def trends(ident, levels=None, outputdir=None, verbose=0):
"""
Parameters
----------
ident
levels
outputdir
verbose
Returns
-------
"""
from raso import load_radiosonde
from raso.config import outdir
import matplotlib.pyplot as plt
yplevs = [1000, 3000, 7000, 12500, 17500, 22500, 30000, 40000, 50000, 60000, 85000, 92500] # Pressure Levels, Ticks
isonde = load_radiosonde(ident, variables=[])
if outputdir is None:
outputdir = outdir + '/figures'
#
# DATA
#
if levels is None:
levels = [10000, 30000, 50000, 60000, 70000, 85000, 92500]
if 'detect_opts' not in isonde.attrs:
print "No Detection Options found ?", ident
return
for icor, iopts in isonde.detect_opts.items():
iname = iopts['savename']
isonde.load_data(iname)
ivar = iopts['variable']
idata = getattr(isonde, iname)
daynight = iopts.get('daynight', False)
#
# Profile
#
varis = [ivar, '%s_mcor' % ivar, '%s_qcor' % ivar, '%s_qecor' % ivar, '%s_era_adj' % ivar, '%s_era' % ivar]
varnames = ['U', 'M', 'Q', 'QE', 'EA', 'E']
# Period 1979 - 2015 (32y)
if daynight:
ax, lgd = _trend_plotter(idata[varis, idata.major_axis.hour == 12, :], slice('1979', '2015'), varis, yplevs,
varnames)
plt.savefig('%s/%s_%s_%s_trends_12Z_79-15.pdf' % (outputdir, ident, iname, ivar), bbox_extra_artists=(lgd,),
bbox_inches='tight')
print_verbose('%s/%s_%s_%s_trends_12Z_79-15.pdf' % (outputdir, ident, iname, ivar), verbose)
ax, lgd = _trend_plotter(idata[varis, idata.major_axis.hour == 0, :], slice('1979', '2015'), varis, yplevs,
varnames)
plt.savefig('%s/%s_%s_%s_trends_00Z_79-15.pdf' % (outputdir, ident, iname, ivar), bbox_extra_artists=(lgd,),
bbox_inches='tight')
print_verbose('%s/%s_%s_%s_trends_00Z_79-15.pdf' % (outputdir, ident, iname, ivar), verbose)
else:
ax, lgd = _trend_plotter(idata[varis], slice('1979', '2015'), varis, yplevs, varnames)
plt.savefig('%s/%s_%s_%s_trends_79-15.pdf' % (outputdir, ident, iname, ivar), bbox_extra_artists=(lgd,),
bbox_inches='tight')
print_verbose('%s/%s_%s_%s_trends_79-15.pdf' % (outputdir, ident, iname, ivar), verbose)
# Period 1990 - 2015 (15y)
if daynight:
ax, lgd = _trend_plotter(idata[varis, idata.major_axis.hour == 12, :], slice('1990', '2015'), varis, yplevs,
varnames)
plt.savefig('%s/%s_%s_%s_trends_12Z_90-15.pdf' % (outputdir, ident, iname, ivar), bbox_extra_artists=(lgd,),
bbox_inches='tight')
print_verbose('%s/%s_%s_%s_trends_12Z_90-15.pdf' % (outputdir, ident, iname, ivar), verbose)
ax, lgd = _trend_plotter(idata[varis, idata.major_axis.hour == 0, :], slice('1990', '2015'), varis, yplevs,
varnames)
plt.savefig('%s/%s_%s_%s_trends_00Z_90-15.pdf' % (outputdir, ident, iname, ivar), bbox_extra_artists=(lgd,),
bbox_inches='tight')
print_verbose('%s/%s_%s_%s_trends_00Z_90-15.pdf' % (outputdir, ident, iname, ivar), verbose)
else:
ax, lgd = _trend_plotter(idata[varis], slice('1990', '2015'), varis, yplevs, varnames)
plt.savefig('%s/%s_%s_%s_trends_79-15.pdf' % (outputdir, ident, iname, ivar), bbox_extra_artists=(lgd,),
bbox_inches='tight')
print_verbose('%s/%s_%s_%s_trends_90-15.pdf' % (outputdir, ident, iname, ivar), verbose)
