def on_get(self, req, resp, project, ident):
query = build_query(req.env, project)
if 'version' in req.params:
version = req.params['version']
else:
raise falcon.HTTPMissingParam('version')
if version == 'latest':
version = query('latest')
if 'family' in req.params:
family = req.params['family']
else:
family = 'C'
if family == 'B': #DT compatible strings are quoted in the database
ident = parse.quote(ident)
symbol_definitions, symbol_references, symbol_doccomments = query(
'ident', version, ident, family)
resp.body = json.dumps({
'definitions': [sym.__dict__ for sym in symbol_definitions],
'references': [sym.__dict__ for sym in symbol_references],
'documentations': [sym.__dict__ for sym in symbol_doccomments]
})
resp.status = falcon.HTTP_200
def eng_response(message_text, sender_id, recipient_id, comment_id):
#message_text = normalization_redis.eng_word_correction(message_text)
print("Inside Response Generator")
query(update_query_normalization, (message_text, comment_id))
try:
api_response = api_ai_query(message_text, comment_id)
except:
send_message(sender_id, comment_id, "There was an error with fetching \
the response from the AI")
return Response(status=200)
return api_response
def fb_msg_parse(data):
for entry in data["entry"]:
for messaging_event in entry["messaging"]:
try:
message_text = messaging_event["message"]["text"]
except Exception as e:
message_text = 'NEW'
sender_id = messaging_event["sender"]["id"]
recipient_id = messaging_event["recipient"]["id"]
comment_id = messaging_event["message"]["mid"]
timestamp = get_timestamp(messaging_event['timestamp'])
query(insert_query,(0,0,0,timestamp,sender_id,comment_id,\
message_text,'','',''))
logging.info("facebook message inserted in db")
return sender_id, recipient_id, comment_id, message_text
def without_select():
layer = iface.activeLayer()
q = (query(layer).where(qstring).where(qstring2).top(top))
results = q()
out = results.next()
assert isinstance(out, dict)
print out
def search():
frase = request.form["palabra"]
st = time.time()
lista_result = query(frase)
et = time.time()
return render_template("result.html", lista=lista_result, tiempo=et - st)
def call_query(query, *args):
cwd = os.getcwd()
os.chdir(ELIXIR_DIR)
ret = query(*args)
os.chdir(cwd)
return ret
def without_select():
layer = iface.activeLayer()
q = query(layer).where(qstring).where(qstring2).top(top)
results = q()
out = results.next()
assert isinstance(out, dict)
print out
def api_ai_query(text, comment_id):
logging.info("Api AI entered")
request = ai.text_request()
request.query = text
response = json.loads(request.getresponse().read().decode('utf-8'))
responseStatus = response['status']['code']
if (responseStatus == 200):
response = response['result']['fulfillment']['speech']
query(update_query_apiai, (response, comment_id))
logging.info("api ai returning")
return response
else:
response = "Sorry, I couldn't understand that question"
query(update_query_apiai, (response, comment_id))
logging.info("api ai returning")
return response
def on_get(self, req, resp, project, ident):
query = build_query(req.env, project)
if 'version' in req.params:
version = req.params['version']
else:
raise falcon.HTTPMissingParam('version')
if version == 'latest':
version = query('latest')
symbol_definitions, symbol_references = query('ident', version, ident)
resp.body = json.dumps({
'definitions': [sym.__dict__ for sym in symbol_definitions],
'references': [sym.__dict__ for sym in symbol_references]
})
resp.status = falcon.HTTP_200
def google_translate(user_text, comment_id):
'''
this function will translate the received text using google translate
'''
translator = Translator(service_urls=['translate.google.com.pk'])
detected_lang = translator.detect(user_text).lang
if (detected_lang.find('en') != -1):
#passthrough for english
trans_input = user_text
query(update_query_translation, (trans_input, comment_id))
return trans_input
else:
mid_trans = translator.translate(user_text, src="hi", dest="ur").text
trans_input = translator.translate(mid_trans, src="ur", dest="en").text
query(update_query_translation, (trans_input, comment_id))
logging.info("TEXT Translated")
return trans_input
def monthly(start_date, end_date): tables = ['AgeGroupGender', 'MonthlyViews', 'VidSharingService'] print "Ran on: ", now con = None try: con = mdb.connect(**config.mysql_params) cur = con.cursor() videos = getVideoList() while (start_date <= end_date): for table in tables: if table == 'AgeGroupGender' or table == 'MonthlyViews': if table == 'MonthlyViews': end = start_date else: end = start_date+relativedelta(months = +1)+relativedelta(days = -1) response, columns = query(table, "", start_date, end) insert_statement = table_options[table]['insert'] for row in response: cur.execute(insert_statement, getValues(table, "", start_date, columns, row)) con.commit() else: for video in videos: end = start_date+relativedelta(months = +1)+relativedelta(days = -1) response, columns = query(table, video, start_date, end) insert_statement = table_options[table]['insert'] for row in response: cur.execute(insert_statement, getValues(table, video, start_date, columns, row)) con.commit() start_date = start_date+relativedelta(months = +1) except mdb.Error, e: print "Error %d: %s" % (e.args[0],e.args[1]) sys.exit(1)
def without():
def checkassessment(feature):
return int(feature['assessment']) <> 4315968
layer = iface.activeLayer()
q = (query(layer).where(qstring).where(qstring2).where(
checkassessment).top(100))
results = q()
for f in results:
print f['assessment'], f['postcode'], f['subdivided']
def api_ai_query(text, comment_id):
logging.info("Api AI entered")
api_endpoint = "https://api.dialogflow.com/v1/query/?v=20150910"
logging.info("API AI QUERY CALLED")
logging.info("This is the session")
logging.info(session['session_id'])
headers = {'Authorization' : 'Bearer 3a67ab4afb49424587183ae8b04bf88b',
'Content-Type' : 'application/json'}
body = {'query' : text,
'lang' : 'en',
'sessionId' : session['session_id'] }
body_json = json.dumps(body)
apiai_result = requests.post(api_endpoint, \
headers=headers, data=body_json).json()
logging.info(apiai_result)
logging.info("Dict, %s", apiai_result['result']['fulfillment']['speech'])
api_response = apiai_result['result']['fulfillment']['speech']
query(update_query_apiai, (api_response, comment_id))
return api_response
def with_select_customfunction():
def MyValue(feature):
return "Hello World"
layer = iface.activeLayer()
q = query(layer).top(1).select(MyValue)
results = q()
out = results.next()
print out
assert isinstance(out, dict)
assert "MyValue" in out.keys()
def with_select_customfunction():
def MyValue(feature):
return "Hello World"
layer = iface.activeLayer()
q = (query(layer).top(1).select(MyValue))
results = q()
out = results.next()
print out
assert isinstance(out, dict)
assert "MyValue" in out.keys()
def without():
def checkassessment(feature):
return int(feature['assessment']) <> 4315968
layer = iface.activeLayer()
q = (query(layer).where(qstring)
.where(qstring2)
.where(checkassessment)
.top(100))
results = q()
for f in results:
print f['assessment'], f['postcode'], f['subdivided']
def add_distance():
roofq = query("SELECT voorval_nr, latitude, longitude FROM Straatroven",
"sqlite:///Opendata.db")
db = create_engine('sqlite:///Opendata.db')
db.echo = True
metadata = MetaData(db)
db.connect()
Straatroof = Table('Straatroven', metadata,
Column('voorval_nr', String(20), primary_key=True),
Column('distance_pol', Float))
u = Straatroof.update()
distancearray = []
for r in roofq:
voorval_nr = r['voorval_nr']
print(voorval_nr)
rpoint = (r['latitude'], r['longitude'])
distance = None
policeq = query("SELECT latitude, longitude FROM police_stations",
"sqlite:///Opendata.db")
for p in policeq:
ppoint = (p['latitude'], p['longitude'])
if distance is None:
distance = vincenty(rpoint, ppoint).meters
elif distance > vincenty(rpoint, ppoint).meters:
distance = vincenty(rpoint, ppoint).meters
if distance > 10000:
distance = None
distancearray.append([voorval_nr, distance])
print(distancearray)
for i in distancearray:
u2 = u.where(Straatroof.c.voorval_nr == i[0]).values(distance_pol=i[1])
u2.execute()
def main():
print centered('Welcome to The Book of Mormon Reader')
print centered('Created by Chris Hagmann')
time.sleep(.3)
print '\n' * 3
