#Passive Scenario
print('Running passive case..')
SSN2 = Watershed(Model=256)
SSN2.init_custom(links=l_id,
connectivity=connectivity,
A_i=A_i,
L_i=L_i,
A_h=A_h)
SSN2.dam_ids = dams
dam_params256 = SSN2.init_dam_params256(H_spill, H_max, S_max, _alpha,
diam, c1, c2, L_spill, L_crest)
q, s_p, s_t, s_s = Set_InitialConditions(0.5, A_i[0], A_i)
S = [100000 for _ in range(n_dams)]
SSN2.set_dam_state(states=[1 for _ in range(n_dams)])
SSN2.initialize(q=q, S=S, s_t=s_t, s_p=s_p, s_s=s_s)
dc_passive, st_passive = SSN2.Run_256([0, te], forcing, dam_params256)
#Active Control with GA
print('Running active control case')
# watershed object initialization
SSN5 = Watershed(Model=256)
SSN5.init_custom(links=l_id,
connectivity=connectivity,
A_i=A_i,
L_i=L_i,
A_h=A_h)
SSN5.dam_ids = dams
dam_params256 = SSN5.init_dam_params256(H_spill, H_max, S_max, _alpha,
diam, c1, c2, L_spill, L_crest)
q, s_p, s_t, s_s = Set_InitialConditions(0.5, A_i[0], A_i)
S = [100000 for _ in range(n_dams)]
timescale=30)
te = len(forcing) - 1
for key in initial_conditions.keys():
initial_condition = initial_conditions[key]
q = initial_condition['q']
s_p = initial_condition['s_p']
s_t = initial_condition['s_t']
s_s = initial_condition['s_s']
fill_percent = np.repeat(
[.99], n_dams4) #np.random.uniform(0,0.8,n_dams4).round(2)#
S = (S_max * fill_percent).tolist()
SSN5.set_dam_state(states=[1 for _ in range(n_dams4)])
SSN5.initialize(q=q, S=S, s_t=s_t, s_p=s_p, s_s=s_s)
dc_passive_S4, st_passive_S4 = SSN5.Run_256([0, te], forcing,
dam_params256)
out_passive_S4 = SSN5.CalculateOutflow(dam_params256,
st_passive_S4)
temp1 = dc_passive_S4.max(
) #dc_passive_S4[dc_passive_S4.index>120].max()
temp2 = out_passive_S4.max(
) #out_passive_S4[out_passive_S4.index>120].max()
dc_passive_Peak_S4 = dc_passive_Peak_S4.append(temp1,
ignore_index=True)
out_passive_Peak_S4 = out_passive_Peak_S4.append(temp2,
ignore_index=True)
print(
f'(Scenario-4)Storm:{dstorm} is simulated with given initial conditions!'
L_i=L_i,
A_h=A_h)
H_spill, H_max, S_max, _alpha, diam, c1, c2, L_spill, L_crest = PrepareDamParams(
dams5
) #!! TODO: make the code run without this parameters when no dam introduced
dam_params256 = SSN.init_dam_params256(H_spill, H_max, S_max, _alpha, diam,
c1, c2, L_spill, L_crest) # !!
q = initial_condition['q']
s_p = initial_condition['s_p']
s_t = initial_condition['s_t']
s_s = initial_condition['s_s']
SSN.initialize(q=q, s_p=s_p, s_t=s_t, s_s=s_s)
SSN.set_dam_state()
dc_nodam, _ = SSN.Run_256(
[0, te],
forcing,
dam_params256,
rtol=1e-6,
)
dc_nodam.to_csv(
f'/Users/gurbuz/Supp_DamStudy/final_ActiveControl/dc_nodam_{save_ext}.csv'
)
print(f'Done nodam in {time.time()-start}')
###################################################################################################
start = time.time()
print('Running Passive..')
SSN5 = Watershed(Model=256)
SSN5.init_custom(links=l_id,
connectivity=connectivity,
A_i=A_i,
L_i=L_i,
A_h=A_h)
rate=(0.01 * np.diff(rate10, prepend=0)).tolist(),
timescale=30)
te = len(forcing) - 1
for key in initial_conditions.keys():
initial_condition = initial_conditions[key]
q = initial_condition['q']
s_p = initial_condition['s_p']
s_t = initial_condition['s_t']
s_s = initial_condition['s_s']
fill_percent = np.repeat(
[.99], n_dams1) #()np.random.uniform(0,0.8,n_dams1).round(2)
S = (S_max * fill_percent).tolist()
SSN2.set_dam_state(states=[1 for _ in range(n_dams1)])
SSN2.initialize(q=q, S=S, s_t=s_t, s_p=s_p, s_s=s_s)
dc_passive_S1, st_passive_S1 = SSN2.Run_256([0, te], forcing,
dam_params256)
out_passive_S1 = SSN2.CalculateOutflow(dam_params256,
st_passive_S1)
temp1 = dc_passive_S1.max(
) #dc_passive_S1[dc_passive_S1.index>120].max()
temp2 = out_passive_S1.max(
) #out_passive_S1[out_passive_S1.index>120].max()
dc_passive_Peak_S1 = dc_passive_Peak_S1.append(temp1,
ignore_index=True)
out_passive_Peak_S1 = out_passive_Peak_S1.append(temp2,
ignore_index=True)
print(
f'(Scenario-1)Storm:{dstorm} is simulated with given initial conditions!'