50 default to use positive tausfalse

setup.py

@@ -6,7 +6,7 @@
 
 class CMakeBuild(build_ext):
     def run(self):
-        # サブモジュールのビルド
+        # Build submodule
         build_dir = os.path.abspath(self.build_temp)
         os.makedirs(build_dir, exist_ok=True)
 
@@ -19,7 +19,7 @@ def run(self):
 
         subprocess.check_call(['cmake', '--build', '.', '--config', 'Release'], cwd=build_dir)
 
-# sdistとwheelで異なるpackage_dataを設定
+# Set package_data differently for sdist and wheel
 if 'bdist_wheel' in sys.argv:
     package_data = {
         'pylibsparseir': ['libsparseir*.dylib', 'libsparseir*.so', 'libsparseir*.dll'],

src/sparse_ir/augment.py

@@ -254,7 +254,7 @@ def __init__(self, beta):
         self._beta = beta
 
     def __call__(self, tau):
-        tau = _util.check_range(tau, 0, self._beta)
+        tau = _util.check_range(tau, -self._beta, self._beta)
         return np.broadcast_to(1 / np.sqrt(self._beta), tau.shape)
 
     def deriv(self, n=1):
@@ -282,7 +282,7 @@ def __init__(self, beta):
         self._norm = np.sqrt(3/beta)
 
     def __call__(self, tau):
-        tau = _util.check_range(tau, 0, self._beta)
+        tau = _util.check_range(tau, -self._beta, self._beta)
         x = 2/self._beta * tau - 1
         return self._norm * x
 
@@ -314,7 +314,7 @@ def __init__(self, beta):
         self._beta = beta
 
     def __call__(self, tau):
-        tau = _util.check_range(tau, 0, self._beta)
+        tau = _util.check_range(tau, -self._beta, self._beta)
         return np.broadcast_to(np.nan, tau.shape)
 
     def deriv(self, n=1):

src/sparse_ir/basis_set.py

@@ -32,7 +32,7 @@ class FiniteTempBasisSet:
         Sparse sampling for Matsubara frequency & boson
     """
 
-    def __init__(self, beta, wmax, eps=None, sve_result=None):
+    def __init__(self, beta, wmax, eps=None, sve_result=None, use_positive_taus=False):
         """
         Create basis sets for fermion and boson and associated sampling objects.
 
@@ -50,6 +50,12 @@ def __init__(self, beta, wmax, eps=None, sve_result=None):
         sve_result : SVEResult, optional
             Pre-computed SVE result to use for basis construction.
             If not provided, SVE will be computed internally.
+        use_positive_taus : bool, optional
+            If `use_positive_taus=False`, the sampling points are within
+            the range [-β/2, β/2] and the distribution is symmetric.
+            If `use_positive_taus=True`, the sampling points are
+            folded to the positive tau domain [0, β), which is
+            the default behavior of sparseir 1.x.x.
         """
         if sve_result is None:
             # Create bases by sve of the logistic kernel
@@ -64,8 +70,8 @@ def __init__(self, beta, wmax, eps=None, sve_result=None):
             )
 
         # Tau sampling
-        self.smpl_tau_f = TauSampling(self.basis_f)
-        self.smpl_tau_b = TauSampling(self.basis_b)
+        self.smpl_tau_f = TauSampling(self.basis_f, use_positive_taus=use_positive_taus)
+        self.smpl_tau_b = TauSampling(self.basis_b, use_positive_taus=use_positive_taus)
 
         # Matsubara sampling
         self.smpl_wn_f = MatsubaraSampling(self.basis_f)

src/sparse_ir/sampling.py

@@ -11,7 +11,7 @@
 class TauSampling:
     """Sparse sampling in imaginary time."""
 
-    def __init__(self, basis, sampling_points=None, use_positive_taus=True):
+    def __init__(self, basis, sampling_points=None, use_positive_taus=False):
         """
         Initialize tau sampling.
 
@@ -22,7 +22,11 @@ def __init__(self, basis, sampling_points=None, use_positive_taus=True):
         sampling_points : array_like, optional
             Tau sampling points. If None, use default.
         use_positive_taus : bool, optional
-            If `use_positive_taus=True`, the sampling points are folded to the positive tau domain [0, β).
+            If `use_positive_taus=False`, the sampling points are within
+            the range [-β/2, β/2] and the distribution is symmetric.
+            If `use_positive_taus=True`, the sampling points are
+            folded to the positive tau domain [0, β), which is
+            the default behavior of sparseir 1.x.x.
         """
         self.basis = basis
 

tutorials/flex_py.py

@@ -69,6 +69,8 @@ def __init__(self,IR_basis_set,nk1,nk2):
         self.iwn_f = 1j * self.IR_basis_set.wn_f * np.pi * T
         self.iwn_f_ = np.tensordot(self.iwn_f, np.ones(nk), axes=0)
 
+        print(self.IR_basis_set.smpl_tau_f.sampling_points)
+
         # ek mesh
         self.ek_ = np.tensordot(np.ones(len(self.iwn_f)), self.ek, axes=0)
 
@@ -219,7 +221,7 @@ def grit_calc(self):
 
     def ckio_calc(self):
         """ Calculate irreducible susciptibility chi0(iv,q) """
-        ckio = self.grit * self.grit[::-1, :]
+        ckio = self.grit * (self.grit[::-1, :]) # changed for libsparseir
 
         # Fourier transform
         ckio = self.mesh.r_to_k(ckio)
@@ -273,7 +275,7 @@ def mu_calc(self):
 
 # %%
 # initialize calculation
-IR_basis_set = sparse_ir.FiniteTempBasisSet(beta, wmax, eps=IR_tol)
+IR_basis_set = sparse_ir.FiniteTempBasisSet(beta, wmax, eps=IR_tol, use_positive_taus=True)
 mesh = Mesh(IR_basis_set, nk1, nk2)
 solver = FLEXSolver(mesh, U, n, sigma_init=0, sfc_tol=sfc_tol, maxiter=maxiter, U_maxiter=U_maxiter, mix=mix)
 
@@ -428,7 +430,6 @@ def frit_calc(self):
 plt.colorbar()
 plt.show()
 
-# %%
 # %%%%%%%%%%%%%%% Parameter settings
 print('Initialization...')
 # system parameters