My dataset contains 2 variables Y and X. Y was measured every 1.0 seconds.

My Data:

 dput(Dataexample)
structure(list(X = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 
14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 
30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 
46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 
62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 
78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 
94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 
108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 
121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 
134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 
147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 
160, 161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 
173, 174, 175, 176, 177, 178, 179, 180, 181, 182, 183, 184, 185, 
186, 187, 188, 189, 190, 191, 192, 193, 194, 195, 196, 197, 198, 
199, 200, 201, 202, 203, 204, 205, 206, 207, 208, 209, 210, 211, 
212, 213, 214, 215, 216, 217, 218, 219, 220, 221, 222, 223, 224, 
225, 226, 227, 228, 229, 230, 231, 232, 233, 234, 235, 236, 237, 
238, 239, 240, 241, 242, 243, 244, 245, 246, 247, 248, 249, 250, 
251, 252, 253, 254, 255, 256, 257, 258, 259, 260, 261, 262, 263, 
264, 265, 266, 267, 268, 269, 270, 271, 272, 273, 274, 275, 276, 
277, 278, 279, 280, 281, 282, 283, 284, 285, 286, 287, 288, 289, 
290, 291, 292, 293, 294, 295, 296, 297, 298, 299, 300, 301, 302, 
303, 304, 305, 306), Y = c(71756.2344, 71745.85, 70882.42, 71025.61, 
70539.02, 70602.3047, 70811.87, 70514.125, 69998.63, 70531.76, 
70424.9141, 70663.51, 70075.375, 69731.0859, 70029.74, 70519.31, 
69858.63, 69987.23, 70080.56, 69970.63, 69829.6, 69872.12, 69775.68, 
69679.24, 69814.05, 69639.84, 69645.02, 69344.35, 69430.41, 70078.49, 
69239.65, 69734.1953, 69736.27, 69549.63, 69506.0859, 69108, 
69669.91, 69516.45, 69490.54, 69609.77, 69314.29, 69454.25, 69590.07, 
69721.76, 69525.79, 69736.27, 69303.92, 69171.23, 69294.59, 69430.41, 
69457.36, 69462.54, 69144.27, 69590.07, 69446.99, 70083.67, 69358.87, 
69800.56, 69680.28, 69332.95, 69723.83, 69942.63, 69772.56, 69969.59, 
69808.86, 70043.23, 70208.13, 70077.45, 69856.56, 70423.875, 
69490.54, 69984.12, 70175.98, 70192.58, 70279.7, 70480.93, 70594, 
70792.16, 70234.06, 70165.61, 70249.62, 70564.95, 70403.13, 70444.625, 
70426.99, 69907.375, 70327.4141, 70686.3359, 70473.67, 71031.83, 
70864.78, 70710.1953, 70691.52, 70703.97, 70826.39, 70708.12, 
70595.04, 70946.75, 71319.27, 70977.875, 70475.74, 70612.68, 
70680.11, 70527.61, 70461.22, 70877.2344, 70631.35, 70723.68, 
70677, 70433.21, 70306.6641, 71246.63, 70375.125, 70416.62, 70150.0547, 
70733.0156, 70583.63, 70866.86, 70580.5156, 70433.21, 70377.2, 
70114.79, 70347.12, 70613.71, 70576.37, 70599.19, 70407.28, 70581.5547, 
70650.02, 71122.11, 70909.4, 70694.63, 71076.45, 70650.02, 71133.52, 
70810.83, 71240.41, 70630.31, 71144.94, 71493.63, 71117.95, 71374.28, 
71143.9, 70805.64, 71349.375, 71208.2344, 71322.39, 71727.1641, 
71060.88, 71546.56, 71569.4, 70984.1, 72032.37, 71573.55, 71787.375, 
71469.76, 71398.15, 71683.57, 71709.52, 71637.9, 71556.9453, 
71870.4141, 71612.99, 71953.47, 71515.43, 71315.125, 72007.4453, 
72021.9844, 71549.68, 72001.22, 71359.75, 71775.95, 72327.23, 
71949.31, 71844.47, 71857.96, 72128.9141, 72147.6, 71501.94, 
72268.05, 72104, 72217.1641, 72253.51, 72198.48, 72908.78, 72084.27, 
72653.29, 72431.06, 72858.92, 72512.0547, 72632.5156, 72700.02, 
72335.53, 72713.52, 73065.62, 72818.42, 73004.3359, 72458.06, 
73436.48, 73231.82, 73002.26, 73313.89, 73213.125, 72980.4453, 
72948.25, 73106.13, 72931.625, 73409.47, 73057.31, 73141.4453, 
73218.32, 73216.24, 73273.375, 73701.42, 73486.35, 72574.37, 
73229.74, 73576.74, 73195.46, 73697.2656, 73115.48, 73065.62, 
73062.5, 73111.32, 73988.23, 73619.3359, 73874.95, 73683.76, 
73674.41, 73550.7656, 74166.9844, 73875.99, 74013.17, 74092.16, 
73872.875, 74015.25, 73984.07, 73911.33, 73606.87, 74082.8, 73866.64, 
74550.53, 74271.95, 73980.95, 74502.71, 74901.92, 74753.25, 74310.4141, 
75178.51, 74748.05, 74756.37, 75194.1, 74797.95, 75531.0547, 
75549.77, 75293.94, 75378.17, 75457.21, 75676.67, 76087.56, 76141.6641, 
76008.5, 76241.55, 76585.96, 76091.73, 76880.4844, 76898.18, 
77005.38, 77080.32, 77548.78, 77337.4453, 77000.18, 77448.8359, 
76997.0547, 77314.54, 77919.47, 77185.46, 78127.75, 77464.45, 
78349.59, 77824.71, 77465.49, 77818.46, 78140.25, 78547.51, 77850.74, 
78236.06, 78341.2656, 78104.8359, 78464.17, 77888.23, 78392.3, 
78686.0547, 78149.625, 78623.5547, 78672.5156, 78810.03, 78498.55, 
78652.72, 78717.31, 78831.91, 78882.96, 78715.23, 78499.5859, 
78892.3359, 78372.51)), row.names = c(NA, -306L), class = c("tbl_df", 
"tbl", "data.frame"))

I have used ggplot to plot the data and used a loop to calculate the average slope within a moving 60-second-window for the entire duration of the dataset to find the 60 consecutive seconds where the slope is greatest.

Code:

library(readr)
library(ggplot2)

Dataexample<- read_csv("HF-6.csv", skip = 3) 
Dataexample<- head(Dataexample, -1)

Dataexample$X <- as.numeric(Dataexample$X)

df <- data.frame(Dataexample)
 

ggplot(data=df, aes(x=X, y=Y, group=1))  
  geom_line()


slopes <- rep(NA, nrow(Dataexample)-59)
for( i in 1:length(slopes)){
  slopes[i] <- lm(Y ~ X, data=Dataexample[i:(i 59), ])$coefficients[2]
}

print(slopes)

which.max(slopes)
max(slopes)

My questions is how can I then take the results of my loop that show the consecutive 60 seconds where the slope is highest and change the color of the line in the plot during those 60 seconds to highlight where slope is greatest.

CodePudding user response：

This should work:

maxslope_ind <- which.max(slope)
Dataexample$highlight <- ifelse(Dataexample$X %in% maxslope_ind:(maxslope_ind 59), 1, 0)
library(ggplot2)
ggplot(data=Dataexample, aes(x=X, y=Y, group=1))  
  geom_line(aes(colour=as.factor(highlight)), show.legend=FALSE)   
  scale_colour_manual(values=c("black", "red"))