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file_process_tools.py
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def traceproc(aerolevel,aerofilt_dir):
import hysplit_tools as tools
import os, sys
import scipy.io
import numpy as np
startdir = os.getcwd()
topdir = aerofilt_dir+'\Level '+aerolevel
os.chdir(topdir)
data_files = os.listdir(os.getcwd())
d_mean = []
d_std = []
t_mean = []
t_std = []
endpos_mean = []
endpos_std = []
start_time = []
station = []
#run through all location folders
for f in data_files:
if os.path.isdir(f):
os.chdir(f)
tracefile = f+'traceback2'
#open traceback file
tracedict = scipy.io.loadmat(tracefile)
#create a separate dict of lists for each day and put those into a
#list called dictlist
dates = tracedict['start_date']
keys = tracedict.keys()
oldday = dates[0][2]
tempdict = dict()
dictlist = []
#ignore these keys that come attached to the dictionary from loadmat
rejectlist = ['__globals__','__header__','__version__']
for k,v in tracedict.iteritems():
if k not in rejectlist:
tempdict[k] = []
tempdict[k].append(v[0])
for n in range(1,len(dates)):
newday = dates[n][2]
if newday == oldday:
for k,v in tracedict.iteritems():
if k not in rejectlist:
tempdict[k].append(v[n])
oldday = newday
else:
dictlist.append(tempdict)
tempdict = dict()
for k,v in tracedict.iteritems():
if k not in rejectlist:
tempdict[k] = []
tempdict[k].append(v[n])
oldday = newday
dictlist.append(tempdict)
#generate mean daily values for each element of the dictionaires
for line in dictlist:
d_mean.append(np.mean(line['delta_d']))
d_std.append(np.std(line['delta_d']))
t_mean.append(np.mean(line['delta_t']))
t_std.append(np.std(line['delta_t']))
endpos_mean.append(np.mean(line['end_loc'],axis=0))
endpos_std.append(np.std(line['end_loc'],axis=0))
start_time.append(line['start_date'][0])
station.append(str(line['station'][0]))
os.chdir('..')
output_dict = {'d_mean':d_mean,'d_std':d_std,'t_mean':t_mean,'t_std':t_std,\
'endpos_mean':endpos_mean,'endpos_std':endpos_std,\
'start_time':start_time,'station':station}
scipy.io.savemat('Hyproc'+aerolevel,output_dict)
os.chdir(startdir)
def aeroproc(aerolevel,aerofilt_dir):
import hysplit_tools as tools
import os, sys
import scipy.io
import numpy as np
startdir = os.getcwd()
topdir = aerofilt_dir+'\Level '+aerolevel
os.chdir(topdir)
data_files = os.listdir(os.getcwd())
total_mean = []
total_std = []
fine_mean = []
fine_std = []
coarse_mean = []
coarse_std = []
inpoint = []
numdist_mean = []
numdist_std = []
station = []
date = []
diameters = []
#run through all location folders
for f in data_files:
if os.path.isdir(f):
os.chdir(f)
aerofile = 'Aerostats_'+f+'_'+aerolevel
#open traceback file
aerodict = scipy.io.loadmat(aerofile)
#create a separate dict of lists for each day and put those into a
#list called dictlist
dates = aerodict['Date']
keys = aerodict.keys()
oldday = dates[0][-2]
tempdict = dict()
dictlist = []
#ignore these keys that come attached to the dictionary from loadmat
rejectlist = ['__globals__','__header__','__version__']
for k,v in aerodict.iteritems():
if k == 'Diameters':
tempdict[k] = []
tempdict[k].append(v)
elif k == 'Numdist':
tempdict[k] = []
tempdict[k].append(v[:,0])
elif k not in rejectlist:
tempdict[k] = []
tempdict[k].append(v[0])
for n in range(1,len(dates)):
newday = dates[n][-2]
if newday == oldday:
for k,v in aerodict.iteritems():
if k == 'Diameters':
tempdict[k].append(v)
elif k == 'Numdist':
tempdict[k].append(v[:,n])
elif k not in rejectlist:
tempdict[k].append(v[n])
oldday = newday
else:
dictlist.append(tempdict)
tempdict = dict()
for k,v in aerodict.iteritems():
if k == 'Diameters':
tempdict[k] = []
tempdict[k].append(v)
elif k == 'Numdist':
tempdict[k] = []
tempdict[k].append(v[:,n])
elif k not in rejectlist:
tempdict[k] = []
tempdict[k].append(v[n])
oldday = newday
dictlist.append(tempdict)
#generate mean daily values for each element of the dictionaires
for line in dictlist:
total_mean.append([np.mean(line['EffRad-T']),np.mean(line['VolMedianRad-T']),\
np.mean(line['VolCon-T']),np.mean(line['StdDev-T'])])
total_std.append([np.std(line['EffRad-T']),np.std(line['VolMedianRad-T']),
np.std(line['VolCon-T']),np.std(line['StdDev-T'])])
fine_mean.append([np.mean(line['EffRad-F']),np.mean(line['VolMedianRad-F']),
np.mean(line['VolCon-F']),np.mean(line['StdDev-F'])])
fine_std.append([np.std(line['EffRad-F']),np.std(line['VolMedianRad-F']),
np.std(line['VolCon-F']),np.std(line['StdDev-F'])])
coarse_mean.append([np.mean(line['EffRad-C']),np.mean(line['VolMedianRad-C']),
np.mean(line['VolCon-C']),np.mean(line['StdDev-C'])])
coarse_std.append([np.std(line['EffRad-C']),np.std(line['VolMedianRad-C']),
np.std(line['VolCon-C']),np.std(line['StdDev-C'])])
inpoint.append(np.mean(line['Inflection_Point[um]']))
numdist_mean.append(np.mean(line['Numdist'],axis=0))
numdist_std.append(np.std(line['Numdist'],axis=0))
station.append(f)
date.append(np.mean(line['Date'],axis=0))
diameters.append(line['Diameters'])
os.chdir('..')
