ts = []
for i in range(len(times)):
ts.append(calendar.timegm(times[i].timetuple()))
ctd_data = ah.split_csv_profiles(
press, [longitude, latitude, temperature, salinity, ts])
#tehdän se perus aikajana
timesx = ctd_data[:, 0, 5]
times = []
for i in range(len(timesx)):
times.append(dt.datetime.utcfromtimestamp(timesx[i]))
# d=np.ma.masked_where(d==invalid_val,d)
#create mask, for values close to main point:
distance_mask = [False] * len(times_s)
for i in range(len(times_s)):
if (target_rad > ah.distance((target_lat, target_lon),
(latitude[i], longitude[i]))):
distance_mask[i] = True
#Ja perus paikkajanatkin
pressure = ctd_data[:, :, 0]
latitude = ctd_data[:, 0, 2]
longitude = ctd_data[:, 0, 1]
temperature = ctd_data[:, :, 3]
salinity = ctd_data[:, :, 4]
if (draw_images):
for i in range(ctd_data.shape[0]):
plt.plot(temperature[i, :] + 0.5 * i, pressure[i, :])
else:
print("wrong fieltype,", filetype, " aborting!")
filetype = 'exitnow'
if (filetype != 'exitnow'):
for i in range(len(times_s)):
times.append(dt.datetime.strptime(times_s[i],'%Y-%m-%dT%H:%M'))
ts=[]
for i in range(len(times)):
ts.append(calendar.timegm(times[i].timetuple()))
ctd_data=ah.split_csv_profiles(press,[longitude,latitude,temperature,salinity,ts,oxygen])
#tehdän se perus aikajana
timesx=ctd_data[:,0,5]
times=[]
for i in range(len(timesx)):
times.append(dt.datetime.utcfromtimestamp(timesx[i]))
# d=np.ma.masked_where(d==invalid_val,d)
#create mask, for values close to main point:
distance_mask=[False]*len(times_s)
for i in range(len(times_s)):
if(target_rad>ah.distance((target_lat,target_lon),(latitude[i],longitude[i]))):
distance_mask[i]=True
#Ja perus paikkajanatkin
pressure=ctd_data[:,:,0]
latitude=ctd_data[:,0,2]
longitude=ctd_data[:,0,1]
temperature=ctd_data[:,:,3]
salinity=ctd_data[:,:,4]
oxygen=ctd_data[:,:,6]
else:
print "wrong fieltype,",filetype," aborting!"
filetype='exitnow'
if(filetype!='exitnow'):
#
files=[]
for f in all_files:
if(re.match(".*log",f) is not None):
files.append(f)
for i in range(len(files)-1):
alku="".join(open(datadirectory+files[i],'r').readlines())
loppu="".join(open(datadirectory+files[i+1],'r').readlines())
try:
t1=dt.datetime.strptime(re.search("\d\d/../.... ......",alku).group(0),"%m/%d/%Y %H%M%S")
t2=dt.datetime.strptime(re.search("\d\d/../.... ......",loppu).group(0),"%m/%d/%Y %H%M%S")
lat1=float(re.search("Fix:[\s]*(-*\d*\.\d*)\s*(-*\d*\.\d*)",alku).group(2))
lon1=float(re.search("Fix:[\s]*(-*\d*\.\d*)\s*(-*\d*\.\d*)",alku).group(1))
aika=(t2-t1).total_seconds()
lat2=float(re.search("Fix:[\s]*(-*\d*\.\d*)\s*(-*\d*\.\d*)",loppu).group(2))
lon2=float(re.search("Fix:[\s]*(-*\d*\.\d*)\s*(-*\d*\.\d*)",loppu).group(1))
dist=ah.distance((lat1,lon1),(lat2,lon2))
# print aika/60., 'min'
# print '{:.2f} km'.format(dist)
# print '{:.2} m/s'.format(1000.*dist/aika)
print("Move: {:04.2f} km in \t{:02.2f} min.\tSpeed {:02.2f} cm/s\t({},{}) to ({},{}) ".format(
dist, aika/60, 100000.*dist/aika, lat1,lon1,lat2,lon2
))
# print lat1,lon1,lat2,lon2
if(plotting):
x,y=bmap([lon1,lon2],[lat1,lat2])
bmap.plot(x,y,'-*r')
except AttributeError:
print("broken file")
times.append(dt.datetime.strptime(times_s[i], '%Y-%m-%dT%H:%M'))
ts = []
for i in range(len(times)):
ts.append(calendar.timegm(times[i].timetuple()))
ctd_data = ah.split_csv_profiles(
press, [longitude, latitude, temperature, salinity, ts, oxygen])
#tehdän se perus aikajana
timesx = ctd_data[:, 0, 5]
times = []
for i in range(len(timesx)):
times.append(dt.datetime.utcfromtimestamp(timesx[i]))
# d=np.ma.masked_where(d==invalid_val,d)
#create mask, for values close to main point:
distance_mask = [False] * len(times_s)
for i in range(len(times_s)):
if (target_rad > ah.distance((target_lat, target_lon),
(latitude[i], longitude[i]))):
distance_mask[i] = True
#Ja perus paikkajanatkin
pressure = ctd_data[:, :, 0]
latitude = ctd_data[:, 0, 2]
longitude = ctd_data[:, 0, 1]
temperature = ctd_data[:, :, 3]
salinity = ctd_data[:, :, 4]
oxygen = ctd_data[:, :, 6]
else:
print "wrong fieltype,", filetype, " aborting!"
filetype = 'exitnow'
if (filetype != 'exitnow'):
#
#
# distance_mask[i]=True
#Ja perus paikkajanatkin
pressure = ctd_data[:, :, 0]
latitude = ctd_data[:, 0, 2]
longitude = ctd_data[:, 0, 1]
temperature = ctd_data[:, :, 3]
salinity = ctd_data[:, :, 4]
oxygen = ctd_data[:, :, 6]
print "CTD's masked, time T+{}".format(time.time() - last_time)
last_time = time.time()
#create mask, for values close to main point:
distance_mask = [False] * len(times)
for i in range(len(times)):
if (target_rad > ah.distance((target_lat, target_lon),
(latitude[i], longitude[i]))):
distance_mask[i] = True
files = ah.file_names_converted
timesteps = []
last_accepted = True
a_time_all = []
a_distance_mask_all = []
for file_n in files:
fmk = netcdf.netcdf_file(file_n, 'r')
temp = fmk.variables['TEMP_ADJUSTED'][:].copy()
salt = fmk.variables['PSAL_ADJUSTED'][:].copy()
press = fmk.variables['PRES_ADJUSTED'][:].copy()
oxyg = fmk.variables['DOXY'][:].copy()
scat = fmk.variables['SCATTERING'][:].copy()
apetime = np.array(