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NAME

m.neural_network.postprocessing.snapref - Merges classification vector with reference data.

KEYWORDS

vector

SYNOPSIS

m.neural_network.postprocessing.snapref
m.neural_network.postprocessing.snapref --help
m.neural_network.postprocessing.snapref a_input_classification=name b_input_reference=name output=name class_col=name merge_col=name [merge_col_null_value=integer] rmarea_thres_inside=float rmarea_where_inside=sql_query rmarea_thres_outside=float [snap=float] rmarea_where_outside=sql_query [--overwrite] [--help] [--verbose] [--quiet] [--ui]

Flags:

--overwrite
Allow output files to overwrite existing files
--help
Print usage summary
--verbose
Verbose module output
--quiet
Quiet module output
--ui
Force launching GUI dialog

Parameters:

a_input_classification=name [required]
Name of input vector map
Input vector classification (a_<...> for attribute columns)
b_input_reference=name [required]
Name of input vector map
Reference data for merging (b_<...> for attribute columns)
output=name [required]
merged vector output
class_col=name [required]
Attribute column containing attribute of class number
Default: class_number
merge_col=name [required]
Attribute column containing attribute of reference data, along which should be merged
merge_col_null_value=integer
Dummy value for null value areas of reference data (should be value, which is not contained within the not-null attributes)
Default: -1
rmarea_thres_inside=float [required]
Threshold for removing small areas, inside reference area
rmarea_where_inside=sql_query [required]
WHERE conditions of SQL statement without 'where' keyword
User specific SQL query for cleaning up, inside reference area (Use a_ and b_ attributes)
rmarea_thres_outside=float [required]
Threshold for removing small areas, outside reference area
snap=float
Snapping threshold in map units
Default: 0.0001
rmarea_where_outside=sql_query [required]
WHERE conditions of SQL statement without 'where' keyword
User specific SQL query for cleaning up, outside reference area (Use a_ and b_ attributes)

Table of contents

DESCRIPTION

m.neural_network.postprocessing.snapref merges classification vector with reference data.

EXAMPLE

Cleanup with ALKIS Gebäude

m.neural_network.postprocessing.snapref \
    a_input_classification=classification_vect b_input_reference=AX_Gebaeude \
    output=classification_vect_clean_v01 \
    merge_col=gebaeudefunktion \
    rmarea_thres_inside=50 rmarea_where_inside="a_class_number <> 1 and b_gebaeudefunktion <> -1" \
    rmarea_thres_outside=150 rmarea_where_outside="a_class_number = 1 and b_gebaeudefunktion = -1 and compact > 3.8"


SEE ALSO

v.overlay,

AUTHORS

Lina Krisztian, mundialis

SOURCE CODE

Available at: m.neural_network.postprocessing.snapref source code (history)

Accessed: Monday Jul 27 12:26:01 2026


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