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-1.16.42.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-1.16.42-py2.py3-none-any.whl (84.0 kB view details)

Uploaded Python 2Python 3

File details

Details for the file dragonfly-energy-1.16.42.tar.gz.

File metadata

  • Download URL: dragonfly-energy-1.16.42.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-1.16.42.tar.gz
Algorithm Hash digest
SHA256 a834507924db312d9bf3787d46e6102f9021858ef5f8c827e599a45b6dce4801
MD5 7511c645ad0a192385a27668de0dd5e0
BLAKE2b-256 00c30ffbcd3a0bc3b71562e2ff29179379ddc9d5fba9654b692860212414b3de

See more details on using hashes here.

File details

Details for the file dragonfly_energy-1.16.42-py2.py3-none-any.whl.

File metadata

  • Download URL: dragonfly_energy-1.16.42-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-1.16.42-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 3eabc2514f267f07f04def9817bc6751a3e0adefe567936a3d53148b95cf3c7d
MD5 0a738d6c7d68bf6d6a729c6e878f6b89
BLAKE2b-256 e4f813db329807b3bbce0e42fb90aa21e6105b1c5d9f8b63b1bda2a1412d9014

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