Module: sarpyx.snapflow.engine

File: sarpyx/snapflow/engine.py

SNAP GPT (Graph Processing Tool) wrapper for SAR data processing. This module provides a Pythonic interface to ESA's SNAP GPT command-line tool, enabling automated processing of Synthetic Aperture Radar (SAR) data through various operators like calibration, terrain correction, and subsetting.

Exported Symbols (__all__)

No explicit __all__ list. Public symbols inferred from implementation.

Public Functions (0)

No public top-level functions detected.

Public Classes (1)

GPT class

Wrapper class for executing SNAP Graph Processing Tool (GPT) commands. This class provides a high-level interface to SNAP's GPT command-line tool, abstracting away the complexity of command construction and execution.

File location: sarpyx/snapflow/engine.py:20

Class Signature

class GPT

Constructor Parameters

Return Type

GPT instances.

Exceptions

Construction/runtime exceptions are inferred from implementation and method-level documentation.

Side Effects

See method-level side effects below.

Example Usage

from sarpyx.snapflow.engine import GPT

obj = GPT(...)  # inferred from implementation

Edge Cases

No class-level edge-case section is explicitly documented; rely on method-level checks and raised exceptions.

Public Methods (156)

GPT.run_graph method

Execute a standalone GPT XML graph file.

File location: sarpyx/snapflow/engine.py:223

Signature

run_graph(self, graph_path: str | Path, output_path: str | Path, delete_graph: bool=False) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
graph_pathstr | Pathyes-inferred from implementation.
output_pathstr | Pathyes-inferred from implementation.
delete_graphboolnoFalseinferred from implementation.

Return Type

Optional[str]

inferred from implementation.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.run_graph(graph_path=<graph_path>, output_path=<output_path>)

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.

GPT.last_error_summary method

Return a concise summary of the last GPT error.

File location: sarpyx/snapflow/engine.py:324

Signature

last_error_summary(self, max_chars: int=800) -> str

Parameters

ParameterTypeRequiredDefaultDescription
max_charsintno800inferred from implementation.

Return Type

str

inferred from implementation.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.last_error_summary()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.

GPT.import_vector method

Import vector data into the product.

File location: sarpyx/snapflow/engine.py:386

Signature

import_vector(self, vector_data: str | Path, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
vector_datastr | Pathyes-Path to the shapefile or vector data.
output_nameOptional[str]noNoneCustom output filename (without extension).

Return Type

Optional[str]

Path to output product with imported vector, or None if failed.

Exceptions

  • FileNotFoundError

Side Effects

  • io

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.import_vector(vector_data=<vector_data>)

Edge Cases

May raise: FileNotFoundError. Includes optional parameters with implementation-defined fallback behavior. Documented return may be None for some execution paths.

GPT.land_mask method

Apply Land-Sea Masking using a predefined XML graph structure.

File location: sarpyx/snapflow/engine.py:439

Signature

land_mask(self, shoreline_extension: int=300, geometry_name: str='Buff_750', use_srtm: bool=True, invert_geometry: bool=True, land_mask: bool=False, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
shoreline_extensionintno300Distance to extend shoreline in meters.
geometry_namestrno'Buff_750'Name of the geometry to use for masking.
use_srtmboolnoTrueUse SRTM DEM for land/sea determination.
invert_geometryboolnoTrueInvert the geometry mask.
land_maskboolnoFalseMask land (True) or sea (False) areas.
output_nameOptional[str]noNoneCustom output filename (without extension).

Return Type

Optional[str]

Path to masked output product, or None if failed.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • io

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.land_mask()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior. Documented return may be None for some execution paths.

GPT.terrain_mask method

Generate a terrain mask using a DEM.

File location: sarpyx/snapflow/engine.py:535

Signature

terrain_mask(self, dem_name: str='SRTM 3Sec', dem_resampling_method: str='NEAREST_NEIGHBOUR', external_dem_file: Optional[str | Path]=None, external_dem_no_data_value: float=0.0, threshold_in_meter: float=40.0, window_size_str: str='15x15', output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
dem_namestrno'SRTM 3Sec'The digital elevation model to use.
dem_resampling_methodstrno'NEAREST_NEIGHBOUR'DEM resampling method.
external_dem_fileOptional[str | Path]noNonePath to an external DEM file.
external_dem_no_data_valuefloatno0.0No data value for the external DEM.
threshold_in_meterfloatno40.0Elevation threshold for mask detection.
window_size_strstrno'15x15'Size of the window used for filtering.
output_nameOptional[str]noNoneCustom output filename (without extension).

Return Type

Optional[str]

Path to the terrain mask product, or None if failed.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.terrain_mask()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior. Documented return may be None for some execution paths.

GPT.terrain_flattening method

Perform terrain flattening with configurable DEM and output options.

File location: sarpyx/snapflow/engine.py:574

Signature

terrain_flattening(self, additional_overlap: float=0.1, dem_name: str='SRTM 1Sec HGT', dem_resampling_method: str='BILINEAR_INTERPOLATION', external_dem_apply_egm: bool=False, external_dem_file: Optional[str | Path]=None, external_dem_no_data_value: float=0.0, nodata_value_at_sea: bool=True, output_sigma0: bool=False, output_simulated_image: bool=False, oversampling_multiple: float=1.0, source_bands: Optional[List[str]]=None, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
additional_overlapfloatno0.1inferred from implementation.
dem_namestrno'SRTM 1Sec HGT'inferred from implementation.
dem_resampling_methodstrno'BILINEAR_INTERPOLATION'inferred from implementation.
external_dem_apply_egmboolnoFalseinferred from implementation.
external_dem_fileOptional[str | Path]noNoneinferred from implementation.
external_dem_no_data_valuefloatno0.0inferred from implementation.
nodata_value_at_seaboolnoTrueinferred from implementation.
output_sigma0boolnoFalseinferred from implementation.
output_simulated_imageboolnoFalseinferred from implementation.
oversampling_multiplefloatno1.0inferred from implementation.
source_bandsOptional[List[str]]noNoneinferred from implementation.
output_nameOptional[str]noNoneinferred from implementation.

Return Type

Optional[str]

inferred from implementation.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.terrain_flattening()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.

GPT.temporal_percentile method

Compute percentile statistics over time series products.

File location: sarpyx/snapflow/engine.py:613

Signature

temporal_percentile(self, source_products: Optional[List[str | Path]]=None, source_product_paths: Optional[List[str]]=None, band_math_expression: Optional[str]=None, source_band_name: Optional[str]=None, crs: str='EPSG:4326', west_bound: float=-15.0, north_bound: float=75.0, east_bound: float=30.0, south_bound: float=35.0, pixel_size_x: float=0.05, pixel_size_y: float=0.05, resampling: str='Nearest', percentiles: Optional[List[int]]=None, valid_pixel_expression: str='true', gap_filling_method: str='gapFillingLinearInterpolation', start_date: Optional[str]=None, end_date: Optional[str]=None, start_value_fallback: float=0.0, end_value_fallback: float=0.0, keep_intermediate_time_series_product: bool=True, time_series_output_dir: Optional[str | Path]=None, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
source_productsOptional[List[str | Path]]noNoneinferred from implementation.
source_product_pathsOptional[List[str]]noNoneinferred from implementation.
band_math_expressionOptional[str]noNoneinferred from implementation.
source_band_nameOptional[str]noNoneinferred from implementation.
crsstrno'EPSG:4326'inferred from implementation.
west_boundfloatno-15.0inferred from implementation.
north_boundfloatno75.0inferred from implementation.
east_boundfloatno30.0inferred from implementation.
south_boundfloatno35.0inferred from implementation.
pixel_size_xfloatno0.05inferred from implementation.
pixel_size_yfloatno0.05inferred from implementation.
resamplingstrno'Nearest'inferred from implementation.
percentilesOptional[List[int]]noNoneinferred from implementation.
valid_pixel_expressionstrno'true'inferred from implementation.
gap_filling_methodstrno'gapFillingLinearInterpolation'inferred from implementation.
start_dateOptional[str]noNoneinferred from implementation.
end_dateOptional[str]noNoneinferred from implementation.
start_value_fallbackfloatno0.0inferred from implementation.
end_value_fallbackfloatno0.0inferred from implementation.
keep_intermediate_time_series_productboolnoTrueinferred from implementation.
time_series_output_dirOptional[str | Path]noNoneinferred from implementation.
output_nameOptional[str]noNoneinferred from implementation.

Return Type

Optional[str]

inferred from implementation.

Exceptions

  • ValueError

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.temporal_percentile()

Edge Cases

May raise: ValueError. Includes optional parameters with implementation-defined fallback behavior.

GPT.calibration method

Apply radiometric calibration.

File location: sarpyx/snapflow/engine.py:695

Signature

calibration(self, pols: Optional[List[str]]=None, output_complex: bool=True, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
polsOptional[List[str]]noNonePolarizations to calibrate. If None, all polarizations are used.
output_complexboolnoTrueOutput complex values.
output_nameOptional[str]noNoneCustom output filename (without extension).

Return Type

Optional[str]

Path to calibrated product, or None if failed.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.calibration()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior. Documented return may be None for some execution paths.

GPT.thermal_noise_removal method

Remove thermal noise from products.

File location: sarpyx/snapflow/engine.py:726

Signature

thermal_noise_removal(self, pols: Optional[List[str]]=None, output_noise: bool=False, reintroduce_thermal_noise: bool=False, remove_thermal_noise: bool=True, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
polsOptional[List[str]]noNonePolarizations to process. If None, all polarizations are used.
output_noiseboolnoFalseOutput the noise band.
reintroduce_thermal_noiseboolnoFalseRe-introduce thermal noise.
remove_thermal_noiseboolnoTrueRemove thermal noise.
output_nameOptional[str]noNoneCustom output filename (without extension).

Return Type

Optional[str]

Path to output product, or None if failed.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.thermal_noise_removal()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior. Documented return may be None for some execution paths.

GPT.deburst method

Apply TOPSAR Debursting.

File location: sarpyx/snapflow/engine.py:764

Signature

deburst(self, pols: Optional[List[str]]=None, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
polsOptional[List[str]]noNonePolarizations to deburst. If None, all channels are debursted.
output_nameOptional[str]noNoneCustom output filename (without extension).

Return Type

Optional[str]

Path to deburst product, or None if failed.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.deburst()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior. Documented return may be None for some execution paths.

GPT.multilook method

Apply Multilooking.

File location: sarpyx/snapflow/engine.py:788

Signature

multilook(self, n_rg_looks: int, n_az_looks: int, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
n_rg_looksintyes-Number of range looks.
n_az_looksintyes-Number of azimuth looks.
output_nameOptional[str]noNoneCustom output filename (without extension).

Return Type

Optional[str]

Path to multilooked product, or None if failed.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.multilook(n_rg_looks=<n_rg_looks>, n_az_looks=<n_az_looks>)

Edge Cases

Includes optional parameters with implementation-defined fallback behavior. Documented return may be None for some execution paths.

GPT.adaptive_thresholding method

Apply Adaptive Thresholding for object detection.

File location: sarpyx/snapflow/engine.py:810

Signature

adaptive_thresholding(self, background_window_m: float=800, guard_window_m: float=500, target_window_m: float=50, pfa: float=6.5, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
background_window_mfloatno800Background window size in meters.
guard_window_mfloatno500Guard window size in meters.
target_window_mfloatno50Target window size in meters.
pfafloatno6.5Probability of false alarm.
output_nameOptional[str]noNoneCustom output filename (without extension).

Return Type

Optional[str]

Path to thresholded product, or None if failed.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.adaptive_thresholding()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior. Documented return may be None for some execution paths.

GPT.object_discrimination method

Discriminate objects based on size.

File location: sarpyx/snapflow/engine.py:840

Signature

object_discrimination(self, min_target_m: float, max_target_m: float, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
min_target_mfloatyes-Minimum target size in meters.
max_target_mfloatyes-Maximum target size in meters.
output_nameOptional[str]noNoneCustom output filename (without extension).

Return Type

Optional[str]

Path to discriminated product, or None if failed.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.object_discrimination(min_target_m=<min_target_m>, max_target_m=<max_target_m>)

Edge Cases

Includes optional parameters with implementation-defined fallback behavior. Documented return may be None for some execution paths.

GPT.subset method

Create a spatial and/or spectral subset of a data product.

File location: sarpyx/snapflow/engine.py:864

Signature

subset(self, source_bands: Optional[List[str]]=None, tie_point_grids: Optional[List[str]]=None, region: Optional[str]=None, reference_band: Optional[str]=None, geo_region: Optional[str]=None, sub_sampling_x: int=1, sub_sampling_y: int=1, full_swath: bool=False, vector_file: Optional[str | Path]=None, polygon_region: Optional[str]=None, copy_metadata: bool=False, suffix: str='SUB', output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
source_bandsOptional[List[str]]noNoneList of source bands to include. If None, all bands are included.
tie_point_gridsOptional[List[str]]noNoneList of tie-point grid names to include.
regionOptional[str]noNoneSubset region in pixel coordinates.
reference_bandOptional[str]noNoneBand used to indicate the pixel coordinates.
geo_regionOptional[str]noNoneSubset region in geographical coordinates using WKT-format. e.g., 'POLYGON((lon1 lat1, lon2 lat2, ..., lon1 lat1))'. This parameter has precedence over 'region'.
sub_sampling_xintno1Pixel sub-sampling step in X (horizontal direction).
sub_sampling_yintno1Pixel sub-sampling step in Y (vertical direction).
full_swathboolnoFalseForces the operator to extend the subset region to the full swath.
vector_fileOptional[str | Path]noNoneFile from which the polygon is read.
polygon_regionOptional[str]noNoneSubset region in geographical coordinates using WKT-format.
copy_metadataboolnoFalseWhether to copy the metadata of the source product.
suffixstrno'SUB'Suffix for the output filename.
output_nameOptional[str]noNoneCustom output filename (without extension).

Return Type

Optional[str]

Path to the subset output product, or None if failed.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

# Subset by pixel region
    gpt.subset(region='100,200,500,500', source_bands=['Amplitude_VV'])
    
    # Subset by geographic region
    gpt.subset(
        geo_region='POLYGON((10.0 53.0, 11.0 53.0, 11.0 54.0, 10.0 54.0, 10.0 53.0))',
        source_bands=['Intensity_VH', 'Intensity_VV']
    )
    
    # Subset using vector file
    gpt.subset(vector_file='aoi.shp', source_bands=['Sigma0_VV'])

Edge Cases

Includes optional parameters with implementation-defined fallback behavior. Documented return may be None for some execution paths.

GPT.set_no_data_value method

Set the NoDataValue and enable the NoDataValueUsed flag for all bands.

File location: sarpyx/snapflow/engine.py:959

Signature

set_no_data_value(self, no_data_value: float=0.0, no_data_value_used: bool=True, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
no_data_valuefloatno0.0inferred from implementation.
no_data_value_usedboolnoTrueinferred from implementation.
output_nameOptional[str]noNoneinferred from implementation.

Return Type

Optional[str]

inferred from implementation.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.set_no_data_value()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.

GPT.supervised_wishart_classification method

Perform supervised Wishart classification using provided training data.

File location: sarpyx/snapflow/engine.py:974

Signature

supervised_wishart_classification(self, training_dataset: str, window_size: int=5, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
training_datasetstryes-inferred from implementation.
window_sizeintno5inferred from implementation.
output_nameOptional[str]noNoneinferred from implementation.

Return Type

Optional[str]

inferred from implementation.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.supervised_wishart_classification(training_dataset=<training_dataset>)

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.

GPT.subgraph method

Encapsulate an existing graph via the SubGraph operator.

File location: sarpyx/snapflow/engine.py:990

Signature

subgraph(self, graph_file: str, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
graph_filestryes-inferred from implementation.
output_nameOptional[str]noNoneinferred from implementation.

Return Type

Optional[str]

inferred from implementation.

Exceptions

  • FileNotFoundError

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.subgraph(graph_file=<graph_file>)

Edge Cases

May raise: FileNotFoundError. Includes optional parameters with implementation-defined fallback behavior.

GPT.statistics_op method

Compute statistics for the provided source products.

File location: sarpyx/snapflow/engine.py:1004

Signature

statistics_op(self, source_products: Optional[List[str | Path]]=None, source_product_paths: Optional[List[str]]=None, shapefile: Optional[str | Path]=None, feature_id: str='name', start_date: Optional[str]=None, end_date: Optional[str]=None, output_shapefile: Optional[str | Path]=None, output_ascii_file: Optional[str | Path]=None, percentiles: Optional[List[int]]=None, accuracy: int=3, write_data_types_separately: bool=False, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
source_productsOptional[List[str | Path]]noNoneinferred from implementation.
source_product_pathsOptional[List[str]]noNoneinferred from implementation.
shapefileOptional[str | Path]noNoneinferred from implementation.
feature_idstrno'name'inferred from implementation.
start_dateOptional[str]noNoneinferred from implementation.
end_dateOptional[str]noNoneinferred from implementation.
output_shapefileOptional[str | Path]noNoneinferred from implementation.
output_ascii_fileOptional[str | Path]noNoneinferred from implementation.
percentilesOptional[List[int]]noNoneinferred from implementation.
accuracyintno3inferred from implementation.
write_data_types_separatelyboolnoFalseinferred from implementation.
output_nameOptional[str]noNoneinferred from implementation.

Return Type

Optional[str]

inferred from implementation.

Exceptions

  • ValueError

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.statistics_op()

Edge Cases

May raise: ValueError. Includes optional parameters with implementation-defined fallback behavior.

GPT.stamps_export method

Export StaMPS-compatible data products.

File location: sarpyx/snapflow/engine.py:1063

Signature

stamps_export(self, target_folder: str, psi_format: bool=True, source_product: Optional[str | Path]=None, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
target_folderstryes-inferred from implementation.
psi_formatboolnoTrueinferred from implementation.
source_productOptional[str | Path]noNoneinferred from implementation.
output_nameOptional[str]noNoneinferred from implementation.

Return Type

Optional[str]

inferred from implementation.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.stamps_export(target_folder=<target_folder>)

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.

GPT.stack_split method

Split the product into one file per band via Stack-Split.

File location: sarpyx/snapflow/engine.py:1088

Signature

stack_split(self, target_folder: str='target', format_name: str='BEAM-DIMAP', output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
target_folderstrno'target'inferred from implementation.
format_namestrno'BEAM-DIMAP'inferred from implementation.
output_nameOptional[str]noNoneinferred from implementation.

Return Type

Optional[str]

inferred from implementation.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.stack_split()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.

GPT.stack_averaging method

Run Stack-Averaging on the product with the desired statistic.

File location: sarpyx/snapflow/engine.py:1107

Signature

stack_averaging(self, statistic: str='Mean Average', source_product: Optional[str | Path]=None, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
statisticstrno'Mean Average'inferred from implementation.
source_productOptional[str | Path]noNoneinferred from implementation.
output_nameOptional[str]noNoneinferred from implementation.

Return Type

Optional[str]

inferred from implementation.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.stack_averaging()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.

GPT.s2_resampling method

Run the S2Resampling operator with configurable options.

File location: sarpyx/snapflow/engine.py:1127

Signature

s2_resampling(self, source_product: Optional[str | Path]=None, bands: Optional[List[str]]=None, downsampling: str='Mean', flag_downsampling: str='First', masks: Optional[List[str]]=None, resample_on_pyramid_levels: bool=True, resolution: str='60', upsampling: str='Bilinear', output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
source_productOptional[str | Path]noNoneinferred from implementation.
bandsOptional[List[str]]noNoneinferred from implementation.
downsamplingstrno'Mean'inferred from implementation.
flag_downsamplingstrno'First'inferred from implementation.
masksOptional[List[str]]noNoneinferred from implementation.
resample_on_pyramid_levelsboolnoTrueinferred from implementation.
resolutionstrno'60'inferred from implementation.
upsamplingstrno'Bilinear'inferred from implementation.
output_nameOptional[str]noNoneinferred from implementation.

Return Type

Optional[str]

inferred from implementation.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.s2_resampling()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.

GPT.s2rep method

Compute the Sentinel-2 red-edge position index (S2rep).

