Skip to main content

Dragonfly extension for energy simulation.

Project description

Dragonfly

Build Status Coverage Status

Python 3.7 Python 2.7 IronPython

dragonfly-energy

Dragonfly extension for energy simulation.

Installation

pip install dragonfly-energy

QuickStart

import dragonfly_energy

API Documentation

Usage

Since the building geometry in dragonfly is fundamentally 2D, creating a model of a building and assigning energy model properties can be done with a few lines of code. Here is an example:

from dragonfly.model import Model
from dragonfly.building import Building
from dragonfly.story import Story
from dragonfly.room2d import Room2D
from dragonfly.windowparameter import SimpleWindowRatio
from honeybee_energy.lib.programtypes import office_program

# create the Building object
pts_1 = (Point3D(0, 0, 3), Point3D(0, 10, 3), Point3D(10, 10, 3), Point3D(10, 0, 3))
pts_2 = (Point3D(10, 0, 3), Point3D(10, 10, 3), Point3D(20, 10, 3), Point3D(20, 0, 3))
pts_3 = (Point3D(0, 10, 3), Point3D(0, 20, 3), Point3D(10, 20, 3), Point3D(10, 10, 3))
pts_4 = (Point3D(10, 10, 3), Point3D(10, 20, 3), Point3D(20, 20, 3), Point3D(20, 10, 3))
room2d_1 = Room2D('Office1', Face3D(pts_1), 3)
room2d_2 = Room2D('Office2', Face3D(pts_2), 3)
room2d_3 = Room2D('Office3', Face3D(pts_3), 3)
room2d_4 = Room2D('Office4', Face3D(pts_4), 3)
story = Story('OfficeFloor', [room2d_1, room2d_2, room2d_3, room2d_4])
story.solve_room_2d_adjacency(0.01)
story.set_outdoor_window_parameters(SimpleWindowRatio(0.4))
story.multiplier = 4
building = Building('OfficeBuilding', [story])

# assign energy properties
for room in story.room_2ds:
    room.properties.energy.program_type = office_program
    room.properties.energy.add_default_ideal_air()

# create the Model object
model = Model('NewDevelopment', [building])

Once a Dragonfly Model has been created, it can be converted to a honeybee Model, which can then be converted to IDF format like so:

# create the dragonfly Model object
model = Model('NewDevelopment', [building])

# serialize the dragonfly Model to Honeybee Models and convert them to IDF
hb_models = model.to_honeybee('Building', use_multiplier=False, tolerance=0.01)
idfs = [hb_model.to.idf(hb_model) for hb_model in hb_models]

The dragonfly model can also be serialized to a geoJSON to be simulated with URBANopt

from ladybug.location import Location

# create the dragonfly Model object
model = Model('NewDevelopment', [building])

# create a location for the geoJSON and write it to a folder
location = Location('Boston', 'MA', 'USA', 42.366151, -71.019357)
sim_folder = './tests/urbanopt_model'
geojson, hb_model_jsons, hb_models = model.to.urbanopt(model, location, folder=sim_folder)

Local Development

  1. Clone this repo locally
git clone git@github.com:ladybug-tools/dragonfly-energy

# or

git clone https://github.com/ladybug-tools/dragonfly-energy
  1. Install dependencies:
cd dragonfly-energy
pip install -r dev-requirements.txt
pip install -r requirements.txt
  1. Run Tests:
python -m pytest tests/
  1. Generate Documentation:
sphinx-apidoc -f -e -d 4 -o ./docs ./dragonfly_energy
sphinx-build -b html ./docs ./docs/_build/docs

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

dragonfly-energy-1.16.44.tar.gz (369.8 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

dragonfly_energy-1.16.44-py2.py3-none-any.whl (84.0 kB view details)

Uploaded Python 2Python 3

File details

Details for the file dragonfly-energy-1.16.44.tar.gz.

File metadata

  • Download URL: dragonfly-energy-1.16.44.tar.gz
  • Upload date:
  • Size: 369.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.1 importlib_metadata/4.3.1 pkginfo/1.8.2 requests/2.27.1 requests-toolbelt/0.9.1 tqdm/4.63.1 CPython/3.7.12

File hashes

Hashes for dragonfly-energy-1.16.44.tar.gz
Algorithm Hash digest
SHA256 6534b317a592a1ef4a91052efcd222c043100b377ea4a665a153d8414432a3c9
MD5 8a7280b0a62170ef80abee0347b26993
BLAKE2b-256 78943cb388b2a7e97f1367e3301aaf47fb9d3c766098973e63bf97a084b99847

See more details on using hashes here.

File details

Details for the file dragonfly_energy-1.16.44-py2.py3-none-any.whl.

File metadata

  • Download URL: dragonfly_energy-1.16.44-py2.py3-none-any.whl
  • Upload date:
  • Size: 84.0 kB
  • Tags: Python 2, Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.1 importlib_metadata/4.3.1 pkginfo/1.8.2 requests/2.27.1 requests-toolbelt/0.9.1 tqdm/4.63.1 CPython/3.7.12

File hashes

Hashes for dragonfly_energy-1.16.44-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 d526cd1619510763e7c71f9271b528e150b7175f95a45db4af143082eacec5c7
MD5 9e1cc3096160c489cdd2cb9cf7b15ef6
BLAKE2b-256 356ba15118e5872964e2931b8afa6280d96f60c21b253f30041d5d106426a5d5

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page