diff --git a/doc/conf.py b/doc/conf.py
index 2dc91c33b73b77bfd3aad79f62849cea7647084c..a38e42ca2f6c0d368ea321dd412698f4779edefc 100644
--- a/doc/conf.py
+++ b/doc/conf.py
@@ -9,3 +9,7 @@ exclude_patterns = ['_build', 'Thumbs.db', '.DS_Store']
html_theme = 'nature'
autodoc_member_order = "groupwise"
+
+autodoc_default_options = {
+ 'special-members': '__init__, __call__'
+}
diff --git a/tests/test_basic.py b/tests/test_basic.py
index a5a1c8acee589427fbbd5b709f088fb510525d01..117ff572884383de1e36cc3e06d23a6074f42818 100644
--- a/tests/test_basic.py
+++ b/tests/test_basic.py
@@ -38,7 +38,7 @@ def test_solve_dos():
s = basic_setup()
E = np.linspace(-3, 3, 101) + 0.05j
res = s.solve_many(omega=-1j * E)
- g = res.G[:, 10, 2, 0, 0]
+ g = res.G[10, 2, :, 0, 0]
g_an = -1j * E / np.sqrt(1 - E**2)
assert_allclose(g, g_an, rtol=1e-4)
@@ -59,10 +59,10 @@ def test_result_S_J0(omega, h, terminals):
vol = s.Lx * s.Ly / (s.shape[0] * s.shape[1]) * 4j
- assert_allclose(S[:, :, :2, :2], vol * res.G)
- assert_allclose(S[:, :, :2, 2:], vol * res.F)
- assert_allclose(S[:, :, 2:, :2], vol * res.Fc)
- assert_allclose(S[:, :, 2:, 2:], vol * res.Gc)
+ assert_allclose(S[:, :, :2, :2], vol * res.G.A)
+ assert_allclose(S[:, :, :2, 2:], vol * res.F.A)
+ assert_allclose(S[:, :, 2:, :2], vol * res.Fc.A)
+ assert_allclose(S[:, :, 2:, 2:], vol * res.Gc.A)
# Check vs. analytic
print(omega, h)
@@ -73,15 +73,15 @@ def test_result_S_J0(omega, h, terminals):
Fcan = np.diag([1 / np.sqrt(wp**2 + 1), 1 / np.sqrt(wm**2 + 1)])
Gcan = -np.diag([wp / np.sqrt(wp**2 + 1), wm / np.sqrt(wm**2 + 1)])
- shp = res.G.shape
+ shp = res.G.A.shape
- assert_allclose(res.G, np.broadcast_to(Gan, shp), rtol=1e-5)
- assert_allclose(res.F, np.broadcast_to(Fan, shp), rtol=1e-5)
- assert_allclose(res.Fc, np.broadcast_to(Fcan, shp), rtol=1e-5)
- assert_allclose(res.Gc, np.broadcast_to(Gcan, shp), rtol=1e-5)
+ assert_allclose(res.G.A, np.broadcast_to(Gan, shp), rtol=1e-5)
+ assert_allclose(res.F.A, np.broadcast_to(Fan, shp), rtol=1e-5)
+ assert_allclose(res.Fc.A, np.broadcast_to(Fcan, shp), rtol=1e-5)
+ assert_allclose(res.Gc.A, np.broadcast_to(Gcan, shp), rtol=1e-5)
# There are no gradients, hence no currents either
- J = res.J
+ J = res.J.A
assert_allclose(J, 0, atol=1e-5)
diff --git a/tests/test_solver.py b/tests/test_solver.py
index 52d00dc61feef28aa0a73844a80d30a988321e85..3e258d39667886df0d69c33c85ad5ae2a87713e2 100644
--- a/tests/test_solver.py
+++ b/tests/test_solver.py
@@ -341,8 +341,8 @@ def test_soc_analytic(T, n, alpha_soc):
assert_allclose(Jy, Jy_an, rtol=1e-2)
- Fs.append(res0.F.copy())
- Gs.append(res0.G.copy())
+ Fs.append(res0.F.A.copy())
+ Gs.append(res0.G.A.copy())
Phis.append(res0.Phi.copy())
Js.append(J)
Jans.append(Jy_an)
diff --git a/usadelndsoc/solver.py b/usadelndsoc/solver.py
index 664b9098a33ccb49550a6bd2d32a33bc9e682aec..a667c3de0ca8c6d50829e473f154ef2fd25c549a 100644
--- a/usadelndsoc/solver.py
+++ b/usadelndsoc/solver.py
@@ -56,6 +56,9 @@ __all__ = [
"S_z",
"S_0",
