ref: 7a54b37160fa859f8decb918aebbea14dec4c31b
parent: 07382d8c0476840e5a86b3807577c988cc52e28a
author: Paul Brossier <piem@piem.org>
date: Wed Oct 31 15:36:31 EDT 2018
Merge branch 'fix/pyfvec'
--- a/python/lib/aubio/__init__.py
+++ b/python/lib/aubio/__init__.py
@@ -30,7 +30,7 @@
from .slicing import *
class fvec(numpy.ndarray):
- """fvec(input_arg=1024, **kwargs)
+ """fvec(input_arg=1024)
A vector holding float samples.
If `input_arg` is an `int`, a 1-dimensional vector of length `input_arg`
@@ -43,17 +43,7 @@
input_arg : `int` or `array_like`
Can be a positive integer, or any object that can be converted to
a numpy array with :func:`numpy.array`.
- **kwargs
- Additional keyword arguments passed to :func:`numpy.zeros`, if
- `input_arg` is an integer, or to :func:`numpy.array`. Should not
- include `dtype`, which is already specified as
- :data:`aubio.float_type`.
- Returns
- -------
- numpy.ndarray
- Array of shape `(length,)`.
-
Examples
--------
>>> aubio.fvec(10)
@@ -80,10 +70,15 @@
numpy.zeros : create a numpy array filled with zeros
numpy.array : create a numpy array from an existing object
"""
- def __new__(cls, input_arg=1024, **kwargs):
+ def __new__(cls, input_arg=1024):
if isinstance(input_arg, int):
if input_arg == 0:
raise ValueError("vector length of 1 or more expected")- return numpy.zeros(input_arg, dtype=float_type, **kwargs)
+ return numpy.zeros(input_arg, dtype=float_type, order='C')
else:
- return numpy.array(input_arg, dtype=float_type, **kwargs)
+ np_input = numpy.array(input_arg, dtype=float_type, order='C')
+ if len(np_input.shape) != 1:
+ raise ValueError("input_arg should have shape (n,)")+ if np_input.shape[0] == 0:
+ raise ValueError("vector length of 1 or more expected")+ return np_input
--- a/python/tests/test_fvec.py
+++ b/python/tests/test_fvec.py
@@ -60,6 +60,14 @@
self.assertRaises(IndexError, a.__getitem__, 3)
self.assertRaises(IndexError, a.__getitem__, 2)
+ def test_wrong_dimensions(self):
+ a = np.array([[[1, 2], [3, 4]]], dtype=float_type)
+ self.assertRaises(ValueError, fvec, a)
+
+ def test_wrong_size(self):
+ a = np.ndarray([0,], dtype=float_type)
+ self.assertRaises(ValueError, fvec, a)
+
class aubio_wrong_fvec_input(TestCase):
""" uses min_removal to test PyAubio_IsValidVector """