From da8896eadd243d0d2b4bb0815a93e91bee6d3497 Mon Sep 17 00:00:00 2001
From: wea_ondara <wea_ondara@alpenblock.net>
Date: Mon, 27 Jan 2020 11:58:19 +0100
Subject: [PATCH] wip

---
 loader.py | 27 +++++++++++++++++++++++++++
 votes.py  | 44 +++++++++++++++++++++++++++++++++++++-------
 2 files changed, 64 insertions(+), 7 deletions(-)

diff --git a/loader.py b/loader.py
index 2e2e026..100c2b7 100644
--- a/loader.py
+++ b/loader.py
@@ -58,6 +58,33 @@ def load(folder):
     return users, posts, firstcontrib, sumcontrib
 
 
+def readVotes(folder):
+    file = folder + "/Votes.xml"
+    prefix = "readVotes: "
+    printnoln(prefix + "reading xml file ...")
+
+    now = cms()
+    items = [elem for event, elem in et.iterparse(file) if elem.tag == "row"]
+    rprint(prefix + "reading xml file ... took " + str(cms() - now) + "ms")
+
+    votes = dmt(items).map(mapvote, prefix + "mapping votes").getresults()
+
+    print(prefix + "done")
+    return votes
+
+
+def mapvote(item):
+    tags = ['PostId', 'VoteTypeId', 'CreationDate']
+    datetags = ['CreationDate']
+    vote = {tag: getTag(item, tag) for tag in tags}
+    for tag in datetags:
+        if vote[tag] is not None:
+            vote[tag] = datetime.fromisoformat(vote[tag])
+        else:
+            print("map vote: tag " + tag + " is None: " + str(vote))
+    return vote
+
+
 def computesumcontrib(posts):
     x1 = dmt(posts).map(lambda q: q['OwnerUserId'], "calc sum contrib q").getresults()
     x2 = dmt(posts).map(lambda q: [a['OwnerUserId'] for a in q['Answers']], "calc sum contrib a").getresults()
diff --git a/votes.py b/votes.py
index 7983fb9..4399e9e 100644
--- a/votes.py
+++ b/votes.py
@@ -9,7 +9,7 @@ from datetime import timedelta
 from dateutil.relativedelta import relativedelta
 
 from common import calc_intervals, printnoln, rprint, DAYS_NEW_USER
-from loader import load, dmt, cms
+from loader import load, dmt, cms, readVotes
 from sentiments import readtoxleveltxt
 
 colors = ['red', 'green', 'blue', 'orange', 'deeppink']
@@ -51,8 +51,8 @@ def main(folder, intervl):
     # filter nan entries
     for i in range(len(datasingle)):
         if len(datasingle[i]) == 0:
-            datasingle = float("nan")
-        if len(datasingle[i]) == 0:
+            datasingle[i] = float("nan")
+        if len(scoresingle[i]) == 0:
             scoresingle[i] = float("nan")
 
     print("Plotting ...")
@@ -79,14 +79,44 @@ def main(folder, intervl):
                 va = "bottom"
             else:
                 va = "top"
-        ax.text(intervals[i][0], data[i], ("n=" if i == 0 else "") + str(len(datasingle[i])), ha="center", va=va)
-    plt.title("Average sentiments for new users")
+        ax.text(intervals[i][0], data[i], ("n=" if i == 0 else "") + (str(len(datasingle[i])) if str(datasingle[i]) != "nan" else ""), ha="center", va=va)
+    plt.title("Average sentiments and score for new users")
     plt.xticks(rotation=90)
     ax.set_xlabel("months")
     ax.set_ylabel("sentiment")
-    ax.set_ylabel("score (votes)")
+    ax2.set_ylabel("score (votes)")
     plt.legend(l1 + l2, [l.get_label() for l in l1 + l2], loc="upper right")
-    outfile = outputdir + "/average_sentiments-i" + str(intervl) + ".png"
+    outfile = outputdir + "/average_votes-i" + str(intervl) + ".png"
+    plt.savefig(outfile, bbox_inches='tight')
+    plt.close(fig)
+
+    # votes over time
+    votes = readVotes(folder)
+    fig = plt.figure(figsize=(16, 12))
+    ivs = [(datetime.fromisoformat("2010-01-01T00:00:00"), datetime.fromisoformat(str(y) + "-01-01T00:00:00")) for y in range(2011, 2020)]
+    for interval in ivs:
+        print(interval[0].strftime("%d-%m-%Y") + " to " + interval[1].strftime("%d-%m-%Y"))
+        ivvotes = dmt(votes).filter(lambda v: interval[0] <= v['CreationDate'] < interval[1]).getresults()
+        scores = []
+        for (option_date_from, option_date_to) in intervals:
+            if option_date_to > interval[1]:
+                continue
+            intervalposts = dmt(posts).filter(lambda p: option_date_from <= p['CreationDate'] < option_date_to
+                                                        and firstcontrib[p['OwnerUserId']] + timedelta(days=DAYS_NEW_USER) <= p['CreationDate']).getresults()
+            intervalpostsids = set(dmt(intervalposts).map(lambda p: p['Id']).getresults())
+            intervalvotes = dmt(ivvotes).filter(lambda v: v['PostId'] in intervalpostsids).getresults()
+            intervalscore = sum(dmt(intervalvotes).map(lambda v: 1 if v['VoteTypeId'] == "2" else (-1 if v['VoteTypeId'] == "3" else 0)).getresults())
+            intervalscore = intervalscore / len(intervalpostsids) if len(intervalpostsids) != 0 else float("nan")
+            scores.append(((option_date_from, option_date_to), intervalscore))
+        # if all(str(score) == "nan" for iv, score in scores)
+        #     continue
+        plt.plot([iv[0] for iv, score in scores], [score for iv, score in scores], label=str(interval[0].year) + " - " + str(interval[1].year))
+    plt.title("Average score for new users over time")
+    plt.xlabel("months")
+    plt.ylabel("score")
+    plt.legend(loc="upper right")
+    plt.grid(True)
+    outfile = outputdir + "/average_votes_over_time-i" + str(intervl) + ".png"
     plt.savefig(outfile, bbox_inches='tight')
     plt.close(fig)