diff --git a/calctoxdiff.py b/calctoxdiff.py
index bcfa073..2f263d7 100644
--- a/calctoxdiff.py
+++ b/calctoxdiff.py
@@ -9,16 +9,22 @@ import matplotlib.pyplot as plt
 import numpy as np
 from scipy.stats import ks_2samp
 
-from common import imprt, IMAGE_MAGICK
+from analyze_batch import readavgsentsingle
+from common import imprt, IMAGE_MAGICK, calc_intervals
+from loader import load
 
 colors = {'neg': 'red', 'neu': 'green', 'pos': 'blue', 'com': 'orange'}
 
 
 def main(folder, intervl):
+    users, posts, firstcontrib, sumcontrib = load(folder)
+
     outputdir = folder + "/output/ksbatch/"
     os.system("mkdir -p " + outputdir)
     srcfolder = folder + "/output/batch/"
 
+    g(srcfolder + "/averagesentiment.txt", outputdir, calc_intervals(posts, intervl))
+
     onlyfiles = [srcfolder + f for f in listdir(srcfolder) if isfile(join(srcfolder, f)) and f.endswith(".py") and "newusers" in f and "i" + str(intervl) in f]
     onlyfiles = sorted(onlyfiles)
 
@@ -31,6 +37,47 @@ def main(folder, intervl):
     plotbydateold(onlyfiles, oldfiles, outputdir, intervl)
 
 
+class fake:
+    def __init__(self, p, s):
+        pass
+
+
+def g(srcfile, outputdir, intervals):
+    print("ks global")
+    avgss2 = readavgsentsingle(srcfile)
+
+    kscom = []
+    single = []
+    for i in range(1, 6):
+        kscom.append(ks_2samp([np.mean(x) if len(x) > 0 else float("nan") for x in avgss2[0]], [np.mean(x) if len(x) > 0 else float("nan") for x in avgss2[i]]))
+        s = []
+        for j in range(len(avgss2[0])):
+            s.append(ks_2samp(avgss2[0][j], avgss2[i][j]) if len(avgss2[i][j]) > 0 and len(avgss2[0][j]) else float("nan"))
+        single.append(s)
+
+    fig = plt.figure(figsize=(16, 12))
+    for i in range(len(single)):
+        plt.plot([iv[0] for iv in intervals], [s if isinstance(s, float) else s.pvalue for s in single[i]], label=str(i + 1) + " posts - most posters")
+    plt.title("KS 2-sided test for sentiments (X posts to 95%tile posters)")
+    plt.xticks(rotation=90)
+    plt.xlabel("Comparision: time frame X - time frame X+1")
+    plt.ylabel("pvalue")
+    plt.legend(loc="upper right")
+    plt.savefig(outputdir + "/ks_averagesentiments_pval.png", bbox_inches='tight')
+
+    plt.close(fig)
+    fig = plt.figure(figsize=(16, 12))
+    for i in range(len(single)):
+        plt.plot([iv[0] for iv in intervals], [s if isinstance(s, float) else s.statistic for s in single[i]], label=str(i + 1) + " posts - most posters")
+    plt.title("KS 2-sided test for sentiments (X posts to 95%tile posters)")
+    plt.xticks(rotation=90)
+    plt.xlabel("Comparision: time frame X - time frame X+1")
+    plt.ylabel("statistic")
+    plt.legend(loc="upper right")
+    plt.savefig(outputdir + "/ks_averagesentiments_stat.png", bbox_inches='tight')
+    plt.close(fig)
+
+
 def plotbypost(onlyfiles, outputdir, intervl):
     print("plotbypost")
     files = defaultdict(list)
diff --git a/summary b/summary
index f42660f..9a74ca1 100644
--- a/summary
+++ b/summary
@@ -9,7 +9,7 @@ Data: The data sets are aquired from archive.org [https://archive.org/download/s
 - math.stackexchange.com (kaputt timeout)
 - mathoverflow.net
 - serverfault.com
-- stats.stackexchange.com (kaputt analyse_batch letzter plot, 42, 37 datapoints)
+- stats.stackexchange.com
 - stackoverflow.com (not yet)
 - superuser.com
 - tex.stackexchange.com