import openstudio
import pandas as pd
def get_space_object_as_dict(osm_model: openstudio.model.Model, space_handle: str = None, space_name: str = None) -> dict:
"""
Retrieve a space from the OpenStudio model by either handle or name and return its attributes as a dictionary.
Parameters:
- osm_model (openstudio.model.Model): The OpenStudio Model object.
- space_handle (str, optional): The handle of the space to retrieve.
- space_name (str, optional): The name of the space to retrieve.
Returns:
- dict: Dictionary containing information about the specified space.
"""
if space_handle is not None and space_name is not None:
raise ValueError(
"Only one of 'space_handle' or 'space_name' should be provided.")
if space_handle is None and space_name is None:
raise ValueError(
"Either 'space_handle' or 'space_name' must be provided.")
# Find the space by handle or name
if space_handle is not None:
space_object = osm_model.getSpace(space_handle)
if space_object.isNull():
print(f"No space found with the handle: {space_handle}")
return {}
elif space_name is not None:
space_object = osm_model.getSpaceByName(space_name)
if space_object.isNull():
print(f"No space found with the name: {space_name}")
return {}
target_space = space_object.get()
# Define attributes to retrieve in a dictionary
space_dict = {
'Handle': str(target_space.handle()),
'Name': target_space.name().get() if target_space.name().is_initialized() else None,
'Space Type Name': target_space.spaceType().get().name().get() if target_space.spaceType().is_initialized() else None,
'Default Construction Set Name': target_space.defaultConstructionSet().get().name().get() if target_space.defaultConstructionSet().is_initialized() else None,
'Default Schedule Set Name': target_space.defaultScheduleSet().get().name().get() if target_space.defaultScheduleSet().is_initialized() else None,
'Direction of Relative North {deg}': target_space.directionofRelativeNorth(),
'X Origin {m}': target_space.xOrigin(),
'Y Origin {m}': target_space.yOrigin(),
'Z Origin {m}': target_space.zOrigin(),
'Building Story Name': target_space.buildingStory().get().name().get() if target_space.buildingStory().is_initialized() else None,
'Thermal Zone Name': target_space.thermalZone().get().name().get() if target_space.thermalZone().is_initialized() else None,
'Part of Total Floor Area': target_space.partofTotalFloorArea(),
'Design Specification Outdoor Air Object Name': target_space.designSpecificationOutdoorAir().get().name().get() if target_space.designSpecificationOutdoorAir().is_initialized() else None,
'Building Unit Name': target_space.buildingUnit().get().name().get() if target_space.buildingUnit().is_initialized() else None,
'Volume {m3}': target_space.volume(),
'Ceiling Height {m}': target_space.ceilingHeight(),
'Floor Area {m2}': target_space.floorArea()
}
return space_dict
def get_all_space_objects_as_dicts(osm_model: openstudio.model.Model) -> list[dict]:
"""
Retrieve all spaces from the OpenStudio model and return their attributes as a list of dictionaries.
Parameters:
- osm_model (openstudio.model.Model): The OpenStudio Model object.
Returns:
- list[dict]: A list of dictionaries, each containing information about a space.
"""
# Get all spaces in the OpenStudio model.
all_objects = osm_model.getSpaces()
all_objects_dicts = []
for target_object in all_objects:
space_handle = str(target_object.handle())
object_dict = get_space_object_as_dict(osm_model, space_handle)
all_objects_dicts.append(object_dict)
return all_objects_dicts
def get_all_space_objects_as_dataframe(osm_model: openstudio.model.Model) -> pd.DataFrame:
"""
Retrieve all spaces from the OpenStudio model using a specified method and return their attributes as a pandas DataFrame.
Parameters:
- osm_model (openstudio.model.Model): The OpenStudio Model object.
Returns:
- pd.DataFrame: DataFrame containing information about all spaces.
"""
all_objects_dicts = get_all_space_objects_as_dicts(osm_model)
# Create a DataFrame of all spaces.
all_spaces_df = pd.DataFrame(all_objects_dicts)
# Sort the DataFrame alphabetically by the Name column and reset indexes
all_spaces_df = all_spaces_df.sort_values(
by='Name', ascending=True).reset_index(drop=True)
print(f"The OSM model contains {all_spaces_df.shape[0]} spaces")
return all_spaces_df
def get_all_thermal_zones_objects_as_dataframe(osm_model: openstudio.model.Model) -> pd.DataFrame:
"""
Retrieve all thermal zones from the OpenStudio model and organize them into a pandas DataFrame.
Parameters:
- osm_model (openstudio.model.Model): The OpenStudio Model object.
Returns:
- pd.DataFrame: DataFrame containing information about all thermal zones.
"""
all_objects_dicts = get_all_thermal_zones_objects_as_dicts(osm_model)
# Create a DataFrame of all thermal zones.
all_thermal_zones_df = pd.DataFrame(all_objects_dicts)
# Sort the DataFrame alphabetically by the Name column and reset indexes
all_thermal_zones_df = all_thermal_zones_df.sort_values(
by='Name', ascending=True).reset_index(drop=True)
print(f"The OSM model contains {all_thermal_zones_df.shape[0]} thermal zones")
return all_thermal_zones_df
def update_space_object(osm_model, space_handle: str = None, space_name: str = None, attributes: dict = None):
target_object_dict = get_space_object_as_dict(
osm_model, space_handle, space_name)