output_dict = {'station':station,'date':date,'numdist_mean':numdist_mean,'numdist_std':numdist_std,\
'total_mean':total_mean,'total_std':total_std,'fine_mean':fine_mean,'fine_std':fine_std,\
'coarse_mean':coarse_mean,'coarse_std':coarse_std,'inpoint':inpoint,'diameters':diameters}
scipy.io.savemat('Aeroproc'+aerolevel,output_dict)
os.chdir(startdir)
def combproc(level,aerofilt_dir):
import hysplit_tools as tools
import os, sys
import numpy as np
import scipy.io
startdir = os.getcwd()
topdir = aerofilt_dir+'\Level '+aerolevel
os.chdir(topdir)
aerofile = 'Aeroproc'+aerolevel
hyfile = 'Hyproc2'+aerolevel
aerodict = scipy.io.loadmat(aerofile)
hydict = scipy.io.loadmat(hyfile)
#divide both dicts up by station
aerostations = set(aerodict['station'])
hystations = set(hydict['station'])
#ignore these keys that come attached to the dictionary from loadmat
rejectlist = ['__globals__','__header__','__version__']
hylist = []
for stat in hystations:
tempdict = dict()
for n in range(0,len(hydict['station'])):
if hydict['station'][n] == stat:
for key in hydict.keys():
if key not in rejectlist:
if key == 'start_time':
tempval = np.reshape(hydict[key][n],[1,4])
elif key == 'station':
tempval = [hydict[key][n]]
else:
tempval = hydict[key][n]
try:
tempdict[key].append(tempval)
except KeyError:
tempdict[key] = np.array(tempval)
except AttributeError:
tempdict[key] = np.vstack((tempdict[key],tempval))
if len(tempdict['station']) != 1:
hylist.append(tempdict)
aerolist = []
for stat in aerostations:
tempdict = dict()
for n in range(0,len(aerodict['station'])):
if aerodict['station'][n] == stat:
for key in aerodict.keys():
if key not in rejectlist:
if key == 'start_time':
tempval = [np.reshape(aerodict[key][n],[1,4])]
elif key == 'station':
tempval = [aerodict[key][n]]
else:
tempval = aerodict[key][n]
try:
tempdict[key].append(tempval)
except KeyError:
tempdict[key] = np.array(tempval)
except AttributeError:
tempdict[key] = np.vstack((tempdict[key],tempval))
if len(tempdict['station']) != 1:
aerolist.append(tempdict)
#remove dates where hysplit didn't find traces to deserts
aerolist_mod = []
for h in hylist:
hydates = h['start_time'][:,2]
hystation = h['station'][0]
for a in aerolist:
aerostation = a['station'][0]
if aerostation == hystation:
tempdict = dict()
for n in range(0,len(a['station'])):
aerodate = a['date'][n,2]
if aerodate in hydates:
for key in a.keys():
try:
tempdict[key].append(a[key][n])
except KeyError:
tempdict[key] = a[key][n]
except AttributeError:
tempdict[key] = np.vstack((tempdict[key],a[key][n]))
aerolist_mod.append(tempdict)
output_dict = {'Hysplit':hylist,'Aeronet':aerolist_mod}
scipy.io.savemat('Combproc2'+aerolevel,output_dict)