python-awips/_sources/examples/generated/Map_Resources_and_Topography.rst.txt

============================
Map Resources and Topography
============================
`Notebook <http://nbviewer.ipython.org/github/Unidata/python-awips/blob/master/examples/notebooks/Map_Resources_and_Topography.ipynb>`_
Python-AWIPS Tutorial Notebook

--------------

Objectives
==========

-  Use python-awips to connect to an edex server
-  Define data request object specifically for the maps database
-  Manipulate request object for various different map resources
-  Plot map resources in combination with one another for geographical
   context

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Table of Contents
-----------------

| `1
  Imports <https://unidata.github.io/python-awips/examples/generated/Map_Resources_and_Topography.html#imports>`__\ 
| `2 Connect to
  EDEX <https://unidata.github.io/python-awips/examples/generated/Map_Resources_and_Topography.html#connect-to-edex>`__\ 
| `3 Function:
  make_map() <https://unidata.github.io/python-awips/examples/generated/Map_Resources_and_Topography.html#function-make-map>`__\ 
| `4 Create Initial Map From
  CWA <https://unidata.github.io/python-awips/examples/generated/Map_Resources_and_Topography.html#create-initial-map-from-cwa>`__\ 
| `5 Draw Merged
  CWA <https://unidata.github.io/python-awips/examples/generated/Map_Resources_and_Topography.html#draw-merged-cwa>`__\ 
| `6 Draw Interstates using Boundary
  Filter <https://unidata.github.io/python-awips/examples/generated/Map_Resources_and_Topography.html#draw-interstates-using-boundary-filter>`__\ 
| `7 Draw Nearby
  Cities <https://unidata.github.io/python-awips/examples/generated/Map_Resources_and_Topography.html#draw-nearby-cities>`__\ 
| `8 Draw Nearby
  Lakes <https://unidata.github.io/python-awips/examples/generated/Map_Resources_and_Topography.html#draw-nearby-lakes>`__\ 
| `9 Draw Major
  Rivers <https://unidata.github.io/python-awips/examples/generated/Map_Resources_and_Topography.html#draw-major-rivers>`__\ 
| `10 Draw
  Topography <https://unidata.github.io/python-awips/examples/generated/Map_Resources_and_Topography.html#draw-topography>`__\ 
| `11 See
  Also <https://unidata.github.io/python-awips/examples/generated/Map_Resources_and_Topography.html#see-also>`__\ 
|     `11.1 Additional
  Documentation <https://unidata.github.io/python-awips/examples/generated/Map_Resources_and_Topography.html#additional-documentation>`__\ 

1 Imports
---------

The imports below are used throughout the notebook. Note the first
import is coming directly from python-awips and allows us to connect to
an EDEX server. The subsequent imports are for data manipulation and
visualization.

.. code:: ipython3

    from awips.dataaccess import DataAccessLayer
    import matplotlib.pyplot as plt
    import cartopy.crs as ccrs
    import numpy.ma as ma
    from cartopy.mpl.gridliner import LONGITUDE_FORMATTER, LATITUDE_FORMATTER
    from cartopy.feature import ShapelyFeature,NaturalEarthFeature
    from shapely.ops import cascaded_union

`Top <https://unidata.github.io/python-awips/examples/generated/Map_Resources_and_Topography.html>`__

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2 Connect to EDEX
-----------------

First we establish a connection to Unidata’s public EDEX server. With
that connection made, we can create a `new data request
object <http://unidata.github.io/python-awips/api/IDataRequest.html>`__
and set the data type to **maps**.

.. code:: ipython3

    # Server, Data Request Type, and Database Table
    DataAccessLayer.changeEDEXHost("edex-cloud.unidata.ucar.edu")
    request = DataAccessLayer.newDataRequest('maps')

`Top <https://unidata.github.io/python-awips/examples/generated/Map_Resources_and_Topography.html>`__

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3 Function: make_map()
----------------------

In many of our notebooks we end up plotting map images, and this logic
below is the same from those other notebooks. Typically, functions are
defined when they are called multiple times throughout a notebook. In
this case, we only use it in one code block cell, but because it is a
common function from several of our notebooks, it’s nice to keep the
logic neatly defined for consistency.

