Merge pull request #160 from jswhit/cartopy

migrate test/*py from basemap to cartopy

.github/workflows/build.yml

@@ -23,14 +23,24 @@ jobs:
       run: |
         sudo apt-get update
         sudo apt-get install libproj-dev proj-bin libeccodes-dev
+#       sudo apt-get install libgeos-dev
 
     - name: Update Pip
       run: |
         python -m pip install --upgrade pip
 
     - name: Install pygrib dependencies via pip
       run: |
-        python -m pip install cython numpy "pyproj<3.0.0"
+        python -m pip install "numpy>1.10"
+        python -m pip install cython
+        python -m pip install "pyproj<3.0.0"
+#       python -m pip install wheel
+#       python -m pip install pyshp
+#       python -m pip install six
+#       python -m pip install shapely --no-binary shapely
+#       python -m pip install matplotlib
+#       python -m pip install cartopy
+#       python -m pip install scipy
 
     - name: Install pygrib
       run: |
@@ -39,3 +49,4 @@ jobs:
     - name: Test
       run: |
         python test.py
+#       cd test; python run_tests.py

Changelog

@@ -1,3 +1,9 @@
+version 2.1.1 (git tag v2.1.1rel)
+=================================
+* clean up docs.
+* migrate examples in 'test' directory from basemap to cartopy.
+* enable github actions for CI (PR #159).
+
 version 2.1 (git tag v2.1rel)
 ============================
 * split ncepgrib2 module into a separate project

README.md

@@ -16,8 +16,8 @@ The easiest way to get everything installed is to use the [conda](https://conda.
 conda install -c conda-forge pygrib
 ```
 
-If you don't use conda, be sure you have the required dependencies
-(eccodes,numpy,cython,pyproj) installed first. Then, install pygrib with pip:
+If you don't use conda, be sure you have the ECCODES library installed first.
+Then you can install pygrib with pip:
 
 ```
 ECCODES_DIR=path/to/eccodes pip install pygrib

pygrib.pyx

@@ -1,4 +1,4 @@
-__version__ = '2.1'
+__version__ = '2.1.1'
 
 import numpy as np
 import warnings

test/README

@@ -1,6 +1,8 @@
 these examples read GRIB files and generate
-plots of the data using matplotlib and the basemap toolkit
-(both availabe from http://matplotlib.sf.net).
+plots of the data using matplotlib and cartopy
 
 test_spectral.py also uses pyspharm, available from 
-http://code.google.com/p/pyspharm.
+http://github.com/jswhit/pyspharm
+
+to run all the tests with a non-gui backend (Agg) and compare
+images to archived baselines, run 'python run_tests.py'.

test/animate.py

@@ -1,39 +1,44 @@
 import pygrib, time
 import matplotlib.pyplot as plt
 import numpy as np
-from mpl_toolkits.basemap import Basemap
+from cartopy.util import add_cyclic_point
+import cartopy.crs as ccrs
+import cartopy.feature as cfeature
 import matplotlib.animation as animation
 
 # animation example.
 
 grbs = pygrib.open('../sampledata/safrica.grib2')
 # grab all "brightness temp" grib messages.
-btemps = [grb for grb in grbs if grb['name']=='Brightness temperature']
+btemps = [grb for grb in grbs if grb.name=='Brightness temperature']
 grb = btemps[0]
 lats, lons = grb.latlons()
 projd = grb.projparams
+print(projd)
 grbs.close()
 
