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plotting with uncertain inputs
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1 changed files with 11 additions and 8 deletions
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@ -56,10 +56,13 @@ def plot_fit(model, plot_limits=None, which_data_rows='all',
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if ax is None:
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if ax is None:
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fig = pb.figure(num=fignum)
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fig = pb.figure(num=fignum)
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ax = fig.add_subplot(111)
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ax = fig.add_subplot(111)
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X, Y = param_to_array(model.X, model.Y)
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if hasattr(model, 'has_uncertain_inputs') and model.has_uncertain_inputs():
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if hasattr(model, 'has_uncertain_inputs') and model.has_uncertain_inputs(): X_variance = model.X_variance
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X = model.X.mean
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X_variance = param_to_array(model.X.variance)
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else:
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X = model.X
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X, Y = param_to_array(X, model.Y)
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if hasattr(model, 'Z'): Z = param_to_array(model.Z)
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if hasattr(model, 'Z'): Z = param_to_array(model.Z)
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#work out what the inputs are for plotting (1D or 2D)
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#work out what the inputs are for plotting (1D or 2D)
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@ -98,10 +101,10 @@ def plot_fit(model, plot_limits=None, which_data_rows='all',
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#add error bars for uncertain (if input uncertainty is being modelled)
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#add error bars for uncertain (if input uncertainty is being modelled)
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#if hasattr(model,"has_uncertain_inputs") and model.has_uncertain_inputs():
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if hasattr(model,"has_uncertain_inputs") and model.has_uncertain_inputs():
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# ax.errorbar(X[which_data_rows, free_dims].flatten(), Y[which_data_rows, which_data_ycols].flatten(),
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ax.errorbar(X[which_data_rows, free_dims].flatten(), Y[which_data_rows, which_data_ycols].flatten(),
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# xerr=2 * np.sqrt(X_variance[which_data_rows, free_dims].flatten()),
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xerr=2 * np.sqrt(X_variance[which_data_rows, free_dims].flatten()),
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# ecolor='k', fmt=None, elinewidth=.5, alpha=.5)
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ecolor='k', fmt=None, elinewidth=.5, alpha=.5)
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#set the limits of the plot to some sensible values
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#set the limits of the plot to some sensible values
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