def _summary_table(labels, data, names=None, datafile=None, infofile=None):
"""
Summarize multiple parameters in a table.
:returns: Table of summary statistics for particular parameters
:rtype: string
"""
# Summarize all parameters by default
if names is None:
names = labels.values()
# Make a string describing credible interval
beta_percent = 100. * (1. - default("alpha")[1])
credible_name = "%.2g%% credible region" % beta_percent
# Headings for a table
headings = ["Name",
"best-fit",
"posterior mean",
credible_name,
""
]
param_table = pt(headings)
param_table.align = "l"
param_table.float_format = "4.2"
# Make summary data and add it to table
posterior = data[0]
chi_sq = data[1]
for key, name in labels.iteritems():
if name in names:
param = data[key]
param_table.add_row(_summary(name, param, posterior, chi_sq))
# Best-fit information and information about chain
min_chi_sq = data[1].min()
p_value = stats.p_value(data[1], default("dof"))
bestfit_table = pt(header=False)
bestfit_table.align = "l"
bestfit_table.float_format = "4.2"
bestfit_table.add_row(["File", datafile])
bestfit_table.add_row(["Info-file", infofile])
bestfit_table.add_row(["Minimum chi-squared", min_chi_sq])
bestfit_table.add_row(["p-value", p_value])
return bestfit_table.get_string() + "\n\n" + param_table.get_string()
def sta():
with open('data.json','r+') as f:
x = f.readlines()
l = re.findall(r'["]([0-9]*[\.]*[0-9]+)%["]',str(x))
print len(l),'data is valid for statistic.\n'
counter_0 = 0
counter_1 = 0
counter_2 = 0
counter_3 = 0
counter_4 = 0
for i in range(0,len(l)):
if float(l[i])<10:
counter_0 = counter_0 + 1
if float(l[i])>=10 and float(l[i])<25:
counter_1 = counter_1 + 1
if float(l[i])>=25 and float(l[i])<40:
counter_2 = counter_2 + 1
if float(l[i])>=40 and float(l[i])<55:
counter_3 = counter_3 + 1
if float(l[i])>55:
counter_4 = counter_4 + 1
tb = pt(["COVERAGE RANGE","COUNT","PERCENTAGE",])
tb.align["COUNT"] = "r"
tb.add_row(["x<10",counter_0,float(counter_0/len(l)*100)])
tb.add_row(["10<=x<25",counter_1,float(counter_1/len(l)*100)])
tb.add_row(["25<=x<40",counter_2,float(counter_2/len(l)*100)])
tb.add_row(["40<=x<55",counter_3,float(counter_3/len(l)*100)])
tb.add_row(["x>55",counter_4,float(counter_4/len(l)*100)])
print tb
def Euler ():
TbE = pt()
TbE.field_names = ["№", "x", "y", "y'=f(x,y)", "Delta(y)=y'h"]
gotoxy(40, 2)
SetColor(5, 15)
print ('Задача: решить данное ДУ методом Эйлера')
SetColor(0, 15)
Form = Formula()
x, y = CheckErrorFormula (Form)
gotoxy(2, 7)
print ('Введите шаг итерации h:')
h = Enter_float (0, 2, '', 26, 7)
gotoxy(2, 8)
print ('Введите количество итераций:')
k = Enter_int (1, 10, '', 31, 8)
gotoxy(2, 9)
SetColor(5, 15)
print ('Решение будет производится на интервале [',x,', ',h*k+x,']')
gotoxy(2, 10)
print ('y(',h*k+x,') = ?\n')
SetColor(0, 15)
for i in range (k+1): #Цикл вычисления ДУ методом Эйлера
fxy = eval (Form)
dy = fxy*h
TbE.add_row ([i, "%.2f" %x, "%.2f" %y, "%.5f" %fxy, "%.5f" %dy])
y += dy
x += h
print (TbE)
def show_movie_projections(self, *args):
'''
show_movie_projections <movie_id> [<date>]
- print all projections of a given movie for the given date (date is optional).
'''
# print(args)
tbl_headers = ['Projection_ifno']
tbl = pt(tbl_headers)
tbl.align['Projection_ifno'] = 'l'
cur = self.con.cursor()
movie_id_sql = '''SELECT m.name, "["||p.id||"] - "||p.date||" "||
p.time||" ("||p.type||")" as p_info from movies m left join
projections p on (m.id = p.movie_id) where m.id=?'''
movie_and_date_sql = '''SELECT m.name, p.date, "["||p.id||"] - "||
p.time||" ("||p.type||")" as p_info from movies m left join
projections p on (m.id = p.movie_id) where m.id=? and p.date =?'''
