Hi,
have you tried the examples that I have provided a couple days ago,
see below? I cannot see why it should not work. These are the absolute
basics that you need to understand.
Btw, there is no need to use csv2rec unless you want/need column or row headers.
Here's a full script that does what you want. Now, please take the
time and work through the example that I have provided. In case you
need further help, please don't start a new thread but reply to this
one.
Best regards,
Daniel
# -*- coding: utf-8 -*-
import matplotlib.pyplot as plt
import pylab
import scipy
datafile1 = 'ch1_s1_lrr.csv'
datafile2 = 'ch1_s1_baf.csv'
## create dummy data
data = pylab.rand(10000,12)
pylab.savetxt(datafile1, data, delimiter=';')
pylab.savetxt(datafile2, data, delimiter=';')
## load data and transpose
a1 = pylab.loadtxt(datafile1, comments='#', delimiter=';').T
print 'loading', datafile1
b1 = pylab.loadtxt(datafile2, comments='#', delimiter=';').T
print 'loading', datafile2
## axis limits
#v1 = [0,98760,0,1]
#v2 = [0,98760,-2,2]
v1 = [0,1]
v2 = [-2,2]
plt.close('all')
plt.figure()
plt.subplot(2,1,1)
#plt.axis(v2)
plt.ylim(v2)
#plt.plot(a1, 'r.')
for i in range(6):
plt.plot(a1[i])
plt.subplot(2,1,2)
#plt.axis(v1)
plt.ylim(v1)
#plt.plot(b1, 'b.')
## need masked arrays here
## http://physics.nmt.edu/~raymond/software/python_notes/paper003.html
m = b1 >= 0.05
b1masked = scipy.ma.array(b1,mask=m)
## print first two cols
print b1masked[0:2]
for i in range(6,12):
plt.plot(b1masked[i])
plt.show()
2011/6/3 Karthikraja Velmurugan <velmurugan.karthikr...@gmail.com>:
> import matplotlib.pyplot as plt
> import pylab
> datafile1 = 'ch1_s1_lrr.csv'
> datafile2 = 'ch1_s1_baf.csv'
>
> a1 = pylab.loadtxt(datafile1, comments='#', delimiter=';')
> b1 = pylab.loadtxt(datafile2, comments='#', delimiter=';')
>
> v1 = [0,98760,0,1]
> v2 = [0,98760,-2,2]
>
> plt.figure(1)
>
> plt.subplot(2,1,1)
> print 'loading', datafile1
> plt.axis(v2)
> plt.plot(a1, 'r.')
>
> plt.subplot(2,1,2)
> print 'loading', datafile2
> plt.axis(v1)
> plt.plot(b1, 'b.')
>
> plt.show()
2011/5/30 Daniel Mader <danielstefanma...@googlemail.com>:
> Hi,
>
> the content of the CSV is stored as an array after reading. You can
> simply access rows and columns like in Matlab:
>
> firstrow = a1[0]
> firstcol = a1.T[0]
>
> The .T transposes the array.
>
> The second element of the third row would be
>
> elem32 = a1[2][1]
> which is equivalent to
> elem32 = a1[2,1]
>
> A range of e.g. rows 3 to 6 is
> range36 = a1[2:6]
>
> Please have a look here for getting started with scipy/numpy:
> http://pages.physics.cornell.edu/~myers/teaching/ComputationalMethods/python/arrays.html
> and
> http://www.scipy.org/NumPy_for_Matlab_Users
>
> Hope this helps,
> Daniel
>
> 2011/5/27 Karthikraja Velmurugan <velmurugan.karthikr...@gmail.com>:
>> Hello Daniel,
>>
>> The code you have given is simple and works fab. Thank you very much. But I
>> wasn't able to find an example which accesses the columns of a CSV files
>> when I import data through "datafile="filename.csv"" option. It will be
>> great if you could help with accessing individual columns. What excatly I am
>> looking for is to access individual coulmns (of the same CSV file), do
>> calculations using the two coumns and plot them into seperate subplots of
>> the same graph.
>> I modified the script a lil bit. Please find it below:
>>
>> import matplotlib.pyplot as plt
>> import pylab
>> datafile1 = 'ch1_s1_lrr.csv'
>> datafile2 = 'ch1_s1_baf.csv'
>> a1 = pylab.loadtxt(datafile1, comments='#', delimiter=';')
>> b1 = pylab.loadtxt(datafile2, comments='#', delimiter=';')
>> v1 = [0,98760,0,1]
>> v2 = [0,98760,-2,2]
>> plt.figure(1)
>> plt.subplot(4,1,1)
>> print 'loading', datafile1
>> plt.axis(v2)
>> plt.plot(a1, 'r.')
>> plt.subplot(4,1,2)
>> print 'loading', datafile2
>> plt.axis(v1)
>> plt.plot(b1, 'b.')
>> plt.show()
>>
>> Thank you very much in advance for your time and suggestions.
>>
>> Karthik
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