def populate(self):
"""
Compute value count using the objects value count parameters.
"""
# Update status
self.status = self.COMPUTING
self.save()
try:
# Compute aggregate result
agg = Aggregator(
layer_dict=self.layer_names,
formula=self.formula,
zoom=self.zoom,
geom=self.aggregationarea.geom,
acres=self.units.lower() == 'acres',
grouping=self.grouping,
)
aggregation_result = agg.value_count()
self.stats_min, self.stats_max, self.stats_avg, self.stats_std = agg.statistics()
# Track cumulative data to be able to generalize stats over
# multiple aggregation areas.
self.stats_cumsum_t0 = agg._stats_t0
self.stats_cumsum_t1 = agg._stats_t1
self.stats_cumsum_t2 = agg._stats_t2
# Convert values to string for storage in hstore
self.value = {k: str(v) for k, v in aggregation_result.items()}
self.status = self.FINISHED
except:
self.status = self.FAILED
self.save()
def test_layer_with_no_tiles(self):
agg = Aggregator(layer_dict={
'a': self.rasterlayer.id,
'b': self.empty_rasterlayer.id
},
formula='a*b')
self.assertDictEqual(agg.value_count(), {})
def test_memory_efficient(self):
agg = Aggregator(
layer_dict={'a': self.rasterlayer.id},
formula='a',
grouping='discrete',
memory_efficient=True,
)
self.assertDictEqual(
agg.value_count(),
{str(k): v for k, v in self.expected_totals.items()}
)
agg = Aggregator(
layer_dict={'a': self.rasterlayer.id},
formula='a',
grouping='continuous',
memory_efficient=True,
hist_range=(0, 100),
)
self.assertDictEqual(
agg.value_count(),
{
'(10.0, 20.0)': 0, '(60.0, 70.0)': 0, '(40.0, 50.0)': 0,
'(90.0, 100.0)': 0, '(70.0, 80.0)': 0, '(50.0, 60.0)': 0,
'(30.0, 40.0)': 0, '(20.0, 30.0)': 0, '(0.0, 10.0)': 62440,
'(80.0, 90.0)': 0
},
)
def populate(self):
"""
Compute value count using the objects value count parameters.
"""
# Update status
self.status = self.COMPUTING
self.save()
try:
# Compute aggregate result
agg = Aggregator(
layer_dict=self.layer_names,
formula=self.formula,
zoom=self.zoom,
geom=self.aggregationarea.geom,
acres=self.units.lower() == 'acres',
grouping=self.grouping,
)
aggregation_result = agg.value_count()
self.stats_min, self.stats_max, self.stats_avg, self.stats_std = agg.statistics()
# Track cumulative data to be able to generalize stats over
# multiple aggregation areas.
self.stats_cumsum_t0 = agg._stats_t0
self.stats_cumsum_t1 = agg._stats_t1
self.stats_cumsum_t2 = agg._stats_t2
# Convert values to string for storage in hstore
self.value = {k: str(v) for k, v in aggregation_result.items()}
self.status = self.FINISHED
except:
self.status = self.FAILED
self.save()
def value_count(self, geom=None, area=False, zoom=None):
"""
Compute value counts or histograms for rasterlayers within a geometry.
"""
from raster.valuecount import Aggregator
agg = Aggregator(layer_dict={'a': self.id}, formula='a', zoom=zoom, geom=geom, acres=area)
return agg.value_count()
def test_layer_discrete_grouping(self):
agg = Aggregator(layer_dict={'a': self.rasterlayer.id},
formula='a',
grouping='discrete')
self.assertDictEqual(
agg.value_count(),
{str(k): v
for k, v in self.expected_totals.items()})
def test_layer_with_json_grouping(self):
# Use a legend with simple int expression
agg = Aggregator(layer_dict={'a': self.rasterlayer.id},
formula='a',
grouping=self.legend.json)
self.assertDictEqual(agg.value_count(), {
'2': self.expected_totals[2],
'10': 0
})
def test_layer_continuous_grouping(self):
agg = Aggregator(
layer_dict={'a': self.rasterlayer.id},
formula='a',
grouping='continuous'
)
self.assertDictEqual(
agg.value_count(),
self.continuous_expected_histogram
)
def test_memory_efficient_error(self):
msg = 'Secify a histogram range for memory efficient continuous aggregation.'
