def dotest():
# copy files over to somewhere read/writeable
dircopy(PyHum.__path__[0], os.path.expanduser("~")+os.sep+'pyhum_test')
shutil.copy(PyHum.__path__[0]+os.sep+'test.DAT', os.path.expanduser("~")+os.sep+'pyhum_test'+os.sep+'test.DAT')
# general settings
humfile = os.path.expanduser("~")+os.sep+'pyhum_test'+os.sep+'test.DAT' #PyHum.__path__[0]+os.sep+'test.DAT'
sonpath = os.path.expanduser("~")+os.sep+'pyhum_test' #PyHum.__path__[0]
doplot = 1 #yes
# reading specific settings
cs2cs_args = "epsg:26949" #arizona central state plane
bedpick = 1 # auto bed pick
c = 1450 # speed of sound fresh water
t = 0.108 # length of transducer
f = 455 # frequency kHz
draft = 0.3 # draft in metres
flip_lr = 1 # flip port and starboard
# correction specific settings
maxW = 1000 # rms output wattage
# for texture calcs
win = 50 # pixel window
shift = 10 # pixel shift
density = win/2
numclasses = 4 # number of discrete classes for contouring and k-means
maxscale = 20 # Max scale as inverse fraction of data length (for wavelet analysis)
notes = 4 # Notes per octave (for wavelet analysis)
# for mapping
#imagery = 1 # server='http://server.arcgisonline.com/ArcGIS', service='World_Imagery'
dogrid = 1 # yes
calc_bearing = 0 #no
filt_bearing = 1 #yes
res = 0.05 # grid resolution in metres
chunk_size = 0 # auto chunk size
PyHum.read(humfile, sonpath, cs2cs_args, c, draft, doplot, t, f, bedpick, flip_lr, chunk_size)
PyHum.correct(humfile, sonpath, maxW, doplot)
PyHum.texture(humfile, sonpath, win, shift, doplot, density, numclasses, maxscale, notes)
PyHum.map(humfile, sonpath, cs2cs_args, dogrid, calc_bearing, filt_bearing, res)
res = 0.5 # grid resolution in metres
PyHum.map_texture(humfile, sonpath, cs2cs_args, dogrid, calc_bearing, filt_bearing, res)
def dotest():
# copy files over to somewhere read/writeable
dircopy(PyHum.__path__[0], os.path.expanduser("~")+os.sep+'pyhum_test')
shutil.copy(PyHum.__path__[0]+os.sep+'test.DAT', os.path.expanduser("~")+os.sep+'pyhum_test'+os.sep+'test.DAT')
# general settings
humfile = os.path.expanduser("~")+os.sep+'pyhum_test'+os.sep+'test.DAT' #PyHum.__path__[0]+os.sep+'test.DAT'
sonpath = os.path.expanduser("~")+os.sep+'pyhum_test' #PyHum.__path__[0]
doplot = 1 #yes
# reading specific settings
cs2cs_args = "epsg:26949" #arizona central state plane
bedpick = 1 # auto bed pick
c = 1450 # speed of sound fresh water
t = 0.108 # length of transducer
f = 455 # frequency kHz
draft = 0.3 # draft in metres
flip_lr = 1 # flip port and starboard
model = 998 # humminbird model
chunk_size = 1000 # chunk size = 1000 pings
#chunk_size = 0 # auto chunk size
# correction specific settings
maxW = 1000 # rms output wattage
# for texture calcs
win = 50 # pixel window
shift = 10 # pixel shift
density = win/2
numclasses = 4 # number of discrete classes for contouring and k-means
maxscale = 20 # Max scale as inverse fraction of data length (for wavelet analysis)
notes = 4 # Notes per octave (for wavelet analysis)
# for mapping
dogrid = 1 # yes
calc_bearing = 0 #no
filt_bearing = 1 #yes
res = 0.2 # grid resolution in metres
cog = 1 # GPS course-over-ground used for heading
