geocell

Geocell

The Google Maps Geolocation API actually lets you define multiple gsm cell towers into its request. But it will just return the location and accuracy based on the first cell(serving cell), doing nothing meaningful about the neighbour cells, rssi and timing advance values.

So this is an attempt to do something a bit more meaningful...

Installation

Use pip:

::

pip install geocell

Or clone the repo and:

::

pip setup.py install

Setting your Google Maps API Key

The key will be used in:

• Google Maps Geolocation API for requesting cell locations
• Google Maps Javascript API for drawing maps

If you don't have a google maps api key. Go here <https://developers.google.com/maps/documentation/javascript/get-api-key>__ and follow the instructions to get your key.

Set your api key using either of the following methods:

• Set your key as the GOOGLE_MAPS_API_KEY environment variable
• import geocell then geocell.api_key="<your api key>"

Usage

Simple location request

.. code:: python

    >>> import geocell
    >>> sample_cell = {"mnc":2,"mcc":286,"cid":51861,"lac":54110}
    >>> geocell.locate(sample_cell)
    {'location': {'lat': 40.7018889, 'lng': 29.8912834}, 'accuracy': 3250.0}

Location Estimation
~~~~~~~~~~~~~~~~~~~

We need the rssi values and multiple cell information to make an
estimation

.. code:: python

    >>> sample_cells = [
    ...     {"rssi":-82,"mnc":2,"mcc":286,"cid":51861,"lac":54110},
    ...     {"rssi":-85,"mnc":2,"mcc":286,"cid":16116,"lac":54110},
    ...     {"rssi":-93,"mnc":2,"mcc":286,"cid":0,"lac":54108},
    ...     {"rssi":-94,"mnc":2,"mcc":286,"cid":38344,"lac":54110},
    ...     {"rssi":-97,"mnc":2,"mcc":286,"cid":52555,"lac":54110},
    ...     {"rssi":-98,"mnc":2,"mcc":286,"cid":51857,"lac":54108},
    ...     {"rssi":-99,"mnc":2,"mcc":286,"cid":39684,"lac":54110}
    ... ]
    >>> geocell.estimate(sample_cells)
    {'location': {'lat': 40.70356939393244, 'lng': 29.88564243119295}, 'accuracy': 251.3839360809747}

.. NOTE::

    You will notice that this function takes couple of seconds to
    return, the reason is that the *Google Maps Geolocation API*
    requests take some time. But the cell requests are cached internally
    in the module so the next time you request the same cell, the value
    will be returned instantly. If you like, you can also set
    ``geocell.is_multiprocess = True`` to do multiple requests, just
    don't use multiprocessing inside a interpreter, it doesn't like it.

Let's see it in action now:

.. code:: python

    >>> geocell.estimate(sample_cells, "map.html")
    {'location': {'lat': 40.70356939393244, 'lng': 29.88564243119295}, 'accuracy': 251.38393
    60809747}

Looking at the generated map:

-  **Light yellow circle** is the serving cell
-  **Red colored** are the neighbour cells
-  **The blue lines** are the flight path showing estimation done at
   each step. Starting point of the flight path is the center of the
   serving cell
-  **The marker** shows the end of the flight path and the last
   estimated location

.. figure:: https://cloud.githubusercontent.com/assets/3398029/18313982/d0a5a9a0-7519-11e6-99e3-70743cffdf78.jpg
   :alt: all


Let's take a closer look:

.. code:: python

    >>> geocell.estimate(sample_cells, "map_estimate.html", cell_display="estimate")
    {'location': {'lat': 40.70356939393244, 'lng': 29.88564243119295}, 'accuracy': 251.38393
    60809747}

Now the map shows only the estimated location(marker) and estimated
accuracy(radius). The arrow points to the actual location.

.. figure:: https://cloud.githubusercontent.com/assets/3398029/18313986/d32f370e-7519-11e6-9250-6ae622daf013.jpg
   :alt: estimate