def get_results_windows(sql_files):
# set initial values that will be computed based on results
total_floor_area, total_energy = 0, 0
end_uses = OrderedDict()
# loop through the sql files in the directory and add the energy use
for result_file in sql_files:
# parse the SQL file
sql_obj = SQLiteResult(result_file)
# get the total floor area of the model
area_dict = sql_obj.tabular_data_by_name('Building Area')
areas = tuple(area_dict.values())
total_floor_area += areas[0][0]
# get the energy use
eui_dict = sql_obj.tabular_data_by_name('End Uses By Subcategory')
for catgory, vals in eui_dict.items():
total_use = sum([val for val in vals[:12]])
if total_use != 0:
total_energy += total_use
cat, sub_cat = catgory.split(':')
eu_cat = cat if sub_cat == 'General' or sub_cat == 'Other' else sub_cat
try:
end_uses[eu_cat] += total_use
except KeyError:
end_uses[eu_cat] = total_use
# assemble all of the results into a final dictionary
eui = round(total_energy / total_floor_area, 3)
gross_floor = round(total_floor_area, 3)
end_use_pairs = OrderedDict([(key, round(val / total_floor_area, 3))
for key, val in end_uses.items()])
return eui, gross_floor, end_use_pairs
def get_results_windows(sql_files):
# set initial values that will be computed based on results
total_floor_area, total_energy = 0, 0
all_uses = \
('heating', 'cooling', 'interior_lighting', 'exterior_lighting',
'interior_equipment', 'exterior_equipment', 'fans', 'pumps',
'heat_rejection', 'humidification', 'heat_recovery', 'water_systems',
'refrigeration', 'generators')
end_uses = OrderedDict()
for use in all_uses:
end_uses[use] = 0
# loop through the sql files in the directory and add the energy use
for result_file in sql_files:
# parse the SQL file
sql_obj = SQLiteResult(result_file)
# get the total floor area of the model
area_dict = sql_obj.tabular_data_by_name('Building Area')
areas = tuple(area_dict.values())
total_floor_area += areas[0][0]
# get the energy use
eui_dict = sql_obj.tabular_data_by_name('End Uses')
euis = tuple(eui_dict.values())
total_energy += sum([val for val in euis[-2][:12]])
end_uses['heating'] += sum([val for val in euis[0][:12]])
end_uses['cooling'] += sum([val for val in euis[1][:12]])
end_uses['interior_lighting'] += sum([val for val in euis[2][:12]])
end_uses['exterior_lighting'] += sum([val for val in euis[3][:12]])
end_uses['interior_equipment'] += sum([val for val in euis[4][:12]])
end_uses['exterior_equipment'] += sum([val for val in euis[5][:12]])
end_uses['fans'] += sum([val for val in euis[6][:12]])
end_uses['pumps'] += sum([val for val in euis[7][:12]])
end_uses['heat_rejection'] += sum([val for val in euis[8][:12]])
end_uses['humidification'] += sum([val for val in euis[9][:12]])
end_uses['heat_recovery'] += sum([val for val in euis[10][:12]])
end_uses['water_systems'] += sum([val for val in euis[11][:12]])
end_uses['refrigeration'] += sum([val for val in euis[12][:12]])
end_uses['generators'] += sum([val for val in euis[13][:12]])
# assemble all of the results into a final dictionary
eui = round(total_energy / total_floor_area, 3)
gross_floor = round(total_floor_area, 3)
end_use_pairs = OrderedDict([(key, round(val / total_floor_area, 3))
for key, val in end_uses.items() if val != 0])
return eui, gross_floor, end_use_pairs
def test_sqlite_tabular_data():
"""Test the tabular_data_by_name method."""
sql_path = './tests/assets/sql/eplusout_monthly.sql'
sql_obj = SQLiteResult(sql_path)
data = sql_obj.tabular_data_by_name(
'Utility Use Per Conditioned Floor Area')
assert len(data) == 4
assert len(data['Lighting']) == 6
col_names = sql_obj.tabular_column_names(
'Utility Use Per Conditioned Floor Area')
assert len(col_names) == 6
assert 'Electricity Intensity' in col_names[0]
def tabular_data(result_sql, table_name, output_file):
"""Get all the data within a table of a Summary Report using the table name.
\b
Args:
result_sql: Full path to an SQLite file that was generated by EnergyPlus.
table_name: Text string for the name of a table within a summary
report. (eg. 'General').
"""
try:
sql_obj = SQLiteResult(result_sql)
table_dict = sql_obj.tabular_data_by_name(str(table_name))
output_file.write(json.dumps(list(table_dict.values())))
except Exception as e:
_logger.exception('Failed to retrieve table data from sql file.\n{}'.format(e))
sys.exit(1)
else:
sys.exit(0)
def tabular_metadata(result_sql, table_name, output_file):
"""Get a dictionary with the names of a table's rows and columns.
\b
Args:
result_sql: Full path to an SQLite file that was generated by EnergyPlus.
table_name: Text string for the name of a table within a summary
report. (eg. 'General').
