def produce(self, product_id, price, quality):
# если норм по капиталам, себестоимости и производственным мощностям, то вперёд
if (price > self.cost) and (quality <=
self.max_quality) and (self.check() == 0):
self.price = price
return product.product(id=product_id, quality=quality, price=price)
else:
self.price = -10000
return product.product(id=-1)
def test_duplicates():
assert list(product([[2, 2], [2, 2]])) == [
(2, 2),
(2, 2),
(2, 2),
(2, 2),
]
def dm_init(name):
dm_url = {
"LG0":
"https://www.dm.de/aptamil-pronutra-pre-von-geburt-an-p4056631001202.html",
"LG1":
"https://www.dm.de/aptamil-pronutra-anfangsmilch-1-von-geburt-an-p4056631001226.html",
"LG2":
"https://www.dm.de/aptamil-pronutra-folgemilch-2-nach-dem-6-monat-p4056631001240.html",
"LG3":
"https://www.dm.de/aptamil-pronutra-folgemilch-3-ab-dem-10-monat-p4008976022343.html",
"ZH1":
"https://www.dm.de/aptamil-pronutra-kindermilch-ab-1-jahr-p4008976022985.html",
"ZH2":
"https://www.dm.de/aptamil-kindermilch-ab-2-jahren-p4008976022992.html",
"BJ0":
"https://www.dm.de/aptamil-profutura-anfangsmilch-pre-von-geburt-an-p4008976022923.html",
"BJ1":
"https://www.dm.de/aptamil-profutura-anfangsmilch-1-p4008976022909.html",
"BJ2":
"https://www.dm.de/aptamil-profutura-folgemilch-2-nach-dem-6-monat-p4008976022916.html"
}
dm_lst = []
for i in name:
milk = product()
milk.setName(name_ch[i])
milk.setUrl(dm_url[i])
dm_lst.append(milk)
return dm_lst
def test_duplicates():
assert list(product([[2, 2], [2, 2]])) == [
(2, 2),
(2, 2),
(2, 2),
(2, 2),
]
def testFloats(self):
for x in range(-10, 10):
for y in range(-10, 10):
x = x / 10.0
y = y / 10.0
p = product.product(x, y)
self.failUnless(p == x * y, 'Float multip;ication failed')
def consume(self, products):
# возвращать будем продукт
fun_result = product.product(id=-1)
available_product_lst = []
# цикл для фильтрации тех, что не карману
for pr in products:
if self.money >= pr.price:
available_product_lst.append(pr)
best_price = max_price
best_qv = min_qv
# цикл поиска лучшего качества
for pr in available_product_lst:
if pr.quality >= best_qv:
best_qv = pr.quality
product_qv_lst = []
# сбор всех продуктов лучшего качества
for pr in available_product_lst:
if pr.quality == best_qv:
product_qv_lst.append(pr)
# выбор из них тех, что дешевле
for pr in product_qv_lst:
if pr.price <= best_price:
best_price = pr.price
# вывод продукта с лучшими характеристиками
for pr in product_qv_lst:
if pr.price == best_price:
fun_result = pr
break
return fun_result
def newRec(self,
code=0,
name='',
typel='',
material=None,
weight=0,
price=0):
self.appendList(product(code, name, typel, material, weight, price))
def factorial(n):
result=[]
if n==0:
return 1
else:
for idx in range(1,n+1):
result.append(idx)
return product.product(result)
def display_page(pathname):
if pathname == '/trends':
return trends()
if pathname == "/survey":
return contribute()
if pathname == "/about":
return about()
return product()
def test_one_float_and_one_int(self):
"""
product(1.3, 10) should return 13
need to use AlmostEqual because of floating point precision
after several decimal places!!!
"""
self.assertAlmostEqual(product(1.3, 10), 13)
def test_product():
assert product([5, 4, 1, 3, 9]) == 540
assert product([-2, 6, 7, 8]) == -672
assert product([10]) == 10
assert product([0, 2, 9, 7]) == 0
assert product(None) is None
assert product([]) is None
def main():
#calling the inventory functions from the class
inventory1 = inventory("1", "Jacket", "12", "$59.95")
print(inventory1)
print()
#the spacing on this constructor helps shape it when it is printed
#storing 4 arguments into the three variables
Product1 = product(" 1 ", "Jacket ", " 12 ", " $59.95 ")
Product2 = product(" 2 ", "Designer Jeans ", " 40 ", " $34.95 ")
Product3 = product(" 3 ", "Shirt ", " 20 ", " $24.95 ")
print(" ID: " + " Desription: " + "Quantity: " + "Price: ")
print(Product1)
print()
print(Product2)
print()
print(Product3)
def test_product():
assert list(product([[0, 1, 2], [0, 1, 2]])) == [
(0, 0),
(0, 1),
(1, 0),
(0, 2),
(1, 1),
(2, 0),
(1, 2),
(2, 1),
(2, 2),
]
assert list(product([[0, 1, 2], [0, 1, 2]], key=sqrt)) == [
(0, 0),
(0, 1),
(1, 0),
(0, 2),
(2, 0),
(1, 1),
(1, 2),
(2, 1),
(2, 2),
]
assert list(product([[0, 1, 2], [0, 1, 2]], key=lambda i: i**2)) == [
(0, 0),
(0, 1),
(1, 0),
(1, 1),
(0, 2),
(2, 0),
(1, 2),
(2, 1),
(2, 2),
]
def test_product():
assert list(product([[0, 1, 2], [0, 1, 2]])) == [
(0, 0),
(0, 1),
(1, 0),
(0, 2),
(1, 1),
(2, 0),
(1, 2),
(2, 1),
(2, 2),
]
assert list(product([[0, 1, 2], [0, 1, 2]], key=sqrt)) == [
(0, 0),
(0, 1),
(1, 0),
(0, 2),
(2, 0),
(1, 1),
(1, 2),
(2, 1),
(2, 2),
]
assert list(product([[0, 1, 2], [0, 1, 2]], key=lambda i: i**2)) == [
