def plotts(args):
ifiles = args.ifiles
times = [gettimes(ifile) for ifile in ifiles]
fig = plt.figure()
ax = fig.add_subplot(111) # add_axes([.1, .15, .8, .8])
ax.set_xlabel('Time (UTC)')
split = 25
for target in args.variables:
vars = [ifile.variables[target] for ifile in ifiles]
unit = getattr(vars[0], 'units', 'unknown')
ax.set_ylabel(target + '(' + unit + ')')
del ax.lines[:]
nvars = len(vars)
varwidth = .8 / nvars / 1.1
po = np.arange(24) + 0.1 + varwidth / 2
for vi, (time, var) in enumerate(zip(times, vars)):
vals = var[:]
if args.squeeze:
vals = vals.squeeze()
vardesc = getattr(var, 'description', None)
varb = ax.plot(time, vals[:], label=vardesc)
# plt.setp(ax.xaxis.get_ticklabels(),rotation = 45)
plt.legend()
figpath = args.outpath + target + '.' + args.figformat
for pc in args.plotcommands:
exec(pc, globals(), locals())
fig.savefig(figpath)
if args.verbose > 0:
print('Saved fig', figpath)
print(figpath)
def make1d(ifile, args):
if len(args.figure_keywords) > 0:
plt.setp(fig, **args.figure_keywords)
if len(args.axes_keywords) > 0:
plt.setp(ax, **args.axes_keywords)
for fi, ifile in enumerate(ifiles):
variables = args.variables
if variables is None:
variables = [
key for key, var in ifile.variables.items() if var.ndim == 2
]
if len(variables) == 0:
raise ValueError(
'Unable to heuristically determin plottable variables; use -v to specify variables for plotting'
)
for varkey in variables:
if not args.overlay:
ax.cla()
var = ifile.variables[varkey]
vals = var[:]
if args.squeeze:
vals = vals.squeeze()
label = getattr(var, 'standard_name', varkey).strip()
varunit = getattr(var, 'units', 'unknown').strip()
print(varkey, sep='')
dimkey = var.dimensions[0]
ax.set_xlabel(dimkey)
if args.time:
x = gettimes(ifile)
elif dimkey in ifile.variables:
x = ifile.variables[var.dimensions[0]][:]
else:
x = np.arange(var.shape[0])
patches = ax.plot(x, vals, label=label)
ax.set_ylabel(varunit)
plt.legend()
fmt = 'png'
outpath = args.outpath
if len(ifiles) > 1:
lstr = str(fi).rjust(len(str(len(ifiles))), '0')
else:
lstr = ''
figpath = os.path.join(outpath + varkey + lstr + '.' + fmt)
if args.interactive:
csl = PNCConsole(locals=globals())
csl.interact()
fig.savefig(figpath)
if args.verbose > 0:
print('Saved fig', figpath)
def plot_diurnal_box(ifiles, args):
times = [gettimes(ifile) for ifile in ifiles]
hours = [np.array([t.hour for t in time]) for time in times]
fig = plt.figure()
sax = fig.add_subplot(111)
if len(args.figure_keywords) > 0:
plt.setp(fig, **args.figure_keywords)
if len(args.axes_keywords) > 0:
plt.setp(sax, **args.axes_keywords)
sax.set_xlabel('Time (UTC)')
split = 25
for target in args.variables:
vars = [ifile.variables[target] for ifile in ifiles]
unit = getattr(vars[0], 'units', 'unknown')
sax.set_ylabel(target + ' (' + unit + ')')
vals = [var[:] for var in vars]
hvars = [[np.ma.compressed(val[hour == i]) for i in range(24)]
for hour, val in zip(hours, vals)]
del sax.lines[:]
nvars = len(vars)
varwidth = .8 / nvars / 1.1
po = np.arange(24) + 0.1 + varwidth / 2
ncolors = max(float(nvars), 10)
try:
from cycler import cycler
props = cycler('color', [
plt.get_cmap()((nc + .5) / float(ncolors))
for nc in range(ncolors)
])
except:
props = [
dict(color=plt.get_cmap()((nc + .5) / float(ncolors)))
for nc in range(ncolors)
]
for vi, (var, propd) in enumerate(zip(hvars, props)):
varb = sax.boxplot(var,
