Fix issues with full cov

metastable_projections/misc/distTools.py

@@ -27,23 +27,8 @@ def get_mean_and_chol(p: AnyDistribution, expand=False):
 
 
 def get_mean_and_sqrt(p: UniversalGaussianDistribution, expand=False):
-    mean, chol = get_mean_and_chol(p, expand=False)
+    mean, chol = get_mean_and_chol(p, expand=expand)
-    if not hasattr(p, 'cov_sqrt'):
+    return mean, chol
-        if len(p.distribution.scale.shape)==2: # In the factorized case, chol = matSqrt
-            sqrt_cov = p.distribution.scale
-        else:
-            raise Exception(
-                'Distribution was not induced from sqrt. On-demand calculation is not supported.')
-    else:
-        sqrt_cov = p.cov_sqrt
-    if mean.shape[0] != sqrt_cov.shape[0]:
-        shape = list(sqrt_cov.shape)
-        shape[0] = mean.shape[0]
-        shape = tuple(shape)
-        sqrt_cov = sqrt_cov.expand(shape)
-    if expand and len(sqrt_cov.shape) <= 2:
-        sqrt_cov = th.diag_embed(sqrt_cov)
-    return mean, sqrt_cov
 
 
 def get_cov(p: AnyDistribution):
@@ -111,29 +96,3 @@ def new_dist_like(orig_p: AnyDistribution, mean: th.Tensor, chol: th.Tensor):
         return p_out
     else:
         raise Exception('Dist-Type not implemented')
-
-
-def new_dist_like_from_sqrt(orig_p: AnyDistribution, mean: th.Tensor, cov_sqrt: th.Tensor):
-    chol = _sqrt_to_chol(cov_sqrt, only_diag=has_diag_cov(orig_p))
-
-    new = new_dist_like(orig_p, mean, chol)
-
-    new.cov_sqrt = cov_sqrt
-    if hasattr(new, 'distribution'):
-        new.distribution.cov_sqrt = cov_sqrt
-
-    return new
-
-
-def _sqrt_to_chol(cov_sqrt, only_diag=False):
-    if only_diag:
-        return cov_sqrt
-    cov = th.bmm(cov_sqrt.mT, cov_sqrt)
-    cov += th.eye(cov.shape[-1]).expand(cov.shape)*(1e-6)
-
-    chol = th.linalg.cholesky(cov)
-
-    #if only_diag:
-    #    chol = th.diagonal(chol, dim1=-2, dim2=-1)
-
-    return chol