def from_idf(cls, idf_string, type_idf_string=None):
"""Create a ScheduleFixedInterval from an EnergyPlus IDF text strings.
Args:
idf_string: A text string fully describing an EnergyPlus
Schedule:File.
type_idf_string: An optional text string for the ScheduleTypeLimits.
If None, the resulting schedule will have no ScheduleTypeLimit.
"""
# process the schedule inputs
sch_fields = parse_idf_string(idf_string, 'Schedule:File')
schedule_type = ScheduleTypeLimit.from_idf(type_idf_string) if type_idf_string \
is not None else None
timestep = 60 / int(sch_fields[8]) if sch_fields[8] != '' else 1
start_date = Date(1, 1, False) if sch_fields[5] == '8760' else Date(
1, 1, True)
interpolate = False if sch_fields[7] == 'No' or sch_fields[
7] == '' else True
# load the data from the CSV file referenced in the string
assert os.path.isfile(sch_fields[2]), \
'CSV Schedule:File "{}" was not found on this system.'.format(sch_fields[2])
all_data = csv_to_matrix(sch_fields[2])
transposed_data = tuple(zip(*all_data))
csv_data = (float(x) for x in transposed_data[int(sch_fields[3]) -
1][int(sch_fields[4]):])
return cls(sch_fields[0], csv_data, schedule_type, timestep,
start_date, 0, interpolate)
def test_csv_to_matrix():
"""Test the csv_to_matrix functions."""
path = './tests/fixtures/epw/tokyo.epw'
epw_mtx = futil.csv_to_matrix(path)
assert len(epw_mtx) == 8768
with pytest.raises(Exception):
epw_mtx = futil.csv_to_num_matrix(path)
def __init__(self,
file_path,
cooling_date=Date(1, 1),
heating_date=Date(1, 1)):
"""Initialize ZSZ"""
# check that the file exists
assert os.path.isfile(file_path), 'No file was found at {}'.format(
file_path)
assert file_path.endswith('.csv'), \
'{} is not an CSV file ending in .csv.'.format(file_path)
self._file_path = file_path
# parse the data in the file
data_mtx = csv_to_matrix(file_path)
# extract the header and the peak values
headers = data_mtx[0][:] # copy the list
del headers[0]
peak = data_mtx[-3][:] # copy the list
del peak[0]
del data_mtx[0]
for i in range(3):
del data_mtx[-1]
self._headers = headers
self._peak = peak
# process the timestep of the data
data_mtx = list(zip(*data_mtx))
time1 = datetime.strptime(data_mtx[0][0], '%H:%M:%S')
time2 = datetime.strptime(data_mtx[0][1], '%H:%M:%S')
t_delta = time2 - time1
self._timestep = int(3600 / t_delta.seconds)
self._cooling_date = cooling_date
self._heating_date = heating_date
self._cool_a_period = AnalysisPeriod(cooling_date.month,
cooling_date.day,
0,
cooling_date.month,
cooling_date.day,
23,
timestep=self._timestep)
self._heat_a_period = AnalysisPeriod(heating_date.month,
heating_date.day,
0,
heating_date.month,
heating_date.day,
23,
timestep=self._timestep)
# process the body of the data
del data_mtx[0]
self._data = data_mtx
# properties to be computed upon request
self._cooling_load_data = None
self._heating_load_data = None
self._cooling_flow_data = None
self._heating_flow_data = None
def test_shcedule_fixedinterval_to_idf_collective_csv():
"""Test the to_idf_collective_csv method."""
ec_sched_idf = './tests/idf/ElectrochromicControlSchedules.idf'
ec_scheds = ScheduleFixedInterval.extract_all_from_idf_file(ec_sched_idf)
collective_string = ScheduleFixedInterval.to_idf_collective_csv(
ec_scheds, './tests/csv/', 'All Electrochromic')
assert len(collective_string) == 4
assert os.path.isfile('./tests/csv/All_Electrochromic.csv')
all_data = csv_to_matrix('./tests/csv/All_Electrochromic.csv')
assert len(all_data) == 8761
assert len(all_data[0]) >= 4
os.remove('./tests/csv/All_Electrochromic.csv')
1: 'Overloaded',
0: 'Normal'
})
volt_cond = GenericType('Voltage Condition',
'condition',
unit_descr={
-1: 'Undervoltage',
0: 'Normal',
1: 'Overvoltage'
})
if all_required_inputs(ghenv.Component):
factors, condition = [], []
for result_file in _dss_csv:
# parse the data and figure out the timeseries properties
data = csv_to_matrix(result_file)
csv_header = data.pop(0)
a_period = extract_analysis_period(data)
# figure out the type of object to write into the metadata
obj_name = os.path.basename(result_file).replace('.csv', '')
if obj_name.startswith('Line.'):
obj_name = obj_name.replace('Line.', '')
obj_type = 'Electrical Connector Loading'
elif obj_name.startswith('Transformer.'):
obj_name = obj_name.replace('Transformer.', '')
obj_type = 'Transformer Loading'
else:
obj_type = 'Building Voltage'
