def zeros(var, ref='mean', mean=None, getref=True, **kwargs):
"""Get the zeros of a tidal signal
:Returns: A :mod:`cdms2` variable of signs (-1,1) with a time axis
:Usage:
>>> tidal_zeros = zeros(sea_level,ref='demerliac')
>>> print tidal_zeros[0:1]
>>> print tidal_zeros[0:1].getTime().asComponentTime()
"""
# Get anomaly
ref = kwargs.pop('reference', ref)
vara, varref = _get_anomaly_(var, ref=ref, mean=mean)
taxis = vara.getTime()
vara = vara.filled()
longref = hasattr(varref, '__len__')
# Find indices
sign = N.sign(vara)
izeros = N.arange(len(vara) - 1).compress(sign[:-1] != sign[1:])
# Interpolate
units = taxis.units
times = taxis.getValue()
zeros = N.zeros((len(izeros), ))
if getref:
ret = MV2.zeros(len(zeros), id='zeros')
if not longref:
ret[:] = varref
for i, i0 in enumerate(izeros):
dv = vara[i0 + 1] - vara[i0]
zeros[i] = times[i0] * vara[i0 + 1] / dv - times[i0 +
1] * vara[i0] / dv
if getref and longref:
dt = times[i0 + 1] - times[i0]
ret[i] = var_ref[i0] * vara[i0 + 1] / dv - var_ref[
i0 + 1] * vara[i0] / dv
# Format
if not getref:
ret = MV2.array(sign[izeros], id='zeros')
ret.units = '1 up and -1 down'
else:
cp_atts(var, ret)
ret.long_name = 'Zeros'
zeros = create_time(zeros, units)
ret.setAxis(0, zeros)
return ret
def zeros(var, ref='mean',mean=None, getref=True, **kwargs):
"""Get the zeros of a tidal signal
:Returns: A :mod:`cdms2` variable of signs (-1,1) with a time axis
:Usage:
>>> tidal_zeros = zeros(sea_level,ref='demerliac')
>>> print tidal_zeros[0:1]
>>> print tidal_zeros[0:1].getTime().asComponentTime()
"""
# Get anomaly
ref = kwargs.pop('reference', ref)
vara, varref = _get_anomaly_(var, ref=ref,mean=mean)
taxis = vara.getTime()
vara = vara.filled()
longref = hasattr(varref, '__len__')
# Find indices
sign = N.sign(vara)
izeros = N.arange(len(vara)-1).compress(sign[:-1]!=sign[1:])
# Interpolate
units = taxis.units
times = taxis.getValue()
zeros = N.zeros((len(izeros), ))
if getref:
ret = MV2.zeros(len(zeros), id='zeros')
if not longref:
ret[:] = varref
for i, i0 in enumerate(izeros):
dv = vara[i0+1]-vara[i0]
zeros[i] = times[i0]*vara[i0+1]/dv - times[i0+1]*vara[i0]/dv
if getref and longref:
dt = times[i0+1]-times[i0]
ret[i] = var_ref[i0]*vara[i0+1]/dv - var_ref[i0+1]*vara[i0]/dv
# Format
if not getref:
ret = MV2.array(sign[izeros], id='zeros')
ret.units = '1 up and -1 down'
else:
cp_atts(var, ret)
ret.long_name = 'Zeros'
zeros = create_time(zeros, units)
ret.setAxis(0, zeros)
return ret
def load(self, restart_file=None, iterindex=None, nowtime=None):
"""Load the current instance from a netcdf file
:Params:
- **restart_file**, optional: Netcdf restart file.
- **iterindex**, optional: If given, the restart file is not loaded if
``iterindex`` is greater or equal to the file's ``iterindex`` attribute.
- **nowtime**, optional: If given, the restart file is not loaded if
``nowtime`` is greater or equal to the file's ``lasttime`` attribute.
