def test_scatterlog(self):
sim_array = self.merged_df.iloc[:, 0].values
obs_array = self.merged_df.iloc[:, 1].values
# Creating test image array
hv.scatter(sim_array=sim_array,
obs_array=obs_array,
grid=True,
title='Scatter Plot (Log-Log Scale)',
labels=('SFPT', 'GLOFAS'),
line45=True,
metrics=['ME', 'KGE (2012)'],
log_scale=True)
buf = BytesIO()
plt.savefig(buf, format='png')
buf.seek(0)
img_test = mpimg.imread(buf)
buf.close()
# Reading original image
img_original = mpimg.imread(
os.path.join(os.getcwd(), 'baseline_images', 'plot_tests',
'scatterlog.png'))
# Comparing the images
self.assertTrue(np.all(np.isclose(img_test, img_original)))
def test_scatter(self):
# Creating test image array
hv.scatter(merged_data_df=self.merged_df, grid=True, title='Scatter Plot (Normal Scale)',
labels=('SFPT', 'GLOFAS'), best_fit=True)
buf = BytesIO()
plt.savefig(buf, format='png')
buf.seek(0)
img_test = mpimg.imread(buf)
buf.close()
# Reading original image
img_original = mpimg.imread(os.path.join(os.getcwd(), 'baseline_images', 'plot_tests', 'scatter.png'))
# Comparing the images
self.assertTrue(np.all(np.isclose(img_test, img_original)))
hv.plot(merged_df,
legend=('Simulated', 'Observed'),
grid=True,
title='Hydrograph for ' + name + '\n River: ' + rio + '. COMID: ' +
str(comid),
labels=['Datetime', 'Volume (BCM)'],
linestyles=['b-', 'r-'],
fig_size=(15, 9))
plt.savefig(
path.join(plot_out_dir,
'{0}_{1}_hydrographs.png'.format(str(comid), name)))
hv.scatter(merged_data_df=merged_df,
grid=True,
title='Scatter Plot for ' + name + '\n River: ' + rio +
'. COMID: ' + str(comid),
labels=('Simulated', 'Observed'),
line45=True,
best_fit=True,
figsize=(15, 9))
plt.savefig(
path.join(scatter_out_dir,
'{0}_{1}_scatter_plot.png'.format(str(comid), name)))
hv.scatter(sim_array=sim_array,
obs_array=obs_array,
grid=True,
title='Scatter Plot (Log Scale) for ' + name + '\n River: ' +
rio + '. COMID: ' + str(comid),
labels=('Simulated', 'Observed'),
line45=True,
best_fit=True,
labels=['Datetime', 'Streamflow (m$^3$/s)'],
linestyles=['b-', 'r-'],
fig_size=(15, 9),
ebars=monthly_std_error,
ecolor=('b', 'r'),
tight_xlim=False)
#plt.savefig(path.join(monthly_average_out_dir, '{0}_{1}_monthly_average.png'.format(str(id), name)))
plt.savefig(
path.join(monthly_average_out_dir,
'{0}_{1}_monthly_average.png'.format(str(comid), name)))
hv.scatter(
merged_data_df=merged_df,
grid=True,
#title='Scatter Plot for ' + str(id) + ' - ' + name + '\n River: ' + rio + '. COMID: ' + str(comid),
title='Scatter Plot for ' + name + '\n River: ' + rio + '. COMID: ' +
str(comid),
labels=('ERA-Interim', 'ERA-5'),
line45=True,
best_fit=True,
figsize=(15, 9))
#plt.savefig(path.join(scatter_out_dir, '{0}_{1}_scatter_plot.png'.format(str(id), name)))
plt.savefig(
path.join(scatter_out_dir,
'{0}_{1}_scatter_plot.png'.format(str(comid), name)))
hv.scatter(
sim_array=sim_array,
obs_array=obs_array,
grid=True,
#title='Scatter Plot (Log Scale) for ' + str(id) + ' - ' + name + '\n River: ' + rio + '. COMID: ' + str(
# comid),
# This list specifies which metrics to use:
metrics = []
# This list controls the axis labels:
labels = ['Datetime', 'Streamflow (cms)']
# End of Dynamic Input. Do NOT Change the following -------------------------------------------
# Create a list of 18 stream modified Time Series
list_riv_part_era5 = []
for riv in list_riv_mouth_era5:
riv_part_era5 = riv.loc[begin_date:end_date]
list_riv_part_era5.append(riv_part_era5)
for s, o, t, s1, s2 in zip(list_sim, list_obs, range(18), series1, series2):
merged_df = hd.merge_data(sim_df=list_riv_part_era5[s],
obs_df=list_riv_part_era5[o])
filename = year + ' (ERA-5): ' + list_titles[t]
hv.scatter(merged_data_df=merged_df,
title=filename,
labels=(s1, s2),
metrics=metrics,
marker_style=".",
grid=True,
log_scale=False,
line45=True)
plt.tight_layout()
plt.savefig(
'/home/chrisedwards/Documents/rapid_output/graphs/{}.png'.format(
filename))
'ID: Sim (Outlet) vs Obs (gauge-13340600)',
'MO: Sim (Outlet) vs Obs (gauge-07014500)',
'NY: Sim (Outlet) vs Obs (gauge-01413500)',
'OR: Sim (Outlet) vs Obs (gauge-14306500)',
'AZ: Sim (str-60) vs Obs (gauge-09492400)',
'MO: Sim (str-50) vs Obs (gauge-07013000)',
'MO: Sim (str-51) vs Obs (gauge-07014000)',
'NY: Sim (str-47) vs Obs (gauge-01413408)',
'NY: Sim (str-46) vs Obs (gauge-01413398)',
'OR: Sim (str-58) vs Obs (gauge-14306400)',
'OR: Sim (str-47) vs Obs (gauge-14306100)'
]
metrics = []
for s, o, t in zip(range(12), range(12), range(12)):
merged_df = hd.merge_data(sim_df=list_sim_df[s], obs_df=list_obs_df[o])
da_df = hd.daily_average(merged_df)
filename = list_titles[t] + ' Daily Avg Scatter'
hv.scatter(merged_data_df=da_df,
title=filename,
labels=('Sim (cms)', 'Obs (cms)'),
metrics=metrics,
marker_style=".",
grid=True,
log_scale=False,
line45=True)
plt.tight_layout()
plt.savefig(
'/home/chrisedwards/Documents/rapid_output/graphs/{}.png'.format(
filename))
