def get_gridmet(self, start, end, lat, lon):
# gridmet params
gridmet = GridMet('pr', start=start, end=end, lat=lat, lon=lon)
ts_ppt = gridmet.get_point_timeseries()
m_ppt = ts_ppt.groupby(lambda x: x.month).sum().values
gridmet = GridMet('etr', start=start, end=end, lat=lat, lon=lon)
ts_etr = gridmet.get_point_timeseries()
m_etr = ts_etr.groupby(lambda x: x.month).sum().values
return m_ppt, m_etr
def test_agrimet_mesonet_gridmet_etr(self):
agrimet = Agrimet(station=self.fetch_site,
start_date=self.start,
end_date=self.end,
interval='daily')
formed = agrimet.fetch_met_data()
agri_etr = formed['ETRS'].values
s, e = datetime.strptime(self.start, '%Y-%m-%d'), \
datetime.strptime(self.end, '%Y-%m-%d')
gridmet = GridMet('etr', start=s, end=e, lat=self.lat, lon=self.lon)
gridmet_etr = gridmet.get_point_timeseries()
gridmet_etr = gridmet_etr.values
mco = Mesonet(self.covm_mco, start=self.start, end=self.end)
mesonet_daily = mco.mesonet_etr(lat=46.3, elevation=1000.0)
mesonet_etr = mesonet_daily['ETR'].values
plt.plot(gridmet_etr[121:273], label='gridmet')
plt.plot(mesonet_etr[121:273], label='mesonet')
plt.plot(agri_etr[121:273], label='agrimet')
plt.xlabel('GROWING SEASON DAY (MAY 01 - SEP 30)')
plt.ylabel('Tall Crop Reference ET (mm) daily')
plt.legend()
# plt.show()
saved = os.path.join(os.path.dirname(__file__),
'grid_agri_meso_fig.png')
print('saved to {}'.format(saved))
plt.savefig(saved)
ga_ratio = gridmet_etr[121:273].sum() / agri_etr[121:273].sum()
print('gridmet - agrimet ratio: {}'.format(ga_ratio))
ma_ratio = mesonet_etr[121:273].sum() / agri_etr[121:273].sum()
print('mesonet - agrimet ratio: {}'.format(ma_ratio))
def correct_pr_mesonet_gridmet(start, end, lat, lon):
s, e = datetime.strptime(start, '%Y-%m-%d'), \
datetime.strptime(end, '%Y-%m-%d')
gridmet = GridMet('pr', start=s, end=e, lat=lat, lon=lon)
gridmet_ppt = gridmet.get_point_timeseries()
gridmet_ppt = gridmet_ppt.values
mco = Mesonet(LOLO_MCO, start=start, end=end)
mesonet_ppt = mco.mesonet_ppt(daily=True)
mesonet_ppt = mesonet_ppt['Precipitation'].values
mesonet_ppt = mesonet_ppt.reshape((mesonet_ppt.shape[0], 1))
meso_gs_ppt, grid_gs_ppt = mesonet_ppt[121:273], gridmet_ppt[121:273]
comp = hstack((meso_gs_ppt, grid_gs_ppt))
pass
def test_agrimet_gridmet_precip(self):
agrimet = Agrimet(station=self.fetch_site,
start_date=self.start,
end_date=self.end,
interval='daily')
formed = agrimet.fetch_met_data()
agri_ppt = formed['PP'].values
s, e = datetime.strptime(self.start, '%Y-%m-%d'), \
datetime.strptime(self.end, '%Y-%m-%d')
gridmet = GridMet('pr', start=s, end=e, lat=self.lat, lon=self.lon)
gridmet_ppt = gridmet.get_point_timeseries()
gridmet_ppt = gridmet_ppt.values
difference = abs(gridmet_ppt - agri_ppt)
self.assertLess(nanmean(difference), -100000)
def test_get_time_series(self):
""" Test native pet rasters vs. xarray netcdf point extract.
:return:
"""
rasters = os.listdir(self.grimet_raster_dir)
for ras in rasters:
if ras.endswith('pet.tif'):
dt = datetime.strptime(ras[:10], '%Y-%m-%d')
raster = os.path.join(self.grimet_raster_dir, ras)
points = raster_point_extract(raster, self.agri_points, dt)
for key, val in points.items():
lon, lat = val['coords']
_, var = ras.split('_')
var = var.replace('.tif', '')
gridmet = GridMet(var, date=dt, lat=lat, lon=lon)
gridmet_pet = gridmet.get_point_timeseries()
val[dt][1] = gridmet_pet.iloc[0, 0]
for key, val in points.items():
self.assertEqual(val[dt][0], val[dt][1])
def correct_etr_mesonet_gridmet(start, end, lat, lon):
s, e = datetime.strptime(start, '%Y-%m-%d'), \
datetime.strptime(end, '%Y-%m-%d')
gridmet = GridMet('etr', start=s, end=e, lat=lat, lon=lon)
gridmet_etr = gridmet.get_point_timeseries()
gridmet_etr = gridmet_etr.values
mco = Mesonet(LOLO_MCO, start=start, end=end)
mesonet_daily = mco.mesonet_etr(lat=46.3, elevation=1000.0)
mesonet_etr = mesonet_daily['ETR'].values
plt.plot(gridmet_etr[121:273], label='gridmet')
plt.plot(mesonet_etr[121:273], label='mesonet')
plt.xlabel('GROWING SEASON DAY (MAY 01 - SEP 30)')
plt.ylabel('Tall Crop Reference ET (mm) daily')
plt.legend()
plt.show()
ma_ratio = mesonet_etr[121:273].sum() / gridmet_etr[121:273].sum()
print('mesonet - gridmet ratio: {}'.format(ma_ratio))
ma_ratio = gridmet_etr[121:273].sum() / mesonet_etr[121:273].sum()
print('gridmet - mesonet ratio: {}'.format(ma_ratio))
def test_agrimet_gridmet_etr(self):
agrimet = Agrimet(station=self.fetch_site,
start_date=self.start,
end_date=self.end,
interval='daily')
formed = agrimet.fetch_met_data()
agri_etr = formed['ETRS'].values
s, e = datetime.strptime(self.start, '%Y-%m-%d'), \
datetime.strptime(self.end, '%Y-%m-%d')
gridmet = GridMet('etr', start=s, end=e, lat=self.lat, lon=self.lon)
gridmet_etr = gridmet.get_point_timeseries()
gridmet_etr = gridmet_etr.values
# plt.plot(gridmet_etr, label='gridmet')
# plt.plot(agri_etr, label='agrimet')
# plt.legend()
# plt.show()
# plt.close()
ratio = agri_etr.sum() / gridmet_etr.sum()
print('ratio: {}'.format(ratio))
