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Glendale Housing Authority 2. City Council Meeting 2. Housing Rights Workshop 2. Teen Night Out 5. Teen Night Out Non-spatial variables from the associated database i. To run this example, you must have the files "states.
These can be obtained from the National Map. A Python version of this projection is available here. In this case, the historical incidents of F5-class tornadoes in the USA are plotted.
To run this example, you must have the "states" shapefiles from the previous example, along with "tornadx These can be obtained from the USGS's holdings on data.
You cannot use the " HighRes " database with a global map, so the shapefile outlines are your best bet if you need more resolution. It produces two panel plots, so you can compare the various map outlines. See the description of this function for important information.
This particular example reads a shapefile to get an outline of the Mississippi River Basin. You then have the option of masking out all areas inside or outside this outline.
The "mrb. Look at this script if you are interested in seeing the "guts" of what it takes to mask data against a shapefile outline. Demonstrates querying the shapefiles' databases via non-spatial attributes to extract and draw specific geometry. Also provides an example of using table to create a custom map legend. Search for administrative boundaries of Pakistan and download.
The resultant zipfile contains four sets of shapefile files. The first frame shows the default map outline for Switzerland admittedly not very good , and the second frame shows the data from the shapefile. The point is to show that shapefiles tend to have similar formats, and hence you can take a script and easily modify it to draw the outlines you're interested in.
In this example, the outlines are drawn with polylines, and the places of interest with text strings and polymarkers. With versions 6. With version 6. Markers and text may still be slow. The shapefiles were downloaded from several locations. See the comments in the script for details. This demonstrates calculating an areally weighted mean time series for an irregularly shaped region. As in Example 4, an array containing only the desired locations inside the shapefile is created.
Specifially, this computes the areal mean time series of monthly precipitation for the Mississippi River Basin. The data is the monthly GPCP. The mask array is then written to a copy of the input file.
This function only works for data that contains coordinate arrays. You will need to modify it to work with curvilinear or unstructured data. You should be able to use any shapefile that contains polygon data point and polyline data won't work to create the desired mask. You can use any of the other shapefiles that are included with this file, but they are potentially a higher resolution, and hence creating the mask will take longer.
This example draws the lithologic color map on a separate frame, using several labelbars. The New Mexico image additionally adds fault lines. The land mask is written to a NetCDF file so you can use it later for masking other variables on the same grid.
Two USA shapefiles were tried with this example. Which file you use depends on how fine your original grid is, and how good of a mask you need. Special thanks to Dave Allured for his improvement of this script to correctly plot all highway segments with complex entries, like "I- 5, US 30".
Since this function can be slow if you are checking a lot of points, a number of "if" statements are included to prevent unnecessary calls to this function. The outlines for the U.
The first frame is the unzoomed variable, and the second frame shows how to zoom in on the area of interest using the special "ZoomIn" WRF resource. You can customize what outlines are drawn by using command line options. This script will only work with NCL V6. The left image is from running NCL V6. The right image is from running NCL V6. In NCL versions 6. In NCL version 6. This is useful if you want to keep some of your original data points that fall just outside a shapefile outline.
We get a lot of questions on this topic, so we decided to create a very basic example that shows both types of masking.
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