File location: sarpyx/snapflow/engine.py:1165

Signature

s2rep(self, downsampling: str='First', nir_factor: float=1.0, nir_source_band: Optional[str]=None, red_b4_factor: float=1.0, red_b5_factor: float=1.0, red_b6_factor: float=1.0, red_source_band4: Optional[str]=None, red_source_band5: Optional[str]=None, red_source_band6: Optional[str]=None, resample_type: str='None', upsampling: str='Nearest', output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
downsamplingstrno'First'inferred from implementation.
nir_factorfloatno1.0inferred from implementation.
nir_source_bandOptional[str]noNoneinferred from implementation.
red_b4_factorfloatno1.0inferred from implementation.
red_b5_factorfloatno1.0inferred from implementation.
red_b6_factorfloatno1.0inferred from implementation.
red_source_band4Optional[str]noNoneinferred from implementation.
red_source_band5Optional[str]noNoneinferred from implementation.
red_source_band6Optional[str]noNoneinferred from implementation.
resample_typestrno'None'inferred from implementation.
upsamplingstrno'Nearest'inferred from implementation.
output_nameOptional[str]noNoneinferred from implementation.

Return Type

Optional[str]

inferred from implementation.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.s2rep()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.

GPT.spectral_angle_mapper method

Classify the product using the Spectral Angle Mapper operator.

File location: sarpyx/snapflow/engine.py:1205

Signature

spectral_angle_mapper(self, reference_bands: Optional[List[str]]=None, thresholds: str='0.0', spectra: Optional[List[str]]=None, hidden_spectra: Optional[List[str]]=None, resample_type: str='None', upsampling: str='Nearest', downsampling: str='First', output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
reference_bandsOptional[List[str]]noNoneinferred from implementation.
thresholdsstrno'0.0'inferred from implementation.
spectraOptional[List[str]]noNoneinferred from implementation.
hidden_spectraOptional[List[str]]noNoneinferred from implementation.
resample_typestrno'None'inferred from implementation.
upsamplingstrno'Nearest'inferred from implementation.
downsamplingstrno'First'inferred from implementation.
output_nameOptional[str]noNoneinferred from implementation.

Return Type

Optional[str]

inferred from implementation.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.spectral_angle_mapper()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.

GPT.speckle_filter method

Apply the Speckle-Filter operator with configurable parameters.

File location: sarpyx/snapflow/engine.py:1238

Signature

speckle_filter(self, source_bands: Optional[List[str]]=None, filter_type: str='Lee Sigma', filter_size_x: int=3, filter_size_y: int=3, damping_factor: int=2, en_l: float=1.0, estimate_enl: bool=False, num_looks_str: str='1', sigma_str: str='0.9', window_size: str='7x7', target_window_size_str: str='3x3', an_size: int=50, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
source_bandsOptional[List[str]]noNoneinferred from implementation.
filter_typestrno'Lee Sigma'inferred from implementation.
filter_size_xintno3inferred from implementation.
filter_size_yintno3inferred from implementation.
damping_factorintno2inferred from implementation.
en_lfloatno1.0inferred from implementation.
estimate_enlboolnoFalseinferred from implementation.
num_looks_strstrno'1'inferred from implementation.
sigma_strstrno'0.9'inferred from implementation.
window_sizestrno'7x7'inferred from implementation.
target_window_size_strstrno'3x3'inferred from implementation.
an_sizeintno50inferred from implementation.
output_nameOptional[str]noNoneinferred from implementation.

Return Type

Optional[str]

inferred from implementation.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.speckle_filter()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.

GPT.speckle_divergence method

Generate urban-area detection via the Speckle-Divergence operator.

File location: sarpyx/snapflow/engine.py:1277

Signature

speckle_divergence(self, source_bands: Optional[List[str]]=None, window_size_str: str='15x15', output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
source_bandsOptional[List[str]]noNoneinferred from implementation.
window_size_strstrno'15x15'inferred from implementation.
output_nameOptional[str]noNoneinferred from implementation.

Return Type

Optional[str]

inferred from implementation.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.speckle_divergence()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.

GPT.snaphu_import method

Import Snaphu results into the product via SnaphuImport.

File location: sarpyx/snapflow/engine.py:1296

Signature

snaphu_import(self, source_products: Optional[List[str | Path]]=None, do_not_keep_wrapped: bool=False, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
source_productsOptional[List[str | Path]]noNoneinferred from implementation.
do_not_keep_wrappedboolnoFalseinferred from implementation.
output_nameOptional[str]noNoneinferred from implementation.

Return Type

Optional[str]

inferred from implementation.

Exceptions

  • ValueError

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.snaphu_import()

Edge Cases

May raise: ValueError. Includes optional parameters with implementation-defined fallback behavior.

GPT.aatsr_sst method

Compute sea surface temperature (SST) from (A)ATSR products.

File location: sarpyx/snapflow/engine.py:1320

Signature

aatsr_sst(self, dual: bool=True, dual_coefficients_file: str='AVERAGE_POLAR_DUAL_VIEW', dual_mask_expression: str='!cloud_flags_nadir.LAND and !cloud_flags_nadir.CLOUDY and !cloud_flags_nadir.SUN_GLINT and !cloud_flags_fward.LAND and !cloud_flags_fward.CLOUDY and !cloud_flags_fward.SUN_GLINT', invalid_sst_value: float=-999.0, nadir: bool=True, nadir_coefficients_file: str='AVERAGE_POLAR_SINGLE_VIEW', nadir_mask_expression: str='!cloud_flags_nadir.LAND and !cloud_flags_nadir.CLOUDY and !cloud_flags_nadir.SUN_GLINT', output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
dualboolnoTrueEnable dual-view SST processing.
dual_coefficients_filestrno'AVERAGE_POLAR_DUAL_VIEW'Coefficients file for dual-view processing.
dual_mask_expressionstrno'!cloud_flags_nadir.LAND and !cloud_flags_nadir.CLOUDY and !cloud_flags_nadir.SUN_GLINT and !cloud_flags_fward.LAND and !cloud_flags_fward.CLOUDY and !cloud_flags_fward.SUN_GLINT'Mask expression for dual-view processing.
invalid_sst_valuefloatno-999.0Value assigned to invalid SST pixels.
nadirboolnoTrueEnable nadir-view SST processing.
nadir_coefficients_filestrno'AVERAGE_POLAR_SINGLE_VIEW'Coefficients file for nadir-view processing.
nadir_mask_expressionstrno'!cloud_flags_nadir.LAND and !cloud_flags_nadir.CLOUDY and !cloud_flags_nadir.SUN_GLINT'Mask expression for nadir-view processing.
output_nameOptional[str]noNoneCustom output filename (without extension).

Return Type

Optional[str]

Path to SST output product, or None if failed.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.aatsr_sst()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior. Documented return may be None for some execution paths.

GPT.aatsr_ungrid method

Ungrid (A)ATSR L1B products and extract geolocation and pixel field of view data.

File location: sarpyx/snapflow/engine.py:1371

Signature

aatsr_ungrid(self, l1b_characterisation_file: Optional[str | Path]=None, corner_reference_flag: bool=True, topographic_flag: bool=False, topography_homogenity: float=0.05, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
l1b_characterisation_fileOptional[str | Path]noNoneL1B characterisation file needed to specify first forward pixel and first nadir pixel.
corner_reference_flagboolnoTrueChoose pixel coordinate reference point for output file. True for corner (default), False for centre.
topographic_flagboolnoFalseApply topographic corrections to tie points.
topography_homogenityfloatno0.05Distance (image coordinates) pixel can be from tie-point to have topographic correction applied.
output_nameOptional[str]noNoneCustom output filename (without extension).

Return Type

Optional[str]

Path to ungridded output product, or None if failed.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.aatsr_ungrid()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior. Documented return may be None for some execution paths.

GPT.smac_op method

Run the SmacOp atmospheric correction operator.

File location: sarpyx/snapflow/engine.py:1412

Signature

smac_op(self, aerosol_type: str, band_names: List[str], invalid_pixel: float=0.0, mask_expression: Optional[str]=None, mask_expression_forward: Optional[str]=None, surf_press: float=1013.0, tau_aero550: float=0.2, u_h2o: float=3.0, u_o3: float=0.15, use_meris_ads: bool=False, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
aerosol_typestryes-inferred from implementation.
band_namesList[str]yes-inferred from implementation.
invalid_pixelfloatno0.0inferred from implementation.
mask_expressionOptional[str]noNoneinferred from implementation.
mask_expression_forwardOptional[str]noNoneinferred from implementation.
surf_pressfloatno1013.0inferred from implementation.
tau_aero550floatno0.2inferred from implementation.
u_h2ofloatno3.0inferred from implementation.
u_o3floatno0.15inferred from implementation.
use_meris_adsboolnoFalseinferred from implementation.
output_nameOptional[str]noNoneinferred from implementation.

Return Type

Optional[str]

inferred from implementation.

Exceptions

  • ValueError

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.smac_op(aerosol_type=<aerosol_type>, band_names=<band_names>)

Edge Cases

May raise: ValueError. Includes optional parameters with implementation-defined fallback behavior.

GPT.sm_dielectric_modeling method

Perform soil moisture inversion using the dielectric model.

File location: sarpyx/snapflow/engine.py:1451

Signature

sm_dielectric_modeling(self, source_products: Optional[List[str | Path]]=None, effective_soil_temperature: float=18.0, max_sm: float=0.55, min_sm: float=0.0, model_to_use: str='Hallikainen', output_land_cover: bool=True, output_rdc: bool=True, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
source_productsOptional[List[str | Path]]noNoneinferred from implementation.
effective_soil_temperaturefloatno18.0inferred from implementation.
max_smfloatno0.55inferred from implementation.
min_smfloatno0.0inferred from implementation.
model_to_usestrno'Hallikainen'inferred from implementation.
output_land_coverboolnoTrueinferred from implementation.
output_rdcboolnoTrueinferred from implementation.
output_nameOptional[str]noNoneinferred from implementation.

Return Type

Optional[str]

inferred from implementation.

Exceptions

  • ValueError

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.sm_dielectric_modeling()

Edge Cases

May raise: ValueError. Includes optional parameters with implementation-defined fallback behavior.

GPT.slice_assembly method

Merge Sentinel-1 slice products using the SliceAssembly operator.

File location: sarpyx/snapflow/engine.py:1487

Signature

slice_assembly(self, source_products: Optional[List[str | Path]]=None, selected_polarisations: Optional[List[str]]=None, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
source_productsOptional[List[str | Path]]noNoneinferred from implementation.
selected_polarisationsOptional[List[str]]noNoneinferred from implementation.
output_nameOptional[str]noNoneinferred from implementation.

Return Type

Optional[str]

inferred from implementation.

Exceptions

  • ValueError

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.slice_assembly()

Edge Cases

May raise: ValueError. Includes optional parameters with implementation-defined fallback behavior.

GPT.wind_field_estimation method

Estimate wind speed and direction from SAR imagery.

File location: sarpyx/snapflow/engine.py:1513

Signature

wind_field_estimation(self, source_bands: Optional[List[str]]=None, window_size_in_km: float=20.0, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
source_bandsOptional[List[str]]noNoneList of source bands to use for wind estimation. If None, all available bands are used.
window_size_in_kmfloatno20.0Window size for wind estimation in kilometers.
output_nameOptional[str]noNoneCustom output filename (without extension).

Return Type

Optional[str]

Path to wind field output product, or None if failed.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.wind_field_estimation()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior. Documented return may be None for some execution paths.

GPT.wdvi method

Compute Weighted Difference Vegetation Index (WDVI).

File location: sarpyx/snapflow/engine.py:1543

Signature

wdvi(self, red_source_band: Optional[str]=None, nir_source_band: Optional[str]=None, red_factor: float=1.0, nir_factor: float=1.0, slope_soil_line: float=1.5, resample_type: str='None', upsampling: str='Nearest', downsampling: str='First', output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
red_source_bandOptional[str]noNoneThe red band for WDVI computation. If None, operator will try to find the best fitting band.
nir_source_bandOptional[str]noNoneThe near-infrared band for WDVI computation. If None, operator will try to find the best fitting band.
red_factorfloatno1.0Multiplication factor for red band values.
nir_factorfloatno1.0Multiplication factor for NIR band values.
slope_soil_linefloatno1.5Slope of the soil line passing through origin.
resample_typestrno'None'Resample method if bands differ in size. Must be one of 'None', 'Lowest resolution', 'Highest resolution'.
upsamplingstrno'Nearest'Interpolation method for upsampling to finer resolution. Must be one of 'Nearest', 'Bilinear', 'Bicubic'.
downsamplingstrno'First'Aggregation method for downsampling to coarser resolution. Must be one of 'First', 'Min', 'Max', 'Mean', 'Median'.
output_nameOptional[str]noNoneCustom output filename (without extension).

Return Type

Optional[str]

Path to WDVI output product, or None if failed.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.wdvi()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior. Documented return may be None for some execution paths.

GPT.savi method

Compute the Soil Adjusted Vegetation Index (SAVI).

File location: sarpyx/snapflow/engine.py:1600

Signature

savi(self, red_source_band: Optional[str]=None, nir_source_band: Optional[str]=None, red_factor: float=1.0, nir_factor: float=1.0, soil_correction_factor: float=0.5, resample_type: str='None', upsampling: str='Nearest', downsampling: str='First', output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
red_source_bandOptional[str]noNoneinferred from implementation.
nir_source_bandOptional[str]noNoneinferred from implementation.
red_factorfloatno1.0inferred from implementation.
nir_factorfloatno1.0inferred from implementation.
soil_correction_factorfloatno0.5inferred from implementation.
resample_typestrno'None'inferred from implementation.
upsamplingstrno'Nearest'inferred from implementation.
downsamplingstrno'First'inferred from implementation.
output_nameOptional[str]noNoneinferred from implementation.

Return Type

Optional[str]

inferred from implementation.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.savi()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.

GPT.warp method

Create warp function and get co-registered images.

File location: sarpyx/snapflow/engine.py:1632

Signature

warp(self, rms_threshold: float=0.05, warp_polynomial_order: int=2, interpolation_method: str='Cubic convolution (6 points)', dem_refinement: bool=False, dem_name: str='SRTM 3Sec', exclude_master: bool=False, open_residuals_file: bool=False, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
rms_thresholdfloatno0.05Confidence level for outlier detection procedure. Lower value accepts more outliers. Must be one of 0.001, 0.05, 0.1, 0.5, 1.0.
warp_polynomial_orderintno2The order of WARP polynomial function. Must be one of 1, 2, or 3.
interpolation_methodstrno'Cubic convolution (6 points)'Interpolation method for resampling. Must be one of 'Nearest-neighbor interpolation', 'Bilinear interpolation', 'Bicubic interpolation', 'Bicubic2 interpolation', 'Linear interpolation', 'Cubic convolution (4 points)', 'Cubic convolution (6 points)', 'Truncated sinc (6 points)', 'Truncated sinc (8 points)', 'Truncated sinc (16 points)'.
dem_refinementboolnoFalseRefine estimated offsets using a-priori DEM.
dem_namestrno'SRTM 3Sec'The digital elevation model to use.
exclude_masterboolnoFalseWhether to exclude the master image from output.
open_residuals_fileboolnoFalseShow the residuals file in a text viewer.
output_nameOptional[str]noNoneCustom output filename (without extension).

Return Type

Optional[str]

Path to warped output product, or None if failed.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.warp()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior. Documented return may be None for some execution paths.

GPT.srgr method

Convert slant range to ground range using SRGR operator.

File location: sarpyx/snapflow/engine.py:1684

Signature

srgr(self, source_bands: Optional[List[str]]=None, interpolation_method: str='Linear interpolation', warp_polynomial_order: int=4, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
source_bandsOptional[List[str]]noNoneinferred from implementation.
interpolation_methodstrno'Linear interpolation'inferred from implementation.
warp_polynomial_orderintno4inferred from implementation.
output_nameOptional[str]noNoneinferred from implementation.

Return Type

Optional[str]

inferred from implementation.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.srgr()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.

GPT.update_geo_reference method

Update geo-reference information in the product.

File location: sarpyx/snapflow/engine.py:1705

Signature

update_geo_reference(self, source_bands: Optional[List[str]]=None, dem_name: str='SRTM 3Sec', dem_resampling_method: str='BICUBIC_INTERPOLATION', external_dem_file: Optional[str | Path]=None, external_dem_no_data_value: float=0.0, re_grid_method: bool=False, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
source_bandsOptional[List[str]]noNoneList of source bands to process. If None, all bands are processed.
dem_namestrno'SRTM 3Sec'The digital elevation model to use. Must be one of 'ACE', 'ASTER 1sec GDEM', 'GETASSE30', 'SRTM 1Sec HGT', 'SRTM 3Sec'.
dem_resampling_methodstrno'BICUBIC_INTERPOLATION'DEM resampling method.
external_dem_fileOptional[str | Path]noNonePath to external DEM file.
external_dem_no_data_valuefloatno0.0No data value for external DEM.
re_grid_methodboolnoFalseApply re-gridding method.
output_nameOptional[str]noNoneCustom output filename (without extension).

Return Type

Optional[str]

Path to output product with updated geo-reference, or None if failed.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.update_geo_reference()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior. Documented return may be None for some execution paths.

GPT.add_elevation method

Add a DEM elevation band to the product.

File location: sarpyx/snapflow/engine.py:1752

Signature

add_elevation(self, dem_name: str='SRTM 3Sec', dem_resampling_method: str='BICUBIC_INTERPOLATION', elevation_band_name: str='elevation', external_dem_file: Optional[str | Path]=None, external_dem_no_data_value: float=0.0, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
dem_namestrno'SRTM 3Sec'The digital elevation model to use. Must be one of 'ACE', 'ASTER 1sec GDEM', 'GETASSE30', 'SRTM 1Sec HGT', 'SRTM 3Sec'.
dem_resampling_methodstrno'BICUBIC_INTERPOLATION'DEM resampling method.
elevation_band_namestrno'elevation'Name of the elevation band.
external_dem_fileOptional[str | Path]noNonePath to external DEM file.
external_dem_no_data_valuefloatno0.0No data value for external DEM.
output_nameOptional[str]noNoneCustom output filename (without extension).

Return Type

Optional[str]

Path to output product with elevation band, or None if failed.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.add_elevation()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior. Documented return may be None for some execution paths.

GPT.three_pass_dinsar method

Perform three-pass differential interferometry.

File location: sarpyx/snapflow/engine.py:1794

Signature

three_pass_dinsar(self, source_products: Optional[List[str | Path]]=None, orbit_degree: int=3, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
source_productsOptional[List[str | Path]]noNoneSource product paths. If None, uses the current product.
orbit_degreeintno3Degree of orbit interpolation polynomial. Valid interval is (1, 10].
output_nameOptional[str]noNoneCustom output filename (without extension).

Return Type

Optional[str]

Path to output product, or None if failed.

Exceptions

  • ValueError

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.three_pass_dinsar()

Edge Cases

May raise: ValueError. Includes optional parameters with implementation-defined fallback behavior. Documented return may be None for some execution paths.

GPT.unmix method

Perform linear spectral unmixing.

File location: sarpyx/snapflow/engine.py:1827

Signature

unmix(self, source_bands: Optional[List[str]]=None, endmember_file: Optional[str | Path]=None, unmixing_model_name: str='Constrained LSU', abundance_band_name_suffix: str='_abundance', error_band_name_suffix: str='_error', compute_error_bands: bool=False, min_bandwidth: float=10.0, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
source_bandsOptional[List[str]]noNoneList of spectral bands providing the source spectrum. If None, all bands are used.
endmember_fileOptional[str | Path]noNoneText file containing endmembers in a table. Wavelengths must be given in nanometers.
unmixing_model_namestrno'Constrained LSU'The unmixing model to use. Must be one of 'Unconstrained LSU', 'Constrained LSU', 'Fully Constrained LSU'.
abundance_band_name_suffixstrno'_abundance'Suffix for generated abundance band names (name = endmember + suffix). Must match pattern '[a-zA-Z_0-9]*'.
error_band_name_suffixstrno'_error'Suffix for generated error band names (name = source + suffix). Must match pattern '[a-zA-Z_0-9]*'.
compute_error_bandsboolnoFalseGenerate error bands for all source bands.
min_bandwidthfloatno10.0Minimum spectral bandwidth for endmember wavelength matching in nanometers. Must be greater than 0.
output_nameOptional[str]noNoneCustom output filename (without extension).

Return Type

Optional[str]

Path to unmixed output product, or None if failed.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.unmix()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior. Documented return may be None for some execution paths.

