def get_algebra(self, data, formula):
parser = RasterAlgebraParser()
# Evaluate raster algebra expression, return 400 if not successful
try:
# Evaluate raster algebra expression
result = parser.evaluate_raster_algebra(data, formula)
except:
raise RasterAlgebraException('Failed to evaluate raster algebra.')
# Get array from algebra result
if result.bands[0].nodata_value is None:
result = result.bands[0].data()
else:
result = numpy.ma.masked_values(
result.bands[0].data(),
result.bands[0].nodata_value,
)
# Get colormap.
colormap = self.get_colormap()
# Render tile using the legend data
img, stats = band_data_to_image(result, colormap)
# Return rendered image
return self.write_img_to_response(img, stats)
def get(self, *args, **kwargs):
"""
Returns an image rendered from a raster tile.
"""
# Get layer
layer = self.get_layer()
# Get colormap.
colormap = self.get_colormap(layer)
# Get tile
tile = self.get_tile(layer.id)
# Render tile
if tile and colormap:
data = numpy.ma.masked_values(
tile.bands[0].data(),
tile.bands[0].nodata_value,
)
# Render tile using the legend data
img, stats = band_data_to_image(data, colormap)
else:
# Create empty image if tile cant be found
img = Image.new("RGBA",
(WEB_MERCATOR_TILESIZE, WEB_MERCATOR_TILESIZE),
(0, 0, 0, 0))
stats = {}
return self.write_img_to_response(img, stats)
def get(self, *args, **kwargs):
"""
Returns an image rendered from a raster tile.
"""
# Get layer
layer = self.get_layer()
# Override color map if arg provided
colormap = self.get_colormap(layer)
# Get tile
tile = self.get_tile(layer.id)
# Render tile
if tile and colormap:
data = numpy.ma.masked_values(
tile.bands[0].data(),
tile.bands[0].nodata_value,
)
# Render tile using the legend data
img, stats = band_data_to_image(data, colormap)
else:
# Create empty image if tile cant be found
img = Image.new("RGBA", (WEB_MERCATOR_TILESIZE, WEB_MERCATOR_TILESIZE), (0, 0, 0, 0))
stats = {}
return self.write_img_to_response(img, stats)
def get(self, request, *args, **kwargs):
parser = RasterAlgebraParser()
# Get layer ids
ids = self.get_ids()
# Get raster data as 1D arrays and store in dict that can be used
# for formula evaluation.
data = {}
for name, layerid in ids.items():
tile = self.get_tile(layerid)
if tile:
data[name] = tile
else:
# Create empty image if any layer misses the required tile
img = Image.new("RGBA", (WEB_MERCATOR_TILESIZE, WEB_MERCATOR_TILESIZE), (0, 0, 0, 0))
return self.write_img_to_response(img, {})
# Get formula from request
formula = request.GET.get('formula')
# Evaluate raster algebra expression, return 400 if not successful
try:
# Evaluate raster algebra expression
result = parser.evaluate_raster_algebra(data, formula)
except:
raise RasterAlgebraException('Failed to evaluate raster algebra.')
# Get array from algebra result
result = numpy.ma.masked_values(
result.bands[0].data(),
result.bands[0].nodata_value,
)
# Render tile
colormap = self.get_colormap()
if colormap:
# Render tile using the legend data
img, stats = band_data_to_image(result, colormap)
else:
# Scale to grayscale rgb (can be colorscheme later on)
result = result.astype('float').ravel()
result = 255 * (result - numpy.min(result)) / (numpy.max(result) - numpy.min(result))
# Create rgba matrix from grayscale array
result = numpy.array((result, result, result, numpy.repeat(255, len(result)))).T
rgba = result.reshape(WEB_MERCATOR_TILESIZE, WEB_MERCATOR_TILESIZE, 4).astype('uint8')
# Create image from array
img = Image.fromarray(rgba)
stats = {}
# Return rendered image
return self.write_img_to_response(img, stats)
def get_algebra(self, data, formula):
parser = RasterAlgebraParser()
# Evaluate raster algebra expression, return 400 if not successful
try:
# Evaluate raster algebra expression
result = parser.evaluate_raster_algebra(data, formula)
except:
raise RasterAlgebraException('Failed to evaluate raster algebra.')
