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Merge branch 'develop'

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This commit is contained in:
Florent Guiotte 2018-10-12 11:02:26 +02:00
commit f3076caa1e
2 changed files with 27 additions and 3 deletions
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15
cvgenerators/jurse.py
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@ -19,15 +19,22 @@ class Split:
If used with a split first description, make sure you use compatible If used with a split first description, make sure you use compatible
settings. settings.
Use `sub_sample (and `random_state`) parameters to sub sample the training
set.
return xtrain, xtest, ytrain, ytest, test_index
""" """
def __init__(self, ground_truth, attributes, n_test=2, order_dim=0, remove_unclassified=True): def __init__(self, ground_truth, attributes, n_test=2, order_dim=0, sub_sample=1.0, random_state=0, remove_unclassified=True):
self._att = attributes self._att = attributes
self._gt = ground_truth self._gt = ground_truth
self._n = n_test self._n = n_test
self._d = order_dim self._d = order_dim
self._s = 0 self._s = 0
self._r = remove_unclassified self._r = remove_unclassified
self._ssp = sub_sample
self._rs = random_state
self._size = ground_truth.shape[order_dim] self._size = ground_truth.shape[order_dim]
self._step = int(ground_truth.shape[order_dim] / n_test) self._step = int(ground_truth.shape[order_dim] / n_test)
@ -48,10 +55,14 @@ class Split:
unclassified = self._gt == 0 unclassified = self._gt == 0
train_index = ~test_index & ~unclassified train_index = ~test_index & ~unclassified
# Sub sample training
np.random.seed(self._rs)
train_index &= np.random.random(train_index.shape) < self._ssp
# Remove unclassified
if self._r: if self._r:
test_index &= ~unclassified test_index &= ~unclassified
#ipdb.set_trace()
xtrain = self._att[train_index] xtrain = self._att[train_index]
xtest = self._att[test_index] xtest = self._att[test_index]
ytrain = self._gt[train_index] ytrain = self._gt[train_index]

15
descriptors/dfc_dsdaps.py
View File

@ -68,7 +68,20 @@ def run(rasters, treshold=1e4, areas=None, sd=None, moi=None, split=1, split_dim
for i, cut in enumerate(dcuts): for i, cut in enumerate(dcuts):
view[i*step:(i+1)*step+1] = np.moveaxis(cut, 0, d) view[i*step:(i+1)*step+1] = np.moveaxis(cut, 0, d)
return descriptors # Merge with original
loader = ld2dap.LoadTIFF(rasters)
raw_in = ld2dap.RawInput(descriptors, vout.metadata)
merger = ld2dap.Merger()
final_out = ld2dap.RawOutput()
final_out.input = merger
merger.input = loader
merger.second.input = raw_in
loader.run()
raw_in.run()
return final_out.data
def version(): def version():
return 'v0.0' return 'v0.0'