>>> np.frombuffer(b'x00x00x80?x00x00x00@x00x00@@x00x00x80@', dtype='<f4') # or dtype=np.dtype('<f4'), or np.float32 on a little-endian system (which most computers are these days)
array([ 1., 2., 3., 4.], dtype=float32)
Or, if you want big-endian:
>>> np.frombuffer(b'x00x00x80?x00x00x00@x00x00@@x00x00x80@', dtype='>f4') # or dtype=np.dtype('>f4'), or np.float32 on a big-endian system
array([ 4.60060299e-41, 8.96831017e-44, 2.30485571e-41,
4.60074312e-41], dtype=float32)
The b
isn't necessary prior to Python 3, of course.
In fact, if you actually are using a binary file to load the data from, you could even skip the using-a-string step and load the data directly from the file with numpy.fromfile()
.
Also, dtype reference, just in case: http://docs.scipy.org/doc/numpy/reference/arrays.dtypes.html
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