Mapbox Vector Tile
Project description
Mapbox Vector Tile
==================
Installation
------------
mapbox-vector-tile is compatible with Python 2.6, 2.7. It is listed on PyPi as `mapbox-vector-tile`. The recommended way to install is via `pip`:
```shell
pip install mapbox-vector-tile
```
Encoding
--------
Encode method expects an array of layers or atleast a single valid layer. A valid layer is a dictionary with the following keys
* `name`: layer name
* `features`: an array of features. A feature is a dictionary with the following keys:
* `geometry`: representation of the feature geometry in WKT, WKB, or a shapely geometry. Coordinates are relative to the tile, scaled in the range `[0, 4096)`. See below for example code to perform the necessary transformation.
* `properties`: a dictionary with a few keys and their corresponding values.
```python
>>> import mapbox_vector_tile
# Using WKT
>>> mapbox_vector_tile.encode([
{
"name": "water",
"features": [
{
"geometry":"POLYGON ((0 0, 0 1, 1 1, 1 0, 0 0))",
"properties":{
"uid":123,
"foo":"bar",
"cat":"flew"
}
}
]
},
{
"name": "air",
"features": [
{
"geometry":"LINESTRING(159 3877, -1570 3877)",
"properties":{
"uid":1234,
"foo":"bar",
"cat":"flew"
}
}
]
}
])
'\x1aH\n\x05water\x12\x18\x12\x06\x00\x00\x01\x01\x02\x02\x18\x03"\x0c\t\x00\x80@\x1a\x00\x01\x02\x00\x00\x02\x0f\x1a\x03foo\x1a\x03uid\x1a\x03cat"\x05\n\x03bar"\x02 {"\x06\n\x04flew(\x80 x\x02\x1aD\n\x03air\x12\x15\x12\x06\x00\x00\x01\x01\x02\x02\x18\x02"\t\t\xbe\x02\xb6\x03\n\x81\x1b\x00\x1a\x03foo\x1a\x03uid\x1a\x03cat"\x05\n\x03bar"\x03 \xd2\t"\x06\n\x04flew(\x80 x\x02'
# Using WKB
>>> mapbox_vector_tile.encode([
{
"name": "water",
"features": [
{
"geometry":"\001\003\000\000\000\001\000\000\000\005\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\360?\000\000\000\000\000\000\360?\000\000\000\000\000\000\360?\000\000\000\000\000\000\360?\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000",
"properties":{
"uid":123,
"foo":"bar",
"cat":"flew"
}
}
]
},
{
"name": "air",
"features": [
{
"geometry":"\001\003\000\000\000\001\000\000\000\005\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\360?\000\000\000\000\000\000\360?\000\000\000\000\000\000\360?\000\000\000\000\000\000\360?\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000",
"properties":{
"uid":1234,
"foo":"bar",
"cat":"flew"
}
}
]
}
])
'\x1aJ\n\x05water\x12\x1a\x08\x01\x12\x06\x00\x00\x01\x01\x02\x02\x18\x03"\x0c\t\x00\x80@\x1a\x00\x01\x02\x00\x00\x02\x0f\x1a\x03foo\x1a\x03uid\x1a\x03cat"\x05\n\x03bar"\x02 {"\x06\n\x04flew(\x80 x\x02\x1aY\n\x03air\x12\x1c\x08\x01\x12\x08\x00\x00\x01\x01\x02\x02\x03\x03\x18\x03"\x0c\t\x00\x80@\x1a\x00\x01\x02\x00\x00\x02\x0f\x1a\x03foo\x1a\x03uid\x1a\x05balls\x1a\x03cat"\x05\n\x03bar"\x03 \xd2\t"\x05\n\x03foo"\x06\n\x04flew(\x80 x\x02'
```
### Coordinate transformations for encoding
The encoder expects geometries in tile-relative coordinates, where the lower left corner is origin and values grow up and to the right, and the tile is 4096 pixels square. For example, `POINT(0 0)` is the lower left corner of the tile and `POINT(4095, 4095)` is the upper right corner of the tile. Per the specification, geometries are expected to be in spherical mercator projection before this transformations
If you have geometries in longitude and latitude (EPSG:4326), you can convert to tile-based coordinates by first projecting to Spherical Mercator (EPSG:3857) and then computing the pixel location within the tile. This example code uses Django's included GEOS library to do the transformation for `LineString` objects:
```python
SRID_SPHERICAL_MERCATOR = 3857
def linestring_in_tile(tile_bounds, line):