try:
if len(args[0]) == 1:
cur.execute(movie_id_sql, (int(args[0][0]), ))
result = cur.fetchall()
for i in result:
tbl.add_row([i[1], ])
return "\nProjections for movie '{}':\n".format(result[0][0]) + str(tbl)
else:
cur.execute(movie_and_date_sql, (int(args[0][0]), args[0][1]))
result = cur.fetchall()
for i in result:
tbl.add_row([i[2], ])
return "\nProjections for movie '{}' on date {}:\n".format(
result[0][0], result[0][1]) + str(tbl)
except (IndexError, KeyError, ValueError):
return '''
def main():
URL = "http://mail-archives.apache.org/mod_mbox/"
try:
fh=open('items.json')
except:
print "Generate items.json file first"
foobar=json.loads(fh.read())
for item in foobar:
if 'project' in item.keys():
print item['project'][0].upper()
for list in item['list']:
print list
if 'ml' in item.keys():
x = pt(["Date","# Messages"," URL ", " Size"])
print item['ml']
for dt in item['datatime']:
date = dt[0].split(' ')[0]
url_mbox = URL + item['ml'] + date.split('-')[0] + date.split('-')[1] + ".mbox"
ml_open = urllib.urlopen(url_mbox)
meta = ml_open.info()
ml_size = meta.getheaders("Content-Length")[0]
x.add_row([date,dt[1], url_mbox, ml_size])
print x
def print_words(table):
'''print words table using pretty table'''
x = pt(['word', 'translation'])
for line in table:
x.add_row(line)
print(x)
def ImprovedEuler ():
TbImE = pt()
TbImE.field_names = ["№", "x", "y", "f(x,y)", "x+h/2", "y+h/2*f(x,y)", "f(x+h/2, y+h/2*f(x,y))", "Delta(y)=f(x+h/2, y+h/2*f(x,y))*h"]
gotoxy(35, 2)
SetColor(5, 15)
print ('Задача: решить данное ДУ усовершенствованным методом Эйлера')
SetColor(0, 15)
Form = Formula()
x, y = CheckErrorFormula (Form)
gotoxy(2, 7)
print ('Введите шаг итерации h:')
h = Enter_float (0, 2, '', 26, 7)
t = len(str(h)) - str(h).index('.') - 1
Flag = False
gotoxy(2, 8)
print ('Введите X конечное:')
while Flag == False: #Цикл проверки правильности вода x конечного
ShowCursor(True) #и расчёта количества итераций
k = Enter_float (x+h-0.0001, 20, '', 22, 8)
sizecicle = (k - x) / h
if round(k - h * round(sizecicle), t) == x: #Условие проверки правильности вода x конечного
Flag = True
else:
ShowCursor(False)
gotoxy(22, 8)
print ('\t\t\t\t\t\t\t\t\t\t\t\t\t\t')
gotoxy(33, 20)
SetColor(4, 15)
print ('Ошибка!!! Введите X конечное, соответствующее шагу итерации!')
sleep(4)
SetColor(0, 15)
gotoxy(33, 20)
print ('\t\t\t\t\t\t\t\t\t')
gotoxy(2, 9)
SetColor(5, 15)
print ('Решение будет производится на интервале [',x,',',k,']')
gotoxy(2, 10)
print ('y(',k,') = ?\n')
SetColor(0, 15)
for i in range (round(sizecicle)+1): #Цикл вычисления ДУ усовершенствованным
chx = x #методом Эйлера
chy = y
fxy = eval (Form)
x = x+h*0.5
y = y+h*0.5*fxy
xh = x
yh = y
fxhyh = eval (Form)
x = chx
y = chy
dy = fxhyh*h
TbImE.add_row ([i, round(x, t), round(y, t),"%.5f" %fxy, "%.5f" %xh, "%.5f" %yh, "%.5f" %fxhyh, "%.5f" %dy])
y += dy
x += h
print (TbImE)
def help(self):
table = pt(['Command', 'Format'])
table.add_row(["show_movies", 'List of Movies'])
table.add_row(["show_movie_projections", "show_movie_projections <movie_id> [<date>]"])
table.add_row(["make_reservation", 'Interactive input'])
table.add_row(["show_tickets", 'Interactive input <projection_id>'])
table.add_row(["quit", ""])
return table
def show_movies(self):
sql = "SELECT * FROM MOVIES ORDER BY `rating` DESC;"
self.cur.execute(sql)
table = pt(["N:", "Title", "Rating"])
for movie in self.cur.fetchall():
table.add_row([movie['id'], movie['name'], movie['rating']])
table.sortby = "N:"
return table
def __init__(self, rounds):
x, com_rounds, human_rounds, ties, flag = pt(
), 0, 0, 0, False # My field variables
x.field_names = [
"Round number", "You played", "COM played", "Wins", "COM wins",
"Ties"
] # Yhe header for my table
self.flag, self.x, self.rounds, self.com_rounds, self.human_rounds, self.ties = flag, x, rounds, com_rounds, human_rounds, ties
def show_dic(sorted_dic):
c = 1
product_table = pt(["s.no", "Product", "Location"])
