# Parameters ncfile = "menor.nc" lon = (3.0, 4.5) lat = (42, 42.8) # Imports from vcmq import DS, map2, data_sample from vacumm.diag.thermdyn import mixed_layer_depth # Read temperature and depth ncfile = data_sample(ncfile) ds = DS(ncfile, "mars", lon=lon, lat=lat) temp = ds.get_temp(squeeze=1) depth = ds.get_depth(squeeze=1) # Compute MLD mld = mixed_layer_depth(temp, depth, mode="deltatemp") # Plot map2(mld, proj="merc", figsize=(6, 6), autoresize=0, colorbar_shrink=0.7, right=1, savefigs=__file__, show=False) print "Done"
"""Test :func:`~vacumm.diag.thermdyn.mixed_layer_depth` on MENOR"""
# Inits
ncfile = "menor.nc"
# Imports
from vcmq import DS, data_sample, mixed_layer_depth, rc, map2, os, code_file_name
# Read data
ds = DS(data_sample(ncfile),'mars', logger_level='critical')
temp = ds.get_temp(squeeze=True)
sal = ds.get_sal(squeeze=True)
depth = ds.get_depth(squeeze=True)
kz = ds.get_kz(squeeze=True)
# Compute MLD
kw = dict(depth=depth, format_axes=True)
mld = {}
mld['deltatemp'] = mixed_layer_depth(temp, mode='deltatemp',**kw)
mld['deltadens'] = mixed_layer_depth((temp,sal), mode='deltadens', **kw)
mld['kz'] = mixed_layer_depth(kz, mode='kz', **kw)
vmin = min([v.min() for v in mld.values()])
vmax = max([v.max() for v in mld.values()])
# Plot it
rc('font', size=8)
for i,(mode, var) in enumerate(mld.items()):
m = map2(var, fill='pcolormesh', nmax=20, vmin=vmin, vmax=vmax,
subplot=(len(mld),1,i+1), figsize=(4.1,8),
contour_linewidths=0.7, cmap='vacumm_rnb2_hymex', hspace=0.25, bottom=0.08,
title='%%(long_name)s: mode = "%s"'%mode, show=False)
"""Test the asvar keyword of :meth:`~vacumm.data.misc.dataset.Dataset.finalize_object` on MFS"""
# Inits
ncfile = "mfs.nc"
# Imports
from vcmq import DS, data_sample
# Read data
ds = DS(data_sample(ncfile), 'nemo', logger_level='critical')
temp = ds.get_temp()
depth = ds.get_depth(asvar=temp)
# For unittest
result = {'assertTupleEqual':[depth.shape, temp.shape]}
print ds.dataset
# Logging
ds.info('Pratique') # -> ESSAYER WARNING
ds.set_loglevel('debug')
# Coordonnees
lon = ds.get_lon() # -> ESSAYER AU POINT U
grid = ds.get_grid()
# Variables
temp = ds.get_temp(level=slice(-1, None), squeeze=True)
sst = ds.get_sst(squeeze=True) # -> VERIFIER ATTRIBUTS
ds.info('Plot SST')
map2(sst)
sal = ds.get_sal(lon=(4., 4.5))
print temp.shape, sal.shape
# Generique
ds2 = DS(data_sample('mfs.nc'), 'nemo', lon=(4, 5), lat=(42.5, 43.5))
sst2 = ds2.get_sst(squeeze=True) # -> VERIFIER ATTRIBUTS
# Plus evolue
depth = ds.get_depth() # sigma
print depth.shape
mld = ds.get_mld()
ds.plot_transect('temp', lons=(4.1, 4.9), lats=(43.3, 42.6), figsize=(12, 6)) # -> OUTAXIS=
def load_model_at_regular_dates(ncpat,
varnames=None,
time=None,
lat=None,
lon=None,
level=None,
depths=None,
modeltype='mars',
nt=50,
dtfile=None,
sort=True,
asdict=False,
logger=None,
**kwargs):
"""Read model output at nearest unique dates with optional linear interpolation
Parameters
----------
ncpat: string or list of strings
varnames: string, strings
Generic var names. If None, all variables that are known from the
:mod:`vacumm.data.cf` module are used.
level: string, None, list of floats, array, tuple of them, dict
Here are some possible values:
- "surf" or "bottom": self explenatory
- None or "3d": No slice, so get all levels with no interpolation.
- A list or array of negative depths: get all levels and
interpolate at these depths.
Variables sliced with "surf" and "bottom" are returned with
an id suffixed with "_surf" or "_bottom".
You can speficy different slicings using a tuple
of depth specifications.
You can specialise slicings of a variable using a dictionary with
the key as the variable name.
