I have four time-series, two of each observation type (two different methods). For visualization, I want to overlay the two corresponding methods. So, essentially I have two multi-panel time-series that I want to plot on top of each other. However, this isn't working. If I plot everything in just one panel, it works fine, but once I try it with multi-panel, the second graph of the second set of time-series is only plotted in the first panel. My time-series are zoo objects created with read.zoo.
我有四个时间序列，每种观察类型两种（两种不同的方法）。对于可视化，我想重叠两个相应的方法。所以，基本上我有两个多面板时间序列，我想在彼此之上绘制。但是，这不起作用。如果我只在一个面板中绘制所有内容，它可以正常工作，但是一旦我尝试使用多面板，第二组时间序列的第二个图形仅绘制在第一个面板中。我的时间序列是用read.zoo创建的动物园对象。
From the suggested questions I already tried mfg = c(1, 1), but that didn't help, either.
从建议的问题我已经尝试了mfg = c（1,1），但这也没有帮助。
PS: I know that the time-ranges don't match, yet, but that is easily fixed, later. Right now I really need to get them to plot on top of each other, first.
PS：我知道时间范围不匹配，但稍后很容易修复。现在我真的需要让他们首先在彼此之上进行绘图。
method1.ts
2017 2018
2017-01-22 NA 12.833333
2017-01-24 NA 12.166667
2017-01-26 NA 9.666667
2017-01-27 7.666667 NA
2017-01-29 NA 13.000000
2017-01-31 13.666667 16.200000
2017-02-07 NA 25.800000
2017-02-08 12.833333 NA
2017-02-09 NA 14.333333
2017-02-12 NA 20.833333
2017-02-14 NA 14.500000
2017-02-15 14.500000 NA
2017-02-16 NA 21.800000
2017-02-17 18.400000 NA
2017-02-21 NA 11.333333
2017-02-23 11.000000 10.000000
2017-02-26 NA 9.000000
2017-02-28 NA 5.333333
2017-03-03 11.200000 NA
2017-03-06 14.000000 8.500000
2017-03-07 15.166667 11.000000
2017-03-08 18.500000 NA
2017-03-09 10.600000 6.400000
2017-03-10 5.666667 NA
2017-03-14 NA 7.833333
2017-03-16 17.166667 6.333333
2017-03-19 NA 6.200000
2017-03-20 10.666667 NA
2017-03-21 NA 4.833333
2017-03-23 NA 2.200000
2017-03-27 NA 5.000000
2017-03-29 5.000000 NA
2017-03-30 2.166667 3.500000
2017-03-31 2.166667 NA
2017-04-02 NA 4.333333
2017-04-04 2.666667 NA
2017-04-06 NA 5.666667
2017-04-09 NA 3.000000
2017-04-11 4.000000 NA
method2.ts
2017SMA10 2018SMA10
2017-01-01 103.47929 105.55044
2017-01-02 103.65610 105.99537
2017-01-03 103.95392 106.34103
2017-01-04 104.46880 106.60617
2017-01-05 104.73571 107.03311
2017-01-06 105.22571 107.51610
2017-01-07 105.66239 107.86581
2017-01-08 106.32076 108.15234
2017-01-09 106.71721 108.23427
2017-01-10 107.13703 108.62571
2017-01-11 107.33828 108.96101
2017-01-12 108.00310 109.32104
2017-01-13 108.08786 109.60690
2017-01-14 108.39603 109.79566
2017-01-15 109.14699 109.78634
2017-01-16 109.59578 109.88837
2017-01-17 109.94503 110.04936
2017-01-18 110.01586 110.29642
2017-01-19 110.28466 110.35866
2017-01-20 110.62044 110.46795
2017-01-21 110.89312 110.42743
2017-01-22 110.95852 110.37680
2017-01-23 111.36118 110.09512
2017-01-24 111.05119 109.97177
2017-01-25 110.90067 109.92303
2017-01-26 110.62912 109.82026
2017-01-27 110.60603 109.60733
2017-01-28 110.47436 109.21956
2017-01-29 110.42441 109.12986
2017-01-30 110.51541 109.06790
2017-01-31 110.53018 109.22308
2017-02-01 110.73878 109.07460
2017-02-02 111.12024 109.19609
2017-02-03 111.73241 109.43983
2017-02-04 112.24936 109.59187
2017-02-05 112.62716 109.92450
