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问题:
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?
回答1:
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
.
回答2:
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
.
回答3:
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.
回答4:
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,)
回答5:
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
回答6:
firstly u 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. Eg.
`>>> import numpy >>> a=numpy.array([[1,1],[1,1]]) >>> a.shape (2, 2)`