positions=po + vi * varwidth * 1.1,
widths=varwidth,
patch_artist=True)
plt.setp([i for i in varb.values()], **propd)
plt.setp(varb['medians'], color='k')
plt.setp(varb['fliers'], markeredgecolor=propd['color'])
sax.set_xlim(-.5, 24.5)
sax.set_xticks(range(0, 25))
sax.set_xticklabels([str(i) for i in range(0, 25)])
#plt.setp(sax.xaxis.get_ticklabels(),rotation = 45)
figpath = args.outpath + target + '.' + args.figformat
fig.savefig(figpath)
if args.verbose > 0: print('Saved fig', figpath)
def writearlpackedbit(infile, path):
"""
path - path to existing arl packed bit file or location for new file
infile - NetCDF-like file with
- vertical 2-D (surface) and 3-D (layers) variables
with 4 character names
- a z variable with vertical coordinates
- all properties from the first index record
"""
requiredkeys = list(thdtype.names)
for key in requiredkeys:
getattr(infile, key)
svars = {}
lvars = {}
props = {}
sfckeys = props['sfckeys'] = []
laykeys = props['laykeys'] = []
for vark, var in infile.variables.items():
if len(var.shape) == 3:
svars[vark] = var
sfckeys.append(vark.encode('ascii'))
elif len(var.shape) == 4:
lvars[vark] = var
lvar = var
laykeys.append(vark.encode('ascii'))
else:
pass
vglvls = np.append(float(infile.SFCVGLVL),
infile.variables['z'][:].array())
# vgtxts = getvgtxts(vglvls)
# plus one includes surface
props['NZ'] = lvar.shape[1] + 1
props['NY'] = lvar.shape[2]
props['NX'] = lvar.shape[3]
datamap = maparlpackedbit(path,
mode='write',
shape=(lvar.shape[0], ),
**props)
theads = datamap['timehead']
# for key in thdtype.names:
# theads[key] = getattr(infile, key)
# vardefs = datamap['vardef']
# for ti, vardef in enumerate(vardefs):
# sfcvardeftxt = vgtxts[0] + '%2d' % len(svars) +
# ''.join(['%-4s -1 ' % skey.decode()
# for skey in sfckeys])
# layvardeftxt = ''
# for vgtxt in vgtxts[1:]:
# layvardeftxt += vgtxt + '%2d' % len(lvars) +
# ''.join(['%-4s -1 ' % lkey.decode()
# for lkey in laykeys])
#
#
# vardeftxt = sfcvardeftxt + layvardeftxt
# defsize = 8+8*len(svars)+(8+8*len(lvars))*len(vgtxts[1:])
# assert(len(vardeftxt) == defsize)
# vardefs[:] = vardeftxt
YYMMDDHHFF = getattr(infile, 'YYMMDDHHFF', '0000000000')
FF = YYMMDDHHFF[-2:]
times = gettimes(infile)
checksums = {}
for ti, (time, thead) in enumerate(zip(times, theads)):
for propk in thead.dtype.names:
if propk in ('NX', 'NY', 'NZ'):
thead[propk] = '%3d' % props[propk]
elif propk == 'LENH':
thead[propk] = '%4d' % datamap['vardef'][ti].itemsize
else:
thead[propk] = getattr(infile, propk)
timestr = time.strftime('%y%m%d%H').encode('ascii') + FF
thead['YYMMDDHHFF'] = timestr
for sfck in sfckeys:
invar = infile.variables[sfck.decode()]
var_time = datamap['surface'][sfck.decode()]
varhead = var_time['head']
_skipprop = ('YYMMDDHHFF', 'LEVEL', 'EXP', 'PREC', 'VAR1')
for varpropk in varhead.dtype.names:
if varpropk not in _skipprop:
varhead[varpropk][ti] = getattr(invar, varpropk)
indata = invar[ti]
CVAR, PREC, NEXP, VAR1, KSUM = pack2d(indata, verbose=False)
varhead['YYMMDDHHFF'][ti] = timestr
varhead['LEVEL'][ti] = '%2d' % 0
varhead['PREC'][ti] = '%14.7E' % PREC
varhead['EXP'][ti] = '%4d' % NEXP
varhead['VAR1'][ti] = '%14.7E' % VAR1
checksums[vglvls[0], sfck] = KSUM
var_time['data'][ti] = CVAR
for layk in laykeys:
invar = infile.variables[layk.decode()]
var_time = datamap['layers'][layk.decode()][ti]
for li, var_time_lay in enumerate(var_time):
