生理周期_Python智能预测

生理周期_智能预测
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人的生理周期呈正弦函数上下波动，查阅了一些算法，写了如下代码。

运行程序，只需输入某人生日，计算机就可智能列出此人生理周期最值（max,min），并可以图形化展示，抽取部分数据验证，程序计算准确。

但仍有一些小瑕疵，以后有空改进。

测试截图
1990,"march",4是一个90后的生日，表示1990年3月4号出生，计算机智能统计出，二月27，28,29，30日，八月8,9号，3月初是此人生理周期最差值，可参考这些时间用于攻击。

Intelligence
Physical
#time transformation
#common year, month accumulation of days
#python 2.7 import do not support """ """ mark format
import leap_common_year
def total_day_calculate(year,month,day):
which_year=leap_common_year.leap_common_year(year)
#for common year
if which_year[0].lower()=='c':
dict_of_month={"january":0,"feburary":59,"march":90,"april":120,
"may":151,"june":181,"july":212,"august":243,"september":273
,"october":304,"november":334,"december":365} #month means accumulation of days
for i in dict_of_month:
if month==i:
month=dict_of_month[i]
total_day=month+day
return total_day
#for leap year
if which_year[0].lower()=='l':
dict_of_month={"january":0,"feburary":60,"march":91,"april":121,
"may":152,"june":182,"july":213,"august":244,"september":274
,"october":305,"november":335,"december":366} for i in dict_of_month:
if month==i:
month=dict_of_month[i]
total_day=month+day
return total_day
def number_to_time(year,number):
which_year=leap_common_year.leap_common_year(year)
#for common year
if which_year[0].lower()=='c':
dict_of_month={"january":0,"feburary":59,"march":90,"april":120,
"may":151,"june":181,"july":212,"august":243,"september":273
,"october":304,"november":334,"december":365} sorted_dict_of_month=sorted(dict_of_month.items(), key=lambda d: d[1])
count=0
for i in sorted_dict_of_month:
if number<i[1]:
month=sorted_dict_of_month[count-1][0]
#print "month:",month
day=number-dict_of_month[month]
return (month,day)
count+=1
#for leap year
if which_year[0].lower()=='l':
dict_of_month={"january":0,"feburary":60,"march":91,"april":121,
"may":152,"june":182,"july":213,"august":244,"september":274
,"october":305,"november":335,"december":366} sorted_dict_of_month=sorted(dict_of_month.items(), key=lambda d: d[1])
count=0
for i in sorted_dict_of_month:
#print "i:",i
#print "i[1]:",i[1]
#print "count:",count
if number<i[1]:
#print "i[0]:",i[0]
#print "i[1]:",i[1]
month=sorted_dict_of_month[count-1][0]
#print "month:",month
day=number-dict_of_month[month]
return (month,day)
count+=1
#input birth day and period to plot your emotional,intelligent,physical sine curve
#y=sin(Bx+C),
import leap_common_year, day_transformation,math,pylab,numpy
def plot_sine_all(year,month,day):
B_emotion=(2*math.pi)/23
B_physical=(2*math.pi)/28
B_intelligence=(2*math.pi)/33
birthday_number=day_transformation.total_day_calculate(year,month,day )
initial_number_emotion=birthday_number%23 #initial_number是正弦函数起始值
initial_number_physical=birthday_number%28
initial_number_intelligence=birthday_number%33
C_emotion=(-B_emotion)*initial_number_emotion
C_physical=(-B_physical)*initial_number_physical
C_intelligence=(-B_intelligence)*initial_number_intelligence
#use numpy arange to get an array of float values.
x_values=numpy.arange(0,366,0.001) #精确值到1.4秒
y_values_emotion=numpy.sin(x_values*B_emotion+C_emotion)
#numpy.sin() 表示y值
y_values_physical=numpy.sin(x_values*B_physical+C_physical)
y_values_intelligence=numpy.sin(x_values*B_intelligence+C_intelligenc e)
