Refactor statistics computations
This commit is contained in:
parent
55f5964867
commit
ada2317435
156
src/build.py
156
src/build.py
|
|
@ -128,6 +128,24 @@ def build_session_page(config):
|
|||
content=config["SESSION_PAGE"],
|
||||
citeblock="")
|
||||
|
||||
def reverse_statistics_dict(stats, reverse=True):
|
||||
"""
|
||||
Transforms a dictionary mapping titles to a value into a list of values
|
||||
and lists of titles. The list is sorted by the value, and the titles are
|
||||
sorted alphabetically.
|
||||
"""
|
||||
rev = {}
|
||||
for key, value in stats.items():
|
||||
if value not in rev:
|
||||
rev[value] = []
|
||||
rev[value].append(key)
|
||||
for key, value in rev.items():
|
||||
rev[key] = sorted(value, key=lambda t: utils.titlesort(t))
|
||||
return sorted(rev.items(), key=lambda x:x[0], reverse=reverse)
|
||||
|
||||
def itemize(stats_list):
|
||||
return map(lambda x: "{0} – {1}".format(x[0], "; ".join(x[1])), stats_list)
|
||||
|
||||
def build_statistics_page(articles, config):
|
||||
"""
|
||||
Builds the full HTML of the statistics page.
|
||||
|
|
@ -136,61 +154,58 @@ def build_statistics_page(articles, config):
|
|||
cite_map = {
|
||||
article.title : [
|
||||
cite_tuple[1]
|
||||
for cite_tuple in article.citations.values()]
|
||||
for cite_tuple
|
||||
in article.citations.values()
|
||||
]
|
||||
for article in articles}
|
||||
|
||||
# Pages by pagerank
|
||||
content += "<div class=\"moveable\">\n"
|
||||
content += "<p><u>Top 10 pages by page rank:</u><br>\n"
|
||||
# Top pages by pagerank
|
||||
# Compute pagerank for each article
|
||||
G = networkx.Graph()
|
||||
for citer, citeds in cite_map.items():
|
||||
for cited in citeds:
|
||||
G.add_edge(citer, cited)
|
||||
ranks = networkx.pagerank(G)
|
||||
sranks = sorted(ranks.items(), key=lambda x: x[1], reverse=True)
|
||||
ranking = list(enumerate(map(lambda x: x[0], sranks)))
|
||||
content += "<br>\n".join(map(lambda x: "{0} – {1}".format(x[0]+1, x[1]), ranking[:10]))
|
||||
content += "</p>\n"
|
||||
content += "</div>\n"
|
||||
rank_by_article = networkx.pagerank(G)
|
||||
# Get the top ten articles by pagerank
|
||||
top_pageranks = reverse_statistics_dict(rank_by_article)[:10]
|
||||
# Replace the pageranks with ordinals
|
||||
top_ranked = enumerate(map(lambda x: x[1], top_pageranks), start=1)
|
||||
# Format the ranks into strings
|
||||
top_ranked_items = itemize(top_ranked)
|
||||
# Write the statistics to the page
|
||||
content += "<div class=\"moveable\">\n"
|
||||
content += "<p><u>Top 10 pages by page rank:</u><br>\n"
|
||||
content += "<br>\n".join(top_ranked_items)
|
||||
content += "</p>\n</div>\n"
|
||||
|
||||
# Top number of citations made
|
||||
citations_made = { title : len(cites) for title, cites in cite_map.items() }
|
||||
top_citations = reverse_statistics_dict(citations_made)[:3]
|
||||
top_citations_items = itemize(top_citations)
|
||||
content += "<div class=\"moveable\">\n"
|
||||
content += "<p><u>Most citations made from:</u><br>\n"
|
||||
citation_tally = [(kv[0], len(kv[1])) for kv in cite_map.items()]
|
||||
citation_count = defaultdict(list)
|
||||
for title, count in citation_tally: citation_count[count].append(title)
