Data Contoh¶

The GDAL/OGR tools described here are designed to help you read in your geospatial data, in order for most of them to be useful you have to have some data to work with. If you're starting out and don't yet have any data of your own to use, GeoDjango tests contain a number of simple data sets that you can use for testing. You can download them here:

$ wget https://raw.githubusercontent.com/django/django/master/tests/gis_tests/data/cities/cities.{shp,prj,shx,dbf}
$ wget https://raw.githubusercontent.com/django/django/master/tests/gis_tests/data/rasters/raster.tif

DataSource¶

DataSource adalah sebuah pembungkus untuk obyek sumber data OGR yang mendukung membaca data dari beragam dari bentuk berkas geospasial didukung-OGR dan sumber data menggunakan sederhana, konsisten antarmuka. Setiap sumber data diwakili oleh sebuah obyek DataSource yang mengandung satu atau lebih lapisan data. Setiap lapisan, diwakili oleh Layer object, mengandung beberapa nomor dari fitur-fitur geografik (Feature), informasi tentang jenis dari fitur-fitur mengandung di lapisan itu (sebagai contoh titik, poligon, dll.), sama halnya nama-nama dan jenis-jenis dari bidang tambahan apapun (Field) dari data yang mungkin terhubung dengan setiap fitur di lapisan itu.

class DataSource(ds_input, encoding='utf-8')¶

Pembangun untuk DataSource hanya membutuhkan satu parameter: jalur dari berkas anda ingin baca. Bagaimanapun, OGR juga mendukung beragam sumber data lebih rumit, termasuk basisdata, yang mungkin diakses dengan melewatkan string nama khusus daripada jalur. Untuk informasi lebih, lihat dokumentasi OGR Vector Formats. Sifat name dari sebuah instance DataSource memberikan nama OGR dari sumber data pokok yang itu sedang gunakan.

Pilihan parameter encoding mengizinkan anda menentukan penyandian bukan-standar dari string di sumber. Ini khususnya berguna ketika anda mendapatkan pengecualian DjangoUnicodeDecodeError selagi membaca nilai bidang.

Sekali anda telah membuat DataSource anda, anda dapat menemukan seberapa banyak lapisan data itu kandung dengan mengakses sifat layer_count, atau (setara) dengan menggunakan fungsi len(). Untuk informasi pada mengakses lapisan dari data mereka sendiri, lihat bagian lain:

>>> from django.contrib.gis.gdal import DataSource
>>> ds = DataSource('/path/to/your/cities.shp')
>>> ds.name
'/path/to/your/cities.shp'
>>> ds.layer_count                  # This file only contains one layer
1

layer_count¶

Mengembalikan sejumlah lapisan di sumber data.

name¶

Mengembalikan nama dari sumber data.

Lapisan¶

class Layer¶

Layer adalah sebuah pembungkus untuk lapisan dari data di obyek DataSource. Anda tidak pernah membuat obyek Layer secara langsung. Sebagai gantinya, anda mengambil mereka dari obyek DataSource, yang pada dasarnya wadah standar Python dari obyek Layer. Sebagai contoh, anda dapat mengakses lapisan khusus dengan indeksnya (sebagai contoh ds[0] untuk mengakses lapisan pertama), atau anda dapat mengulang terhadap semua lapisan di wadah dalam perulangan loop. Layer itu sendiri bertindak sebagai sebuah wadah untuk fitur-fitur geometris.

Khususnya, semua fitur di lapisan yang diberikan mempunyai jenis geometri sama. Sifat geom_type dari lapisan adalah sebuah OGRGeomType yang mencirikan jenis fitur. Kami dapat menggunakan itu untuk mencetak beberapa informasi dasar tentang setiap lapisan di DataSource:

>>> for layer in ds:
...     print('Layer "%s": %i %ss' % (layer.name, len(layer), layer.geom_type.name))
...
Layer "cities": 3 Points

Keluaran contoh adalah dari sumber data kota, dimuat diatas, yang ternyata mengandung satu lapisan, dipanggil "cities", yang mengandung tida titik fitur. Untuk kemudahan, contoh-contoh diatas menganggap bahwa anda telah menyimpan lapisan itu di variabel layer:

>>> layer = ds[0]

name¶

Mengembalikan nama lapisan ini di sumber data.

>>> layer.name
'cities'

num_feat¶

Mengembalikan sejumlah fitur-fitur di lapisan. Sama seperti len(layer):

>>> layer.num_feat
3

geom_type¶

Mengembalikan jenis geometri dari lapisan, sebagai sebuah obyek OGRGeomType:

>>> layer.geom_type.name
'Point'

num_fields¶

Mengembalikan sejumlah bidang di lapisan, yaitu sejumlah bidang dari data terhubung dengan setiap fitur di lapisan:

>>> layer.num_fields
4

fields¶

Mengembalikan daftar nama dari setiap bidang di lapisan ini:

>>> layer.fields
['Name', 'Population', 'Density', 'Created']

Mengembalikan daftar dari jenis-jenis data dari setiap bidang di lapisan ini. Ini adalah subkelas dari Field, diobrolkan dibawah:

>>> [ft.__name__ for ft in layer.field_types]
['OFTString', 'OFTReal', 'OFTReal', 'OFTDate']

field_widths¶

Mengembalikan daftar dari bidang maksimal untuk setiap bidang dalam lapisan ini:

>>> layer.field_widths
[80, 11, 24, 10]

field_precisions¶

Mengembalikan daftar dari angka ketelitian untuk setiap dari bidang-bidang dalam lapisan ini. Ini tidak berarti (dan disetel ke nol) untuk bidang bukan-numerik:

>>> layer.field_precisions
[0, 0, 15, 0]

extent¶

Mengembalikan tingkatan spasial dari lapisan ini, sebagai sebuah obyek Envelope:

>>> layer.extent.tuple
(-104.609252, 29.763374, -95.23506, 38.971823)

srs¶

Sifat yang mengembalikan SpatialReference terkait dengan lapisan ini:

