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fixed scaling in 'add_mean' plotting option & added notebook to play around with new plotting options
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docs/source/notebooks/mmm/mmm_plotting_options.ipynb

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pymc_marketing/mmm/base.py

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@@ -434,11 +434,6 @@ def plot_posterior_predictive(
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dim=["chain", "draw"]
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)
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if original_scale:
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mean_prediction = transform_1d_array(
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self.get_target_transformer().inverse_transform, mean_prediction
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)
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ax.plot(
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np.asarray(posterior_predictive_data.date),
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mean_prediction,

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