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pyallconditioner.py
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pyallconditioner.py
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#name: pyALLConditioner
#created: April 2018
#by: [email protected]
#description: python module to pre-process a Kongsberg ALL sonar file and do useful things with it
#See readme.md for more details
import csv
import sys
import time
import math
import os
import fnmatch
from argparse import ArgumentParser
from argparse import RawTextHelpFormatter
from datetime import datetime
from datetime import timedelta
from glob import glob
import pyall
import POSMVRead
import struct
import numpy as np
# from bisect import bisect_left, bisect_right
# import sortedcollection
# from operator import itemgetter
from collections import deque
from collections import defaultdict
import matplotlib.pyplot as plt
from scipy import stats
from scipy import signal
###############################################################################
def main():
parser = ArgumentParser(description='Read Kongsberg ALL file and condition the file by removing redundant records and injecting updated information to make the file self-contained.',
epilog='Example: \n To condition a single file use -i c:/temp/myfile.all \n to condition all files in a folder use -i c:/temp/*.all\n To condition all .all files recursively in a folder, use -r -i c:/temp \n To condition all .all files recursively from the current folder, use -r -i ./ \n', formatter_class=RawTextHelpFormatter)
parser.add_argument('-r', action='store_true', default=False, dest='recursive', help='Search Recursively from the current folder. [Default: False]')
parser.add_argument('-i', dest='inputFile', action='store', help='Input ALL filename to image. It can also be a wildcard, e.g. *.all')
parser.add_argument('-odir', dest='odir', action='store', default="", help='Specify a relative output folder e.g. -odir conditioned')
parser.add_argument('-odix', dest='odix', action='store', default="_conditioned", help='Specify an output filename appendage e.g. -odix _savgol')
parser.add_argument('-exclude', dest='exclude', action='store', default="", help='Exclude these datagrams. Note: this needs to be case sensitive e.g. -exclude PYNn')
parser.add_argument('-extractposition', action='store_true', default=False, dest='extractposition', help='Extract a CSV file of "P" POSITION datagrams. [Default: False]')
parser.add_argument('-extractattitude', action='store_true', default=False, dest='extractattitude', help='Extract a CSV file of "A" ATTITUDE. [Default: False]')
parser.add_argument('-extractattitudeheight', action='store_true', default=False, dest='extractattitudeheight', help='Extract a CSV file of the COMBINED "A" ATTITUDE and "h" HEIGHT. [Default: False]')
parser.add_argument('-extractheight', action='store_true', default=False, dest='extractheight', help='Extract a CSV file of "h" HEIGHT datagrams. [Default: False]')
parser.add_argument('-extractnadir', action='store_true', default=False, dest='extractnadir', help='Extract a CSV file of the nadir beam. [Default: False]')
parser.add_argument('-extractbackscatter', action='store_true', default=False, dest='extractbackscatter', help='Extract backscatter from Y datagram so we can analyse. [Default: False]')
parser.add_argument('-extractsvp', action='store_true', default=False, dest='extractsvp', help='Extract a CARIS compatible SVP file based on the sound velocity datagram. [Default: False]')
parser.add_argument('-extractclock', action='store_true', default=False, dest='extractclock', help='Extract a CSV file containing the clock datagrams. Very usefulfor QC of timing subsystem . [Default: False]')
parser.add_argument('-extractinstall', action='store_true', default=False, dest='extractinstall', help='Output the installation parameters to a CSV. [Default: False]')
parser.add_argument('-extractruntime', action='store_true', default=False, dest='extractruntime', help='extract the runtime records for QC purposes')
parser.add_argument('-extractbscorr', action='store_true', default=False, dest='extractbscorr', help='Extract the backscatter bscorr.txt file as used in the PU. This is useful for backscatter calibration and processing, and removes the need to telnet into the PU. [Default: False]')
parser.add_argument('-injectA', dest='injectAFileName', action='store', default="", help='Inject this ATTITUDE file as "A" datagrams. e.g. -injectA "*.srh|*.txt" (Hint: remember the quotes!)')
parser.add_argument('-injectAH', dest='injectAHFileName', action='store', default="", help='Inject this ATTIDUE+HEIGHT file as "A" and "H" datagrams. e.g. -injectAH "*.txt" (Hint: remember the quotes!)')
parser.add_argument('-injectP', dest='injectPOSITIONFileName', action='store', default="", help='Inject this POSITION file as "P" datagrams. e.g. -inject myposition.txt or -injectP "*.txt" (Hint: remember the quotes for wildcard!)')
parser.add_argument('-injectbscorr', dest='injectbscorr', action='store', default="", help='Apply a correction to the Y_SeabedImage datagrams by adding a CSV correction file as createed with the -extractbscorr option. eg. -injectbscorr c:/angularResponse.csv')
parser.add_argument('-splitd', action='store_true', default=False, dest='splitd', help='split the .all file every time the depth mode changes. [Default: False]')
parser.add_argument('-splitf', action='store_true', default=False, dest='splitf', help='split the .all file every time the central frequency changes. [Default: False]')
parser.add_argument('-splitt', dest='splitt', action='store', default="", help='Split the .all file based on time in seconds e.g. -splitt 60')
parser.add_argument('-wobble', dest='wobble', action='store_true', default=False, help='compute the heave and roll related wobble from the raw observations for QC purposes')
parser.add_argument('-beamqc', dest='beamqc', action='store_true', default=False, help='for QC purposes compute a best fit line through each ping and the delta Z for each beam, then compute the mean deviation. Identify noisy beams.')
parser.add_argument('-testfwrite', dest='testfwrite', action='store_true', default=False, help='test the encoding of f records.')
parser.add_argument('-testdwrite', dest='testdwrite', action='store_true', default=False, help='test the encoding of D records.')
