Mask subset folder

operators.val.mask_subset_folder(client, folder_values1_in='/folder_values1_in', folder_mask_in='/folder_mask_in', folder_values_out='/folder_values_out', worker_instance_type='x2large', manager_instance_type='small', extension_file_values1_in='.npy', extension_file_mask_in='.npy', extension_file_values_out='.txt', skip_existing_files=False)

mask_subset_folder(client,

folder_values1_in=’/folder_values1_in’,

folder_mask_in=’/folder_mask_in’,

folder_values_out=’/folder_values_out’,

worker_instance_type=’x2large’,

manager_instance_type=”small”,

extension_folder_values1_in=”.npy”,

extension_folder_mask_in=”.npy”,

extension_folder_values_out=”.txt”,

skip_existing_files = False )

Parameters:

folder_values1_in – input folder [.txt or .npy]
folder_mask_in – input folder that contains [0,1] values
folder_values_out – output folder [.txt or .npy]
worker_instance_type – cloud instance type of worker nodes
manager_instance_type – cloud instance type of manager node
extension_folder_values1_in – File extension of files in folder for folder_values1_in
extension_folder_mask_in – File extension of files in folder for folder_mask_in
extension_folder_values_out – File extension of files in folder for folder_values_out
skip_existing_files – skip files that already exist in the output folder