01f9d3debc2f1b35a88a2398119809835b4431f0,features/eolearn/features/interpolation.py,InterpolationTask,execute,#InterpolationTask#Any#,283

Before Change

        // Prepare mask of valid data
        if self.mask_feature:
            mask_type, mask_name = next(self.mask_feature(eopatch))
            if feature_data.shape[0] == 1:
                feature_data = np.squeeze(feature_data,axis=0)
            feature_data[~eopatch[mask_type][mask_name].squeeze(), :] = np.nan

        // Flatten array
        feature_data = np.reshape(feature_data, (time_num, height * width * band_num))

After Change

        // Make a copy not to change original numpy array
        feature_data = eopatch[feature_type][feature_name].copy()
        time_num, height, width, band_num = feature_data.shape
        if time_num <= 1:
            raise ValueError("Feature {} has time dimension of size {}, required at least size "
                             "2".format((feature_type, feature_name), time_num))

        // Apply a mask on data
        feature_data = self._mask_feature_data(feature_data, eopatch)

        // Flatten array
        feature_data = np.reshape(feature_data, (time_num, height * width * band_num))

Instances