Python get_options_parser Examples

Example #1

File: export_csv.py Project: futurulus/colors-in-context

#   mkdir runs/s1_samples
#   cp runs/l2/s1_samples.0.jsons runs/s1_samples/predictions.eval.jsons
#   cp runs/l2/data.eval.jsons runs/s1_samples/
#   echo '{}' > runs/s1_samples/config.json
#   touch runs/s1_samples/scores.eval.jsons
#   python export_csv.py --run_dir runs/s1_samples --filtered true --source pragmatic
import csv
import os
import StringIO
import warnings

from stanza.research import config
from html_report import get_output


parser = config.get_options_parser()
parser.add_argument('--listener', type=config.boolean, default=False,
                    help='If True, create a listener "clickedObj" csv file. Otherwise '
                         'create a speaker "message" csv file.')
parser.add_argument('--suffix', type=str, default='',
                    help='Append this to the end of filenames (before the ".csv") when '
                         'locating the Hawkins data.')
parser.add_argument('--filtered', type=config.boolean, default=False,
                    help='If True, look for the filteredCorpus csv file. --suffix should '
                         'be empty.')
parser.add_argument('--source', type=str, default='model',
                    help='"Source" entry for filtered csv (as opposed to "human").')

ID_COLUMNS = (0, 2)
SPEAKER_MESSAGE_COLUMN = 4
FILTERED_MESSAGE_COLUMN = 4

Example #2

import glob
import json
import Levenshtein as lev
import numpy as np
import os
import warnings
from collections import namedtuple

from stanza.util.unicode import uprint
from stanza.research import config

parser = config.get_options_parser()
parser.add_argument(
    '--max_examples',
    type=int,
    default=100,
    help='The maximum number of examples to display in error analysis.')
parser.add_argument('--html',
                    type=config.boolean,
                    default=False,
                    help='If true, output errors in HTML.')

Output = namedtuple('Output', 'config,results,data,scores,predictions')

COLORS = ['black', 'red', 'green', 'yellow', 'blue', 'purple', 'cyan', 'white']
HTML = [
    'Black', 'DarkRed', 'DarkGreen', 'Olive', 'Blue', 'Purple', 'DarkCyan',
    'White'
]