Metadata-Version: 1.0
Name: vectortile
Version: 1.3.1
Summary: A set of classes for managing tiles of geospatial vector data
Home-page: https://github.com/SkyTruth/vectortile
Author: Paul Woods
Author-email: paul@skytruth.org
License: The MIT License (MIT)

Copyright (c) 2014 SkyTruth

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.

Description: Vector Tile Tools
        =================
        A set of classes for managing tiles of geospatial vector data
        
        ![Build Status](https://travis-ci.org/SkyTruth/vectortile.svg)
        
        
        Installation and Unittests
        --------------------------
        Install via pip:
        
            pip install vectortile
        
        Source:
            
            $ git clone https://github.com/SkyTruth/vectortile.git
            $ cd vectortile
            $ pip install -r requirements.txt
            $ nosetests
            $ python setup.py install
        
        
        TypedMatrix
        -----------
        TypedMatrix is a binary coded format optimized for delivering large amounts of
        tabular data from a web server to a javascript client without the need for
        parsing in javascript on the client side.
        
        The vectortile.TypedMatrix module provides functions to read and write
        typed-matrix formatted strings.
        
        
        ### Format Details ###
        A TypedMatrix is a packed 2 dimensional array of typed values suitable for
        typecasting to a set of javascript arrays.  Currently two fundamental data
        types are supported:
        
        - Int32
        - Float32
        
        Special handling is provided for converting datetime values to Float32.  The
        format includes a header containing a json object, which can contain arbitrary
        content.  The header must contain at least:
        
        - length: indicated the number of rows in the data section
        - cols: an array of column definitions.  The length of this array indicates the number of columns in each row
        
        For example, a TypedMatrix with 2 rows and 3 columns:
        
            {
                'length': 2,
                'cols': [
                    {
                        'type': 'Float32',
                        'name': 'float'
                    },
                    {
                        'type': 'Int32',
                        'name': 'int'
                    },
                    {
                        'type': 'Float32',
                        'name': 'timestamp'
                    }
                ]
            }
        
        
        ### Usage Examples ###
        
            >>> from vectortile import TypedMatrix
            >>> from datetime import datetime
            >>> from pprint import pprint
        
            # Create two rows of 3 columns each: int, float and datetime
            >>> data = [{'int':1, 'float':1.0, 'timestamp': datetime(2014,1,1)}]
            >>> data.append ({'int':2, 'float':2.0, 'timestamp':datetime(2014,1,2)})
            >>> t_str = TypedMatrix.pack(data)
        
            # Typedmatrix is now coded as a binary string, packed row-wise
            >>> t_str
            'tmtx\x01\x00\x00\x00r\x89\x00\x00\x00{"length": 2, "cols": [{"type": "Float32", "name": "float"}, {"type": "Int32", "name": "int"}, {"type": "Float32", "name": "timestamp"}]}\x00\x00\x80?\x01\x00\x00\x00\x8d\xa5\xa1S\x00\x00\x00@\x02\x00\x00\x00 \xa8\xa1S'
            
            >>> header, data = TypedMatrix.unpack(t_str)
            >>> pprint(header)
            {
                'cols': [
                    {
                        'name': 'float',
                        'type': 'Float32'
                    },
                    {
                        'name': 'int',
                        'type': 'Int32'
                    },
                    {
                        'name': 'timestamp',
                        'type': 'Float32'
                    }
                ],
                'length': 2
            }
            
            >>> pprint(data)
            [
                {
                    'float': 1.0,
                    'int': 1,
                    'timestamp': 1388534431744.0
                },
                {
                    'float': 2.0,
                    'int': 2,
                    'timestamp': 1388620808192.0
                }
            ]
        
            # Pack data column-wise
            >>> TypedMatrix.pack(data,orientation='columnwise')
            'tmtx\x01\x00\x00\x00c\x89\x00\x00\x00{"length": 2, "cols": [{"type": "Float32", "name": "float"}, {"type": "Int32", "name": "int"}, {"type": "Float32", "name": "timestamp"}]}\x00\x00\x80?\x00\x00\x00@\x01\x00\x00\x00\x02\x00\x00\x00\x8d\xa5\xa1S \xa8\xa1S'
            
            >>> header, data = TypedMatrix.unpack(t_str)
            >>> pprint(header)
            {
                'cols': [
                    {
                        'name': 'float',
                        'type': 'Float32'
                    },
                    {
                        'name': 'int',
                        'type': 'Int32'
                    },
                    {
                        'name': 'timestamp',
                        'type': 'Float32'
                    }
                ],
                'length': 2
            }
            
            >>> pprint(data)
            [
                {
                    'float': 1.0,
                    'int': 1,
                    'timestamp': 1388534431744.0
                },
                {
                    'float': 2.0,
                    'int': 2,
                    'timestamp': 1388620808192.0
                }
            ]
        
        
        ### Javascript Example ###
        See [data-visualization-tools](https://github.com/SkyTruth/data-visualization-tools)
        
Platform: UNKNOWN
