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Delft 3D-Flow produces NEFIS compliant history and map file output (*.dat files). The view capability of Delft 3D 's post processor is good but not as advanced as the specialized (scientific) visualization software like ParaView or VisIt. I want to view Delft 3D output in in ParaView but ParaView cannot open Delft 3D files directly.
One possible way is to convert Delft 3D output files to NetCDF (*.nc) files and then view it in ParaView as it can open *.nc files. I have even found a Matlab (see this https://oss.deltares.nl/web/delft3d/general/-/message_boards/view_message/1379779 and https://svn.oss.deltares.nl/repos/openearthtools/trunk/matlab/applications/delft3d/vs_trim2nc.m ) script as well to do the job however it failed with an error message ( Undefined function or variable 'filenameext' )
I do not know any other possible way to do the job. If someone would guide, suggest any other possibility or just comment, it will be highly appreciated.
Thanks and Regards
Ahmed
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I think you could find more clarifications of your question in the 15 Delft3d webinar "15. 'Efficient pre- and post-processing in Delft3D using the OpenEarthTools' " .
Sincerly.
Hamza
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I have three datasets A,B and C. Each includes tens of thousands of chemical compounds. We know that A[1], the first compound in A, is similar to B[30] and both are similar to C[9999] and we call this compound NEO; A,B &C share a lot of such compounds. I wanna show A, B and C in such a way that each compound is a dot (Properties of the compound such as molecular weight can be used as 2D or 3D coordinates) and I also wanna show that they all share NEO and many more of such shared molecules and many more molecules that are only in A and not others, etc,etc.
 A venn diagram would be the simplest way. But, can I make a venn diagram of the actual data, by showing each fragment as a dot and visualize the shared ones as overlapping? 
Or a plot like the microarray having bins for compounds with certain properties and showing A,B,C with different colors (or A&C, A&B, B&C and A&B&C with colors)?
I also came across hiveplot but I'm not sure if that is a good option or not! 
In reality A,B and C are datasets of compounds in natural products, FDA approved drugs and synthetic chemicals. I wanna visualize the distribution of these compounds, in other words which compounds are shared between these datasets. 
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Thanks Narasim. I like the idea of converting data to pixels but that's too general. I will most probably use the hiveplot. 
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Hi everybody
I want to save an image which constructed in Amira software in Microvisu3d format (.mv3d).Does anyone know if it is possible to save an image in this format? I only know Amira can open a file in this format but I don't know how I can save a file in this format.
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Thanks a lot!
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I am always fascinated by the kind of diagrams that people publish in Cell, Nature, Science etc.. I want to get such a software that can help me in my research.
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I have measured gene expression across eight time points, and multiple comparisons show many differences between the time points. I'd like to indicate these significant differences on my bar graph. Usually I would draw a line above the relevant bars and put * or ** above the line, but there are so many differences that the lines would become unwieldy and I feel my graph would just look too messy! Any suggestions? Should I just relegate the p values to a table?
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I had a similar problem when looking at the EMG of 8 different muscles and different exercises. I allocated individual symbols to each then added the description under the graph. e.g.,
# Significant difference from 1
† Significant difference from 2
‡ Significant difference from 3
¥ Significant difference from 4
¢ Significant difference from 5
¤ Significant difference from 6
● Significant difference from 7
Ø Significant difference from 8
*Significant difference from all
Then if the result were significant from 1,2 and 3 I added # † ‡ above the relevant bar in the graph etc.
The study I am doing just now has less permutations of significance but still requires tidying up. I have opted for a slightly different approach by doing the following.
* = Significant difference from all (p < 0.05)
*** = Significant difference from all (p < 0.001)
$ = Significant difference from 1, 2 and 4 (p < 0.05)
¥ = Significant difference from 2 and 3 (p < 0.05)
¢ = Significant difference from 4 (p < 0.05)
Obviously can be altered to your study.
Hope this helps.
 
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I've tried to upload your visualization ontology : http://code.know-center.tugraz.at/static/ontology/visual-analytics.owl in Protégé 3.5, but I encountered a error. Did you check such a import?
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OK. It works fine. Thks !
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I am searching for a good visualization tool for presenting my research results in a conference. Do you have any fancy tools in mind?
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Please visit our research web site http://ncva.itn.liu.se and try the visualization tools for exploring large statistical data sets.
