def stat_spatial(ifile0,
ifile1,
funcs=__all__,
variables=['O3'],
counties=False):
"""
ifile0 - left hand side of equation
ifile1 - right hand side of equation
variables - list of variables to plot
"""
from mpl_toolkits.basemap import Basemap
from matplotlib.pyplot import figure, show
lonlatcoords = getattr(ifile0, 'lonlatcoords',
getattr(ifile1, 'lonlatcoords', ''))
lon, lat = np.array(
map(lambda x: map(float, x.split(',')), lonlatcoords.split('/'))).T
latmin, latmax = lat.min(), lat.max()
lonmin, lonmax = lon.min(), lon.max()
bmap = Basemap(llcrnrlat=latmin,
llcrnrlon=lonmin,
urcrnrlat=latmax,
urcrnrlon=lonmax,
resolution='i')
for vark in variables:
for statname in funcs:
statfunc = eval(statname)
fig = figure()
ax = fig.add_subplot(111)
ax.set_title(vark + ' ' + statname)
var_0 = ifile0.variables[vark]
var_1 = ifile1.variables[vark]
try:
pidx = list(var_0.dimensions).index('points')
except Exception:
pidx = list(var_1.dimensions).index('points')
statvs = []
for sitei in range(var_0.shape[pidx]):
val_0 = var_0[:].take([sitei], axis=pidx).ravel()
val_1 = var_1[:].take([sitei], axis=pidx).ravel()
statvs.append(statfunc(val_0, val_1))
dots = bmap.scatter(x=lon, y=lat, c=statvs, ax=ax, cmap='jet')
bmap.drawcoastlines(ax=ax)
bmap.drawcountries(ax=ax)
bmap.drawstates(ax=ax)
fig.colorbar(dots)
if counties:
bmap.counties(ax=ax)
show()
def stat_spatial(ifile0, ifile1, funcs = __all__, variables = ['O3'], counties = False):
"""
ifile0 - left hand side of equation
ifile1 - right hand side of equation
variables - list of variables to plot
"""
from mpl_toolkits.basemap import Basemap
from matplotlib.pyplot import figure, show
lonlatcoords = getattr(ifile0, 'lonlatcoords', getattr(ifile1, 'lonlatcoords', ''))
lon, lat = np.array(map(lambda x: map(float, x.split(',')), lonlatcoords.split('/'))).T
latmin, latmax = lat.min(), lat.max()
lonmin, lonmax = lon.min(), lon.max()
bmap = Basemap(llcrnrlat = latmin, llcrnrlon = lonmin, urcrnrlat = latmax, urcrnrlon = lonmax, resolution = 'i')
for vark in variables:
for statname in funcs:
statfunc = eval(statname)
fig = figure()
ax = fig.add_subplot(111)
ax.set_title(vark + ' ' + statname)
var_0 = ifile0.variables[vark]
var_1 = ifile1.variables[vark]
try:
pidx = list(var_0.dimensions).index('points')
except:
pidx = list(var_1.dimensions).index('points')
statvs = []
for sitei in range(var_0.shape[pidx]):
val_0 = var_0[:].take([sitei], axis = pidx).ravel()
val_1 = var_1[:].take([sitei], axis = pidx).ravel()
statvs.append(statfunc(val_0, val_1))
dots = bmap.scatter(x = lon, y = lat, c = statvs, ax = ax, cmap = 'jet')
bmap.drawcoastlines(ax = ax)
bmap.drawcountries(ax = ax)
bmap.drawstates(ax = ax)
fig.colorbar(dots)
if counties: bmap.counties(ax = ax)
show()
