Is there a way to get the x, y and z point values of a particular surface in petrel through Ocean and print them out in the Petrel output window?
Assuming you are referring to a RegularHeightFieldSurface, all the information you need is readily available in the Ocean SDK. I believe you are looking for RegularHeightFieldSample.
The PetrelLogger can be used to output strings to the Message Log, log files or standard message boxes.
You asked an almost identical question here: How to generate a surface from other surfaces in Petrel. Both current answers, that you acknowledged, also answers this question.
Ocean (like most moderately complex APIs) does require some upfront investment in getting acquainted with the basics. Stack Overflow is no substitute for self study.... :-)
Related
In 2007, when I was young and foolish and before I knew about Open Street Map, I started an urban historical map project. I was working in Illustrator, it was going to be an interactive Flash piece, and my process was to draw the maps first, with the thought that I'd label some, but not all, of the street later on.
As we know Flash was began to die about 2010 and I put the project away for a number of years. I picked it up again a couple years ago and continued my earlier practice of just drawing streets and water features, this time with the intention of making it a conventional web map. Now I'm pretty close to finishing the drawing of a five-layer (1871, 1903, 1932, 1952 and 2016) historical map of a medium-sized city, though it still lacks labels.
My problem now is how to add large numbers of labels, many of them duplicates. There could be as many as 10,000 for all five layers, though as a practical matter I may have to settle for a smallish fraction of that number. Based on web searches I gather my workflow is unusual and that mine is therefore an unusual problem.
I've exported my maps and brought them into QGIS and played with the software a little. The process of adding labels to objects doesn't seem terribly efficient or user-friendly, but that's probably due to my unfamiliarity with the program.
So my question is this: Are there any tricks to speed up the painful process of adding large numbers of duplicate labels in either QGIS or ArcGIS? Since so many of the streets exist in all five layers, functionality like the ability to select multiple objects in different layers and edit their attributes simultaneously in the Attribute Table would be a godsend. (Doesn't seem possible.) So would the ability to copy the attributes from one object and paste them onto other objects. Or the ability to do either of these things in Illustrator via a plugin and then export the data along with the shapes to a GIS program.
Thanks for your help!
If I understand the issue correctly I think are several different solutions. When you say that you
Typically for a spatial layer in ArcGIS or QGIS you define how to label all features in a layer once by defining a label scheme to use across all features, 1 or 1 million. This assumes that each feature in the layer has one or more attributes in the associated table for the layer.
How are you converting the Illustrator vectors to a spatial layer? DXF?
You will likely have better/faster responses to this question by posting it to the GIS Stack exchange. https://gis.stackexchange.com/
I am interested in visualizing meteorological and climatological data.
Here we are talking about 2D/3D visualization for weather and climate elements:
Temperature
Pressure
Wind
Example
We have used some tools previously, such as:
GrADS
Surfer (commercial software)
GIS Meteo (commercial software)
What another tools (preferably open source) would you suggest for that purpose nowadays?
I know you mentioned GrADS, but it was the tool I used mostly for development of weather products, a little more intuitive and resource friendly than IDV when I coded, and generally pretty good rate of development. You mentioned Open Source... did you know there is an OpenGrADS (http://opengrads.org/)? Most friends involved in weather product development use a combination of GrADS\OpenGrADS for much of their work. But I agree it doesn't produce knock-your-socks-off graphics.
Another commonly used free program is Gempak, another Unidata product, which really seems to be becoming outdated in my personal opinion).
And then you can talk high end graphics, you're going to pay more. http://moe.met.fsu.edu/~hrw22/movies/WIND_Katrina_2005-08-28_00Z.gif is a great video of Katrina that was produced by someone I knew using Amira. According to Wikipedia, you're looking at
"Cost: $4,000 USD + $800/year support (2009)... although now has much more ugly/complex pricing structure where each feature is priced separately (eg: Amira Mesh Option $360). I believe at NCMIR we pay ~$9000/year for five user-license." Ouch!
I don't have an open source tool, but if you can get access to a Level-II data feed (Level-II is minimally post processed radar data), I and a meteorologist friend use GR2Analyst. I would assume you know enough about weather sources to be able to figure out how to set this up.
If you're looking for an open source (and free) tool that can do 2D and 3D, which also includes access to a wide variety of datasets (obs, model output, remote sensing - radar level 2 and 3, satellite, and more!), then you might want to check out the Unidata Integrated Data Viewer (IDV):
http://www.unidata.ucar.edu/software/idv/
Source code available here:
https://github.com/Unidata/IDV
The interface is a bit complex, but we have some youtube screencasts to help people get up and going:
http://www.youtube.com/user/unidatanews/videos
If you'd like to see a video for a specific thing, we are taking requests :-) (email support-idv#unidata.ucar.edu). We do yearly training workshops as well, and those materials are available online here:
http://www.unidata.ucar.edu/software/idv/docs/workshop/
Cheers!
Sean
Panoply is a multiplataform desktop option if data is available in formats such NetCDF, HDF or GRIB.
I extracted the following text from his site that describes some of the characteristics:
Slice and plot geo-gridded latitude-longitude, latitude-vertical, longitude-vertical, or time-latitude arrays from larger multidimensional variables.
Slice and plot "generic" 2D arrays from larger multidimensional variables.
Slice 1D arrays from larger multidimensional variables and create line plots.
Combine two geo-gridded arrays in one plot by differencing, summing or averaging.
Plot lon-lat data on a global or regional map using any of over 100 map projections or make a zonal average line plot.
Overlay continent outlines or masks on lon-lat map plots.
Use any of numerous color tables for the scale colorbar, or apply your own custom ACT, CPT, or RGB color table.
