def get_update_frame_interval(self, tracking_fps):
source_video_fps = self.get_source_video_fps()
interval = float(source_video_fps / tracking_fps)
# round
interval = Context(prec=1, rounding=ROUND_HALF_UP).create_decimal(interval)
self.pym.PY_LOG(False, 'D', self.__class__, 'update frame interval : %.2f' % interval)
return interval
def get_pick_up_frame_interval(self, vott_video_fps):
source_video_fps = self.get_source_video_fps()
self.pym.PY_LOG(False, 'D', self.__class__, 'source_video_fps: %d' % source_video_fps)
interval = float(source_video_fps / vott_video_fps)
# round
interval = Context(prec=1, rounding=ROUND_HALF_UP).create_decimal(interval)
self.pym.PY_LOG(False, 'D', self.__class__, 'pick up frame interval : %.2f' % interval)
return interval
def Check_mouse_speed(messageL):
global hit_flag
global start
global end
global text
if hit_flag == 0:
start = time.perf_counter()
hit_flag = 1
var_username.set("开始")
messageL["bg"] = "green"
else:
hit_flag = 0
end = time.perf_counter()
end = end - start
#print(Context(prec=5, rounding=ROUND_HALF_UP).create_decimal('1.315097868'))
text = str(
Context(prec=5, rounding=ROUND_HALF_UP).create_decimal(
str(end))) + "s"
var_username.set(text)
messageL["bg"] = "red"
①.当被修约的值为5时，如果他前面的数为偶数且被修约数的后面没有数时则舍弃；
②.当被修约的值为5时，如果他前面的数为偶数时且被修约数的后面还有数时，则进位。
③.当被修约的值为5时，如果他前面的数为奇数时则进位；
被修约的数字等于5时，要看5前面的数字，
若是奇数则进位，
若是偶数则将5舍掉，即修约后末尾数字都成为偶数；
若5的后面还有不为“0”的任何数，则此时无论5的前面是奇数还是偶数，均应进位。
'''
print(round(22.5))
print(round(22.51))
print(round(23.5))
print(round(22.51))
#四舍五入方法
# 1.扩大100倍然后缩小100
# 2.用decmicial模块
from _pydecimal import Decimal, Context, ROUND_HALF_UP
print(Context(prec=4, rounding=ROUND_HALF_UP).create_decimal('0.3255'))
#利用’’%.af’’%b——其中 b 代表要限定的数字， a 代表要求限定小数点的位数，结果自动四舍五入。
c = 1.264871331241212
# for each in data:
# print("%.3f"%each)
data = [[22.4999, 22.5551, 23.5555, 23.5551],
[22.5555, 22.5551, 23.5555, 23.5551]]
print(np.round(data, decimals=3))
print(type(np.round(1.23456, decimals=3)))
def roundValue(value, n=None):
return (Context(prec=3, rounding=ROUND_HALF_UP).create_decimal(str(value)))
def result(self, festival, product_id, source_id):
self.result_data[str(product_id)] = {}
if self.oneday:
self.result_data[str(product_id)][str(self.special_day_year)] = []
if source_id:
#Pandas dataframe 模式
df_product_id = self.table.query(
f'product_id in @product_id and (source_id in @source_id)')
#Django ORM 模式
# df_product_id = self.table.filter(product__in=product_id).filter(source__in=source_id)
else:
#Pandas dataframe 模式
df_product_id = self.table.query(f'product_id in @product_id')
#Django ORM 模式
# df_product_id = self.table.filter(product__in=product_id)
#Pandas dataframe 模式
if df_product_id['avg_price'].any():
has_volume = df_product_id['volume'].notna().sum(
) / df_product_id['avg_price'].count() > 0.8
has_weight = df_product_id['avg_weight'].notna().sum(
) / df_product_id['avg_price'].count() > 0.8
else:
has_volume = False
has_weight = False
if has_volume and has_weight:
avgprice = (df_product_id['avg_price'] *
df_product_id['avg_weight'] *
df_product_id['volume']).sum() / (
df_product_id['avg_weight'] *
df_product_id['volume']).sum()
elif has_volume:
avgprice = (df_product_id['avg_price'] *
df_product_id['volume']
).sum() / df_product_id['volume'].sum()
else:
avgprice = df_product_id['avg_price'].mean()
#Django ORM 模式
# total_price = list()
# total_volume = list()
# if df_product_id.count():
# if df_product_id.filter(volume__isnull=False).count() / df_product_id.count() > 0.8:
# for q in df_product_id:
# total_price.append(q.avg_price * q.volume)
# total_volume.append(q.volume)
# avgprice = sum(total_price) / sum(total_volume) if len(total_volume) else 0
# else:
# for q in df_product_id:
# total_price.append(q.avg_price)
# avgprice = sum(total_price) / len(total_price) if len(total_price) else 0
# else:
# avgprice = 'nan'
self.result_data[str(product_id)][str(
self.special_day_year)].append(
float(
Context(
prec=28,
rounding=ROUND_HALF_UP).create_decimal(avgprice)))
else:
for y in range(self.roc_before5years, self.roc_year + 1):
self.result_data[str(product_id)][str(y)] = []
for y in range(self.roc_before5years, self.roc_year + 1):
if festival == 1:
date_range = self.Chinese_New_Year_dict[str(y)]
if festival == 2:
date_range = self.Dragon_Boat_Festival_dict[str(y)]
if festival == 3:
date_range = self.Mid_Autumn_Festival_dict[str(y)]
for d in date_range:
start_date = datetime.strptime(
"{}".format(d.split('~')[0]), "%Y-%m-%d").date()
end_date = datetime.strptime("{}".format(d.split('~')[1]),
"%Y-%m-%d").date()
if source_id:
df_product_id = self.table.query(
f'product_id in @product_id and date >= "{start_date}" and date <= "{end_date}" and (source_id in @source_id)'
)
# df_product_id = self.table.filter(product__in=product_id).filter(source__in=source_id).filter(date >=start_date).filter(date <= end_date)
else:
df_product_id = self.table.query(
f'product_id in @product_id and date >= "{start_date}" and date <= "{end_date}"'
)
# df_product_id = self.table.filter(product__in=product_id).filter(date >=start_date).filter(date <= end_date)
if df_product_id.shape[0]:
has_volume = df_product_id['volume'].count(
) / df_product_id.shape[0] > 0.8
has_weight = df_product_id['avg_weight'].count(
) / df_product_id.shape[0] > 0.8
else:
has_volume = False
has_weight = False
if has_volume and has_weight:
avgprice = (df_product_id['avg_price'] *
df_product_id['avg_weight'] *
df_product_id['volume']).sum() / (
df_product_id['avg_weight'] *
df_product_id['volume']).sum()
elif has_volume:
avgprice = (df_product_id['avg_price'] *
df_product_id['volume']
).sum() / df_product_id['volume'].sum()
else:
avgprice = df_product_id['avg_price'].mean()
# total_price = list()
# total_volume = list()
# if df_product_id.count():
# if df_product_id.filter(volume__isnull=False).count() / df_product_id.count() > 0.8:
# for q in df_product_id:
# total_price.append(q.avg_price * q.volume)
# total_volume.append(q.volume)
# avgprice = sum(total_price) / sum(total_volume) if len(total_volume) else 0
# else:
# for q in df_product_id:
# total_price.append(q.avg_price)
# avgprice = sum(total_price) / len(total_price) if len(total_price) else 0
# else:
# avgprice = 'nan'
self.result_data[str(product_id)][str(y)].append(
float(
Context(prec=28,
rounding=ROUND_HALF_UP).create_decimal(
avgprice)))
return self.result_data
def area_proportion(convert_target, full_size):
new_convert_target = convert_target*100
result = Context(prec=3, rounding=ROUND_HALF_UP).create_decimal((new_convert_target*100)/full_size)
return result