if len(sys.argv)==1:
parser.print_help()
sys.exit(1)
args = parser.parse_args()
fileCounter=0
matches = []
correctBackscatter = False
writeConditionedFile= True
splitd = False
splitfileend = 0
splitt = 0
latitude = 0
longitude = 0
wobble = False
beamQC = False
testfwrite = False
testdwrite = False
centerFrequency = 0
outFilePtr = None
if args.recursive:
for root, dirnames, filenames in os.walk(os.path.dirname(args.inputFile)):
for f in fnmatch.filter(filenames, '*.all'):
matches.append(os.path.join(root, f))
else:
if os.path.exists(args.inputFile):
matches.append (os.path.abspath(args.inputFile))
else:
for filename in glob(args.inputFile):
matches.append(filename)
if len(matches) == 0:
print ("No files found in %s to process, quitting" % args.inputFile)
exit()
if len(args.splitt) > 0:
splitt = int(args.splitt)
print ("Splitting on time interval: %s :" % splitt)
if len(args.exclude) > 0:
print ("Excluding datagrams: %s :" % args.exclude)
if args.testfwrite:
testfwrite = True
# args.exclude = 'f' # we need to NOT write out the original data as we will be creating new records
writeConditionedFile = True # we dont need to write a conditioned .all file
if args.testdwrite:
testdwrite = True
# args.exclude += 'D' # we need to NOT write out the original data as we will be creating new records
writeConditionedFile = True # we dont need to write a conditioned .all file
dwrite = 0
if len(args.injectbscorr) > 0:
beamPointingAngles = []
ARC = loadARC(args.injectbscorr)
args.exclude = 'Y' # we need to NOT write out the original data as we will be creating new records
if args.extractbackscatter:
writeConditionedFile= False #we do not need to write out a .all file
# we need a generic set of beams into which we can insert individual ping data. Thhis will be the angular respnse curve
beamdetail = [0,0,0,0]
startAngle = -90
ARC = [pyall.cBeam(beamdetail, i) for i in range(startAngle, -startAngle)]
beamPointingAngles = []
transmitSector = []
outFileName = os.path.join(os.path.dirname(os.path.abspath(matches[0])), args.odir, "AngularResponseCurve.csv")
outFileName = createOutputFileName(outFileName)
# the user has specified a file for injection, so load it into a dictionary so we inject them into the correct spot in the file
if args.injectAFileName:
print ("Injector will inject system 1 'A' records as an active attitude data sensor with pitch,roll,heave and heading data. You may well need to also use the -exclude A to remove the existing records so the .all file is not conflicted")
if args.injectAFileName.lower().endswith('.srh'):
SRH = SRHReader()
SRH.loadFiles(args.injectAFileName) # load all the filenames
print ("Records to inject: %d" % len(SRH.SRHData))
if args.injectAFileName.lower().endswith('.txt'):
ATT = ATTReader()
ATT.loadFiles(args.injectAFileName)
print ("Records to inject: %d" % len(ATT.ATTData))
else:
print ("Injecting POSMV True Heave Data...")
if args.injectAHFileName:
print ("Injector will inject system 1 'A' attitude records as an active attitude data sensor with pitch,roll,heave and heading data. You may well need to also use the -exclude A to remove the existing records so the .all file is not conflicted")
print ("Injector will inject 'h' height records GPS height from atttitde CSV file You may well need to also use the -exclude h to remove the existing records so the .all file is not conflicted")
if args.injectAHFileName.lower().endswith('.txt'):
ATT = ATTReader()
ATT.loadFiles(args.injectAHFileName)
print ("Records to inject: %d" % len(ATT.ATTData))
# auto exclude attitude records. on reflection, we should probably NOT do this.
# args.exclude = 'n'
if args.injectPOSITIONFileName:
print ("Injector will inject system 1 'P' attitude records as an active attitude data sensor with latitude, longitude data. You may well need to also use the -exclude P to remove the existing records so the .all file is not conflicted")
if args.injectPOSITIONFileName.lower().endswith('.txt'):
POS = POSITIONReader()
POS.loadFiles(args.injectPOSITIONFileName)
print ("Records to inject: %d" % len(POS.PositionData))
# auto exclude attitude records. on reflection, we should probably NOT do this.
# args.exclude = 'n'
if args.extractinstall:
writeConditionedFile= False #we do not need to write out a .all file
r = pyall.ALLReader(matches[0])
installStart, installStop, initialMode, datagram = r.loadInstallationRecords()
r.close()
# header = "Waterline(m),Transmit X(m), Transmit Y(m), Transmit Z(m), Receive(X), Receive(Y), Receive(Z), "
# print(header)
header = "Filename"
for code in datagram.installationParameters:
header = header + "," + InstallationCodeToText(code) + " (" + code + ")"
print (header)
if args.extractruntime:
writeConditionedFile= False #we do not need to write out a .all file
if args.extractclock:
timestamps=[]
writeConditionedFile= False #we do not need to write out a .all file
if args.extractattitude:
writeConditionedFile= False #we do not need to write out a .all file
if args.extractheight:
writeConditionedFile= False #we do not need to write out a .all file
if args.extractposition:
writeConditionedFile= False #we do not need to write out a .all file
if args.extractattitudeheight:
writeConditionedFile= False #we do not need to write out a .all file
if args.extractnadir:
writeConditionedFile= False #we do not need to write out a .all file
if args.extractbscorr:
writeConditionedFile= False #we do not need to write out a .all file
if args.extractsvp:
writeConditionedFile= False #we do not need to write out a .all file
if args.splitd:
splitd=True
initialDepthMode = ""
if args.splitf:
centerFrequency = 0
if args.beamqc:
beamQC=True
heads = {}
writeConditionedFile= False
r = pyall.ALLReader(matches[0])