book, chapter = '',''
while book not in Books:
if book in Chapter_list:
parsed = book.split()
chapter = int(parsed.pop())
book = ' '.join(parsed)
else:
book = query('In which book of The Book of Mormon would you like to read? ', response=str)
book = book.replace('First','1').replace('Second','2').replace('Third','3').replace('Fourth','4')
if bom[book] == 1:
chapter = 1
else:
while reference(book, chapter) not in Chapter_list:
chapter = query('Which chapter in {} would you like to read [Last chapter: {}]? '.format(book,bom[book]), response=int)
numofchapters = query('How many chapters do you want to read? ', default=1, response=int)
current_chapter = reference(book, chapter)
start_flag = reference(book, chapter) + '\n'
end_flag = Chapter_list[Chapter_list.index(current_chapter) + numofchapters] + '\n'
filename = ''.join(str(c) for c in book + str(chapter) + '.txt' if str(c) != ' ')
with open('BoM.txt','r') as f, open(filename,'w') as g:
line = ''
while next(f) != start_flag:
pass
while line != end_flag:
line = next(f)
if line != '\n':
if len(line) == 1:
g.write(line)
elif not any(c.isdigit() for c in line.split()[-1]):
g.write(line)
next
speed = query('How fast do you want to read in words per minute? ', default=450, response=int)
if speed < 400:
weigthed = False
else:
weighted = query('Do you want to try the weighted words feature', default='Y', response=boolean)
columnmode = query('Do you want to try the column mode', default='Y', response=boolean)
if columnmode:
columnsize = query('What size column? ', default=50, response=int)
speed_reader(filename, speed, weighted, columnmode, columnsize)
def post(self):
emaila=self.get_argument('email')
password=self.get_argument('pass1')
condition={'emaila':emaila}
getpasswd=query(condition)
returnpwd=getpasswd.query_one()
if password != returnpwd['password']:
self.redirect("/")
else:
self.request.cookies()
return True
def with_select_mapview():
layer = iface.activeLayer()
q = (query(layer).restict_to(Query.MapView()).top(top).select(
'assessment',
'address',
'lot',
geom=lambda f: f.geometry(),
mylot=lambda f: int(f['house_numb']) * 100))
results = q()
out = results.next()
assert isinstance(out, dict)
print out
def on_get(self, req, resp, project, ident):
query = build_query(req.env, project)
if 'version' in req.params:
version = req.params['version']
else:
raise falcon.HTTPMissingParam('version')
if version == 'latest':
version = query('latest')
symbol_definitions, symbol_references = query('ident', version, ident)
if len(symbol_definitions) or len(symbol_references):
resp.body = json.dumps({
'definitions': [sym.__dict__ for sym in symbol_definitions],
'references': [sym.__dict__ for sym in symbol_references]
})
resp.status = falcon.HTTP_200
else:
raise falcon.HTTPNotFound({
'title':
'Requested identifier not found in {} project'.format(project)
})
def with_select_mapview():
layer = iface.activeLayer()
q = (
query(layer)
.restict_to(Query.MapView())
.top(top)
.select("assessment", "address", "lot", geom=lambda f: f.geometry(), mylot=lambda f: int(f["house_numb"]) * 100)
)
results = q()
out = results.next()
assert isinstance(out, dict)
print out
def with_select_mapview():
def checkassessment(feature):
return int(feature['assessment']) <> 4315968
layer = iface.activeLayer()
q = (query(layer).restict_to(Query.MapView()).top(10).select(
'assessment',
'address',
'lot',
geom=lambda f: f.geometry(),
mylot=lambda f: int(f['house_numb']) * 100))
results = q()
for f in results:
print f
def with_select():
def checkassessment(feature):
return int(feature['assessment']) <> 4315968
layer = iface.activeLayer()
q = (query(layer).where(qstring).where(qstring2).where(
checkassessment).top(10).select(
'assessment',
'address',
'lot',
geom=lambda f: f.geometry(),
mylot=lambda f: int(f['house_numb']) * 100))
results = q()
for f in results:
print f
def main():
DEFAULT = query('Use default values for Indices? ', default='y', response=boolean)
S = query('Number of stores: ', **q_opts(3, int, DEFAULT))
V = query('Number of vendors: ', **q_opts(3, int, DEFAULT))
P = query('Number of basic products: ', **q_opts(3, int, DEFAULT))
Q = query('Number of fashion products: ', **q_opts(3, int, DEFAULT))
T = query('Number of time periods: ', **q_opts(7, int, DEFAULT))
DEFAULT = query('Use default values for parameters? ', default='y', response=boolean)
print
rd = instance_generator(S, V, P, Q, T, DEFAULT=DEFAULT)
if rd:
print "Instance Created!"
else:
print "Failed to create instance!"
return rd
def with_select_mapview():
def checkassessment(feature):
return int(feature['assessment']) <> 4315968
layer = iface.activeLayer()
q = (query(layer).restict_to(Query.MapView())
.top(10)
.select('assessment',
'address',
'lot',
geom = lambda f: f.geometry(),
mylot = lambda f: int(f['house_numb']) * 100)
)
results = q()
for f in results:
print f
def upload_file():
if request.method == 'POST':
# Check to see if the post request has the file part
if 'file' not in request.files:
flash('No file part')
return redirect(request.url)
file = request.files['file']
# If the user does not select a file
if file.filename == '':
flash('No selected file')
return redirect(request.url)
# If everything looks good, proceed
if file and allowed_file(file.filename):
filename = secure_filename(file.filename)
filepath = os.path.join(app.config['UPLOAD_FOLDER'], filename)
file.save(filepath)
predicted_class = predict_class(filepath)
# List of classes not used in this app
bad_list = ['straight', 'unsure','braids','dreadlocks','nonhair', 'short']
if predicted_class in bad_list:
return render_template('complete.html', predicted_class = predicted_class)
# Query the product database, return products and amazon URLS for products
prods, urls = query(predicted_class)
shampoo,conditioner,leavein,gel,deep,protein,cream,serum,clarify = prods
ushampoo,uconditioner,uleavein,ugel,udeep,uprotein,ucream,userum,uclarify = urls
# Passes hair class, products, and URLS to the second HTML page
return render_template('complete.html', predicted_class = predicted_class,
shampoo = shampoo, conditioner = conditioner,
leavein = leavein, gel = gel, deep = deep, protein = protein,
cream = cream, serum = serum, clarify = clarify, ushampoo = ushampoo,
uconditioner = uconditioner, uleavein = uleavein,ugel = ugel,
udeep = udeep, ucream = ucream, userum = userum, uprotein = uprotein,
uclarify = uclarify)
return redirect(url_for('main'))
return render_template('main.html')
def with_select():
def checkassessment(feature):
if feature['assessment'] is None:
return False
return int(feature['assessment']) == 4315968
layer = iface.activeLayer()
q = (query(layer).where("postcode = 6164").where("subdivided = 'Y'").where(
checkassessment).top(top).select(
'assessment',
'address',
'lot',
geom=lambda f: f.geometry(),
mylot=lambda f: int(f['house_numb']) * 100))
results = q()
out = results.next()
assert isinstance(out, dict)
print out
def with_select():
def checkassessment(feature):
return int(feature['assessment']) <> 4315968
layer = iface.activeLayer()
q = (query(layer).where(qstring)
.where(qstring2)
.where(checkassessment)
.top(10)
.select('assessment',
'address',
'lot',
geom = lambda f: f.geometry(),
mylot = lambda f: int(f['house_numb']) * 100)
)
results = q()
for f in results:
print f
def with_select():
def checkassessment(feature):
if feature["assessment"] is None:
return False
return int(feature["assessment"]) == 4315968
layer = iface.activeLayer()
q = (
query(layer)
.where("postcode = 6164")
.where("subdivided = 'Y'")
.where(checkassessment)
.top(top)
.select("assessment", "address", "lot", geom=lambda f: f.geometry(), mylot=lambda f: int(f["house_numb"]) * 100)
)
results = q()
out = results.next()
assert isinstance(out, dict)
print out
def main():
DEFAULT = query('Use default values for Indices? ',
default='y',
response=boolean)
S = query('Number of stores: ', **q_opts(3, int, DEFAULT))
V = query('Number of vendors: ', **q_opts(3, int, DEFAULT))
P = query('Number of basic products: ', **q_opts(3, int, DEFAULT))
Q = query('Number of fashion products: ', **q_opts(3, int, DEFAULT))
T = query('Number of time periods: ', **q_opts(7, int, DEFAULT))
DEFAULT = query('Use default values for parameters? ',
default='y',
response=boolean)
print
rd = instance_generator(S, V, P, Q, T, DEFAULT=DEFAULT)
if rd:
print "Instance Created!"