2017-02-06 112.61923 110.30853
2017-02-07 112.97632 110.71683
2017-02-08 113.39098 110.97291
2017-02-09 113.45327 110.98421
2017-02-10 113.48387 111.02553
2017-02-11 113.25614 111.28360
2017-02-12 113.02449 111.19611
2017-02-13 112.92730 110.83878
2017-02-14 112.54101 110.91351
2017-02-15 112.71891 110.91647
2017-02-16 113.11793 110.92492
2017-02-17 113.19623 111.01643
2017-02-18 113.42685 111.03396
2017-02-19 113.45987 111.12398
2017-02-20 113.58438 111.27783
2017-02-21 113.75347 111.26295
2017-02-22 113.67686 111.55714
2017-02-23 113.61202 111.77674
2017-02-24 113.71818 111.84619
2017-02-25 113.53106 111.78978
2017-02-26 113.27395 111.52515
2017-02-27 113.37993 111.07457
2017-02-28 112.99659 110.72079
2017-03-01 113.03771 110.26982
2017-03-02 113.03668 109.62535
2017-03-03 113.01434 109.60159
2017-03-04 112.97362 109.40245
2017-03-05 113.11412 109.45290
2017-03-06 112.96689 109.24544
2017-03-07 112.98576 109.14174
2017-03-08 113.08641 109.07428
2017-03-09 112.70413 109.25517
2017-03-10 112.62559 109.46077
2017-03-11 112.19805 109.52448
2017-03-12 112.08765 109.75256
2017-03-13 111.81722 109.47225
2017-03-14 111.73174 109.22018
2017-03-15 111.55903 108.96538
2017-03-16 111.47345 108.71323
2017-03-17 111.47883 108.40790
2017-03-18 111.26682 107.86127
2017-03-19 111.29885 107.46722
2017-03-20 111.26148 106.55255
2017-03-21 111.16590 106.25858
2017-03-22 110.77000 105.54820
2017-03-23 110.32807 104.84036
2017-03-24 109.68646 104.49891
2017-03-25 108.74408 104.04718
2017-03-26 107.68592 103.63353
2017-03-27 106.52149 103.28782
2017-03-28 105.84684 103.04769
2017-03-29 105.07075 102.77137
2017-03-30 104.20832 103.04664
2017-03-31 103.63085 102.78385
2017-04-01 102.73122 102.84506
2017-04-02 101.91008 102.77019
2017-04-03 101.44941 102.51452
2017-04-04 101.24398 102.48821
2017-04-05 101.18613 102.32695
2017-04-06 101.54618 102.32948
2017-04-07 101.54394 102.40627
2017-04-08 101.33914 102.26635
2017-04-09 101.27709 101.93674
2017-04-10 101.11309 101.79369
2017-04-11 101.22372 101.64324
2017-04-12 101.36781 101.42651
2017-04-13 101.53346 101.14693
2017-04-14 101.21404 100.64058
2017-04-15 101.13418 100.27125
2017-04-16 100.57103 99.72244
2017-04-17 100.29517 99.24280
2017-04-18 99.70332 98.84724
2017-04-19 99.15901 98.52565
2017-04-20 98.64558 98.19044
2017-04-21 98.27425 97.76493
2017-04-22 98.12550 97.59279
2017-04-23 97.80408 97.47610
2017-04-24 97.89017 97.44518
2017-04-25 97.63646 97.41834
2017-04-26 96.95511 97.28475
2017-04-27 95.99498 97.31325
2017-04-28 95.63205 97.64434
2017-04-29 95.46168 97.63731
2017-04-30 95.41300 97.67666
plot(method1.ts, type="h", lwd=3, lend=1, plot.type="multiple")
par(new=T, mfrow=c(2,1))
plot(method2.ts, lty=1, lwd=2, plot.type="multiple", xaxt="n", yaxt="n", xlab="", ylab="")
1 个解决方案
#1
1
Multi-panel plots should be done all in one call. Merge the two zoo objects and then do it all at once. See ?plot.zoo
多面板图应该在一次调用中完成。合并两个动物园对象，然后一次完成所有操作。见？plot.zoo
library(zoo)
both <- merge(method1.ts, method2.ts, all = TRUE)
plot(both, screen = c("2017", "2018"), type = list("h", "h", "l", "l"))
The above plot line would also work with lattice by replacing plot with xyplot.