"interpolate_J",
+ "interpolate_S",
+ "Density",
+ "Current",
]
_log = logging.getLogger(__name__)
@@ -110,13 +113,26 @@ def _core_property(name, doc=None):
def fset(self, value):
setattr(self._core, name, value)
- return property(fget, fset, doc=doc or getattr(Core, name).__doc__)
+ fget.__name__ = name
+ fset.__name__ = f"set_{name}"
+ doc = doc or getattr(Core, name).__doc__
+ return property(fget, fset, doc=doc)
-def _array_property(name, doc=None):
+def _array_property(name, doc=None, cls=None):
def fget(self):
- return getattr(self, name)
-
+ v = getattr(self, name)
+ if cls is not None:
+ return cls(self, v)
+ else:
+ return v
+
+ fget.__name__ = name
+ if doc is None:
+ doc = ""
+ doc = textwrap.dedent(doc)
+ if cls is not None:
+ doc += f"\n\n:Type: :any:`{cls.__name__}`"
return property(fget, doc=doc)
@@ -135,6 +151,94 @@ def _norm(z):
raise ValueError("Invalid data type")
+class Density:
+ """
+ Density interpolator.
+ """
+
+ def __init__(self, parent, data):
+ self.__parent = parent
+ self.__data = data
+
+ def __getitem__(self, ix):
+ return self.__data[ix]
+
+ @property
+ def A(self):
+ """Raw data array. Shape (nx, ny, ...)"""
+ return self.__data
+
+ def __call__(self, x, y, method="bilinear"):
+ """
+ Interpolate density at given coordinates.
+
+ Parameters
+ ----------
+ x : array, shape (...)
+ x-coordinates of the points to interpolate at
+ y : array, shape x.shape
+ y-coordinates of the points to interpolate at
+ method : {'bilinear'}
+ Interpolation method
+
+ Returns
+ -------
+ S : array, shape x.shape + (...)
+ Interpolated density.
+
+ See Also
+ --------
+ interpolate_S
+ """
+ return interpolate_S(
+ self.__parent.x, self.__parent.y, self.__data, x, y, method
+ )
+
+
+class Current:
+ """
+ Current interpolator.
+ """
+
+ def __init__(self, parent, data):
+ self.__parent = parent
+ self.__data = data
+
+ def __getitem__(self, ix):
+ return self.__data[ix]
+
+ @property
+ def A(self):
+ """Raw data array. Shape (nx, ny, 4(direction), ...)"""
+ return self.__data
+
+ def __call__(self, x, y, method="bilinear"):
+ """
+ Interpolate current at given coordinates.
+
+ Parameters
+ ----------
+ x : array, shape (...)
+ x-coordinates of the points to interpolate at
+ y : array, shape x.shape
+ y-coordinates of the points to interpolate at
+ method : {'bilinear'}
+ Interpolation method
+
+ Returns
+ -------
+ J : array, shape x.shape + (2, ...)
+ Interpolated current x and y components.
+
+ See Also
+ --------
+ interpolate_J
+ """
+ return interpolate_S(
+ self.__parent.x, self.__parent.y, self.__data, x, y, method
+ )
+
+
class Solver:
__global_id = 0
@@ -175,6 +279,7 @@ class Solver:
Phi = _array_property(
"_Phi",
doc=r"""Current saddle-point solution in Riccati parametrization. Array of complex, shape (nx, ny, 2, 2, 2).""",
+ cls=Density,
)
J_tot = _array_property(
"_J_tot",
@@ -182,12 +287,14 @@ class Solver:
Matsubara-summed matrix current between cells, :math:`J = -i \pi T\sum_{\omega_n} \mathcal{J}(\omega_n)`.