else:
print "Failed to create instance!"
return rd
def parse_xl(file_path, table_name, primary_key=None):
#f = urllib2.urlopen(file_name)
file_name = file_path.split('/')[-1]
#file_suffix = file_path.split('/')[-1]
#if file_suffix.split(".")[1] == "xls":
# file_name += "x"
f = urllib.urlretrieve(file_path, file_name)
wb = load_workbook(file_name, read_only=True)
# local files
#wb = load_workbook(file_name, read_only= True)
sheets = wb.get_sheet_names()
print(sheets)
queries = []
ws = None
types = {}
for sheet in sheets:
col_names = []
sheet_data = []
ws = wb[sheet]
i = 0
for row in ws.rows:
if i == 0:
col_names = [cell.value for cell in row]
i += 1
elif i == 1:
for j in range(len(row)):
if cell.value.isdigit():
types[col_names[j]] = 'integer'
else:
types[col_names[j]] = 'text'
i += 1
else:
row_data = [cell.value for cell in row]
sheet_data.append(row_data)
q = query(sheet, None, col_names, sheet_data, types)
queries.append(q)
f.close()
return queries
def parse_csv(file_path, table_name, primary_key=None):
# for remote files
f = urllib2.urlopen(file_path)
# for local files
#f = open(filename)
data = []
types = {}
col_names = []
try:
i = 0
col_names = []
reader = csv.reader(f.read().splitlines())
for row in reader:
if i == 0:
col_names = row
i += 1
print(col_names)
elif i == 1:
try:
for j in range(len(row)):
if row[j].isdigit():
types[col_names[j]] = 'integer'
else:
types[col_names[j]] = 'text'
data.append(row)
assert (len(row) == len(col_names))
except:
print "Data does not have equal number of column as column names"
i += 1
else:
data.append(row)
except Exception as e:
print e
#print(col_names)
f.close()
q = query(table_name, primary_key, col_names, data, types)
return q
def postsearch():
search = request.forms.get("search")
results = query(search)
Nextstep=check()
#Activate Spellchecking functionality:
#Nextstep will return a value whether it is 0 or 1.
#If it's 0, that means the input spelling is correct and also the word_id is in database
#If it's 1, that means we have already modify the input word and search the modify_id in the database, and return the new result
if Nextstep==0:
results.append(search)
output = template('format_data', rows=results)
return output
if Nextstep==1:
nword=get()
#If for both words the user input and the modify word that we fixed don't have word_id in database
#A "special" web page will be given to indicate the result is empty.
if not results:
f = open("no.html")
html = "".join(f.readlines())
return html
#otherwise, we will return the result based on the fixed word.
results.append(nword)
output = template('format_data_after_spellCheck', rows=results)
return output
def get_stocks_data(stocks_code, date):
q = query(
valuation.code, # 股票代码
# 税息前利润(EBIT) = 营业利润
income.operating_profit, # 营业利润(元) 独自代表企业业务的盈利能力 EBIT
# 净流动资本 + 净固定资产 = 资产总计 - 商誉 - 无形资产
# 投资回报率 = EBIT / (净流动资本 + 净固定资产)
balance.total_assets, # 资产总计(元)
balance.good_will, # 商誉(元)
balance.intangible_assets, # 无形资产(元)
# 企业价值 = 总市值 + 负债合计
# 收益率 = EBIT / 企业价值
valuation.market_cap, # 总市值(亿元)
balance.total_liability, # 负债合计(元)
).filter(
income.net_profit > 0,
# valuation.market_cap > 50,
valuation.code.in_(stocks_code))
data = get_fundamentals(q, date=date).fillna(value=0).set_index('code')
return data
def on_click(self):
getStart = self.lineEdit_start.text()
getEnd = self.lineEdit_end.text()
getDate = self.dateTimeEdit_start.date().getDate()
finalDate = str(getDate[0])
finalDate += '-' + str(getDate[1]).zfill(2)
finalDate += '-' + str(getDate[2]).zfill(2)
if isStationExist() == True:
station = eval(read())
if getStart != "" and getEnd != "":
if getStart in station and getEnd in station:
start = station[getStart]
end = station[getEnd]
data = query(start, end, finalDate)
if len(data) != 0:
self.displayTable(len(data), 16, data)
else:
self.messageDialog('警告', '此阶段没有车辆运行！')
else:
self.messageDialog('警告', '输入的站名不存在')
else:
self.messageDialog('警告', '请填写车站名称！')
else:
self.messageDialog('警告', '未下载车站查询文件！')
def without():
layer = iface.activeLayer()
q = (query(layer).where(qstring).where(qstring2).top(top))
results = q()
out = results.next()
def start_func():
mail.select("Inbox") # connect to inbox.
result, data = mail.search(None,'(UNSEEN)')
ids = data[0] # data is a list.
id_list = ids.split() # ids is a space separated string
i=0;
for fold in range(1,num_folders):
path, dirs, files = os.walk('class_new'+str(fold)).next()
count=0
for i in files:
if 'inbox' not in i.lower():
count+=1
nfiles=count/2
#nfiles = len(os.listdir('class_new'+str(fold)))/2
#print nfiles
mail_header[folders[fold]]=[]
for i in range(0,nfiles):
filename = str(folders[fold])+"_header"+str(i+1)
try:
f=open('class_new'+str(fold)+'/'+filename,'r').readlines()
data_body = []
for line in f:
data_body.append(line)
mail_header[folders[fold]].append(data_body)
except:
pass
mail_header["Inbox"]=[]
i=0;
for email_id in id_list:
i=i+1
#mail.store(email_id, '+FLAGS', '\\UnSeen') #to tag the read mail as seen..
