Read miniSEED file (Scripts) Publisher's description
from FranГ§ois Beauducel
cThe Standard for the Exchange of Earthquake Data (SEED) is an international standard format for the exchange of digital seismological data.
cThe Standard for the Exchange of Earthquake Data (SEED) is an international standard format for the exchange of digital seismological data. SEED was designed for use by the earthquake research community, primarily for the exchange between institutions of unprocessed earth motion data. It is a format for digital data measured at one point in space and at equal intervals of time. The SEED format consists of Volume Control Headers, Abbreviation Control Headers, Station Control Headers, Time Span Control Headers and finally Data Records. In complement to вЂњDatalessвЂќ SEED volumes, exists the вЂњData-onlyвЂќ volume called Mini-SEED (see http://www.iris.edu for further information).
The purpose of this function is to read miniSEED data files directly from Matlab, avoiding intermediate format conversion (like SAC or other formats for which many functions exist), and retrieving complete headers. Each data record is imported into a structure array, allowing to adress data blocks and header fields individually (useful for multi-channel files), just as concatenating all data with a simple cat(1,X.d) function. Time stamps are also converted into Matlab datenum format.
The function reads miniSEED "data-only" using the two mostly used compression formats Steim-1 and Steim-2. General FDSN formats have also been implemented (ASCII, 16/24/32-bit integers, IEEE floats and doubles), and GEOSCOPE multiplexed old formats (24-bit, 16/3 or 16/4-bit gain ranged). All these formats should work but some of them have not been tested using real data.
The function detects also automatically big/little-endian coded files.
Known Blockettes are 1000, 1001 and 100. If there is no Blockette 1000, default 4096-byte record length, big-endian and Steim-1 compression are used. These values can be set using additional arguments.
Some analysis can be done on the data stream (detection of gaps and overlaps), using extra output argument. Without any output argument, the function plots the data (works also in case of multi-channel file).
Steim-1/2 compression decoding strategy has been deeply optimized for Matlab. The proposed method, as vectorized as possible, is about 30 times faster than a 'C-like' loops coding... which is still 10 times slower than the same C-compiled program, but, well, this is the Matlab's other side of the coin!
Type "help rdmseed" or "doc rdmseed" for detailed usage and some examples.
System Requirements:MATLAB 7.9 (2009b)
Program Release Status: New Release
Program Install Support: Install and Uninstall