class PointInTimeGridRayTracing(DAG):
"""Point-in-time grid-based ray tracing."""
# inputs
sensor_count = Inputs.int(
default=200,
description='The maximum number of grid points per parallel execution',
spec={
'type': 'integer',
'minimum': 1
})
radiance_parameters = Inputs.str(
description='The radiance parameters for ray tracing',
default='-ab 2 -aa 0.1 -ad 2048 -ar 64')
metric = Inputs.str(
description=
'Text for the type of metric to be output from the calculation. '
'Choose from: illuminance, irradiance, luminance, radiance.',
default='illuminance',
spec={
'type': 'string',
'enum': ['illuminance', 'irradiance', 'luminance', 'radiance']
})
octree_file = Inputs.file(description='A Radiance octree file.',
extensions=['oct'])
grid_name = Inputs.str(
description=
'Sensor grid file name. This is useful to rename the final result '
'file to {grid_name}.res')
sensor_grid = Inputs.file(description='Sensor grid file.',
extensions=['pts'])
bsdfs = Inputs.folder(
description='Folder containing any BSDF files needed for ray tracing.')
@task(template=SplitGrid)
def split_grid(self, sensor_count=sensor_count, input_grid=sensor_grid):
return [{
'from': SplitGrid()._outputs.grids_list
}, {
'from': SplitGrid()._outputs.output_folder,
'to': 'sub_grids'
}]
@task(template=RayTracingPointInTime,
needs=[split_grid],
loop=split_grid._outputs.grids_list,
sub_folder='results',
sub_paths={'grid': '{{item.path}}'})
def ray_tracing(self,
radiance_parameters=radiance_parameters,
metric=metric,
grid=split_grid._outputs.output_folder,
scene_file=octree_file,
bsdf_folder=bsdfs):
return [{
'from': RayTracingPointInTime()._outputs.result,
'to': '{{item.name}}.res'
}]
@task(template=MergeFiles, needs=[ray_tracing])
def merge_results(self,
name=grid_name,
extension='.res',
folder='results'):
return [{
'from': MergeFiles()._outputs.result_file,
'to': '../../results/{{self.name}}.res'
}]
class AnnualDaylightRayTracing(DAG):
# inputs
radiance_parameters = Inputs.str(
description='The radiance parameters for ray tracing',
default='-ab 2 -ad 5000 -lw 2e-05')
octree_file_with_suns = Inputs.file(
description='A Radiance octree file with suns.', extensions=['oct'])
octree_file = Inputs.file(description='A Radiance octree file.',
extensions=['oct'])
grid_name = Inputs.str(
description=
'Sensor grid file name. This is useful to rename the final result '
'file to {grid_name}.ill')
sensor_grid = Inputs.file(description='Sensor grid file.',
extensions=['pts'])
sensor_count = Inputs.int(
description='Number of sensors in the input sensor grid.')
sun_modifiers = Inputs.file(description='A file with sun modifiers.')
sky_matrix = Inputs.file(description='Path to total sky matrix file.')
sky_matrix_direct = Inputs.file(
description='Path to direct skymtx file (i.e. gendaymtx -d).')
sky_dome = Inputs.file(description='Path to sky dome file.')