GPT.undersample method

Undersample the dataset by reducing spatial resolution.

File location: sarpyx/snapflow/engine.py:1882

Signature

undersample(self, source_bands: Optional[List[str]]=None, method: str='LowPass Filtering', filter_size: str='3x3', sub_sampling_x: int=2, sub_sampling_y: int=2, output_image_by: str='Ratio', target_image_height: int=1000, target_image_width: int=1000, width_ratio: float=0.5, height_ratio: float=0.5, range_spacing: float=12.5, azimuth_spacing: float=12.5, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
source_bandsOptional[List[str]]noNoneList of source bands to undersample. If None, all bands are processed.
methodstrno'LowPass Filtering'Undersampling method to use. Must be one of 'Sub-Sampling', 'LowPass Filtering'.
filter_sizestrno'3x3'Filter size for low-pass filtering. Must be one of '3x3', '5x5', '7x7'.
sub_sampling_xintno2Sub-sampling factor in X direction.
sub_sampling_yintno2Sub-sampling factor in Y direction.
output_image_bystrno'Ratio'Method to determine output image size. Must be one of 'Image Size', 'Ratio', 'Pixel Spacing'.
target_image_heightintno1000Row dimension of output image (pixels).
target_image_widthintno1000Column dimension of output image (pixels).
width_ratiofloatno0.5Width ratio of output/input images.
height_ratiofloatno0.5Height ratio of output/input images.
range_spacingfloatno12.5Range pixel spacing in meters.
azimuth_spacingfloatno12.5Azimuth pixel spacing in meters.
output_nameOptional[str]noNoneCustom output filename (without extension).

Return Type

Optional[str]

Path to undersampled output product, or None if failed.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.undersample()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior. Documented return may be None for some execution paths.

GPT.tsavi method

Compute Transformed Soil Adjusted Vegetation Index (TSAVI).

File location: sarpyx/snapflow/engine.py:1947

Signature

tsavi(self, red_source_band: Optional[str]=None, nir_source_band: Optional[str]=None, red_factor: float=1.0, nir_factor: float=1.0, slope: float=0.5, intercept: float=0.5, adjustment: float=0.08, resample_type: str='None', upsampling: str='Nearest', downsampling: str='First', output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
red_source_bandOptional[str]noNoneThe red band for TSAVI computation. If None, operator will try to find the best fitting band.
nir_source_bandOptional[str]noNoneThe near-infrared band for TSAVI computation. If None, operator will try to find the best fitting band.
red_factorfloatno1.0Multiplication factor for red band values.
nir_factorfloatno1.0Multiplication factor for NIR band values.
slopefloatno0.5The soil line slope.
interceptfloatno0.5The soil line intercept.
adjustmentfloatno0.08Adjustment factor to minimize soil background.
resample_typestrno'None'Resample method if bands differ in size. Must be one of 'None', 'Lowest resolution', 'Highest resolution'.
upsamplingstrno'Nearest'Interpolation method for upsampling to finer resolution. Must be one of 'Nearest', 'Bilinear', 'Bicubic'.
downsamplingstrno'First'Aggregation method for downsampling to coarser resolution. Must be one of 'First', 'Min', 'Max', 'Mean', 'Median'.
output_nameOptional[str]noNoneCustom output filename (without extension).

Return Type

Optional[str]

Path to TSAVI output product, or None if failed.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.tsavi()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior. Documented return may be None for some execution paths.

GPT.tndvi method

Compute Transformed Normalized Difference Vegetation Index (TNDVI).

File location: sarpyx/snapflow/engine.py:2010

Signature

tndvi(self, red_source_band: Optional[str]=None, nir_source_band: Optional[str]=None, red_factor: float=1.0, nir_factor: float=1.0, resample_type: str='None', upsampling: str='Nearest', downsampling: str='First', output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
red_source_bandOptional[str]noNoneThe red band for TNDVI computation. If None, operator will try to find the best fitting band.
nir_source_bandOptional[str]noNoneThe near-infrared band for TNDVI computation. If None, operator will try to find the best fitting band.
red_factorfloatno1.0Multiplication factor for red band values.
nir_factorfloatno1.0Multiplication factor for NIR band values.
resample_typestrno'None'Resample method if bands differ in size. Must be one of 'None', 'Lowest resolution', 'Highest resolution'.
upsamplingstrno'Nearest'Interpolation method for upsampling to finer resolution. Must be one of 'Nearest', 'Bilinear', 'Bicubic'.
downsamplingstrno'First'Aggregation method for downsampling to coarser resolution. Must be one of 'First', 'Min', 'Max', 'Mean', 'Median'.
output_nameOptional[str]noNoneCustom output filename (without extension).

Return Type

Optional[str]

Path to TNDVI output product, or None if failed.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.tndvi()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior. Documented return may be None for some execution paths.

GPT.topsar_split method

Create a new product with only the selected subswath.

File location: sarpyx/snapflow/engine.py:2063

Signature

topsar_split(self, subswath: Optional[str]=None, selected_polarisations: Optional[List[str]]=None, first_burst_index: int=1, last_burst_index: int=9999, wkt_aoi: Optional[str]=None, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
subswathOptional[str]noNoneThe subswath to select (e.g., 'IW1', 'IW2', 'IW3'). If None, all subswaths are included.
selected_polarisationsOptional[List[str]]noNoneList of polarisations to include. If None, all polarisations are included.
first_burst_indexintno1The first burst index to include (1-based). Must be >= 1.
last_burst_indexintno9999The last burst index to include (1-based). Must be >= 1.
wkt_aoiOptional[str]noNoneWKT polygon to be used for selecting bursts.
output_nameOptional[str]noNoneCustom output filename (without extension).

Return Type

Optional[str]

Path to split output product, or None if failed.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.topsar_split()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior. Documented return may be None for some execution paths.

GPT.topsar_merge method

Merge subswaths of a Sentinel-1 TOPSAR product.

File location: sarpyx/snapflow/engine.py:2111

Signature

topsar_merge(self, selected_polarisations: Optional[List[str]]=None, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
selected_polarisationsOptional[List[str]]noNoneList of polarisations to merge. If None, all polarisations are merged.
output_nameOptional[str]noNoneCustom output filename (without extension).

Return Type

Optional[str]

Path to merged output product, or None if failed.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.topsar_merge()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior. Documented return may be None for some execution paths.

GPT.topsar_deramp_demod method

Perform deramp and demodulation for TOPSAR burst co-registration.

File location: sarpyx/snapflow/engine.py:2139

Signature

topsar_deramp_demod(self, output_deramp_demod_phase: bool=True, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
output_deramp_demod_phaseboolnoTrueOutput the deramp/demod phase.
output_nameOptional[str]noNoneCustom output filename (without extension).

Return Type

Optional[str]

Path to deramp/demod output product, or None if failed.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.topsar_deramp_demod()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior. Documented return may be None for some execution paths.

GPT.topo_phase_removal method

Compute and subtract topographic phase from interferogram.

File location: sarpyx/snapflow/engine.py:2164

Signature

topo_phase_removal(self, orbit_degree: int=3, dem_name: str='SRTM 3Sec', external_dem_file: Optional[str | Path]=None, external_dem_no_data_value: float=0.0, tile_extension_percent: str='100', output_topo_phase_band: bool=False, output_elevation_band: bool=False, output_lat_lon_bands: bool=False, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
orbit_degreeintno3Degree of orbit interpolation polynomial. Must be in range (1, 10].
dem_namestrno'SRTM 3Sec'The digital elevation model to use.
external_dem_fileOptional[str | Path]noNonePath to external DEM file.
external_dem_no_data_valuefloatno0.0No data value for external DEM.
tile_extension_percentstrno'100'Extension of tile for DEM simulation (optimization parameter).
output_topo_phase_bandboolnoFalseOutput topographic phase band.
output_elevation_bandboolnoFalseOutput elevation band.
output_lat_lon_bandsboolnoFalseOutput latitude/longitude bands.
output_nameOptional[str]noNoneCustom output filename (without extension).

Return Type

Optional[str]

Path to output product with topographic phase removed, or None if failed.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.topo_phase_removal()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior. Documented return may be None for some execution paths.

GPT.tool_adapter method

Execute a custom tool adapter operator.

File location: sarpyx/snapflow/engine.py:2215

Signature

tool_adapter(self, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
output_nameOptional[str]noNoneCustom output filename (without extension).

Return Type

Optional[str]

Path to tool adapter output product, or None if failed.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.tool_adapter()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior. Documented return may be None for some execution paths.

GPT.apply_orbit_file method

Apply orbit file correction to SAR products.

File location: sarpyx/snapflow/engine.py:2239

Signature

apply_orbit_file(self, orbit_type: str='Sentinel Precise (Auto Download)', poly_degree: int=3, continue_on_fail: bool=False, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
orbit_typestrno'Sentinel Precise (Auto Download)'Type of orbit file to apply. Valid options include 'Sentinel Precise (Auto Download)', 'Sentinel Restituted (Auto Download)', etc.
poly_degreeintno3Degree of polynomial for orbit interpolation.
continue_on_failboolnoFalseContinue processing if orbit file application fails.
output_nameOptional[str]noNoneCustom output filename (without extension).

Return Type

Optional[str]

Path to the output product with applied orbit file, or None if failed.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.apply_orbit_file()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior. Documented return may be None for some execution paths.

GPT.terrain_correction method

Apply terrain correction (orthorectification) using Range-Doppler method.

File location: sarpyx/snapflow/engine.py:2271

Signature

terrain_correction(self, source_bands: Optional[List[str]]=None, dem_name: str='Copernicus 30m Global DEM', external_dem_file: Optional[str | Path]=None, external_dem_no_data_value: float=0.0, external_dem_apply_egm: bool=True, dem_resampling_method: str='BILINEAR_INTERPOLATION', img_resampling_method: str='BISINC_21_POINT_INTERPOLATION', pixel_spacing_in_meter: float=0.0, pixel_spacing_in_degree: float=0.0, map_projection: str='WGS84(DD)', align_to_standard_grid: bool=False, standard_grid_origin_x: float=0.0, standard_grid_origin_y: float=0.0, nodata_value_at_sea: bool=False, save_dem: bool=True, save_lat_lon: bool=False, save_incidence_angle_from_ellipsoid: bool=False, save_local_incidence_angle: bool=True, save_projected_local_incidence_angle: bool=False, save_selected_source_band: bool=True, save_layover_shadow_mask: bool=False, output_complex: bool=True, apply_radiometric_normalization: bool=False, save_sigma_nought: bool=False, save_gamma_nought: bool=False, save_beta_nought: bool=False, incidence_angle_for_sigma0: str='Use projected local incidence angle from DEM', incidence_angle_for_gamma0: str='Use projected local incidence angle from DEM', aux_file: str='Latest Auxiliary File', external_aux_file: Optional[str | Path]=None, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
source_bandsOptional[List[str]]noNoneList of source bands to process. If None, all bands are processed.
dem_namestrno'Copernicus 30m Global DEM'Digital elevation model name. (CDEM, SRTM 3Sec, Copernicus 30m Global DEM, ...)
external_dem_fileOptional[str | Path]noNonePath to external DEM file.
external_dem_no_data_valuefloatno0.0No data value for external DEM.
external_dem_apply_egmboolnoTrueApply EGM96 geoid to external DEM.
dem_resampling_methodstrno'BILINEAR_INTERPOLATION'DEM resampling method.
img_resampling_methodstrno'BISINC_21_POINT_INTERPOLATION'Image resampling method.
pixel_spacing_in_meterfloatno0.0Output pixel spacing in meters (0 = automatic).
pixel_spacing_in_degreefloatno0.0Output pixel spacing in degrees (0 = automatic).
map_projectionstrno'WGS84(DD)'Map projection in WKT format.
align_to_standard_gridboolnoFalseAlign output to standard grid.
standard_grid_origin_xfloatno0.0X-coordinate of standard grid origin.
standard_grid_origin_yfloatno0.0Y-coordinate of standard grid origin.
nodata_value_at_seaboolnoFalseMask sea areas with no data value.
save_demboolnoTrueSave DEM band in output.
save_lat_lonboolnoFalseSave latitude/longitude bands.
save_incidence_angle_from_ellipsoidboolnoFalseSave incidence angle from ellipsoid.
save_local_incidence_angleboolnoTrueSave local incidence angle.
save_projected_local_incidence_angleboolnoFalseSave projected local incidence angle.
save_selected_source_bandboolnoTrueSave selected source bands.
save_layover_shadow_maskboolnoFalseSave layover/shadow mask.
output_complexboolnoTrueOutput complex data.
apply_radiometric_normalizationboolnoFalseApply radiometric normalization.
save_sigma_noughtboolnoFalseSave sigma nought band.
save_gamma_noughtboolnoFalseSave gamma nought band.
save_beta_noughtboolnoFalseSave beta nought band.
incidence_angle_for_sigma0strno'Use projected local incidence angle from DEM'Incidence angle type for sigma0.
incidence_angle_for_gamma0strno'Use projected local incidence angle from DEM'Incidence angle type for gamma0.
aux_filestrno'Latest Auxiliary File'Auxiliary file selection.
external_aux_fileOptional[str | Path]noNonePath to external auxiliary file.
output_nameOptional[str]noNoneCustom output filename (without extension).

Return Type

Optional[str]

Path to the terrain-corrected output product, or None if failed.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.terrain_correction()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior. Documented return may be None for some execution paths.

GPT.sar_sim_terrain_correction method

Orthorectify the product using SARSim Terrain Correction.

File location: sarpyx/snapflow/engine.py:2390

Signature

sar_sim_terrain_correction(self, map_projection: str='WGS84(DD)', img_resampling_method: str='BILINEAR_INTERPOLATION', pixel_spacing_in_meter: float=0.0, pixel_spacing_in_degree: float=0.0, align_to_standard_grid: bool=False, standard_grid_origin_x: float=0.0, standard_grid_origin_y: float=0.0, rms_threshold: float=1.0, warp_polynomial_order: int=1, apply_radiometric_normalization: bool=False, aux_file: str='Latest Auxiliary File', external_aux_file: Optional[str | Path]=None, open_shifts_file: bool=False, open_residuals_file: bool=False, output_complex: bool=False, save_dem: bool=False, save_lat_lon: bool=False, save_local_incidence_angle: bool=False, save_projected_local_incidence_angle: bool=False, save_selected_source_band: bool=True, save_sigma_nought: bool=False, save_gamma_nought: bool=False, save_beta_nought: bool=False, incidence_angle_for_sigma0: str='Use projected local incidence angle from DEM', incidence_angle_for_gamma0: str='Use projected local incidence angle from DEM', output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
map_projectionstrno'WGS84(DD)'inferred from implementation.
img_resampling_methodstrno'BILINEAR_INTERPOLATION'inferred from implementation.
pixel_spacing_in_meterfloatno0.0inferred from implementation.
pixel_spacing_in_degreefloatno0.0inferred from implementation.
align_to_standard_gridboolnoFalseinferred from implementation.
standard_grid_origin_xfloatno0.0inferred from implementation.
standard_grid_origin_yfloatno0.0inferred from implementation.
rms_thresholdfloatno1.0inferred from implementation.
warp_polynomial_orderintno1inferred from implementation.
apply_radiometric_normalizationboolnoFalseinferred from implementation.
aux_filestrno'Latest Auxiliary File'inferred from implementation.
external_aux_fileOptional[str | Path]noNoneinferred from implementation.
open_shifts_fileboolnoFalseinferred from implementation.
open_residuals_fileboolnoFalseinferred from implementation.
output_complexboolnoFalseinferred from implementation.
save_demboolnoFalseinferred from implementation.
save_lat_lonboolnoFalseinferred from implementation.
save_local_incidence_angleboolnoFalseinferred from implementation.
save_projected_local_incidence_angleboolnoFalseinferred from implementation.
save_selected_source_bandboolnoTrueinferred from implementation.
save_sigma_noughtboolnoFalseinferred from implementation.
save_gamma_noughtboolnoFalseinferred from implementation.
save_beta_noughtboolnoFalseinferred from implementation.
incidence_angle_for_sigma0strno'Use projected local incidence angle from DEM'inferred from implementation.
incidence_angle_for_gamma0strno'Use projected local incidence angle from DEM'inferred from implementation.
output_nameOptional[str]noNoneinferred from implementation.

Return Type

Optional[str]

inferred from implementation.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.sar_sim_terrain_correction()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.

GPT.sar_simulation method

Run the rigorous SAR Simulation operator.

File location: sarpyx/snapflow/engine.py:2455

Signature

sar_simulation(self, dem_name: str='SRTM 3Sec', dem_resampling_method: str='BICUBIC_INTERPOLATION', external_dem_apply_egm: bool=True, external_dem_file: Optional[str | Path]=None, external_dem_no_data_value: float=0.0, save_layover_shadow_mask: bool=False, source_bands: Optional[List[str]]=None, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
dem_namestrno'SRTM 3Sec'inferred from implementation.
dem_resampling_methodstrno'BICUBIC_INTERPOLATION'inferred from implementation.
external_dem_apply_egmboolnoTrueinferred from implementation.
external_dem_fileOptional[str | Path]noNoneinferred from implementation.
external_dem_no_data_valuefloatno0.0inferred from implementation.
save_layover_shadow_maskboolnoFalseinferred from implementation.
source_bandsOptional[List[str]]noNoneinferred from implementation.
output_nameOptional[str]noNoneinferred from implementation.

Return Type

Optional[str]

inferred from implementation.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.sar_simulation()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.

GPT.sar_mosaic method

Mosaic multiple SAR products with adjustable blending parameters.

File location: sarpyx/snapflow/engine.py:2486

Signature

sar_mosaic(self, source_bands: Optional[List[str]]=None, average: bool=True, convergence_threshold: float=0.0001, feather: int=0, gradient_domain_mosaic: bool=False, max_iterations: int=5000, normalize_by_mean: bool=True, pixel_size: float=0.0, presampling_method: str='NEAREST_NEIGHBOUR', scene_height: int=0, scene_width: int=0, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
source_bandsOptional[List[str]]noNoneinferred from implementation.
averageboolnoTrueinferred from implementation.
convergence_thresholdfloatno0.0001inferred from implementation.
featherintno0inferred from implementation.
gradient_domain_mosaicboolnoFalseinferred from implementation.
max_iterationsintno5000inferred from implementation.
normalize_by_meanboolnoTrueinferred from implementation.
pixel_sizefloatno0.0inferred from implementation.
presampling_methodstrno'NEAREST_NEIGHBOUR'inferred from implementation.
scene_heightintno0inferred from implementation.
scene_widthintno0inferred from implementation.
output_nameOptional[str]noNoneinferred from implementation.

Return Type

Optional[str]

inferred from implementation.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.sar_mosaic()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.

GPT.do_subaps method

Run sub-aperture decomposition on a SNAP DIM product.

File location: sarpyx/snapflow/engine.py:2523

Signature

do_subaps(self, dim_path: Optional[Union[str, Path]]=None, safe_path: Optional[Union[str, Path]]=None, numberofLooks: int=3, n_decompositions: Optional[Union[int, List[int]]]=None, DownSample: bool=True, byte_order: int=1, prefix: str='', VERBOSE: bool=False) -> Path

Parameters

ParameterTypeRequiredDefaultDescription
dim_pathOptional[Union[str, Path]]noNonePath or str, optional Path to the DIM product to process. If None, self.prod_path is used.
safe_pathOptional[Union[str, Path]]noNonePath or str Path to the original SAFE product (required by sub-aperture processing).
numberofLooksintno3int Number of looks used for azimuth bandwidth estimation.
n_decompositionsOptional[Union[int, List[int]]]noNoneint or list[int], optional Sub-aperture decomposition scheme (e.g. [2, 3]).
DownSampleboolnoTruebool Whether to downsample the output images.
byte_orderintno1int Byte order of output ENVI files (0=little endian, 1=big endian).
prefixstrno''str Prefix for generated band names.
VERBOSEboolnoFalsebool Verbose mode.

Return Type

Path

Path Path to the processed DIM product.

Exceptions

  • ValueError

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.do_subaps()

Edge Cases

May raise: ValueError. Includes optional parameters with implementation-defined fallback behavior. Documented return may be None for some execution paths.

GPT.demodulate method

Perform demodulation and deramping of SLC data.

File location: sarpyx/snapflow/engine.py:2592

Signature

demodulate(self, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
output_nameOptional[str]noNoneCustom output filename (without extension).

