def nwm_stage(self, forecast):
from pynwm import nwm
"""Retrieve nwm forecast using pynwm module, and retrieve rating curves
for self.comid, and provide probabilistic stage height distribution"""
series = nwm.get_streamflow(forecast,
self.comid,
timezone='US/Central')
interp = scipy.interpolate.interp1d(self.handq,
self.handh) # kind=cubic
self.qdict = {}
if len(series) > 1: # long_range ensemble
for s in series:
datevals = zip(s['dates'], s['values'])
for (d, v) in (datevals):
d = d.strftime('%y-%m-%d %H')
self.qdict[d] = v
else: # all other models (short_range, med_range, analysis_assym)
s = series[0]
datevals = zip(s['dates'], s['values'])
for (d, v) in (datevals):
d = d.strftime('%y-%m-%d %H')
self.qdict[d] = v
fcast_d = scipy.array(self.qdict.keys())
fcast_v = scipy.array(self.qdict.values())
return (fcast_d, interp(fcast_v))
def make_graph(products, comid, gage, start_date, clip_to_gage_dates, width):
print 'COMID:', comid
fig_size = [width, width / 1.61803398875] # golden ratio
gage_vals = None
gage_dates = None
s_series = None
m_series = None
l_series = None
# Download data and figure out data ranges
print ' Getting USGS data'
gage_start = start_date - timedelta(hours=6)
gage_name, gage_vals, gage_dates = _get_usgs_flow(gage, gage_start)
if 'short' in products:
print ' Getting short range forecast from HydroShare'
s_series = nwm.get_streamflow('short_range', comid, start_date,
'America/Chicago')
if 'medium' in products:
medium_start = datetime.combine(start_date.date(), time(6))
print ' Getting medium range forecast from HydroShare'
m_series = nwm.get_streamflow('medium_range', comid, medium_start,
'America/Chicago')
if 'long' in products:
print ' Getting long range forecast from HydroShare'
l_series = nwm.get_streamflow('long_range', comid, start_date,
'America/Chicago')
max_val, min_date, max_date = _get_limits(gage_vals, gage_dates, s_series,
m_series, l_series,
clip_to_gage_dates)
if max_val > 0 and min_date < max_date:
try:
# Make the plot
fig, ax = plt.subplots(figsize=fig_size)
plt.title(gage_name, fontsize=12)
if gage_vals:
ax.plot(gage_dates,
gage_vals,
label='Gage',
color='green',
linewidth='4')
# Short
if s_series:
for s in s_series:
nwm_dates = s['dates']
nwm_vals = s['values']
ax.plot(nwm_dates,
nwm_vals,
label='Short Range',
color='blue',
linewidth='7')
# Medium
if m_series:
for s in m_series:
nwm_dates = s['dates']
nwm_vals = s['values']
ax.plot(nwm_dates,
nwm_vals,
label='Medium Range',
color='purple',
linewidth='2')
# Long
if l_series:
for i, s in enumerate(l_series):
nwm_dates = s['dates']
nwm_vals = s['values']
if i == 0:
ax.plot(nwm_dates,
nwm_vals,
label='Ensemble',
color='brown',
linestyle=':')
else:
ax.plot(nwm_dates,
nwm_vals,
color='brown',
linestyle=':')
# Format plot layout
ax.legend(loc='best', fontsize=10)
plt.ylabel('Flow (cfs)', fontsize=12)
ax.tick_params(labelsize=10)
ax.xaxis.set_major_formatter(DateFormatter('%b %d'))
ax.set_ylim(0.0, max_val * 1.05)
ax.set_xlim(min_date, max_date)
ax.margins(0, 0.1)
fig.autofmt_xdate() # Show date labels at an angle
fig.tight_layout() # Removes some of the margin around the graph
# Save the result
png_file = '{0}-{1}-{2}.png'.format(gage_name, gage, comid)
plt.savefig(png_file, facecolor=fig.get_facecolor())
print ' Saved', png_file
except:
raise
finally:
plt.close() # free memory after each plot
else:
print ' Max value is zero or no date intersection found. Skipping plot.'