def proc_cube(cube):
for i, frt_cube in enumerate(cube.slices_over("time")):
print "Processing timestep ", i, "...",
img_array = imageproc.tileArray(frt_cube.data)
img_array /= img_array.max()
img_array *= 255
print "Writing image"
with open("data%03d.png" % i, "wb") as img:
imageproc.writePng(img_array, img, nchannels=3, alpha=False)
print "Writing video"
sp.call(["avconv", "-y",
"-r", "1", "-i", "data%03d.png",
"-r", "1", "-vcodec", os.getenv("CODEC", "libtheora"), "-qscale:v", os.getenv("QUALITY", 2), os.getenv("FILE_OUT", "out.ogv"])
print "Cleaning up"
fs = glob.glob("./data???.png")
for f in fs:
os.remove(f)
if __name__=="__main__":
varname = os.getenv("VAR_NAME")
if varname != None:
cube = iris.load_cube(os.getenv("FILE_IN"), iris.Constraint(varname))
else:
cube = iris.load_cube(os.getenv("FILE_IN"))
proc_cube(cube)
def procDataToImage(data,
image_dest,
profile):
"""
Main processing function. Processes an model_level_number, lat, lon cube,
including all regridding and restratification of data,
calculates shadows, and then ultimately posts a tiled
image to the data service.
Args:
* data (iris cube): lat, lon, model_level_number cube
* image_dest (str): URL to the data service image destination
* regrid_shape (tuple): lon, lat, alt dimensions to regrid to
"""
# # tidy up any problems arising from the on-the-fly altitude calc
# print "Sanitizing data after altitude restratification"
# san_data = dataproc.sanitizeAlt(data) #TESTING ONLY
# # regrid and restratify the data
print "Regridding data to " + str(data.shape)
rg_data = dataproc.regridData(data,
len(data.coords(axis="Y")[0].points),
len(data.coords(axis="X")[0].points),
len(data.coords(axis="Z")[0].points),
extent=profile.extent)
# # do any further processing (saturation etc) and convert to 8 bit uints
# try:
# print "Applying custom data processing from profile"
# rg_data = profile.proc_fn(rg_data)
# except AttributeError:
# pass
print "Applying standard data processing (e.g. 8 bit scaling)"
proced_data = dataproc.procDataCube(rg_data)
print "Tiling data"
data_tiled = imageproc.tileArray(proced_data.data)
return data_tiled, proced_data
def procDataToImage(data, image_dest, profile):
"""
Main processing function. Processes an model_level_number, lat, lon cube,
including all regridding and restratification of data,
calculates shadows, and then ultimately posts a tiled
image to the data service.
Args:
* data (iris cube): lat, lon, model_level_number cube
* image_dest (str): URL to the data service image destination
* regrid_shape (tuple): lon, lat, alt dimensions to regrid to
"""
# # tidy up any problems arising from the on-the-fly altitude calc
# print "Sanitizing data after altitude restratification"
# san_data = dataproc.sanitizeAlt(data) #TESTING ONLY
# # regrid and restratify the data
print "Regridding data to " + str(data.shape)
rg_data = dataproc.regridData(
data,
len(data.coords(axis="Y")[0].points),
len(data.coords(axis="X")[0].points),
len(data.coords(axis="Z")[0].points),
extent=profile.extent,
)
# # do any further processing (saturation etc) and convert to 8 bit uints
# try:
# print "Applying custom data processing from profile"
# rg_data = profile.proc_fn(rg_data)
# except AttributeError:
# pass
print "Applying standard data processing (e.g. 8 bit scaling)"
proced_data = dataproc.procDataCube(rg_data)
print "Tiling data"
data_tiled = imageproc.tileArray(proced_data.data)
return data_tiled, proced_data
