Coverage for test/test_main.py: 100%
171 statements
« prev ^ index » next coverage.py v7.10.6, created at 2025-09-15 20:42 -0400
1import tempfile
2from dataclasses import dataclass, field
4import numpy as np
5import pandas as pd
6import pytest
7from pytest import fixture
9from peakipy.cli.main import (
10 get_vclist,
11 check_for_include_column_and_add_if_missing,
12 check_data_shape_is_consistent_with_dims,
13 select_specified_planes,
14 exclude_specified_planes,
15 remove_excluded_peaks,
16 warn_if_trying_to_fit_large_clusters,
17 unpack_xy_bounds,
18 validate_plane_selection,
19 validate_sample_count,
20 unpack_plotting_colors,
21 get_fit_data_for_selected_peak_clusters,
22)
25@fixture
26def actual_vclist():
27 with tempfile.TemporaryFile() as fp:
28 fp.write(b"1\n2\n3\n")
29 fp.seek(0)
30 vclist = np.genfromtxt(fp)
31 return vclist
34@dataclass
35class PeakipyData:
36 df: pd.DataFrame = field(default_factory=lambda: pd.DataFrame())
37 data: np.array = field(default_factory=lambda: np.zeros((4, 10, 20)))
38 dims: list = field(default_factory=lambda: [0, 1, 2])
39 pt_per_ppm_f2 = 10
40 pt_per_ppm_f1 = 20
43def test_get_vclist(actual_vclist):
44 expected_vclist = np.array([1.0, 2.0, 3.0])
45 np.testing.assert_array_equal(actual_vclist, expected_vclist)
48def test_get_vclist_none():
49 vclist = None
50 args = {}
51 args = get_vclist(vclist, args)
52 expected_args = dict(vclist=False)
53 assert args == expected_args
56def test_get_vclist_error():
57 vclist = "vclist"
58 args = {}
59 with pytest.raises(Exception):
60 get_vclist(vclist, args)
63def test_check_for_include_column():
64 peakipy_data = PeakipyData(pd.DataFrame())
65 peakipy_data = check_for_include_column_and_add_if_missing(peakipy_data)
66 assert "include" in peakipy_data.df.columns
69def test_select_specified_planes():
70 plane = None
71 expected_plane_numbers = np.arange(4)
72 actual_plane_numbers, peakipy_data = select_specified_planes(plane, PeakipyData())
73 np.testing.assert_array_equal(expected_plane_numbers, actual_plane_numbers)
76def test_select_specified_planes_2():
77 plane = [1, 2]
78 expected_plane_numbers = np.array([1, 2])
79 actual_plane_numbers, peakipy_data = select_specified_planes(plane, PeakipyData())
80 np.testing.assert_array_equal(expected_plane_numbers, actual_plane_numbers)
81 assert peakipy_data.data.shape == (2, 10, 20)
84def test_select_specified_planes_all_planes_excluded(capsys):
85 plane = [10]
86 with pytest.raises(SystemExit):
87 select_specified_planes(plane, PeakipyData())
88 captured = capsys.readouterr()
89 assert "" in captured.err
92def test_exclude_specified_planes():
93 plane = None
94 expected_plane_numbers = np.arange(4)
95 actual_plane_numbers, peakipy_data = exclude_specified_planes(plane, PeakipyData())
96 np.testing.assert_array_equal(expected_plane_numbers, actual_plane_numbers)
99def test_exclude_specified_planes_2():
100 plane = [1, 2]
101 expected_plane_numbers = np.array([0, 3])
102 actual_plane_numbers, peakipy_data = exclude_specified_planes(plane, PeakipyData())
103 np.testing.assert_array_equal(expected_plane_numbers, actual_plane_numbers)
104 assert peakipy_data.data.shape == (2, 10, 20)
107def test_exclude_specified_planes_all_planes_excluded(capsys):
108 plane = [0, 1, 2, 3]
109 with pytest.raises(SystemExit):
110 exclude_specified_planes(plane, PeakipyData())
111 captured = capsys.readouterr()
112 assert "" in captured.err
115def test_remove_excluded_peaks():
116 actual_dict = dict(
117 include=["yes", "yes", "no"],
118 peak=[1, 2, 3],
119 INDEX=[0, 1, 2],
120 ASS=["one", "two", "three"],
121 X_PPM=[1, 2, 3],
122 Y_PPM=[1, 2, 3],
123 CLUSTID=[1, 2, 3],
124 MEMCNT=[1, 1, 1],
125 )
126 expected_dict = {k: v[:-1] for k, v in actual_dict.items()}
127 actual_df = pd.DataFrame(actual_dict)
128 expected_df = pd.DataFrame(expected_dict)
129 peakipy_data = PeakipyData(df=actual_df)
130 pd.testing.assert_frame_equal(remove_excluded_peaks(peakipy_data).df, expected_df)
133def test_warn_if_trying_to_fit_large_clusters():
134 max_cluster_size = 7
