def step4_load_sst_monthlies(latest_year, latest_month):
files = step4_find_monthlies(latest_year, latest_month)
if not files:
print "No more recent sea-surface data files.\n"
return None
first_year = files[0][0][0]
last_year = files[-1][0][0]
n_years = last_year - first_year + 1
# Read in the SST data for recent years
sst = make_3d_array(360, 180, 12 * n_years)
dates = []
for (date, file) in files:
dates.append(date)
(year, month) = date
f = open_or_uncompress(file)
print "reading", file
f = fort.File(f, bos = ">")
f.readline() # discard first record
data = f.readline()
f.close()
month = 12 * (year - first_year) + month - 1
p = 0
for lat in range(180):
for long in range(360):
v, = struct.unpack(">f", data[p:p+4])
p += 4
sst[long][lat][month] = v
return sst, dates
def zone_series(f):
"""Convert the Fortran data file *f* into a sequence of monthly
anomalies for the zones. The file must be a ZON.* file generated by
GISTEMP Step 5. The return value is an iterable over a sequence of
pairs ((zone, year, month), datum) with *month* running from 0 to
11; the datum is a float; when the datum is invalid, the
corresponding pair is absent from the stream.
"""
bos = '>' # Byte order and size (for struct.{un,}pack).
f = fort.File(f, bos)
# The first record is a header
l = f.readline()
info = struct.unpack('%s8i' % bos, l[:8 * 4])
nmonths = info[3]
first_year = info[5]
missing = info[6]
descriptor = bos + '%df80s' % (nmonths * 2)
for z, r in enumerate(f):
data = struct.unpack(descriptor, r)
for i, v in enumerate(data[:nmonths]):
if v != missing:
yield ((z, first_year + i // 12, i % 12), v)
def __init__(self, rawfile, bos='>'):
self.bos = bos
self.f = fort.File(rawfile, bos=self.bos)
rec = self.f.readline()
(self.mo1, kq, mavg, monm, monm4, yrbeg, missing_flag,
precipitation_flag,
title) = struct.unpack(self.bos + '8i80s', rec)
self.meta = code.giss_data.SubboxMetaData(self.mo1, kq, mavg, monm,
monm4, yrbeg, missing_flag, precipitation_flag, title)
assert self.meta.mavg == 6, "Only monthly averages supported"
def __init__(self, rawfile, bos='>'):
self.bos = bos
self.f = fort.File(rawfile, bos=self.bos)
rec = self.f.readline()
(self.min_month, kq, mavg, monm, monm4, yrbeg, missing_flag,
precipitation_flag, self.max_month,
title) = struct.unpack(self.bos + '9i80s', rec)
self.meta = code.giss_data.StationMetaData(self.min_month, kq, mavg,
monm, monm4, yrbeg, missing_flag, precipitation_flag,
self.max_month, title)
def totext(file, output=sys.stdout, log=sys.stderr, metaonly=False, bos='>'):
"""Convert zonal monthly averages to text format.
If metaonly is True then only the zonal metadata is output, the
time series are not.
"""
# :todo: move into common module
from zonav import swaw
# The width of a standard word according to Python's struct module...
w = len(struct.pack('=I', 0))
f = fort.File(file, bos=bos)
r = f.readline()
# Number of words in header, preceding title.
n = 8
info = struct.unpack(bos + ('%di' % n), r[:n * w])
output.write(repr(info))
output.write('\n%s\n' % r[n * w:n * w + 80])
output.write('%s\n' % r[n * w + 80:])
# m: time frames per year
if info[2] == 6:
m = 12
else:
m = 4
first_year = info[5]
months = info[3]
years = months / m
last_year = first_year + years - 1
# Each line contains N ar values and N weight (area?) values,
# followed by an 80-character title string.
descriptor = bos + '%df80s' % (months * 2)
for i in range(jzm):
r = f.readline()
if r is None:
raise Error('Unexpected end of file.')
