profiles.py

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"""
Calls functions defined in "hitbottom.py" and uses them for computation

Globally stored data that is available here after reading in the data (for each profile):
df: flags (flags, depth)
mat: data (z, T)
mat: gradient (z, dTdz)
mat: dT9pt (z, T_av)
mat: secDer (d, d2Tdz2)
list: bath_lon
list: bath_lat
mat: bath_height (lat, long)
var: latitude
var: longitude 
var: date
var: hb_depth

Computation function outputs:
mat/arr: dTdz_peaks (z, T)
mat/arr: const_consec (z,T)

Functions callable (computation):
 - grad_spike(data, gradient, threshold)
 - T_spike(data, threshold)
 - const_temp(data, gradient, consec_points, detection_threshold)
 - temp_increase(data, consec_points)
 - bath_depth(latitude, longitude, bath_lon, bath_lat, bath_height)
 
Reading files or plotting (non-computational):
 - read_data(filename) | returns:	flags, hb_depth, latitude, longitude, date, data, gradient
						 opetionl (need to add): secDer, dT9pt
 - plot_data(plot) | creates plot	
 - bathymetry(filename) | returns:	bath_height, bath_lon, bath_lat
"""


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# libraries

import numpy as np
import pandas as pd
import math
import time
import os.path
import sys, getopt
import matplotlib.pyplot as plt
from netCDF4.utils import ncinfo
from netCDF4 import Dataset
import hitbottom as hb


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# computation using code from hitbottom.py

# filename generation
path = "../HBfiles/"

# taking sample of files from the name file
#namefile = open("HBfiles_golden.txt","r")
namefile = open("nn_filecheck.txt","r")
name_array = []
raw_name = []
for line in namefile:
	line = line.rstrip()
	name = str(path+line)
	raw_name.append(str(line))
	name_array.append(name)
namefile.close()

# reading files
for i in range(0,len(name_array)):
	
	# reading in file here
	filename = name_array[i]
	rawname = raw_name[i]
	print(i,filename)
	[data, gradient, flags, hb_depth, latitude, longitude, date] = hb.read_data(filename)
	[bath_height, bath_lon, bath_lat] = hb.bathymetry("../terrainbase.nc")

	# code for the points on the plot
	const = hb.const_temp(data, gradient, 100, 0.001)
	inc = hb.temp_increase(data, 50)
	error_pts = hb.concat(const, inc)
	Tspike = hb.T_spike(data, 0.05)
	dTspike = hb.grad_spike(data, gradient, 3)
	pot_hb = hb.concat(Tspike,dTspike)
	bathydepth = hb.bath_depth(latitude, longitude, bath_lon, bath_lat, bath_height)
	low_gradvar = hb.grad_var(data, gradient, 5, 100)
	up_lim = hb.depth_limits(latitude, longitude, bath_lon, bath_lat, bath_height)
	hb.plot_data(True, data, gradient, flags, bathydepth, error_pts, pot_hb, rawname, 
				 low_gradvar, up_lim)
	print("\n")


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