Documentation

usadelndsoc/matsubara.py

@@ -63,11 +63,11 @@ def _gauss_series_weights(n):
     # bessel_poly_yn = lambda n, x: np.sqrt(2/(np.pi*x)) * np.exp(1/x) * special.kv(n+0.5, 1/x)
 
     # Recurrence formula from [1]
-    a = 2 * np.pi ** 2 / (4 * j + 1) / (4 * j + 5)
-    a[0] = np.pi ** 2 / 15
-    sqrt_b = np.pi ** 2 / np.sqrt((4 * j1 - 1) * (4 * j1 + 3)) / (4 * j1 + 1)
+    a = 2 * np.pi**2 / (4 * j + 1) / (4 * j + 5)
+    a[0] = np.pi**2 / 15
+    sqrt_b = np.pi**2 / np.sqrt((4 * j1 - 1) * (4 * j1 + 3)) / (4 * j1 + 1)
 
-    m0 = pi ** 2 / 6  # = sum_{k=1}^oo 1/k^2
+    m0 = pi**2 / 6  # = sum_{k=1}^oo 1/k^2
 
     # Compute eigenvalues and first elements of eigenvectors
     #
@@ -98,7 +98,7 @@ def _gauss_series_weights(n):
     # Then find eigenvectors, one by one
 
     # Convert back to unweighted sum (z = 1/x^2)
-    w = m0 * w ** 2 / z
+    w = m0 * w**2 / z
     x = z ** (-0.5)
 
     # Swap order
@@ -147,7 +147,7 @@ def get_matsubara_sum(T, E_typical=1.0, max_ne=2000, steps=1):
     Examples
     --------
     >>> import numpy as np
-    >>> from nfiscomp.matsubara import get_matsubara_sum
+    >>> from usadelndsoc.matsubara import get_matsubara_sum
     >>> w, a = get_matsubara_sum(T=1, E_typical=1)
     >>> n = w / (2*np.pi) + 0.5; n
     array([-55.01190294, -17.89542335, -10.6225115 ,  -7.63686822,
@@ -189,7 +189,7 @@ def get_matsubara_sum(T, E_typical=1.0, max_ne=2000, steps=1):
 
     E_max = 100 * abs(E_typical)
     try:
-        ne = 5 + int(np.sqrt(4 * E_max / (pi ** 2 * abs(T))))
+        ne = 5 + int(np.sqrt(4 * E_max / (pi**2 * abs(T))))
         k, rem = divmod(ne, steps)
         if rem != 0:
             k += 1