data = struct.unpack(descriptor, r)
output.write(swaw(data[-1]) + '\n')
if metaonly:
continue
for set in range(2):
for year in range(first_year, last_year + 1):
offset = (year - first_year) * m + (months * set)
output.write('%s[%4d]: %s\n' %
(['AR', 'WT'][set], year, ' '.join(
map(repr, data[offset:offset + m]))))
def step4_load_clim():
f = open_or_uncompress("input/oisstv2_mod4.clim")
f = fort.File(f, bos='>')
data = f.readline()
f.close()
clim_title = data[:80]
clim = make_3d_array(360, 180, 12)
p = 0
for month in range(12):
for lat in range(180):
for long in range(360):
v, = struct.unpack(">f", data[p+80:p+84])
p += 4
clim[long][lat][month] = v
return clim
def step5_bx_output(data):
bos = '>'
box = open('result/BX.Ts.ho2.GHCN.CL.PA.1200', 'wb')
boxf = fort.File(box, bos=bos)
(info, title) = data.next()
boxf.writeline(struct.pack('%s8i' % bos, *info) + title)
yield (info, title)
for record in data:
(avgr, wtr, ngood, box) = record
n = len(avgr)
fmt = '%s%df' % (bos, n)
boxf.writeline(struct.pack(fmt, *avgr) +
struct.pack(fmt, *wtr) +
struct.pack('%si' % bos, ngood) +
struct.pack('%s4i' % bos, *box))
yield record
print "Step5: Closing box file"
boxf.close()
def totext(file, output=sys.stdout):
"""The file argument should be a binary file opened for reading. It
is treated as a Fortran binary file and converted to a text format,
emitted on the file object output. Each (binary) record is treated
as a sequence of words (words being "standard-sized ints" in the native
byte-ordering), followed by a possible remainder sequence of bytes
(where the record length is not a multiple of a word). The output
format is one line per record, with each word being output as a
fixed width hexadecimal number, and each trailing byte being output
as a 2-digit hexadecimal number. Spaces separate. A "standard-size
int" is interpreted the same way that struct.unpack('=I', x)
interprets it.
"""
# Compute the width of a standard word according to Python's struct
# module...
w = len(struct.pack('=I', 0))
# and a suitable string format.
# http://www.python.org/doc/2.3.5/lib/typesseq-strings.html
# The string format is of the form '%08x' but the value of 8 may be
# replaced.
fmt = '%%0%dx' % (2*w)
f = fort.File(file)
# Iterate over all the records
for r in f:
# We unpack as much as the record as we can as a sequence of
# binary words (typically 32-bits each); then the rest as a
# sequence of bytes.
# Number of words
n = len(r) // w
sep = ''
for i in struct.unpack('%dI' % n, r[:n*w]):
output.write(sep + (fmt % i))
sep = ' '
# Remainder of record, as bytes
for c in r[n*w:]:
output.write(sep + ('%02x' % ord(c)))
sep = ' '
output.write('\n')
def box_series(f):
"""Convert the Fortran data file *f* into a sequence of monthly
anomalies for the geographical boxes. The file must be a BX.* file
generated by GISTEMP step 5. The return value is an iterable over a
sequence of pairs ((box, year, month), datum) with month running
from 0 to 11; the datum is an integer; when the datum is invalid,
the corresponding pair is absent from the stream.
"""
bos = '>' # Byte order and size (for struct.{un,}pack).
f = fort.File(f, bos)
# The first record of the file is a header (see step5.SBBXtoBX).
l = f.readline()
info = struct.unpack('%s8i' % bos, l[:8 * 4])
nmonths = info[3] # Number of months in data series.
nfields = info[4] # Number of fields in each record.
year = info[5] # First year in the series.
missing = info[6] # Value for a missing datum.
assert nfields == nmonths * 2 + 5
# Each successive record contains a temperature anomaly series for
# one box: first, 'nmonths' fields giving the anomalies for each
# month; then 'nmonths' fields giving the weights for that box for
# each month, then the number of good months in the series (?), then
# four values describing the box (see eqarea.grid).
box = 0
while 1:
l = f.readline()
if l is None:
return
assert len(l) == nfields * 4
data = struct.unpack('%s%df' % (bos, nmonths), l[:4 * nmonths])
for i in xrange(nmonths):
if data[i] != missing:
yield (((box, year + i // 12, i % 12), data[i]))
box += 1
def totext(inp,
output=sys.stdout,
log=sys.stderr,
metaonly=False,
bos='>',
format='v3'):
"""
Convert monthly averages to text format; *inp* is the input file
and should be either a binary zone file (ZON.*) or a binary box file
(BX.*).
If metaonly is True then only the zonal metadata is output, the
time series are not.
