曲线拟合到形式'datetime'中的时间序列? [英] Curve Fitting to a time series in the formate 'datetime'?

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问题描述

这是我的问题: polyfit 不采用datetime值,因此我将日期时间转换为 mktime 多项式拟合工作

  z4 = polyfit(d,y,3)
p4 = poly1d(z4)

然而,对于情节,我希望在轴上的datetime描述,没有找出如何做那。你可以帮助我吗?

  fig = plt.figure(1)
cx = fig.add_subplot(111)

xx = linspace(0,d [3],100)
pylab.plot(d,y,'+',xx,p4(xx),' - g')
cx.plot(d,y,'+',color ='b',label ='blub')
plt.errorbar(d,y,
yerr,
marker = '''
color ='k',
ecolor ='b',
markerfacecolor ='b',
label =series 1,
capsize = 0,
linestyle ='')

cx.grid()
cx.set_ylim(0,0.03)
plt.show()

其余代码:

  import numpy as np 
import matplotlib.pyplot as plt
from matplotlib import axis
from datetime import datetime
from numpy import *
import pylab
进口时间

我的前4个时间数据点

  x = [datetime(1978,7,7),
datetime(1980,9,26),
datetime(1983,8,1),
datetime(1985,8,8)]

d = []
for i in x:
d.append(time.mktime(i.timetuple()))

我的前4个数据值

  y = [0.00134328779552718,
0.00155187668863844,
0.0039431374327427,
0.00780037563783297]

我计算出的误差标准偏差

  yerr = [0.0000137547160254577,
0.0000225670232594083,
0.000105623642510075,
0.00011343121508]


解决方案

而不是绘制数据库,请使用相关的数据时间。






  import numpy as np 
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
import datetime as DT
import时间

dates = [DT.datetime(1978,7,7),
DT.datetime(1980,9,26),
DT.datetime (1983,8,1),
DT.datetime(1985,8,8)]

y = [0.00134328779552718,
0.00155187668863844,
0.0039431374327427,
0.00780037563783297]


yerr = [0.0000137547160254577,
0.0000225670232594083,
0.000105623642510075,
0.00011343121508]

x = mdates.date2num (日期)

z4 = np.polyfit(x,y,3)
p4 = np.poly1d(z4)

fig,cx = plt.subplots ()

xx = np.linspace(x.min(),x.max(),100)
dd = mdates.num2date(xx)

cx.plot(dd,p4(xx),'-g')
cx.plot(dates,y,'+',color ='b',label ='blub')
cx。 errorbar(dates,y,
yerr,
marker ='。',
color ='k',
ecolor ='b',
markerfacecolor ='b ',
label =series 1,
capsize = 0,
linestyle ='')

cx.grid()
cx.set_ylim (0,0.03)
plt



$ p



$ p $ img src =https://i.stack.imgur.com/X0VVJ.pngalt =在此输入图像描述>



请注意您的代码 x 表示数据列表,而 d 表示数字。我已经决定扭转:我使用日期来获取数据列表,而 x 来表示数字。


Here is my problem: polyfit does not take datetime values, so that I converted datetime with mktime producing the polynomial fit works

z4 = polyfit(d, y, 3) 
p4 = poly1d(z4)

For the plot however, I would like the datetime description on the axis and didn't # figure out how to do that. Can you help me?

fig = plt.figure(1)
cx= fig.add_subplot(111) 

xx = linspace(0,  d[3], 100)
pylab.plot(d, y, '+', xx, p4(xx),'-g')
cx.plot(d, y,'+', color= 'b', label='blub')
plt.errorbar(d, y,
           yerr,
           marker='.',
           color='k',
           ecolor='b',
           markerfacecolor='b',
           label="series 1",
           capsize=0,
           linestyle='')

cx.grid()
cx.set_ylim(0,0.03)
plt.show()

rest of the code:

import numpy as np
import matplotlib.pyplot as plt
from matplotlib import axis
from datetime import datetime
from numpy import *
import pylab
import time

my first 4 time data points

x = [datetime(1978, 7, 7), 
     datetime(1980, 9, 26), 
     datetime(1983, 8, 1), 
     datetime(1985,8,8)]

d=[]
for i in x:
    d.append(time.mktime(i.timetuple()))

my first 4 data values

y = [0.00134328779552718,
     0.00155187668863844,
     0.0039431374327427,
     0.00780037563783297]

my calculated standard deviations for error bars

yerr = [0.0000137547160254577,
        0.0000225670232594083,
        0.000105623642510075,
        0.00011343121508]

解决方案

Instead of plotting datenums, use the associated datetimes.


import numpy as np
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
import datetime as DT
import time

dates = [DT.datetime(1978, 7, 7),
     DT.datetime(1980, 9, 26),
     DT.datetime(1983, 8, 1),
     DT.datetime(1985, 8, 8)]

y = [0.00134328779552718,
     0.00155187668863844,
     0.0039431374327427,
     0.00780037563783297]


yerr = [0.0000137547160254577,
        0.0000225670232594083,
        0.000105623642510075,
        0.00011343121508]

x = mdates.date2num(dates)

z4 = np.polyfit(x, y, 3)
p4 = np.poly1d(z4)

fig, cx = plt.subplots()

xx = np.linspace(x.min(), x.max(), 100)
dd = mdates.num2date(xx)

cx.plot(dd, p4(xx), '-g')
cx.plot(dates, y, '+', color='b', label='blub')
cx.errorbar(dates, y,
             yerr,
             marker='.',
             color='k',
             ecolor='b',
             markerfacecolor='b',
             label="series 1",
             capsize=0,
             linestyle='')

cx.grid()
cx.set_ylim(0, 0.03)
plt.show()

yields

Note in your code, x represented a list of datetimes, and d represented numbers. I've decided to reverse that: I use dates for a list of datetimes, and x to represent numbers.

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