Values distance folder

operators.val.values_distance_folder(client, foldername_is='/foldername_is', foldername_should='/foldername_should', output_folder='/output_folder', dtype='float', no_type=0.0, value=1.0, gridsize=1.0, worker_instance_type='x2large', manager_instance_type='small', extension_filename_is='.npy', extension_filename_should='.npy', extension_output_file='.npy', skip_existing_files=False)

Compute Euclidean distance from is matrix to should matrix.

values_distance_folder(client,

foldername_is=’/foldername_is’,

foldername_should=’/foldername_should’,

output_folder=’/output_folder’,

dtype=’float’,

no_type=0.0,

value=1.0,

gridsize=1.0,

worker_instance_type=’x2large’,

manager_instance_type=”small”,

extension_foldername_is=”.npy”,

extension_foldername_should=”.npy”,

extension_output_folder=”.npy”,

skip_existing_files = False )

Parameters:

• 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)

• foldername_is – Input folder folder for is matrix

• foldername_should – Input folder folder for should matrix

• output_folder – Output folder folder for distances matrix

• worker_instance_type – cloud instance type of worker nodes

• manager_instance_type – cloud instance type of manager node

• extension_foldername_is – File extension of files in folder for foldername_is

• extension_foldername_should – File extension of files in folder for foldername_should

• extension_output_folder – File extension of files in folder for output_folder

• skip_existing_files – skip files that already exist in the output folder