result_uid,data_uid = mail.fetch(email_id, "(UID)")
try:
msg_uid = parse_uid(data_uid[0])
except:
pass
result_mail,data_mail = mail.fetch(email_id, "(RFC822)");
raw_email = data_mail[0][1] # here's the body, which is raw text of the whole email
email_message = email.message_from_string(raw_email)
receiver = email_message['To']
subject = email_message['Subject']
sender = email.utils.parseaddr(email_message['From'])
payload=email_message.get_payload()
body = extract_body(payload)
if email_message.get_content_type() == "multipart/mixed":
continue
elif email_message.get_content_type() == "text/html":
body = nltk.clean_html(body)
indx1 = body.find("html")
indx2 = body.find("<p>")
if indx1!=-1 and indx2!=-1:
if indx1<indx2:
body = body[ :indx1]
else:
body = body[ :indx2]
elif indx1!=-1:
body = body[ :indx1]
elif indx2!=-1:
body = body[ :indx2]
file1 = "Inbox"+str(i);
#var="Receiver: "+str(receiver) +"\nSender: "+str(sender)+"\nSubject:"+str(subject)+"\nBody: "+str(body);
info = str(sender)+" "+str(subject)
try:
mail_header["Inbox"].append(info)
except:
pass
f2 = open('class_new0/'+file1,'w')
f2.write(body)
f2.close()
file_send = open("check",'w')
file_send.write(str(info) +"\n"+ str(body))
file_send.close()
return_index = query(open("check").read())
path, dirs, files = os.walk('class_new'+str(return_index)).next()
count=0
for j in files:
if 'inbox' not in j.lower():
count+=1
nfiles=count/2+1
if return_index!=0:
shutil.move("class_new0/file1","class_new"+str(return_index)+"/"+folders[return_index]+nfiles);
file_send = open("class_new"+str(return_index)+"/"+folders[return_index]+"_header"+nfiles,'w')
file_send.write(str(info))
file_send.close()
mail_header["Inbox"].pop()
file_send = open("class_"+str(return_index)+"/"+"file"+nfiles,'w')
file_send.write(str(info)+"\n"+ str(body))
file_send.close()
result = mail.uid('COPY', msg_uid, folders[return_index])
if result[0] == 'OK':
mov_del, data_del = mail.uid('STORE', msg_uid , '+FLAGS', '(\Deleted)')
mail.expunge()
def withbindex():
layer = iface.activeLayer()
q = query(layer).where(qstring).top(top).with_index(bindex)
results = q().next()
for dataset in listaDataSet:
queryEliminaCollection(db)
data = utility.caricaDatiDaJson("../../../dataset_lokomat/" + dataset)
#Inserisco dataSet
for i in data:
queryInserisciDati(db,i['id'],i['name'],i['width'],i['height'],i['l_shank'],i['l_thigh'],i['lokomat_shank'],i['lokomat_thigh']
,i['lokomat_recorded'],i['version'],i['legtype'],i['lwalk_training_duration'],i['lwalk_distance']
,i['step_datas'])
#Eseguo query
contatore = 0
for query in listaQuery:
#Stessa query 31 volte
tempiOtherQuery = []
for _ in range(0, 31):
tempo = time.time()
query(db)
tempoFinale = time.time() - tempo
if (_ == 0):
listaDatiPrimaQuery.append(tempoFinale)
print str("PRIMA QUERY ") + str(tempoFinale) + str("\n")
else:
tempiOtherQuery.append(tempoFinale)
print str(tempoFinale)
listaTempiOtherQuery.append(tempiOtherQuery)
contatore = contatore + 1
#Grafici
for __ in range(0, 3):
i = __
numDataset = 0
def instance_generator(S, V, P, Q, T, AD=None, DEFAULT=True, seed=None):
I, J = 6, 6
hpt = 8 # hours per time period t
tpy = 28 # time period per year
if seed is None:
seed = query('seed value: ', **q_opts(-1, float, DEFAULT))
if seed < 0:
seed = round(1000 * random.random(), 2)
random.seed(seed)
# -----------------------------------------------------------------------------
# SET NUMBER OF EVERYTHING
# -----------------------------------------------------------------------------
rd = Struct()
rd.STORES = list("s" + str(s + 1) for s in xrange(S))
rd.PRODUCTS = list("p" + str(p + 1) for p in xrange(P))
rd.FASHION = list("q" + str(q + 1) for q in xrange(Q))
items = rd.PRODUCTS + rd.FASHION
rd.PUTAWAY = list("i" + str(i + 1) for i in xrange(I))
rd.PICKING = list("j" + str(j + 1) for j in xrange(J))
tech = rd.PUTAWAY + rd.PICKING
rd.TIMES = list("" + str(t + 1) for t in xrange(T))
rd.TIMES = range(1, T + 1)
rd.T_minus_One = dict(zip(rd.TIMES[1:] + rd.TIMES[0:-1], rd.TIMES))
Vq = int(Q * V / (P + Q))
Vp = V - Vq
rd.VENDORS_Q = list("vq" + str(v + 1) for v in xrange(Vq))
rd.VENDORS_P = list("vp" + str(v + 1) for v in xrange(Vp))
rd.VENDORS = rd.VENDORS_P + rd.VENDORS_Q
# -----------------------------------------------------------------------------
# GENERATE MODEL PARAMETERS
# -----------------------------------------------------------------------------
# Generate fashion period window
rd.L_s = {s: 0 for s in rd.STORES}
maxL = max(rd.L_s.values())
rd.pt = 1
tb_range = range(1, T + 1)
try:
for i in xrange(8):
tb_default = tb_range[-i]
except:
pass
rd.tb = query('fashion period start: ',
**q_opts(tb_default, tb_range, int, DEFAULT, False))
te_range = range(rd.tb, T - maxL - rd.pt + 1)
rd.te = query('fashion period end: ',
**q_opts(te_range[-1], te_range, int, DEFAULT, False))
rd.ty = rd.te + rd.pt + maxL
P_ratio = P / Vp
Q_ratio = Q / Vq
Omega = {}
v_to_p = []
if P_ratio > 0:
PRODUCTS = list(rd.PRODUCTS)
for v in rd.VENDORS_P:
p_from_v = [PRODUCTS.pop(0) for _ in xrange(P_ratio)]
v_to_p += [(v, p) for p in p_from_v]
else:
v_to_p += [(v, p) for p in PRODUCTS]
else:
v_to_p += zip(rd.VENDORS_P, rd.PRODUCTS)
if Q_ratio > 0:
FASHION = list(rd.FASHION)
for v in rd.VENDORS_Q:
q_from_v = [FASHION.pop(0) for _ in xrange(Q_ratio)]
v_to_p += [(v, q) for q in q_from_v]
else:
v_to_p += [(v, q) for q in FASHION]
else:
v_to_p += zip(rd.VENDORS_Q, rd.FASHION)
vqq = list(itertools.product(rd.VENDORS_Q, rd.FASHION))
vpp = list(itertools.product(rd.VENDORS_P, rd.PRODUCTS))
Omega = {(v, p): 1 if (v, p) in v_to_p else 0 for v, p in chain(vqq, vpp)}
rd.Omega_q = [(v, q) for v in rd.VENDORS_Q for q in rd.FASHION
if Omega[v, q]]
rd.Omega_p = [(v, p) for v in rd.VENDORS_P for p in rd.PRODUCTS
if Omega[v, p]]
#Generate labor costs for full- and part-time employers
ft_hourly = query('full time labor costs: ',
**q_opts(40, [25], int, DEFAULT))
pt_hourly = 30 if ft_hourly == 40 else 20
rd.C_alpha = ft_hourly * hpt * T
rd.C_beta = pt_hourly * hpt
# Generate various sensitivity parameters
rd.gamma = query('gamma: ', **q_opts(.5, [.5, 1, 1.5, 2], float, DEFAULT))
rd.phi_put = query('phi_1: ', **q_opts(1, [.75, 1], float, DEFAULT))
rd.phi_pick = rd.phi_put
# Generate volume of the truck
rd.script_Q = 15000
