#a tool for generating a control file for use with HYSPLIT to make trajectories

import os,sys

os.chdir('c:/hysplit4/working/')

if os.path.isfile('CONTROL'):

os.remove('CONTROL')

year = str(start_time[0]).zfill(2)

month = str(start_time[1]).zfill(2)

day = str(start_time[2]).zfill(2)

hour = str(start_time[3]).zfill(2)

time_in = year+' '+month+' '+day+' '+hour

latlonht = str(location[1])+' '+str(location[2])+' '+str(height)

output_path = output_dir+'/'+location[0]+'/'

if not os.path.isdir(output_path):

os.makedirs(output_path)

output_file = location[0]+year+month+day+hour+'_'+str(height)+'.txt'

cont_file = open('CONTROL','w')

cont_file.writelines(time_in+'\n'+'1\n'+latlonht+'\n'+str(run_hours)+'\n'+\

'0\n20000\n'+str(len(meteo_files))+'\n')

for n in meteo_files:

[meteo_path,meteo_filename] = os.path.split(n)

cont_file.writelines(meteo_path+'/\n'+meteo_filename+'\n')

cont_file.writelines(output_path+'\n'+output_file)

#simply sets the current working directory to one selected by the useer

from Tkinter import Tk

import tkFileDialog

master = Tk()

master.withdraw() #hiding tkinter window

file_path = tkFileDialog.askdirectory(title=titlestring)

if file_path != "":

return str(file_path)

else:

#grabs all files in a folder that contain the titlestring input

from Tkinter import Tk

import tkFileDialog

master = Tk()

master.withdraw() #hiding tkinter window

file_path = []

file_path = tkFileDialog.askopenfilename(title=titlestring, filetypes=[filetype,("All files",".*")],multiple='True')

if file_path != "":

return str(file_path)

else:

# import aeronet data file into a list of dictionaries

# filename must include full path to file

import csv

filetoread = open(filename,'r')

header = []

headerlines = 3

for n in range(0,headerlines):

header.append(next(filetoread))

tempdict = csv.DictReader(filetoread)

aerodict = []

for row in tempdict:

aerodict.append(row)

filetoread.close()

# import hysplit data file into a list

# filename must include full path to file

import csv

import numpy as np

filetoread = open(filename,'rb')

h = next(filetoread)

header = []

headmarker = '1 PRESSURE'

while headmarker not in h:

header.append([h])

h = next(filetoread)

temp = csv.reader(filetoread,delimiter = ' ',skipinitialspace = 'True')

hysplitdata = np.array([])

for row in temp:

hysplitdata = np.append(hysplitdata,row)

hysplitdata = np.reshape(hysplitdata,(-1,13))

hysplitdata = hysplitdata.astype('float16')

filetoread.close()

#import data dictionary and filter for desired keys

#output goes into matlab file (filename.mat) in selected output folder

#with each key pointing to a list of values date time and data type (1.5 or 2.0) are included

#filterkeys is a list of variables to extract from the Aeronet file

import os,sys

import datetime as dt

[header,aerodict] = aeronet_import(aerofile)

datelist = []

datatypelist = []

output_dict = dict()

for line in aerodict:

tempdate = line['Date(dd-mm-yyyy)'].split(':')

temptime = line['Time(hh:mm:ss)'].split(':')

year = int(tempdate[2])

month = int(tempdate[1])

day = int(tempdate[0])

hour = int(temptime[0])

tempdatatype = line['DATA_TYPE']

date = dt.datetime(year,month,day,hour)

datelist.append(date)

datatypelist.append(tempdatatype)

output_dict['Date'] = datelist

output_dict['Data Type'] = datatypelist

for key in filterkeys:

temp = []

for line in aerodict:

temp.append(float(line[key]))

output_dict[key] = temp

#takes in a full path to an aeronet file, then extracts the days for whcih

#data were collected and filters a folder full of hysplit files to

#include only days for which aeronet data exist and dumps filtered list into

#a new directory in "aerofilt_dir" directory with the same folder

#name as the one containing original hysplit files

import os,sys

import shutil

print 'Performing Aeronet Dayfilter ...'

