Reputation: 2581
In my situation I get a numpy.ndarray
as unit8
of size 4 * n
which represents raw binary data of float32
entities. So 4 items together represent one float32
. To get float32
numbers I currently convert uint8
raw data to a binary string and than read from this string the float32
values.
np.fromstring(raw_unit8_data.tostring(), dtype='<f4')
Is there a possibility to do this conversion directly without converting the uint8
data to a string first?
Upvotes: 5
Views: 8694
Reputation: 176938
You could use view
to have NumPy reinterpret the raw data as the appropriate data type. For example:
>>> raw_unit8_data = np.array([32, 14, 135, 241], dtype='uint8')
>>> raw_unit8_data.view('<f4')
array([ -1.33752168e+30], dtype=float32)
This has the advantage of not using any temporary arrays or buffers (we're just changing how the memory is read) and gives the same values as your current method:
>>> np.fromstring(raw_unit8_data.tostring(), dtype='<f4')
array([ -1.33752168e+30], dtype=float32)
Upvotes: 6