I have checked the questions/answers given in the following links and found nothing that can help me: 1) how to read array of numbers from text file in python 2) TypeError: iteration over a 0-d array Python 3) How to index 0-d array in Python?
This post is the closest: Why does python think my array is 0-d? (TypeError: iteration over a 0-d array)
So, I am going to write my question here, rather than opening up a new tag. I hope this is fine, I am new here, so pardon me if this is not the way.
My case:
I made a randomSampling function (for a class exercise), like this:
def randomSamples(array):
print(array)
print(type(array))
i = 0
while i < len(array):
sampling1 = np.random.choice((array), 5)
i += 1
sampling1 = np.concatenate([sampling1])
print(sampling1)
print(type(sampling1))
I then run the function like this:
test1 = np.random.choice(15, 13)
sampling2 = randomSamples(test1)
sampling3 = np.asarray(sampling2)
print(type(sampling3))
sampling3.shape # Nothing comes out, something may be wrong.
The output is:
[ 7 9 6 3 13 7 1 1 9 9 0 6 12]
<class 'numpy.ndarray'>
[6 9 7 9 9]
[12 1 1 13 12]
[ 9 7 13 0 1]
[3 1 9 3 1]
[ 1 1 7 6 13]
[ 6 9 7 12 0]
[ 9 12 3 3 6]
[3 9 6 3 3]
[ 1 9 9 6 13]
[6 1 1 3 3]
[1 9 9 3 1]
[13 9 13 9 9]
[ 7 1 6 0 12]
<class 'numpy.ndarray'>
<class 'numpy.ndarray'>
When I run:
SEM(sampling3)
I get:
<class 'numpy.ndarray'>
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-556-1456ec9b184d> in <module>
----> 1 SEM(sampling3)
<ipython-input-269-90a8bbeb1e1a> in SEM(array)
4 array1 = []
5
----> 6 for i in array:
7 counter += i
8 a1 = float(counter/len(array))
TypeError: iteration over a 0-d array
I don't understand why the outcome of the function although it is 'numpy.ndarray' class, and I even created another variable (sampling3) with np.asarray to make sure it is a np.array.
I notice that the shape attribute comes out empty. Ideally, the array would be: name = [[6 9 7 9 9],[12 1 1 13 12],...,[ 7 1 6 0 12]], with shape (13,5).
Any help would be appreciated. Thanks in advance.
Let's step through your function's action:
Make the initial sample:
In [22]: arr = np.random.choice(15,13)
In [23]: arr
Out[23]: array([ 1, 3, 0, 14, 13, 13, 10, 9, 5, 0, 12, 12, 2])
Inside the loop take a sampling from that:
In [25]: samp = np.random.choice((arr), 5)
In [26]: samp
Out[26]: array([14, 5, 5, 3, 3])
The concatenate
does nothing. What was it supposed to do?
In [27]: samp = np.concatenate([samp])
In [28]: samp
Out[28]: array([14, 5, 5, 3, 3])
take another sample (the () arr
do nothing):
In [29]: samp = np.random.choice(arr, 5)
In [30]: samp
Out[30]: array([13, 3, 9, 9, 12])
In [31]: samp = np.concatenate([samp])
In [32]: samp
Out[32]: array([13, 3, 9, 9, 12])
The samp
from Out[28]
has been lost. If you want save values in a loop you need to collect them in a structure, such as a list.
alist = []
for i in range(3):
alist.append(np.random.choice(arr, 5)
produces a list of 3 arrays.
Your function does not have a return statement, so it returns None
:
In [33]: np.asarray(None)
Out[33]: array(None, dtype=object)
In [34]: _.shape
Out[34]: ()
making an array out of None
produces a 0d array.
In [36]: for i in np.asarray(None): pass
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-36-8942a42b4c6b> in <module>
----> 1 for i in np.asarray(None): pass
TypeError: iteration over a 0-d array
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