>>> print(layer.srs)
GEOGCS["GCS_WGS_1984",
    DATUM["WGS_1984",
        SPHEROID["WGS_1984",6378137,298.257223563]],
    PRIMEM["Greenwich",0],
    UNIT["Degree",0.017453292519943295]]

Jika Layer tidak mempunyai informasi acuan spasial terkait dengan itu, `` None`` dikembalikan.

spatial_filter¶

Property that may be used to retrieve or set a spatial filter for this layer. A spatial filter can only be set with an OGRGeometry instance, a 4-tuple extent, or None. When set with something other than None, only features that intersect the filter will be returned when iterating over the layer:

>>> print(layer.spatial_filter)
None
>>> print(len(layer))
3
>>> [feat.get('Name') for feat in layer]
['Pueblo', 'Lawrence', 'Houston']
>>> ks_extent = (-102.051, 36.99, -94.59, 40.00) # Extent for state of Kansas
>>> layer.spatial_filter = ks_extent
>>> len(layer)
1
>>> [feat.get('Name') for feat in layer]
['Lawrence']
>>> layer.spatial_filter = None
>>> len(layer)
3

get_fields()¶

Sebuah metode yang mengembalikan sebuah daftar dari nilai-nilai dari bidang yang diberikan untuk setiap fitur dalam lapisan:

>>> layer.get_fields('Name')
['Pueblo', 'Lawrence', 'Houston']

get_geoms(geos=False)¶

A method that returns a list containing the geometry of each feature in the layer. If the optional argument geos is set to True then the geometries are converted to GEOSGeometry objects. Otherwise, they are returned as OGRGeometry objects:

>>> [pt.tuple for pt in layer.get_geoms()]
[(-104.609252, 38.255001), (-95.23506, 38.971823), (-95.363151, 29.763374)]

test_capability(capability)¶

Returns a boolean indicating whether this layer supports the given capability (a string). Examples of valid capability strings include: 'RandomRead', 'SequentialWrite', 'RandomWrite', 'FastSpatialFilter', 'FastFeatureCount', 'FastGetExtent', 'CreateField', 'Transactions', 'DeleteFeature', and 'FastSetNextByIndex'.

Feature¶

class Feature¶

Feature membungkus fitur OGR. Anda tidak pernah membuat obyek Feature secara langsung. Sebagai gantinya, anda mengambil mereka dari obyek Layer. Setiap fitur terdiri dari sebuah geometri dan sekumpulan bidang mengandung sifat-sifat tambahan. Geometri dari sebuah bidang adalah dapat diakses melalui sifat geom nya, yang mengembalikan sebuah obyek OGRGeometry. Sebuah Feature berperilaku seperti wadah Python standar untuk bidangnya, yang itu dikembalikan sebagai obyek Field: anda dapat mengakses sebuah bidang secara langsung berdasarkan indeks atau namanya, atau dapat berulang terhadap bidang-bidang fitur, sebagai contoh di sebuah perulangan for.

geom¶

Mengembalikan geometri untuk fotur ini, sebagai sebuah obyek OGRGeometry:

>>> city.geom.tuple
(-104.609252, 38.255001)

get¶

Sebuah metode yang mengembalikan nilai dari bidang yang diberikan (ditentukan oleh nama) untuk fitur ini, bukan sebuah obyek pembungkus Field:

>>> city.get('Population')
102121

geom_type¶

Returns the type of geometry for this feature, as an OGRGeomType object. This will be the same for all features in a given layer and is equivalent to the Layer.geom_type property of the Layer object the feature came from.

num_fields¶

Returns the number of fields of data associated with the feature. This will be the same for all features in a given layer and is equivalent to the Layer.num_fields property of the Layer object the feature came from.

fields¶

Returns a list of the names of the fields of data associated with the feature. This will be the same for all features in a given layer and is equivalent to the Layer.fields property of the Layer object the feature came from.

fid¶

Mengembalikan penciri fitur dalam lapisan:

>>> city.fid
0

layer_name¶

Mengembalikan nama dari Layer yang berasal fitur. Ini akan menjadi sama untuk semua fitur dalam lapisan yang diberikan:

>>> city.layer_name
'cities'

index¶

Sebuah metode yang mengembalikan indeks dari nama bidang yang diberikan. Ini akan sama untuk semua fitur-fitur dalam lapisan yang diberikan:

>>> city.index('Population')
1

Field¶

class Field¶

name¶

Mengembalikan nama dari bidang ini:

>>> city['Name'].name
'Name'

type¶

Mengembalikan jenis OGR dari bidang ini, sebagai sebuah integer. Dictionary FIELD_CLASSES memetakan nilai-nilai ini kedalam subkelas dari Field:

>>> city['Density'].type
2

type_name¶

Mengembalikan string dengan nama dari jenis data dari bidang ini:

>>> city['Name'].type_name
'String'

value¶

Mengembalikan nilai dari bidang ini. Kelas Field itu sendiri mengembalikan nilai sebagai sebuah string, tetapi setiap subkelas mengembalikan nilai dalam bentuk paling sesuai:

>>> city['Population'].value
102121

width¶

Mengembalikan lebar bidang ini:

>>> city['Name'].width
80

precision¶

Mengembalikan ketelitian numerik dari bidang ini. Ini tidak berarti (dan disetel ke nol) untuk bidang-bidang bukan-numerik:

>>> city['Density'].precision
15

as_double()¶

Mengembalikan nilai dari bidang sebagai double (float):

>>> city['Density'].as_double()
874.7

as_int()¶

Mengembalikan nilai dari bidang sebagai integer:

>>> city['Population'].as_int()
102121

as_string()¶

Mengembalikan nilai dari bidang sebagai deretan kalimat:

>>> city['Name'].as_string()
'Pueblo'

as_datetime()¶

Mengembalikan nilai dari bidang sebagai tuple dari komponen tanggal dan waktu:

>>> city['Created'].as_datetime()
(c_long(1999), c_long(5), c_long(23), c_long(0), c_long(0), c_long(0), c_long(0))

Driver¶

class Driver(dr_input)¶

Kelas Driver digunakan secara mendalam untuk membungkus sebuah driver DataSource OGR.

driver_count¶

Mengembalikan sejumlah driver vektor OGR saat ini terdaftar.

