I am starting to get acquainted with the use of ELK for work purposes, but struggle to find a solution to use simple mathematic requests in my database.
As shown on the picture, my DB contains 16 available fields, but I would like to create others, without doing it on Excel before converting my file in CVS again.
For example, I would like to create a variable #Bugs/Release. I've heard that this is quite easy to make with no need of scripting, but I can't find the way to do it... Has anybody the solution of this problem?
Huge thanksenter image description here
Can someone guide me on how best to add a background map to two seaborn jointplots I created?
To give context, I am currently analyzing a dataset from Austin Police Dept's Crime Reports database. What I am attempting to do is visualize the density of murders and capital murders in Austin, TX. The dataset extends from the beginning of 2003 to the present.
The notebook can be located at: https://github.com/rgrantham82/Hate_Crimes_Analysis/blob/master/Austin%20Crimes%20Report%20Analysis.ipynb
So far, I visualized both data frames using the seaborn jointplot method, using latitude and longitude.
I BELIEVE this is a good method to plot the density of murders judging by the dataset but if someone has a better idea, I am open to instruction on that as well.
So, if it is even possible, how do I add a basemap to both plots?
So far, I attempted the contextily method and the geopandas method. Admittedly, this is my first attempt (outside of DataCamp class) using either method. As of to date, I am unsuccessful with both.
The contextily addbasemap() method did not produce a map (I guess it does not have one for the Austin area?). And also with the geopandas method I could not get it to work in producing a viable basemap either. I seem to be simply swamped by it.
Murders Plot
Capital Murders Plot
I am trying to create a topojson file projected using geoAlbersUsa, originating from the US Census's ZCTA (Zip Codes, essentially) shapefile. I was able to successfully get through the examples in the excellent https://medium.com/#mbostock/command-line-cartography-part-1-897aa8f8ca2c using the specified maps, and now I'm trying to get the same result using the Zip Code-level shapefiles.
I keep running into various issues due to the size of the file and the length of the strings within the file. While I have been able to create a geojson file and a topojson file, I haven't been able to give it the geoAlbersUsa projection I want. I was hoping to find something to convert the current topojson file into a topojson file with a geoAlbersUsa projection but I haven't been able to find any way.
I know this can be done programmatically in the browser, but everything I've read indicates that performance will be significantly better if as much as possible can be done in the files themselves first.
Attempt 1: I was able to convert the ZCTA-level shapefile to a geojson file successfully using shp2json (as in Mike Bostock's example) but when I try to run geoproject (from d3-geo-projection) I get errors related to excessive string length. In node (using npm) I installed d3-geo-projection (npm install -g d3-geo-projection) then ran the following:
geoproject "d3.geoAlbersUsa()" < us_zips.geojson > us_zips_albersUsa.json
I get errors stating "Error: Cannot create a string longer than 0x3fffffe7 characters"
Attempt 2: I used ogr2ogr (https://gdal.org/programs/ogr2ogr.html) to create the geojson file (instead of shp2json), then ran tried to run the same geoproject code as above and got the same error.
Attempt 3: I used ogr2ogr to create the geojson sequence file (instead of a geojson file), then ran geo2topo to create the topojson file from the geojsons file. While this succeeded in creating the topojson file, it still doesn't include the geoAlbersUsa projection in the resulting topojson file.
I get from the rather obtuse documentation of ogr2ogr that an output projection can be specified using -a_srs but I can't for the life of me figure out how to specify something that would get me the geoAlbersUsa projection. I found this reference https://spatialreference.org/ref/sr-org/44/ but I think that would get me the Albers and it may chop off Alaska and Hawaii, which is not what I want.
Any suggestions here? I was hoping I'd find a way to change the projection in the topojson file itself since that would avoid the excessively-long-string issue I seem to run into whenever I try to do anything in node that requires the use of the geojson file. It seems like possibly that was something that could be done in earlier versions of topojson (see Ways to project topojson?) but I don't see any way to do it now.
