| Parameters: |
- data : ndarray (nsamples, ndim)
The samples. This should be a 1- or 2-dimensional array. For a 1-D
array this results in 1-D kernel density plot. For a 2-D array, this
generates a 2-D contour plot.
- ax : matplotlib axis, optional
matplotlib figure axis
- obs : int or tuple, optional (default: 0)
Observables to plot.
- temperature : float, optional (default: 300.0)
Simulation temperature in degrees Kelvin.
- n_samples : int, optional
Number of points to subsample from original data.
- pi : array-like, optional
Equilibrium ensemble weights for each observation.
- bw : {‘scott’ | ‘silverman’ | scalar | pair of scalars }, optional
Name of reference method to determine kernel size, scalar factor, or
scalar for each dimension of the bivariate plot.
- gridsize : int, optional
Number of discrete points in the evaluation grid per dimensional.
- cut : scalar, optional (default: 3)
Draw the estimate to cut * bw from the extreme data points.
- clip : pair of scalars, or pair of pair of scalars, optional
Lower and upper bounds for datapoints used to fit KDE. Can provide a
pair of (low, high) bounds for bivariate plots.
- color : str, optional (default: ‘beryl’)
Color of the univariate KDE curve.
- shade : bool, optional
If True, shade in the area over the KDE curve (or draw with filled
contours when data is bivariate).
- alpha : float, optional (default: 0.5)
Opacity of shaded area.
- cmap : str or matplotlib colormap, optional (default: ‘bone’)
Colormap to use in the filled contour plot.
- vmin : float, optional
The minimum value used in contour plot. If None the minimum value
of the KDE is used.
- vmax : float, optional
The maximum value used in contour plot. If None the median value
of the KDE is used.
- n_levels : int, optional (default: 10)
Number of contour levels to include.
- clabel : bool, optional (default: False)
Adds labels to contours in counter plot.
- clabel_kwargs : dict, optional
Arguments to pass to matplotlib clabel.
- cbar: bool, optional (default: False)
Adds a colorbar that maps the free energy colors
- cbar_kwargs: dict, optional
Arguments to pass to matplotlib cbar
- xlabel : str, optional
x-axis label
- ylabel : str, optional
y-axis label
- labelsize : int, optional (default: 14)
x- and y-label font size
- random_state : integer or numpy.RandomState, optional
The generator used to initialize the centers. If an integer is
given, it fixes the seed. Defaults to the global numpy random
number generator
- return_data : Boolean,optional
Whether or not to return the plotting data
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