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Fix labelled data counts not covering all selected train IDs #751

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Fix labelled data counts not covering all selected train IDs #751

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4 changes: 3 additions & 1 deletion extra_data/keydata.py
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Original file line number Diff line number Diff line change
Expand Up @@ -398,7 +398,9 @@ def data_counts(self, labelled=True):

if labelled:
import pandas as pd
return pd.Series(counts, index=train_ids)
res = pd.Series(0, index=self.train_ids)
res.loc[train_ids] = counts
return res
else:
all_tids_arr = np.array(self.train_ids)
res = np.zeros(len(all_tids_arr), dtype=np.uint64)
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14 changes: 11 additions & 3 deletions extra_data/tests/test_keydata.py
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Original file line number Diff line number Diff line change
Expand Up @@ -170,7 +170,7 @@ def test_get_train_keep_dims(mock_jungfrau_run):
assert val.shape == (1, 16, 512, 1024)


def test_data_counts(mock_reduced_spb_proc_run):
def test_data_counts(mock_reduced_spb_proc_run, mock_jungfrau_run):
run = RunDirectory(mock_reduced_spb_proc_run)

# control data
Expand All @@ -189,6 +189,14 @@ def test_data_counts(mock_reduced_spb_proc_run):
assert count.index.tolist() == mod.train_ids
assert count.values.sum() == mod.shape[0]

# Combine data with more train IDs than our original sources, and
# ensure that the data counts now cover these additional train IDs
# as well with 0.
multi_run = run.union(RunDirectory(mock_jungfrau_run))
mod = multi_run['SPB_DET_AGIPD1M-1/DET/0CH0:xtdf', 'image.data']
count = mod.data_counts()
assert count.index.tolist() == mod.train_ids


def test_data_counts_empty(mock_fxe_raw_run):
run = RunDirectory(mock_fxe_raw_run)
Expand Down Expand Up @@ -230,8 +238,8 @@ def test_data_counts_missing_train(fxe_run_module_offset):
lpd_m8 = run['FXE_DET_LPD1M-1/DET/8CH0:xtdf', 'image.cellId']

ser = lpd_m8.data_counts(labelled=True)
assert len(ser) == 480
np.testing.assert_array_equal(ser.index, run.train_ids[1:])
assert len(ser) == 481
np.testing.assert_array_equal(ser.index, run.train_ids)

arr = lpd_m8.data_counts(labelled=False)
assert len(arr) == 481
Expand Down