def plot_val_table(fsp, func, freq, quantile, stationlist):
#
freq = climpy.check_freq(freq)
if freq == _c.FR_MTH:
(periodtype, periodnames) = ("monthly", hdf5io.monthenum._names.keys())
periodnames = ['Dec', 'Jan', 'Feb', 'Mar', 'Apr', 'May',
'Jun', 'Jul', 'Aug', 'Sep', 'Oct', 'Nov']
elif (freq // _c.FR_QTR == 1):
(periodtype, periodnames) = ("quarterly", fqtr2names[freq])
else:
raise NotImplementedError, "Unrecognized frequency %s" % freq
#
funcdict = dict(med='median',
mean='mean',
)
funcname = funcdict[func]
qtlname = '%03i' % (100 * quantile)
qtlleg = {'000':'Minimum',
'025':'Lower Quartile'}['%03i' % (100 * quantile)]
#
freq = climpy.check_freq(freq)
if freq == _c.FR_MTH:
(periodtype, periodnames) = ("monthly", hdf5io.monthenum._names.keys())
periodnames = ['Dec', 'Jan', 'Feb', 'Mar', 'Apr', 'May',
'Jun', 'Jul', 'Aug', 'Sep', 'Oct', 'Nov']
elif (freq // _c.FR_QTR == 1):
(periodtype, periodnames) = ("quarterly", fqtr2names[freq])
else:
raise NotImplementedError, "Unrecognized frequency %s" % freq
#
#
flow_basename = "USGS_Q%s_%s%s.hdf5" % (qtlname, fqname, func)
# Define the HDF5 files ....................................
hdf5flow_filename = os.path.join(hdf5_archive_dir, flow_basename)
file = hdf5io.openFile(hdf5flow_filename, 'r+')
hdf5flow = hdf5io.remove_duplicates(file)
#
val = hdf5flow.getNode("/".join(['', 'values', 'modified', 'noenso'])).read()
for (marker, color, station) in zip(['o'] * 3 + ['s'] * 4,
['k'] * 3 + ['r'] * 4,
stationlist):
locval = val[val['id'] == station]
fsp.plot(range(12), [locval[p] for p in periodnames],
marker=marker, label=station, c=color)
fsp.set_yscale('log')
fsp.xaxis.set_major_locator(pylab.MultipleLocator(1))
fsp.set_xticklabels(periodnames)
fsp.set_ylabel("Flows (cfs)", fontweight='bold')
fsp.set_title("%s flows - %s" % (qtlleg, funcname), fontweight='bold')
pylab.show()
def plot_val(fsp, station, func, quantile, group='modified'):
#
freq = _c.FR_MTH
freq = climpy.check_freq(freq)
if freq == _c.FR_MTH:
# (periodtype, periodnames) = ("monthly", hdf5io.monthenum._names.keys())
periodnames = ['Dec', 'Jan', 'Feb', 'Mar', 'Apr', 'May',
'Jun', 'Jul', 'Aug', 'Sep', 'Oct', 'Nov']
elif (freq // _c.FR_QTR == 1):
(periodtype, periodnames) = ("quarterly", fqtr2names[freq])
else:
raise NotImplementedError, "Unrecognized frequency %s" % freq
#
funcdict = dict(med='median',
mean='mean',
)
funcname = funcdict[func]
qtlname = '%03i' % (100 * quantile)
qtlleg = {'000':'Minimum',
'025':'Lower Quartile'}['%03i' % (100 * quantile)]
#
#
flow_basename = "USGS_Q%s_%s%s.hdf5" % (qtlname, fqname, func)
