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-1.16.78.tar.gz (65.2 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-1.16.78-py2.py3-none-any.whl (84.0 kB view details)

Uploaded Python 2Python 3

File details

Details for the file dragonfly-energy-1.16.78.tar.gz.

File metadata

  • Download URL: dragonfly-energy-1.16.78.tar.gz
  • Upload date:
  • Size: 65.2 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/4.64.0 CPython/3.7.13

File hashes

Hashes for dragonfly-energy-1.16.78.tar.gz
Algorithm Hash digest
SHA256 7e8e96752812669174374f74b80760c8d01e70281af24cfd7a79ea282dc10b71
MD5 42d65a63f8c42e659bb5ed952b481a30
BLAKE2b-256 0a995c0e2711b3ef6ec678ab3e2ca6c45f2ce05eaa2651dbe70db5d820ce3360

See more details on using hashes here.

File details

Details for the file dragonfly_energy-1.16.78-py2.py3-none-any.whl.

File metadata

  • Download URL: dragonfly_energy-1.16.78-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/4.64.0 CPython/3.7.13

File hashes

Hashes for dragonfly_energy-1.16.78-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 cfa8fedc2b56e72f397f3f280dcb066fc0583b846789d5ff87e86931e955588b
MD5 997affccd508fba423896fb7d424b349
BLAKE2b-256 bb1b79bbf5d6236d2ccbe11134f5014bc8bbc51d9a8ec1be67c3531a202e25af

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