging rule in makefile.
Feature safe: yes
is designed to produce publication-ready Postscript or PDF
output. SVG, EMF and bitmap formats export are also supported.
The program runs under Unix/Linux, Windows or Mac OS X, and
binaries are provided. Data can be read from text, CSV or FITS
files, and data can be manipulated or examined from within the
application.
WWW: http://home.gna.org/veusz/
PR: ports/153686
Submitted by: Stas Timokhin <devel@stasyan.com>
