The scatterplot3D function seems to be plotting incorrectly and I am unsure about why. For example, the following commands should yield identical plots but they do not. I also providing reproducible code to create the data structures below. I guess it is not correctly processing my input?
install.packages("scatterplot3d")
library("scatterplot3d")
cent = array(dim=c(4,3))
cll = c("Factor1", "Factor2", "Factor3")
colnames(cent) = cll
cent[1,] = c(-0.25320707, -0.5878291, -0.4522262)
cent[2,] = c(2.49368231, 0.5911989, -0.3728652)
cent[3,] = c(-0.02927063, -0.2627355, 1.6147719)
cent[4,] = c(-0.63391974, 1.0109955, -0.1542808)
new.cent = array(dim=c(4,3))
colnames(new.cent) = cll
new.cent[1,] = c(2.1572533, 0.4985594, -0.1989068)
new.cent[2,] = c(-0.1362396, -0.4134629, 1.2677813)
new.cent[3,] = c(-0.2566698, -0.6602819, -0.5245323)
new.cent[4,] = c(-0.5847768, 0.7672588, -0.1918044)
Now I try to plot
plot.new()
scatterplot3d(new.cent, pch = 10)
points(cent, pch = 3)
plot of new.cent with cent added as points in different format
plot.new()
scatterplot3d(cent, pch = 3)
points(new.cent, pch = 10)
plot of cent with new.cent added as points in different format
The above points don't seem correct in any case... Moreover, if I try to add a single point as in "points(cent[1,])" it adds three points which is also indicative of the malfunction.
Please refer to linked manual, how to add points3d to the plot. Also, to compare plots, please make sure they axes limits are the same.
library("scatterplot3d")
cent = array(dim=c(4,3))
cll = c("Factor1", "Factor2", "Factor3")
colnames(cent) = cll
cent[1,] = c(-0.25320707, -0.5878291, -0.4522262)
cent[2,] = c(2.49368231, 0.5911989, -0.3728652)
cent[3,] = c(-0.02927063, -0.2627355, 1.6147719)
cent[4,] = c(-0.63391974, 1.0109955, -0.1542808)
new.cent = array(dim=c(4,3))
colnames(new.cent) = cll
new.cent[1,] = c(2.1572533, 0.4985594, -0.1989068)
new.cent[2,] = c(-0.1362396, -0.4134629, 1.2677813)
new.cent[3,] = c(-0.2566698, -0.6602819, -0.5245323)
new.cent[4,] = c(-0.5847768, 0.7672588, -0.1918044)
plot.new()
a <- scatterplot3d(new.cent, pch = 10, xlim = c(-1,2.5), ylim = c(-1,1.5), zlim = c(-1,2))
a$points3d(cent, pch = 3)
b <- scatterplot3d(cent, pch = 3, xlim = c(-1,2.5), ylim = c(-1,1.5), zlim = c(-1,2))
b$points3d(new.cent, pch = 10)
Created on 2022-01-27 by the reprex package (v2.0.1)
Related
I am trying to create an heatmap with a row annotation inclusive of p-values as reported in the example in the guide for the use of the ComplexHeatmap package (https://jokergoo.github.io/ComplexHeatmap-reference/book/heatmap-annotations.html#simple-annotation).
I tried to reproduce the example:
library(ComplexHeatmap)
library(circlize) # colorRamp2 function
set.seed(123)
pvalue = 10^-runif(10, min = 0, max = 3)
is_sig = pvalue < 0.01
pch = rep("*", 10)
pch[!is_sig] = NA
# color mapping for -log10(pvalue)
pvalue_col_fun = colorRamp2(c(0, 2, 3), c("green", "white", "red"))
ha = HeatmapAnnotation(
pvalue = anno_simple(-log10(pvalue), col = pvalue_col_fun, pch = pch),
annotation_name_side = "left")
ht = Heatmap(matrix(rnorm(100), 10), name = "mat", top_annotation = ha)
# now we generate two legends, one for the p-value
# see how we define the legend for pvalue
lgd_pvalue = Legend(title = "p-value", col = pvalue_col_fun, at = c(0, 1, 2, 3),
labels = c("1", "0.1", "0.01", "0.001"))
# and one for the significant p-values
lgd_sig = Legend(pch = "*", type = "points", labels = "< 0.01")
# these two self-defined legends are added to the plot by `annotation_legend_list`
draw(ht, annotation_legend_list = list(lgd_pvalue, lgd_sig))
but when I am creating the annotation ha I get the error
Error in anno_simple(-log10(pvalue), col = pvalue_col_fun, pch = pch) :
could not find function "anno_simple"
likely showing a possible problem with the package.
