def run(plot=True, customized_kpi_config=None):
'''Run test case.
Parameters
----------
plot : bool, optional
True to plot timeseries results.
Default is False.
customized_kpi_config : string, optional
The path of the json file which contains the customized kpi information.
Default is None.
Returns
-------
kpi : dict
Dictionary of core KPI names and values.
{kpi_name : value}
res : dict
Dictionary of trajectories of inputs and outputs.
customizedkpis_result: dict
Dictionary of tracked custom KPI calculations.
Empty if no customized KPI calculations defined.
'''
# SETUP TEST CASE
# ---------------
# Set URL for testcase
url = 'http://127.0.0.1:5000'
# Set simulation parameters
length = 24*3600*2
step = 3600
# ---------------
# GET TEST INFORMATION
# --------------------
print('\nTEST CASE INFORMATION\n---------------------')
# Test case name
name = requests.get('{0}/name'.format(url)).json()
print('Name:\t\t\t\t{0}'.format(name))
# Inputs available
inputs = requests.get('{0}/inputs'.format(url)).json()
print('Control Inputs:\t\t\t{0}'.format(inputs))
# Measurements available
measurements = requests.get('{0}/measurements'.format(url)).json()
print('Measurements:\t\t\t{0}'.format(measurements))
# Default simulation step
step_def = requests.get('{0}/step'.format(url)).json()
print('Default Simulation Step:\t{0}'.format(step_def))
# Define customized KPI if any
customizedkpis=[] # Initialize customzied kpi calculation list
customizedkpis_result={} # Initialize tracking of customized kpi calculation results
if customized_kpi_config is not None:
with open(customized_kpi_config) as f:
config=json.load(f,object_pairs_hook=collections.OrderedDict)
for key in config.keys():
customizedkpis.append(kpicalculation.cutomizedKPI(config[key]))
customizedkpis_result[kpicalculation.cutomizedKPI(config[key]).name]=[]
customizedkpis_result['time']=[]
# --------------------
# RUN TEST CASE
# -------------
start = time.time()
# Initialize test case
print('Initializing test case simulation.')
res = requests.put('{0}/initialize'.format(url), data={'start_time':0,'warmup_period':0}).json()
if res:
print('Successfully initialized the simulation')
print('\nRunning test case...')
# Set simulation step
res = requests.put('{0}/step'.format(url), data={'step':step})
# Initialize u
u = sup.initialize()
# Simulation Loop
for i in range(int(length/step)):
# Advance simulation
y = requests.post('{0}/advance'.format(url), data=u).json()
# Compute next control signal
u = sup.compute_control(y)
# Compute customized KPIs if any
if customized_kpi_config is not None:
for customizedkpi in customizedkpis:
customizedkpi.processing_data(y) # Process data as needed for custom KPI
customizedkpi_value = customizedkpi.calculation() # Calculate custom KPI value
customizedkpis_result[customizedkpi.name].append(round(customizedkpi_value,2)) # Track custom KPI value
print('KPI:\t{0}:\t{1}'.format(customizedkpi.name,round(customizedkpi_value,2))) # Print custom KPI value
customizedkpis_result['time'].append(y['time']) # Track custom KPI calculation time
print('\nTest case complete.')
print('Elapsed time of test was {0} seconds.'.format(time.time()-start))
# -------------
# VIEW RESULTS
# ------------
# Report KPIs
kpi = requests.get('{0}/kpi'.format(url)).json()
print('\nKPI RESULTS \n-----------')
for key in kpi.keys():
if key == 'ener_tot':
unit = 'kWh'
elif key == 'tdis_tot':
unit = 'Kh'
elif key == 'idis_tot':
unit = 'ppmh'
elif key == 'cost_tot':
unit = 'Euro or $'
elif key == 'emis_tot':
unit = 'KgCO2'
elif key =='timdis_tot':
unit = 'h'
elif key == 'dT_max_dict':
unit = '(K, s)'
elif key == 'pow_peak':
unit = 'W'
else:
unit = None
print('{0}: {1} {2}'.format(key, kpi[key], unit))
# ------------
# POST PROCESS RESULTS
# --------------------
# Get result data
res = requests.get('{0}/results'.format(url)).json()
t = [x/3600 for x in res['y']['time']] # convert s --> hr
TRooAir = [x-273.15 for x in res['y']['TRooAir_y']] # convert K --> C
TSetRooHea = [x-273.15 for x in res['u']['oveTSetRooHea_u']] # convert K --> C
TSetRooCoo = [x-273.15 for x in res['u']['oveTSetRooCoo_u']] # convert K --> C
PFan = res['y']['PFan_y']
PCoo = res['y']['PCoo_y']
PHea = res['y']['PHea_y']
PPum = res['y']['PPum_y']
# Plot results
if plot:
from matplotlib import pyplot as plt
plt.figure(1)
plt.title('Zone Temperature')
plt.plot(t, TRooAir)
plt.plot(t, TSetRooHea)
plt.plot(t, TSetRooCoo)
plt.ylabel('Temperature [C]')
plt.xlabel('Time [hr]')
plt.figure(2)
plt.title('HVAC Power')
plt.plot(t, PHea, label='Heating')
plt.plot(t, PCoo, label='Cooling')
plt.plot(t, PFan, label='Fan')
plt.plot(t, PPum, label='Pump')
plt.ylabel('Electrical Power [W]')
plt.xlabel('Time [hr]')
plt.legend()
plt.show()
# --------------------
return kpi,res,customizedkpis_result
def run(plot=False, customized_kpi_config=None):
'''Run test case.
