I would like to divide the 102×102 matrix into 17×17 matrices.
The 102 matrix has the number of the matrix, so
When I read it, I changed it from Dataframe to an array.
I was able to read the 102 matrix, but how should I divide it?
Should I use split for division?
Thank you for your cooperation.
The code to read the matrix is as follows:
dfs=[]
for filename in filenames:
# print(filename)
df=pd.read_csv(filename,index_col=0)
# print(df)
a_df=df.values
print(a_df)
print(a_df.shape)
I tried dividing the matrix using only the slicing of numpy.
def func1(arr,block_size,block_num):
size=block_size*block_num
result = [ ]
for row in range (0, size, block_size):
block=[ ]
for colin range(0,size,block_size):
block.append(arr[row:row+block_size, col:col+block_size])
result.append(block)
return result
def func2(arr,block_size,block_num):
size=block_size*block_num
return [[arr[row:row+block_size, col:col+block_size] for col in range(0,size,block_size)] for row in range(0,size,block_size)]
Google Colab measured 115 ss for func1 and 107 ss for func2 and 470 ss for np.split.
a_df is NumPyarray, so I tried to implement np.split to form a block matrix in two stages.
Sample Code:
block_size=6
block_num=17
size=block_size*block_num
arr=np.array([i*j for jin range(size)] for i in range (size)])
h_arr=np.split(arr,block_num,axis=0)
hv_arr = [np.split(elm, block_num,axis=1) for elmin h_arr]
np.split returns a list of NumPyarrays.So I cut them vertically first, and then cut each part vertically to make a list of NumPyarray lists.
Also, I have found that other methods are organized into Slice2d array into smallers, so I will link them for your reference.
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