Commit 78ea95de authored by Niklas Bohn's avatar Niklas Bohn
Browse files

Merge branch 'bugfix/Issue#84' into 'master'

Bugfix/issue#84

See merge request !79
parents d25b76f5 3526d6a2
......@@ -71,7 +71,7 @@ test_sicor_s2:
- export GDAL_DATA=/root/miniconda3/envs/sicor_env/share/gdal
- export PYTHONPATH=$PYTHONPATH:/root # /root <- directory needed later
- pip install pycodestyle --upgrade
- mamba install -c conda-forge pygrib cachetools gdown scikit-learn=0.21.3
- mamba install -c conda-forge pygrib cachetools gdown scikit-learn
- make lint
- make nosetests_s2 # sentinel-2 tests are called here
- pip install sphinx_rtd_theme # Read-the-docs theme for SPHINX documentation
......
......@@ -26,7 +26,6 @@
import numpy as np
from multiprocessing import Pool
import platform
from tqdm import tqdm
from sicor.Tools.EnMAP.multiprocessing import initializer
......@@ -106,10 +105,11 @@ def empirical_line_solution(X, rdn_subset, data_l2a_seg, rows, cols, bands, segs
# about geographic or 3D locations
row_grid, col_grid = np.meshgrid(np.arange(rows), np.arange(cols))
locations = np.array([col_grid.flatten(), row_grid.flatten()]).T
locations_subset = np.zeros((segs, 2))
if land_only:
lbl = np.unique(labels)[1:]
segs = len(lbl)
locations_subset = np.zeros((segs, 2))
for ii, idx in enumerate(lbl):
locations_subset[ii, :] = locations[labels.flat == idx, :].mean(axis=0)
......@@ -122,8 +122,9 @@ def empirical_line_solution(X, rdn_subset, data_l2a_seg, rows, cols, bands, segs
unique_labels = np.arange(0, np.max(lbl) + 1 - len(missing_labels), 1)
else:
locations_subset = np.zeros((segs, 2))
for i in range(segs):
if np.count_nonzero(segs == 1) == 0:
if np.count_nonzero(segs == i) == 0:
pass
else:
locations_subset[i, :] = locations[labels.flat == i, :].mean(axis=0)
......@@ -135,7 +136,7 @@ def empirical_line_solution(X, rdn_subset, data_l2a_seg, rows, cols, bands, segs
if ii not in unique_labels:
missing_labels.append(ii)
unique_labels = np.arange(0, np.max(unique_labels) - len(missing_labels), 1)
unique_labels = np.arange(0, np.max(unique_labels) + 1 - len(missing_labels), 1)
tree = KDTree(locations_subset)
......
......@@ -147,7 +147,7 @@ def sicor_ac_enmap(enmap_l1b, options, unknowns=False, logger=None):
rows=fo_enmap.data_vnir.shape[0],
cols=fo_enmap.data_vnir.shape[1],
bands=fo_enmap.data_vnir.shape[2],
segs=labels_trans.max(),
segs=np.unique(labels_trans).shape[0],
labels=labels_trans,
land_only=fo_enmap.land_only,
processes=fo_enmap.cpu,
......@@ -160,7 +160,7 @@ def sicor_ac_enmap(enmap_l1b, options, unknowns=False, logger=None):
rows=fo_enmap.data_swir.shape[0],
cols=fo_enmap.data_swir.shape[1],
bands=fo_enmap.data_swir.shape[2],
segs=fo_enmap.segs,
segs=np.unique(fo_enmap.labels).shape[0],
labels=fo_enmap.labels,
land_only=fo_enmap.land_only,
processes=fo_enmap.cpu,
......
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