Skip to main content

Dragonfly extension for energy simulation.

Project description

Dragonfly

Build Status Coverage Status

Python 2.7 Python 3.6 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-1.12.105.tar.gz (361.6 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-1.12.105-py2.py3-none-any.whl (76.5 kB view details)

Uploaded Python 2Python 3

File details

Details for the file dragonfly-energy-1.12.105.tar.gz.

File metadata

  • Download URL: dragonfly-energy-1.12.105.tar.gz
  • Upload date:
  • Size: 361.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.1 importlib_metadata/4.3.1 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.61.0 CPython/3.7.10

File hashes

Hashes for dragonfly-energy-1.12.105.tar.gz
Algorithm Hash digest
SHA256 8baba33a7ae1c39ffbb417c74b5c1841a31a299351fd0d0a1027e6f4d4ab5909
MD5 e0ff7b457e8cea8660fcdabe27629760
BLAKE2b-256 9d2abc13d594400ecbe9634a52748c0759833a0b683d990589f7a0da3e511ec0

See more details on using hashes here.

File details

Details for the file dragonfly_energy-1.12.105-py2.py3-none-any.whl.

File metadata

  • Download URL: dragonfly_energy-1.12.105-py2.py3-none-any.whl
  • Upload date:
  • Size: 76.5 kB
  • Tags: Python 2, Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.1 importlib_metadata/4.3.1 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.61.0 CPython/3.7.10

File hashes

Hashes for dragonfly_energy-1.12.105-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 cb21efa5e2b6e54c44b10b6d17d8df573436c055b83e3c50971b7d8b902bd8be
MD5 9f8056fe7bdf151acd68347582f97012
BLAKE2b-256 3233e3f1768eb28c332bf065024f3151aa52cc90c47536e9e26af2f05b0a5767

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