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Published March 3, 2022 | Version 1.0
Software Open

TIITBA - a graphical interface for historical seismograms, vectorization, analysis and, correction

  • 1. Posgrado, UNAM
  • 2. Instituto de Geofisica, UNAM

Description

Tiitba is a new interactive portable multi-platform software developed to vectorize smoked paper seismograms from, but not limited to, Wiechert seismographs. It is completely coded in Python as an open-source Graphical User Interface (GUI).

This software aims for the preservation of historical seismograms, mainly those from the early 20th century recorded on smoked paper, and the use of the vectorized time-series for a modern seismological re-analysis.

  • # DOWNLOAD

Download all the files from the zenodo repository. DOI: 10.5281/zenodo.6272823
Unpack the bin.tar and Pictures.tar files, the resulting folders should be placed in the same directory as the rest of the files.

  • # INSTALATION

Tiitba is coded on Python3, we recommend Python by Anaconda for running the program.

For Linux and MacOS operating systems run the bash file install_??.sh
This file checks if Anaconda3 is installed and creates the tiitba virtual environment.
This also creates a directory that contains the Python source code of Tiitba GUI on a given local directory and a desktop shortcut.

If you have Anaconda3 installed, you just need to create the virtual environment.

$ conda activate

$ conda env create -f tiitba_env.yml

If you do not have an Anaconda3 and you do not want to install it, the following libraries must be installed on your local python to execute Tiitba GUI: OpenCV V4.5.3, ObsPy, Pillow, numpy, and matplotlib.

Every time you want to use Tiitba GUI, you have to activate the tiitba python environment

$ conda activate tiitba

You can add the Tiitba installation path on your bash to run the GUI from any directory. To start the GUI just type in a terminal tiitbaGUI.py in any directory.

For Windows operating system, there is a beta version Setup Installer.
Any failure, comment, and recommendation are very well received by the authors.

Files

README.md

Files (256.1 MB)

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Additional details

Related works

Cites
Dataset: 10.5281/zenodo.6262066 (DOI)