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Figure 15. Azimuthal distribution.

Figure 15 Azimuthal distribution.

Related Figures (51)

description of what they do. Below is the list of all SeisComP3 modules, the group they belong and a short
description of what they do. Below is the list of all SeisComP3 modules, the group they belong and a short
Figure 3. SeisComP3’s modules and their description with most library functionality accessible from Python scripts through
Figure 3. SeisComP3’s modules and their description with most library functionality accessible from Python scripts through
Scisola: Automatic Moment Tensor solution for SeisComP3
Scisola: Automatic Moment Tensor solution for SeisComP3
Figure 5. Screenshot of the ISOLA-GUI tool for data pre-processing.[12] it is available for free.[11][12] source code is documented in a manual, accompanied by a test example an
Figure 5. Screenshot of the ISOLA-GUI tool for data pre-processing.[12] it is available for free.[11][12] source code is documented in a manual, accompanied by a test example an
license. [17]
license. [17]
Figure 7. Search screen example of PyQt usage on linux Mint OS. commercial license, but not the GNU Lesser General Public License (LGPL) 2.6.7 MySQLadb and psycopg2
Figure 7. Search screen example of PyQt usage on linux Mint OS. commercial license, but not the GNU Lesser General Public License (LGPL) 2.6.7 MySQLadb and psycopg2
Nikolaos Triantafyllis — ID 926 Scisola: Automatic Moment Tensor solution for SeisComP3
Nikolaos Triantafyllis — ID 926 Scisola: Automatic Moment Tensor solution for SeisComP3
Scisola: Automatic Moment Tensor solution for SeisComP3 Figure 8. Scisola’s database tables and attributes.
Scisola: Automatic Moment Tensor solution for SeisComP3 Figure 8. Scisola’s database tables and attributes.
Scisola: Automatic Moment Tensor solution for SeisComP3
Scisola: Automatic Moment Tensor solution for SeisComP3
Figure 10. Scisola’s structure schema.
Figure 10. Scisola’s structure schema.
Scisola: Automatic Moment Tensor solution for SeisComP3 Nikolaos Triantafyllis — ID 926
Scisola: Automatic Moment Tensor solution for SeisComP3 Nikolaos Triantafyllis — ID 926
Nikolaos Triantafyllis — ID 926 Scisola: Automatic Moment Tensor solution for SeisComP3
Nikolaos Triantafyllis — ID 926 Scisola: Automatic Moment Tensor solution for SeisComP3
Figure 13. Scisola’s interconnection with SeisComP3. implemented by the watcher package.
Figure 13. Scisola’s interconnection with SeisComP3. implemented by the watcher package.
Figure 14. The 8 steps of the automatic procedure. In figure 14, the description of the eight steps mentioned above is given.
Figure 14. The 8 steps of the automatic procedure. In figure 14, the description of the eight steps mentioned above is given.
Figure 17. Plot containing the best inversion results for each depth. Scisola: Automatic Moment Tensor solution for SeisComP3
Figure 17. Plot containing the best inversion results for each depth. Scisola: Automatic Moment Tensor solution for SeisComP3
Figure 18. Plot of observed and synthetic waveforms.
Figure 18. Plot of observed and synthetic waveforms.
Figure 19. Watcher’s process triggering in parallel. of the watcher’s steps.
Figure 19. Watcher’s process triggering in parallel. of the watcher’s steps.
Figure 20. The steps of the watcher’s functionality. Scisola: Automatic Moment Tensor solution for SeisComP3
Figure 20. The steps of the watcher’s functionality. Scisola: Automatic Moment Tensor solution for SeisComP3
Athens) in a manual way. Figure 21. Distribution of evaluation dataset (red dots are epicenters).
Athens) in a manual way. Figure 21. Distribution of evaluation dataset (red dots are epicenters).
mechanisms of the evaluation dataset. For the comparison the Kagan metric has been used. This angle expresses the
mechanisms of the evaluation dataset. For the comparison the Kagan metric has been used. This angle expresses the
The scisola settings were configured as displayed in figure 23.
