def table(self):
"""総理大臣のCSVファイルを基にしたテーブルから、HTMLページを基にするテーブルに変換して、それを応答する。"""
html_table = table.Table('output')
html_at = html_table.attributes()
tuples = self._input_table.tuples()
is_first = True
for a_tuple in tuples:
if is_first:
is_first = False
else:
values = a_tuple.values()
keys = a_tuple.attributes().keys()
attributes = a_tuple.attributes()
output = []
output.append(values[keys.index('no')])
output.append(values[keys.index('order')])
output.append(values[keys.index('_names')])
output.append(values[keys.index('kana')])
output.append(values[keys.index('period')])
output.append(self.compute_string_of_days(values[keys.index('period')]))
output.append(values[keys.index('school')])
output.append(values[keys.index('party')])
output.append(values[keys.index('birth')])
output.append(self.compute_string_of_image(a_tuple))
output_tuple = tuple.Tuple(html_at, output)
self._output_table.add(output_tuple)
return self._output_table
def table(self):
"""総理大臣のCSVファイルを基にしたテーブルから、HTMLページを基にするテーブルに変換して、それを応答する。"""
html_table = []
attributes = self._input_table.attributes()
keys = attributes.keys()
tuples = self._input_table.tuples()
values = []
for index, a_tuple in enumerate(tuples):
values = a_tuple.values()
html_table.append([])
html_table[index].append(values[keys.index("no")])
html_table[index].append(values[keys.index("order")])
html_table[index].append(values[keys.index("names")])
html_table[index].append(values[keys.index("kana")])
html_table[index].append(values[keys.index("period")])
html_table[index].append(
self.compute_string_of_days(values[keys.index("period")]))
html_table[index].append(values[keys.index("school")])
html_table[index].append(values[keys.index("party")])
html_table[index].append(values[keys.index("birth")])
html_table[index].append(self.compute_string_of_image(a_tuple))
for row in html_table:
self._output_table.add(
tuple.Tuple(self._output_table.attributes(), row))
return self._output_table
def table(self):
"""ダウンロードしたCSVファイルを読み込んでテーブルを応答する。"""
reader_list = io.IO().read_csv(self.csv_filename)
input_table = table.Table('input')
for a_list in reader_list:
a_tuple = tuple.Tuple(input_table.attributes(), a_list)
input_table.add(a_tuple)
return input_table
def table(self):
"""ダウンロードしたCSVファイルを読み込んでテーブルを応答する。"""
print "[Reader]tableの起動を確認"
csv_table = table.Table('input')
print "[Reader]ファイルネーム確認", self._csv_name
#継承の確認
#test = super(Reader,self).test()
#print test
reader = super(Reader, self).read_csv(self._csv_name)
#print reader
for row in reader:
csv_table.add(tuple.Tuple(csv_table.attributes(), row))
#print row
return csv_table
if not (int(row[0]) == year and int(row[1]) == month):
continue
if int(str(row[3])[14:16]) != 0:
continue
if not support.double_contains(row[8], dict["nations"]):
continue
if "CA" in row[7]:
continue
current_date = datetime(int(row[0]), int(row[1]),
int(row[2]))
current_tuple = tuple.Tuple()
current_tuple.nation = row[8]
current_tuple.year = year
current_tuple.day_in_year = current_date.timetuple(
).tm_yday
current_tuple.hour = int(str(row[3])[11:13])
current_tuple.holiday = support.is_business_day(
current_date, current_tuple.nation)
current_tuple.date = current_date
# checking if tuple's day already encountered
found = False
for value in tuples:
if value == current_tuple:
current_tuple = value
found = True
break
else:
print("Usage: %s -m minPts -e eps" % sys.argv[0])
print(minPts)
print(eps)
'''
Read data
'''
data = []
file = open("./compound.txt", "r")
#i =0
for line in file:
temp = line.split('\t')
temp = list(map(float, temp))
temp.pop()
data.append(tuple.Tuple(temp))
#i+=1
#if i==5000: break
file.close()
'''
Dbscan
'''
print("start dbscan")
dbscan = db.Dbscan(data,minPts,eps)
clusters = dbscan.perform()
print("start drawing")
i = 0
print("Liczba klastrow = " + str(len(clusters)))
i += 1
file.close()
means = data.mean(0)
sd = []
for a in range(num_of_atributes):
temp = 0
for r in range(num_of_records):
temp += (data[r][a] - means[a])**2
sd.append(math.sqrt(temp / num_of_records))
for r in range(num_of_records):
for a in range(num_of_atributes):
data[r][a] = (data[r][a] - means[a]) / sd[a]
data_set = []
for r in range(num_of_records):
data_set.append(tuple.Tuple(data[r]))
print(data_set[0].values)
dbscan = db.Dbscan(data_set, minPts, eps)
clusters = dbscan.perform()
color = [
'ro', 'go', 'bo', 'co', 'mo', 'yo', 'ko', 'wo', 'rs', 'gs', 'bs', 'cs',
'ms', 'ys', 'ks', 'ws', 'r^', 'g^', 'b^', 'c^', 'm^', 'y^', 'k^', 'w^',
'r*', 'g*', 'b*', 'c*', 'm*', 'y*', 'k*', 'w*'
]
i = 0
print("Liczba klastrow = " + str(len(clusters)))
for c in clusters:
x = []
y = []