(0, 0),
(0, 1),
(1, 0),
(1, 1),
(0, 2),
(2, 0),
(1, 2),
(2, 1),
(2, 2),
]
def getPrice(search):
searchURL = 'http://www.newegg.com/Product/ProductList.aspx?Submit=ENE&DEPA=0&Order=BESTMATCH&N=-1&isNodeId=1&Description='+ str(search) +'&x=-852&y=-112'
try:
newegg = urllib2.urlopen(searchURL)
except:
raise
newegg_content = newegg.read().replace('\n','')
newegg_content = newegg_content.replace('\t','')
# file = open('newegg.html', 'w')
# file.write(newegg_content)
modelList = []
items = re.findall(r'\<div class="itemCell"(.*?)\<br class="clear"', newegg_content)
for item in items:
p = product()
#print item + '\n'
url = re.findall(r'\<a href="(.*?)"',item)
if len(url) > 0:
p.url = url[0]
# p.url = p.url.encode('utf8')
name = re.findall(r'\<span class="itemDescription" id="titleDescription.*?\>(.*?)</span>',item)
if len(name) > 0:
p.name = name[0]
price = re.findall(r'\<input type="hidden" name="priceBefore" value="\$([,0-9\.]+?)"',item)
if len(price) > 0:
p.price = float(filter(lambda x : x not in ',', price[0]))
else:
p.price = None
p.source = '/images/newegg-logo.jpg'
# Get the product photo
imgurl = re.findall(r'\<div class="itemGraphics"\>.*?src="(.*?)"', item)
if len(imgurl) > 0:
imgurl = imgurl[0]
p.imgurl = imgurl
else:
p.imgurl = p.source
modelList.append(p)
# html = '<li><a href="' + p.url + '">' + p.name + '</a><br>' + p.price + '<br>Newegg</li>'
# file.write(html)
# file.close()
newegg.close()
return modelList
def rossmannInit(name):
rossmann_url = {"LG0": "https://www.rossmann.de/produkte/aptamil/pronutra-advance-pre-anfangsmilch-von-geburt-an/4056631001202.html",
"LG1": "https://www.rossmann.de/produkte/aptamil/pronutra-advance-1-anfangsmilch-von-geburt-an/4056631001226.html",
"LG2": "https://www.rossmann.de/produkte/aptamil/pronutra-advance-2-folgemilch-nach-dem-6-monat/4056631001240.html",
"LG3": "https://www.rossmann.de/produkte/aptamil/pronutra-advance-3-folgemilch-ab-dem-10-monat/4056631001264.html",
"ZH1": "https://www.rossmann.de/produkte/aptamil/pronutra-kindermilch-1/4008976022985.html",
"ZH2": "https://www.rossmann.de/produkte/aptamil/pronutra-kindermilch-2/4008976022992.html",
"BJ0": "https://www.rossmann.de/produkte/aptamil/profutura-pre-anfangsmilch-von-geburt-an/4056631001301.html",
"BJ1": "https://www.rossmann.de/produkte/aptamil/profutura-1-anfangsmilch-von-geburt-an/4056631001325.html",
"BJ2": "https://www.rossmann.de/produkte/aptamil/profutura-2-folgemilch-nach-dem-6-monat/4056631001349.html"}
rm_lst = []
for i in name:
milk = product()
milk.setName(name_ch[i])
milk.setUrl(rossmann_url[i])
rm_lst.append(milk)
return rm_lst
def scrape_product(nextPage, i=1):
categories = get_categories(nextPage)
x = "continue"
while x == "continue":
source1 = requests.get(nextPage).text
soup = BeautifulSoup(source1, "lxml")
i += 1
actual_page = soup.find("a", class_="disabledLink")
try:
prox_page = str(int(actual_page.text) + 1)
nextPage = (
"https://www.cotodigital3.com.ar"
+ soup.find("a", title=str("Ir a página " + prox_page)).attrs["href"]
)
except:
x = "stop"
print("no next")
li = soup.findAll("li", class_="clearfix")
for each in li:
producto = each.find("div", class_="descrip_full").text.strip()
try:
price = (
each.find("span", class_="atg_store_newPrice")
.text.split("$")[1]
.strip()
)
except:
price = 0
sku = (
each.find("div", class_="descrip_full")
.attrs["id"]
.split("sku")[1]
.strip()
)
insert_product(
product(
categories[0], categories[1], categories[2], sku, producto, price
)
)
return
def reweInit(name):
rewe_url = {"LG0": "https://shop.rewe.de/PD1958158?variantArticleId=4008976022350",
"LG1": "https://shop.rewe.de/PD1958156?variantArticleId=4008976022329",
"LG2": "https://shop.rewe.de/PD1958154?variantArticleId=4008976022336",
"LG3": "https://shop.rewe.de/PD1958152?variantArticleId=4008976022343",
"ZH1": "https://shop.rewe.de/PD1964189?variantArticleId=4008976022985",
"ZH2": "https://shop.rewe.de/PD1964191?variantArticleId=4008976022992",
"BJ0": "https://shop.rewe.de/PD2522946?variantArticleId=4008976022923",
"BJ1": "https://shop.rewe.de/PD2522955?variantArticleId=4008976022909",
"BJ2": "https://shop.rewe.de/PD2522960?variantArticleId=4008976022916",
}
rewe_lst = []
for i in name:
milk = product()
milk.setName(name_ch[i])
milk.setUrl(rewe_url[i])
rewe_lst.append(milk)
return rewe_lst
def totient(num):
"""
Counts the numbers that are relative prime to the number.
This means that if a number 'x' has common divisors with another number 'a' lower than itself,
it is, 'a' is not relative prime to 'x'.
This means that if a number is prime, its totient function is its value - 1, as
all numbers lower than the number itself are relative prime to the number.
