Your message dated Wed, 24 Feb 2021 20:34:17 +0000
with message-id <[email protected]>
and subject line Bug#983397: fixed in qutip 4.5.2-2
has caused the Debian Bug report #983397,
regarding qutip: TestDicke fails with scipy 1.6.1: TypeError: can't convert
complex to float
to be marked as done.
This means that you claim that the problem has been dealt with.
If this is not the case it is now your responsibility to reopen the
Bug report if necessary, and/or fix the problem forthwith.
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--
983397: https://bugs.debian.org/cgi-bin/bugreport.cgi?bug=983397
Debian Bug Tracking System
Contact [email protected] with problems
--- Begin Message ---
Source: qutip
Version: 4.5.2-1
Severity: normal
Control: forwarded -1 https://github.com/qutip/qutip/issues/1451
Control: affects -1 src:scipy
Some TestDicke tests in test_piqs.py (test_lindbladian,
test_lindbladian_dims, test_liouvillian) fail with the
recent scipy 1.6.1 release, (scipy 1.6.1-1 is uploaded to
experimental). They were previously passing with scipy 1.6.0.
It's probably relevant that scipy 1.6.1 fixed some problems with
sparse matrices (with COO format constructor), see
https://docs.scipy.org/doc/scipy-1.6.1/reference/release.1.6.1.html
including PR#13403 https://github.com/scipy/scipy/pull/13403
To Reproduce
$ cp -r qutip/tests/ /tmp/qutip
$ cd /tmp/qutip
$ pytest-3 -v -k "TestDicke"
The test error message from TestDicke.test_lindbladian is
___________________________________________________________________________________________
TestDicke.test_lindbladian
____________________________________________________________________________________________
self = <tests.test_piqs.TestDicke object at 0x7f55475a0c10>
def test_lindbladian(self):
"""
PIQS: Test the generation of the Lindbladian matrix.
"""
N = 1
gCE = 0.5
gCD = 0.5
gCP = 0.5
gE = 0.1
gD = 0.1
gP = 0.1
system = Dicke(
N=N,
emission=gE,
pumping=gP,
dephasing=gD,
collective_emission=gCE,
collective_pumping=gCP,
collective_dephasing=gCD,
)
> lindbladian = system.lindbladian()
tests/test_piqs.py:450:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
/usr/lib/python3/dist-packages/qutip/piqs.py:509: in lindbladian
return cythonized_dicke.lindbladian()
qutip/cy/piqs.pyx:313: in qutip.cy.piqs.Dicke.lindbladian
???
qutip/cy/piqs.pyx:431: in qutip.cy.piqs.Dicke.lindbladian
???
/usr/lib/python3/dist-packages/scipy/sparse/compressed.py:54: in __init__
other = self.__class__(coo_matrix(arg1, shape=shape,
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <[AttributeError('dtype not found') raised in repr()] coo_matrix object
at 0x7f55475a0ca0>
arg1 = ([(-0.6000000238418579+0j), (0.6000000238418579+0j),
(-0.9000000357627869+0j), (-0.9000000357627869+0j), (-0.6000000238418579+0j),
(0.6000000014901161+0j)], ([3, 3, 2, 1, 0, 0], [3, 0, 2, 1, 0, 3]))
shape = (4, 4), dtype = None, copy = False
def __init__(self, arg1, shape=None, dtype=None, copy=False):
_data_matrix.__init__(self)
if isinstance(arg1, tuple):
if isshape(arg1):
M, N = arg1
self._shape = check_shape((M, N))
idx_dtype = get_index_dtype(maxval=max(M, N))
data_dtype = getdtype(dtype, default=float)
self.row = np.array([], dtype=idx_dtype)
self.col = np.array([], dtype=idx_dtype)
self.data = np.array([], dtype=data_dtype)
self.has_canonical_format = True
else:
try:
obj, (row, col) = arg1
except (TypeError, ValueError) as e:
raise TypeError('invalid input format') from e
if shape is None:
if len(row) == 0 or len(col) == 0:
raise ValueError('cannot infer dimensions from zero '
'sized index arrays')
M = operator.index(np.max(row)) + 1
N = operator.index(np.max(col)) + 1
self._shape = check_shape((M, N))
else:
