From 6e847a5ca0916bab97348f04657d22c303ae6131 Mon Sep 17 00:00:00 2001 From: Nathanael Bosch Date: Tue, 18 Aug 2020 18:10:18 +0200 Subject: [PATCH] Fixed sphinx warnings --- .../filtsmooth/gaussfiltsmooth/unscentedtransform.py | 2 +- .../filtsmooth/statespace/continuous/linearsdemodel.py | 6 +++--- 2 files changed, 4 insertions(+), 4 deletions(-) diff --git a/src/probnum/filtsmooth/gaussfiltsmooth/unscentedtransform.py b/src/probnum/filtsmooth/gaussfiltsmooth/unscentedtransform.py index a1b9b60bb..baa85e741 100644 --- a/src/probnum/filtsmooth/gaussfiltsmooth/unscentedtransform.py +++ b/src/probnum/filtsmooth/gaussfiltsmooth/unscentedtransform.py @@ -95,7 +95,7 @@ def propagate(self, time, sigmapts, modelfct): Time :math:`t` which is passed on to the modelfunction. sigmapts : np.ndarray, shape=(2 N+1, N) Sigma points (N is the spatial dimension of the dynamic model) - modelfct : callable, signature=(t, x, **kwargs) + modelfct : callable, signature=(t, x, \\**kwargs) Function through which to propagate Returns diff --git a/src/probnum/filtsmooth/statespace/continuous/linearsdemodel.py b/src/probnum/filtsmooth/statespace/continuous/linearsdemodel.py index dee581c99..71c89016d 100644 --- a/src/probnum/filtsmooth/statespace/continuous/linearsdemodel.py +++ b/src/probnum/filtsmooth/statespace/continuous/linearsdemodel.py @@ -25,15 +25,15 @@ class LinearSDEModel(continuousmodel.ContinuousModel): Parameters ---------- - driftmatrixfct : callable, signature=(t, **kwargs) + driftmatrixfct : callable, signature=(t, \\**kwargs) This is F = F(t). The evaluations of this function are called the drift(matrix) of the SDE. Returns np.ndarray with shape=(n, n) - forcfct : callable, signature=(t, **kwargs) + forcfct : callable, signature=(t, \\**kwargs) This is u = u(t). Evaluations of this function are called the force(vector) of the SDE. Returns np.ndarray with shape=(n,) - dispmatrixfct : callable, signature=(t, **kwargs) + dispmatrixfct : callable, signature=(t, \\**kwargs) This is L = L(t). Evaluations of this function are called the dispersion(matrix) of the SDE. Returns np.ndarray with shape=(n, s)