class MergeImages(Function):
"""Merge several .HDR image files with similar starting name into one."""
folder = Inputs.folder(
description='Target folder with the input .HDR image files.',
path='input_folder')
name = Inputs.str(description='Base name for files to be merged.',
default='view')
extension = Inputs.str(
description='File extension including the . before the extension '
'(e.g. .HDR, .pic, .unf)',
default='.unf')
scale_factor = Inputs.float(
description='A number that will be used to scale the dimensions of the '
'output image as it is filtered for anti-aliasing.',
default=1)
@command
def merge_files(self):
return 'honeybee-radiance view merge input_folder view ' \
'{{self.extension}} --scale-factor {{self.scale_factor}} ' \
'--name {{self.name}}'
result_image = Outputs.file(description='Output combined image file.',
path='{{self.name}}.HDR')
class EnergyUseIntensity(Function):
"""Get information about energy use intensity from energy simulation SQLite files."""
result_folder = Inputs.folder(
description='Path to folder containing SQLite files that were generated '
'by EnergyPlus. This can be a single EnergyPlus simulation folder or '
'it can be a folder with multiple sql files, in which case EUI will '
'be computed across all results.',
path='result_folder')
units = Inputs.str(
description=
'A switch to indicate whether the data in the resulting JSON '
'should be in SI or IP units. Valid values are "si" and "ip".',
default='si',
spec={
'type': 'string',
'enum': ['si', 'ip']
})
@command
def energy_use_intensity(self):
return 'honeybee-energy result energy-use-intensity result_folder ' \
'--{{inputs.units}} --output-file output.json'
eui_json = Outputs.file(
description=
'A JSON object with the following keys - eui, total_floor_area, '
'total_energy, end_uses. The eui value is the energy use intensity across '
'the total floor area. The end_uses value is a dictionary containing a '
'breakdown of the eui by end use.',
path='output.json')
class CreateOctree(Function):
"""Generate an octree from a Radiance folder."""
# inputs
include_aperture = Inputs.str(
default='include',
description=
'A value to indicate if the static aperture should be included in '
'octree. Valid values are include and exclude. Default is include.',
spec={
'type': 'string',
'enum': ['include', 'exclude']
})
black_out = Inputs.str(
default='default',
description=
'A value to indicate if the black material should be used. Valid '
'values are default and black. Default value is default.',
spec={
'type': 'string',
'enum': ['black', 'default']
})
model = Inputs.folder(description='Path to Radiance model folder.',
path='model')
@command
def create_octree(self):
return 'honeybee-radiance octree from-folder model --output scene.oct ' \
'--{{self.include_aperture}}-aperture --{{self.black_out}}'
# outputs
scene_file = Outputs.file(description='Output octree file.',
path='scene.oct')
class MergeFiles(Function):
"""Merge several files with similar starting name into one."""
name = Inputs.str(
description='Base name for files to be merged.',
default='grid'
)
extension = Inputs.str(
description='File extension including the . before the extension (e.g. .res, '
'.ill)'
)
folder = Inputs.folder(
description='Target folder with the input files.',
path='input_folder'
)
@command
def merge_files(self):
return 'honeybee-radiance grid merge input_folder grid ' \
' {{self.extension}} --name {{self.name}}'
result_file = Outputs.file(
description='Output result file.', path='{{self.name}}{{self.extension}}'
)
class AnnualDaylightMetrics(Function):
"""Calculate annual daylight metrics for annual daylight simulation."""