startdir = os.getcwd()

[aeronet_dir,aeronet_file] = os.path.split(aeronet_path)

os.chdir(aeronet_dir)

[aeronet_header,aerodict] = aeronet_import(aeronet_file)

[hysplit_dir,hysplit_folder] = os.path.split(hysplit_path)

aerodir = aerofilt_dir+'/'+hysplit_folder

try:

os.mkdir(aerodir)

except OSError:

pass

datestring = []

for line in aerodict:

tempdate = line['Date(dd-mm-yyyy)'].split(':')

year = tempdate[2][-2:]

month = tempdate[1]

day = tempdate[0]

temp_datestring = year+month+day

if temp_datestring not in datestring:

datestring.append(temp_datestring)

os.chdir(hysplit_path)

hysplit_files = os.listdir('.')

numdays = len(hysplit_files)

n = 0

for f in hysplit_files:

for s in datestring:

if s in f:

n += 1

#print f, n

if not os.path.isfile(aerodir+'\\'+f):

shutil.copy2(f,aerodir)

print '%i out of %i total files used' %(n, numdays)

os.chdir(startdir)

#function to compute distance and bearing between

#two latitude/longitude coordinates

#output distance is in km, bearing is in degrees

from math import *

R = 6371 #radius of Earth in km

dlat = radians(lat2-lat1)

dlong = radians(long2-long1)

lat1 = radians(lat1)

lat2 = radians(lat2)

a = sin(dlat/2)**2 + sin(dlong/2)**2 * cos(lat1) * cos(lat2)

b = 2*atan2(sqrt(a),sqrt(1-a))

d = R*b

y = sin(dlong)*cos(lat2)

x = cos(lat1)*sin(lat2) - sin(lat1)*cos(lat2)*cos(dlong)

theta = degrees(atan2(y,x))

#function to output distance from center to edge of a tilted ellipse

#a = major axis

#b = minor axis

#theta1 = heading between center and point in Earth-centerd coordinates (0 deg = N)

#theta2 = angle between major axis and N-S axis

from math import *

dtheta = theta2-theta1

x = b*cos(radians(dtheta))

y = a*sin(radians(dtheta))

r = a*b/sqrt(x**2 + y**2)

#check if a file is a .mat file

nametest1 = filename.split('.')

if nametest1[-1] == 'txt':

for htest in filelist:

nametest2 = htest.split('.')

if nametest2[0] == nametest1[0] and nametest2[-1] == 'mat':

return False

return True

else:

#check if a file is a .pickle file

nametest1 = filename.split('.')

if nametest1[-1] == 'txt':

for htest in filelist:

nametest2 = htest.split('.')

if nametest2[0] == nametest1[0] and nametest2[-1] == 'pickle':

return False

return True

else:

#tool for extracting data from hysplit trajectory files and putting it into

#mat files for storage in float16 format

import numpy as np

import scipy.io

import os,sys

data_cats = ('year','month','day','hour','delta_t','lat','lon','alt','press')

startdir = os.getcwd()

os.chdir(aerofilt_dir)

hysplit_files = os.listdir(os.getcwd())

print 'Generating Hysplit .mat files ...'

for h in hysplit_files:

if matfile_test(h,hysplit_files):

#import hysplit text file

[head,data] = hysplit_import(h)

#create dictionary with {varname: array} based on column names

output_data = [data[:,2],data[:,3],data[:,4],data[:,5],data[:,8],\

data[:,9],data[:,10],data[:,11],data[:,12]]

output_dict = dict(zip(data_cats,output_data))

#use scipy.savemat to save it as a .mat file

savename = h.split('.')[0]

scipy.io.savemat(savename,output_dict)

os.chdir(startdir)

