visualizer interface

python/src/robyn/visualization/allocator_visualizer.py

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+from typing import Dict, Any
+import matplotlib.pyplot as plt
+from .base_visualizer import BaseVisualizer
+
+class AllocatorVisualizer(BaseVisualizer):
+    def __init__(self, allocator_data: Dict[str, Any]):
+        super().__init__()
+        self.allocator_data = allocator_data
+
+    def plot_allocator(self) -> plt.Figure:
+        """
+        Plot allocator's output.
+
+        Returns:
+            plt.Figure: The generated figure.
+        """
+        pass

python/src/robyn/visualization/base_visualizer.py

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+import matplotlib.pyplot as plt
+
+class BaseVisualizer:
+    def __init__(self):
+        pass
+
+    def _setup_plot(self):
+        # Common plot setup logic
+        pass

python/src/robyn/visualization/input_visualizer.py

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+from typing import Dict, Any
+import matplotlib.pyplot as plt
+from .base_visualizer import BaseVisualizer
+
+class InputVisualizer(BaseVisualizer):
+    def __init__(self, input_data: Dict[str, Any]):
+        super().__init__()
+        self.input_data = input_data
+
+    def plot_adstock(self) -> plt.Figure:
+        """
+        Create example plots for adstock hyperparameters.
+
+        Returns:
+            plt.Figure: The generated figure.
+        """
+        fig, ax = plt.subplots()
+        # Add plotting logic here
+        return fig
+
+    def plot_saturation(self) -> plt.Figure:
+        """
+        Create example plots for saturation hyperparameters.
+
+        Returns:
+            plt.Figure: The generated figure.
+        """
+        fig, ax = plt.subplots()
+        # Add plotting logic here
+        return fig
+
+    def plot_spend_exposure_fit(self) -> Dict[str, plt.Figure]:
+        """
+        Check spend exposure fit if available.
+
+        Returns:
+            Dict[str, plt.Figure]: A dictionary of generated figures.
+        """
+        figures = {}
+        # Add plotting logic here
+        return figures

python/src/robyn/visualization/model_visualizer.py

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+from typing import Dict, Any
+import matplotlib.pyplot as plt
+from .base_visualizer import BaseVisualizer
+
+class ModelVisualizer(BaseVisualizer):
+    def __init__(self, model_data: Dict[str, Any]):
+        super().__init__()
+        self.model_data = model_data
+
+    def plot_moo_distribution(self) -> plt.Figure:
+        """
+        Plot MOO (multi-objective optimization) distribution.
+
+        Returns:
+            plt.Figure: The generated figure.
+        """
+        pass
+
+    def plot_moo_cloud(self) -> plt.Figure:
+        """
+        Plot MOO (multi-objective optimization) cloud.
+
+        Returns:
+            plt.Figure: The generated figure.
+        """
+        pass
+
+    def plot_ts_validation(self) -> plt.Figure:
+        """
+        Plot time-series validation.
+
+        Returns:
+            plt.Figure: The generated figure.
+        """
+        pass
+
+    def plot_onepager(self, input_collect: Dict[str, Any], output_collect: Dict[str, Any], select_model: str) -> Dict[str, plt.Figure]:
+        """
+        Generate one-pager plots for a selected model.
+
+        Args:
+            input_collect (Dict[str, Any]): The input collection data.
+            output_collect (Dict[str, Any]): The output collection data.
+            select_model (str): The selected model identifier.
+
+        Returns:
+            Dict[str, plt.Figure]: A dictionary of generated figures.
+        """
+        pass

python/src/robyn/visualization/response_visualizer.py

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+from typing import Dict, Any
+import matplotlib.pyplot as plt
+from .base_visualizer import BaseVisualizer
+
+class ResponseVisualizer(BaseVisualizer):
+    def __init__(self, response_data: Dict[str, Any]):
+        super().__init__()
+        self.response_data = response_data
+
+    def plot_response(self) -> plt.Figure:
+        """
+        Plot response curves.
+
+        Returns:
+            plt.Figure: The generated figure.
+        """
+        pass
+
+    def plot_marginal_response(self) -> plt.Figure:
+        """
+        Plot marginal response curves.
+
+        Returns:
+            plt.Figure: The generated figure.
+        """
+        pass

python/src/robyn/visualization/robyn_visualizer.py

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+from typing import Dict, Any
+import matplotlib.pyplot as plt
+from .input_visualizer import InputVisualizer
+from .model_visualizer import ModelVisualizer
+from .allocator_visualizer import AllocatorVisualizer
+from .response_visualizer import ResponseVisualizer
+
+class RobynVisualizer:
+    def __init__(self):
+        self.input_visualizer = None
+        self.model_visualizer = None
+        self.allocator_visualizer = None
+        self.response_visualizer = None
+
+    def set_input_data(self, input_data: Dict[str, Any]):
+        self.input_visualizer = InputVisualizer(input_data)
+
+    def set_model_data(self, model_data: Dict[str, Any]):
+        self.model_visualizer = ModelVisualizer(model_data)
+
+    def set_allocator_data(self, allocator_data: Dict[str, Any]):
+        self.allocator_visualizer = AllocatorVisualizer(allocator_data)
+
+    def set_response_data(self, response_data: Dict[str, Any]):
+        self.response_visualizer = ResponseVisualizer(response_data)
+
+    def plot_adstock(self) -> plt.Figure:
+        return self.input_visualizer.plot_adstock()
+
+    def plot_saturation(self) -> plt.Figure:
+        return self.input_visualizer.plot_saturation()
+
+    def plot_moo_distribution(self) -> plt.Figure:
+        return self.model_visualizer.plot_moo_distribution()
+
+    def plot_moo_cloud(self) -> plt.Figure:
+        return self.model_visualizer.plot_moo_cloud()
+
+    def plot_ts_validation(self) -> plt.Figure:
+        return self.model_visualizer.plot_ts_validation()
+
+    def plot_onepager(self, input_collect: Dict[str, Any], output_collect: Dict[str, Any], select_model: str) -> Dict[str, plt.Figure]:
+        return self.model_visualizer.plot_onepager(input_collect, output_collect, select_model)
+
+    def plot_allocator(self) -> plt.Figure:
+        return self.allocator_visualizer.plot_allocator()
+
+    def plot_response(self) -> plt.Figure:
+        return self.response_visualizer.plot_response()
+
+    def plot_marginal_response(self) -> plt.Figure:
+        return self.response_visualizer.plot_marginal_response()