whenxuan: remove the demo test to data

Author: wwhenxuan

examples/example.npy

@@ -67,13 +67,4 @@ where = ["."]
 include = ["pysdkit*"]
 
 [tool.setuptools.package-data]
-"*" = ["*.txt", "*.npy"]
-"pysdkit.data" = ["*.txt", "*.npy"]
-"pysdkit._tid" = ["data/*.npy"]
-"pysdkit._tid.data" = ["*.npy"]
-"pysdkit._imd" = ["data/*.npy"]
-"pysdkit._imd.data" = ["*.npy"]
-"pysdkit._vmd" = ["data/*.npy"]
-"pysdkit._vmd.data" = ["*.npy"]
-"pysdkit._tfa" = ["data/*.npy"]
-"pysdkit._tfa.data" = ["*.npy"]
+"pysdkit.data" = ["*.npy", "*.txt"]

examples/plot_imfs.jpg

@@ -13,6 +13,8 @@
 import numpy as np
 from scipy.interpolate import CubicSpline, interp1d
 
+from pysdkit.data._loaders import load_wind_demo
+
 
 def find_extrema(x: np.ndarray) -> Tuple[np.ndarray, np.ndarray]:
     """
@@ -438,19 +440,6 @@ def make_esmd_example3(
     }
 
 
-def load_wind_demo(path: str) -> Dict[str, np.ndarray]:
-    """
-    Load a wind-demo CSV/TXT file (column 0 = wind series, ``dt=0.05`` s).
-
-    :param path: path to a comma-separated file whose first column is the series
-    """
-    data = np.loadtxt(path, delimiter=",")
-    y = data[:, 0]
-    dt = 0.05
-    t = np.arange(y.size, dtype=float) * dt
-    return {"t": t, "signal": y, "dt": dt}
-
-
 class ESMD(object):
     """
     Extreme-Point Symmetric Mode Decomposition (ESMD).

examples/texture.mat

@@ -10,9 +10,8 @@
     imd,
     fft_bandpass,
     segment_sparsity,
-    load_imd_input_sig,
-    load_imd_gearbox_snippet,
 )
+from pysdkit.data._loaders import load_imd_gearbox_snippet, load_imd_input_sig
 
 __all__ = [
     "APMD",

examples/texture.txt

@@ -9,12 +9,13 @@
 
 from __future__ import annotations
 
-from pathlib import Path
 from typing import Callable, Dict, List, Optional, Tuple, Union
 
 import numpy as np
 from scipy.signal import hilbert
 
+from pysdkit.data._loaders import load_imd_gearbox_snippet, load_imd_input_sig
+
 
 def fft_bandpass(
     signal: np.ndarray,
@@ -200,27 +201,6 @@ def band_split(
     return np.asarray(parts, dtype=float)
 
 
-def load_imd_input_sig() -> Dict[str, np.ndarray]:
-    """Load the packaged MATLAB ``InputSig`` demo (Fs = 12800 Hz, 2 s)."""
-    path = Path(__file__).resolve().parent / "data" / "input_sig.npy"
-    signal = np.load(path).astype(np.float64).ravel()
-    fs = 12800.0
-    t = np.arange(signal.size, dtype=float) / fs
-    return {"signal": signal, "fs": fs, "t": t}
-
-
-def load_imd_gearbox_snippet() -> Dict[str, np.ndarray]:
-    """
-    Load a short packaged snippet of the MCC5-THU gearbox CSV
-    (``gearbox_vibration_x``, first 4096 samples, Fs = 12800 Hz).
-    """
-    path = Path(__file__).resolve().parent / "data" / "gearbox_fault_snippet.npy"
-    signal = np.load(path).astype(np.float64).ravel()
-    fs = 12800.0
-    t = np.arange(signal.size, dtype=float) / fs
-    return {"signal": signal, "fs": fs, "t": t}
-
-
 class IMD(object):
     """
     Impulsive Mode Decomposition (IMD).

pyproject.toml

@@ -18,9 +18,11 @@
     smooth_if,
     moving_average_if,
     omega_bins_to_hz,
+)
+from pysdkit.data._loaders import (
     load_dual_signal_noise,
-    load_single_nsignal,
     load_map2,
+    load_single_nsignal,
 )
 
 __all__ = [