GIS QuerySet API ReferenceLink para este cabeçalho
Spatial LookupsLink para este cabeçalho
The spatial lookups in this section are available for GeometryField
and RasterField.
For an introduction, see the spatial lookups introduction. For an overview of what lookups are compatible with a particular spatial backend, refer to the spatial lookup compatibility table.
Lookups with rastersLink para este cabeçalho
All examples in the reference below are given for geometry fields and inputs, but the lookups can be used the same way with rasters on both sides. Whenever a lookup doesn’t support raster input, the input is automatically converted to a geometry where necessary using the ST_Polygon function. See also the introduction to raster lookups.
The database operators used by the lookups can be divided into three categories:
Native raster support
N: the operator accepts rasters natively on both sides of the lookup, and raster input can be mixed with geometry inputs.Bilateral raster support
B: the operator supports rasters only if both sides of the lookup receive raster inputs. Raster data is automatically converted to geometries for mixed lookups.Geometry conversion support
C. The lookup does not have native raster support, all raster data is automatically converted to geometries.
The examples below show the SQL equivalent for the lookups in the different types of raster support. The same pattern applies to all spatial lookups.
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N, B |
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N, B |
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B, C |
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B, C |
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B, C |
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Spatial lookups with rasters are only supported for PostGIS backends (denominated as PGRaster in this section).
bbcontainsLink para este cabeçalho
Availability: PostGIS, MariaDB, MySQL, SpatiaLite, PGRaster (Native)
Tests if the geometry or raster field’s bounding box completely contains the lookup geometry’s bounding box.
Exemplo
Zipcode.objects.filter(poly__bbcontains=geom)
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SQL Equivalent |
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PostGIS |
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MariaDB |
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MySQL |
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SpatiaLite |
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bboverlapsLink para este cabeçalho
Availability: PostGIS, MariaDB, MySQL, SpatiaLite, PGRaster (Native)
Tests if the geometry field’s bounding box overlaps the lookup geometry’s bounding box.
Exemplo
Zipcode.objects.filter(poly__bboverlaps=geom)
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SQL Equivalent |
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PostGIS |
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MariaDB |
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MySQL |
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SpatiaLite |
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containedLink para este cabeçalho
Availability: PostGIS, MariaDB, MySQL, SpatiaLite, PGRaster (Native)
Tests if the geometry field’s bounding box is completely contained by the lookup geometry’s bounding box.
Exemplo
Zipcode.objects.filter(poly__contained=geom)
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SQL Equivalent |
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PostGIS |
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MariaDB |
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MySQL |
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SpatiaLite |
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containsLink para este cabeçalho
Availability: PostGIS, Oracle, MariaDB, MySQL, SpatiaLite, PGRaster (Bilateral)
Tests if the geometry field spatially contains the lookup geometry.
Exemplo
Zipcode.objects.filter(poly__contains=geom)
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SQL Equivalent |
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PostGIS |
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Oracle |
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MariaDB |
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MySQL |
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SpatiaLite |
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contains_properlyLink para este cabeçalho
Availability: PostGIS, PGRaster (Bilateral)
Returns true if the lookup geometry intersects the interior of the geometry field, but not the boundary (or exterior).
Exemplo
Zipcode.objects.filter(poly__contains_properly=geom)
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SQL Equivalent |
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PostGIS |
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coveredbyLink para este cabeçalho
Availability: PostGIS, Oracle, PGRaster (Bilateral), SpatiaLite
Tests if no point in the geometry field is outside the lookup geometry. [3]
Exemplo
Zipcode.objects.filter(poly__coveredby=geom)
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SQL Equivalent |
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PostGIS |
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Oracle |
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SpatiaLite |
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coversLink para este cabeçalho
Availability: PostGIS, Oracle, PGRaster (Bilateral), SpatiaLite
Tests if no point in the lookup geometry is outside the geometry field. [3]
Exemplo
Zipcode.objects.filter(poly__covers=geom)
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SQL Equivalent |
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PostGIS |
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Oracle |
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SpatiaLite |
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crossesLink para este cabeçalho
Availability: PostGIS, MariaDB, MySQL, SpatiaLite, PGRaster (Conversion)
Tests if the geometry field spatially crosses the lookup geometry.
Exemplo
Zipcode.objects.filter(poly__crosses=geom)
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SQL Equivalent |
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PostGIS |
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MariaDB |
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MySQL |
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SpatiaLite |
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disjointLink para este cabeçalho
Availability: PostGIS, Oracle, MariaDB, MySQL, SpatiaLite, PGRaster (Bilateral)
Tests if the geometry field is spatially disjoint from the lookup geometry.
