fishBelly.py

#Jordan Pierce
#This is a program that can be used with a Lowrance fishfinder in order to obtain
#	the GPS locations, depth soundings, elevation, and temperatures. The program 
#	takes in a file in .csv format, strips the data listed above and stores it into a
#	multidimensional array. The array then goes through and transforms the 
#	GCS  positions (Lowrence uses a Mercator meter format), to an decimal degree format 
# 	that can be used to project the locations on an standard projection (WGS84), 
#	[Function: MeterstoDeg()]. The last thing it does it takes all of the excess values,
#	the zeros, and the NULL values for each record and removes them. The GPS records
#	a position between .1-.9 seconds, while the depth sounder records a value every
#	.1 seconds, because of this, their are many records that have no GPS locations
#	but plenty of other fluff I didn't need [Extractonator()]. It then stores the
#	rest of the information to another .csv file that can be used in mapping
#	software (ArcGIS) 
#
#	I made this program specifically to make a 3D model of a body of water, using
#	a Lowrance fishfinder, and ArcGIS. The variables saved are just the ones I needed
#	but changes are welcomed if needed. Cheers. 
#-------------------------------------------------------------------------------------

#Libraries
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import datetime


#This function takes in two arrays, lat and lon, and the number of records.
#It takes the values, transforms them, and stores them into new arrays, and
# then returns it back to main.
##------------------------------------------------------------------------------------
def MetersToDeg(Lat, Lon, MAX):
    RADtoDEG = 57.295779513082322
    EarthRad = 6356752.3142
    count = 0
    New_lat = []
    New_lon = []
    
    #Formula to do the transformation for Lat
    for i in range(0,MAX):
        temp = float(Lat[count]/EarthRad)
        temp = np.exp(temp)
        temp = (2*np.arctan(temp))-(np.pi/2)
        temp = temp * RADtoDEG
        New_lat.append(temp)
        count+=1
    
    #Formula to do the transformation for Lon
    count = 0
    for i in range(0, MAX):
        temp = float(Lon[count])
        New_lon.append(temp/EarthRad * RADtoDEG)
        count+=1
        
    return New_lat, New_lon
    
##--------------------------------------------------------------------------------


#This function takes the new arrays, and the other information, and loops through
# all of them. If the record doesn't contain a NULL value as a coordinate, then 
# the record is saved to a new array. A lot of the sounding information is lost
# but it's due to the fact that it takes measurements 10x faster than the GPS.
# I figured the data lost isn't that important because the amount of change in the
# bathymetry within one second isn't going to be drastic. A way to save the data
# could be implemented, or even averaged for each coordinate if you so desire.
# The new arrays with the data are returned to main.
##--------------------------------------------------------------------------------
def Extractonator(New_lat, New_lon, Elevation, Temp, Depth, MAXVALUE):
    
    lat = []
    lon = []
    elevation = []
    temp = []
    depth = []
    count = 0
    
    print "Points:" 
    
    while count < MAXVALUE:
        if New_lat[count] != 0.0:
            lat.append(New_lat[count])
            lon.append(New_lon[count])
            elevation.append(Elevation[count])
            temp.append(Temp[count])
            depth.append(Depth[count])
        count+=1
        print count
    
    count = 0
    
    return lat, lon, elevation, temp, depth
##------------------------------------------------------------------------------

#Main

#requests input from the user
ans = raw_input("Enter the file name and extension: ")
print 'Filename: ', ans

#Stores  the filename
filename = file(ans)

#opens the file using Panda
Position = pd.read_csv(ans)
 
#arrays for each (in panda format (integers), must be changed to doubles)
Lat = Position.PositionY
Lon = Position.PositionX

#Checks to make sure the positions are paired correctly (just in case)
if Lat.size == Lon.size:
    MAXVALUE = Lat.size
else:
    print 'bad data'
    exit()

#Program call and new arrays
New_lat, New_lon = MetersToDeg(Lat,Lon, MAXVALUE)
Elevation = Position.Altitude 
Temp = Position.WaterTemp
Depth = Position.Depth
  
lat, lon, elevation, temp, depth = Extractonator(New_lat, New_lon, Elevation, Temp, Depth, MAXVALUE)

#outputs the data using Pandas in a orderly, .csv format for use in other software
df = pd.DataFrame({'depth':depth,'temp':temp,'lat':lat,'lon':lon,'elevation':elevation})
df.to_csv('OutputSonar.txt', columns = ('depth', 'temp', 'lat', 'lon', 'elevation'),sep= '\t')

print 'Done. File outputted to folder'