def tag_polygons_by_grid(polygons, grid, threshold=0, tag='affected'):
"""Tag polygons by raster values
Args:
* polygons: Polygon layer
* grid: Raster layer
* threshold: Threshold for grid value to tag polygon
* tag: Name of new tag
Returns:
Polygon layer: Same as input polygon but with extra attribute tag
set according to grid values
"""
verify(polygons.is_polygon_data)
verify(grid.is_raster)
polygon_attributes = polygons.get_data()
polygon_geometry = polygons.get_geometry(as_geometry_objects=True)
# Separate grid points by polygon
res, _ = clip_grid_by_polygons(
grid.get_data(),
grid.get_geotransform(),
polygon_geometry)
# Create new polygon layer with tag set according to grid values
# and threshold
new_attributes = []
for i, (_, values) in enumerate(res):
# For each polygon check if any grid value in it exceeds the threshold
affected = False
for val in values:
# Check each grid value in this polygon
if val > threshold:
affected = True
# Existing attributes for this polygon
attr = polygon_attributes[i].copy()
# Create tagged polygon feature
if affected:
attr[tag] = True
else:
attr[tag] = False
new_attributes.append(attr)
R = Vector(data=new_attributes,
projection=polygons.get_projection(),
geometry=polygon_geometry,
name='%s_tagged_by_%s' % (polygons.name, grid.name))
return R
def interpolate_polygon_raster(source,
target,
layer_name=None,
attribute_name=None):
"""Interpolate from polygon layer to raster data
Args
* source: Polygon data set
* target: Raster data set
* layer_name: Optional name of returned interpolated layer.
If None the name of source is used for the returned layer.
* attribute_name: Name for new attribute.
If None (default) the name of layer target is used
Output
I: Vector data set; points located as target with
values interpolated from source
Note:
Each point in the resulting dataset will have an attribute
'polygon_id' which refers to the polygon it belongs to.
"""
# Input checks
verify(target.is_raster)
verify(source.is_vector)
verify(source.is_polygon_data)
# Run underlying clipping algorithm
polygon_geometry = source.get_geometry(as_geometry_objects=True)
polygon_attributes = source.get_data()
res = clip_grid_by_polygons(target.get_data(scaling=False),
target.get_geotransform(), polygon_geometry)
# Create one new point layer with interpolated attributes
new_geometry = []
new_attributes = []
for i, (geometry, values) in enumerate(res):
# For each polygon assign attributes to points that fall inside it
for j, geom in enumerate(geometry):
attr = polygon_attributes[i].copy() # Attributes for this polygon
attr[attribute_name] = values[j] # Attribute value from grid cell
attr['polygon_id'] = i # Store id for associated polygon
new_attributes.append(attr)
new_geometry.append(geom)
R = Vector(data=new_attributes,
projection=source.get_projection(),
geometry=new_geometry,
name=layer_name)
return R
def interpolate_polygon_raster(source, target,
layer_name=None, attribute_name=None):
"""Interpolate from polygon layer to raster data
Args
* source: Polygon data set
* target: Raster data set
* layer_name: Optional name of returned interpolated layer.
If None the name of source is used for the returned layer.
* attribute_name: Name for new attribute.
If None (default) the name of layer target is used
Output
I: Vector data set; points located as target with
values interpolated from source
Note:
Each point in the resulting dataset will have an attribute
'polygon_id' which refers to the polygon it belongs to.
"""
# Input checks
verify(target.is_raster)
verify(source.is_vector)
verify(source.is_polygon_data)
# Run underlying clipping algorithm
polygon_geometry = source.get_geometry(as_geometry_objects=True)
polygon_attributes = source.get_data()
res = clip_grid_by_polygons(target.get_data(scaling=False),
target.get_geotransform(),
polygon_geometry)
# Create one new point layer with interpolated attributes
new_geometry = []
new_attributes = []
for i, (geometry, values) in enumerate(res):
# For each polygon assign attributes to points that fall inside it
for j, geom in enumerate(geometry):
attr = polygon_attributes[i].copy() # Attributes for this polygon
attr[attribute_name] = values[j] # Attribute value from grid cell
attr['polygon_id'] = i # Store id for associated polygon
new_attributes.append(attr)
new_geometry.append(geom)
R = Vector(data=new_attributes,
projection=source.get_projection(),
geometry=new_geometry,
name=layer_name)
return R
def tag_polygons_by_grid(polygons, grid, threshold=0, tag='affected'):
"""Tag polygons by raster values
Args:
* polygons: Polygon layer
* grid: Raster layer
* threshold: Threshold for grid value to tag polygon
* tag: Name of new tag
Returns:
Polygon layer: Same as input polygon but with extra attribute tag
set according to grid values
"""
verify(polygons.is_polygon_data)
verify(grid.is_raster)
polygon_attributes = polygons.get_data()
polygon_geometry = polygons.get_geometry(as_geometry_objects=True)
# Separate grid points by polygon
res, _ = clip_grid_by_polygons(grid.get_data(), grid.get_geotransform(),
polygon_geometry)
# Create new polygon layer with tag set according to grid values
# and threshold
new_attributes = []
for i, (_, values) in enumerate(res):
# For each polygon check if any grid value in it exceeds the threshold
affected = False
for val in values:
# Check each grid value in this polygon
if val > threshold:
affected = True
# Existing attributes for this polygon
attr = polygon_attributes[i].copy()
# Create tagged polygon feature
if affected:
attr[tag] = True
else:
attr[tag] = False
new_attributes.append(attr)
R = Vector(data=new_attributes,
projection=polygons.get_projection(),
geometry=polygon_geometry,
name='%s_tagged_by_%s' % (polygons.name, grid.name))
return R
def interpolate_polygon_raster(source,
target,
layer_name=None,
attribute_name=None):
"""Interpolate from polygon layer to raster data.