# Generate product characteristics (Volume and Weight)
rd.V_p = {p: round(random.uniform(.01, 1.0), 2) for p in rd.PRODUCTS}
rd.V_q = {q: round(random.uniform(.01, 1.0), 2) for q in rd.FASHION}
rd.W_p = {p: round(random.uniform(0.1, .99), 2) for p in rd.PRODUCTS}
rd.W_q = {q: round(random.uniform(0.1, .99), 2) for q in rd.FASHION}
# Generate cost of various technologies
putaway_tech_choices = [(600, 0), (1200, 5945), (2400, 19817),
(3600, 26849), (4800, 57534), (6000, 76712)]
picking_tech_choices = [(100, 639), (200, 3388), (300, 7671), (400, 11506),
(500, 17900), (1000, 51141)]
rd.MHE = dict(zip(rd.PUTAWAY, [9, 27, 37, 87, 0, 0]))
temp = dict(zip(tech, putaway_tech_choices + picking_tech_choices))
Ct = {t: int((temp[t][1] / tpy) * T) for t in tech}
rd.C_put = {i: Ct[i] for i in rd.PUTAWAY}
rd.C_pick = {j: Ct[j] for j in rd.PICKING}
Lambda = {t: temp[t][0] * hpt for t in tech}
rd.lambda_put = {i: Lambda[i] for i in rd.PUTAWAY}
rd.lambda_pick = {j: Lambda[j] for j in rd.PICKING}
spt = itertools.product(rd.STORES, rd.PRODUCTS, rd.TIMES)
sq = itertools.product(rd.STORES, rd.FASHION)
Base_Load = 4000. / (P + Q) if AD is None else AD
random_load = Base_Load, .4 * Base_Load
daily_load = lambda: int(
max([0, round(random.normalvariate(*random_load), 0)]))
rd.Demand = {(s, p, t): daily_load() for s, p, t in spt}
rd.X_osq = {(s, q): daily_load() * T for s, q in sq}
rd.X_ivq = {(v, q): sum([rd.X_osq[s, q] for s in rd.STORES]) * Omega[v, q]
for v, q in vqq}
rd.BigM = sum(rd.Demand.itervalues()) + sum(rd.X_osq.itervalues())
rd.M_MHE = 87 * (500 + 500) # Max MHE * (UPPER BOUNDS OF ALPHA AND BETA)
#-------------------------------------------------------------------
# GENERATE TRANSPORTATION COSTS
#-------------------------------------------------------------------
TransportDataA = [
25, 50, 75, 100, 150, 200, 250, 300, 350, 400, 500, 600, 700, 800, 900,
1000, 1100
]
TransportDataB = [
40.42, 45.59, 52.27, 66.13, 75.28, 85.67, 97.5, 110.96, 126.26, 143.71,
186.09, 217.05, 253.17, 297.11, 344.43, 401.77, 468.61
]
TransportDataC = [
427.6, 441.14, 482.83, 492.45, 521.43, 541.39, 570.02, 598.03, 622.3,
659.96, 727.61, 802.19, 884.41, 975.07, 1075.01, 1185.2, 1306.68
]
TransportDataD = [
0.022, 0.027, 0.029, 0.034, 0.036, 0.041, 0.042, 0.045, 0.047, 0.05,
0.055, 0.061, 0.067, 0.074, 0.081, 0.09, 0.099
]
DistanceInMiles = TransportDataA
FixedCost = dict(zip(TransportDataA, TransportDataB))
Variable_Fixed = dict(zip(TransportDataA, TransportDataC))
Variable = dict(zip(TransportDataA, TransportDataD))
'''Randomly generate distances'''
dist_VW, dist_WS, Cf, Cv, Cvf = {}, {}, {}, {}, {}
for v in rd.VENDORS:
dist_VW[v] = random.choice([x for x in DistanceInMiles if x >= 250])
Cf[v] = FixedCost[dist_VW[v]]
Cv[v] = Variable[dist_VW[v]]
Cvf[v] = Variable_Fixed[dist_VW[v]]
for s in rd.STORES:
rnd_num = random.random()
if rnd_num <= .4:
dist_WS[s] = random.choice(
[x for x in DistanceInMiles if x <= 300])
elif .4 < rnd_num <= .7:
dist_WS[s] = random.choice(
[x for x in DistanceInMiles if 300 <= x <= 800])
else:
dist_WS[s] = random.choice(DistanceInMiles)
Cf[s] = FixedCost[dist_WS[s]]
Cv[s] = Variable[dist_WS[s]]
Cvf[s] = Variable_Fixed[dist_WS[s]]
rd.C_vs = {s: Cv[s] for s in rd.STORES}
rd.C_fv = {v: Cvf[v] + Cf[v] for v in rd.VENDORS}
rd.C_fs = {s: Cvf[s] + Cf[s] for s in rd.STORES}
rd.C_vv = {v: Cv[v] for v in rd.VENDORS}
#-------------------------------------------------------------------
# CREATE BHANU'S HEURISTIC FILES
#-------------------------------------------------------------------
warehouses = ['w1']
WarehouseVolume = {w: 100000000 for w in warehouses}
K = {s: 10000000 for s in rd.STORES}
key = 'v{}q{}s{}p{}t{}'.format(V, Q, S, P, T)
filename = 'WITPdataSet_' + key + '.txt'
with open(filename, 'wb') as g:
Xpress_data(g, 'WarehouseVolume', WarehouseVolume, warehouses)
Xpress_data(g, 'StoreVolume', K, rd.STORES)
Xpress_data(g, 'StoreDemand', rd.Demand,
[rd.STORES, rd.PRODUCTS, rd.TIMES])
Xpress_data(g, 'FixedCostVendorToWarehouse', Cf,
[rd.VENDORS_P, warehouses])
Xpress_data(g, 'FixedCostWarehouseToStore', Cf,
[warehouses, rd.STORES])
Xpress_data(g, 'Variable_FixedCostVendorToWarehouse', Cvf,
[rd.VENDORS_P, warehouses])
Xpress_data(g, 'VariableCostVendorToWarehouse', Cv,
[rd.VENDORS_P, warehouses])
Xpress_data(g, 'Variable_FixedCostWarehouseToStore', Cvf,
[warehouses, rd.STORES])
Xpress_data(g, 'VariableCostWarehouseToStore', Cv,
[warehouses, rd.STORES])
Xpress_data(g, 'ProductVolume', rd.V_p, rd.PRODUCTS)
Xpress_data(g, 'ProductWeight', rd.W_p, rd.PRODUCTS)
Xpress_data(g, 'MapVendorToProduct', Omega,
[rd.VENDORS_P, rd.PRODUCTS])
Xpress_data(g, 'LeadTimeWarehouseToStores', rd.L_s,
[warehouses, rd.STORES])
Xpress_data(g, 'StoreDemandForFashionProducts', rd.X_osq,
[rd.STORES, rd.FASHION])
Xpress_data(g, 'FixedCostFashionVendorToWarehouse', Cf,
[rd.VENDORS_Q, warehouses])
Xpress_data(g, 'Variable_FixedCostFashionVendorToWarehouse', Cvf,
[rd.VENDORS_Q, warehouses])
Xpress_data(g, 'VariableCostFashionVendorToWarehouse', Cv,
[rd.VENDORS_Q, warehouses])
Xpress_data(g, 'FashionProductVolume', rd.V_q, rd.FASHION)
Xpress_data(g, 'FashionProductWeight', rd.W_q, rd.FASHION)
Xpress_data(g, 'MapFashionVendorToProduct', Omega,
[rd.VENDORS_Q, rd.FASHION])
print "Created {FILE}".format(FILE=filename)
SED = {}
SED['FILENAMEVAL'] = key
SED['FULLTIMECOSTVAL'] = rd.C_alpha / T
SED['PARTTIMECOSTVAL'] = rd.C_beta
SED['GAMMAVAL'] = rd.gamma
SED['PHIVAL'] = rd.phi_put
SED['BEGINTIMEVAL'] = rd.tb - 1
SED['ENDTIMEVAL'] = rd.te - 1
SED['DUETIMEVAL'] = rd.ty - 1
SED['PROCESSINGTIMEVAL'] = rd.pt
LARGE_FILE = sum(1 for _ in open(filename)) > 100000
SED['NOTOTALITERATIONSVAL'] = 200 if LARGE_FILE else 1000
SED['NOOFITERATIONSVAL'] = 200 if LARGE_FILE else 1000
SED['NUMSWAPITERATIONSVAL'] = 3 if LARGE_FILE else 5
SED['STOPITERVAL'] = 3 if LARGE_FILE else 5
SED = {k: str(v) for k, v in SED.items()}
with open('BhanuCode/WITP-TPH/TEMPLATE.cs', 'r') as f:
lines = f.readlines()
for i in range(100):
lines[i] = multiple_replace(lines[i], SED)
with open('BhanuCode/WITP-TPH/TPH.cs', 'w') as f:
for line in lines:
f.write(line)
_ = bash_command('xbuild BhanuCode/WITP-TPH.sln')
_ = bash_command('rm -f WITP-TPH.exe')
_ = bash_command('cp BhanuCode/WITP-TPH/bin/Debug/WITP-TPH.exe ./')
_ = bash_command('cp BhanuCode/WITP-TPH/TPH.cs ./')
