How multiple plots can be compared - vb.net

I have two plots. and i have to compare these plots by making one plot.
example
plot1 x range (0 - 50), some y-range
plot2 x range (50 - 100), some y-range
resultant plot x range (0 -100)
How this can be done?

Am I missing something or can you just do:
plot(x1,y1);
points(x2-50,y2);
More generally, you can plot any 2 things together. You have to make the x and y scales constant across both plots. Something like this should work:
# assume I have vars: x1 and x2 and y1 and y2
# figure out the range of all y vars
yRange = range(y1,y2)
xRange = range(x1,x2)
plot(xRange,yRange, type='n') #creates the axes but doesn't put any points on them
points(x1,y1)
points(x2,y2, col='red')
My apologies, I thought this was in the R group and answered based on that.

Related

Adding specific range for y axis to plot

I cannot work out how to apply a specific y axis range to my violin plot
current code is :
library(ggplot2)
X21$`gggnnn`<-as.factor(X21$`gggnnn`)
X21$`RTtype`<-as.factor(X21$`RTtype`)
bp<-ggplot(data=X21,aes(x=RTtype,y=RT,group=RTtype))+
geom_violin(aes(colour=RTtype),outlier.alpha = 1)+
facet_grid(.~gggnnn) +
labs(x="AM or PM", y='Reaction time /ms')+
geom_boxplot(width=0.1,colour="black",alpha=1,outlier.shape=4)+
ggtitle("AM and PM Reaction Time Distributions among Gamers and Non-gamers")+
geom_jitter(data=X21,aes(x=RTtype,y=RT,group=RTtype, colour=RTtype,shape=gggnnn))+
bp
this gives the plot as shown:
[1]:https://i.stack.imgur.com/3Aggm.png
I then tried to set y axis limits with adding a '+ylim(150,900)' , however this just truncated my data:
[2]:https://i.stack.imgur.com/kDiRs.png
I now see that this is a limit on the range of the data, not the values on the axis (i am looking for the y axis to go from 150 to 900, also i do not know how to change the y axis grid spacing, as it is currently in intervals of 250, which is harder to interperit, i would like to set this to 100.
I attempted to do this with '+scale_y_continuous(breaks = seq(150,900, by = 100))', However it had no effect on the plot
Any help would be much appreciated
datasheet format:
[3]: https://i.stack.imgur.com/iXKXF.png
in order to set y coordinate limits use
coord_cartesian(ylim = c(100,900))
generalised this is:
coordinates_cartesian(xlim = c(lower limit,upper limit), ylim( c =(lower,upper)
in order to set spacing use
scale_y_continuous(breaks = seq(100, 900, by = 200))

Matplotlib - x axis does not match the data

The description of the data frame
When I try to find the relationship between budget and revenue_of_investment
x = dfm_2.budget
y = dfm_2.revenue_of_investment
plt.figure(figsize = (10,8))
plt.xlim((40000,42500000))
plt.scatter(x,y)
The output is:
I know the range of the budget is big, but I do not figure out the data on the x-axis.
I even set the range, however, the x-axis doesn't fit the data.
If I understand your question correctly (i.e. that the plot is not displaying all of the data on the x-axis), it's because your upper xlim is too small.
The maximum value of dfm_2.budget is 4.25 * 1e8 (i.e. 425000000), but your xlim upper limit is set to 4.25 * 1e7 (i.e. 42500000) (i.e. you're missing a zero in your plt.xlim())