folder = Inputs.folder(
description='This folder is an output folder of annual daylight recipe. Folder '
'should include grids_info.json and sun-up-hours.txt. The command uses the list '
'in grids_info.json to find the result files for each sensor grid.',
path='raw_results'
)
schedule = Inputs.file(
description='Path to an annual schedule file. Values should be 0-1 separated '
'by new line. If not provided an 8-5 annual schedule will be created.',
path='schedule.txt', optional=True
)
thresholds = Inputs.str(
description='A string to change the threshold for daylight autonomy and useful '
'daylight illuminance. Valid keys are -t for daylight autonomy threshold, -lt '
'for the lower threshold for useful daylight illuminance and -ut for the upper '
'threshold. The defult is -t 300 -lt 100 -ut 3000. The order of the keys is not '
'important and you can include one or all of them. For instance if you only '
'want to change the upper threshold to 2000 lux you should use -ut 2000 as '
'the input.', default='-t 300 -lt 100 -ut 3000'
)
@command
def calculate_annual_metrics(self):
return 'honeybee-radiance post-process annual-daylight raw_results ' \
'--schedule schedule.txt {{self.thresholds}} --sub_folder ../metrics'
# outputs
annual_metrics = Outputs.folder(
description='Annual metrics folder. This folder includes all the other '
'subfolders which are also exposed as separate outputs.', path='metrics'
)
daylight_autonomy = Outputs.folder(
description='Daylight autonomy results.', path='metrics/da'
)
continuous_daylight_autonomy = Outputs.folder(
description='Continuous daylight autonomy results.', path='metrics/cda'
)
useful_daylight_illuminance_lower = Outputs.folder(
description='Lower useful daylight illuminance results.',
path='metrics/udi_lower'
)
useful_daylight_illuminance = Outputs.folder(
description='Useful daylight illuminance results.', path='metrics/udi'
)
useful_daylight_illuminance_upper = Outputs.folder(
description='Upper useful daylight illuminance results.',
path='metrics/udi_upper'
)
class RayTracingPicture(Function):
"""Run ray-tracing with rpict command for an input octree and a view file.."""
view = Inputs.file(description='Input view file.', path='view.vf')
scene_file = Inputs.file(
description='Path to an octree file to describe the scene.', path='scene.oct'
)
radiance_parameters = Inputs.str(
description='Radiance parameters to be exposed within recipes. -h is '
'usually already included in the fixed_radiance_parameters and -I will '
'be overwritten based on the input metric.', default='-ab 2'
)
metric = Inputs.str(
description='Text for the type of metric to be output from the calculation. '
'Choose from: illuminance, irradiance, luminance, radiance.',
default='luminance',
spec={'type': 'string',
'enum': ['illuminance', 'irradiance', 'luminance', 'radiance']}
)
resolution = Inputs.int(
description='An integer for the maximum dimension of the image in pixels '
'(either width or height depending on the input view angle and type).',
spec={'type': 'integer', 'minimum': 1}, default=512
)
scale_factor = Inputs.float(
description='A number that will be multiplied by the input resolution to '
'scale the dimensions of the output image. This is useful in workflows if '
'one plans to re-scale the image after the ray tracing calculation to '
'improve anti-aliasing.', default=1
)
ambient_cache = Inputs.file(
description='Path to the ambient cache if an overture calculation was '
'specified. If unspecified, no ambient cache will be used.',
path='view.amb', optional=True
)
bsdf_folder = Inputs.folder(
description='Folder containing any BSDF files needed for ray tracing.',
path='model/bsdf', optional=True
)
@command
def ray_tracing(self):
return 'honeybee-radiance rpict rpict scene.oct view.vf ' \
'--rad-params "{{self.radiance_parameters}}" --metric {{self.metric}} ' \
'--resolution {{self.resolution}} --scale-factor {{self.scale_factor}} ' \
'--output view.HDR'
result_image = Outputs.file(
description='Path to the High Dynamic Range (HDR) image file of the '
'input view.', path='view.HDR'
)
class RayTracingPointInTime(Function):
"""Run ray-tracing and post-process the results for a point-in-time simulation."""
