Right now, for an annual simulation the result are returned as an array. There needs to be a way through which it is possible to map a specific row of the results to a timestep (point in time)
For example, for the code snippet below....

# Instantiate a Two Phase Run
workflow2=methods.TwoPhaseMethod(config=config)

# Set up the matrices for the two phase run
workflow2.generate_matrices()

# Run the simulation and return a numpy array.
rsults = workflow2.calculate_sensor_from_wea('Perimeter_bot_ZN_1_Perimeter_bot_ZN_1_Floor')

...the results are returned as a dataframe below:

Currently, it is not possible to know which row/column of the above dataframe corresponds to which timestep.

It would be nice to have some documentation for this functionality as and when it gets merged to the main branch.

Given a radiance scene containing polygons, it would be useful to have a utility function that calculates view factors for every surface in the scene.
For example, if a scene contains 100 polygons, then the function should generate a 100 x 100 dataframe where each line contains the view factor for a specific surface and all the other surfaces in the scene.

Include reference models and weather files for convenience.

from frads.data_sets import reference_models, weather_files

epmodel = load_energyplus_model(reference_models["medium-office"])
epw_file = weather_files["us-il-chicago"]

Currently there is no way to construct a glazing system with applied films.

It would be nice to have a way to find out what actuators and variables are available during runtime and what output variables can the simulation generate.

Currently, actuators are defined by component_type, name, and key. It would be nice to be able to search actuators by component type, name, or key.

Ideally, there will be a function that checks the actuator and variable names before running the simulation. If the name doesn't exist, then generate suggested variable names.

It'd be nice to be able to zip input data and results of glazing system calc and reuse it later or share with others. Such zipped file can also be used to generate other Radiance primitives.

The zipped file structure may look something like this:

• system.json
• layers
  -- layer1.json
  -- lyaer2.xml
• system
  --system.xml

There should be some rudimentary check of data integrity between system.json and other files such as any direct modification would render the zipped file invalid.

We need to add methods inside GlazingSystem class to generate such zip file and also a classmethod instantiate a GlazingSystem class with such file.

Pywincalc.PredefinedGasMixture will be deprecated in the next major release.
We need to change to use pywincalc.create_gas instead.

Based on the current generic implementation of EnergyPlusSetup.actuate, implement some commonly used actuators such as:

• actuate_construction_state(surface_name, state)
• actuate_heating_setpoint(zone_name, value)
• actuate_cooling_setpoint(zone_name, value)
• actuate_lighting_power(zone_name, value)

Upcoming frads version will no longer support Python 3.8.

Right users trying to use Radiance workflow when running EnergyPlus simulation needs to manually setup Radiance workflow outside.

It'd be nice encapsulate and automatically generate such Radiance workflow inside EnergyPlusSetup object. All required data for Radiance workflow should be inside EnergyPlusSetup already.

Right now users have to manually request variables that they're trying to access in the callback function.

We can alternatively analyze the syntax of the callback function to identify the requested variable name and key.

Right now pyenergyplus needs to be incorporated into the project using sys.path.append or by using settings in the IDE. Neither of these approaches are particularly stable or portable. On my windows machine I need to append C:\EnergyPlusV22-2-0 to the sys.path to ensure that the runtime api works. In linux machines its something else.

A three phase annual simulation fails with matrix multiplication errors. For example, this code snippet:

.. fails with the following error.

The traceback leads to the following line:

I am currently working through this tutorial.

https://lbnl-eta.github.io/frads/how-to/guide_rad1/

gen room 12 14 3
-w 0.4 1 2.5 1.8
-w 3.3 1 2.5 1.8
-w 6.2 1 2.5 1.8
-w 9.1 1 2.5 1.8
-t 0.1 -n aroom

does not work. It returns me the following error:

gen room 12 14 3 \
-w 0.4 1 2.5 1.8
-w 3.3 1 2.5 1.8
-w 6.2 1 2.5 1.8
-w 9.1 1 2.5 1.8 \
-t 0.1 -n aroom
usage: gen room [-h] [-w start_x start_z width height] [-n NAME] [-t Facade thickness] [-r ROTATE] width depth flrflr flrclg
gen room: error: the following arguments are required: flrclg

Just to be sure, I currently have version:

