NestedDict

Overview

NestedDict is a helper class very similar to the python dict or OrderedDict with the following extra features:

1. NestedDict enables attribute access as well as key access to the stored items:

   nd = NestedDict( a=1, b=2 )
   nd['a']
   # 1
   nd.a
   # 1
   

2. NestedDict enables nesting (unlimited):

   • Each stored dictionary will be converted to the NestedDict instance.

   • Assigning to nd['a.b'] will create NestedDict nd['a'] and assign nd['a']['b'].

   • Assigning to nd.a.b also works, but only for existing nd.a.

   • Nested NestedDict may be also created by calling nd('a') or nd('a.b') or, etc.

   • Parent dictionary may be accessed by calling nd.parent() method.

3. Usual dict methods like set, setdefault, get, keys, values and items are also supported.

It should be noted that the keys set, setdefault, get, keys, values and items may be accessed only via [] operator or the methods themselves, but not via attribute access.

Example

An example of the configuration of the bundlechain_v01 via NestedDict may be found below:

cfg = NestedDict()
cfg.detector = NestedDict(
        bundle = 'bundlechain_v01',
        detectors = [ 'AD11', 'AD21', 'AD31' ],
        chain = [ 'iav', 'nonlinearity', 'eres', 'rebin' ]
        )
cfg.detector.nonlinearity = NestedDict(
        bundle = 'detector_nonlinearity_db_root_v01',
        names = [ 'nominal', 'pull0', 'pull1', 'pull2', 'pull3' ],
        filename = 'output/detector_nl_consModel_450itr.root',
        uncertainty = 0.2*percent,
        uncertainty_type = 'relative'
        )
cfg.detector.iav = NestedDict(
        bundle = 'detector_iav_db_root_v01',
        parname = 'OffdiagScale',
        uncertainty = 4*percent,
        uncertainty_type = 'relative',
        ndiag = 1,
        filename = 'data/dayabay/tmp/detector_iavMatrix_P14A_LS.root',
        matrixname = 'iav_matrix'
        )
cfg.detector.eres = NestedDict(
        bundle = 'detector_eres_common3',
        # pars: sigma_e/e = sqrt( a^2 + b^2/E + c^2/E^2 ),
        values  = [ 0.014764, 0.0869, 0.0271 ],
        uncertainties = [30.0*percent]*3,
        uncertainty_type = 'relative'
        )
cfg.detector.rebin = NestedDict(
        bundle = 'rebin',
        rounding = 3,
        edges = [ 0.0, 5.0, 10.0 ]
        )

Loading configuration from file

The configurator module contains the configurator function that can read any python file and return it as NestedDict. The following variables may be used within the NestedDict file:

• percent equals to 0.01.

• numpy to access numpy functions.

• load to load nested configuration files. load is a shortcut for configurator.

The file may be located anywhere. Also, all the created dict instances will be converted to NestedDict.

Example code is below:

from gna.configurator import configurator
cfg = configurator( 'path/to/python/file.py' )

See also

There testing files that may be used as example:

# reading configuration files:
./tests/elementary/test_cfgloader.py
# assigning items:
./tests/elementary/test_cfg.py