whenxuan: update the wiener filter for simulate

s2generator/__init__.py

@@ -1,6 +1,6 @@
 # -*- coding: utf-8 -*-
 
-__version__ = "0.0.6"
+__version__ = "0.0.7"
 
 __all__ = [
     "Node",

s2generator/simulator/wiener_filter.py

@@ -178,9 +178,6 @@ def transform(
             # New sequence = White noise * Wiener filter (convolution)
             simulated_series[i, :] = self.invoke(white_noise=white_noise[i, :])
 
-        # Remove edge effects after filtering (first filter_order points)
-        simulated_series = simulated_series[:, self.filter_order :]
-
         # If normalization was performed previously,
         # denormalization is now needed to maintain the same mean and variance as the original sequence.
         if self.revin:

s2generator/utils/__init__.py

@@ -39,6 +39,7 @@
     "exponential_smoothing",
     "smooth_show_info",
     "MovingDecomp",
+    "plot_time_series",
     "plot_series",
     "plot_symbol",
     "plot_shapiro_wilk",
@@ -102,6 +103,7 @@
 
 # The Shapiro-Wilk test for normality of the residuals
 from .visualization import (
+    plot_time_series,
     plot_series,
     plot_symbol,
     plot_shapiro_wilk,

s2generator/utils/visualization.py

@@ -6,6 +6,7 @@
 """
 
 __all__ = [
+    "plot_time_series",
     "plot_series",
     "plot_symbol",
     "plot_shapiro_wilk",
@@ -25,6 +26,28 @@
 from s2generator.utils.print_symbol import symbol_to_markdown
 
 
+def plot_time_series(
+    time_series: np.ndarray, figsize: Tuple[int, int] = (12, 3), dpi: int = 256
+) -> plt.Figure:
+    """
+    Visualize a single time series.
+
+    :param time_series: The time series data to be visualized.
+    :param figsize: The size of the figure for the generated plot.
+    :param dpi: Dots per inch (resolution) for the generated plot.
+
+    :return: A matplotlib Figure object containing the time series plot.
+    """
+    fig, ax = plt.subplots(figsize=figsize, dpi=dpi)
+    ax.plot(time_series, color="royalblue")
+    ax.set_title("Time Series Visualization", fontweight="bold", fontsize=13)
+    ax.set_xlabel("Time Steps", fontsize=11.5)
+    ax.set_ylabel("Value", fontsize=11.5)
+    ax.grid(True)
+
+    return fig
+
+
 def plot_series(x: np.ndarray, y: np.ndarray) -> plt.Figure:
     """
     Visualize S2 data
@@ -307,6 +330,7 @@ def plot_simulator_statistics(
     nlags: int = 50,
     nperseg: int = 128,
     bins: int = 30,
+    figsize: Tuple[int, int] = None,
 ) -> plt.Figure:
     """
     Compare the statistical properties of the original series and the generated series.
@@ -320,6 +344,7 @@ def plot_simulator_statistics(
     :param nlags: The number of lags to compute for the autocorrelation function.
     :param nperseg: The length of each segment for the Welch method in power spectral density estimation.
     :param bins: The number of bins to use for the histogram plots.
+    :param figsize: The size of the figure for the generated plots. If None, it will be automatically determined.
 
     :return: A matplotlib Figure object containing the comparison plots.
     """
@@ -339,9 +364,9 @@ def plot_simulator_statistics(
     # Here we need to determine if the residuals from the model fit have been passed in.
     # If residuals are present, a subplot can be added to display their statistical properties.
     if residuals is not None:
-        fig, axes = plt.subplots(3, 2, figsize=(12, 10))
+        fig, axes = plt.subplots(3, 2, figsize=(12, 10) if figsize is None else figsize)
     else:
-        fig, axes = plt.subplots(2, 2, figsize=(8, 10))
+        fig, axes = plt.subplots(2, 2, figsize=(12, 7) if figsize is None else figsize)
 
     # Original sequence and generated sequence
     axes[0, 0].plot(original_series, label="Original", alpha=0.7, color="royalblue")

setup.py

@@ -6,7 +6,7 @@
 setuptools.setup(
     name="S2Generator",
     packages=setuptools.find_packages(),
-    version="0.0.6",
+    version="0.0.7",
     description="A series-symbol (S2) dual-modality data generation mechanism, enabling the unrestricted creation of high-quality time series data paired with corresponding symbolic representations.",  # 包的简短描述
     url="https://github.com/wwhenxuan/S2Generator",
     author="whenxuan, johnfan12, changewam",