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