original_docstring: 
      Return the string representation of an array.
  
      Parameters
      ----------
      arr : ndarray
          Input array.
      max_line_width : int, optional
          The maximum number of columns the string should span. Newline
          characters split the string appropriately after array elements.
      precision : int, optional
          Floating point precision. Default is the current printing precision
          (usually 8), which can be altered using `set_printoptions`.
      suppress_small : bool, optional
          Represent very small numbers as zero, default is False. Very small
          is defined by `precision`, if the precision is 8 then
          numbers smaller than 5e-9 are represented as zero.
  
      Returns
      -------
      string : str
        The string representation of an array.
  
      See Also
      --------
      array_str, array2string, set_printoptions
  
      Examples
      --------
      >>> np.array_repr(np.array([1,2]))
      'array([1, 2])'
      >>> np.array_repr(np.ma.array([0.]))
      'MaskedArray([ 0.])'
      >>> np.array_repr(np.array([], np.int32))
      'array([], dtype=int32)'
  
      >>> x = np.array([1e-6, 4e-7, 2, 3])
      >>> np.array_repr(x, precision=6, suppress_small=True)
      'array([ 0.000001,  0.      ,  2.      ,  3.      ])'
  
      
docstring: Return the string representation of an array.
  Parameters
  
  arr : ndarray
  Input array.
  max_line_width : int, optional
  The maximum number of columns the string should span. Newline
  characters split the string appropriately after array elements.
  precision : int, optional
  Floating point precision. Default is the current printing precision
  (usually 8), which can be altered using `set_printoptions`.
  suppress_small : bool, optional
  Represent very small numbers as zero, default is False. Very small
  is defined by `precision`, if the precision is 8 then
  numbers smaller than 5e-9 are represented as zero.
  
  Returns
  
  string : str
  The string representation of an array.
  
  See Also
  
  
  
  Examples
  
  
  
  
docstring_tokens: Return the string representation of an array . Parameters arr : ndarray Input array . max_line_width : int optional The maximum number of columns the string should span . Newline characters split the string appropriately after array elements . precision : int optional Floating point precision . Default is the current printing precision ( usually 8 ) which can be altered using ` set_printoptions ` . suppress_small : bool optional Represent very small numbers as zero default is False . Very small is defined by ` precision ` if the precision is 8 then numbers smaller than 5e - 9 are represented as zero . Returns string : str The string representation of an array . See Also Examples
code: def array_repr(arr, max_line_width=None, precision=None, suppress_small=None):
      """
      Return the string representation of an array.
  
      Parameters
      ----------
      arr : ndarray
          Input array.
      max_line_width : int, optional
          The maximum number of columns the string should span. Newline
          characters split the string appropriately after array elements.
      precision : int, optional
          Floating point precision. Default is the current printing precision
          (usually 8), which can be altered using `set_printoptions`.
      suppress_small : bool, optional
          Represent very small numbers as zero, default is False. Very small
          is defined by `precision`, if the precision is 8 then
          numbers smaller than 5e-9 are represented as zero.
  
      Returns
      -------
      string : str
        The string representation of an array.
  
      See Also
      --------
      array_str, array2string, set_printoptions
  
      Examples
      --------
      >>> np.array_repr(np.array([1,2]))
      'array([1, 2])'
      >>> np.array_repr(np.ma.array([0.]))
      'MaskedArray([ 0.])'
      >>> np.array_repr(np.array([], np.int32))
      'array([], dtype=int32)'
  
      >>> x = np.array([1e-6, 4e-7, 2, 3])
      >>> np.array_repr(x, precision=6, suppress_small=True)
      'array([ 0.000001,  0.      ,  2.      ,  3.      ])'
  
      """
      if type(arr) is not ndarray:
          class_name = type(arr).__name__
      else:
          class_name = "array"
  
      if arr.size > 0 or arr.shape == (0,):
          lst = array2string(arr, max_line_width, precision, suppress_small,
                             ', ', class_name + "(")
      else:  # show zero-length shape unless it is (0,)
          lst = "[], shape=%s" % (repr(arr.shape),)
  
      skipdtype = (arr.dtype.type in _typelessdata) and arr.size > 0
  
      if skipdtype:
          return "%s(%s)" % (class_name, lst)
      else:
          typename = arr.dtype.name
          # Quote typename in the output if it is "complex".
          if typename and not (typename[0].isalpha() and typename.isalnum()):
              typename = "'%s'" % typename
  
          lf = ' '
          if issubclass(arr.dtype.type, flexible):
              if arr.dtype.names:
                  typename = "%s" % str(arr.dtype)
              else:
                  typename = "'%s'" % str(arr.dtype)
              lf = '\n'+' '*len(class_name + "(")
          return "%s(%s,%sdtype=%s)" % (class_name, lst, lf, typename)
code_tokens: def array_repr ( arr , max_line_width = None , precision = None , suppress_small = None ) : if type ( arr ) is not ndarray : class_name = type ( arr ) . __name__ else : class_name = "array" if arr . size > 0 or arr . shape == ( 0 , ) : lst = array2string ( arr , max_line_width , precision , suppress_small , ', ' , class_name + "(" ) else : lst = "[], shape=%s" % ( repr ( arr . shape ) , ) skipdtype = ( arr . dtype . type in _typelessdata ) and arr . size > 0 if skipdtype : return "%s(%s)" % ( class_name , lst ) else : typename = arr . dtype . name if typename and not ( typename [ 0 ] . isalpha ( ) and typename . isalnum ( ) ) : typename = "'%s'" % typename lf = ' ' if issubclass ( arr . dtype . type , flexible ) : if arr . dtype . names : typename = "%s" % str ( arr . dtype ) else : typename = "'%s'" % str ( arr . dtype ) lf = '\n' + ' ' * len ( class_name + "(" ) return "%s(%s,%sdtype=%s)" % ( class_name , lst , lf , typename )
short_docstring: Return the string representation of an array.
short_docstring_tokens: Return the string representation of an array .
comment: """
      Return the string representation of an array.
  
      Parameters
      ----------
      arr : ndarray
          Input array.
      max_line_width : int, optional
          The maximum number of columns the string should span. Newline
          characters split the string appropriately after array elements.
      precision : int, optional
          Floating point precision. Default is the current printing precision
          (usually 8), which can be altered using `set_printoptions`.
      suppress_small : bool, optional
          Represent very small numbers as zero, default is False. Very small
          is defined by `precision`, if the precision is 8 then
          numbers smaller than 5e-9 are represented as zero.
  
      Returns
      -------
      string : str
        The string representation of an array.
  
      See Also
      --------
      array_str, array2string, set_printoptions
  
      Examples
      --------
      >>> np.array_repr(np.array([1,2]))
      'array([1, 2])'
      >>> np.array_repr(np.ma.array([0.]))
      'MaskedArray([ 0.])'
      >>> np.array_repr(np.array([], np.int32))
      'array([], dtype=int32)'
  
      >>> x = np.array([1e-6, 4e-7, 2, 3])
      >>> np.array_repr(x, precision=6, suppress_small=True)
      'array([ 0.000001,  0.      ,  2.      ,  3.      ])'
  
      """$SEP$# show zero-length shape unless it is (0,)$SEP$# Quote typename in the output if it is "complex".