I want to make a plot for this table using stacked probability area plot
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The result of the table should be similar to this
the value of i changes form 0 to 1 and it is increased by 0.1
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Related
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I want the y axis to represent percentage instead of count
I want to plot 2D bar graph in LabVIEW showing total number of counts on Y-axis and Month/day(abbreviated) on x-axis. How can I do it?
Drop an XY graph.
Go to the plot properties and set Bar Plots to have the style you want and Interpolation to be just points.
If you open the context help window and hover over the terminal for the graph, you can see the data types it supports. You want the cluster which has a 1D array for the X values (timestamps of a time in the specific day) and a 1D array for the Y values. Generate your data in that format and wire it into the graph.
Right click the X scale and select Formatting.... In the properties dialog, set the format to be absolute time and to only show the day and the month.
Run the VI and you should have your graph.
I have just made a plot using raster data that consists of 6 different land types and fit them to polygon vectors. I'm trying to change the values on the continuous scale bar (1-6) to the names of each landtype (e.g. grasslands, urban, etc) which is what each different colour represents. I have tried inserting breaks, however then each box in the legend contains labels (1-2, 2-3, 3-4 etc.)
Raster plot where each diff colour represents diff land type
This is my code:
rasterxpolygonplotcode
Example data
library(terra)
r <- rast(nrows=10, ncols=10)
values(r) <- sample(3, ncell(r), replace=TRUE)
cover <- c("forest", "water", "urban")
You can either do:
plot(r, type="classes", levels=cover)
Or first make the raster categorical
levels(r) <- data.frame(id=1:3, cover=c("forest", "water", "urban"))
plot(r)
I want to create a scatter plot showing my treatment assignment on the y-axis and the margin of winning on the x-axis.
To create a binary treatment variable, where a margin over 0 indicates that a Republican candidate won the local election.
gen republican_win = (margin>0)
Here is a data example:
* Example generated by -dataex-. For more info, type help dataex
clear
input double margin float republican_win
-.356066316366196 0
-.54347825050354 0
-.204092293977737 0
-.449720650911331 1
-.201149433851242 1
-.505899667739868 0
-.206885248422623 1
end
To generate a scatter plot, I ran this. While the code ran well, I was wondering if it would be possible to display a continuous distribution of the margin of Republican wins and losses?
scatter margin republican_win
You can use the predicted probabilities by storing them in a variable, and then plot it at the same time as your scatter plot.
I would then reverse the axes to show your logistic distribution.
logit republican_win margin
predict win_hat
twoway scatter win_hat republican_win margin, ///
connect(l i) msymbol(i 0) sort ylabel(0 1)
There are not enough data points in your data example to show a nice fitted curve, but I'm sure it will look better on your whole dataset.
Let's say i have an image where maximum value is 1 and minimum is 0.8 (very brighty image).
when i use plt.imshow(image) i expect to see high intensity image, but for some reason i still see black, that means that plt.imshow normalize the range [0.8,1] to be [0,1]
how can i see the image without this normalization process?
for example, here is my image:
and min value is 0.57, where max value is 1. so why there is black in the image..?