Coding For Slope

This is a covariance[0] plot for a no-kidnapping data collection trial:

I first implemented what I talked about in the last post: I took 3 windows of 3 prior points a piece and averaged each window into a number.  If the previous window's average was bigger, I coded this as a 0. Otherwise, it was a 1.

This didn't work so well - there were more 1's than I wanted to see in a normal, no-kidnapping dataset. 

The next thing I tried was taking the same 9 previous points and comparing them consecutively - if prev_point9 > prev_point8, it's a 0, and otherwise a 1.  That resulted in the dataset below. 


I like this one because it represents short-lived spikes and longer-term increases.

Weaknesses of this modeling approach:
1. Doesn't represent the intensity of the increase (magnitude of the slope). I think it's mostly the degree of the slope that differentiates a kidnapping instance's covariance spike from a regular localization covariance spike. 
2. I'd like a way of identifying "This timestep and the 5 previous timesteps were ALL 1's" - somehow, that needs to make it into the model.

Time/Covariance[0]	t9>8	t 8>7	t7>6	t 6>5	t 5>4	t 4>3	t 3>2	t 2>1
32.68	0	0	0	0	0	0	0	0
43	0	0	0	0	0	0	0	1
43.36	0	0	0	0	0	0	1	0
43.64	0	0	0	0	0	1	0	0
44.18	0	0	0	0	1	0	0	0
50.3	0	0	0	1	0	0	0	0
50.57	0	0	1	0	0	0	0	0
54	0	1	0	0	0	0	0	0
56.17	1	0	0	0	0	0	0	0
57.52	0	0	0	0	0	0	0	0
58.44	0	0	0	0	0	0	0	0
61.6	0	0	0	0	0	0	0	0
62.4	0	0	0	0	0	0	0	0
65.14	0	0	0	0	0	0	0	0
69.98	0	0	0	0	0	0	0	1
73.63	0	0	0	0	0	0	1	0
73.93	0	0	0	0	0	1	0	0
74.33	0	0	0	0	1	0	0	0
77.55	0	0	0	1	0	0	0	0
80.56	0	0	1	0	0	0	0	1
81.55	0	1	0	0	0	0	1	1
85.61	1	0	0	0	0	1	1	1
86.2	0	0	0	0	1	1	1	1
88.1	0	0	0	1	1	1	1	1
89.54	0	0	1	1	1	1	1	0
91.81	0	1	1	1	1	1	0	0
93.91	1	1	1	1	1	0	0	1
94.47	1	1	1	1	0	0	1	1
95.91	1	1	1	0	0	1	1	0
97.32	1	1	0	0	1	1	0	0
102.73	1	0	0	1	1	0	0	1
104.1	0	0	1	1	0	0	1	1
104.61	0	1	1	0	0	1	1	1
105.72	1	1	0	0	1	1	1	1
107.29	1	0	0	1	1	1	1	0
108.7	0	0	1	1	1	1	0	1
110.17	0	1	1	1	1	0	1	1
111.98	1	1	1	1	0	1	1	1
113.45	1	1	1	0	1	1	1	0
114.23	1	1	0	1	1	1	0	0
114.82	1	0	1	1	1	0	0	0
118.75	0	1	1	1	0	0	0	0
120.1	1	1	1	0	0	0	0	0
123.97	1	1	0	0	0	0	0	0
126.51	1	0	0	0	0	0	0	0
129.75	0	0	0	0	0	0	0	1
130	0	0	0	0	0	0	1	1
130.29	0	0	0	0	0	1	1	0
130.56	0	0	0	0	1	1	0	0
131.8	0	0	0	1	1	0	0	0
131.28	0	0	1	1	0	0	0	1
131.59	0	1	1	0	0	0	1	1
132.75	1	1	0	0	0	1	1	0
133.5	1	0	0	0	1	1	0	0
134.2	0	0	0	1	1	0	0	1
134.76	0	0	1	1	0	0	1	0
135.62	0	1	1	0	0	1	0	1
136.23	1	1	0	0	1	0	1	0
137.76	1	0	0	1	0	1	0	0
138.89	0	0	1	0	1	0	0	1
140.61	0	1	0	1	0	0	1	1
141.88	1	0	1	0	0	1	1	1
143.37	0	1	0	0	1	1	1	1
144.71	1	0	0	1	1	1	1	1