通过用xyplot替换plot，上面的绘图线也适用于晶格。
Note
Inputs in reproducible form:
可重复输入的输入：
Lines1 <- "Date 2017 2018
2017-01-22 NA 12.833333
2017-01-24 NA 12.166667
2017-01-26 NA 9.666667
2017-01-27 7.666667 NA
2017-01-29 NA 13.000000
2017-01-31 13.666667 16.200000
2017-02-07 NA 25.800000
2017-02-08 12.833333 NA
2017-02-09 NA 14.333333
2017-02-12 NA 20.833333
2017-02-14 NA 14.500000
2017-02-15 14.500000 NA
2017-02-16 NA 21.800000
2017-02-17 18.400000 NA
2017-02-21 NA 11.333333
2017-02-23 11.000000 10.000000
2017-02-26 NA 9.000000
2017-02-28 NA 5.333333
2017-03-03 11.200000 NA
2017-03-06 14.000000 8.500000
2017-03-07 15.166667 11.000000
2017-03-08 18.500000 NA
2017-03-09 10.600000 6.400000
2017-03-10 5.666667 NA
2017-03-14 NA 7.833333
2017-03-16 17.166667 6.333333
2017-03-19 NA 6.200000
2017-03-20 10.666667 NA
2017-03-21 NA 4.833333
2017-03-23 NA 2.200000
2017-03-27 NA 5.000000
2017-03-29 5.000000 NA
2017-03-30 2.166667 3.500000
2017-03-31 2.166667 NA
2017-04-02 NA 4.333333
2017-04-04 2.666667 NA
2017-04-06 NA 5.666667
2017-04-09 NA 3.000000
2017-04-11 4.000000 NA"
Lines2 <- "Date 2017SMA10 2018SMA10
2017-01-01 103.47929 105.55044
2017-01-02 103.65610 105.99537
2017-01-03 103.95392 106.34103
2017-01-04 104.46880 106.60617
2017-01-05 104.73571 107.03311
2017-01-06 105.22571 107.51610
2017-01-07 105.66239 107.86581
2017-01-08 106.32076 108.15234
2017-01-09 106.71721 108.23427
2017-01-10 107.13703 108.62571
2017-01-11 107.33828 108.96101
2017-01-12 108.00310 109.32104
2017-01-13 108.08786 109.60690
2017-01-14 108.39603 109.79566
2017-01-15 109.14699 109.78634
2017-01-16 109.59578 109.88837
2017-01-17 109.94503 110.04936
2017-01-18 110.01586 110.29642
2017-01-19 110.28466 110.35866
2017-01-20 110.62044 110.46795
2017-01-21 110.89312 110.42743
2017-01-22 110.95852 110.37680
2017-01-23 111.36118 110.09512
2017-01-24 111.05119 109.97177
2017-01-25 110.90067 109.92303
2017-01-26 110.62912 109.82026
2017-01-27 110.60603 109.60733
2017-01-28 110.47436 109.21956
2017-01-29 110.42441 109.12986
2017-01-30 110.51541 109.06790
2017-01-31 110.53018 109.22308
2017-02-01 110.73878 109.07460
2017-02-02 111.12024 109.19609
2017-02-03 111.73241 109.43983
2017-02-04 112.24936 109.59187
2017-02-05 112.62716 109.92450
2017-02-06 112.61923 110.30853
2017-02-07 112.97632 110.71683
2017-02-08 113.39098 110.97291
2017-02-09 113.45327 110.98421
2017-02-10 113.48387 111.02553
2017-02-11 113.25614 111.28360
2017-02-12 113.02449 111.19611
2017-02-13 112.92730 110.83878
2017-02-14 112.54101 110.91351
2017-02-15 112.71891 110.91647
2017-02-16 113.11793 110.92492
2017-02-17 113.19623 111.01643
2017-02-18 113.42685 111.03396
2017-02-19 113.45987 111.12398
2017-02-20 113.58438 111.27783
