diff options
Diffstat (limited to 'gi/evaluation')
| -rw-r--r-- | gi/evaluation/conditional_entropy.py | 61 | ||||
| -rw-r--r-- | gi/evaluation/confusion_matrix.py | 123 | ||||
| -rw-r--r-- | gi/evaluation/entropy.py | 38 | ||||
| -rw-r--r-- | gi/evaluation/extract_ccg_labels.py | 129 | ||||
| -rw-r--r-- | gi/evaluation/tree.py | 485 |
5 files changed, 0 insertions, 836 deletions
diff --git a/gi/evaluation/conditional_entropy.py b/gi/evaluation/conditional_entropy.py deleted file mode 100644 index 356d3b1d..00000000 --- a/gi/evaluation/conditional_entropy.py +++ /dev/null @@ -1,61 +0,0 @@ -#!/usr/bin/env python - -import sys, math, itertools, getopt - -def usage(): - print >>sys.stderr, 'Usage:', sys.argv[0], '[-s slash_threshold] input-1 input-2' - sys.exit(0) - -optlist, args = getopt.getopt(sys.argv[1:], 'hs:') -slash_threshold = None -for opt, arg in optlist: - if opt == '-s': - slash_threshold = int(arg) - else: - usage() -if len(args) != 2: - usage() - -ginfile = open(args[0]) -pinfile = open(args[1]) - -# evaluating: H(G | P) = sum_{g,p} p(g,p) log { p(p) / p(g,p) } -# = sum_{g,p} c(g,p)/N { log c(p) - log N - log c(g,p) + log N } -# = 1/N sum_{g,p} c(g,p) { log c(p) - log c(g,p) } -# where G = gold, P = predicted, N = number of events - -N = 0 -gold_frequencies = {} -predict_frequencies = {} -joint_frequencies = {} - -for gline, pline in itertools.izip(ginfile, pinfile): - gparts = gline.split('||| ')[1].split() - pparts = pline.split('||| ')[1].split() - assert len(gparts) == len(pparts) - - for gpart, ppart in zip(gparts, pparts): - gtag = gpart.split(':',1)[1] - ptag = ppart.split(':',1)[1] - - if slash_threshold == None or gtag.count('/') + gtag.count('\\') <= slash_threshold: - joint_frequencies.setdefault((gtag, ptag), 0) - joint_frequencies[gtag,ptag] += 1 - - predict_frequencies.setdefault(ptag, 0) - predict_frequencies[ptag] += 1 - - gold_frequencies.setdefault(gtag, 0) - gold_frequencies[gtag] += 1 - - N += 1 - -hg2p = 0 -hp2g = 0 -for (gtag, ptag), cgp in joint_frequencies.items(): - hp2g += cgp * (math.log(predict_frequencies[ptag], 2) - math.log(cgp, 2)) - hg2p += cgp * (math.log(gold_frequencies[gtag], 2) - math.log(cgp, 2)) -hg2p /= N -hp2g /= N - -print 'H(P|G)', hg2p, 'H(G|P)', hp2g, 'VI', hg2p + hp2g diff --git a/gi/evaluation/confusion_matrix.py b/gi/evaluation/confusion_matrix.py deleted file mode 100644 index 2dd7aa47..00000000 --- a/gi/evaluation/confusion_matrix.py +++ /dev/null @@ -1,123 +0,0 @@ -#!/usr/bin/env python - -import sys, math, itertools, getopt - -def usage(): - print >>sys.stderr, 'Usage:', sys.argv[0], '[-s slash_threshold] [-p output] [-m] input-1 input-2' - sys.exit(0) - -optlist, args = getopt.getopt(sys.argv[1:], 'hs:mp:') -slash_threshold = None -output_fname = None -show_matrix = False -for opt, arg in optlist: - if opt == '-s': - slash_threshold = int(arg) - elif opt == '-p': - output_fname = arg - elif opt == '-m': - show_matrix = True - else: - usage() -if len(args) != 2 or (not show_matrix and not output_fname): - usage() - -ginfile = open(args[0]) -pinfile = open(args[1]) - -if output_fname: - try: - import Image, ImageDraw - except ImportError: - print >>sys.stderr, "Error: Python Image Library not available. Did you forget to set your PYTHONPATH environment variable?" - sys.exit(1) - -N = 0 -gold_frequencies = {} -predict_frequencies = {} -joint_frequencies = {} - -for gline, pline in itertools.izip(ginfile, pinfile): - gparts = gline.split('||| ')[1].split() - pparts = pline.split('||| ')[1].split() - assert len(gparts) == len(pparts) - - for gpart, ppart in zip(gparts, pparts): - gtag = gpart.split(':',1)[1] - ptag = ppart.split(':',1)[1] - - if slash_threshold == None or gtag.count('/') + gtag.count('\\') <= slash_threshold: - joint_frequencies.setdefault((gtag, ptag), 0) - joint_frequencies[gtag,ptag] += 1 - - predict_frequencies.setdefault(ptag, 0) - predict_frequencies[ptag] += 1 - - gold_frequencies.setdefault(gtag, 0) - gold_frequencies[gtag] += 1 - - N += 1 - -# find top tags -gtags = gold_frequencies.items() -gtags.sort(lambda x,y: x[1]-y[1]) -gtags.reverse() -#gtags = gtags[:50] - -preds = predict_frequencies.items() -preds.sort(lambda x,y: x[1]-y[1]) -preds.reverse() - -if show_matrix: - print '%7s %7s' % ('pred', 'cnt'), - for gtag, gcount in gtags: print '%7s' % gtag, - print - print '=' * 80 - - for ptag, pcount in preds: - print '%7s %7d' % (ptag, pcount), - for gtag, gcount in gtags: - print '%7d' % joint_frequencies.get((gtag, ptag), 0), - print - - print '%7s %7d' % ('total', N), - for gtag, gcount in gtags: print '%7d' % gcount, - print - -if output_fname: - offset=10 - - image = Image.new("RGB", (len(preds), len(gtags)), (255, 255, 255)) - #hsl(hue, saturation%, lightness%) - - # re-sort preds to get a better diagonal - ptags=[] - if True: - ptags = map(lambda (p,c): p, preds) - else: - remaining = set(predict_frequencies.keys()) - for y, (gtag, gcount) in enumerate(gtags): - best = (None, 0) - for ptag in remaining: - #pcount = predict_frequencies[ptag] - p = joint_frequencies.get((gtag, ptag), 0)# / float(pcount) - if p > best[1]: best = (ptag, p) - ptags.append(ptag) - remaining.remove(ptag) - if not remaining: break - - print 'Predicted tag ordering:', ' '.join(ptags) - print 'Gold tag ordering:', ' '.join(map(lambda (t,c): t, gtags)) - - draw = ImageDraw.Draw(image) - for x, ptag in enumerate(ptags): - pcount = predict_frequencies[ptag] - minval = math.log(offset) - maxval = math.log(pcount + offset) - for y, (gtag, gcount) in enumerate(gtags): - f = math.log(offset + joint_frequencies.get((gtag, ptag), 0)) - z = int(240. * (maxval - f) / float(maxval - minval)) - #print x, y, z, f, maxval - draw.point([(x,y)], fill='hsl(%d, 100%%, 50%%)' % z) - del draw - image.save(output_fname) diff --git a/gi/evaluation/entropy.py b/gi/evaluation/entropy.py deleted file mode 100644 index ec1ef502..00000000 --- a/gi/evaluation/entropy.py +++ /dev/null @@ -1,38 +0,0 @@ -#!/usr/bin/env python - -import sys, math, itertools, getopt - -def usage(): - print >>sys.stderr, 'Usage:', sys.argv[0], '[-s slash_threshold] input file' - sys.exit(0) - -optlist, args = getopt.getopt(sys.argv[1:], 'hs:') -slash_threshold = None -for opt, arg in optlist: - if opt == '-s': - slash_threshold = int(arg) - else: - usage() -if len(args) != 1: - usage() - -infile = open(args[0]) -N = 0 -frequencies = {} - -for line in infile: - - for part in line.split('||| ')[1].split(): - tag = part.split(':',1)[1] - - if slash_threshold == None or tag.count('/') + tag.count('\\') <= slash_threshold: - frequencies.setdefault(tag, 0) - frequencies[tag] += 1 - N += 1 - -h = 0 -for tag, c in frequencies.items(): - h -= c * (math.log(c, 2) - math.log(N, 2)) -h /= N - -print 'entropy', h diff --git a/gi/evaluation/extract_ccg_labels.py b/gi/evaluation/extract_ccg_labels.py deleted file mode 100644 index e0034648..00000000 --- a/gi/evaluation/extract_ccg_labels.py +++ /dev/null @@ -1,129 +0,0 @@ -#!