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| Next revision | Previous revisionLast revisionBoth sides next revision | ||
| technical:sliding_window [2019/09/25 14:25] – created chunchung | technical:sliding_window [2020/10/13 19:27] – [Sliding window time histogram] chunchung | ||
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| =====Sliding window time histogram===== | =====Sliding window time histogram===== | ||
| + | Given the spike time, plot the event rate within a sliding window. | ||
| <code python> | <code python> | ||
| def sliding_window(ts, | def sliding_window(ts, | ||
| Line 36: | Line 37: | ||
| tts.append(tw) | tts.append(tw) | ||
| rrs.append(0) | rrs.append(0) | ||
| - | return np.array(tts)+wsz/ | + | return np.array(tts)+wsz/ |
| </ | </ | ||
| + | ====Example==== | ||
| + | <code python> | ||
| + | a = np.array([1, | ||
| + | tts,rrs = sliding_window(a) | ||
| + | plt.plot(tts, | ||
| + | plt.plot(a, | ||
| + | </ | ||
| + | {{ : | ||