# we need the head installation parameters so we can compute and use the take off angles.
installStart, installStop, initialMode, datagram = r.loadInstallationRecords()
head = getHead(heads, datagram.SerialNumber)
head.installationParameters = datagram.installationParameters
head.installationRollAngle = float(head.installationParameters['S1R'])
head = getHead(heads, datagram.SecondarySerialNumber)
head.installationParameters = datagram.installationParameters
head.installationRollAngle = float(head.installationParameters['S2R'])
r.close()
if args.wobble:
wobble=True
writeConditionedFile= False
wobbleResults = []
attitudeData = []
# #################################################################################
for filename in matches:
if args.injectAFileName:
# find out the first and last timestamps in the .all file
r = pyall.ALLReader(filename)
count, start, end = r.getRecordCount()
# load the heave data from the posmv files
POSMVRead.loadData(args.injectAFileName, start, end)
r.close()
if args.extractruntime:
# create an output file based on the input
outFileName = os.path.join(os.path.dirname(os.path.abspath(filename)), args.odir, os.path.basename(filename))
outFileName = os.path.splitext(outFileName)[0]+'_RUNTIME.txt'
# outFileName = addFileNameAppendage(outFileName, args.odix)
outFileName = createOutputFileName(outFileName)
outRuntimeFilePtr = open(outFileName, 'w')
print ("writing RUNTIME to file: %s" % outFileName)
if args.extractnadir:
# create an output file based on the input
outFileName = os.path.join(os.path.dirname(os.path.abspath(filename)), args.odir, os.path.basename(filename))
outFileName = os.path.splitext(outFileName)[0]+'_NADIR.txt'
# outFileName = addFileNameAppendage(outFileName, args.odix)
outFileName = createOutputFileName(outFileName)
outNadirFilePtr = open(outFileName, 'w')
print ("writing NADIR to file: %s" % outFileName)
if args.extractattitude:
# create an output file based on the input
outFileName = os.path.join(os.path.dirname(os.path.abspath(filename)), args.odir, os.path.basename(filename))
outFileName = os.path.splitext(outFileName)[0]+'_ATTITUDE.txt'
# outFileName = addFileNameAppendage(outFileName, args.odix)
outFileName = createOutputFileName(outFileName)
outAttitudeFilePtr = open(outFileName, 'w')
print ("writing ATTITUDE to file: %s" % outFileName)
if args.extractclock:
# create an output file based on the input
outFileName = os.path.join(os.path.dirname(os.path.abspath(filename)), args.odir, os.path.basename(filename))
outFileName = os.path.splitext(outFileName)[0]+'_CLOCK.txt'
# outFileName = addFileNameAppendage(outFileName, args.odix)
outFileName = createOutputFileName(outFileName)
outClockFilePtr = open(outFileName, 'w')
print ("writing CLOCK to file: %s" % outFileName)
if args.extractheight:
# create an output file based on the input
outFileName = os.path.join(os.path.dirname(os.path.abspath(filename)), args.odir, os.path.basename(filename))
outFileName = os.path.splitext(outFileName)[0]+'_HEIGHT.txt'
# outFileName = addFileNameAppendage(outFileName, args.odix)
outFileName = createOutputFileName(outFileName)
outHeightFilePtr = open(outFileName, 'w')
print ("writing HEIGHT to file: %s" % outFileName)
if args.extractposition:
# create an output file based on the input
outFileName = os.path.join(os.path.dirname(os.path.abspath(filename)), args.odir, os.path.basename(filename))
outFileName = os.path.splitext(outFileName)[0]+'_POSITION.txt'
# outFileName = addFileNameAppendage(outFileName, args.odix)
outFileName = createOutputFileName(outFileName)
outPositionFilePtr = open(outFileName, 'w')
print ("writing POSITION to file: %s" % outFileName)
if args.extractattitudeheight:
# create an output file based on the input
outFileName = os.path.join(os.path.dirname(os.path.abspath(filename)), args.odir, os.path.basename(filename))
outFileName = os.path.splitext(outFileName)[0]+'_ATTITUDEHEIGHT.txt'
# outFileName = addFileNameAppendage(outFileName, args.odix)
outFileName = createOutputFileName(outFileName)
outAttitudeHeightFilePtr = open(outFileName, 'w')
print ("writing ATTITUDE+HEIGHT to file: %s" % outFileName)
attitudeData = []
heightData = []
# if writeConditionedFile:
# # create an output file based on the input
# outFileName = os.path.join(os.path.dirname(os.path.abspath(filename)), args.odir, os.path.basename(filename))
# outFileName = addFileNameAppendage(outFileName, args.odix)
# outFileName = createOutputFileName(outFileName)
# outFilePtr = open(outFileName, 'wb')
# print ("writing to conditioned file: %s" % outFileName)
# open the file and do some initialisation stuff
r = pyall.ALLReader(filename)
counter = 0
if args.extractruntime:
s = "Runtime"
run = pyall.R_RUNTIME(outRuntimeFilePtr, 0)
s = run.header()
outRuntimeFilePtr.write(s + "\n")
if args.extractclock:
s = "RecordDate,ExternalDate,RecordTime,ExternalTime,Difference,PPSInUse"
outClockFilePtr.write(s + "\n")
if args.extractattitude:
# read the first record so we get a date for the file header
typeOfDatagram, datagram = r.readDatagram()
s = r.currentRecordDateTime().strftime('%Y%m%d') + ",Timestamp, Roll, Pitch, Heave, Heading"
outAttitudeFilePtr.write(s + "\n")
if args.extractheight:
# read the first record so we get a date for the file header
typeOfDatagram, datagram = r.readDatagram()
s = r.currentRecordDateTime().strftime('%Y%m%d') + ",Timestamp, Height"
outHeightFilePtr.write(s + "\n")
if args.extractnadir:
# read the first record so we get a date for the file header
typeOfDatagram, datagram = r.readDatagram()
