How to pretty-print a numpy.array without scientific notation and with given precision?

Question

I'm curious, whether there is any way to print formatted numpy.arrays, e.g., in a way similar to this:

x = 1.23456 print '%.3f' % x 

If I want to print the numpy.array of floats, it prints several decimals, often in 'scientific' format, which is rather hard to read even for low-dimensional arrays. However, numpy.array apparently has to be printed as a string, i.e., with %s. Is there a solution for this?

Answer 1

You can use set_printoptions to set the precision of the output:

import numpy as np x=np.random.random(10) print(x) # [ 0.07837821  0.48002108  0.41274116  0.82993414  0.77610352  0.1023732 #   0.51303098  0.4617183   0.33487207  0.71162095]  np.set_printoptions(precision=3) print(x) # [ 0.078  0.48   0.413  0.83   0.776  0.102  0.513  0.462  0.335  0.712] 

And suppress suppresses the use of scientific notation for small numbers:

y=np.array([1.5e-10,1.5,1500]) print(y) # [  1.500e-10   1.500e+00   1.500e+03] np.set_printoptions(suppress=True) print(y) # [    0.      1.5  1500. ] 

See the docs for set_printoptions for other options.

---

To apply print options locally, using NumPy 1.15.0 or later, you could use the numpy.printoptions context manager. For example, inside the with-suite precision=3 and suppress=True are set:

x = np.random.random(10) with np.printoptions(precision=3, suppress=True):     print(x)     # [ 0.073  0.461  0.689  0.754  0.624  0.901  0.049  0.582  0.557  0.348] 

But outside the with-suite the print options are back to default settings:

print(x)     # [ 0.07334334  0.46132615  0.68935231  0.75379645  0.62424021  0.90115836 #   0.04879837  0.58207504  0.55694118  0.34768638] 

If you are using an earlier version of NumPy, you can create the context manager yourself. For example,

import numpy as np import contextlib  @contextlib.contextmanager def printoptions(*args, **kwargs):     original = np.get_printoptions()     np.set_printoptions(*args, **kwargs)     try:         yield     finally:          np.set_printoptions(**original)  x = np.random.random(10) with printoptions(precision=3, suppress=True):     print(x)     # [ 0.073  0.461  0.689  0.754  0.624  0.901  0.049  0.582  0.557  0.348] 

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To prevent zeros from being stripped from the end of floats:

np.set_printoptions now has a formatter parameter which allows you to specify a format function for each type.

np.set_printoptions(formatter={'float': '{: 0.3f}'.format}) print(x) 

which prints

[ 0.078  0.480  0.413  0.830  0.776  0.102  0.513  0.462  0.335  0.712] 

instead of

[ 0.078  0.48   0.413  0.83   0.776  0.102  0.513  0.462  0.335  0.712]