def add_grid_bounds(self,lon_p=None,lat_p=None):
"""Generate grid cell boundaries
either by sub-sampling lon and lat or from input arguments
Parameters
----------
lon_p,lat_p : 2D arrays, optional
lon,lat axes of grid cell boundaries
Attributes added
----------------
lon_p,lat_p : lon,lat axes of p vertices (u boundaries)
"""
if lon_p is None or lat_p is None:
lo,la = geo.waypoints_segments(self.lon,self.lat,n=2)
self.lon_p = lo[1:len(lo):2]
self.lat_p = la[1:len(la):2]
else:
self.lon_p = lon_p[self.j,self.ii]
self.lat_p = lat_p[self.j,self.ii]
def __init__(self, longrid, latgrid,
lat0, lonw=None, lone=None,
add_bounds=False):
self.lat0 = lat0
# take care of NaN masks
latgrid = np.ma.masked_invalid(latgrid)
longrid = np.ma.masked_invalid(longrid)
longrid = np.mod(longrid[:], 360)
# mask the latgrid for mean taking
if lonw is None or lone is None:
latgrid_masked = latgrid
else:
self.lone = np.mod(lone, 360) or 360
self.lonw = np.mod(lonw, 360) or 360
# limit the selectable region zonally
if self.lonw <= self.lone:
latgrid_masked = np.ma.masked_where(
((longrid >= self.lonw) & (longrid <= self.lone)),latgrid[:])
else:
latgrid_masked = np.ma.masked_where(
((longrid >= self.lonw) | (longrid <= self.lone)),latgrid[:])
# find position of best fitting zonal section
latmean = np.mean(latgrid_masked, axis=1)
self.j = j = np.argmin(np.abs(latmean-lat0))
# find the zonal boundaries of the section
lonband = longrid[j,:]
if lonw is None or lone is None:
regmask = ~np.ma.getmaskarray(latgrid_masked[j,:])
if regmask.all(): # nothing masked
iw,ie = 0,len(lonband)-1
elif regmask[[0,-1]].all(): # region wraps around
# find largest connected region of False
cr = np.cumsum(regmask)
regmask_largest = cr == np.argmax(np.bincount(cr))
ie,iw = np.where(regmask_largest)[0][[0,-1]] ; ie+=1
else:
iw,ie = np.where(regmask)[0][[0,-1]]
else:
iw = np.argmin(np.abs(lonband-self.lonw))
ie = np.argmin(np.abs(lonband-self.lone))
if iw > ie:
ii = np.concatenate([np.arange(iw,len(lonband)),np.arange(0,ie+1)])
else:
ii = np.arange(iw,ie+1)
self.ii = ii
if add_bounds:
iipad = np.concatenate(([ii[0]-1], ii, [ii[-1]+1]))
iipad = np.mod(iipad, len(lonband))
else:
iipad = ii
# make sure longitude axis is monotonically increasing
lontmp = geo.make_lon_continuous(np.ma.getdata(longrid[j,iipad]))
lattmp = np.ma.getdata(latgrid[j,iipad])
if add_bounds:
self.lon_p, self.lat_p = geo.waypoints_segments(lontmp, lattmp, f=0.5)
self.lon_p = geo.make_lon_continuous(self.lon_p)
self.lon = lontmp[1:-1]
self.lat = lattmp[1:-1]
else:
self.lon = lontmp
self.lat = lattmp
self.ii = ii
self.jj = np.ones(len(ii), 'i4') * j
# latitude axis
self.meanlat = np.mean(self.lat)
# add descriptions
self.desc = 'zonal transect around {:.2f} N'.format(self.meanlat)
self.lat0str = '{:.0f}S'.format(-lat0) if lat0 < 0 else '{:.0f}N'.format(lat0)
self.meanlatstr = '{:.2f}S'.format(-self.meanlat) if lat0 < 0 else '{:.2f}N'.format(self.meanlat)
