(ll, intervals)
| 109 | |
| 110 | |
| 111 | def list_cut_average(ll, intervals): |
| 112 | if intervals == 1: |
| 113 | return ll |
| 114 | |
| 115 | bins = math.ceil(len(ll) * 1.0 / intervals) |
| 116 | ll_new = [] |
| 117 | for i in range(bins): |
| 118 | l_low = intervals * i |
| 119 | l_high = l_low + intervals |
| 120 | l_high = l_high if l_high < len(ll) else len(ll) |
| 121 | ll_new.append(np.mean(ll[l_low:l_high])) |
| 122 | return ll_new |
| 123 | |
| 124 | |
| 125 | def motion_temporal_filter(motion, sigma=1): |
nothing calls this directly
no outgoing calls
no test coverage detected