翻译强力驱动I have a numpy_array. Something like [ a b c ].
And then I want to append it into another NumPy array (just like we create a list of lists). How do we create an array of NumPy arrays containing NumPy arrays?
I tried to do the following without any luck
>>> M = np.array([]) >>> M array([], dtype=float64) >>> M.append(a,axis=0) Traceback (most recent call last): File "", line 1, in AttributeError: 'numpy.ndarray' object has no attribute 'append' >>> a array([1, 2, 3]) In [1]: import numpy as np In [2]: a = np.array([[1, 2, 3], [4, 5, 6]]) In [3]: b = np.array([[9, 8, 7], [6, 5, 4]]) In [4]: np.concatenate((a, b)) Out[4]: array([[1, 2, 3], [4, 5, 6], [9, 8, 7], [6, 5, 4]])or this:
In [1]: a = np.array([1, 2, 3]) In [2]: b = np.array([4, 5, 6]) In [3]: np.vstack((a, b)) Out[3]: array([[1, 2, 3], [4, 5, 6]])Well, the error message says it all: NumPy arrays do not have an append() method. There's a free function numpy.append() however:
numpy.append(M, a)This will create a new array instead of mutating M in place. Note that using numpy.append() involves copying both arrays. You will get better performing code if you use fixed-sized NumPy arrays.
Sven said it all, just be very cautious because of automatic type adjustments when append is called.
In [2]: import numpy as np In [3]: a = np.array([1,2,3]) In [4]: b = np.array([1.,2.,3.]) In [5]: c = np.array(['a','b','c']) In [6]: np.append(a,b) Out[6]: array([ 1., 2., 3., 1., 2., 3.]) In [7]: a.dtype Out[7]: dtype('int64') In [8]: np.append(a,c) Out[8]: array(['1', '2', '3', 'a', 'b', 'c'], dtype='|S1')As you see based on the contents the dtype went from int64 to float32, and then to S1
You may use numpy.append()...
import numpy B = numpy.array([3]) A = numpy.array([1, 2, 2]) B = numpy.append( B , A ) print B > [3 1 2 2]This will not create two separate arrays but will append two arrays into a single dimensional array.
Actually one can always create an ordinary list of numpy arrays and convert it later.
In [1]: import numpy as np In [2]: a = np.array([[1,2],[3,4]]) In [3]: b = np.array([[1,2],[3,4]]) In [4]: l = [a] In [5]: l.append(b) In [6]: l = np.array(l) In [7]: l.shape Out[7]: (2, 2, 2) In [8]: l Out[8]: array([[[1, 2], [3, 4]], [[1, 2], [3, 4]]])If I understand your question, here's one way. Say you have:
a = [4.1, 6.21, 1.0]so here's some code...
def array_in_array(scalarlist): return [(x,) for x in scalarlist]Which leads to:
In [72]: a = [4.1, 6.21, 1.0] In [73]: a Out[73]: [4.1, 6.21, 1.0] In [74]: def array_in_array(scalarlist): ....: return [(x,) for x in scalarlist] ....: In [75]: b = array_in_array(a) In [76]: b Out[76]: [(4.1,), (6.21,), (1.0,)]