def run():
mtime = {}
needup = []
region_tiles = glob.glob("region.*x*.png")
# first pass get all tile st_mtime
for fregion in region_tiles:
XxY = fregion.split('.')[1]
sregion = os.stat(fregion)
mtime[XxY] = sregion.st_mtime
fprecis = "display.%s.precis.png" % XxY
if os.path.isfile(fprecis):
sprecis = os.stat(fprecis)
if sregion.st_mtime <= sprecis.st_mtime:
continue
needup.append(XxY)
mtime_min = min(mtime.values())
mtime_max = max(mtime.values())
mtime_fac = 1. / (mtime_max - mtime_min)
mtime_col = lambda mt: (mt - mtime_min) * mtime_fac
for XxY in needup:
img = load("region.%s.png" % XxY)
alpha = img[:, :, 1]
save("display.%s.precis.png" % XxY,
(viridis(alpha) * 255).astype('uint8'))
alpha.fill(mtime_col(mtime[XxY]) * 255)
save("display.%s.mtime.png" % XxY,
(viridis(alpha) * 255).astype('uint8'))
def run():
mtime = {}
needup = []
region_tiles = glob.glob("region.*x*.png")
# first pass get all tile st_mtime
for fregion in region_tiles:
XxY = fregion.split('.')[1]
sregion = os.stat(fregion)
mtime[XxY] = sregion.st_mtime
fprecis = "display.%s.precis.png"%XxY
if os.path.isfile(fprecis):
sprecis = os.stat(fprecis)
if sregion.st_mtime <= sprecis.st_mtime:
continue
needup.append(XxY)
mtime_min = min(mtime.values())
mtime_max = max(mtime.values())
mtime_fac = 1./(mtime_max - mtime_min)
mtime_col = lambda mt: (mt - mtime_min) * mtime_fac
for XxY in needup:
img = load("region.%s.png"%XxY)
alpha = img[:,:,1]
save("display.%s.precis.png"%XxY, (viridis(alpha)*255).astype('uint8'))
alpha.fill(mtime_col(mtime[XxY])*255)
save("display.%s.mtime.png"%XxY, (viridis(alpha)*255).astype('uint8'))
def convert(fin, fout, cmin, cmax, cmap="viridis"):
geo = gdal2(fin)
npt = geo.bands[geo.names["N_POINTS"]]
img = geo.bands[geo.names["Z_MEAN"]]
img = (img - cmin) * (1.0 / (cmax - cmin))
img[img > 1] = 1
img[img < 0] = 0
cmap = getattr(cm, cmap)
img = (cmap(img) * 255).astype("uint8")
img[npt < 1] = 0
save(fout, img)
def convert(fin, fout, cmin, cmax, cmap='viridis'):
iin = load(fin) # get band as a numpy.array
img = iin[:,:,0]
alp = iin[:,:,1]
img = (img - cmin) * (1./(cmax - cmin))
img[img > 1] = 1
img[img < 0] = 0
cmap = getattr(cm, cmap)
img = (cmap(img)*255).astype('uint8')
img[alp < 1] = 255
save(fout, img)
def convert(fin, fout, cmin, cmax, cmap=colormap, npt=None):
geo = gdal2(fin)
img = geo.bands
if len(img.shape) > 2: # multi-layer
npt = geo.bands[geo.names["N_POINTS"]]
img = geo.bands[geo.names["Z_MEAN"]]
img = (img - cmin) * (1./(cmax - cmin))
img[img > 1] = 1
img[img < 0] = 0
img[npt < 1] = 0
# in case of JPEG or WebP, set quality to 90%, else this option is ignored
save(fout, (cmap(img)*255).astype('uint8'))
def convert(fin, fout, cmin, cmax, cmap=colormap, npt=None):
geo = gdal2(fin)
img = geo.bands
if len(img.shape) > 2: # multi-layer
npt = geo.bands[geo.names["N_POINTS"]]
img = geo.bands[geo.names["Z_MEAN"]]
img = (img - cmin) * (1. / (cmax - cmin))
img[img > 1] = 1
img[img < 0] = 0
img[npt < 1] = 0
# in case of JPEG or WebP, set quality to 90%, else this option is ignored
save(fout, (cmap(img) * 255).astype('uint8'))