"""
# File
if restart_file is None:
restart_file = self.restart_file
if restart_file is None:
restart_file = self.default_restart_file
self.restart_file = restart_file
f = cdms2.open(restart_file)
# Config
# - check status
if iterindex is not None:
self.iterindex = iterindex
if hasattr(self, 'iterindex') and f.iterindex<=self.iterindex:
return -1
if nowtime is not None:
self.lasttime = comptime(nowtime)
if (hasattr(self, 'lasttime') and f.withtime>0 and self.lasttime
and reltime(f.lasttime, 'hours since 2000').value <=
reltime(self.lasttime, 'hours since 2000').value):
return -1
# - what was initially asked and some more
for sname in self.all_stats + ('sum', 'sqr', 'prod', 'stats'):
for st in 'st':
if not hasattr(f, st+sname): continue
value = getattr(f, st+sname)
setattr(self, st+sname, bool(value))
# - current status
self.iterindex = int(f.iterindex)
self.nitems = int(f.nitems)
if f.withtime==-1:
self.withtime = None
else:
self.withtime = bool(f.withtime)
if f.withtime:
self.lasttime = cdtime.s2c(f.lasttime)
if N.isscalar(f.bin_edges):
self.bins = None
else:
self.bins = N.asarray(f.bin_edges)
self.nbins = self.bins.shape[0]-1
self._baxis = f.getAxis('hbin').clone()
if self.nitems==0: # Still no data
f.close()
return 0
# - already had some data
self.dual = bool(f.dual)
self.ns = int(f.ns)
self.nt = int(f.nt)
self._nts = f.nts.tolist()
self.tstats = bool(f.tstats)
self.sstats = bool(f.sstats)
if not self.withtime:
self._stimes = None
# Spatial statistics
if self.sstats:
# Time axes
if self.withtime:
self._stimes = tuple([[] for i in xrange(self.nitems)])
for i, tt in enumerate(self._stimes):
taxis = f.getAxis('t'+str(i))
tvalues = self._aslist_(taxis[:])
oldid = taxis.stataccum_oldid
for tvals in tvalues:
tx = create_time(tvals, taxis.units, id=oldid)
cp_atts(taxis, tx, id=False, exclude=[oldid])
self._stimes[i].append(tx)
# Count
self._scount = self._load_array_(f, id='scount')
# Other stats
self._sstats = {}
for key in self.single_stats:
if not self.dual: # single var
vid = 's' + key
if vid not in f.variables:
continue
self._sstats[key] = self._load_array_(f, vid),
else: # two vars
for i in xrange(self.nitems):
vid = 's%s%s'%(key, str(i))
if vid not in f.variables:
break
self._sstats.setdefault(key, ())
self._sstats[key] += self._load_array_(f, vid),
for key in self.dual_stats:
vid = 's%s'%key
if vid in f.variables:
self._sstats[key] = self._load_array_(f, vid)
# Temporal statistics
if self.tstats:
# Count
self._tcount = self._load_array_(f, 'tcount')
# Other stats
for key in self._dual_accums+self._single_accums:
tid = 't'+key
if not getattr(self, tid): continue
if key in self._dual_accums:
value = self._load_array_(f, tid)
setattr(self, '_'+tid, value)
else:
value = ()
for i in xrange(self.nitems):
value += self._load_array_(f, tid+str(i)),
setattr(self, '_'+tid, value)
# Templates
# - base arrays
self._tbase = N.zeros(self.ns)
if self.thist:
self._thbase = N.zeros((self.nbins, self.ns), 'l')
# - cdat templates
self._ttemplates = ()
self._thtemplates = None
if self.thist:
self._thtemplates = ()
for i in xrange(self.nitems):
prefix = 'var%i_'%i
for vname in f.variables:
if vname.startswith(prefix) and vname != prefix+'atts': break
ttpl = f(vname)
_rm_id_prefix_(ttpl, 'var%i_'%i, exc=self._baxis)
self._ttemplates += ttpl,
if self.thist:
self._thtemplates += self._template_t2ht_(ttpl),
# Attributes
self._atts = ()
for ivar in xrange(self.nitems):
attrs = f['var%i_atts'%ivar].attributes.copy()
attrs['id'] = attrs['stataccum_id']
del attrs['stataccum_id']
self._atts += attrs,
f.close()
return self.iterindex
def _template_t2ht_(self, tpl):
htpl = MV2.resize(tpl.astype('l'), (self.nbins,)+tpl.shape)
htpl.setAxisList([self._baxis]+tpl.getAxisList())
set_grid(htpl, get_grid(tpl))
cp_atts(tpl, htpl)
return htpl
def load(self, restart_file=None, iterindex=None, nowtime=None):
"""Load the current instance from a netcdf file
:Params:
- **restart_file**, optional: Netcdf restart file.
- **iterindex**, optional: If given, the restart file is not loaded if
``iterindex`` is greater or equal to the file's ``iterindex`` attribute.
