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meaniceinbox_bakup.py
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#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Fri Dec 20 13:15:11 2019
@author: strausz
"""
import argparse
import glob
import numpy as np
import datetime as dt
import pandas as pd
import math
import sys
from haversine import haversine
import yaml
import pathlib
parser = argparse.ArgumentParser(description='Get ice concentration around a point')
parser.add_argument('-latlon', '--latlon', nargs=2,
help='latitude and longitude of desired point, W lon must be negative', type=float)
parser.add_argument('-y', '--years', nargs=2, help='year range ie "2015 2019"; must have at least 2 years, can be the same year',
type=int, required=True)
parser.add_argument('-a', '--name', help='optional name of point', type=str)
parser.add_argument('-d', '--distance', help='size of box around point in km',
type=float, required=True)
parser.add_argument('-n', '--nm', help='use nautical miles instead of km',
action="store_true")
parser.add_argument('-r', '--radius', help='use distance as radius around point instead of box',
action="store_true")
parser.add_argument('-m', '--mooring', help='Mooring name, choose from ck1-9, or bs2-8')
parser.add_argument('-v', '--verbose', help='Print some details while processing files',
action="store_true")
args=parser.parse_args()
#this gets the path of where the executable file is located so that you can
#run from anywhere and don't have to tell it where the config file is
file_path=str(pathlib.Path(__file__).parent.resolve())
config_file=file_path + '/' + 'meaniceinbox_config.yaml'
#get config settings from yaml file
#view yaml setup file for descriptions of these variables
with open(config_file, 'r') as file:
config = yaml.safe_load(file)
latfile = config['latfile']
lonfile = config['lonfile']
bootstrap = config['bootstrap']
nrt = config['nrt']
boot_year = config['boot_year']
file.close()
#mooring locaitons taken from 'https://www.pmel.noaa.gov/foci/foci_moorings/mooring_info/mooring_location_info.html'
moorings = {'bs2':[56.869,-164.050], 'bs4':[57.895,-168.878], 'bs5':[59.911,-171.73],
'bs8':[62.194,-174.688], 'bs14':[64.00,-167.933], 'ck1':[70.838,-163.125], 'ck2':[71.231,-164.223],
'ck3':[71.828,-166.070], 'ck4':[71.038,-160.514], 'ck5':[71.203,-158.011],
'ck9':[72.464,-156.548], 'ck10':[70.211,-167.787],
'ck11':[70.013,-166.855], 'ck12':[67.911,-168.195]}
if args.mooring:
if args.mooring in moorings:
inlat = moorings[args.mooring][0]
inlon = moorings[args.mooring][1]
else:
sys.exit("Mooring not listed")
mooring = args.mooring + "_"
else:
inlat = args.latlon[0]
inlon = args.latlon[1]
mooring = ''
if args.nm:
units = 'nm'
else:
units = 'km'
if args.name:
pointname = args.name + "_"
else:
pointname = ''
def decode_datafile(filename):
#determine if it's nrt or bootstrap from filename prefix
#note that we remove path first if it exists
prefix = filename.split('/')[-1:][0][:2]
icefile = open(filename, 'rb')
if prefix == 'nt':
#remove the header
icefile.seek(300)
ice = np.fromfile(icefile,dtype=np.uint8)
ice[ice >= 253] = 0
ice = ice/2.5
elif prefix == 'bt':
ice = np.fromfile(icefile,dtype=np.uint16)
ice = ice/10.
