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91 lines
4.0 KiB
YAML
91 lines
4.0 KiB
YAML
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# Example of a survey configuration file.
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#
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# These files, of which there should be one per project,
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# describe where to find the relevant data and other
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# parameters of interest.
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archived: true # If true, the data in the database will be “frozen”.
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id: EQ19221 # Not used. See bin/create_survey.sh
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name: "4D PRM seismic survey Norway Blocks 25/8 & 25/11" # Not used. See bin/create_survey.sh
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schema: survey_1 # This must be the schema returned by bin/create_survey.sh
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epsg: 23031 # The EPSG code used in bin/create_survey.sh
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binning: # P6 data. Eventually will be replaced with the location of the P6 file.
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theta: 206.47 # Direction of I axis, degrees
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I_inc: 1 # Increment along I
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J_inc: 1 # Increment along J
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I_width: 12.50 # Inline bin width
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J_width: 12.50 # Crossline bin width
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origin:
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easting: 479735.00
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northing: 6565048.00
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I: 5000
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J: 1000
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preplots: # List of preplot files
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-
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type: sps # Always "sps"
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class: "S" # Source preplots
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path: /srv/Data/EQ22222/preplots/Preplot_Source.sps
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format:
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# The “SPS” files seen in the while have all different layouts. Rather than
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# forcing our own choice of layout upon the user, we let him describe what
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# his files look like.
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# This is done by providing:
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# * a list of field widths (negative values cause that number of columns to be skipped)
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# * a list of field names, its length must equal the number of positive field widths
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# * a list of type conversions – this is the name of a Python function to which the
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# value will be passed. An exception is that `int` is our own custom function that
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# can take a string like "3.0" without barfing.
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widths: [ -1, 10, 10, -25, 10, 10 ]
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names: [ "line_name", "point_number", "easting", "northing" ]
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types: [ "int", "int", "float", "float" ]
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-
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type: sps
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class: "V" # Vessel preplots
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path: /srv/Data/EQ22222/preplots/Preplot_Vessel.sps
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format:
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widths: [ -1, 10, 10, -25, 10, 10 ]
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names: [ "line_name", "point_number", "easting", "northing" ]
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types: [ "int", "int", "float", "float" ]
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raw:
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# This section tells us where to find the raw data and what kind it is.
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# (raw data is what is produced by the navigation system during or right after acquisition)
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p190: # We have raw P1/90 files
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timestamp_format: "%d%m%Y" # Different software can't seem to agree on what format to use
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pattern:
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# Some of the information we want is not even *in* the P1/90 but is conveyed
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# via the file name. So we parse the file name via a regular expression to
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# get those details. There are two items of data that we *must* get from the
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# file name: the sequence and the sailline number.
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# The following items are:
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# * regex: a Python (and ideally JavaScript) compatible regular expression
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# * flags: regular expression flags
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# * captures: the capture groups. "line" and "sequence" are required.
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regex: '^.*(10|20)([0-9]{4})([0-9])([0-9]{3})S00000\.([0-9]+)\.[Pp]?190$'
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flags: i
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captures: [ "direction", "line", "attempt", "sequence", "file_no" ]
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globs:
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# A list of glob expressions to capture P1/90 files
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- "*.P190"
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paths:
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# A list of directories to search for P1/90 files
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- /srv/Data/EQ19221/_live/raw
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final:
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# This section is analogue to "raw" above, but for final data.
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# (final data is what is given to the client)
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p190:
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timestamp_format: "%d%m%Y"
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pattern:
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regex: '^.*(10|20)([0-9]{4})([0-9])([0-9]{3})S00000\.([0-9]+)\.[Pp]?190$'
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flags: i
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captures: [ "direction", "line", "attempt", "sequence", "file_no" ]
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globs:
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- "*.190"
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- "*.p190"
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- "*.P190"
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paths:
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- /srv/Data/EQ19221/_live/final
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