An example: totient(9):
1, 2, 4, 5, 7, 8 are all relative prime
3, 6, and 9 have at least one common divisor with 9
returns 6, as there are 6 numbers relative prime to 9
If you visit 'https://en.wikipedia.org/wiki/Euler%27s_totient_function'
this function uses the function described under euler's product formula.
"""
# set(prime_factors(num)) to get only unique primes.
# it is the (1 - 1/p) part from the wiki-page
uniqe_primes = [(1 - 1 / p) for p in set(prime_factors(num))]
phi = num * product(uniqe_primes) # The totient function is commonly called phi
phi = int(round(phi)) # As phi is a whole number
return phi
def scan_items(self, some_product):
temp = int(0)
for pro_data in range(len(self.storing_products)):
if self.storing_products[pro_data][0].__contains__(some_product):
# store the items into the product list
data_in_list = product.product(
self.storing_products[pro_data][0],
self.storing_products[pro_data][1],
self.storing_products[pro_data][2],
self.storing_products[pro_data][3])
self.bucket.append(data_in_list)
self.price_of_products += float(
self.storing_products[pro_data][3])
temp = 1
print(self.storing_products[pro_data][1] + ", " +
self.storing_products[pro_data][2] + " - $" +
self.storing_products[pro_data][3])
break
self.temp_pro_amount = self.price_of_products
if temp == 0:
print("This product does not exists in our inventory.")
def getProductInfo(url,headers2):
data=requests.get(url,headers=headers2).text
soup=BeautifulSoup(data,"lxml")
productTitle =soup.select("#J_Property > h1")
productSeller =soup.select("#J_SellerInfo > div.simple > div.wangwang > a")
price= soup.select("#J_Property > ul.price-info > li:nth-of-type(1) > span.price.big > em")
costPrice=soup.select("#J_Property > ul.price-info > li:nth-of-type(2) > span:nth-of-type(2)")
productCondition=soup.select("#J_Property > ul.idle-info > li:nth-of-type(1) > em")
adders=soup.select("#J_Property > ul.idle-info > li:nth-of-type(2) > em")
particulars=soup.select("#J_DescContent")
flow=soup.select("#J_Browse")
date=soup.select("#idle-detail > div.top-nav.clearfix > div.others-wrap > ul > li:nth-of-type(2) > span")
title = productTitle if len(productTitle) == 0 else productTitle[0].get_text()
seller = productSeller[0].get_text()
price = price[0].get_text()
cost = costPrice if len(costPrice) == 0 else costPrice[0].get_text()
condition = productCondition[0].get_text()
adder = adders[0].get_text()
particular = getParticular(particulars[0].get("data-url"))
flow = getFlow(flow[0].get("data-url"))
date = date[0].get_text()
return product(title,seller,price,cost,condition,adder,particular,flow,date)
def getPrice(search):
searchURL = 'http://www.amazon.com/s/ref=nb_sb_noss_1?url=search-alias%3Daps&field-keywords=' + str(search)
#print searchURL
try:
amazon = urllib2.urlopen(searchURL)
except:
raise
amazon_content = amazon.read().replace('\n', '')
# file = open('amazon.html', 'w')
# file.write(amazon_content)
modelList = []
items = re.findall(r'\<div class="result product"(.*?)\<br clear', amazon_content)
# print len(items)
for i in range(len(items)):
item = items[i]
p = product()
# print i+1
#print item
url = re.findall(r'\<div class="productTitle".*?href="(.*?)"\>', item)
if len(url) > 0:
url = url[0]
p.url = url
# p.url = p.url.encode('utf8')
name = re.findall(r'\<div class="productTitle".*?href=".*?"\>(.*?)\</a\>', item)
if len(name) > 0:
name = name[0]
p.name = name
# print name
price = re.findall(r'\<div class="newPrice"\>.*?\<span\>.*?\$([,0-9\.]+?)\</span\>', item)
if len(price) > 0:
price = price[0]
p.price = float(filter(lambda x : x not in ',', price))
else:
price = re.findall(r'\<div class="subPrice"\>.*?\<span\>.*?\$([,0-9\.]+?)\</span\>', item)
if len(price) > 0:
price = price[0]
p.price = float(filter(lambda x : x not in ',', price))
else:
p.price = None
# print price
#model = re.findall(r'\<strong itemprop="model"\>(.*?)\</strong\>', item)[0]
p.source = '/images/amazon-logo.jpg'
# Get the product photo
imgurl = re.findall(r'\<div class="productImage".+?src="(.*?)"', item)
if len(imgurl) > 0:
imgurl = imgurl[0]
p.imgurl = imgurl
else:
p.imgurl = p.source
#p.model = model
modelList.append(p)
# html = '<li><a href="' + p.url + '">' + p.name + '</a><br>$' + str(p.price) + '<br>Amazon</li>'
# file.write(html)
# print p.name, '\n'
# print p.url, '\n'
# print p.price, '\n'
# print '\n'
# print amazon_content
# file.write(amazon_content)
# file.close()
return modelList
amazon.close()
K = len(demand_possibility[0]) # scenario number in a period
S = K**T # total scenario number
# set values for scenario links: whether scenario i links with scenario j in period t
scenarioLink = [[[0 for s in range(S)] for s in range(S)] for t in range(T)]
for t in range(T):
slices = round(S * (1 / K)**(t + 1)) # number of scenario in a slice
slice_num = round(K**(t + 1)) # totoal number of slices
for i in range(slice_num):
for j in range(slices * i, slices * (i + 1)):
for k in range(slices * i, slices * (i + 1)):
scenarioLink[t][j][k] = 1