/usr/bin/env python - -# -# Takes spans input along with treebank and spits out CG style categories for each span. -# spans = output from CDEC's extools/extractor with --base_phrase_spans option -# treebank = PTB format, one tree per line -# -# Output is in CDEC labelled-span format -# - -import sys, itertools, tree - -tinfile = open(sys.argv[1]) -einfile = open(sys.argv[2]) - -def number_leaves(node, next=0): - left, right = None, None - for child in node.children: - l, r = number_leaves(child, next) - next = max(next, r+1) - if left == None or l < left: - left = l - if right == None or r > right: - right = r - - #print node, left, right, next - if left == None or right == None: - assert not node.children - left = right = next - - node.left = left - node.right = right - - return left, right - -def ancestor(node, indices): - #print node, node.left, node.right, indices - # returns the deepest node covering all the indices - if min(indices) >= node.left and max(indices) <= node.right: - # try the children - for child in node.children: - x = ancestor(child, indices) - if x: return x - return node - else: - return None - -def frontier(node, indices): - #print 'frontier for node', node, 'indices', indices - if node.left > max(indices) or node.right < min(indices): - #print '\toutside' - return [node] - elif node.children: - #print '\tcovering at least part' - ns = [] - for child in node.children: - n = frontier(child, indices) - ns.extend(n) - return ns - else: - return [node] - -def project_heads(node): - #print 'project_heads', node - is_head = node.data.tag.endswith('-HEAD') - if node.children: - found = 0 - for child in node.children: - x = project_heads(child) - if x: - node.data.tag = x - found += 1 - assert found == 1 - elif is_head: - node.data.tag = node.data.tag[:-len('-HEAD')] - - if is_head: - return node.data.tag - else: - return None - -for tline, eline in itertools.izip(tinfile, einfile): - if tline.strip() != '(())': - if tline.startswith('( '): - tline = tline[2:-1].strip() - tr = tree.parse_PST(tline) - if tr != None: - number_leaves(tr) - #project_heads(tr) # assumes Bikel-style head annotation for the input trees - else: - tr = None - - parts = eline.strip().split(" ||| ") - zh, en = parts[:2] - spans = parts[-1] - print '|||', - for span in spans.split(): - sps = span.split(":") - i, j, x, y = map(int, sps[0].split("-")) - - if tr: - a = ancestor(tr, range(x,y)) - try: - fs = frontier(a, range(x,y)) - except: - print >>sys.stderr, "problem with line", tline.strip(), "--", eline.strip() - raise - - #print x, y - #print 'ancestor', a - #print 'frontier', fs - - cat = a.data.tag - for f in fs: - if f.right < x: - cat += '\\' + f.data.tag - else: - break - fs.reverse() - for f in fs: - if f.left >= y: - cat += '/' + f.data.tag - else: - break - else: - cat = 'FAIL' - - print '%d-%d:%s' % (x, y, cat), - print diff --git a/gi/evaluation/tree.py b/gi/evaluation/tree.py deleted file mode 100644 index 702d80b6..00000000 --- a/gi/evaluation/tree.py +++ /dev/null @@ -1,485 +0,0 @@ -import re, sys - -class Symbol: - def __init__(self, nonterm, term=None, var=None): - assert not (term != None and var != None) - self.tag = nonterm - self.token = term - self.variable = var - - def is_variable(self): - return self.variable != None - - def __eq__(self, other): - return self.tag == other.tag and self.token == other.token and self.variable == other.variable - - def __ne__(self, other): - return not (self == other) - - def __hash__(self): - return