def set_string_function(f, repr=True):
"""
Set a Python function to be used when pretty printing arrays.
Parameters
----------
f : function or None
Function to be used to pretty print arrays. The function should expect
a single array argument and return a string of the representation of
the array. If None, the function is reset to the default NumPy function
to print arrays.
repr : bool, optional
If True (default), the function for pretty printing (``__repr__``)
is set, if False the function that returns the default string
representation (``__str__``) is set.
See Also
--------
set_printoptions, get_printoptions
Examples
--------
>>> def pprint(arr):
... return 'HA! - What are you going to do now?'
...
>>> np.set_string_function(pprint)
>>> a = np.arange(10)
>>> a
HA! - What are you going to do now?
>>> print a
[0 1 2 3 4 5 6 7 8 9]
We can reset the function to the default:
>>> np.set_string_function(None)
>>> a
array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])
`repr` affects either pretty printing or normal string representation.
Note that ``__repr__`` is still affected by setting ``__str__``
because the width of each array element in the returned string becomes
equal to the length of the result of ``__str__()``.
>>> x = np.arange(4)
>>> np.set_string_function(lambda x:'random', repr=False)
>>> x.__str__()
'random'
>>> x.__repr__()
'array([ 0, 1, 2, 3])'
"""
if f is None:
if repr:
return multiarray.set_string_function(array_repr, 1)
else:
return multiarray.set_string_function(array_str, 0)
else:
return multiarray.set_string_function(f, repr)
def set_string_function(f, repr=True):
"""
Set a Python function to be used when pretty printing arrays.
Parameters
----------
f : function or None
Function to be used to pretty print arrays. The function should expect
a single array argument and return a string of the representation of
the array. If None, the function is reset to the default NumPy function
to print arrays.
repr : bool, optional
If True (default), the function for pretty printing (``__repr__``)
is set, if False the function that returns the default string
representation (``__str__``) is set.
See Also
--------
set_printoptions, get_printoptions
Examples
--------
>>> def pprint(arr):
... return 'HA! - What are you going to do now?'
...
>>> np.set_string_function(pprint)
>>> a = np.arange(10)
>>> a
HA! - What are you going to do now?
>>> print a
[0 1 2 3 4 5 6 7 8 9]
We can reset the function to the default:
>>> np.set_string_function(None)
>>> a
array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])
`repr` affects either pretty printing or normal string representation.
Note that ``__repr__`` is still affected by setting ``__str__``
because the width of each array element in the returned string becomes
equal to the length of the result of ``__str__()``.
>>> x = np.arange(4)
>>> np.set_string_function(lambda x:'random', repr=False)
>>> x.__str__()
'random'
>>> x.__repr__()
'array([ 0, 1, 2, 3])'
"""
if f is None:
if repr:
return multiarray.set_string_function(array_repr, 1)
else:
return multiarray.set_string_function(array_str, 0)
else:
return multiarray.set_string_function(f, repr)
"can only do cross product for axes with dimensions 2 or 3")
#Use Konrad's printing function (modified for both str and repr now)
from ArrayPrinter import array2string
def array_repr(a, max_line_width=None, precision=None, suppress_small=None):
return array2string(a, max_line_width, precision, suppress_small, ', ', 1)
def array_str(a, max_line_width=None, precision=None, suppress_small=None):
return array2string(a, max_line_width, precision, suppress_small, ' ', 0)
multiarray.set_string_function(array_str, 0)
multiarray.set_string_function(array_repr, 1)
#This is a nice value to have around
#Maybe in sys some day
LittleEndian = fromstring("\001" + "\000" * 7, 'i')[0] == 1
def resize(a, new_shape):
"""resize(a,new_shape) returns a new array with the specified shape.
The original array's total size can be any size.
"""
a = ravel(a)
if not len(a): return zeros(new_shape, a.typecode())
total_size = multiply.reduce(new_shape)
"""Numeric module defining a multi-dimensional array and useful procedures for Numerical computation. Functions - array - NumPy Array construction - zeros - Return an array of all zeros - fromstring - Construct array from (byte) string - take - Select sub-arrays using sequence of indices - put - Set sub-arrays using sequence of 1-D indices - putmask - Set portion of arrays using a mask - reshape - Return array with new shape - repeat - Repeat elements of array - choose - Construct new array from indexed array tuple - cross_correlate - Correlate two 1-d arrays - searchsorted - Search for element in 1-d array - sum - Total sum over a specified dimension - cumsum - Cumulative sum over a specified dimension - product - Total product over a specified dimension - cumproduct - Cumulative product over a specified dimension - alltrue - Logical and over an entire axis - sometrue - Logical or over an entire axis - allclose - Tests if sequences are essentially equal More Functions: - arrayrange (arange) - Return regularly spaced array - asarray - Guarantee NumPy array - sarray - Guarantee a NumPy array that keeps precision - convolve - Convolve two 1-d arrays - swapaxes - Exchange axes - concatenate - Join arrays together - transpose - Permute axes - sort - Sort elements of array
try:
from dotblas import dot, innerproduct, vdot
except ImportError: pass
#This is obsolete, don't use in new code
matrixmultiply = dot
#Use Konrad's printing function (modified for both str and repr now)
from ArrayPrinter import array2string
def array_repr(a, max_line_width = None, precision = None, suppress_small = None):
return array2string(a, max_line_width, precision, suppress_small, ', ', 1)
def array_str(a, max_line_width = None, precision = None, suppress_small = None):
return array2string(a, max_line_width, precision, suppress_small, ' ', 0)
multiarray.set_string_function(array_str, 0)
multiarray.set_string_function(array_repr, 1)
#This is a nice value to have around
#Maybe in sys some day
LittleEndian = fromstring("\001"+"\000"*7, 'i')[0] == 1
def resize(a, new_shape):
"""resize(a,new_shape) returns a new array with the specified shape.
The original array's total size can be any size.
"""
a = ravel(a)
if not len(a): return zeros(new_shape, a.typecode())
total_size = multiply.reduce(new_shape)
n_copies = int(total_size / len(a))
"""Numeric module defining a multi-dimensional array and useful procedures for Numerical computation. Functions - array - NumPy Array construction - zeros - Return an array of all zeros - fromstring - Construct array from (byte) string - take - Select sub-arrays using sequence of indices - put - Set sub-arrays using sequence of 1-D indices - putmask - Set portion of arrays using a mask - reshape - Return array with new shape - repeat - Repeat elements of array - choose - Construct new array from indexed array tuple - cross_correlate - Correlate two 1-d arrays - searchsorted - Search for element in 1-d array - sum - Total sum over a specified dimension - cumsum - Cumulative sum over a specified dimension - product - Total product over a specified dimension - cumproduct - Cumulative product over a specified dimension - alltrue - Logical and over an entire axis - sometrue - Logical or over an entire axis - allclose - Tests if sequences are essentially equal More Functions: - arrayrange (arange) - Return regularly spaced array - asarray - Guarantee NumPy array - sarray - Guarantee a NumPy array that keeps precision - convolve - Convolve two 1-d arrays - swapaxes - Exchange axes - concatenate - Join arrays together - transpose - Permute axes - sort - Sort elements of array