varhead = var_time_lay['head']
for varpropk in varhead.dtype.names:
if varpropk not in _skipprop:
varhead[varpropk] = getattr(invar, varpropk)
indata = invar[ti, li]
CVAR, PREC, NEXP, VAR1, KSUM = pack2d(indata)
varhead['YYMMDDHHFF'] = timestr
varhead['LEVEL'] = '%2d' % (li + 1)
var_time_lay['data'] = CVAR
varhead['PREC'] = '%14.7E' % PREC
varhead['EXP'] = '%4d' % NEXP
varhead['VAR1'] = '%14.7E' % VAR1
vglvl = vglvls[li + 1]
checksums[vglvl, layk] = KSUM
keys = {vglvls[0]: sfckeys}
for vglvl in vglvls[1:]:
keys[vglvl] = laykeys
vardef = writevardef(vglvls, keys, checksums)
datamap['vardef'][ti] = ' '.ljust(datamap['vardef'][ti].itemsize)
datamap['hdr'][ti] = ' '.ljust(datamap['hdr'][ti].itemsize)
datamap['vardef'][ti] = vardef.encode('ascii')
thead['LENH'] = datamap['vardef'][ti].itemsize
datamap.flush()
def plot(ifiles, args):
from PseudoNetCDF.coordutil import getsigmamid, getpresmid, gettimes
import pylab as pl
from pylab import figure, NullFormatter, close, rcParams
rcParams['text.usetex'] = False
from matplotlib.colors import LinearSegmentedColormap, BoundaryNorm, LogNorm
scale = args.scale;
minmax = eval(args.minmax)
minmaxq = eval(args.minmaxq)
sigma = args.sigma
maskzeros = args.maskzeros
outunit = args.outunit
tespaths = args.tespaths
omipaths = args.omipaths
edges = args.edges
try:
f, = ifiles
except:
raise ValueError('curtain plot expects one file when done. Try stack time --stack=time to concatenate')
# Add CF conventions if necessary
if 'latitude_bounds' not in f.variables.keys():
try:
from PseudoNetCDF import getvarpnc
from PseudoNetCDF.conventions.ioapi import add_cf_from_ioapi
f = getvarpnc(f, None)
add_cf_from_ioapi(f)
except:
pass
if sigma:
vertcrd = getsigmamid(f)
else:
vertcrd = getpresmid(f, pref = 101325., ptop = getattr(f, 'VGTOP', 10000))
if vertcrd.max() > 2000: vertcrd /= 100.
try:
lonb = f.variables['geos_longitude_bounds']
latb = f.variables['geos_latitude_bounds']
except:
lonb = f.variables['longitude_bounds']
latb = f.variables['latitude_bounds']
for var_name in args.variables:
temp = defaultdict(lambda: 1)
try:
eval(var_name, None, temp)
var = eval(var_name, None, f.variables)[:]
except:
temp[var_name]
var = f.variables[var_name][:]
if maskzeros: var = np.ma.masked_values(var, 0)
unit = f.variables[temp.keys()[0]].units.strip()
if unit in unitconvert:
var = unitconvert.get((unit, outunit), lambda x: x)(var)
else:
outunit = unit
bmap = None
vmin, vmax = np.percentile(np.ma.compressed(var).ravel(), list(minmaxq))
if minmax[0] is not None:
vmin = minmax[0]
if minmax[1] is not None:
vmax = minmax[1]
if edges:
fig = pl.figure(figsize = (16, 4))
offset = 0.05
ax = fig.add_axes([.1 - offset, .15, .22, .725])
ax = fig.add_axes([.325 - offset, .15, .22, .725])
ax = fig.add_axes([.55 - offset, .15, .22, .725])
ax = fig.add_axes([.775 - offset, .15, .22, .725])
ss = 0
se = ss + f.NCOLS + 1
es = se
ee = se + f.NROWS + 1
ns = ee
ne = ee + f.NCOLS + 1
ws = ne
we = ws + f.NROWS + 1
axs = fig.axes
for ax in fig.axes[1:]:
ax.yaxis.set_major_formatter(pl.NullFormatter())
vars = [var[:, :, ss:se], var[:, :, es:ee], var[:, :, ns:ne][:, :, ::-1], var[:, :, ws:we][:, :, ::-1]]
lonbss = [lonb[ss:se], lonb[es:ee], lonb[ns:ne][::-1], lonb[ws:we][::-1]]
latbss = [latb[ss:se], latb[es:ee], latb[ns:ne][::-1], latb[ws:we][::-1]]
else:
fig = pl.figure(figsize = (8, 4))