# for downward-looking echosounder echogram (e1-e2) analysis
ph = 7.0 # acidity on the pH scale
temp = 10.0 # water temperature in degrees Celsius
salinity = 0.0
beam = 20.0
transfreq = 200.0
integ = 5
numclusters = 3
PyHum.read(humfile, sonpath, cs2cs_args, c, draft, doplot, t, f, bedpick, flip_lr, chunk_size, model)
PyHum.correct(humfile, sonpath, maxW, doplot)
PyHum.texture(humfile, sonpath, win, shift, doplot, density, numclasses, maxscale, notes)
PyHum.map(humfile, sonpath, cs2cs_args, dogrid, calc_bearing, filt_bearing, res, cog)
res = 0.5 # grid resolution in metres
PyHum.map_texture(humfile, sonpath, cs2cs_args, dogrid, calc_bearing, filt_bearing, res, cog)
PyHum.e1e2(humfile, sonpath, cs2cs_args, ph, temp, salinity, beam, transfreq, integ, numclusters, doplot)
Tk().withdraw() # we don't want a full GUI, so keep the root window from appearing
humfile = askopenfilename(filetypes=[("DAT files","*.DAT")])
# prompt user to supply directory if no input sonpath is given
if not sonpath:
print 'A *.SON directory is required!!!!!!'
Tk().withdraw() # we don't want a full GUI, so keep the root window from appearing
sonpath = askdirectory()
# print given arguments to screen and convert data type where necessary
if humfile:
print 'Input file is %s' % (humfile)
if sonpath:
print 'Son files are in %s' % (sonpath)
doplot = 1 #yes
# for texture calcs
win = 100 # pixel window
shift = 10 # pixel shift
density = win/2 # win/2
numclasses = 4 # number of discrete classes for contouring and k-means
maxscale = 20 # Max scale as inverse fraction of data length (for wavelet analysis)
notes = 4 # Notes per octave (for wavelet analysis)
## Calculate texture lengthscale maps using the method of Buscombe et al. (2015)
PyHum.texture(humfile, sonpath, win, shift, doplot, density, numclasses, maxscale, notes)
def correct(humfiles, sonpath, cww):
PyHum.correct(humfiles, sonpath, correct_withwater=cww)
def read_sondata(hmf, sonDir, c1, f1, model1, chunk1):
PyHum.read(hmf, sonDir, c=c1, f=f1, model=model1, chunk=chunk1)
) # we don't want a full GUI, so keep the root window from appearing
sonpath = askdirectory()
# print given arguments to screen and convert data type where necessary
if humfile:
print 'Input file is %s' % (humfile)
if sonpath:
print 'Son files are in %s' % (sonpath)
doplot = 1 #yes
# reading specific settings
cs2cs_args = "epsg:" + str(cs)
# read-specific settings
bedpick = 1 # auto bed pick
c = 1500 # speed of sound in (fresh) water
t = 0.108 # length of transducer
draft = 0.4 # draft in metres
model = 1199 # humminbird model
calc_bearing = 0 #no
filt_bearing = 0 #no
chunk = 'd100' # distance, 100m
#chunk = 'p1000' # pings, 1000
#chunk = 'h15' # heading deviation, 15 deg
## read data in SON files into PyHum memory mapped format (.dat)
PyHum.read(humfile, sonpath, cs2cs_args, c, draft, doplot, t, bedpick,
flip_lr, model, calc_bearing, filt_bearing, chunk)
print 'An input file is required!!!!!!'
Tk().withdraw() # we don't want a full GUI, so keep the root window from appearing
humfile = askopenfilename(filetypes=[("DAT files","*.DAT")])
# prompt user to supply directory if no input sonpath is given
if not sonpath:
print 'A *.SON directory is required!!!!!!'