2017-02-21 113.75347 111.26295
2017-02-22 113.67686 111.55714
2017-02-23 113.61202 111.77674
2017-02-24 113.71818 111.84619
2017-02-25 113.53106 111.78978
2017-02-26 113.27395 111.52515
2017-02-27 113.37993 111.07457
2017-02-28 112.99659 110.72079
2017-03-01 113.03771 110.26982
2017-03-02 113.03668 109.62535
2017-03-03 113.01434 109.60159
2017-03-04 112.97362 109.40245
2017-03-05 113.11412 109.45290
2017-03-06 112.96689 109.24544
2017-03-07 112.98576 109.14174
2017-03-08 113.08641 109.07428
2017-03-09 112.70413 109.25517
2017-03-10 112.62559 109.46077
2017-03-11 112.19805 109.52448
2017-03-12 112.08765 109.75256
2017-03-13 111.81722 109.47225
2017-03-14 111.73174 109.22018
2017-03-15 111.55903 108.96538
2017-03-16 111.47345 108.71323
2017-03-17 111.47883 108.40790
2017-03-18 111.26682 107.86127
2017-03-19 111.29885 107.46722
2017-03-20 111.26148 106.55255
2017-03-21 111.16590 106.25858
2017-03-22 110.77000 105.54820
2017-03-23 110.32807 104.84036
2017-03-24 109.68646 104.49891
2017-03-25 108.74408 104.04718
2017-03-26 107.68592 103.63353
2017-03-27 106.52149 103.28782
2017-03-28 105.84684 103.04769
2017-03-29 105.07075 102.77137
2017-03-30 104.20832 103.04664
2017-03-31 103.63085 102.78385
2017-04-01 102.73122 102.84506
2017-04-02 101.91008 102.77019
2017-04-03 101.44941 102.51452
2017-04-04 101.24398 102.48821
2017-04-05 101.18613 102.32695
2017-04-06 101.54618 102.32948
2017-04-07 101.54394 102.40627
2017-04-08 101.33914 102.26635
2017-04-09 101.27709 101.93674
2017-04-10 101.11309 101.79369
2017-04-11 101.22372 101.64324
2017-04-12 101.36781 101.42651
2017-04-13 101.53346 101.14693
2017-04-14 101.21404 100.64058
2017-04-15 101.13418 100.27125
2017-04-16 100.57103 99.72244
2017-04-17 100.29517 99.24280
2017-04-18 99.70332 98.84724
2017-04-19 99.15901 98.52565
2017-04-20 98.64558 98.19044
2017-04-21 98.27425 97.76493
2017-04-22 98.12550 97.59279
2017-04-23 97.80408 97.47610
2017-04-24 97.89017 97.44518
2017-04-25 97.63646 97.41834
2017-04-26 96.95511 97.28475
2017-04-27 95.99498 97.31325
2017-04-28 95.63205 97.64434
2017-04-29 95.46168 97.63731
2017-04-30 95.41300 97.67666"
library(zoo)
method1.ts <- read.zoo(text = Lines1, header = TRUE, check.names = FALSE)
method2.ts <- read.zoo(text = Lines2, header = TRUE, check.names = FALSE)
#1
1
Multi-panel plots should be done all in one call. Merge the two zoo objects and then do it all at once. See ?plot.zoo
多面板图应该在一次调用中完成。合并两个动物园对象，然后一次完成所有操作。见？plot.zoo
library(zoo)
both <- merge(method1.ts, method2.ts, all = TRUE)
plot(both, screen = c("2017", "2018"), type = list("h", "h", "l", "l"))
The above plot line would also work with lattice by replacing plot with xyplot.