ax = fig.add_axes([.1, .15, .8, .725])
axs = fig.axes
vars = [var]
lonbss = [lonb[:]]
latbss = [latb[:]]
for ax, var, lonbs, latbs in zip(axs, vars, lonbss, latbss):
vals = var.swapaxes(0, 1).reshape(var.shape[1], -1)
ax.text(.05, .9, 'n = %d' % vals.shape[1], transform = ax.transAxes)
modl, modr = minmaxmean(ax, vals, vertcrd, facecolor = 'k', edgecolor = 'k', alpha = .2, zorder = 4, label = 'GC', ls = '-', lw = 2, color = 'k')
llines = [(modl, modr)]
ymin, ymax = vertcrd.min(), vertcrd.max()
ax.set_ylim(ymax, ymin)
ax.set_xscale(scale)
ax.set_xlim(vmin, vmax)
#if scale == 'log':
# ax.set_xticklabels(['%.1f' % (10**x) for x in ax.get_xticks()])
if 'TFLAG' in f.variables.keys():
SDATE = f.variables['TFLAG'][:][0, 0, 0]
EDATE = f.variables['TFLAG'][:][-1, 0, 0]
STIME = f.variables['TFLAG'][:][0, 0, 1]
ETIME = f.variables['TFLAG'][:][-1, 0, 1]
if SDATE == 0:
SDATE = 1900001
EDATE = 1900001
sdate = datetime.strptime('%07d %06d' % (SDATE, STIME), '%Y%j %H%M%S')
edate = datetime.strptime('%07d %06d' % (EDATE, ETIME), '%Y%j %H%M%S')
elif 'tau0' in f.variables.keys():
sdate = datetime(1985, 1, 1, 0) + timedelta(hours = f.variables['tau0'][0])
edate = datetime(1985, 1, 1, 0) + timedelta(hours = f.variables['tau1'][-1])
else:
times = gettimes(f)
sdate = times[0]
edate = times[-1]
if len(tespaths) > 0:
tesl, tesr = plot_tes(ax, lonbs, latbs, tespaths)
if not tesl is None:
llines.append((tesl, tesr))
if len(omipaths) > 0:
omil, omir = plot_omi(ax, lonbs, latbs, omipaths, airden = f.variables['AIRDEN'][:].mean(0).mean(1), airdenvert = vertcrd)
if not omil is None:
llines.append((omil, omir))
try:
title = '%s to %s' % (sdate.strftime('%Y-%m-%d'), edate.strftime('%Y-%m-%d'))
except:
title = var_name
if sigma:
axs[0].set_ylabel('sigma')
else:
axs[0].set_ylabel('pressure')
xmax = -np.inf
xmin = np.inf
for ax in fig.axes:
tmp_xmin, tmp_xmax = ax.get_xlim()
xmax = max(tmp_xmax, xmax)
xmin = min(tmp_xmin, xmin)
for ax in fig.axes:
ax.set_xlim(xmin, xmax)
if len(axs) == 1:
axs[0].set_xlabel('%s %s' % (var_name, outunit))
else:
axs[0].set_xlabel('South')
axs[1].set_xlabel('East')
axs[2].set_xlabel('North')
axs[3].set_xlabel('West')
fig.text(.5, .90, '%s %s' % (var_name, outunit), horizontalalignment = 'center', fontsize = 16)
nl = 0
for ax in axs:
if len(ax.get_lines()) > nl:
nl = len(ax.get_lines())
pl.sca(ax)
llabels = [l[0].get_label() for l in llines]
pl.legend(llines, llabels, bbox_to_anchor = (.1, 1), loc = 'upper left', bbox_transform = fig.transFigure, ncol = 6)
if edges:
fig.text(0.95, 0.975, title, horizontalalignment = 'right', verticalalignment = "top", fontsize = 16)
else:
fig.text(0.95, 0.025, title, horizontalalignment = 'right', verticalalignment = "bottom", fontsize = 16)
fig.savefig('%s_%s.%s' % (args.outpath, var_name, args.figformat))
pl.close(fig)
return fig
def pncdump(f,
name='unknown',
header=False,
variables=[],
line_length=80,
full_indices=None,
float_precision=8,
double_precision=16,
isgroup=False,
timestring=False,
outfile=sys.stdout):
"""
pncdump is designed to implement basic functionality
of the NetCDF ncdump binary.
f - a PseudoNetCDFFile object
name - string name for the file
(equivalent to ncdump -n name)
header - boolean value for display of header only
(equivalent to ncdump -h)
variables - iterable of variable names for subsetting
data display (equivalent to ncddump -v var[,...]