ice[ice == 110] = 100 #110 is polar hole
ice[ice == 120] = np.nan #120 is land
else:
ice=np.nan
icefile.close()
return ice;
def get_date(filename):
#gets date from filename
#first remove path from filename if it is there
filename = filename.split('/')[-1:][0]
date = filename[3:11]
date = dt.datetime.strptime(date,"%Y%m%d")
return date;
def decode_latlon(filename):
latlon_file = open(filename, 'rb')
output = np.fromfile(latlon_file,dtype='<i4')
output = output/100000.0
#output = int(output * 1000)/1000 #sets decimal place at 3 without rounding
latlon_file.close()
return output;
def find_box(lat1, lon1, dist, nm):
#formula pulled from this website:
#http://www.movable-type.co.uk/scripts/latlong.html
if nm:
r=3440
else:
r=6371
dist = dist/2
wlon = math.radians(lon1) + math.atan2(math.sin(math.radians(270)) *
math.sin(dist/r) * math.cos(math.radians(lat1)),
math.cos(dist/r) - math.sin(math.radians(lat1)) *
math.sin(math.radians(lat1)))
elon = math.radians(lon1) + math.atan2(math.sin(math.radians(90)) *
math.sin(dist/r) * math.cos(math.radians(lat1)),
math.cos(dist/r) - math.sin(math.radians(lat1)) *
math.sin(math.radians(lat1)))
nlat = math.asin(math.sin(math.radians(lat1)) * math.cos(dist/r) +
math.cos(math.radians(lat1)) * math.sin(dist/r) *
math.cos(math.radians(0)))
slat = math.asin(math.sin(math.radians(lat1)) * math.cos(dist/r) +
math.cos(math.radians(lat1)) * math.sin(dist/r) *
math.cos(math.radians(180)))
wlon = round(math.degrees(wlon), 4)
elon = round(math.degrees(elon), 4)
nlat = round(math.degrees(nlat), 4)
slat = round(math.degrees(slat), 4)
return([nlat,slat,wlon,elon])
if args.radius:
nlat, slat, wlon, elon = find_box(inlat, inlon, 2*args.distance, nm=args.nm)
dist_type = 'Radius'
else:
nlat, slat, wlon, elon = find_box(inlat, inlon, args.distance, nm=args.nm)
dist_type = 'Box'
#put desired years in list
years = list(range(args.years[0],args.years[1]+1))
files = []
for i in years:
year = str(i)
if i <= boot_year:
path = bootstrap + year + '/'
files = files + glob.glob(path + '*.bin')
else:
path = nrt
files = files + glob.glob(path + '*' + year + '*.bin')
output_date = []
output_ice = []
for i in files:
#print('decoding filename: ' + i)
data_ice={'latitude':decode_latlon(latfile), 'longitude':decode_latlon(lonfile),
'ice_conc':decode_datafile(i)}
df_ice=pd.DataFrame(data_ice)
df_ice_chopped = df_ice[(df_ice.latitude <= nlat) & (df_ice.latitude >= slat) &
(df_ice.longitude >= wlon) & (df_ice.longitude <= elon)]
date = get_date(i)
if args.radius:
fn = lambda x: haversine((inlat, inlon),(x.latitude,x.longitude))
distance = df_ice_chopped.apply(fn, axis=1)
df_ice_chopped = df_ice_chopped.assign(dist=distance.values)
df_ice_chopped = df_ice_chopped.loc[df_ice_chopped.dist < args.distance]
#date_string = date.strftime("%Y,%j")
ice = df_ice_chopped.ice_conc.mean().round(decimals=1)
#print(date_string+','+str(ice))
if args.verbose:
print("Working on File: " + i)
print("For " + date.strftime("%Y-%m-%d") + " ice concentration was "
+ str(ice) + "%")
output_date.append(date)
output_ice.append(ice)
data = {'date':output_date, 'ice_concentration': output_ice}
df = pd.DataFrame(data)
df.set_index(['date'], inplace=True)
years_grouped = df.groupby(df.index.year)
df_out=pd.DataFrame()
for name, group in years_grouped:
year = str(name)
group.index=group.index.dayofyear
group.index.rename("day_of_year", inplace=True)
group.rename(columns={"ice_concentration" : year}, inplace=True)
df_out = pd.concat([df_out,group], axis=1)
#df_out = pd.DataFrame.from_dict(output, orient='index').transpose()
#df_out['DOY']=df_out.DOY.astype(int)
#get longiude suffix, assum lat is north
lat_suffix = 'N'
if inlon < 0:
lon_suffix = 'W'
else:
lon_suffix = 'E'
filename = ("meaniceinbox_" + mooring + pointname + str(inlat) + lat_suffix + "_" +
str(abs(inlon)) + lon_suffix + "_" + str(args.distance) + units +
"_" + dist_type + "_" + str(args.years[0]) + "-" + str(args.years[1]) + ".csv")
df_out.to_csv(filename)