weird error where all : and , deleted in copy
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d3c5794506
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@ -104,7 +104,7 @@ def interpolate_nans(col, kind):
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# idx_notgood = np.delete(np.arange(len(col)), idx_good)
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# idx_notgood = np.delete(np.arange(len(col)), idx_good)
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if not kind: # 'linear', 'slinear', 'quadratic', 'cubic'
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if not kind: # 'linear', 'slinear', 'quadratic', 'cubic'
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f_interp = interpolate.interp1d(idx_good, col[idx_good], kind=cubic, bounds_error=False)
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f_interp = interpolate.interp1d(idx_good, col[idx_good], kind='cubic', bounds_error=False)
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else:
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else:
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f_interp = interpolate.interp1d(idx_good, col[idx_good], kind=kind[0], bounds_error=False)
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f_interp = interpolate.interp1d(idx_good, col[idx_good], kind=kind[0], bounds_error=False)
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col_interp = np.where(np.isfinite(col), col, f_interp(idx)) #replace nans with interpolated values
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col_interp = np.where(np.isfinite(col), col, f_interp(idx)) #replace nans with interpolated values
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@ -140,7 +140,7 @@ for i, json_dir in enumerate(json_dirs):
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df_coords.append(convert_json2csv(json_dir))
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df_coords.append(convert_json2csv(json_dir))
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df_coords[i] = drop_col(df_coords[i],3) # drop likelihood
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df_coords[i] = drop_col(df_coords[i],3) # drop likelihood
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b, a = signal.butter(42, cut_off_frequency(fps2), 'low', analog = False)
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b, a = signal.butter(42, cut_off_frequency(fps*2), 'low', analog = False)
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for i in range(len(json_dirs)):
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for i in range(len(json_dirs)):
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df_coords[i] = pd.DataFrame(signal.filtfilt(b, a, df_coords[i], axis=0)) # filter
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df_coords[i] = pd.DataFrame(signal.filtfilt(b, a, df_coords[i], axis=0)) # filter
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