My project https://www.mathworks.com/help/matlab/matlab_prog/loma-prieta-earthquake.html

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On 3/11/2023 6:54 PM, a a wrote:

My project https://www.mathworks.com/help/matlab/matlab_prog/loma-prieta-earthquake.html

If your goal is to step through this Matlab example, then clearly you
should use Matlab. If you do not have access to Matlab or cannot afford
it, then you would have to use something else, and Python would be a
prime candidate. However, each of the techniques and graphs in the
lesson have been pre-packaged for you in the Matlab case but not with
Python (many other case studies on various topics that use Python Python
can be found, though).

Everything in the Matlab analysis can be done with Python and associated libraries. You would have to learn various processing and graphing
techniques. You would also have to get the data from somewhere. It's prepackaged for this analysis and you would have to figure out where to
get it. There is at least one Python package that can read and convert
Matlab files - I do not remember its name, though.

A more important question is whether doing the Matlab example prepares
you to do any other analyses on your own. To shed some light on this,
here is a post on some rather more advanced analysis using data on the
same earthquake, done with Python tools -

https://towardsdatascience.com/earthquake-time-series-forecasts-using-a-hybrid-clustering-lstm-approach-part-i-eda-6797b22aed8c

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A a,

Consider asking a more specific question. Many things can be done in many different programming languages.

Are you asking if there are helpers you can use such as modules that
implement parts of the algorithms you need? Are you asking about speed or efficiency?

Have you considered how few people here are likely to know much about a specialized field and perhaps a search using a search engine might get you something like this:

https://www.google.com/search?q=python+process+seimographic+signals&oq=pytho n+process+seimographic+signals&aqs=chrome..69i57j0i546l5.16718j0j7&sourceid= chrome&ie=UTF-8

For example:

https://www.geophysik.uni-muenchen.de/~megies/www_obsrise/

You can of course search for say signal processing or whatever makes sense
to you.

My answer, if not clear, is that your question may not be primarily about Python and about finding whatever environment gives you both access to
software that helps you as well as a language that lets you wrap lots of it together, make reports and so on. Python is likely a decent choice but
perhaps others are better for your own situation, such as having others
nearby you can learn from.

Good luck.

-----Original Message-----
From: Python-list <python-list-bounces+avi.e.gross=gmail.com@python.org> On Behalf Of a a
Sent: Saturday, March 11, 2023 6:54 PM
To: python-list@python.org
Subject: Can you process seismographic signals in Python or should I switch
to Matlab ?

My project https://www.mathworks.com/help/matlab/matlab_prog/loma-prieta-earthquake.htm
l
--
https://mail.python.org/mailman/listinfo/python-list

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I have used GNU Octave as a sort of replacement for MATLAB as a free
resource. I have no idea if it might meet your needs.

Although Python is a good environment for many things, if you have no
knowledge of it yet, it can take a while to know enough and if you just need
it for one project, ...

-----Original Message-----
From: Python-list <python-list-bounces+avi.e.gross=gmail.com@python.org> On Behalf Of Thomas Passin
Sent: Sunday, March 12, 2023 12:02 AM
To: python-list@python.org
Subject: Re: Can you process seismographic signals in Python or should I
switch to Matlab ?

On 3/11/2023 6:54 PM, a a wrote:

My project

https://www.mathworks.com/help/matlab/matlab_prog/loma-prieta-earthquake.htm
l

If your goal is to step through this Matlab example, then clearly you
should use Matlab. If you do not have access to Matlab or cannot afford
it, then you would have to use something else, and Python would be a
prime candidate. However, each of the techniques and graphs in the
lesson have been pre-packaged for you in the Matlab case but not with
Python (many other case studies on various topics that use Python Python
can be found, though).

Everything in the Matlab analysis can be done with Python and associated libraries. You would have to learn various processing and graphing
techniques. You would also have to get the data from somewhere. It's prepackaged for this analysis and you would have to figure out where to
get it. There is at least one Python package that can read and convert
Matlab files - I do not remember its name, though.

