Numpy converting array from float to strings

Question

I have an array of floats that I have normalised to one  i e  the largest number in the array is 1   and I wanted to use it as colour indices for a graph  In using matplotlib to use grayscale  this requires using strings between 0 and 1  so I wanted to convert the array of floats to an array of strings  I was attempting to do this by using  astype  str     but this appears to create some values that are not the same  or even close  to the originals   I notice this because matplotlib complains about finding the number 8 in the array  which is odd as it was normalised to one   In short  I have an array phis  of float64  such that   numpy where phis astype  str   astype  float64      phis    is non empty  This is puzzling as  hopefully naively  it appears to be a bug in numpy  is there anything that I could have done wrong to cause this   Edit  after investigation this appears to be due to the way the string function handles high precision floats  Using a vectorized toString function  as from robbles answer   this is also the case  however if the lambda function is   lambda x     2f    x   Then the graphing works - curiouser and curiouser   Obviously the arrays are no longer equal however

User · Accepted Answer

You seem a bit confused as to how numpy arrays work behind the scenes. Each item in an array must be the same size.

The string representation of a float doesn't work this way. For example, repr(1.3) yields '1.3', but repr(1.33) yields '1.3300000000000001'.

A accurate string representation of a floating point number produces a variable length string.

Because numpy arrays consist of elements that are all the same size, numpy requires you to specify the length of the strings within the array when you're using string arrays.

If you use x.astype('str'), it will always convert things to an array of strings of length 1.

For example, using x = np.array(1.344566), x.astype('str') yields '1'!

You need to be more explict and use the '|Sx' dtype syntax, where x is the length of the string for each element of the array.

For example, use x.astype('|S10') to convert the array to strings of length 10.

Even better, just avoid using numpy arrays of strings altogether. It's usually a bad idea, and there's no reason I can see from your description of your problem to use them in the first place...

User · Answer

This is probably slower than what you want  but you can do    gt  gt  gt  tostring   vectorize lambda x  str x    gt  gt  gt  numpy where tostring phis  astype  float64      phis   array     dtype int64      It looks like it rounds off the values when it converts to str from float64  but this way you can customize the conversion however you like

User · Answer

If you have an array of numbers and you want an array of strings  you can write   strings       2f    number for number in numbers    If your numbers are floats  the array would be an array with the same numbers as strings with two decimals    gt  gt  gt  a    1 2 3 4 5   gt  gt  gt  min a  max a   min a   max a   gt  gt  gt  a normalized    float x-min a   max a-min a  for x in a   gt  gt  gt  a normalized  0 0  0 25  0 5  0 75  1 0   gt  gt  gt  a strings       2f    x for x in a normalized   gt  gt  gt  a strings   0 00    0 25    0 50    0 75    1 00     Notice that it also works with numpy arrays    gt  gt  gt  a   numpy array  0 0  0 25  0 75  1 0    gt  gt  gt  print     2f    x for x in a    0 00    0 25    0 50    0 75    1 00     A similar methodology can be used if you have a multi-dimensional array   new array   numpy array     2f    x for x in old array reshape old array size    new array   new array reshape old array shape    Example    gt  gt  gt  x   numpy array   0 0 1 0 2   0 3 0 4 0 5   0 6  0 7  0 8     gt  gt  gt  y   numpy array     2f    w for w in x reshape x size     gt  gt  gt  y   y reshape x shape   gt  gt  gt  print y    0 00   0 10   0 20      0 30   0 40   0 50      0 60   0 70   0 80      If you check the Matplotlib example for the function you are using  you will notice they use a similar methodology  build empty matrix and fill it with strings built with the interpolation method  The relevant part of the referenced code is   colortuple     y    b   colors   np empty X shape  dtype str  for y in range ylen       for x in range xlen           colors x  y    colortuple  x   y    len colortuple    surf   ax plot surface X  Y  Z  rstride 1  cstride 1  facecolors colors          linewidth 0  antialiased False

User · Answer

If the main problem is the loss of precision when converting from a float to a string  one possible way to go is to convert the floats to the decimalS  http   docs python org library decimal html   In python 2 7 and higher you can directly convert a float to a decimal object

[python] Numpy converting array from float to strings

Examples related to python

Examples related to numpy

Examples related to matplotlib