for item in sorted_dic:
#print("{}. {} {}".format(c,item[0],item[1]))
product_table.add_row([c, item[0], item[1]])
c += 1
print(product_table)
def show_table(html):
'''打印考试安排表。'''
table = pt(["课程名称", "考试时间", "考试地点", "座位号"])
for tr in bs(html).find_all('tr')[1:]:
td = tr.find_all('td')
l = [x.get_text() for x in td[1:]]
table.add_row([l[0], l[2], l[3], l[5]])
print(table.get_string(sortby="考试时间", reversesort=False))
def high_score():
print("\nHIGH SCORE")
#buka file user_score
hiscore_list = open("user_score.txt", "r")
#membaca file user_score
a = hiscore_list.read()
#mengubah isi file user_score menjadi list, disimpan di variabel a1
a1 = a.split("\n")
#menghapus isi file user_score yang mengandung spasi atau blank
a1.remove("")
#mengambil data username
a2 = [i.split("#$", 1)[0] for i in a1]
list_user = set(a2)
#mengambil data score
a3 = [i.split("#$", 1)[1] for i in a1]
#BUAT DICTIONARY
#kenapa dictionary, biar bisa memetakan score2 milik username siapa
dic = {}
#proses memetakan score2 yg ada ke username
for x, y in zip(a2, a3):
dic.setdefault(x, []).append(y)
list_user = list()
#proses mengambil data username utk dimasukkan ke list_user
for i in dic.keys():
list_user.append(i)
list_score = list()
#AMBIL DATA SOCRE DIMASUKIN KE LIST_SCORE
for i in dic.values():
for j in range(0, len(i)):
i[j] = int(i[j])
list_score.append(max(i))
#membuat tabel high score
hiscore_table = pt()
#NAMBAH KOLOM USERNAME SAMA ISI USERNAME
hiscore_table.add_column("Username", list_user)
#NAMBAH KOLOM SKOR SAMA ISI KOLOM
hiscore_table.add_column("Score", list_score)
#URUTKAN TABEL DARI SKOR PALING TINGGI
hiscore_table.sortby = "Score"
hiscore_table.reversesort = True
#TOP 10 HIGH SCORE
print(hiscore_table.get_string(start=0, end=10))
hiscore_list.close()
def __init__(self, name: str, path: str) -> None:
""" Initialization function for University class """
self.name: str = name
os.chdir(path)
# key = instructor CWID, value = respective instructor class object
self.instructors: Dict[str, Instructor] = {}
# key = student CWID, value = respective student class object
self.students: Dict[str, Student] = {}
self.p_instructors = pt()
self.p_students = pt()
# read in respective files
self.read_students("students.txt")
self.read_instructors("instructors.txt")
self.read_grades("grades.txt")
# have __init__ call pretty_print for students and instructors
self._pretty_print_students()
self._pretty_print_instructors()
def show_items(self):
self.mycursor.execute("select prod_name from product_details;")
avail_items=self.mycursor.fetchall()
c=1
product_table=pt(["s.no","Product"])
for item in avail_items:
#print("{}. {}".format(c,item[0]),end="\n")
product_table.add_row([c,item[0]])
c+=1
print(product_table)
def printStudentScore(self, info, tb_name):
print("".ljust(24) + tb_name.center(45, "*"))
tb = pt(list(info.keys()))
tb.border = False
if tb_name in "总分" or tb_name in "平均分":
tb.add_row(list(info.values()))
else:
tb.add_row([self.data["info"][str(val[1])]["姓名"] for val in info.values()]) # 先输出姓名，再输出成绩
tb.add_row([val[0] for val in info.values()])
for s in tb.get_string().splitlines(): print("".ljust(37) + s)
input("".ljust(23) + ">按任意键继续<".center(43))
def show_movie_projections(self, movie_id, date=False):
rows = self.set_movie_projections(movie_id, date)
table = pt(["Projection ID", "Title", "Type", "Date", "Time", "Saets Available"])
i = 0
for projection in rows:
table.add_row([projection['id'], projection['Title'],
projection['Type'], projection['projection_date'],
projection['projection_time'], "{} spots available".format(
(self.col * self.row)-self.available_seats(projection['id']))])
i += 1
return table
def print_tickets(self):
table = pt(["Registerd To", "Title", "Rating", "Date", "Time", "Seat Row", "Seat Col"])
for i in range(len(self.ticket["seats"])):
table.add_row([self.ticket["username"],
self.ticket["movie"]["Title"],
