pyhum.e1e2 module

Analysis of first (e1, ‘roughness’) and second (e2, ‘hardness’) echo returns from the high-frequency downward looking echosounder

Generates generalised acoustic parameters for the purposes of point classification of submerged substrates/vegetation

Accounts for the absorption of sound in water

Does a basic k-means cluster of e1 and e2 coefficients into specified number of ‘acoustic classes’

Based on code by Barb Fagetter (blueseas@oceanecology.ca)

Syntax

You call the function like this:

[] = PyHum.e1e2(humfile, sonpath, cs2cs_args, ph, temp, salinity, beam, transfreq, integ, numclusters, doplot)

Parameters

humfile : str
path to the .DAT file
sonpath : str
path where the *.SON files are
cs2cs_args : int, optional [Default=”epsg:26949”]
arguments to create coordinates in a projected coordinate system this argument gets given to pyproj to turn wgs84 (lat/lon) coordinates into any projection supported by the proj.4 libraries
ph : float, optional [Default=7.0]
water acidity in pH
temp : float, optional [Default=10.0]
water temperature in degrees Celsius
salinity : float, optional [Default=0.0]
salinity of water in parts per thousand
beam : float, optional [Default=20.0]
beam width in degrees
transfreq : float, optional [Default=200.0]
transducer frequency in kHz
integ : int, optional [Default=5]
number of pings over which to integrate
numclusters : int, optional [Default=3]
transducer frequency in kHz
doplot : int, optional [Default=1]
1 = make plots, otherwise do not

Returns

sonpath+base+’rough_and_hard’+str(p)+’.csv’ : csv file
contains the following fields: ‘longitude’, ‘latitude’, ‘easting’, ‘northing’, ‘depth’, ‘roughness’, ‘hardness’, ‘average roughness’, ‘average hardness’,’k-mean label’ of the pth chunk ‘average’ implies average over ‘integ’ successive pings

The following are returned if doplot==1:

sonpath+’e1e2_scan’+str(p).png : png image file
png image file showing the downward echosounder echogram overlain with the locations of the start and end of the first and second echo region envelope
sonpath+’e1e2_kmeans’+str(p).png: png image file
png image file showing 1) (left) volume scattering coefficient 1 versus volume scattering coefficient 2, colour-coded by k-means acoustic class, and 2) (right) e1 versus e2, colour-coded by k-means acoustic class
sonpath+’rgh_hard_kmeans’+str(p).png : png image file
png image file showing scatter plot of easting versus northing colour-coded by k-means acoustic class
sonpath+’map_rgh’+str(p).png : png image file
png image file showing scatter plot of ‘roughness’ (e1) overlying an aerial image pulled from an ESRI image server
sonpath+’map_hard’+str(p).png : png image file
png image file showing scatter plot of ‘hardness’ (e2) overlying an aerial image pulled from an ESRI image server
sonpath,’Rough’+str(p).png : png image file
png image overlay associated with the kml file, sonpath,’Hard’+str(p).kml
sonpath,’Rough’+str(p).kml : kml file
kml overlay for showing roughness scatter plot (sonpath,’Rough’+str(p).png)
sonpath,’Hard’+str(p).png : png image file
png image overlay associated with the kml file, sonpath,’Hard’+str(p).kml
sonpath,’Hard’+str(p).kml : kml file
kml overlay for showing harness scatter plot (sonpath,’Hard’+str(p).png)
_images/pyhum_logo_colour_sm.png