pylab.plot(x_values,y_values_emotion,'r') #plot 命令允许绘制二维线图,红色是情绪图，绿色是体力图，蓝色是智力图
pylab.plot(x_values,y_values_physical,'g')
pylab.plot(x_values,y_values_intelligence,'b')
pylab.xlabel('x axis') #x轴标签命名'x values'
pylab.ylabel('y axis') #y轴标签命名'sin of x' pylab.title("red=emotion,green=physical,blue=intelligence") #
图表的题目
pylab.grid(True) #图表添加一个网格
pylab.show() #展示图表
def plot_sine_single(year,month,day,period):
B=(2*math.pi)/period
birthday_number=day_transformation.total_day_calculate(year,month,day )
initial_number=birthday_number%period #initial_number是正弦函数起始值
C=-B*initial_number
#use numpy arange to get an array of float values.
x_values=numpy.arange(0,math.pi*20,0.1)
y_values=numpy.sin(x_values*B+C) #numpy.sin() 表示y值
pylab.plot(x_values,y_values) #plot命令允许绘制二维线图
pylab.xlabel('x axis') #x轴标签命名'x values'
pylab.ylabel('y axis') #y轴标签命名'sin of x' pylab.title("sine curve") #图表的题目
pylab.grid(True) #图表添加一个网格
pylab.show() #展示图表
#to calculate the physiologic_index
#calculate_physiologic_index(year,month,day):#输入的年月日是生日import leap_common_year,day_transformation,math,pylab,numpy
physiologic_index=0
dict_physiologic_index={}
def calculate_physiologic_index(year,month,day):#输入的年月日是生日
B_emotion=(2*math.pi)/23
B_physical=(2*math.pi)/28
B_intelligence=(2*math.pi)/33
birthday_number=day_transformation.total_day_calculate(year,month,day )
initial_number_emotion=birthday_number%23 #initial_number是正弦函数起始值
initial_number_physical=birthday_number%28
initial_number_intelligence=birthday_number%33
C_emotion=(-B_emotion)*initial_number_emotion
C_physical=(-B_physical)*initial_number_physical
C_intelligence=(-B_intelligence)*initial_number_intelligence
x_values=numpy.arange(0,366,1)
y_values_emotion=numpy.sin(x_values*B_emotion+C_emotion)
#numpy.sin() 表示y值
y_values_physical=numpy.sin(x_values*B_physical+C_physical)
y_values_intelligence=numpy.sin(x_values*B_intelligence+C_intelligenc e)
# to calculate the physiologic_index
for i in x_values:
y_values_emotion=numpy.sin(i*B_emotion+C_emotion)
#numpy.sin() 表示y值
y_values_physical=numpy.sin(i*B_physical+C_physical)
y_values_intelligence=numpy.sin(i*B_intelligence+C_intelligence)
physiologic_index=(y_values_emotion+y_values_physical+y_values_intell igence)/3
dict_physiologic_index[i]=physiologic_index
small_sorted_physiologic_index=sorted(dict_physiologic_index.items(), key=lambda d:d[1],reverse=False) #排序有小到大
big_sorted_physiologic_index=sorted(dict_physiologic_index.items(),ke y=lambda d:d[1],reverse=True) #排序有小到大
#print "small_sorted_physiologic_index is:",small_sorted_physiologic_index
#print "big_sorted_physiologic_index is:",big_sorted_physiologic_index
print "day of small values are:"
i=0
while i<10:
#print big_sorted_physiologic_index[i]
#print big_sorted_physiologic_index[i][0]
#测试输出时间相对应的具体值
#print small_sorted_physiologic_index[i]
print
day_transformation.number_to_time(year,small_sorted_physiologic_index [i][0])
i+=1
print "day of big values are:"
i=0
while i<10:
print
day_transformation.number_to_time(year,big_sorted_physiologic_index[i ][0])
i+=1
#leap year and common year
def leap_common_year(year):
if year%100==0:
if year%400==0:
return "leap year"
else:
return "common year"
elif year%4==0:
return "leap year"
else:
return "common year"。