def save_grid_to_image(grid, path, classes, colormap, geo_transform=None):
"""Save this grid as an image.
Assumes that all values in the grid are values that come from
one of the classes. Translates the values in the classes to colors
from the colormap, then finds all the places in the grid that are
equal to that class and sets all those to the right color.
Because of the above (classes) this save functions is not exactly
the same as the ColorMap.apply_to_grid() and files.save_geopng()
functions.
The type of image is decided by the path, but I only test with
PNG."""
classvalues = set()
for classline in classes:
for value in classline:
classvalues.add(value)
class_to_color = dict()
for classvalue in classvalues:
class_to_color[classvalue] = (
colormap.value_to_color(classvalue) or (0, 0, 0, 0))
n, m = grid.shape
colorgrid = numpy.zeros((4, n, m), dtype=numpy.uint8)
redgrid = numpy.zeros((n, m))
greengrid = numpy.zeros((n, m))
bluegrid = numpy.zeros((n, m))
for classvalue, color in class_to_color.items():
mask = (grid == classvalue)
redgrid += mask * color[0]
greengrid += mask * color[1]
bluegrid += mask * color[2]
colorgrid[0] = redgrid
colorgrid[1] = greengrid
colorgrid[2] = bluegrid
# Colored pixels get opacity 255, non-colored pixels opacity 0
# (transparent)
colorgrid[3] = (
((redgrid > 0) | (greengrid > 0) | (bluegrid > 0)) * 255)
files.save_geopng(path, colorgrid, geo_transform)
def save_grid_to_image(grid, path, classes, colormap, geo_transform=None):
"""Save this grid as an image.
Assumes that all values in the grid are values that come from
one of the classes. Translates the values in the classes to colors
from the colormap, then finds all the places in the grid that are
equal to that class and sets all those to the right color.
Because of the above (classes) this save functions is not exactly
the same as the ColorMap.apply_to_grid() and files.save_geopng()
functions.
The type of image is decided by the path, but I only test with
PNG."""
classvalues = set()
for classline in classes:
for value in classline:
classvalues.add(value)
class_to_color = dict()
for classvalue in classvalues:
class_to_color[classvalue] = (colormap.value_to_color(classvalue)
or (0, 0, 0, 0))
n, m = grid.shape
colorgrid = numpy.zeros((4, n, m), dtype=numpy.uint8)
redgrid = numpy.zeros((n, m))
greengrid = numpy.zeros((n, m))
bluegrid = numpy.zeros((n, m))
for classvalue, color in class_to_color.items():
mask = (grid == classvalue)
redgrid += mask * color[0]
greengrid += mask * color[1]
bluegrid += mask * color[2]
colorgrid[0] = redgrid
colorgrid[1] = greengrid
colorgrid[2] = bluegrid
# Colored pixels get opacity 255, non-colored pixels opacity 0
# (transparent)
colorgrid[3] = (((redgrid > 0) | (greengrid > 0) | (bluegrid > 0)) * 255)
files.save_geopng(path, colorgrid, geo_transform)
def generate_from_asc(
output_dir_name, input_files, colormapobject, result):
input_files = sorted(i for i in input_files if i.lower().endswith('.asc'))
amount = len(input_files)
if amount == 1:
basename = os.path.basename(input_files[0])[:8]
output_file = os.path.join(output_dir_name, basename + ".png")
elif amount > 1:
basename = os.path.basename(input_files[0])[:4]
output_file = os.path.join(
output_dir_name, basename[:4] + "{:04d}.png")
else:
logger.warning('no files found to generate pngs')
return 0, None
for i, filename in enumerate(input_files):
real_filename = output_file.format(i)
try:
dataset = gdal.Open(str(filename))
if dataset is None:
logger.debug("Dataset None: " + str(filename))
else:
grid = dataset.ReadAsArray()
# Hack -- correct grid_ta for start moment of breach
if result.resulttype.name == 'gridta':
correct_gridta(grid, result)
colored_grid = colormapobject.apply_to_grid(grid)
files.save_geopng(
real_filename, colored_grid, dataset.GetGeoTransform())
finally:
del dataset # Closes the file object so that it can be
# deleted on Windows
return amount, basename
def generate_from_asc(output_dir_name, input_files, colormapobject, result):
input_files = sorted(i for i in input_files if i.lower().endswith('.asc'))
amount = len(input_files)
if amount == 1:
basename = os.path.basename(input_files[0])[:8]
output_file = os.path.join(output_dir_name, basename + ".png")
elif amount > 1:
basename = os.path.basename(input_files[0])[:4]
output_file = os.path.join(output_dir_name,
basename[:4] + "{:04d}.png")
else:
logger.warning('no files found to generate pngs')
return 0, None
for i, filename in enumerate(input_files):
real_filename = output_file.format(i)
try:
dataset = gdal.Open(str(filename))
if dataset is None:
logger.debug("Dataset None: " + str(filename))
else:
grid = dataset.ReadAsArray()
# Hack -- correct grid_ta for start moment of breach
if result.resulttype.name == 'gridta':
correct_gridta(grid, result)
colored_grid = colormapobject.apply_to_grid(grid)
files.save_geopng(real_filename, colored_grid,
dataset.GetGeoTransform())
finally:
del dataset # Closes the file object so that it can be
# deleted on Windows
return amount, basename
