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from __future__ import with_statement
from ..dream import views as dream_views
from ..dream import stats as dream_stats
from ..dream import varplot as dream_varplot
from .. import errplot
from .plot_view import PlotView
class UncertaintyView(PlotView):
title = "Uncertainty"
def plot(self):
if not self.plot_state:
return
history, stats = self.plot_state
with self.pylab_interface as pylab:
pylab.clf()
dream_varplot.plot_vars(history.draw(), stats)
pylab.draw()
def update(self, state):
self.plot_state = state
self.plot()
def fit_progress(self, problem, uncertainty_state, stats):
if problem != self.model:
return
self.update((uncertainty_state, stats))
class CorrelationView(PlotView):
title = "Correlations"
def plot(self):
if not self.plot_state:
return
# suppress correlation plot if too many variables
if self.plot_state.Nvar > 15:
return
history = self.plot_state
with self.pylab_interface as pylab:
pylab.clf()
dream_views.plot_corrmatrix(history.draw())
pylab.draw()
def update(self, state):
self.plot_state = state
self.plot()
def fit_progress(self, problem, uncertainty_state):
if problem != self.model:
return
self.update(uncertainty_state)
class TraceView(PlotView):
title = "Parameter Trace"
def plot(self):
if not self.plot_state:
return
history = self.plot_state
with self.pylab_interface as pylab:
pylab.clf()
dream_views.plot_trace(history)
pylab.draw()
def update(self, state):
self.plot_state = state
self.plot()
def fit_progress(self, problem, uncertainty_state):
if problem != self.model:
return
self.plot_state = uncertainty_state
self.plot()
class ModelErrorView(PlotView):
title = "Model Uncertainty"
def plot(self):
if not self.plot_state:
return
with self.pylab_interface as pylab:
pylab.clf()
# Won't get here if plot_state is None
errplot.show_errors(self.plot_state)
pylab.draw()
def update(self, problem, state):
# TODO: Should happen in a separate process
self.plot_state = errplot.calc_errors_from_state(problem, state)
self.plot()
def fit_progress(self, problem, uncertainty_state):
if problem != self.model:
return
self.update(problem, uncertainty_state)
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