|
||||
content += "<br>\n".join(map(
|
||||
lambda kv: "{0} – {1}".format(
|
||||
kv[0],
|
||||
"; ".join(sorted(
|
||||
kv[1],
|
||||
key=lambda t: utils.titlesort(t)))),
|
||||
sorted(citation_count.items(), reverse=True)[:3]))
|
||||
content += "</p>\n"
|
||||
content += "</div>\n"
|
||||
content += "<br>\n".join(top_citations_items)
|
||||
content += "</p>\n</div>\n"
|
||||
|
||||
# Top number of times cited
|
||||
content += "<div class=\"moveable\">\n"
|
||||
content += "<p><u>Most citations made to:</u><br>\n"
|
||||
all_cited = set([title for cites in cite_map.values() for title in cites])
|
||||
# Build a map of what cites each article
|
||||
all_cited = set([title for citeds in cite_map.values() for title in citeds])
|
||||
cited_by_map = {
|
||||
cited: [
|
||||
citer
|
||||
for citer in cite_map.keys()
|
||||
if cited in cite_map[citer]]
|
||||
for cited in all_cited }
|
||||
cited_tally = [(kv[0], len(kv[1])) for kv in cited_by_map.items()]
|
||||
cited_count = defaultdict(list)
|
||||
for title, count in cited_tally: cited_count[count].append(title)
|
||||
content += "<br>\n".join(map(
|
||||
lambda kv: "{0} – {1}".format(kv[0], "; ".join(sorted(kv[1]))),
|
||||
sorted(cited_count.items(), reverse=True)[:3]))
|
||||
content += "</p>\n"
|
||||
content += "</div>\n"
|
||||
# Compute the number of citations to each article
|
||||
citations_to = { title : len(cites) for title, cites in cited_by_map.items() }
|
||||
top_cited = reverse_statistics_dict(citations_to)[:3]
|
||||
top_cited_items = itemize(top_cited)
|
||||
content += "<div class=\"moveable\">\n"
|
||||
content += "<p><u>Most citations made to:</u><br>\n"
|
||||
content += "<br>\n".join(top_cited_items)
|
||||
content += "</p>\n</div>\n"
|
||||
|
||||
# Top article length, roughly by words
|
||||
content += "<div class=\"moveable\">\n"
|
||||
content += "<p><u>Longest article:</u><br>\n"
|
||||
article_length = {}
|
||||
for article in articles:
|
||||
format_map = {
|
||||
|
|
@ -198,61 +213,66 @@ def build_statistics_page(articles, config):
|
|||
for format_id, cite_tuple in article.citations.items()
|
||||
}
|
||||
plain_content = article.content.format(**format_map)
|
||||
words = len(plain_content.split())
|
||||
article_length[article.title] = words
|
||||
content += "<br>\n".join(map(
|
||||
lambda kv: "{0} – {1}".format(kv[1], kv[0]),
|
||||
sorted(article_length.items(), reverse=True, key=lambda t: t[1])[:3]))
|
||||
content += "</p>\n"
|
||||
content += "</div>\n"
|
||||
wordcount = len(plain_content.split())
|
||||
article_length[article.title] = wordcount
|
||||
top_length = reverse_statistics_dict(article_length)[:3]
|
||||
top_length_items = itemize(top_length)
|
||||
content += "<div class=\"moveable\">\n"
|
||||
content += "<p><u>Longest article:</u><br>\n"
|
||||
content += "<br>\n".join(top_length_items)
|
||||
content += "</p>\n</div>\n"
|
||||
|
||||
# Total word count
|
||||
content += "<div class=\"moveable\">\n"
|
||||
content += "<p><u>Total word count:</u><br>\n"
|
||||
content += str(sum(article_length.values())) + "</p>"
|
||||
content += "</p>\n</div>\n"
|
||||
|
||||
# Player pageranks
|
||||
content += "<div class=\"moveable\">\n"