radiance_parameters = Inputs.str(
description='Radiance parameters to be exposed within recipes. -h is '
'usually already included in the fixed_radiance_parameters and -I will '
'be overwritten based on the input metric.',
default='-ab 2')
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']
})
fixed_radiance_parameters = Inputs.str(
description=
'Parameters that are meant to be fixed for a given recipe and '
'should not be overwritten by radiance_parameters input.',
default='-h')
grid = Inputs.file(description='Input sensor grid.', path='grid.pts')
scene_file = Inputs.file(
description='Path to an octree file to describe the scene.',
path='scene.oct')
bsdf_folder = Inputs.folder(
description='Folder containing any BSDF files needed for ray tracing.',
path='model/bsdf',
optional=True)
@command
def ray_tracing(self):
return 'honeybee-radiance raytrace point-in-time scene.oct grid.pts ' \
'--rad-params "{{self.radiance_parameters}}" --rad-params-locked ' \
'"{{self.fixed_radiance_parameters}}" --metric {{self.metric}} ' \
'--output grid.res'
result = Outputs.file(
description=
'Point-in-time result file. The result for each sensor is in a '
'new line of the file. Values are in standard SI units of the input '
'metric (lux, W/m2, cd/m2, W/m2-sr).',
path='grid.res')
class SplitGridFromFolder(SplitGrid):
"""Split a single sensor grid file into multiple grids based on maximum number
of sensors.
This function takes a folder of sensor grids and find the target grid based on
grid-name.
"""
name = Inputs.str(description='Grid name.')
input_grid = Inputs.folder(description='Path to sensor grids folder.', path='.')
@command
def split_grid(self):
return 'honeybee-radiance grid split {{self.name}}.pts ' \
'{{self.sensor_count}} --folder output --log-file output/grids_info.json'
class AnnualIrradianceMetrics(Function):
"""Calculate annual irradiance metrics for annual irradiance simulation."""
folder = Inputs.folder(
description='A folder output from and annual irradiance recipe.',
path='raw_results')
wea = Inputs.file(
description=
'The .wea file that was used in the annual irradiance simulation. '
'This will be used to determine the duration of the analysis for computing '
'average irradiance.',
path='weather.wea')
timestep = Inputs.int(
description='The timestep of the Wea file, which is used to ensure the '
'summed row of irradiance yields cumulative radiation over the time '
'period of the Wea.',
default=1)
@command
def calculate_irradiance_metrics(self):
return 'honeybee-radiance post-process annual-irradiance raw_results ' \
'weather.wea --timestep {{self.timestep}} --sub-folder ../metrics'
# outputs
metrics = Outputs.folder(
description='Annual irradiance metrics folder. This folder includes all '
'the other subfolders which are exposed as separate outputs.',
path='metrics')
average_irradiance = Outputs.folder(
description=
'Average irradiance in W/m2 for each sensor over the wea period.',
path='metrics/average_irradiance')
peak_irradiance = Outputs.folder(
description=
'The highest irradiance value in W/m2 for each sensor during '
'the wea period.',
path='metrics/average_irradiance')
cumulative_radiation = Outputs.folder(
description='The cumulative radiation in kWh/m2 for each sensor over '
'the wea period.',
path='metrics/cumulative_radiation')
class LeedIlluminanceCredits(Function):
"""Estimate LEED daylight credits from two point-in-time illuminance folders."""
