def test_pixelscale_metres(self):
scale = 0.00025
shape = (4000, 4000)
origin = (150.0, -34.0)
ggb = GriddedGeoBox(shape, origin, pixelsize=(scale, scale))
(size_x, size_y) = ggb.get_pixelsize_metres(xy=(0, 0))
self.assertAlmostEqual(size_x, 23.0962, places=4)
self.assertAlmostEqual(size_y, 27.7306, places=4)
def test_create(self):
scale = 0.00025
shape = (3, 2)
origin = (150.0, -34.0)
corner = (shape[1] * scale + origin[0], origin[1] - shape[0] * scale)
ggb = GriddedGeoBox(shape, origin)
assert ggb is not None
self.assertEqual(shape, ggb.shape)
self.assertEqual(origin, ggb.origin)
self.assertEqual(corner, ggb.corner)
def test_all_pixelscale_metres(self):
scale = 0.00025
shape = (4000, 4000)
origin = (150.0, -34.0)
ggb = GriddedGeoBox(shape, origin, pixelsize=(scale, scale))
size_array = ggb.get_all_pixelsize_metres()
self.assertEqual(len(size_array), 4000)
(size_x, size_y) = size_array[0]
self.assertAlmostEqual(size_x, 23.0962, places=4)
self.assertAlmostEqual(size_y, 27.7306, places=4)
(size_x, size_y) = size_array[3999]
self.assertAlmostEqual(size_x, 22.8221, places=4)
self.assertAlmostEqual(size_y, 27.7351, places=4)
def no_test_ggb_subsets(self):
# get Land/Sea data file for this bounding box
utmZone = 56
utmDataPath = '/g/data/v10/eoancillarydata/Land_Sea_Rasters/WORLDzone%d.tif' % (utmZone,)
# read the data for the Flinders islet region
with rio.open(utmDataPath) as ds:
# get the gridded box for the full data extent
datasetGGB = GriddedGeoBox.from_dataset(ds)
flindersGGB = getFlindersIsletGGB()
scale = 0.00025
shapeYX = (3, 3)
origin = (150.0, -34.0)
corner = (shapeYX[1] * scale + origin[0], origin[1] - shapeYX[0] * scale)
ggb = GriddedGeoBox(shapeYX, origin)
assert ggb is not None
self.assertEqual(shapeYX, ggb.shape)
self.assertEqual(origin, ggb.origin)
self.assertEqual(corner, ggb.corner)
def test_agdc_copy(self):
scale = 0.00025
shape = (4000, 4000)
origin = (150.0, -34.0)
corner = (shape[1] * scale + 150, -34 - shape[0] * scale)
ggb = GriddedGeoBox(shape, origin, pixelsize=(scale, scale))
# print "ggb=%s" % str(ggb)
assert ggb is not None
self.assertEqual(shape, ggb.shape)
self.assertEqual(corner, ggb.corner)
# now get UTM equilavent
utm_ggb = ggb.copy(crs="EPSG:32756")
# print "utm_ggb=%s" % str(utm_ggb)
self.assertAlmostEqual(utm_ggb.origin[0], 222908.70452156663)
self.assertAlmostEqual(utm_ggb.origin[1], 6233785.283900621)
self.assertAlmostEqual(utm_ggb.corner[0], 317483.90638409054)
self.assertAlmostEqual(utm_ggb.corner[1], 6125129.365269075)
self.assertAlmostEqual(utm_ggb.pixelsize[0], 23.643800465630978)
self.assertAlmostEqual(utm_ggb.pixelsize[1], 27.16397965788655)
def z_axis_stats(self, out_fname=None, raster_bands=None):
"""
Compute statistics over the z-axis of the StackedDataset.
An image containing 14 raster bands, each describing a
statistical measure:
* 1. Sum
* 2. Mean
* 3. Valid Observations
* 4. Variance
* 5. Standard Deviation
* 6. Skewness
* 7. Kurtosis
* 8. Max
* 9. Min
* 10. Median (non-interpolated value)
* 11. Median Index (zero based index)
* 12. 1st Quantile (non-interpolated value)
* 13. 3rd Quantile (non-interpolated value)
* 14. Geometric Mean
:param out_fname:
A string containing the full file system path name of the
image containing the statistical outputs.
:param raster_bands:
If raster_bands is None (Default) then statistics will be
calculated across all bands. Otherwise raster_bands can be
a list containing the raster bands of interest. This can be
sequential or non-sequential.
:return:
An instance of StackedDataset referencing the stats file.
"""
# Check if the image tiling has been initialised
if self.n_tiles == 0:
self.init_tiling()
# Get the band names for the stats file
band_names = [
'Sum', 'Mean', 'Valid Observations', 'Variance',
'Standard Deviation', 'Skewness', 'Kurtosis', 'Max', 'Min',
'Median (non-interpolated value)',
'Median Index (zero based index)',
'1st Quantile (non-interpolated value)',
'3rd Quantile (non-interpolated value)', 'Geometric Mean'
]
# out number of bands
out_nb = 14
# Construct the output image file to contain the result
if out_fname is None:
out_fname = pjoin(self.fname, '_z_axis_stats')
geobox = GriddedGeoBox(shape=(self.lines, self.samples),
origin=(self.geotransform[0],
self.geotransform[3]),
pixelsize=(self.geotransform[1],
self.geotransform[5]),
crs=self.projection)
outds = TiledOutput(out_fname,
self.samples,
self.lines,
out_nb,
geobox,
no_data=numpy.nan,
dtype=gdal.GDT_Float32)
# Write the band names
for i in range(out_nb):
outds.out_bands[i].SetDescription(band_names[i])
# If we have None, set to read all bands
if raster_bands is None:
raster_bands = range(1, self.bands + 1)
# Check that we have an iterable
if not isinstance(raster_bands, collections.Sequence):
msg = 'raster_bands is not a list but a {}'
msg = msg.format(type(raster_bands))
raise TypeError(msg)
# Loop over every tile
for tile_n in range(self.n_tiles):
tile = self.get_tile(tile_n)
subset = self.read_tile(tile, raster_bands)
stats = bulk_stats(subset, no_data=self.no_data)
outds.write_tile(stats, tile)
outds.close()
return StackedDataset(out_fname)