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From: Benjamin R. <ben...@ou...> - 2012-07-28 04:16:45
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On Friday, July 27, 2012, JonBL wrote: > > I'm unsure about the role of numpy method arange in Matplotlib plots. All > Matplotlib examples I have seen call numpy's method arange, and pass the > result as the first arg to Matplotlib's plot method. > > But the following works as expected: > > --- quote --- > import matplotlib.pyplot as plt > import numpy as np > > dom = [1, 3, 4, 5, 7] # Plot domain on x-axis in ascending order > of values > ran = [7, -2, 11, 5.8, 0] # Plot range on y-axis in 1-to-1 > correspondence > with domain items > > fig = plt.figure() > ax = plt.subplot(111) > ax.plot(dom, ran) > plt.grid() > plt.show() > --- end quote --- > > I'm not calling numpy.arange(arg) here, but I see the expected plot of 5 > co-ordinate points. When should I use numpy.arange(arg) instead of what I > have done above? Something to do with the domain that I want to include in > the plot? > > TIA, > Jon > > Nothing is special about arange, it is just a way to generate an array of floating point numbers, much like python's range(). You can specify start and end values and the stepsize as well, just like for range(), except the stepsize can be a floating point number. In many examples, you could use python's range() and get the same results. All that is important is to provide coordinates for each need dimension, from arange(), linspace(), range(), or some other source. I hope that clears it up. Ben Root |