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

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Yet another option is to use the decimal module   import numpy as np from decimal import    arr   np array    56 83   385 3      6 65   126 63    85 76   192 72   112 81  10 55   arr2    str Decimal i  quantize Decimal   01     for i in arr       56 83    385 30    6 65    126 63    85 76    192 72    112 81    10 55

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The numpy arrays have the method round precision  which return a new numpy array with elements rounded accordingly   import numpy as np  x   np random random  5 5   print x round 3

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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      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

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numpy char mod may also be useful  depending on the details of your application e g  numpy char mod  Value  4 2f   numpy arange 5  10  0 1   will return a string array with elements  Value 5 00    Value 5 10  etc   as a somewhat contrived example

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The gem that makes it all too easy to obtain the result as a string  in today s numpy versions  is hidden in denis answer  np array2string   gt  gt  gt  import numpy as np  gt  gt  gt  x np random random 10   gt  gt  gt  np array2string x  formatter   float kind    0  3f   format     0 599 0 847 0 513 0 155 0 844 0 753 0 920 0 797 0 427 0 420

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I use  def np print array fmt  10 5f        print  array size       fmt       format  array    It s not difficult to modify it for multi-dimensional arrays

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Years later  another one is below  But for everyday use I just  np set printoptions  threshold 20  edgeitems 10  linewidth 140      formatter   dict  float   lambda x     3g    x       float arrays   3g         printf         3g       1f        arg  arg       for numpy arrays too  Example      printf      x    3g   A    1f   s   s   B   s                         x         A          str    B    If  x  and  A  are numbers  this is like   format     x  A   str   B   in python  If they re numpy arrays  each element is printed in its own format       x   e g    1 23 1 23e-6        3 digits      A       1 digit after the decimal point             with the current  np set printoptions     For example  with     np set printoptions  threshold 100  edgeitems 3  suppress True   only the edges of big  x  and  A  are printed   B  is printed as  str B    for any  B  -- a number  a list  a numpy object       printf    tries to handle too few or too many arguments sensibly  but this is iffy and subject to change   How it works  numpy has a function  np array2string  A     3g      simplifying a bit    printf    splits the format string  and for format   arg pairs     format    d e f g     arg  try  np asanyarray    -- gt    s  np array2string  arg  format   Other formats and non-ndarray args are left alone  formatted as usual   Notes    printf      end  file     are passed on to the python  print    function   Only formats     optional width   precision  d e f g  are implemented  not    varname format      d truncates floats  e g  0 9 and -0 9 to 0    0f rounds  0 9 to 1    g is the same as   6g  6 digits     is a single     character   The function  sprintf    returns a long string  For example      title   sprintf    s  m  g  n  g  X   3g                         file    m  n  X       print  title               pl title  title    Module globals   fmt      3g     default for extra args  squeeze   np squeeze     n 1   1 n  - gt   n   print in 1 line not n  See also  http   docs scipy org doc numpy reference generated numpy set printoptions html http   docs python org 2 7 library stdtypes html string-formatting        http   stackoverflow com questions 2891790 pretty-printing-of-numpy-array                                                                                    from   future   import division  print function import re import numpy as np    version      2014-02-03 feb denis    splitformat   re compile  r                  lt           not        -     d         optional width precision      w           re X              3 0f       g       -10s           - gt           3 0f          g          -10s               odd len  first or last may be      fmt      3g     default for extra args  squeeze   np squeeze     n 1   1 n  - gt   n   print in 1 line not n                                                                                   def printf  format   args    kwargs        print  sprintf  format   args      kwargs      end  file   printf   doc       doc     def sprintf  format   args            sprintf   text   3g text  4 1f      s        numpy arrays or                 defg  array - gt  np array2string  formatter                args   list args      if not isinstance  format  basestring            args    format    args         format           tf    splitformat split  format        text  e text  f           nfmt   len tf     2     nargs   len args      if nargs  lt  nfmt          args     nfmt - nargs       arg        elif nargs  gt  nfmt          tf     nargs - nfmt      fmt          default  fmt      for j  arg in enumerate  args            fmt   tf  2 j   1           if arg is None           or isinstance  arg  basestring             or  hasattr  arg     iter      and len arg     0               tf  2 j   1       s      f - gt   s  not error             continue         args j   isarray    tonumpyarray arg          if isarray  and fmt -1  in  defgEFG               tf  2 j   1       s              fmtfunc    lambda x  fmt   x              formatter   dict  float kind fmtfunc  int fmtfunc               args j    np array2string  args j   formatter formatter       try          return    join tf    tuple args      except TypeError     shouldn t happen         print   error  tf  s  types  s     tf  map  type  args             raise   def  tonumpyarray  a            a  isarray    tonumpyarray  a           - gt   scalar  False             np asanyarray a   float or int             a  False             a   getattr  a   value   a      cvxpy     if np isscalar a           return a  False     if hasattr  a     iter       and len a     0          return a  False     try            map  value           a   np asanyarray  a       except ValueError          return a  False     if hasattr  a   dtype     and a dtype kind in  fi      complex           if callable   squeeze                a    squeeze  a      np squeeze         return a  True     else          return a  False                                                                                    if   name         main         import sys      n   5     seed   0           run this py n       in sh or ipython     for arg in sys argv 1            exec  arg       np set printoptions  1  threshold 4  edgeitems 2  linewidth 80  suppress True       np random seed seed       A   np random exponential  size  n n       10     x   A 0       printf   x    3g   nA    1f   ns   s   nB   s                    x          A           str     A       printf   x   d   d   x       printf   x    0f    0f   x       printf   x    1e    1e   x       printf   x   g   g   x       printf   x   s uses np printoptions   s   x        printf   x with default  fmt     x       printf   no args        printf   too few args   g  g   x       printf  x       printf  x  x       printf  None       printf                  printf    3      3        printf  np array            printf            squeeze