metadata = {'type': obj_type, 'name': obj_name}
values.append(val)
parameters.append(key.replace('_', ' ').title())
elif key == 'wind' and len(val) != 0:
wind = val[0]['size_kw']
elif key == 'solar_pv' and len(val) != 0:
pv = val[0]['size_kw']
elif key == 'storage' and len(val) != 0:
storage = [val[0]['size_kw'], val[0]['size_kwh']]
elif key == 'generator' and len(val) != 0:
generator = val[0]['size_kw']
# parse the CSV results of the simulation if successful
if os.path.isfile(re_csv):
data = [] # final list of data to be collected
# parse the data and figure out the timeseries properties
csv_data = csv_to_matrix(re_csv)
csv_header = csv_data.pop(0)
a_period = extract_analysis_period(csv_data)
for col, col_name in zip(zip(*csv_data), csv_header):
if col_name.startswith('REopt:'):
# figure out the type of object to write into the metadata
base_name = col_name.replace('REopt:', '').split(':')
end_name, units_init = base_name[-1].split('(')
units_init = units_init.replace(')', '')
if units_init == 'kw':
units, data_type = 'kW', Power()
elif units_init == 'pct':
units, data_type = 'fraction', Fraction()
else:
continue
metadata = {'type': ':'.join(base_name[:-1] + [end_name])}
def constructions_2004(model_json, climate_zone, output_file):
"""Convert a Model's constructions to be conformant with ASHRAE 90.1-2004 appendix G.
This includes assigning a ConstructionSet that is compliant with Table 5.5 to
all rooms in the model.
\b
Args:
model_json: Full path to a Model JSON file.
climate_zone: Text indicating the ASHRAE climate zone. This can be a single
integer (in which case it is interpreted as A) or it can include the
A, B, or C qualifier (eg. 3C).
"""
try:
# re-serialize the Model to Python and get the glazing ratios
with open(model_json) as json_file:
data = json.load(json_file)
model = Model.from_dict(data)
w_area = model.exterior_wall_area
r_area = model.exterior_roof_area
wr = model.exterior_wall_aperture_area / w_area if w_area != 0 else 0
sr = model.exterior_skylight_aperture_area / r_area if r_area != 0 else 0
# get the base ConstructionSet from the standards library
clean_cz = str(climate_zone)[0]
constr_set_id = '2004::ClimateZone{}::SteelFramed'.format(clean_cz)
base_set = construction_set_by_identifier(constr_set_id)
# parse the CSV file with exceptions to the base construction set
ex_file = os.path.join(os.path.dirname(__file__), 'data',
'ashrae_2004.csv')
ex_data = csv_to_matrix(ex_file)
ex_cz = clean_cz if climate_zone != '3C' else climate_zone
ex_ratio = '100'
for ratio in (40, 30, 20, 10):
if wr < ratio / 100 + 0.001:
ex_ratio = str(ratio)
for row in ex_data:
if row[0] == ex_cz and row[1] == ex_ratio:
vert_except = [float(val) for val in row[2:]]
break
# change the constructions for fixed and operable windows
si_ip_u = 5.678263337
fixed_id = 'U {} SHGC {} Fixed Glz'.format(vert_except[0],
vert_except[2])
fixed_mat = EnergyWindowMaterialSimpleGlazSys(fixed_id,
vert_except[0] * si_ip_u,
vert_except[2])
fixed_constr = WindowConstruction(fixed_id.replace('Glz', 'Window'),
[fixed_mat])
oper_id = 'U {} SHGC {} Operable Glz'.format(vert_except[1],
vert_except[2])
oper_mat = EnergyWindowMaterialSimpleGlazSys(oper_id,
vert_except[1] * si_ip_u,
vert_except[2])
oper_constr = WindowConstruction(oper_id.replace('Glz', 'Window'),
[oper_mat])
base_set.aperture_set.window_construction = fixed_constr
base_set.aperture_set.operable_construction = oper_constr
# change the construction for skylights if the ratio is greater than 2%
if sr > 0.021:
for row in ex_data:
if row[0] == ex_cz and row[1] == 'sky_5':
sky_except = [float(row[2]), float(row[4])]
break
sky_id = 'U {} SHGC {} Skylight Glz'.format(
sky_except[0], sky_except[1])
sky_mat = EnergyWindowMaterialSimpleGlazSys(
sky_id, sky_except[0] * si_ip_u, sky_except[1])
sky_constr = WindowConstruction(sky_id.replace('Glz', 'Window'),
[sky_mat])
base_set.aperture_set.skylight_construction = sky_constr
# remove child constructions ans assign the construction set to all rooms
model.properties.energy.remove_child_constructions()
for room in model.rooms:
room.properties.energy.construction_set = base_set
# write the Model JSON string
output_file.write(json.dumps(model.to_dict()))
except Exception as e:
_logger.exception(
'Model baseline construction creation failed.\n{}'.format(e))
sys.exit(1)
else:
sys.exit(0)