s = "NadirDepth, TransducerDepth, currentRoll, currentPitch, currentHeave, currentHeading"
outNadirFilePtr.write(s + "\n")
if args.extractposition:
# read the first record so we get a date for the file header
typeOfDatagram, datagram = r.readDatagram()
s = "Timestamp, Counter, Latitude, Longitude, Quality, Speed, Course, Heading, Descriptor, numBytes, Datagram"
# s = r.currentRecordDateTime().strftime('%Y%m%d') + ",Timestamp, Counter, Latitude, Longitude, Quality, Speed, Course, Heading, Descriptor, numBytes, Datagram"
outPositionFilePtr.write(s + "\n")
if args.extractattitudeheight:
# read the first record so we get a date for the file header
typeOfDatagram, datagram = r.readDatagram()
s = r.currentRecordDateTime().strftime('%Y%m%d') + ",Timestamp, Roll, Pitch, Heave, Heading, Height"
outAttitudeHeightFilePtr.write(s + "\n")
if splitd or args.splitf or splitt>0:
InstallStart, InstallEnd, initialDepthMode = r.loadInstallationRecords()
centerFrequency = r.loadCenterFrequency()
if args.injectAFileName:
TypeOfDatagram, datagram = r.readDatagram()
if args.injectAFileName.lower().endswith('.srh'):
# kill off the leading records so we do not swamp the filewith unwanted records
SRHSubset = deque(SRH.SRHData)
SRHSubset = trimInjectionData(pyall.to_timestamp(r.currentRecordDateTime()), SRHSubset)
r.rewind()
if args.injectAFileName.lower().endswith('.txt'):
# kill off the leading records so we do not swamp the filewith unwanted records
ATTSubset = deque(ATT.ATTData)
ATTSubset = trimInjectionData(pyall.to_timestamp(r.currentRecordDateTime()), ATTSubset)
r.rewind()
if args.injectAHFileName:
TypeOfDatagram, datagram = r.readDatagram()
if args.injectAHFileName.lower().endswith('.txt'):
# kill off the leading records so we do not swamp the filewith unwanted records
ATTSubset = deque(ATT.ATTData)
ATTSubset = trimInjectionData(pyall.to_timestamp(r.currentRecordDateTime()), ATTSubset)
r.rewind()
lastHeightTimeStamp = 0
if args.injectPOSITIONFileName:
TypeOfDatagram, datagram = r.readDatagram()
if args.injectPOSITIONFileName.lower().endswith('.txt'):
# kill off the leading records so we do not swamp the filewith unwanted records
POSSubset = deque(POS.PositionData)
POSSubset = trimInjectionData(pyall.to_timestamp(r.currentRecordDateTime()), POSSubset)
r.rewind()
lastPositionTimeStamp = 0
if args.extractsvp:
# we need the position of the SVP dip in the SVP file, so use the first position record in the file
nav = r.loadNavigation(True)
if len(nav) > 0:
latitude = nav[0][1]
longitude = nav[0][2]
currPitch = 0
currRoll = 0
currHeave = 0
currHeading = 0
currRuntime = ""
###############################################################
################ main loop through all records ################
###############################################################
while r.moreData():
# read a datagram. If we support it, return the datagram type and aclass for that datagram
TypeOfDatagram, datagram = r.readDatagram()
if splitfileend == 0:
splitfileend = pyall.to_timestamp(r.currentRecordDateTime())
# read the bytes into a buffer
rawBytes = r.readDatagramBytes(datagram.offset, datagram.numberOfBytes)
if beamQC:
if TypeOfDatagram == 'f':
datagram.read()
# figure out which head
head = getHead(heads, datagram.SerialNumber)
ping = cPing(datagram.NumReceiveBeams, head.installationRollAngle)
ping.BeamPointingAngle = datagram.BeamPointingAngle
ping.TwoWayTravelTime = datagram.TwoWayTravelTime
ping.SoundSpeedAtTransducer = datagram.SoundSpeedAtTransducer
ping.BeamNumber = datagram.BeamNumber
# now compute the approximate depth
ping.calcDepth()
# compute a best fit line through the ping of data so we can compute the slope and intercept
slope, intercept, rvalue, pvalue, stderr = stats.linregress(ping.Dy, ping.Dz)
# y = mx + c
for idx, val in enumerate(ping.Dy):
# if datagram.QualityFactor[idx] > 0:
# continue #skip rejected beams
beamNum = ping.BeamNumber[idx]
if not beamNum in head.beamSum:
head.beamSum[beamNum] = (ping.Dz[idx] - ((slope * val) + intercept))
head.beamAngle[beamNum] = ping.BeamPointingAngle[idx]
head.beamCount[beamNum] = 1
else:
head.beamSum[beamNum] += (ping.Dz[idx] - ((slope * val) + intercept))
head.beamAngle[beamNum] = ping.BeamPointingAngle[idx]
head.beamCount[beamNum] += 1
# draw a single profile good for debugging
# plt.figure(figsize=(12,4))
# plt.title(datagram.SerialNumber)
# raw = plt.plot(ping.Dy, ping.Dz)
# plt.show(False)
continue
if TypeOfDatagram == 'D' or TypeOfDatagram == 'X':
datagram.read()
if len(datagram.AcrossTrackDistance) > 1:
# figure out which head
head = getHead(heads, datagram.SerialNumber)
# compute a best fit line through the ping of data so we can compute the slope and intercept
slope, intercept, rvalue, pvalue, stderr = stats.linregress(datagram.AcrossTrackDistance, datagram.Depth)
# y = mx + c
for idx, val in enumerate(datagram.AcrossTrackDistance):
# if datagram.QualityFactor[idx] > 0:
# continue #skip rejected beams
if datagram.BeamDepressionAngle[idx] < 30:
continue
if not datagram.BeamNumber[idx] in head.beamSum:
head.beamSum[datagram.BeamNumber[idx]] = (datagram.Depth[idx] - ((slope * val) + intercept))
head.beamAngle[datagram.BeamNumber[idx]] = datagram.BeamDepressionAngle[idx]
head.beamCount[datagram.BeamNumber[idx]] = 1
else:
head.beamSum[datagram.BeamNumber[idx]] += (datagram.Depth[idx] - ((slope * val) + intercept))
head.beamAngle[datagram.BeamNumber[idx]] = datagram.BeamDepressionAngle[idx]
head.beamCount[datagram.BeamNumber[idx]] += 1
if wobble:
if TypeOfDatagram == 'D' or TypeOfDatagram == 'X':