# Use 2 steps to ensure shape has length 2.
M, N = shape
self._shape = check_shape((M, N))
idx_dtype = get_index_dtype(maxval=max(self.shape))
data_dtype = getdtype(dtype, obj, default=float)
self.row = np.array(row, copy=copy, dtype=idx_dtype)
self.col = np.array(col, copy=copy, dtype=idx_dtype)
> self.data = np.array(obj, copy=copy, dtype=data_dtype)
E TypeError: can't convert complex to float
/usr/lib/python3/dist-packages/scipy/sparse/coo.py:161: TypeError
Likewise for TestDicke.test_lindbladian_dims and TestDicke.test_liouvillian.
Test fails also with qutip 4.5.3 built on Debian unstable.
qutip.about()
QuTiP: Quantum Toolbox in Python
================================
Copyright (c) QuTiP team 2011 and later.
Current admin team: Alexander Pitchford, Nathan Shammah, Shahnawaz Ahmed, Neill
Lambert, Eric Giguère, Boxi Li and Jake Lishman.
Board members: Daniel Burgarth, Robert Johansson, Anton F. Kockum, Franco Nori
and Will Zeng.
Original developers: R. J. Johansson & P. D. Nation.
Previous lead developers: Chris Granade & A. Grimsmo.
Currently developed through wide collaboration. See https://github.com/qutip
for details.
QuTiP Version: 4.5.3
Numpy Version: 1.19.5
Scipy Version: 1.6.1
Cython Version: 0.29.21
Matplotlib Version: 3.3.4
Python Version: 3.9.1
Number of CPUs: 4
BLAS Info: OPENBLAS
OPENMP Installed: True
INTEL MKL Ext: False
Platform Info: Linux (x86_64)
Installation path: /usr/lib/python3/dist-packages/qutip
================================================================================
Please cite QuTiP in your publication.
================================================================================
For your convenience a bibtex reference can be easily generated using
`qutip.cite()`
-- System Information:
Debian Release: bullseye/sid
APT prefers unstable
APT policy: (500, 'unstable'), (1, 'experimental')
Architecture: amd64 (x86_64)
Foreign Architectures: i386
Kernel: Linux 5.10.0-3-amd64 (SMP w/8 CPU threads)
Kernel taint flags: TAINT_PROPRIETARY_MODULE, TAINT_OOT_MODULE
Locale: LANG=en_AU.UTF-8, LC_CTYPE=en_AU.UTF-8 (charmap=UTF-8),
LANGUAGE=en_AU:en
Shell: /bin/sh linked to /usr/bin/dash
Init: systemd (via /run/systemd/system)
LSM: AppArmor: enabled
--- End Message ---
--- Begin Message ---
Source: qutip
Source-Version: 4.5.2-2
Done: Drew Parsons <[email protected]>
We believe that the bug you reported is fixed in the latest version of
qutip, which is due to be installed in the Debian FTP archive.
A summary of the changes between this version and the previous one is
attached.
Thank you for reporting the bug, which will now be closed. If you
have further comments please address them to [email protected],
and the maintainer will reopen the bug report if appropriate.
Debian distribution maintenance software
pp.
Drew Parsons <[email protected]> (supplier of updated qutip package)
(This message was generated automatically at their request; if you
believe that there is a problem with it please contact the archive
administrators by mailing [email protected])
-----BEGIN PGP SIGNED MESSAGE-----
Hash: SHA256
Format: 1.8
Date: Wed, 24 Feb 2021 19:55:30 +0100
Source: qutip
Architecture: source
Version: 4.5.2-2
Distribution: unstable
Urgency: medium
Maintainer: Debian Science Maintainers
<[email protected]>
Changed-By: Drew Parsons <[email protected]>
Closes: 983397
Changes:
qutip (4.5.2-2) unstable; urgency=medium
.
* debian patch sparse_matrix_explicit_dtype_1452.patch applies
upstream PR#1452 to explicitly set dtype=np.complex128 when
constructing scipy.sparse matrices with csr_matrix. Required for
working with scipy 1.6.1. Closes: #983397.
* Standards-Version: 4.5.1
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