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139 lines
4.8 KiB
ReStructuredText
139 lines
4.8 KiB
ReStructuredText
==========================
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Watch and Warning Polygons
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==========================
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`Notebook <http://nbviewer.ipython.org/github/Unidata/python-awips/blob/master/examples/notebooks/Watch_and_Warning_Polygons.ipynb>`_
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This example uses matplotlib, cartopy, shapely, and python-awips to plot
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watch and warning polygons requested from a real-time AWIPS EDEX server.
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First, set up our imports and define functions to be used later:
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.. code:: ipython3
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from awips.dataaccess import DataAccessLayer
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from awips.tables import vtec
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from datetime import datetime
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import numpy as np
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import matplotlib.pyplot as plt
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import cartopy.crs as ccrs
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import cartopy.feature as cfeature
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from cartopy.mpl.gridliner import LONGITUDE_FORMATTER, LATITUDE_FORMATTER
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from cartopy.feature import ShapelyFeature,NaturalEarthFeature
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from shapely.geometry import MultiPolygon,Polygon
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def warning_color(phensig):
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return vtec[phensig]['color']
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def make_map(bbox, projection=ccrs.PlateCarree()):
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fig, ax = plt.subplots(figsize=(20,12),
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subplot_kw=dict(projection=projection))
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ax.set_extent(bbox)
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gl = ax.gridlines(draw_labels=True)
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gl.top_labels = gl.right_labels = False
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gl.xformatter = LONGITUDE_FORMATTER
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gl.yformatter = LATITUDE_FORMATTER
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return fig, ax
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Next, we create a request for the “warning” data type:
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.. code:: ipython3
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DataAccessLayer.changeEDEXHost("edex-cloud.unidata.ucar.edu")
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request = DataAccessLayer.newDataRequest()
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request.setDatatype("warning")
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request.setParameters('phensig')
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times = DataAccessLayer.getAvailableTimes(request)
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# Get records for last 50 available times
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response = DataAccessLayer.getGeometryData(request, times[-50:-1])
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print("Using " + str(len(response)) + " records")
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# Each record will have a numpy array the length of the number of "parameters"
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# Default is 1 (request.setParameters('phensig'))
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parameters = {}
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for x in request.getParameters():
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parameters[x] = np.array([])
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print(parameters)
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.. parsed-literal::
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Using 109 records
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{'phensig': array([], dtype=float64)}
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Now loop through each record and plot it as either Polygon or
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MultiPolygon, with appropriate colors
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.. code:: ipython3
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%matplotlib inline
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bbox=[-127,-64,24,49]
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fig, ax = make_map(bbox=bbox)
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siteids=np.array([])
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periods=np.array([])
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reftimes=np.array([])
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for ob in response:
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poly = ob.getGeometry()
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site = ob.getLocationName()
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pd = ob.getDataTime().getValidPeriod()
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ref = ob.getDataTime().getRefTime()
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# do not plot if phensig is blank (SPS)
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if ob.getString('phensig'):
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phensigString = ob.getString('phensig')
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siteids = np.append(siteids,site)
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periods = np.append(periods,pd)
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reftimes = np.append(reftimes,ref)
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for parm in parameters:
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parameters[parm] = np.append(parameters[parm],ob.getString(parm))
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if poly.geom_type == 'MultiPolygon':
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geometries = np.array([])
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geometries = np.append(geometries,MultiPolygon(poly))
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geom_count = ", " + str(len(geometries)) +" geometries"
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else:
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geometries = np.array([])
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geometries = np.append(geometries,Polygon(poly))
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geom_count=""
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for geom in geometries:
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bounds = Polygon(geom)
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intersection = bounds.intersection
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geoms = (intersection(geom)
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for geom in geometries
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if bounds.intersects(geom))
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#print(vtec[phensigString]['hdln']
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# + " (" + phensigString + ") issued at " + str(ref)
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# + " ("+str(poly.geom_type) + geom_count + ")")
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color = warning_color(phensigString)
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shape_feature = ShapelyFeature(geoms,ccrs.PlateCarree(),
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facecolor=color, edgecolor=color)
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ax.add_feature(shape_feature)
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states_provinces = cfeature.NaturalEarthFeature(
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category='cultural',
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name='admin_1_states_provinces_lines',
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scale='50m',
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facecolor='none')
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political_boundaries = cfeature.NaturalEarthFeature(category='cultural',
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name='admin_0_boundary_lines_land',
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scale='50m', facecolor='none')
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ax.add_feature(cfeature.LAND)
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ax.add_feature(cfeature.COASTLINE)
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ax.add_feature(states_provinces, edgecolor='black')
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ax.add_feature(political_boundaries, edgecolor='black')
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plt.show()
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.. image:: Watch_and_Warning_Polygons_files/Watch_and_Warning_Polygons_5_0.png
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