"""
# The width of a standard word according to Python's struct module.
w = len(struct.pack('=I', 0))
f = fort.File(inp, bos=bos)
r = f.readline()
# Number of words in header, preceding title.
n = 8
info = struct.unpack(bos + ('%di' % n), r[:n * w])
title = r[n * w:]
if 'zones' in title.lower():
content = 'zones'
else:
content = 'boxes'
if metaonly or 'v3' != format:
output.write(repr(info))
output.write('\n' + title + '\n')
if metaonly:
return
if 'v3' == format:
ghcnm_out = gio.GHCNV3Writer(file=output, scale=0.01)
# m: time frames per year
if info[2] == 6:
m = 12
else:
m = 4
first_year = info[5]
months = info[3]
years = months / m
last_year = first_year + years - 1
# Each line contains N ar values and N weight (area?) values,
# followed by...
# - (for zones) an 80-character title string.
# - (for boxes) 5 words.
rest = dict(zones=80, boxes=5 * w)[content]
descriptor = bos + '%df%ds' % (months * 2, rest)
# Number of records following header.
N = dict(zones=16, boxes=80)[content]
i = None
for i, r in enumerate(f):
data = struct.unpack(descriptor, r)
suffix = data[-1]
if format == 'v3':
if 'zones' == content:
title = id11fromzone(suffix)
else:
title = id11frombox(suffix, bos=bos)
else:
title = suffix
output.write(title + '\n')
for idx in range(2):
if 'v3' == format and idx > 0:
# Only output temps, not weights. :todo: fix this.
continue
for year in range(first_year, last_year + 1):
offset = (year - first_year) * m + (months * idx)
temps = data[offset:offset + m]
if 'v3' == format:
assert 12 == m
element = ['TAVG', 'WGHT'][idx]
ghcnm_out.writeyear(title, element, year, temps)
else:
output.write(
'%s[%4d]: %s\n' %
(['AR', 'WT'][idx], year, ' '.join(map(repr, temps))))
if i is None:
raise Error('No records found in file %r.' % inp.name)
if i != N - 1:
way = "many" if i >= N else "few"
raise Error('Too %s records. Expected %d, found %d.' % (way, N, i + 1))
def totext(file, output=sys.stdout, error=sys.stderr, metaflag=False):
"""The file argument should be a binary file opened for reading. It
is treated as a Fortran binary file and converted to a text format,
emitted on the file object output.
"""
# Compute the width of a standard word according to Python's struct
# module...
w = len(struct.pack('=I', 0))
# and a suitable string format.
# http://www.python.org/doc/2.3.5/lib/typesseq-strings.html
# The string format is of the form '%08x' but the value of 8 may be
# replaced.
fmt = '%%0%dx' % (2*w)
f = fort.File(file)
r = f.readline()
# First record contains various INFO items.
# When referring to comments in to.SBBXgrid.f recall that Fortran
# arrays are typically indexed from 1 onwards; Python from 0
# onwards. Therefore INFO(2) corresponds to a[0]
a = struct.unpack('9i', r[:9*w])
mfirst = a[0]
mlast = a[8]
kq = a[1]
mavg = a[2]
monm = a[3]
recsize = a[4]
yrbeg = a[5]
bad = a[6]
trace = a[7]
if metaflag:
output.write('KQ=%d MAVG=%d MONM=%d YRBEG=%d BAD=%d TRACE=%d\n' %
(kq, mavg, monm, yrbeg, bad, trace))
# Length of record trail, the non-variable part, in bytes.
ltrail = 15*w
# Iterate over remaining records
for r in f:
trail = r[-ltrail:]
lat,lon,id,height = struct.unpack('4i', trail[:4*w])
lat *= 0.1
lon *= 0.1
if len(r[:-ltrail]) != w*(mlast-mfirst+1):
error.write(('Station ID %09d has suspect record length.' +
'mfirst=%s mlast=%d record-length=%d\n') %
(id, mfirst, mlast, len(r)))
name = trail[4*w:-2*w]
# Some metadata is stored in the name field, *sigh*
meta = name[-6:]
name = name[:-6]
# 3 digit country code
cc = meta[3:6]
meta = meta[0:3]
# Prepend country code to station ID. Note: id becomes a string.
id = '%s%09d' % (cc, id)
# Replace any spaces in meta with '*', mostly to preserve the
# "words separated by spaces" format. Note that all these
# replacements are where (non US) stations do not have
# USHCN-brightness indexes.
meta = meta.replace(' ', '*')
