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@@ -0,0 +1,61 @@
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+def overlapintervals(i1, i2):
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+ """
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+ Calculate intersection of two lists of intervals.
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+
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+ :param i1: list of intervals
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+ :param i2: list of intervals
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+
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+ :return: list of intervals with overlap of both intervals only
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+ """
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+ ollist = []
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+ for i in i1:
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+ for j in i2:
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+ if j[0] < i[0]+i[1] and j[0]+j[1] > i[0]:
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+ ollist += [[max(i[0], j[0]),
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+ min(i[0]+i[1], j[0]+j[1])-max(i[0], j[0])]]
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+ return ollist
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+
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+
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+
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+def calcPrecisionRecall(detection, groundtruth, setlength):
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+ """
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+ Calculated precision and recall for intervals in time series
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+
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+ :param detection: array with detected intervals
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+ :param groundtruth: array with ground truth
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+ :param setlength: length of time series
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+
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+ :return: precision, recall
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+ """
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+ import numpy as np
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+
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+
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+ if len(groundtruth) == 0 and len(detection) == 0:
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+ precision = 1
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+ recall = 1
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+ else:
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+ # Turn detection into array
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+ detArray = IntervalsToBinary(detection, setlength)
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+ gtArray = IntervalsToBinary(groundtruth, setlength)
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+ if np.sum(gtArray) == 0:
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+ gtArray = -1 * (gtArray - 1)
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+ detArray = -1*(detArray-1)
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+
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+ unique, counts = np.unique(detArray+gtArray, return_counts=True)
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+ countvalues = dict(zip(unique, counts))
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+ tp = countvalues[2] if 2 in countvalues else 0
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+ tn = countvalues[0] if 0 in countvalues else 0
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+
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+ unique, counts = np.unique(detArray-gtArray, return_counts=True)
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+ countvalues = dict(zip(unique, counts))
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+ fp = countvalues[1] if 1 in countvalues else 0
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+
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+ unique, counts = np.unique(gtArray-detArray, return_counts=True)
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+ countvalues = dict(zip(unique, counts))
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+ fn = countvalues[1] if 1 in countvalues else 0
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+
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+ precision = tp / (tp + fp) if tp + fp > 0 else 0
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+ recall = tp / (fn + tp) if tp + fn > 0 else 0
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+
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+ #print(detection, groundtruth, precision, recall)
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+ return precision, recall
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