 # create a map projection for the domain, plot 1st image on it.
-m =\
-Basemap(projection=projd['proj'],lat_ts=projd['lat_ts'],lon_0=projd['lon_0'],\
-        lat_0=projd['lat_0'],rsphere=(projd['a'],projd['b']),\
-        llcrnrlat=lats[0,0],urcrnrlat=lats[-1,-1],\
-        llcrnrlon=lons[0,0],urcrnrlon=lons[-1,-1],resolution='i')
 fig = plt.figure(figsize=(8,7))
-m.drawcoastlines()
-m.drawcountries()
+globe = ccrs.Globe(ellipse='sphere', semimajor_axis=projd['a'], semiminor_axis=projd['b'])
+pj = ccrs.Stereographic(globe=globe,central_longitude=projd['lon_0'],
+     central_latitude=projd['lat_0'],
+     true_scale_latitude=projd['lat_ts']) 
+ax = fig.add_subplot(1,1,1,projection=pj)
+coords = pj.transform_points(                                                                
+    ccrs.PlateCarree(), np.asarray([lons[0,0],lons[-1,-1]]), np.asarray([lats[0,0],lats[-1,-1]]))
+ax.set_extent([coords[0, 0], coords[1, 0], coords[0, 1], coords[1, 1]], crs=pj)
+ax.coastlines()
+ax.add_feature(cfeature.BORDERS, linestyle='-');
 grb = btemps[0]
-im = m.imshow(grb['values'],interpolation='nearest',vmin=230,vmax=310)
-plt.colorbar(orientation='horizontal')
-m.drawparallels(np.arange(-80,10,10),labels=[1,0,0,0])
-m.drawmeridians(np.arange(-80,81,20),labels=[0,0,0,1])
+im = plt.imshow(np.empty(lons.shape),vmin=230,vmax=310,transform=ccrs.PlateCarree(),origin='lower')
+im.set_data(grb.values)
+plt.colorbar(im,orientation='horizontal')
 txt = plt.title(grb,fontsize=8)
 
 def updatefig(nt):
     global im,txt,btemps,cnt,delay
     grb = btemps[nt]
-    im.set_data(grb['values'])
+    im.set_data(grb.values)
     txt.set_text(repr(grb))
 
 ani = animation.FuncAnimation(fig, updatefig, frames=len(btemps))

test/run_tests.py

@@ -0,0 +1,11 @@
+# run all matplotlib based tests
+import glob
+import matplotlib
+matplotlib.rcParams.update(matplotlib.rcParamsDefault)
+matplotlib.use('agg')
+# Find all test files.
+test_files = glob.glob('test_*.py')
+#test_files.remove('test_spectral.py') # skip spectral transform test
+for f in test_files:
+    print('running %s...' % f)
+    exec(open(f).read())

test/test_ectigge.py

@@ -1,25 +1,30 @@
 import pygrib
+import matplotlib
 import matplotlib.pyplot as plt
 import numpy as np
-from numpy import ma
-from mpl_toolkits.basemap import Basemap
-
+from cartopy.util import add_cyclic_point
+import cartopy.crs as ccrs
+from matplotlib.testing.compare import compare_images
 
 grbs = pygrib.open('../sampledata/ecmwf_tigge.grb')
 grb = grbs.select(parameterName='Soil moisture')[0]
 fld = grb.values; lats,lons = grb.latlons()
+lons1 = lons[0,:]; lats1 = lats[:,0]
+# add cyclic (wrap-around) point to global grid
+fld,lons1 = add_cyclic_point(fld, coord=lons1)
+lons,lats = np.meshgrid(lons1,lats1)
 
-m = Basemap(lon_0=180)
-CS = m.contourf(lons,lats,fld,15,cmap=plt.cm.jet)
-plt.colorbar(shrink=0.6)
-m.drawcoastlines()
-# draw parallels
-delat = 30.
-circles = np.arange(-90.,90.+delat,delat)
-m.drawparallels(circles,labels=[1,0,0,0])
-# draw meridians
-delon = 60.
-meridians = np.arange(0,360,delon)
-m.drawmeridians(meridians,labels=[0,0,0,1])
-plt.title(grb['parameterName']+' on ECMWF Reduced Gaussian Grid')
+plt.figure()
+ax = plt.axes(projection=ccrs.PlateCarree(central_longitude=0))
+cs = ax.contourf(lons,lats,fld,15,cmap=plt.cm.jet)
+plt.colorbar(cs, shrink=0.6)
+ax.coastlines()
+gl = ax.gridlines(draw_labels=True)
+gl.ylabels_top = False; gl.xlabels_top = False
+gl.ylabels_right = False; gl.xlabels_right = False
+plt.title(grb.parameterName+' on ECMWF Reduced Gaussian Grid')
+if matplotlib.get_backend().lower() == 'agg':
+    # raise exception if generated image doesn't match baseline 
+    plt.savefig('ectigge.png')
+    assert( compare_images('ectigge_baseline.png','ectigge.png',10) is None )
 plt.show()