Parameters
----------
plot : bool, optional
True to plot timeseries results.
Default is False.
customized_kpi_config : string, optional
The path of the json file which contains the customized kpi information.
Default is None.
Returns
-------
kpi : dict
Dictionary of core KPI names and values.
{kpi_name : value}
res : dict
Dictionary of trajectories of inputs and outputs.
customizedkpis_result: dict
Dictionary of tracked custom KPI calculations.
Empty if no customized KPI calculations defined.
'''
# SETUP TEST CASE
# ---------------
# Set URL for testcase
url = 'http://127.0.0.1:5000'
# Set simulation parameters
length = 48 * 3600
step = 300
# ---------------
# GET TEST INFORMATION
# --------------------
print('\nTEST CASE INFORMATION\n---------------------')
# Test case name
name = requests.get('{0}/name'.format(url)).json()
print('Name:\t\t\t\t{0}'.format(name))
# Inputs available
inputs = requests.get('{0}/inputs'.format(url)).json()
print('Control Inputs:\t\t\t{0}'.format(inputs))
# Measurements available
measurements = requests.get('{0}/measurements'.format(url)).json()
print('Measurements:\t\t\t{0}'.format(measurements))
# Default simulation step
step_def = requests.get('{0}/step'.format(url)).json()
print('Default Simulation Step:\t{0}'.format(step_def))
# --------------------
# Define customized KPI if any
customizedkpis = [] # Initialize customzied kpi calculation list
customizedkpis_result = {
} # Initialize tracking of customized kpi calculation results
if customized_kpi_config is not None:
with open(customized_kpi_config) as f:
config = json.load(f, object_pairs_hook=collections.OrderedDict)
for key in config.keys():
customizedkpis.append(kpicalculation.cutomizedKPI(config[key]))
customizedkpis_result[kpicalculation.cutomizedKPI(
config[key]).name] = []
customizedkpis_result['time'] = []
# --------------------
# RUN TEST CASE
# -------------
# Reset test case
print('Initializing the simualation.')
res = requests.put('{0}/initialize'.format(url),
data={
'start_time': 0,
'warmup_period': 0
})
if res:
print('Successfully initialized the simulation')
# Set simulation step
print('Setting simulation step to {0}.'.format(step))
res = requests.put('{0}/step'.format(url), data={'step': step})
print('\nRunning test case...')
# Initialize u
u = pid.initialize()
# Simulation Loop
for i in range(int(length / step)):
# Advance simulation
y = requests.post('{0}/advance'.format(url), data=u).json()
# Compute next control signal
u = pid.compute_control(y)
# Compute customized KPIs if any
if customized_kpi_config is not None:
for customizedkpi in customizedkpis:
customizedkpi.processing_data(
y) # Process data as needed for custom KPI
customizedkpi_value = customizedkpi.calculation(
) # Calculate custom KPI value
customizedkpis_result[customizedkpi.name].append(
round(customizedkpi_value, 2)) # Track custom KPI value
print('KPI:\t{0}:\t{1}'.format(
customizedkpi.name, round(customizedkpi_value,
2))) # Print custom KPI value
customizedkpis_result['time'].append(
y['time']) # Track custom KPI calculation time
print('\nTest case complete.')
# -------------
# VIEW RESULTS
# ------------
# Report KPIs
kpi = requests.get('{0}/kpi'.format(url)).json()
print('\nKPI RESULTS \n-----------')
for key in kpi.keys():
if key == 'tdis_tot':
unit = 'Kh'
if key == 'idis_tot':
unit = 'ppmh'
elif key == 'ener_tot':
unit = 'kWh'
elif key == 'cost_tot':
unit = 'euro or $'
elif key == 'emis_tot':
unit = 'kg CO2'
elif key == 'time_rat':
unit = ''
print('{0}: {1} {2}'.format(key, kpi[key], unit))
# ------------
# POST PROCESS RESULTS
# --------------------
# Get result data into result df
points = measurements.keys() + inputs.keys()
df_res = pd.DataFrame()
for point in points:
res = requests.put('{0}/results'.format(url),
data={
'point_name': point,
'start_time': 0,
'final_time': length
}).json()
df_res = pd.concat(
(df_res,
pd.DataFrame(data=res[point], index=res['time'], columns=[point
])),
axis=1)
df_res.index.name = 'time'
time = df_res.index.values / 3600 # convert s --> hr
TZone = df_res['TRooAir_y'].values - 273.15 # convert K --> C
PHeat = df_res['PHea_y'].values
QHeat = df_res['oveAct_u'].values
# Plot results
if plot:
from matplotlib import pyplot as plt
plt.figure(1)
plt.title('Zone Temperature')
plt.plot(time, TZone)
plt.plot(time, 20 * np.ones(len(time)), '--')
plt.plot(time, 23 * np.ones(len(time)), '--')
plt.ylabel('Temperature [C]')
plt.xlabel('Time [hr]')
plt.figure(2)
plt.title('Heater Power')
plt.plot(time, PHeat)
plt.ylabel('Electrical Power [W]')
plt.xlabel('Time [hr]')
plt.show()
# --------------------
return kpi, df_res, customizedkpis_result