#hard_start = 0
hard_start = eventpaths.index(boxpath + '/cutdata_s/Event_2010_06_13_03_08_57/AZ_PFO_HHE__2010_06_13_03_08_57.SAC')
print(hard_start)
#read in cut data, rmean and rtrend, find .resp file, correct and add to icorr dir
for i in range(hard_start,len(eventpaths)):#in this case event paths are all sac files
base = path.basename(eventpaths[i])
print 'correcting file: ' + base
folder = eventpaths[i].split('/')[-2]
network = base.split('_')[0]
station = base.split('_')[1]
full_channel = base.split('_')[2]
#find response file
respfile = response_path + '/' + network + '.' + station + '.' + channel + '.resp'
#first rmean and rtrend
stream = read(eventpaths[i])
tr = stream[0]
#check and make sure that the trace isn't empty
if(tr.stats.npts > 0):
tr.detrend(type = 'demean')#removes mean of data
tr.detrend(type = 'simple')#rtrend linear from first and last samples
#rewrite to a sac file
tr.write('temp.sac', format = 'sac')
sacfile = 'temp.sac'
icorr_sacfile = icorr_path + '/' + folder + '/'+ base
#uncorrected_sac_file,resp_file,corrected_sac_file,water_level_bds,resp_unit
wf.remove_response(sacfile,respfile,icorr_sacfile,prefilt,tsunit)#prefilt values for HH
raw_file_N = boxpath + '/cutdata_s/Event_' + eventid + '/' + network + '_' + station + '_HHN_' + loc + '_' + eventid + '.SAC'
prefilt = (0, 0.4, 35, 50)
respfile = top_dir + '/boxes/' + box + '/respfiles/' + network + '.' + station + '.HH*.resp'
tsunit = 'VEL'
icorr_sacfile = top_dir + '/boxes/' + box + '/icorrN.SAC'
stream = read(raw_file_N)
tr = stream[0]
# tr.detrend(type = 'demean')#removes mean of data
# tr.detrend(type = 'simple')#rtrend linear from first and last samples
#rewrite to a sac file
tr.write('temp.sac', format='sac')
sacfile = 'temp.sac'
wf.remove_response(sacfile, respfile, icorr_sacfile, prefilt, tsunit)
stream = read(icorr_sacfile)
tr = stream[0]
dataN = tr.data
raw_file_E = boxpath + '/cutdata_s/Event_' + eventid + '/' + network + '_' + station + '_HHE_' + loc + '_' + eventid + '.SAC'
respfile = top_dir + '/boxes/' + box + '/respfiles/AZ.BZN.HH*.resp'
tsunit = 'VEL'
icorr_sacfile = top_dir + '/boxes/' + box + '/icorrE.SAC'
stream = read(raw_file_E)
tr = stream[0]
# tr.detrend(type = 'demean')#removes mean of data
# tr.detrend(type = 'simple')#rtrend linear from first and last samples
#rewrite to a sac file
# st = stream
tr = stream[0]
ny = tr.stats.sampling_rate * 0.5
print ny
# ny = 0.125
####################
prefilt = (0.0, 0.01, 0.7 * ny, ny)
tr.detrend(type='demean') #removes mean of data
tr.detrend(type='simple') #rtrend linear from first and last samples
#rewrite to a sac file
tr.write('temp.sac', format='sac')
sacfile = 'temp.sac'
icorr_sacfile = icorr_path + '/' + base
wf.remove_response(sacfile, respfile, icorr_sacfile, prefilt,
'VEL') #, plot=True)#prefilt values for HH
f = glob.glob(workingdir + 'corrected/*.sac')
for i in range(len(f)):
st = read(f[i])
name = (f[i].split('/')[-1])[0:-4] #.split('.')[0:4]
print name
fig = st.plot()
fig.savefig(workingdir + 'corrected/' + name + '.png')
#f = glob.glob(workingdir + 'corrected/*.sac')
#for i in range(len(f)):
# st = read(f[i])
# name = (f[i].split('/')[-1])[0:-4]#.split('.')[0:4]
# print name
## st.filter("bandpass", freqmin=.001, freqmax=0.125,corners=2, zerophase=False)