# set values for scenario probabilities
scenario_permulations = product.product(range(K), T)
scenario_probs = [0 for s in range(S)]
scenario_values = [0 for s in range(S)]
for s in range(S):
index = scenario_permulations[s][0]
scenario_probs[s] = demand_possibility[0][index]
for i in range(1, len(scenario_permulations[s])):
index = scenario_permulations[s][i]
index2 = booming_demand[i]
scenario_probs[
s] = scenario_probs[s] * demand_possibility[index2][index]
# compute value of perfect information: final_value
for s in range(S):
mean_demand = [[[0 for i in range(N)] for j in range(2)] for t in range(T)]
for n in range(N):
def getPrice(search):
# testing output
# file = open('bestbuy.html', 'w')
# result product list for return
pList = []
# Bestbuy's search URL
searchURL = 'http://www.bestbuy.com/site/searchpage.jsp?_dyncharset=ISO-8859-1&_dynSessConf=ATG12474449190&id=pcat17071&type=page&sc=Global&cp=1&nrp=15&sp=&qp=&list=n&iht=y&usc=All+Categories&ks=960&saas=saas&st=%s' % search
try:
bestbuy = urllib2.urlopen(searchURL)
except:
raise
# Get the content and eliminate the \n so we can use regex
bestbuy_content = bestbuy.read().replace('\n', '')
# find all the product divs and store in a list
items = re.findall(r'\<div class="hproduct"(.*?)itemprop="description"', bestbuy_content)
# For each product, we build out product object
for i in range(len(items)):
item = items[i]
p = product()
# print i
# print item
url = re.findall(r'\<a.*?rel="product" href="(.*?)"', item)
if len(url) > 0:
url = url[0]
p.url = 'http://www.bestbuy.com' + url
# p.url = p.url.encode('utf8')
name = re.findall(r'\<h3.*\>\<a.*?rel="product".*?\>(.*?)\</a\>', item)
if len(name) > 0:
name = name[0]
p.name = name
price = re.findall(r'\<h4 class="price sale"\>.*?\$([,0-9\.]+).*?\</h4\>', item)
if len(price) > 0:
price = price[0]
p.price = float(filter(lambda x : x not in ',', price))
else:
p.price = None
model = re.findall(r'\<strong itemprop="model"\>(.*?)\</strong\>', item)
if len(model) > 0:
p.model = model[0]
# build our product object
# print name
# print price
p.source = '/images/bestbuy-logo.jpg'
# Get the product photo
imgurl = re.findall(r'\<img itemprop="image".*?src="(.*?)"', item)
if len(imgurl) > 0:
imgurl = imgurl[0]
p.imgurl = imgurl
else:
p.imgurl = p.source
# add to list
pList.append(p)
# html = '<li><a href="' + p.url + '">' + p.name + '</a><br>' + p.price + '<br>' + p.model + '</li>'
# file.write(html)
# print p.name, '\n'
# print p.url, '\n'
# print p.price, '\n'
# print '\n'
# print bestbuy_content
# file.write(bestbuy_content)
# file.close()
bestbuy.close()
return pList
def test_two_positive_integers(self):
"""
product(2,3) should return 6
"""
self.assertEqual(product(2,3), 6)
from gantt import *
def colonne(
liste, j
): ## fonction pour avoir la colonne j+1 d'une matrice (liste de listes)
return [item[j] for item in liste]
start_time = time.time()
mfab = 3
lin = 2
netmin = [0.5, 1]
netmaj = [4, 16]
#on définit les produit
prod1 = product('produit1', [3, 5, 3, 16, 0], 16, 2, 0, 0, 1)
prod2 = product('produit2', [3, 5, 3, 21, 0], 21, 3, 0, 0, 1)
prod3 = product('produit3', [3, 5, 3, 22, 22], 22, 2, 0, 0, 1)
prod4 = product('produit4', [3, 5, 3, 0, 15], 15, 1, 0, 0, 1)
prod5 = product('produit5', [3, 5, 3, 0, 24], 24, 46, 0, 0, 23)
prod6 = product('produit1', [3, 5, 3, 16, 0], 16, 46, 0, 0, 46)
prod = [prod1, prod2, prod3, prod4, prod5, prod6]
jssp = instance(mfab, lin, netmin, netmaj, prod)
jssp.process_input()
sol_const = construct_sol(jssp)
sol_const.greedy()
sol = solution(jssp, sol_const.X, sol_const.Y, sol_const.U)
sol.decode()
print("Y =", sol.Y)
def test_two_negative_integers(self):
"""
product(-2, -3) should return 6
"""
self.assertEqual(product(-2,-3), 6)
NAMES = []
PROD = []
print('run',this_simname)
#p_tc_raw = product.product('Tc_raw',fname='%s/data_small/%s_ct.h5'%(basedir,this_simname),field='collapse_times',style='value',width=400)
#p_tc_raw_log = product.product('Log Tc_raw',fname='%s/data_small/%s_mean_collapse_log.h5'%(basedir,this_simname),field='collapse_times',style='value',width=400,number_format="%0.2f")
#p_distance = product.product('Log Distance to Next',fname='%s/data_small/%s_neighbors_distance_0_log.h5'%(basedir,this_simname),field='distance_0',style='value',width=400,number_format='%0.2f')
#p_mean_density = product.product('Log Core Density',fname='%s/data_small/%s_neighbors_mean_density_log.h5'%(basedir,this_simname),field='mean_density',style='value',width=400, number_format='%0.2f')
#u05_neighbors_distance_0.h5
#u05_neighbors_mean_density.h5
p_peak_density = product.product('Peak Density',fname="browser_data/%s_mountain_top.h5"%this_simname,
field='peak_density',style='value_target_file',width=400)
p_nparticles = product.product('Nparticles',fname="browser_data/u50%d_nparticles.h5"%nsim,
field='n_particles',style='value')
p_neighbor = product.product('Neighborhood',fname="browser_data/neighborhood_by_core_u50%d.h5"%nsim,
field='neighborhood',style='value',number_format='%d')
PROD.append(p_peak_density)
PROD.append(p_nparticles)
PROD.append(p_neighbor)
