specl mods

[jdkleiner]

@njit
def _specl_(ui, ts, state, step, specactions):
    # todo determine best way to do error handling in specl
    errors_specl = zeros(int(1)).astype(int64)

    # state[1] = state[1] + 1000
    state[1] += 1000
    state[2] = 99
    # state[3]

    return errors_specl  

for step in range(steps):

        # print("OUTDGT[step, :]", OUTDGT[step, :])
        # call specl
        # errors = _hydr_(ui, ts, COLIND, OUTDGT, rchtab, funct, Olabels, OVOLlabels, specactions) 

        # print(OUTDGT[step])
        # print(OUTDGT[step, 0])
        # print(OUTDGT[step, 1])
        # print(OUTDGT[step, 2])
        
        state = Dict.empty(key_type=types.int64, value_type=types.float64)
        # state[2] = 1.0 # value of the variable constant from the equation for discharge_mgd 
        # state[3] = 0.15 # the value of the variable "consumption"
        state[1] = OUTDGT[step, 0]
        state[2] = OUTDGT[step, 1]
        state[3] = OUTDGT[step, 2]

        print("state before specl()")
        [print(key,':',value) for key, value in state.items()]

        errors_specl = specl(ui, ts, state, step, specactions)

        print("state after specl()")
        [print(key,':',value) for key, value in state.items()]

        print("OUTDGT[step, :]", OUTDGT[step, :])
        OUTDGT[step, :] = [state[1], state[2], state[3]]
        print("OUTDGT[step, :]", OUTDGT[step, :])

        convf  = CONVF[step]
        outdgt[:] = OUTDGT[step, :]
        colind[:] = COLIND[step, :]
        roseff = ro
        oseff[:] = o[:]

[jdkleiner]

streamlined code

# The following occurs at the beginning of the HYDR for-loop

# set up state dictionary
state = Dict.empty(key_type=types.int64, value_type=types.float64)
state[1] = OUTDGT[step, 0]
state[2] = OUTDGT[step, 1]
state[3] = OUTDGT[step, 2]

# specl modifies state variables
errors_specl = specl(ui, ts, state, step, specactions)

# set OUTDGT arry using the modified state variables 
OUTDGT[step, :] = [state[1], state[2], state[3]]

See SPECL.py:

@njit
def _specl_(ui, ts, state, step, specactions):
    errors_specl = zeros(int(1)).astype(int64)

    state[1] += 1000
    state[2] = 99

    return errors_specl

[jdkleiner]

Test implementation of state dictionary approach for specl

See SPECL.py:

@njit
def _specl_(ui, ts, state, step, specactions):
    errors_specl = zeros(int(1)).astype(int64)

    state[1] += 1000
    state[2] = 99

    return errors_specl

See HYDR.py:

# The following occurs at the beginning of the HYDR for-loop

# set up state dictionary
state = Dict.empty(key_type=types.int64, value_type=types.float64)
state[1] = OUTDGT[step, 0]
state[2] = OUTDGT[step, 1]
state[3] = OUTDGT[step, 2]

# specl modifies state variables
errors_specl = specl(ui, ts, state, step, specactions)

# set OUTDGT arry using the modified state variables 
OUTDGT[step, :] = [state[1], state[2], state[3]]

Result console output:

step 8669 of 8760
state before specl()
1 : 83.55184936523438
2 : -0.0
3 : 0.0
state after specl()
1 : 1083.5518493652344
2 : 99.0
3 : 0.0
OUTDGT[step, :] [1083.55184937   99.            0.        ]