def iv_ds(ds, full=False, return_ma=False, **kwargs): if full: a = iolib.ds_getma(ds) else: a, ds = iolib.ds_getma_sub(ds, return_ds=True) ax = iv(a, ds=ds, **kwargs) if return_ma: out = (ax, a) else: out = ax return out
#dem_clim = (760, 2270) #Baker #dem_clim = (550, 2650) #Ngozumpa #dem_clim = (4500, 7400) #GM #dem_clim = (1766, 3247) #SBB #dem_clim = (2934, 3983) hs_clim = (1, 255) for i, dem_fn in enumerate(dem_fn_list): ax = grid[i] print(dem_fn) dem_ds = iolib.fn_getds(dem_fn) dem = iolib.ds_getma_sub(dem_ds) dem_hs_fn = os.path.splitext(dem_fn)[0] + '_hs_az315.tif' if os.path.exists(dem_hs_fn): dem_hs = iolib.fn_getma_sub(dem_hs_fn) else: dem_hs = geolib.gdaldem_mem_ds(dem_ds, 'hillshade', returnma=True) dt = timelib.fn_getdatetime(dem_fn) if dt is not None: title = dt.strftime('%Y-%m-%d') t = ax.set_title(title, fontdict={'fontsize': 6}) t.set_position([0.5, 0.95]) hs_im = ax.imshow(dem_hs, vmin=hs_clim[0], vmax=hs_clim[1], cmap='gray') dem_im = ax.imshow(dem, vmin=dem_clim[0], vmax=dem_clim[1], cmap='cpt_rainbow',
def main(): parser = get_parser() args = parser.parse_args() fn_list = args.fn_list print print "Reviewing %i images" % len(fn_list) print good = [] bad = [] good_fn = "good_list.txt" if args.prefix is not None: good_fn = args.prefix + '_' + good_fn good_f = open(good_fn, 'a', 0) bad_fn = "bad_list.txt" if args.prefix is not None: bad_fn = args.prefix + '_' + bad_fn bad_f = open(bad_fn, 'a', 0) fig = plt.figure() ax = fig.add_subplot(111) plt.ion() plt.show() #Use PIL Image basic = False for fn in fn_list: print fn plt.clf() if basic: im = mpimg.imread(fn) if im.ndim == 3: cmap = None plt.imshow(im, cmap=cmap) else: ds = gdal.Open(fn) a = iolib.ds_getma_sub(ds) perc = malib.calcperc(a) cmap = 'cpt_rainbow' alpha = 1.0 if '_hs' in fn: cmap = 'gray' else: hs_fn = os.path.splitext(fn)[0] + '_hs.tif' if os.path.exists(hs_fn): hs_ds = gdal.Open(hs_fn) hs = iolib.ds_getma_sub(hs_ds) hs_perc = malib.calcperc(hs) plt.imshow(hs, cmap='gray', clim=hs_perc) alpha = 0.5 plt.imshow(a, cmap=cmap, clim=perc, alpha=alpha) fig.canvas.draw() if query_yes_no("{} good?".format(fn)): good.append(fn) good_f.write("%s\n" % fn) else: bad.append(fn) bad_f.write("%s\n" % fn) plt.close() print print "Good: %i" % (len(good)) print good print print "Bad: %i" % (len(bad)) print bad print good_f.close() bad_f.close()
def get_bma(src_ds, bn, full): if full: return iolib.ds_getma(src_ds, bn) else: return iolib.ds_getma_sub(src_ds, bn)