Data-types¶
This section contains the documentation for float_type
,
fvec
, and cvec
.
-
aubio.
float_type
¶ A string constant describing the floating-point representation used in
fvec
,cvec
, and elsewhere in this module.Defaults to “float32”.
If aubio was built specifically with the option –enable-double, this string will be defined to “float64”. See Double precision in Installing aubio for Python for more details on building aubio in double precision mode.
Examples
>>> aubio.float_type 'float32' >>> numpy.zeros(10).dtype 'float64' >>> aubio.fvec(10).dtype 'float32' >>> np.arange(10, dtype=aubio.float_type).dtype 'float32'
-
class
aubio.
fvec
(input_arg=1024)[source]¶ A vector holding float samples.
If input_arg is an int, a 1-dimensional vector of length input_arg will be created and filled with zeros. Otherwise, if input_arg is an array_like object, it will be converted to a 1-dimensional vector of type
float_type
.Parameters: input_arg (int or array_like) – Can be a positive integer, or any object that can be converted to a numpy array with numpy.array()
.Examples
>>> aubio.fvec(10) array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], dtype=float32) >>> aubio.fvec([0,1,2]) array([0., 1., 2.], dtype=float32) >>> a = np.arange(10); type(a), type(aubio.fvec(a)) (<class 'numpy.ndarray'>, <class 'numpy.ndarray'>) >>> a.dtype, aubio.fvec(a).dtype (dtype('int64'), dtype('float32'))
Notes
In the Python world, fvec is simply a subclass of
numpy.ndarray
. In practice, any 1-dimensional numpy.ndarray of dtypefloat_type
may be passed to methods accepting fvec as parameter. For instance, sink() or pvoc().See also
cvec
- a container holding spectral data
numpy.ndarray
- parent class of
fvec
numpy.zeros
- create a numpy array filled with zeros
numpy.array
- create a numpy array from an existing object
-
class
aubio.
cvec
(size)¶ A container holding spectral data.
Create one cvec to store the spectral information of a window of size points. The data will be stored in two vectors,
phas
andnorm
, each of shape (length
,), with length = size // 2 + 1.Parameters: size (int) – Size of spectrum to create. Examples
>>> c = aubio.cvec(1024) >>> c aubio cvec of 513 elements >>> c.length 513 >>> c.norm.dtype, c.phas.dtype (dtype('float32'), dtype('float32')) >>> c.norm.shape, c.phas.shape ((513,), (513,))
-
length
¶ Length of norm and phas vectors.
Type: int
-
norm
¶ Vector of shape (length,) containing the magnitude.
Type: numpy.ndarray
-
phas
¶ Vector of shape (length,) containing the phase.
Type: numpy.ndarray
-