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- shape, loc, scale = sm.lognorm.fit(dataToLearn, floc = 0)
- for b in bounds:
- toPlot.append((b, currCount+sm.lognorm.ppf(b, s = shape, loc = loc, scale = scale)))
- for i, d in enumerate(dataToLearn):
- dataToLearn2 += int(w[i] * 100) * [d]
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