adding small fixes, whats_new, and reference

doc/python_reference.rst

@@ -682,6 +682,10 @@ Inverse Solutions
    lcmv
    lcmv_epochs
    lcmv_raw
+   make_lcmv
+   apply_lcmv
+   apply_lcmv_epochs
+   apply_lcmv_raw
    dics
    dics_epochs
    dics_source_power

doc/whats_new.rst

@@ -126,6 +126,7 @@ BUG
 
 API
 ~~~
+    - Add :func:`mne.beamformer.make_lcmv` and :func:`mne.beamformer.apply_lcmv`, :func:`mne.beamformer.apply_lcmv_epochs`, and :func:`mne.beamformer.apply_lcmv_raw` to enable the separate computation and application of LCMV beamformer weights by `Britta Westner'_, `Alex Gramfort`_, and `Denis Engemann`_.
 
     - Add ``weight_norm'' parameter to enable both unit-noise-gain beamformer and neural activity index (weight normalization) and make whitening optional by allowing ``noise_cov=None'' in :func:`mne.beamformer.lcmv`, :func:`mne.beamformer.lcmv_epochs`, and :func:`mne.beamformer.lcmv_raw`, by `Britta Westner'_, `Alex Gramfort`_, and `Denis Engemann`_.
 

mne/beamformer/_lcmv.py

@@ -4,10 +4,10 @@
 #          Roman Goj <[email protected]>
 #
 # License: BSD (3-clause)
+from copy import deepcopy
 
 import numpy as np
 from scipy import linalg
-from copy import deepcopy
 
 from ..io.constants import FIFF
 from ..io.proj import make_projector
@@ -429,9 +429,6 @@ def apply_lcmv(evoked, filters, max_ori_out='abs', verbose=None):
     Apply Linearly Constrained Minimum Variance (LCMV) beamformer weights
     on evoked data.
 
-    .. note:: This implementation has not been heavily tested so please
-              report any issue or suggestions.
-
     Parameters
     ----------
     evoked : Evoked
@@ -482,9 +479,6 @@ def apply_lcmv_epochs(epochs, filters, max_ori_out='abs',
     Apply Linearly Constrained Minimum Variance (LCMV) beamformer weights
     on single trial data.
 
-    .. note:: This implementation has not been heavily tested so please
-              report any issue or suggestions.
-
     Parameters
     ----------
     epochs : Epochs
@@ -596,8 +590,6 @@ def lcmv(evoked, forward, noise_cov=None, data_cov=None, reg=0.05, label=None,
 
     Compute Linearly Constrained Minimum Variance (LCMV) beamformer
     on evoked data.
-    .. note:: This implementation has not been heavily tested so please
-              report any issue or suggestions.
 
     Parameters
     ----------
@@ -687,8 +679,6 @@ def lcmv_epochs(epochs, forward, noise_cov, data_cov, reg=0.05, label=None,
 
     Compute Linearly Constrained Minimum Variance (LCMV) beamformer
     on single trial data.
-    .. note:: This implementation has not been heavily tested so please
-              report any issue or suggestions.
 
     Parameters
     ----------

mne/beamformer/tests/test_lcmv.py

@@ -1,11 +1,11 @@
 import os.path as op
+from copy import deepcopy
 
 from nose.tools import assert_true, assert_raises
 import numpy as np
 from numpy.testing import (assert_array_almost_equal, assert_array_equal,
                            assert_almost_equal)
 import warnings
-from copy import deepcopy
 
 import mne
 from mne import compute_covariance