ruff check

src/antropy/__init__.py

@@ -1,6 +1,6 @@
 # Import AntroPy objects
-from .utils import *
 from .entropy import *
 from .fractal import *
+from .utils import *
 
 __version__ = "0.1.7"

src/antropy/entropy.py

@@ -1,10 +1,11 @@
 """Entropy functions"""
 
+from math import factorial, log
+
 import numpy as np
 from numba import jit, types
-from math import factorial, log
-from sklearn.neighbors import KDTree
 from scipy.signal import periodogram, welch
+from sklearn.neighbors import KDTree
 
 from .utils import _embed, _xlogx
 

src/antropy/fractal.py

@@ -1,8 +1,9 @@
 """Fractal functions"""
 
+from math import floor, log
+
 import numpy as np
 from numba import jit, types
-from math import log, floor
 
 from .entropy import num_zerocross
 from .utils import _linear_regression, _log_n

src/antropy/utils.py

@@ -1,8 +1,9 @@
 """Helper functions"""
 
+from math import floor, log
+
 import numpy as np
 from numba import jit
-from math import log, floor
 
 all = ["_embed", "_linear_regression", "_log_n", "_xlog2x"]
 epsilon = 10e-9

tests/test_entropy.py

@@ -1,24 +1,24 @@
 """Test entropy functions."""
 
 import unittest
+
 import numpy as np
-from numpy.testing import assert_equal
 from numpy import apply_along_axis as aal
+from numpy.testing import assert_equal
+from utils import ARANGE, NORMAL_TS, PURE_SINE, RANDOM_TS, RANDOM_TS_LONG, TEST_DTYPES
+
 from antropy import (
-    perm_entropy,
-    spectral_entropy,
-    svd_entropy,
-    sample_entropy,
     app_entropy,
+    hjorth_params,
     lziv_complexity,
     num_zerocross,
-    hjorth_params,
+    perm_entropy,
+    sample_entropy,
+    spectral_entropy,
+    svd_entropy,
 )
-
 from antropy.utils import _xlogx
 
-from utils import RANDOM_TS, NORMAL_TS, RANDOM_TS_LONG, PURE_SINE, ARANGE, TEST_DTYPES
-
 SF_TS = 100
 BANDT_PERM = [4, 7, 9, 10, 6, 11, 3]
 

tests/test_fractal.py

@@ -1,14 +1,13 @@
 """Test fractal dimension functions."""
 
 import unittest
+
 import numpy as np
-from numpy.testing import assert_equal
 from numpy import apply_along_axis as aal
-from antropy import petrosian_fd, katz_fd, higuchi_fd, detrended_fluctuation
-import stochastic.processes.noise as sn
-
+from numpy.testing import assert_equal
+from utils import ARANGE, NORMAL_TS, PURE_COSINE, PURE_SINE, RANDOM_TS, TEST_DTYPES
 
-from utils import RANDOM_TS, NORMAL_TS, PURE_SINE, PURE_COSINE, ARANGE, TEST_DTYPES
+from antropy import detrended_fluctuation, higuchi_fd, katz_fd, petrosian_fd
 
 PPG_SIGNAL = np.array(
     [