# Period 1980 - 2000 (20y)
if daynight:
ax, lgd = _trend_plotter(idata[varis, idata.major_axis.hour == 12, :], slice('1980', '2000'), varis, yplevs,
varnames)
plt.savefig('%s/%s_%s_%s_trends_12Z_80-00.pdf' % (outputdir, ident, iname, ivar), bbox_extra_artists=(lgd,),
bbox_inches='tight')
print_verbose('%s/%s_%s_%s_trends_12Z_80-00.pdf' % (outputdir, ident, iname, ivar), verbose)
ax, lgd = _trend_plotter(idata[varis, idata.major_axis.hour == 0, :], slice('1980', '2000'), varis, yplevs,
varnames)
plt.savefig('%s/%s_%s_%s_trends_00Z_80-00.pdf' % (outputdir, ident, iname, ivar), bbox_extra_artists=(lgd,),
bbox_inches='tight')
print_verbose('%s/%s_%s_%s_trends_00Z_80-00.pdf' % (outputdir, ident, iname, ivar), verbose)
else:
ax, lgd = _trend_plotter(idata[varis], slice('1980', '2000'), varis, yplevs, varnames)
plt.savefig('%s/%s_%s_%s_trends_80-00.pdf' % (outputdir, ident, iname, ivar), bbox_extra_artists=(lgd,),
bbox_inches='tight')
print_verbose('%s/%s_%s_%s_trends_80-00.pdf' % (outputdir, ident, iname, ivar), verbose)
# Period 1975 - 2015 (30y)
if daynight:
ax, lgd = _trend_plotter(idata[varis, idata.major_axis.hour == 12, :], slice('1985', '2015'), varis, yplevs,
varnames)
plt.savefig('%s/%s_%s_%s_trends_12Z_85-15.pdf' % (outputdir, ident, iname, ivar), bbox_extra_artists=(lgd,),
bbox_inches='tight')
print_verbose('%s/%s_%s_%s_trends_12Z_85-15.pdf' % (outputdir, ident, iname, ivar), verbose)
ax, lgd = _trend_plotter(idata[varis, idata.major_axis.hour == 0, :], slice('1985', '2015'), varis, yplevs,
varnames)
plt.savefig('%s/%s_%s_%s_trends_00Z_85-15.pdf' % (outputdir, ident, iname, ivar), bbox_extra_artists=(lgd,),
bbox_inches='tight')
print_verbose('%s/%s_%s_%s_trends_00Z_85-15.pdf' % (outputdir, ident, iname, ivar), verbose)
else:
ax, lgd = _trend_plotter(idata[varis], slice('1985', '2015'), varis, yplevs, varnames)
plt.savefig('%s/%s_%s_%s_trends_85-15.pdf' % (outputdir, ident, iname, ivar), bbox_extra_artists=(lgd,),
bbox_inches='tight')
print_verbose('%s/%s_%s_%s_trends_85-15.pdf' % (outputdir, ident, iname, ivar), verbose)
plt.close('all')
#
# LEVEL
#
for ilev in levels:
if daynight:
fig, ax = plt.subplots(len(varis), 1, figsize=(12, len(varis)), sharex=True, sharey=True)
ym = int(idata[ivar, idata.major_axis.hour == 12, ilev].mean())
for j, jvar in enumerate(varis):
if jvar in idata.items:
ax[j] = timeseries_line_trend(idata[:, idata.major_axis.hour == 12, :], jvar,
'%s_dep_snht' % ivar, ilev, '%s [K]' % varnames[j], ax=ax[j],
plabel=ym + 4, ylim=(ym - 5, ym + 5), window=365,
label=varnames[j])
ax[j].grid(True)
# lgd = ax.legend(bbox_to_anchor=(1.1, 1), loc='upper left', fontsize=10)
ax[j].set_xlim('1979', '2016')
ax[-1].set_xlabel('Time (RM:365)')
plt.savefig('%s/%s_%s_%s_trends_12Z_%04d.pdf' % (outputdir, ident, iname, ivar, ilev / 100)) #, bbox_extra_artists=(lgd,), bbox_inches='tight')
print_verbose('%s/%s_%s_%s_trends_12Z_%04d.pdf' % (outputdir, ident, iname, ivar, ilev / 100), verbose)
plt.close()
#
fig, ax = plt.subplots(1, 1, figsize=(12, 4))