Tk().withdraw() # we don't want a full GUI, so keep the root window from appearing
sonpath = askdirectory()
# print given arguments to screen and convert data type where necessary
if humfile:
print 'Input file is %s' % (humfile)
if sonpath:
print 'Son files are in %s' % (sonpath)
doplot = 1 #yes
# correction specific settings
maxW = 1000 # rms output wattage
dofilt = 0 # 1 = apply a phase preserving filter (WARNING!! takes a very long time for large scans)
correct_withwater = 0 # don't retain water column in radiometric correction (1 = retains water column for radiometric corrections)
ph = 6.7 # acidity on the pH scale
salinity = 0.0
## correct scans and remove water column
PyHum.correct(humfile, sonpath, maxW, doplot, dofilt, correct_withwater, ph, temp, salinity)
def dotest():
# copy files over to somewhere read/writeable
dircopy(PyHum.__path__[0], os.path.expanduser("~")+os.sep+'pyhum_test')
shutil.copy(PyHum.__path__[0]+os.sep+'test.DAT', os.path.expanduser("~")+os.sep+'pyhum_test'+os.sep+'test.DAT')
# general settings
humfile = os.path.normpath(os.path.join(os.path.expanduser("~"),'pyhum_test','test.DAT'))
sonpath = os.path.normpath(os.path.join(os.path.expanduser("~"),'pyhum_test'))
doplot = 1 #yes
# reading specific settings
cs2cs_args = "epsg:26949" #arizona central state plane
bedpick = 1 # auto bed pick
c = 1450 # speed of sound fresh water
t = 0.108 # length of transducer
draft = 0.3 # draft in metres
flip_lr = 1 # flip port and starboard
model = 998 # humminbird model
calc_bearing = 1 #1=yes
filt_bearing = 1 #1=yes
chunk = '1' ##'d100' # distance, 100m
#chunk = 'p1000' # pings, 1000
#chunk = 'h10' # heading deviation, 10 deg
# correction specific settings
maxW = 1000 # rms output wattage
dofilt = 0 # 1 = apply a phase preserving filter (WARNING!! takes a very long time for large scans)
correct_withwater = 0 # don't retain water column in radiometric correction (1 = retains water column for radiomatric corrections)
ph = 7.0 # acidity on the pH scale
temp = 10.0 # water temperature in degrees Celsius
salinity = 0.0
dconcfile = None
# for shadow removal
shadowmask = 0 # 0= automatic shadow removal, 1=manual
win = 31
dissim=3
correl=0.2
contrast=6
energy=0.15
mn=4
# for texture calcs
shift = 50 ##10 # pixel shift
density =win/2 # win/2
numclasses = 8 #4 # number of discrete classes for contouring and k-means
maxscale = 20 # Max scale as inverse fraction of data length (for wavelet analysis)
notes = 4 # Notes per octave (for wavelet analysis)
# for mapping
res = 0.05 #99 # grid resolution in metres
# if res==99, the program will automatically calc res from the spatial res of the scans
mode = 1 # gridding mode (simple nearest neighbour)
#mode = 2 # gridding mode (inverse distance weighted nearest neighbour)
#mode = 3 # gridding mode (gaussian weighted nearest neighbour)
use_uncorrected = 0
scalemax=40
nn = 64 #number of nearest neighbours for gridding (used if mode > 1)
##influence = 1 #Radius of influence used in gridding. Cut off distance in meters
numstdevs = 5 #Threshold number of standard deviations in sidescan intensity per grid cell up to which to accept
# for downward-looking echosounder echogram (e1-e2) analysis
beam = 20.0
transfreq = 200.0 # frequency (kHz) of downward looking echosounder
integ = 5
numclusters = 3 # number of acoustic classes to group observations
## read data in SON files into PyHum memory mapped format (.dat)
PyHum.read(humfile, sonpath, cs2cs_args, c, draft, doplot, t, bedpick, flip_lr, model, calc_bearing, filt_bearing, chunk) #cog