NAMES.append("mountain top")
RE.append(r"/*mountain_tops/%s/mountain_top_%s_c(\d\d\d\d)_Projection_x_density.png"%( this_simname, this_simname))
NAMES.append('GE mass')
RE.append(r"/*ge_cuml/u50%d/u50%d_cuml_c(\d\d\d\d).png"%(nsim,nsim))
NAMES.append("mountain rings")
def test_multiplies_numbers_1(self):
# Failure message:
# expected product(2, 2) to equal 4
self.assertEqual(product(2, 2), 4)
def main1():
print("***LOGIN***")
a = login.login()
b = staff.staff()
c = product.product()
d = billing.product1()
while (1):
print("1.login 2.set password")
a1 = int(input("enter your choice:>"))
if (a1 == 1):
a.login1()
break
if (a1 == 2):
a.setpassword()
continue
else:
print("try again")
while (1):
print("1.staff details 2.product details 3.billing 4.exit")
a2 = int(input("enter your choice:>"))
if (a2 == 1):
b.print_details()
continue
if (a2 == 2):
while (1):
print("1.product search")
print("2.add product")
print("3.update price")
print("4.update quantity")
print("5.quit")
a3 = int(input('enter your choice:>'))
if (a3 == 1):
c.product_search()
continue
if (a3 == 2):
c.add_product()
continue
if (a3 == 3):
c.update_price()
continue
if (a3 == 4):
c.update_quantity()
continue
if (a3 == 5):
break
else:
continue
if (a2 == 3):
while (1):
print("1.buy product")
print('2.quit')
a4 = int(input("enter your choice:>"))
if (a4 == 1):
d.buy_product()
continue
if (a4 == 2):
break
else:
continue
if (a2 == 4):
quit()
else:
print("wrong choice")
from go import *
import product
reload(product)
import make_page
reload(make_page)
basedir = '/Users/dcollins/RESEARCH3/Paper19_47_overlap/0000_main_plots/'
basedir = '/Users/dcollins/RESEARCH3/Paper19_47_overlap/0000_main_plots/'
glob1 = "%s/density_radius/density_radius_c????.png" % basedir
reg1 = re.compile(r"%s/density_radius/density_radius_c(\d\d\d\d).png" %
basedir)
p1 = product.product('rho_r',
regexp=reg1,
myglob=glob1,
parameters=['core_id'],
style='single',
width=400)
p1.get_frames()
glob1 = "%s/core_proj_follow/density_radius_c????.png" % basedir
glob2 = r"%s/core_proj_follow/follow_c????_n????_centered_Projection_x_density.png" % (
basedir)
reg2 = re.compile(
r"%s/core_proj_follow/follow_c(\d\d\d\d)_n(\d\d\d\d)_centered_Projection_x_density.png"
% (basedir))
p2 = product.product('core_proj_follow',
regexp=reg2,
myglob=glob2,
parameters=['core_id', 'frame'],
style='frames',
width=400)
#p2.check_glob()
#sim_list=['u301']
for this_simname in sim_list:
print('run', this_simname)
#p_tc_raw = product.product('Tc_raw',fname='%s/data_small/%s_ct.h5'%(basedir,this_simname),field='collapse_times',style='value',width=400)
#p_tc_raw_log = product.product('Log Tc_raw',fname='%s/data_small/%s_mean_collapse_log.h5'%(basedir,this_simname),field='collapse_times',style='value',width=400,number_format="%0.2f")
#p_distance = product.product('Log Distance to Next',fname='%s/data_small/%s_neighbors_distance_0_log.h5'%(basedir,this_simname),field='distance_0',style='value',width=400,number_format='%0.2f')
#p_mean_density = product.product('Log Core Density',fname='%s/data_small/%s_neighbors_mean_density_log.h5'%(basedir,this_simname),field='mean_density',style='value',width=400, number_format='%0.2f')
#u05_neighbors_distance_0.h5
#u05_neighbors_mean_density.h5
p_peak_density = product.product(
'Peak Density',
fname="datasets_small/%s_mountain_tops_take_9.h5" % this_simname,
field='peak_density',
style='value_target_file',
width=400)
r_mountain = r"%s/mountain_tops/%s/%s_peak_p(\d\d\d\d)_34_Projection_x_density.png" % (
basedir, this_simname, this_simname)
p_mountain = product.product("mountain top",
regexp=r2,
parameters=['core_id'],
style='single',
width=400)
p_mountain.get_frames()
r_density = r"%s/density_time/%s/%s_density_6_c(\d\d\d\d).png" % (
basedir, this_simname, this_simname)
p_density = product.product("density time",
def test_product(self):
self.assertEqual(product.product([1, 2], [3, 4]),
'(1, 3) (1, 4) (2, 3) (2, 4)')
def run(iterables):
list(product(iterables))
from go import *
import product
reload(product)
import make_page
reload(make_page)
basedir = '/Users/dcollins/RESEARCH3_USE_R4/Paper19_47_overlap/0000_main_plots/'
glob1 = "%s/density_radius/density_radius_c????.png" % basedir
reg1 = re.compile(r"%s/density_radius/density_radius_c(\d\d\d\d).png" %
basedir)
p1 = product.product('rho_r',
regexp=reg1,
myglob=glob1,
parameters=['core_id'],
style='single',
width=400)
p1.get_frames()
glob1 = "%s/core_proj_follow/density_radius_c????.png" % basedir
glob2 = r"%s/core_proj_follow/follow_c????_n????_centered_Projection_x_density.png" % (
basedir)
reg2 = re.compile(
r"%s/core_proj_follow/follow_c(\d\d\d\d)_n(\d\d\d\d)_centered_Projection_x_density.png"
% (basedir))
p2 = product.product('core_proj_follow',
regexp=reg2,
myglob=glob2,
parameters=['core_id', 'frame'],
style='frames',
width=400)
from product import product
from jssp_instance import instance
from construct_heurstic import construct_sol
from solution import solution
from tabu_new import tabu_serach
import time
start_time = time.time()
mfab = 3
n = 6