Exemplo
Zipcode.objects.filter(poly__disjoint=geom)
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SQL Equivalent |
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PostGIS |
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Oracle |
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MariaDB |
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MySQL |
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SpatiaLite |
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equalsLink para este cabeçalho
Availability: PostGIS, Oracle, MariaDB, MySQL, SpatiaLite, PGRaster (Conversion)
Tests if the geometry field is spatially equal to the lookup geometry.
Exemplo
Zipcode.objects.filter(poly__equals=geom)
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SQL Equivalent |
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PostGIS |
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Oracle |
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MariaDB |
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MySQL |
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SpatiaLite |
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exact, same_asLink para este cabeçalho
Availability: PostGIS, Oracle, MariaDB, MySQL, SpatiaLite, PGRaster (Bilateral)
Tests if the geometry field is “equal” to the lookup geometry. On Oracle, MySQL, and SpatiaLite, it tests spatial equality, while on PostGIS it tests equality of bounding boxes.
Exemplo
Zipcode.objects.filter(poly=geom)
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SQL Equivalent |
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PostGIS |
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Oracle |
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MariaDB |
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MySQL |
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SpatiaLite |
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intersectsLink para este cabeçalho
Availability: PostGIS, Oracle, MariaDB, MySQL, SpatiaLite, PGRaster (Bilateral)
Tests if the geometry field spatially intersects the lookup geometry.
Exemplo
Zipcode.objects.filter(poly__intersects=geom)
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SQL Equivalent |
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PostGIS |
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Oracle |
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MariaDB |
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MySQL |
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SpatiaLite |
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isemptyLink para este cabeçalho
Availability: PostGIS
Tests if the geometry is empty.
Exemplo
Zipcode.objects.filter(poly__isempty=True)
isvalidLink para este cabeçalho
Availability: MySQL, PostGIS, Oracle, SpatiaLite
Tests if the geometry is valid.
Exemplo
Zipcode.objects.filter(poly__isvalid=True)
Backend |
SQL Equivalent |
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MySQL, PostGIS, SpatiaLite |
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Oracle |
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overlapsLink para este cabeçalho
Availability: PostGIS, Oracle, MariaDB, MySQL, SpatiaLite, PGRaster (Bilateral)
Tests if the geometry field spatially overlaps the lookup geometry.
Backend |
SQL Equivalent |
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PostGIS |
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Oracle |
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MariaDB |
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MySQL |
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SpatiaLite |
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relateLink para este cabeçalho
Availability: PostGIS, MariaDB, Oracle, SpatiaLite, PGRaster (Conversion)
Tests if the geometry field is spatially related to the lookup geometry by
the values given in the given pattern. This lookup requires a tuple parameter,
(geom, pattern); the form of pattern will depend on the spatial backend:
MariaDB, PostGIS, and SpatiaLiteLink para este cabeçalho
On these spatial backends the intersection pattern is a string comprising
nine characters, which define intersections between the interior, boundary,
and exterior of the geometry field and the lookup geometry.
The intersection pattern matrix may only use the following characters:
1, 2, T, F, or *. This lookup type allows users to “fine tune”
a specific geometric relationship consistent with the DE-9IM model. [1]
Geometry example:
# A tuple lookup parameter is used to specify the geometry and
# the intersection pattern (the pattern here is for 'contains').
Zipcode.objects.filter(poly__relate=(geom, "T*T***FF*"))
PostGIS and MariaDB SQL equivalent:
SELECT ... WHERE ST_Relate(poly, geom, 'T*T***FF*')
SpatiaLite SQL equivalent:
SELECT ... WHERE Relate(poly, geom, 'T*T***FF*')
Raster example:
Zipcode.objects.filter(poly__relate=(rast, 1, "T*T***FF*"))
Zipcode.objects.filter(rast__2__relate=(rast, 1, "T*T***FF*"))
PostGIS SQL equivalent:
SELECT ... WHERE ST_Relate(poly, ST_Polygon(rast, 1), 'T*T***FF*')
SELECT ... WHERE ST_Relate(ST_Polygon(rast, 2), ST_Polygon(rast, 1), 'T*T***FF*')
OracleLink para este cabeçalho
Here the relation pattern is comprised of at least one of the nine relation
strings: TOUCH, OVERLAPBDYDISJOINT, OVERLAPBDYINTERSECT,
EQUAL, INSIDE, COVEREDBY, CONTAINS, COVERS, ON, and
ANYINTERACT. Multiple strings may be combined with the logical Boolean
operator OR, for example, 'inside+touch'. [2] The relation
strings are case-insensitive.
Exemplo
Zipcode.objects.filter(poly__relate=(geom, "anyinteract"))
Oracle SQL equivalent:
SELECT ... WHERE SDO_RELATE(poly, geom, 'anyinteract')
touchesLink para este cabeçalho
Availability: PostGIS, Oracle, MariaDB, MySQL, SpatiaLite
Tests if the geometry field spatially touches the lookup geometry.