OGRGeometry¶

Obyek-obyek OGRGeometry berbagi fungsi mirip dengan obyek GEOSGeometry dan pembungkus tipis disekitar perwakilan geometri internal OGR. Dengan demikian, mereka mengizinkan untuk lebih efektid mengakses ke data ketika menggunakan DataSource. Tidak seprti pasangan GEOS nya, OGRGeometry mendukung sistem acuan spasial dan perubahan kordinat:

>>> from django.contrib.gis.gdal import OGRGeometry
>>> polygon = OGRGeometry('POLYGON((0 0, 5 0, 5 5, 0 5))')

class OGRGeometry(geom_input, srs=None)¶

Obyek ini adalah sebuah pembungkus untuk kelas OGR Geometry. Obyek-obyek ini diinstasiasikan secara langsung dari parameter geom_input yang diberikan, yang mungkin berupa string mengandung WKT, HEX, GeoJSON, sebuah buffer mengandung data WKB, atau sebuah obyek OGRGeomType. Obyek-obyek ini juga dikembalikan dari atribut Feature.geom, ketika membaca data vektor dari Layer (yaitu pada giliran bagian dari sebuah DataSource).

classmethod from_gml(gml_string)¶

New in Django 1.11.

Membangun sebuah OGRGeometry dari string GML yang diberikan.

classmethod from_bbox(bbox)¶

Membangun sebuah Polygon dari kotak-terikat diberikan (4-tuple).

__len__()¶

Mengembalikan sejumlah titik dalam sebuah LineString, sejumlah geometri dalam sebuah GeometryCollection. Tidak diberlakukan ke jenis geometri lain.

__iter__()¶

Iterates over the points in a LineString, the rings in a Polygon, or the geometries in a GeometryCollection. Not applicable to other geometry types.

__getitem__()¶

Returns the point at the specified index for a LineString, the interior ring at the specified index for a Polygon, or the geometry at the specified index in a GeometryCollection. Not applicable to other geometry types.

dimension¶

Mengembalikan sejumlah dimensi kordinat dari geometri, yaitu 0 untuk titik, 1 untuk baris, dan sebagainya:

>> polygon.dimension
2

coord_dim¶

Returns or sets the coordinate dimension of this geometry. For example, the value would be 2 for two-dimensional geometries.

geom_count¶

Mengembalikan sejumlah unsur dalam geometri ini:

>>> polygon.geom_count
1

point_count¶

Mengembalikan sejumlah titik digunakan untuk menggambarkan geometri ini:

>>> polygon.point_count
4

num_points¶

Nama lain untuk point_count.

num_coords¶

Nama lain untuk point_count.

geom_type¶

Mengembalikan jenis dari geometri ini, sebagai sebuah obyek OGRGeomType.

geom_name¶

Mengembalikan nama dari jenis dari geometri ini:

>>> polygon.geom_name
'POLYGON'

area¶

Mengembalikan kawasan dari geometri ini, atau 0 untuk geometri yang tidak mengandung sebuah kawasan:

>>> polygon.area
25.0

envelope¶

Mengembalikan sampul dari geometri ini, sebagai sebuah obyek Envelope.

extent¶

Returns the envelope of this geometry as a 4-tuple, instead of as an Envelope object:

>>> point.extent
(0.0, 0.0, 5.0, 5.0)

srs¶

Sifat ini mengendalikan acuan spasial untuk geometri ini, atau None jika tidak ada sisterm acuan spasia telah diberikan ke itu. Jika diberikan, mengakses sifat ini mengembalikan sebuah obyek SpatialReference. Itu mungkin disetel dengan obyek SpatialReference lain, atau masukan apapun yang SpatialReference terima. Contoh:

>>> city.geom.srs.name
'GCS_WGS_1984'

srid¶

Returns or sets the spatial reference identifier corresponding to SpatialReference of this geometry. Returns None if there is no spatial reference information associated with this geometry, or if an SRID cannot be determined.

geos¶

Mengebalikan obyek GEOSGeometry sesuai pada geometri ini.

gml¶

Mengembalikan sebuah string perwakilan dari geometri ini dalam bentuk GML:

>>> OGRGeometry('POINT(1 2)').gml
'<gml:Point><gml:coordinates>1,2</gml:coordinates></gml:Point>'

hex¶

Mengembalikan perwakilan string dari geometri ini dalam bentuk HEX WKB:

>>> OGRGeometry('POINT(1 2)').hex
'0101000000000000000000F03F0000000000000040'

json¶

Mengembalikan string perwakilan dari geometri ini dalam bentuk JSON:

>>> OGRGeometry('POINT(1 2)').json
'{ "type": "Point", "coordinates": [ 1.000000, 2.000000 ] }'

kml¶

Mengembalikan perwakilan string dari geometri ini dalam bentuk KML.

wkb_size¶

Mengembalikan ukuran dari penyangga WKB untuk menahan perwakilan WKB dari geometri ini:

>>> OGRGeometry('POINT(1 2)').wkb_size
21

wkb¶

Mengembalikan sebuah buffer mengandung perwakilan WKB dari geometri ini.

wkt¶

Mengembalikan perwakilan string dari geometri ini dalam bentuk WKT.

ewkt¶

Mengembalikan perwakilan EWKT dari geometri ini.

clone()¶

Mengembalikan klon baru OGRGeometry dari obyek geometri ini.

close_rings()¶

Jika ada lingkaran apapun dalam geometri ini yang belum ditutup, rutin ini akan melakukannya dengan menambahkan titik awalan ke akhiran:

>>> triangle = OGRGeometry('LINEARRING (0 0,0 1,1 0)')
>>> triangle.close_rings()
>>> triangle.wkt
'LINEARRING (0 0,0 1,1 0,0 0)'

transform(coord_trans, clone=False)¶

Transforms this geometry to a different spatial reference system. May take a CoordTransform object, a SpatialReference object, or any other input accepted by SpatialReference (including spatial reference WKT and PROJ.4 strings, or an integer SRID).

