cbcBayesCombinePosteriors.py File Reference

Go to the source code of this file.

Namespaces
namespace	cbcBayesCombinePosteriors

Variables
string	cbcBayesCombinePosteriors.posterior_grp_name = "posterior_samples"
	cbcBayesCombinePosteriors.parser = argparse.ArgumentParser(description="Combine some posterior samples.")
	cbcBayesCombinePosteriors.dest
	cbcBayesCombinePosteriors.default
	cbcBayesCombinePosteriors.help
	cbcBayesCombinePosteriors.metavar
	cbcBayesCombinePosteriors.action
	cbcBayesCombinePosteriors.required
	cbcBayesCombinePosteriors.type
	cbcBayesCombinePosteriors.shuffleGroup = parser.add_mutually_exclusive_group()
	cbcBayesCombinePosteriors.fileGroup = parser.add_mutually_exclusive_group()
	cbcBayesCombinePosteriors.args = parser.parse_args()
	cbcBayesCombinePosteriors.nPos = np.size(args.infilename)
	cbcBayesCombinePosteriors.nWeight = np.size(args.weightings)
	cbcBayesCombinePosteriors.weightings
string	cbcBayesCombinePosteriors.combineID = "combined"
list	cbcBayesCombinePosteriors.samples = []
list	cbcBayesCombinePosteriors.paramsList = []
list	cbcBayesCombinePosteriors.sizeList = []
dictionary	cbcBayesCombinePosteriors.metadata
	cbcBayesCombinePosteriors.group = inFile["lalinference"]
	cbcBayesCombinePosteriors.run_id = list(group.keys())[0]
list	cbcBayesCombinePosteriors.posDtype = []
	cbcBayesCombinePosteriors.shape = group[key].shape
	cbcBayesCombinePosteriors.posData = np.empty(shape, dtype=posDtype)
	cbcBayesCombinePosteriors.paramsOut = list(set.intersection(*paramsList))
list	cbcBayesCombinePosteriors.datatypes = samples[0][paramsOut].dtype
	cbcBayesCombinePosteriors.sizeOut = sum(sizeList)
	cbcBayesCombinePosteriors.samplesOut = np.empty(sizeOut, dtype=datatypes)
list	cbcBayesCombinePosteriors.indexSize = sizeList
	cbcBayesCombinePosteriors.fracWeight = np.asarray(args.weightings) / float(sum(args.weightings))
	cbcBayesCombinePosteriors.testNum = fracWeight * float(sum(sizeList))
	cbcBayesCombinePosteriors.minIndex = np.argmin(np.asarray(sizeList) / np.asarray(testNum))
list	cbcBayesCombinePosteriors.testSize = sizeList[minIndex] / fracWeight[minIndex]
	cbcBayesCombinePosteriors.weightNum = np.around(fracWeight * testSize).astype(int)
int	cbcBayesCombinePosteriors.startIndex = 0
int	cbcBayesCombinePosteriors.stopIndex = startIndex + indexSize[posIndex]
	cbcBayesCombinePosteriors.key
	cbcBayesCombinePosteriors.data
	cbcBayesCombinePosteriors.shuffle
	cbcBayesCombinePosteriors.True
	cbcBayesCombinePosteriors.compression
string	cbcBayesCombinePosteriors.paramHeader = "\t".join(paramsOut)
	cbcBayesCombinePosteriors.T
	cbcBayesCombinePosteriors.delimiter
	cbcBayesCombinePosteriors.header
	cbcBayesCombinePosteriors.comments