Return Type

Optional[str]

Path to the demodulated output product, or None if failed.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.demodulate()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior. Documented return may be None for some execution paths.

GPT.write method

Write a data product to a file with explicit control over write parameters.

File location: sarpyx/snapflow/engine.py:2613

Signature

write(self, output_file: Optional[str | Path]=None, format_name: Optional[str]=None, clear_cache_after_row_write: bool=False, delete_output_on_failure: bool=True, write_entire_tile_rows: bool=False) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
output_fileOptional[str | Path]noNoneThe output file path. If None, uses standard path construction.
format_nameOptional[str]noNoneThe output file format name. If None, uses the instance format.
clear_cache_after_row_writeboolnoFalseClear internal tile cache after a tile row has been written. Only effective if write_entire_tile_rows is True.
delete_output_on_failureboolnoTrueDelete all output files after a failed write operation.
write_entire_tile_rowsboolnoFalseWait until an entire tile row is computed before writing.

Return Type

Optional[str]

Path to the written output product, or None if failed.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.write()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior. Documented return may be None for some execution paths.

GPT.tile_writer method

Write a data product to tiles.

File location: sarpyx/snapflow/engine.py:2658

Signature

tile_writer(self, output_file: Optional[str | Path]=None, format_name: Optional[str]=None, division_by: str='Tiles', number_of_tiles: str='4', pixel_size_x: int=200, pixel_size_y: int=200, overlap: int=0, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
output_fileOptional[str | Path]noNoneThe output file path. If None, uses standard path construction.
format_nameOptional[str]noNoneThe output file format name. If None, uses the instance format.
division_bystrno'Tiles'How to divide the tiles. Must be one of 'Tiles', 'Pixels'.
number_of_tilesstrno'4'The number of output tiles. Must be one of '2', '4', '9', '16', '36', '64', '100', '256'.
pixel_size_xintno200Tile pixel width.
pixel_size_yintno200Tile pixel height.
overlapintno0Tile overlap in pixels.
output_nameOptional[str]noNoneCustom output filename (without extension).

Return Type

Optional[str]

Path to tiled output product, or None if failed.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.tile_writer()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior. Documented return may be None for some execution paths.

GPT.band_maths method

inferred from implementation.

File location: sarpyx/snapflow/engine.py:2752

Signature

band_maths(self, target_bands=None, variables=None, output_name=None)

Parameters

ParameterTypeRequiredDefaultDescription
target_bandsinferred from implementationnoNoneinferred from implementation.
variablesinferred from implementationnoNoneinferred from implementation.
output_nameinferred from implementationnoNoneinferred from implementation.

Return Type

inferred from implementation

inferred from implementation.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.band_maths()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.

GPT.band_select method

Creates a new product with only selected bands.

File location: sarpyx/snapflow/engine.py:2766

Signature

band_select(self, source_bands: Optional[List[str]]=None, band_name_pattern: Optional[str]=None, selected_polarisations: Optional[List[str]]=None, selected_sub_images: Optional[List[str]]=None, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
source_bandsOptional[List[str]]noNoneList of source band names to include.
band_name_patternOptional[str]noNoneBand name regular expression pattern.
selected_polarisationsOptional[List[str]]noNoneList of polarisations to select.
selected_sub_imagesOptional[List[str]]noNoneList of imagettes or sub-images to select.
output_nameOptional[str]noNoneCustom output filename (without extension).

Return Type

Optional[str]

Path to output product with selected bands, or None if failed.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.band_select()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior. Documented return may be None for some execution paths.

GPT.band_merge method

Allows copying raster data from any number of source products to a specified 'master' product.

File location: sarpyx/snapflow/engine.py:2808

Signature

band_merge(self, source_products: Optional[List[str | Path]]=None, source_bands: Optional[List[str]]=None, geographic_error: float=1e-05, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
source_productsOptional[List[str | Path]]noNoneList of source product paths.
source_bandsOptional[List[str]]noNoneList of source band names.
geographic_errorfloatno1e-05Maximum lat/lon error in degrees between products.
output_nameOptional[str]noNoneCustom output filename (without extension).

Return Type

Optional[str]

Path to merged output product, or None if failed.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.band_merge()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior. Documented return may be None for some execution paths.

GPT.coherence method

Estimate coherence from stack of coregistered images.

File location: sarpyx/snapflow/engine.py:2839

Signature

coherence(self, coh_win_az: int=10, coh_win_rg: int=10, subtract_flat_earth_phase: bool=False, srp_polynomial_degree: int=5, srp_number_points: int=501, orbit_degree: int=3, square_pixel: bool=True, subtract_topographic_phase: bool=False, dem_name: str='SRTM 3Sec', external_dem_file: Optional[str | Path]=None, external_dem_no_data_value: float=0.0, external_dem_apply_egm: bool=True, tile_extension_percent: str='100', single_master: bool=True, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
coh_win_azintno10Size of coherence estimation window in Azimuth direction. Valid interval is (1, 90].
coh_win_rgintno10Size of coherence estimation window in Range direction. Valid interval is (1, 90].
subtract_flat_earth_phaseboolnoFalseSubtract flat earth phase.
srp_polynomial_degreeintno5Order of 'Flat earth phase' polynomial. Must be one of 1, 2, 3, 4, 5, 6, 7, 8.
srp_number_pointsintno501Number of points for the 'flat earth phase' polynomial estimation. Must be one of 301, 401, 501, 601, 701, 801, 901, 1001.
orbit_degreeintno3Degree of orbit (polynomial) interpolator. Must be one of 1, 2, 3, 4, 5.
square_pixelboolnoTrueUse ground square pixel.
subtract_topographic_phaseboolnoFalseSubtract topographic phase.
dem_namestrno'SRTM 3Sec'The digital elevation model.
external_dem_fileOptional[str | Path]noNonePath to external DEM file.
external_dem_no_data_valuefloatno0.0No data value for external DEM.
external_dem_apply_egmboolnoTrueApply EGM96 geoid to external DEM.
tile_extension_percentstrno'100'Define extension of tile for DEM simulation.
single_masterboolnoTrueSingle master mode.
output_nameOptional[str]noNoneCustom output filename (without extension).

Return Type

Optional[str]

Path to coherence output product, or None if failed.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.coherence()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior. Documented return may be None for some execution paths.

GPT.interferogram method

Compute interferograms from stack of coregistered S-1 images.

File location: sarpyx/snapflow/engine.py:2911

Signature

interferogram(self, subtract_flat_earth_phase: bool=True, srp_polynomial_degree: int=5, srp_number_points: int=501, orbit_degree: int=3, include_coherence: bool=True, coh_win_az: int=10, coh_win_rg: int=10, square_pixel: bool=True, subtract_topographic_phase: bool=False, dem_name: str='SRTM 3Sec', external_dem_file: Optional[str | Path]=None, external_dem_no_data_value: float=0.0, external_dem_apply_egm: bool=True, tile_extension_percent: str='100', output_flat_earth_phase: bool=False, output_topo_phase: bool=False, output_elevation: bool=False, output_lat_lon: bool=False, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
subtract_flat_earth_phaseboolnoTrueSubtract flat earth phase.
srp_polynomial_degreeintno5Order of 'Flat earth phase' polynomial.
srp_number_pointsintno501Number of points for polynomial estimation.
orbit_degreeintno3Degree of orbit interpolator.
include_coherenceboolnoTrueInclude coherence estimation.
coh_win_azintno10Coherence window size in azimuth.
coh_win_rgintno10Coherence window size in range.
square_pixelboolnoTrueUse ground square pixel.
subtract_topographic_phaseboolnoFalseSubtract topographic phase.
dem_namestrno'SRTM 3Sec'The digital elevation model.
external_dem_fileOptional[str | Path]noNonePath to external DEM file.
external_dem_no_data_valuefloatno0.0No data value for external DEM.
external_dem_apply_egmboolnoTrueApply EGM96 geoid to external DEM.
tile_extension_percentstrno'100'Tile extension for DEM simulation.
output_flat_earth_phaseboolnoFalseOutput flat earth phase band.
output_topo_phaseboolnoFalseOutput topographic phase band.
output_elevationboolnoFalseOutput elevation band.
output_lat_lonboolnoFalseOutput latitude/longitude bands.
output_nameOptional[str]noNoneCustom output filename (without extension).

Return Type

Optional[str]

Path to interferogram output product, or None if failed.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.interferogram()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior. Documented return may be None for some execution paths.

GPT.goldstein_phase_filtering method

Phase filtering using Goldstein method.

File location: sarpyx/snapflow/engine.py:2990

Signature

goldstein_phase_filtering(self, alpha: float=1.0, fft_size_string: str='64', window_size_string: str='3', use_coherence_mask: bool=False, coherence_threshold: float=0.2, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
alphafloatno1.0Adaptive filter exponent. Valid interval is (0, 1].
fft_size_stringstrno'64'FFT size. Must be one of '32', '64', '128', '256'.
window_size_stringstrno'3'Window size. Must be one of '3', '5', '7'.
use_coherence_maskboolnoFalseUse coherence mask.
coherence_thresholdfloatno0.2The coherence threshold. Valid interval is [0, 1].
output_nameOptional[str]noNoneCustom output filename (without extension).

Return Type

Optional[str]

Path to filtered output product, or None if failed.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.goldstein_phase_filtering()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior. Documented return may be None for some execution paths.

GPT.back_geocoding method

Bursts co-registration using orbit and DEM.

File location: sarpyx/snapflow/engine.py:3028

Signature

back_geocoding(self, dem_name: str='SRTM 3Sec', dem_resampling_method: str='BICUBIC_INTERPOLATION', external_dem_file: Optional[str | Path]=None, external_dem_no_data_value: float=0.0, resampling_type: str='BISINC_5_POINT_INTERPOLATION', mask_out_area_without_elevation: bool=True, output_range_azimuth_offset: bool=False, output_deramp_demod_phase: bool=False, disable_reramp: bool=False, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
dem_namestrno'SRTM 3Sec'The digital elevation model.
dem_resampling_methodstrno'BICUBIC_INTERPOLATION'DEM resampling method.
external_dem_fileOptional[str | Path]noNonePath to external DEM file.
external_dem_no_data_valuefloatno0.0No data value for external DEM.
resampling_typestrno'BISINC_5_POINT_INTERPOLATION'Method for resampling slave grid onto master grid.
mask_out_area_without_elevationboolnoTrueMask areas without elevation data.
output_range_azimuth_offsetboolnoFalseOutput range/azimuth offset bands.
output_deramp_demod_phaseboolnoFalseOutput deramp/demod phase band.
disable_rerampboolnoFalseDisable reramp operation.
output_nameOptional[str]noNoneCustom output filename (without extension).

Return Type

Optional[str]

Path to coregistered output product, or None if failed.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.back_geocoding()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior. Documented return may be None for some execution paths.

GPT.create_stack method

Collocates two or more products based on their geo-codings.

File location: sarpyx/snapflow/engine.py:3080

Signature

create_stack(self, master_bands: Optional[List[str]]=None, source_bands: Optional[List[str]]=None, resampling_type: str='NONE', extent: str='Master', initial_offset_method: str='Orbit', output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
master_bandsOptional[List[str]]noNoneList of master bands.
source_bandsOptional[List[str]]noNoneList of source bands.
resampling_typestrno'NONE'Method for resampling slave grid onto master grid.
extentstrno'Master'The output image extents. Must be one of 'Master', 'Minimum', 'Maximum'.
initial_offset_methodstrno'Orbit'Method for computing initial offset. Must be one of 'Orbit', 'Product Geolocation'.
output_nameOptional[str]noNoneCustom output filename (without extension).

Return Type

Optional[str]

Path to stack output product, or None if failed.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.create_stack()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior. Documented return may be None for some execution paths.

GPT.resample method

Resampling of a multi-size source product to a single-size target product.

File location: sarpyx/snapflow/engine.py:3123

Signature

resample(self, reference_band: Optional[str]=None, target_width: Optional[int]=None, target_height: Optional[int]=None, target_resolution: Optional[int]=None, upsampling: str='Nearest', downsampling: str='First', flag_downsampling: str='First', resampling_preset: Optional[str]=None, band_resamplings: Optional[str]=None, resample_on_pyramid_levels: bool=True, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
reference_bandOptional[str]noNoneName of reference band. All other bands resampled to match it.
target_widthOptional[int]noNoneTarget width in pixels.
target_heightOptional[int]noNoneTarget height in pixels.
target_resolutionOptional[int]noNoneTarget resolution.
upsamplingstrno'Nearest'Interpolation method for upsampling. Must be one of 'Nearest', 'Bilinear', 'Bicubic'.
downsamplingstrno'First'Aggregation method for downsampling. Must be one of 'First', 'Min', 'Max', 'Mean', 'Median'.
flag_downsamplingstrno'First'Aggregation method for flags. Must be one of 'First', 'FlagAnd', 'FlagOr', 'FlagMedianAnd', 'FlagMedianOr'.
resampling_presetOptional[str]noNoneResampling preset name.
band_resamplingsOptional[str]noNoneBand-specific resampling settings.
resample_on_pyramid_levelsboolnoTrueIncrease performance for viewing.
output_nameOptional[str]noNoneCustom output filename (without extension).

Return Type

Optional[str]

Path to resampled output product, or None if failed.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.resample()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior. Documented return may be None for some execution paths.

GPT.linear_to_from_db method

Converts bands to/from dB.

File location: sarpyx/snapflow/engine.py:3191

Signature

linear_to_from_db(self, source_bands: Optional[List[str]]=None, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
source_bandsOptional[List[str]]noNoneList of source bands to convert.
output_nameOptional[str]noNoneCustom output filename (without extension).

Return Type

Optional[str]

Path to converted output product, or None if failed.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.linear_to_from_db()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior. Documented return may be None for some execution paths.

GPT.remove_grd_border_noise method

Mask no-value pixels for GRD product.

File location: sarpyx/snapflow/engine.py:3218

Signature

remove_grd_border_noise(self, selected_polarisations: Optional[List[str]]=None, border_limit: int=500, trim_threshold: float=0.5, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
selected_polarisationsOptional[List[str]]noNoneList of polarisations to process.
border_limitintno500The border margin limit in pixels.
trim_thresholdfloatno0.5The trim threshold.
output_nameOptional[str]noNoneCustom output filename (without extension).

Return Type

Optional[str]

Path to noise-removed output product, or None if failed.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.remove_grd_border_noise()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior. Documented return may be None for some execution paths.

GPT.collocate method

Collocates two products based on their geo-codings.

File location: sarpyx/snapflow/engine.py:3252

Signature

collocate(self, source_product_paths: Optional[List[str]]=None, reference_product_name: Optional[str]=None, target_product_type: str='COLLOCATED', copy_secondary_metadata: bool=False, rename_reference_components: bool=True, rename_secondary_components: bool=True, reference_component_pattern: str='${ORIGINAL_NAME}_M', secondary_component_pattern: str='${ORIGINAL_NAME}_S${SLAVE_NUMBER_ID}', resampling_type: str='NEAREST_NEIGHBOUR', output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
source_product_pathsOptional[List[str]]noNoneComma-separated list of source product paths.
reference_product_nameOptional[str]noNoneName of the reference product.
target_product_typestrno'COLLOCATED'Product type string for target product.
copy_secondary_metadataboolnoFalseCopy metadata from secondary products.
rename_reference_componentsboolnoTrueRename reference components in target.
rename_secondary_componentsboolnoTrueRename secondary components in target.
reference_component_patternstrno'${ORIGINAL_NAME}_M'Text pattern for renaming reference components.
secondary_component_patternstrno'${ORIGINAL_NAME}_S${SLAVE_NUMBER_ID}'Text pattern for renaming secondary components.
resampling_typestrno'NEAREST_NEIGHBOUR'Method for resampling secondary grid onto reference grid.
output_nameOptional[str]noNoneCustom output filename (without extension).

Return Type

Optional[str]

Path to collocated output product, or None if failed.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.collocate()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior. Documented return may be None for some execution paths.

GPT.polarimetric_decomposition method

Perform Polarimetric decomposition of a given product.

File location: sarpyx/snapflow/engine.py:3306

Signature

polarimetric_decomposition(self, decomposition: str='Sinclair Decomposition', window_size: int=5, output_ha_alpha: bool=False, output_beta_delta_gamma_lambda: bool=False, output_alpha123: bool=False, output_lambda123: bool=False, output_touzi_param_set0: bool=False, output_touzi_param_set1: bool=False, output_touzi_param_set2: bool=False, output_touzi_param_set3: bool=False, output_huynen_param_set0: bool=True, output_huynen_param_set1: bool=False, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
decompositionstrno'Sinclair Decomposition''Sinclair Decomposition', 'Pauli Decomposition', 'Freeman-Durden Decomposition', 'Generalized Freeman-Durden Decomposition', 'Yamaguchi Decomposition', 'van Zyl Decomposition', 'H-A-Alpha Quad Pol Decomposition', 'H-Alpha Dual Pol Decomposition', 'Cloude Decomposition', 'Touzi Decomposition', 'Huynen Decomposition', 'Yang Decomposition', 'Krogager Decomposition', 'Cameron Decomposition', 'Model-free 3-component Decomposition', 'Model-free 4-component Decomposition', 'Model-Based Dual Pol Decomposition'.
window_sizeintno5The sliding window size. Valid interval is [1, 100].
output_ha_alphaboolnoFalseOutput entropy, anisotropy, alpha.
output_beta_delta_gamma_lambdaboolnoFalseOutput beta, delta, gamma, lambda.
output_alpha123boolnoFalseOutput alpha 1, 2, 3.
output_lambda123boolnoFalseOutput lambda 1, 2, 3.
output_touzi_param_set0boolnoFalseOutput psi, tau, alpha, phi.
output_touzi_param_set1boolnoFalseOutput psi1, tau1, alpha1, phi1.
output_touzi_param_set2boolnoFalseOutput psi2, tau2, alpha2, phi2.
output_touzi_param_set3boolnoFalseOutput psi3, tau3, alpha3, phi3.
output_huynen_param_set0boolnoTrueOutput 2A0_b, B0_plus_B, B0_minus_B.
output_huynen_param_set1boolnoFalseOutput A0, B0, B, C, D, E, F, G, H.
output_nameOptional[str]noNoneCustom output filename (without extension).

Return Type

Optional[str]

Path to decomposed output product, or None if failed.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.polarimetric_decomposition()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior. Documented return may be None for some execution paths.

GPT.polarimetric_parameters method

Compute general polarimetric parameters.

File location: sarpyx/snapflow/engine.py:3373

Signature

polarimetric_parameters(self, use_mean_matrix: bool=True, window_size_x_str: str='5', window_size_y_str: str='5', output_span: bool=True, output_pedestal_height: bool=False, output_rvi: bool=False, output_rfdi: bool=False, output_csi: bool=False, output_vsi: bool=False, output_bmi: bool=False, output_iti: bool=False, output_hhvv_ratio: bool=False, output_hhhv_ratio: bool=False, output_vvvh_ratio: bool=False, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
use_mean_matrixboolnoTrueUse mean coherency or covariance matrix.
window_size_x_strstrno'5'Window size in X direction. Must be one of '3', '5', '7', '9', '11', '13', '15', '17', '19'.
window_size_y_strstrno'5'Window size in Y direction. Must be one of '3', '5', '7', '9', '11', '13', '15', '17', '19'.
output_spanboolnoTrueOutput Span.
output_pedestal_heightboolnoFalseOutput pedestal height.
output_rviboolnoFalseOutput RVI.
output_rfdiboolnoFalseOutput RFDI.
output_csiboolnoFalseOutput CSI.
output_vsiboolnoFalseOutput VSI.
output_bmiboolnoFalseOutput BMI.
output_itiboolnoFalseOutput ITI.
output_hhvv_ratioboolnoFalseOutput Co-Pol HH/VV ratio.
output_hhhv_ratioboolnoFalseOutput Cross-Pol HH/HV ratio.
output_vvvh_ratioboolnoFalseOutput Cross-Pol VV/VH ratio.
output_nameOptional[str]noNoneCustom output filename (without extension).

Return Type

Optional[str]

Path to output product with polarimetric parameters, or None if failed.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.polarimetric_parameters()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior. Documented return may be None for some execution paths.

GPT.offset_tracking method

Create velocity vectors from offset tracking.

