def __init__(self, filename, mode):
if mode == 'w':
self.FILE = pycdf.CDF(
filename,
pycdf.NC.WRITE | pycdf.NC.CREATE | pycdf.NC.TRUNC)
if mode == 'r':
self.FILE = pycdf.CDF(filename, pycdf.NC.NOWRITE)
if mode == 'a':
self.FILE = pycdf.CDF(filename, pycdf.NC.WRITE)
self.FILE.automode()
def __init__(self,
filename,
perm='r',
interface=Interface,
version=3,
ncdump=False):
if interface != 'netcdf4': version = 3
if perm == 't': # trunc
if os.path.isfile(filename): os.remove(filename)
perm = 'w'
if interface == 'pycdf':
if perm == 'w':
perm = pnc.NC.WRITE | pnc.NC.CREATE
elif perm == 'a':
perm = pnc.NC.WRITE | pnc.NC.CREATE
else:
perm = pnc.NC.NOWRITE
nc = pnc.CDF(filename, perm)
nc.automode()
elif interface == 'scientific':
nc = pnc.NetCDFFile(filename, perm)
elif interface == 'netcdf4':
if perm == 'w' and os.path.isfile(filename): perm = 'a'
if not isinstance(version, basestring):
format = 'NETCDF' + str(version)
if format == 'NETCDF3': format = 'NETCDF3_CLASSIC'
else: format = version
if not isinstance(filename, basestring) or filename.find(
'*') != -1 or filename.find('?') != -1:
nc = pnc.MFDataset(filename)
else:
if os.path.isfile(filename):
nc = pnc.Dataset(filename, perm)
else:
nc = pnc.Dataset(filename, perm, format=format)
self.perm = perm
# root info:
info = {}
info['interface'] = interface
info['filename'] = filename
info['version'] = version
if ncdump:
from ncdump import ncdump_info
info['ncdump_info'] = ncdump_info(filename)
else:
info['ncdump_info'] = False
# init group:
Pyncgroup.__init__(self, nc, info=info)
def add_landmask(self):
g = pycdf.CDF(self.datadir + '/scb_grid.nc')
self.landmask = g.var('mask_rho')[:]
def main(argv):
sUsage = "%%prog [options] DATA_DIRECTORY BEGIN END"
sDesc = """
Reads Themis spectral density auto-correlation values from archive CDFs.
Format is similar to the Cluster Active Archive, see document: CAA-EST-UG-002
for details.
"""
psr = optparse.OptionParser(
usage=sUsage, description=sDesc, prog=bname(argv[0])
)
psr.add_option('-l', "--log-level", dest="sLevel", metavar="LOG_LEVEL",
help="Logging level one of [critical, error, warning, "+\
"info, debug]. The default is info.", type="string",
action="store", default="info")
(opts, lArgs) = psr.parse_args(argv[1:])
log = setupLogger(opts.sLevel)
log = logging.getLogger('')
if len(lArgs) < 1:
return serverErr(log, "Misconfigured DSDF, data directory is missing")
sRoot = lArgs[0]
if len(lArgs) < 3:
return queryErr(log, "Start and or Stop time is missing")
try:
dtBeg = das2.DasTime(lArgs[1])
except:
return queryErr(log, "Couldn't parse time value '%s'"%lArgs[1])
try:
dtEnd = das2.DasTime(lArgs[2])
except:
return queryErr(log, "Couldn't parse time value '%s'"%lArgs[2])
# Take all the rest of the arguments and glop them together in a single
# string. That way running the reader from the command line feels the
# same as running it from Autoplot
sParams = ''
if len(lArgs) > 3: sParams = ' '.join(lArgs[3:])
# pull out the polar style output, i.e: Magnitude and Phase Angle
bPolar = True
if sParams.find('complex') != -1:
sParams = sParams.replace('complex','').strip()
bPolar = False
# Default to printing all the autocorrelations
sComp = 'BxBx ByBy BzBz ExEx EyEy EzEz'
if len(sParams) > 0: sComp = sParams
lComp = sComp.split()
lComp.sort()
# Look in directory tree for files that match. We sort the file names
# under the assumption that sort order = numerical time order, but that
# may not be true for some file types
lDir = os.listdir(sRoot)
lDir.sort()
nSent = 0
bSentHdr = False
for sF in lDir:
if not sF.endswith('.cdf'): continue # only want CDFs
if not sF.startswith('tha_l3_sm'): continue # Only want L3 SM
# Make ISO-8601 strings
sBeg = "%s-%s-%sT%s:%s:%s"%(
sF[10:14], sF[14:16], sF[16:18], sF[19:21], sF[21:23], sF[23:25]
)
sEnd = "%s-%s-%sT%s:%s:%s"%(
sF[26:30], sF[30:32], sF[32:34], sF[35:37], sF[37:39], sF[39:41]
)
sPath = pjoin(sRoot, sF)
try:
dtFileBeg = das2.DasTime(sBeg)
dtFileEnd = das2.DasTime(sEnd)
# Since the themis files truncate the seconds field, round up by
# one second for the file end time...
dtFileEnd += 1.0
except ValueError as e:
log.waring("Unknown file %s in data area"%sPath)
continue
# If overlaps with desired range, include it in the output, send header
# if haven't done so
if (dtFileBeg < dtEnd) and (dtFileEnd > dtBeg):
log.info("Reading %s"%sPath)
cdf = pycdf.CDF(sPath)
# Assmue all the files are similar enough that an informational
# header can be created from the first one that fits the range
if not bSentHdr:
lIgnore = ['TIME_MAX','TIME_MIN', 'TIME_resolution']
dExtra = {
'title':getVespaTitle(cdf, 'THEMIS', lComp),
'Datum:xTagWidth':'0.5 s' # Max interp width for Autoplot
}
cdfToDas22Hdr(cdf, lIgnore, dExtra)
bSentHdr = True
nSent += sendDataPackets(cdf, dtBeg, dtEnd, lComp, bPolar)
if nSent == 0:
if not bSentHdr: writeHdrPkt(0, '<stream version="2.2" />\n')
sFmt = '<exception type="NoDataInInterval" message="%s" />\n'
sOut = sFmt%("No data in interval %s to %s UTC"%(str(dtBeg), str(dtEnd)))
writeHdrPkt('xx', sOut)
return 0
def display_cdf(filename, desc):
cdf = pycdf.CDF(filename)
print("R%04d %s" %(0, cdf[desc][0]))
print("R%04d %s" %(len(cdf[desc]), cdf[desc][-1]))