This module contains the InputCollection and InputIterator classes. These classes are for ImageReader to keep track of the inputs it has and deal with resampling.

class rios.inputcollection.InputCollection(imageList, loggingstream=<open file '<stdout>', mode 'w'>)[source]

InputCollection class. Keeps all of the inputs and the information we need about them in one place.

Gets passed a list of filenames and opens them, creates a PixelGridDefn and pulls out their null values.

Setting the reference dataset is done via setReference() (is first dataset by default). Resampling can be performed by resampleToReference().

Use checkAllMatch() to see if resampling is necessary.


Returns whether any resampling necessary to match reference dataset.

Use as a check if no resampling is done that we can proceed ok.


Removes any temp files. To be called from destructor? Seems not given Neil’s experience - needs to be called from finally clause - not sure how to enforce this in user’s script....


Closes all open datasets


Work out what the combined pixel grid should be, in terms of the given reference input raster. Returns a PixelGridDefn object.

static makePixGridFromDataset(ds)[source]

Make a pixelgrid object from the given dataset.

static makeWarpNullOptions(nullValList)[source]

Make appropriate options for gdalwarp, to handle null value properly. If any of the null values in the list is None, then we can’t do it because the null value is not set on the file, so the return value is None.

Normally returns a list of arguments, formatted with -srcnodata and -dstnodata

Note since this is to be passed to gdalwarp directly, ie not thru a shell, we don’t need to quote the nulls string.

resampleAllToReference(footprint, resamplemethodlist, tempdir='.', useVRT=False)[source]

Reamples all datasets that don’t match the reference to the same as the reference.

footprint is imageio.INTERSECTION, imageio.UNION or imageio.BOUNDS_FROM_REFERENCE resamplemethod is a string containing a method supported by gdalwarp.

resampleToReference(ds, nullValList, workingRegion, resamplemethod, tempdir='.', useVRT=False)[source]

Resamples any inputs that do not match the reference, to the reference image.

ds is the GDAL dataset that needs to be resampled. nullValList is the list of null values for that dataset. workingRegion is a PixelGridDefn resamplemethod is a string containing a method supported by gdalwarp.

Returns the new (temporary) resampled dataset instance.

Do not call directly, use resampleAllToReference()

setReference(refpath=None, refgeotrans=None, refproj=None, refNCols=None, refNRows=None, refPixgrid=None)[source]

Sets the reference dataset for resampling purposes.

Either set refpath to a path to a GDAL file and all necessary values will be extracted. Or pass refgeotrans, refproj, refNCols and refNRows.

static specialProjFixes(projwkt)[source]

Does any special fixes required for the projection. Returns the fixed projection WKT string.

Specifically this does two things, both of which are to cope with rubbish that Imagine has put into the projection. Firstly, it removes the crappy TOWGS84 parameters which Imagine uses for GDA94, and secondly removes the crappy name which Imagine gives to the correct GDA94.

If neither of these things is found, returns the string unchanged.

class rios.inputcollection.InputIterator(collection)[source]

Class to allow iteration across an InputCollection instance. Do not instantiate this class directly - it is created by InputCollection.__iter__().

See for a description of how this works. There is another way, see: but it seemed too much like Windows 3.1 programming which scared me!

Returns a image name, GDAL Dataset, PixelGridDefn, nullvallist and datatype for each iteration