self.ticket["movie"]["Rating"],
self.ticket["projection_date"],
self.ticket["projection_time"],
self.ticket["seats"][i][0],
self.ticket["seats"][i][1],
])
return table
def pprint_playlist(self):
songs_tbl = pt(['Artist', 'Song', 'Length'])
songs_tbl.align['Artist'] = 'l'
songs_tbl.align['Song'] = 'l'
for i in self.playlist1:
row = [i.get_artist(), i.get_title(), i.get_length()]
songs_tbl.add_row(row)
songs_tbl.add_row(['', '', ''])
songs_tbl.add_row(['', '', ''])
songs_tbl.add_row(['', '---------------------------', '----------'])
songs_tbl.add_row(['', ' Total Playlist Length ', self.total_lenght()])
return str(songs_tbl)
def print_info():
'''print date_info table'''
new_info = list(date_info.keys())
new_info.sort()
x = pt(['Date', 'Recite words', 'Add words', 'Del words', 'Mod words'])
for key in new_info:
x.add_row([
key, date_info[key]['recite_counts'], date_info[key]['add_counts'],
date_info[key]['del_counts'], date_info[key]['mod_counts']
])
print(x)
def main(url):
html = urllib2.urlopen(url).read()
soup = bs(html)
title = soup.title.string.replace(' - YouTube','')
encoded_links = re.findall(r"\"url_encoded_fmt_stream_map\":\"(.*?)\"",html)[0]
encoded_links2 = re.findall(r"\"adaptive_fmts\":\"(.*?)\"",html)[0]
link_list = encoded_links.split(',')
ll2 = encoded_links2.split(',')
for i in ll2:
if '1920x1080' in i:
link_list.append(i)
break
fin_list = []
for i in link_list:
d = {'url':'','quality':'','type':''}
if '1920x1080' in i:
d['quality'] = '1080p'
l = i.split('\u0026')
for j in l:
dct = j.split('=')
d[dct[0]] = dct[1]
fin_list.append(d)
for i in fin_list:
while '%25' in i['url']:
i['url'] = urllib2.unquote(i['url'])
i['url'] = urllib2.unquote(i['url'])
# print fin_list
print 'Found %d videos.' % (len(fin_list))
id = 0
table = pt(["id","quality","type","size"])
for i in fin_list:
table.add_row([id,i['quality'],gettype(i['type']),prettify(getsize(i['url']))])
id += 1
print table
print 'Select any one of the above videos using id:'
a = int(raw_input())
# print fin_list[a]
print "Preparing to download the video..."
sz = getsize(fin_list[a]['url'])
size = prettify(sz)
dest = title+'.'+gettype(fin_list[a]['type'])
dl = Thread(target=download, args=[fin_list[a]['url'],dest,sz])
dl.setDaemon(True)
dl.start()
progress = 0
while progress != 100:
time.sleep(2)
progress = 100 * os.path.getsize(dest)/float(sz)
sys.stdout.write("\r [%s%s] %0.2f%% done of %s" % ("#"*int(progress/10),
"-"*(10-int(progress/10)),progress,size))
sys.stdout.flush()
dl.join()
print '\nDownload Finished.\n'
def _print_seats(self, projection_id):
sql = "SELECT * FROM Reservations WHERE projection_id = ?"
self.cur.execute(sql, (projection_id,))
seats_taken = self.cur.fetchall()
for place in seats_taken:
self.seats[place["_row"]][place["_col"]] = 'x'
t = pt([" ", "1", "2", "3", "4", "5", "6", "7", "8", "9", "10"])
i = 1
for x in self.seats:
t.add_row([i]+x)
i += 1
return t
def cellChangeloca(oldLoca, newLoca, operator, date):
with open('cell_info.json', 'r') as f:
cellDic = json.load(f)
tb = pt(['Cell Name', 'Old Location', 'New Location'])
# 检查对应出库位置是否存在细胞
for i in range(len(oldLoca)):
try:
if cellDic[oldLoca[i]][0] is None:
# 确认该位置是否存在细胞
print(f'{oldLoca[i]}无细胞，请检查输入信息')
return
elif cellDic[newLoca[i]][0]:
# 确认该位置是否存在细胞
print(
f'转移后位置“{newLoca[i]}”存在细胞{cellDic[newLoca[i]][0]}，请检查输入信息')
return
else:
tb.add_row([cellDic[oldLoca[i]][0], oldLoca[i], newLoca[i]])
except KeyError as key:
# 确保保存位置的格式正确
print(f'{key}位置输入有误，请检查输入信息')
return
print(">>>>转移位置信息如下：")
print(tb)
# 确认是否执行操作
s = input(">>>请输入y确认操作，按任意键取消\n").lower()
if s == 'y':
flowInfo = []
# 细胞出库
for i in range(len(oldLoca)):
# 生成流水记录信息['细胞名称','数量','位置','操作','操作日期','操作人']
flowInfo.append([
cellDic[oldLoca[i]][0], '1', oldLoca[i], '出库', date, operator
])
flowInfo.append([
cellDic[oldLoca[i]][0], '1', newLoca[i], '入库', date, operator
])
# 细胞出入库
cellDic[newLoca[i]] = cellDic[oldLoca[i]]
