Values distance

operators.val.values_distance(client, filename_is='in1.npy', filename_should='in2.npy', output_file='out.npy', dtype='float', no_type=0.0, value=1.0, gridsize=1.0, instance_type='x2large')

Compute Euclidean distance from is matrix to should matrix.

values_distance( client,

filename_is=’in1.npy’,

filename_should=’in2.npy’,

output_file=’out.npy’,

dtype=’float’,

no_type=0.0,

value=1.0,

gridsize=1.0,

instance_type=’x2large’ )

Parameters:

• filename_is – Input file path for is matrix

• filename_should – Input file path for should matrix

• output_file – Output file path for distances matrix

• dtype – Data type of the matrices (default: float)

• no_type – Value representing no_type in the matrices (default: 0.0)

• value – Value representing value in the matrices (default: 1.0)

• gridsize – Resolution of the spatial grid in meters (default: 1.0)

• instance_type – type of cloud instance used for processing