File location: sarpyx/snapflow/engine.py:3440

Signature

offset_tracking(self, grid_azimuth_spacing: int=40, grid_range_spacing: int=40, registration_window_width: str='128', registration_window_height: str='128', x_corr_threshold: float=0.1, registration_oversampling: str='16', average_box_size: str='5', max_velocity: float=5.0, radius: int=4, resampling_type: str='BICUBIC_INTERPOLATION', spatial_average: bool=True, fill_holes: bool=True, roi_vector: Optional[str]=None, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
grid_azimuth_spacingintno40Output grid azimuth spacing in pixels.
grid_range_spacingintno40Output grid range spacing in pixels.
registration_window_widthstrno'128'Registration window width. Must be one of '32', '64', '128', '256', '512', '1024', '2048'.
registration_window_heightstrno'128'Registration window height. Must be one of '32', '64', '128', '256', '512', '1024', '2048'.
x_corr_thresholdfloatno0.1The cross-correlation threshold.
registration_oversamplingstrno'16'Registration oversampling factor. Must be one of '2', '4', '8', '16', '32', '64', '128', '256', '512'.
average_box_sizestrno'5'Average box size. Must be one of '3', '5', '9', '11'.
max_velocityfloatno5.0Threshold for eliminating invalid GCPs.
radiusintno4Radius for hole-filling.
resampling_typestrno'BICUBIC_INTERPOLATION'Method for velocity interpolation. Must be one of 'NEAREST_NEIGHBOUR', 'BILINEAR_INTERPOLATION', 'BICUBIC_INTERPOLATION', 'BISINC_5_POINT_INTERPOLATION', 'CUBIC_CONVOLUTION'.
spatial_averageboolnoTrueApply spatial averaging.
fill_holesboolnoTrueFill holes in velocity field.
roi_vectorOptional[str]noNoneRegion of interest vector.
output_nameOptional[str]noNoneCustom output filename (without extension).

Return Type

Optional[str]

Path to offset tracking output product, or None if failed.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.offset_tracking()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior. Documented return may be None for some execution paths.

GPT.ndvi method

The retrieves the Normalized Difference Vegetation Index (NDVI).

File location: sarpyx/snapflow/engine.py:3510

Signature

ndvi(self, red_source_band: Optional[str]=None, nir_source_band: Optional[str]=None, red_factor: float=1.0, nir_factor: float=1.0, resample_type: str='None', upsampling: str='Nearest', downsampling: str='First', output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
red_source_bandOptional[str]noNoneThe red band for NDVI computation. If not provided, the operator will try to find the best fitting band.
nir_source_bandOptional[str]noNoneThe near-infrared band for NDVI computation. If not provided, the operator will try to find the best fitting band.
red_factorfloatno1.0The value of the red source band is multiplied by this value.
nir_factorfloatno1.0The value of the NIR source band is multiplied by this value.
resample_typestrno'None'If selected bands differ in size, the resample method used. Must be one of 'None', 'Lowest resolution', 'Highest resolution'.
upsamplingstrno'Nearest'Method for interpolation (upsampling to finer resolution). Must be one of 'Nearest', 'Bilinear', 'Bicubic'.
downsamplingstrno'First'Method for aggregation (downsampling to coarser resolution). Must be one of 'First', 'Min', 'Max', 'Mean', 'Median'.
output_nameOptional[str]noNoneCustom output filename (without extension).

Return Type

Optional[str]

Path to NDVI output product, or None if failed.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.ndvi()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior. Documented return may be None for some execution paths.

GPT.reproject method

Reprojection of a source product to a target Coordinate Reference System.

File location: sarpyx/snapflow/engine.py:3563

Signature

reproject(self, crs: Optional[str]=None, wkt_file: Optional[str | Path]=None, resampling: str='Nearest', reference_pixel_x: Optional[float]=None, reference_pixel_y: Optional[float]=None, easting: Optional[float]=None, northing: Optional[float]=None, orientation: float=0.0, pixel_size_x: Optional[float]=None, pixel_size_y: Optional[float]=None, width: Optional[int]=None, height: Optional[int]=None, tile_size_x: Optional[int]=None, tile_size_y: Optional[int]=None, orthorectify: bool=False, elevation_model_name: Optional[str]=None, no_data_value: Optional[float]=None, include_tie_point_grids: bool=True, add_delta_bands: bool=False, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
crsOptional[str]noNoneTarget Coordinate Reference System in WKT or as authority code.
wkt_fileOptional[str | Path]noNoneFile containing target CRS in WKT format.
resamplingstrno'Nearest'Resampling method for floating-point raster data. Must be one of 'Nearest', 'Bilinear', 'Bicubic'.
reference_pixel_xOptional[float]noNoneX-position of reference pixel.
reference_pixel_yOptional[float]noNoneY-position of reference pixel.
eastingOptional[float]noNoneEasting of reference pixel.
northingOptional[float]noNoneNorthing of reference pixel.
orientationfloatno0.0Orientation of output product in degrees. Valid interval is [-360, 360].
pixel_size_xOptional[float]noNonePixel size in X direction in CRS units.
pixel_size_yOptional[float]noNonePixel size in Y direction in CRS units.
widthOptional[int]noNoneWidth of target product.
heightOptional[int]noNoneHeight of target product.
tile_size_xOptional[int]noNoneTile size in X direction.
tile_size_yOptional[int]noNoneTile size in Y direction.
orthorectifyboolnoFalseWhether to orthorectify the source product.
elevation_model_nameOptional[str]noNoneElevation model name for orthorectification.
no_data_valueOptional[float]noNoneValue used to indicate no-data.
include_tie_point_gridsboolnoTrueInclude tie-point grids in output.
add_delta_bandsboolnoFalseWhether to add delta longitude and latitude bands.
output_nameOptional[str]noNoneCustom output filename (without extension).

Return Type

Optional[str]

Path to reprojected output product, or None if failed.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.reproject()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior. Documented return may be None for some execution paths.

GPT.polarimetric_matrices method

Generate covariance or coherency matrix for given product.

File location: sarpyx/snapflow/engine.py:3674

Signature

polarimetric_matrices(self, matrix: str='T3', output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
matrixstrno'T3'The covariance or coherency matrix type to generate. Must be one of 'C2', 'C3', 'C4', 'T3', 'T4'.
output_nameOptional[str]noNoneCustom output filename (without extension).

Return Type

Optional[str]

Path to output product with generated matrix, or None if failed.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.polarimetric_matrices()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior. Documented return may be None for some execution paths.

GPT.polarimetric_speckle_filter method

Apply polarimetric speckle filtering for noise reduction.

File location: sarpyx/snapflow/engine.py:3698

Signature

polarimetric_speckle_filter(self, filter: str='Refined Lee Filter', filter_size: int=5, num_looks_str: str='1', window_size: str='7x7', target_window_size_str: str='3x3', an_size: int=50, sigma_str: str='0.9', search_window_size_str: str='15', patch_size_str: str='5', scale_size_str: str='1', output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
filterstrno'Refined Lee Filter'The speckle filter to apply. Must be one of 'Box Car Filter', 'IDAN Filter', 'Refined Lee Filter', 'Improved Lee Sigma Filter'.
filter_sizeintno5(1, 100].
num_looks_strstrno'1'Number of looks. Must be one of '1', '2', '3', '4'.
window_sizestrno'7x7'The window size. Must be one of '5x5', '7x7', '9x9', '11x11', '13x13', '15x15', '17x17'.
target_window_size_strstrno'3x3'The target window size. Must be one of '3x3', '5x5'.
an_sizeintno50(1, 200].
sigma_strstrno'0.9'Sigma parameter. Must be one of '0.5', '0.6', '0.7', '0.8', '0.9'.
search_window_size_strstrno'15'The search window size. Must be one of '3', '5', '7', '9', '11', '13', '15', '17', '19', '21', '23', '25'.
patch_size_strstrno'5'The patch size. Must be one of '3', '5', '7', '9', '11'.
scale_size_strstrno'1'The scale size. Must be one of '0', '1', '2'.
output_nameOptional[str]noNoneCustom output filename (without extension).

Return Type

Optional[str]

Path to filtered output product, or None if failed.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.polarimetric_speckle_filter()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior. Documented return may be None for some execution paths.

GPT.polarimetric_classification method

Perform polarimetric classification of SAR data.

File location: sarpyx/snapflow/engine.py:3760

Signature

polarimetric_classification(self, classification: str='H Alpha Wishart', window_size: int=5, max_iterations: int=3, num_initial_classes: int=90, num_final_classes: int=15, mixed_category_threshold: float=0.5, decomposition: str='Sinclair Decomposition', output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
classificationstrno'H Alpha Wishart'The classification method to use. Must be one of 'Cloude-Pottier', 'Cloude-Pottier Dual Pol', 'H Alpha Wishart', 'H Alpha Wishart Dual Pol', 'Freeman-Durden Wishart', 'General Wishart'.
window_sizeintno5(1, 100].
max_iterationsintno3[1, 100].
num_initial_classesintno90[9, 1000].
num_final_classesintno15[9, 100].
mixed_category_thresholdfloatno0.5The threshold for classifying pixels to mixed category. Valid range: (0, *).
decompositionstrno'Sinclair Decomposition'The polarimetric decomposition method. Must be one of 'Sinclair Decomposition', 'Pauli Decomposition', 'Freeman-Durden Decomposition', 'Generalized Freeman-Durden Decomposition', 'Yamaguchi Decomposition', 'van Zyl Decomposition', 'H-A-Alpha Quad Pol Decomposition', 'Cloude Decomposition', 'Touzi Decomposition'.
output_nameOptional[str]noNoneCustom output filename (without extension).

Return Type

Optional[str]

Path to classified output product, or None if failed.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.polarimetric_classification()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior. Documented return may be None for some execution paths.

GPT.read_product method

Read a data product from a given file location.

File location: sarpyx/snapflow/engine.py:3812

Signature

read_product(self, file: str | Path, format_name: Optional[str]=None, source_bands: Optional[List[str]]=None, source_masks: Optional[List[str]]=None, pixel_region: Optional[str]=None, geometry_region: Optional[str]=None, vector_file: Optional[str | Path]=None, polygon_region: Optional[str]=None, use_advanced_options: bool=False, copy_metadata: bool=True, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
filestr | Pathyes-The file from which the data product is read.
format_nameOptional[str]noNoneAn optional format name to specify the reader.
source_bandsOptional[List[str]]noNoneList of source band names to read.
source_masksOptional[List[str]]noNoneList of source mask names to read.
pixel_regionOptional[str]noNone'x,y,width,height').
geometry_regionOptional[str]noNoneSubset region in geographical coordinates using WKT-format.
vector_fileOptional[str | Path]noNoneFile from which the polygon geometry is read.
polygon_regionOptional[str]noNoneSubset region in geographical coordinates using WKT-format.
use_advanced_optionsboolnoFalseWhether to use advanced options for reading.
copy_metadataboolnoTrueWhether to copy the metadata of the source product.
output_nameOptional[str]noNoneCustom output filename (without extension).

Return Type

Optional[str]

Path to read output product, or None if failed.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.read_product(file=<file>)

Edge Cases

Includes optional parameters with implementation-defined fallback behavior. Documented return may be None for some execution paths.

GPT.merge_products method

Merge several source products using a master product as reference.

File location: sarpyx/snapflow/engine.py:3880

Signature

merge_products(self, geographic_error: float=1e-05, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
geographic_errorfloatno1e-05Maximum lat/lon error in degrees between products.
output_nameOptional[str]noNoneCustom output filename (without extension).

Return Type

Optional[str]

Path to merged output product, or None if failed.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.merge_products()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior. Documented return may be None for some execution paths.

GPT.mosaic method

Create a mosaic from a set of source products.

File location: sarpyx/snapflow/engine.py:3904

Signature

mosaic(self, combine: str='OR', crs: str='EPSG:4326', east_bound: float=30.0, north_bound: float=75.0, south_bound: float=35.0, west_bound: float=-15.0, pixel_size_x: float=0.05, pixel_size_y: float=0.05, orthorectify: bool=False, elevation_model_name: Optional[str]=None, resampling: str='Nearest', output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
combinestrno'OR'Specifies how conditions are combined. Must be 'OR' or 'AND'.
crsstrno'EPSG:4326'The CRS of the target product (WKT or authority code).
east_boundfloatno30.0[-180, 180].
north_boundfloatno75.0[-90, 90].
south_boundfloatno35.0[-90, 90].
west_boundfloatno-15.0[-180, 180].
pixel_size_xfloatno0.05Size of a pixel in X-direction in map units.
pixel_size_yfloatno0.05Size of a pixel in Y-direction in map units.
orthorectifyboolnoFalseWhether the source product should be orthorectified.
elevation_model_nameOptional[str]noNoneElevation model name for orthorectification.
resamplingstrno'Nearest'Resampling method. Must be 'Nearest', 'Bilinear', or 'Bicubic'.
output_nameOptional[str]noNoneCustom output filename (without extension).

Return Type

Optional[str]

Path to mosaic output product, or None if failed.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.mosaic()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior. Documented return may be None for some execution paths.

GPT.flip method

Flip a product horizontally, vertically, or both.

File location: sarpyx/snapflow/engine.py:3962

Signature

flip(self, flip_type: str='Vertical', source_bands: Optional[List[str]]=None, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
flip_typestrno'Vertical'The type of flip to apply. Must be 'Horizontal', 'Vertical', or 'Horizontal and Vertical'.
source_bandsOptional[List[str]]noNoneList of source bands to flip.
output_nameOptional[str]noNoneCustom output filename (without extension).

Return Type

Optional[str]

Path to flipped output product, or None if failed.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.flip()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior. Documented return may be None for some execution paths.

GPT.image_filter method

Apply common image processing filters.

File location: sarpyx/snapflow/engine.py:3992

Signature

image_filter(self, selected_filter_name: Optional[str]=None, source_bands: Optional[List[str]]=None, user_defined_kernel_file: Optional[str | Path]=None, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
selected_filter_nameOptional[str]noNoneThe name of the filter to apply.
source_bandsOptional[List[str]]noNoneList of source bands to filter.
user_defined_kernel_fileOptional[str | Path]noNonePath to file containing a user-defined kernel.
output_nameOptional[str]noNoneCustom output filename (without extension).

Return Type

Optional[str]

Path to filtered output product, or None if failed.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.image_filter()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior. Documented return may be None for some execution paths.

GPT.convert_datatype method

Convert product data type.

File location: sarpyx/snapflow/engine.py:4030

Signature

convert_datatype(self, target_data_type: str='uint8', target_scaling_str: str='Linear (between 95% clipped histogram)', target_no_data_value: float=0.0, source_bands: Optional[List[str]]=None, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
target_data_typestrno'uint8'The target data type. Must be one of 'int8', 'int16', 'int32', 'uint8', 'uint16', 'uint32', 'float32', 'float64'.
target_scaling_strstrno'Linear (between 95% clipped histogram)'The scaling method for data type conversion. Must be one of 'Truncate', 'Linear (slope and intercept)', 'Linear (between 95% clipped histogram)', 'Linear (peak clipped histogram)', 'Logarithmic'.
target_no_data_valuefloatno0.0The no-data value for the target product.
source_bandsOptional[List[str]]noNoneList of source bands to convert.
output_nameOptional[str]noNoneCustom output filename (without extension).

Return Type

Optional[str]

Path to converted output product, or None if failed.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.convert_datatype()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior. Documented return may be None for some execution paths.

GPT.land_sea_mask method

Create a bitmask defining land versus ocean areas.

File location: sarpyx/snapflow/engine.py:4072

Signature

land_sea_mask(self, land_mask: bool=True, use_srtm: bool=True, geometry: Optional[str]=None, invert_geometry: bool=False, shoreline_extension: int=0, source_bands: Optional[List[str]]=None, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
land_maskboolnoTrueIf True, masks land areas; if False, masks sea areas.
use_srtmboolnoTrueUse SRTM water body data for land/sea determination.
geometryOptional[str]noNoneName of geometry to use for masking.
invert_geometryboolnoFalseInvert the geometry mask.
shoreline_extensionintno0Distance in pixels to extend the shoreline.
source_bandsOptional[List[str]]noNoneList of source bands to apply the mask to.
output_nameOptional[str]noNoneCustom output filename (without extension).

Return Type

Optional[str]

Path to masked output product, or None if failed.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.land_sea_mask()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior. Documented return may be None for some execution paths.

GPT.enhanced_spectral_diversity method

Estimate constant range and azimuth offsets for a stack of images.

File location: sarpyx/snapflow/engine.py:4117

Signature

enhanced_spectral_diversity(self, fine_win_width_str: str='512', fine_win_height_str: str='512', fine_win_acc_azimuth: str='16', fine_win_acc_range: str='16', fine_win_oversampling: str='128', x_corr_threshold: float=0.1, coh_threshold: float=0.3, num_blocks_per_overlap: int=10, esd_estimator: str='Periodogram', weight_func: str='Inv Quadratic', temporal_baseline_type: str='Number of images', max_temporal_baseline: int=4, integration_method: str='L1 and L2', do_not_write_target_bands: bool=False, use_supplied_range_shift: bool=False, overall_range_shift: float=0.0, use_supplied_azimuth_shift: bool=False, overall_azimuth_shift: float=0.0, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
fine_win_width_strstrno'512'Width of fine registration window.
fine_win_height_strstrno'512'Height of fine registration window.
fine_win_acc_azimuthstrno'16'Fine registration azimuth accuracy.
fine_win_acc_rangestrno'16'Fine registration range accuracy.
fine_win_oversamplingstrno'128'Fine registration oversampling factor.
x_corr_thresholdfloatno0.1Peak cross-correlation threshold.
coh_thresholdfloatno0.3Coherence threshold for outlier removal.
num_blocks_per_overlapintno10Number of windows per overlap for ESD.
esd_estimatorstrno'Periodogram'ESD estimator used for azimuth shift computation.
weight_funcstrno'Inv Quadratic'Weight function of coherence for azimuth shift estimation.
temporal_baseline_typestrno'Number of images'Baseline type for building integration network.
max_temporal_baselineintno4Maximum temporal baseline between image pairs.
integration_methodstrno'L1 and L2'Method used for integrating shifts network.
do_not_write_target_bandsboolnoFalseDo not write target bands.
use_supplied_range_shiftboolnoFalseUse user supplied range shift.
overall_range_shiftfloatno0.0The overall range shift value.
use_supplied_azimuth_shiftboolnoFalseUse user supplied azimuth shift.
overall_azimuth_shiftfloatno0.0The overall azimuth shift value.
output_nameOptional[str]noNoneCustom output filename (without extension).

Return Type

Optional[str]

Path to ESD-corrected output product, or None if failed.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.enhanced_spectral_diversity()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior. Documented return may be None for some execution paths.

GPT.phase_to_displacement method

Convert unwrapped phase to displacement along line of sight.

File location: sarpyx/snapflow/engine.py:4194

Signature

phase_to_displacement(self, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
output_nameOptional[str]noNoneCustom output filename (without extension).

Return Type

Optional[str]

Path to displacement output product, or None if failed.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.phase_to_displacement()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior. Documented return may be None for some execution paths.

GPT.phase_to_elevation method

Convert interferometric phase to elevation (DEM generation).

File location: sarpyx/snapflow/engine.py:4213

Signature

phase_to_elevation(self, dem_name: str='SRTM 3Sec', dem_resampling_method: str='BILINEAR_INTERPOLATION', external_dem_file: Optional[str | Path]=None, external_dem_no_data_value: float=0.0, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
dem_namestrno'SRTM 3Sec'The digital elevation model to use as reference.
dem_resampling_methodstrno'BILINEAR_INTERPOLATION'DEM resampling method.
external_dem_fileOptional[str | Path]noNonePath to external DEM file.
external_dem_no_data_valuefloatno0.0No data value for external DEM.
output_nameOptional[str]noNoneCustom output filename (without extension).

Return Type

Optional[str]

Path to elevation output product, or None if failed.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.phase_to_elevation()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior. Documented return may be None for some execution paths.

GPT.phase_to_height method

Convert unwrapped phase to height.

