#********************************************** # calc fractional cumulative precipitation #---------------------------------------------- lfcp = [] for xth in lxth: sp = da3sp_reg[xth, -1].sum() sp_c = da3sp_reg[xth, 0].sum() if sp == 0.0: fcp = miss_dbl else: fcp = sp_c / sp #-------- lfcp.append(fcp) #---- ax = ma.masked_where(array(lfcp) == miss_dbl, array(lxth)) afcp = array( func.del_miss(lfcp, miss_dbl)) #********************************************** # output name #---------------------------------------------- xth_fcp_name = pictdir + "/r%04d.xth-fcp.cmulti.%s.%02d.png"%(crad, reg, nclass) #********************************************** # plot #---------------------------------------------- plt.clf() plt.plot(ax, afcp, lw = wline) # plt.ylim(0.0, 1.0) plt.savefig(xth_fcp_name) print xth_fcp_name
#********************************************** # calc mean precipitation intensity #---------------------------------------------- lmp = [] for crad in lcrad: p = da3sp_reg[crad, 0].sum() * 60.0*60.0*24.0 n = da3num_reg[crad, 0].sum() if ( n == 0): mp = miss_dbl else: mp = p / n #-------- lmp.append(mp) #---- ax = ma.masked_where(array(mp) == miss_dbl, array(lcrad)) amp = array( func.del_miss(lmp, miss_dbl)) #********************************************** # output name #---------------------------------------------- crad_mp_name = pictdir + "/crad-mp.cmulti.p%05.2f.%s.%02d.png"%(xth, reg, nclass) #********************************************** # plot #---------------------------------------------- plt.clf() plt.plot(ax, amp, lw = wline) # plt.ylim(0.0, amp.max()*1.2) plt.savefig(crad_mp_name) print crad_mp_name
plt.title(sspec0) plt.savefig(c_rn_name) print c_rn_name #----------------- # w-p #----------------- for iclass in [0]: plt.clf() w_p_name = pictdir + "/p%05.2f.r%04d.w.p.c%02d.%02d.%s.png"%(xth, crad, iclass,nclass, reg) # ly = array(ap[iclass][1:]) lx = ma.masked_where(ly==miss_dbl, lwbin[1:]).filled(miss_dbl) lye = ma.masked_where(ly==miss_dbl, asig_p[iclass][1:]).filled(miss_dbl) # lx = func.del_miss(lx, miss_dbl) ly = func.del_miss(ly, miss_dbl) lye = func.del_miss(lye, miss_dbl) # ly = array(ly) * 60.*60.*24. lye = array(lye)* 60.*60.*24. # plt.plot(lx, ly, c=col0, lw = wline) ## plt.errorbar(lx, ly, yerr = lye) ## plt.ylim(0, 120.0) # plt.suptitle("W.vs.P") plt.title(sspec0) plt.savefig(w_p_name)