# It just so happens that underscore does not appear in any of
# the "name" fields, so we use that instead of space. That
# preserves the "words separated by spaces" format.
name = name.replace(' ', '_')
# It's tidier if we return the trailing underscores back into
# spaces.
m = re.search('_*$', name)
name = name[:m.start()] + ' '*(m.end() - m.start())
if metaflag:
output.write('ID %s %s %s %s M%04d\n' %
(id, name, meta, iso6709(lat, lon, height), mfirst))
else:
n = len(r[:-ltrail])//w
data = struct.unpack('%di' % n, r[:-ltrail])
# Convert to 0 == January indexing:
mfirst -= 1
assert mfirst >= 0
year = mfirst // 12
year += yrbeg
# Pad data at beginning...
m = mfirst % 12
data = (bad,)*m + data
# ... and at end.
m = (-len(data)) % 12
data = data + (bad,)*m
assert 0 == len(data) % 12
def changebad(datum):
"""Convert to GHCN v2.mean BAD format."""
if datum == bad:
return -9999
return datum
data = map(changebad, data)
for y,yeardata in enumerate(data[i:i+12]
for i in range(0,len(data),12)):
output.write('%s%d' % (id, year + y))
output.write(('%5d'*12 + '\n') % tuple(yeardata))
mfirst, mlast = struct.unpack('2I', trail[-2*w:])
def cmp(a, b, dt=1e-4, dd=0.5, output=sys.stdout, error=sys.stderr):
"""Compare two files."""
# Compute the width of a standard word according to Python's struct
# module...
w = len(struct.pack('=I', 0))
# and a suitable string format.
# http://www.python.org/doc/2.3.5/lib/typesseq-strings.html
# The string format is of the form '%08x' but the value of 8 may be
# replaced.
fmt = '%%0%dx' % (2 * w)
# Width of a float
wf = len(struct.pack('f', 0.0))
a = fort.File(a)
b = fort.File(b)
ra = a.readline()
rb = b.readline()
rn = 0
# Number of words in header, preceding title.
n = 8
if ra[:n * w] != rb[:n * w]:
error.write('headers differ:\n' +
str(struct.unpack('%di' % n, ra[:n * w])) +
str(struct.unpack('%di' % n, rb[:n * w])) + '\n')
sys.exit(4)
dmax = -1
dmaxrn = None
tmax = -1
tmaxrni = ()
while True:
ra = a.readline()
rb = b.readline()
rn += 1
if ra == None and rb == None:
break
if ra == None or rb == None:
error.write('files differ in size')
sys.exit(4)
if len(ra) != len(rb):
error.write('Record %d is different size' % rn)
break
traila = ra[-7 * w:]
trailb = rb[-7 * w:]
if traila[:4 * w] != trailb[:4 * w]:
error.write('Record %d is for different boxes' % rn)
break
counta = struct.unpack('2I', traila[4 * w:6 * w])
countb = struct.unpack('2I', trailb[4 * w:6 * w])
if counta[0] != countb[0]:
output.write('Record %d NSTNS: %d %d\n' %
(rn, counta[0], countb[0]))
if counta[1] != countb[1]:
output.write('Record %d NSTMNS: %d %d\n' %
(rn, counta[1], countb[1]))
da = struct.unpack('f', traila[6 * w:])[0]
db = struct.unpack('f', trailb[6 * w:])[0]
if abs(da - db) >= dd:
output.write('Record %d D: %s %s\n' % (rn, repr(da), repr(db)))
if abs(da - db) >= dmax:
dmax = abs(da - db)
dmaxrn = rn
ra = ra[:-7 * w]
rb = rb[:-7 * w]
n = len(ra) // wf # number of time series entries
ta = struct.unpack('%df' % n, ra)
tb = struct.unpack('%df' % n, rb)
for i in range(n):
d = abs(ta[i] - tb[i])
if d >= dt:
output.write('Record %d data %i: %s %s diff: %s\n' %
(rn, i, repr(ta[i]), repr(tb[i]), repr(d)))
if d >= tmax:
tmax = d
tmaxrni = (rn, i)
output.write('Maximum difference in d (record %d): %s\n' %
(dmaxrn, repr(dmax)))
output.write('Maximum difference in t (record %d item %d): %s\n' %
(tmaxrni[0], tmaxrni[1], repr(tmax)))
def totext(file,
output=sys.stdout,
log=sys.stderr,
metaonly=False,
bos='>',
trimmed='fromfile'):
"""Convert binary gridded subbox file to text format.
If metaonly is True then only the subbox metadata is output, the
time series are not.