# `mapbox-vector-tile` has a hardcoded tile extent of 4096 units.
MVT_EXTENT = 4096
from django.contrib.gis.geos import LineString
# We need tile bounds in spherical mercator
assert tile_bounds.srid == SRID_SPHERICAL_MERCATOR
# And we need the line to be in a known projection so we can re-project
assert line.srid is not None
line.transform(SRID_SPHERICAL_MERCATOR)
(x0, y0, x_max, y_max) = tile_bounds.extent
x_span = x_max - x0
y_span = y_max - y0
def xy_pairs():
for x_merc, y_merc in line:
yield (
int((x_merc - x0) * MVT_EXTENT / x_span),
int((y_merc - y0) * MVT_EXTENT / y_span),
```
The tile bounds can be found with `mercantile`, so a complete usage example might look like this:
```python
from django.contrib.gis.geos import LineString, Polygon
import mercantile
import mapbox_vector_tile
SRID_LNGLAT = 4326
SRID_SPHERICAL_MERCATOR = 3857
tile_xyz = (2452, 3422, 18)
tile_bounds = Polygon.from_bbox(mercantile.bounds(*tile_xyz))
tile_bounds.srid = SRID_LNGLAT
tile_bounds.transform(SRID_SPHERICAL_MERCATOR)
lnglat_line = LineString(((-122.1, 45.1), (-122.2, 45.2)), srid=SRID_LNGLAT)
tile_line = linestring_in_tile(tile_bounds, lnglat_line)
tile_pbf = mapbox_vector_tile.encode({
"name": "my-layer",
"features": [ {
"geometry": tile_line.wkt,
"properties": { "stuff": "things" },
} ]
})
```
Note that this example may not have anything visible within the tile when rendered. It's up to you to make sure you put the right data in the tile!
Also note that the spec allows the extents to be modified, even though they are often set to 4096 by convention. `mapbox-vector-tile` assumes an extent of 4096.
### Quantization
The encoder also has options to quantize the data for you via the `quantize_bounds` option. When encoding, pass in the bounds in the form (minx, maxx, miny, maxy) and the coordinates will be scaled appropriately during encoding.
```python
mapbox_vector_tile.encode([
{
"name": "water",
"features": [
{
"geometry":"POINT(15 15)",
"properties":{
"foo":"bar",
}
}
]
}
], quantize_bounds=(10.0, 10.0, 20.0, 20.0))
```
In this example, the coordinate that would get encoded would be (2048, 2048)
Additionally, if the data is already in a cooridnate system with y values going down, the encoder supports an option, `y_coord_down`, that can be set to True. This will suppress flipping the y coordinate values during encoding.
### Custom extents
The encoder also supports passing in custom extents. These will be passed through to the layer in the pbf, and honored during any quantization or y coordinate flipping.
```python
mapbox_vector_tile.encode([
{
"name": "water",
"features": [
{
"geometry":"POINT(15 15)",
"properties":{
"foo":"bar",
}
}
]
}
], quantize_bounds=(0.0, 0.0, 10.0, 10.0), extents=50)
```
Decoding
--------
Decode method takes in a valid google.protobuf.message Tile and returns decoded string in the following format:
```python
{
layername: {
'extent': 'integer layer extent'
'version': 'integer'
'features': [{
'geometry': 'list of points',
'properties': 'dictionary of key/value pairs',
'id': 'unique id for the given feature within the layer '
}, ...
