Dear Mark,
I have recently installed geopsy version 3.5.2 implementing ARDS and ARTB methods. I have applied such methods to my dataset obtaining results which are quite different from those obtained by other methods, such as Wavedec (Maranò et al 2017). Therefore, I would like to perform some tests using the available Mirandola dataset and following Wathelet 2024, GJI. Could you please share with me the param file you have used for the analyses shown in you paper? Thank you in advance,
best regards,
Salomon
new ARDS and RTBF methods
Re: new ARDS and RTBF methods
Hi Salomon,
What do you mean by "quite different"? Can you show us some details?
Have you already had a look at this page?
To get Fig. 12d, I ran
Upon building the figure, I restricted the velocity range:
To get Fig. 14:
It is plotted with the same velocity limits.
The default values for parameters have probably been adjusted in the code since then. For instance, RELATIVE_THRESHOLD, FREQ_BAND_WIDTH and PERIOD_COUNT default currently to these values, hence it is useless to specify them, but at that time it was not the case.
Cheers,
Marc
What do you mean by "quite different"? Can you show us some details?
Have you already had a look at this page?
To get Fig. 12d, I ran
Code: Select all
geopsy-fk -db Mirandola.gpy -group C135_405-3C -nobugreport -set RELATIVE_THRESHOLD=1 -set FREQ_BAND_WIDTH=0 -set PERIOD_COUNT=50 -set STATISTIC_MAX_OVERLAP=100 -set GRID_SIZE_FACTOR=4 -no-overwrite -set STEP_FREQUENCY=1.01 -set MINIMUM_FREQUENCY=0.5 -set MAXIMUM_FREQUENCY=10 -set MIN_V=100 -set MAX_V=2000 -set PROCESS_TYPE=ARDS -set ELLIPTICITY_CORRECTION=None -o fine-noellcorr
Code: Select all
gpviewmax fine-noellcorr-ards-C135_405-3C.max -v-min 200
Code: Select all
geopsy-fk -db Mirandola.gpy -group C135_405-3C -nobugreport -set RELATIVE_THRESHOLD=1 -set FREQ_BAND_WIDTH=0 -set PERIOD_COUNT=50 -set STATISTIC_MAX_OVERLAP=100 -set GRID_SIZE_FACTOR=4 -no-overwrite -set STEP_FREQUENCY=1.01 -set MINIMUM_FREQUENCY=0.5 -set MAXIMUM_FREQUENCY=10 -set MIN_V=100 -set MAX_V=2000 -set PROCESS_TYPE=ARDS -o fine
The default values for parameters have probably been adjusted in the code since then. For instance, RELATIVE_THRESHOLD, FREQ_BAND_WIDTH and PERIOD_COUNT default currently to these values, hence it is useless to specify them, but at that time it was not the case.
Cheers,
Marc
Re: new ARDS and RTBF methods
Dear Marc,
thank you very much for your reply.
I run the analysis on the Mirandola dataset following the instruction at the provided link.
I have obtained the same results as you show in your paper.
I am running the analysis on my dataset following the same procedure (namely by command line instruction). I will keep you updated on the results.
Cheers,
Salomon
thank you very much for your reply.
I run the analysis on the Mirandola dataset following the instruction at the provided link.
I have obtained the same results as you show in your paper.
I am running the analysis on my dataset following the same procedure (namely by command line instruction). I will keep you updated on the results.
Cheers,
Salomon
Re: new ARDS and RTBF methods
Dear Marc,
I have the feeling, as suggested by our common friend Giuseppe, that my problem was related to the definition of the grid-step. Using the graphic window and default parameters for the analysis, grid-step was incorrectly defined for dense arrays (40 sensors) with rather short inter-station distances (3-5m). Explicitly defining the grid step using the command line seems to have fixed my problem.
Thank you very much,
cheers,
Salomon
I have the feeling, as suggested by our common friend Giuseppe, that my problem was related to the definition of the grid-step. Using the graphic window and default parameters for the analysis, grid-step was incorrectly defined for dense arrays (40 sensors) with rather short inter-station distances (3-5m). Explicitly defining the grid step using the command line seems to have fixed my problem.
Thank you very much,
cheers,
Salomon
Re: new ARDS and RTBF methods
Dear Salomon,
The aliasing limit may not be correctly estimated with kmax for dense arrays. I'm surprised that grid step is not correctly calculated. It is based on kmin which can be generally calculated without ambiguity.
The grid-step is specified in the parameter section of the results. I would be interested if you illustrate the problem and the solution by a figure and portions of the parameter log.
Cheers
Marc
The aliasing limit may not be correctly estimated with kmax for dense arrays. I'm surprised that grid step is not correctly calculated. It is based on kmin which can be generally calculated without ambiguity.
The grid-step is specified in the parameter section of the results. I would be interested if you illustrate the problem and the solution by a figure and portions of the parameter log.
Cheers
Marc