A more important question is whether doing the Matlab example prepares
you to do any other analyses on your own. To shed some light on this,
here is a post on some rather more advanced analysis using data on the
same earthquake, done with Python tools -

https://towardsdatascience.com/earthquake-time-series-forecasts-using-a-hybr id-clustering-lstm-approach-part-i-eda-6797b22aed8c



--
https://mail.python.org/mailman/listinfo/python-list

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On Sunday, 12 March 2023 at 06:17:54 UTC+1, avi.e...@gmail.com wrote:

I have used GNU Octave as a sort of replacement for MATLAB as a free resource. I have no idea if it might meet your needs.

Although Python is a good environment for many things, if you have no knowledge of it yet, it can take a while to know enough and if you just need it for one project, ...
-----Original Message-----
From: Python-list <python-list-bounces+avi.e.gross=gmai...@python.org> On Behalf Of Thomas Passin
Sent: Sunday, March 12, 2023 12:02 AM
To: pytho...@python.org
Subject: Re: Can you process seismographic signals in Python or should I switch to Matlab ?
On 3/11/2023 6:54 PM, a a wrote:

My project

https://www.mathworks.com/help/matlab/matlab_prog/loma-prieta-earthquake.htm l

If your goal is to step through this Matlab example, then clearly you
should use Matlab. If you do not have access to Matlab or cannot afford
it, then you would have to use something else, and Python would be a
prime candidate. However, each of the techniques and graphs in the
lesson have been pre-packaged for you in the Matlab case but not with
Python (many other case studies on various topics that use Python Python
can be found, though).

Everything in the Matlab analysis can be done with Python and associated libraries. You would have to learn various processing and graphing techniques. You would also have to get the data from somewhere. It's prepackaged for this analysis and you would have to figure out where to
get it. There is at least one Python package that can read and convert Matlab files - I do not remember its name, though.

A more important question is whether doing the Matlab example prepares
you to do any other analyses on your own. To shed some light on this,
here is a post on some rather more advanced analysis using data on the
same earthquake, done with Python tools -

https://towardsdatascience.com/earthquake-time-series-forecasts-using-a-hybr id-clustering-lstm-approach-part-i-eda-6797b22aed8c
--
https://mail.python.org/mailman/listinfo/python-list

Thank you my dear friends for your kind opinions.

Matlab is pro, commercial, paid and demo is available for tests only.
So it's hard to dicuss projects, apps in Matlab if cannot be verified by peers.

What is hot today is the following 3D plot animation in Matplotlib

https://twitter.com/gmrpetricca/status/1633477532526817281

But some unknown reasons Matplotlib and numpy crash my Python 3.8 for Windows , 32-bit and no support is offered

Ok, I can read 100 research papers daily, preview hundreds pages of text from search engines.

But what I need is analysis of seismograms from 4,000 seismographs world wide to detect P-wave energy distribution underground around the earthquake to verify EQ Domino Effect

As you can see below, the Matlab project named in my first submission turned into Python project
and EQ energy envelope makes sense.

But I would prefer to join 100+ man project in seismology since it may take me months to download
seismograms, process seismograms, preview, select features and build EQ energy envelope 3D plots for earthquakes in Turkey alone.

To develop another theory, to get data, process data and get results for analysis to verify EQ energy envelope Domino Effect


I am afraid there are no team research projects in seismology.
What is published and discussed is one-man project.

----

PICOSS: Python Interface for the Classification of
Seismic Signals
A. Buenoa, L. Zuccarellob,c, A. D ́ıaz-Morenod, J. Woolamd, M. Titosb, L. Garc ́ıaa, I. ́Alvareza, J. Prudenciob, S. De Angelisd
aDepartment of Signal Theory, Telematic and Communications, University of Granada,
Spain.
bDepartment of Theoretical Physics and Cosmos, University of Granada, Spain. cIstituto Nazionale di Geofisica e Vulcanologia, Sezione di Pisa, Italy dDepartment of Earth, Ocean and Ecological Sciences, University of Liverpool, UK

https://core.ac.uk/download/pdf/334413225.pdf


seismic-signal

https://github.com/topics/seismic-signal

STA-LTA Algorithm and Seismometer Trajectory visualization in 3D

Tonumoy /
STA-LTA-Algorithm-and-Seismometer-Trajectory-visualization-in-3D


https://github.com/Tonumoy/STA-LTA-Algorithm-and-Seismometer-Trajectory-visualization-in-3D


PICOSS

A Python Interface for the Classification of Seismic Signals.