]
},
layername2: {
# ...
}
}
```
```python
>>> import mapbox_vector_tile
>>> mapbox_vector_tile.decode('\x1aJ\n\x05water\x12\x1a\x08\x01\x12\x06\x00\x00\x01\x01\x02\x02\x18\x03"\x0c\t\x00\x80@\x1a\x00\x01\x02\x00\x00\x02\x0f\x1a\x03foo\x1a\x03uid\x1a\x03cat"\x05\n\x03bar"\x02 {"\x06\n\x04flew(\x80 x\x02\x1aY\n\x03air\x12\x1c\x08\x01\x12\x08\x00\x00\x01\x01\x02\x02\x03\x03\x18\x03"\x0c\t\x00\x80@\x1a\x00\x01\x02\x00\x00\x02\x0f\x1a\x03foo\x1a\x03uid\x1a\x05balls\x1a\x03cat"\x05\n\x03bar"\x03 \xd2\t"\x05\n\x03foo"\x06\n\x04flew(\x80 x\x02')
{
'water': {
'extent': 4096,
'version': 2,
'features': [{
'geometry': [[0, 0], [0, 1], [1, 1], [1, 0], [0, 0]],
'properties': {
'foo': 'bar',
'uid': 123,
'cat': 'flew'
},
'type': 3,
'id': 1
}
]
},
'air': {
'extent': 4096,
'version': 2,
'features': [{
'geometry': [[0, 0], [0, 1], [1, 1], [1, 0], [0, 0]],
'properties': {
'foo': 'bar',
'uid': 1234,
'balls': 'foo',
'cat': 'flew'
},
'type': 3,
'id': 1
}
]
}
}
```
Here's how you might decode a tile from a file.
```python
>>> import mapbox_vector_tile
>>> with open('tile.mvt', 'rb') as f:
>>> data = f.read()
>>> decoded_data = mapbox_vector_tile.decode(data)
>>> with open('out.txt', 'w') as f:
>>> f.write(repr(decoded_data))
```
Changelog
---------
Click [here](https://github.com/mapzen/mapbox-vector-tile/blob/master/CHANGELOG.rst) to see what changed over time in various versions.
==================
Installation
------------
mapbox-vector-tile is compatible with Python 2.6, 2.7. It is listed on PyPi as `mapbox-vector-tile`. The recommended way to install is via `pip`:
```shell
pip install mapbox-vector-tile
```
Encoding
--------
Encode method expects an array of layers or atleast a single valid layer. A valid layer is a dictionary with the following keys
* `name`: layer name
* `features`: an array of features. A feature is a dictionary with the following keys:
* `geometry`: representation of the feature geometry in WKT, WKB, or a shapely geometry. Coordinates are relative to the tile, scaled in the range `[0, 4096)`. See below for example code to perform the necessary transformation.
* `properties`: a dictionary with a few keys and their corresponding values.
```python
>>> import mapbox_vector_tile
# Using WKT
>>> mapbox_vector_tile.encode([
{
"name": "water",
"features": [
{
"geometry":"POLYGON ((0 0, 0 1, 1 1, 1 0, 0 0))",
"properties":{
"uid":123,
"foo":"bar",
"cat":"flew"
}
}
]
},
{
"name": "air",
"features": [
{
"geometry":"LINESTRING(159 3877, -1570 3877)",
"properties":{
"uid":1234,
"foo":"bar",
"cat":"flew"
}
}
]
}
])
'\x1aH\n\x05water\x12\x18\x12\x06\x00\x00\x01\x01\x02\x02\x18\x03"\x0c\t\x00\x80@\x1a\x00\x01\x02\x00\x00\x02\x0f\x1a\x03foo\x1a\x03uid\x1a\x03cat"\x05\n\x03bar"\x02 {"\x06\n\x04flew(\x80 x\x02\x1aD\n\x03air\x12\x15\x12\x06\x00\x00\x01\x01\x02\x02\x18\x02"\t\t\xbe\x02\xb6\x03\n\x81\x1b\x00\x1a\x03foo\x1a\x03uid\x1a\x03cat"\x05\n\x03bar"\x03 \xd2\t"\x06\n\x04flew(\x80 x\x02'
# Using WKB
>>> mapbox_vector_tile.encode([
{
"name": "water",
"features": [
{
"geometry":"\001\003\000\000\000\001\000\000\000\005\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\360?\000\000\000\000\000\000\360?\000\000\000\000\000\000\360?\000\000\000\000\000\000\360?\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000",