ym = int(idata[ivar, idata.major_axis.hour == 0, ilev].mean())
for j, jvar in enumerate(varis):
if jvar in idata.items:
ax = timeseries_line_trend(idata[:, idata.major_axis.hour == 0, :], jvar,
'%s_dep_snht' % ivar, ilev, '%s [K]' % ivar, ax=ax,
plabel=ym + 4, ylim=(ym - 5, ym + 5), window=365,
label=varnames[j])
ax.grid(True)
lgd = ax.legend(bbox_to_anchor=(1.1, 1), loc='upper left', fontsize=10)
ax.set_xlim('1979', '2016')
ax.set_xlabel('Time (RM:365)')
plt.savefig('%s/%s_%s_%s_trends_00Z_%04d.pdf' % (outputdir, ident, iname, ivar, ilev / 100),
bbox_extra_artists=(lgd,), bbox_inches='tight')
print_verbose('%s/%s_%s_%s_trends_12Z_%04d.pdf' % (outputdir, ident, iname, ivar, ilev / 100), verbose)
plt.close()
else:
fig, ax = plt.subplots(1, 1, figsize=(12, 4))
ym = int(idata[ivar, :, ilev].mean())
for j, jvar in enumerate(varis):
if jvar in idata.items:
ax = timeseries_line_trend(idata, jvar, '%s_dep_snht' % ivar, ilev, '%s [K]' % ivar,
ax=ax, plabel=ym + 4, ylim=(ym - 5, ym + 5), window=730,
label=varnames[j])
ax.grid(True)
lgd = ax.legend(bbox_to_anchor=(1.1, 1), loc='upper left', fontsize=10)
ax.set_xlim('1979', '2016')
ax.set_xlabel('Time (RM:730)')
plt.savefig('%s/%s_%s_%s_trends_%04d.pdf' % (outputdir, ident, iname, ivar, ilev / 100),
bbox_extra_artists=(lgd,), bbox_inches='tight')
print_verbose('%s/%s_%s_%s_trends_%04d.pdf' % (outputdir, ident, iname, ivar, ilev / 100), verbose)
plt.close()
plt.close('all')
def corrections(ident, levels=None, outputdir=None, verbose=0):
"""
Parameters
----------
ident
levels
outputdir
verbose
Returns
-------
"""
from raso import load_radiosonde
from raso.config import outdir
import matplotlib.pyplot as plt
yplevs = [1000, 3000, 7000, 12500, 17500, 22500, 30000, 40000, 50000, 60000, 85000, 92500] # Pressure Levels, Ticks
isonde = load_radiosonde(ident, variables=[])
if outputdir is None:
outputdir = outdir + '/figures'
#
# DATA
#
if 'detect_opts' not in isonde.attrs:
print "No Detection Options found ?", ident
return
if levels is None:
levels = [10000, 30000, 50000, 60000, 70000, 85000, 92500]
for icor, iopts in isonde.detect_opts.items():
iname = iopts['savename']
isonde.load_data(iname)
ithres = iopts['thres']
ivar = iopts['variable']
idata = getattr(isonde, iname)
daynight = iopts.get('daynight', False)
#
# CONTOUR
#
for j, jvar in enumerate(['%s_mcor' % ivar, '%s_qcor' % ivar, '%s_qecor' % ivar]):
if jvar not in idata.items:
continue
if daynight:
timeseries_var(idata[:, idata.major_axis.hour == 12, :], jvar, freq='M', yticklabels=yplevs)
plt.savefig("%s/%s_%s_%s_12Z.pdf" % (outputdir, ident, iname, jvar))
print_verbose("%s/%s_%s_%s_12Z.pdf" % (outputdir, ident, iname, jvar), verbose)
timeseries_anomaly(idata[:, idata.major_axis.hour == 12, :], jvar, '%s_era' % ivar, freq='M',
yticklabels=yplevs)
plt.savefig("%s/%s_%s_%s_dep_12Z.pdf" % (outputdir, ident, iname, jvar))
print_verbose("%s/%s_%s_%s_dep_12Z.pdf" % (outputdir, ident, iname, jvar), verbose)
timeseries_var(idata[:, idata.major_axis.hour == 0, :], jvar, freq='M', yticklabels=yplevs)