File location: sarpyx/snapflow/engine.py:4249

Signature

phase_to_height(self, n_points: int=200, n_heights: int=3, degree_1d: int=2, degree_2d: int=5, orbit_degree: int=3, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
n_pointsintno200Number of points for evaluation of flat earth phase.
n_heightsintno3Number of height samples in range [0,5000).
degree_1dintno2Degree of 1D polynomial to fit reference phase through.
degree_2dintno5Degree of 2D polynomial to fit reference phase through.
orbit_degreeintno3Degree of orbit (polynomial) interpolator.
output_nameOptional[str]noNoneCustom output filename (without extension).

Return Type

Optional[str]

Path to height output product, or None if failed.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.phase_to_height()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior. Documented return may be None for some execution paths.

GPT.snaphu_export method

Download and execute SNAPHU on interferograms.

File location: sarpyx/snapflow/engine.py:4286

Signature

snaphu_export(self, snaphu_processing_location: Optional[str | Path]=None, snaphu_install_location: Optional[str | Path]=None, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
snaphu_processing_locationOptional[str | Path]noNoneDirectory for SNAPHU processing.
snaphu_install_locationOptional[str | Path]noNoneDirectory to install SNAPHU binary.
output_nameOptional[str]noNoneCustom output filename (without extension).

Return Type

Optional[str]

Path to SNAPHU export output product, or None if failed.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.snaphu_export()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior. Documented return may be None for some execution paths.

GPT.cross_correlation method

Automatic GCP selection using cross-correlation.

File location: sarpyx/snapflow/engine.py:4317

Signature

cross_correlation(self, num_gcp_to_generate: int=2000, coarse_registration_window_width: str='128', coarse_registration_window_height: str='128', row_interp_factor: str='2', column_interp_factor: str='2', max_iteration: int=10, gcp_tolerance: float=0.5, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
num_gcp_to_generateintno2000Number of GCPs to use in a grid.
coarse_registration_window_widthstrno'128'Coarse registration window width.
coarse_registration_window_heightstrno'128'Coarse registration window height.
row_interp_factorstrno'2'Row interpolation factor.
column_interp_factorstrno'2'Column interpolation factor.
max_iterationintno10Maximum number of iterations.
gcp_tolerancefloatno0.5Tolerance in slave GCP validation check.
output_nameOptional[str]noNoneCustom output filename (without extension).

Return Type

Optional[str]

Path to coregistered output product, or None if failed.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.cross_correlation()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior. Documented return may be None for some execution paths.

GPT.dem_assisted_coregistration method

Perform orbit and DEM based coregistration.

File location: sarpyx/snapflow/engine.py:4360

Signature

dem_assisted_coregistration(self, dem_name: str='SRTM 3Sec', dem_resampling_method: str='BICUBIC_INTERPOLATION', external_dem_file: Optional[str | Path]=None, external_dem_no_data_value: float=0.0, resampling_type: str='BISINC_5_POINT_INTERPOLATION', mask_out_area_without_elevation: bool=True, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
dem_namestrno'SRTM 3Sec'The digital elevation model to use.
dem_resampling_methodstrno'BICUBIC_INTERPOLATION'DEM resampling method.
external_dem_fileOptional[str | Path]noNonePath to external DEM file.
external_dem_no_data_valuefloatno0.0No data value for external DEM.
resampling_typestrno'BISINC_5_POINT_INTERPOLATION'Method for resampling slave grid onto master grid.
mask_out_area_without_elevationboolnoTrueMask out areas without elevation.
output_nameOptional[str]noNoneCustom output filename (without extension).

Return Type

Optional[str]

Path to coregistered output product, or None if failed.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.dem_assisted_coregistration()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior. Documented return may be None for some execution paths.

GPT.eap_phase_correction method

Apply EAP (Equivalent Aperture Position) phase correction.

File location: sarpyx/snapflow/engine.py:4402

Signature

eap_phase_correction(self, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
output_nameOptional[str]noNoneCustom output filename (without extension).

Return Type

Optional[str]

Path to phase-corrected output product, or None if failed.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.eap_phase_correction()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior. Documented return may be None for some execution paths.

GPT.ellipsoid_correction_rd method

Apply ellipsoid correction with Range-Doppler method.

File location: sarpyx/snapflow/engine.py:4420

Signature

ellipsoid_correction_rd(self, source_bands: Optional[List[str]]=None, pixel_spacing_in_meter: float=0.0, map_projection: str='WGS84(DD)', output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
source_bandsOptional[List[str]]noNoneList of source bands to process.
pixel_spacing_in_meterfloatno0.0Pixel spacing in meters.
map_projectionstrno'WGS84(DD)'Coordinate reference system in WKT format.
output_nameOptional[str]noNoneCustom output filename (without extension).

Return Type

Optional[str]

Path to terrain-corrected output product, or None if failed.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.ellipsoid_correction_rd()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior. Documented return may be None for some execution paths.

GPT.range_filter method

Apply range filtering for spectral analysis.

File location: sarpyx/snapflow/engine.py:4453

Signature

range_filter(self, fft_length: int=8, alpha_hamming: float=0.75, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
fft_lengthintno8Length of filtering window.
alpha_hammingfloatno0.75Weight for Hamming filter.
output_nameOptional[str]noNoneCustom output filename (without extension).

Return Type

Optional[str]

Path to range-filtered output product, or None if failed.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.range_filter()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior. Documented return may be None for some execution paths.

GPT.azimuth_filter method

Apply azimuth filtering for spectral analysis.

File location: sarpyx/snapflow/engine.py:4481

Signature

azimuth_filter(self, fft_length: int=256, alpha_hamming: float=0.75, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
fft_lengthintno256Length of filtering window.
alpha_hammingfloatno0.75Weight for Hamming filter.
output_nameOptional[str]noNoneCustom output filename (without extension).

Return Type

Optional[str]

Path to azimuth-filtered output product, or None if failed.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.azimuth_filter()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior. Documented return may be None for some execution paths.

GPT.band_pass_filter method

Create basebanded SLC based on a subband of 1/3 the original bandwidth.

File location: sarpyx/snapflow/engine.py:4509

Signature

band_pass_filter(self, subband: str='low', alpha: float=1.0, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
subbandstrno'low'Subband selection ('low' or 'high').
alphafloatno1.0Hamming alpha parameter.
output_nameOptional[str]noNoneCustom output filename (without extension).

Return Type

Optional[str]

Path to band-pass filtered output product, or None if failed.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.band_pass_filter()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior. Documented return may be None for some execution paths.

GPT.oversample method

Oversample the dataset to increase spatial resolution.

File location: sarpyx/snapflow/engine.py:4537

Signature

oversample(self, source_bands: Optional[List[str]]=None, output_image_by: str='Ratio', width_ratio: float=2.0, height_ratio: float=2.0, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
source_bandsOptional[List[str]]noNoneList of source bands to oversample.
output_image_bystrno'Ratio'Method to specify output dimensions.
width_ratiofloatno2.0Width ratio of output/input images.
height_ratiofloatno2.0Height ratio of output/input images.
output_nameOptional[str]noNoneCustom output filename (without extension).

Return Type

Optional[str]

Path to oversampled output product, or None if failed.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.oversample()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior. Documented return may be None for some execution paths.

GPT.glcm method

Extract texture features using Gray Level Co-occurrence Matrix.

File location: sarpyx/snapflow/engine.py:4573

Signature

glcm(self, source_bands: Optional[List[str]]=None, window_size_str: str='9x9', angle_str: str='ALL', quantization_levels_str: str='32', output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
source_bandsOptional[List[str]]noNoneList of source bands for texture analysis.
window_size_strstrno'9x9'Size of the analysis window.
angle_strstrno'ALL'Angle for co-occurrence matrix computation.
quantization_levels_strstrno'32'Number of quantization levels.
output_nameOptional[str]noNoneCustom output filename (without extension).

Return Type

Optional[str]

Path to GLCM output product with texture features, or None if failed.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.glcm()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior. Documented return may be None for some execution paths.

GPT.pca method

Perform Principal Component Analysis (PCA).

File location: sarpyx/snapflow/engine.py:4609

Signature

pca(self, source_band_names: Optional[List[str]]=None, component_count: int=-1, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
source_band_namesOptional[List[str]]noNoneNames of bands to use for analysis.
component_countintno-1Maximum number of components (-1 for all).
output_nameOptional[str]noNoneCustom output filename (without extension).

Return Type

Optional[str]

Path to PCA output product, or None if failed.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.pca()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior. Documented return may be None for some execution paths.

GPT.k_means_cluster_analysis method

Perform K-Means cluster analysis.

File location: sarpyx/snapflow/engine.py:4637

Signature

k_means_cluster_analysis(self, source_band_names: Optional[List[str]]=None, cluster_count: int=14, iteration_count: int=30, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
source_band_namesOptional[List[str]]noNoneNames of bands to use for cluster analysis.
cluster_countintno14Number of clusters.
iteration_countintno30Number of iterations.
output_nameOptional[str]noNoneCustom output filename (without extension).

Return Type

Optional[str]

Path to clustered output product, or None if failed.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.k_means_cluster_analysis()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior. Documented return may be None for some execution paths.

GPT.em_cluster_analysis method

Perform Expectation-Maximization cluster analysis.

File location: sarpyx/snapflow/engine.py:4670

Signature

em_cluster_analysis(self, source_band_names: Optional[List[str]]=None, cluster_count: int=14, iteration_count: int=30, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
source_band_namesOptional[List[str]]noNoneNames of bands to use for cluster analysis.
cluster_countintno14Number of clusters.
iteration_countintno30Number of iterations.
output_nameOptional[str]noNoneCustom output filename (without extension).

Return Type

Optional[str]

Path to clustered output product, or None if failed.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.em_cluster_analysis()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior. Documented return may be None for some execution paths.

GPT.random_forest_classifier method

Perform Random Forest classification.

File location: sarpyx/snapflow/engine.py:4703

Signature

random_forest_classifier(self, tree_count: int=10, feature_bands: Optional[List[str]]=None, training_vectors: Optional[List[str]]=None, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
tree_countintno10Number of trees in the forest.
feature_bandsOptional[List[str]]noNoneNames of bands to use as features.
training_vectorsOptional[List[str]]noNoneVectors to train on.
output_nameOptional[str]noNoneCustom output filename (without extension).

Return Type

Optional[str]

Path to classified output product, or None if failed.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.random_forest_classifier()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior. Documented return may be None for some execution paths.

GPT.decision_tree method

Perform Decision Tree classification.

File location: sarpyx/snapflow/engine.py:4736

Signature

decision_tree(self, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
output_nameOptional[str]noNoneCustom output filename (without extension).

Return Type

Optional[str]

Path to classified output product, or None if failed.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.decision_tree()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior. Documented return may be None for some execution paths.

GPT.arvi method

Compute Atmospherically Resistant Vegetation Index.

File location: sarpyx/snapflow/engine.py:4754

Signature

arvi(self, red_source_band: Optional[str]=None, nir_source_band: Optional[str]=None, blue_source_band: Optional[str]=None, red_factor: float=1.0, nir_factor: float=1.0, blue_factor: float=1.0, gamma_parameter: float=1.0, resample_type: str='None', upsampling: str='Nearest', downsampling: str='First', output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
red_source_bandOptional[str]noNoneinferred from implementation.
nir_source_bandOptional[str]noNoneinferred from implementation.
blue_source_bandOptional[str]noNoneinferred from implementation.
red_factorfloatno1.0inferred from implementation.
nir_factorfloatno1.0inferred from implementation.
blue_factorfloatno1.0inferred from implementation.
gamma_parameterfloatno1.0inferred from implementation.
resample_typestrno'None'inferred from implementation.
upsamplingstrno'Nearest'inferred from implementation.
downsamplingstrno'First'inferred from implementation.
output_nameOptional[str]noNoneinferred from implementation.

Return Type

Optional[str]

inferred from implementation.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.arvi()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.

GPT.dvi method

Compute Difference Vegetation Index.

File location: sarpyx/snapflow/engine.py:4788

Signature

dvi(self, red_source_band: Optional[str]=None, nir_source_band: Optional[str]=None, red_factor: float=1.0, nir_factor: float=1.0, resample_type: str='None', upsampling: str='Nearest', downsampling: str='First', output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
red_source_bandOptional[str]noNoneinferred from implementation.
nir_source_bandOptional[str]noNoneinferred from implementation.
red_factorfloatno1.0inferred from implementation.
nir_factorfloatno1.0inferred from implementation.
resample_typestrno'None'inferred from implementation.
upsamplingstrno'Nearest'inferred from implementation.
downsamplingstrno'First'inferred from implementation.
output_nameOptional[str]noNoneinferred from implementation.

Return Type

Optional[str]

inferred from implementation.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.dvi()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.

GPT.gemi method

Compute Global Environmental Monitoring Index.

File location: sarpyx/snapflow/engine.py:4815

Signature

gemi(self, red_source_band: Optional[str]=None, nir_source_band: Optional[str]=None, red_factor: float=1.0, nir_factor: float=1.0, resample_type: str='None', upsampling: str='Nearest', downsampling: str='First', output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
red_source_bandOptional[str]noNoneinferred from implementation.
nir_source_bandOptional[str]noNoneinferred from implementation.
red_factorfloatno1.0inferred from implementation.
nir_factorfloatno1.0inferred from implementation.
resample_typestrno'None'inferred from implementation.
upsamplingstrno'Nearest'inferred from implementation.
downsamplingstrno'First'inferred from implementation.
output_nameOptional[str]noNoneinferred from implementation.

Return Type

Optional[str]

inferred from implementation.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.gemi()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.

GPT.gndvi method

Compute Green Normalized Difference Vegetation Index.

File location: sarpyx/snapflow/engine.py:4842

Signature

gndvi(self, green_source_band: Optional[str]=None, nir_source_band: Optional[str]=None, green_factor: float=1.0, nir_factor: float=1.0, resample_type: str='None', upsampling: str='Nearest', downsampling: str='First', output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
green_source_bandOptional[str]noNoneinferred from implementation.
nir_source_bandOptional[str]noNoneinferred from implementation.
green_factorfloatno1.0inferred from implementation.
nir_factorfloatno1.0inferred from implementation.
resample_typestrno'None'inferred from implementation.
upsamplingstrno'Nearest'inferred from implementation.
downsamplingstrno'First'inferred from implementation.
output_nameOptional[str]noNoneinferred from implementation.

Return Type

Optional[str]

inferred from implementation.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.gndvi()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.

GPT.ipvi method

Compute Infrared Percentage Vegetation Index.

File location: sarpyx/snapflow/engine.py:4869

Signature

ipvi(self, red_source_band: Optional[str]=None, nir_source_band: Optional[str]=None, red_factor: float=1.0, nir_factor: float=1.0, resample_type: str='None', upsampling: str='Nearest', downsampling: str='First', output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
red_source_bandOptional[str]noNoneinferred from implementation.
nir_source_bandOptional[str]noNoneinferred from implementation.
red_factorfloatno1.0inferred from implementation.
nir_factorfloatno1.0inferred from implementation.
resample_typestrno'None'inferred from implementation.
upsamplingstrno'Nearest'inferred from implementation.
downsamplingstrno'First'inferred from implementation.
output_nameOptional[str]noNoneinferred from implementation.

Return Type

Optional[str]

inferred from implementation.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.ipvi()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.

GPT.mcari method

Compute Modified Chlorophyll Absorption Ratio Index.

File location: sarpyx/snapflow/engine.py:4896

Signature

mcari(self, red1_source_band: Optional[str]=None, red2_source_band: Optional[str]=None, green_source_band: Optional[str]=None, red1_factor: float=1.0, red2_factor: float=1.0, green_factor: float=1.0, resample_type: str='None', upsampling: str='Nearest', downsampling: str='First', output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
red1_source_bandOptional[str]noNoneinferred from implementation.
red2_source_bandOptional[str]noNoneinferred from implementation.
green_source_bandOptional[str]noNoneinferred from implementation.
red1_factorfloatno1.0inferred from implementation.
red2_factorfloatno1.0inferred from implementation.
green_factorfloatno1.0inferred from implementation.
resample_typestrno'None'inferred from implementation.
upsamplingstrno'Nearest'inferred from implementation.
downsamplingstrno'First'inferred from implementation.
output_nameOptional[str]noNoneinferred from implementation.

Return Type

Optional[str]

inferred from implementation.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.mcari()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.

GPT.mndwi method

Compute Modified Normalized Difference Water Index.

File location: sarpyx/snapflow/engine.py:4928

Signature

mndwi(self, green_source_band: Optional[str]=None, mir_source_band: Optional[str]=None, green_factor: float=1.0, mir_factor: float=1.0, resample_type: str='None', upsampling: str='Nearest', downsampling: str='First', output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
green_source_bandOptional[str]noNoneinferred from implementation.
mir_source_bandOptional[str]noNoneinferred from implementation.
green_factorfloatno1.0inferred from implementation.
mir_factorfloatno1.0inferred from implementation.
resample_typestrno'None'inferred from implementation.
upsamplingstrno'Nearest'inferred from implementation.
downsamplingstrno'First'inferred from implementation.
output_nameOptional[str]noNoneinferred from implementation.

Return Type

Optional[str]

inferred from implementation.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.mndwi()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.

GPT.msavi2 method

Compute second Modified Soil Adjusted Vegetation Index.

File location: sarpyx/snapflow/engine.py:4955

Signature

msavi2(self, red_source_band: Optional[str]=None, nir_source_band: Optional[str]=None, red_factor: float=1.0, nir_factor: float=1.0, resample_type: str='None', upsampling: str='Nearest', downsampling: str='First', output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
red_source_bandOptional[str]noNoneinferred from implementation.
nir_source_bandOptional[str]noNoneinferred from implementation.
red_factorfloatno1.0inferred from implementation.
nir_factorfloatno1.0inferred from implementation.
resample_typestrno'None'inferred from implementation.
upsamplingstrno'Nearest'inferred from implementation.
downsamplingstrno'First'inferred from implementation.
output_nameOptional[str]noNoneinferred from implementation.

Return Type

Optional[str]

inferred from implementation.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.msavi2()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.

GPT.msavi method

Compute Modified Soil Adjusted Vegetation Index.

File location: sarpyx/snapflow/engine.py:4982

Signature

msavi(self, red_source_band: Optional[str]=None, nir_source_band: Optional[str]=None, red_factor: float=1.0, nir_factor: float=1.0, slope: float=0.5, resample_type: str='None', upsampling: str='Nearest', downsampling: str='First', output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
red_source_bandOptional[str]noNoneinferred from implementation.
nir_source_bandOptional[str]noNoneinferred from implementation.
red_factorfloatno1.0inferred from implementation.
nir_factorfloatno1.0inferred from implementation.
slopefloatno0.5inferred from implementation.
resample_typestrno'None'inferred from implementation.
upsamplingstrno'Nearest'inferred from implementation.
downsamplingstrno'First'inferred from implementation.
output_nameOptional[str]noNoneinferred from implementation.

Return Type

Optional[str]

inferred from implementation.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.msavi()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.

GPT.mtci method

Compute MERIS Terrestrial Chlorophyll Index.

File location: sarpyx/snapflow/engine.py:5011

Signature

mtci(self, red_source_band4: Optional[str]=None, red_source_band5: Optional[str]=None, nir_source_band: Optional[str]=None, red_b4_factor: float=1.0, red_b5_factor: float=1.0, nir_factor: float=1.0, resample_type: str='None', upsampling: str='Nearest', downsampling: str='First', output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
red_source_band4Optional[str]noNoneinferred from implementation.
red_source_band5Optional[str]noNoneinferred from implementation.
nir_source_bandOptional[str]noNoneinferred from implementation.
red_b4_factorfloatno1.0inferred from implementation.
red_b5_factorfloatno1.0inferred from implementation.
nir_factorfloatno1.0inferred from implementation.
resample_typestrno'None'inferred from implementation.
upsamplingstrno'Nearest'inferred from implementation.
downsamplingstrno'First'inferred from implementation.
output_nameOptional[str]noNoneinferred from implementation.

Return Type

Optional[str]

inferred from implementation.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.mtci()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.

GPT.ndwi method

Compute Normalized Difference Water Index.

File location: sarpyx/snapflow/engine.py:5043

Signature

ndwi(self, nir_source_band: Optional[str]=None, mir_source_band: Optional[str]=None, nir_factor: float=1.0, mir_factor: float=1.0, resample_type: str='None', upsampling: str='Nearest', downsampling: str='First', output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
nir_source_bandOptional[str]noNoneinferred from implementation.
mir_source_bandOptional[str]noNoneinferred from implementation.
nir_factorfloatno1.0inferred from implementation.
mir_factorfloatno1.0inferred from implementation.
resample_typestrno'None'inferred from implementation.
upsamplingstrno'Nearest'inferred from implementation.
downsamplingstrno'First'inferred from implementation.
output_nameOptional[str]noNoneinferred from implementation.