`trimmed` determines whether the input file is trimmed; it can be
one of ``True`` (file is trimmed), ``False`` (file is not trimmed),
or ``'fromfile'`` (will examine file to determine if it is trimmed
or not).
"""
assert trimmed in [True, False, 'fromfile']
# Compute the width of a standard word according to Python's struct
# module...
w = len(struct.pack('=I', 0))
# Width of a float
wf = len(struct.pack('f', 0.0))
# and a suitable string format.
# http://www.python.org/doc/2.3.5/lib/typesseq-strings.html
# The string format is of the form '%08x' but the value of 8 may be
# replaced.
fmt = '%%0%dx' % (2 * w)
f = fort.File(file, bos=bos)
r = f.readline()
# Number of words in header, preceding title.
n = 8
info = struct.unpack(bos + ('%di' % n), r[:n * w])
print info
print r[n * w:]
yrbeg = info[5]
mavg = info[2]
km = 1
if mavg == 6:
km = 12
if trimmed == 'fromfile':
trimmed = info[0] != 1
print >> log, "Determined that trimmed=%s from file." % trimmed
for r in f:
if trimmed:
meta = r[1 * w:8 * w]
r = r[8 * w:]
else:
meta = r[-7 * w:]
r = r[:-7 * w]
box = struct.unpack(bos + '4i', meta[:4 * w])
box = tuple(map(lambda x: x / 100.0, box))
nstns, nstmns = struct.unpack(bos + '2I', meta[4 * w:6 * w])
d = struct.unpack(bos + 'f', meta[6 * w:])[0]
loc = '%+06.2f%+06.2f%+07.2f%+07.2f' % box
n = len(r) // wf # number of time series entries
output.write('%s META %6d %3d %6d %f\n' % (loc, n, nstns, nstmns, d))
if metaonly:
continue
t = struct.unpack(bos + ('%df' % n), r)
# 12 entries per output line, which is usually one year's worth,
# (but see km).
p = 12
for i in range(len(t) // p):
output.write('%s %d' % (loc, (yrbeg + i * p // km)))
for j in range(p):
k = i * p + j
output.write(' %s' % repr(t[k]))
output.write('\n')
def step5_output(data):
(info, data, wt, ann, monmin, title) = data
XBAD = 9999
iy1tab = 1880
zone_titles = step5_zone_titles()
titl2 = ' zones: 90->64.2->44.4->23.6->0->-23.6->-44.4->-64.2->-90 '
iyrbeg = info[5]
jzm = len(ann)
iyrs = len(ann[0])
monm = iyrs * 12
out = ['ZonAnn', 'GLB', 'NH', 'SH']
out = [open('result/'+bit+'.Ts.ho2.GHCN.CL.PA.txt', 'w')
for bit in out]
zono = open('result/ZON.Ts.ho2.GHCN.CL.PA.1200', 'wb')
bos = '>'
zono = fort.File(zono, bos)
# Create and write out the header record of the output files.
print >> out[0], ' Annual Temperature Anomalies (.01 C) - ' + title[28:80]
for f in out[1:]:
print >> f, title
# iord literal borrowed exactly from Fortran...
iord = [14,12,13, 9,10,11, 1,2,3,4,5,6,7,8]
# ... and then adjusted for Python index convention.
iord = map(lambda x: x-1, iord)
# Display the annual means.
def annasstr(z):
"""Helper function that returns the annual anomaly for zone *z*
as a string representation of an integer (the integer is the
anomaly scaled by 100 to convert to centikelvin).
The returned value is a string that is 5 characters long. If
the integer will not fit into a 5 character string, '*****' is
returned (this emulates the Fortran convention of formatting
999900 (which is the XBAD value in centikelvin) as a '*****'.
The year, *iy*, is lexically captured which is a bit horrible.