plt.savefig("%s/%s_%s_%s_00Z.pdf" % (outputdir, ident, iname, jvar))
print_verbose("%s/%s_%s_%s_00Z.pdf" % (outputdir, ident, iname, jvar), verbose)
timeseries_anomaly(idata[:, idata.major_axis.hour == 0, :], jvar, '%s_era' % ivar, freq='M',
yticklabels=yplevs)
plt.savefig("%s/%s_%s_%s_dep_00Z.pdf" % (outputdir, ident, iname, jvar))
print_verbose("%s/%s_%s_%s_dep_00Z.pdf" % (outputdir, ident, iname, jvar), verbose)
else:
timeseries_var(idata, jvar, freq='M', yticklabels=yplevs)
plt.savefig("%s/%s_%s_%s.pdf" % (outputdir, ident, iname, jvar))
print_verbose("%s/%s_%s_%s.pdf" % (outputdir, ident, iname, jvar), verbose)
timeseries_anomaly(idata, jvar, '%s_era' % ivar, freq='M', yticklabels=yplevs)
plt.savefig("%s/%s_%s_%s_dep.pdf" % (outputdir, ident, iname, jvar))
print_verbose("%s/%s_%s_%s_dep.pdf" % (outputdir, ident, iname, jvar), verbose)
#
# LEVEL
#
for ilev in levels:
if daynight:
fig, ax = plt.subplots(3, 1, figsize=(12, 6), sharex=True, sharey=True)
varnames = ['M', 'Q', 'QE']
ym = int(idata["%s_dep" % ivar, idata.major_axis.hour == 12, ilev].mean())
for j, jvar in enumerate(['%s_mcor' % ivar, '%s_qcor' % ivar, '%s_qecor' % ivar]):
if jvar not in idata.items:
continue
timeseries_line_correction(idata[:, idata.major_axis.hour == 12, :], jvar,
'%s_dep_snht' % ivar, ilev, '%s dep [K]' % ivar,
breaks='%s_dep_breaks' % ivar, ax=ax[j],
departures='%s_era' % ivar, ylim=(ym - 5, ym + 5),
force_snht=True, post_snht=True, plabel=None)
idata['%s_dep' % ivar, idata.major_axis.hour == 12, ilev].resample('12h').mean().rolling(window=60,
min_periods=1).mean().plot(
ax=ax[j], color='gray', zorder=1)
ax[j].set_xlim('1979', '2016')
ax[j].set_ylabel(varnames[j] + ' dep (ERA) [K]')
ax[j].grid(True)
ax[0].set_title('Corrections at %d hPa 12Z' % (ilev / 100))
ax[-1].set_xlabel('Time (RM:60)')
plt.savefig('%s/%s_%s_%s_corr_12Z_%04d.pdf' % (outputdir, ident, iname, ivar, (ilev / 100)))
print_verbose('%s/%s_%s_%s_corr_12Z_%04d.pdf' % (outputdir, ident, iname, ivar, (ilev / 100)), verbose)
fig, ax = plt.subplots(3, 1, figsize=(12, 6), sharex=True, sharey=True)
ym = int(idata["%s_dep" % ivar, idata.major_axis.hour == 0, ilev].mean())
for j, jvar in enumerate(['%s_mcor' % ivar, '%s_qcor' % ivar, '%s_qecor' % ivar]):
if jvar not in idata.items:
continue
timeseries_line_correction(idata[:, idata.major_axis.hour == 0, :], jvar,
'%s_dep_snht' % ivar, ilev, '%s dep [K]' % ivar,
breaks='%s_dep_breaks' % ivar, ax=ax[j],
departures='%s_era' % ivar, ylim=(ym - 5, ym + 5),
force_snht=True, post_snht=True, plabel=None)
idata['%s_dep' % ivar, idata.major_axis.hour == 0, ilev].resample('12h').mean().rolling(window=60,
min_periods=1).mean().plot(
ax=ax[j], color='gray', zorder=1)
ax[j].set_xlim('1979', '2016')
ax[j].set_ylabel(varnames[j] + ' dep (ERA) [K]')
ax[j].grid(True)
ax[0].set_title('Corrections at %d hPa 00Z' % (ilev / 100))
ax[-1].set_xlabel('Time (RM:60)')
plt.savefig('%s/%s_%s_%s_corr_00Z_%04d.pdf' % (outputdir, ident, iname, ivar, (ilev / 100)))
print_verbose('%s/%s_%s_%s_corr_00Z_%04d.pdf' % (outputdir, ident, iname, ivar, (ilev / 100)), verbose)
