Hi,

I created a numpy matrix(1 row, 3 cols) with the following values [4 6 8]. What I want to do is to concatenate all these values into a single entry of binary values. So instead of [4 6 8] I would want to have a numpy matrix of just 1 entry [010001101000]. I would like each number to be represented by a 4 digit binary number. I looked at reshape for numpy but am still unsure how to do this? Would appreciate it if anyone could help.

Thanks

You could matrix multiply on the right by matrix with 3 rows and 1 column [16*16, 16, 1].

>>> import numpy
>>> m = numpy.array([4, 6, 8])
>>> m
array([4, 6, 8])
>>> print m[-1]+16*m[-2]+16**2*m[-3]
1128
>>> sum(m*[16**2, 16, 1])
1128
>>> bin(1128)
'0b10001101000'
>>>

Ok, thanks that makes sense. Now, what if I have a numpy array as follows.

m = numpy.array([0xfe,0xff,0xf7,0xff,0x65,0xef,0xcc,0xff])

I want to be able to converge this numpy array into one entry. So I would like to have one entry of 64 bits for m. I am having trouble left shifting to get the correct value. I am wondering if there is some limitation to left shifting over so many places? Is there a better way of doing this for so many bits? Thanks.

I think you should be using struct module.