folder = Inputs.folder(
description=
'Project folder for a LEED illuminance simulation. It should '
'contain a HBJSON model and two sub-folders of complete point-in-time '
'illuminance simulations labeled "9AM" and "3PM". These two sub-folders should '
'each have results folders that include a grids_info.json and .res files with '
'illuminance values for each sensor. If Meshes are found for the sensor '
'grids in the HBJSON file, they will be used to compute percentages '
'of occupied floor area that pass vs. fail. Otherwise, all sensors will '
'be assumed to represent an equal amount of floor area.',
path='raw_results')
glare_control_devices = Inputs.str(
description=
'A switch to note whether the model has "view-preserving automatic '
'(with manual override) glare-control devices," which means that illuminance '
'only needs to be above 300 lux and not between 300 and 3000 lux.',
default='glare-control',
spec={
'type': 'string',
'enum': ['glare-control', 'no-glare-control']
})
@command
def calculate_leed_credits(self):
return 'honeybee-radiance post-process leed-illuminance raw_results ' \
'--{{self.glare_control_devices}} --sub-folder ../pass_fail ' \
'--output-file credit_summary.json'
# outputs
pass_fail_results = Outputs.folder(
description='Pass/Fail results folder. This folder includes results for '
'each sensor indicating whether they pass or fail the LEED criteria.',
path='pass_fail')
credit_summary = Outputs.folder(
description=
'JSON file containing the number of LEED credits achieved and '
'a summary of the percentage of the sensor grid area that meets the criteria.',
path='credit_summary.json')
class RayTracingDaylightFactor(Function):
"""Run ray-tracing and post-process the results for a daylight factor simulation."""
radiance_parameters = Inputs.str(
description=
'Radiance parameters to be exposed within recipes. -I and -h are '
'usually already included in the fixed_radiance_parameters.',
default='-ab 2')
sky_illum = Inputs.int(
description='Sky illuminance level for the sky included in octree.',
default=100000)
fixed_radiance_parameters = Inputs.str(
description=
'Parameters that are meant to be fixed for a given recipe and '
'should not be overwritten by radiance_parameters input.',
default='-I -h')
grid = Inputs.file(description='Input sensor grid.', path='grid.pts')
scene_file = Inputs.file(
description='Path to an octree file to describe the scene.',
path='scene.oct')
bsdf_folder = Inputs.folder(
description='Folder containing any BSDF files needed for ray tracing.',
path='model/bsdf',
optional=True)
@command
def ray_tracing(self):
return 'honeybee-radiance raytrace daylight-factor scene.oct grid.pts ' \
'--rad-params "{{self.radiance_parameters}}" --rad-params-locked ' \
'"{{self.fixed_radiance_parameters}}" --sky-illum {{self.sky_illum}} ' \
'--output grid.res'
result = Outputs.file(
description=
'Daylight factor results file. The results for each sensor is in a '
'new line.',
path='grid.res')
class DaylightCoefficient(Function):
"""Calculate daylight coefficient for a grid of sensors from a sky matrix."""
radiance_parameters = Inputs.str(
description=
'Radiance parameters. -I, -c 1 and -aa 0 are already included in '
'the command.',
default='')
fixed_radiance_parameters = Inputs.str(
description=
'Radiance parameters. -I, -c 1 and -aa 0 are already included in '
'the command.',
default='-aa 0')
sensor_count = Inputs.int(
description='Number of maximum sensors in each generated grid.',
spec={
'type': 'integer',
'minimum': 1
})
sky_matrix = Inputs.file(description='Path to a sky matrix.',
path='sky.mtx',
extensions=['mtx', 'smx'])
sky_dome = Inputs.file(description='Path to a sky dome.', path='sky.dome')
sensor_grid = Inputs.file(description='Path to sensor grid files.',
path='grid.pts',
extensions=['pts'])
scene_file = Inputs.file(
description='Path to an octree file to describe the scene.',
path='scene.oct',
extensions=['oct'])
conversion = Inputs.str(
description=
'Conversion values as a string which will be passed to rmtxop -c.'