Array of complex, shape (nx, ny, 4(direction), 4, 4).
""",
+ cls=Current,
)
S_tot = _array_property(
"_S_tot",
doc=r"""Matsubara-summed density, :math:`S = \pi T \sum_{\omega_n} [Q(\omega_n) - \tau_3]`.
Array of complex, shape (nx, ny, 4, 4).
""",
+ cls=Density,
)
def reset(self):
@@ -647,7 +754,7 @@ class Solver:
omega0 = np.asarray(omega)
omega = omega0.ravel()
- Phi = np.zeros(omega.shape + self.Phi.shape, dtype=self.Phi.dtype)
+ Phi = np.zeros(omega.shape + self.Phi.A.shape, dtype=self.Phi.A.dtype)
js = np.lexsort((-abs(omega), np.sign(omega.real)))
@@ -723,7 +830,7 @@ class Solver:
mask = self.mask == MASK_NONE
self.Delta[mask] = 2 * T_c0[mask, None, None] * np.eye(2)
res = _self_consistency(self, T, T_c0, **kw)
- self.Delta[...], self.J_tot[...], self.S_tot[...], cx, success = res
+ self.Delta[...], self._J_tot[...], self._S_tot[...], cx, success = res
return self.Delta, self.J_tot, self.S_tot, cx, success
@@ -751,72 +858,113 @@ class Result:
self.Phi = Phi
self.mask = parent.mask
+ def _density(self, v):
+ if np.asarray(self.omega).ndim == 0:
+ r = v
+ else:
+ r = np.moveaxis(v, 0, 2)
+ return Density(self, r)
+
+ def _current(self, v):
+ if np.asarray(self.omega).ndim == 0:
+ r = v
+ else:
+ r = np.moveaxis(v, 0, 3)
+ return Current(self, r)
+
@property
def Delta(self):
"""
- Order parameter. Shape (nx, ny, 2, 2).
+ Order parameter.
+
+ :Type: :any:`Density`
+ :Shape: (nx, ny, 2, 2)
"""
- return _DeltaArray(self.Omega)
+ return Density(self, _DeltaArray(self.Omega).A)
@property
def G(self):
"""
- Green function Nambu 11-block. Shape ([nw,] nx, ny, 2, 2).
+ Green function Nambu 11-block.
+
+ :Type: :any:`Density`
+ :Shape: (nx, ny, [nw,] 2, 2)
"""
g = self.Phi[..., 0, :, :]
gt = self.Phi[..., 1, :, :]
I = np.eye(2)
s = _bcast_left(np.sign(self.omega), g.shape)
with np.errstate(invalid="ignore"):
- return s * np.linalg.solve(I + g @ gt, I - g @ gt)
+ r = s * np.linalg.solve(I + g @ gt, I - g @ gt)
+ return self._density(r)
@property
def Gc(self):
"""
- Green function Nambu 22-block. Shape ([nw,] nx, ny, 2, 2).
+ Green function Nambu 22-block.
+
+ :Type: :any:`Density`
+ :Shape: (nx, ny, [nw,] 2, 2)
"""
g = self.Phi[..., 0, :, :]
gt = self.Phi[..., 1, :, :]
I = np.eye(2)
s = _bcast_left(np.sign(self.omega), g.shape)
with np.errstate(invalid="ignore"):
- return -s * np.linalg.solve(I + gt @ g, I - gt @ g)
+ r = -s * np.linalg.solve(I + gt @ g, I - gt @ g)
+ return self._density(r)
@property
def F(self):
"""
- Green function Nambu 12-block. Shape ([nw,] nx, ny, 2, 2).
+ Green function Nambu 12-block.
