根据一行数据创建一个numpy数组

Question

My data file has a sample for each row. Each row is 400 float number. It's a 20x20 image on a single line. I have to write a numpy array with dimensions (number of row, 20, 20, 1). Last dimension is the value (the float number in the file).

I tried something like:

X1=[]
for x in range (1,nrow+1):
    for a in range (1,21):
        for b in range (1,21):
           index = a*b-1
           X1.append((x,a,b,X[x,index]))
X = np.array(X1)

but I know this is wrong.

EDIT:

Maybe this is the solution:

X1=[]
for x in range (1,Nsamples+1):
    for a in range (1,21):
        for b in range (1,21):
           index = a*b-1
           X1.append((X[x,index]))
           #X1.append((X[x,index], x))
X = np.array(X1)
X = X.reshape(Nsamples,20,20,1)

Answer 1

try using reshape

X = X.reshape(X.shape[0],20,20,1)

it will give you a numpy array of reshaped images with same number of lines

Answer 2

This seems to be the correct answer, thanks to people who helped.

X1=[]
for x in range (1,Nsamples+1):
    for a in range (1,21):
        for b in range (1,21):
           index = a*b-1
           X1.append((X[x,index]))
X = np.array(X1)
X = X.reshape(Nsamples,20,20,1)