Formed in 2009, the Archive Team (not to be confused with the archive.org Archive-It Team) is a rogue archivist collective dedicated to saving copies of rapidly dying or deleted websites for the sake of history and digital heritage. The group is 100% composed of volunteers and interested parties, and has expanded into a large amount of related projects for saving online and digital history.
Wrapper around daft for easily creating DBN.
Install
Alternative A) Install systemwide
python setup.py build
sudo python setup.py installAlternative B) Install dependencies + include
pip install daft --user1. Usage
see examples
Example: Creating a Model
This example creates a HMM with two explicitely visualized parameters pi and Sigma:
dbn = DBN()
dbn.attach(NodeProperties("X", 0, 0, parentsPrevious="X"))
dbn.attach(NodeProperties(name="Y",x=0, y=1,parentsNow="X", nodeType=NodeType.Observed, continuous=True))
dbn.attach(NodeProperties(name="\Sigma",x=0, y=2,parentsNow="Y", nodeType=NodeType.Variable))
dbn.attach(NodeProperties(name="\pi",x=0, y=2,parentsPrevious="Y", nodeType=NodeType.Variable))Example: Exporting a Model
Depending on whether the first few time slices are to be visualized (1) or the time slices around the current time, the plot can be exported via
k.export(sliceBefore=0, sliceAfter=3, centerSuffix="") #< variant 1: export first few time slicesor (2):
k.export(sliceBefore=2, sliceAfter=1, centerSuffix="\\tau") #< variant 2: export 2 before - 1
# after the current time (referred
# to as \tau)These 7 lines of code create the following two vector graphics:
Output - format:
Supports pdf svg jpg and a lot more.