def getDailyMax(fil):
# Get meta info for this station
fw = FixedWidth(META_CONFIG)
# Get number of observations
nday = (sum(1 for line in open(fil,'rb')) - 1)/2
# read in observations
f = open(fil, 'rb')
header = f.readline()
meta = fw._string_to_dict(header)
fw = FixedWidth(TIDE_CONFIG)
cols = ['Gauge','Name','Lat','Lon','Method','Datum','Offset','Year','Month','Day','Max_Tide']
dfOut = pd.DataFrame(columns=cols)
charOut = np.empty((nday,len(cols)),dtype=object)
lat,lon = fmtll(meta['lat'],meta['lon'])
date_last = -9999
nobs_last = -9999
i = 0
for line in f:
parts = fw._string_to_dict(line)
lvls = [int(parts[str(ii)]) for ii in range(1, 13)]
if meta['datum'] == 'X':
lvls = [9999 for jj in lvls] # these data are not referenced to a datum
date = parts['year']+parts['month']+parts['day']
if date == date_last:
this_max = np.max(lvls)
if this_max == 9999:
this_max = np.nan
if (nobs_last + sum([lvls[ii]!=9999 for ii in range(len(lvls))])) < 12:
dayMax = -999
else:
dayMax = np.max([this_max,max_last])
if np.isnan(dayMax): dayMax = -999
charOut[i,:] = [meta['number']+meta['version'],meta['name'],"{0:.2f}".format(lat),"{0:.2f}".format(lon),meta['method'], \
meta['datum'], meta['offset'],parts['year'],parts['month'],parts['day'],str(dayMax)]
i+=1
else:
nobs_last = sum([lvls[ii]!=9999 for ii in range(len(lvls))])
max_last = np.max(lvls)
if max_last == 9999:
max_last = np.nan
date_last = date
#return dfOut,int(str(date)[0:4]),meta
return charOut,int(str(date)[0:4]),meta
def getMonMean(fil):
print "Opening file: %s" %fil
fw = FixedWidth(META_CONFIG_MON)
# determine how many years we will read
f = open(fil, 'rb')
header = f.readline()
all_years = [int(line[0:12].strip()) for line in f]
# read in observations
f = open(fil, 'rb')
header = f.readline()
meta = fw._string_to_dict(header)
nlin = (max(all_years) - min(all_years) + 1)*12
charOut = np.empty((nlin,7),dtype=object)
lat,lon = fmtll(meta['lat'],meta['lon'])
i = 0
nmiss = 0
_sum = 0.
this_mon = 1
cnt = 0
for ii,line in enumerate(f):
line = line.split()
mon = int(line[1])
if mon == this_mon:
year = line[0]
if line[3] == '9999' or meta['datum'] == 'X':
nmiss += 1
else:
_sum = _sum + float(line[3])
cnt += 1
else:
# The monthly values are calculated from the daily data with a
# simple average of all the daily values in a month. If seven or
# fewer values are missing, the monthly value is calculated.
if (nmiss <= 7):
avg = _sum / float(cnt)
else:
avg = -999
charOut[i,:] = [meta['number']+meta['version'],meta['name'],"{0:.2f}".format(lat),"{0:.2f}".format(lon), \
year,str(this_mon).zfill(2),str(int(avg))]
nmiss = 0
_sum = 0.
cnt = 0
this_mon = mon
i += 1
if (nmiss <= 7):
avg = _sum / float(cnt)
else:
avg = -999
charOut[i,:] = [meta['number']+meta['version'],meta['name'],"{0:.2f}".format(lat),"{0:.2f}".format(lon), \
year,str(this_mon).zfill(2),str(int(avg))]
return charOut,meta