The version of the ComplexHeatmap package I am running is 1.20.0.
The R version is 3.5.1.
Could you please help me solving this problem?
Thanks
> dput(head(inputData))
structure(list(Date = c("2018:07:00", "2018:06:00", "2018:05:00",
"2018:04:00", "2018:03:00", "2018:02:00"), IIP = c(125.8, 127.5,
129.7, 122.6, 140.3, 127.4), CPI = c(139.8, 138.5, 137.8, 137.1,
136.5, 136.4), `Term Spread` = c(1.580025, 1.89438, 2.020112,
1.899074, 1.470544, 1.776862), RealMoney = c(142713.9916, 140728.6495,
140032.2762, 139845.5215, 139816.4682, 139625.865), NSE50 = c(10991.15682,
10742.97381, 10664.44773, 10472.93333, 10232.61842, 10533.10526
), CallMoneyRate = c(6.161175, 6.10112, 5.912088, 5.902226, 5.949956,
5.925538), STCreditSpread = c(-0.4977, -0.3619, 0.4923, 0.1592,
0.3819, -0.1363)), row.names = c(NA, -6L), class = c("tbl_df",
"tbl", "data.frame"))
I want to make my autoregressive plot like this plot:
#------> importing all libraries
library(readr)
install.packages("lubridtae")
library("lubridate")
install.packages("forecast")
library('ggplot2')
library('fpp')
library('forecast')
library('tseries')
#--------->reading data
inputData <- read_csv("C:/Users/sanat/Downloads/exercise_1.csv")
#--------->calculating the lag=1 for NSE50
diff_NSE50<-(diff(inputData$NSE50, lag = 1, differences = 1)/lag(inputData$NSE50))
diff_RealM2<-(diff(inputData$RealMoney, lag = 1, differences = 1)/lag(inputData$RealMoney))
plot.ts(diff_NSE50)
#--------->
lm_fit = dynlm(IIP ~ CallMoneyRate + STCreditSpread + diff_NSE50 + diff_RealM2, data = inputData)
summary(lm_fit)
#--------->
inputData_ts = ts(inputData, frequency = 12, start = 2012)
#--------->area of my doubt is here
VAR_data <- window(ts.union(ts(inputData$IIP), ts(inputData$CallMoneyRate)))
VAR_est <- VAR(y = VAR_data, p = 12)
plot(VAR_est)
I want to my plots to get plotted together in same plot. How do I serparate the var() plots to two separate ones.
Current plot:
My dataset :
dataset
Okay, so this still needs some work, but it should set the right framework for you. I would look more into working with the ggplot2 for future.
Few extra packages needed, namely library(vars) and library(dynlm).
Starting from,
VAR_est <- VAR(y = VAR_data, p = 12)
Now we extract the values we want from the VAR_est object.
y <- as.numeric(VAR_est$y[,1])
z <- as.numeric(VAR_est$y[,2])
x <- 1:length(y)
## second data set on a very different scale
par(mar = c(5, 4, 4, 4) + 0.3) # Leave space for z axis
plot(x, y, type = "l") # first plot
par(new = TRUE)
plot(x, z, type = "l", axes = FALSE, bty = "n", xlab = "", ylab = "")
axis(side=4, at = pretty(range(z)))
mtext("z", side=4, line=3)
I will leave you to add the dotted lines on etc...
Hint: Decompose the VAR_est object, for example, VAR_est$datamat, then see which bit of data corresponds to the part of the plot you want.
Used some of this
In the following igraph there are dates to be plotted as marks on the x-axis. Below I provided an example. As the dates are specified in the label matrix they are formatted into an atomic value. How do I get the dates on the x-axis to be displayed in a regular date format?
library(igraph)
nodes=data.frame(
c(0,1,2,3),
c("A","B","C","D")
)
colnames(nodes) = c("id","name")
links = data.frame(
c(0,0,1,2),
c(1,2,3,3)
)
colnames(links) = c("from","to")
layout = matrix(
c(as.Date('2010-01-01'),1, as.Date('2010-01-02'),1, as.Date('2010-01-02'),2, as.Date('2010-01-06'),1), byrow = TRUE, nrow=4
)
net = graph.data.frame(links, vertices = nodes)
plot.igraph(
net, xaxt="n",layout=layout,axes=TRUE,asp=0, rescale=FALSE,xlim=c(as.Date('2010-01-01'),as.Date('2010-01-06')),ylim=c(1,2)
)
You can replace the axis by your own values as explained here.
