rhoz = p/(c.Rd*np.mean(np.mean(T, axis=3), axis=2))
print 'calculating daily averages'
CRH_tave = np.mean(CRH, axis=0)
T_tave = np.mean(T, axis=0)
w_tave = np.mean(w, axis=0)
rhoz_tave = np.mean(rhoz, axis=0)
#number of grid points in a block
db=16
PW_tave = np.mean(PW, axis=0)
PWxy_sorted = blockxysort2D(PW_tave, xx, yy, db)
PWsort = PWxy_sorted.keys()
PWxycoords = PWxy_sorted.values()
mcenter = PWxycoords[-1]
binwidth=5e3
bins = np.arange(0, domsize*1e3, binwidth)
#wrsort = np.zeros(z.size, bins.size)
psi = np.zeros((z.size, bins.size-1))
chi = np.zeros((z.size, bins.size-1))
#calculate the stream function in cylindrical coords
for i, zlev in enumerate(z):
#time period to look at #t=-25*ntave3D #nave=5 #nave2D=5*ntave2D #nave3D=5*ntave3D #number of blocks to find PW max db = 1 print 'calulating max PW, blocked' #PW_t = np.mean(PW_tave[t-nave:t,:,:], axis=0) #PW_t = np.mean(PW[t-nave2D:t,:,:], axis=0) #calculate where the convective center is by using blocked max(PW) PW_tave = np.mean(PW, axis=0) PW_blocked = blockave2D(PW_tave, db) PWxy_sorted = blockxysort2D(PW_tave, xx, yy, db) PWsort = PWxy_sorted.keys() PWxycoords = PWxy_sorted.values() mcenter = PWxycoords[-1] binwidth = 5e3 rbins = np.arange(0, 1 / np.sqrt(2) * domsize * 1e3, binwidth) #calculate where the convective 'edge' is by using standard deviation definition #(other definitions may be better) PWrbins, PWmeans = radprof(PW_tave, xx, yy, mcenter, rbins) PWrbin_centers = (PWrbins[1:] + PWrbins[:-1]) / 2. a = 1.5