PICOSS is a Python GUI designed as a modular data-curator platform for volcano-seismic data analysis. Detection, segmentation and classification. With exportability and standardization at its core, users can select automatic or manual workflows to
annotate seismic data from the suite of included tools.

Originally, PICOSS was designed for the purposes of seismicity research as a collaboration between University of Granada (UGR) and University of Liverpool (UoL). However, the system can be used within a wide range of geophysical applications.
We are currently working on switching the interface from Python 2.7 to Python 3.0+

https://github.com/srsudo/PICOSS

https://github.com/srsudo/PICOSS/blob/master/info/tutorials/howto.md


Simulations of the Loma Prieta earthquake using an energy-based envelope shape.
https://www.researchgate.net/figure/Simulations-of-the-Loma-Prieta-earthquake-using-an-energy-based-envelope-shape-Response_fig12_315724830

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On 3/13/2023 12:39 AM, a a wrote:

But some unknown reasons Matplotlib and numpy crash my Python 3.8 for Windows , 32-bit and no support is offered

It is possible, using pip, to downgrade versions (e.g., of Matplotlob
and numpy) to see if you can find versions that work. Of course moving
to 64-bit Python >= 3.10 would be better, but if that were possible I
imagine you would have done it already.

BTW, it would be useful if you said what operating system you are using
(I've been assuming Windows).

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On Monday, 13 March 2023 at 16:16:28 UTC+1, Thomas Passin wrote:

On 3/13/2023 12:39 AM, a a wrote:

But what I need is analysis of seismograms from 4,000 seismographs world wide to detect P-wave energy distribution underground around the earthquake to verify EQ Domino Effect

In that case, you will have to do a great deal of work to get all that
data into a common usable form, cleaned and errors removed. That will
be a lot of effort no matter what language you use. In the Matplotlib
lesson you pointed to, the work was already done, for one one earthquake
at one location.

The reference I gave, https://towardsdatascience.com/earthquake-time-series-forecasts-using-a-hybr

id-clustering-lstm-approach-part-i-eda-6797b22aed8c

actually includes a Python script that does this work for some selected ranges of data, so it might be a good starting point.

Thank you
excellent example

"The imported json files were heavily-nested; hence, during data cleaning, I “denested” the json files, transformed them into dataframes, fixed the column datatypes, imputed the NaN values, and finally concatenated them into a global dataframe, which
was workable. For a full description of data cleaning, visit my GitHub profile. Finally, I indexed the dataframe by timestamps as a time-series dataframe:

https://towardsdatascience.com/earthquake-time-series-forecasts-using-a-hybrid-clustering-lstm-approach-part-i-eda-6797b22aed8c


I would like to work with Saied Mighani one day but unfortunately, seismology projects, studies are one-man activity.

I am success oriented in building Earthquake Prediction System
and I am sure, P-wave energy envelope calculate for every earthquake, for every seismographic station can give valuable hints on how earthquake energy is distributed underground, since what is recorded by surface seismographs is some form of such P-wave
envelope energy transferred at the direction of surface placed seismograph.

Ideas are great but life is for real ;)

thank you

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On 3/13/2023 11:23 AM, Rich Shepard wrote:

On Mon, 13 Mar 2023, Thomas Passin wrote:

But what I need is analysis of seismograms from 4,000 seismographs
world wide to detect P-wave energy distribution underground around
the earthquake to verify EQ Domino Effect

In that case, you will have to do a great deal of work to get all that
data into a common usable form, cleaned and errors removed. That will
be a
lot of effort no matter what language you use. In the Matplotlib lesson
you pointed to, the work was already done, for one one earthquake at one
location.

Wouldn't Pandas help here?