with self.assertRaisesMessage(RasterAggregationException, msg):
agg = Aggregator(
layer_dict={'a': self.rasterlayer.id},
formula='a',
grouping='continuous',
memory_efficient=True,
)
agg.value_count()
def test_layer_continuous_grouping(self):
agg = Aggregator(
layer_dict={'a': self.rasterlayer.id},
formula='a',
grouping='continuous'
)
self.assertDictEqual(
agg.value_count(),
self.continuous_expected_histogram
)
def test_layer_discrete_grouping(self):
agg = Aggregator(
layer_dict={'a': self.rasterlayer.id},
formula='a',
grouping='discrete'
)
self.assertDictEqual(
agg.value_count(),
{str(k): v for k, v in self.expected_totals.items()}
)
def test_memory_efficient_error(self):
msg = 'Secify a histogram range for memory efficient continuous aggregation.'
with self.assertRaisesMessage(RasterAggregationException, msg):
agg = Aggregator(
layer_dict={'a': self.rasterlayer.id},
formula='a',
grouping='continuous',
memory_efficient=True,
)
agg.value_count()
def test_layer_with_json_grouping(self):
# Use a legend with simple int expression
agg = Aggregator(
layer_dict={'a': self.rasterlayer.id},
formula='a',
grouping=self.legend.json
)
self.assertDictEqual(
agg.value_count(),
{'2': self.expected_totals[2]}
)
def test_layer_stats(self):
# Use a legend with simple int expression
agg = Aggregator(
layer_dict={'a': self.rasterlayer.id},
formula='a',
)
# Get original band metadata
meta = self.rasterlayer.rasterlayerbandmetadata_set.first()
# The comparison here is loose, as one is computed on tiles and the other
# other value are the original band values. So there are differences from
# rescaling.
for dat in zip(agg.statistics(), meta.statistics()):
self.assertAlmostEqual(dat[0], dat[1], 1)
def test_full_mask_data(self):
# Override all tiles to be fully masked.
for tile in self.rasterlayer.rastertile_set.all():
tile.rast.bands[0].data([0], shape=(1, 1))
tile.rast.bands[0].nodata_value = 0
tile.save()
# Use a legend with simple int expression
agg = Aggregator(
layer_dict={'a': self.rasterlayer.id},
formula='a',
)
self.assertEqual((None, None, None, None), agg.statistics())
def test_layer_stats(self):
# Use a legend with simple int expression
agg = Aggregator(
layer_dict={'a': self.rasterlayer.id},
formula='a',
)
# Get original band metadata
meta = self.rasterlayer.rasterlayerbandmetadata_set.first()
# The comparison here is loose, as one is computed on tiles and the other
# other value are the original band values. So there are differences from
# rescaling.
for dat in zip(agg.statistics(), meta.statistics()):
self.assertAlmostEqual(dat[0], dat[1], 1)
def test_full_mask_data(self):
# Override all tiles to be fully masked.
for tile in self.rasterlayer.rastertile_set.all():
tile.rast.bands[0].data([0], shape=(1, 1))
tile.rast.bands[0].nodata_value = 0
tile.save()
# Use a legend with simple int expression
agg = Aggregator(
layer_dict={'a': self.rasterlayer.id},
formula='a',
)
self.assertEqual((None, None, None, None), agg.statistics())
def test_histogram_range(self):
agg = Aggregator(
layer_dict={'a': self.rasterlayer.id},
formula='a',
grouping='continuous',
hist_range=(0, 100)
)
self.assertDictEqual(
agg.value_count(),
{
'(0.0, 10.0)': 62440, '(20.0, 30.0)': 0, '(70.0, 80.0)': 0,
'(80.0, 90.0)': 0, '(30.0, 40.0)': 0, '(10.0, 20.0)': 0,
'(90.0, 100.0)': 0, '(60.0, 70.0)': 0, '(50.0, 60.0)': 0,
'(40.0, 50.0)': 0,
}
)
def test_histogram_range(self):
agg = Aggregator(layer_dict={'a': self.rasterlayer.id},
formula='a',
grouping='continuous',
hist_range=(0, 100))
self.assertDictEqual(
agg.value_count(), {
'(0.0, 10.0)': 62440,
'(20.0, 30.0)': 0,
'(70.0, 80.0)': 0,
'(80.0, 90.0)': 0,
'(30.0, 40.0)': 0,
'(10.0, 20.0)': 0,
'(90.0, 100.0)': 0,
'(60.0, 70.0)': 0,
'(50.0, 60.0)': 0,
'(40.0, 50.0)': 0,
})
def test_valuecount_exception(self):
# Invalid input type
msg = 'Invalid grouping value found for valuecount.'
with self.assertRaisesMessage(RasterAggregationException, msg):
agg = Aggregator(
layer_dict={'a': self.rasterlayer.id},
formula='a',
grouping='unknown'
)
agg.value_count()
# Invalid legend ID
msg = 'Invalid legend ID found in grouping value for valuecount.'
