Commit ecedc71f authored by Martin Reinecke's avatar Martin Reinecke

Merge branch 'cosm' into 'NIFTy_5'

Cosm

See merge request ift/nifty-dev!204
parents 1a9b8429 ab3f1c2f
......@@ -29,4 +29,6 @@ add_module_names = False
html_theme = "sphinx_rtd_theme"
html_logo = 'nifty_logo_black.png'
exclude_patterns = ['mod/modules.rst', 'mod/*version.rst']
exclude_patterns = [
'mod/modules.rst', 'mod/nifty5.git_version.rst', 'mod/nifty5.logger.rst'
]
......@@ -14,12 +14,12 @@ Plotting support is added via::
pip3 install --user matplotlib
FFTW support is added via:
FFTW support is added via::
sudo apt-get install libfftw3-dev
pip3 install --user pyfftw
To actually use FFTW in your Nifty calculations, you need to call
To actually use FFTW in your Nifty calculations, you need to call::
nifty5.fft.enable_fftw()
......
......@@ -57,10 +57,10 @@ class MetricGaussianKL(Energy):
Notes
-----
For further details see: Metric Gaussian Variational Inference
(in preparation)
(FIXME in preparation)
"""
def __init__(self, mean, hamiltonian, n_sampels, constants=[],
def __init__(self, mean, hamiltonian, n_samples, constants=[],
point_estimates=None, mirror_samples=False,
_samples=None):
super(MetricGaussianKL, self).__init__(mean)
......@@ -75,7 +75,7 @@ class MetricGaussianKL(Energy):
met = hamiltonian(Linearization.make_partial_var(
mean, point_estimates, True)).metric
_samples = tuple(met.draw_sample(from_inverse=True)
for _ in range(n_sampels))
for _ in range(n_samples))
if mirror_samples:
_samples += tuple(-s for s in _samples)
self._samples = _samples
......
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