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diff --git a/‎doc/whats_new/v0.20.rst
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diff --git a/‎sklearn/decomposition/dict_learning.py
Lines changed: 24 additions & 0 deletions b/‎sklearn/decomposition/dict_learning.py
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@@ -142,6 +142,10 @@ Decomposition, manifold learning and clustering
   sample weights via new parameter ``sample_weight`` in ``fit`` function.
   :issue:`10933` by :user:`Johannes Hansen <jnhansen>`.
 
+- :mod:`dict_learning` functions and models now support positivity constraints.
+  This applies to the dictionary and sparse code.
+  :issue:`6374` by :user:`John Kirkham <jakirkham>`.
+
 Metrics
 
 - Partial AUC is available via ``max_fpr`` parameter in
 
@@ -83,6 +83,8 @@ def _sparse_encode(X, dictionary, gram, cov=None, algorithm='lasso_lars',
     positive: boolean
         Whether to enforce a positivity constraint on the sparse code.
 
+        .. versionadded:: 0.20
+
     Returns
     -------
     code : array of shape (n_components, n_features)
@@ -256,6 +258,8 @@ def sparse_encode(X, dictionary, gram=None, cov=None, algorithm='lasso_lars',
     positive : boolean, optional
         Whether to enforce positivity when finding the encoding.
 
+        .. versionadded:: 0.20
+
     Returns
     -------
     code : array of shape (n_samples, n_components)
@@ -358,6 +362,8 @@ def _update_dict(dictionary, Y, code, verbose=False, return_r2=False,
     positive : boolean, optional
         Whether to enforce positivity when finding the dictionary.
 
+        .. versionadded:: 0.20
+
     Returns
     -------
     dictionary : array of shape (n_features, n_components)
@@ -478,9 +484,13 @@ def dict_learning(X, n_components, alpha, max_iter=100, tol=1e-8,
     positive_dict : bool
         Whether to enforce positivity when finding the dictionary.
 
+        .. versionadded:: 0.20
+
     positive_code : bool
         Whether to enforce positivity when finding the code.
 
+        .. versionadded:: 0.20
+
     Returns
     -------
     code : array of shape (n_samples, n_components)
@@ -684,9 +694,13 @@ def dict_learning_online(X, n_components=2, alpha=1, n_iter=100,
     positive_dict : bool
         Whether to enforce positivity when finding the dictionary.
 
+        .. versionadded:: 0.20
+
     positive_code : bool
         Whether to enforce positivity when finding the code.
 
+        .. versionadded:: 0.20
+
     Returns
     -------
     code : array of shape (n_samples, n_components),
@@ -942,6 +956,8 @@ class SparseCoder(BaseEstimator, SparseCodingMixin):
     positive_code : bool
         Whether to enforce positivity when finding the code.
 
+        .. versionadded:: 0.20
+
     Attributes
     ----------
     components_ : array, [n_components, n_features]
@@ -1080,9 +1096,13 @@ class DictionaryLearning(BaseEstimator, SparseCodingMixin):
     positive_code : bool
         Whether to enforce positivity when finding the code.
 
+        .. versionadded:: 0.20
+
     positive_dict : bool
         Whether to enforce positivity when finding the dictionary
 
+        .. versionadded:: 0.20
+
     Attributes
     ----------
     components_ : array, [n_components, n_features]
@@ -1256,9 +1276,13 @@ class MiniBatchDictionaryLearning(BaseEstimator, SparseCodingMixin):
     positive_code : bool
         Whether to enforce positivity when finding the code.
 
+        .. versionadded:: 0.20
+
     positive_dict : bool
         Whether to enforce positivity when finding the dictionary.
 
+        .. versionadded:: 0.20
+
     Attributes
     ----------
     components_ : array, [n_components, n_features]