Not quite an answer, but more than a comment..
So, I Googled just "0x3fffffe7" and found this comment on a random Github/NodeJS project, and based on reading it, my gut feeling is that the node stuff, and/or the D3 stuff you're using is reducing your entire ZCTA-level shapefile down to ....a single string stored in memory!! That's not good for a continent-scale map with such granular detail.
Moreover, the person who left that comment suggested that the OP in that case would need a different approach to introduce their dataset to the client. (Which I suppose is a browser?) In your case, might it work if you query out each state's collection of zips into a single shapefile (ogr2ogr can do this using OGR-SQL), which would give you 5 different shapefiles. Then for each of these, run them through your conversions to get json/geoalbers. To test this concept, try exporting just one state and see if everything else works as expected.
That being said, I'm concerned that your approach to this project has an unworkable UI/architectural expectation: I just don't think you can put that much geodata in a browser DIV! How big is the DIV, full screen I hope?!?
My advice would be to think of a different way to present the data. For example an inset-DIV to "select your state", then clicking the state zooms the main DIV to a larger view of that state and simultaneously pulls down and randers that state's-specific ZCTA-level data using the 50 files you prepped using the strategy I mentioned above. Does that make sense?
Here's a quick example for how I expect you can apply the OGR_SQL to your scenario, adapt to fit:
ogr2ogr idaho_zcta.shp USA_zcta.shp -sql "SELECT * FROM USA_zcta WHERE STATE_NAME = 'ID'"
Parameters as follows:
idaho_zcta.shp < this is your new file
USA_zcta.shp < this is your source shapefile
-sql < this signals the OGR_SQL query expression
As for the query itself, a couple tips. First, wrap the whole query string in double-quotes. If something weird happens, try adding leading and trailing spaces to the start and end of your query, like..
" SELECT ... 'ID' "
It's odd I know, but I once had a situation where it only worked that way.
Second, relative to the query, the table name is the same as the shapefile name, only without the ".shp" file extension. I can't remember whether or not there is case-sensitivity between the shapefile name and the query string's table name. If you run into a problem, give the shapefile and all lowercase name and use lowercase in the SQL, too.
As for your projection conversion--you're on your own there. That geoAlbersUSA looks like it's not an industry standard (i.e EPSG-coded) and is D3-specific, intended exclusively for a browser. So ogr2ogr isn't going to handle it. But I agree with the strategy of converting the data in advance. Hopefully the conversion pipeline you already researched will work if you just have much smaller (i.e. state-scale) datasets to put through it.
Good luck.
I am putting together a project where I need to be able to source outside data as a means of inputting skeleton joint positions into Maya. Basically I have a spreadsheet of sequential joint positions for the skeleton which I would like to load into Maya and then link to the skin. Does anyone know a way to upload or reference these positions (as FK into Maya)?
Probably the easiest thing to do is to convert your spreadsheet data to atom format
Atom is a json based format for exchanging animation data and, since its JSON based you should be able to concoct a CSV to ATOM translator using Python's built in csv and json modules.
I am trying to render a local elevation data on World Wind. And then use the world wind's tessellation algorithm to tessellate the data and render it on the globe.
I know about the LocalElevationModel. and I was able to store a DEM file using this:
LocalElevationModel localElevationModel = new LocalElevationModel();
String filepath = "";
localElevationModel.addElevations(filepath);
I can access this model using the lookupElevation method over the max,min lat log from the localElevation data. But I don't know how to proceed forward. I have looked into the RectangularTessellator class but couldn't understand how to use it.
Any clues on how I can do this?
PS:I was looking at their source code but couldn't understand much to make much scene out of it. So I wanted to know more about it.
PPS: If not possible can someone guide me to an easy to implement and optimized algorithm for rendering of the terrain. Which supports various LODs of the generated mess.
Thanks,