cellDic[oldLoca[i]] = [None, None]
# 记录流水信息
flowRecord(flowInfo)
# 保存细胞库文件并保存一份副本
saveFile(cellDic)
print('记录完成')
else:
print("出库已取消")
def show_movies(self):
'''
print all movies ORDERED BY rating desc
'''
tbl_header = ['ID', 'Name', 'Rating']
tbl = pt(tbl_header)
tbl.align['Name'] = 'l'
tbl.align['Rating'] = 'l'
cur = self.con.cursor()
cur.execute("select * from movies order by rating desc")
for i in cur.fetchall():
tbl.add_row(i)
return "\nCurrent movies:\n" + str(tbl)
def show_movies(self):
'''
print all movies ORDERED BY rating desc
'''
tbl_header = ['ID', 'Name', 'Rating']
tbl = pt(tbl_header)
tbl.align['Name'] = 'l'
tbl.align['Rating'] = 'l'
cur = self.con.cursor()
cur.execute("select * from movies order by rating desc")
for i in cur.fetchall():
tbl.add_row(i)
return "\nCurrent movies:\n" + str(tbl)
def available_seats(self):
self.gen_seats_matrix()
tbl_headers = ['', '1', '2', '3', '4', '5', '6', '7', '8', '9', '10']
tbl = pt(tbl_headers)
tbl.align[''] = 'r'
r_seats = self.return_reserved_seats(self.reservation_projection_id)
for seat in r_seats:
self.seats_matrix[seat[0] - 1][seat[1] - 1] = 'X'
row_num = [1]
for i in self.seats_matrix:
tbl.add_row(row_num + i)
row_num[0] += 1
return str(tbl)
def available_seats(self):
self.gen_seats_matrix()
tbl_headers = ['', '1', '2', '3', '4', '5', '6', '7', '8', '9', '10']
tbl = pt(tbl_headers)
tbl.align[''] = 'r'
r_seats = self.return_reserved_seats(self.reservation_projection_id)
for seat in r_seats:
self.seats_matrix[seat[0]-1][seat[1]-1] = 'X'
row_num = [1]
for i in self.seats_matrix:
tbl.add_row(row_num + i)
row_num[0] += 1
return str(tbl)
def main():
input1 = '../data/input1.txt' #Original Test Case
input2 = '../data/input2.txt' #Extra Test Case
output1 = '../data/output1.txt' #Original Test Case
output2 = '../data/output2.txt' #Extra Test Case
correctfile1 = '../data/correct_output_1.txt' # correct output for test case 1
correctfile2 = '../data/correct_output_2.txt' # correct output for test case 2
correct_output = open(correctfile1, 'r', encoding="GBK")
check_output = open(output1, 'r', encoding="GBK")
py_input = open(input1, 'r', encoding="GBK")
score = list()
total_checks = 0
total_correct = 0
for correct, check, py in zip(correct_output, check_output, py_input):
sentence = list()
correct = correct.replace(" ", '').rstrip("\n")
check = check.replace(" ", '').rstrip("\n")
py = py.rstrip("\n")
sentence.append(str(py))
sentence.append(str(correct))
sentence.append(str(check))
total_char_py = len(correct)
total_checks += total_char_py
num_correct = 0
for a, b in zip(correct, check):
# print(a + " " + b)
if a == b:
num_correct += 1
total_correct += 1
sentence.append(str(num_correct) + "/" + str(total_score))
# print(str(num_correct)+"/"+ str(total_score))
score.append(sentence)
x = pt(["Pinyin", "Correct", "Mine", "Score"])
x.align["Correct"] = "l"
x.align["Mine"] = "l"
x.align["Score"] = "l"
x.align["Pinyin"] = "l"
x.padding_width = 1
for a in score:
x.add_row([a[0], a[1], a[2], a[3]])
with open('../src/score.txt', 'w', encoding="GBK") as score:
score.write("Reading from " + input2 + "and compare to " +
correctfile2 + "\n")
score.write(str(x))
score.write("\nTotal Percentage Correct " +
str(total_correct / total_checks))
def enter(self):
print("\nThis is the total customers we've had in each store")
cursor = db.cursor()
sqlcommand =("SELECT Count(CUST_ID) as TotalCustomers, STORE FROM TRANSACT GROUP BY STORE ORDER BY TotalCustomers DESC;")
cursor.execute(sqlcommand)
col_names = [cn[0] for cn in cursor.description]
rows = cursor.fetchall()
y1 = pt()
y1.padding_width = 1
y1.add_column(col_names[0],[row[0] for row in rows])
y1.add_column(col_names[1],[row[1] for row in rows])
print(y1)
return 'central'
def printStudentInfoLine(self, suid, flag=False):
table = pt(lt)
table.align[lt[1]] = "l"
row = [suid] + list(self.data["info"][suid].values()) + list(self.data["score"][suid].values()) + \
