The Problem

The table showing the azimuthal HVSR statistics in azimuthal_hvsrpy_interface.ipynb is missing. The notebook produces no error.

Specific Problem

The method HvsrRotated.print_stats() is empty. Problem only exists in v0.4.1.

Fix

Reimplement the HvsrRotated.print_stats() method.

Hi,

It seems that the clarity criteria are not drawing their statistics from between f_range_low and f_range_high.

For example:
Criteria iii): Pass
A0[f0mc]=3.017 is > 2.0

I got this result when using 3 Hz to 5 Hz. You can see in the image below that this amplitude is almost certainly coming from the large peak that I'm trying to avoid.

I haven't check the other criteria so it may be that only the amplitude is an issue.

Dear hvsrpy Community,
It is hard to believe but hvsrpy (Vantassel, 2020) has just turned three. Over that time hvsrpy has seen widespread use in the fields of seismology, geophysics, and engineering and a rapidly growing userbase (over 30k downloads & over 45 stars on GitHub). As such, I have decided to undertake the first major overhaul of the hvsrpy codebase to add new features and streamline its API. Throughout this process I am looking for feedback (via this survey https://forms.gle/36aWUKrgGwiYddnSA) to understand how the community currently processes HVSR data and what new features the community would like to see in the future. Your responses are greatly appreciated. Keep an eye out for the release of hvsrpy v2.0.0 later this year.

Hi,

First of all, thanks for your efforts for HVSRpy.

I'm currently exploring the use of multiprocessing with HVSRpy.
However, I've noticed that the processing utilizes all available CPU resources extensively.
Is there an option to limit the number of CPUs for a single process, similar to the -j option in geopsy?

Thank you,
segu

Problem Summary

Researchers use various equipment to measure ambient noise for HVSR, and this variety of equipment unfortunately results in a variety of data formats. Ideally hvsrpy will allow for convenient handling of a variety of common data formats and not only miniSEED.

Proposed Solution

As most researchers are able to convert their data to ASCII/UTF-8 characters it makes sense to extend hvsrpy to include that functionality as a first step. However, as the format of any text file may vary, its difficult to produce a single script that will extract the data appropriately. Therefore, it is important to keep in mind that the example provided below is in fact only an example of a potential solution that can/must be modified appropriately.

Examples

For MiniShark:

# Load metadata
with open(fname, "r") as f:
    lines = f.readlines()
for line in lines:
    if line.startswith("#Sample rate (sps):"):
        _, sample_rate = line.split(":\t")
sample_rate = float(sample_rate)
dt = 1/sample_rate

# Load data
keys = ["vt", "ew", "ns"]
df = pd.read_csv(file_name, comment="#", sep="\t", names=keys)
components= {key:sigpropy.TimeSeries(df[key], dt) for key in keys}

# Create Sensor3c object to replace hvsrpy.Sensor3c.from_mseed() 
sensor = hvsrpy.Sensor3c(**components, meta={"File Name": file_name})

For SESAME ASCII data format (SAF) v1

fname = "MT_20211122_133110.SAF"

with open(fname, "r") as f:
    lines = f.readlines()
    
for idx, line in enumerate(lines):
    if line.startswith("SAMP_FREQ = "):
        fs = float(line[len("SAMP_FREQ = "):])
    if line.startswith("####--------"):
        idx += 1
        break

vt = []
ns = []
ew = []
for line in lines[idx:]:
    _vt, _ns, _ew = line.split()
    vt.append(_vt)
    ns.append(_ns)
    ew.append(_ew)

vt = sigpropy.TimeSeries(vt, dt=1/fs)
ns = sigpropy.TimeSeries(ns, dt=1/fs)
ew = sigpropy.TimeSeries(ew, dt=1/fs)
    
sensor = hvsrpy.Sensor3c(ns, ew, vt)

API Change Request: Multi-Azimuth Output File

On behalf of Alan Thorp, Ground Investigation Ltd.

Problem

The output file created when considering multiple azimuths (i.e., via a HvsrRotated object) is comma delimited. However, many of the metadata parameters (e.g., LMf0,AZ and SigmaLNf0,AZ) contain commas, making it difficult to parse the files programmatically.

Proposed Solution

Remove the offending commas such that LMf0,AZ and SigmaLNf0,AZ become LMf0AZ and SigmaLNf0AZ, respectively.

Hey Joe,

I ma having some issue installing hvsrpy on my Jupiter lab. I run it via anaconda navigator to manage my environments and I am trying to install it on my obspy environment. The traceback/installation error I get when I execute "!pip install hvsrpy" is attached

issue installing hvsrpy.docx

To anyone who reads this,

I recorded ambient noise in a test site, and I am using hvsrpy to estimate f0 and a0. I had 4 sensors per site and the first two worked perfectly. However, when I tried to insert the miniseed of the third station, I always get the error "ValueError: illegal value in 4-th argument of internal None". I am attaching both the miniseed that worked and the miniseed that pops the error. This work is part of my PhD thesis, and I would gladly accept any assistance! The waveforms are here for 30 days: https://easyupload.io/m/r8n6ms

Thank you again,
Angelos Zymvragakis, MSc Geologist - Seismologist

It would be nice to be able to run the program from the command line for a list of files. This is the way that I have implemented by own HVSR calculation software. The following is an example of my command line interface:

usage: H/V Calculator [-h] [--version] [-a] [-c CONFIG] [-m {both,welch,sesame,raw_only}]
                      [-p {auto,manual}]
                      [inputs [inputs ...]]

Calculator for V/H ratios from mini-seed

positional arguments:
  inputs                Input file(s) to read

optional arguments:
  -h, --help            show this help message and exit
  --version             show program's version number and exit
  -a, --all             Compute all usable
  -c CONFIG, --config CONFIG
                        Specify configuration
  -m {both,welch,sesame,raw_only}, --method {both,welch,sesame,raw_only}
                        Method for computing H/V ratio
  -p {auto,manual}, --peakselect {auto,manual}
                        Method for selecting the peak

A few things:

• I would also add an argument for the output directory, and then a sub-directory would be based on the input file name.
• In each output directory, standard plots and output files are created.
• A configuration file can be specified so that an analysis is repeated. The configuration is also saved to the output to document that calculation.

I think such an interface would help in bulk processing of recordings. Additionally, interactively selecting frequency ranges could be done using matplotlib GUI support.

Problem Summary

Some seismic testing instruments save their measurements into three one-component miniseed files (one for north, east, and vertical). hvsrpy and the associated web-application hvsrweb assume a three-component miniseed file (i.e., all three traces are saved in the same miniseed file) by default. While Sensor3c's .from_mseed classmethod allows for the provision of three one-component files in lieu of a single three-component file (see docs for details), this feature has not yet been added to hsvrweb and remains a frequent point of inquiry.

Proposed Solution

Fortunately, combining three one-component miniseed files into a single three-component miniseed file is quite straightforward using obspy. I have posted code demonstrating how to do this as a gist here. I hope that if you are reading this you find it helpful.

Hi Joseph,

Thanks for putting together this amazing package!

I'm doing some initial exploration with a raw data set collected from East Antarctica and encountered some 'interesting' spectra:

Being a relative beginner with HVSR processing, I wanted to ask what your recommended data pre-processing steps are before HVSR analysis in hvsrpy, beyond the implemented time-domain filtering and spectral smoothing? I understand instrumental response correction may not be necessary if responses across components are similar, but can, e.g., detrending, static shift corrections be implemented in hvsrpy? What are the typical steps you take? I'd be grateful for any advice you could give!

Cheers,

Ian