else:
fig, ax = plt.subplots(3, 1, figsize=(12, 6), sharex=True, sharey=True)
varnames = ['M', 'Q', 'QE']
ym = int(idata["%s_dep" % ivar, :, ilev].mean())
for j, jvar in enumerate(['%s_mcor' % ivar, '%s_qcor' % ivar, '%s_qecor' % ivar]):
if jvar not in idata.items:
continue
timeseries_line_correction(idata, jvar, '%s_dep_snht' % ivar, ilev, '%s dep [K]' % ivar,
breaks='%s_dep_breaks' % ivar, ax=ax[j],
departures='%s_era' % ivar, ylim=(ym - 5, ym + 5),
force_snht=True, post_snht=True, plabel=None)
idata['%s_dep' % ivar, :, ilev].resample('12h').mean().rolling(window=60,
min_periods=1).mean().plot(ax=ax[j],
color='gray',
zorder=1)
ax[j].set_xlim('1979', '2016')
ax[j].set_ylabel(varnames[j] + ' dep (ERA) [K]')
ax[j].grid(True)
ax[0].set_title('Corrections at %d hPa' % (ilev / 100))
ax[-1].set_xlabel('Time (RM:60)')
plt.savefig('%s/%s_%s_%s_corr_%04d.pdf' % (outputdir, ident, iname, ivar, (ilev / 100)))
print_verbose('%s/%s_%s_%s_corr_%04d.pdf' % (outputdir, ident, iname, ivar, (ilev / 100)), verbose)
plt.close('all')
def data(ident, outputdir=None, verbose=0):
""" Automated Data count plots
Parameters
----------
ident
outputdir
verbose
Returns
-------
"""
from raso import load_radiosonde
from raso.config import outdir
import matplotlib.pyplot as plt
yplevs = [1000, 3000, 7000, 12500, 17500, 22500, 30000, 40000, 50000, 60000, 85000, 92500] # Pressure Levels, Ticks
isonde = load_radiosonde(ident, variables=['igra', 'data', 'std_data'])
if outputdir is None:
outputdir = outdir + '/figures'
#
# DATA
#
if 'data' in isonde.vars:
varis = ['t', 'r']
if isonde.data.columns.isin(varis).sum() == len(varis):
dates = pd.Series(1, index=pd.DatetimeIndex(
isonde.data[varis].dropna().index.unique())) # events with t,r variables
else:
varis = isonde.data.columns.tolist()
dates = pd.Series(1, index=pd.DatetimeIndex(isonde.data.index.unique())) # events with all variables
events = dates.groupby(dates.index.to_period(freq='M')).count() # events per month
events.plot(grid=True, kind='area')
plt.title("Radiosonde %s (DATA), Sounding Events (%s)" % (isonde.id, ",".join(varis)))
plt.xlabel("Month")
plt.ylabel("Soundings per Month [#]")
plt.savefig('%s/%s_data_counts.pdf' % (outputdir, ident))
print_verbose('%s/%s_data_counts.pdf' % (outputdir, ident), verbose)
plt.close()
#
# IGRA
#
if 'igra' in isonde.vars:
varis = ['t', 'dpd']
if isonde.igra.columns.isin(varis).sum() == len(varis):
dates = pd.Series(1, index=pd.DatetimeIndex(
isonde.igra[varis].dropna().index.unique())) # events with t,r variables
else:
varis = isonde.igra.columns.tolist()
dates = pd.Series(1, index=pd.DatetimeIndex(isonde.igra.index.unique())) # events with all variables
events = dates.groupby(dates.index.to_period(freq='M')).count() # events per month
events.plot(grid=True, kind='area')
plt.title("Radiosonde %s (IGRA), Sounding Events (%s)" % (isonde.id, ",".join(varis)))
plt.xlabel("Month")
plt.ylabel("Soundings per Month [#]")
plt.savefig('%s/%s_igra_counts.pdf' % (outputdir, ident))
print_verbose('%s/%s_igra_counts.pdf' % (outputdir, ident), verbose)