[self.data["tot_score"][suid]]
table.add_row(row)
# 去掉边框，因为边框存在布局错误，再转换为字符串逐行对齐输出
table.border = False
# 通过多次调用逐行打印学生成绩达到打印整个表的效果，但是只能输出一次表头
for s in table.get_string().splitlines():
if flag: # 如果执行的是打印整个表，则不会打印表头
flag = not flag
continue
print("".ljust(19) + s)
def enter(self):
print("\nOkay, you want to know how many customers spent more than $500")
cursor = db.cursor()
sqlcommand =("SELECT COUNT(CUST_ID) as TotalCustomers, TRAN_DATE as TransactionDate FROM TRANSACT WHERE TRAN_AMT > 500 GROUP BY TRAN_DATE ORDER BY TRAN_DATE desc")
cursor.execute(sqlcommand)
col_names = [cn[0] for cn in cursor.description]
rows = cursor.fetchall()
y1 = pt()
y1.padding_width = 1
y1.add_column(col_names[0],[row[0] for row in rows])
y1.add_column(col_names[1],[row[1] for row in rows])
print(y1)
return 'central'
def printvtable(data):
"""Generate a prettytable for output data. Table is generated
vertically. Each row only consists of 2 columns and there is no
"field data". Data should be passed as a list of tuples. The tuples
represent each row."""
fields = ["0", "1"]
table = pt()
table.field_names = fields
table.align = "l"
table.padding_width = 1
table.header = False
for row in data:
table.add_row(row)
print table
def printhtable(fields, data, sort=None):
"""Generate a prettytable for output data. Table is generated
horizontally, much like mysql tables. Fields must be a list and
data must be a list with the rows as tuples."""
table = pt()
table.field_names = fields
if sort != None:
table.sortby = fields[int(sort)]
else:
table.sortby = fields[0]
table.align = "c"
table.padding_width = 1
for row in data:
table.add_row(row)
print table
def learn_s(self):
data_student = pickle.load(open('%s/student.db' % settings.DB_DIR, 'rb'))
data_course = pickle.load(open('%s/course.db' % settings.DB_DIR, 'rb'))
filed = ['课程ID', '课程名', '课时费用', '主讲']
print_out = pt(filed)
print_out.align['课程ID'] = '1'
print_out.padding_width = 1
for i in data_student.keys():
print_out.add_row([i, data_student[i][0], data_student[i][1], data_student[i][2]])
print(print_out)
while True:
choose_input = input('请选择要学习的课程：').strip()
if choose_input not in data_student:
print("选择无效！")
else:
print(data_course[choose_input][3])
break
def choose(user_ID):
data_student = pickle.load(open('%s/student.db' % settings.DB_DIR, 'rb'))
data_course = pickle.load(open('%s/course.db' % settings.DB_DIR, 'rb'))
filed = ['课程ID', '课程名', '课时费用', '主讲']
print_out = pt(filed)
print_out.align['课程ID'] = '1'
print_out.padding_width = 1
for i in data_course.keys():
print_out.add_row([i, data_course[i][0], data_course[i][1], data_course[i][2]])
print(print_out)
choose = input('请选择：').strip()
if choose not in data_course.keys():
print("选择无效！")
else:
if choose not in data_student:
data = pickle.load(open('%s/student.db' % settings.DB_DIR, 'rb'))
data[user_ID] = [choose, data[choose][0], data[choose][1], data[choose][2]]
pickle.dump(data, open('%s/student.db' % settings.DB_DIR, 'wb'))
print('选课成功！')
else:
print("该课程已添加！")
def show_movie_projections_and_seats(self, movie_id):
tbl_headers = ['Projection info']
tbl = pt(tbl_headers)
tbl.align['Projection info'] = 'l'
cur = self.con.cursor()
sql = '''SELECT m.name, "["||p.id||"] - "||p.date||" "||
p.time||" ("||p.type||")"||" - "||(100 - COUNT(R.PROJECTION_ID))||
' available seats' as p_info
from movies m
left join projections p
on (m.id = p.movie_id)
left join reservations r
on (p.id = r.projection_id)
group by m.name, p.id, p.date, p.time, r.projection_id
having m.id = ?'''
cur.execute(sql, (movie_id, ))
result = cur.fetchall()
for i in result:
tbl.add_row([i[1]])
return "\nProjections for movie '{}':\n".format(
result[0][0]) + str(tbl)
def problem_10():
"""
This function provides the solution to problem 10. We use the 4 data
sets from problem 5 to generate moments regarding data filtered with
an HP filter, BK filter, and first-difference filter.