+
+ :Type: :any:`Density`
+ :Shape: (nx, ny, [nw,] 2, 2)
"""
g = self.Phi[..., 0, :, :]
gt = self.Phi[..., 1, :, :]
I = np.eye(2)
s = _bcast_left(np.sign(self.omega), g.shape)
with np.errstate(invalid="ignore"):
- return 2 * s * np.linalg.solve(I + g @ gt, g)
+ r = 2 * s * np.linalg.solve(I + g @ gt, g)
+ return self._density(r)
@property
def Fc(self):
"""
- Green function Nambu 21-block. Shape ([nw,] nx, ny, 2, 2).
+ Green function Nambu 21-block.
+
+ :Type: :any:`Density`
+ :Shape: (nx, ny, [nw,] 2, 2)
"""
g = self.Phi[..., 0, :, :]
gt = self.Phi[..., 1, :, :]
I = np.eye(2)
s = _bcast_left(np.sign(self.omega), g.shape)
with np.errstate(invalid="ignore"):
- return 2 * s * np.linalg.solve(I + gt @ g, gt)
+ r = 2 * s * np.linalg.solve(I + gt @ g, gt)
+ return self._density(r)
@property
def Q(self):
"""
- Full Green function / Q-matrix. Shape ([nw,] nx, ny, 4, 4).
+ Full Green function / Q-matrix.
+
+ :Type: :any:`Density`
+ :Shape: (nx, ny, [nw,] 4, 4)
"""
- r = np.zeros(self.shape + (4, 4), dtype=complex)
- r[..., :2, :2] = self.G
- r[..., 2:, 2:] = self.Gc
- r[..., :2, 2:] = self.F
- r[..., 2:, :2] = self.Fc
- return r
+ w = np.asarray(self.omega)
+ if w.ndim == 0:
+ r = np.zeros(self.shape + (4, 4), dtype=complex)
+ else:
+ r = np.zeros(self.shape + w.shape + (4, 4), dtype=complex)
+
+ r[..., :2, :2] = self.G.A
+ r[..., 2:, 2:] = self.Gc.A
+ r[..., :2, 2:] = self.F.A
+ r[..., 2:, :2] = self.Fc.A
+ return Density(self, r)
def _get_J(self, omega, Phi):
old_omega = self._core.omega
@@ -837,19 +985,23 @@ class Result:
@property
def S(self):
"""
- Matrix density, dS/dOmega. Shape ([nw,] nx, ny, 4, 4)
+ Matrix density, dS/dOmega.
+
+ :Type: :any:`Density`
+ :Shape: (nx, ny, [nw,] 4, 4)
"""
if np.asarray(self.omega).ndim == 0:
- return self._get_S(self.omega, self.Phi)
+ r = self._get_S(self.omega, self.Phi)
else:
- return np.array(
+ r = np.array(
[self._get_S(w, P) for w, P in zip(self.omega, self.Phi)], dtype=complex
)
+ return self._density(r)
@property
def J(self):
"""
- Matrix current, dS/dA. Shape ([nw,] nx, ny, 4(direction), 4, 4).
+ Matrix current, dS/dA.
The meaning of the direction index is:
@@ -857,37 +1009,52 @@ class Result:
- UP (1): current exiting cell (x,y) to cell (x,y+1)
- LEFT (2): current entering cell (x,y) from cell (x-1,y)
- DOWN (3): current entering cell (x,y) from cell (x,y-1)
+
+ :Type: :any:`Current`
+ :Shape: (nx, ny, 4(direction), [nw,] 4, 4)
"""
if np.asarray(self.omega).ndim == 0:
- return self._get_J(self.omega, self.Phi)
+ r = self._get_J(self.omega, self.Phi)
else:
- return np.array(
+ r = np.array(
[self._get_J(w, P) for w, P in zip(self.omega, self.Phi)], dtype=complex
)
+ return self._current(r)
@property
def J_c(self):
"""
- Spectral charge current. Shape ([nw,] nx, ny, 4(direction)).
+ Spectral charge current.
+
+ Direction index has same meaning as for :any:`J`.
- Direction index has same meaning as for :ref:`J`.
+ :Type: :any:`Current`
+ :Shape: ([nw,] nx, ny, 4(direction))
"""
t3 = np.diag([1, 1, -1, -1])
- return tr(self.J @ t3)
+ r = tr(self.J.A @ t3)
+ return Current(self, r)
@property
def J_s(self):
"""
- Spectral spin current. Shape ([nw,] nx, ny, 4(direction), 3(spin-direction)).
