set new y_err with value zero (#215)
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closes #215
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parent
d83e112515
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@ -29,10 +29,10 @@ jobs:
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env:
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GPG_KEYGRIP: ${{ vars.GPG_KEYGRIP }}
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GPG_PASSPHRASE: ${{ secrets.GPG_PASSPHRASE }}
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GO_PIPELINE_LABEL: ${{ env.YEAR }}.${{ gitea.run_number }}_${{ env.SHA_SHORT }}_bookworm
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GO_PIPELINE_LABEL: ${{ env.YEAR }}.${{ gitea.run_number }}_${{ env.SHA_SHORT }}
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- name: Upload AppImage
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run: ./tools/upload_gitea.sh
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env:
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GO_PIPELINE_LABEL: ${{ env.YEAR }}.${{ gitea.run_number }}_${{ env.SHA_SHORT }}_bookworm
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GO_PIPELINE_LABEL: ${{ env.YEAR }}.${{ gitea.run_number }}_${{ env.SHA_SHORT }}
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UPLOAD_TOKEN: ${{ secrets.UPLOAD_TOKEN }}
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UPLOAD_USER: ${{ vars.UPLOAD_USER }}
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@ -3,14 +3,21 @@ import numpy.polynomial.polynomial as poly
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from scipy import signal as signal
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__all__ = ['smooth', 'loess', 'savgol',
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'running_max', 'running_min',
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'running_var', 'running_std',
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'running_median', 'running_mean',
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'running_sum']
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__all__ = [
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'smooth',
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'loess',
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'savgol',
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'running_max',
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'running_min',
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'running_var',
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'running_std',
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'running_median',
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'running_mean',
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'running_sum',
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]
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def loess(x, y, window_size, it=0, deg=2):
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def loess(x, y, window_size: int, it: int = 0, deg: int = 2):
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# ULTRA LANGSAM !!!
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it = max(it, 0)
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@ -81,19 +88,19 @@ def savgol(x, y, window_size: int, deg: int = 2, mode: str = 'mirror'):
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return new_y
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def running_mean(x, y, window_size):
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def running_mean(x, y, window_size: int):
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return _running_func(np.nanmean, x, y, window_size)
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def running_median(x, y, window_size):
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def running_median(x, y, window_size: int):
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return _running_func(np.nanmedian, x, y, window_size)
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def running_std(x, y, window_size):
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def running_std(x, y, window_size: int):
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return _running_func(np.nanstd, x, y, window_size)
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def running_var(x, y, window_size):
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def running_var(x, y, window_size: int):
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return _running_func(np.nanvar, x, y, window_size)
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@ -132,11 +139,27 @@ def _moving_window(arr, nn):
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return np.lib.stride_tricks.as_strided(arr, shapes, strides)
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_funcs = {'loess': loess, 'savgol': savgol, 'mean': running_mean, 'median': running_median,
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'std': running_std, 'var': running_var, 'max': running_max, 'min': running_min, 'sum': running_sum}
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_funcs = {
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'loess': loess,
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'savgol': savgol,
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'mean': running_mean,
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'median': running_median,
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'std': running_std,
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'var': running_var,
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'max': running_max,
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'min': running_min,
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'sum': running_sum,
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}
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def smooth(data, window_size, mode='mean', logx=False, logy=False, **kwargs):
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def smooth(
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data: 'Data',
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window_size: int,
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mode: str = 'mean',
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logx: bool = False,
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logy: bool = False,
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**kwargs
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):
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try:
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func = _funcs[mode]
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except KeyError:
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@ -162,6 +185,6 @@ def smooth(data, window_size, mode='mean', logx=False, logy=False, **kwargs):
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new_y = 10**new_y
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new_data = data.copy()
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new_data.set_data(x=new_x, y=new_y, y_err=None)
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new_data.set_data(x=new_x, y=new_y, y_err=np.zeros_like(new_y))
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return new_data
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