Save plots to disk GIF, JPEG, PNG or TIFF bitmap images or as PDF or PostScript graphics files.
Export lon-lat map plots in KMZ format.
Export animations as AVI or MOV video or as a collection of invididual frame images.
Explore remote THREDDS and OpenDAP catalogs and open datasets served from them.
If you are interested in interactive visualization over web, there are some options such as:
ncWMS: an webmapping server that reads NetCDF data and publish it using Web Mapping Service standard.
GeoServer: another webmapping server that has plugin to read NetCDF data.
Vtk (visualization Toolkit) is a C++ open source 2D and 3D visualization library that I use to visualize radar data in 3D.
I am a software tester by profession and I have worked on various technologies till date. I got a new assignment which is a GIS application. I am not aware of how to test GIS application, what parameters should be considered while testing etc.
I will really appreciate if anyone could help me out with some guidelines for testing GIS application.
Thank you in advance. :)
Ashok, possibly since the time whn the question has been asked you have been turned into GIS testing expert, but let me try to answer )))
I would focus on what the app should do with geometries:
does it takes into account the correct type of geometries, does it ignore the incorrect ones
If the app builds own geometries based on the original geometries, I would try different topologies that may be problematic for doing this. Say, the app should draw a geometry 5 px left to some original geometry, in parallel to it. I would try a loop that is lesser than 10 px diameter in order to have no space to 5 px left. And so on
I would test the huge values of data, so what will be if the app would try to consume the worldwide net of such geometries.
I'm currently using a Processing Kinect library which supplies a depth map. I was wondering how I could take that and use it to create a 2D skeleton, if possible. Not looking for any code here, just a general process I could use to achieve those results.
Also, given that we've seen this in several of the Kinect games so far, would it be difficult to have multiple skeletons running at once?
Disclaimer: the reason why you still didn't get an answer for this question is probably because that's a current research problem. So I can't give you a direct answer but will try to help with some information and useful resources for this topic.
There are mainly 2 different approaches to create a skeleton from a depth map. The first one is to use machine learning, the second is purely algorithmic.
For the machine learning one, you'd need many samples of people doing a predetermined move, and use those samples to train your favorite learning algorithm. That's the approach that was taken and implemented by Microsoft in the XBox (source), it works really well BUT you need millions of samples to make it reliable... quite a drawback.
The "algorithmic" approach (understand without using a training set) can be done in many different ways and is a research problem. It's often based on modeling the possible body postures and trying to match that with the depth image received. That's the approach that was chosen by PrimeSense (the guys behind the kinect depth camera technology) for their skeleton tracking tool NITE.
The OpenKinect community maintains a wiki where they list some interesting research material about this topic. You might also be interested in this thread on the OpenNI mailing list.
If you're looking for an implementation of a skeleton tracking tool, PrimeSense released NITE (closed source), the one they made: it's part of the OpenNI framework. That's what's used in most of the videos you might have seen that involve skeleton tracking. I think it's able to handle up to 2 skeletons at the same time, but that requires confirmation.
The best solution is to use FAAST (http://projects.ict.usc.edu/mxr/faast/) which requires OpenNI. I have struggled to get OpenNI to work on my computer. I have not seen an approach yet using Code Laboratories' CL NUI.
An algorithmic approach is http://code.google.com/p/skeletonization/ but you may have a problem because your depthmap only represents surfaces and no closed objects.
In case somebody doesn't know: A cartogram is a type of map where some country/region-dependent numeric property scales the respective regions so that that property's density is (close to) constant. An example is
from worldmapper.org. In this example, countries are scaled according to their population, resulting in near-constant population density.
Needless to say, this is really cool. Does anyone know of a Matplotlib-based library for drawing such maps? The method used at worldmapper.org is described in (1), so it would surprise me if no one has implemented this yet...
I'm also interested in hearing about other cartogram libraries, even if they're not made for Matplotlib.
(1) Michael T. Gastner and M. E. J. Newman,
Diffusion-based method for producing density-equalizing maps,
Proc. Nat. Acad. Sci. USA, 101, 7499-7504 (2004). Available at arXiv.
There's this, though it's based and a different algorithm (and though it's on the ESRI site, it doesn't require ArcGIS). Of course, once you have the cartogram you can plot it in matplotlib.
Here is a Javascript plugin to make cartograms using D3. It is a good, simple solution if you are not too concerned about the regions being sized accurately. If accuracy is important, there are other options available that give you more freedom to play with the algorithm's parameters to get to a more accurate result.
Here are two great standalone programs I know of:
Scapetoad
Carto3F
Scapetoad is very easy to use. Just give it a shapefile, tell it which attribute to use for the scaling, and set a few accuracy parameters. If there is any doubt, this post describes the process.
Carto3F is more complex and allows for greater accuracy, though it is a bit trickier to figure out - lots of parameter settings without much documentation explaining them.
There is also a QGIS cartogram plugin, written in Python. Though I have not been able to get it to work, so cannot comment on that one.
In short, no. But Newman has an excellent little implementation of his and Gastner's method on his website. Installing it is easy and it works from the command line. Here's an example of a workflow using this software that worked for me.
Compute a grid of density estimates over some region, e.g. in Python. Store it as a matrix of numbers.
Run the cart program with your density matrix as input from the command line or from as subprocess in Python.
The program returns a list of new coordinates for each grid point.
Pipe your shapefile points through the interp program and into a new shapefile to get the transformed map.
There are nice instructions on the main page.
The geoplot.cartogram function in
Geoplot: geospatial data visualization — geoplot 0.2.0
says it is a high-level Python geospatial plotting library, and an extension to cartopy and matplotlib.
Try this library if you are using geopandas, it is quick and doesnt require much customization. https://github.com/mthh/cartogram_geopandas