plt.close()
#
# STD DATA
#
if 'std_data' in isonde.vars:
varis = ['t', 'r']
if isonde.std_data.columns.isin(varis).sum() == len(varis):
dates = pd.Series(1, index=pd.DatetimeIndex(
isonde.std_data[varis].dropna().index.unique())) # events with t,r variables
else:
varis = isonde.std_data.columns.tolist()
dates = pd.Series(1, index=pd.DatetimeIndex(isonde.std_data.index.unique())) # events with all variables
events = dates.groupby(dates.index.to_period(freq='M')).count() # events per month
events.plot(grid=True, kind='area')
plt.title("Radiosonde %s (STDDATA), Sounding Events (%s)" % (isonde.id, ",".join(varis)))
plt.xlabel("Month")
plt.ylabel("Soundings per Month [#]")
plt.savefig('%s/%s_std_data_counts.pdf' % (outputdir, ident))
plt.close()
#
for ivar in isonde.std_data.columns.tolist():
if ivar in ['p', 'u', 'v', 'qual']:
continue
timeseries_var(isonde.std_data, ivar, freq='M', title='RASO %s' % isonde.id, yticklabels=yplevs)
plt.savefig("%s/%s_%s_contour.pdf" % (outputdir, ident, ivar))
plt.close()
plt.close('all')
def breakpoints(ident, levels=None, outputdir=None, verbose=0):
"""
Parameters
----------
ident
levels
outputdir
verbose
Returns
-------
"""
from raso import load_radiosonde
from raso.config import outdir
import matplotlib.pyplot as plt
isonde = load_radiosonde(ident, variables=[])
if outputdir is None:
outputdir = outdir + '/figures'
#
# DATA
#
if 'detect_opts' not in isonde.attrs:
print "No Detection Options found ?", ident
return
if levels is None:
levels = [10000, 30000, 50000, 60000, 70000, 85000, 92500]
for icor, iopts in isonde.detect_opts.items():
iname = iopts['savename']
isonde.load_data(iname)
ithres = iopts['thres']
ivar = iopts['variable']
idata = getattr(isonde, iname)
daynight = iopts.get('daynight', False)
#
# LEVEL
#
for ilev in levels:
if daynight:
ym = int(idata[ivar, idata.major_axis.hour == 12, ilev].mean())
breakpoint_timeseries(idata[:, idata.major_axis.hour == 12, :], ivar, p=ilev, post_snht=True,
window=365, min_periods=1, ylim=(ym - 5, ym + 5))
plt.savefig("%s/%s_%s_%s_12Z_breakstat_%04d.pdf" % (outputdir, ident, iname, ivar, ilev / 100))
print_verbose("%s/%s_%s_%s_12Z_breakstat_%04d.pdf" % (outputdir, ident, iname, ivar, ilev / 100),
verbose)
ym = int(idata[ivar, idata.major_axis.hour == 0, ilev].mean())
breakpoint_timeseries(idata[:, idata.major_axis.hour == 0, :], ivar, p=ilev, post_snht=True,
window=365, min_periods=1, ylim=(ym - 5, ym + 5))
plt.savefig("%s/%s_%s_%s_00Z_breakstat_%04d.pdf" % (outputdir, ident, iname, ivar, ilev / 100))
print_verbose("%s/%s_%s_%s_00Z_breakstat_%04d.pdf" % (outputdir, ident, iname, ivar, ilev / 100),
verbose)
else:
ym = int(idata[ivar, :, ilev].mean())
breakpoint_timeseries(idata, ivar, p=ilev, post_snht=True, window=730, min_periods=1,
ylim=(ym - 5, ym + 5))
plt.savefig("%s/%s_%s_%s_breakstat_%04d.pdf" % (outputdir, ident, iname, ivar, ilev / 100))
print_verbose("%s/%s_%s_%s_breakstat_%04d.pdf" % (outputdir, ident, iname, ivar, ilev / 100), verbose)
plt.close('all')