"properties":{
"uid":123,
"foo":"bar",
"cat":"flew"
}
}
]
},
{
"name": "air",
"features": [
{
"geometry":"\001\003\000\000\000\001\000\000\000\005\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\360?\000\000\000\000\000\000\360?\000\000\000\000\000\000\360?\000\000\000\000\000\000\360?\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000",
"properties":{
"uid":1234,
"foo":"bar",
"cat":"flew"
}
}
]
}
])
'\x1aJ\n\x05water\x12\x1a\x08\x01\x12\x06\x00\x00\x01\x01\x02\x02\x18\x03"\x0c\t\x00\x80@\x1a\x00\x01\x02\x00\x00\x02\x0f\x1a\x03foo\x1a\x03uid\x1a\x03cat"\x05\n\x03bar"\x02 {"\x06\n\x04flew(\x80 x\x02\x1aY\n\x03air\x12\x1c\x08\x01\x12\x08\x00\x00\x01\x01\x02\x02\x03\x03\x18\x03"\x0c\t\x00\x80@\x1a\x00\x01\x02\x00\x00\x02\x0f\x1a\x03foo\x1a\x03uid\x1a\x05balls\x1a\x03cat"\x05\n\x03bar"\x03 \xd2\t"\x05\n\x03foo"\x06\n\x04flew(\x80 x\x02'
```
### Coordinate transformations for encoding
The encoder expects geometries in tile-relative coordinates, where the lower left corner is origin and values grow up and to the right, and the tile is 4096 pixels square. For example, `POINT(0 0)` is the lower left corner of the tile and `POINT(4095, 4095)` is the upper right corner of the tile. Per the specification, geometries are expected to be in spherical mercator projection before this transformations
If you have geometries in longitude and latitude (EPSG:4326), you can convert to tile-based coordinates by first projecting to Spherical Mercator (EPSG:3857) and then computing the pixel location within the tile. This example code uses Django's included GEOS library to do the transformation for `LineString` objects:
```python
SRID_SPHERICAL_MERCATOR = 3857
def linestring_in_tile(tile_bounds, line):
# `mapbox-vector-tile` has a hardcoded tile extent of 4096 units.
MVT_EXTENT = 4096
from django.contrib.gis.geos import LineString
# We need tile bounds in spherical mercator
assert tile_bounds.srid == SRID_SPHERICAL_MERCATOR
# And we need the line to be in a known projection so we can re-project
assert line.srid is not None
line.transform(SRID_SPHERICAL_MERCATOR)
(x0, y0, x_max, y_max) = tile_bounds.extent
x_span = x_max - x0
y_span = y_max - y0
def xy_pairs():
for x_merc, y_merc in line:
yield (
int((x_merc - x0) * MVT_EXTENT / x_span),
int((y_merc - y0) * MVT_EXTENT / y_span),
```
The tile bounds can be found with `mercantile`, so a complete usage example might look like this:
```python
from django.contrib.gis.geos import LineString, Polygon
import mercantile
import mapbox_vector_tile
SRID_LNGLAT = 4326
SRID_SPHERICAL_MERCATOR = 3857
tile_xyz = (2452, 3422, 18)
tile_bounds = Polygon.from_bbox(mercantile.bounds(*tile_xyz))
tile_bounds.srid = SRID_LNGLAT
tile_bounds.transform(SRID_SPHERICAL_MERCATOR)
lnglat_line = LineString(((-122.1, 45.1), (-122.2, 45.2)), srid=SRID_LNGLAT)
tile_line = linestring_in_tile(tile_bounds, lnglat_line)
tile_pbf = mapbox_vector_tile.encode({
"name": "my-layer",
"features": [ {
"geometry": tile_line.wkt,
"properties": { "stuff": "things" },
} ]
})
```
Note that this example may not have anything visible within the tile when rendered. It's up to you to make sure you put the right data in the tile!