"""
x = int(math.floor(100*ann[z][iy] + 0.5))
x = '%5d' % x
if len(x) > 5:
return '*****'
return x
iyrsp = iyrs
# Check (and skip) incomplete year.
if data[-1][-1][-1] > 8000:
iyrsp -= 1
banner = """
24N 24S 90S 64N 44N 24N EQU 24S 44S 64S 90S
Year Glob NHem SHem -90N -24N -24S -90N -64N -44N -24N -EQU -24S -44S -64S Year
""".strip('\n')
for iy in range(iy1tab - iyrbeg, iyrsp):
if (iy+iyrbeg >= iy1tab+5 and ((iy+iyrbeg) % 20 == 1) or
iy == iy1tab - iyrbeg):
print >> out[0]
print >> out[0], banner
iyr = iyrbeg+iy
print >> out[0], ('%4d' + ' %s'*3 + ' ' + ' %s'*3 +
' ' + ' %s'*8 + '%5d') % tuple([iyr] +
[annasstr(iord[zone]) for zone in range(jzm)] + [iyr])
# The trailing banner is just like the repeated banner, except that
# "Year Glob NHem SHem" appears on on the first line, not the
# second line (and the same for the "Year" that appears at the end
# of the line). *sigh*.
banner = banner.split('\n')
banner[0] = banner[1][:24] + banner[0][24:] + ' Year'
banner[1] = ' '*24 + banner[1][24:-5]
banner = '\n'.join(banner)
print >> out[0], banner
print >> out[0]
tit = [' GLOBAL','N.HEMISPH.','S.HEMISPH.']
# Shift the remaining 3 output files so that the indexing works out.
out = out[1:]
banner = 'Year Jan Feb Mar Apr May Jun Jul Aug' + \
' Sep Oct Nov Dec J-D D-N DJF MAM JJA SON Year'
# All the "WRITE(96+J" stuff in the Fortran is replaced with this
# enumeration into the *out* array (an array of file descriptors).
for j,outf in enumerate(out):
print >> outf, (tit[j] + ' Temperature Anomalies' +
' in .01 C base period: 1951-1980')
for iy in range(iy1tab-iyrbeg, iyrs):
iout = [100*XBAD]*18
if (iy+iyrbeg >= iy1tab+5 and ((iy+iyrbeg) % 20 == 1) or
iy == iy1tab - iyrbeg):
print >> outf
print >> outf, banner
# *data* for this zone, avoids some duplication of code.
zdata = data[iord[j]]
# :todo: Would probably be better to have a little 4-long
# seasonal array to do the computation in.
awin = 9999
if iy > 0:
awin = zdata[iy-1][11] + zdata[iy][0] + zdata[iy][1]
aspr = sum(zdata[iy][2:5])
asmr = sum(zdata[iy][5:8])
afl = sum(zdata[iy][8:11])
if awin < 8000:
iout[14] = int(round(100.0*awin/3))
if aspr < 8000:
iout[15] = int(round(100.0*aspr/3))
if asmr < 8000:
iout[16] = int(round(100.0*asmr/3))
if afl < 8000:
iout[17] = int(round(100.0*afl/3))
ann2=awin+aspr+asmr+afl
if ann2 < 8000:
iout[13] = int(round(100.0*ann2/12))
ann1=ann[iord[j]][iy]
if iy == iyrs-1 and zdata[iy][-1] > 8000:
ann1 = 9999
if ann1 < 8000:
iout[12] = int(round(100.0*ann[iord[j]][iy]))
for m in range(12):
iout[m] = int(round(100.0*zdata[iy][m]))
iyr = iyrbeg+iy
# Convert each of *iout* to a string, storing the results in
# *sout*.
sout = [None]*len(iout)
for i,x in enumerate(iout):
# All the elements of iout are formatted to width 5,
# except for element 13 (14 in the Fortran code), which
# is length 4.
if i == 13:
x = '%4d' % x
if len(x) > 4:
x = '****'
else:
x = '%5d' % x
if len(x) > 5:
x = '*****'
sout[i] = x
print >> outf, (
'%4d ' + '%s'*12 + ' %s%s ' + '%s'*4 + '%6d') % tuple(
[iyr] + sout + [iyr])
print >> outf, banner
# Save monthly means on disk.
zono.writeline(struct.pack(bos + '8i', *info) +
title + titl2)
fmt_mon = bos + '%df' % monm
for jz in range(jzm):
zono.writeline(struct.pack(fmt_mon, *itertools.chain(*data[jz])) +
struct.pack(fmt_mon, *itertools.chain(*wt[jz])) +
zone_titles[jz])
return "Step 5 Completed"
def __init__(self, rawfile, bos='>'):
self.bos = bos
self.f = fort.File(rawfile, bos=self.bos)
self.meta = None
self.buf_record = None
def __init__(self, rawfile, bos='>', trimmed=True):
self.trimmed = trimmed
self.bos = bos
self.f = fort.File(rawfile, bos=self.bos)
self.meta = None
self.buf_record = None