- **nowtime**, optional: If given, the restart file is not loaded if
``nowtime`` is greater or equal to the file's ``lasttime`` attribute.
"""
# File
if restart_file is None:
restart_file = self.restart_file
if restart_file is None:
restart_file = self.default_restart_file
self.restart_file = restart_file
f = cdms2.open(restart_file)
# Config
# - check status
if iterindex is not None:
self.iterindex = iterindex
if hasattr(self, 'iterindex') and f.iterindex<=self.iterindex:
return -1
if nowtime is not None:
self.lasttime = comptime(nowtime)
if (hasattr(self, 'lasttime') and f.withtime>0 and self.lasttime
and comptime(f.lasttime)<=comptime(self.lasttime)):
return -1
# - what was initially asked and some more
for sname in self.all_stats + ('sum', 'sqr', 'prod', 'stats'):
for st in 'st':
if not hasattr(f, st+sname): continue
value = getattr(f, st+sname)
setattr(self, st+sname, bool(value))
# - current status
self.iterindex = int(f.iterindex)
self.nitems = int(f.nitems)
if f.withtime==-1:
self.withtime = None
else:
self.withtime = bool(f.withtime)
if f.withtime:
self.lasttime = cdtime.s2c(f.lasttime)
if N.isscalar(f.bin_edges):
self.bins = None
else:
self.bins = N.asarray(f.bin_edges)
self.nbins = self.bins.shape[0]-1
self._baxis = f.getAxis('hbin').clone()
if self.nitems==0: # Still no data
f.close()
return 0
# - already had some data
self.dual = bool(f.dual)
self.ns = int(f.ns)
self.nt = int(f.nt)
self._nts = f.nts.tolist()
self.tstats = bool(f.tstats)
self.sstats = bool(f.sstats)
if not self.withtime:
self._stimes = None
# Spatial statistics
if self.sstats:
# Time axes
if self.withtime:
self._stimes = tuple([[] for i in xrange(self.nitems)])
for i, tt in enumerate(self._stimes):
taxis = f.getAxis('t'+str(i))
tvalues = self._aslist_(taxis[:])
oldid = taxis.stataccum_oldid
for tvals in tvalues:
tx = create_time(tvals, taxis.units, id=oldid)
cp_atts(taxis, tx, id=False, exclude=[oldid])
self._stimes[i].append(tx)
# Count
self._scount = self._load_array_(f, id='scount')
# Other stats
self._sstats = {}
for key in self.single_stats:
self._sstats[key] = ()
for i in xrange(self.nitems):
self._sstats[key] += self._load_array_(f, 's%s%s'%(key, str(i))),
for key in self.dual_stats:
self._sstats[key] = self._load_array_(f, 's%s'%key)
# Temporal statistics
if self.tstats:
# Count
self._tcount = self._load_array_(f, 'tcount')
# Other stats
for key in self._dual_accums+self._single_accums:
tid = 't'+key
if not getattr(self, tid): continue
if key in self._dual_accums:
value = self._load_array_(f, tid)
setattr(self, '_'+tid, value)
else:
value = ()
for i in xrange(self.nitems):
value += self._load_array_(f, tid+str(i)),
setattr(self, '_'+tid, value)
# Templates
# - base arrays
self._tbase = N.zeros(self.ns)
if self.thist:
self._thbase = N.zeros((self.nbins, self.ns), 'l')
# - cdat templates
self._ttemplates = ()
if self.thist:
self._thtemplates = ()
for i in xrange(self.nitems):
prefix = 'var%i_'%i
for vname in f.variables:
if vname.startswith(prefix): break
ttpl = f(vname)
_rm_id_prefix_(ttpl, 'var%i_'%i, exc=self._baxis)
self._ttemplates += ttpl,
if self.thist:
self._thtemplates += self._template_t2ht_(ttpl),
# Attributes
self._atts = ()
for ivar in xrange(self.nitems):
attrs = f['var%i_atts'%ivar].attributes.copy()
attrs['id'] = attrs['stataccum_id']
del attrs['stataccum_id']
self._atts += attrs,
f.close()
return self.iterindex
def _template_t2ht_(self, tpl):
htpl = MV2.resize(tpl.astype('l'), (self.nbins,)+tpl.shape)
htpl.setAxisList([self._baxis]+tpl.getAxisList())
set_grid(htpl, get_grid(tpl))
cp_atts(tpl, htpl)
return htpl