By default nothing is returned and the geometry is transformed in-place. However, if the clone keyword is set to True then a transformed clone of this geometry is returned instead.

intersects(other)¶

Mengembalikan True jika geometri ini memotong ke lain, sebaliknya mengembalikan False.

equals(other)¶

Mengembalikan True jika geometri ini setara dengan lain, sebaliknya mengembalikan True.

disjoint(other)¶

Returns True if this geometry is spatially disjoint to (i.e. does not intersect) the other, otherwise returns False.

touches(other)¶

Mengembalikan True jika geometri ini menyentuh lainnya, sebaliknya mengembalikan False.

crosses(other)¶

Mengembalikan True jika geometri ini bersilangan ke lainnya, sebaliknya mengembalikan False.

within(other)¶

Returns True if this geometry is contained within the other, otherwise returns False.

contains(other)¶

Returns True if this geometry contains the other, otherwise returns False.

overlaps(other)¶

Returns True if this geometry overlaps the other, otherwise returns False.

boundary()¶

The boundary of this geometry, as a new OGRGeometry object.

convex_hull¶

The smallest convex polygon that contains this geometry, as a new OGRGeometry object.

difference()¶

Returns the region consisting of the difference of this geometry and the other, as a new OGRGeometry object.

intersection()¶

Returns the region consisting of the intersection of this geometry and the other, as a new OGRGeometry object.

sym_difference()¶

Returns the region consisting of the symmetric difference of this geometry and the other, as a new OGRGeometry object.

union()¶

Returns the region consisting of the union of this geometry and the other, as a new OGRGeometry object.

tuple¶

Mengembalikan kordinat-kordinat dari titik geometri sebagai sebuah tuple, kordinat-kordinat dari baris geometri sebagai sebuah tuple dari tuple, dan sebagainya:

>>> OGRGeometry('POINT (1 2)').tuple
(1.0, 2.0)
>>> OGRGeometry('LINESTRING (1 2,3 4)').tuple
((1.0, 2.0), (3.0, 4.0))

coords¶

Sebuah nama lain untuk tuple.

class Point¶

x¶

Mengembalikan kordinat X dari titik ini:

>>> OGRGeometry('POINT (1 2)').x
1.0

y¶

Mengembalikan kordinat Y dari titik ini:

>>> OGRGeometry('POINT (1 2)').y
2.0

z¶

Returns the Z coordinate of this point, or None if the point does not have a Z coordinate:

>>> OGRGeometry('POINT (1 2 3)').z
3.0

class LineString¶

x¶

Mengembalikan sebuah daftar dari kordinat X dalam baris ini:

>>> OGRGeometry('LINESTRING (1 2,3 4)').x
[1.0, 3.0]

y¶

Mengembalikan sebuah daftar dari kordinat Y dalam baris ini:

>>> OGRGeometry('LINESTRING (1 2,3 4)').y
[2.0, 4.0]

z¶

Returns a list of Z coordinates in this line, or None if the line does not have Z coordinates:

>>> OGRGeometry('LINESTRING (1 2 3,4 5 6)').z
[3.0, 6.0]

class Polygon¶

shell¶

Returns the shell or exterior ring of this polygon, as a LinearRing geometry.

exterior_ring¶

Sebuah nama lain untuk shell.

centroid¶

Returns a Point representing the centroid of this polygon.

class GeometryCollection¶

add(geom)¶

Adds a geometry to this geometry collection. Not applicable to other geometry types.

OGRGeomType¶

class OGRGeomType(type_input)¶

Kelas ini mengizinkan untuk gambaran dari jenis geometri OGR dalam beberapa cara:

>>> from django.contrib.gis.gdal import OGRGeomType
>>> gt1 = OGRGeomType(3)             # Using an integer for the type
>>> gt2 = OGRGeomType('Polygon')     # Using a string
>>> gt3 = OGRGeomType('POLYGON')     # It's case-insensitive
>>> print(gt1 == 3, gt1 == 'Polygon') # Equivalence works w/non-OGRGeomType objects
True True

name¶

Returns a short-hand string form of the OGR Geometry type:

>>> gt1.name
'Polygon'

num¶

Mengembalikan sejumlah kaitan pada jenis geometri OGR:

>>> gt1.num
3

django¶

Returns the Django field type (a subclass of GeometryField) to use for storing this OGR type, or None if there is no appropriate Django type:

>>> gt1.django
'PolygonField'

Envelope¶

class Envelope(*args)¶

Represents an OGR Envelope structure that contains the minimum and maximum X, Y coordinates for a rectangle bounding box. The naming of the variables is compatible with the OGR Envelope C structure.

min_x¶

Nilai minimal kordinat X

min_y¶

Nilai maksimal kordinat X.

max_x¶

Nilai minimal kordinat Y.

max_y¶

Nilai maksimal kordinat Y.

ur¶

Kordinat atas-kanan, sebagai sebuah tuple.

ll¶

Kordinat kiri-bawah, sebagai sebuah tuple.

tuple¶

A tuple representing the envelope.

wkt¶

A string representing this envelope as a polygon in WKT format.

expand_to_include(*args)¶

SpatialReference¶

class SpatialReference(srs_input)¶

Spatial reference objects are initialized on the given srs_input, which may be one of the following:

• OGC Well Known Text (WKT) (sebuah string)
• Kode EPSG(integer atau string)
• String PROJ.4
• A shorthand string for well-known standards ('WGS84', 'WGS72', 'NAD27', 'NAD83')

Contoh:

>>> wgs84 = SpatialReference('WGS84') # shorthand string
>>> wgs84 = SpatialReference(4326) # EPSG code
>>> wgs84 = SpatialReference('EPSG:4326') # EPSG string
>>> proj4 = '+proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs '
>>> wgs84 = SpatialReference(proj4) # PROJ.4 string
>>> wgs84 = SpatialReference("""GEOGCS["WGS 84",
DATUM["WGS_1984",
     SPHEROID["WGS 84",6378137,298.257223563,
         AUTHORITY["EPSG","7030"]],
     AUTHORITY["EPSG","6326"]],
 PRIMEM["Greenwich",0,
     AUTHORITY["EPSG","8901"]],
 UNIT["degree",0.01745329251994328,
     AUTHORITY["EPSG","9122"]],
 AUTHORITY["EPSG","4326"]]""") # OGC WKT