'This option is useful to post-process the results from 3 RGB components into '
'one as part of this command.',
default='')
order_by = Inputs.str(
description=
'An option to change how results are ordered in each row. By '
'default each row are the results for each sensor during all the datetime. '
'Valid options are sensor and datetime.',
default='sensor',
spec={
'type': 'string',
'enum': ['sensor', 'datetime']
})
output_format = Inputs.str(
description=
'Output format for converted results. Valid inputs are a, f and '
'd for ASCII, float or double.',
default='f',
spec={
'type': 'string',
'enum': ['a', 'd', 'f']
})
bsdf_folder = Inputs.folder(
description='Folder containing any BSDF files needed for ray tracing.',
path='model/bsdf',
optional=True)
@command
def run_daylight_coeff(self):
return 'honeybee-radiance dc scoeff scene.oct grid.pts sky.dome sky.mtx ' \
'--sensor-count {{self.sensor_count}} --output results.ill --rad-params ' \
'"{{self.radiance_parameters}}" --rad-params-locked '\
'"{{self.fixed_radiance_parameters}}" --conversion "{{self.conversion}}" ' \
'--output-format {{self.output_format}} --order-by-{{self.order_by}}'
result_file = Outputs.file(description='Output result file.',
path='results.ill')
class DaylightContribution(Function):
"""
Calculate daylight contribution for a grid of sensors from a series of modifiers
using rcontrib command.
"""
radiance_parameters = Inputs.str(
description='Radiance parameters. -I and -aa 0 are already included in '
'the command.', default=''
)
fixed_radiance_parameters = Inputs.str(
description='Radiance parameters. -I and -aa 0 are already included in '
'the command.', default='-aa 0'
)
calculate_values = Inputs.str(
description='A switch to indicate if the values should be multiplied. '
'Otherwise the contribution is calculated as a coefficient. Default is set to '
'value. Use coeff for contribution', default='value',
spec={'type': 'string', 'enum': ['value', 'coeff']}
)
conversion = Inputs.str(
description='Conversion values as a string which will be passed to rmtxop -c.',
default=''
)
order_by = Inputs.str(
description='An option to change how results are grouped in each row. By '
'default each row are the results for each sensor during all the datetimes. '
'Valid options are sensor and datetime.',
default='sensor', spec={'type': 'string', 'enum': ['sensor', 'datetime']}
)
output_format = Inputs.str(
description='Output format for converted results. Valid inputs are a, f and '
'd for ASCII, float or double. If conversion is not provided you can change the '
'output format using rad-params options.', default='a',
spec={'type': 'string', 'enum': ['a', 'd', 'f']}
)
sensor_count = Inputs.int(
description='Number of maximum sensors in each generated grid.',
spec={'type': 'integer', 'minimum': 1}
)
modifiers = Inputs.file(
description='Path to modifiers file. In most cases modifiers are sun modifiers.',
path='suns.mod'
)
sensor_grid = Inputs.file(
description='Path to sensor grid files.', path='grid.pts',
extensions=['pts']
)
scene_file = Inputs.file(
description='Path to an octree file to describe the scene.', path='scene.oct',
extensions=['oct']
)
bsdf_folder = Inputs.folder(
description='Folder containing any BSDF files needed for ray tracing.',
path='model/bsdf', optional=True
)
@command
def run_daylight_coeff(self):
return 'honeybee-radiance dc scontrib scene.oct grid.pts suns.mod ' \
'--{{self.calculate_values}} --sensor-count {{self.sensor_count}} ' \
'--rad-params "{{self.radiance_parameters}}" --rad-params-locked ' \
'"{{self.fixed_radiance_parameters}}" --conversion "{{self.conversion}}" ' \
'--output-format {{self.output_format}} --output results.ill ' \
'--order-by-{{self.order_by}}'
result_file = Outputs.file(description='Output result file.', path='results.ill')
class SplitView(Function):
"""Split a single view file (.vf) into multiple smaller views."""