with self.assertRaisesMessage(RasterAggregationException, msg):
agg = Aggregator(
layer_dict={'a': self.rasterlayer.id},
formula='a',
grouping='99999'
)
def test_layer_with_legend_grouping(self):
# Use a legend with simple int expression
agg = Aggregator(
layer_dict={'a': self.rasterlayer.id},
formula='a',
grouping=self.legend.id
)
self.assertDictEqual(
agg.value_count(),
{'2': self.expected_totals[2]}
)
# Use a legend with formula expression
agg = Aggregator(
layer_dict={'a': self.rasterlayer.id},
formula='a',
grouping=self.legend_with_expression.id
)
self.assertDictEqual(
agg.value_count(),
{'(x >= 2) & (x < 5)': self.expected_totals[2] + self.expected_totals[3] + self.expected_totals[4]}
)
def test_layer_with_legend_grouping(self):
# Use a legend with simple int expression
agg = Aggregator(
layer_dict={'a': self.rasterlayer.id},
formula='a',
grouping=self.legend.id,
)
self.assertDictEqual(
agg.value_count(),
{
'2': self.expected_totals[2],
'10': 0
},
)
# Use a legend with formula expression
agg = Aggregator(
layer_dict={'a': self.rasterlayer.id},
formula='a',
grouping=self.legend_with_expression.id,
)
self.assertDictEqual(
agg.value_count(),
{
'(x >= 2) & (x < 5)':
self.expected_totals[2] + self.expected_totals[3] +
self.expected_totals[4]
},
)
def test_memory_efficient(self):
agg = Aggregator(
layer_dict={'a': self.rasterlayer.id},
formula='a',
grouping='discrete',
memory_efficient=True,
)
self.assertDictEqual(
agg.value_count(),
{str(k): v for k, v in self.expected_totals.items()}
)
agg = Aggregator(
layer_dict={'a': self.rasterlayer.id},
formula='a',
grouping='continuous',
memory_efficient=True,
hist_range=(0, 100),
)
self.assertDictEqual(
agg.value_count(),
{
'(10.0, 20.0)': 0, '(60.0, 70.0)': 0, '(40.0, 50.0)': 0,
'(90.0, 100.0)': 0, '(70.0, 80.0)': 0, '(50.0, 60.0)': 0,
'(30.0, 40.0)': 0, '(20.0, 30.0)': 0, '(0.0, 10.0)': 62440,
'(80.0, 90.0)': 0
},
)
def test_valuecount_exception(self):
# Invalid input type
msg = 'Invalid grouping value found for valuecount.'
with self.assertRaisesMessage(RasterAggregationException, msg):
agg = Aggregator(layer_dict={'a': self.rasterlayer.id},
formula='a',
grouping='unknown')
agg.value_count()
# Invalid legend ID
msg = 'Invalid legend ID found in grouping value for valuecount.'
with self.assertRaisesMessage(RasterAggregationException, msg):
agg = Aggregator(layer_dict={'a': self.rasterlayer.id},
formula='a',
grouping='99999')
def test_histogram_range(self):
agg = Aggregator(
layer_dict={'a': self.rasterlayer.id},
formula='a',
grouping='continuous',
hist_range=(0, 100)
)
self.assertDictEqual(
agg.value_count(),
{
'(0.0, 10.0)': 62440, '(20.0, 30.0)': 0, '(70.0, 80.0)': 0,
'(80.0, 90.0)': 0, '(30.0, 40.0)': 0, '(10.0, 20.0)': 0,
'(90.0, 100.0)': 0, '(60.0, 70.0)': 0, '(50.0, 60.0)': 0,
'(40.0, 50.0)': 0,
}
)
# Limit histogram range.
agg = Aggregator(
layer_dict={'a': self.rasterlayer.id},
formula='a',
grouping='continuous',
hist_range=(0.5, 8)
)
# Compute value count.
vals = agg.value_count()
self.assertDictEqual(
vals,
{
'(0.5, 1.25)': 695,
'(1.25, 2.0)': 0,
'(2.0, 2.75)': 56,
'(2.75, 3.5)': 4131,
'(3.5, 4.25)': 31490,
'(4.25, 5.0)': 0,
'(5.0, 5.75)': 0,
'(5.75, 6.5)': 0,
'(6.5, 7.25)': 0,
'(7.25, 8.0)': 1350
}
)
# Statistics are clipped to range.
self.assertEqual(agg._stats_min_value, 1)
self.assertEqual(agg._stats_max_value, 8)
self.assertEqual(agg._stats_t0, 37722)
self.assertEqual(sum(vals.values()), agg._stats_t0)
self.assertEqual(agg._stats_t1, 149960)
self.assertEqual(agg._stats_t2, 628338)
def test_layer_with_no_tiles(self):
agg = Aggregator(
layer_dict={'a': self.rasterlayer.id, 'b': self.empty_rasterlayer.id},
formula='a*b'
)
self.assertDictEqual(agg.value_count(), {})