pncdump(vertical_diffusivity('camx_kv.20000825.hgbpa_04km.TCEQuh1_eta.v43.tke',rows=65,cols=83))
"""
file_type = str(type(f)).split("'")[1]
float_fmt = "%%.%dg" % (float_precision, )
double_fmt = "%%.%dg" % (double_precision, )
int_fmt = "%i"
formats = defaultdict(lambda: "%s",
float = double_fmt, \
float64 = double_fmt, \
float32 = float_fmt, \
int32 = "%i", \
uint32 = "%i", \
int64 = "%i", \
str = "%s", \
bool = "%s", \
string8 = "'%s'")
funcs = dict(
) #float = lambda x: double_fmt % x) # initialize indentation as 8 characters
# based on ncdump
indent = 8 * " "
if isgroup:
startindent = 4 * " "
else:
startindent = 4 * ""
# First line of CDL
if not isgroup: outfile.write("%s %s {\n" % (
file_type,
name,
))
###########################
# CDL Section 1: dimensions
###########################
outfile.write(startindent + "dimensions:\n")
for dim_name, dim in f.dimensions.items():
if dim.isunlimited():
outfile.write(startindent + 1 * indent +
("%s = UNLIMITED // (%s currently) \n" %
(dim_name, len(dim))))
else:
outfile.write(startindent + 1 * indent + ("%s = %s ;\n" %
(dim_name, len(dim))))
###################################
# CDL Section 2: variables metadata
###################################
if len(f.variables.keys()) > 0:
outfile.write("\n" + startindent + "variables:\n")
for var_name, var in f.variables.items():
var_type = dict(float32='float', \
float64='double', \
int32='integer', \
uint32='integer', \
int64='long', \
bool='bool', \
string8='char', \
string80='char').get(var.dtype.name, var.dtype.name)
outfile.write(startindent + 1 * indent +
("%s %s%s;\n" %
(var_type, var_name, str(var.dimensions).replace(
'u\'', '').replace('\'', '').replace(',)', ')'))))
for prop_name in var.ncattrs():
prop = getattr(var, prop_name)
outfile.write(startindent + 2 * indent + (
"%s:%s = %s ;\n" %
(var_name, prop_name, repr(prop).replace("'", '"'))))
################################
# CDL Section 3: global metadata
################################
outfile.write("\n\n// global properties:\n")
for prop_name in f.ncattrs():
prop = getattr(f, prop_name)
outfile.write(startindent + 2 * indent +
(":%s = %s ;\n" %
(prop_name, repr(prop).replace("'", '"'))))
if hasattr(f, 'groups'):
for group_name, group in f.groups.items():
outfile.write(startindent + 'group %s:\n' % group_name)
pncdump(group,
name=name,
header=header,
variables=variables,
line_length=line_length,
full_indices=full_indices,
float_precision=float_precision,
double_precision=double_precision,
isgroup=True)
if not header:
# Error trapping prevents the user from getting an error
# when they cancel a dump or when they break a redirected
# pipe
try:
#####################
# CDL Section 4: data
#####################
outfile.write("\n\n" + startindent + "data:\n")
# data indentation is only 1 space
indent = " "
# Subset variables for output
display_variables = [
var_name for var_name in f.variables.keys()
if var_name in variables or variables == []
]
if variables != []:
if len(variables) < len(display_variables):
warn("Not all specified variables were available")
# For each variable output data
# currently assumes 3-D data
for var_name in display_variables:
var = f.variables[var_name]
if isinstance(var, PseudoNetCDFMaskedVariable) or hasattr(
var, '_FillValue'):
def writer(row, last):
if isscalar(row) or row.ndim == 0:
outfile.write(startindent + ' ' +
str(row.filled().astype(ndarray)) +
';\n')
return
#old = get_printoptions()
#set_printoptions(threshold = inf, linewidth = line_length)
#tmpstr = startindent + ' ' + array2string(row, separator = commaspace, formatter = funcs).replace('\n', '\n' + startindent + ' ')[1:-1].replace('--', '_')
#if last:
# tmpstr += ';'
#else:
# tmpstr += commaspace
#set_printoptions(**old)