lin = 2
netmin = [0.5, 1]
netmaj = [4, 16]
jssp = []
prod1 = product("Produit1", [3, 5, 3, 32, 0], 32, 1, 14, 14, 1)
prod2 = product("Produit2", [3, 5, 3, 42, 0], 42, 1, 6, 6, 1 )
prod3 = product("Produit3", [3, 5, 3, 44, 44], 44, 1, 0, 0, 1)
prod4 = product("Produit4", [3, 5, 3, 0, 30], 30, 1, 0, 0, 1)
prod5 = product("Produit5", [3, 5, 3, 0, 48], 48, 1, 0, 0, 1)
prod6 = product("Produit6", [3, 5, 3, 32, 0], 32, 1, 0, 0, 1)
prod = [prod1, prod2, prod3, prod4,prod5,prod6]
jssp = instance(mfab, lin, netmin, netmaj, prod)
jssp.process_input()
print("b=", jssp.b)
print("g=", jssp.g)
print("fab=", jssp.fab)
print("con=", jssp.con)
sol_const = construct_sol(jssp)
sol_const.greedy()
try:
return int(value)
except:
return value
@signature.setter
def signature(self, value):
self.builder.tkvariables["signature"].set(value)
if __name__ == '__main__':
colorama.init()
if len(sys.argv) > 1 and sys.argv[1] == "product":
signer = product()
modulo = 1014265245160156964
bounds = 2**60, 2**64
else:
signer = addition()
modulo = 4386756709
bounds = 2**32, 2**40
app = MyApplication(signer, bounds)
app.modulo = modulo
ready = False
while not ready:
try:
app.makeKeys()
except ValueError as e:
def test_one_postive_and_one_negative_integer(self):
"""
product(2, -3) should return -6
"""
self.assertEqual(product(2,-3), -6)
def select_mip(scenario_selected, demand_scenarios, demand_possibility,
booming_demand, T, delay_length):
K = len(demand_possibility[0]) # scenario number in a period
M = len(scenario_selected) # total selected scenario number
S = K**T # total scenario number
N = len(demand_scenarios[0]) # number of items
# parameter values
ini_I = [0, 0, 0]
prices = [189, 144, 239]
vari_costs = [140, 70, 150]
ini_cash = 20000
overhead_cost = [2 * i for i in overhead_cost]
discount_rate = 0.003
B = 10000 # total quantity of order loan
ro = 0.015 # loan rate
MM = 10000
scenario_permulations = product.product(range(K), T)
scenario_select_detail = [[0 for t in range(T)] for i in range(M)]
index = 0
for i in scenario_selected:
scenario_select_detail[index] = scenario_permulations[i]
index = index + 1
# set values for scenario links: whether scenario i links with scenario j in period t
# should be checked and revised
scenarioLink = [[[0 for s in range(M)] for s in range(M)]
for t in range(T)]
for t in range(T):
for i in range(M):
for j in range(M):
if t == 0:
if scenario_select_detail[i][t] == scenario_select_detail[
j][t]:
scenarioLink[t][i][j] = 1
else:
if scenarioLink[t - 1][i][j] == 1 and \
scenario_select_detail[i][t] == scenario_select_detail[j][t]:
scenarioLink[t][i][j] = 1
# set values for scenario probabilities
scenario_probs = [0 for s in range(M)]
for s in range(M):
index = scenario_permulations[scenario_selected[s]][0]
scenario_probs[s] = demand_possibility[booming_demand[0]][index]
for i in range(1, len(scenario_permulations[scenario_selected[s]])):
index = scenario_permulations[scenario_selected[s]][i]
scenario_probs[s] = scenario_probs[s] * demand_possibility[
booming_demand[i]][index]
scenario_probs_all = [0 for s in range(S)]
for s in range(S):
index = scenario_permulations[s][0]
scenario_probs_all[s] = demand_possibility[booming_demand[0]][index]
for i in range(1, len(scenario_permulations[s])):
index = scenario_permulations[s][i]
scenario_probs_all[s] = scenario_probs_all[s] * demand_possibility[
booming_demand[i]][index]
# add probability
d = [[0 for s in range(S)] for s in range(S)]
for i in range(S):
for j in range(i, S):
for k in range(len(scenario_permulations[0])):
d[i][j] += (scenario_permulations[i][k] -
scenario_permulations[j][k])**2
d[i][j] = math.sqrt(d[i][j])
d[j][i] = d[i][j]
for i in range(S):
if i not in scenario_selected:
min_d = 1000000
min_index = 0
for j in range(M):
if d[i][scenario_selected[j]] < min_d:
min_d = d[i][scenario_selected[j]]
min_index = j
scenario_probs[
min_index] = scenario_probs[min_index] + scenario_probs_all[i]
try:
# Create a new model
m = Model("select-scenario-mip")
# Create variables
Q = [[[m.addVar(vtype=GRB.CONTINUOUS) for s in range(M)]
for n in range(N)] for t in range(T)
] # ordering quantity in each period for each product
I = [[[m.addVar(vtype=GRB.CONTINUOUS) for s in range(M)]
for n in range(N)] for t in range(T)
] # end-of-period inventory in each period for each product
delta = [[[m.addVar(vtype=GRB.BINARY) for s in range(M)]
for n in range(N)]
for t in range(T)] # whether lost-sale not occurs
C = [[LinExpr() for s in range(M)]
for t in range(T)] # LinExpr, end-of-period cash in each period
R = [[[LinExpr() for s in range(M)] for n in range(N)]
for t in range(T + delay_length)
] # LinExpr, revenue for each product in each period
# revenue expression
for s in range(M):
for n in range(N):
for t in range(T + delay_length):
if t < delay_length:
R[t][n][s] = LinExpr(0)
else:
if t == delay_length:
R[t][n][s] = prices[n] * (
ini_I[n] + Q[t - delay_length][n][s] -
I[t - delay_length][n][s])
else:
R[t][n][s] = prices[n] * (
I[t - delay_length - 1][n][s] +
Q[t - delay_length][n][s] -