print "Compiled WITP-TPH.exe"
#-------------------------------------------------------------------
# CREATE PYOMO FILES
#-------------------------------------------------------------------
with open('Pickled_Data', 'wb') as f:
pickle.dump(rd, f, protocol=-1)
print "Pickled Data"
return rd if os.path.isfile('WITP-TPH.exe') else False
def withbindex():
layer = iface.activeLayer()
q = query(layer).where(qstring).top(top).with_index(bindex)
results = q().next()
def get_file(path, version):
if version == 'latest':
version = query('latest')
return query('file', version, path)
def instance_generator(S, V, P, Q, T, AD=None, DEFAULT=True, seed=None):
I, J = 6, 6
hpt = 8 # hours per time period t
tpy = 28 # time period per year
if seed is None:
seed = query('seed value: ', **q_opts(-1, float, DEFAULT))
if seed < 0:
seed = round(1000 * random.random(), 2)
random.seed(seed)
# -----------------------------------------------------------------------------
# SET NUMBER OF EVERYTHING
# -----------------------------------------------------------------------------
rd = Struct()
rd.STORES = list("s" + str(s + 1) for s in xrange(S))
rd.PRODUCTS = list("p" + str(p + 1) for p in xrange(P))
rd.FASHION = list("q" + str(q + 1) for q in xrange(Q))
items = rd.PRODUCTS + rd.FASHION
rd.PUTAWAY = list("i" + str(i + 1) for i in xrange(I))
rd.PICKING = list("j" + str(j + 1) for j in xrange(J))
tech = rd.PUTAWAY + rd.PICKING
rd.TIMES = list("" + str(t + 1) for t in xrange(T))
rd.TIMES = range(1, T + 1)
rd.T_minus_One = dict(zip(rd.TIMES[1:] + rd.TIMES[0:-1], rd.TIMES))
Vq = int(Q * V / (P + Q))
Vp = V - Vq
rd.VENDORS_Q = list("vq" + str(v + 1) for v in xrange(Vq))
rd.VENDORS_P = list("vp" + str(v + 1) for v in xrange(Vp))
rd.VENDORS = rd.VENDORS_P + rd.VENDORS_Q
# -----------------------------------------------------------------------------
# GENERATE MODEL PARAMETERS
# -----------------------------------------------------------------------------
# Generate fashion period window
rd.L_s = {s: 0 for s in rd.STORES}
maxL = max(rd.L_s.values())
rd.pt = 1
tb_range = range(1, T + 1)
try:
for i in xrange(8):
tb_default = tb_range[-i]
except:
pass
rd.tb = query('fashion period start: ',
**q_opts(tb_default, tb_range, int, DEFAULT, False))
te_range = range(rd.tb, T - maxL - rd.pt + 1)
rd.te = query('fashion period end: ',
**q_opts(te_range[-1], te_range, int, DEFAULT, False))
rd.ty = rd.te + rd.pt + maxL
P_ratio = P / Vp
Q_ratio = Q / Vq
Omega = {}
v_to_p = []
if P_ratio > 0:
PRODUCTS = list(rd.PRODUCTS)
for v in rd.VENDORS_P:
p_from_v = [PRODUCTS.pop(0) for _ in xrange(P_ratio)]
v_to_p += [(v, p) for p in p_from_v]
else:
v_to_p += [(v, p) for p in PRODUCTS]
else:
v_to_p += zip(rd.VENDORS_P, rd.PRODUCTS)
if Q_ratio > 0:
FASHION = list(rd.FASHION)
for v in rd.VENDORS_Q:
q_from_v = [FASHION.pop(0) for _ in xrange(Q_ratio)]
v_to_p += [(v, q) for q in q_from_v]
else:
v_to_p += [(v, q) for q in FASHION]
else:
v_to_p += zip(rd.VENDORS_Q, rd.FASHION)
vqq = list(itertools.product(rd.VENDORS_Q, rd.FASHION))
vpp = list(itertools.product(rd.VENDORS_P, rd.PRODUCTS))
Omega = {(v, p): 1 if (v, p) in v_to_p else 0 for v, p in chain(vqq, vpp)}
rd.Omega_q = [(v, q) for v in rd.VENDORS_Q for q in rd.FASHION if Omega[v, q]]
rd.Omega_p = [(v, p) for v in rd.VENDORS_P for p in rd.PRODUCTS if Omega[v, p]]
#Generate labor costs for full- and part-time employers
ft_hourly = query('full time labor costs: ', **q_opts(40, [25], int, DEFAULT))
pt_hourly = 30 if ft_hourly == 40 else 20
rd.C_alpha = ft_hourly * hpt * T
rd.C_beta = pt_hourly * hpt
# Generate various sensitivity parameters
rd.gamma = query('gamma: ', **q_opts(.5, [.5, 1, 1.5, 2], float, DEFAULT))
rd.phi_put = query('phi_1: ', **q_opts(1, [.75, 1], float, DEFAULT))
rd.phi_pick = rd.phi_put
# Generate volume of the truck
rd.script_Q = 15000
# Generate product characteristics (Volume and Weight)
rd.V_p = {p: round(random.uniform(.01, 1.0), 2) for p in rd.PRODUCTS}
rd.V_q = {q: round(random.uniform(.01, 1.0), 2) for q in rd.FASHION}
rd.W_p = {p: round(random.uniform(0.1, .99), 2) for p in rd.PRODUCTS}
rd.W_q = {q: round(random.uniform(0.1, .99), 2) for q in rd.FASHION}
# Generate cost of various technologies
putaway_tech_choices = [(600, 0),
(1200, 5945),
(2400, 19817),
(3600, 26849),
(4800, 57534),
(6000, 76712)]
picking_tech_choices = [(100, 639),
(200, 3388),
(300, 7671),
(400, 11506),
(500, 17900),
(1000, 51141)]
rd.MHE = dict(zip(rd.PUTAWAY, [9, 27, 37, 87, 0, 0]))
temp = dict(zip(tech, putaway_tech_choices + picking_tech_choices))
Ct = {t: int((temp[t][1] / tpy) * T) for t in tech}
rd.C_put = {i: Ct[i] for i in rd.PUTAWAY}
rd.C_pick = {j: Ct[j] for j in rd.PICKING}
Lambda = {t: temp[t][0] * hpt for t in tech}
rd.lambda_put = {i: Lambda[i] for i in rd.PUTAWAY}
rd.lambda_pick = {j: Lambda[j] for j in rd.PICKING}
spt = itertools.product(rd.STORES, rd.PRODUCTS, rd.TIMES)
sq = itertools.product(rd.STORES, rd.FASHION)
Base_Load = 4000. / (P + Q) if AD is None else AD
random_load = Base_Load, .4 * Base_Load
daily_load = lambda: int(max([0, round(random.normalvariate(*random_load), 0)]))
rd.Demand = {(s, p, t): daily_load() for s, p, t in spt}
rd.X_osq = {(s, q): daily_load() * T for s, q in sq}
rd.X_ivq = {(v, q): sum([rd.X_osq[s, q] for s in rd.STORES]) * Omega[v, q] for v, q in vqq}
rd.BigM = sum(rd.Demand.itervalues()) + sum(rd.X_osq.itervalues())
rd.M_MHE = 87 * (500 + 500) # Max MHE * (UPPER BOUNDS OF ALPHA AND BETA)
#-------------------------------------------------------------------
# GENERATE TRANSPORTATION COSTS
#-------------------------------------------------------------------
TransportDataA = [25, 50, 75, 100, 150,
200, 250, 300, 350, 400,
500, 600, 700, 800, 900, 1000, 1100]
TransportDataB = [40.42, 45.59, 52.27, 66.13, 75.28,
85.67, 97.5, 110.96, 126.26, 143.71,
186.09, 217.05, 253.17, 297.11, 344.43, 401.77, 468.61]
TransportDataC = [427.6, 441.14, 482.83, 492.45, 521.43,
541.39, 570.02, 598.03, 622.3, 659.96,
727.61, 802.19, 884.41, 975.07, 1075.01, 1185.2, 1306.68]
TransportDataD = [0.022, 0.027, 0.029, 0.034, 0.036,
0.041, 0.042, 0.045, 0.047, 0.05,
0.055, 0.061, 0.067, 0.074, 0.081, 0.09, 0.099]
DistanceInMiles = TransportDataA
FixedCost = dict(zip(TransportDataA, TransportDataB))
Variable_Fixed = dict(zip(TransportDataA, TransportDataC))
