def test_flowdir_noflats_optimized(fillednoflatsdata, flowdirdata):
speedups.enable()
assert speedups.enabled
flowdir = flow.terrain_flowdirection(fillednoflatsdata)
assert np.all(flowdir >= 0)
assert np.all(flowdir <= 8)
assert np.all(flowdir == flowdirdata)
def test_optimized_fill(dtmdata, filleddata):
speedups.enable()
assert speedups.enabled
filled = fill.fill_terrain(dtmdata)
assert np.all(filled >= np.min(dtmdata))
assert np.max(filled) == np.max(dtmdata)
assert np.all(filled == filleddata)
def test_optimized_fill_no_flats(dtmdata, fillednoflatsdata):
speedups.enable()
assert speedups.enabled
short, diag = fill.minimum_safe_short_and_diag(dtmdata)
filled = fill.fill_terrain_no_flats(dtmdata, short, diag)
assert np.sum(filled > dtmdata) > 0
assert np.all(filled <= np.max(dtmdata) +
(dtmdata.shape[0] + dtmdata.shape[1]) * diag)
assert np.all(filled == fillednoflatsdata)
def test_accumulated_flow_optimized(flowdirdata):
from malstroem.algorithms import speedups
assert speedups.available
speedups.enable()
assert speedups.enabled
accum = flow.accumulated_flow(flowdirdata)
assert np.min(accum) >= 1 # All cells MUST be >= 1
assert np.max(accum) == 11158
assert np.sum(accum) == 3578615
def test_compare_label_stats(filleddata, bspotdata):
speedups.disable()
assert not speedups.enabled
stats = label.label_stats(filleddata, bspotdata)
speedups.enable()
assert speedups.enabled
statsopt = label.label_stats(filleddata, bspotdata)
for s, so in zip(stats, statsopt):
assert s == so
def test_speedups_toggl(method):
speedups.disable()
assert not is_speedups_method(getattr(
label, method)), f"Speedup for {method} not disabled"
speedups.enable()
assert is_speedups_method(getattr(
label, method)), f"Speedup for {method} not enabled"
speedups.disable()
assert not is_speedups_method(getattr(
label, method)), f"Speedup for {method} not disabled"
def test_compare_fill_no_flats_python_and_optimized(dtmdata):
speedups.enable()
assert speedups.enabled
short, diag = fill.minimum_safe_short_and_diag(dtmdata)
filled_optimized = fill.fill_terrain_no_flats(dtmdata, short, diag)
speedups.disable()
assert not speedups.enabled
filled_python = fill.fill_terrain_no_flats(dtmdata, short, diag)
assert np.all(filled_optimized == filled_python)
def test_compare_fill_python_and_optimized(dtmdata):
speedups.enable()
assert speedups.enabled
filled_optimized = fill.fill_terrain(dtmdata)
speedups.disable()
assert not speedups.enabled
filled_python = fill.fill_terrain(dtmdata)
assert np.all(filled_optimized == filled_python)
def test_compare_label_min_index(fillednoflatsdata, bspotdata):
speedups.disable()
assert not speedups.enabled
min_ix = label.label_min_index(fillednoflatsdata, bspotdata)
speedups.enable()
assert speedups.enabled
min_ix_opt = label.label_min_index(fillednoflatsdata, bspotdata)
assert len(min_ix) == len(min_ix_opt)
for m, mopt in zip(min_ix, min_ix_opt):
for v, vopt in zip(m, mopt):
assert np.isclose(v, vopt)
def test_watersheds_optimized32(flowdirdata, bspotdata):
speedups.enable()
assert speedups.enabled
watersheds = np.copy(bspotdata)
assert watersheds.dtype == np.int32
flow.watersheds_from_labels(flowdirdata, watersheds, unassigned=0)
labelled_indexes = bspotdata > 0
assert np.all(watersheds[labelled_indexes] == bspotdata[labelled_indexes])
assert np.max(watersheds) == np.max(bspotdata)
assert np.sum(watersheds) == 2337891
# Check that all watersheds are a connected component
for lbl in range(1, np.max(watersheds) + 1):
labeled, nlabels = label.connected_components(watersheds == lbl)
assert nlabels == 1, "Watershed {} is not a connected component".format(
lbl)
def test_label_stats_optimized(filleddata, bspotdata):
speedups.enable()
assert speedups.enabled
stats = label.label_stats(filleddata, bspotdata)
assert len(stats) == np.max(bspotdata) + 1
assert np.all(stats[:]['min'] <= stats[:]['max'])
assert np.sum(stats[:]['count']) == bspotdata.shape[0] * bspotdata.shape[1]
assert np.min(stats[:]['min']) == np.min(filleddata)
assert np.max(stats[:]['max']) == np.max(filleddata)
# Check label with most cells
lbl = np.argmax(stats[:]['count'])
lblix = bspotdata == lbl
assert stats[lbl]['min'] == np.min(filleddata[lblix])
assert stats[lbl]['max'] == np.max(filleddata[lblix])
np.testing.assert_almost_equal(
stats[lbl]['sum'], np.sum(filleddata.astype(np.float64)[lblix]))
assert stats[lbl]['count'] == np.sum(lblix)
def test_label_data_optimized(bspotdata, depthsdata):
speedups.enable()
assert speedups.enabled
data_per_label = label.label_data(depthsdata,
bspotdata,
nlabels=None,
background=0)
assert len(data_per_label) > 0
assert len(data_per_label) == np.max(bspotdata) + 1
assert len(data_per_label[0]) == 0, "Background data list should be empty"
for e, values_list in enumerate(data_per_label[1:]):
assert len(values_list) > 0, f"label {e+1} has zero data values"
# Sum collected values
sums = [sum(x) for x in data_per_label]
global_sum = sum(sums)
# Make sum in numpy using rasters only
np_sum = np.sum(depthsdata[bspotdata != 0])
assert pytest.approx(
np_sum) == global_sum, "Returned values do not sum correctly"
def test_label_min_index_optimized(fillednoflatsdata, bspotdata):
speedups.enable()
assert speedups.enabled
min_ix = label.label_min_index(fillednoflatsdata, bspotdata)
assert len(min_ix) == np.max(bspotdata) + 1
