Created
December 11, 2017 12:29
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Demonstrate the different behaviours of numpy arange and linspace with regard to truncation error
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| import numpy as np | |
| eps = np.finfo(np.float64).eps | |
| print "This is epsilon:", eps | |
| print "\nnumpy.arange" | |
| dX = 0.1 | |
| X = np.arange(34.,38.,dX) | |
| udX = np.unique(np.diff(X)) | |
| print "Unique dX:", udX | |
| trunc_err = (np.diff(X)/dX-1)/eps | |
| print "Float truncation error (as N x eps) with arange:", trunc_err | |
| print "Mean float truncation error (as N x eps) with arange:", np.mean(trunc_err) | |
| print "\nnumpy.linspace" | |
| X = np.linspace(34.,38.,(38-34)/dX+1) | |
| udX = np.unique(np.diff(X)) | |
| print "Unique dX:", udX | |
| trunc_err = (np.diff(X)/dX-1)/eps | |
| print "Float truncation error (as N x eps) with linspace:", trunc_err | |
| print "Mean float truncation error (as N x eps) with linspace:", np.mean(trunc_err) |
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This code will print the following: