def wordSummary(db, table):
f = open("wordSummary_%s.txt" % table, 'w')
d = {}
header = "word, length, rtAVG, rtSTD, total, percCorrect\n"
f.write(header)
wordList = []
sql = "SELECT DISTINCT(word) FROM %s" % table
for w in db.query(sql):
wordList.append(w[0])
for word in wordList:
sql = "SELECT RT FROM %s WHERE word = '%s' AND incorrect = 0" % (table, word)
wordLen = len(word)
rtList = []
zList = []
for rt in db.query(sql):
rtList.append(rt[0])
rtAVG = stats.mean(rtList)
rtSTD = stats.samplestdev(rtList)
total = db.query("SELECT COUNT(*) FROM %s WHERE word = '%s'" % (table, word))[0][0]
percCorrect = float(len(rtList)) / float(total) * 100.0
print len(rtList), total
myString = "%s, %i, %f, %f, %i, %f\n" % (word, wordLen, rtAVG, rtSTD, total, percCorrect)
print myString
f.write(myString)
f.close()
def wordSummary(db, table):
f = open("wordSummary_%s.txt" % table, 'w')
d = {}
header = "word, length, rtAVG, rtSTD, total, percCorrect\n"
f.write(header)
wordList = []
sql = "SELECT DISTINCT(word) FROM %s" % table
for w in db.query(sql):
wordList.append(w[0])
for word in wordList:
sql = "SELECT RT FROM %s WHERE word = '%s' AND incorrect = 0" % (table,
word)
wordLen = len(word)
rtList = []
zList = []
for rt in db.query(sql):
rtList.append(rt[0])
rtAVG = stats.mean(rtList)
rtSTD = stats.samplestdev(rtList)
total = db.query("SELECT COUNT(*) FROM %s WHERE word = '%s'" %
(table, word))[0][0]
percCorrect = float(len(rtList)) / float(total) * 100.0
print len(rtList), total
myString = "%s, %i, %f, %f, %i, %f\n" % (word, wordLen, rtAVG, rtSTD,
total, percCorrect)
print myString
f.write(myString)
f.close()
def writeByCategory(db, table):
f = open("%s_by_category.txt" % table, "w")
subList = db.getSubjects(table)
for subject in subList:
sex = db.getSex(subject, table)
if sex == "male":
se = 2
elif sex == "female":
se = 1
f.write(str(subject) + "," + str(se) + ",")
total = db.query("SELECT COUNT(*) FROM %s WHERE subject = %s" % (table, subject))[0][0]
correct = db.query("SELECT SUM(incorrect) FROM %s WHERE subject = %s" % (table, subject))[0][0]
if correct:
percCorrect = float(correct) / float(total) * 100.0
else:
percCorrect = 0.0
sql = "SELECT category, RT, zscore, incorrect FROM %s WHERE subject = %s" % (table, subject)
d = {}
for cat, RT, zscore, incorrect in db.query(sql):
if d.has_key(cat):
pass
else:
d[cat] = []
if incorrect == 0 and zscore <= 3 and zscore >= -3:
#print s, cat, RT, zscore, incorrect
d[cat].append(RT)
key = d.keys()
key.sort()
string = ""
for k in key:
print k
if d[k]:
avg = stats.mean(d[k])
std = stats.samplestdev(d[k])
else:
avg = "NA"
std = "NA"
string = string + "," + str(avg) + "," + str(std)
f.write(string)
f.write("," + str(percCorrect) + "\n")
f.close()
def writeByCategory(db, table):
f = open("%s_by_category.txt" % table, "w")
subList = db.getSubjects(table)
for subject in subList:
sex = db.getSex(subject, table)
if sex == "male":
se = 2
elif sex == "female":
se = 1
f.write(str(subject) + "," + str(se) + ",")
total = db.query("SELECT COUNT(*) FROM %s WHERE subject = %s" %
(table, subject))[0][0]
correct = db.query("SELECT SUM(incorrect) FROM %s WHERE subject = %s" %
(table, subject))[0][0]
if correct:
percCorrect = float(correct) / float(total) * 100.0
else:
percCorrect = 0.0
sql = "SELECT category, RT, zscore, incorrect FROM %s WHERE subject = %s" % (
table, subject)
d = {}
for cat, RT, zscore, incorrect in db.query(sql):
if d.has_key(cat):
pass
else:
d[cat] = []
if incorrect == 0 and zscore <= 3 and zscore >= -3:
#print s, cat, RT, zscore, incorrect
d[cat].append(RT)
key = d.keys()
key.sort()
string = ""
for k in key:
print k
if d[k]:
avg = stats.mean(d[k])
std = stats.samplestdev(d[k])
else:
avg = "NA"
std = "NA"
string = string + "," + str(avg) + "," + str(std)
f.write(string)
f.write("," + str(percCorrect) + "\n")
f.close()
def calculateZ(db, table):
subList = db.getSubjects(table)
for s in subList:
d = {}
sql = "SELECT ROWID, RT, incorrect FROM %s WHERE subject = %s" % (table, s)
for rowid, RT, incorrect in db.query(sql):
if not incorrect:
d[str(rowid)] = RT
avg = stats.mean(d.values())
std = stats.samplestdev(d.values())
for rowid in d.keys():
z = d[rowid] - avg / std
sql = "UPDATE %s SET zscore = %f WHERE ROWID = %s" % (table, z, rowid)
db.query(sql)
def calculateZ(db, table):
subList = db.getSubjects(table)
for s in subList:
d = {}
sql = "SELECT ROWID, RT, incorrect FROM %s WHERE subject = %s" % (
table, s)
for rowid, RT, incorrect in db.query(sql):
if not incorrect:
d[str(rowid)] = RT
avg = stats.mean(d.values())
std = stats.samplestdev(d.values())
for rowid in d.keys():
z = d[rowid] - avg / std
sql = "UPDATE %s SET zscore = %f WHERE ROWID = %s" % (table, z,
rowid)
db.query(sql)
def make_subtrees_stddev(graph, ratio, distance, relabel=1, lab="cluster."):
import stats
cur_label = 0
remove = []
i = 0
for edge in graph.get_edges():
lengths = []
path = {}
#print node().get_main_id(), edge.cost
get_lengths(edge.from_node, distance, lengths, 0, path)
lengths.remove(edge.cost)
#print lengths
if not (len(lengths) > 1):
continue
mean = stats.mean(lengths)
stdev2 = stats.samplestdev([mean, edge.cost])
#print mean, stdev2, edge.cost, len(lengths)
if stdev2 > ratio:
#graph.remove_edge(edge)
remove.append(edge)
for edge in remove:
graph.remove_edge(edge)
if relabel:
cur_label = 0
for node in graph.get_nodes():
node().classify_manual("")
for node in graph.get_nodes():
if node().get_main_id() == "":
label(graph, node, lab, cur_label)
cur_label += 1
nodes = []
for node in graph.get_nodes():
nodes.append(node())
return nodes
print('relfreq:')
print(stats.relfreq(l))
print(stats.relfreq(lf))
print(stats.relfreq(a))
print(stats.relfreq(af))
print('\nVARIATION')
print('obrientransform:')
l = range(1,21)
a = N.array(l)
ll = [l]*5
aa = N.array(ll)
print(stats.obrientransform(l,l,l,l,l))
print(stats.obrientransform(a,a,a,a,a))
print('samplevar:',stats.samplevar(l),stats.samplevar(a))
print('samplestdev:',stats.samplestdev(l),stats.samplestdev(a))
print('var:',stats.var(l),stats.var(a))
print('stdev:',stats.stdev(l),stats.stdev(a))
print('sterr:',stats.sterr(l),stats.sterr(a))
print('sem:',stats.sem(l),stats.sem(a))
print('z:',stats.z(l,4),stats.z(a,4))
print('zs:')
print(stats.zs(l))
print(stats.zs(a))
print('\nTRIMMING')
print('trimboth:')
print(stats.trimboth(l,.2))
print(stats.trimboth(lf,.2))
print(stats.trimboth(a,.2))
print(stats.trimboth(af,.2))
print('trim1:')