def snht(ident, levels=None, outputdir=None, verbose=0):
"""
Parameters
----------
ident
levels
outputdir
verbose
Returns
-------
"""
from raso import load_radiosonde
from raso.config import outdir
import matplotlib.pyplot as plt
yplevs = [1000, 3000, 7000, 12500, 17500, 22500, 30000, 40000, 50000, 60000, 85000, 92500] # Pressure Levels, Ticks
isonde = load_radiosonde(ident, variables=[])
if outputdir is None:
outputdir = outdir + '/figures'
#
# DATA
#
if 'detect_opts' not in isonde.attrs:
print "No Detection Options found ?", ident
return
if levels is None:
levels = [10000, 30000, 50000, 60000, 70000, 85000, 92500]
for icor, iopts in isonde.detect_opts.items():
iname = iopts['savename']
isonde.load_data(iname)
ithres = iopts['thres']
ivar = iopts['variable']
idata = getattr(isonde, iname)
daynight = iopts.get('daynight', False)
#
# CONTOUR
#
if daynight:
timeseries_snht(idata[:, idata.major_axis.hour == 12, :], '%s_dep' % ivar,
levels=list(ithres * np.array([1, 2, 5, 10, 20])), yticklabels=yplevs)
plt.savefig("%s/%s_%s_%s_12Z_snht.pdf" % (outputdir, ident, iname, ivar))
print_verbose("%s/%s_%s_%s_12Z_snht.pdf" % (outputdir, ident, iname, ivar), verbose)
timeseries_snht(idata[:, idata.major_axis.hour == 0, :], '%s_dep' % ivar,
levels=list(ithres * np.array([1, 2, 5, 10, 20])), yticklabels=yplevs)
plt.savefig("%s/%s_%s_%s_00Z_snht.pdf" % (outputdir, ident, iname, ivar))
print_verbose("%s/%s_%s_%s_00Z_snht.pdf" % (outputdir, ident, iname, ivar), verbose)
else:
timeseries_snht(idata, '%s_dep' % ivar, levels=list(ithres * np.array([1, 2, 5, 10, 20])),
yticklabels=yplevs)
plt.savefig("%s/%s_%s_%s_snht.pdf" % (outputdir, ident, iname, ivar))
print_verbose("%s/%s_%s_%s_snht.pdf" % (outputdir, ident, iname, ivar), verbose)
#
# LEVEL
#
for ilev in levels:
fig, ax = plt.subplots(1, 1, figsize=(12, 2))
if daynight:
timeseries_line_snht(idata[:, idata.major_axis.hour == 12, :], '%s_dep' % ivar,
'%s_dep_snht' % ivar, ilev, '%s dep (12Z) [K]' % ivar,
breaks='%s_dep_breaks' % ivar, ax=ax, ylim=(-10, 10))
ax.set_xlabel('Time (RM:60)')
plt.savefig('%s/%s_%s_%s_12Z_snht_%04d.pdf' % (outputdir, ident, iname, ivar, (ilev / 100)))
print_verbose('%s/%s_%s_%s_12Z_snht_%04d.pdf' % (outputdir, ident, iname, ivar, (ilev / 100)), verbose)
timeseries_line_snht(idata[:, idata.major_axis.hour == 0, :], '%s_dep' % ivar,
'%s_dep_snht' % ivar, ilev, '%s dep (00Z) [K]' % ivar,
breaks='%s_dep_breaks' % ivar, ax=ax, ylim=(-10, 10))
ax.set_xlabel('Time (RM:60)')
plt.savefig('%s/%s_%s_%s_00Z_snht_%04d.pdf' % (outputdir, ident, iname, ivar, (ilev / 100)))
print_verbose('%s/%s_%s_%s_00Z_snht_%04d.pdf' % (outputdir, ident, iname, ivar, (ilev / 100)), verbose)
else:
timeseries_line_snht(idata, '%s_dep' % ivar, '%s_dep_snht' % ivar, ilev, '%s dep [K]' % ivar,
breaks='%s_dep_breaks' % ivar, ax=ax, ylim=(-10, 10))
ax.set_xlabel('Time (RM:60)')
plt.savefig('%s/%s_%s_%s_snht_%04d.pdf' % (outputdir, ident, iname, ivar, (ilev / 100)))
print_verbose('%s/%s_%s_%s_snht_%04d.pdf' % (outputdir, ident, iname, ivar, (ilev / 100)), verbose)
plt.close('all')