|
||||
content += "<p><u>Player total page rank:</u><br>\n"
|
||||
players = sorted(set([article.player for article in articles if article.player is not None]))
|
||||
articles_by = {
|
||||
articles_by_player = {
|
||||
player : [
|
||||
a
|
||||
for a in articles
|
||||
if a.player == player]
|
||||
for player in players}
|
||||
player_rank = {
|
||||
player : sum(map(lambda a: ranks[a.title] if a.title in ranks else 0, articles))
|
||||
for player, articles in articles_by.items()}
|
||||
content += "<br>\n".join(map(
|
||||
lambda kv: "{0} – {1}".format(kv[0], round(kv[1], 3)),
|
||||
sorted(player_rank.items(), key=lambda t:t[1], reverse=True)))
|
||||
content += "</p>\n"
|
||||
content += "</div>\n"
|
||||
pagerank_by_player = {
|
||||
player : round(
|
||||
sum(map(
|
||||
lambda a: rank_by_article[a.title] if a.title in rank_by_article else 0,
|
||||
articles)),
|
||||
3)
|
||||
for player, articles
|
||||
in articles_by_player.items()}
|
||||
player_rank = reverse_statistics_dict(pagerank_by_player)
|
||||
player_rank_items = itemize(player_rank)
|
||||
content += "<div class=\"moveable\">\n"
|
||||
content += "<p><u>Player total page rank:</u><br>\n"
|
||||
content += "<br>\n".join(player_rank_items)
|
||||
content += "</p>\n</div>\n"
|
||||
|
||||
# Player citations made
|
||||
content += "<div class=\"moveable\">\n"
|
||||
content += "<p><u>Citations made by player</u><br>\n"
|
||||
player_cite_count = {
|
||||
player : sum(map(lambda a:len(a.wcites | a.pcites), articles))
|
||||
for player, articles in articles_by.items()}
|
||||
content += "<br>\n".join(map(
|
||||
lambda kv: "{0} – {1}".format(kv[0], kv[1]),
|
||||
sorted(player_cite_count.items(), key=lambda t:t[1], reverse=True)))
|
||||
content += "</p>\n"
|
||||
content += "</div>\n"
|
||||
for player, articles in articles_by_player.items()}
|
||||
player_cites_made_ranks = reverse_statistics_dict(player_cite_count)
|
||||
player_cites_made_items = itemize(player_cites_made_ranks)
|
||||
content += "<div class=\"moveable\">\n"
|
||||
content += "<p><u>Citations made by player</u><br>\n"
|
||||
content += "<br>\n".join(player_cites_made_items)
|
||||
content += "</p>\n</div>\n"
|
||||
|
||||
# Player cited count
|
||||
content += "<div class=\"moveable\">\n"
|
||||
content += "<p><u>Citations made to player</u><br>\n"
|
||||
cited_times = {player : 0 for player in players}
|
||||
for article in articles:
|
||||
if article.player is not None:
|
||||
cited_times[article.player] += len(article.citedby)
|
||||
content += "<br>\n".join(map(
|
||||
lambda kv: "{0} – {1}".format(kv[0], kv[1]),
|
||||
sorted(cited_times.items(), key=lambda t:t[1], reverse=True)))
|
||||
content += "</p>\n"
|
||||
content += "</div>\n"
|
||||
cited_times_ranked = reverse_statistics_dict(cited_times)
|
||||
cited_times_items = itemize(cited_times_ranked)
|
||||
content += "<div class=\"moveable\">\n"
|
||||
content += "<p><u>Citations made to player</u><br>\n"
|
||||
content += "<br>\n".join(cited_times_items)
|
||||
content += "</p>\n</div>\n"
|
||||
|
||||
# Fill in the entry skeleton
|
||||
entry_skeleton = utils.load_resource("entry-page.html")
|
||||
|
|
|
|||
Loading…
Reference in New Issue