I have some LVIS Lidar data in hdf5 format.
The data has Lat and Long co-ordinates, so I have been able to visualise them on a map using Basemap:
f = h5py.File('ILVIS1B_GA2016_0304_R1701_043591.h5','r')
LONG = f['/LON0/']
LAT = f['/LAT0/']
X = LONG[...]
Y = LAT[...]
m = Basemap(projection='merc',llcrnrlat=-0.5,urcrnrlat=0.5,\
llcrnrlon=9,urcrnrlon=10,lat_ts=0.25,resolution='i')
m.drawcoastlines()
m.drawcountries()
parallels = np.arange(-9.,10.,0.5)
m.drawparallels(parallels,labels=[False,True,True,False])
meridians = np.arange(-1.,1.,0.5)
m.drawmeridians(meridians,labels=[True,False,False,True])
m.drawmapboundary(fill_color='white')
x,y = m(X, Y)
scatter = plt.scatter(x,y)
m.scatter(x,y)
plt.show()
This gets me this, where the orange bands are very dense points:
The hdf5 file also has the full waveform data for each mapped point (each datapoint is a reflection detected at the sensor, as a function of time) so that each of the orange points has data associated with it like:
Ultimately, I would like to be able to click on any of the orange points and for the subsequent waveform to be displayed. I have looked into interactive plots for this and have come across a number of libraries (mpl3d, plotly etc).
I'm having some trouble getting my head around some of these and how I can get my data into the examples - my python isn't up to this level. Does anyone have any advice on where to start? Which libraries would be best suited to this? A little help to understand the basics would be appreciated.
Apologies there is no direct question here, I'm just after some info from the knowledgable community.
The question seems to be: How do I tackle a task I have no clue how to solve?
Step 1: Search for a possible solution. It may happen that someone else has already solved your problem. This will mostly not be the case, but you may be lucky.
Step 2: Abstract the task. What would be the general problem that a lot of people might have and for which there might be a solution? Does it need to be hdf5 files? No. Is georeferencing important? Maybe, but one could neglect for the moment. Which requirements are really important, which not?
Step 3: Search again. You will have more success now for finding similar or related problems.
Step 4: Look at the tools in use. Make a list of possible tools and check against your requirements. Interactivity, Application or web-based, accuracy etc.
Step 5: Decide for one tool and go for it. Start with a general case study. Can I plot a map on the left and a graph on the right side using this tool? If not, find out why - maybe there is a general problem with this, maybe there is just an implementation detail missing. At this point you may ask a question about the case study problem, specifying the tool in use and providing the code that gives the problem. Do not think about your actual problem until this is solved.
Step 6: Proceed and try to add interactivity. Can I get something to happen when clicking? Again treat this independent of the actual problem. Search for solutions and if there none, ask a question about it.
Step 7: Proceed further up to the point where you're truely stuck. Now is the time to finally ask a question here, but with all the details that have brought you down to step 7 inside the question.
Related
I'm working on a problem that will eventually run in an embedded microcontroller (ESP8266). I need to perform some fairly simple operations on linear equations. I don't need much, but do need to be able work with points and linear equations to:
Define an equations for lines either from two known points, or one
point and a gradient
Calculate a new x,y point on an equation line that is a specific distance from another point on that equation line
Drop a perpendicular onto an equation line from a point
Perform variations of cosine-rule calculations on points and triangle sides defined as equations
I've roughed up some code for this a while ago based on high school "y = mx + c" concepts, but it's flawed (it fails with infinities when lines are vertical), and currently in Scala. Since I suspect I'm reinventing a wheel that's not my primary goal, I'd like to use someone else's work for this!
I've come across CGAL, and it seems very likely it's capable of all this and more, but I have two questions about it (given that it seems to take ages to get enough understanding of this kind of huge library to actually be able to answer simple questions!)
It seems to assert some kind of mathematical perfection in it's calculations, but that's not important to me, and my system will be severely memory constrained. Does it use/offer memory efficient approximations?
Is it possible (and hopefully easy) to separate out just a limited subset of features, or am I going to find the entire library (or even a very large subset) heading into my memory limited machine?
And, I suppose the inevitable follow up: are there more suitable libraries I'm unaware of?
TIA!
The problems that you are mentioning sound fairly simple indeed, so I'm wondering if you really need any library at all. Maybe if you post your original code we could help you fix it--your problem sounds like you need to redo a calculation avoiding a division by zero.
As for your point (2) about separating a limited number of features from CGAL, giving the size and the coding style of that project, from my experience that will be significantly more complicated (if at all possible) than fixing your own code.
In case you want to try a simpler library than CGAL, maybe you could try Boost.Geometry
Regards,
I am attempting to mesh a complicated design (~80,000 faces) for a microchannel heat sink, as pictured, and I would appreciate some advice. I have tried a range of different mesh controls (especially face sizing and body sizing), mesh settings and element sizes, and all have failed to produce a working mesh. The most common errors are shown in the linked picture, in particular the one regarding "The following surfaces cannot be meshed with acceptable quality. Try using a different element size or virtual topology." However, I have already reduced the element size to 2x10^-6 m, which takes two days to resolve before failure.