Return Type

Optional[str]

inferred from implementation.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.ndwi()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.

GPT.rvi method

Compute Ratio Vegetation Index.

File location: sarpyx/snapflow/engine.py:5070

Signature

rvi(self, red_source_band: Optional[str]=None, nir_source_band: Optional[str]=None, red_factor: float=1.0, nir_factor: float=1.0, resample_type: str='None', upsampling: str='Nearest', downsampling: str='First', output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
red_source_bandOptional[str]noNoneinferred from implementation.
nir_source_bandOptional[str]noNoneinferred from implementation.
red_factorfloatno1.0inferred from implementation.
nir_factorfloatno1.0inferred from implementation.
resample_typestrno'None'inferred from implementation.
upsamplingstrno'Nearest'inferred from implementation.
downsamplingstrno'First'inferred from implementation.
output_nameOptional[str]noNoneinferred from implementation.

Return Type

Optional[str]

inferred from implementation.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.rvi()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.

GPT.bi2 method

Second Brightness Index.

File location: sarpyx/snapflow/engine.py:5097

Signature

bi2(self, red_source_band: Optional[str]=None, green_source_band: Optional[str]=None, nir_source_band: Optional[str]=None, red_factor: float=1.0, green_factor: float=1.0, nir_factor: float=1.0, resample_type: str='None', upsampling: str='Nearest', downsampling: str='First', output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
red_source_bandOptional[str]noNoneinferred from implementation.
green_source_bandOptional[str]noNoneinferred from implementation.
nir_source_bandOptional[str]noNoneinferred from implementation.
red_factorfloatno1.0inferred from implementation.
green_factorfloatno1.0inferred from implementation.
nir_factorfloatno1.0inferred from implementation.
resample_typestrno'None'inferred from implementation.
upsamplingstrno'Nearest'inferred from implementation.
downsamplingstrno'First'inferred from implementation.
output_nameOptional[str]noNoneinferred from implementation.

Return Type

Optional[str]

inferred from implementation.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.bi2()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.

GPT.bi method

Brightness Index.

File location: sarpyx/snapflow/engine.py:5129

Signature

bi(self, red_source_band: Optional[str]=None, green_source_band: Optional[str]=None, red_factor: float=1.0, green_factor: float=1.0, resample_type: str='None', upsampling: str='Nearest', downsampling: str='First', output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
red_source_bandOptional[str]noNoneinferred from implementation.
green_source_bandOptional[str]noNoneinferred from implementation.
red_factorfloatno1.0inferred from implementation.
green_factorfloatno1.0inferred from implementation.
resample_typestrno'None'inferred from implementation.
upsamplingstrno'Nearest'inferred from implementation.
downsamplingstrno'First'inferred from implementation.
output_nameOptional[str]noNoneinferred from implementation.

Return Type

Optional[str]

inferred from implementation.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.bi()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.

GPT.ci method

Colour Index.

File location: sarpyx/snapflow/engine.py:5156

Signature

ci(self, red_source_band: Optional[str]=None, green_source_band: Optional[str]=None, red_factor: float=1.0, green_factor: float=1.0, resample_type: str='None', upsampling: str='Nearest', downsampling: str='First', output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
red_source_bandOptional[str]noNoneinferred from implementation.
green_source_bandOptional[str]noNoneinferred from implementation.
red_factorfloatno1.0inferred from implementation.
green_factorfloatno1.0inferred from implementation.
resample_typestrno'None'inferred from implementation.
upsamplingstrno'Nearest'inferred from implementation.
downsamplingstrno'First'inferred from implementation.
output_nameOptional[str]noNoneinferred from implementation.

Return Type

Optional[str]

inferred from implementation.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.ci()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.

GPT.ireci method

Inverted Red-Edge Chlorophyll.

File location: sarpyx/snapflow/engine.py:5183

Signature

ireci(self, red_source_band4: Optional[str]=None, red_source_band5: Optional[str]=None, red_source_band6: Optional[str]=None, nir_source_band: Optional[str]=None, red_b4_factor: float=1.0, red_b5_factor: float=1.0, red_b6_factor: float=1.0, nir_factor: float=1.0, resample_type: str='None', upsampling: str='Nearest', downsampling: str='First', output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
red_source_band4Optional[str]noNoneinferred from implementation.
red_source_band5Optional[str]noNoneinferred from implementation.
red_source_band6Optional[str]noNoneinferred from implementation.
nir_source_bandOptional[str]noNoneinferred from implementation.
red_b4_factorfloatno1.0inferred from implementation.
red_b5_factorfloatno1.0inferred from implementation.
red_b6_factorfloatno1.0inferred from implementation.
nir_factorfloatno1.0inferred from implementation.
resample_typestrno'None'inferred from implementation.
upsamplingstrno'Nearest'inferred from implementation.
downsamplingstrno'First'inferred from implementation.
output_nameOptional[str]noNoneinferred from implementation.

Return Type

Optional[str]

inferred from implementation.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.ireci()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.

GPT.ndi45 method

Normalized Difference Index.

File location: sarpyx/snapflow/engine.py:5220

Signature

ndi45(self, red_source_band4: Optional[str]=None, red_source_band5: Optional[str]=None, red_b4_factor: float=1.0, red_b5_factor: float=1.0, resample_type: str='None', upsampling: str='Nearest', downsampling: str='First', output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
red_source_band4Optional[str]noNoneinferred from implementation.
red_source_band5Optional[str]noNoneinferred from implementation.
red_b4_factorfloatno1.0inferred from implementation.
red_b5_factorfloatno1.0inferred from implementation.
resample_typestrno'None'inferred from implementation.
upsamplingstrno'Nearest'inferred from implementation.
downsamplingstrno'First'inferred from implementation.
output_nameOptional[str]noNoneinferred from implementation.

Return Type

Optional[str]

inferred from implementation.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.ndi45()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.

GPT.ndpi method

Normalized Differential Pond.

File location: sarpyx/snapflow/engine.py:5247

Signature

ndpi(self, green_source_band: Optional[str]=None, mir_source_band: Optional[str]=None, green_factor: float=1.0, mir_factor: float=1.0, resample_type: str='None', upsampling: str='Nearest', downsampling: str='First', output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
green_source_bandOptional[str]noNoneinferred from implementation.
mir_source_bandOptional[str]noNoneinferred from implementation.
green_factorfloatno1.0inferred from implementation.
mir_factorfloatno1.0inferred from implementation.
resample_typestrno'None'inferred from implementation.
upsamplingstrno'Nearest'inferred from implementation.
downsamplingstrno'First'inferred from implementation.
output_nameOptional[str]noNoneinferred from implementation.

Return Type

Optional[str]

inferred from implementation.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.ndpi()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.

GPT.ndti method

Normalized Difference Turbidity.

File location: sarpyx/snapflow/engine.py:5274

Signature

ndti(self, red_source_band: Optional[str]=None, green_source_band: Optional[str]=None, red_factor: float=1.0, green_factor: float=1.0, resample_type: str='None', upsampling: str='Nearest', downsampling: str='First', output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
red_source_bandOptional[str]noNoneinferred from implementation.
green_source_bandOptional[str]noNoneinferred from implementation.
red_factorfloatno1.0inferred from implementation.
green_factorfloatno1.0inferred from implementation.
resample_typestrno'None'inferred from implementation.
upsamplingstrno'Nearest'inferred from implementation.
downsamplingstrno'First'inferred from implementation.
output_nameOptional[str]noNoneinferred from implementation.

Return Type

Optional[str]

inferred from implementation.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.ndti()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.

GPT.ndwi2 method

Normalized Difference Water.

File location: sarpyx/snapflow/engine.py:5301

Signature

ndwi2(self, green_source_band: Optional[str]=None, nir_source_band: Optional[str]=None, green_factor: float=1.0, nir_factor: float=1.0, resample_type: str='None', upsampling: str='Nearest', downsampling: str='First', output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
green_source_bandOptional[str]noNoneinferred from implementation.
nir_source_bandOptional[str]noNoneinferred from implementation.
green_factorfloatno1.0inferred from implementation.
nir_factorfloatno1.0inferred from implementation.
resample_typestrno'None'inferred from implementation.
upsamplingstrno'Nearest'inferred from implementation.
downsamplingstrno'First'inferred from implementation.
output_nameOptional[str]noNoneinferred from implementation.

Return Type

Optional[str]

inferred from implementation.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.ndwi2()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.

GPT.pssra method

Pigment Specific Simple.

File location: sarpyx/snapflow/engine.py:5328

Signature

pssra(self, red_source_band: Optional[str]=None, nir_source_band: Optional[str]=None, red_factor: float=1.0, nir_factor: float=1.0, resample_type: str='None', upsampling: str='Nearest', downsampling: str='First', output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
red_source_bandOptional[str]noNoneinferred from implementation.
nir_source_bandOptional[str]noNoneinferred from implementation.
red_factorfloatno1.0inferred from implementation.
nir_factorfloatno1.0inferred from implementation.
resample_typestrno'None'inferred from implementation.
upsamplingstrno'Nearest'inferred from implementation.
downsamplingstrno'First'inferred from implementation.
output_nameOptional[str]noNoneinferred from implementation.

Return Type

Optional[str]

inferred from implementation.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.pssra()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.

GPT.pvi method

Perpendicular Vegetation Index.

File location: sarpyx/snapflow/engine.py:5355

Signature

pvi(self, red_source_band: Optional[str]=None, nir_source_band: Optional[str]=None, red_factor: float=1.0, nir_factor: float=1.0, angle_soil_line_nir_axis: float=45.0, resample_type: str='None', upsampling: str='Nearest', downsampling: str='First', output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
red_source_bandOptional[str]noNoneinferred from implementation.
nir_source_bandOptional[str]noNoneinferred from implementation.
red_factorfloatno1.0inferred from implementation.
nir_factorfloatno1.0inferred from implementation.
angle_soil_line_nir_axisfloatno45.0inferred from implementation.
resample_typestrno'None'inferred from implementation.
upsamplingstrno'Nearest'inferred from implementation.
downsamplingstrno'First'inferred from implementation.
output_nameOptional[str]noNoneinferred from implementation.

Return Type

Optional[str]

inferred from implementation.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.pvi()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.

GPT.reip method

Red Edge Inflection.

File location: sarpyx/snapflow/engine.py:5384

Signature

reip(self, red_source_band4: Optional[str]=None, red_source_band5: Optional[str]=None, red_source_band6: Optional[str]=None, nir_source_band: Optional[str]=None, red_b4_factor: float=1.0, red_b5_factor: float=1.0, red_b6_factor: float=1.0, nir_factor: float=1.0, resample_type: str='None', upsampling: str='Nearest', downsampling: str='First', output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
red_source_band4Optional[str]noNoneinferred from implementation.
red_source_band5Optional[str]noNoneinferred from implementation.
red_source_band6Optional[str]noNoneinferred from implementation.
nir_source_bandOptional[str]noNoneinferred from implementation.
red_b4_factorfloatno1.0inferred from implementation.
red_b5_factorfloatno1.0inferred from implementation.
red_b6_factorfloatno1.0inferred from implementation.
nir_factorfloatno1.0inferred from implementation.
resample_typestrno'None'inferred from implementation.
upsamplingstrno'Nearest'inferred from implementation.
downsamplingstrno'First'inferred from implementation.
output_nameOptional[str]noNoneinferred from implementation.

Return Type

Optional[str]

inferred from implementation.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.reip()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.

GPT.ri method

Redness Index.

File location: sarpyx/snapflow/engine.py:5421

Signature

ri(self, red_source_band: Optional[str]=None, green_source_band: Optional[str]=None, red_factor: float=1.0, green_factor: float=1.0, resample_type: str='None', upsampling: str='Nearest', downsampling: str='First', output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
red_source_bandOptional[str]noNoneinferred from implementation.
green_source_bandOptional[str]noNoneinferred from implementation.
red_factorfloatno1.0inferred from implementation.
green_factorfloatno1.0inferred from implementation.
resample_typestrno'None'inferred from implementation.
upsamplingstrno'Nearest'inferred from implementation.
downsamplingstrno'First'inferred from implementation.
output_nameOptional[str]noNoneinferred from implementation.

Return Type

Optional[str]

inferred from implementation.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.ri()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.

GPT.c2rcc_msi method

C2RCC MSI atmospheric correction.

File location: sarpyx/snapflow/engine.py:5448

Signature

c2rcc_msi(self, valid_pixel_expression: Optional[str]='B8 > 0 && B8 < 0.1', salinity: float=35.0, temperature: float=15.0, ozone: float=330.0, press: float=1000.0, elevation: float=0.0, tsm_fac: float=1.06, tsm_exp: float=0.942, chl_exp: float=1.04, chl_fac: float=21.0, threshold_rtosa_oos: float=0.05, threshold_ac_reflec_oos: float=0.1, threshold_cloud_t_down865: float=0.955, atmospheric_aux_data_path: Optional[str]=None, alternative_nn_path: Optional[str]=None, net_set: str='C2RCC-Nets', output_as_rrs: bool=False, derive_rw_from_path_and_transmittance: bool=False, use_ecmwf_aux_data: bool=False, dem_name: str='Copernicus 90m Global DEM', output_rtoa: bool=True, output_rtosa_gc: bool=False, output_rtosa_gc_aann: bool=False, output_rpath: bool=False, output_tdown: bool=False, output_tup: bool=False, output_ac_reflectance: bool=True, output_rhown: bool=True, output_oos: bool=False, output_kd: bool=True, output_uncertainties: bool=True, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
valid_pixel_expressionOptional[str]no'B8 > 0 && B8 < 0.1'inferred from implementation.
salinityfloatno35.0inferred from implementation.
temperaturefloatno15.0inferred from implementation.
ozonefloatno330.0inferred from implementation.
pressfloatno1000.0inferred from implementation.
elevationfloatno0.0inferred from implementation.
tsm_facfloatno1.06inferred from implementation.
tsm_expfloatno0.942inferred from implementation.
chl_expfloatno1.04inferred from implementation.
chl_facfloatno21.0inferred from implementation.
threshold_rtosa_oosfloatno0.05inferred from implementation.
threshold_ac_reflec_oosfloatno0.1inferred from implementation.
threshold_cloud_t_down865floatno0.955inferred from implementation.
atmospheric_aux_data_pathOptional[str]noNoneinferred from implementation.
alternative_nn_pathOptional[str]noNoneinferred from implementation.
net_setstrno'C2RCC-Nets'inferred from implementation.
output_as_rrsboolnoFalseinferred from implementation.
derive_rw_from_path_and_transmittanceboolnoFalseinferred from implementation.
use_ecmwf_aux_databoolnoFalseinferred from implementation.
dem_namestrno'Copernicus 90m Global DEM'inferred from implementation.
output_rtoaboolnoTrueinferred from implementation.
output_rtosa_gcboolnoFalseinferred from implementation.
output_rtosa_gc_aannboolnoFalseinferred from implementation.
output_rpathboolnoFalseinferred from implementation.
output_tdownboolnoFalseinferred from implementation.
output_tupboolnoFalseinferred from implementation.
output_ac_reflectanceboolnoTrueinferred from implementation.
output_rhownboolnoTrueinferred from implementation.
output_oosboolnoFalseinferred from implementation.
output_kdboolnoTrueinferred from implementation.
output_uncertaintiesboolnoTrueinferred from implementation.
output_nameOptional[str]noNoneinferred from implementation.

Return Type

Optional[str]

inferred from implementation.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.c2rcc_msi()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.

GPT.c2rcc_olci method

C2RCC OLCI atmospheric correction.

File location: sarpyx/snapflow/engine.py:5524

Signature

c2rcc_olci(self, valid_pixel_expression: Optional[str]='!quality_flags.invalid && (!quality_flags.land || quality_flags.fresh_inland_water)', salinity: float=35.0, temperature: float=15.0, ozone: float=330.0, press: float=1000.0, tsm_fac: float=1.06, tsm_exp: float=0.942, chl_exp: float=1.04, chl_fac: float=21.0, threshold_rtosa_oos: float=0.01, threshold_ac_reflec_oos: float=0.15, threshold_cloud_t_down865: float=0.955, atmospheric_aux_data_path: Optional[str]=None, alternative_nn_path: Optional[str]=None, output_as_rrs: bool=False, derive_rw_from_path_and_transmittance: bool=False, use_ecmwf_aux_data: bool=True, dem_name: Optional[str]=None, output_rtoa: bool=True, output_rtosa_gc: bool=False, output_rtosa_gc_aann: bool=False, output_rpath: bool=False, output_tdown: bool=False, output_tup: bool=False, output_ac_reflectance: bool=True, output_rhown: bool=True, output_oos: bool=False, output_kd: bool=True, output_uncertainties: bool=True, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
valid_pixel_expressionOptional[str]no'!quality_flags.invalid && (!quality_flags.land || quality_flags.fresh_inland_water)'inferred from implementation.
salinityfloatno35.0inferred from implementation.
temperaturefloatno15.0inferred from implementation.
ozonefloatno330.0inferred from implementation.
pressfloatno1000.0inferred from implementation.
tsm_facfloatno1.06inferred from implementation.
tsm_expfloatno0.942inferred from implementation.
chl_expfloatno1.04inferred from implementation.
chl_facfloatno21.0inferred from implementation.
threshold_rtosa_oosfloatno0.01inferred from implementation.
threshold_ac_reflec_oosfloatno0.15inferred from implementation.
threshold_cloud_t_down865floatno0.955inferred from implementation.
atmospheric_aux_data_pathOptional[str]noNoneinferred from implementation.
alternative_nn_pathOptional[str]noNoneinferred from implementation.
output_as_rrsboolnoFalseinferred from implementation.
derive_rw_from_path_and_transmittanceboolnoFalseinferred from implementation.
use_ecmwf_aux_databoolnoTrueinferred from implementation.
dem_nameOptional[str]noNoneinferred from implementation.
output_rtoaboolnoTrueinferred from implementation.
output_rtosa_gcboolnoFalseinferred from implementation.
output_rtosa_gc_aannboolnoFalseinferred from implementation.
output_rpathboolnoFalseinferred from implementation.
output_tdownboolnoFalseinferred from implementation.
output_tupboolnoFalseinferred from implementation.
output_ac_reflectanceboolnoTrueinferred from implementation.
output_rhownboolnoTrueinferred from implementation.
output_oosboolnoFalseinferred from implementation.
output_kdboolnoTrueinferred from implementation.
output_uncertaintiesboolnoTrueinferred from implementation.
output_nameOptional[str]noNoneinferred from implementation.

Return Type

Optional[str]

inferred from implementation.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.c2rcc_olci()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.

GPT.c2rcc_s2_msi method

C2RCC S2 MSI correction.

