Please advise some R packages on rotating or flipping image on R.
Thru package and , i'm able to read pic and turn into matrices (or data frame), however, duto the angle of shooting, the photo is tiled (or not directly facing me). I would like to manipulate the data, so I can adjust the angle.
My plan is to define the normal line of the left pic, and recalculate the angle, but failed. Guess there could be some image manipulation packages for this.
Have tried the CRAN TASKS, yet, most of the packages are for creating images, not to manipulate the outside-in images.
Related
I am trying to manually identify/correct trees using LiDAR data (1.7 GB object) and a tree tops object via the locate_trees function. Part of the problem is:
Rgl is rendering very slow even though the 4 GB Nvidia 3050 should be able to handle it.
The tree tops (red 3D dots) are not even showing in the rgl window. When I close the rgl window, the tree tops start popping up (red dots appear and disappear resulting in a blank white window) in a new rgl window. And if I close that window, a new tree top window opens up so I stop the process to prevent this from happening.
Does rgl automatically use the GPU or does it default to the integrated graphics on the motherboard? Is there a way to fasten up the rendering?
My other system specs are Corei9 (14 threads) and 64 GB RAM. Moreover, I am using R 4.2.1.
Code:
library(lidR)
# Import LiDAR data
LiDAR_File = readLAS("path/file_name.las")
# Find tree tops
TTops = find_trees(LiDAR_File , lmf(ws = 15, hmin = 5))
# Manually correct tree identification
TTops_Manual = locate_trees(LiDAR_File , manual(TTops)) # This is where rgl rendering becomes too slow if there are too many points involved.
There were two problems here. First, the lidR::manual() function which is used to select trees has a loop where one sphere is drawn for each tree. By default rgl will redraw the whole scene after each change; this should be suppressed. The patch in https://github.com/r-lidar/lidR/pull/611 fixes this. You can install a version with this fix as
remotes::install_github("r-lidar/lidR")
Second, rgl was somewhat inefficient in drawing the initial point cloud of data, duplicating the data unnecessarily. When you have tens of millions of points, this can exhaust all R memory, and things slow to a crawl. The development version of rgl fixes this. It's available via
remotes::install_github("dmurdoch/rgl")
The LiDAR images are very big, so you might find you still have problems even with these changes. Getting more regular RAM will help R: you may need this if the time to the first display is too long. After the first display, almost all the work is done in the graphics system; if things are still too slow, you may need a faster graphics card (or more memory for it).
rgl has trouble displaying too many points. The plot function in lidR is convenient and allows to produce ready to publish illustrations but cannot replace a real point cloud viewer for big point clouds. I don't have GPU on my computer and I don't know if and how rgl can take advantage of GPU.
In the doc of the lidR function your are talking about you can see:
This is only suitable for small-sized plots
In the R d3heatmap package, is there a way to rotate the x axis label to be 90 degrees (perpendicular to the axis) instead of 45?
I couldn't find an easy option to pass a rotation value to the function, but you can go into the innards of the d3heatmap package and change the rotation in the javascript code.
Run ".libPaths()" in R to find where your R packages and their data are stored. In my case I found the d3heatmap package in '/home/nick/R/x86_64-suse-linux-gnu-library/3.1/d3heatmap/'.
The file you are looking for is something like '/home/nick/R/x86_64-suse-linux-gnu-library/3.1/d3heatmap/htmlwidgets/lib/d3heatmapcore/heatmapcore.js'
Open the file with a text editor. There are two places where there is a setting: "rotate(45),translate(6, 0)".
So search for "rotate(45)" and replace "45" with "90" in both places. You'll also have to change "translate(6, 0)" to something that places the text better. I found that "translate(12, -20)" (shifting the text down by 12 pixels and right by 20 pixels) worked well using the "mtcars" dataset as a test.
d3heatmap with vertical row labels
When using datasets with more or less rows, you'll have to play around with the right translation, changing it a bit from -20 so that things align correctly. There is probably a way to do this automatically, but I mostly just know R, not javascript, so I don't know how to do it.
I'm new to R - which will be obvious in a sec here...and I was hoping someone could point me to the some packages to attempt to solve a specific problem:
I get Excel tables from scientists with analytical data for specific GIS point sample locations, we usually copy/paste these tables into the layout of GIS map documents; however quite often the line weights, fonts, etc get messed up...and the data gets updated/revised etc. - tedious copy/paste again...
I'd like to try to read these Excel files, have R create a multiple formatted tables for each sample location, and plot these tables with real world coordinates for use in GIS (ESRI or QGIS, etc.), where the tables would ideally show up offset some distance from the point sample locations in some sort of GIS file format.
I was thinking the export from R might be a .dwg, or even a raster geotiff with a transparent background...a format that would preserve formatting and position - not sure what the possibilities here could be...has anyone ever tried anything like this - I see several excel and geospatial packages, and understand that they can be used for regular geospatial data analysis, but in this case I'm trying to merge graphics (formatted tables from R) and GIS - which is something I'm having a hard time finding any info about.
Hopefully this question is not too vague...
edit - I have the SP package and am reading up on it, I guess I'm really stuck on the whole make several tables with R > get those tables all at once into a format that GIS can read - try this - imagine a georeferenced aerial photo - then imagine a layer of floating boxes on top of the aerial image, these boxes are placed with coordinates (i.e. lat/long, state plane feet, etc.) - can I make a layer like this with R and the geospatial packages?
I have a code to plot a world map with a meteorological field for one moment (or one measure).
Is it possible to successively plot the map for different moments (for i from 1 to 125) in order to view a sort of video when we run the code?
Yes, look at the animation package.
It can creates an animated gif for you (as well as other tricks). There are live examples you can look at as eg Buffon's needle, a CLT demo and much more.
The package abstracts away some of the OS-dependent layers. If you know the basics, you can of course just call the corresponding tool from the imagemagick project which is likely to be available on OS of choice too.
I'm currently generating 3D graphs in R using the persp-command. To change the viewpoint one has to set the parameters theta and phi. To evaluate (a good viewpoint on) the graph, one has to try lots of combinations for these parameters.
I was wondering if one can define an interactive output device that allows to rotate the graph using the mouse. It would be also nice if this device gives the current values for theta and phi.
Is there such a device/package?
See the rgl package: http://cran.r-project.org/web/packages/rgl/index.html
It won't report the theta and phi values you need, IIRC (though see #Dieter's comment below for a solution to this), but you can use rgl.snapshot() or rgl.postscript() to grab the current display as a bitmap or vector image. The package has persp3d() which is very similar to persp().
See the package rggobi http://cran.r-project.org/web/packages/rggobi/index.html
For data visualisation in 3 or even more dimensions, try the package rggobi which makes use of the program ggobi. It is possible to manipulate the data using the mouse, "brush" data, identify points in the data all while visualizing in a number of dimensions.