#outfile.write(tmpstr)
#outfile.write('\n')
tmpstr = StringIO()
if ma.getmaskarray(row).all():
tmpstr.write(b', '.join([b'_'] * row.size) + b', ')
else:
savetxt(tmpstr,
ma.filled(row),
fmt,
delimiter=commaspace,
newline=commaspace)
if last:
tmpstr.seek(-2, 1)
tmpstr.write(semicolon)
tmpstr.seek(0, 0)
tmpstr = tmpstr.read().decode('ASCII')
tmpstr = tmpstr.replace(
fmt % getattr(row, 'fill_value', 0) + ',', '_,')
tmpstr = textwrap.fill(
tmpstr,
line_length,
initial_indent=startindent + ' ',
subsequent_indent=startindent + ' ')
try:
outfile.write(tmpstr)
outfile.write('\n')
except Exception as e:
exception_handler(e, outfile)
else:
def writer(row, last):
if isscalar(row) or row.ndim == 0:
outfile.write(startindent + ' ' +
str(row.astype(ndarray)) + ';\n')
return
old = get_printoptions()
set_printoptions(threshold=inf, linewidth=line_length)
tmpstr = startindent + ' ' + array2string(
row, separator=commaspace,
formatter=funcs).replace(
'\n', '\n' + startindent + ' ')[1:-1]
#tmpstr = StringIO()
#savetxt(tmpstr, row, fmt, delimiter = commaspace, newline =commaspace)
if last:
tmpstr += ';'
#tmpstr.seek(-2, 1)
#tmpstr.write(semicolon)
else:
tmpstr += commaspace
#tmpstr.seek(0, 0)
#outfile.write(textwrap.fill(str(tmpstr.read()), line_length, initial_indent = startindent + ' ', subsequent_indent = startindent + ' '))
set_printoptions(**old)
try:
outfile.write(tmpstr)
outfile.write('\n')
except Exception as e:
exception_handler(e, outfile)
outfile.write(startindent + 1 * indent + ("%s =\n" % var_name))
if var_name in ('time', 'time_bounds') and timestring:
from PseudoNetCDF.coordutil import gettimes, gettimebnds
if var_name == 'time':
times = gettimes(f)
elif var_name == 'time_bounds':
times = gettimebnds(f)
for i in ndindex(var.shape):
val = var[i]
if ma.is_masked(val):
array_str = '_'
else:
array_str = startindent + 2 * indent + str(val)
if i == tuple(map(lambda x_: x_ - 1, var.shape)):
array_str += ";"
else:
array_str += ","
array_str += " // %s%s %s \n" % (var_name, i,
str(times[i]))
try:
outfile.write(array_str)
except Exception as e:
exception_handler(e, outfile)
elif full_indices is not None:
id_display = {'f': lambda idx: str(tuple([idx[i]+1 for i in range(len(idx)-1,-1,-1)])), \
'c': lambda idx: str(idx)}[full_indices]
#for i, val in ndenumerate(var):
for i in ndindex(var.shape):
val = var[i]
if ma.is_masked(val):
array_str = '_'
else:
fmt = startindent + 2 * indent + formats[
var.dtype.name]
array_str = fmt % val
if i == tuple(map(lambda x_: x_ - 1, var.shape)):
array_str += ";"
else:
array_str += ","
array_str += " // %s%s \n" % (var_name, id_display(i))
try:
outfile.write(array_str)
except Exception as e:
exception_handler(e, outfile)
else:
dimensions = [len(f.dimensions[d]) for d in var.dimensions]
if len(dimensions) > 1:
first_dim = prod(dimensions[:-1])
second_dim = dimensions[-1]
shape = [first_dim, second_dim]
else:
shape = [1] + dimensions
var2d = var[...].reshape(*shape)
fmt = ', '.join(shape[-1] * [formats[var.dtype.name]])
fmt = formats[var.dtype.name]
lastrow = var2d.shape[0] - 1
for rowi, row in enumerate(var2d):
try:
writer(row, rowi == lastrow)
except Exception as e:
exception_handler(e, outfile)
except Exception as e:
exception_handler(e, outfile)
outfile.write("}\n")
return outfile
def pnceval(args):
from warnings import warn
from PseudoNetCDF.core._functions import pncbfunc
if args.variables is None:
args.variables = set(args.ifiles[0].variables.keys()).difference(
args.coordkeys)
console = createconsole(args.ifiles, args)
ifile0, ifile1 = args.ifiles
from PseudoNetCDF.coordutil import gettimes
print('# ifile0=' + args.ipath[0])
print('# ifile1=' + args.ipath[1])
print('# Stats calculated as func(ifile0, ifile1)')
print('# Generally: func(obs, mod, ....)')