.. code:: ipython3

    # Standard map plot
    def make_map(bbox, projection=ccrs.PlateCarree()):
        fig, ax = plt.subplots(figsize=(12,12),
                subplot_kw=dict(projection=projection))
        ax.set_extent(bbox)
        ax.coastlines(resolution='50m')
        gl = ax.gridlines(draw_labels=True)
        gl.top_labels = gl.right_labels = False
        gl.xformatter = LONGITUDE_FORMATTER
        gl.yformatter = LATITUDE_FORMATTER
        return fig, ax

`Top <https://unidata.github.io/python-awips/examples/generated/Map_Resources_and_Topography.html>`__

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4 Create Initial Map From CWA
-----------------------------

The python-awips package provides access to the entire AWIPS Maps
Database for use in Python GIS applications. Map objects are returned as
Shapely geometries and can be easily plotted by many Python packages.

-  Each map database table has a geometry field called ``the_geom``,
   which can be used to spatially select map resources for any column of
   type geometry.

..

   **Tip**: Note the geometry definition of ``the_geom`` for each data
   type, which can be **Point**, **MultiPolygon**, or
   **MultiLineString**.

Here we’ll be using Boulder (BOU) as our example for plotting the County
Warning Area (CWA). We’ll query our EDEX server to get all counties in
the CWA for BOU, and then plot those counties along withe the state
boundaries and lines of longitude and latitude. In order to get this
information from EDEX, we’ll need to set several characteristics on our
data request object. We will use
`request.setParameters() <http://unidata.github.io/python-awips/api/IDataRequest.html#awips.dataaccess.IDataRequest.setParameters>`__
to refine our query to EDEX.

.. code:: ipython3

    # Specify the necessary identifiers for requesting the Boulder CWA
    request.addIdentifier('table', 'mapdata.county')
    # Define a WFO ID for location
    # tie this ID to the mapdata.county column "cwa" for filtering
    request.setLocationNames('BOU')
    request.addIdentifier('cwa', 'BOU')
    # enable location filtering (inLocation)
    # locationField is tied to the above cwa definition (BOU)
    request.addIdentifier('geomField', 'the_geom')
    request.addIdentifier('inLocation', 'true')
    request.addIdentifier('locationField', 'cwa')
    
    # Get response and create dict of county geometries
    response = DataAccessLayer.getGeometryData(request)
    counties = []
    for ob in response:
        counties.append(ob.getGeometry())
    print("Using " + str(len(counties)) + " county MultiPolygons")
    
    
    # All WFO counties merged to a single Polygon
    merged_counties = cascaded_union(counties)
    envelope = merged_counties.buffer(2)
    boundaries=[merged_counties]
    
    # Get bounds of this merged Polygon to use as buffered map extent
    bounds = merged_counties.bounds
    bbox=[bounds[0]-1,bounds[2]+1,bounds[1]-1.5,bounds[3]+1.5]
    
    # Create the map we'll use for the rest of this notebook based on the 
    # boundaries of the CWA
    fig, ax = make_map(bbox=bbox)
    
    # Plot political/state boundaries handled by Cartopy
    political_boundaries = NaturalEarthFeature(category='cultural',
                                   name='admin_0_boundary_lines_land',
                                   scale='50m', facecolor='none')
    states = NaturalEarthFeature(category='cultural',
                                   name='admin_1_states_provinces_lines',
                                   scale='50m', facecolor='none')
    ax.add_feature(political_boundaries, linestyle='-', edgecolor='black')
    ax.add_feature(states, linestyle='-', edgecolor='black',linewidth=2)
    
    # Plot CWA counties
    shape_feature = ShapelyFeature(counties,ccrs.PlateCarree(), 
                        facecolor='none', linestyle="-",edgecolor='#86989B')
    ax.add_feature(shape_feature)


.. parsed-literal::

    Using 22 county MultiPolygons




.. parsed-literal::

    <cartopy.mpl.feature_artist.FeatureArtist at 0x11568f6d0>




.. image:: Map_Resources_and_Topography_files/Map_Resources_and_Topography_13_2.png


`Top <https://unidata.github.io/python-awips/examples/generated/Map_Resources_and_Topography.html>`__

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5 Draw Merged CWA
-----------------

In the previous section we created a merged polygon with the applicable
counties. Here, we draw this new shape on top of our existing map in a
burnt orange color.