Grouping the factors in ggplot

I am trying to create a graph based on matrix similar to one below... I am trying to group the Erosion values based on "Slope"...
library(ggplot2)
new_mat<-matrix(,nrow = 135, ncol = 7)
colnames(new_mat)<-c("Scenario","Runoff (mm)","Erosion (t/ac)","Slope","Soil","Tillage","Rotation")
for ( i in 1:nrow(new_mat)){
new_mat[i,2]<-sample(10:50, 1)
new_mat[i,3]<-sample(0.1:20, 1)
new_mat[i,4]<-sample(c("S2","S3","S4","S5","S1"),1)
new_mat[i,5]<-sample(c("Deep","Moderate","Shallow"),1)
new_mat[i,7]<-sample(c("WBP","WBF","WF"),1)
new_mat[i,6]<-sample(c("Intense","Reduced","Notill"),1)
new_mat[i,1]<-paste0(new_mat[i,4],"_",new_mat[i,5],"_",new_mat[i,6],"_",new_mat[i,7],"_")
}
#### Graph part ########
grphs_mat<-as.data.frame(new_mat)
grphs_mat$`Runoff (mm)`<-as.numeric(as.character(grphs_mat$`Runoff (mm)`))
grphs_mat$`Erosion (t/ac)`<-as.numeric(as.character(grphs_mat$`Erosion (t/ac)`))
ggplot(grphs_mat, aes(Scenario, `Erosion (t/ac)`,group=Slope, colour = Slope))+
scale_y_continuous(limits=c(0,max(as.numeric((grphs_mat$`Erosion (t/ac)`)))))+
geom_point()+geom_line()
But when i run this code.. The values are distributed in x-axis for all 135 scenarios. But what i want is grouping to be done in terms of slope but it also picks up the other common factors such as Soil+Rotation+Tillage and place it in x-axis. For example:
For these five scenarios:
S1_Deep_Intense_WBF_
S2_Deep_Intense_WBF_
S3_Deep_Intense_WBF_
S4_Deep_Intense_WBF_
S5_Deep_Intense_WBF_
It separates the S1, S2, S3,S4,S5 but also be able to know that other factors are same and put them in x-axis such that the slope lines are stacked on top of each other in 135/5 = 27 x-axis points. The final figure should look like this (Refer image). Apologies for not being able to explain it better.
I think i am making a mistake in grouping or assigning the x-axis values.
I will appreciate your suggestions.
In the example you give, I didn't get every possible factor combination represented so the plots looked a bit weird. What I did instead was start with the following:
set.seed(42)
new_mat <- matrix(,nrow = 1000, ncol = 7)
And then deduplicated this by summarising the values. A possible relevant step here for you analysis is that I made new variable with the interaction() function that is the combination of three other factors.
library(tidyverse)
df <- grphs_mat
df$x <- with(df, interaction(Rotation, Soil, Tillage))
# The simulation did not yield unique combinations
df <- df %>% group_by(x, Slope) %>%
summarise(n = sum(`Erosion (t/ac)`))
Next, I plotted this new x variable on the x-axis and used "stack" positions for the lines and points.
g <- ggplot(df, aes(x, y = n, colour = Slope, group = Slope)) +
geom_line(position = "stack") +
geom_point(position = "stack")
To make the x-axis slightly more readable, you can replace the . that the interaction() function placed by newlines.
g + scale_x_discrete(labels = function(x){gsub("\\.", "\n", x)})
Another option is to simply rotate the x axis labels:
g + theme(axis.text.x.bottom = element_text(angle = 90))
There are a few additional options for the x-axis if you go into ggplot2 extension packages.

Creating a 3 category binned colormap for continuous variable for matplotlib plot?

I have two measurements x & y and one calculation f(x, y) where f(x, y) can be broken into 3 categories: Acceptable(>1.2), At Risk (1 < x <=1.2), and Not Acceptable (<=1). I was wondering what is the best way to bin and plot this where f(x,y) is the colormap for a y v x scatter plot.
Thanks!
I'm not sure if this is exactly what you are after but sounds like you might be interested in pd.cut

Excel VBA: change x axis value as desired

I am creating charts with origin(100,0) i.e, x axis value=100. At first I used,
ActiveChart.Axes(xlValue).MajorUnit = 10
and I got the x axis ... 70,80,90,100,110,120,130....etc
I thought it would be better if I had axis values as ...60,80,100,120,140... etc. So I edited my code as follows,
ActiveChart.Axes(xlValue).MajorUnit = 20
But now I am getting ...70,90,110,130... etc.
How can I get my x axis as ...60,80,100,120,140...?