bsdfs = Inputs.folder(
description='Folder containing any BSDF files needed for ray tracing.',
optional=True)
@task(template=DaylightContribution)
def direct_sunlight(
self,
name=grid_name,
radiance_parameters=radiance_parameters,
fixed_radiance_parameters='-aa 0.0 -I -ab 0 -dc 1.0 -dt 0.0 -dj 0.0 -dr 0',
sensor_count=sensor_count,
modifiers=sun_modifiers,
sensor_grid=sensor_grid,
output_format='a', # make it ascii so we expose the file as a separate output
scene_file=octree_file_with_suns,
bsdf_folder=bsdfs):
return [{
'from': DaylightContribution()._outputs.result_file,
'to': '../final/direct/{{self.name}}.ill'
}]
@task(template=DaylightCoefficient)
def direct_sky(self,
radiance_parameters=radiance_parameters,
fixed_radiance_parameters='-aa 0.0 -I -ab 1 -c 1 -faf',
sensor_count=sensor_count,
sky_matrix=sky_matrix_direct,
sky_dome=sky_dome,
sensor_grid=sensor_grid,
scene_file=octree_file,
bsdf_folder=bsdfs):
return [{
'from': DaylightCoefficient()._outputs.result_file,
'to': 'direct_sky.ill'
}]
@task(template=DaylightCoefficient)
def total_sky(self,
radiance_parameters=radiance_parameters,
fixed_radiance_parameters='-aa 0.0 -I -c 1 -faf',
sensor_count=sensor_count,
sky_matrix=sky_matrix,
sky_dome=sky_dome,
sensor_grid=sensor_grid,
scene_file=octree_file,
bsdf_folder=bsdfs):
return [{
'from': DaylightCoefficient()._outputs.result_file,
'to': 'total_sky.ill'
}]
@task(template=AddRemoveSkyMatrix,
needs=[direct_sunlight, total_sky, direct_sky])
def output_matrix_math(
self,
name=grid_name,
direct_sky_matrix=direct_sky._outputs.result_file,
total_sky_matrix=total_sky._outputs.result_file,
sunlight_matrix=direct_sunlight._outputs.result_file,
conversion='47.4 119.9 11.6'):
return [{
'from': AddRemoveSkyMatrix()._outputs.results_file,
'to': '../final/total/{{self.name}}.ill'
}]
class DynamicShadeContribEntryPoint(DAG):
"""Entry point for computing the contributions from dynamic windows."""
# inputs
radiance_parameters = Inputs.str(
description='Radiance parameters for ray tracing.',
default='-ab 2 -ad 5000 -lw 2e-05',
)
octree_file = Inputs.file(
description=
'A Radiance octree file with a completely transparent version '
'of the dynamic shade group.',
extensions=['oct'])
octree_file_with_suns = Inputs.file(
description='A Radiance octree file with sun modifiers.',
extensions=['oct'])
group_name = Inputs.str(
description='Name for the dynamic aperture group being simulated.')
sensor_grid_folder = Inputs.folder(
description=
'A folder containing all of the split sensor grids in the model.')
sensor_grids = Inputs.file(
description=
'A JSON file with information about sensor grids to loop over.')
sky_dome = Inputs.file(description='Path to sky dome file.')
sky_matrix = Inputs.file(description='Path to total sky matrix file.')
sky_matrix_direct = Inputs.file(
description='Path to direct skymtx file (gendaymtx -d).')
sun_modifiers = Inputs.file(description='A file with sun modifiers.')
sun_up_hours = Inputs.file(
description=
'A sun-up-hours.txt file output by Radiance and aligns with the '
'input irradiance files.')
@task(template=ReadJSONList)
def read_grids_for_shade(self, src=sensor_grids) -> List[Dict]:
return [{
'from': ReadJSONList()._outputs.data,
'description': 'Sensor grids information.'
}]
@task(template=ShadeContribEntryPoint,
needs=[read_grids_for_shade],
loop=read_grids_for_shade._outputs.data,
sub_folder='shortwave',
sub_paths={
'sensor_grid': '{{item.full_id}}.pts',
'ref_sensor_grid': '{{item.full_id}}_ref.pts',
})
def run_radiance_shade_contrib(self,
radiance_parameters=radiance_parameters,
octree_file=octree_file,
octree_file_with_suns=octree_file_with_suns,
group_name=group_name,
grid_name='{{item.full_id}}',
sensor_grid=sensor_grid_folder,
ref_sensor_grid=sensor_grid_folder,
sensor_count='{{item.count}}',
sky_dome=sky_dome,
sky_matrix=sky_matrix,
sky_matrix_direct=sky_matrix_direct,
sun_modifiers=sun_modifiers,
sun_up_hours=sun_up_hours) -> List[Dict]:
pass
class ComfortMappingEntryPoint(DAG):
"""Entry point for Comfort calculations."""
