def plotDifference(GlobModel,sciamachy):
""" Takes two arguments, the name of NetCDF file containing the GlobModel
simulated ozone data, and the name of the csv file containing SCIAMACHY ozone
data. Extracts data from the two datasets, subtracts the GlobModel data
from the SCIAMACHY data for each point. Produces a scatter plot of the difference"""
#Libraries to extract data & coordinates and plot Scatter Plot
import globmodel
import matplotlib.pyplot as plt
import matplotlib.mlab as mlab
import matplotlib as mpl
#Extract Latitudes, longitudes and ozone satellite Data
r=mlab.csv2rec(sciamachy)
latvals=r.lat
lonvals=r.lon
satelliteData=r.o3_du
#Extract ozone simulated data from GlobModel using lat & lon from sciamachy
GlobModelData=globmodel.readGlobModel(GlobModel,lonvals,latvals)
#Substract GlobModel ozone simulated data from Sciamachy sattellite ozone data
diff=satelliteData-GlobModelData
#Clear previous figures
plt.clf()
#Generating the scatter plot, axis labels and the colorbar
plt.title("Sciamachy-GlobModel Difference Scatter Plot")
plt.xlabel("Longitude (degrees east)")
plt.ylabel("Latitude (degrees north)")
plt.scatter(lonvals, latvals, c=diff,edgecolors='none', norm=mpl.colors.SymLogNorm(linthresh=10, vmin=min(diff), vmax=max(diff)))
plt.colorbar()
plt.show()
return
def plotDifferenceBasemap(GlobModel,sciamachy,mapProjection):
""" Takes three arguments, the name of NetCDF file containing the GlobModel
simulated ozone data, the name of the csv file containing SCIAMACHY ozone
data and a string representing the Map projection to use. Uses the
readGlobModel() function from the globmodel module to extract data from
the GlobModel NetCDFdata, subtracts it from the SCIAMACHY data at
each point.Produces a scatter plot of the difference on the selected map projection """
#Libraries to extract data & coordinates and plot on map projection
import matplotlib.pyplot as plt
import matplotlib.mlab as mlab
import matplotlib as mpl
import globmodel
import numpy as np
from mpl_toolkits.basemap import Basemap
#Extract Latitudes, longitudes and ozone Data from the sciamachy
r=mlab.csv2rec(sciamachy)
latvals=r.lat #array of latitude values
lonvals=r.lon #array of longitude values
satelliteData=r.o3_du #array of sciamachy ozone data values
#Extract ozone simulated data from GlobModel using lat & lon from sciamachy
GlobModelData=globmodel.readGlobModel(GlobModel,lonvals,latvals)
#Substract GlobModel ozone simulated data from Sciamachy sattellite ozone data
diff=satelliteData-GlobModelData
#Plotting using different map projections
#North-Polar-Stereographic (npstere),South-Polar-Stereographic (spstere) &
#Equidistant- Cylindrical Projections (cyl)
#North-Polar-Stereographic (npstere)
if mapProjection=='npstere':
#Clear previous figures
plt.clf()
# Setup north polar stereographic basemap. The longitude lon_0 is at
#6-o'clock, and the latitude circle boundinglat is tangent to the edge
#of the map at lon_0. Default value of lat_ts (latitude of true scale) is pole.
m = Basemap(projection='npstere',boundinglat=10,lon_0=270,resolution='l')
m.drawcoastlines()
m.fillcontinents(color='none',lake_color='none')
# Convert latitude & longitude to map projection coordinates
nlonvals,nlatvals= m(lonvals,latvals)
# Draw parallels and meridians.
m.drawparallels(np.arange(-80.,81.,20.),labels=[False,True,True,False])
m.drawmeridians(np.arange(-180.,181.,20.),labels=[True,False,False,True])
# Draw continental boundaries
m.drawmapboundary(fill_color='none')
#Generate scatter Plots and colorbar on the North Polar Stereographic Projection
m.scatter(nlonvals, nlatvals, c=diff,edgecolors='none', norm=mpl.colors.SymLogNorm(linthresh=10, vmin=min(diff), vmax=max(diff)))
plt.colorbar()
plt.title("Sciamachy-GlobModel Difference Scatter Plot""\n""North Polar Stereographic Projection")
plt.show()
#South-Polar-Stereographic (spstere)
if mapProjection=='spstere':
#Clear previous figures
plt.clf()
# setup north polar stereographic basemap. The longitude lon_0 is at
#6-o'clock, and the latitude circle boundinglat is tangent to the edge
# of the map at lon_0. Default value of lat_ts (latitude of true scale) is pole.
m = Basemap(projection='spstere',boundinglat=-10,lon_0=90,resolution='c')
m.drawcoastlines()
m.fillcontinents(color='none',lake_color='none')
# Convert latitude & longitude to map projection coordinates
nlonvals,nlatvals= m(lonvals,latvals)
# draw parallels and meridians.
m.drawparallels(np.arange(-80.,81.,20.),labels=[False,True,True,False])
m.drawmeridians(np.arange(-180.,181.,20.),labels=[True,False,False,True])
# Draw continental boundaries
m.drawmapboundary(fill_color='none')
#Generate scatter Plots and colorbar on the South Polar Stereographic Projection
m.scatter(nlonvals, nlatvals, c=diff,edgecolors='none', norm=mpl.colors.SymLogNorm(linthresh=10, vmin=min(diff), vmax=max(diff)))
m.colorbar()
plt.title("Sciamachy-GlobModel Difference Scatter Plot""\n""South Polar Stereographic Projection")
plt.show()
#Equidistant- Cylindrical Projections (cyl)
if mapProjection=='cyl':
#Clear previous figures
plt.clf()
# llcrnrlat,llcrnrlon,urcrnrlat,urcrnrlon
# are the lat/lon values of the lower left and upper right corners of the map.
# resolution = 'c' means use crude resolution coastlines.
m = Basemap(projection='cyl',llcrnrlat=latvals[min(latvals)],urcrnrlat=latvals[max(latvals)],llcrnrlon=-180,urcrnrlon=180,resolution='c')
m.drawcoastlines()
# Convert latitude & longitude to map projection coordinates
nlonvals,nlatvals= m(lonvals,latvals)
# draw parallels and meridians.
m.drawparallels(np.arange(-90.,91.,30.),labels=[False,True,True,False])
m.drawmeridians(np.arange(-180.,181.,60.),labels=[True,False,False,True])
# Draw continental boundaries and fill colors
m.fillcontinents(color='none',lake_color='none')
m.drawmapboundary(fill_color='none')
#Generate scatter Plots and colorbar on the Equidistant Cylindrical Projection
plt.scatter(nlonvals, nlatvals, c=diff, edgecolors='none', norm=mpl.colors.SymLogNorm(linthresh=10, vmin=min(diff), vmax=max(diff)))
plt.colorbar(orientation="horizontal")
plt.title("Sciamachy-GlobModel Difference Scatter Plot""\n""Equidistant Cylindrical Projection")
plt.xlabel('longitude')
plt.show()
return
