-
Create a
conda
environment with:pandas
andobspy
-
Clone the repository:
$ git clone https://github.com/lvanderlaat/lakiy_utils.git
-
Install the package in the
conda
environment:(env) $ cd lakiy_utils (env) $ pip install -e .
Copy the daily records of the Google Docs file in a txt file with format name %Y-%m-%d.txt
. Clean, format:
Label_1- %H:%M, %H:%M,
Label_2- %H:%M, %H:%M,
...
$ txt-to-swarm %Y-%m-%d.txt
$ download-waves %Y-%m-%d_Swarm.csv
Move the pick to the onset and add an end label.
$ check-swarm %Y-%m-%d_Swarm.csv
You must have a csv
file with stations information (network,station,channel
columns)
$ download-segments %Y-%m-%d_segments.csv stations.csv outpath
$ download-retro year julday stations.csv outpath
Move the pick to the onset and add an end label.
$ check-swarm %Y-%m-%d_Swarm.csv
trim-segments %Y-%m-%d_segments.csv path/to/mseed path/to/out
$ db-stats path/to/wfs
db2TOMODD
extracts a PHA
(hypoDD
format) catalog from the Antelope database:
db2TOMODD database output [julianstartdate julianenddate] [latmin latmax lonmin lonmax][Mmin][Nass] [EIDadd]
Example:
db2TOMODD ../locate/vulca lakiy-VT 2014-001 2021-001 9.955 10.066 -83.809 -83.682 2 0
Use the PHA
catalog to extract waveforms (.msd
) and event information (xml
).
(env) $ VT-extract PHA_FILE STATIONS.CSV OUTPUT
For events occured before CVTR inclusion we add the correspondant waveforms:
(env) $ waves-add-CVTR -i path/to/wfs_in -o path/to/wfs_out -w path/to/raw
Copy the folder containing the extracted data to your computer.
Once the coda is picked, we copy the files to a new folder to discriminate picked events.
(env) $ VT-pick -i path/to/wfs_in -o path/to/wfs_out -e eventid