make_ds_mask.py
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	#!/usr/bin/env python
	import numpy as np
	import pandas as pd
	import xarray as xr
	import os
	import sys
	import time
	from features import Training, Testing

	data_path = sys.argv[1]
	dataset = sys.argv[2]
	features = sys.argv[3].split(",")
	targets = sys.argv[4].split(",")
	mask = sys.argv[5]
	val_ratio = float(sys.argv[6])
	year = 2001

	# set location masks for the training and test
	train_locs = "locations/"+mask+"_train.txt"
	test_locs = "locations/"+mask+"_test.txt"

	new_set = Training(data_path, dataset, features, targets)
	new_set.make_dataset(year = year, sample_name = train_locs, test_name = test_locs)

	new_set.normalize_all(feature_norm = 'mean', target_norm = 'mean', val_ratio = val_ratio, force_normalization = True)