for ipath, ifile in zip(args.ipath, args.ifiles):
print('# Meta-data from %s' % ipath)
try:
times = gettimes(ifile)
tstart = times[:].min()
tstop = times[:].max()
print('# Date Range: ' + str(tstart) + ' to ' + str(tstop))
except Exception as e:
warn(str(e))
try:
lon = ifile.variables['longitude']
print('# Longitude Range: ' + str(float(lon.min())) + ' to ' +
str(float(lon.max())))
except Exception as e:
warn(str(e))
try:
lat = ifile.variables['latitude']
print('# Latitude Range: ' + str(float(lat.min())) + ' to ' +
str(float(lat.max())))
except Exception as e:
warn(str(e))
np.seterr(divide='ignore', invalid='ignore')
if args.csv:
from collections import OrderedDict
output = OrderedDict()
for k in args.funcs:
console.locals[k] = func = eval(k)
output[k] = OrderedDict()
if args.csv:
print('# %s: %s' % (k, func.__doc__.strip()))
try:
console.locals[k + '_f'] = ofile = pncbfunc(func, ifile0, ifile1)
except Exception as e:
warn("Skipped " + k + ';' + str(e))
continue
for vk in args.variables:
if vk in ('time', 'TFLAG'):
continue
if args.csv:
outv = ofile.variables[vk][:]
outv = np.ma.array(outv)
output[k][vk] = outv.ravel()[0]
else:
print('%s,%s,%s,%f' % (vk, func.__doc__.strip(), k,
ofile.variables[vk].ravel()[0]))
if args.csv:
print(','.join(['VAR'] + args.funcs))
for vk in args.variables:
print(','.join(
[vk] +
['%f' % output[fk].get(vk, np.nan) for fk in args.funcs]))
np.seterr(divide='warn', invalid='warn')
if args.interactive:
console.interact()
def pncdump(f, name = 'unknown', header = False, variables = [], line_length = 80, full_indices = None, float_precision = 8, double_precision = 16, isgroup = False, timestring = False, outfile = sys.stdout):
"""
pncdump is designed to implement basic functionality
of the NetCDF ncdump binary.
f - a PseudoNetCDFFile object
name - string name for the file
(equivalent to ncdump -n name)
header - boolean value for display of header only
(equivalent to ncdump -h)
variables - iterable of variable names for subsetting
data display (equivalent to ncddump -v var[,...]
pncdump(vertical_diffusivity('camx_kv.20000825.hgbpa_04km.TCEQuh1_eta.v43.tke',rows=65,cols=83))
"""
file_type = str(type(f)).split("'")[1]
formats = defaultdict(lambda: "%s", float64 = "%%.%de" % (double_precision,), \
float32 = "%%.%de" % (float_precision,), \
int32 = "%i", \
uint32 = "%i", \
int64 = "%i", \
str = "%s", \
bool = "%s", \
string8 = "'%s'")
float_fmt = "%%.%df" % (float_precision,)
int_fmt = "%i"
# initialize indentation as 8 characters
# based on ncdump
indent = 8*" "
if isgroup:
startindent = 4*" "
else:
startindent = 4*""
# First line of CDL
if not isgroup: outfile.write("%s %s {\n" % (file_type, name,))
###########################
# CDL Section 1: dimensions
###########################
outfile.write(startindent + "dimensions:\n")
for dim_name, dim in f.dimensions.items():
if dim.isunlimited():
outfile.write(startindent + 1*indent+("%s = UNLIMITED // (%s currently) \n" % (dim_name,len(dim))))
else:
outfile.write(startindent + 1*indent+("%s = %s ;\n" % (dim_name,len(dim))))
###################################
# CDL Section 2: variables metadata
###################################
if len(f.variables.keys()) > 0:
outfile.write("\n" + startindent + "variables:\n")
for var_name, var in f.variables.items():
var_type = dict(float32='float', \
float64='double', \
int32='integer', \
uint32='integer', \
int64='long', \
bool='bool', \
string8='char', \
string80='char').get(var.dtype.name, var.dtype.name)
outfile.write(startindent + 1*indent+("%s %s%s;\n" % (var_type, var_name,str(var.dimensions).replace('u\'', '').replace('\'','').replace(',)',')'))))
for prop_name in var.ncattrs():
prop = getattr(var, prop_name)
outfile.write(startindent + 2*indent+("%s:%s = %s ;\n" % (var_name,prop_name,repr(prop).replace("'", '"'))))
################################
# CDL Section 3: global metadata
################################
outfile.write("\n\n// global properties:\n")
for prop_name in f.ncattrs():
prop = getattr(f, prop_name)
outfile.write(startindent + 2*indent+(":%s = %s ;\n" % (prop_name, repr(prop).replace("'",'"'))))
