Analyzing MiniSEED seismic data in MATLAB
For details on the usage, visit the earthinversion post: https://www.earthinversion.com/utilities/converting-mseed-data-to-mat-and-analyzing-in-matlab/
Output data structure
statscontains all the meta data information corresponding to each trace, anddatacontain the time series data
mat_file.mat -> stats, data
stats -> stats_0, stats_1, ...
data -> data_0, data_1, ...
Usage
from miniseed2mat.miniseed2mat import convertmseed2mat
mseedfile = "myStream.mseed"
convertmseed2mat(mseedfile, output_mat=None)
Read mat file in MATLAB
clear; close all; clc;
wdir='./';
fileloc0=[wdir,'myStream'];
fileloc_ext = '.mat';
fileloc = [fileloc0 fileloc_ext];
if exist(fileloc,'file')
disp(['File exists ', fileloc]);
load(fileloc);
all_stats = fieldnames(stats);
all_data = fieldnames(data);
% for id=1:length(fieldnames(data))
for id=1
stats_0 = stats.(all_stats{id});
data_0 = data.(all_data{id});
sampling_rate = getfield(stats_0,'sampling_rate');
delta = getfield(stats_0,'delta');
starttime = getfield(stats_0,'starttime');
endtime = getfield(stats_0,'endtime');
t1 = datetime(starttime,'InputFormat',"yyyy-MM-dd'T'HH:mm:ss.SSS'Z'");
t2 = datetime(endtime,'InputFormat',"yyyy-MM-dd'T'HH:mm:ss.SSS'Z'");
datetime_array = t1:seconds(delta):t2;
%% plot time series
fig = figure('Renderer', 'painters', 'Position', [100 100 1000 400], 'color','w');
plot(t1:seconds(delta):t2, data_0, 'k-')
title([getfield(stats_0,'network'),'-', getfield(stats_0,'station'), '-', getfield(stats_0,'channel')])
axis tight;
print(fig,['./',fileloc0, '_ts', num2str(id),'.jpg'],'-djpeg')
% close all;
end
end
Metadata
Release files for miniseed2mat 0.1.7
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| File | Size | Uploaded | Provenance | Actions |
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Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
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| miniseed2mat-0.1.7-py3-none-any.whl | Python 3 | none | any | Details for miniseed2mat-0.1.7-py3-none-any.whl |
Total release size: 6.2 kB
Release files / miniseed2mat-0.1.7.tar.gz
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