No doubt, depending on the data formats used. But it's still going to
be a big task.

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On Mon, 13 Mar 2023, Thomas Passin wrote:

But what I need is analysis of seismograms from 4,000 seismographs world
wide to detect P-wave energy distribution underground around the earthquake >> to verify EQ Domino Effect

In that case, you will have to do a great deal of work to get all that
data into a common usable form, cleaned and errors removed. That will be a lot of effort no matter what language you use. In the Matplotlib lesson
you pointed to, the work was already done, for one one earthquake at one location.

Wouldn't Pandas help here?

Rich

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On 3/13/2023 12:39 AM, a a wrote:

But what I need is analysis of seismograms from 4,000 seismographs world wide to detect P-wave energy distribution underground around the earthquake to verify EQ Domino Effect

In that case, you will have to do a great deal of work to get all that
data into a common usable form, cleaned and errors removed. That will
be a lot of effort no matter what language you use. In the Matplotlib
lesson you pointed to, the work was already done, for one one earthquake
at one location.

The reference I gave, https://towardsdatascience.com/earthquake-time-series-forecasts-using-a-hybr

id-clustering-lstm-approach-part-i-eda-6797b22aed8c

actually includes a Python script that does this work for some selected
ranges of data, so it might be a good starting point.

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On Monday, 13 March 2023 at 16:12:04 UTC+1, Thomas Passin wrote:

On 3/13/2023 12:39 AM, a a wrote:

But some unknown reasons Matplotlib and numpy crash my Python 3.8 for Windows , 32-bit and no support is offered

It is possible, using pip, to downgrade versions (e.g., of Matplotlob
and numpy) to see if you can find versions that work. Of course moving
to 64-bit Python >= 3.10 would be better, but if that were possible I imagine you would have done it already.

BTW, it would be useful if you said what operating system you are using (I've been assuming Windows).

sorry
Windows 7

My concept in building Earthquake Prediction System based on Precognition is
to use RTL Software Defined Radio (SDR) to receive data from outdoor seismic sensors (smartphones turned into seismographs - sending acceleration data via audio output, to be transmitted by radio transmitter to a remote RTL SDR station, for real time
processing, P-wave energy envelope calculation, earthquake depth calculation sine in case of Turkey, USGS assigns 10km depth value by default to a single EQ event.

Why SDR ?
Since I don't expect Cellular network to work and be operational in remote, mountain regions of Turkey after the strong 7,8 earthquake, so SDR should work as backup for cellular 3G/LTE network in the region.

In case of Android smartphones I need to switch to Python for Android to get flexibility offered by scripting to support earthquake study ideas just in time and to share such ideas with friends.


---

python-for-android · PyPI
https://pypi.org/project/python-for-android

python-for-android is a packaging tool for Python apps on Android. You can create your own Python distribution including the modules and dependencies you want, and bundle it in an APK or AAB along with your own code. Features include: Different app
backends including Kivy, PySDL2, and a WebView with Pyt… See more Documentation

Follow the quickstartinstructionsto install and begin creating APKs and AABs. Quick instructions: install python-for-android with: (for the develop branch: pip install git+https://github.com/kivy/… See more
Contributing

We love pull requests and discussing novel ideas. Check out the Kivyproject contribution guideandfeel free to improve python-for-android. See ou… See more
Support

If you need assistance, you can ask for help on our mailing list: 1. User Group: https://groups.google.com/group/kivy-users 2. Email: kivy-users@googlegroups.com … See more
History

In 2015 these tools wer

On 3/13/2023 11:54 AM, Rich Shepard wrote:> On Mon, 13 Mar 2023, Thomas
Passin wrote:

No doubt, depending on the data formats used. But it's still going
to be a big task.

Thomas,

True, but once you have a dataframe with all the information about
all the earthquakes you can extract data for every analysis you want
to do.

This message would better have gone to the list instead of just me.

I'm not saying that Pandas is a bad choice! I'm saying that getting all
that data into shape so that it can be ingested into a usable dataframe
will be a lot of hard work.