See also
--------
:func:`sonat.misc.list_files_from_pattern` for more options
Examples
--------
>>> mdict = load_model_at_regular_dates('myfile.nc', level='surf')
>>> mdict = load_model_at_regular_dates('myfile.nc', level=('surf', 'bottom')
>>> mdict = load_model_at_regular_dates('myfile.nc', varnames=['temp', 'sal'],
level={'temp':('surf', 'bottom'), 'sal':[-50, -10]})
>>> mdict = load_model_at_regular_dates('myfile.nc', varnames=['temp', 'sal'],
level={'temp':('surf', '3d'), 'sal':None}, depths=[-50, -10])
"""
# Logger
kwlog = kwfilter(kwargs, 'logger_')
if logger is None:
logger = get_logger(**kwlog)
logger.debug('Loading model at regular dates')
# Get file list
ncfiles = list_files_from_pattern(ncpat, time, dtfile=dtfile, sort=True)
if not ncfiles:
raise SONATError('No file found')
# Time interval
reqtime = time
if time is None:
# First
taxis = ncget_time(ncfiles[0])
if taxis is None:
raise SONATError("Can't get time axis for: " + ncfiles[0])
ctimes = taxis.asComponentTime()
ct0 = ctimes[0]
# Last
if ncfiles[0] != ncfiles[-1]:
taxis = ncget_time(ncfiles[-1])
if taxis is None:
raise SONATError("Can't get time axis for: " + ncfiles[-1])
ctimes = taxis.asComponentTime()
ct1 = ctimes[-1]
# Time
time = (ct0, ct1)
# Generate dates
dates = lindates(time[0], time[1], nt)
# Get time indices
iidict, iiinfo = ncfiles_time_indices(ncfiles,
dates,
getinfo=True,
asslices=True)
if iiinfo['missed'] or iiinfo['duplicates']:
msg = ("You must provide at least {nt} model time steps to read "
"independant dates")
if reqtime:
msg = msg + (", and your requested time range must be enclosed "
"by model time range.")
raise SONATError(msg)
# Read
single = isinstance(varnames, basestring)
if single:
varnames = [varnames]
out = OrderedDict()
vlevels = {}
if not isinstance(level, dict):
level = {'__default__': level}
for ncfile, tslices in iidict.items():
# Dataset instance
ds = DS(ncfile,
modeltype,
logger_name='SONAT.Dataset',
logger_level='error')
# List of well known variables
if varnames is None:
varnames = []
for ncvarname in ds.get_variable_names():
varname = match_known_var(ds[0][ncvarname])
if varname:
varnames.append(varname)
# Loop on variables
vardepth = None
kwvar = dict(lat=lat, lon=lon, verbose=False, bestestimate=False)
for vname in list(varnames):
# Level selector for this variable
if vname in vlevels: # cached
vlevel = vlevels[vname]
else:
vlevel = interpret_level(dicttree_get(level, vname),
astuple=True)
vlevels[vname] = vlevel # cache it
# Loop on level specs
for vlev in vlevel:
# Output vname and vlev check
if not isinstance(vlev, basestring):
vnameo = vname
elif vlev not in ('surf', "bottom", "3d"):
raise SONATError('Depth string must one of '
'surf, bottom, 3d')
elif vlev != '3d':
vnameo = vname + '_' + vlev
else:
vlev = None
vnameo = vname
# Slicing level and output depths
if vlev not in ['surf', 'bottom']:
# numeric so interpolation
if vlev is None:
vdep = depths if depths is not None else None
else:
vdep = vlev
interp = vdep is not None
if interp:
vlev = None
else:
interp = False
# Read and aggregate
vout = out.setdefault(vnameo, [])
# vinterp = None
for tslice in tslices:
# Get var
kwvar['time'] = tslice
var = ds(vname, level=vlev, **kwvar)
# Interpolate at numeric depths
if interp and var.getLevel() is not None:
# Get depths
if True or vardepth is None: #FIXME: bad to always read it
vardepth = ds.get_depth(level=vlev,
zerolid=True,
**kwvar)
# Interpolate
var = ds._interp_at_depths_(var,
vardepth,
vdep,
extrap='top')
# Id with suffix
var.id = vnameo
# Store results
vout.append(var)
# Concatenate
for vname, vout in out.items():
out[vname] = MV2_concatenate(vout)
# Dict
if asdict:
return out
# Single
out = out.values()
if single:
return out[0]
return out
#!/usr/bin/env python
# -*- coding: utf8 -*-
"""Diagnostics thermodynamiques et dynamiques (:mod:`vacumm.diag.thermdyn` et :mod:`vacumm.diag.dynamics`)"""
from vcmq import DS, data_sample, map2, density, mixed_layer_depth, barotropic_geostrophic_velocity, kinetic_energy, shapiro2d
# Lecture des données de base
ds = DS(data_sample('menor.nc'))
temp = ds.get_temp(squeeze=1)
sal = ds.get_sal(squeeze=1)
depth = ds.get_depth(squeeze=1)
ssh = ds.get_ssh(squeeze=1)
# Densité
dens_surf = density(temp[-1], sal[-1]) # -> CALCULER DENSITE 3D
map2(dens_surf)
# Couche mélangée
mld = mixed_layer_depth((temp, sal), depth, mode='deltadens') # -> ESSAYER AUTRES MODES
map2(mld, vmax=600.)
# Vitesse geostrophique
# - vitesses
ug, vg = barotropic_geostrophic_velocity(ssh)
# - energie cinetique
ke = kinetic_energy((ug, vg)) # -> TESTER AVEC SSH
ke.long_name = 'Surface geostrophique kinetic energy'
ke = shapiro2d(ke)
