Python Numpy – Suppress Scientific Notation in Array

number-formattingnumpypythonscientific-notation

I have a nested Python list that looks like the following:

my_list = [[3.74, 5162, 13683628846.64, 12783387559.86, 1.81],
 [9.55, 116, 189688622.37, 260332262.0, 1.97],
 [2.2, 768, 6004865.13, 5759960.98, 1.21],
 [3.74, 4062, 3263822121.39, 3066869087.9, 1.93],
 [1.91, 474, 44555062.72, 44555062.72, 0.41],
 [5.8, 5006, 8254968918.1, 7446788272.74, 3.25],
 [4.5, 7887, 30078971595.46, 27814989471.31, 2.18],
 [7.03, 116, 66252511.46, 81109291.0, 1.56],
 [6.52, 116, 47674230.76, 57686991.0, 1.43],
 [1.85, 623, 3002631.96, 2899484.08, 0.64],
 [13.76, 1227, 1737874137.5, 1446511574.32, 4.32],
 [13.76, 1227, 1737874137.5, 1446511574.32, 4.32]]

I then import Numpy, and set print options to (suppress=True). When I create an array:

my_array = numpy.array(my_list)

I can't for the life of me suppress scientific notation:

[[  3.74000000e+00   5.16200000e+03   1.36836288e+10   1.27833876e+10
    1.81000000e+00]
 [  9.55000000e+00   1.16000000e+02   1.89688622e+08   2.60332262e+08
    1.97000000e+00]
 [  2.20000000e+00   7.68000000e+02   6.00486513e+06   5.75996098e+06
    1.21000000e+00]
 [  3.74000000e+00   4.06200000e+03   3.26382212e+09   3.06686909e+09
    1.93000000e+00]
 [  1.91000000e+00   4.74000000e+02   4.45550627e+07   4.45550627e+07
    4.10000000e-01]
 [  5.80000000e+00   5.00600000e+03   8.25496892e+09   7.44678827e+09
    3.25000000e+00]
 [  4.50000000e+00   7.88700000e+03   3.00789716e+10   2.78149895e+10
    2.18000000e+00]
 [  7.03000000e+00   1.16000000e+02   6.62525115e+07   8.11092910e+07
    1.56000000e+00]
 [  6.52000000e+00   1.16000000e+02   4.76742308e+07   5.76869910e+07
    1.43000000e+00]
 [  1.85000000e+00   6.23000000e+02   3.00263196e+06   2.89948408e+06
    6.40000000e-01]
 [  1.37600000e+01   1.22700000e+03   1.73787414e+09   1.44651157e+09
    4.32000000e+00]
 [  1.37600000e+01   1.22700000e+03   1.73787414e+09   1.44651157e+09
    4.32000000e+00]]

If I create a simple numpy array directly:

new_array = numpy.array([1.5, 4.65, 7.845])

I have no problem and it prints as follows:

[ 1.5    4.65   7.845]

Does anyone know what my problem is?

Best Answer

This is what you need:

np.set_printoptions(suppress=True)

Here is the documentation which says

suppress: bool, optional

If True, always print floating point numbers using fixed point notation, in which case numbers equal to zero in the current precision will print as zero. If False, then scientific notation is used when absolute value of the smallest number is < 1e-4 or the ratio of the maximum absolute value to the minimum is > 1e3. The default is False.

In the original question, the difference between the array created "directly" and the original "big" array is that the big array contains very large numbers (e.g. 1.44651157e+09), so NumPy chooses the scientific notation for it, unless it's suppressed.

Changing how `numpy` arrays are printed

The way that numpy arrays are displayed interactively is controlled by numpy.set_printoptions.

Note that this does not convert the numbers to strings or change them in any way.

As a quick example:

In [1]: import numpy as np

In [2]: x = 1e9 * np.random.random(5)

In [3]: x
Out[3]:
array([  4.96602724e+08,   5.42486095e+08,   4.74495681e+08,
         7.37709684e+07,   9.75410927e+08])

In [4]: np.set_printoptions(formatter={'float_kind':'{:f}'.format})

In [5]: x
Out[5]:
array([496602723.824146, 542486095.316912, 474495680.688025,
       73770968.413642, 975410926.873148])

We've only changed how numpy will display the numbers. They're still floats.

We can operate on them mathematically, and they'll behave like numbers:

In [6]: x[0]
Out[6]: 496602723.82414573

In [7]: x[0] * 2
Out[7]: 993205447.64829147

Converting to `string`s

Now let's say we had converted them to a list of strings:

In [1]: import numpy as np

In [2]: x = 1e9 * np.random.random(5)

In [3]: x
Out[3]:
array([  2.56619581e+08,   2.55721261e+08,   3.36984986e+08,
         2.67541556e+08,   9.01048842e+08])

In [4]: x = ['{:f}'.format(item) for item in x]

In [5]: x
Out[5]:
['256619580.697790',
 '255721261.271977',
 '336984986.430552',
 '267541556.373619',
 '901048842.193849']

Now they're a list of strings. If we operate on them mathematically, they'll behave like strings, not numbers:

In [6]: x[0] * 2
Out[6]: '256619580.697790256619580.697790'

Controlling how `numpy` arrays are saved with `savetxt`

Finally, if you're using numpy.savetxt, and would like to control how the data is output to disk, consider using the fmt parameter instead of manually converting elements of the array to strings.

For example, if we were to do:

np.savetxt('temp.txt', x)

By default, the ascii representation of the array would use scientific notation if it is more compact:

8.702970453168644905e+08
9.991634082796489000e+08
5.032002956810175180e+08
2.382398232565869987e+08
1.868727085152311921e+08

However, we can control that using fmt. Note that it expects the "old-style" % formatting strings:

np.savetxt('temp2.txt', x, fmt='%f')

And we'll get:

870297045.316864
999163408.279649
503200295.681018
238239823.256587
186872708.515231

Best Answer

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