# Define the HDF5 files ....................................
hdf5flow_filename = os.path.join(hdf5_archive_dir, flow_basename)
file = hdf5io.openFile(hdf5flow_filename, 'r+')
hdf5flow = hdf5io.remove_duplicates(file)
#
if fsp.is_first_col():
labels = {'G':u"Global",
'C':u"La Ni\xf1a",
'N':u"Neutral",
'W':u"El Ni\xf1o",
'NS':"N/S",
'90': '_nolabel_',
'95': '_nolabel_',
'99': '_nolabel_'}
else:
labels = {'G':'_nolabel_',
'C':'_nolabel_',
'N':'_nolabel_',
'W':'_nolabel_',
'NS':"N/S",
'90': "90%",
'95': "95%",
'99': "99%"}
#
val = hdf5flow.getNode("/".join(['', 'values', group, 'noenso'])).read()
val = val[val['id'] == station]
fsp.plot(range(12), [val[p] for p in periodnames],
marker='^', ms=6, label=labels['G'], c=ENSOlines['G'])
#
val = hdf5flow.getNode("/".join(['', 'values', group, 'cold'])).read()
val = val[val['id'] == station]
val = numpy.array([val[p] for p in periodnames])
apx = hdf5flow.getNode("/".join(['', 'apxpvalues', group, 'CN'])).read()
apx = apx[apx['id'] == station]
apx = numpy.array([apx[p] for p in periodnames])
col_C = ENSOlines['C']
fsp.plot(range(12), val, marker='', label='_nolabel_', c=col_C)
fsp.plot(range(12), ma.array(val, mask=(apx < 0.1)),
marker='^', label=labels['C'], c=col_C)
fsp.plot(range(12), ma.array(val, mask=(apx >= 0.1) | (apx < 0.05)) ,
marker='d', label='_nolabel_', ls='', c=col_C, ms=10)
fsp.plot(range(12), ma.array(val, mask=(apx >= 0.05) | (apx < 0.01)) ,
marker='s', label='_nolabel_', ls='', c=col_C, ms=10)
fsp.plot(range(12), ma.array(val, mask=(apx > 0.01)) ,
marker='o', label='_nolabel_', ls='', c=col_C, ms=10)
#
val = hdf5flow.getNode("/".join(['', 'values', group, 'neutral'])).read()
val = val[val['id'] == station]
fsp.plot(range(12), [val[p] for p in periodnames],
marker='o', ms=6, label=labels['N'], c=ENSOlines['N'])
#
val = hdf5flow.getNode("/".join(['', 'values', group, 'warm'])).read()
val = val[val['id'] == station]
val = numpy.array([val[p] for p in periodnames])
apx = hdf5flow.getNode("/".join(['', 'apxpvalues', group, 'WN'])).read()
apx = apx[apx['id'] == station]
apx = numpy.array([apx[p] for p in periodnames])
col_W = ENSOlines['W']
fsp.plot(range(12), val, marker='', label='_nolabel_', c=col_W)
fsp.plot(range(12), ma.array(val, mask=(apx < 0.1)),
marker='^', label=labels['W'], c=col_W)
fsp.plot(range(12), ma.array(val, mask=(apx >= 0.1) | (apx < 0.05)) ,
marker='d', label=labels['90'], ls='', c=col_W, ms=10)
fsp.plot(range(12), ma.array(val, mask=(apx >= 0.05) | (apx < 0.01)) ,
marker='s', label=labels['95'], ls='', c=col_W, ms=10)
fsp.plot(range(12), ma.array(val, mask=(apx > 0.01)) ,
marker='o', label=labels['99'], ls='', c=col_W, ms=10)
#
#fsp.set_yscale('log')
#
fsp.xaxis.set_major_locator(pylab.MultipleLocator(1))
if fsp.is_last_row():
fsp.set_xticklabels(periodnames, fontsize=10)
else:
fsp.set_xticklabels([])
fsp.set_ylabel("Flows (cfs)", fontweight='bold', fontsize=10)
fsp.yaxis.major.formatter.set_powerlimits((-3, 3))
# fsp.set_title("%s Q%02i flows - %s" % (funcname.capitalize(),
# 100.*quantile,
# station), fontweight='bold')
fsp.set_title("%s" % (station), fontweight='bold', fontsize=10)
if fsp.is_last_row():
fsp.legend(numpoints=1, prop=dict(size='x-small'))
hdf5flow.close()
return