Variable = dict(zip(TransportDataA, TransportDataD))
'''Randomly generate distances'''
dist_VW, dist_WS, Cf, Cv, Cvf = {}, {}, {}, {}, {}
for v in rd.VENDORS:
dist_VW[v] = random.choice([x for x in DistanceInMiles if x >= 250])
Cf[v] = FixedCost[dist_VW[v]]
Cv[v] = Variable[dist_VW[v]]
Cvf[v] = Variable_Fixed[dist_VW[v]]
for s in rd.STORES:
rnd_num = random.random()
if rnd_num <= .4:
dist_WS[s] = random.choice([x for x in DistanceInMiles if x <= 300])
elif .4 < rnd_num <= .7:
dist_WS[s] = random.choice([x for x in DistanceInMiles if 300 <= x <= 800])
else:
dist_WS[s] = random.choice(DistanceInMiles)
Cf[s] = FixedCost[dist_WS[s]]
Cv[s] = Variable[dist_WS[s]]
Cvf[s] = Variable_Fixed[dist_WS[s]]
rd.C_vs = {s: Cv[s] for s in rd.STORES}
rd.C_fv = {v: Cvf[v] + Cf[v] for v in rd.VENDORS}
rd.C_fs = {s: Cvf[s] + Cf[s] for s in rd.STORES}
rd.C_vv = {v: Cv[v] for v in rd.VENDORS}
#-------------------------------------------------------------------
# CREATE BHANU'S HEURISTIC FILES
#-------------------------------------------------------------------
warehouses = ['w1']
WarehouseVolume = {w: 100000000 for w in warehouses}
K = {s: 10000000 for s in rd.STORES}
key = 'v{}q{}s{}p{}t{}'.format(V, Q, S, P, T)
filename = 'WITPdataSet_' + key + '.txt'
with open(filename, 'wb') as g:
Xpress_data(g, 'WarehouseVolume', WarehouseVolume, warehouses)
Xpress_data(g, 'StoreVolume', K, rd.STORES)
Xpress_data(g, 'StoreDemand', rd.Demand, [rd.STORES, rd.PRODUCTS, rd.TIMES])
Xpress_data(g, 'FixedCostVendorToWarehouse', Cf, [rd.VENDORS_P, warehouses])
Xpress_data(g, 'FixedCostWarehouseToStore', Cf, [warehouses, rd.STORES])
Xpress_data(g, 'Variable_FixedCostVendorToWarehouse', Cvf, [rd.VENDORS_P, warehouses])
Xpress_data(g, 'VariableCostVendorToWarehouse', Cv, [rd.VENDORS_P, warehouses])
Xpress_data(g, 'Variable_FixedCostWarehouseToStore', Cvf, [warehouses, rd.STORES])
Xpress_data(g, 'VariableCostWarehouseToStore', Cv, [warehouses, rd.STORES])
Xpress_data(g, 'ProductVolume', rd.V_p, rd.PRODUCTS)
Xpress_data(g, 'ProductWeight', rd.W_p, rd.PRODUCTS)
Xpress_data(g, 'MapVendorToProduct', Omega, [rd.VENDORS_P, rd.PRODUCTS])
Xpress_data(g, 'LeadTimeWarehouseToStores', rd.L_s, [warehouses, rd.STORES])
Xpress_data(g, 'StoreDemandForFashionProducts', rd.X_osq, [rd.STORES, rd.FASHION])
Xpress_data(g, 'FixedCostFashionVendorToWarehouse', Cf, [rd.VENDORS_Q, warehouses])
Xpress_data(g, 'Variable_FixedCostFashionVendorToWarehouse', Cvf, [rd.VENDORS_Q, warehouses])
Xpress_data(g, 'VariableCostFashionVendorToWarehouse', Cv, [rd.VENDORS_Q, warehouses])
Xpress_data(g, 'FashionProductVolume', rd.V_q, rd.FASHION)
Xpress_data(g, 'FashionProductWeight', rd.W_q, rd.FASHION)
Xpress_data(g, 'MapFashionVendorToProduct', Omega, [rd.VENDORS_Q, rd.FASHION])
print "Created {FILE}".format(FILE=filename)
SED = {}
SED['FILENAMEVAL'] = key
SED['FULLTIMECOSTVAL'] = rd.C_alpha / T
SED['PARTTIMECOSTVAL'] = rd.C_beta
SED['GAMMAVAL'] = rd.gamma
SED['PHIVAL'] = rd.phi_put
SED['BEGINTIMEVAL'] = rd.tb - 1
SED['ENDTIMEVAL'] = rd.te - 1
SED['DUETIMEVAL'] = rd.ty - 1
SED['PROCESSINGTIMEVAL'] = rd.pt
LARGE_FILE = sum(1 for _ in open(filename)) > 100000
SED['NOTOTALITERATIONSVAL'] = 200 if LARGE_FILE else 1000
SED['NOOFITERATIONSVAL'] = 200 if LARGE_FILE else 1000
SED['NUMSWAPITERATIONSVAL'] = 3 if LARGE_FILE else 5
SED['STOPITERVAL'] = 3 if LARGE_FILE else 5
SED = {k: str(v) for k, v in SED.items()}
with open('BhanuCode/WITP-TPH/TEMPLATE.cs', 'r') as f:
lines = f.readlines()
for i in range(100):
lines[i] = multiple_replace(lines[i], SED)
with open('BhanuCode/WITP-TPH/TPH.cs', 'w') as f:
for line in lines:
f.write(line)
_ = bash_command('xbuild BhanuCode/WITP-TPH.sln')
_ = bash_command('rm -f WITP-TPH.exe')
_ = bash_command('cp BhanuCode/WITP-TPH/bin/Debug/WITP-TPH.exe ./')
_ = bash_command('cp BhanuCode/WITP-TPH/TPH.cs ./')
print "Compiled WITP-TPH.exe"
#-------------------------------------------------------------------
# CREATE PYOMO FILES
#-------------------------------------------------------------------
with open('Pickled_Data', 'wb') as f:
pickle.dump(rd, f, protocol=-1)
print "Pickled Data"
return rd if os.path.isfile('WITP-TPH.exe') else False
def main(argv):
serial = False;
options_per_page = 5
try:
opts, args = getopt.getopt(argv,"hs:",["serial="])
except getopt.GetoptError:
print "main.py -serial <Y|N>"
sys.exit(2)
for opt, arg in opts:
if opt in ('-s', '--serial'):
if (arg == 'Y'):
serial = True
print """
-------------------------
| Welcome to BUS-L! |
-------------------------
"""
#SYSTEM SETUP
#Check for network access
if internet_on() == False:
print "No Internet = No BUSL! \n Please Check Your Interwebs"
return -1
#HUE SETUP
#Check for hue
print """
-------------------------
| Connecting to hue! |
-------------------------
"""
# TODO: add in options to do this better (select a specific light, etc)
lights = hue.hue_connect()
light = lights[1]
hue.ack(light)
if (serial):
ports = get_ports()
if len(ports) != 0:
#Set up GPIO for hardware
print """
-------------------------
| Select Serial Port: |
-------------------------"""
display_serial_ports(ports, 0)
index = get_user_int("\nPlease pick a serial port for the Arduino: ", len(ports))
if test_hardware(ports[index]) == False:
print "No Microcontroller = No BUSL Lights! \n Please Check Your Ports"
#USER CONFIG
print """
-------------------------
| Lets Find Some Stops! |
-------------------------
"""
location = get_user_addr()
#find X closest stops to user
all_stops = go.get_all_umich_stops()
ordering = ERROR_VAL
while (ordering == ERROR_VAL):
ordering = maplib.order_by_distance(location, all_stops)
#present X stop choices (with estimated distances)
print """
-------------------------
| Stops closest to you: |
-------------------------"""
page_index = 0
user_input = "c"
while (user_input == "c"):
display_results(ordering, page_index, options_per_page)
page_index += options_per_page
user_input = raw_input("\nSelect a stop number or press 'c' to see more stops: ")
#get preferred stop
stop_info = ordering[int(user_input)]
preferred_stop = stop_info[2]
preferred_stop_dist = stop_info[1]
preferred_stop_walk_time = stop_info[0]
print "\nLooking up route information for " + preferred_stop.names[1] + " (" + preferred_stop.names[0] + ") . . ."
