I have a numpy array with numeric data of the form:
example = numpy.array([[[i for i in range(0, 5)],[0 for j in range(0, 5)]] for k in range(0, 10)])
So it's array of 10 groups, where each group consists of 2 lists of equal length and contains only numbers. Running the following save code gives me the error below:
numpy.savetxt('exampleData.csv', test, delimiter=',') TypeError: Mismatch between array dtype ('int32') and format specifier ('%.18e %.18e')
I'm guessing this could be fixed with something in the fmt='xyz' argument, but the documentation isn't particularly clear. Any help would be appreciated.
(In my actual data, the i and j lists are lists of long floats, e.g.'0.0047322940571' etc.)
Your example is a 3d array
In [82]: example=np.array([[[i for i in range(0, 5)],[0 for j in range(0, 5)]] for k in range(0, 3)]) # chg 10 to 3 for display In [83]: example.shape Out[83]: (3L, 2L, 5L) In [84]: example Out[84]: array([[[0, 1, 2, 3, 4], [0, 0, 0, 0, 0]], [[0, 1, 2, 3, 4], [0, 0, 0, 0, 0]], [[0, 1, 2, 3, 4], [0, 0, 0, 0, 0]]])
trying to save the whole thing results in an error (different message due to different version):
In [87]: np.savetxt('test.csv',example, delimiter=',') .... TypeError: float argument required, not numpy.ndarray
but saving one 'row' is ok
In [88]: np.savetxt('test.csv',example[1,...], delimiter=',')
Save with integer format makes a prettier output
In [94]: np.savetxt('test.csv',example[1,...], delimiter=',',fmt='%d') In [95]: with open('test.csv') as f:print f.read() 0,1,2,3,4 0,0,0,0,0
So how do you want the 3d array to be saved? Keep in mind how you will use it/read it. Multiple files? Multiple blocks within one file?
https://stackoverflow.com/a/3685339/901925 is a 6 yr old SO answer on how to save a 3d array. The simple answer is to open a file, and perform multiple savetxt for slices of the array. This saves the data in blocks. But loading those blocks is another SO question (which has come up before).
In [100]: with open('test.csv','w') as f: ...: for row in example: ...: np.savetxt(f,row,delimiter=',',fmt='%d',footer='====') ...: In [101]: with open('test.csv') as f:print f.read() 0,1,2,3,4 0,0,0,0,0 # ==== 0,1,2,3,4 0,0,0,0,0 # ==== 0,1,2,3,4 0,0,0,0,0 # ====
In response to your comment, this works
example=np.ones((4,2,100)) np.savetxt('test.csv',example[1,...], delimiter=',',fmt='%.18e')
Another way to save a 3d array is to reshape it to 2d. You reshape it back to 3d after loading, possibly using information that you stored in a comment line
np.savetxt('test.csv',example.reshape(-1,example.shape[-1]), delimiter=',',fmt='%.18e')
import numpy example = numpy.array([[[i for i in range(0, 5)],[0 for j in range(0, 5)]] for k in range(0, 10)]) f = open('exampleData.csv', 'ab') for i in example: numpy.savetxt(f, i, fmt='%i')
