pyhum.read module

Read a .DAT and associated set of .SON files recorded by a Humminbird(R) instrument.

Parse the data into a set of memory mapped files that will subsequently be used by the other functions of the PyHum module.

Export time-series data and metadata in other formats.

Create a kml file for visualising boat track

Syntax

You call the function like this:

[] = PyHum.read(humfile, sonpath, cs2cs_args, c, draft, doplot, t, bedpick, flip_lr, chunksize, model, calc_bearing, filt_bearing, cog, chunk)

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
c : float, optional [Default=1450.0]
speed of sound in water (m/s). Defaults to a value of freshwater
draft : float, optional [Default=0.3]
draft from water surface to transducer face (m)
doplot : float, optional [Default=1]
if 1, plots will be made
t : float, optional [Default=0.108]
length of transducer array (m). Default value is that of the 998 series Humminbird(R)
bedpick : int, optional [Default=1]
if 1, bedpicking with be carried out automatically if 0, user will be prompted to pick the bed location on screen
flip_lr : int, optional [Default=0]
if 1, port and starboard scans will be flipped (for situations where the transducer is flipped 180 degrees)
model: int, optional [Default=998]
A 3 or 4 number code indicating the model number Examples: 998, 997, 1198, 1199
cog : int, optional [Default=1]
if 1, heading calculated assuming GPS course-over-ground rather than using a compass
calc_bearing : float, optional [Default=0]
if 1, bearing will be calculated from coordinates
filt_bearing : float, optional [Default=0]
if 1, bearing will be filtered
chunk : str, optional [Default=’d100’ (distance, 100 m)]
letter, followed by a number. There are the following letter options: ‘d’ - parse chunks based on distance, then number which is distance in m ‘p’ - parse chunks based on number of pings, then number which is number of pings ‘h’ - parse chunks based on change in heading, then number which is the change in heading in degrees ‘1’ - process just 1 chunk

Returns

sonpath+base+’_data_port.dat’: memory-mapped file
contains the raw echogram from the port side sidescan sonar (where present)
sonpath+base+’_data_port.dat’: memory-mapped file
contains the raw echogram from the starboard side sidescan sonar (where present)
sonpath+base+’_data_dwnhi.dat’: memory-mapped file
contains the raw echogram from the high-frequency echosounder (where present)
sonpath+base+’_data_dwnlow.dat’: memory-mapped file
contains the raw echogram from the low-frequency echosounder (where present)
sonpath+base+”trackline.kml”: google-earth kml file
contains the trackline of the vessel during data acquisition
sonpath+base+’rawdat.csv’: comma separated value file
contains time-series data. columns corresponding to longitude latitude easting (m) northing (m) depth to bed (m) alongtrack cumulative distance (m) vessel heading (deg.)
sonpath+base+’meta.mat’: .mat file
matlab format file containing a dictionary object holding metadata information. Fields are: e : ndarray, easting (m) n : ndarray, northing (m) es : ndarray, low-pass filtered easting (m) ns : ndarray, low-pass filtered northing (m) lat : ndarray, latitude lon : ndarray, longitude shape_port : tuple, shape of port scans in memory mapped file shape_star : tuple, shape of starboard scans in memory mapped file shape_hi : tuple, shape of high-freq. scans in memory mapped file shape_low : tuple, shape of low-freq. scans in memory mapped file dep_m : ndarray, depth to bed (m) dist_m : ndarray, distance along track (m) heading : ndarray, heading of vessel (deg. N) pix_m: float, size of 1 pixel in across-track dimension (m) bed : ndarray, depth to bed (m) c : float, speed of sound in water (m/s) t : length of sidescan transducer array (m) f : frequency of sidescan sound (kHz) spd : ndarray, vessel speed (m/s) time_s : ndarray, time elapsed (s) caltime : ndarray, unix epoch time (s)
_images/pyhum_logo_colour_sm.png