通过用xyplot替换plot，上面的绘图线也适用于晶格。
Note
Inputs in reproducible form:
可重复输入的输入：
Lines1 <- "Date 2017 2018
2017-01-22 NA 12.833333
2017-01-24 NA 12.166667
2017-01-26 NA 9.666667
2017-01-27 7.666667 NA
2017-01-29 NA 13.000000
2017-01-31 13.666667 16.200000
2017-02-07 NA 25.800000
2017-02-08 12.833333 NA
2017-02-09 NA 14.333333
2017-02-12 NA 20.833333
2017-02-14 NA 14.500000
2017-02-15 14.500000 NA
2017-02-16 NA 21.800000
2017-02-17 18.400000 NA
2017-02-21 NA 11.333333
2017-02-23 11.000000 10.000000
2017-02-26 NA 9.000000
2017-02-28 NA 5.333333
2017-03-03 11.200000 NA
2017-03-06 14.000000 8.500000
2017-03-07 15.166667 11.000000
2017-03-08 18.500000 NA
2017-03-09 10.600000 6.400000
2017-03-10 5.666667 NA
2017-03-14 NA 7.833333
2017-03-16 17.166667 6.333333
2017-03-19 NA 6.200000
2017-03-20 10.666667 NA
2017-03-21 NA 4.833333
2017-03-23 NA 2.200000
2017-03-27 NA 5.000000
2017-03-29 5.000000 NA
2017-03-30 2.166667 3.500000
2017-03-31 2.166667 NA
2017-04-02 NA 4.333333
2017-04-04 2.666667 NA
2017-04-06 NA 5.666667
2017-04-09 NA 3.000000
2017-04-11 4.000000 NA"
Lines2 <- "Date 2017SMA10 2018SMA10
2017-01-01 103.47929 105.55044
2017-01-02 103.65610 105.99537
2017-01-03 103.95392 106.34103
2017-01-04 104.46880 106.60617
2017-01-05 104.73571 107.03311
2017-01-06 105.22571 107.51610
2017-01-07 105.66239 107.86581
2017-01-08 106.32076 108.15234
2017-01-09 106.71721 108.23427
2017-01-10 107.13703 108.62571
2017-01-11 107.33828 108.96101
2017-01-12 108.00310 109.32104
2017-01-13 108.08786 109.60690
2017-01-14 108.39603 109.79566
2017-01-15 109.14699 109.78634
2017-01-16 109.59578 109.88837
2017-01-17 109.94503 110.04936
2017-01-18 110.01586 110.29642
2017-01-19 110.28466 110.35866
2017-01-20 110.62044 110.46795
2017-01-21 110.89312 110.42743
2017-01-22 110.95852 110.37680
2017-01-23 111.36118 110.09512
2017-01-24 111.05119 109.97177
2017-01-25 110.90067 109.92303
2017-01-26 110.62912 109.82026
2017-01-27 110.60603 109.60733
2017-01-28 110.47436 109.21956
2017-01-29 110.42441 109.12986
2017-01-30 110.51541 109.06790
2017-01-31 110.53018 109.22308
2017-02-01 110.73878 109.07460
2017-02-02 111.12024 109.19609
2017-02-03 111.73241 109.43983
2017-02-04 112.24936 109.59187
2017-02-05 112.62716 109.92450
2017-02-06 112.61923 110.30853
2017-02-07 112.97632 110.71683
2017-02-08 113.39098 110.97291
2017-02-09 113.45327 110.98421
2017-02-10 113.48387 111.02553
2017-02-11 113.25614 111.28360
2017-02-12 113.02449 111.19611
2017-02-13 112.92730 110.83878