test/test_gaussian.py

@@ -1,15 +1,27 @@
 import pygrib
+import numpy as np
+import matplotlib
 import matplotlib.pyplot as plt
-from mpl_toolkits.basemap import Basemap
+from cartopy.util import add_cyclic_point
+from matplotlib.testing.compare import compare_images
+import cartopy.crs as ccrs
 grbs = pygrib.open('../sampledata/flux.grb')
 grb = grbs.message(2)
 lats, lons = grb.latlons()
-data = grb['values']
-m = Basemap(lon_0=180)
-#m.scatter(lons.flat,lats.flat,1,marker='o',color='k',zorder=10)
-x,y = m(lons,lats)
-m.drawcoastlines()
-m.contourf(x,y,data,15)
-#m.fillcontinents()
+lons1 = lons[0,:]; lats1 = lats[:,0]
+data = grb.values
+# add cyclic (wrap-around) point to global grid
+data,lons1 = add_cyclic_point(data, coord=lons1)
+lons,lats = np.meshgrid(lons1,lats1)
+plt.figure()
+ax = plt.axes(projection=ccrs.PlateCarree(central_longitude=0))
+ax.coastlines()
+ax.contourf(lons,lats,data,15)
+# plot location of every 4th grid point
+plt.scatter(lons[::4,::4].ravel(),lats[::4,::4].ravel(),1,marker='o',color='k',zorder=10)
 plt.title('Global Gaussian Grid')
+if matplotlib.get_backend().lower() == 'agg':
+    # raise exception if generated image doesn't match baseline 
+    plt.savefig('gaussian.png')
+    assert( compare_images('gaussian_baseline.png','gaussian.png',10) is None )
 plt.show()

test/test_lambert.py

@@ -1,26 +1,30 @@
 import pygrib
+import numpy as np
+import matplotlib
 import matplotlib.pyplot as plt
-from mpl_toolkits.basemap import Basemap
+import cartopy.crs as ccrs
+from matplotlib.testing.compare import compare_images
+
 grbs = pygrib.open('../sampledata/eta.grb')
 grb = grbs.select(parameterName='Pressure',typeOfLevel='surface')[0]
 data = grb.values
 lats, lons = grb.latlons()
-llcrnrlon = lons[0,0]
-llcrnrlat = lats[0,0]
-urcrnrlon = lons[-1,-1]
-urcrnrlat = lats[-1,-1]
-rsphere = (grb.projparams['a'], grb.projparams['b'])
-lon_0 = grb.projparams['lon_0']
-lat_1 = grb.projparams['lat_1']
-lat_2 = grb.projparams['lat_2']
-projection = grb.projparams['proj']
-m = Basemap(llcrnrlon=llcrnrlon,llcrnrlat=llcrnrlat,
-            urcrnrlon=urcrnrlon,urcrnrlat=urcrnrlat,rsphere=rsphere,lon_0=lon_0,
-            lat_1=lat_1,lat_2=lat_2,resolution='l',projection=projection)
-x,y = m(lons, lats)
-m.scatter(x.flat,y.flat,3,marker='o',color='k',zorder=10)
-m.drawcoastlines()
-x,y = m(lons,lats)
-m.contourf(x,y,data,15)
+
+globe = ccrs.Globe(ellipse='sphere', semimajor_axis=grb.projparams['a'], semiminor_axis=grb.projparams['b'])
+pj = ccrs.LambertConformal(globe=globe,central_longitude=grb.projparams['lon_0'],
+     central_latitude=grb.projparams['lat_0'],
+     standard_parallels =(grb.projparams['lat_1'],grb.projparams['lat_2']))
+ax = plt.axes(projection=pj)
+coords = pj.transform_points(                                                                
+         ccrs.PlateCarree(), np.asarray([lons[0,0],lons[-1,-1]]), np.asarray([lats[0,0],lats[-1,-1]]))
+ax.set_extent([coords[0, 0], coords[1, 0], coords[0, 1], coords[1, 1]], crs=pj)
+ax.scatter(lons.flat,lats.flat,3,marker='o',color='k',zorder=10,transform=ccrs.PlateCarree())
+ax.coastlines()
+coords = pj.transform_points(ccrs.PlateCarree(), lons, lats)
+cs = ax.contourf(coords[:,:,0],coords[:,:,1],data,15)
 plt.title('Lambert Conformal Model Grid')
+if matplotlib.get_backend().lower() == 'agg':
+    # raise exception if generated image doesn't match baseline 
+    plt.savefig('lambert.png')
+    assert( compare_images('lambert_baseline.png','lambert.png',10) is None )
 plt.show()