datagram.read()
# intercept is hwobble
# slope is rwobble
if len(datagram.AcrossTrackDistance) > 1:
# compute a best fit line through the ping of data so we can compute the slope and intercept
slope, intercept, rvalue, pvalue, stderr = stats.linregress(datagram.AcrossTrackDistance, datagram.Depth)
wobbleResults.append([pyall.to_timestamp(r.currentRecordDateTime()), intercept, slope, stderr])
else:
print (len(datagram.AcrossTrackDistance), len(datagram.Depth))
if TypeOfDatagram == 'A':
datagram.read()
for a in datagram.Attitude:
dateobject = pyall.to_DateTime(a[0], a[1])
# date, time, roll, pitch, heave, heading
s = ("%d,%.3f,%.3f,%.3f,%.3f,%.3f\n" % (a[0],a[1],a[3],a[4],a[5],a[6]))
ts = pyall.to_timestamp(pyall.to_DateTime(a[0], a[1]))
attitudeData.append([ts, a[3], a[4], a[5], a[6]])
if args.extractnadir:
if TypeOfDatagram == 'D' or TypeOfDatagram == 'X':
datagram.read()
# find the depth nearest to Nadir
# https://stackoverflow.com/questions/9706041/finding-index-of-an-item-closest-to-the-value-in-a-list-thats-not-entirely-sort
nadirBeam = min(range(len(datagram.AcrossTrackDistance)), key=lambda i: abs(datagram.AcrossTrackDistance[i]))
s = "%.3f,%.3f,%.3f,%.3f,%.3f, %.3f\n" % (datagram.Depth[nadirBeam], datagram.TransducerDepth/100, currRoll, currPitch, currHeave, currHeading)
outNadirFilePtr.write(s)
if args.extractclock:
if TypeOfDatagram == 'C':
datagram.read()
# print (datagram)
outClockFilePtr.write(str(datagram) + "\n")
timestamps.append(datagram.time-datagram.ExternalTime)
if args.extractattitude:
if TypeOfDatagram == 'A':
datagram.read()
for a in datagram.Attitude:
ts = pyall.to_timestamp(pyall.to_DateTime(a[0], a[1])) #remember to add the millisecs for each sub record!
# timetamp, roll, pitch, heave, heading
s = ("%.3f,%.3f,%.3f,%.3f,%.3f\n" % (ts,a[3],a[4],a[5],a[6]))
outAttitudeFilePtr.write(s)
if args.extractheight:
if TypeOfDatagram == 'h':
datagram.read()
# dateobject = pyall.to_DateTime(a[0], a[1])
# date, time, height
ts = pyall.to_timestamp(pyall.to_DateTime(datagram.RecordDate, datagram.Time))
s = ("%.3f,%.3f\n" % (ts, datagram.Height))
# s = ("%d,%.3f,%.3f,%.3f,%.3f,%.3f\n" % (datagram.RecordDate, datagram.Time, datagram.Height, datagram.Height, datagram.Height, datagram.Height))
outHeightFilePtr.write(s)
if args.extractposition:
if TypeOfDatagram == 'P':
datagram.read()
# dateobject = pyall.to_DateTime(a[0], a[1])
# date, time, height
ts = pyall.to_timestamp(pyall.to_DateTime(datagram.RecordDate, datagram.Time))
s = ("%.3f,%d,%.7f,%.7f,%.3f,%.3f,%.3f,%.3f,%d,%d,%s\n" % (ts, datagram.Counter,
datagram.Latitude,
datagram.Longitude,
datagram.Quality,
datagram.SpeedOverGround,
datagram.CourseOverGround,
datagram.Heading,
datagram.Descriptor,
datagram.NBytesDatagram,
datagram.data.decode("utf-8").replace('\x00', '')))
# s = ("%d,%.3f,%.3f,%.3f,%.3f,%.3f\n" % (datagram.RecordDate, datagram.Time, datagram.Height, datagram.Height, datagram.Height, datagram.Height))
outPositionFilePtr.write(s)
if args.extractattitudeheight:
if TypeOfDatagram == 'A':
datagram.read()
for a in datagram.Attitude:
# dateobject = pyall.to_DateTime(a[0], a[1])
# date, time, roll, pitch, heave, heading
ts = pyall.to_timestamp(pyall.to_DateTime(a[0], a[1])) #remember to add the millisecs for each sub record!
attitudeData.append([ts, a[3], a[4], a[5], a[6]])
if TypeOfDatagram == 'h':
datagram.read()
ts = pyall.to_timestamp(pyall.to_DateTime(datagram.RecordDate, datagram.Time))
heightData.append([ts, datagram.Height])
if args.extractinstall:
if TypeOfDatagram == 'I':
datagram.read()
row = filename
for i in datagram.installationParameters :
if len(datagram.installationParameters[i]) == 0:
datagram.installationParameters[i] = "0.00"
row = row + "," + datagram.installationParameters[i]
# row.replace(",,",",")
print (row)
# break
if args.extractruntime:
if TypeOfDatagram == 'R':
datagram.read()
# if currRuntime != datagram.parameters():
# print (filename, "," ,datagram)
outRuntimeFilePtr.write(str(datagram) + "\n")
# currRuntime = datagram.parameters()
# break
if splitt:
# datagram.read()
if pyall.to_timestamp(r.currentRecordDateTime()) > (splitfileend + splitt):
# write out the closing install record then close the file
print ("closing the file as the duration has exceeded the split time")
outFilePtr.write(InstallEnd)
outFilePtr.close()
outFileName = os.path.join(os.path.dirname(os.path.abspath(filename)), args.odir, os.path.basename(filename))
outFileName = addFileNameAppendage(outFileName, args.odix)
outFileName = createOutputFileName(outFileName)
outFilePtr = open(outFileName, 'wb')
print ("writing to split file: %s" % outFileName)
outFilePtr.write(InstallStart)
outFilePtr.write(rawBytes)
splitfileend = pyall.to_timestamp(r.currentRecordDateTime())
if splitd:
if TypeOfDatagram == 'R':
datagram.read()
if initialDepthMode is not datagram.DepthMode:
# write out the closing install record then close the file
print ("closing the file as the depth mode has changed")
outFilePtr.write(InstallEnd)
outFilePtr.close()
outFileName = os.path.join(os.path.dirname(os.path.abspath(filename)), args.odir, os.path.splitext(filename)[0] + "_" + datagram.DepthMode + "." + os.path.splitext(filename)[1],)
outFileName = addFileNameAppendage(outFileName, args.odix)
outFileName = createOutputFileName(outFileName)
outFilePtr = open(outFileName, 'wb')
print ("writing to split file: %s" % outFileName)
outFilePtr.write(InstallStart)
outFilePtr.write(rawBytes)
initialDepthMode = datagram.DepthMode #remember the new depth mode!