Inputs:
None
Outputs:
the_tables: This is the tables containing mean, standard deviation,
autocorrelation, and correlation with GDP for the
following filters for each data set:
HP(1600)
BK(16, 6, 32)
first difference.
"""
# Generate GDP filtered data
first_diff_gdp = gdp[1:] - gdp[:-1]
hp_gdp = hp.hp_filter(gdp)[1]
bp_gdp = bpf.bandpass_filter(gdp, 16, 6, 32)[16:-16]
all_gdp = np.array([first_diff_gdp, hp_gdp, bp_gdp])
# Generate cpi filtered data
first_diff_cpi = cpi[1:] - cpi[:-1]
hp_cpi = hp.hp_filter(cpi)[1]
bp_cpi = bpf.bandpass_filter(cpi, 16, 6, 32)[16:-16]
all_cpi = np.array([first_diff_cpi, hp_cpi, bp_cpi])
# Generate consumption filtered data
first_diff_cons = cons[1:] - cons[:-1]
hp_cons = hp.hp_filter(cons)[1]
bp_cons = bpf.bandpass_filter(cons, 16, 6, 32)[16:-16]
all_cons = np.array([first_diff_cons, hp_cons, bp_cons])
# Generate investment filtered data
first_diff_inv = inv[1:] - inv[:-1]
hp_inv = hp.hp_filter(inv)[1]
bp_inv = bpf.bandpass_filter(inv, 16, 6, 32)[16:-16]
all_inv = np.array([first_diff_inv, hp_inv, bp_inv])
all_data = np.vstack([all_gdp, all_cpi, all_cons, all_inv])
all_tables = np.empty((4, 4, 3))
data_titles = ['GDP', "CPI", 'Consumption', 'Investment']
filter_labels = ['First Diff', 'HP', 'BP']
for data_set in range(all_data.shape[0]):
plt.figure()
for filt in range(all_data.shape[1]):
plt.plot(
range(all_data[data_set, filt].size),
all_data[data_set,filt],
label = filter_labels[filt])
plt.title(data_titles[data_set])
plt.legend(loc=0)
plt.show()
for data_set in range(all_data.shape[0]):
for i in range(all_data.shape[1]):
all_tables[data_set, 0, i] = np.mean(all_data[data_set, i])
all_tables[data_set, 1, i] = np.std(all_data[data_set, i])
all_tables[data_set, 2, i] = np.corrcoef(all_data[data_set, i][:-1],
all_data[data_set, i][1:])[0,1]
all_tables[data_set, 3, i] = np.corrcoef(all_data[data_set, i],
all_data[0, i])[0,1]
titles = ['Parameters [GDP]', 'Parameters [CPI]',
'Parameters [cons]', 'Parameters [inv]']
col_names = ['First Diff', 'HP (1600)', 'BK (16)']
params = ['Mean', 'Std', 'Autocorrelation', 'Corr w/GDP']
pretty_gdp = pt()
pretty_cpi = pt()
pretty_cons = pt()
pretty_inv = pt()
pretty_all = [pretty_gdp, pretty_cpi, pretty_cons, pretty_inv]
for tab in range(4):
pretty_all[tab].add_column(titles[tab], params)
for col in range(3):
pretty_all[tab].add_column(col_names[col], all_tables[tab, :, col])
print pretty_all[tab]
return pretty_all
#!/usr/bin/env python3
import numpy as np
from datetime import datetime, timedelta, date
from prettytable import PrettyTable as pt
import sys
import random
import math
import itertools
# Output and date format
#===============================================================================
table = pt(['Being', 'Birth', 'Death', 'Died at'])
table.align['Being'] = 'l'
def formDate(t):
strFmt = '{year:4}-{month:02}-{day:02}'
return strFmt.format(year=t.year, month=t.month, day=t.day)
# Being list
#===============================================================================
beings = [
# weight , being , mean , stdDev
[ 1910 , 'worm' , 2000 , 150],
[ 1110 , 'crab' , 1460 , 530],
[ 9999 , 'insect' , 28 , 300],
[ 490 , 'snail' , 4380 , 300],
[ 1910 , 'fish' , 1700 , 700],
[ 4610 , 'marineInv' , 800 , 910],
def main():
tt = pt(["Bin", "ID", "Text"])
tt.align["Bin"]
tt.padding_with = 1
p = optparse.OptionParser()
p.add_option('--duration', '-d', default = 300)
p.add_option('--binsize', '-b', default = 1)
p.add_option('--query', '-q', default = 'i am groot')
options, arguments = p.parse_args()
