def __iadd__(self, other):
t = [
self.t[0], self.t[1], self.t[2], self.t[4], self.t[5],
self.t[6] + other
]
self.t = list(_das2.tnorm(t[0], t[1], t[2], t[3], t[4], t[5]))
return self
def ceil(self, nSecs):
"""Find the nearest time, evenly divisible by nSec that is greater
than the current time value."""
if nSecs - int(nSecs) != 0:
raise ValueError("%s is not an integer" % nSecs)
nSecs = int(nSecs)
if nSecs < 1:
raise ValueError("%s is < 1" % nSecs)
elif nSecs == 1:
rFrac = self.t[6] - int(self.t[6])
if rFrac > 0.0:
self.t[6] = int(self.t[6]) + 1
elif nSecs < 86400:
nSecOfDay = self.t[4] * 60 * 60 + self.t[5] * 60 + int(
M.ceil(self.t[6]))
nFloor = (nSecOfDay // nSecs) * nSecs
if nSecOfDay - nFloor == 0:
nCeil = nFloor
else:
nCeil = nFloor + nSecs
self.t[4] = nCeil // (60 * 60)
nRem = nCeil - (self.t[4] * 60 * 60)
self.t[5] = nRem // 60
nRem = nRem - (self.t[5] * 60)
self.t[6] = float(nRem)
elif nSecs == 86400:
if (self.t[4] > 0) or (self.t[5] > 0) or (self.t[6] > 0.0):
self.t[2] += 1
self.t[4] = 0
self.t[5] = 0
self.t[6] = 0.0
else:
raise ValueError(
"Can't yet provide floor values for times > 1 day")
self.t = list(
_das2.tnorm(self.t[0], self.t[1], self.t[2], self.t[4], self.t[5],
self.t[6]))
def adjust(self, nYear, nMonth=0, nDom=0, nHour=0, nMin=0, fSec=0.0):
"""Adjust one or more of the field, either positive or negative,
calls self.norm internally"""
if nYear == 0 and nMonth == 0 and nDom == 0 and nHour == 0 and \
nMin == 0 and fSec == 0.0:
return
t = [
self.t[0] + nYear, self.t[1] + nMonth, self.t[2] + nDom,
self.t[4] + nHour, self.t[5] + nMin, self.t[6] + fSec
]
self.t = list(_das2.tnorm(t[0], t[1], t[2], t[3], t[4], t[5]))
def floor(self, nSecs):
'''Find the nearest time, evenly divisable by nSec, that is
less that the current time value.
'''
if nSecs - int(nSecs) != 0:
raise ValueError("%s is not an integer" % nSecs)
nSecs = int(nSecs)
if nSecs < 1:
raise ValueError("%s is < 1" % nSecs)
elif nSecs == 1:
self.t[6] = int(self.t[6])
elif nSecs < 86400:
nFloor = self.t[4] * 60 * 60 + self.t[5] * 60 + int(self.t[6])
nFloor = (nFloor // nSecs) * nSecs
self.t[4] = nFloor // (60 * 60)
nRem = nFloor - (self.t[4] * 60 * 60)
self.t[5] = nRem // 60
self.t[6] = float(nRem - (self.t[5] * 60))
elif nSec == 86400:
self.t[4] = 0
self.t[5] = 0
self.t[6] = 0.0
else:
raise ValueError(
"Can't yet provide floor values for times > 1 day")
self.t = list(
_das2.tnorm(self.t[0], self.t[1], self.t[2], self.t[4], self.t[5],
self.t[6]))
def __init__(self, nYear=0, nMonth=0, nDom=0, nHour=0, nMin=0, fSec=0.0):
"""Initalize from field values
Note: If nYear is a string, and all other values are zero, then
parsetime is called to generate the field values from the time
string.
"""
# Handle bytes to string conversion up front
if (sys.version_info[0] > 2) and isinstance(nYear, bytes):
nYear = nYear.decode('utf-8')
# Initialize from any type of string
if isinstance(nYear, basestring):
try:
tTmp = _das2.parsetime(nYear)
(nYear, nMonth, nDom, nDoy, nHour, nMin, fSec) = tTmp
except ValueError as e:
raise ValueError(
"String '%s' was not parseable as a datetime" % nYear)
# Initialize from a python datetime
elif isinstance(nYear, datetime.datetime):
pdt = nYear
nYear = pdt.year
nMonth = pdt.month
nDom = pdt.day
nHour = pdt.hour
nMin = pdt.minute
fSec = float(pdt.second) + (pdt.microsecond / 1000000.0)
# initialize form a numpy datetime64
elif isinstance(nYear, numpy.datetime64):
# Numpy's decision to print local time is very irritating. Get epoch seconds
nEpoch = nYear.astype(int)
sType = nYear.dtype.str
sType = sType[sType.find('[') +
1:sType.find(']')] # Gives timestamp units
# datetime64 always uses the unix epoch, but at different units.
r1970 = nEpoch * g_dDt64Scale[sType]
tTmp = _das2.parse_epoch(r1970, "t1970")
(nYear, nMonth, nDom, nDoy, nHour, nMin, fSec) = tTmp
# Initialize float plus das2 epoch units
elif isinstance(nMonth, str):
tTmp = _das2.parse_epoch(nYear, nMonth)
(nYear, nMonth, nDom, nDoy, nHour, nMin, fSec) = tTmp
elif isinstance(nYear, DasTime):
# Just work as a copy constructor
nMonth = nYear.t[1]
nDom = nYear.t[2]
nHour = nYear.t[4]
nMin = nYear.t[5]
fSec = nYear.t[6]
nYear = nYear.t[0]
# Assume years less than 100 but greater than 57 are old 2 digit years
# that need to be incremented. I don't like this but what can
# you do when reading old data.
if isinstance(nYear, (tuple, list)):
self.t = [0, 0, 0, 0, 0, 0, 0.0]
for i in xrange(0, len(nYear)):
j = i
if i >= 3:
j = i + 1
self.t[j] = nYear[i]
if self.t[0] < 100 and self.t[0] > 57:
self.t[0] = self.t[0] + 1900
self.t = list(_das2.tnorm(t[0], t[1], t[2], t[4], t[5], t[6]))
else:
if nYear < 100 and nYear >= 57:
nYear += 1900
self.t = list(_das2.tnorm(nYear, nMonth, nDom, nHour, nMin, fSec))
if abs(self.t[0]) > 9999:
raise OverflowError("Year value is outside range +/- 9999")
def norm(self):
"""Normalize the time fields so that all contain legal values."""
tNew = _das2.tnorm(self.t[0], self.t[1], self.t[2], self.t[4],
self.t[5], self.t[6])
self.t = list(tNew)