Beispiel #1
0
def compare(gold_text, test_text, out_dict, error_counts, language='english'):
    """ Compares two trees in text form.
	This checks for empty trees and mismatched numbers
	of words.
	"""
    gold_text = gold_text.strip()
    test_text = test_text.strip()
    if len(gold_text) == 0:
        mprint("No gold tree", out_dict, ['out', 'err'])
        return
    elif len(test_text) == 0:
        mprint("Not parsed", out_dict, ['out', 'err'])
        return
    gold_tree = read_tree(gold_text, out_dict, 'gold')
    test_tree = read_tree(test_text, out_dict, 'test')
    if gold_tree is None or test_tree is None:
        mprint("Not parsed, but had output", out_dict,
               ['out', 'err', 'init_errors'])
        return
    mprint(
        render_tree.text_coloured_errors(test_tree, gold_tree).strip(),
        out_dict, 'init_errors')

    gold_words = gold_tree.word_yield()
    test_words = test_tree.word_yield()
    if len(test_words.split()) != len(gold_words.split()):
        mprint("Sentence lengths do not match...", out_dict, ['out', 'err'])
        mprint("Gold: " + gold_words.__repr__(), out_dict, ['out', 'err'])
        mprint("Test: " + test_words.__repr__(), out_dict, ['out', 'err'])
        return

    return compare_trees(gold_tree, test_tree, out_dict, error_counts,
                         language)
def compare(gold_text, test_text, out_dict, error_counts, language='english'):
	""" Compares two trees in text form.
	This checks for empty trees and mismatched numbers
	of words.
	"""
	gold_text = gold_text.strip()
	test_text = test_text.strip()
	if len(gold_text) == 0:
		mprint("No gold tree", out_dict, ['out', 'err'])
		return
	elif len(test_text) == 0:
		mprint("Not parsed", out_dict, ['out', 'err'])
		return
	gold_tree = read_tree(gold_text, out_dict, 'gold')
	test_tree = read_tree(test_text, out_dict, 'test')
	if gold_tree is None or test_tree is None:
		mprint("Not parsed, but had output", out_dict, ['out', 'err', 'init_errors'])
		return
	mprint(render_tree.text_coloured_errors(test_tree, gold_tree).strip(), out_dict, 'init_errors')

	gold_words = gold_tree.word_yield()
	test_words = test_tree.word_yield()
	if len(test_words.split()) != len(gold_words.split()):
		mprint("Sentence lengths do not match...", out_dict, ['out', 'err'])
		mprint("Gold: " + gold_words.__repr__(), out_dict, ['out', 'err'])
		mprint("Test: " + test_words.__repr__(), out_dict, ['out', 'err'])
		return

	return compare_trees(gold_tree, test_tree, out_dict, error_counts, language)
Beispiel #3
0
def compare_trees(gold_tree,
                  test_tree,
                  out_dict,
                  error_counts,
                  language='english'):
    """ Compares two trees. """
    init_errors = test_tree.get_errors(gold_tree)
    error_count = len(init_errors)
    mprint("%d Initial errors" % error_count, out_dict, 'out')
    iters, path = greedy_search(gold_tree, test_tree, language)
    mprint("%d on fringe, %d iterations" % iters, out_dict, 'out')
    if path is not None:
        mprint(test_tree.__repr__(), out_dict, 'test_trees')
        mprint(gold_tree.__repr__(), out_dict, 'gold_trees')
        for tree in path[1:]:
            mprint(
                str(tree[2]) + " Error:" + tree[1]['classified_type'],
                out_dict, 'out')

        if len(path) > 1:
            for tree in path:
                mprint("Step:" + tree[1]['classified_type'], out_dict, 'out')
                error_counts[tree[1]['classified_type']].append(tree[2])
                mprint(tree[1].__repr__(), out_dict, 'out')
                mprint(
                    render_tree.text_coloured_errors(tree[0],
                                                     gold=gold_tree).strip(),
                    out_dict, 'out')
    else:
        mprint("no path found", out_dict, 'out')

    mprint("", out_dict, ['out', 'err'])
def compare_trees(gold_tree, test_tree, out_dict, error_counts, language='english'):
	""" Compares two trees. """
	init_errors = test_tree.get_errors(gold_tree)
	error_count = len(init_errors)
	mprint("%d Initial errors" % error_count, out_dict, 'out')
	iters, path = greedy_search(gold_tree, test_tree, language)
	mprint("%d on fringe, %d iterations" % iters, out_dict, 'out')
	if path is not None:
		mprint(test_tree.__repr__(), out_dict, 'test_trees')
		mprint(gold_tree.__repr__(), out_dict, 'gold_trees')
		for tree in path[1:]:
			mprint(str(tree[2]) + " Error:" + tree[1]['classified_type'], out_dict, 'out')

		if len(path) > 1:
			for tree in path:
				mprint("Step:" + tree[1]['classified_type'], out_dict, 'out')
				error_counts[tree[1]['classified_type']].append(tree[2])
				mprint(tree[1].__repr__(), out_dict, 'out')
				mprint(render_tree.text_coloured_errors(tree[0], gold=gold_tree).strip(), out_dict, 'out')
	else:
		mprint("no path found", out_dict, 'out')

	mprint("", out_dict, ['out', 'err'])