# For pixel value requests, return result as json.
if self.is_pixel_request:
xcoord = float(self.kwargs.get('xcoord'))
ycoord = float(self.kwargs.get('ycoord'))
val = pixel_value_from_point(result, [xcoord, ycoord])
return HttpResponse(
json.dumps({
'x': xcoord,
'y': ycoord,
'value': val
}),
content_type='application/json',
)
# For tif requests, skip colormap and return georeferenced tif file.
if self.kwargs.get('frmt') == 'tif':
vsi_path = os.path.join(VSI_FILESYSTEM_BASE_PATH,
str(uuid.uuid4()))
rast = result.warp({
'name': vsi_path,
'driver': 'tif',
'compress': 'DEFLATE',
})
content_type = IMG_FORMATS['tif'][1]
return HttpResponse(rast.vsi_buffer, content_type)
# Get array from algebra result
if result.bands[0].nodata_value is None:
result = result.bands[0].data()
else:
result = numpy.ma.masked_values(
result.bands[0].data(),
result.bands[0].nodata_value,
)
# Get colormap.
colormap = self.get_colormap()
# Render tile using the legend data
img, stats = band_data_to_image(result, colormap)
# Return rendered image
return self.write_img_to_response(img, stats)
def get_algebra(self, data, formula):
parser = RasterAlgebraParser()
# Evaluate raster algebra expression, return 400 if not successful
try:
# Evaluate raster algebra expression
result = parser.evaluate_raster_algebra(data, formula)
except:
raise RasterAlgebraException('Failed to evaluate raster algebra.')
# For pixel value requests, return result as json.
if self.is_pixel_request:
xcoord = float(self.kwargs.get('xcoord'))
ycoord = float(self.kwargs.get('ycoord'))
val = pixel_value_from_point(result, [xcoord, ycoord])
return HttpResponse(
json.dumps({
'x': xcoord,
'y': ycoord,
'value': val
}),
content_type='application/json',
)
# Get array from algebra result
if result.bands[0].nodata_value is None:
result = result.bands[0].data()
else:
result = numpy.ma.masked_values(
result.bands[0].data(),
result.bands[0].nodata_value,
)
# Get colormap.
colormap = self.get_colormap()
# Render tile using the legend data
img, stats = band_data_to_image(result, colormap)
# Return rendered image
return self.write_img_to_response(img, stats)
def get_algebra(self, data, formula):
parser = RasterAlgebraParser()
# Evaluate raster algebra expression, return 400 if not successful
try:
# Evaluate raster algebra expression
result = parser.evaluate_raster_algebra(data, formula)
except:
raise RasterAlgebraException('Failed to evaluate raster algebra.')
# Get array from algebra result
result = numpy.ma.masked_values(
result.bands[0].data(),
result.bands[0].nodata_value,
)
# Render tile
colormap = self.get_colormap()
if colormap:
# Render tile using the legend data
img, stats = band_data_to_image(result, colormap)
else:
# Scale to grayscale rgb (can be colorscheme later on)
result = result.astype('float').ravel()
result = 255 * (result - numpy.min(result)) / (numpy.max(result) -
numpy.min(result))
# Create rgba matrix from grayscale array
result = numpy.array(
(result, result, result, numpy.repeat(255, len(result)))).T
rgba = result.reshape(WEB_MERCATOR_TILESIZE, WEB_MERCATOR_TILESIZE,
4).astype('uint8')
# Create image from array
img = Image.fromarray(rgba)
stats = {}
# Return rendered image
return self.write_img_to_response(img, stats)