.. code:: ipython3

    # Plot CWA envelope
    shape_feature = ShapelyFeature(boundaries,ccrs.PlateCarree(), 
                        facecolor='none', linestyle="-",linewidth=3.,edgecolor='#cc5000')
    ax.add_feature(shape_feature)
    
    fig




.. image:: Map_Resources_and_Topography_files/Map_Resources_and_Topography_16_0.png



`Top <https://unidata.github.io/python-awips/examples/generated/Map_Resources_and_Topography.html>`__

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6 Draw Interstates using Boundary Filter
----------------------------------------

Now, we’ll use the previously-defined
**envelope=merged_counties.buffer(2)** in a **newDataRequest()** to
request interstate geometries which fall inside the buffered boundary.

.. code:: ipython3

    # Define the request for the interstate query
    request = DataAccessLayer.newDataRequest('maps', envelope=envelope)
    request.addIdentifier('table', 'mapdata.interstate')
    request.addIdentifier('geomField', 'the_geom')
    interstates = DataAccessLayer.getGeometryData(request)
    print("Using " + str(len(interstates)) + " interstate MultiLineStrings")
    
    # Plot interstates
    for ob in interstates:
        shape_feature = ShapelyFeature(ob.getGeometry(),ccrs.PlateCarree(), 
                            facecolor='none', linestyle="-",edgecolor='orange')
        ax.add_feature(shape_feature)
    fig


.. parsed-literal::

    Using 225 interstate MultiLineStrings




.. image:: Map_Resources_and_Topography_files/Map_Resources_and_Topography_19_1.png



`Top <https://unidata.github.io/python-awips/examples/generated/Map_Resources_and_Topography.html>`__

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7 Draw Nearby Cities
--------------------

Request the city table based using the **envelope** attribute and filter
by population and progressive disclosure level.

   **Warning**: The ``prog_disc`` field is not entirely understood and
   values appear to change significantly depending on WFO site.

.. code:: ipython3

    # Define the request for the city query
    request = DataAccessLayer.newDataRequest('maps', envelope=envelope)
    request.addIdentifier('table', 'mapdata.city')
    request.addIdentifier('geomField', 'the_geom')
    request.setParameters('name','population','prog_disc')
    cities = DataAccessLayer.getGeometryData(request)
    print("Queried " + str(len(cities)) + " total cities")
    
    # Set aside two arrays - one for the geometry of the cities and one for their names
    citylist = []
    cityname = []
    # For BOU, progressive disclosure values above 50 and pop above 5000 looks good
    for ob in cities:
        if ob.getString("population") != 'None':
            if ob.getNumber("prog_disc") > 50 and int(ob.getString("population")) > 5000:
                citylist.append(ob.getGeometry())
                cityname.append(ob.getString("name"))
    print("Plotting " + str(len(cityname)) + " cities")
    
    # Plot city markers
    ax.scatter([point.x for point in citylist],
           [point.y for point in citylist],
           transform=ccrs.PlateCarree(),marker="+",facecolor='black')
    # Plot city names
    for i, txt in enumerate(cityname):
        ax.annotate(txt, (citylist[i].x,citylist[i].y),
                    xytext=(3,3), textcoords="offset points")
    
    fig


.. parsed-literal::

    Queried 1205 total cities
    Plotting 58 cities




.. image:: Map_Resources_and_Topography_files/Map_Resources_and_Topography_22_1.png



`Top <https://unidata.github.io/python-awips/examples/generated/Map_Resources_and_Topography.html>`__

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8 Draw Nearby Lakes
-------------------

Again, use the **envelope** attribute to define a new data requst for
the nearby lakes.

.. code:: ipython3

    # Define request for lakes
    request = DataAccessLayer.newDataRequest('maps', envelope=envelope)
    request.addIdentifier('table', 'mapdata.lake')
    request.addIdentifier('geomField', 'the_geom')
    
    # Get lake geometries
    response = DataAccessLayer.getGeometryData(request)
    print("Using " + str(len(response)) + " lake MultiPolygons")
    
    # Plot lakes
    shape_feature = ShapelyFeature([lake.getGeometry() for lake in response],ccrs.PlateCarree(), 
                        facecolor='blue', linestyle="-",edgecolor='#20B2AA')
    ax.add_feature(shape_feature)
    fig



.. parsed-literal::

    Using 208 lake MultiPolygons




.. image:: Map_Resources_and_Topography_files/Map_Resources_and_Topography_25_1.png



`Top <https://unidata.github.io/python-awips/examples/generated/Map_Resources_and_Topography.html>`__

