switching to high quality piper tts and added label translations

2026-01-29 23:48:19 +01:00
commit d80c619df9
3934 changed files with 1451600 additions and 0 deletions
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+"""A cache for storing small matrices in multiple formats."""
+
+from sympy.core.numbers import (I, Rational, pi)
+from sympy.core.power import Pow
+from sympy.functions.elementary.exponential import exp
+from sympy.matrices.dense import Matrix
+
+from sympy.physics.quantum.matrixutils import (
+    to_sympy, to_numpy, to_scipy_sparse
+)
+
+
+class MatrixCache:
+    """A cache for small matrices in different formats.
+
+    This class takes small matrices in the standard ``sympy.Matrix`` format,
+    and then converts these to both ``numpy.matrix`` and
+    ``scipy.sparse.csr_matrix`` matrices. These matrices are then stored for
+    future recovery.
+    """
+
+    def __init__(self, dtype='complex'):
+        self._cache = {}
+        self.dtype = dtype
+
+    def cache_matrix(self, name, m):
+        """Cache a matrix by its name.
+
+        Parameters
+        ----------
+        name : str
+            A descriptive name for the matrix, like "identity2".
+        m : list of lists
+            The raw matrix data as a SymPy Matrix.
+        """
+        try:
+            self._sympy_matrix(name, m)
+        except ImportError:
+            pass
+        try:
+            self._numpy_matrix(name, m)
+        except ImportError:
+            pass
+        try:
+            self._scipy_sparse_matrix(name, m)
+        except ImportError:
+            pass
+
+    def get_matrix(self, name, format):
+        """Get a cached matrix by name and format.
+
+        Parameters
+        ----------
+        name : str
+            A descriptive name for the matrix, like "identity2".
+        format : str
+            The format desired ('sympy', 'numpy', 'scipy.sparse')
+        """
+        m = self._cache.get((name, format))
+        if m is not None:
+            return m
+        raise NotImplementedError(
+            'Matrix with name %s and format %s is not available.' %
+            (name, format)
+        )
+
+    def _store_matrix(self, name, format, m):
+        self._cache[(name, format)] = m
+
+    def _sympy_matrix(self, name, m):
+        self._store_matrix(name, 'sympy', to_sympy(m))
+
+    def _numpy_matrix(self, name, m):
+        m = to_numpy(m, dtype=self.dtype)
+        self._store_matrix(name, 'numpy', m)
+
+    def _scipy_sparse_matrix(self, name, m):
+        # TODO: explore different sparse formats. But sparse.kron will use
+        # coo in most cases, so we use that here.
+        m = to_scipy_sparse(m, dtype=self.dtype)
+        self._store_matrix(name, 'scipy.sparse', m)
+
+
+sqrt2_inv = Pow(2, Rational(-1, 2), evaluate=False)
+
+# Save the common matrices that we will need
+matrix_cache = MatrixCache()
+matrix_cache.cache_matrix('eye2', Matrix([[1, 0], [0, 1]]))
+matrix_cache.cache_matrix('op11', Matrix([[0, 0], [0, 1]]))  # |1><1|
+matrix_cache.cache_matrix('op00', Matrix([[1, 0], [0, 0]]))  # |0><0|
+matrix_cache.cache_matrix('op10', Matrix([[0, 0], [1, 0]]))  # |1><0|
+matrix_cache.cache_matrix('op01', Matrix([[0, 1], [0, 0]]))  # |0><1|
+matrix_cache.cache_matrix('X', Matrix([[0, 1], [1, 0]]))
+matrix_cache.cache_matrix('Y', Matrix([[0, -I], [I, 0]]))
+matrix_cache.cache_matrix('Z', Matrix([[1, 0], [0, -1]]))
+matrix_cache.cache_matrix('S', Matrix([[1, 0], [0, I]]))
+matrix_cache.cache_matrix('T', Matrix([[1, 0], [0, exp(I*pi/4)]]))
+matrix_cache.cache_matrix('H', sqrt2_inv*Matrix([[1, 1], [1, -1]]))
+matrix_cache.cache_matrix('Hsqrt2', Matrix([[1, 1], [1, -1]]))
+matrix_cache.cache_matrix(
+    'SWAP', Matrix([[1, 0, 0, 0], [0, 0, 1, 0], [0, 1, 0, 0], [0, 0, 0, 1]]))
+matrix_cache.cache_matrix('ZX', sqrt2_inv*Matrix([[1, 1], [1, -1]]))
+matrix_cache.cache_matrix('ZY', Matrix([[I, 0], [0, -I]]))