In [1]: import frads

In [2]: print(frads.version)
0.2.10

However the installation of the below did not quite work, because a file was missing:

pip install git+https://github.com/taoning/pyenergyplus_wheels
Collecting git+https://github.com/taoning/pyenergyplus_wheels
Cloning https://github.com/taoning/pyenergyplus_wheels to /private/var/folders/c2/tthc2_6j741c3rvx9vpjppwh0000gn/T/pip-req-build-ihxnqfnq
Running command git clone --filter=blob:none --quiet https://github.com/taoning/pyenergyplus_wheels /private/var/folders/c2/tthc2_6j741c3rvx9vpjppwh0000gn/T/pip-req-build-ihxnqfnq
Resolved https://github.com/taoning/pyenergyplus_wheels to commit 664456bc5428ad50ace2c2bc729bbc486afa0435
Preparing metadata (setup.py) ... done
Collecting pyenergyplus@ https://github.com/taoning/pyenergyplus/raw/main/wheels/darwin/pyenergyplus-23.1.0-py3-none-macosx_10_13_x86_64.whl
ERROR: HTTP error 404 while getting https://github.com/taoning/pyenergyplus/raw/main/wheels/darwin/pyenergyplus-23.1.0-py3-none-macosx_10_13_x86_64.whl
ERROR: Could not install requirement pyenergyplus@ https://github.com/taoning/pyenergyplus/raw/main/wheels/darwin/pyenergyplus-23.1.0-py3-none-macosx_10_13_x86_64.whl from https://github.com/taoning/pyenergyplus/raw/main/wheels/darwin/pyenergyplus-23.1.0-py3-none-macosx_10_13_x86_64.whl (from pyenergyplus-wheels==0.1.0) because of HTTP error 404 Client Error: Not Found for url: https://github.com/taoning/pyenergyplus/raw/main/wheels/darwin/pyenergyplus-23.1.0-py3-none-macosx_10_13_x86_64.whl for URL https://github.com/taoning/pyenergyplus/raw/main/wheels/darwin/pyenergyplus-23.1.0-py3-none-macosx_10_13_x86_64.whl

Desktop (please complete the following information):

• OS: [MacOS]
• Browser [Safari]

Current: can only handle simple glazing systems and complex fenestration construction state conversion from EnergyPlus to Radiance

New feature: A converter that handles other EnergyPlus window construction modeling methods

1. Analyze the methods used in EnergyPlus file
2. Generate corresponding BRTDfunc/ BSDF for Radiance

Dear all,

In the context of outdoor long wave radiation, it is necessary to calculate view factors between surfaces and also between the surface and the sky.

Using the surfaces_view_factor function, is there a way to determine the view factors between, for example, the sky and the ground and a given geometry and in between ground and geometry?

The sky is discretized following the Reinhart sky model for a usage with daylight coefficient for shortwave radiation with the following skyglow.rad file:

#@rfluxmtx u=+Y h=u
void glow groundglow
0
0
4 1 1 1 0

groundglow source ground
0
0
4 0 0 -1 180

#@rfluxmtx u=+Y h=r1
void glow skyglow
0
0
4 1 1 1 0

skyglow source skydome
0
0
4 0 0 1 180

Sincerely,
Arthur

It would be nice to have a way to write out zones from an IDF directly as radFiles. For example, it should be possible to write out the geometry of Perimeter_bot_ZN_1 as a series of rad files.

api=EnergyPlusAPI()
epModel=fr.load_epmodel(Path('in.idf'),api)

mdl=fr.epjson2rad(epModel.epjs,'in.epw')
config=methods.WorkflowConfig.from_dict(mdl['Perimeter_bot_ZN_1'])

Now that we have epmodel, we should use it for our EnergyPlus model modification and validation.

For example. adding a CFS to an EnergyPlus model now should look something like this:

import epmodel
import json

with open("model.epJSON", "r") as f:
    data = json.load(f)
model = epmodel.EnergyPlusModel.model_validate(data)

# add CFS, data validation happens automatically here
model.construction_complex_fenestration_state = {
    "cfs1": epmodel.ConstructionComplexFenestrationState(
        ...
    )
}

1. We can start by creating a new branch and add epmodel to the list of dependencies
2. Figure out a way to convert a frads.GlazingSystem object into a epmodel.ConstructionComplexFenestrationState object.
3. Maybe frads.EnergyPlusModel class becomes a subclass of epmodel.EnergyPlusModel?

Running or parsing invalid EnergyPlus model gives obscure error message that are difficult to figure out.

We should be able to check the validity of the epjson model against the schema before doing anything.

This would requires some 3rd party json schema validator, which can be problematic to maintain later on.