__getitem__(target)¶

Returns the value of the given string attribute node, None if the node doesn't exist. Can also take a tuple as a parameter, (target, child), where child is the index of the attribute in the WKT. For example:

>>> wkt = 'GEOGCS["WGS 84", DATUM["WGS_1984, ... AUTHORITY["EPSG","4326"]]')
>>> srs = SpatialReference(wkt) # could also use 'WGS84', or 4326
>>> print(srs['GEOGCS'])
WGS 84
>>> print(srs['DATUM'])
WGS_1984
>>> print(srs['AUTHORITY'])
EPSG
>>> print(srs['AUTHORITY', 1]) # The authority value
4326
>>> print(srs['TOWGS84', 4]) # the fourth value in this wkt
0
>>> print(srs['UNIT|AUTHORITY']) # For the units authority, have to use the pipe symbol.
EPSG
>>> print(srs['UNIT|AUTHORITY', 1]) # The authority value for the units
9122

attr_value(target, index=0)¶

The attribute value for the given target node (e.g. 'PROJCS'). The index keyword specifies an index of the child node to return.

auth_name(target)¶

Returns the authority name for the given string target node.

auth_code(target)¶

Returns the authority code for the given string target node.

clone()¶

Returns a clone of this spatial reference object.

identify_epsg()¶

Metode ini memeriksa WKT dari SpatialReference ini dan akan menambahkan node-node wewenang EPSG dimana sebuah penciri EPSG dapat diterapkan.

from_esri()¶

Morphs this SpatialReference from ESRI's format to EPSG

to_esri()¶

Morphs this SpatialReference to ESRI's format.

validate()¶

Memeriksa untuk melihat jika acuan spasial diberikan adalah sah, jika tidak sebuah pengecualian akan dimunculkan.

import_epsg(epsg)¶

Import spatial reference from EPSG code.

import_proj(proj)¶

Import spatial reference from PROJ.4 string.

import_user_input(user_input)¶

import_wkt(wkt)¶

Import spatial reference from WKT.

import_xml(xml)¶

Import spatial reference from XML.

name¶

Returns the name of this Spatial Reference.

srid¶

Returns the SRID of top-level authority, or None if undefined.

linear_name¶

Mengambalikan nama dari satuan linear.

linear_units¶

Mengembalikan nilai dari satuan linear.

angular_name¶

Mengembalikan nama dari satuan sudut."

angular_units¶

Mengembalikan nilai dari satuan sudut.

units¶

Returns a 2-tuple of the units value and the units name and will automatically determines whether to return the linear or angular units.

ellipsoid¶

Returns a tuple of the ellipsoid parameters for this spatial reference: (semimajor axis, semiminor axis, and inverse flattening).

semi_major¶

Returns the semi major axis of the ellipsoid for this spatial reference.

semi_minor¶

Returns the semi minor axis of the ellipsoid for this spatial reference.

inverse_flattening¶

Returns the inverse flattening of the ellipsoid for this spatial reference.

geographic¶

Returns True if this spatial reference is geographic (root node is GEOGCS).

local¶

Returns True if this spatial reference is local (root node is LOCAL_CS).

projected¶

Returns True if this spatial reference is a projected coordinate system (root node is PROJCS).

wkt¶

Returns the WKT representation of this spatial reference.

pretty_wkt¶

Returns the 'pretty' representation of the WKT.

proj¶

Returns the PROJ.4 representation for this spatial reference.

proj4¶

Nama lain untuk SpatialReference.proj.

xml¶

Returns the XML representation of this spatial reference.

CoordTransform¶

class CoordTransform(source, target)¶

Represents a coordinate system transform. It is initialized with two SpatialReference, representing the source and target coordinate systems, respectively. These objects should be used when performing the same coordinate transformation repeatedly on different geometries:

>>> ct = CoordTransform(SpatialReference('WGS84'), SpatialReference('NAD83'))
>>> for feat in layer:
...     geom = feat.geom # getting clone of feature geometry
...     geom.transform(ct) # transforming

GDALRaster¶

GDALRaster is a wrapper for the GDAL raster source object that supports reading data from a variety of GDAL-supported geospatial file formats and data sources using a simple, consistent interface. Each data source is represented by a GDALRaster object which contains one or more layers of data named bands. Each band, represented by a GDALBand object, contains georeferenced image data. For example, an RGB image is represented as three bands: one for red, one for green, and one for blue.

class GDALRaster(ds_input, write=False)¶

The constructor for GDALRaster accepts two parameters. The first parameter defines the raster source, and the second parameter defines if a raster should be opened in write mode. For newly-created rasters, the second parameter is ignored and the new raster is always created in write mode.

The first parameter can take three forms: a string representing a file path, a dictionary with values defining a new raster, or a bytes object representing a raster file.

If the input is a file path, the raster is opened from there. If the input is raw data in a dictionary, the parameters width, height, and srid are required. If the input is a bytes object, it will be opened using a GDAL virtual filesystem.

For a detailed description of how to create rasters using dictionary input, see Membuat raster dari data. For a detailed description of how to create rasters in the virtual filesystem, see Using GDAL's Virtual Filesystem.

The following example shows how rasters can be created from different input sources (using the sample data from the GeoDjango tests; see also the Data Contoh section).

