# para generar las matrices de GEFS de lat lon segui los siguientes pasos en ipython: #Martin Iglesias Github SudestadaARG import numpy as np from grads import GrADS ga = GrADS(Bin='grads', Echo=False, Port=True, Window=False) CTL = ga.open('gens_20151201_0000_012_01.ctl') ga('set lev 1000') t = ga.exp('TMPPRS') lats = t.grid.lat[:] # (181,) lons = t.grid.lon[:] # (361,) np.save('lon_gefs.npy', lons) np.save('lat_gefs.npy', lats) # Para generar las 2D con dimension (181,361): lat2d = np.empty((181, 361)) for i in range(0, 361): lat2d[:, i] = lats lon2d = np.empty((181, 361)) for i in range(0, 181): lon2d[i, :] = lons np.save('lon2d_gefs.npy', lon2d) np.save('lat2d_gefs.npy', lat2d)
#!/usr/bin/env python # # Simple script testing the ext()/expr() methods # from pylab import * from grads import GrADS # Start GrADS and open the data file # ---------------------------------- ga = GrADS(Bin='grads', Echo=False, Port=True, Window=False) ga.open('../data/model.ctl') # XY slices # --------- ts1 = ga.exp('ts') ts2 = ga.expr('ts') print "XY Skin temperature: " print ts1.data - ts2.data # XYT slices # ---------- ga('set t 2 3') ts1 = ga.exp('ts') ts2 = ga.expr('ts') print "XYT Skin temperature: " print ts1.data - ts2.data # XYZ slices # ---------- ga('set t 3')
# gridpoint. # from pylab import * from numpy import float32 from grads import GrADS, GaField # Start GrADS and open the data file # ---------------------------------- ga = GrADS(Bin='gradsnc',Echo=False,Port=True) ga.open('../data/slp_djf.nc') # Extract a timeseries # -------------------- ga('set t 1 41') x = ga.exp('djfslp/100') g = x.grid # Transpose spatial/temporal dimensions # ------------------------------------- (nt,ny,nx) = x.shape; x = transpose(x.reshape((nt,nx*ny))) # Compute percentiles using Matlab compatible prctile function # ------------------------------------------------------------ p = ( 0, 10, 20, 30, 40, 50, 60, 70, 80, 90 ) y = zeros((nx*ny,10),dtype=float32) for i in range(nx*ny): y[i,:] = prctile(x[i,:],p) y = transpose(y); y = y.reshape((10,ny,nx)) # save the pecentile dimension as time