'list' object has no attribute 'shape'
Question:
how to create an array to numpy array?
def test(X, N):
[n,T] = X.shape
print "n : ", n
print "T : ", T
if __name__=="__main__":
X = [[[-9.035250067710876], [7.453250169754028], [33.34074878692627]], [[-6.63700008392334], [5.132999956607819], [31.66075038909912]], [[-5.1272499561309814], [8.251499891281128], [30.925999641418457]]]
N = 200
test(X, N)
I am getting error as
AttributeError: 'list' object has no attribute 'shape'
So, I think I need to convert my X to numpy array?
Answers:
Use numpy.array
to use shape
attribute.
>>> import numpy as np
>>> X = np.array([
... [[-9.035250067710876], [7.453250169754028], [33.34074878692627]],
... [[-6.63700008392334], [5.132999956607819], [31.66075038909912]],
... [[-5.1272499561309814], [8.251499891281128], [30.925999641418457]]
... ])
>>> X.shape
(3L, 3L, 1L)
NOTE X.shape
returns 3-items tuple for the given array; [n, T] = X.shape
raises ValueError
.
import numpy
X = numpy.array(the_big_nested_list_you_had)
It’s still not going to do what you want; you have more bugs, like trying to unpack a 3-dimensional shape into two target variables in test
.
list object in python does not have ‘shape’ attribute because ‘shape’ implies that all the columns (or rows) have equal length along certain dimension.
Let’s say list variable a has following properties:
a = [[2, 3, 4]
[0, 1]
[87, 8, 1]]
it is impossible to define ‘shape’ for variable ‘a’.
That is why ‘shape’ might be determined only with ‘arrays’ e.g.
b = numpy.array([[2, 3, 4]
[0, 1, 22]
[87, 8, 1]])
I hope this explanation clarifies well this question.
Alternatively, you can use np.shape(...)
For instance:
import numpy as np
a=[1,2,3]
and np.shape(a)
will give an output of (3,)
If the type is list, use len(list)
and len(list[0])
to get the row and column.
l = [[1,2,3,4], [0,1,3,4]]
len(l)
will be 2.
len(l[0])
will be 4.
Firstly you have to import numpy library (refer code for making a numpy array).
shape
only gives the output only if the variable is attribute of numpy library. In other words it must be a np.array or any other data structure of numpy.
E.g.
import numpy
a=numpy.array([[1,1],[1,1]])
a.shape
(2, 2)
İf you have list, you can print its shape as if it is converted to array
import numpy as np
print(np.asarray(X).shape)
how to create an array to numpy array?
def test(X, N):
[n,T] = X.shape
print "n : ", n
print "T : ", T
if __name__=="__main__":
X = [[[-9.035250067710876], [7.453250169754028], [33.34074878692627]], [[-6.63700008392334], [5.132999956607819], [31.66075038909912]], [[-5.1272499561309814], [8.251499891281128], [30.925999641418457]]]
N = 200
test(X, N)
I am getting error as
AttributeError: 'list' object has no attribute 'shape'
So, I think I need to convert my X to numpy array?
Use numpy.array
to use shape
attribute.
>>> import numpy as np
>>> X = np.array([
... [[-9.035250067710876], [7.453250169754028], [33.34074878692627]],
... [[-6.63700008392334], [5.132999956607819], [31.66075038909912]],
... [[-5.1272499561309814], [8.251499891281128], [30.925999641418457]]
... ])
>>> X.shape
(3L, 3L, 1L)
NOTE X.shape
returns 3-items tuple for the given array; [n, T] = X.shape
raises ValueError
.
import numpy
X = numpy.array(the_big_nested_list_you_had)
It’s still not going to do what you want; you have more bugs, like trying to unpack a 3-dimensional shape into two target variables in test
.
list object in python does not have ‘shape’ attribute because ‘shape’ implies that all the columns (or rows) have equal length along certain dimension.
Let’s say list variable a has following properties:
a = [[2, 3, 4]
[0, 1]
[87, 8, 1]]
it is impossible to define ‘shape’ for variable ‘a’.
That is why ‘shape’ might be determined only with ‘arrays’ e.g.
b = numpy.array([[2, 3, 4]
[0, 1, 22]
[87, 8, 1]])
I hope this explanation clarifies well this question.
Alternatively, you can use np.shape(...)
For instance:
import numpy as np
a=[1,2,3]
and np.shape(a)
will give an output of (3,)
If the type is list, use len(list)
and len(list[0])
to get the row and column.
l = [[1,2,3,4], [0,1,3,4]]
len(l)
will be 2.
len(l[0])
will be 4.
Firstly you have to import numpy library (refer code for making a numpy array).
shape
only gives the output only if the variable is attribute of numpy library. In other words it must be a np.array or any other data structure of numpy.
E.g.
import numpy
a=numpy.array([[1,1],[1,1]])
a.shape
(2, 2)
İf you have list, you can print its shape as if it is converted to array
import numpy as np
print(np.asarray(X).shape)