+ Spectral spin current.
- The current direction index has same meaning as for :ref:`J`.
+ The current direction index has same meaning as for :any:`J`.
The spin direction index means (x, y, z).
+
+ :Type: :any:`Current`
+ :Shape: (nx, ny, 4(direction), [nw,] 3(spin-direction))
"""
- jx = tr(self.J @ np.kron(s0, sx))
- jy = tr(self.J @ np.kron(s0, sy))
- jz = tr(self.J @ np.kron(s0, sz))
- return np.array([jx, jy, jz]).transpose(1, 2, 3, 0)
+ jx = tr(self.J.A @ np.kron(s0, sx))
+ jy = tr(self.J.A @ np.kron(s0, sy))
+ jz = tr(self.J.A @ np.kron(s0, sz))
+ if np.asarray(self.omega).ndim == 0:
+ r = np.array([jx, jy, jz]).transpose(1, 2, 3, 0)
+ else:
+ r = np.array([jx, jy, jz]).transpose(1, 2, 3, 4, 0)
+ return Current(self, r)
class UmfpackILU(LinearOperator):
@@ -1240,10 +1407,10 @@ def _mp_one(args, solver=None, solver_kw=None):
for wx, ax in zip(w, a):
res = solver.solve(omega=wx, **solver_kw)
- r = singlet(solver.Delta) / abs(wx) - singlet(res.F)
+ r = singlet(solver.Delta) / abs(wx) - singlet(res.F.A)
rtot += (2 * np.pi * ax) * r
- Jtot += (-2j * np.pi * ax) * res.J
- Stot += (2 * np.pi * ax) * (res.Q - tau_3)
+ Jtot += (-2j * np.pi * ax) * res.J.A
+ Stot += (2 * np.pi * ax) * (res.Q.A - tau_3)
finally:
_log_solve.setLevel(old_level)
@@ -1404,7 +1571,7 @@ def cpr(
state.Deltas = [solver.Delta.copy()]
state.phis = [0]
state.dss = [0]
- state.Js = [solver.J_tot.copy()]
+ state.Js = [solver.J_tot.A.copy()]
phi = state.phis[-1] + ds / 4
@@ -1417,7 +1584,7 @@ def cpr(
)
state.Deltas.append(solver.Delta.copy())
state.phis.append(float(phi))
- state.Js.append(solver.J_tot.copy())
+ state.Js.append(solver.J_tot.A.copy())
for j in range(len(state.phis), max_points):
if auto_stop and len(state.phis) > 2:
@@ -1469,7 +1636,7 @@ def cpr(
return np.asarray(dr)
constraint_x = np.asarray(phi).ravel()
- Delta, J_tot, cx, success = solver.self_consistency(
+ Delta, J_tot, S_tot, cx, success = solver.self_consistency(
T=T,
T_c0=T_c0,
constraint_x=constraint_x,
@@ -1507,10 +1674,10 @@ def cpr(
state.dss.append(float(np.squeeze(ds_cur)))
state.Deltas.append(Delta.copy())
state.phis.append(float(np.squeeze(phi)))
- state.Js.append(solver.J_tot.copy())
+ state.Js.append(solver.J_tot.A.copy())
t3 = np.diag([1, 1, -1, -1])
- J_avg = np.mean(tr(solver.J_tot[:, :, 0].real @ t3))
+ J_avg = np.mean(tr(solver.J_tot.A[:, :, 0].real @ t3))
_log.info(f"CPR #{j}: phi = {phi}, J = {J_avg}")
if filename is not None:
@@ -1538,7 +1705,7 @@ def interpolate_J(x0, y0, J, x, y, method="bilinear"):
Cell x-coordinates
y0 : array, shape (ny,)
Cell y-coordinates
- J : array, shape (nx, ny, 4, ...)
+ J : array, shape (nx, ny, 4(direction), ...)
Matrix current, defined on links between cells.
x : array
x-coordinate to interpolate J at.