>>> from django.contrib.gis.gdal import GDALRaster
>>> rst = GDALRaster('/path/to/your/raster.tif', write=False)
>>> rst.name
'/path/to/your/raster.tif'
>>> rst.width, rst.height  # This file has 163 x 174 pixels
(163, 174)
>>> rst = GDALRaster({  # Creates an in-memory raster
...     'srid': 4326,
...     'width': 4,
...     'height': 4,
...     'datatype': 1,
...     'bands': [{
...         'data': (2, 3),
...         'offset': (1, 1),
...         'size': (2, 2),
...         'shape': (2, 1),
...         'nodata_value': 5,
...     }]
... })
>>> rst.srs.srid
4326
>>> rst.width, rst.height
(4, 4)
>>> rst.bands[0].data()
array([[5, 5, 5, 5],
       [5, 2, 3, 5],
       [5, 2, 3, 5],
       [5, 5, 5, 5]], dtype=uint8)
>>> rst_file = open('/path/to/your/raster.tif', 'rb')
>>> rst_bytes = rst_file.read()
>>> rst = GDALRaster(rst_bytes)
>>> rst.is_vsi_based
True
>>> rst.name  # Stored in a random path in the vsimem filesystem.
'/vsimem/da300bdb-129d-49a8-b336-e410a9428dad'

Changed in Django 1.11:

Added the ability to pass the size, shape, and offset parameters when creating GDALRaster objects. The parameters can be passed through the ds_input dictionary. This allows to finely control initial pixel values. The functionality is similar to the GDALBand.data() method.

Changed in Django 2.0:

Added the ability to read and write rasters in GDAL's memory-based virtual filesystem. GDALRaster objects can now be converted to and from binary data in-memory.

name¶

The name of the source which is equivalent to the input file path or the name provided upon instantiation.

>>> GDALRaster({'width': 10, 'height': 10, 'name': 'myraster', 'srid': 4326}).name
'myraster'

driver¶

The name of the GDAL driver used to handle the input file. For GDALRasters created from a file, the driver type is detected automatically. The creation of rasters from scratch is a in-memory raster by default ('MEM'), but can be altered as needed. For instance, use GTiff for a GeoTiff file. For a list of file types, see also the GDAL Raster Formats list.

An in-memory raster is created through the following example:

>>> GDALRaster({'width': 10, 'height': 10, 'srid': 4326}).driver.name
'MEM'

A file based GeoTiff raster is created through the following example:

>>> import tempfile
>>> rstfile = tempfile.NamedTemporaryFile(suffix='.tif')
>>> rst = GDALRaster({'driver': 'GTiff', 'name': rstfile.name, 'srid': 4326,
...                   'width': 255, 'height': 255, 'nr_of_bands': 1})
>>> rst.name
'/tmp/tmp7x9H4J.tif'           # The exact filename will be different on your computer
>>> rst.driver.name
'GTiff'

width¶

The width of the source in pixels (X-axis).

>>> GDALRaster({'width': 10, 'height': 20, 'srid': 4326}).width
10

height¶

The height of the source in pixels (Y-axis).

>>> GDALRaster({'width': 10, 'height': 20, 'srid': 4326}).height
20

srs¶

The spatial reference system of the raster, as a SpatialReference instance. The SRS can be changed by setting it to an other SpatialReference or providing any input that is accepted by the SpatialReference constructor.

>>> rst = GDALRaster({'width': 10, 'height': 20, 'srid': 4326})
>>> rst.srs.srid
4326
>>> rst.srs = 3086
>>> rst.srs.srid
3086

srid¶

The Spatial Reference System Identifier (SRID) of the raster. This property is a shortcut to getting or setting the SRID through the srs attribute.

>>> rst = GDALRaster({'width': 10, 'height': 20, 'srid': 4326})
>>> rst.srid
4326
>>> rst.srid = 3086
>>> rst.srid
3086
>>> rst.srs.srid  # This is equivalent
3086

geotransform¶

The affine transformation matrix used to georeference the source, as a tuple of six coefficients which map pixel/line coordinates into georeferenced space using the following relationship:

Xgeo = GT(0) + Xpixel*GT(1) + Yline*GT(2)
Ygeo = GT(3) + Xpixel*GT(4) + Yline*GT(5)

The same values can be retrieved by accessing the origin (indices 0 and 3), scale (indices 1 and 5) and skew (indices 2 and 4) properties.

Awalnya adalah [0.0, 1.0, 0.0, 0.0, 0.0, -1.0].

>>> rst = GDALRaster({'width': 10, 'height': 20, 'srid': 4326})
>>> rst.geotransform
[0.0, 1.0, 0.0, 0.0, 0.0, -1.0]

origin¶

Coordinates of the top left origin of the raster in the spatial reference system of the source, as a point object with x and y members.

>>> rst = GDALRaster({'width': 10, 'height': 20, 'srid': 4326})
>>> rst.origin
[0.0, 0.0]
>>> rst.origin.x = 1
>>> rst.origin
[1.0, 0.0]

scale¶

Pixel width and height used for georeferencing the raster, as a as a point object with x and y members. See geotransform for more information.

>>> rst = GDALRaster({'width': 10, 'height': 20, 'srid': 4326})
>>> rst.scale
[1.0, -1.0]
>>> rst.scale.x = 2
>>> rst.scale
[2.0, -1.0]

skew¶

Skew coefficients used to georeference the raster, as a point object with x and y members. In case of north up images, these coefficients are both 0.

>>> rst = GDALRaster({'width': 10, 'height': 20, 'srid': 4326})
>>> rst.skew
[0.0, 0.0]
>>> rst.skew.x = 3
>>> rst.skew
[3.0, 0.0]

extent¶

Extent (boundary values) of the raster source, as a 4-tuple (xmin, ymin, xmax, ymax) in the spatial reference system of the source.

>>> rst = GDALRaster({'width': 10, 'height': 20, 'srid': 4326})
>>> rst.extent
(0.0, -20.0, 10.0, 0.0)
>>> rst.origin.x = 100
>>> rst.extent
(100.0, -20.0, 110.0, 0.0)

bands¶

List of all bands of the source, as GDALBand instances.

>>> rst = GDALRaster({"width": 1, "height": 2, 'srid': 4326,
...                   "bands": [{"data": [0, 1]}, {"data": [2, 3]}]})
>>> len(rst.bands)
2
>>> rst.bands[1].data()
array([[ 2.,  3.]], dtype=float32)

warp(ds_input, resampling='NearestNeighbour', max_error=0.0)¶

Returns a warped version of this raster.

