Download correlation functions in Julia format

You can download the correlation functions by selecting the station pairs and components:


Read the correlation functions

You can read the correlation functions stored in the .jld2 file as follows:

julia> using SeisIO, SeisNoise, JLD2

julia> t = jldopen("SeisMonitoring_Paper/Appx/plot_CCF/data/BP.EADB-BP.LCCB-11.jld2", "r")
JLDFile SeisMonitoring_Paper/Appx/plot_CCF/data/BP.EADB-BP.LCCB-11.jld2 (read-only)
 โ”œโ”€๐Ÿ“‚ 2002-01-01T00:00:00--2002-01-02T00:00:00
 โ”‚  โ”œโ”€๐Ÿ”ข 0.2-0.5
 โ”‚  โ”œโ”€๐Ÿ”ข 0.5-0.9
 โ”‚  โ”œโ”€๐Ÿ”ข 0.9-1.2
 โ”‚  โ””โ”€๐Ÿ”ข 1.2-2.0
 โ”œโ”€๐Ÿ“‚ 2002-01-02T00:00:00--2002-01-03T00:00:00
 โ”‚  โ”œโ”€๐Ÿ”ข 0.2-0.5
 โ”‚  โ”œโ”€๐Ÿ”ข 0.5-0.9
 โ”‚  โ””โ”€ โ‹ฏ (2 more entries)
 โ””โ”€ โ‹ฏ (7256 more entries)

julia> C = t["2002-09-01T00:00:00--2002-09-02T00:00:00/0.9-1.2"]
CorrData with 1 Corrs
      NAME: "BP.EADB..BP1.BP.LCCB..BP1"
        ID: "2002-09-01"
       LOC: 35.8952 N, -120.423 E, 224.0 m
      COMP: "11"
   ROTATED: false
 CORR_TYPE: "CC"
        FS: 20.0
      GAIN: 1.0
   FREQMIN: 0.9
   FREQMAX: 1.2
    CC_LEN: 3600.0
   CC_STEP: 1800.0
  WHITENED: false
 TIME_NORM: ""
      RESP: a0 1.0, f0 1.0, 1z, 1p
      MISC: 10 entries
     NOTES: 13 entries
      DIST: 12.528
       AZI: 318.74
       BAZ: 138.686
    MAXLAG: 100.0
         T: 2002-09-01T00:30:00                โ€ฆ
      CORR: 4001ร—1 Matrix{Float32}

julia>

Here C is the type of SeisNoise.CorrData containing the correlation function in C.corr and the meta data. See the documentation of SeisNoise.jl for the usage of the CorrData.

Download correlation functions in .npz format

To plot the correlation function in Appx/plot_CCF, we generated the correlation functions associated with the frequency range of 0.9-1.2Hz in .npz format. You can download and locate it in Appx/plot_CCF/data_npz/ and run Appx/plot_CCF/code/plot_ccf_master_v04_medianmute.ipynb to plot the CFs.


Contents of .npz corrfile

keyvalue
coda_init_factorcoda window starts from the ballistic wave arrival time x coda_init_factor
max_coda_lengththe end of coda window, which is fixed in this study
lagslag time vector
linstacklinear stack reference of corrs over the entire study period
ttime windows used for the linear stack
corrcross-correlation function
velvelocity used to estimate ballistic wave arrival time in [km/s]
codainitstart time of coda window, symmetric with positive and negative lags
codaendend time of coda window, symmetric with positive and negative lags

You can extract data as followings:

import numpy as np
D = np.load(f"corrdata_{fi_stachanpair}_0.9-1.2.npz")
lags = D["lags"]
t = D["t"]
corr_raw = D["corr"]
linstack_raw = D["linstack"]
codainit = D["codainit"]
codaend = D["codaend"]