135 df = pd.DataFrame(dict(MEMCNT=[1, 6], CLUSTID=[0, 1]))
136 peakipy_data = PeakipyData(df=df)
137 assert (
138 warn_if_trying_to_fit_large_clusters(max_cluster_size, peakipy_data)
139 == max_cluster_size
140 )
143def test_warn_if_trying_to_fit_large_clusters_none():
144 max_cluster_size = None
145 df = pd.DataFrame(dict(MEMCNT=[1, 12], CLUSTID=[0, 1]))
146 peakipy_data = PeakipyData(df=df)
147 assert warn_if_trying_to_fit_large_clusters(max_cluster_size, peakipy_data) == 12
150def test_unpack_xy_bounds_case_00():
151 xy_bounds = (0, 0)
152 result = unpack_xy_bounds(xy_bounds, PeakipyData())
153 assert result == None
156def test_unpack_xy_bounds_case_xy():
157 xy_bounds = (1, 2)
158 result = unpack_xy_bounds(xy_bounds, PeakipyData())
159 assert result == [10, 40]
162def test_unpack_xy_bounds_invalid_input():
163 with pytest.raises(TypeError):
164 unpack_xy_bounds(None, PeakipyData())
167class MockPseudo3D:
168 def __init__(self, n_planes):
169 self.n_planes = n_planes
172def test_empty_plane_selection():
173 pseudo3D = MockPseudo3D(n_planes=5)
174 assert validate_plane_selection([], pseudo3D) == [0, 1, 2, 3, 4]
177def test_plane_selection_none():
178 pseudo3D = MockPseudo3D(n_planes=5)
179 assert validate_plane_selection(None, pseudo3D) == [0, 1, 2, 3, 4]
182def test_valid_plane_selection():
183 pseudo3D = MockPseudo3D(n_planes=5)
184 assert validate_plane_selection([0, 1, 2], pseudo3D) == [0, 1, 2]
187def test_invalid_plane_selection_negative():
188 pseudo3D = MockPseudo3D(n_planes=5)
189 with pytest.raises(ValueError):
190 validate_plane_selection([-1], pseudo3D)
193def test_invalid_plane_selection_too_high():
194 pseudo3D = MockPseudo3D(n_planes=5)
195 with pytest.raises(ValueError):
196 validate_plane_selection([5], pseudo3D)
199def test_invalid_plane_selection_mix():
200 pseudo3D = MockPseudo3D(n_planes=5)
201 with pytest.raises(ValueError):
202 validate_plane_selection([-1, 3, 5], pseudo3D)
205def test_valid_sample_count():
206 assert validate_sample_count(10) == 10
209def test_invalid_sample_count_type():
210 with pytest.raises(TypeError):
211 validate_sample_count("10")
214def test_invalid_sample_count_float():
215 with pytest.raises(TypeError):
216 validate_sample_count(10.5)
219def test_invalid_sample_count_list():
220 with pytest.raises(TypeError):
221 validate_sample_count([10])
224def test_invalid_sample_count_dict():
225 with pytest.raises(TypeError):
226 validate_sample_count({"count": 10})
229def test_invalid_sample_count_none():
230 with pytest.raises(TypeError):
231 validate_sample_count(None)
234def test_valid_colors():
235 assert unpack_plotting_colors(("red", "black")) == ("red", "black")
238def test_default_colors():
239 assert unpack_plotting_colors(()) == ("green", "blue")
242def test_invalid_colors_type():
243 assert unpack_plotting_colors("red") == ("green", "blue")
246def test_invalid_colors_single():
247 assert unpack_plotting_colors(("red",)) == ("green", "blue")
250def test_invalid_colors_length():
251 assert unpack_plotting_colors(("red", "black", "green")) == ("green", "blue")
254def test_no_clusters():
255 fits = pd.DataFrame({"clustid": [1, 2, 3]})
256 assert get_fit_data_for_selected_peak_clusters(fits, None).equals(fits)
259def test_empty_clusters():
260 fits = pd.DataFrame({"clustid": [1, 2, 3]})
261 assert get_fit_data_for_selected_peak_clusters(fits, []).equals(fits)
264def test_valid_clusters():
265 fits = pd.DataFrame({"clustid": [1, 2, 3]})
266 selected_clusters = [1, 3]
267 expected_result = pd.DataFrame({"clustid": [1, 3]})
268 assert (
269 get_fit_data_for_selected_peak_clusters(fits, selected_clusters)
270 .reset_index(drop=True)
271 .equals(expected_result)
272 )
275def test_invalid_clusters():
276 fits = pd.DataFrame({"clustid": [1, 2, 3]})
277 with pytest.raises(SystemExit):
278 get_fit_data_for_selected_peak_clusters(fits, [4, 5, 6])
281def test_check_data_shape_is_consistent_with_dims():
282 peakipy_data = PeakipyData(data=np.zeros((4, 10)))
283 with pytest.raises(SystemExit):
284 check_data_shape_is_consistent_with_dims(peakipy_data)