2017-02-14 112.54101 110.91351
2017-02-15 112.71891 110.91647
2017-02-16 113.11793 110.92492
2017-02-17 113.19623 111.01643
2017-02-18 113.42685 111.03396
2017-02-19 113.45987 111.12398
2017-02-20 113.58438 111.27783
2017-02-21 113.75347 111.26295
2017-02-22 113.67686 111.55714
2017-02-23 113.61202 111.77674
2017-02-24 113.71818 111.84619
2017-02-25 113.53106 111.78978
2017-02-26 113.27395 111.52515
2017-02-27 113.37993 111.07457
2017-02-28 112.99659 110.72079
2017-03-01 113.03771 110.26982
2017-03-02 113.03668 109.62535
2017-03-03 113.01434 109.60159
2017-03-04 112.97362 109.40245
2017-03-05 113.11412 109.45290
2017-03-06 112.96689 109.24544
2017-03-07 112.98576 109.14174
2017-03-08 113.08641 109.07428
2017-03-09 112.70413 109.25517
2017-03-10 112.62559 109.46077
2017-03-11 112.19805 109.52448
2017-03-12 112.08765 109.75256
2017-03-13 111.81722 109.47225
2017-03-14 111.73174 109.22018
2017-03-15 111.55903 108.96538
2017-03-16 111.47345 108.71323
2017-03-17 111.47883 108.40790
2017-03-18 111.26682 107.86127
2017-03-19 111.29885 107.46722
2017-03-20 111.26148 106.55255
2017-03-21 111.16590 106.25858
2017-03-22 110.77000 105.54820
2017-03-23 110.32807 104.84036
2017-03-24 109.68646 104.49891
2017-03-25 108.74408 104.04718
2017-03-26 107.68592 103.63353
2017-03-27 106.52149 103.28782
2017-03-28 105.84684 103.04769
2017-03-29 105.07075 102.77137
2017-03-30 104.20832 103.04664
2017-03-31 103.63085 102.78385
2017-04-01 102.73122 102.84506
2017-04-02 101.91008 102.77019
2017-04-03 101.44941 102.51452
2017-04-04 101.24398 102.48821
2017-04-05 101.18613 102.32695
2017-04-06 101.54618 102.32948
2017-04-07 101.54394 102.40627
2017-04-08 101.33914 102.26635
2017-04-09 101.27709 101.93674
2017-04-10 101.11309 101.79369
2017-04-11 101.22372 101.64324
2017-04-12 101.36781 101.42651
2017-04-13 101.53346 101.14693
2017-04-14 101.21404 100.64058
2017-04-15 101.13418 100.27125
2017-04-16 100.57103 99.72244
2017-04-17 100.29517 99.24280
2017-04-18 99.70332 98.84724
2017-04-19 99.15901 98.52565
2017-04-20 98.64558 98.19044
2017-04-21 98.27425 97.76493
2017-04-22 98.12550 97.59279
2017-04-23 97.80408 97.47610
2017-04-24 97.89017 97.44518
2017-04-25 97.63646 97.41834
2017-04-26 96.95511 97.28475
2017-04-27 95.99498 97.31325
2017-04-28 95.63205 97.64434
2017-04-29 95.46168 97.63731
2017-04-30 95.41300 97.67666"
library(zoo)
method1.ts <- read.zoo(text = Lines1, header = TRUE, check.names = FALSE)
method2.ts <- read.zoo(text = Lines2, header = TRUE, check.names = FALSE)