if args.splitf:
if TypeOfDatagram == 'N':
datagram.read()
if centerFrequency != datagram.CentreFrequency[0]:
# write out the closing install record then close the file
print ("closing the file as the frequency has changed")
outFilePtr.write(InstallEnd)
outFilePtr.close()
outFileName = os.path.join(os.path.dirname(os.path.abspath(filename)), args.odir, os.path.basename(filename))
outFileName = addFileNameAppendage(outFileName, "_" + str(datagram.CentreFrequency[0]))
outFileName = addFileNameAppendage(outFileName, args.odix)
outFileName = createOutputFileName(outFileName)
outFilePtr = open(outFileName, 'wb')
print ("writing to split file: %s" % outFileName)
outFilePtr.write(InstallStart)
outFilePtr.write(rawBytes)
centerFrequency = datagram.CentreFrequency #remember the new centre frequency
# before we write the datagram out, we need to inject records with a smaller from_timestamp
if args.injectAFileName:
if args.injectAFileName.lower().endswith('.srh'):
counter, lastHeightTimeStamp = injector(outFilePtr, pyall.to_timestamp(r.currentRecordDateTime()), SRHSubset, counter)
if args.injectAFileName.lower().endswith('.txt'):
counter, lastHeightTimeStamp = injector(outFilePtr, pyall.to_timestamp(r.currentRecordDateTime()), ATTSubset, counter)
if TypeOfDatagram in args.exclude:
# dont trigger on records we are rejecting!
continue
if args.injectAHFileName:
if args.injectAHFileName.lower().endswith('.txt'):
counter, lastPositionTimeStamp = injector(outFilePtr, pyall.to_timestamp(r.currentRecordDateTime()), TypeOfDatagram, ATTSubset, counter, True, lastHeightTimeStamp)
# continue
if TypeOfDatagram in args.exclude:
# dont trigger on records we are rejecting!
continue
if args.injectPOSITIONFileName:
if args.injectPOSITIONFileName.lower().endswith('.txt'):
counter, lastPositionTimeStamp = injector(outFilePtr, pyall.to_timestamp(r.currentRecordDateTime()), TypeOfDatagram, POSSubset, counter, True, lastPositionTimeStamp)
# continue
if TypeOfDatagram in args.exclude:
# dont trigger on records we are rejecting!
continue
if args.extractbackscatter:
'''to extract backscatter angular response curve we need to keep a count and sum of all samples in a per degree sector'''
'''to do this, we need to take into account the take off angle of each beam'''
if TypeOfDatagram == 'N':
datagram.read()
beamPointingAngles = datagram.BeamPointingAngle
transmitSector = datagram.TransmitSectorNumber
if TypeOfDatagram == 'Y':
if len(beamPointingAngles)==0:
continue #we dont yet have any raw ranges so we dont have a beam pattern so skip
datagram.read()
for i in range(len(datagram.beams)):
arcIndex = round(beamPointingAngles[i]-startAngle) #quickly find the correct slot for the data
ARC[arcIndex].sampleSum = ARC[arcIndex].sampleSum + sum(datagram.beams[i].samples)
ARC[arcIndex].numberOfSamplesPerBeam = ARC[arcIndex].numberOfSamplesPerBeam + len(datagram.beams[i].samples)
ARC[arcIndex].sector = transmitSector[i]
continue
if testdwrite:
if TypeOfDatagram == 'D':
datagram.read()
for idx, val in enumerate(datagram.QualityFactor):
datagram.QualityFactor[idx] = 255
# datagram.Depth[idx] += 100
bytes = datagram.encode()
outFilePtr.write(bytes)
# test to figure out how caris rejects records
dwrite += 1
if dwrite == 5:
break
continue
# test by rejecting all f records as well...
if TypeOfDatagram == 'f':
datagram.read()
for idx, val in enumerate(datagram.QualityFactor):
datagram.QualityFactor[idx] = 255
# for idx, val in enumerate(datagram.TwoWayTravelTime):
# if idx > 113 and idx < 126:
# datagram.TwoWayTravelTime[idx] *= 0.90
bytes = datagram.encode()
outFilePtr.write(bytes)
continue
if TypeOfDatagram == 'O':
datagram.read()
for idx, val in enumerate(datagram.QualityFactor):
datagram.QualityFactor[idx] = 255
bytes = datagram.encode()
outFilePtr.write(bytes)
continue
if testfwrite:
if TypeOfDatagram == 'f':
datagram.read()
# for idx, val in enumerate(datagram.TwoWayTravelTime):
# if idx > 113 and idx < 126:
# datagram.TwoWayTravelTime[idx] *= 0.90
bytes = datagram.encode()
outFilePtr.write(bytes)
continue
if args.injectbscorr:
if TypeOfDatagram == 'N':
datagram.read()
beamPointingAngles = datagram.BeamPointingAngle
if TypeOfDatagram == 'Y':
if len(beamPointingAngles)==0:
continue #we dont yet have any raw ranges so we dont have a beam pattern so skip
datagram.read()
datagram.ARC = ARC
datagram.BeamPointingAngle = beamPointingAngles
bytes = datagram.encode()
outFilePtr.write(bytes)
continue
if args.extractsvp:
extractProfile(datagram, TypeOfDatagram, r.currentRecordDateTime(), latitude, longitude, filename, args.odir)
continue
if args.extractbscorr:
extractBSCorrData(datagram, TypeOfDatagram, filename, args.odir)
continue
# the user has opted to skip this datagram, so continue
if TypeOfDatagram in args.exclude:
continue
if writeConditionedFile:
if outFilePtr is None:
# create an output file based on the input
outFileName = os.path.join(os.path.dirname(os.path.abspath(filename)), args.odir, os.path.basename(filename))
