rat

This module contains routines for reading and writing Raster Attribute Tables (RATs). These are designed to be able to be called from outside of RIOS.

Within RIOS, these are called from the ReaderInfo and ImageWriter classes.

It is recommended that the ratapplier module be used instead of this interface where possible.

rios.rat.genColorTable(numEntries, colortype)[source]

Generate a colour table array. The type of colour table generated is controlled by the colortype string. Possible values are:

  • “rainbow”
  • “gray”
  • “random”

See corresponding genColorTable_<colortype> function for details of each.

rios.rat.genColorTable_gray(numEntries)[source]

Generate a color table array with the given number of entries, with all colors being shades of grey. First entry is black, last entry is white.

Returns the array as a 4 column array, suitable for use with the rios.rat.setColorTable() function.

rios.rat.genColorTable_rainbow(numEntries)[source]

Generate a color table array with the given number of entries, with colors notionally describing a rainbow (i.e. red-orange-yellow-green-blue-indigo-violet). Probably not what a painter would call a rainbow, but it will do.

Returns the array as a 4 column array, suitable for use with the rios.rat.setColorTable() function.

rios.rat.genColorTable_random(numEntries)[source]

Generate a color table array with the given number of entries by assigning random red/green/blue values. No attempt is made to always generate unique colours, i.e. it is randomly possibly for different entries to have the same colour.

Returns the array as a 4 column array, suitable for use with the rios.rat.setColorTable() function.

rios.rat.getColorTable(imgFile, bandNumber=1)[source]

Given either an open gdal dataset, or a filename, reads the color table as an array that can be passed to ImageWriter.setColorTable() or rat.setColorTable()

The returned colour table is a numpy array, described in detail in the docstring for rat.setColorTable().

rios.rat.getColumnNames(imgFile, bandNumber=1)[source]

Given either an open gdal dataset, or a filename, Return the names of the columns in the attribute table associated with the file as a list.

rios.rat.getColumnNamesFromBand(gdalBand)[source]

Return the names of the columns in the attribute table associated with the gdalBand as a list.

rios.rat.getUsageOfColumn(imgFile, colName, bandNumber=1)[source]

Given either an open gdal dataset, or a filename, returns the ‘usage’ of the column which can then be passed to writeColumn to preserve usage when copying

rios.rat.getUsageOfColumnFromBand(gdalBand, colName)[source]

Given a gdalBand returns the usage of the named column

rios.rat.inferColumnType(sequence)[source]

Infer from the type of the first element in the sequence

rios.rat.isColorColFromUsage(usage)[source]

Tells if usage is one of the color column types

rios.rat.readColumn(imgFile, colName, bandNumber=1)[source]

Given either an open gdal dataset, or a filename, extract the Raster Attribute with the given name. Returns an array of ints or floats for numeric data types, or a list of strings.

rios.rat.readColumnFromBand(gdalBand, colName)[source]

Given a GDAL Band, extract the Raster Attribute with the given name. Returns an array of ints or floats for numeric data types, or a list of strings.

rios.rat.setColorTable(imgfile, colorTblArray, layernum=1)[source]

Set the color table for the specified band. You can specify either the imgfile as either a filename string or a gdal.Dataset object. The layer number defaults to 1, i.e. the first layer in the file.

The color table is given as a numpy array of 5 columns. There is one row (i.e. first array index) for every value to be set, and the columns are:

  • pixelValue
  • Red
  • Green
  • Blue
  • Opacity

The Red/Green/Blue values are on the range 0-255, with 255 meaning full color, and the opacity is in the range 0-255, with 255 meaning fully opaque.

The pixels values in the first column must be in ascending order, but do not need to be a complete set (i.e. you don’t need to supply a color for every possible pixel value - any not given will default to transparent black). It does not even need to be contiguous.

For reasons of backwards compatability, a 4-column array will also be accepted, and will be treated as though the row index corresponds to the pixelValue (i.e. starting at zero).

rios.rat.writeColumn(imgFile, colName, sequence, colType=None, bandNumber=1, colUsage=<Mock name='mock.gdal.GFU_Generic' id='139767081899920'>)[source]

Given either an open gdal dataset, or a filename, writes the data specified in sequence (can be list, tuple or array etc) to the named column in the attribute table assocated with the file. colType must be one of gdal.GFT_Integer,gdal.GFT_Real,gdal.GFT_String. can specify one of the gdal.GFU_* constants for colUsage - default is ‘generic’

rios.rat.writeColumnToBand(gdalBand, colName, sequence, colType=None, colUsage=<Mock name='mock.gdal.GFU_Generic' id='139767081899920'>)[source]

Given a GDAL band, Writes the data specified in sequence (can be list, tuple or array etc) to the named column in the attribute table assocated with the gdalBand. colType must be one of gdal.GFT_Integer,gdal.GFT_Real,gdal.GFT_String. can specify one of the gdal.GFU_* constants for colUsage - default is ‘generic’ GDAL dataset must have been created, or opened with GA_Update