Exemplo
Zipcode.objects.filter(poly__touches=geom)
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SQL Equivalent |
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PostGIS |
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MariaDB |
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MySQL |
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Oracle |
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SpatiaLite |
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withinLink para este cabeçalho
Availability: PostGIS, Oracle, MariaDB, MySQL, SpatiaLite, PGRaster (Bilateral)
Tests if the geometry field is spatially within the lookup geometry.
Exemplo
Zipcode.objects.filter(poly__within=geom)
Backend |
SQL Equivalent |
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PostGIS |
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MariaDB |
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MySQL |
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Oracle |
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SpatiaLite |
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leftLink para este cabeçalho
Availability: PostGIS, PGRaster (Conversion)
Tests if the geometry field’s bounding box is strictly to the left of the lookup geometry’s bounding box.
Exemplo
Zipcode.objects.filter(poly__left=geom)
PostGIS equivalent:
SELECT ... WHERE poly << geom
rightLink para este cabeçalho
Availability: PostGIS, PGRaster (Conversion)
Tests if the geometry field’s bounding box is strictly to the right of the lookup geometry’s bounding box.
Exemplo
Zipcode.objects.filter(poly__right=geom)
PostGIS equivalent:
SELECT ... WHERE poly >> geom
overlaps_leftLink para este cabeçalho
Availability: PostGIS, PGRaster (Bilateral)
Tests if the geometry field’s bounding box overlaps or is to the left of the lookup geometry’s bounding box.
Exemplo
Zipcode.objects.filter(poly__overlaps_left=geom)
PostGIS equivalent:
SELECT ... WHERE poly &< geom
overlaps_rightLink para este cabeçalho
Availability: PostGIS, PGRaster (Bilateral)
Tests if the geometry field’s bounding box overlaps or is to the right of the lookup geometry’s bounding box.
Exemplo
Zipcode.objects.filter(poly__overlaps_right=geom)
PostGIS equivalent:
SELECT ... WHERE poly &> geom
overlaps_aboveLink para este cabeçalho
Availability: PostGIS, PGRaster (Conversion)
Tests if the geometry field’s bounding box overlaps or is above the lookup geometry’s bounding box.
Exemplo
Zipcode.objects.filter(poly__overlaps_above=geom)
PostGIS equivalent:
SELECT ... WHERE poly |&> geom
overlaps_belowLink para este cabeçalho
Availability: PostGIS, PGRaster (Conversion)
Tests if the geometry field’s bounding box overlaps or is below the lookup geometry’s bounding box.
Exemplo
Zipcode.objects.filter(poly__overlaps_below=geom)
PostGIS equivalent:
SELECT ... WHERE poly &<| geom
strictly_aboveLink para este cabeçalho
Availability: PostGIS, PGRaster (Conversion)
Tests if the geometry field’s bounding box is strictly above the lookup geometry’s bounding box.
Exemplo
Zipcode.objects.filter(poly__strictly_above=geom)
PostGIS equivalent:
SELECT ... WHERE poly |>> geom
strictly_belowLink para este cabeçalho
Availability: PostGIS, PGRaster (Conversion)
Tests if the geometry field’s bounding box is strictly below the lookup geometry’s bounding box.
Exemplo
Zipcode.objects.filter(poly__strictly_below=geom)
PostGIS equivalent:
SELECT ... WHERE poly <<| geom
Distance LookupsLink para este cabeçalho
Availability: PostGIS, Oracle, MariaDB, MySQL, SpatiaLite, PGRaster (Native)
For an overview on performing distance queries, please refer to the distance queries introduction.
Distance lookups take the following form:
<field>__<distance lookup>=(<geometry/raster>, <distance value>[, "spheroid"])
<field>__<distance lookup>=(<raster>, <band_index>, <distance value>[, "spheroid"])
<field>__<band_index>__<distance lookup>=(<raster>, <band_index>, <distance value>[, "spheroid"])
The value passed into a distance lookup is a tuple; the first two
values are mandatory, and are the geometry to calculate distances to,
and a distance value (either a number in units of the field, a
Distance object, or a query
expression). To pass a band index to the lookup, use
a 3-tuple where the second entry is the band index.
On every distance lookup except dwithin, an optional element,
'spheroid', may be included to use the more accurate spheroid distance
calculation functions on fields with a geodetic coordinate system.
On PostgreSQL, the 'spheroid' option uses ST_DistanceSpheroid instead of
ST_DistanceSphere. The
simpler ST_Distance function is
used with projected coordinate systems. Rasters are converted to geometries for
spheroid based lookups.
distance_gtLink para este cabeçalho
Returns models where the distance to the geometry field from the lookup geometry is greater than the given distance value.