The warping parameters can be specified through the ds_input argument. The use of ds_input is analogous to the corresponding argument of the class constructor. It is a dictionary with the characteristics of the target raster. Allowed dictionary key values are width, height, SRID, origin, scale, skew, datatype, driver, and name (filename).

By default, the warp functions keeps most parameters equal to the values of the original source raster, so only parameters that should be changed need to be specified. Note that this includes the driver, so for file-based rasters the warp function will create a new raster on disk.

The only parameter that is set differently from the source raster is the name. The default value of the the raster name is the name of the source raster appended with '_copy' + source_driver_name. For file-based rasters it is recommended to provide the file path of the target raster.

The resampling algorithm used for warping can be specified with the resampling argument. The default is NearestNeighbor, and the other allowed values are Bilinear, Cubic, CubicSpline, Lanczos, Average, and Mode.

The max_error argument can be used to specify the maximum error measured in input pixels that is allowed in approximating the transformation. The default is 0.0 for exact calculations.

Untuk pengguna akrab dengan GDAL, fungsi ini mempunyai fungsionalitas mirip pada kegunaan baris-perintah gdalwarp.

For example, the warp function can be used for aggregating a raster to the double of its original pixel scale:

>>> rst = GDALRaster({
...     "width": 6, "height": 6, "srid": 3086,
...     "origin": [500000, 400000],
...     "scale": [100, -100],
...     "bands": [{"data": range(36), "nodata_value": 99}]
... })
>>> target = rst.warp({"scale": [200, -200], "width": 3, "height": 3})
>>> target.bands[0].data()
array([[  7.,   9.,  11.],
       [ 19.,  21.,  23.],
       [ 31.,  33.,  35.]], dtype=float32)

transform(srid, driver=None, name=None, resampling='NearestNeighbour', max_error=0.0)¶

Returns a transformed version of this raster with the specified SRID.

This function transforms the current raster into a new spatial reference system that can be specified with an srid. It calculates the bounds and scale of the current raster in the new spatial reference system and warps the raster using the warp function.

By default, the driver of the source raster is used and the name of the raster is the original name appended with '_copy' + source_driver_name. A different driver or name can be specified with the driver and name arguments.

The default resampling algorithm is NearestNeighbour but can be changed using the resampling argument. The default maximum allowed error for resampling is 0.0 and can be changed using the max_error argument. Consult the warp documentation for detail on those arguments.

>>> rst = GDALRaster({
...     "width": 6, "height": 6, "srid": 3086,
...     "origin": [500000, 400000],
...     "scale": [100, -100],
...     "bands": [{"data": range(36), "nodata_value": 99}]
... })
>>> target = rst.transform(4326)
>>> target.origin
[-82.98492744885776, 27.601924753080144]

info¶

New in Django 2.0.

Returns a string with a summary of the raster. This is equivalent to the gdalinfo command line utility.

metadata¶

New in Django 2.0.

The metadata of this raster, represented as a nested dictionary. The first-level key is the metadata domain. The second-level contains the metadata item names and values from each domain.

To set or update a metadata item, pass the corresponding metadata item to the method using the nested structure described above. Only keys that are in the specified dictionary are updated; the rest of the metadata remains unchanged.

To remove a metadata item, use None as the metadata value.

>>> rst = GDALRaster({'width': 10, 'height': 20, 'srid': 4326})
>>> rst.metadata
{}
>>> rst.metadata = {'DEFAULT': {'OWNER': 'Django', 'VERSION': '1.0'}}
>>> rst.metadata
{'DEFAULT': {'OWNER': 'Django', 'VERSION': '1.0'}}
>>> rst.metadata = {'DEFAULT': {'OWNER': None, 'VERSION': '2.0'}}
>>> rst.metadata
{'DEFAULT': {'VERSION': '2.0'}}

vsi_buffer¶

New in Django 2.0:

A bytes representation of this raster. Returns None for rasters that are not stored in GDAL's virtual filesystem.

is_vsi_based¶

New in Django 2.0:

A boolean indicating if this raster is stored in GDAL's virtual filesystem.

GDALBand¶

class GDALBand¶

GDALBand instances are not created explicitly, but rather obtained from a GDALRaster object, through its bands attribute. The GDALBands contain the actual pixel values of the raster.

description¶

Nama dari gambaran dari pita, jika ada.

width¶

The width of the band in pixels (X-axis).

height¶

The height of the band in pixels (Y-axis).

pixel_count¶

The total number of pixels in this band. Is equal to width * height.

statistics(refresh=False, approximate=False)¶

Compute statistics on the pixel values of this band. The return value is a tuple with the following structure: (minimum, maximum, mean, standard deviation).

If the approximate argument is set to True, the statistics may be computed based on overviews or a subset of image tiles.

If the refresh argument is set to True, the statistics will be computed from the data directly, and the cache will be updated with the result.

If a persistent cache value is found, that value is returned. For raster formats using Persistent Auxiliary Metadata (PAM) services, the statistics might be cached in an auxiliary file. In some cases this metadata might be out of sync with the pixel values or cause values from a previous call to be returned which don't reflect the value of the approximate argument. In such cases, use the refresh argument to get updated values and store them in the cache.

For empty bands (where all pixel values are "no data"), all statistics are returned as None.

The statistics can also be retrieved directly by accessing the min, max, mean, and std properties.

min¶

The minimum pixel value of the band (excluding the "no data" value).

max¶

The maximum pixel value of the band (excluding the "no data" value).

mean¶

The mean of all pixel values of the band (excluding the "no data" value).

std¶

The standard deviation of all pixel values of the band (excluding the "no data" value).

nodata_value¶

The "no data" value for a band is generally a special marker value used to mark pixels that are not valid data. Such pixels should generally not be displayed, nor contribute to analysis operations.

To delete an existing "no data" value, set this property to None (requires GDAL ≥ 2.1).

datatype(as_string=False)¶

The data type contained in the band, as an integer constant between 0 (Unknown) and 11. If as_string is True, the data type is returned as a string with the following possible values: GDT_Unknown, GDT_Byte, GDT_UInt16, GDT_Int16, GDT_UInt32, GDT_Int32, GDT_Float32, GDT_Float64, GDT_CInt16, GDT_CInt32, GDT_CFloat32, and GDT_CFloat64.

color_interp(as_string=False)¶

New in Django 2.0.

