From 39b4ca8d2ba0e6902be208e461ac0676e3719ff1 Mon Sep 17 00:00:00 2001
From: Joseph Weston <joseph@weston.cloud>
Date: Mon, 25 Nov 2019 12:31:45 +0100
Subject: [PATCH] rename hamiltonian_term data normalization in 'system' module
We will need this normalization in several places, and it is
more general than *just* Hamiltonian terms.
---
kwant/builder.py | 26 ++------------------------
kwant/system.py | 30 ++++++++++++++++++++++++++++++
2 files changed, 32 insertions(+), 24 deletions(-)
diff --git a/kwant/builder.py b/kwant/builder.py
index 01fbc078..8f189ede 100644
--- a/kwant/builder.py
+++ b/kwant/builder.py
@@ -2153,7 +2153,7 @@ class _VectorizedFinalizedBuilderMixin(_FinalizedBuilderMixin):
except Exception as exc:
_raise_user_error(exc, val)
- ham = _normalize_term_value(ham, len(to_site_array))
+ ham = system._normalize_matrix_blocks(ham, len(to_site_array))
return ham
@@ -2392,33 +2392,11 @@ class _IdBySite:
raise KeyError(site)
-def _normalize_term_value(value, expected_n_values):
- try:
- value = np.asarray(value, dtype=complex)
- except TypeError:
- raise ValueError(
- "Matrix elements declared with incompatible shapes."
- ) from None
- # Upgrade to vector of matrices
- if len(value.shape) == 1:
- value = value[:, np.newaxis, np.newaxis]
- if len(value.shape) != 3:
- msg = (
- "Vectorized value functions must return an array of"
- "scalars or an array of matrices."
- )
- raise ValueError(msg)
- if value.shape[0] != expected_n_values:
- raise ValueError("Value functions must return a single value per "
- "onsite/hopping.")
- return value
-
-
def _sort_term(term, value):
term = np.asarray(term)
if not callable(value):
- value = _normalize_term_value(value, len(term))
+ value = system._normalize_matrix_blocks(value, len(term))
# Ensure that values still correspond to the correct
# sites in 'term' once the latter has been sorted.
value = value[term.argsort()]
diff --git a/kwant/system.py b/kwant/system.py
index f25761bf..6e77ea67 100644
--- a/kwant/system.py
+++ b/kwant/system.py
@@ -742,6 +742,36 @@ def is_vectorized(syst):
return isinstance(syst, (FiniteVectorizedSystem, InfiniteVectorizedSystem))
+def _normalize_matrix_blocks(matrix_blocks, expected_length):
+ """Normalize a sequence of matrices into a single 3D numpy array
+
+ Parameters
+ ----------
+ matrix_blocks : sequence of complex array-like
+ expected_length : int
+ """
+ try:
+ matrix_blocks = np.asarray(matrix_blocks, dtype=complex)
+ except TypeError:
+ raise ValueError(
+ "Matrix elements declared with incompatible shapes."
+ ) from None
+ # Upgrade to vector of matrices
+ if len(matrix_blocks.shape) == 1:
+ matrix_blocks = matrix_blocks[:, np.newaxis, np.newaxis]
+ if len(matrix_blocks.shape) != 3:
+ msg = (
+ "Vectorized value functions must return an array of"
+ "scalars or an array of matrices."
+ )
+ raise ValueError(msg)
+ if matrix_blocks.shape[0] != expected_length:
+ raise ValueError("Value functions must return a single value per "
+ "onsite/hopping.")
+ return matrix_blocks
+
+
+
class PrecalculatedLead:
def __init__(self, modes=None, selfenergy=None):
"""A general lead defined by its self energy.
--
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