#tool for extracting data from hysplit trajectory files and putting it into

#a pandas dataframe for storage in float16 format

import pandas as pan

import os,sys

data_cats = ('delta_t','lat','lon','alt','press')

startdir = os.getcwd()

os.chdir(aerofilt_dir)

hysplit_files = os.listdir(os.getcwd())

print 'Generating Hysplit dataframe ...'

for h in hysplit_files:

if pickle_test(h,hysplit_files):

#import hysplit text file

[head,data] = hysplit_import(h)

#create dictionary with {varname: array} based on column names

output_data = [data[:,8],data[:,9],data[:,10],data[:,11],data[:,12]]

output_dict = dict(zip(data_cats,output_data))

#create datetime index

dates = []

for n in range(0,len(data[:,2])):

yr = data[n,2]

mn = data[n,3]

dy = data[n,4]

hr = data[n,5]

dates.append(pan.datetime(yr,mn,dy,hr))

ind = pan.DatetimeIndex(dates)

df_out = pan.DataFrame(output_dict, index = ind)

#save it as a .pickle file

savename = h.split('.')[0]

pan.save(df_out,savename+'.pickle')

os.chdir(startdir)

#tool for extracting values of interest from aeronet data file, putting it into a

#dictionary and saving i as a .mat file

import os, sys

import scipy.io

import numpy as np

startdir = os.getcwd()

print 'Generating Aeronet .mat file ...'

output_path = aerofilt_dir

output_folder = os.path.split(aerofilt_dir)[1]

numdist_keys = ['0.050000','0.065604','0.086077','0.112939','0.148184','0.194429','0.255105',\

'0.334716','0.439173','0.576227','0.756052','0.991996','1.301571','1.707757',\

'2.240702','2.939966','3.857452','5.061260','6.640745','8.713145','11.432287','15.000000']

keylist = ['Inflection_Point[um]','VolCon-T','EffRad-T','VolMedianRad-T','StdDev-T',\

'VolCon-F','EffRad-F','VolMedianRad-F','StdDev-F',\

'VolCon-C','EffRad-C','VolMedianRad-C','StdDev-C']

filename = 'Aerostats_'+output_folder

newdict = aeronet_extract(aerofile,keylist)

temp_dist = []

numdist_diameters = []

for tempkey in numdist_keys:

tempdict = aeronet_extract(aerofile,[tempkey])

temp_dist.append(tempdict[tempkey])

numdist_diameters.append(float(tempkey))

newdict['Numdist'] = np.array(temp_dist, dtype='float16')

newdict['Diameters'] = numdist_diameters

os.chdir(output_path)

scipy.io.savemat(filename,newdict)

os.chdir(startdir)

#tool for extracting values of interest from aeronet data file, putting it into a

#dictionary and saving it as a pandas dataframe

import os, sys

import pandas as pan

import numpy as np

startdir = os.getcwd()

print 'Generating Aeronet dataframe ...'

output_folder = os.path.split(aerofilt_dir)[1]

keylist = ['Inflection_Point[um]','VolCon-T','EffRad-T','VolMedianRad-T','StdDev-T',\

'VolCon-F','EffRad-F','VolMedianRad-F','StdDev-F','VolCon-C','EffRad-C',\

'VolMedianRad-C','StdDev-C',\

'0.050000','0.065604','0.086077','0.112939','0.148184','0.194429','0.255105',\

'0.334716','0.439173','0.576227','0.756052','0.991996','1.301571','1.707757',\

'2.240702','2.939966','3.857452','5.061260','6.640745','8.713145','11.432287',\

'15.000000']

filename = 'Aerostats_'+output_folder+'.pickle'

newdict = aeronet_extract(aerofile,keylist)

#convert dates to datetime index

dates = newdict['Date']

del(newdict['Date'])

df_out = pan.DataFrame(newdict, index = dates)

os.chdir(aerofilt_dir)

pan.save(newdict,filename)

os.chdir(startdir)