# inputs
epw = Inputs.file(
description='Weather file used for the comfort map.',
extensions=['epw']
)
result_sql = Inputs.file(
description='A SQLite file that was generated by EnergyPlus and contains '
'hourly or sub-hourly thermal comfort results.',
extensions=['sql', 'db', 'sqlite']
)
grid_name = Inputs.str(
description='Sensor grid file name (used to name the final result files).'
)
enclosure_info = Inputs.file(
description='A JSON file containing information about the radiant '
'enclosure that sensor points belong to.',
extensions=['json']
)
view_factors = Inputs.file(
description='A CSV of spherical view factors to the surfaces in the result-sql.',
extensions=['csv']
)
modifiers = Inputs.file(
description='Path to a modifiers file that aligns with the view-factors.',
extensions=['mod', 'txt']
)
indirect_irradiance = Inputs.file(
description='An .ill containing the indirect irradiance for each sensor.',
extensions=['ill', 'irr']
)
direct_irradiance = Inputs.file(
description='An .ill containing direct irradiance for each sensor.',
extensions=['ill', 'irr']
)
ref_irradiance = Inputs.file(
description='An .ill containing ground-reflected irradiance for each '
'sensor.', extensions=['ill', 'irr']
)
sun_up_hours = Inputs.file(
description='A sun-up-hours.txt file output by Radiance and aligns with the '
'input irradiance files.'
)
contributions = Inputs.folder(
description='An optional folder containing sub-folders of irradiance '
'contributions from dynamic aperture groups. There should be one sub-folder '
'per window group and each one should contain three .ill files named '
'direct.ill, indirect.ill and reflected.ill. If specified, these will be '
'added to the irradiance inputs before computing shortwave MRT deltas.',
optional=True
)
transmittance_contribs = Inputs.folder(
description='An optional folder containing a transmittance schedule JSON '
'and sub-folders of irradiance results that exclude the shade from the '
'calculation. There should be one sub-folder per window groups and each '
'one should contain three .ill files named direct.ill, indirect.ill and '
'reflected.ill. If specified, these will be added to the irradiance inputs '
'before computing shortwave MRT deltas.', optional=True
)
trans_schedules = Inputs.file(
description='A schedule JSON that contains fractional schedule values '
'for each shade transmittance schedule in the model.'
)
occ_schedules = Inputs.file(
description='A JSON file containing occupancy schedules derived from '
'the input model.'
)
run_period = Inputs.str(
description='An AnalysisPeriod string to set the start and end dates of '
'the simulation (eg. "6/21 to 9/21 between 0 and 23 @1"). If None, '
'the simulation will be annual.', default=''
)
air_speed = Inputs.file(
description='A CSV file containing a single number for air speed in m/s or '
'several rows of air speeds that align with the length of the run period.',
optional=True
)
met_rate = Inputs.file(
description='A CSV file containing a single number for metabolic rate in met '
'or several rows of met values that align with the length of the run period.',
optional=True
)
clo_value = Inputs.file(
description='A CSV file containing a single number for clothing level in clo '
'or several rows of clo values that align with the length of the run period.',
optional=True
)
solarcal_parameters = Inputs.str(
description='A SolarCalParameter string to customize the assumptions of '
'the SolarCal model.', default='--posture seated --sharp 135 '
'--absorptivity 0.7 --emissivity 0.95'