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I use Paraview and have experimented with Mayavi for 3D visualisation (volume rendering, surface plots etc.). I find Paraview can be lacking in quality at times and Mayavi has been difficult to use - are there any alternatives people could recommend?
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There's also OpenDX, http://www.opendx.org/, It is quite powerfull, but personally I never really used it.
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If you are willing to publicly share your experiences, I am very interested to hear your thoughts on the use of visual communication for scientific research. Specifically, I am interested in learning:
- your thoughts on the importance of visuals
- the type of software you use to create charts, graphs, schematics, illustrations
- how much time you spend creating these visuals
- your thoughts on the value of outside expertise to help you create your visuals
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Sean, just to clarify, I was referring to seek any other expertise - not necessarily from visualization or communication professionals. I was trying to make the following point: if you want to address any other audience than your peers, then it is in general helpful to include representatives from the target group in your preparations.
Closer to what you apparently are interested in, it can be of great help to get professional support on any matters of communication, including visualization. However, in order to benefit from their expertise, one has to be very clear about the intended message. I have seen several cases where both parties basically talked about different things and did not end up in much (anything?) useful.
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I am evaluating various Open Source tools for use in EE resarch. Few interesting ones would be Octave, SciLab, Python with Numpy and SciPy. Anyone care to share experiences, good or bad? Any other suggestions?
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I don't know about the specific demands of EE research, but I am using Python in combination with Numpy and SciPy (and matplotlib) as a Matlab substitute. The good thing is that you get to use a "real" programming language that is much more flexible and robust than Matlab and that scales to larger projects. I also quite like the quality of the graphics produced by matplotlib and its configurability; however, its 3D plotting capabilities (using mplot3d) are a bit limited compared to Matlab at this time.
The main drawback might be that SciPy etc. is less comprehensive than a full-blown Matlab installation with all its toolboxes and extensive documentation. You should make sure that SciPy either includes all the tools you need or that there are at least third-party Python libraries satisfying your requirements.
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Two weeks ago, I attended two interesting presentations, one of a British SME (shoothill) on visualizing scientific data for the public (for example applying a technique known as Deep Zoom), the other of the Polytechnic University of Milan on using NASA world wind as a virtual globe in the area of environmental modeling. Both make me think of the role of visualizing research results depending on the target audience and about telling the right story to the right people. I have the feeling that in my filed (geospatial information science and Digital Earth), we still miss a strong commitment to such ideas and also education has to increase on related topics. Do you share this view / maybe also in other research areas? What are your experiences?
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Data visualization is incredibly important as a tool of communication - whether for hard or softer data. We used our clinical data on biobanking to link data on cancer with behavioral data, geographic data and environmental risks data to create a software prototype "User Gateway" so users (scientists and policymakers) can generate hypothesis on what might be linked to what and to allow users to ask questions about combinations of risks to develop scientific proposals.
Commercially JMP, the stats company, has been developing beautiful visuals to show quantitative data analyses.
The Polis Center at IUPUI developed and hosts SAVI http://www.savi.org/savi/ where they took data on urban living, environment etc and set it up so non-scientists, policymakers, new arrivals to Indianapolis, could use. They add health data as it becomes available. It is so nice to use that users dont realize they are applying science!! The other side to story telling! Because of the very severe cuts in funding and criticisms of universities and research progress, I think it is very important for us to communicate our science to non-scientists. Interesting and effective story telling and analogies are the easiest way to do this.
Nice topic. Story telling is an art and free form mostly used as entertainment in the arts. The framework of story telling can be applied very effectively to scientific data to make it intelligible to those learning and those who are not scientists.
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Hi there,
I'd love to hear your thoughts about what you think will be the next generation scientific visualization approach. Will it be interactive? More photo-realistic? What are the skills we need to learn today to keep up in the future?
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Thanks Jana,
I agree that the purpose of the illustration has priority and that it is the task of the illustrator to make it fulfilling this purpose with the techniques at hand.
I make illustrations and animations for research scientists. I'm a research scientist myself, so I understand the field and the needs quite well. I strongly believe that scientific illustrations in this field need to be more easily accessible. It is one of my goals to accomplish this.
Feel free to have a look what we are doing here: http://www.somersault1824.com
luk