def get_args_parser():
import argparse
from argparse import RawTextHelpFormatter
desc = 'Uses WiFi signals and machine learning to predict where you are.'
desc += '\nFeel free to try out commands, if anything is missing it will print help.'
desc += '\n\nYou will want to start with `whereami learn`'
p = argparse.ArgumentParser(description=desc,
formatter_class=RawTextHelpFormatter)
p.add_argument('--version',
'-v',
action='version',
version=print_version())
subparsers = p.add_subparsers(dest="command")
subparsers.add_parser('predict')
subparsers.add_parser('predict_proba')
subparsers.add_parser('crossval')
subparsers.add_parser('locations')
learn_parser = subparsers.add_parser('learn')
learn_parser.add_argument('--location',
'-l',
required=True,
help='A name-tag for location to learn.')
learn_parser.add_argument('--num_samples',
'-n',
type=int,
default=100,
help='Number of samples to take')
return p
def get_args_parser():
import argparse
from argparse import RawTextHelpFormatter
desc = 'Uses WiFi signals and machine learning to predict where you are.'
desc += '\nFeel free to try out commands, if anything is missing it will print help.'
desc += '\n\nYou will want to start with `whereami learn`'
p = argparse.ArgumentParser(description=desc, formatter_class=RawTextHelpFormatter)
p.add_argument('--version', '-v', action='version', version=print_version())
subparsers = p.add_subparsers(dest="command")
predict_parser = subparsers.add_parser('predict')
predict_parser.add_argument('--input_path', '-ip', default=None,
help='The directory containing current.loc.txt')
predict_parser.add_argument('--model_path', '-mp', default=None,
help='The directory of the model / trained data')
predict_parser.add_argument(
'--device', '-d', default="", help='Change the wifi device to use')
predict_proba_parser = subparsers.add_parser('predict_proba')
predict_proba_parser.add_argument(
'--input_path', '-ip', default=None, help='The directory containing current.loc.txt')
predict_proba_parser.add_argument(
'--model_path', '-mp', default=None, help='The directory of the model / trained data')
predict_proba_parser.add_argument(
'--device', '-d', default="", help='Change the wifi device to use')
crossval_parser = subparsers.add_parser('crossval')
crossval_parser.add_argument('--model_path', '-mp', default=None,
help='The directory of the model / trained data')
ls_parser = subparsers.add_parser('ls')
ls_parser.add_argument('--model_path', '-mp', default=None,
help='The directory of the model / trained data')
locations_parser = subparsers.add_parser('locations')
locations_parser.add_argument('--model_path', '-mp', default=None,
help='The directory of the model / trained data')
learn_parser = subparsers.add_parser('learn')
learn_parser.add_argument('--location', '-l', required=True,
help='A name-tag for location to learn.')
learn_parser.add_argument('--device', '-d', default="",
help='Change the wifi device to use')
learn_parser.add_argument('--num_samples', '-n', type=int,
default=100, help='Number of samples to take')
rename = subparsers.add_parser('rename')
rename.add_argument('--label', help='Label to rename')
rename.add_argument('--new_label', help='New label name')
rename.add_argument('--model_path', '-mp', default=None,
help='The directory of the model / trained data')
train_parser = subparsers.add_parser('train')
train_parser.add_argument('--model_path', '-mp', default=None,
help='The directory of the model / trained data')
return p
def get_args_parser():
import argparse
from argparse import RawTextHelpFormatter
desc = 'Uses WiFi signals and machine learning to predict where you are.'
desc += '\nFeel free to try out commands, if anything is missing it will print help.'
desc += '\n\nYou will want to start with `whereami learn`'
p = argparse.ArgumentParser(description=desc, formatter_class=RawTextHelpFormatter)
p.add_argument('--version', '-v', action='version', version=print_version())
subparsers = p.add_subparsers(dest="command")
subparsers.add_parser('predict')
subparsers.add_parser('predict_proba')
subparsers.add_parser('crossval')
subparsers.add_parser('locations')
learn_parser = subparsers.add_parser('learn')
learn_parser.add_argument('--location', '-l', required=True,
help='A name-tag for location to learn.')
learn_parser.add_argument('--num_samples', '-n', type=int, default=100,
help='Number of samples to take')
return p
def test_print():
assert print_version()