def save(self):
micro_material = {}
for book in self.cook_books:
for materials in book['material']:
name = self.clean(materials['name'].strip())
if name not in self.material:
self.material[name] = []
amount = self.clean(self.unit_to_en(materials['amount'].strip().lower()))
amount = self.reverse_num(amount)
if re.match(r'.*\d+.*',amount):
self.material[name].append(amount)
else:
if name not in micro_material:
micro_material[name] = []
micro_material[name].append(amount)
_material = {}
for n in self.material:
if len(self.material[n]) > 0:
_material[n] = self.material[n]
m = Material()
m.name = n
amounts = [pseg.cut(amount) for amount in self.material[n]]
amount_list = []
m.amount = []
for a in amounts:
amount = []
for _a in a:
amount.append({'word':_a.word,'flag':_a.flag})
m.amount.append(amount)
m.save()
self.material = _material
#保存数据
open(CONFIG['DATA_PATH']+'materials.json','w').write(json.dumps(self.material))
def print_name(row):
#if row[cl+1]==0 and row[cl+2]==0:return
if (row[cl + 1] == row[cl + 2] == row[cl + 3] == row[cl + 4] ==
1) or row[cl + 5] > 3:
Material.combine(row[0], row[1], row[8])
#return
#return
elif (row[cl + 1] >= 0.5
or row[cl + 2] >= 0.5) and (row[cl + 3] >= 0.5
or row[cl + 4] >= 0.5):
#try:
m1 = Material.objects(id=row[0]).only('name')
if m1:
m1 = m1.get(0)
m2 = Material.objects(id=row[1]).only('name')
if m2:
m2 = m2.get(0)
if not m1 or not m2: return
#print Material.objects(id=row[0]).only('name')[0].name, Material.objects(id=row[1]).only('name')[0].name
Material.combine(row[0], row[1], row[8], check_dict=True)
#print row[8:]
#print '-'*30
#print row[cl+1:]
#elif (row[cl+3]>=0.5 and row[cl+4]==1) or (row[cl+3]==1 and row[cl+4]>=0.5):
elif row[cl + 3] >= 0.5 and row[cl + 4] >= 0.5:
#print Material.objects(id=row[0]).only('name')[0].name, Material.objects(id=row[1]).only('name')[0].name
Material.combine(row[0], row[1], row[8], check_dict=True)
#pass
#print row[8:]
#print '*'*50
else:
pass
def print_name(row):
#if row[cl+1]==0 and row[cl+2]==0:return
if (row[cl+1] == row[cl+2] == row[cl+3] == row[cl+4] ==1) or row[cl+5]>3:
Material.combine(row[0],row[1],row[8])
#return
#return
elif (row[cl+1]>=0.5 or row[cl+2]>=0.5) and (row[cl+3]>=0.5 or row[cl+4]>=0.5):
#try:
m1 = Material.objects(id=row[0]).only('name')
if m1:
m1 = m1.get(0)
m2 = Material.objects(id=row[1]).only('name')
if m2:
m2 = m2.get(0)
if not m1 or not m2:return
#print Material.objects(id=row[0]).only('name')[0].name, Material.objects(id=row[1]).only('name')[0].name
Material.combine(row[0],row[1],row[8],check_dict=True)
#print row[8:]
#print '-'*30
#print row[cl+1:]
#elif (row[cl+3]>=0.5 and row[cl+4]==1) or (row[cl+3]==1 and row[cl+4]>=0.5):
elif row[cl+3]>=0.5 and row[cl+4]>=0.5 :
#print Material.objects(id=row[0]).only('name')[0].name, Material.objects(id=row[1]).only('name')[0].name
Material.combine(row[0],row[1],row[8],check_dict=True)
#pass
#print row[8:]
#print '*'*50
else:
pass
def save(self):
micro_material = {}
for book in self.cook_books:
for materials in book['material']:
name = self.clean(materials['name'].strip())
if name not in self.material:
self.material[name] = []
amount = self.clean(
self.unit_to_en(materials['amount'].strip().lower()))
amount = self.reverse_num(amount)
if re.match(r'.*\d+.*', amount):
self.material[name].append(amount)
else:
if name not in micro_material:
micro_material[name] = []
micro_material[name].append(amount)
_material = {}
for n in self.material:
if len(self.material[n]) > 0:
_material[n] = self.material[n]
m = Material()
m.name = n
amounts = [pseg.cut(amount) for amount in self.material[n]]
amount_list = []
m.amount = []
for a in amounts:
amount = []
for _a in a:
amount.append({'word': _a.word, 'flag': _a.flag})
m.amount.append(amount)
m.save()
self.material = _material
#保存数据
open(CONFIG['DATA_PATH'] + 'materials.json',
'w').write(json.dumps(self.material))
from config import CONFIG
from orm.Material import Material
import sys
reload(sys)
sys.setdefaultencoding("utf-8")
import json
import pandas as pd
import re
import nltk
import jieba
import jieba.posseg as pseg
data = Material.objects()
units = []
_units = {}
all_amount = {}
known_units = set([u"个", u"种", u"個", u"大个"])
for material in data:
amounts = material.amount
if material.name not in all_amount:
all_amount[material.name] = {"name": material.name, "amount": 0.0, "unit": set(), "count": 0}
for amount in amounts:
# 对分词成3个以上的，暂时忽略，如"1/4个",会拆成 "1" "/" "4" "个"
if len(amount) > 2:
continue
def __init__(self):
Material.drop_collection()
print 'Initiating complete ! Material collection droped !!'
def find_similar():
#similar = {}
similar_grid = []
global material_names
pair_done = set()
for mid1 in material_names:
for mid2 in material_names:
#对称词对跳过
if (mid2, mid1) in pair_done: continue
pair_done.add((mid1, mid2))
char_inter = material_names[mid1]['char'].intersection(
material_names[mid2]['char'])
if mid1 == mid2 or len(char_inter) == 0: continue
word_inter = material_names[mid1]['word'].intersection(
material_names[mid2]['word'])
#不要动这行，以下计算基于这些元素顺序取值
res = [
len(word_inter),
len(char_inter),
len(material_names[mid1]['word']),
len(material_names[mid2]['word']),
len(material_names[mid1]['char']),
len(material_names[mid2]['char']), ''.join(char_inter)
]
#res += [len(material_names[mid1]['cut']),len(material_names[mid2]['cut'])]
res += [
Material.objects(id=mid1).only('name')[0].name,
Material.objects(id=mid2).only('name')[0].name
]
#res += []
#similar[(mid1,mid2)] = tuple(res)
similar_grid.append([mid1, mid2] + res)
#for s in similar:
# print '%s,%s'%(s,similar[s])
df = pd.DataFrame(similar_grid)
#df = pd.DataFrame(similar_grid[:1000])
cl = len(similar_grid[0]) - 1
df[cl + 1] = df[2] / df[4] #m1 word ratio
df[cl + 2] = df[2] / df[5] #m2 word ratio
df[cl + 3] = df[3] / df[6] #m1 char ratio
df[cl + 4] = df[3] / df[7] #m2 char ratio
df[cl + 5] = (df[cl + 1] + df[cl + 2]) + (df[cl + 3] + df[cl + 4])
df = df.sort(columns=15, ascending=False)
df.to_csv('res.csv')
#sys.exit()
#df[8] = df[6]+df[7]
def print_name(row):
#if row[cl+1]==0 and row[cl+2]==0:return
if (row[cl + 1] == row[cl + 2] == row[cl + 3] == row[cl + 4] ==
1) or row[cl + 5] > 3:
Material.combine(row[0], row[1], row[8])
#return
#return
elif (row[cl + 1] >= 0.5
or row[cl + 2] >= 0.5) and (row[cl + 3] >= 0.5
or row[cl + 4] >= 0.5):
#try:
m1 = Material.objects(id=row[0]).only('name')
if m1:
m1 = m1.get(0)
m2 = Material.objects(id=row[1]).only('name')
if m2:
m2 = m2.get(0)
if not m1 or not m2: return
#print Material.objects(id=row[0]).only('name')[0].name, Material.objects(id=row[1]).only('name')[0].name
Material.combine(row[0], row[1], row[8], check_dict=True)
#print row[8:]
#print '-'*30
#print row[cl+1:]