)
comfort_parameters = Inputs.str(
description='An PMVParameter string to customize the assumptions of '
'the PMV comfort model.', default='--ppd-threshold 10'
)
write_set_map = Inputs.str(
description='A switch to note whether the output temperature CSV should '
'record Operative Temperature or Standard Effective Temperature (SET).',
default='write-op-map'
)
@task(template=LongwaveMrtMap)
def create_longwave_mrt_map(
self,
result_sql=result_sql,
view_factors=view_factors,
modifiers=modifiers,
enclosure_info=enclosure_info,
epw=epw,
run_period=run_period,
name=grid_name
) -> List[Dict]:
return [
{
'from': LongwaveMrtMap()._outputs.longwave_mrt_map,
'to': 'conditions/longwave_mrt/{{self.name}}.csv'
}
]
@task(template=ShortwaveMrtMap)
def create_shortwave_mrt_map(
self,
epw=epw,
indirect_irradiance=indirect_irradiance,
direct_irradiance=direct_irradiance,
ref_irradiance=ref_irradiance,
sun_up_hours=sun_up_hours,
contributions=contributions,
transmittance_contribs=transmittance_contribs,
trans_schedules=trans_schedules,
solarcal_par=solarcal_parameters,
run_period=run_period,
name=grid_name
) -> List[Dict]:
return [
{
'from': ShortwaveMrtMap()._outputs.shortwave_mrt_map,
'to': 'conditions/shortwave_mrt/{{self.name}}.csv'
}
]
@task(template=AirMap)
def create_air_temperature_map(
self,
result_sql=result_sql,
enclosure_info=enclosure_info,
epw=epw,
run_period=run_period,
metric='air-temperature',
name=grid_name
) -> List[Dict]:
return [
{
'from': AirMap()._outputs.air_map,
'to': 'conditions/air_temperature/{{self.name}}.csv'
}
]
@task(template=AirMap)
def create_rel_humidity_map(
self,
result_sql=result_sql,
enclosure_info=enclosure_info,
epw=epw,
run_period=run_period,
metric='relative-humidity',
name=grid_name
) -> List[Dict]:
return [
{
'from': AirMap()._outputs.air_map,
'to': 'conditions/rel_humidity/{{self.name}}.csv'
}
]
@task(template=AirSpeedJson)
def create_air_speed_json(
self, epw=epw, enclosure_info=enclosure_info, multiply_by=0.5,
indoor_air_speed=air_speed, run_period=run_period, name=grid_name
) -> List[Dict]:
return [
{
'from': AirSpeedJson()._outputs.air_speeds,
'to': 'conditions/air_speed/{{self.name}}.json'
}
]
@task(
template=PmvMtx,
needs=[
create_longwave_mrt_map, create_shortwave_mrt_map,
create_air_temperature_map, create_rel_humidity_map, create_air_speed_json
]
)
def process_pmv_matrix(
self,
air_temperature_mtx=create_air_temperature_map._outputs.air_map,
rel_humidity_mtx=create_rel_humidity_map._outputs.air_map,
rad_temperature_mtx=create_longwave_mrt_map._outputs.longwave_mrt_map,
rad_delta_mtx=create_shortwave_mrt_map._outputs.shortwave_mrt_map,
air_speed_json=create_air_speed_json._outputs.air_speeds,
met_rate=met_rate,
clo_value=clo_value,
comfort_par=comfort_parameters,
write_set_map=write_set_map,
name=grid_name
) -> List[Dict]:
return [
{
'from': PmvMtx()._outputs.temperature_map,
'to': 'results/temperature/{{self.name}}.csv'
},
{
'from': PmvMtx()._outputs.condition_map,
'to': 'results/condition/{{self.name}}.csv'
},
{
'from': PmvMtx()._outputs.pmv_map,
'to': 'results/condition_intensity/{{self.name}}.csv'
}
]
@task(
template=Tcp,
needs=[process_pmv_matrix]
)
def compute_tcp(
self,
condition_csv=process_pmv_matrix._outputs.condition_map,
enclosure_info=enclosure_info,
occ_schedule_json=occ_schedules,
name=grid_name
) -> List[Dict]:
return [
{'from': Tcp()._outputs.tcp, 'to': 'metrics/TCP/{{self.name}}.csv'},
{'from': Tcp()._outputs.hsp, 'to': 'metrics/HSP/{{self.name}}.csv'},
{'from': Tcp()._outputs.csp, 'to': 'metrics/CSP/{{self.name}}.csv'}
]