diff --git a/docs/pyerrors/obs.html b/docs/pyerrors/obs.html
index 47c84625..e301d6fe 100644
--- a/docs/pyerrors/obs.html
+++ b/docs/pyerrors/obs.html
@@ -485,7 +485,7 @@
278
279 def _compute_drho(i):
280 tmp = (self.e_rho[e_name][i + 1:w_max]
- 281 + np.concatenate([self.e_rho[e_name][i - 1:None if i - w_max // 2 <= 0 else 2 * (i - w_max // 2):-1],
+ 281 + np.concatenate([self.e_rho[e_name][i - 1:None if i - w_max // 2 <= 0 else (2 * i - (2 * w_max) // 2):-1],
282 self.e_rho[e_name][1:max(1, w_max - 2 * i)]])
283 - 2 * self.e_rho[e_name][i] * self.e_rho[e_name][1:w_max - i])
284 self.e_drho[e_name][i] = np.sqrt(np.sum(tmp ** 2) / e_N)
@@ -2133,7 +2133,7 @@
279
280 def _compute_drho(i):
281 tmp = (self.e_rho[e_name][i + 1:w_max]
-282 + np.concatenate([self.e_rho[e_name][i - 1:None if i - w_max // 2 <= 0 else 2 * (i - w_max // 2):-1],
+282 + np.concatenate([self.e_rho[e_name][i - 1:None if i - w_max // 2 <= 0 else (2 * i - (2 * w_max) // 2):-1],
283 self.e_rho[e_name][1:max(1, w_max - 2 * i)]])
284 - 2 * self.e_rho[e_name][i] * self.e_rho[e_name][1:w_max - i])
285 self.e_drho[e_name][i] = np.sqrt(np.sum(tmp ** 2) / e_N)
@@ -2981,7 +2981,7 @@ list of ranges or lists on which the samples are defined
279
280 def _compute_drho(i):
281 tmp = (self.e_rho[e_name][i + 1:w_max]
-282 + np.concatenate([self.e_rho[e_name][i - 1:None if i - w_max // 2 <= 0 else 2 * (i - w_max // 2):-1],
+282 + np.concatenate([self.e_rho[e_name][i - 1:None if i - w_max // 2 <= 0 else (2 * i - (2 * w_max) // 2):-1],
283 self.e_rho[e_name][1:max(1, w_max - 2 * i)]])
284 - 2 * self.e_rho[e_name][i] * self.e_rho[e_name][1:w_max - i])
285 self.e_drho[e_name][i] = np.sqrt(np.sum(tmp ** 2) / e_N)
@@ -3184,7 +3184,7 @@ of the autocorrelation function (default True)
279
280 def _compute_drho(i):
281 tmp = (self.e_rho[e_name][i + 1:w_max]
-282 + np.concatenate([self.e_rho[e_name][i - 1:None if i - w_max // 2 <= 0 else 2 * (i - w_max // 2):-1],
+282 + np.concatenate([self.e_rho[e_name][i - 1:None if i - w_max // 2 <= 0 else (2 * i - (2 * w_max) // 2):-1],
283 self.e_rho[e_name][1:max(1, w_max - 2 * i)]])
284 - 2 * self.e_rho[e_name][i] * self.e_rho[e_name][1:w_max - i])
285 self.e_drho[e_name][i] = np.sqrt(np.sum(tmp ** 2) / e_N)