#elif (row[cl+3]>=0.5 and row[cl+4]==1) or (row[cl+3]==1 and row[cl+4]>=0.5):
elif row[cl + 3] >= 0.5 and row[cl + 4] >= 0.5:
#print Material.objects(id=row[0]).only('name')[0].name, Material.objects(id=row[1]).only('name')[0].name
Material.combine(row[0], row[1], row[8], check_dict=True)
#pass
#print row[8:]
#print '*'*50
else:
pass
#print Material.objects(id=row[0]).only('name')[0].name, Material.objects(id=row[1]).only('name')[0].name
#pass
#print row[8:]
#print '-'*30
df.apply(print_name, axis=1)
import os, sys
sys.path.append(os.environ['DOUGUO_BASE'])
from config import CONFIG
from orm.Material import Material
import sys
reload(sys)
sys.setdefaultencoding('utf-8')
import pandas as pd
import jieba
jieba.load_userdict(CONFIG['DICT_PATH'] + "jieba_user.dict")
jieba.enable_parallel(4)
import jieba.posseg as pseg
data = Material.objects().only('name') #[:2]
#[{id:,:word:,char:}]
material_names = {}
def init_grams():
global material_names
global data
for m in data:
word = []
mn = {}
mn['word'] = set()
mn['char'] = set()
name = m.name.split(u'的')[-1]
mn['origin'] = name
import os,sys
sys.path.append(os.environ['DOUGUO_BASE'])
from config import CONFIG
from orm.Material import Material
import json
import pandas as pd
import sys
reload(sys)
sys.setdefaultencoding('utf-8')
import matplotlib.pyplot as plt
plt.rcParams['font.sans-serif'] = ['Droid Sans Fallback']
#_materials = json.loads(open('../data/materials.json','r').read())
_materials = Material.objects()
#materials = [{'name':u'%s'%m,'count':len(_materials[m])} for m in _materials if len(_materials[m])>=10]
materials = [{'name':u'%s'%m.name,'count':len(m.amount)} for m in _materials if len(m.amount)>=10]
df = pd.DataFrame(materials).sort(columns='count',ascending=False)
#导出成json
open('result/material_count.json','w').write(json.dumps(df.to_dict(outtype='records')))
fig = df.plot(kind='barh',legend=False,fontsize=6).get_figure()
plt.yticks(xrange(df.count()[0]), df['name'])
plt.xlabel(u'使用次数')
plt.ylabel(u'食材')
plt.title(u'全部作品中各食材的使用次数')
fig.savefig('out.png')
from config import CONFIG
from orm.Material import Material
import json
import pandas as pd
import sys
reload(sys)
sys.setdefaultencoding('utf-8')
import matplotlib.pyplot as plt
plt.rcParams['font.sans-serif'] = ['Droid Sans Fallback']
#_materials = json.loads(open('../data/materials.json','r').read())
_materials = Material.objects()
#materials = [{'name':u'%s'%m,'count':len(_materials[m])} for m in _materials if len(_materials[m])>=10]
materials = [{
'name': u'%s' % m.name,
'count': len(m.amount)
} for m in _materials if len(m.amount) >= 10]
df = pd.DataFrame(materials).sort(columns='count', ascending=False)
#导出成json
open('result/material_count.json',
'w').write(json.dumps(df.to_dict(outtype='records')))
fig = df.plot(kind='barh', legend=False, fontsize=6).get_figure()
plt.yticks(xrange(df.count()[0]), df['name'])
plt.xlabel(u'使用次数')
plt.ylabel(u'食材')
sys.path.append(os.environ['DOUGUO_BASE'])
from config import CONFIG
from orm.Material import Material
import sys
reload(sys)
sys.setdefaultencoding('utf-8')
import json
import pandas as pd
import re
import nltk
import jieba
import jieba.posseg as pseg
data = Material.objects()
units = []
_units = {}
all_amount = {}
known_units = set([u'个', u'种', u'個', u'大个'])
for material in data:
amounts = material.amount
if material.name not in all_amount:
all_amount[material.name] = {
'name': material.name,
'amount': 0.0,
'unit': set(),
'count': 0
}
def find_similar():
#similar = {}
similar_grid = []
global material_names
pair_done = set()
for mid1 in material_names:
for mid2 in material_names:
#对称词对跳过
if (mid2,mid1) in pair_done:continue
pair_done.add((mid1,mid2))
char_inter = material_names[mid1]['char'].intersection(material_names[mid2]['char'])
if mid1 == mid2 or len(char_inter) == 0 :continue
word_inter = material_names[mid1]['word'].intersection(material_names[mid2]['word'])
#不要动这行，以下计算基于这些元素顺序取值
res = [len(word_inter),len(char_inter),len(material_names[mid1]['word']),len(material_names[mid2]['word']),len(material_names[mid1]['char']),len(material_names[mid2]['char']),''.join(char_inter)]
#res += [len(material_names[mid1]['cut']),len(material_names[mid2]['cut'])]
res += [Material.objects(id=mid1).only('name')[0].name, Material.objects(id=mid2).only('name')[0].name]
#res += []
#similar[(mid1,mid2)] = tuple(res)
similar_grid.append([mid1,mid2]+res)
#for s in similar:
# print '%s,%s'%(s,similar[s])
df = pd.DataFrame(similar_grid)
#df = pd.DataFrame(similar_grid[:1000])
cl = len(similar_grid[0])-1
df[cl+1] = df[2]/df[4]#m1 word ratio
df[cl+2] = df[2]/df[5]#m2 word ratio
df[cl+3] = df[3]/df[6]#m1 char ratio
df[cl+4] = df[3]/df[7]#m2 char ratio
df[cl+5] = (df[cl+1]+df[cl+2]) + (df[cl+3]+df[cl+4])
df = df.sort(columns=15,ascending=False)
df.to_csv('res.csv')
#sys.exit()
#df[8] = df[6]+df[7]
def print_name(row):
#if row[cl+1]==0 and row[cl+2]==0:return
if (row[cl+1] == row[cl+2] == row[cl+3] == row[cl+4] ==1) or row[cl+5]>3:
Material.combine(row[0],row[1],row[8])
#return
#return
elif (row[cl+1]>=0.5 or row[cl+2]>=0.5) and (row[cl+3]>=0.5 or row[cl+4]>=0.5):
#try:
m1 = Material.objects(id=row[0]).only('name')
if m1:
m1 = m1.get(0)
m2 = Material.objects(id=row[1]).only('name')
if m2:
m2 = m2.get(0)
if not m1 or not m2:return
#print Material.objects(id=row[0]).only('name')[0].name, Material.objects(id=row[1]).only('name')[0].name
Material.combine(row[0],row[1],row[8],check_dict=True)
#print row[8:]
#print '-'*30
#print row[cl+1:]
#elif (row[cl+3]>=0.5 and row[cl+4]==1) or (row[cl+3]==1 and row[cl+4]>=0.5):
elif row[cl+3]>=0.5 and row[cl+4]>=0.5 :
#print Material.objects(id=row[0]).only('name')[0].name, Material.objects(id=row[1]).only('name')[0].name
Material.combine(row[0],row[1],row[8],check_dict=True)
#pass
#print row[8:]
#print '*'*50
else:
pass
#print Material.objects(id=row[0]).only('name')[0].name, Material.objects(id=row[1]).only('name')[0].name
#pass
#print row[8:]
#print '-'*30
df.apply(print_name,axis=1)
import os,sys
sys.path.append(os.environ['DOUGUO_BASE'])
from config import CONFIG
from orm.Material import Material
import sys
reload(sys)
sys.setdefaultencoding('utf-8')
import pandas as pd
import jieba
jieba.load_userdict(CONFIG['DICT_PATH']+"jieba_user.dict")
jieba.enable_parallel(4)
import jieba.posseg as pseg
data = Material.objects().only('name')#[:2]
#[{id:,:word:,char:}]
material_names = {}
def init_grams():
global material_names
global data
for m in data:
word = []
mn = {}
mn['word'] = set()
mn['char'] = set()
name = m.name.split(u'的')[-1]
mn['origin'] = name
for pair in pseg.cut(name):
def __init__(self):
Material.drop_collection()
print 'Initiating complete ! Material collection droped !!'