hash((self.tag, self.token, self.variable)) - - def __repr__(self): - return str(self) - - def __cmp__(self, other): - return cmp((self.tag, self.token, self.variable), - (other.tag, other.token, other.variable)) - - def __str__(self): - parts = [] - if False: # DEPENDENCY - if self.token: - parts.append(str(self.token)) - elif self.variable != None: - parts.append('#%d' % self.variable) - if self.tag: - parts.append(str(self.tag)) - return '/'.join(parts) - else: - if self.tag: - parts.append(str(self.tag)) - if self.token: - parts.append(str(self.token)) - elif self.variable != None: - parts.append('#%d' % self.variable) - return ' '.join(parts) - -class TreeNode: - def __init__(self, data, children=None, order=-1): - self.data = data - self.children = [] - self.order = order - self.parent = None - if children: self.children = children - - def insert(self, child): - self.children.append(child) - child.parent = self - - def leaves(self): - ls = [] - for node in self.xtraversal(): - if not node.children: - ls.append(node.data) - return ls - - def leaf_nodes(self): - ls = [] - for node in self.xtraversal(): - if not node.children: - ls.append(node) - return ls - - def max_depth(self): - d = 1 - for child in self.children: - d = max(d, 1 + child.max_depth()) - if not self.children and self.data.token: - d = 2 - return d - - def max_width(self): - w = 0 - for child in self.children: - w += child.max_width() - return max(1, w) - - def num_internal_nodes(self): - if self.children: - n = 1 - for child in self.children: - n += child.num_internal_nodes() - return n - elif self.data.token: - return 1 - else: - return 0 - - def postorder_traversal(self, visit): - """ - Postorder traversal; no guarantee that terminals will be read in the - correct order for dep. trees. - """ - for child in self.children: - child.traversal(visit) - visit(self) - - def traversal(self, visit): - """ - Preorder for phrase structure trees, and inorder for dependency trees. - In both cases the terminals will be read off in the correct order. - """ - visited_self = False - if self.order <= 0: - visited_self = True - visit(self) - - for i, child in enumerate(self.children): - child.traversal(visit) - if i + 1 == self.order: - visited_self = True - visit(self) - - assert visited_self - - def xpostorder_traversal(self): - for child in self.children: - for node in child.xpostorder_traversal(): - yield node - yield self - - def xtraversal(self): - visited_self = False - if self.order <= 0: - visited_self = True - yield self - - for i, child in enumerate(self.children): - for d in child.xtraversal(): - yield d - - if i + 1 == self.order: - visited_self = True - yield self - - assert visited_self - - def xpostorder_traversal(self): - for i, child in enumerate(self.children): - for d in child.xpostorder_traversal(): - yield d - yield self - - def edges(self): - es = [] - self.traverse_edges(lambda h,c: es.append((h,c))) - return es - - def traverse_edges(self, visit): - for child in self.children: - visit(self.data, child.data) - child.traverse_edges(visit) - - def subtrees(self, include_self=False): - st = [] - if include_self: - stack = [self] - else: - stack = self.children[:] - - while stack: - node = stack.pop() - st.append(node) - stack.extend(node.children) - return st - - def find_parent(self, node): - try: - index = self.children.index(node) - return self, index - except ValueError: - for child in self.children: - if isinstance(child, TreeNode): - r = child.find_parent(node) - if r: return r - return None - - def is_ancestor_of(self, node): - if self == node: - return True - for child in self.children: - if child.is_ancestor_of(child): - return True - return False - - def find(self, node): - if self == node: - return self - for child in self.children: - if isinstance(child, TreeNode): - r = child.find(node) - if r: return r - else: - if child == node: - return r - return None - - def equals_ignorecase(self, other): - if not isinstance(other, TreeNode): - return False - if self.data != other.data: - return False - if len(self.children) != len(other.children): - return False - for mc, oc in zip(self.children, other.children): - if isinstance(mc, TreeNode): - if not mc.equals_ignorecase(oc): - return False - else: - if mc.lower() != oc.lower(): - return False - return True - - def node_number(self, numbering, next=0): - if self.order <= 0: - numbering[id(self)] = next - next += 1 - - for i, child in enumerate(self.children): - next = child.node_number(numbering, next) - if i + 1 == self.order: - numbering[id(self)] = next - next += 1 - - return next - - def display_conll(self, out): - numbering = {} - self.node_number(numbering) - next = 0 - self.children[0].traversal(lambda x: \ - out.write('%d\t%s\t%s\t%s\t%s\t_\t%d\tLAB\n' \ - % (numbering[id(x)], x.data.token, x.data.token, - x.data.tag, x.data.tag, numbering[id(x.parent)]))) - out.write('\n') - - def size(self): - sz = 1 - for child in self.children: - sz += child.size() - return sz - - def __eq__(self, other): - if isinstance(other, TreeNode) and self.data == other.data \ - and self.children == other.children: - return True - return False - - def __cmp__(self, other): - if not isinstance(other, TreeNode): return 1 - n = cmp(self.data, other.data) - if n != 0: return n - n = len(self.children) - len(other.children) - if n != 0: return n - for sc, oc in zip(self.children, other.children): - n = cmp(sc, oc) - if n != 0: return n - return 0 - - def __ne__(self, other): - return not self.__eq__(other) - - def __hash__(self): - return hash((self.data, tuple(self.children))) - - def __repr__(self): - return str(self) - - def __str__(self): - s = '(' - space = False - if self.order <= 0: - s += str(self.data) - space = True - for i, child in enumerate(self.children): - if space: s += ' ' - s += str(child) - space = True - if i+1 == self.order: - s += ' ' + str(self.data) - return s + ')' - -def read_PSTs(fname): - infile = open(fname) - trees = [] - for line in infile: - trees.append(parse_PST(line.strip())) - infile.close() - return trees - -def parse_PST_multiline(infile, hash_is_var=True): - buf = '' - num_open = 0 - while True: - line = infile.readline() - if not line: - return None - buf += ' ' + line.rstrip() - num_open += line.count('(') - line.count(')') - if num_open == 0: - break - - return parse_PST(buf, hash_is_var) - -def parse_PST(line, hash_is_var=True): - line = line.rstrip() - if not line or line.lower() == 'null': - return None - - # allow either (a/DT) or (DT a) - #parts_re = re.compile(r'(\(*)([^/)]*)(?:/([^)]*))?