# we are splitting of frequency, so the filename is a little different.
if args.splitf:
outFileName = addFileNameAppendage(outFileName, "_" + str(centerFrequency))
outFileName = addFileNameAppendage(outFileName, args.odix)
outFileName = createOutputFileName(outFileName)
outFilePtr = open(outFileName, 'wb')
print ("writing to conditioned file: %s" % outFileName)
outFilePtr.write(rawBytes)
# if r.recordCounter > 1000:
# break
# update_progress("Processed: %s (%d/%d)" % (filename, fileCounter, len(matches)), (fileCounter/len(matches)))
fileCounter +=1
r.close()
if args.extractattitudeheight:
# now we need to merge the heights into the attitude records using a time interpolation
if len(heightData) == 0:
print("Sorry, no height data to extract. Please try extracting attitude data instead")
else:
ts_height = cTimeSeries(heightData)
for rec in attitudeData:
height = ts_height.getValueAt(rec[0])
# rec.append(height)
# now save to the regular file format...
# d = pyall.dateToKongsbergDate(from_timestamp(rec[0]))
# t = pyall.dateToKongsbergTime(from_timestamp(rec[0]))
# s = ("%s,%s,%.3f,%.3f,%.3f,%.3f,%.3f\n" % ( d, t, rec[1], rec[2], rec[3], rec[4], height))
s = ("%.3f,%.3f,%.3f,%.3f,%.3f,%.3f\n" % (rec[0], rec[1], rec[2], rec[3], rec[4], height))
outAttitudeHeightFilePtr.write(s)
if writeConditionedFile:
print ("Saving conditioned file to: %s" % outFileName)
outFilePtr.close()
if args.extractclock:
plt.figure(figsize=(12,4))
# plt.axhline(0, color='black', linewidth=0.3)
plt.grid(linestyle='-', linewidth='0.2', color='black')
raw = plt.plot(timestamps, color='red', linewidth=0.5, label='Clock Difference')
plt.legend()
plt.xlabel('Sample #')
plt.ylabel('Record - External Clock Difference(Sec)')
plt.title("Clock Stability:" + os.path.basename(filename))
outFileName = os.path.join(os.path.dirname(os.path.abspath(filename)), args.odir, os.path.basename(filename))
outFileName = createOutputFileName(outFileName)
plt.savefig(os.path.splitext(outFileName)[0]+'_clock.png', dpi = 300)
plt.close()
timestamps.clear()
# print out the extracted backscatter angular response curve
if args.extractbackscatter:
print("Writing backscatter angular response curve to: %s" % outFileName)
# compute the mean response across the swath
responseSum = 0
responseCount = 0
for beam in ARC:
if beam.numberOfSamplesPerBeam > 0:
responseSum = responseSum = (beam.sampleSum/10) #tenths of a dB
responseCount = responseCount = beam.numberOfSamplesPerBeam
responseAverage = responseSum/responseCount
with open(outFileName, 'w') as f:
# write out the backscatter response curve
f.write("TakeOffAngle(Deg), BackscatterAmplitude(dB), Sector, SampleSum, SampleCount, Correction, %s \n" % args.inputFile )
for beam in ARC:
if beam.numberOfSamplesPerBeam > 0:
beamARC = (beam.sampleSum/beam.numberOfSamplesPerBeam)
f.write("%.3f, %.3f, %d, %d, %d, %.3f\n" % (beam.takeOffAngle, beamARC, beam.sector, beam.sampleSum, beam.numberOfSamplesPerBeam , beamARC + responseAverage))
if wobble:
plt.figure(figsize=(12,4))
# plt.axhline(0, color='black', linewidth=0.3)
plt.grid(linestyle='-', linewidth='0.2', color='black')
# extract the lists of data for display
w = np.array(wobbleResults)
tWobble = w[:,0]
hWobble = w[:,1]
rWobble = w[:,2]
raw = plt.plot(tWobble, rWobble, color='red', linewidth=0.5, label='RWobble')
# plot the HWobble moving it nearer to the zero origin
raw = plt.plot(tWobble, hWobble - np.average(hWobble), 'ro', label='Levelled HWobble')
hWobble = hWobble - np.average(hWobble)
# isolate the low frequency signal in the heave(which should not exist)
level = 10
sm_hWobble = signal.savgol_filter(hWobble, 11, 1)
# # for i in range(level):
# # smoothedHeave = signal.savgol_filter(smoothedHeave, 11, 1)
# # subtract the very smoothed signal from the input signal, thereby applying a lowcut filter (AKA high band pass)
# diff = np.subtract(hWobble, smoothedHeave)
# raw = plt.plot(tWobble, hWobble, color='blue', linewidth=0.5, label='HWobble')
# raw = plt.plot(tWobble, sm_hWobble, color='gray', linewidth=1.5, label='SmoothedHeave')
d = np.array(attitudeData)
tAttitude = d[:,0]
roll = d[:,1] / 10
roll = roll - np.average(roll)
pitch = d[:,2] / 10
pitch = pitch - np.average(pitch)
heave = d[:,3]
# heave = heave - np.average(heave)
raw = plt.plot(tAttitude, roll, color='yellow', linewidth=1, label='Roll')
raw = plt.plot(tAttitude, pitch, color='blue', linewidth=1, label='Pitch')
# raw = plt.plot(tAttitude, heave, 'bo', label='Heave')
# raw = plt.plot(tAttitude, heave, color='green', linewidth=1, label='Heave')
#######################
# savgol the raw heave
# subtract the settled heave
# then plot and correlate to pitch/roll
level = 1000
sm_heave = signal.savgol_filter(heave, 101, 1)
for i in range(level):
sm_heave = signal.savgol_filter(sm_heave, 101, 1)
# subtract the very smoothed signal from the input signal, thereby applying a lowcut filter (AKA high band pass)
settledHeave = np.subtract(heave, sm_heave)
