From: surfcast23 <surfcast23@gm...>  20110826 01:44:37

Hi Ryan, I think your solution will work thank you!! I did get an error though it is " f.next() # You want to skip the first line, I guess. AttributeError: '_io.TextIOWrapper' object has no attribute 'next' " thank you Khary rcnelson wrote: > > If I understand your question correctly, I may have a solution to your > problem. First of all, the statement below, when converted to Python > code, will generate an array of numbers the same length of your masses > list. >> 'y runs fron 0 to n where n == len(masses) ' > However, this statement will give you a single number: >> x = 'mass_avg = sum(masses)/len(masses)' > You will not be able to plot these two objects because of the different > sizes. If you are asking about a 'running' or cumulative mean, then you > may > want to use the cumulative sum function from Numpy (cumsum). To convert > this > into a cumulative average, you can do a simple division. > > Below is a modification to your script that incorporates this averaging > technique. (I don't know why you want to print everything. Surely you > can't > see all of the data as the file gets processed. It is also a very slow > operation... I'll just ignore those parts.) > > import numpy as np > import matplotlib.pyplot as plt > f = open('myfile.txt') > f.next() # You want to skip the first line, I guess. > mass = [] > for line in f: > # This will skip the lines that are spaces. > if line.isspace(): continue > # The strip function is unnecessary. The defalut for the split > function > takes care of that. > columns = line.split() > # Don't call the float function every time. It's a waste. > mass.append( columns[8] ) > # Here we can convert the list of strings into an array of floats with the > dtype keyword. > mass = np.array( mass, dtype='float') > # Here's the cumulative average steps. > mass_sum = np.cumsum(mass) > mass_average = mass_sum/ np.arange(1, len(mass_sum) + 1) > # If you only plot one array or list of values, they are assumed to be the > y > values. > # The x values in that case are the indices of the y value array. > plt.plot(mass_average) > plt.show() > > > Ryan > > >> Message: 5 >> Date: Thu, 25 Aug 2011 11:15:57 0700 (PDT) >> From: surfcast23 <surfcast23@...> >> Subject: Re: [Matplotlibusers] How do you Plot data generated by a >> python script? >> To: matplotlibusers@... >> MessageID: <32336570.post@...> >> ContentType: text/plain; charset=usascii >> >> >> Hi Martin, >> >> Thank for the relpy. What I have is a script that reads the data >> from >> a large file then prints out the values listed in a particular column. >> What >> I now need to do is have the information in that column plotted as the >> number of rows vs. the mean value of all of the rows. What I have so far >> is >> >> import matplotlib.pyplot as plt >> >> masses = [] >> >> f = open( 'myfile.txt','r') >> f.readline() >> for line in f: >> if line != ' ': >> line = line.strip() # Strips end of line character >> columns = line.split() # Splits into coloumn >> mass = columns[8] # Column which contains mass values >> mass = float(mass) >> masses.append(mass) >> print(mass) >> >> plt.plot() >> plt.show >> >> >> I am thinking I can do something like >> >> 'y runs fron 0 to n where n == len(masses) ' >> x = 'mass_avg = sum(masses)/len(masses)' >> >> Problem is I don' tknow how to have matplotlib do it with out giving me >> an >> error about dimentions. I would also like to do this with out having to >> write and read from another file. I alos need to to be able to work on >> files >> with ddifering numbers of rows. >> >> Thanks >> >> >> >> >> >> mdekauwe wrote: >> > >> > I wasn't quite able to follow exactly what you wanted to do but maybe >> this >> > will help. I am going to generate some "data" that I think sounds a bit >> > like yours, write it to a file, clearly you already have this. Then I >> am >> > going to read it back in and plot it, e.g. >> > >> > import matplotlib.pyplot as plt >> > import numpy as np >> > >> > # Generate some data a little like yours, I think? >> > # print it to a file, i.e. I am making your myfile.txt >> > numrows = 100 >> > numcols = 8 >> > mass = np.random.normal(0, 1, (numrows * numcols)).reshape(numrows, >> > numcols) >> > f = open("myfile.txt", "w") >> > for i in xrange(numrows): >> > for j in xrange(numcols): >> > print >>f, mass[i,j], >> > print >> f >> > f.close() >> > >> > # read the file back in >> > mass = np.loadtxt("myfile.txt") >> > >> > # plot the 8th column >> > fig = plt.figure() >> > ax = fig.add_subplot(111) >> > ax.plot(mass[:,7], 'ro') >> > ax.set_xlabel("Time") >> > ax.set_ylabel("Mass") >> > plt.show() >> > >> > >> > I wasn't clear on the mean bit, but that is easy to do with numpy, e.g. >> > >> > mean_mass = np.mean(mass[:,8]) >> > >> > etc. >> > >> > Numpy et al is great for stuff like this. >> > >> > Hope that helps, >> > >> > Martin >> > >> > >> >>  >> View this message in context: >> http://old.nabble.com/HowdoyouPlotdatageneratedbyapythonscripttp32328822p32336570.html >> Sent from the matplotlib  users mailing list archive at Nabble.com. >> >> > >  > EMC VNX: the world's simplest storage, starting under $10K > The only unified storage solution that offers unified management > Up to 160% more powerful than alternatives and 25% more efficient. > Guaranteed. http://p.sf.net/sfu/emcvnxdev2dev > _______________________________________________ > Matplotlibusers mailing list > Matplotlibusers@... > https://lists.sourceforge.net/lists/listinfo/matplotlibusers > >  View this message in context: http://old.nabble.com/HowdoyouPlotdatageneratedbyapythonscripttp32328822p32338782.html Sent from the matplotlib  users mailing list archive at Nabble.com. 