I programmed a little bit when I was younger but I was never really good. I find Python perfect for what I want to do.
I have an Excel file which contains data (64 columns, 18496 lines) that I read using the numpy genfromtxt function. I want to put everything in a 3D matrix named H. I use three loops to do so but I know that this is not the most efficient.
data = np.genfromtxt(filename, delimiter = ";",skiprows = 11)
H = np.zeros((N,N,Nt))
for k in np.arange(N):
for l in np.arange(N):
for m in np.arange(Nt):
H[k,l,m] = data[m+Nt*k,l]
Is there a cleaver (faster computing wise) to do so. I though about using numpy shape but I'm not able to do it.
Thanks
You could reshape with np.reshape
& then re-arrange dimensions with np.transpose
, like so -
H = data.reshape(N,Nt,N).transpose(0,2,1)
Instead of np.transpose
, one can also use np.swapaxes
as basically we are swapping axes 1,2
there, like so -
H = data.reshape(N,Nt,N).swapaxes(1,2)
Sample run -
In [300]: N = 2
...: Nt = 3
...: data = np.random.randint(0,9,(N*Nt,N))
...:
In [301]: data
Out[301]:
array([[3, 6],
[7, 4],
[8, 1],
[8, 7],
[4, 8],
[2, 3]])
In [302]: H = np.zeros((N,N,Nt),dtype=data.dtype)
...: for k in np.arange(N):
...: for l in np.arange(N):
...: for m in np.arange(Nt):
...: H[k,l,m] = data[m+Nt*k,l]
...:
In [303]: H
Out[303]:
array([[[3, 7, 8],
[6, 4, 1]],
[[8, 4, 2],
[7, 8, 3]]])
In [304]: data.reshape(N,Nt,N).transpose(0,2,1)
Out[304]:
array([[[3, 7, 8],
[6, 4, 1]],
[[8, 4, 2],
[7, 8, 3]]])
Runtime test -
In [8]: # Input
...: N = 10
...: Nt = 10*50
...: data = np.random.randint(0,9,(N*Nt,N))
...:
...: def original_app(data):
...: H = np.zeros((N,N,Nt),dtype=data.dtype)
...: for k in np.arange(N):
...: for l in np.arange(N):
...: for m in np.arange(Nt):
...: H[k,l,m] = data[m+Nt*k,l]
...: return H
...:
In [9]: np.allclose(original_app(data),data.reshape(N,Nt,N).transpose(0,2,1))
Out[9]: True
In [10]: %timeit original_app(data)
10 loops, best of 3: 56.1 ms per loop
In [11]: %timeit data.reshape(N,Nt,N).transpose(0,2,1)
1000000 loops, best of 3: 1.25 µs per loop
The technical post webpages of this site follow the CC BY-SA 4.0 protocol. If you need to reprint, please indicate the site URL or the original address.Any question please contact:yoyou2525@163.com.