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conf.yaml
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conf.yaml
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#
# Directory scanned for segy files. The folder must contains
# subfolders inside which the segy files are created:
#
# scan_dir
# subdir1 #e.g. 2024_03_12
# file1.sg2
# file2.sg2
# ...
# subdir2 #e.g. 2024_03_13
# file1.sg2
# file2.sg2
# ...
#
scan_dir : /path/to/somewhere # absolute path!
#
# The subdirs and segy file name patters to look for.
# The patterns support the python re (regular expression) syntax.
# Most used re special characters are:
# . : any single character
# \. : the dot '.', which require escaping '\'
# .+ : any string (+ means any repetition of preceding re)
# .* : any string including empty string
# \d : any decimal digit (i.e. 0-9)
# \D : any character which is not a decimal digit (opposite of \d)
# | : or e.g. str1|str2 means str1 or str2
# () : grouping e.g file_(01|02|03)_\.segy
#
subdir_pattern : \d\d\d\d_\d\d_\d\d # yyyy_mm_dd
file_pattern : m_.+\.sg2
#
# This option cause a buffering_sec delay in the data streaming,
# This delay time is used to read files and buffering data.
# That allows to deal with delays in the file generation
# process without incurring in data gaps, as long as the delay is
# within buffering_sec
#
buffering_sec : 60
#
# This option controls the behaviour in case of delayed files
# generation.
# If new files are not produced for more than buffering_sec,
# then the data buffers empty and the streaming stop.
# When new files become finally available, it is possible to
# stream them, even though they are late (allow_delayed_data=true)
# or to drop all the files that contain delayed data
# and resume from the current time files (allow_delayed_data=false).
# allow_delayed_data=true guarantees no data gaps
# allow_delayed_data=false guarantees no delayed data streaming (it
# takes some time to transmit delayed data)
#
allow_delayed_data : true
#
# Change the timestamp of the streamed data to current UTC time
# This can be useful to simulate the streaming of old data as if
# it was generated now
#
simulate_real_time_data : false
#
# The segy files will be split in chunks and streamed
# in packets whose size is packet_size_microsec
#
packet_size_microsec : 200000
#
# This is how the data contained in the segy files will be
# presented to SeisComP (seedlink raw plugin).
# Each trace in a segy file is represented as a channel id
# e.g. first trace -> channel id 1, third trace -> channel id 3
# For each channel id (trace) we have to define its frequency
# and the sample format we want to stream the data. The frequency
# must be the same frequency we expect the data to have in the
# segy file. The sample format can be anything between
# int8, int16, int32, float32, float64. However it makes sense
# to stream the data in the same format as the original segy
# files, so there is no risk in losing precision during conversion
#
channel_settings:
- ids : [1-24]
sampling_frequency : 4000
sample_format : float32
- ids : [25-48]
sampling_frequency : 4000
sample_format : float32
- ids : [49-54]
sampling_frequency : 4000
sample_format : float32
- ids : [55-63]
sampling_frequency : 4000
sample_format : float32
#
# Here you can define how many servers you want to spawn
# and for each server you defines the channel ids served
# by the server and the port the server listen to
# Normally one server is enough, but since each server
# is a separate process, it might be useful for performance
# reason to serve the channels via multiple servers
#
streaming_servers:
- host : "" # emtpy means all interfaces/ip addresses
port : 65535
channels : [1-63]