"""
try:
sql_obj = SQLiteResult(result_sql)
table_dict = sql_obj.tabular_data_by_name(str(table_name))
row_names = list(table_dict.keys())
col_names = sql_obj.tabular_column_names(str(table_name))
output_file.write(json.dumps(
{'row_names': row_names, 'column_names': col_names}))
except Exception as e:
_logger.exception('Failed to retrieve table data from sql file.\n{}'.format(e))
sys.exit(1)
else:
sys.exit(0)
raise ImportError('\nFailed to import ladybug:\n\t{}'.format(e))
try:
from honeybee.config import folders
except ImportError as e:
raise ImportError('\nFailed to import honeybee:\n\t{}'.format(e))
try:
from ladybug_rhino.grasshopper import all_required_inputs, list_to_data_tree
except ImportError as e:
raise ImportError('\nFailed to import ladybug_rhino:\n\t{}'.format(e))
if all_required_inputs(ghenv.Component):
if os.name == 'nt': # we are on windows; use IronPython like usual
sql_obj = SQLiteResult(_sql) # create the SQL result parsing object
results = sql_obj.tabular_data_by_name(_table_name)
values = list_to_data_tree(list(results.values()))
row_names = list(results.keys())
col_names = sql_obj.tabular_column_names(_table_name)
else: # we are on Mac; sqlite3 module doesn't work in Mac IronPython
# Execute the honybee CLI to obtain the results via CPython
cmds = [
folders.python_exe_path, '-m', 'honeybee_energy', 'result',
'tabular-data', _sql, _table_name
]
process = subprocess.Popen(cmds, stdout=subprocess.PIPE)
stdout = process.communicate()
results = json.loads(stdout[0])
values = list_to_data_tree(results)
cmds = [
def energy_use_intensity(result_paths, si, output_file):
"""Get information about energy use intensity and an EUI breakdown by end use.
\b
Args:
result_paths: Path to one or more SQLite files that were generated by
EnergyPlus or folders containing such files. Folders can be from a
single EnergyPlus simulation or may contain multiple SQLite files.
EUI will be computed across all files provided.
"""
try:
# set initial values that will be computed based on results
total_floor_area, conditioned_floor_area, total_energy = 0, 0, 0
all_uses = \
('heating', 'cooling', 'interior_lighting', 'exterior_lighting',
'interior_equipment', 'exterior_equipment', 'fans', 'pumps',
'heat_rejection', 'humidification', 'heat_recovery', 'water_systems',
'refrigeration', 'generators')
end_uses = {}
for use in all_uses:
end_uses[use] = 0
# create a list of sql file path that were either passed directly or are
# contained within passed folders
sql_paths = []
for file_or_folder_path in result_paths:
if os.path.isdir(file_or_folder_path):
for file_path in os.listdir(file_or_folder_path):
if file_path.endswith('.sql'):
sql_paths.append(os.path.join(file_or_folder_path, file_path))
elif file_or_folder_path.endswith('.sql'):
sql_paths.append(file_or_folder_path)
# loop through the sql files and add the energy use
for sql_path in sql_paths:
# parse the SQL file
sql_obj = SQLiteResult(sql_path)
# get the total floor area of the model
area_dict = sql_obj.tabular_data_by_name('Building Area')
areas = tuple(area_dict.values())
total_floor_area += areas[0][0]
conditioned_floor_area += areas[1][0]
# get the energy use
eui_dict = sql_obj.tabular_data_by_name('End Uses')
euis = tuple(eui_dict.values())
total_energy += sum([val for val in euis[-2][:12]])
end_uses['heating'] += sum([val for val in euis[0][:12]])
end_uses['cooling'] += sum([val for val in euis[1][:12]])
end_uses['interior_lighting'] += sum([val for val in euis[2][:12]])
end_uses['exterior_lighting'] += sum([val for val in euis[3][:12]])
end_uses['interior_equipment'] += sum([val for val in euis[4][:12]])
end_uses['exterior_equipment'] += sum([val for val in euis[5][:12]])
end_uses['fans'] += sum([val for val in euis[6][:12]])
end_uses['pumps'] += sum([val for val in euis[7][:12]])
end_uses['heat_rejection'] += sum([val for val in euis[8][:12]])
end_uses['humidification'] += sum([val for val in euis[9][:12]])
end_uses['heat_recovery'] += sum([val for val in euis[10][:12]])
end_uses['water_systems'] += sum([val for val in euis[11][:12]])
end_uses['refrigeration'] += sum([val for val in euis[12][:12]])
end_uses['generators'] += sum([val for val in euis[13][:12]])
# assemble all of the results into a final dictionary
result_dict = {
'eui': round(total_energy / total_floor_area, 3),
'total_floor_area': total_floor_area,
'conditioned_floor_area': conditioned_floor_area,
'total_energy': round(total_energy, 3)
}
result_dict['end_uses'] = {key: round(val / total_floor_area, 3)
for key, val in end_uses.items() if val != 0}
# convert data to IP if requested
if not si:
eui_typ, a_typ, e_typ = EnergyIntensity(), Area(), Energy()
result_dict['eui'] = \
round(eui_typ.to_ip([result_dict['eui']], 'kWh/m2')[0][0], 3)
result_dict['total_floor_area'] = \
round(a_typ.to_ip([result_dict['total_floor_area']], 'm2')[0][0], 3)
result_dict['conditioned_floor_area'] = \
round(a_typ.to_ip(
[result_dict['conditioned_floor_area']], 'm2')[0][0], 3)
result_dict['total_energy'] = \
round(e_typ.to_ip([result_dict['total_energy']], 'kWh')[0][0], 3)
result_dict['end_uses'] = \
{key: round(eui_typ.to_ip([val], 'kWh/m2')[0][0], 3)
for key, val in result_dict['end_uses'].items()}
# write everthing into the output file
output_file.write(json.dumps(result_dict, indent=4))
except Exception as e:
_logger.exception('Failed to compute EUI from sql files.\n{}'.format(e))
sys.exit(1)
else:
sys.exit(0)