## correct scans and remove water column
PyHum.correct(humfile, sonpath, maxW, doplot, dofilt, correct_withwater, ph, temp, salinity, dconcfile)
## remove acoustic shadows (caused by distal acoustic attenuation or sound hitting shallows or shoreline)
PyHum.rmshadows(humfile, sonpath, win, shadowmask, doplot, dissim, correl, contrast, energy, mn)
win = 10
PyHum.texture2(humfile, sonpath, win, doplot, numclasses)
## grid and map the scans
PyHum.map(humfile, sonpath, cs2cs_args, res, mode, nn, numstdevs, use_uncorrected, scalemax)
## calculate and map the e1 and e2 acoustic coefficients from the downward-looking sonar
PyHum.e1e2(humfile, sonpath, cs2cs_args, ph, temp, salinity, beam, transfreq, integ, numclusters, doplot)
res = 1 # grid resolution in metres
numstdevs = 5
def dotest():
# copy files over to somewhere read/writeable
dircopy(PyHum.__path__[0], os.path.expanduser("~") + os.sep + 'pyhum_test')
shutil.copy(
PyHum.__path__[0] + os.sep + 'test.DAT',
os.path.expanduser("~") + os.sep + 'pyhum_test' + os.sep + 'test.DAT')
# general settings
humfile = os.path.normpath(
os.path.join(os.path.expanduser("~"), 'pyhum_test', 'test.DAT'))
sonpath = os.path.normpath(
os.path.join(os.path.expanduser("~"), 'pyhum_test'))
doplot = 1 #yes
# reading specific settings
cs2cs_args = "epsg:26949" #arizona central state plane
bedpick = 1 # auto bed pick
c = 1450 # speed of sound fresh water
t = 0.108 # length of transducer
draft = 0.3 # draft in metres
flip_lr = 1 # flip port and starboard
model = 998 # humminbird model
calc_bearing = 1 #1=yes
filt_bearing = 1 #1=yes
chunk = 'd100' # distance, 100m
#chunk = 'p1000' # pings, 1000
#chunk = 'h10' # heading deviation, 10 deg
# correction specific settings
maxW = 1000 # rms output wattage
dofilt = 0 # 1 = apply a phase preserving filter (WARNING!! takes a very long time for large scans)
correct_withwater = 0 # don't retain water column in radiometric correction (1 = retains water column for radiomatric corrections)
ph = 7.0 # acidity on the pH scale
temp = 10.0 # water temperature in degrees Celsius
salinity = 0.0
# for shadow removal
shadowmask = 0 #automatic shadow removal
win = 31
# for texture calcs
shift = 10 # pixel shift
density = win / 2 # win/2
numclasses = 4 # number of discrete classes for contouring and k-means
maxscale = 20 # Max scale as inverse fraction of data length (for wavelet analysis)
notes = 4 # Notes per octave (for wavelet analysis)
# for mapping
res = 0.2 #99 # grid resolution in metres
# if res==99, the program will automatically calc res from the spatial res of the scans
mode = 1 # gridding mode (simple nearest neighbour)
#mode = 2 # gridding mode (inverse distance weighted nearest neighbour)
#mode = 3 # gridding mode (gaussian weighted nearest neighbour)
use_uncorrected = 0
nn = 64 #number of nearest neighbours for gridding (used if mode > 1)
##influence = 1 #Radius of influence used in gridding. Cut off distance in meters
numstdevs = 5 #Threshold number of standard deviations in sidescan intensity per grid cell up to which to accept
# for downward-looking echosounder echogram (e1-e2) analysis
beam = 20.0
transfreq = 200.0 # frequency (kHz) of downward looking echosounder
integ = 5
numclusters = 3 # number of acoustic classes to group observations
## read data in SON files into PyHum memory mapped format (.dat)
PyHum.read(humfile, sonpath, cs2cs_args, c, draft, doplot, t, bedpick,
flip_lr, model, calc_bearing, filt_bearing, chunk) #cog
## correct scans and remove water column
PyHum.correct(humfile, sonpath, maxW, doplot, dofilt, correct_withwater,
