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I have in input a single band 2 axis tif raster (float32 values). Using gdal_calc I need to produce an output raster (same dimensions of input) that contains in every pixel the mean value of the whole input raster (to be used in other calculation) - basically a "uniform" raster. To do this I use:

gdal_calc.py    --calc="mean(A,dtype=float64)"  --type="Float32"    --overwrite --NoDataValue=-32768    --outfile   output.tif  -A  input.tif

Based on

gdalinfo -stats input.tif

I get a mean of 0.45 approx. So I was expecting an output.tif with this value for every pixel, but what I get is a different image (constant horizontally but different values vertically). I tried several numpy.mean parameters (axis, keepdims) but nothing changed.

Any suggestion or work around?

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    this is probably due to streaming (memory handling per stripe). A workaround would be to use computestatistics and create a new band using the python wrapping of GDAL. – radouxju Jun 20 '18 at 10:24
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try --calc="mean(A,dtype=float64,axis=0)"

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