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Looking at the second graphic it looks like edge_list is all the coordinate values mixed together and sorted in order, not coordinate pairs. For the shapefile geometry you should be appending (x,y) tu …

Rasterio's docs for pad say: pad_width: int number of pixels to pad array on all four sides So you need to pass a single value, not numpy's sequence of before/after values: pilpadimg = rasteri …

In this type of analysis it can be nice to jump out of nested cursors and buffers and work directly on the data with a spatial index. In doing similar work I've found that using the rtree library cuts …

Inverting your current filter means you would have the rest of the 43m points to search through, so that doesn't sound good. Since you know the radius of your circles, you can buffer the big polygons …

If you're looking just at shapefiles, you could also use pyshp. import shapefile sf = shapefile.Reader("shapefiles/blockgroups") shapes = sf.shapes() for shape in shapes: for vertex in shape.points …

You could go the GIS route - use QGIS, and use its Python automation to generate a map and export it to an image. If you like Javascript, D3 can make nice maps. … Another Python alternative would be to use a combination of Shapely, MatPlotLib, and Descartes. Here's a blog post that shows a map creation workflow. …

The subprocess module should do the job: import subprocess # ... do what you need to do grapher = "\path\to\grapher.exe" x_opt = '-x' bas_file = "\path\to\filename.bas" result = subprocess.check_outp …

Your KML still isn't interleaved correctly. Your original data is approximately -70 longitude and 10 latitude, you have a cluster of points and around (-70, -70), and another cluster around (10, 10). …

The problem is that rtree is a ctypes wrapper around libspatialindex, and pickle has no way of storing the pointer to the rtree in memory. You could instead store the index to disk: from multiproces …

First see this post for how to write GCPs: In python gdal how to add Ground Control point to GeoTiff image by using gdal_translate You can then get the GCPs in your source image with ds.GetGCPs So all …

Importing Fiona can set some GDAL library paths, so you may want to run your subprocess using a copy of your original environment before the Fiona import changes anything. import subprocess, os my_en …

Is the built-in disk serialization an acceptable solution? Make an index and flush it to disk: from rtree.index import Index idx = Index('filename') idx.insert(0, (1, 2, 3, 4)) idx.get_bounds() # [1 …

You may need to set some of GDAL's environmental variables when you run subprocess, such as GDAL_DATA. You can see which are being set in the MS4W setenv.bat script.

I don't totally understand the output of your analysis, but it seems like that for each feature being evaluated you're doing a lot fiddling - copying datatsets, joining them, adding fields, deleting t …

You can use the json or simplejson library to convert the geojson to a Python object, then loop through each LineString. …