File location: sarpyx/snapflow/engine.py:5597

Signature

c2rcc_s2_msi(self, valid_pixel_expression: Optional[str]='B8 > 0 && B8 < 0.1', salinity: float=35.0, temperature: float=15.0, ozone: float=330.0, press: float=1000.0, elevation: float=0.0, tsm_fac: float=1.06, tsm_exp: float=0.942, chl_exp: float=1.04, chl_fac: float=21.0, threshold_rtosa_oos: float=0.05, threshold_ac_reflec_oos: float=0.1, threshold_cloud_t_down865: float=0.955, atmospheric_aux_data_path: Optional[str]=None, alternative_nn_path: Optional[str]=None, net_set: str='C2RCC-Nets', output_as_rrs: bool=False, derive_rw_from_path_and_transmittance: bool=False, use_ecmwf_aux_data: bool=False, dem_name: str='Copernicus 90m Global DEM', output_rtoa: bool=True, output_rtosa_gc: bool=False, output_rtosa_gc_aann: bool=False, output_rpath: bool=False, output_tdown: bool=False, output_tup: bool=False, output_ac_reflectance: bool=True, output_rhown: bool=True, output_oos: bool=False, output_kd: bool=True, output_uncertainties: bool=True, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
valid_pixel_expressionOptional[str]no'B8 > 0 && B8 < 0.1'inferred from implementation.
salinityfloatno35.0inferred from implementation.
temperaturefloatno15.0inferred from implementation.
ozonefloatno330.0inferred from implementation.
pressfloatno1000.0inferred from implementation.
elevationfloatno0.0inferred from implementation.
tsm_facfloatno1.06inferred from implementation.
tsm_expfloatno0.942inferred from implementation.
chl_expfloatno1.04inferred from implementation.
chl_facfloatno21.0inferred from implementation.
threshold_rtosa_oosfloatno0.05inferred from implementation.
threshold_ac_reflec_oosfloatno0.1inferred from implementation.
threshold_cloud_t_down865floatno0.955inferred from implementation.
atmospheric_aux_data_pathOptional[str]noNoneinferred from implementation.
alternative_nn_pathOptional[str]noNoneinferred from implementation.
net_setstrno'C2RCC-Nets'inferred from implementation.
output_as_rrsboolnoFalseinferred from implementation.
derive_rw_from_path_and_transmittanceboolnoFalseinferred from implementation.
use_ecmwf_aux_databoolnoFalseinferred from implementation.
dem_namestrno'Copernicus 90m Global DEM'inferred from implementation.
output_rtoaboolnoTrueinferred from implementation.
output_rtosa_gcboolnoFalseinferred from implementation.
output_rtosa_gc_aannboolnoFalseinferred from implementation.
output_rpathboolnoFalseinferred from implementation.
output_tdownboolnoFalseinferred from implementation.
output_tupboolnoFalseinferred from implementation.
output_ac_reflectanceboolnoTrueinferred from implementation.
output_rhownboolnoTrueinferred from implementation.
output_oosboolnoFalseinferred from implementation.
output_kdboolnoTrueinferred from implementation.
output_uncertaintiesboolnoTrueinferred from implementation.
output_nameOptional[str]noNoneinferred from implementation.

Return Type

Optional[str]

inferred from implementation.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.c2rcc_s2_msi()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.

GPT.biophysical method

Biophysical processor.

File location: sarpyx/snapflow/engine.py:5673

Signature

biophysical(self, sensor: str='S2A', resolution: str='60', compute_lai: bool=True, compute_fapar: bool=True, compute_fcover: bool=True, compute_cab: bool=True, compute_cw: bool=True, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
sensorstrno'S2A'inferred from implementation.
resolutionstrno'60'inferred from implementation.
compute_laiboolnoTrueinferred from implementation.
compute_faparboolnoTrueinferred from implementation.
compute_fcoverboolnoTrueinferred from implementation.
compute_cabboolnoTrueinferred from implementation.
compute_cwboolnoTrueinferred from implementation.
output_nameOptional[str]noNoneinferred from implementation.

Return Type

Optional[str]

inferred from implementation.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.biophysical()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.

GPT.biophysical_10m method

Biophysical processor 10m.

File location: sarpyx/snapflow/engine.py:5698

Signature

biophysical_10m(self, sensor: str='S2A_10m', compute_lai: bool=True, compute_fapar: bool=True, compute_fcover: bool=True, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
sensorstrno'S2A_10m'inferred from implementation.
compute_laiboolnoTrueinferred from implementation.
compute_faparboolnoTrueinferred from implementation.
compute_fcoverboolnoTrueinferred from implementation.
output_nameOptional[str]noNoneinferred from implementation.

Return Type

Optional[str]

inferred from implementation.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.biophysical_10m()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.

GPT.biophysical_landsat8 method

Biophysical Landsat8 processor.

File location: sarpyx/snapflow/engine.py:5717

Signature

biophysical_landsat8(self, compute_lai: bool=True, compute_fapar: bool=True, compute_fcover: bool=True, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
compute_laiboolnoTrueinferred from implementation.
compute_faparboolnoTrueinferred from implementation.
compute_fcoverboolnoTrueinferred from implementation.
output_nameOptional[str]noNoneinferred from implementation.

Return Type

Optional[str]

inferred from implementation.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.biophysical_landsat8()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.

GPT.compactpol_radar_vegetation_index method

Compact-pol radar vegetation index.

File location: sarpyx/snapflow/engine.py:5734

Signature

compactpol_radar_vegetation_index(self, window_size_str: str='3', output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
window_size_strstrno'3'inferred from implementation.
output_nameOptional[str]noNoneinferred from implementation.

Return Type

Optional[str]

inferred from implementation.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.compactpol_radar_vegetation_index()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.

GPT.generalized_radar_vegetation_indices method

Generalized radar vegetation indices.

File location: sarpyx/snapflow/engine.py:5745

Signature

generalized_radar_vegetation_indices(self, window_size: int=5, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
window_sizeintno5inferred from implementation.
output_nameOptional[str]noNoneinferred from implementation.

Return Type

Optional[str]

inferred from implementation.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.generalized_radar_vegetation_indices()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.

GPT.radar_vegetation_index method

Radar vegetation index.

File location: sarpyx/snapflow/engine.py:5756

Signature

radar_vegetation_index(self, window_size: int=5, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
window_sizeintno5inferred from implementation.
output_nameOptional[str]noNoneinferred from implementation.

Return Type

Optional[str]

inferred from implementation.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.radar_vegetation_index()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.

GPT.change_detection method

Log ratio change detection.

File location: sarpyx/snapflow/engine.py:5767

Signature

change_detection(self, source_bands: Optional[List[str]]=None, mask_upper_threshold: float=2.0, mask_lower_threshold: float=-2.0, include_source_bands: bool=False, output_difference: bool=False, output_ratio: bool=False, output_log_ratio: bool=True, output_normalized_ratio: bool=False, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
source_bandsOptional[List[str]]noNoneinferred from implementation.
mask_upper_thresholdfloatno2.0inferred from implementation.
mask_lower_thresholdfloatno-2.0inferred from implementation.
include_source_bandsboolnoFalseinferred from implementation.
output_differenceboolnoFalseinferred from implementation.
output_ratioboolnoFalseinferred from implementation.
output_log_ratioboolnoTrueinferred from implementation.
output_normalized_ratioboolnoFalseinferred from implementation.
output_nameOptional[str]noNoneinferred from implementation.

Return Type

Optional[str]

inferred from implementation.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.change_detection()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.

GPT.change_vector_analysis method

Change vector analysis.

File location: sarpyx/snapflow/engine.py:5795

Signature

change_vector_analysis(self, source_band1: Optional[str]=None, source_band2: Optional[str]=None, magnitude_threshold: str='0', output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
source_band1Optional[str]noNoneinferred from implementation.
source_band2Optional[str]noNoneinferred from implementation.
magnitude_thresholdstrno'0'inferred from implementation.
output_nameOptional[str]noNoneinferred from implementation.

Return Type

Optional[str]

inferred from implementation.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.change_vector_analysis()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.

GPT.add_land_cover method

Add land cover band.

File location: sarpyx/snapflow/engine.py:5812

Signature

add_land_cover(self, land_cover_names: Optional[List[str]]=None, external_files: Optional[List[str]]=None, resampling_method: str='NEAREST_NEIGHBOUR', output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
land_cover_namesOptional[List[str]]noNoneinferred from implementation.
external_filesOptional[List[str]]noNoneinferred from implementation.
resampling_methodstrno'NEAREST_NEIGHBOUR'inferred from implementation.
output_nameOptional[str]noNoneinferred from implementation.

Return Type

Optional[str]

inferred from implementation.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.add_land_cover()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.

GPT.cloud_prob method

Cloud probability detection.

File location: sarpyx/snapflow/engine.py:5829

Signature

cloud_prob(self, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
output_nameOptional[str]noNoneinferred from implementation.

Return Type

Optional[str]

inferred from implementation.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.cloud_prob()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.

GPT.double_difference_interferogram method

Compute double difference interferogram.

File location: sarpyx/snapflow/engine.py:5838

Signature

double_difference_interferogram(self, coh_win_size: str='5', output_coherence: bool=False, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
coh_win_sizestrno'5'inferred from implementation.
output_coherenceboolnoFalseinferred from implementation.
output_nameOptional[str]noNoneinferred from implementation.

Return Type

Optional[str]

inferred from implementation.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.double_difference_interferogram()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.

GPT.add_elevation method

Creates DEM band.

File location: sarpyx/snapflow/engine.py:5853

Signature

add_elevation(self, dem_name: str='SRTM 3Sec', dem_resampling_method: str='BICUBIC_INTERPOLATION', elevation_band_name: str='elevation', external_dem_file: Optional[str]=None, external_dem_no_data_value: float=0.0, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
dem_namestrno'SRTM 3Sec'inferred from implementation.
dem_resampling_methodstrno'BICUBIC_INTERPOLATION'inferred from implementation.
elevation_band_namestrno'elevation'inferred from implementation.
external_dem_fileOptional[str]noNoneinferred from implementation.
external_dem_no_data_valuefloatno0.0inferred from implementation.
output_nameOptional[str]noNoneinferred from implementation.

Return Type

Optional[str]

inferred from implementation.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.add_elevation()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.

GPT.fill_dem_hole method

Fill DEM holes.

File location: sarpyx/snapflow/engine.py:5875

Signature

fill_dem_hole(self, no_data_value: float=0.0, source_bands: Optional[List[str]]=None, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
no_data_valuefloatno0.0inferred from implementation.
source_bandsOptional[List[str]]noNoneinferred from implementation.
output_nameOptional[str]noNoneinferred from implementation.

Return Type

Optional[str]

inferred from implementation.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.fill_dem_hole()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.

GPT.compute_slope_aspect method

Compute slope and aspect.

File location: sarpyx/snapflow/engine.py:5889

Signature

compute_slope_aspect(self, dem_band_name: str='elevation', dem_name: str='SRTM 1Sec HGT', dem_resampling_method: str='BILINEAR_INTERPOLATION', external_dem_apply_egm: bool=False, external_dem_file: Optional[str]=None, external_dem_no_data_value: float=0.0, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
dem_band_namestrno'elevation'inferred from implementation.
dem_namestrno'SRTM 1Sec HGT'inferred from implementation.
dem_resampling_methodstrno'BILINEAR_INTERPOLATION'inferred from implementation.
external_dem_apply_egmboolnoFalseinferred from implementation.
external_dem_fileOptional[str]noNoneinferred from implementation.
external_dem_no_data_valuefloatno0.0inferred from implementation.
output_nameOptional[str]noNoneinferred from implementation.

Return Type

Optional[str]

inferred from implementation.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.compute_slope_aspect()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.

GPT.cp_decomposition method

Compact polarimetric decomposition.

File location: sarpyx/snapflow/engine.py:5913

Signature

cp_decomposition(self, decomposition: str='M-Chi Decomposition', window_size_x_str: str='5', window_size_y_str: str='5', compute_alpha_by_t3: bool=True, output_rvog: bool=True, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
decompositionstrno'M-Chi Decomposition'inferred from implementation.
window_size_x_strstrno'5'inferred from implementation.
window_size_y_strstrno'5'inferred from implementation.
compute_alpha_by_t3boolnoTrueinferred from implementation.
output_rvogboolnoTrueinferred from implementation.
output_nameOptional[str]noNoneinferred from implementation.

Return Type

Optional[str]

inferred from implementation.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.cp_decomposition()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.

GPT.cp_simulation method

Compact pol simulation.

File location: sarpyx/snapflow/engine.py:5934

Signature

cp_simulation(self, compact_mode: str='Right Circular Hybrid Mode', output_format: str='Covariance Matrix C2', noise_power: float=-25.0, simulate_noise_floor: bool=False, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
compact_modestrno'Right Circular Hybrid Mode'inferred from implementation.
output_formatstrno'Covariance Matrix C2'inferred from implementation.
noise_powerfloatno-25.0inferred from implementation.
simulate_noise_floorboolnoFalseinferred from implementation.
output_nameOptional[str]noNoneinferred from implementation.

Return Type

Optional[str]

inferred from implementation.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.cp_simulation()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.

GPT.cp_stokes_parameters method

Compact pol Stokes parameters.

File location: sarpyx/snapflow/engine.py:5953

Signature

cp_stokes_parameters(self, window_size_x_str: str='5', window_size_y_str: str='5', output_stokes_vector: bool=False, output_degree_of_polarization: bool=True, output_degree_of_depolarization: bool=True, output_degree_of_circularity: bool=True, output_degree_of_ellipticity: bool=True, output_cpr: bool=True, output_lpr: bool=True, output_relative_phase: bool=True, output_alphas: bool=True, output_conformity: bool=True, output_phase_phi: bool=True, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
window_size_x_strstrno'5'inferred from implementation.
window_size_y_strstrno'5'inferred from implementation.
output_stokes_vectorboolnoFalseinferred from implementation.
output_degree_of_polarizationboolnoTrueinferred from implementation.
output_degree_of_depolarizationboolnoTrueinferred from implementation.
output_degree_of_circularityboolnoTrueinferred from implementation.
output_degree_of_ellipticityboolnoTrueinferred from implementation.
output_cprboolnoTrueinferred from implementation.
output_lprboolnoTrueinferred from implementation.
output_relative_phaseboolnoTrueinferred from implementation.
output_alphasboolnoTrueinferred from implementation.
output_conformityboolnoTrueinferred from implementation.
output_phase_phiboolnoTrueinferred from implementation.
output_nameOptional[str]noNoneinferred from implementation.

Return Type

Optional[str]

inferred from implementation.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.cp_stokes_parameters()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.

GPT.coregistration method

Coregister two rasters.

File location: sarpyx/snapflow/engine.py:5990

Signature

coregistration(self, master_source_band: Optional[str]=None, slave_source_band: Optional[str]=None, levels: int=6, rank: int=4, iterations: int=2, radius: str='32, 28, 24, 20, 16, 12, 8', output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
master_source_bandOptional[str]noNoneinferred from implementation.
slave_source_bandOptional[str]noNoneinferred from implementation.
levelsintno6inferred from implementation.
rankintno4inferred from implementation.
iterationsintno2inferred from implementation.
radiusstrno'32, 28, 24, 20, 16, 12, 8'inferred from implementation.
output_nameOptional[str]noNoneinferred from implementation.

Return Type

Optional[str]

inferred from implementation.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.coregistration()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.

GPT.ellipsoid_correction_gg method

GG ellipsoid correction.

File location: sarpyx/snapflow/engine.py:6015

Signature

ellipsoid_correction_gg(self, img_resampling_method: str='BILINEAR_INTERPOLATION', map_projection: str='WGS84(DD)', source_bands: Optional[List[str]]=None, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
img_resampling_methodstrno'BILINEAR_INTERPOLATION'inferred from implementation.
map_projectionstrno'WGS84(DD)'inferred from implementation.
source_bandsOptional[List[str]]noNoneinferred from implementation.
output_nameOptional[str]noNoneinferred from implementation.

Return Type

Optional[str]

inferred from implementation.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.ellipsoid_correction_gg()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.

GPT.cross_resampling method

Cross resampling operation.

File location: sarpyx/snapflow/engine.py:6033

Signature

cross_resampling(self, warp_polynomial_order: int=2, interpolation_method: str='Cubic convolution (6 points)', target_geometry: str='ERS', output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
warp_polynomial_orderintno2inferred from implementation.
interpolation_methodstrno'Cubic convolution (6 points)'inferred from implementation.
target_geometrystrno'ERS'inferred from implementation.
output_nameOptional[str]noNoneinferred from implementation.

Return Type

Optional[str]

inferred from implementation.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.cross_resampling()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.

GPT.bands_difference method

Bands difference operation.

File location: sarpyx/snapflow/engine.py:6050

Signature

bands_difference(self, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
output_nameOptional[str]noNoneinferred from implementation.

Return Type

Optional[str]

inferred from implementation.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.bands_difference()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.

GPT.bands_extractor method

Extract specific bands.

File location: sarpyx/snapflow/engine.py:6059

Signature

bands_extractor(self, source_band_names: Optional[List[str]]=None, source_mask_names: Optional[List[str]]=None, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
source_band_namesOptional[List[str]]noNoneinferred from implementation.
source_mask_namesOptional[List[str]]noNoneinferred from implementation.
output_nameOptional[str]noNoneinferred from implementation.

Return Type

Optional[str]

inferred from implementation.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.bands_extractor()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.

GPT.binning method

Spatial temporal binning.

File location: sarpyx/snapflow/engine.py:6075

Signature

binning(self, num_rows: int=2160, mask_expr: Optional[str]=None, source_product_paths: Optional[List[str]]=None, source_product_format: Optional[str]=None, region: Optional[str]=None, start_date_time: Optional[str]=None, period_duration: Optional[float]=None, time_filter_method: str='NONE', min_data_hour: Optional[float]=None, super_sampling: int=1, max_distance_on_earth: int=-1, output_binned_data: bool=False, output_mapped_product: bool=True, output_type: str='Product', output_format: str='BEAM-DIMAP', output_file: Optional[str]=None, metadata_aggregator_name: str='NAME', output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
num_rowsintno2160inferred from implementation.
mask_exprOptional[str]noNoneinferred from implementation.
source_product_pathsOptional[List[str]]noNoneinferred from implementation.
source_product_formatOptional[str]noNoneinferred from implementation.
regionOptional[str]noNoneinferred from implementation.
start_date_timeOptional[str]noNoneinferred from implementation.
period_durationOptional[float]noNoneinferred from implementation.
time_filter_methodstrno'NONE'inferred from implementation.
min_data_hourOptional[float]noNoneinferred from implementation.
super_samplingintno1inferred from implementation.
max_distance_on_earthintno-1inferred from implementation.
output_binned_databoolnoFalseinferred from implementation.
output_mapped_productboolnoTrueinferred from implementation.
output_typestrno'Product'inferred from implementation.
output_formatstrno'BEAM-DIMAP'inferred from implementation.
output_fileOptional[str]noNoneinferred from implementation.
metadata_aggregator_namestrno'NAME'inferred from implementation.
output_nameOptional[str]noNoneinferred from implementation.

Return Type

Optional[str]

inferred from implementation.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.binning()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.

GPT.fu_classification method

Forel-Ule classification.

File location: sarpyx/snapflow/engine.py:6128

Signature

fu_classification(self, copy_all_source_bands: bool=False, input_is_irradiance_reflectance: bool=False, valid_expression: Optional[str]=None, reflectance_name_pattern: Optional[str]=None, instrument: str='AUTO_DETECT', include_dominant_lambda: bool=False, include_intermediate_results: bool=True, output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
copy_all_source_bandsboolnoFalseinferred from implementation.
input_is_irradiance_reflectanceboolnoFalseinferred from implementation.
valid_expressionOptional[str]noNoneinferred from implementation.
reflectance_name_patternOptional[str]noNoneinferred from implementation.
instrumentstrno'AUTO_DETECT'inferred from implementation.
include_dominant_lambdaboolnoFalseinferred from implementation.
include_intermediate_resultsboolnoTrueinferred from implementation.
output_nameOptional[str]noNoneinferred from implementation.

Return Type

Optional[str]

inferred from implementation.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.fu_classification()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.

GPT.flh_mci method

Fluorescence line height.

File location: sarpyx/snapflow/engine.py:6155

Signature

flh_mci(self, preset: str='NONE', lower_baseline_band_name: Optional[str]=None, upper_baseline_band_name: Optional[str]=None, signal_band_name: Optional[str]=None, line_height_band_name: Optional[str]=None, slope: bool=True, slope_band_name: Optional[str]=None, mask_expression: Optional[str]=None, cloud_correction_factor: float=1.005, invalid_flh_mci_value: float=float('nan'), output_name: Optional[str]=None) -> Optional[str]

Parameters

ParameterTypeRequiredDefaultDescription
presetstrno'NONE'inferred from implementation.
lower_baseline_band_nameOptional[str]noNoneinferred from implementation.
upper_baseline_band_nameOptional[str]noNoneinferred from implementation.
signal_band_nameOptional[str]noNoneinferred from implementation.
line_height_band_nameOptional[str]noNoneinferred from implementation.
slopeboolnoTrueinferred from implementation.
slope_band_nameOptional[str]noNoneinferred from implementation.
mask_expressionOptional[str]noNoneinferred from implementation.
cloud_correction_factorfloatno1.005inferred from implementation.
invalid_flh_mci_valuefloatnofloat('nan')inferred from implementation.
output_nameOptional[str]noNoneinferred from implementation.

Return Type

Optional[str]

inferred from implementation.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

  • inferred from implementation

Example Usage

from sarpyx.snapflow.engine import GPT

# Constructor arguments are inferred from implementation.
obj = GPT(...)  # inferred from implementation
result = obj.flh_mci()

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.