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And here is what I use  and it s pretty uncomplicated   print np vectorize    2f    mod    sparse

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Was surprised to not see around method mentioned - means no messing with print options   import numpy as np  x   np random random  5 5   print np around x decimals 3    Output    0 475 0 239 0 183 0 991 0 171    0 231 0 188 0 235 0 335 0 049    0 87  0 212 0 219 0 9   0 3      0 628 0 791 0 409 0 5   0 319    0 614 0 84  0 812 0 4   0 307

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FYI Numpy 1 15  release date pending  will include a context manager for setting print options locally  This means that the following will work the same as the corresponding example in the accepted answer  by unutbu and Neil G  without having to write your own context manager  E g   using their example   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

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I often want different columns to have different formats   Here is how I print a simple 2D array using some variety in the formatting by converting  slices of  my NumPy array to a tuple   import numpy as np dat   np random random  10 11   100    Array of random values between 0 and 100 print dat                              Lines get truncated and are hard to read for i in range 10       print  4   6 2f  7   9 4f     tuple dat i

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Unutbu gave a really complete answer  they got a  1 from me too   but here is a lo-tech alternative    gt  gt  gt  x np random randn 5   gt  gt  gt  x array   0 25276524   2 28334499  -1 88221637   0 69949927   1 0285625     gt  gt  gt       2f   format i  for i in x    0 25    2 28    -1 88    0 70    1 03     As a function  using the format   syntax for formatting    def ndprint a  format string    0  2f         print  format string format v i  for i v in enumerate a     Usage    gt  gt  gt  ndprint x    0 25    2 28    -1 88    0 70    1 03     gt  gt  gt  ndprint x     10 4e      2 5277e-01    2 2833e 00    -1 8822e 00    6 9950e-01    1 0286e 00     gt  gt  gt  ndprint x      8g      0 25276524    2 283345    -1 8822164    0 69949927    1 0285625     The index of the array is accessible in the format string    gt  gt  gt  ndprint x   Element  1 d    0  2f      Element 0  0 25    Element 1  2 28    Element 2  -1 88    Element 3  0 70    Element 4  1 03

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You can get a subset of the np set printoptions functionality from the np array str command  which applies only to a single print statement   http   docs scipy org doc numpy reference generated numpy array str html  For example   In  27   x   np array   1 1  0 9  1e-6   3   In  28   print x     1 10000000e 00   9 00000000e-01   1 00000000e-06      1 10000000e 00   9 00000000e-01   1 00000000e-06      1 10000000e 00   9 00000000e-01   1 00000000e-06    In  29   print np array str x  precision 2      1 10e 00   9 00e-01   1 00e-06      1 10e 00   9 00e-01   1 00e-06      1 10e 00   9 00e-01   1 00e-06    In  30   print np array str x  precision 2  suppress small True     1 1  0 9  0       1 1  0 9  0       1 1  0 9  0

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I find that the usual float format   9 5f  works properly -- suppressing small-value e-notations -- when displaying a list or an array using a loop   But that format sometimes fails to suppress its e-notation when a formatter has several items in a single print statement   For example   import numpy as np np set printoptions suppress True  a3   4E-3 a4   4E-4 a5   4E-5 a6   4E-6 a7   4E-7 a8   4E-8  --first  display separate numbers----------- print  Case 3   a3  a4  a5                9 5f   9 5f   9 5f   format a3 a4 a5   print  Case 4   a3  a4  a5  a6            9 5f   9 5f   9 5f   9 5   format a3 a4 a5 a6   print  Case 5   a3  a4  a5  a6  a7        9 5f   9 5f   9 5f   9 5   9 5f   format a3 a4 a5 a6 a7   print  Case 6   a3  a4  a5  a6  a7  a8    9 5f   9 5f   9 5f   9 5f   9 5   9 5f   format a3 a4 a5 a6 a7 a8    ---second  display a list using a loop---------- myList    a3 a4 a5 a6 a7 a8  print  List 6   a3  a4  a5  a6  a7  a8     end     for x in myList       print    9 5f   format x   end     print    ---third  display a numpy array using a loop------------ myArray   np array myList  print  Array 6  a3  a4  a5  a6  a7  a8     end     for x in myArray      print    9 5f   format x   end     print     My results show the bug in cases 4  5  and 6   Case 3   a3  a4  a5                0 00400  0 00040  0 00004 Case 4   a3  a4  a5  a6            0 00400  0 00040  0 00004    4e-06 Case 5   a3  a4  a5  a6  a7        0 00400  0 00040  0 00004    4e-06  0 00000 Case 6   a3  a4  a5  a6  a7  a8    0 00400  0 00040  0 00004  0 00000    4e-07  0 00000 List 6   a3  a4  a5  a6  a7  a8    0 00400  0 00040  0 00004  0 00000  0 00000  0 00000 Array 6  a3  a4  a5  a6  a7  a8    0 00400  0 00040  0 00004  0 00000  0 00000  0 00000   I have no explanation for this  and therefore I always use a loop for floating output of multiple values

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

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