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)