Hi,
The input is a parameter termed dipole moment. I want to see how it decays
with respect to time.
On Tue, Jun 19, 2012 at 11:12 AM, francesco oteri <francesco.ot...@gmail.com
> wrote:
> Hi bala,
> what is the input? How did you calculate it?
>
> Francesco
>
> 2012/6/19 Bala subramanian <bala.biophys...@gmail.com>
>
>> Friends,
>> I want to plot the autocorrelation of my data as a function of time as
>> given in the following link, with autocorrelation coef in Y axis and Time
>> in x-axis.
>>
>> http://www.itl.nist.gov/div898/handbook/eda/section3/autocopl.htm
>>
>> I used the following code to achieve the same using the acorr function.
>> But the acorr function doesnt seem to plot the autocorrelation coef. as a
>> function of time. Why is it so ?. The output figure is attached. I want to
>> plot the time dependent decay of my values.
>>
>>
>> import matplotlib.pyplot as plt
>> import numpy as np
>>
>> data1=np.loadtxt('oe_short.dat',usecols=(5,))
>> data2=np.loadtxt('7o_short.dat',usecols=(5,))
>>
>> #Assignments
>> FIG=plt.figure(figsize=(4.0,2.5),dpi=50)
>> FIG.subplots_adjust(hspace=0.15)
>> NR=1;NC=1
>> cols=['black','red']
>> ax1=FIG.add_subplot(NR,NC,1)
>> ax1.xcorr(data1,data1,color=cols[0],usevlines=False)
>> ax1.acorr(data2,color=cols[1],usevlines=False)
>> plt.savefig('auto.png',dpi=50)
>> plt.show()
>>
>>
>> --
>> C. Balasubramanian
>>
>>
>>
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>
>
> --
> Cordiali saluti, Dr.Oteri Francesco
>
--
C. Balasubramanian
------------------------------------------------------------------------------
Live Security Virtual Conference
Exclusive live event will cover all the ways today's security and
threat landscape has changed and how IT managers can respond. Discussions
will include endpoint security, mobile security and the latest in malware
threats. http://www.accelacomm.com/jaw/sfrnl04242012/114/50122263/
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