Unfortunately I cannot alter the geometry significantly, as it is imported from generation in SolidWORKS as either a STEP or an x.t file. As such, any advice for how I can successfully mesh the geometry for CFD analysis in FLUENT would be greatly appreciated.
I can provide more details or the geometry file itself if required.
Thanks in advance.
Meshing Attempt
Probably your cad design is not clean at all. But it is impossible to notice from this image. If you don't have control over the geometry source it is trouble. Because you might ask somebody else about check and fix something. First check you can do with your model it's trying to reduce the number of elements until the minimum possible value. Then if the mesh runs properly you can relay in the surfaces of your cad model. After that, you can refine the mesh, but the refining process is something that you have to do following some error criteria. If you are also the designer why not try to simplify a bit the geometry if you consider it is really hard to mesh? Meshing properly is a hard task, you should go step-by-step until you reach some solution. Also, you must not allow the preprocessor mesh automatically, without giving some criteria. Probably the first thing you have to answer even before apply any mesh is, what is your Reynolds number? And what is the most valuable result in which you can base the goodness of your discretization?
Thank you for your suggestions. In the end I solved the issue by importing the original mesh generated by COMSOL into SpaceClaim, then employing both the "Smooth" and "Reduce Faces" tools in tandem to simplify the geometry, before finally using SolidWORKS to turn the smoothed mesh into a solid body. This body retained many of the same features as the original, but was much less complex, having two orders of magnitude fewer faces. In turn, this permitted both meshing and heat transfer analysis in FLUENT.
I have a task: to determine the sound source location.
I had some experience working with tensorflow, creating predictions on some simple features and datasets. I assume that for this task, there would be necessary to analyze the sound frequences and probably other related data on training and then prediction steps. The sound goes from the headset, so human ear is able to detect the direction.
1) Did somebody already perform that? (unfortunately couldn't find any similar project)
2) What kind of caveats could I meet while trying to achieve that?
3) Am I able to do that using this technology approach? Are there any other sound processing frameworks / technologies / open source projects that could help me ?
I am asking that here, since my research on google, github, stackoverflow didn't show me any relevant results on that specific topic, so any help is highly appreciated!
This is typically done with more traditional DSP with multiple sensors. You might want to look into time difference of arrival(TDOA) and direction of arrival(DOA). Algorithms such as GCC-PHAT and MUSIC will be helpful.
Issues that you might encounter are: DOA accuracy is function of the direct to reverberant ratio of the source, i.e. the more reverberant the environment the harder it is to determine the source location.
Also you might want to consider the number of location dimensions you want to resolve. A point in 3D space is much more difficult than a direction relative to the sensors
Using ML as an approach to this is not entirely without merit but you will have to consider what it is you would be learning, i.e. you probably don't want to learn the test rooms reverberant properties but instead the sensors spatial properties.
I am trying to extract rotation matrix and translation matrix from essential matrix.
I took these answers as reference:
Correct way to extract Translation from Essential Matrix through SVD
Extract Translation and Rotation from Fundamental Matrix
Now I've done the above steps applying SVD to essential matrix, but here comes the problem. According to my understanding about this subject, both R and T has two answers, which leads to 4 possible solutions of [R|T]. However only one of the solutions would fit in the physical situation.
My question is how can I determine which one of the 4 solutions is the correct one?
I am just a beginner on studying camera position. So if possible, please make the answer be as clear (but simple) as possible. Any suggestion would be appreciated, thanks.
The simplest is testing a point 3D position using the possible solution, that is, a reconstructed point will be in front of both cameras in only one of the possible 4 solutions.
So assuming one camera matrix is P = [I|0], you have 4 options for the other camera, but only one of the pairs will place such point in front them.
More details in Hartley and Zisserman's multiple view geometry (page 259)
If you can use Opencv (version 3.0+), you count with a function called "recoverPose", this function will do that job for you.
Ref: OpenCV documentation, http://docs.opencv.org/trunk/modules/calib3d/doc/calib3d.html
I just downloaded libsvm-3.17 abt two weeks ago. I tried heart_scale (dataset provided in the libsvm-3.17 package) with easy.py. An image or plot is produced (from gnuplot) to illustrate the best c and best gamma. I cannot post the image here because I am new here and do not have enough reputation.
I would like to ask from the many colors curves in the plot, how to extract from the plot that the best log2(c)=11 (which gives c=2048) and the best log2(gamma)=-13 (which gives gamma = 0.0001220703125).
Thank you very much.
the chosen parameters are reported by easy.py (cannot run it now, but you will find them). the plot is just a visual aid to manually verify the parameter neighborhood. with some experience you can interpret the diagram. without experience simply trust easy.py