Exemplo
Zipcode.objects.filter(poly__distance_gt=(geom, D(m=5)))
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SQL Equivalent |
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PostGIS |
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MariaDB |
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MySQL |
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Oracle |
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SpatiaLite |
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distance_gteLink para este cabeçalho
Returns models where the distance to the geometry field from the lookup geometry is greater than or equal to the given distance value.
Exemplo
Zipcode.objects.filter(poly__distance_gte=(geom, D(m=5)))
Backend |
SQL Equivalent |
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PostGIS |
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MariaDB |
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MySQL |
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Oracle |
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SpatiaLite |
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distance_ltLink para este cabeçalho
Returns models where the distance to the geometry field from the lookup geometry is less than the given distance value.
Exemplo
Zipcode.objects.filter(poly__distance_lt=(geom, D(m=5)))
Backend |
SQL Equivalent |
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PostGIS |
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MariaDB |
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MySQL |
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Oracle |
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SpatiaLite |
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distance_lteLink para este cabeçalho
Returns models where the distance to the geometry field from the lookup geometry is less than or equal to the given distance value.
Exemplo
Zipcode.objects.filter(poly__distance_lte=(geom, D(m=5)))
Backend |
SQL Equivalent |
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PostGIS |
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MariaDB |
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MySQL |
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Oracle |
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SpatiaLite |
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dwithinLink para este cabeçalho
Returns models where the distance to the geometry field from the lookup
geometry are within the given distance from one another. Note that you can only
provide Distance objects if the targeted
geometries are in a projected system. For geographic geometries, you should use
units of the geometry field (e.g. degrees for WGS84) .
Exemplo
Zipcode.objects.filter(poly__dwithin=(geom, D(m=5)))
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SQL Equivalent |
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PostGIS |
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Oracle |
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SpatiaLite |
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Funções de AgregaçãoLink para este cabeçalho
Django provides some GIS-specific aggregate functions. For details on how to use these aggregate functions, see the topic guide on aggregation.
Keyword Argument |
Descrição |
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This keyword is for Oracle only. It is for the
tolerance value used by the |
Example:
>>> from django.contrib.gis.db.models import Extent, Union
>>> WorldBorder.objects.aggregate(Extent("mpoly"), Union("mpoly"))
CollectLink para este cabeçalho
- class Collect(geo_field, filter=None)Link para esta definição
Availability: PostGIS, MySQL, SpatiaLite
Returns a GEOMETRYCOLLECTION or a MULTI geometry object from the geometry
column. This is analogous to a simplified version of the Union
aggregate, except it can be several orders of magnitude faster than performing
a union because it rolls up geometries into a collection or multi object, not
caring about dissolving boundaries.
ExtentLink para este cabeçalho
- class Extent(geo_field, filter=None)Link para esta definição
Availability: PostGIS, Oracle, SpatiaLite
Returns the extent of all geo_field in the QuerySet as a 4-tuple,
comprising the lower left coordinate and the upper right coordinate.
Example:
>>> qs = City.objects.filter(name__in=("Houston", "Dallas")).aggregate(Extent("poly"))
>>> print(qs["poly__extent"])
(-96.8016128540039, 29.7633724212646, -95.3631439208984, 32.782058715820)
Extent3DLink para este cabeçalho
- class Extent3D(geo_field, filter=None)Link para esta definição
Availability: PostGIS
Returns the 3D extent of all geo_field in the QuerySet as a 6-tuple,
comprising the lower left coordinate and upper right coordinate (each with x, y,
and z coordinates).
Example:
>>> qs = City.objects.filter(name__in=("Houston", "Dallas")).aggregate(Extent3D("poly"))
>>> print(qs["poly__extent3d"])
(-96.8016128540039, 29.7633724212646, 0, -95.3631439208984, 32.782058715820, 0)
MakeLineLink para este cabeçalho
- class MakeLine(geo_field, filter=None)Link para esta definição
Availability: PostGIS, SpatiaLite
Returns a LineString constructed from the point field geometries in the
QuerySet. Currently, ordering the queryset has no effect.
Example:
>>> qs = City.objects.filter(name__in=("Houston", "Dallas")).aggregate(MakeLine("poly"))
>>> print(qs["poly__makeline"])
LINESTRING (-95.3631510000000020 29.7633739999999989, -96.8016109999999941 32.7820570000000018)
UnionLink para este cabeçalho
- class Union(geo_field, filter=None)Link para esta definição
Availability: PostGIS, Oracle, SpatiaLite
This method returns a GEOSGeometry object
comprising the union of every geometry in the queryset. Please note that use of
Union is processor intensive and may take a significant amount of time on
large querysets.
Example:
>>> u = Zipcode.objects.aggregate(Union(poly)) # This may take a long time.
>>> u = Zipcode.objects.filter(poly__within=bbox).aggregate(
... Union(poly)
... ) # A more sensible approach.
Notas de rodapé