Using your code, it gives:
layout <- data.frame(Date = as.Date(c('2010-01-01','2010-01-02','2010-01-02','2010-01-06')), value = c(1,2,1,1))
plot.igraph(
net,
layout = layout,
rescale = FALSE,
axis = FALSE,
asp = 0,
xlim = as.Date(c('2010-01-01', '2010-01-06')),
ylim = c(1,2)
)
axis(1, at = as.numeric(layout$Date), labels = layout$Date, cex.axis = 0.9)
axis(2, at = 1:max(layout$value), labels = 1:max(layout$value))
I am plotting a time series with the timePlot function of the open air package of R. The graph has grey grid lines in the background that I would like to turn off but I do not find a way to do it. I would expect something simple such as grid = FALSE, but that is not the case. It appears to be rather complex, requiring the use of extra arguments which are passed to xyplot of the library lattice. I believe the answer lies some where in the par.settings function but all attempts have failed. Does anyone have any suggestions to this issue?
Here is by script:
timeozone <- import(i, date="date", date.format = "%m/%d/%Y", header=TRUE, na.strings="")
ROMO = timePlot(timeozone, pollutant = c("C7", "C9", "C10"), group = TRUE, stack = FALSE,y.relation = "same", date.breaks = 9, lty = c(1,2,3), lwd = c(2, 3, 3), fontsize = 15, cols = c("black", "black"), ylab = "Ozone (ppbv)")
panel = function(x, y) {
panel.grid(h = 0, v = 0)
panel.xyplot(x,y)
}
I have a question about the par function in R.
I want to change the color and/or width of a line in a graph with par function. (I am using par function because the gaps.plot command below does not allow "col" option to be included. The gaps.plot command is used after the synth command).
So, I used the following command. But I noticed that the lines of the BOX are changed rather than the lines of the GRAPHS.
synth1<-read.csv(file="C:\\Users\\Research\\R\\synthinR_v4.csv",header=TRUE)
attach(synth1)
library("Synth")
dataprep.out34 <- dataprep(foo = synth1, predictors = c("lncdsales", "md1", "md2","md3", "md4", "md5", "md6", "md7", "md8", "md9", "md10", "md11", "yd1", "yd2", "yd3", "yd4", "yd5", "yd6", "yd7", "yd8"), predictors.op = "mean", time.predictors.prior = -13:1, dependent = "lndigital", unit.variable = "artistalbumcode", time.variable = "release", treatment.identifier = 34, controls.identifier = c(1:33, 35:49), time.optimize.ssr = -13:1, time.plot = -13:25)
synth.out34 <- synth(data.prep.obj = dataprep.out34, method = "BFGS")
par(lwd = 2, col="#cccccc")
gaps.plot(synth.res = synth.out34, dataprep.res = dataprep.out34, Ylab = " Log Digital Sales ", Xlab = "Release", Ylim = c(-7, 7) , Main = NA)
Does anyone know how to fix this problem??
Thank you in advance for your willingness to help. I greatly appreciate it!
The col argument to par sets the default plotting colour (i.e. when col is not explicitly specified in plotting calls), but unfortunately col = "black" is hard-coded into the source of gaps.plot.
You can make a modified copy of the function by either (1) viewing the source (F2 in RStudio, or just executing gaps.plot), editing it and assigning it to a new object, or (2) doing something like the following:
gaps.plot2 <- eval(parse(text=gsub('col = "black"', 'col = "red"',
deparse(Synth:::gaps.plot))))
and then using gaps.plot2 as you would use gaps.plot:
gaps.plot2(synth.res = synth.out34, dataprep.res = dataprep.out34,
Ylab = " Log Digital Sales ", Xlab = "Release", Ylim = c(-7, 7) ,
Main = NA)
Alter the lwd similarly. For example to make lines red and have width of 3, use nested gsub calls like this:
gaps.plot2 <- eval(parse(text=gsub('lwd = 2', 'lwd = 3',
gsub('col = "black"', 'col = "red"',
deparse(Synth:::gaps.plot)))))