def label_peaks_parsimonious(peaks, known_emission_lines, delta):
'''
Out of all the peaks that are within +/-delta of at least one
known emission line, find a minimal set of elements
(via unweighted greedy set cover) that "explains" all such peaks
'''
known_emission_lines = known_emission_lines.sort_values(by="wav_mars")
peaks = sorted(peaks)
elts_to_peak_indices = defaultdict(set)
for row_index, row in known_emission_lines.iterrows():
elt = row["elt"]
i_lo, i_hi = nearby_peaks(peaks, row["wav_mars"], delta = delta)
for i in xrange(i_lo, i_hi):
elts_to_peak_indices[elt].add(i)
sets = []
elts = sorted(list(np.unique(known_emission_lines["elt"])))
for elt in elts:
sets.append(list(elts_to_peak_indices[elt]))
best_cover = set_cover_approx_fast(sets)
cover_elts_to_peaks = OrderedDict()
cover_peaks_to_elts = OrderedDict()
unlabeled = set(peaks)
for i in best_cover:
elt = elts[i]
for peak_index in elts_to_peak_indices[elt]:
peak = peaks[peak_index]
if elt not in cover_elts_to_peaks:
cover_elts_to_peaks[elt] = []
cover_elts_to_peaks[elt].append(peak)
if peak not in cover_peaks_to_elts:
cover_peaks_to_elts[peak] = []
cover_peaks_to_elts[peak].append(elt)
unlabeled -= set([peak])
return cover_elts_to_peaks, cover_peaks_to_elts, sorted(list(unlabeled))
def test_set_cover_approx_fast():
result = set_cover_approx_fast(example_sets)
assert result == [4, 3, 2]
result = set_cover_approx_fast([[30], [20,30], [10]])
assert result == [1, 2]