If you've not read Wes McKinney's "Python for Data Analysis: Data
Wrangling with Pandas, NumPy, and IPython" I encourage you to do so.

I've been interested in that title, but since I don't currently have any
large, complex data wrangling problems I've put it off.

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On Mon, 13 Mar 2023, Thomas Passin wrote:

No doubt, depending on the data formats used. But it's still going to be a big task.

Thomas,

True, but once you have a dataframe with all the information about all the earthquakes you can extract data for every analysis you want to do.

If you've not read Wes McKinney's "Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython" I encourage you to do so.

Regards,

Rich

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Hi,

This seems again to be a topic wandering. Was the original question whether Python could be used for dealing with Seismic data of some unspecified sort
as in PROCESSING it and now we are debating how to clean various aspects of data and make things like data.frames and extract subsets for analysis?

Plenty of the above can be done in any number of places ranging from
languages like Python and R to databases and SQL. If the result you want to analyze can then be written in a format with rows and columns containing the usual suspects like numbers and text and dates and so on, then this part of
the job can be done anywhere you want.

And when you have assembled your data and now want to make a query to
generate a subset such as data in a date range that is from a set of
measuring stations and with other qualities, then you can simply save the
data to a file in whatever format, often something like a .CSV.

It is the following steps where you want to choose your language based on
what is available. Are you using features like a time series, for example?
Are you looking or periodicity. Is graphing a major aspect and do you need
some obscure graph types not easily found but that are parts of packages/modules in some language like R or Python? Do you need the analysis
to have interactive aspects such as from a GUI, or a web page? Does any
aspect of your work include things like statistical analyses or machine learning? The list goes on.

As mentioned, people who do lots of stuff along these lines can share some tools in python, or elsewhere, they find useful and that might help fit the needs of the OP but they work best when they have a better idea of what
exactly you want to do. Part of what I gleaned, was a want to do a 3-D graph that rotates. Python has multiple graphics packages and so on as do
languages like R. The likelihood of finding something useful goes up if you identify if there are communities of people doing similar work and can share some of their tools.

Hence the idea of focused searches. Asking here will largely get you people mainly who use Python and if it turns out R or something entirely else meets your needs better, perhaps Mathematica even if you have to pay for it if
that is expected by your peers.

My guess is that python would be a decent choice as it can do almost
anything, but for practical purposes, you do not want to stick with what is
in the base and probably want to use extensions like numpy/pandas and
perhaps others like scipy and if doing graphics, there are too many
including matplotlib and seaborn but you may need something specialized for your needs.

I cannot stress the importance of making sure the people evaluating and
using your work can handle it. Python is fairly mainstream and free enough
that it can foot your bill. But it has various versions and clearly nobody would advise you to use version 2. Some versions are packaged with many of
the tools you may want to use, such as Anaconda. It depends on your level of expertise already and how much you want to learn to get this task done. You make it sound like your kind of work must be done alone, and that can
simplify things but also mean more work for you.

-----Original Message-----
From: Python-list <python-list-bounces+avi.e.gross=gmail.com@python.org> On Behalf Of Thomas Passin
Sent: Monday, March 13, 2023 2:10 PM
To: python-list@python.org
Subject: Re: Can you process seismographic signals in Python or should I
switch to Matlab ?

On 3/13/2023 11:54 AM, Rich Shepard wrote:> On Mon, 13 Mar 2023, Thomas
Passin wrote:

No doubt, depending on the data formats used. But it's still going
to be a big task.

Thomas,

True, but once you have a dataframe with all the information about
all the earthquakes you can extract data for every analysis you want
to do.

This message would better have gone to the list instead of just me.

I'm not saying that Pandas is a bad choice! I'm saying that getting all
that data into shape so that it can be ingested into a usable dataframe
will be a lot of hard work.

If you've not read Wes McKinney's "Python for Data Analysis: Data
Wrangling with Pandas, NumPy, and IPython" I encourage you to do so.

I've been interested in that title, but since I don't currently have any
large, complex data wrangling problems I've put it off.




--
https://mail.python.org/mailman/listinfo/python-list

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