if hasattr(f, 'groups'):
for group_name, group in f.groups.items():
outfile.write(startindent + 'group %s:\n' % group_name)
pncdump(group, name = name, header = header, variables = variables, line_length = line_length, full_indices = full_indices, float_precision = float_precision, double_precision = double_precision, isgroup = True)
if not header:
# Error trapping prevents the user from getting an error
# when they cancel a dump or when they break a redirected
# pipe
try:
#####################
# CDL Section 4: data
#####################
outfile.write("\n\n" + startindent + "data:\n")
# data indentation is only 1 space
indent = " "
# Subset variables for output
display_variables = [var_name for var_name in f.variables.keys() if var_name in variables or variables == []]
if variables != []:
if len(variables) < len(display_variables):
warn("Not all specified variables were available")
# For each variable output data
# currently assumes 3-D data
for var_name in display_variables:
var = f.variables[var_name]
if isinstance(var, PseudoNetCDFMaskedVariable) or hasattr(var, '_FillValue'):
def writer(row, last):
if isscalar(row) or row.ndim == 0:
outfile.write(startindent + ' ' + str(row.filled().astype(ndarray)))
return
tmpstr = StringIO(bytes('', 'utf-8'))
if ma.getmaskarray(row).all():
tmpstr.write(', '.join(['_'] * row.size) + ', ')
else:
savetxt(tmpstr, ma.filled(row), fmt, delimiter = ', ', newline =', ')
if last:
tmpstr.seek(-2, 1)
tmpstr.write(b';')
tmpstr.seek(0, 0)
tmpstr = tmpstr.read()
tmpstr = tmpstr.replace(bytes(fmt % getattr(row, 'fill_value', 0) + ',', 'utf-8'), bytes('_,', 'utf-8'))
outfile.write(textwrap.fill(tmpstr.decode('utf-8'), line_length, initial_indent = startindent + ' ', subsequent_indent = startindent + ' '))
outfile.write('\n')
else:
def writer(row, last):
if isscalar(row) or row.ndim == 0:
outfile.write(startindent + ' ' + str(row.astype(ndarray)))
return
tmpstr = StringIO(bytes('', 'utf-8'))
savetxt(tmpstr, row, fmt, delimiter = ', ', newline =', ')
if last:
tmpstr.seek(-2, 1)
tmpstr.write(';')
tmpstr.seek(0, 0)
outfile.write(textwrap.fill(tmpstr.read().decode('utf-8'), line_length, initial_indent = startindent + ' ', subsequent_indent = startindent + ' '))
outfile.write('\n')
outfile.write(startindent + 1*indent+("%s =\n" % var_name))
if var_name in ('time', 'time_bounds') and timestring:
from PseudoNetCDF.coordutil import gettimes, gettimebnds
if var_name == 'time':
times = gettimes(f)
elif var_name == 'time_bounds':
times = gettimebnds(f)
for i in ndindex(var.shape):
val = var[i]
if ma.is_masked(val):
array_str = '_'
else:
array_str = startindent + 2*indent + str(val)
if i == tuple(map(lambda x_: x_ - 1, var.shape)):
array_str += ";"
else:
array_str += ","
array_str += " // %s%s %s \n" % (var_name, i, str(times[i]))
try:
outfile.write(array_str)
except IOError:
outfile.close()
exit()
elif full_indices is not None:
id_display = {'f': lambda idx: str(tuple([idx[i]+1 for i in range(len(idx)-1,-1,-1)])), \
'c': lambda idx: str(idx)}[full_indices]
#for i, val in ndenumerate(var):
for i in ndindex(var.shape):
val = var[i]
if ma.is_masked(val):
array_str = '_'
else:
fmt = startindent + 2*indent+formats[var.dtype.name]
array_str = fmt % val
if i == tuple(map(lambda x_: x_ - 1, var.shape)):
array_str += ";"
else:
array_str += ","
array_str += " // %s%s \n" % (var_name, id_display(i))
try:
outfile.write(array_str)
except IOError:
outfile.close()
exit()
else:
dimensions = [len(f.dimensions[d]) for d in var.dimensions]
if len(dimensions) > 1:
first_dim = prod(dimensions[:-1])
second_dim = dimensions[-1]
shape = [first_dim, second_dim]
else:
shape = [1]+dimensions
var2d = var[...].reshape(*shape)
fmt = ', '.join(shape[-1] * [formats[var.dtype.name]])
fmt = formats[var.dtype.name]
lastrow = var2d.shape[0] - 1
for rowi, row in enumerate(var2d):
try:
writer(row, rowi == lastrow)
except IOError as e:
warn(repr(e) + "; Typically from CTRL+C or exiting less")
exit()
except KeyboardInterrupt:
outfile.flush()
exit()
outfile.write("}\n")
return outfile
