fix(206): Fix ValueError in cwt_coefficients (#208)

functime/feature_extractors.py

@@ -594,10 +594,10 @@ def cwt_coefficients(
         for i, width in enumerate(widths):
             points = np.min([10 * width, x.len()])
             wavelet_x = np.conj(ricker(points, width)[::-1])
-            convolution[i] = np.convolve(x.to_numpy(zero_copy_only=True), wavelet_x)
+            convolution[i] = np.convolve(x.to_numpy(zero_copy_only=True), wavelet_x, mode="same")
         coeffs = []
         for coeff_idx in range(min(n_coefficients, convolution.shape[1])):
-            coeffs.extend(convolution[widths.index(), coeff_idx] for _ in widths)
+            coeffs.extend(convolution[widths.index(w), coeff_idx] for w in widths)
         return coeffs
     else:
         logger.info(

tests/test_feature_extractors.py

@@ -0,0 +1,12 @@
+import numpy as np
+import polars as pl
+import pytest
+from functime.feature_extractors import cwt_coefficients
+
+
+@pytest.mark.parametrize("length", np.random.random_integers(low=1, high=100, size=5))
+@pytest.mark.parametrize("widths", [(2,), (2, 5, 10, 20), (2, 5, 10, 20, 30)])
+@pytest.mark.parametrize("n_coefficients", np.random.random_integers(low=1, high=100, size=5))
+def test_cwt(length: int, widths: tuple, n_coefficients: int) -> None:
+    out = cwt_coefficients(pl.Series([1 for _ in range(length)]), widths=widths, n_coefficients=n_coefficients)
+    assert len(out) == min(n_coefficients, length) * len(widths)