gmsp processes ground-motion time histories, computes
response spectra and intensity measures, selects and matches records,
and composes modal decomposition and reconstruction through
xemd.
library(gmsp)
describeModule()
help(package = "gmsp")describeModule() returns the installed package name and
version. The function help documents arguments, returned objects and
effects.
| Work | Entry points | Result |
|---|---|---|
| Time histories | buildTSL(), normalizeTSL() |
Acceleration, velocity and displacement histories; scaling by a reference peak |
| Spectra and intensities | computeSpectraTSL(),
measureIntensitiesTSL() |
Response spectra and scalar intensity measures |
| Provider records | parseRecord(), selectRecords() |
Native-unit samples and selected record identities |
| Modal analysis | decomposeRecords(),
reconstructRecords() |
Native xemd tables, mode selection and reintegrated
histories |
| Project products | selectProject(), rankProject(),
processProject(), matchProject(),
exportProject() |
Selection, processing, matching and delivery files from JSON contracts |
Time-history tables use OCID, ID,
t and s for component, quantity, time in
seconds and sample value. The explicit by argument
identifies record metadata; character() declares one record
without metadata. buildTSL() returns AT,
VT and DT on a common grid per record. Its
unit arguments declare the source and target length bases.
computeSpectraTSL() requires damping ratios and positive
periods; rotated D50 or D100 components also require
nTheta. reconstructRecords() selects modes by
a frequency band or energy fraction with an explicit keep/remove action.
The modal results retain native diagnostics and termination fields,
including iteration limits and non-convergence. Stochastic
decomposeRecords() calls consume the caller’s random
stream.
Project functions read their JSON contract relative to
root and publish the products described in their help.
processProject() supports the gmsp,
trim, imf, imfTS and
psa stages with explicit scientific controls. Its
stochastic modal stage requires an explicit seed and serial execution
settings and records execution evidence.
The function manuals describe arguments, data requirements and publication behavior. The documentation site, https://kanameishi.github.io/gmsp/, publishes the function reference and the books Mathematical Basis and Numerical Implementation.