# raw = plt.plot(tAttitude, settledHeave, color='black', linewidth=2, label='Heave')
ts_heave = cTimeSeries(tAttitude, settledHeave)
corr_hWobble = []
for t, h in zip(tWobble, hWobble):
correction = ts_heave.getValueAt(t)
corr_hWobble.append(h + correction)
raw = plt.plot(tWobble, corr_hWobble, color='black', linewidth=1, label='HeaveCorrectedNadirDepth')
#######################
plt.legend()
plt.xlabel('Sample #')
plt.ylabel('Wobble')
plt.title("Wobble Errors:" + os.path.basename(filename))
outFileName = os.path.join(os.path.dirname(os.path.abspath(filename)), args.odir, os.path.basename(filename))
outFileName = addFileNameAppendage(outFileName, args.odix)
outFileName = createOutputFileName(outFileName)
plt.show()
plt.savefig(os.path.splitext(outFileName)[0]+'_wobble.png', dpi = 300)
plt.close()
# timestamps.clear()
if beamQC:
plt.figure(figsize=(12,4))
# plt.axhline(0, color='black', linewidth=0.3)
plt.grid(linestyle='-', linewidth='0.2', color='black')
trace=[]
names =[]
for key, head in heads.items():
names.append(head.ID)
beamsum = head.beamSum.values()
count = head.beamCount.values()
beam = head.beamCount.keys()
profile = []
for s,c in zip(beamsum, count):
profile.append(s/c)
trace.append(plt.bar(beam, profile))
plt.legend([trace[0], trace[1]], names)
plt.xlabel('Beam #')
plt.ylabel('Deviation(m)')
plt.title("Mean Slope Rectified Profile")
plt.ylim(-0.1,0.1)
# plt.text(0.05, 0.95, heads[names[0]].beamCount[100], fontsize=14, verticalalignment='top')
outFileName = os.path.join(os.path.dirname(os.path.abspath(filename)), args.odir, os.path.basename(filename))
outFileName = createOutputFileName(outFileName)
plt.savefig(os.path.splitext(outFileName)[0]+'_BeamQC.png', dpi = 300)
plt.show()
plt.close()
# update_progress("Process Complete: ", (fileCounter/len(matches)))
def getHead(heads, serialNumber):
if not serialNumber in heads:
heads[serialNumber] = cMBESHead(serialNumber)
return heads[serialNumber]
###############################################################################
def InstallationCodeToText(code):
allcodes = defaultdict(str)
allcodes['WLZ'] = 'Water line vertical location in m'
allcodes['SMH'] = 'System main head serial number'
allcodes['HUN'] = 'Hull Unit'
allcodes['HUT'] = 'Hull Unit tilt offset'
allcodes['TXS'] = 'TX serial number'
allcodes['T2X'] = 'TX no. 2 serial number'
allcodes['R1S'] = 'RX no. 1 serial number'
allcodes['R2S'] = 'RX no. 2 serial number'
allcodes['STC'] = 'System transducer configuration'
allcodes['S0Z'] = 'Transducer 0 vertical location in m'
allcodes['S0X'] = 'Transducer 0 along location in m'
allcodes['S0Y'] = 'Transducer 0 athwart location in m'
allcodes['S0H'] = 'Transducer 0 heading in degrees'
allcodes['S0R'] = 'Transducer 0 roll in degrees re horizontal'
allcodes['S0P'] = 'Transducer 0 pitch in degrees'
allcodes['S1Z'] = 'Transducer 1 vertical location in m'
allcodes['S1X'] = 'Transducer 1 along location in m'
allcodes['S1Y'] = 'Transducer 1 athwart location in m'
allcodes['S1H'] = 'Transducer 1 heading in degrees'
allcodes['S1R'] = 'Transducer 1 roll in degrees re horizontal'
allcodes['S1P'] = 'Transducer 1 pitch in degrees'
allcodes['S1N'] = 'Transducer 1 no of modules'
allcodes['S2Z'] = 'Transducer 2 vertical location in m'
allcodes['S2X'] = 'Transducer 2 along location in m'
allcodes['S2Y'] = 'Transducer 2 athwart location in m'
allcodes['S2H'] = 'Transducer 2 heading in degrees'
allcodes['S2R'] = 'Transducer 2 roll in degrees re horizontal'
allcodes['S2P'] = 'Transducer 2 pitch in degrees'
allcodes['S2N'] = 'Transducer 2 no of modules'
allcodes['S2Z'] = 'Transducer 3 vertical location in m'
allcodes['S3Z'] = 'Transducer 3 along location in m'
allcodes['S3Y'] = 'Transducer 3 athwart location in m'
allcodes['S2H'] = 'Transducer 3 heading in degrees'
allcodes['S3R'] = 'Transducer 3 roll in degrees re horizontal'
allcodes['S3P'] = 'Transducer 3 pitch in degrees'
allcodes['S1S'] = 'TX array size (0=0.5 1=1 2=2)'
allcodes['S2S'] = 'RX array size (1=1 2=2)'
allcodes['GO1'] = 'System (sonar head 1) gain offset'
allcodes['GO2'] = 'Sonar head 2 gain offset'
allcodes['OBO'] = 'Outer beam offset'
allcodes['FGD'] = 'High/Low Frequency Gain Difference'
allcodes['TSV'] = 'Transmitter (sonar head no1) software version'
allcodes['RSV'] = 'Receiver (sonar head 2) software version'
allcodes['BSV'] = 'BSP software version'
allcodes['PSV'] = 'Processing unit software version'
allcodes['DDS'] = 'DDS software version'
allcodes['OSV'] = 'Operator station software version'
allcodes['DSV'] = 'Datagram format version'
allcodes['DSX'] = 'Depth (pressure) sensor along location in m'
allcodes['DSY'] = 'Depth (pressure) sensor athwart location in m'
allcodes['DSZ'] = 'Depth (pressure) sensor vertical location in m'
allcodes['DSD'] = 'Depth (pressure) sensor time delay in millisec'
allcodes['DSO'] = 'Depth (pressure) sensor offset'