I generate some data in my memory and I want to cast it into numpy.memmap to save up RAM. What should I do? my data is in:
X_list_total_standardized=np.array(X_list_total_standardized)
I know that I could initialize an empty numpy.memmap:
X_list_total_standardized_memmap=np.memmap(self._prepared_data_location_npmemmap_X,dtype='float32',mode='w+')
What is the most convenient way to store X_list_total_standardized into the memmap? Thank you
PS: would the following command be ok?
X_list_total_standardized_memmap[:]=X_list_total_standardized[:]
I found next example in numpy documentation :
data = np.arange(12, dtype='float32')
data.resize((3,4))
fp = np.memmap(filename, dtype='float32', mode='w+', shape=(3,4))
fp[:] = data[:]
So your last command is ok.