view_count = Inputs.int(
description=
'Number of views into which the input view will be subdivided.',
spec={
'type': 'integer',
'minimum': 1
})
input_view = Inputs.file(description='Input view file.', path='view.vf')
overture = Inputs.str(
description='A switch to note whether an ambient file (.amb) should be '
'generated for an overture calculation before the view is split into smaller '
'views. With an overture calculation, the ambient file (aka ambient cache) is '
'first populated with values. Thereby ensuring that - when reused to create '
'an image - Radiance uses interpolation between already calculated values '
'rather than less reliable extrapolation. The overture calculation has '
'comparatively small computation time to full rendering but is single-core '
'can become time consuming in situations with very high numbers of '
'rendering multiprocessors.',
default='overture',
spec={
'type': 'string',
'enum': ['overture', 'skip-overture']
})
scene_file = Inputs.file(
description=
'Path to an octree file for the overture calculation. This must be '
'specified when the overture is not skipped.',
path='scene.oct',
optional=True)
radiance_parameters = Inputs.str(
description='Radiance parameters for the overture calculation. '
'If unspecified, default rpict paramters will be used.',
default='-ab 2')
bsdf_folder = Inputs.folder(
description='Folder containing any BSDF files needed for ray tracing.',
path='model/bsdf',
optional=True)
@command
def split_view(self):
return 'honeybee-radiance view split view.vf ' \
'{{self.view_count}} --{{self.overture}} ' \
'--octree {{self.scene_file}} --rad-params "{{self.radiance_parameters}}" ' \
'--folder output --log-file output/views_info.json'
views_list = Outputs.list(
description='A JSON array that includes information about generated '
'views.',
path='output/views_info.json')
output_folder = Outputs.folder(
description='Output folder with new view files.', path='output')
ambient_cache = Outputs.file(
description='Path to the ambient cache if an overture calculation was '
'specified.',
path='output/view.amb',
optional=True)
class ShortwaveMrtMap(Function):
"""Get CSV files with maps of shortwave MRT Deltas from Radiance results."""
epw = Inputs.file(
description='Weather file used to compute sun positions.',
path='weather.epw',
extensions=['epw'])
indirect_irradiance = Inputs.file(
description=
'A Radiance .ill containing the indirect irradiance for each '
'sensor. Alternatively, if the indirect-is-total input is used, then this '
'input should be the total irradiance for each sensor.',
path='indirect.ill',
extensions=['ill', 'irr'])
direct_irradiance = Inputs.file(
description=
'A Radiance .ill containing direct irradiance for each sensor.',
path='direct.ill',
extensions=['ill', 'irr'])
ref_irradiance = Inputs.file(
description=
'A Radiance .ill containing ground-reflected irradiance for each '
'sensor.',
path='ref.ill',
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.',
path='sun-up-hours.txt')
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 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.',
path='dynamic',
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.',
path='dyn_shade',
optional=True)
trans_schedules = Inputs.file(
description=
'An optional path to a transmittance schedule JSON output by '
'the honeybee-energy model-transmittance-schedules command, which is '
'coordinated with the --transmittance-contribs.',
path='trans_schedules.json',
optional=True)
solarcal_par = 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')
run_period = Inputs.str(
description=
'An AnalysisPeriod string to set the start and end dates of the '
'analysis (eg. "6/21 to 9/21 between 8 and 16 @1"). If unspecified, results '
'will be annual.',
default='')
indirect_is_total = Inputs.str(
description=
'A switch to note whether the indirect-irradiance argument is '
'actually the total irradiance.',
default='is-indirect',
spec={
'type': 'string',
'enum': ['is-indirect', 'indirect-is-total']
})
@command
def run_shortwave_map(self):
return 'ladybug-comfort map shortwave-mrt weather.epw indirect.ill direct.ill ' \
'ref.ill sun-up-hours.txt --contributions dynamic ' \
'--transmittance-contribs dyn_shade --trans-schedule-json ' \
'trans_schedules.json --solarcal-par "{{self.solarcal_par}}" ' \
'--run-period "{{self.run_period}}" --{{self.indirect_is_total}} ' \
'--output-file shortwave.csv'
shortwave_mrt_map = Outputs.file(
description='CSV file containing a map of shortwave MRT deltas.',
path='shortwave.csv')