The scisola settings were configured as displayed in figure 23.
Figure 23. Scisola’s settings for the evaluation dataset. Scisola: Automatic Moment Tensor solution for SeisComP3
Figure 23. Scisola’s settings for the evaluation dataset. Scisola: Automatic Moment Tensor solution for SeisComP3
Figure 24, displays a histogram of the Kagan value distribution. manual MT focal mechanisms of 34 out of 46 events are very similar (Kags
Figure 24, displays a histogram of the Kagan value distribution. manual MT focal mechanisms of 34 out of 46 events are very similar (Kags
Figure 25, displays a histogram of the Moment magnitude -Mw- (size of the seismic source) difference between manual and automatic solution. According to this diagram, the respective automatic and manual MT solutions of 39 out of 46 events produce almost the same size of the seismic source (Moment magnitude -Mw-). Thus, it produces a success of about 85% on Mw calculation. Additionally, the maximum Mw difference for the whole evaluation dataset was not more than 0.3 units of Mw. Scisola: Automatic Moment Tensor solution for SeisComP3
Figure 25, displays a histogram of the Moment magnitude -Mw- (size of the seismic source) difference between manual and automatic solution. According to this diagram, the respective automatic and manual MT solutions of 39 out of 46 events produce almost the same size of the seismic source (Moment magnitude -Mw-). Thus, it produces a success of about 85% on Mw calculation. Additionally, the maximum Mw difference for the whole evaluation dataset was not more than 0.3 units of Mw. Scisola: Automatic Moment Tensor solution for SeisComP3
Centroid Depth Difference The diagram in figure 26, displays a histogram of the Centroid Depth (CD)
Centroid Depth Difference The diagram in figure 26, displays a histogram of the Centroid Depth (CD)
Figure 27. Scisola’s usage files. and run scisola is given. In figure 27, a description of the important files and folders in order to install 5.38 Installation
Figure 27. Scisola’s usage files. and run scisola is given. In figure 27, a description of the important files and folders in order to install 5.38 Installation
prompt with the main window of scisola. Figure 28. Database log-in. password (the same for both tabs). After successful log-in, the user will bi
prompt with the main window of scisola. Figure 28. Database log-in. password (the same for both tabs). After successful log-in, the user will bi
displaying the version of scisola. Figure 29. Main screen.
displaying the version of scisola. Figure 29. Main screen.
and fifth tab, the user can zoom in and out.
and fifth tab, the user can zoom in and out.
Figure 33. Review screen 2. Figure 32. Review screen 1.
Figure 33. Review screen 2. Figure 32. Review screen 1.
Scisola: Automatic Moment Tensor solution for SeisComP3
Scisola: Automatic Moment Tensor solution for SeisComP3
Figure 34. Review screen 3. Figure 35. Review screen 4.
Figure 34. Review screen 3. Figure 35. Review screen 4.
Scisola: Automatic Moment Tensor solution for SeisComP3
Scisola: Automatic Moment Tensor solution for SeisComP3
Figure 37. Review screen 6. Figure 36. Review screen 5.
Figure 37. Review screen 6. Figure 36. Review screen 5.
Figure 38. Review screen 7. Scisola: Automatic Moment Tensor solution for SeisComP3
Figure 38. Review screen 7. Scisola: Automatic Moment Tensor solution for SeisComP3
Figure 41. Settings screen 2. Scisola: Automatic Moment Tensor solution for SeisComP3
Figure 41. Settings screen 2. Scisola: Automatic Moment Tensor solution for SeisComP3
Scisola: Automatic Moment Tensor solution for SeisComP3
Scisola: Automatic Moment Tensor solution for SeisComP3
Figure 44. Stations/streams screen.
Figure 44. Stations/streams screen.
Nikolaos Triantafyllis — ID 926 Scisola: Automatic Moment Tensor solution for SeisComP3
Nikolaos Triantafyllis — ID 926 Scisola: Automatic Moment Tensor solution for SeisComP3
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