I[t - delay_length][n][s])
m.update()
# cash flow
revenue_total = [[LinExpr() for t in range(T)] for s in range(M)]
vari_costs_total = [[LinExpr() for t in range(T)] for s in range(M)]
expect_revenue_total = [LinExpr() for t in range(T)]
expect_vari_costs_total = [LinExpr() for t in range(T)]
for s in range(M):
for t in range(T):
revenue_total[s][t] = sum([R[t][n][s] for n in range(N)])
vari_costs_total[s][t] = sum(
[vari_costs[n] * Q[t][n][s] for n in range(N)])
if t == 0:
C[t][s] = ini_cash + revenue_total[s][
t] - vari_costs_total[s][t] - overhead_cost[t]
else:
C[t][s] = C[t - 1][s] + revenue_total[s][
t] - vari_costs_total[s][t] - overhead_cost[t]
for t in range(T):
expect_revenue_total[t] = sum(
[revenue_total[s][t] * scenario_probs[s] for s in range(M)])
expect_vari_costs_total[t] = sum(
[vari_costs_total[s][t] * scenario_probs[s] for s in range(M)])
m.update()
# objective function
discounted_cash = [LinExpr() for s in range(M)]
for s in range(M):
for n in range(N):
for k in range(delay_length):
discounted_cash[s] = discounted_cash[s] + R[
T + k][n][s] / (1 + discount_rate)**(k + 1)
final_cash = sum([
scenario_probs[s] * (C[T - 1][s] + discounted_cash[s])
for s in range(M)
])
expect_discounted_cash = sum(
[scenario_probs[s] * (discounted_cash[s]) for s in range(M)])
# Set objective
m.update()
m.setObjective(final_cash, GRB.MAXIMIZE)
# Add constraints
# inventory flow
for s in range(M):
for n in range(N):
for t in range(T):
index = scenario_permulations[s][t]
index2 = booming_demand[t]
if t == 0:
m.addConstr(I[t][n][s] <= ini_I[n] + Q[t][n][s] -
demand_scenarios[index2][n][index] +
(1 - delta[t][n][s]) * MM)
m.addConstr(I[t][n][s] >= ini_I[n] + Q[t][n][s] -
demand_scenarios[index2][n][index] -
(1 - delta[t][n][s]) * MM)
m.addConstr(ini_I[n] + Q[t][n][s] -
demand_scenarios[index2][n][index] <=
delta[t][n][s] * MM - 0.1)
m.addConstr(
ini_I[n] +
Q[t][n][s] >= demand_scenarios[index2][n][index] -
(1 - delta[t][n][s]) * MM)
else:
m.addConstr(I[t][n][s] <= I[t - 1][n][s] + Q[t][n][s] -
demand_scenarios[index2][n][index] +
(1 - delta[t][n][s]) * MM)
m.addConstr(I[t][n][s] >= I[t - 1][n][s] + Q[t][n][s] -
demand_scenarios[index2][n][index] -
(1 - delta[t][n][s]) * MM)
m.addConstr(I[t - 1][n][s] + Q[t][n][s] -
demand_scenarios[index2][n][index] <=
delta[t][n][s] * MM - 0.1)
m.addConstr(
I[t - 1][n][s] +
Q[t][n][s] >= demand_scenarios[index2][n][index] -
(1 - delta[t][n][s]) * MM)
m.addConstr(I[t][n][s] <= delta[t][n][s] * MM)
# m.computeIIS() # this function is only for infeasible model
# m.write("model.ilp")
# cash constraint
for s in range(M):
for t in range(T):
if t == 0:
m.addConstr(
ini_cash >=
sum([vari_costs[n] * Q[t][n][s] for n in range(N)]) +
overhead_cost[t]) # cash constaints
else:
m.addConstr(
C[t - 1][s] >=
sum([vari_costs[n] * Q[t][n][s] for n in range(N)]) +
overhead_cost[t]) # cash constaints
# non-negativity of I_t
for s in range(M):
for n in range(N):
for t in range(T):
m.addConstr(I[t][n][s] >= 0)
# non-anticipativity
# s1 与 s 的顺序没啥影响
# no need for I, R, C
for t in range(T):
for n in range(N):
for s in range(M):
m.addConstr(sum([scenarioLink[t][s1][s] * scenario_probs[s1] * Q[t][n][s1] for s1 in range(M)]) == \
Q[t][n][s] * sum([scenarioLink[t][s1][s] * scenario_probs[s1] for s1 in range(M)]))
m.addConstr(sum([scenarioLink[t][s1][s] * scenario_probs[s1] * I[t][n][s1] for s1 in range(M)]) == \
I[t][n][s] * sum([scenarioLink[t][s1][s] * scenario_probs[s1] for s1 in range(M)]))
m.addConstr(
sum([scenarioLink[t][s1][s] * scenario_probs[s1] * delta[t][n][s1] for s1 in range(M)]) == \
delta[t][n][s] * sum([scenarioLink[t][s1][s] * scenario_probs[s1] for s1 in range(M)]))
# first-stage decision
for s in range(M - 1):
for n in range(N):
m.addConstr(Q[0][n][s] == Q[0][n][s + 1])
# solve
m.update()
m.optimize()
print('')
# output in txt files
Qv = [[[0 for s in range(M)] for n in range(N)] for t in range(T)
] # ordering quantity in each period for each product
Iv = [[[0 for s in range(M)] for n in range(N)] for t in range(T)
] # end-of-period inventory in each period for each product
deltav = [[[0 for s in range(M)] for n in range(N)]
for t in range(T)] # whether lost-sale not occurs
gv = [[[0 for s in range(M)] for n in range(N)] for t in range(T)
] # order-loan quantity in each period for each product
with open('results.txt', 'w') as f:
f.write('*********************************\n')
f.write('ordering quantity Q in each scenario:\n')
for s in range(M):
f.write('S%d:\n' % s)
for n in range(N):
f.write('item %d: ' % n)
for t in range(T):
f.write('%.1f ' % Q[t][n][s].X)
Qv[t][n][s] = Q[t][n][s].X
f.write('\n')
f.write('\n')
f.write(
'***************************************************************************************************************\n'
)
f.write('end-of-period inventory I in each scenario:\n')
for s in range(M):
f.write('S%d:\n' % s)
for n in range(N):
f.write('item %d: ' % n)
for t in range(T):
f.write('%.1f ' % I[t][n][s].X)
Iv[t][n][s] = I[t][n][s].X
f.write('\n')
f.write('\n')
f.write(
'***************************************************************\n'
