demcompare

Demcompare init module file. Demcompare aims at coregistering and comparing two Digital Elevation Models(DEM)

Subpackages

• demcompare.classification_layer
  • demcompare.classification_layer.classification_layer
  • demcompare.classification_layer.classification_layer_template
  • demcompare.classification_layer.fusion_classification
  • demcompare.classification_layer.global_classification
  • demcompare.classification_layer.segmentation_classification
  • demcompare.classification_layer.slope_classification
• demcompare.coregistration
  • demcompare.coregistration.coregistration
  • demcompare.coregistration.coregistration_template
  • demcompare.coregistration.nuth_kaab_internal
• demcompare.metric
  • demcompare.metric.metric
  • demcompare.metric.metric_template
  • demcompare.metric.scalar_metrics
  • demcompare.metric.vector_metrics

Submodules

• demcompare.dataset_tools
• demcompare.dem_tools
• demcompare.demcompare
• demcompare.helpers_init
• demcompare.img_tools
• demcompare.internal_typing
• demcompare.log_conf
• demcompare.output_tree_design
• demcompare.report
• demcompare.sphinx_project_generator
• demcompare.stats_dataset
• demcompare.stats_processing
• demcompare.transformation

Package Contents

Functions

run(json_file_path[, loglevel])	Demcompare RUN execution.
load_input_dems(→ Tuple[xarray.Dataset, Union[None, ...)	Loads the input dems according to the input cfg
run_coregistration(→ Tuple[xarray.Dataset, ...)	Runs the dems coregistration
compute_stats_after_coregistration(...)	Compute stats after coregistration

Attributes

__version__
__author__
__email__

demcompare.__version__

demcompare.__author__ = 'CNES'

demcompare.__email__ = 'cars@cnes.fr'

demcompare.run(json_file_path: str, loglevel: int = logging.WARNING)

Demcompare RUN execution.

Parameters:

• json_file_path – Input Json configuration file

• loglevel (int) – Choose Loglevel (default: WARNING)

demcompare.load_input_dems(cfg: internal_typing.ConfigType) → Tuple[xarray.Dataset, None | xarray.Dataset]

Loads the input dems according to the input cfg

Parameters:

cfg (ConfigType) – input configuration

Returns:

input_ref and input_dem datasets or None

Return type:

Tuple(xr.Dataset, xr.dataset) The xr.Datasets containing :

• im : 2D (row, col) xarray.DataArray float32

• trans: 1D (trans_len) xarray.DataArray

demcompare.run_coregistration(cfg: internal_typing.ConfigType, input_ref: xarray.Dataset, input_sec: xarray.Dataset) → Tuple[xarray.Dataset, xarray.Dataset, xarray.Dataset, xarray.Dataset]

Runs the dems coregistration

Parameters:

• cfg (ConfigType) – coregistration configuration

• input_ref – input ref

• input_sec – input dem

Returns:

reproj_sec, reproj_ref, reproj_coreg_sec, reproj_coreg_ref

Return type:

Tuple(xr.Dataset, xr.dataset, xr.Dataset, xr.dataset) The xr.Datasets containing :

• im : 2D (row, col) xarray.DataArray float32

• trans: 1D (trans_len) xarray.DataArray

demcompare.compute_stats_after_coregistration(cfg: internal_typing.ConfigType, coreg_sec: xarray.Dataset, coreg_ref: xarray.Dataset, initial_sec: xarray.Dataset = None, initial_ref: xarray.Dataset = None) → stats_dataset.StatsDataset

Compute stats after coregistration

For the initial_dh and final_dh the alti_diff plot, the cdf and the pdf are computed if the output_dir has been specified in order to evaluate the coregistration effect.

For the final_dh, the different classification layers and metrics specified in the input cfg are also computed.

Parameters:

• cfg (ConfigType) – configuration dictionary

• coreg_sec (xr.Dataset) –

  coreg dem to align xr.DataSet containing :

  • image : 2D (row, col) xr.DataArray float32

  • georef_transform: 1D (trans_len) xr.DataArray

  • classification_layer_masks : 3D (row, col, indicator) xr.DataArray

• coreg_ref (xr.Dataset) –

  coreg reference dem xr.DataSet containing :

  • image : 2D (row, col) xr.DataArray float32

  • georef_transform: 1D (trans_len) xr.DataArray

  • classification_layer_masks : 3D (row, col, indicator) xr.DataArray

• initial_sec –

  optional initial dem to align xr.DataSet containing :

  • image : 2D (row, col) xr.DataArray float32

  • georef_transform: 1D (trans_len) xr.DataArray

  • classification_layer_masks : 3D (row, col, indicator) xr.DataArray

• initial_ref (xr.Dataset) –

  optional initial reference dem xr.DataSet containing :

  • image : 2D (row, col) xr.DataArray float32

  • georef_transform: 1D (trans_len) xr.DataArray

  • classification_layer_masks : 3D (row, col, indicator) xr.DataArray

Returns:

StatsDataset

Return type:

StatsDataset