pp = partial(json.dumps, indent = 1)
q = options.query #query phrase
start_time = str(datetime.datetime.now())[:-7]
ttf = open("tweet-table" + " " + q +".txt", 'w')
f.write(start_time+"/"+start_time + "\n")
def oauth_login():
CONSUMER_KEY = ''
CONSUMER_SECRET =''
OAUTH_TOKEN = '-'
OAUTH_TOKEN_SECRET = ''
auth = twitter.oauth.OAuth(OAUTH_TOKEN, OAUTH_TOKEN_SECRET, CONSUMER_KEY, CONSUMER_SECRET)
twitter_api = twitter.Twitter(auth=auth)
return twitter_api
""" ---- DO THINGS ---- """
print >> sys.stderr, 'Filtering the public timeline for track="%s"' % (q,)
twitter_api = oauth_login()
print twitter_api
twitter_stream = twitter.TwitterStream(auth=twitter_api.auth)
stream = twitter_stream.statuses.filter(track=q)
#CHANGE NEEDED VARIABLES HERE
c = 0
tc = 0
alpha = 0.3
s_s = []
s_x = []
s_times = {}
s_raw = {}
gr = []
abs_tc = 0
sfreq = [0]
freq = []
#change these two values to choose how long the program shall run, and also how large each bin will be
lim = options.duration
timeframe = options.binsize
def find_smooth(c, depth = 0): #not called when c is 0
global sfreq
global freq
global alpha
if c == 0:
return sfreq[0]
elif not c == 0 and depth > 500:
return sfreq[c-501]
else:
return alpha * freq[c-1] + (1-alpha) * find_smooth(c-1, depth + 1)
g = open("raw-tweets.txt", 'w')
z = open("ema-tweet-freq.txt", 'w')
rawh = open("raw_freq.txt", 'w')
dt_i = int(time.time())
dt_t = str(datetime.datetime.now())[:-7]
for tweet in stream:
abs_tc += 1
#print "tweet"
dt = int(time.time()) - dt_i #current time
#print "current time: " + str(dt) + "\n"
try:
g.write(str(dt) + " " + tweet['text'].encode('ascii', 'ignore') + "\n")
except:
g.write("UNSUPPORTED TEXT \n")
try:
zz = s_times[(dt//timeframe)]
zz = s_times[(dt//timeframe)]
except KeyError:
s_times[(dt//timeframe)] = []
s_raw[(dt//timeframe)] = 0
try:
s_times[(dt//timeframe)].append(tweet['text'].encode('ascii', 'ignore'))
except:
s_times[(dt//timeframe)].append("nope")
s_raw[(dt//timeframe)] += 1
try:
tt.add_row([str(dt//timeframe), tweet['id'], tweet['text'].encode('ascii', 'ignore')])
except KeyError:
pass
try:
dt == prev #is this tweet the same bin as the previous one?
except NameError: #only happens for 1st tweet
prev = dt
continue
if dt == prev: #if same bin
# print "dt is " + str(dt)
# print "prev is " + str(prev) + "\n"
tc += 1 #increase number in bin
else: #if not same bin
c += 1
tc = 0
prev = dt
if dt >= lim:
ttf.write(str(tt))
print pp(s_raw)
for a in s_raw:
rawh.write(str(s_raw[a]) + "\n")
_maxa = 0
#print "smoothed : " + str(s_s)
for a in xrange(_maxa):
if a not in [b for b in iter(s_raw)]:
freq.append(0)
else:
freq.append(s_raw[a])
print pp(freq)
print "length of freq is: " + str(len(freq)) + "\n"
for a in xrange(len(freq)):
if a == 0:
sfreq.append(0)
else:
print "smoothing " + str(freq[a])
sfreq.append(find_smooth(a))
z.write(pp(sfreq))
print pp(sfreq)
print "processed " + str(abs_tc) + " tweets"
plt.plot([a for a in s_times], [len(s_times[a]) for a in s_times], '-r')
plt.plot([a for a in xrange(len(sfreq))], [a for a in sfreq], '-b')
plt.plot([a for a in xrange(len(sfreq))], [a for a in sfreq], '+')
plt.title(q + ' ' + dt_t)
plt.xlabel("Time frame of " + str(timeframe) + " second(s)")
plt.ylabel("Bin size")
plt.draw()
fig1 = plt.gcf()
fig1.savefig("plot" + ".svg")
break
# <codecell> cpi_table # <codecell> cons_table # <codecell> inv_table # <codecell> gtab = pt() # <codecell> all_tables = np.array([gdp_table, cpi_table, cons_table, inv_table]) # <codecell> blank_tables = np.zeros((4,4,3)) # <codecell> # <codecell>