def test_is_supy_running_multi_grid_par(self):
df_state_init, df_forcing_tstep = sp.load_SampleData()
df_state_init = pd.concat([df_state_init for x in range(6)])
df_forcing_part = df_forcing_tstep.iloc[:]
t_start = time()
df_output, df_state = sp.run_supy(
df_forcing_part, df_state_init)
t_end = time()
# only print to screen on macOS due incompatibility on Windows
if platform.system() == 'Darwin':
capturedOutput = io.StringIO() # Create StringIO object
sys.stdout = capturedOutput # and redirect stdout.
# Call function.
n_grid = df_state_init.index.size
print(f'Running time: {t_end-t_start:.2f} s for {n_grid} grids')
sys.stdout = sys.__stdout__ # Reset redirect.
# Now works as before.
print('Captured:\n', capturedOutput.getvalue())
test_non_empty = np.all(
[
not df_output.empty,
not df_state.empty,
]
)
self.assertTrue(test_non_empty)
def test_is_supy_save_working(self):
df_state_init, df_forcing_tstep = sp.load_SampleData()
# df_state_init = pd.concat([df_state_init for x in range(6)])
df_forcing_part = df_forcing_tstep.iloc[:288*2]
t_start = time()
df_output, df_state = sp.run_supy(
df_forcing_part, df_state_init)
t_end = time()
with tempfile.TemporaryDirectory() as dir_temp:
list_outfile = sp.save_supy(
df_output, df_state, path_dir_save=dir_temp)
# only print to screen on macOS due incompatibility on Windows
if platform.system() == 'Darwin':
capturedOutput = io.StringIO() # Create StringIO object
sys.stdout = capturedOutput # and redirect stdout.
# Call function.
n_grid = df_state_init.index.size
print(f'Running time: {t_end-t_start:.2f} s for {n_grid} grids')
sys.stdout = sys.__stdout__ # Reset redirect.
# Now works as before.
print('Captured:\n', capturedOutput.getvalue())
test_non_empty = np.all(
[isinstance(fn, Path) for fn in list_outfile]
)
self.assertTrue(test_non_empty)
def test_is_supy_running_single_step(self):
df_state_init, df_forcing_tstep = sp.load_SampleData()
df_forcing_part = df_forcing_tstep.iloc[: 288 * 1]
df_output, df_state = sp.run_supy(
df_forcing_part, df_state_init, save_state=True
)
test_non_empty = np.all([not df_output.empty, not df_state.empty,])
self.assertTrue(test_non_empty)
def test_is_supy_running_multi_step(self):
df_state_init, df_forcing_tstep = sp.load_SampleData()
df_forcing_part = df_forcing_tstep.iloc[:]
df_output, df_state = sp.run_supy(
df_forcing_part, df_state_init, check_input=True
)
# # only print to screen on macOS due incompatibility on Windows
# if platform.system() == "Darwin":
# # capturedOutput = io.StringIO() # Create StringIO object
# # sys.stdout = capturedOutput # and redirect stdout.
# # Call function.
# print(f"Running time: {t_end-t_start:.2f} s")
# # sys.stdout = sys.__stdout__ # Reset redirect.
# # Now works as before.
# # print("Captured:\n", capturedOutput.getvalue())
test_non_empty = np.all([not df_output.empty, not df_state.empty,])
self.assertTrue(test_non_empty)
import os
try:
os.chdir(os.path.join(os.getcwd(), 'docs/source/data-structure'))
print(os.getcwd())
except:
pass
#%% [markdown]
# # Key IO Data Structures in SuPy
#%% [markdown]
# ## Introduction
#%% [markdown]
# The Cell below demonstrates a minimal case of SuPy simulation with all key IO data structures included:
#%%
import supy as sp
df_state_init, df_forcing = sp.load_SampleData()
df_output, df_state_final = sp.run_supy(df_forcing.iloc[:288], df_state_init)
#%% [markdown]
# * Input:
# * `df_state_init`: model initial states
# * `df_forcing`: forcing data
# * Output:
# * `df_state_final`: model final states
# * `df_output`: model output results
#%% [markdown]
# ## Input
#%% [markdown]
# ### `df_state_init`: model initial states