(\)*)$') - - # only allow (DT a) - parts_re = re.compile(r'(\(*)([^)]*)(\)*)$') - - root = TreeNode(Symbol('TOP')) - stack = [root] - for part in line.rstrip().split(): - m = parts_re.match(part) - #opening, tok_or_tag, tag, closing = m.groups() - opening, tok_or_tag, closing = m.groups() - tag = None - #print 'token', part, 'bits', m.groups() - for i in opening: - node = TreeNode(Symbol(None)) - stack[-1].insert(node) - stack.append(node) - - if tag: - stack[-1].data.tag = tag - if hash_is_var and tok_or_tag.startswith('#'): - stack[-1].data.variable = int(tok_or_tag[1:]) - else: - stack[-1].data.token = tok_or_tag - else: - if stack[-1].data.tag == None: - stack[-1].data.tag = tok_or_tag - else: - if hash_is_var and tok_or_tag.startswith('#'): - try: - stack[-1].data.variable = int(tok_or_tag[1:]) - except ValueError: # it's really a token! - #print >>sys.stderr, 'Warning: # used for token:', tok_or_tag - stack[-1].data.token = tok_or_tag - else: - stack[-1].data.token = tok_or_tag - - for i in closing: - stack.pop() - - #assert str(root.children[0]) == line - return root.children[0] - -def read_DTs(fname): - infile = open(fname) - trees = [] - while True: - t = parse_DT(infile) - if t: trees.append(t) - else: break - infile.close() - return trees - -def read_bracketed_DTs(fname): - infile = open(fname) - trees = [] - for line in infile: - trees.append(parse_bracketed_DT(line)) - infile.close() - return trees - -def parse_DT(infile): - tokens = [Symbol('ROOT')] - children = {} - - for line in infile: - parts = line.rstrip().split() - #print parts - if not parts: break - index = len(tokens) - token = parts[1] - tag = parts[3] - parent = int(parts[6]) - if token.startswith('#'): - tokens.append(Symbol(tag, var=int(token[1:]))) - else: - tokens.append(Symbol(tag, token)) - children.setdefault(parent, set()).add(index) - - if len(tokens) == 1: return None - - root = TreeNode(Symbol('ROOT'), [], 0) - schedule = [] - for child in sorted(children[0]): - schedule.append((root, child)) - - while schedule: - parent, index = schedule[0] - del schedule[0] - - node = TreeNode(tokens[index]) - node.order = 0 - parent.insert(node) - - for child in sorted(children.get(index, [])): - schedule.append((node, child)) - if child < index: - node.order += 1 - - return root - -_bracket_split_re = re.compile(r'([(]*)([^)/]*)(?:/([^)]*))?([)]*)') - -def parse_bracketed_DT(line, insert_root=True): - line = line.rstrip() - if not line or line == 'NULL': return None - #print line - - root = TreeNode(Symbol('ROOT')) - stack = [root] - for part in line.rstrip().split(): - m = _bracket_split_re.match(part) - - for c in m.group(1): - node = TreeNode(Symbol(None)) - stack[-1].insert(node) - stack.append(node) - - if m.group(3) != None: - if m.group(2).startswith('#'): - stack[-1].data.variable = int(m.group(2)[1:]) - else: - stack[-1].data.token = m.group(2) - stack[-1].data.tag = m.group(3) - else: - stack[-1].data.tag = m.group(2) - stack[-1].order = len(stack[-1].children) - # FIXME: also check for vars - - for c in m.group(4): - stack.pop() - - assert len(stack) == 1 - if not insert_root or root.children[0].data.tag == 'ROOT': - return root.children[0] - else: - return root - -_bracket_split_notag_re = re.compile(r'([(]*)([^)/]*)([)]*)') - -def parse_bracketed_untagged_DT(line): - line = line.rstrip() - if not line or line == 'NULL': return None - - root = TreeNode(Symbol('TOP')) - stack = [root] - for part in line.rstrip().split(): - m = _bracket_split_notag_re.match(part) - - for c in m.group(1): - node = TreeNode(Symbol(None)) - stack[-1].insert(node) - stack.append(node) - - if stack[-1].data.token == None: - stack[-1].data.token = m.group(2) - stack[-1].order = len(stack[-1].children) - else: - child = TreeNode(Symbol(nonterm=None, term=m.group(2))) - stack[-1].insert(child) - - for c in m.group(3): - stack.pop() - - return root.children[0] |