)
f.write('not lost-sale delta in each scenario:\n')
for s in range(M):
f.write('S%d:\n' % s)
for n in range(N):
f.write('item %d: ' % n)
for t in range(T):
f.write('%.1f ' % delta[t][n][s].X)
deltav[t][n][s] = delta[t][n][s].X
f.write('\n')
f.write('\n')
f.write('*********************************\n')
f.write('revenue R in each scenario:\n')
for s in range(M):
f.write('S%d:\n' % s)
for n in range(N):
f.write('item %d: ' % n)
for t in range(T):
f.write('%.1f ' % R[t][n][s].getValue())
f.write('\n')
f.write('\n')
f.write('*********************************\n')
f.write('discounted cash in each scenario:\n')
for s in range(M):
f.write('S%d: ' % s)
f.write('%.1f ' % discounted_cash[s].getValue())
f.write('\n')
f.write('*********************************\n')
f.write('end-of-period cash C in each scenario:\n')
for s in range(M):
f.write('S%d:\n' % s)
for t in range(T):
f.write('%.1f ' % C[t][s].getValue())
f.write(' %.3f:\n' % scenario_probs[s])
f.write('\n')
f.write('*********************************\n')
f.write('expectd Revenue in each period:\n')
for t in range(T):
f.write('%.1f ' % expect_revenue_total[t].getValue())
f.write('\n')
f.write('varicosts in each period:\n')
for t in range(T):
f.write('%.1f ' % expect_vari_costs_total[t].getValue())
f.write('\n')
f.write('expected end-of-period cash in each period:\n')
f.write('%.1f ' % ini_cash)
expect_cash = [LinExpr() for t in range(T)]
for t in range(T):
expect_cash[t] = sum(
[C[t][s] * scenario_probs[s] for s in range(M)])
f.write('%.1f ' % expect_cash[t].getValue())
f.write('\n')
f.write('final expected discounted cash is: %g\n' %
expect_discounted_cash.getValue())
f.write('final expected cash is: %g' % final_cash.getValue())
print('final expected value is: %g' % m.objVal)
return m.objVal
except GurobiError as e:
print('Error code ' + str(e.errno) + ": " + str(e))
except AttributeError:
print('Encountered an attribute error')
print "Loading the baseline..."
latitude, longitude, baseline_array = product.get_bayes_array(os.path.join(outdir, variety + "-product.nc4"))
print "Creating final result..."
medians = np.zeros((len(latitude), len(longitude)))
confs = np.zeros((len(latitude), len(longitude)))
for rr in range(len(latitude)):
print rr
for cc in range(len(longitude)):
values = []
for bayeskey in bayes_arrays:
array = bayes_arrays[bayeskey]
for gaezkey in gaez_grids:
grid = gaez_grids[gaezkey]
values.append(product.product(latitude, longitude, array, grid, rr, cc))
values = np.array(values) - baseline_array[rr, cc]
if np.all(map(np.isnan, values)):
#print "All NaN"
medians[rr, cc] = np.nan
confs[rr, cc] = np.nan
else:
median = np.median(values)
medians[rr, cc] = median
if median > 0:
confs[rr, cc] = (2 * sum((values < median) & (values > 0)) + sum(values == median)) / float(len(values))
elif median < 0:
confs[rr, cc] = (2 * sum((values > median) & (values < 0)) + sum(values == median)) / float(len(values))
elif median == 0:
confs[rr, cc] = sum(values == median) / float(len(values))
# using inheritance importing product
import product
# and checkoutregister classes
import checkoutregister
# adding some products into the supermarket
product.product("123", "Milk", "2 Litres", "2.0")
product.product("789", "Fruits", "2 kgs", "4.0")
product.product("456", "Bread", "", "3.5")
# greeting message generated for the user
print("-----Welcome to FedUni checkout! -----")
while True:
# using the checkoutregister class from checkoutregister file
check_pro_list_items = checkoutregister.checkoutregister()
# while condition is true run the code
while True:
main_class_list = product.product.list_products
print()
# prompt to get the entry of the product from the user
product_code_data = input("Please enter the barcode of your item: ")
# add the entered data and scan the product if it is available or not
check_pro_list_items.scan_items(product_code_data)
print()
# prompt to get the entry from the user to continue or not
user_loop = input("Would you like to scan another product? (Y/N) ").upper()
ALGO returns all the data, the three dictionaries
then here in routes, we look at the ID for the store requested, and return data for
the store opposite 3->5 5->8 8->3
then we look at this data and convert to JSON
- change numbers for locations to names
- change numbers for products to names
- add in increase/decrease/staff based on data provided (which array we select from or if staff 1/2/0)
(best_prod_per_loc_per_week)
(worst_prod_per_loc_per_week)
(staff_count_per_loc)
"""
location_map = {3: "Astoria", 5: "Lower Manhattan", 8: "Hell's Kitchen"}
product_file_name = "archive/product.csv"
prod_obj = product(product_file_name)
@app.route('/shop/{id}/insight/current')
def current_insight():
ret = algo.weekoverweek()
# return json objects for week 3-4 diffs
# look at store 5 looking at data for store 3
best_prod = ret[0][3][2]
worst_prod = ret[1][3][2]
staff_count = ret[2][3][2]
# get name of best product
# get name for worst product
# get increase or decrease staff
staff_item = None