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9 Draw Major Rivers
-------------------

.. code:: ipython3

    # Define request for rivers
    request = DataAccessLayer.newDataRequest('maps', envelope=envelope)
    request.addIdentifier('table', 'mapdata.majorrivers')
    request.addIdentifier('geomField', 'the_geom')
    rivers = DataAccessLayer.getGeometryData(request)
    print("Using " + str(len(rivers)) + " river MultiLineStrings")
    
    # Plot rivers
    shape_feature = ShapelyFeature([river.getGeometry() for river in rivers],ccrs.PlateCarree(), 
                        facecolor='none', linestyle=":",edgecolor='#20B2AA')
    ax.add_feature(shape_feature)
    fig


.. parsed-literal::

    Using 1400 river MultiLineStrings




.. image:: Map_Resources_and_Topography_files/Map_Resources_and_Topography_28_1.png



`Top <https://unidata.github.io/python-awips/examples/generated/Map_Resources_and_Topography.html>`__

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10 Draw Topography
------------------

Spatial envelopes are required for topo requests, which can become slow
to download and render for large (CONUS) maps.

.. code:: ipython3

    # Define topography request
    request = DataAccessLayer.newDataRequest("topo", envelope=envelope)
    request.addIdentifier("group", "/")
    request.addIdentifier("dataset", "full")
    gridData = DataAccessLayer.getGridData(request)
    print(gridData)
    print("Number of grid records: " + str(len(gridData)))
    print("Sample grid data shape:\n" + str(gridData[0].getRawData().shape) + "\n")
    print("Sample grid data:\n" + str(gridData[0].getRawData()) + "\n")


.. parsed-literal::

    [<awips.dataaccess.PyGridData.PyGridData object at 0x115a20370>]
    Number of grid records: 1
    Sample grid data shape:
    (778, 1058)
    
    Sample grid data:
    [[1694. 1693. 1688. ...  757.  761.  762.]
     [1701. 1701. 1701. ...  758.  760.  762.]
     [1703. 1703. 1703. ...  760.  761.  762.]
     ...
     [1767. 1741. 1706. ...  769.  762.  768.]
     [1767. 1746. 1716. ...  775.  765.  761.]
     [1781. 1753. 1730. ...  766.  762.  759.]]
    


.. code:: ipython3

    grid=gridData[0]
    topo=ma.masked_invalid(grid.getRawData()) 
    lons, lats = grid.getLatLonCoords()
    print(topo.min()) # minimum elevation in our domain (meters)
    print(topo.max()) # maximum elevation in our domain (meters)
    
    # Plot topography
    cs = ax.contourf(lons, lats, topo, 80, cmap=plt.get_cmap('terrain'),alpha=0.1, extend='both')
    cbar = fig.colorbar(cs, shrink=0.5, orientation='horizontal')
    cbar.set_label("topography height in meters")
    
    fig


.. parsed-literal::

    623.0
    4328.0




.. image:: Map_Resources_and_Topography_files/Map_Resources_and_Topography_32_1.png



`Top <https://unidata.github.io/python-awips/examples/generated/Map_Resources_and_Topography.html>`__

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11 See Also
-----------

11.1 Additional Documentation
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

-  This notebook requires: **python-awips, numpy, matplotplib, cartopy,
   shapely**
-  Use datatype **maps** and **addIdentifier(‘table’, <postgres maps
   schema>)** to define the map table:
   DataAccessLayer.changeEDEXHost(“edex-cloud.unidata.ucar.edu”) request
   = DataAccessLayer.newDataRequest(‘maps’)
   request.addIdentifier(‘table’, ‘mapdata.county’)
-  Use **request.setLocationNames()** and **request.addIdentifier()** to
   spatially filter a map resource. In the example below, WFO ID **BOU**
   (Boulder, Colorado) is used to query counties within the BOU county
   watch area (CWA)

   ::

        request.addIdentifier('geomField', 'the_geom')
        request.addIdentifier('inLocation', 'true')
        request.addIdentifier('locationField', 'cwa')
        request.setLocationNames('BOU')
        request.addIdentifier('cwa', 'BOU')

See the `Maps Database Reference
Page <http://unidata.github.io/awips2/python/maps-database/#mapdatacw>`__
for available database tables, column names, and types.

`Top <https://unidata.github.io/python-awips/examples/generated/Map_Resources_and_Topography.html>`__

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