.. note:
Each point in the resulting dataset will have an attribute
'polygon_id' which refers to the polygon it belongs to and
'grid_point' which refers to the grid point of the target.
:param source: Polygon data set.
:type source: Vector
:param target: Raster data set.
:type target: Raster
:param layer_name: Optional name of returned interpolated layer. If None
the name of source is used for the returned layer.
:type layer_name: basestring
:param attribute_name: Name for new attribute. If None (default) the name
of layer target is used
:type attribute_name: basestring
:returns: Tuple of Vector (points located as target with values
interpolated from source) and Raster (raster data that are coincide
with the source)
:rtype: Vector
"""
# Input checks
verify(source.is_polygon_data)
verify(target.is_raster)
# Run underlying clipping algorithm
polygon_geometry = source.get_geometry(as_geometry_objects=True)
polygon_attributes = source.get_data()
covered_source, covered_target = clip_grid_by_polygons(
target.get_data(scaling=False), target.get_geotransform(),
polygon_geometry)
# Create one new point layer with interpolated attributes
new_geometry = []
new_attributes = []
for i, (geometry, values) in enumerate(covered_source):
# For each polygon assign attributes to points that fall inside it
for j, geom in enumerate(geometry):
attr = polygon_attributes[i].copy() # Attributes for this polygon
attr[attribute_name] = values[j] # Attribute value from grid cell
attr['polygon_id'] = i # Store id for associated polygon
attr['grid_point'] = geom # Store grid point for associated grid
new_attributes.append(attr)
new_geometry.append(geom)
interpolated_layer = Vector(data=new_attributes,
projection=source.get_projection(),
geometry=new_geometry,
name=layer_name)
covered_target = Raster(data=covered_target,
projection=target.get_projection(),
geotransform=target.get_geotransform(),
name=layer_name)
return interpolated_layer, covered_target
def interpolate_polygon_raster(
source, target, layer_name=None, attribute_name=None):
"""Interpolate from polygon layer to raster data.
.. note:
Each point in the resulting dataset will have an attribute
'polygon_id' which refers to the polygon it belongs to and
'grid_point' which refers to the grid point of the target.
:param source: Polygon data set.
:type source: Vector
:param target: Raster data set.
:type target: Raster
:param layer_name: Optional name of returned interpolated layer. If None
the name of source is used for the returned layer.
:type layer_name: basestring
:param attribute_name: Name for new attribute. If None (default) the name
of layer target is used
:type attribute_name: basestring
:returns: Tuple of Vector (points located as target with values
interpolated from source) and Raster (raster data that are coincide
with the source)
:rtype: Vector
"""
# Input checks
verify(source.is_polygon_data)
verify(target.is_raster)
# Run underlying clipping algorithm
polygon_geometry = source.get_geometry(as_geometry_objects=True)
polygon_attributes = source.get_data()
covered_source, covered_target = clip_grid_by_polygons(
target.get_data(scaling=False),
target.get_geotransform(),
polygon_geometry
)
# Create one new point layer with interpolated attributes
new_geometry = []
new_attributes = []
for i, (geometry, values) in enumerate(covered_source):
# For each polygon assign attributes to points that fall inside it
for j, geom in enumerate(geometry):
attr = polygon_attributes[i].copy() # Attributes for this polygon
attr[attribute_name] = values[j] # Attribute value from grid cell
attr['polygon_id'] = i # Store id for associated polygon
attr['grid_point'] = geom # Store grid point for associated grid
new_attributes.append(attr)
new_geometry.append(geom)
interpolated_layer = Vector(
data=new_attributes,
projection=source.get_projection(),
geometry=new_geometry,
name=layer_name)
covered_target = Raster(
data=covered_target,
projection=target.get_projection(),
geotransform=target.get_geotransform(),
name=layer_name)
return interpolated_layer, covered_target