ph, temp, salinity)
## remove acoustic shadows (caused by distal acoustic attenuation or sound hitting shallows or shoreline)
PyHum.rmshadows(humfile, sonpath, win, shadowmask, doplot)
win = 100 # pixel window
## Calculate texture lengthscale maps using the method of Buscombe et al. (2015)
PyHum.texture(humfile, sonpath, win, shift, doplot, density, numclasses,
maxscale, notes)
## grid and map the scans
PyHum.map(humfile, sonpath, cs2cs_args, res, mode, nn, numstdevs,
use_uncorrected) #dowrite,
res = 1 # grid resolution in metres
numstdevs = 5
## grid and map the texture lengthscale maps
PyHum.map_texture(humfile, sonpath, cs2cs_args, res, mode, nn, numstdevs)
## calculate and map the e1 and e2 acoustic coefficients from the downward-looking sonar
PyHum.e1e2(humfile, sonpath, cs2cs_args, ph, temp, salinity, beam,
transfreq, integ, numclusters, doplot)
# print given arguments to screen and convert data type where necessary
if humfile:
print 'Input file is %s' % (humfile)
if sonpath:
print 'Son files are in %s' % (sonpath)
doplot = 1 #yes
# reading specific settings
cs2cs_args = "epsg:" + str(cs)
# for mapping
res = 99 # grid resolution in metres
# if res==99, the program will automatically calc res from the spatial res of the scans
mode = 1 # gridding mode (simple nearest neighbour)
#mode = 2 # gridding mode (inverse distance weighted nearest neighbour)
#mode = 3 # gridding mode (gaussian weighted nearest neighbour)
#dowrite = 1 #writing of point cloud data to file
use_uncorrected = 0
nn = 64 # number of nearest neighbours for gridding (used if mode > 1)
#influence = 1 # Radius of influence used in gridding. Cut of distance in meters.
numstdevs = 5 # Threshold number of standard deviations in sidescan intensity per grid cell up to which to accept
## grid and map the scans
PyHum.map(humfile, sonpath, cs2cs_args, res, mode, nn, numstdevs,
use_uncorrected) #dowrite,
# print given arguments to screen and convert data type where necessary
if humfile:
print 'Input file is %s' % (humfile)
if sonpath:
print 'Son files are in %s' % (sonpath)
doplot = 1 #yes
# reading specific settings
cs2cs_args = "epsg:"+str(cs)
# for mapping
res = 99 # grid resolution in metres
# if res==99, the program will automatically calc res from the spatial res of the scans
mode = 1 # gridding mode (simple nearest neighbour)
#mode = 2 # gridding mode (inverse distance weighted nearest neighbour)
#mode = 3 # gridding mode (gaussian weighted nearest neighbour)
#dowrite = 1 #writing of point cloud data to file
use_uncorrected = 0
nn = 64 # number of nearest neighbours for gridding (used if mode > 1)
#influence = 1 # Radius of influence used in gridding. Cut of distance in meters.
numstdevs = 5 # Threshold number of standard deviations in sidescan intensity per grid cell up to which to accept
## grid and map the texture lengthscale maps
PyHum.map_texture(humfile, sonpath, cs2cs_args, res, mode, nn, numstdevs)
def correct(humfiles,sonpath,cww):
PyHum.correct(humfiles,sonpath,correct_withwater=cww)
def read_sondata(hmf,sonDir,c1,f1,model1,chunk1):
PyHum.read(hmf,sonDir,c=c1,f=f1,model=model1,chunk=chunk1)
# prompt user to supply file if no input file given
if not humfile:
print 'An input file is required!!!!!!'
Tk().withdraw() # we don't want a full GUI, so keep the root window from appearing
humfile = askopenfilename(filetypes=[("DAT files","*.DAT")])
# prompt user to supply directory if no input sonpath is given
if not sonpath:
print 'A *.SON directory is required!!!!!!'