#present available bus routes
active_routes = preferred_stop.active_routes
print """
----------------------
| Active bus routes: |
----------------------"""
page_index = 0
user_input = ""
while (user_input == ""):
i = 0
for route in active_routes:
print "\n [" + str(i) + "]\t" + route
i += 1
page_index += options_per_page
user_input = raw_input("\nSelect one or more route numbers (e.g. 1 or 1, 2, 3): ")
route_nums = user_input.split(',')
route_nums = [int(x.strip()) for x in route_nums]
#get selection(s)
preferred_routes = [active_routes[x] for x in route_nums]
print "\nWatching for routes! \n"
#START BUS LIGHT SERVER
query(preferred_stop.names[0], preferred_stop_walk_time*60, preferred_routes, light)
from labels import get_label_from_key, get_label_trail_from_key_trail
from query import query
logging.basicConfig(filename='example.log', level=logging.DEBUG, format='%(asctime)s: %(levelname)s: %(message)s', datefmt='%m/%d/%Y %H:%M:%S')
random.seed()
root_dir = join_and_normalize(os.getcwd(), "test_library")
meta_tree = create_item_meta_data_cache(root_dir)
# print(meta_tree)
def test_agg_predicate(item_file_path, meta_data_dict):
return isinstance(meta_data_dict, dict) and "artist" in meta_data_dict and (meta_data_dict["artist"] == "DAISHI DANCE" or str(meta_data_dict["artist"]).casefold().startswith("dj"))
for q_result in query(test_agg_predicate, meta_tree):
print(q_result)
# # all_key_trails = metatree.generate_all_keytrails(meta_tree)
# # sample_key_trails = random.sample(all_key_trails, 8)
# # specific_key_trail = ["ALBUM_00016", "TRACK_00006.ogg"]
# query_func = query.generate_query_regex_match(r"(?i)\bcl", fields=("artist", "title"))
# #query_func = query.generate_query_contains_string("cl", fields=("artist", "title"))
# result_set = query.run_query(meta_tree, query_func)
# for result in result_set:
# print(result)
# print(metatree.get_metadata(meta_tree, *result))
# print("----")
def get_ident(ident, version):
if version == 'latest':
version = query('latest')
return query('ident', version, ident)
def daily(start_date, end_date):
tables = ['VidGeneralMetrics', 'VidInsightPlaybackLocationType', 'VidInsightTrafficSourceType', 'VidLifetimeAgeGroupGender']
con = None
print "Ran on: ", now
print "Start Date: ", str(start_date)
print "End Date: ", str(end_date)
try:
con = mdb.connect(**config.mysql_params)
cur = con.cursor()
trunc_statement = """TRUNCATE VideoInfo"""
cur.execute(trunc_statement)
con.commit()
trunc_VidLifetimeAgeGroupGender = """TRUNCATE VidLifetimeAgeGroupGender"""
cur.execute(trunc_VidLifetimeAgeGroupGender)
con.commit()
videos = getVideoList()
for video in videos:
insert_statement = """INSERT INTO VideoInfo (VideoID, Name, PublishedDate) VALUE (%s, %s, %s)"""
cur.execute(insert_statement, [video, videos[video][0], videos[video][1]])
con.commit()
for video in videos:
for table in tables:
if table == 'VidLifetimeAgeGroupGender':
start_date = lifetime_start
else:
start_date = daily_start
response, columns = query(table, video, start_date, end_date)
insert_statement = table_options[table]['insert']
for row in response:
#print row
cur.execute(insert_statement, getValues(table, video, start_date, columns, row))
con.commit()
#get daily metrics
start_date = daily_start
response, columns = query("DailyMetrics", "", start_date, end_date)
insert_statement = table_options["DailyMetrics"]['insert']
for row in response:
cur.execute(insert_statement, getValues("DailyMetrics", "", start_date, columns, row))
con.commit()
#Twitter
response = urllib2.urlopen('TWITTERFEED')
html = response.read()
soup = BeautifulSoup(html)
# put Day, NumFollowers in Database
values = [datetime.today().strftime('%Y-%m-%d'), soup.findAll(href="/USER/followers")[1].find('strong').text.replace(",", "")]
cur.execute("""INSERT INTO TwitterFollowers VALUES (%s, %s);""", values)
con.commit()
#Youtube Cumulative
response = urllib2.urlopen('http://gdata.youtube.com/feeds/api/users/USER?alt=json')
youtube_data = json.load(response)
stats = youtube_data['entry']['yt$statistics']
values = [datetime.today().strftime('%Y-%m-%d'), stats['subscriberCount'], stats['totalUploadViews']]
cur.execute("""INSERT INTO YoutubeOverall VALUES (%s, %s, %s);""", values)
con.commit()
#Facebook
response = urllib2.urlopen('http://graph.facebook.com/USER/')
facebook_data = json.load(response)
values = [datetime.today().strftime('%Y-%m-%d'), facebook_data["talking_about_count"], facebook_data["likes"]]
cur.execute("""INSERT INTO FacebookOverall VALUES (%s, %s, %s);""", values)
con.commit()
except mdb.Error, e:
print "Error %d: %s" % (e.args[0],e.args[1])
sys.exit(1)
def without():
layer = iface.activeLayer()
q = query(layer).where(qstring).where(qstring2).top(top)
results = q()
out = results.next()
def main():
options_per_page = 5
print """
-------------------------
| Welcome to BUS-L! |
-------------------------
"""
#SYSTEM SETUP
#Check for network access
if internet_on() == False:
print "No Internet = No BUSL! \n Please Check Your Interwebs"
return -1
ports = get_ports()
if len(ports) != 0:
#Set up GPIO for hardware
print """
-------------------------
| Select Serial Port: |
-------------------------"""
display_serial_ports(ports, 0)
index = get_user_int("\nPlease pick a serial port for the Arduino: ", len(ports))
if test_hardware(ports[index]) == False:
print "No Microcontroller = No BUSL Lights! \n Please Check Your Ports"
#USER CONFIG
location = get_user_addr()
#find X closest stops to user
all_stops = go.get_all_umich_stops()
ordering = maplib.order_by_distance(location, all_stops)
#present X stop choices (with estimated distances)
print """
-------------------------
| Stops closest to you: |
-------------------------"""
page_index = 0
user_input = "c"
while (user_input == "c"):
display_results(ordering, page_index, options_per_page)
page_index += options_per_page
user_input = raw_input("\nSelect a stop number or press 'c' to see more stops: ")
#get preferred stop
stop_info = ordering[int(user_input)]
preferred_stop = stop_info[2]
preferred_stop_dist = stop_info[1]
preferred_stop_walk_time = stop_info[0]
print "\nLooking up route information for " + preferred_stop.names[1] + " (" + preferred_stop.names[0] + ") . . ."
#present available bus routes
active_routes = preferred_stop.active_routes
print """
----------------------
| Active bus routes: |
----------------------"""
page_index = 0
user_input = ""
while (user_input == ""):
i = 0
for route in active_routes:
print "\n [" + str(i) + "]\t" + route
i += 1
page_index += options_per_page
user_input = raw_input("\nSelect one or more route numbers (e.g. 1 or 1, 2, 3): ")
route_nums = user_input.split(',')
route_nums = [int(x.strip()) for x in route_nums]
#get selection(s)
preferred_routes = [active_routes[x] for x in route_nums]
print "\nWatching for routes! \n"
#START BUS LIGHT SERVER
query(preferred_stop.names[0], preferred_stop_walk_time*60, preferred_routes)
