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chore: Replace deprecated zero_copy_only argument with allow_copy #222

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chore: Replace deprecated zero_copy_only argument with allow_copy #222

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chore: Replace deprecated `zero_copy_only` argument with `allow_copy`
khrapovs Jun 6, 2024
302d745
Merge branch 'refs/heads/main' into chore/replace-deprecated-argument…
khrapovs Jun 7, 2024
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16 changes: 7 additions & 9 deletions functime/feature_extractors.py
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Original file line number Diff line number Diff line change
Expand Up @@ -194,7 +194,7 @@ def augmented_dickey_fuller(x: TIME_SERIES_T, n_lags: int) -> float:
),
pl.lit(1),
) # was a frame
y = data_x.drop_in_place("0").to_numpy(zero_copy_only=True)
y = data_x.drop_in_place("0").to_numpy(allow_copy=False)
data_x = data_x.to_numpy() # to NumPy matrix

coeffs, resids, _, _ = lstsq(data_x, y, cond=None)
Expand Down Expand Up @@ -272,7 +272,7 @@ def autoregressive_coefficients(x: TIME_SERIES_T, n_lags: int) -> List[float]:
)
.to_numpy()
)
y_ = y.tail(length).to_numpy(zero_copy_only=True).reshape((-1, 1))
y_ = y.tail(length).to_numpy(allow_copy=False).reshape((-1, 1))
out: np.ndarray = rs_faer_lstsq1(data_x, y_)
return out.ravel()
else:
Expand Down Expand Up @@ -593,9 +593,7 @@ 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, mode="same"
)
convolution[i] = np.convolve(x.to_numpy(allow_copy=False), wavelet_x, mode="same")
coeffs = []
for coeff_idx in range(min(n_coefficients, convolution.shape[1])):
coeffs.extend(convolution[widths.index(w), coeff_idx] for w in widths)
Expand Down Expand Up @@ -743,8 +741,8 @@ def friedrich_coefficients(
# This is a Vandermonde matrix. May have shortcuts in our use case, as again length >> degree.
# Not sure if NumPy is taking advantage of this though.
return np.polyfit(
x_means.get_column("signal").to_numpy(zero_copy_only=True),
x_means.get_column("delta").to_numpy(zero_copy_only=True),
x_means.get_column("signal").to_numpy(allow_copy=False),
x_means.get_column("delta").to_numpy(allow_copy=False),
deg=polynomial_order,
)
else:
Expand Down Expand Up @@ -1183,7 +1181,7 @@ def number_cwt_peaks(x: TIME_SERIES_T, max_width: int = 5) -> float:
if isinstance(x, pl.Series):
return len(
find_peaks_cwt(
vector=x.to_numpy(zero_copy_only=True),
vector=x.to_numpy(allow_copy=False),
widths=np.array(list(range(1, max_width + 1))),
wavelet=ricker,
)
Expand Down Expand Up @@ -1895,7 +1893,7 @@ def fft_coefficients(x: TIME_SERIES_T) -> MAP_LIST_EXPR:
dict of list of floats | Expr
"""

fft = np.fft.rfft(x.to_numpy(zero_copy_only=True))
fft = np.fft.rfft(x.to_numpy(allow_copy=False))
real = fft.real
imag = fft.imag
angle = np.arctan2(real, imag)
Expand Down