init

forecasting_model/io/plotting.py

@@ -0,0 +1,75 @@
+import matplotlib.pyplot as plt
+import seaborn as sns
+import numpy as np
+from typing import Optional
+import logging
+
+logger = logging.getLogger(__name__)
+
+def setup_plot_style() -> None:
+    """
+    Set up consistent plotting style.
+    """
+    # TODO: Implement plot style configuration
+    pass
+
+def save_plot(fig: plt.Figure, filename: str) -> None:
+    """
+    Save plot to file with proper error handling.
+    """
+    # TODO: Implement plot saving with error handling
+    pass
+
+def create_time_series_plot(
+    x: np.ndarray,
+    y_true: np.ndarray,
+    y_pred: np.ndarray,
+    title: str,
+    xlabel: str,
+    ylabel: str,
+    max_points: Optional[int] = None
+) -> plt.Figure:
+    """
+    Create a time series plot with actual vs predicted values.
+    """
+    # TODO: Implement time series plot creation
+    pass
+
+def create_scatter_plot(
+    y_true: np.ndarray,
+    y_pred: np.ndarray,
+    title: str,
+    xlabel: str,
+    ylabel: str
+) -> plt.Figure:
+    """
+    Create a scatter plot of actual vs predicted values.
+    """
+    # TODO: Implement scatter plot creation
+    pass
+
+def create_residuals_plot(
+    x: np.ndarray,
+    residuals: np.ndarray,
+    title: str,
+    xlabel: str,
+    ylabel: str,
+    max_points: Optional[int] = None
+) -> plt.Figure:
+    """
+    Create a plot of residuals over time.
+    """
+    # TODO: Implement residuals plot creation
+    pass
+
+def create_residuals_distribution_plot(
+    residuals: np.ndarray,
+    title: str,
+    xlabel: str,
+    ylabel: str
+) -> plt.Figure:
+    """
+    Create a distribution plot of residuals.
+    """
+    # TODO: Implement residuals distribution plot creation
+    pass