xdem.DEM.get_stats

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xdem.DEM.get_stats#

DEM.get_stats(stats_name=None, inlier_mask=None, band=1, counts=None)#
Overloads:

  • self, stats_name (str | Callable[[NDArrayNum], np.floating[Any]]), inlier_mask (Raster | NDArrayBool | None), band (int), counts (tuple[int, int] | None) → np.floating[Any]

  • self, stats_name (list[str | Callable[[NDArrayNum], np.floating[Any]]] | None), inlier_mask (Raster | NDArrayBool | None), band (int), counts (tuple[int, int] | None) → dict[str, np.floating[Any]]

Retrieve specified statistics or all available statistics for the raster data. Allows passing custom callables to calculate custom stats.

Common statistics are :

  • Mean: arithmetic mean of the data, ignoring masked values.

  • Median: middle value when the valid data points are sorted in increasing order, ignoring masked values.

  • Max: maximum value among the data, ignoring masked values.

  • Min: minimum value among the data, ignoring masked values.

  • Sum: sum of all data, ignoring masked values.

  • Sum of squares: sum of the squares of all data, ignoring masked values.

  • 90th percentile: point below which 90% of the data falls, ignoring masked values.

  • IQR (Interquartile Range): difference between the 75th and 25th percentile of a dataset, ignoring masked values.

  • LE90 (Linear Error with 90% confidence): difference between the 95th and 5th percentiles of a dataset, representing the range within which 90% of the data points lie. Ignore masked values.

  • NMAD (Normalized Median Absolute Deviation): robust measure of variability in the data, less sensitive to outliers compared to standard deviation. Ignore masked values.

  • RMSE (Root Mean Square Error): commonly used to express the magnitude of errors or variability and can give insight into the spread of the data. Only relevant when the raster represents a difference of two objects. Ignore masked values.

  • Std (Standard deviation): measures the spread or dispersion of the data around the mean, ignoring masked values.

  • Valid count: number of finite data points in the array. It counts the non-masked elements.

  • Total count: total size of the raster.

  • Percentage valid points: ratio between Valid count and Total count.

For all statistics up to and including “Std”, NumPy Masked functions are used (directly or in the calculation) in case of a masked array, NumPy module otherwise.

“Valid count” represents all non zero and not masked pixels in the input data (final_count_nonzero), calculated before the mask application in case of an inlier_mask. NumPy Masked functions are used is this case or if the Raster was already a masked array. “Percentage valid points” is calculated accordingly.

If an inlier mask is passed:

  • Total inlier count: number of data points in the inlier mask.

  • Valid inlier count: number of unmasked data points in the array after applying the inlier mask.

  • Percentage inlier points: ratio between Valid inlier count and Valid count. Useful for classification statistics.

  • Percentage valid inlier points: ratio between Valid inlier count and Total inlier count.

They are all computed based on the previously stated final_count_nonzero.

Callable functions are supported as well.

Parameters:

  • stats_name (str | Callable[[ndarray[tuple[Any, ...], dtype[floating[Any] | integer[Any]]]], floating[Any]] | list[str | Callable[[ndarray[tuple[Any, ...], dtype[floating[Any] | integer[Any]]]], floating[Any]]] | None) – Name or list of names of the statistics to retrieve. If None, all statistics are returned. Accepted names include: mean, median, max, min, sum, sum of squares, 90th percentile, iqr, LE90, nmad, rmse, std, valid count, total count, percentage valid points and if an inlier mask is passed : valid inlier count, total inlier count, percentage inlier point, percentage valid inlier points. Custom callables can also be provided.

  • inlier_mask (Raster | ndarray[tuple[Any, ...], dtype[bool]] | None) – Mask or boolean array of areas to include (inliers=True).

  • band (int) – The index of the band for which to compute statistics. Default is 1.

  • counts (tuple[int, int] | None) – (number of finite data points in the array, number of valid points (=True, to keep) in inlier_mask), initialize in case of a inlier_mask. DO NOT USE.

Returns:

The requested statistic or a dictionary of statistics if multiple or all are requested.

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