From bd885029d90f5655bd87f272ca95d2e7b0b199fc Mon Sep 17 00:00:00 2001
From: Joseph Weston <joseph.weston08@gmail.com>
Date: Mon, 11 Sep 2017 17:47:21 +0200
Subject: [PATCH] remove superfluous return value from 'prepare_for_lapack'
---
kwant/linalg/decomp_ev.py | 2 +-
kwant/linalg/decomp_lu.py | 6 +++---
kwant/linalg/decomp_schur.py | 14 +++++++-------
kwant/linalg/lapack.pyx | 20 +++++++-------------
4 files changed, 18 insertions(+), 24 deletions(-)
diff --git a/kwant/linalg/decomp_ev.py b/kwant/linalg/decomp_ev.py
index 1d3bb587..8e7b95d6 100644
--- a/kwant/linalg/decomp_ev.py
+++ b/kwant/linalg/decomp_ev.py
@@ -50,5 +50,5 @@ def gen_eig(a, b, left=False, right=True, overwrite_ab=False):
The right eigenvector corresponding to the eigenvalue
``alpha[i]/beta[i]`` is the column ``vr[:,i]``.
"""
- ltype, a, b = lapack.prepare_for_lapack(overwrite_ab, a, b)
+ a, b = lapack.prepare_for_lapack(overwrite_ab, a, b)
return lapack.ggev(a, b, left, right)
diff --git a/kwant/linalg/decomp_lu.py b/kwant/linalg/decomp_lu.py
index ace2af08..639b547b 100644
--- a/kwant/linalg/decomp_lu.py
+++ b/kwant/linalg/decomp_lu.py
@@ -45,7 +45,7 @@ def lu_factor(a, overwrite_a=False):
singular : boolean
Whether the matrix a is singular (up to machine precision)
"""
- ltype, a = lapack.prepare_for_lapack(overwrite_a, a)
+ a = lapack.prepare_for_lapack(overwrite_a, a)
return lapack.getrf(a)
@@ -71,7 +71,7 @@ def lu_solve(matrix_factorization, b):
"a singular matrix. Result of solve step "
"are probably unreliable")
- ltype, lu, b = lapack.prepare_for_lapack(False, lu, b)
+ lu, b = lapack.prepare_for_lapack(False, lu, b)
ipiv = np.ascontiguousarray(np.asanyarray(ipiv), dtype=lapack.int_dtype)
return lapack.getrs(lu, ipiv, b)
@@ -102,5 +102,5 @@ def rcond_from_lu(matrix_factorization, norm_a, norm="1"):
"""
(lu, ipiv, singular) = matrix_factorization
norm = norm.encode('utf8') # lapack expects bytes
- ltype, lu = lapack.prepare_for_lapack(False, lu)
+ lu = lapack.prepare_for_lapack(False, lu)
return lapack.gecon(lu, norm_a, norm)
diff --git a/kwant/linalg/decomp_schur.py b/kwant/linalg/decomp_schur.py
index af50f1e8..d6543213 100644
--- a/kwant/linalg/decomp_schur.py
+++ b/kwant/linalg/decomp_schur.py
@@ -62,7 +62,7 @@ def schur(a, calc_q=True, calc_ev=True, overwrite_a=False):
LinAlgError
If the underlying QR iteration fails to converge.
"""
- ltype, a = lapack.prepare_for_lapack(overwrite_a, a)
+ a = lapack.prepare_for_lapack(overwrite_a, a)
return lapack.gees(a, calc_q, calc_ev)
@@ -182,7 +182,7 @@ def order_schur(select, t, q, calc_ev=True, overwrite_tq=False):
``calc_ev == True``
"""
- ltype, t, q = lapack.prepare_for_lapack(overwrite_tq, t, q)
+ t, q = lapack.prepare_for_lapack(overwrite_tq, t, q)
# Figure out if select is a function or array.
isfun = isarray = True
@@ -255,7 +255,7 @@ def evecs_from_schur(t, q, select=None, left=False, right=True,
``right == True``.
"""
- ltype, t, q = lapack.prepare_for_lapack(overwrite_tq, t, q)
+ t, q = lapack.prepare_for_lapack(overwrite_tq, t, q)
# check if select is a function or an array
if select is not None:
@@ -346,7 +346,7 @@ def gen_schur(a, b, calc_q=True, calc_z=True, calc_ev=True,
LinAlError
If the underlying QZ iteration fails to converge.
"""
- ltype, a, b = lapack.prepare_for_lapack(overwrite_ab, a, b)
+ a, b = lapack.prepare_for_lapack(overwrite_ab, a, b)
return lapack.gges(a, b, calc_q, calc_z, calc_ev)
@@ -408,7 +408,7 @@ def order_gen_schur(select, s, t, q=None, z=None, calc_ev=True,
LinAlError
If the problem is too ill-conditioned.
"""
- ltype, s, t, q, z = lapack.prepare_for_lapack(overwrite_stqz, s, t, q, z)
+ s, t, q, z = lapack.prepare_for_lapack(overwrite_stqz, s, t, q, z)
# Figure out if select is a function or array.
@@ -491,7 +491,7 @@ def convert_r2c_gen_schur(s, t, q=None, z=None):
If it fails to convert a 2x2 block into complex form (unlikely).
"""
- ltype, s, t, q, z = lapack.prepare_for_lapack(True, s, t, q, z)
+ s, t, q, z = lapack.prepare_for_lapack(True, s, t, q, z)
# Note: overwrite=True does not mean much here, the arrays are all copied
if (s.ndim != 2 or t.ndim != 2 or
@@ -611,7 +611,7 @@ def evecs_from_gen_schur(s, t, q=None, z=None, select=None,
"""
- ltype, s, t, q, z = lapack.prepare_for_lapack(overwrite_qz, s, t, q, z)
+ s, t, q, z = lapack.prepare_for_lapack(overwrite_qz, s, t, q, z)
if left and q is None:
raise ValueError("Matrix q must be provided for left eigenvectors")
diff --git a/kwant/linalg/lapack.pyx b/kwant/linalg/lapack.pyx
index 53fdaab2..e173bc0c 100644
--- a/kwant/linalg/lapack.pyx
+++ b/kwant/linalg/lapack.pyx
@@ -1274,8 +1274,7 @@ def prepare_for_lapack(overwrite, *args):
If an argument is ``None``, it is just passed through and not used to
determine the proper LAPACK type.
- `prepare_for_lapack` returns a character indicating the proper LAPACK data
- type ('s', 'd', 'c', 'z') and a list of properly converted arrays.
+ Returns a list of properly converted arrays.
"""
# Make sure we have NumPy arrays
@@ -1296,18 +1295,10 @@ def prepare_for_lapack(overwrite, *args):
# kind.
dtype = np.common_type(*[arr for arr, ovwrt in mats if arr is not None])
- if dtype == np.float32:
- lapacktype = 's'
- elif dtype == np.float64:
- lapacktype = 'd'
- elif dtype == np.complex64:
- lapacktype = 'c'
- elif dtype == np.complex128:
- lapacktype = 'z'
- else:
+ if dtype not in (np.float32, np.float64, np.complex64, np.complex128):
raise AssertionError("Unexpected data type from common_type")
- ret = [ lapacktype ]
+ ret = []
for npmat, ovwrt in mats:
# Now make sure that the array is contiguous, and copy if necessary.
if npmat is not None:
@@ -1332,4 +1323,7 @@ def prepare_for_lapack(overwrite, *args):
ret.append(npmat)
- return tuple(ret)
+ if len(ret) == 1:
+ return ret[0]
+ else:
+ return tuple(ret)
--
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