Also note that the spec allows the extents to be modified, even though they are often set to 4096 by convention. `mapbox-vector-tile` assumes an extent of 4096.
### Quantization
The encoder also has options to quantize the data for you via the `quantize_bounds` option. When encoding, pass in the bounds in the form (minx, maxx, miny, maxy) and the coordinates will be scaled appropriately during encoding.
```python
mapbox_vector_tile.encode([
{
"name": "water",
"features": [
{
"geometry":"POINT(15 15)",
"properties":{
"foo":"bar",
}
}
]
}
], quantize_bounds=(10.0, 10.0, 20.0, 20.0))
```
In this example, the coordinate that would get encoded would be (2048, 2048)
Additionally, if the data is already in a cooridnate system with y values going down, the encoder supports an option, `y_coord_down`, that can be set to True. This will suppress flipping the y coordinate values during encoding.
### Custom extents
The encoder also supports passing in custom extents. These will be passed through to the layer in the pbf, and honored during any quantization or y coordinate flipping.
```python
mapbox_vector_tile.encode([
{
"name": "water",
"features": [
{
"geometry":"POINT(15 15)",
"properties":{
"foo":"bar",
}
}
]
}
], quantize_bounds=(0.0, 0.0, 10.0, 10.0), extents=50)
```
Decoding
--------
Decode method takes in a valid google.protobuf.message Tile and returns decoded string in the following format:
```python
{
layername: {
'extent': 'integer layer extent'
'version': 'integer'
'features': [{
'geometry': 'list of points',
'properties': 'dictionary of key/value pairs',
'id': 'unique id for the given feature within the layer '
}, ...
]
},
layername2: {
# ...
}
}
```
```python
>>> import mapbox_vector_tile
>>> mapbox_vector_tile.decode('\x1aJ\n\x05water\x12\x1a\x08\x01\x12\x06\x00\x00\x01\x01\x02\x02\x18\x03"\x0c\t\x00\x80@\x1a\x00\x01\x02\x00\x00\x02\x0f\x1a\x03foo\x1a\x03uid\x1a\x03cat"\x05\n\x03bar"\x02 {"\x06\n\x04flew(\x80 x\x02\x1aY\n\x03air\x12\x1c\x08\x01\x12\x08\x00\x00\x01\x01\x02\x02\x03\x03\x18\x03"\x0c\t\x00\x80@\x1a\x00\x01\x02\x00\x00\x02\x0f\x1a\x03foo\x1a\x03uid\x1a\x05balls\x1a\x03cat"\x05\n\x03bar"\x03 \xd2\t"\x05\n\x03foo"\x06\n\x04flew(\x80 x\x02')
{
'water': {
'extent': 4096,
'version': 2,
'features': [{
'geometry': [[0, 0], [0, 1], [1, 1], [1, 0], [0, 0]],
'properties': {
'foo': 'bar',
'uid': 123,
'cat': 'flew'
},
'type': 3,
'id': 1
}
]
},
'air': {
'extent': 4096,
'version': 2,
'features': [{
'geometry': [[0, 0], [0, 1], [1, 1], [1, 0], [0, 0]],
'properties': {
'foo': 'bar',
'uid': 1234,
'balls': 'foo',
'cat': 'flew'
},
'type': 3,
'id': 1
}
]
}
}
```
Here's how you might decode a tile from a file.
```python
>>> import mapbox_vector_tile
>>> with open('tile.mvt', 'rb') as f:
>>> data = f.read()
>>> decoded_data = mapbox_vector_tile.decode(data)
>>> with open('out.txt', 'w') as f:
>>> f.write(repr(decoded_data))
```
Changelog
---------
Click [here](https://github.com/mapzen/mapbox-vector-tile/blob/master/CHANGELOG.rst) to see what changed over time in various versions.
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