The color interpretation for the band, as an integer between 0and 16. If as_string is True, the data type is returned as a string with the following possible values: GCI_Undefined, GCI_GrayIndex, GCI_PaletteIndex, GCI_RedBand, GCI_GreenBand, GCI_BlueBand, GCI_AlphaBand, GCI_HueBand, GCI_SaturationBand, GCI_LightnessBand, GCI_CyanBand, GCI_MagentaBand, GCI_YellowBand, GCI_BlackBand, GCI_YCbCr_YBand, GCI_YCbCr_CbBand, and GCI_YCbCr_CrBand. GCI_YCbCr_CrBand also represents GCI_Max because both correspond to the integer 16, but only GCI_YCbCr_CrBand is returned as a string.

data(data=None, offset=None, size=None, shape=None)¶

The accessor to the pixel values of the GDALBand. Returns the complete data array if no parameters are provided. A subset of the pixel array can be requested by specifying an offset and block size as tuples.

If NumPy is available, the data is returned as NumPy array. For performance reasons, it is highly recommended to use NumPy.

Data is written to the GDALBand if the data parameter is provided. The input can be of one of the following types - packed string, buffer, list, array, and NumPy array. The number of items in the input should normally correspond to the total number of pixels in the band, or to the number of pixels for a specific block of pixel values if the offset and size parameters are provided.

If the number of items in the input is different from the target pixel block, the shape parameter must be specified. The shape is a tuple that specifies the width and height of the input data in pixels. The data is then replicated to update the pixel values of the selected block. This is useful to fill an entire band with a single value, for instance.

Sebagai contoh:

>>> rst = GDALRaster({'width': 4, 'height': 4, 'srid': 4326, 'datatype': 1, 'nr_of_bands': 1})
>>> bnd = rst.bands[0]
>>> bnd.data(range(16))
>>> bnd.data()
array([[ 0,  1,  2,  3],
       [ 4,  5,  6,  7],
       [ 8,  9, 10, 11],
       [12, 13, 14, 15]], dtype=int8)
>>> bnd.data(offset=(1, 1), size=(2, 2))
array([[ 5,  6],
       [ 9, 10]], dtype=int8)
>>> bnd.data(data=[-1, -2, -3, -4], offset=(1, 1), size=(2, 2))
>>> bnd.data()
array([[ 0,  1,  2,  3],
       [ 4, -1, -2,  7],
       [ 8, -3, -4, 11],
       [12, 13, 14, 15]], dtype=int8)
>>> bnd.data(data='\x9d\xa8\xb3\xbe', offset=(1, 1), size=(2, 2))
>>> bnd.data()
array([[  0,   1,   2,   3],
       [  4, -99, -88,   7],
       [  8, -77, -66,  11],
       [ 12,  13,  14,  15]], dtype=int8)
>>> bnd.data([1], shape=(1, 1))
>>> bnd.data()
array([[1, 1, 1, 1],
       [1, 1, 1, 1],
       [1, 1, 1, 1],
       [1, 1, 1, 1]], dtype=uint8)
>>> bnd.data(range(4), shape=(1, 4))
array([[0, 0, 0, 0],
       [1, 1, 1, 1],
       [2, 2, 2, 2],
       [3, 3, 3, 3]], dtype=uint8)

metadata¶

New in Django 2.0.

The metadata of this band. The functionality is identical to GDALRaster.metadata.

Membuat raster dari data¶

This section describes how to create rasters from scratch using the ds_input parameter.

A new raster is created when a dict is passed to the GDALRaster constructor. The dictionary contains defining parameters of the new raster, such as the origin, size, or spatial reference system. The dictionary can also contain pixel data and information about the format of the new raster. The resulting raster can therefore be file-based or memory-based, depending on the driver specified.

There's no standard for describing raster data in a dictionary or JSON flavor. The definition of the dictionary input to the GDALRaster class is therefore specific to Django. It's inspired by the geojson format, but the geojson standard is currently limited to vector formats.

Examples of using the different keys when creating rasters can be found in the documentation of the corresponding attributes and methods of the GDALRaster and GDALBand classes.

Using GDAL's Virtual Filesystem¶

GDAL has an internal memory-based filesystem, which allows treating blocks of memory as files. It can be used to read and write GDALRaster objects to and from binary file buffers.

This is useful in web contexts where rasters might be obtained as a buffer from a remote storage or returned from a view without being written to disk.

GDALRaster objects are created in the virtual filesystem when a bytes object is provided as input, or when the file path starts with /vsimem/.

Input provided as bytes has to be a full binary representation of a file. For instance:

# Read a raster as a file object from a remote source.
>>> from urllib.request import urlopen
>>> dat = urlopen('http://example.com/raster.tif').read()
# Instantiate a raster from the bytes object.
>>> rst = GDALRaster(dat)
# The name starts with /vsimem/, indicating that the raster lives in the
# virtual filesystem.
>>> rst.name
'/vsimem/da300bdb-129d-49a8-b336-e410a9428dad'

To create a new virtual file-based raster from scratch, use the ds_input dictionary representation and provide a name argument that starts with /vsimem/ (for detail of the dictionary representation, see Membuat raster dari data). For virtual file-based rasters, the vsi_buffer attribute returns the bytes representation of the raster.

Here's how to create a raster and return it as a file in an HttpResponse:

>>> from django.http import HttpResponse
>>> rst = GDALRaster({
...     'name': '/vsimem/temporarymemfile',
...     'driver': 'tif',
...     'width': 6, 'height': 6, 'srid': 3086,
...     'origin': [500000, 400000],
...     'scale': [100, -100],
...     'bands': [{'data': range(36), 'nodata_value': 99}]
... })
>>> HttpResponse(rast.vsi_buffer, 'image/tiff')

GDAL_LIBRARY_PATH¶

A string specifying the location of the GDAL library. Typically, this setting is only used if the GDAL library is in a non-standard location (e.g., /home/john/lib/libgdal.so).