Tk().withdraw() # we don't want a full GUI, so keep the root window from appearing
sonpath = askdirectory()
# print given arguments to screen and convert data type where necessary
if humfile:
print 'Input file is %s' % (humfile)
if sonpath:
print 'Son files are in %s' % (sonpath)
doplot = 1 #yes
# for shadow removal
shadowmask = 0 #auto shadow removal
win = 31 # pixel window
## remove acoustic shadows (caused by distal acoustic attenuation or sound hitting shallows or shoreline)
PyHum.rmshadows(humfile, sonpath, win, shadowmask, doplot)
def dotest():
# copy files over to somewhere read/writeable
dircopy(PyHum.__path__[0], os.path.expanduser("~")+os.sep+'pyhum_test')
shutil.copy(PyHum.__path__[0]+os.sep+'test.DAT', os.path.expanduser("~")+os.sep+'pyhum_test'+os.sep+'test.DAT')
# general settings
humfile = os.path.normpath(os.path.join(os.path.expanduser("~"),'pyhum_test','test.DAT'))
sonpath = os.path.normpath(os.path.join(os.path.expanduser("~"),'pyhum_test'))
doplot = 1 #yes
# reading specific settings
cs2cs_args = "epsg:26949" #arizona central state plane
bedpick = 1 # auto bed pick
c = 1450 # speed of sound fresh water
t = 0.108 # length of transducer
f = 455 # frequency kHz of sidescan sonar
draft = 0.3 # draft in metres
flip_lr = 1 # flip port and starboard
model = 998 # humminbird model
chunk_size = 1000 # chunk size = 1000 pings
#chunk_size = 0 # auto chunk size
cog = 1 # GPS course-over-ground used for heading
calc_bearing = 0 #no
filt_bearing = 1 #yes
# correction specific settings
maxW = 1000 # rms output wattage
# for shadow removal
shadowmask = 0 #automatic shadow removal
# for texture calcs
win = 50 # pixel window
shift = 10 # pixel shift
density = win/2
numclasses = 4 # number of discrete classes for contouring and k-means
maxscale = 20 # Max scale as inverse fraction of data length (for wavelet analysis)
notes = 4 # Notes per octave (for wavelet analysis)
# for mapping
dogrid = 1 # yes
res = 0.1 # grid resolution in metres
mode = 3 # gridding mode (gaussian weighted nearest neighbour)
dowrite = 0 #disable writing of point cloud data to file
nn = 64 #number of nearest neighbours for gridding (used if mode > 1)
influence = 1 #Radius of influence used in gridding. Cut off distance in meters
numstdevs = 4 #Threshold number of standard deviations in sidescan intensity per grid cell up to which to accept
# for downward-looking echosounder echogram (e1-e2) analysis
ph = 7.0 # acidity on the pH scale
temp = 10.0 # water temperature in degrees Celsius
salinity = 0.0
beam = 20.0
transfreq = 200.0 # frequency (kHz) of downward looking echosounder
integ = 5
numclusters = 3 # number of acoustic classes to group observations
# read data in SON files into PyHum memory mapped format (.dat)
PyHum.read(humfile, sonpath, cs2cs_args, c, draft, doplot, t, f, bedpick, flip_lr, chunk_size, model, calc_bearing, filt_bearing, cog)
# correct scans and remove water column
PyHum.correct(humfile, sonpath, maxW, doplot)
# remove acoustic shadows (caused by distal acoustic attenuation or sound hitting shallows or shoreline)
PyHum.rmshadows(humfile, sonpath, win, shadowmask, doplot)
# Calculate texture lengthscale maps using the method of Buscombe et al. (2015)
PyHum.texture(humfile, sonpath, win, shift, doplot, density, numclasses, maxscale, notes)
# grid and map the scans
PyHum.map(humfile, sonpath, cs2cs_args, dogrid, res, dowrite, mode, nn, influence, numstdevs)
res = 0.5 # grid resolution in metres
numstdevs = 5
# grid and map the texture lengthscale maps
PyHum.map_texture(humfile, sonpath, cs2cs_args, dogrid, res, dowrite, mode, nn, influence, numstdevs)
# calculate and map the e1 and e2 acoustic coefficients from the downward-looking sonar
PyHum.e1e2(humfile, sonpath, cs2cs_args, ph, temp, salinity, beam, transfreq, integ, numclusters, doplot)