I have a .dat file that contains two columns of numbers so it looks something like this:
111 112
110.9 109
103 103
and so on.
<import numpy as np
import matplotlib.pyplot as plot
#data = np.loadtxt("plot_me.dat")
#x,y=np.loadtxt("plot_me.dat",unpack=True) #thanks warren!
#x,y = zip(*data)
#plot.plot(x, y, linewidth=2.0)
plot.plot(*np.loadtxt("plot_me.dat",unpack=True), linewidth=2.0)
plot.show()
[Edit]Thanks for the tip i think its as compact as possible now :P
If you want it to be log10 just call log10 on the nparray)
plot.plot(*np.log10(np.loadtxt("plot_me.dat",unpack=True)), linewidth=2.0)
Numpy doesn't support plotting by itself. You usually would use matplotlib for plotting numpy arrays.
If you just want to "look into the file", I think the easiest way would be to use plotfile.
import matplotlib.pyplot as plt
plt.plotfile('data.dat', delimiter=' ', cols=(0, 1),
names=('col1', 'col2'), marker='o')
plt.show()
You can use this function almost like gnuplot
from within ipython:
$ ipython --pylab
...
...
In [1]: plt.plotfile('data.dat', delimiter=' ', cols=(0, 1),
... names=('col1', 'col2'), marker='o')
or put it in a shell script and pass the arguments to it to use it directly from your shell