My main focus will on this page.
First, I don't understand the page. For the first parameter shape,
ndarray.reshape(shape, order='C')
why this method on ndarray allows the elements of the shape parameter to be passed in as separate arguments?
That is, why does this implementation allow a.reshape(10, 11)?
Second, I am wondering where the implementation on GitHub is? Searching the whole sentence "Returns an array containing the same data with a new shape" does not give me a correct link on GitHub. My attempt.
Thank you!
At the risk of being pedantic, here's some comparisons between using the function and the method versions. The function version takes an initial object that it interprets as a array (or makes into an array). The method already has the array object (self).
The function has a python signature, the method is compiled from c so can take some liberties in its signature (especially since it was written years ago before py3 and the current standards).
In [66]: x=np.arange(12)
In [67]: np.reshape(x,(3,4))
Out[67]:
array([[ 0, 1, 2, 3],
[ 4, 5, 6, 7],
[ 8, 9, 10, 11]])
The method can take either a tuple or numbers:
In [68]: x.reshape((3,4))
Out[68]:
array([[ 0, 1, 2, 3],
[ 4, 5, 6, 7],
[ 8, 9, 10, 11]])
In [69]: x.reshape(3,4)
Out[69]:
array([[ 0, 1, 2, 3],
[ 4, 5, 6, 7],
[ 8, 9, 10, 11]])
The function tries to interpret the 3rd argument as order:
In [70]: np.reshape(x,3,4)
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
File ~\miniconda3\lib\site-packages\numpy\core\fromnumeric.py:57, in _wrapfunc(obj, method, *args, **kwds)
56 try:
---> 57 return bound(*args, **kwds)
58 except TypeError:
59 # A TypeError occurs if the object does have such a method in its
60 # class, but its signature is not identical to that of NumPy's. This
(...)
64 # Call _wrapit from within the except clause to ensure a potential
65 # exception has a traceback chain.
TypeError: order must be str, not int
During handling of the above exception, another exception occurred:
TypeError Traceback (most recent call last)
Cell In[70], line 1
----> 1 np.reshape(x,3,4)
File <__array_function__ internals>:200, in reshape(*args, **kwargs)
File ~\miniconda3\lib\site-packages\numpy\core\fromnumeric.py:298, in reshape(a, newshape, order)
198 @array_function_dispatch(_reshape_dispatcher)
199 def reshape(a, newshape, order='C'):
200 """
201 Gives a new shape to an array without changing its data.
202
(...)
296 [5, 6]])
297 """
--> 298 return _wrapfunc(a, 'reshape', newshape, order=order)
File ~\miniconda3\lib\site-packages\numpy\core\fromnumeric.py:66, in _wrapfunc(obj, method, *args, **kwds)
57 return bound(*args, **kwds)
58 except TypeError:
59 # A TypeError occurs if the object does have such a method in its
60 # class, but its signature is not identical to that of NumPy's. This
(...)
64 # Call _wrapit from within the except clause to ensure a potential
65 # exception has a traceback chain.
---> 66 return _wrapit(obj, method, *args, **kwds)
File ~\miniconda3\lib\site-packages\numpy\core\fromnumeric.py:43, in _wrapit(obj, method, *args, **kwds)
41 except AttributeError:
42 wrap = None
---> 43 result = getattr(asarray(obj), method)(*args, **kwds)
44 if wrap:
45 if not isinstance(result, mu.ndarray):
TypeError: order must be str, not int
In [71]: np.reshape(x,(3,4),'F')
Out[71]:
array([[ 0, 3, 6, 9],
[ 1, 4, 7, 10],
[ 2, 5, 8, 11]])
The method requires that the order be a keyword:
In [72]: x.reshape(3,4,'F')
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
Cell In[72], line 1
----> 1 x.reshape(3,4,'F')
TypeError: 'str' object cannot be interpreted as an integer
In [73]: x.reshape(3,4,order='F')
Out[73]:
array([[ 0, 3, 6, 9],
[ 1, 4, 7, 10],
[ 2, 5, 8, 11]])
In [75]: x.reshape((3,4),'F')
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
Cell In[75], line 1
----> 1 x.reshape((3,4),'F')
TypeError: 'tuple' object cannot be interpreted as an integer
In [76]: x.reshape((3,4),order='F')
Out[76]:
array([[ 0, 3, 6, 9],
[ 1, 4, 7, 10],
[ 2, 5, 8, 11]])
Compare these with the errors when the newshape is wrong. Same error, but the function has the additional wrapit layering.
In [77]: x.reshape((3,5))
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
Cell In[77], line 1
----> 1 x.reshape((3,5))
ValueError: cannot reshape array of size 12 into shape (3,5)
In [78]: np.reshape(x,(3,5))
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
Cell In[78], line 1
----> 1 np.reshape(x,(3,5))
File <__array_function__ internals>:200, in reshape(*args, **kwargs)
File ~\miniconda3\lib\site-packages\numpy\core\fromnumeric.py:298, in reshape(a, newshape, order)
198 @array_function_dispatch(_reshape_dispatcher)
199 def reshape(a, newshape, order='C'):
200 """
201 Gives a new shape to an array without changing its data.
202
(...)
296 [5, 6]])
297 """
--> 298 return _wrapfunc(a, 'reshape', newshape, order=order)
File ~\miniconda3\lib\site-packages\numpy\core\fromnumeric.py:57, in _wrapfunc(obj, method, *args, **kwds)
54 return _wrapit(obj, method, *args, **kwds)
56 try:
---> 57 return bound(*args, **kwds)
58 except TypeError:
59 # A TypeError occurs if the object does have such a method in its
60 # class, but its signature is not identical to that of NumPy's. This
(...)
64 # Call _wrapit from within the except clause to ensure a potential
65 # exception has a traceback chain.
66 return _wrapit(obj, method, *args, **kwds)
ValueError: cannot reshape array of size 12 into shape (3,5)
(these error tracebacks are long because the ipython %xmode is set to verbose.)
np.random.rand has this note:
rand(d0, d1, ..., dn)
Random values in a given shape.
.. note::
This is a convenience function for users porting code from Matlab,
and wraps `random_sample`. That function takes a
tuple to specify the size of the output, which is consistent with
other NumPy functions like `numpy.zeros` and `numpy.ones`.
While numpy consistently shows shape as tuple (even the 0d and 1d cases), there are functions/methods that accept it as individual numbers. This note suggests this was an early feature of numpy, from the days when MATLAB still cast a long shaddow.
Of course in Python the 1,2,3 is just as much a tuple as (1,2,3). And in contexts like indexing the () are optional, e.g. x[1,2,3] is the same as x[(1,2,3)]. Both are interpreted as x.__getitem__((1,2,3)).