def __init__(self,
n_space,
n_past_samples,
n_estimates=0,
distr_cmap='bone',
estimate_colors=None,
*args,
**kwargs):
"""
:param n_space: number of samples in the state space discretization
:param n_past_samples: number of past frames in time to maintain in plot
:param n_estimates: number of estimates to plot. defaults to 0
:param distr_cmap: color map for the likelihood distribution
:param estimate_colors: colors for the different estimates. In the form of
matplotlib color formats
All other parameters will be passed to RealtimePlot constructor
"""
RealtimePlot.__init__(self, *args, **kwargs)
self._n_space = n_space
self._n_past_samples = n_past_samples
self._n_estimates = n_estimates
self._distr_cmap = distr_cmap
self._estimate_colors = estimate_colors
self._setup()
def __init__(self, n_space, n_past_samples, n_estimates=0,
distr_cmap='bone', estimate_colors=None, *args, **kwargs):
"""
:param n_space: number of samples in the state space discretization
:param n_past_samples: number of past frames in time to maintain in plot
:param n_estimates: number of estimates to plot. defaults to 0
:param distr_cmap: color map for the likelihood distribution
:param estimate_colors: colors for the different estimates. In the form of
matplotlib color formats
All other parameters will be passed to RealtimePlot constructor
"""
RealtimePlot.__init__(self, *args, **kwargs)
self._n_space = n_space
self._n_past_samples = n_past_samples
self._n_estimates = n_estimates
self._distr_cmap = distr_cmap
self._estimate_colors = estimate_colors
self._setup()
def __init__(self, elev=None, azim=None, **kwargs):
RealtimePlot.__init__(self, projection='3d', **kwargs)
self._elev_ang = elev
self._azim_ang = azim
self._setup_axis()
def __init__(self, elev=None, azim=None, **kwargs): RealtimePlot.__init__(self, projection='3d', **kwargs) self._elev_ang = elev self._azim_ang = azim self._setup_axis()
