Coverage for tests / tests_references / test_spherical_heart.py: 100%

1# SPDX-FileCopyrightText: Copyright INRIA 

2# 

3# SPDX-License-Identifier: LGPL-3.0-only 

4# 

5# Copyright INRIA 

6# 

7# This file is part of PhysioBlocks, a library mostly developed by the 

8# [Ananke project-team](https://team.inria.fr/ananke) at INRIA. 

9# 

10# Authors: 

11# - Colin Drieu 

12# - Dominique Chapelle 

13# - François Kimmig 

14# - Philippe Moireau 

15# 

16# PhysioBlocks is free software: you can redistribute it and/or modify it under the 

17# terms of the GNU Lesser General Public License as published by the Free Software 

18# Foundation, version 3 of the License. 

19# 

20# PhysioBlocks is distributed in the hope that it will be useful, but WITHOUT ANY 

21# WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A 

22# PARTICULAR PURPOSE. See the GNU Lesser General Public License for more details. 

23# 

24# You should have received a copy of the GNU Lesser General Public License along with 

25# PhysioBlocks. If not, see <https://www.gnu.org/licenses/>. 

26 

27import logging 

28from copy import copy 

29 

30import pandas as pd 

31 

32from physioblocks.configuration.aliases import unwrap_aliases 

33from physioblocks.configuration.functions import load 

34from physioblocks.io.configuration import read_json 

35from physioblocks.simulation.runtime import ForwardSimulation 

36from physioblocks.simulation.time_manager import TIME_QUANTITY_ID 

37from physioblocks.utils.gradient_test_utils import gradient_test_from_file 

38 

39from .io import read_reference, results_close_to_data 

40 

41_logger = logging.getLogger() 

42spherical_heart_gradient_path = ( 

43 "tests/tests_references/spherical_heart/spherical_heart_sim_gradient_test.json" 

44) 

45 

46spherical_heart_path = "references/spherical_heart_sim.jsonc" 

47spherical_heart_reference_path = ( 

48 "tests/tests_references/spherical_heart/ref_spherical_heart_sim.csv" 

49) 

50 

51spherical_heart_respiration_path = "references/spherical_heart_respiration_sim.jsonc" 

52spherical_heart_respiration_reference_path = ( 

53 "tests/tests_references/spherical_heart/ref_spherical_heart_respiration_sim.csv" 

54) 

55 

56 

57def test_spherical_heart_gradient(): 

58 assert gradient_test_from_file(spherical_heart_gradient_path) 

59 

60 

61def test_spherical_heart_ref(): 

62 sim_config = read_json(spherical_heart_path) 

63 sim_config = unwrap_aliases(sim_config) 

64 sim: ForwardSimulation = load(sim_config) 

65 sim.time_manager.duration = 5.0 # Shorten simulation time to avoid test too long 

66 results = sim.run() 

67 

68 ref_df = read_reference(spherical_heart_reference_path) 

69 ref_df = ref_df.set_index(TIME_QUANTITY_ID) 

70 

71 matching_ids = {data_id: data_id for data_id in results[0] if data_id != "time"} 

72 

73 tol_factors = copy(sim.magnitudes) 

74 tol_factors["cavity.volume"] = 1.0e-3 

75 tol_factors["atrial.blood_pressure"] = 1.0e2 

76 tol_factors["active_law.activation"] = 1.0 

77 

78 results_df = pd.DataFrame(results) 

79 results_df = results_df.set_index(TIME_QUANTITY_ID) 

80 

81 assert results_close_to_data( 

82 results_df, 

83 ref_df, 

84 matching_ids, 

85 1e-9, 

86 tol_factors, 

87 (sim.time_manager.start, sim.time_manager.start + sim.time_manager.duration), 

88 ) 

89 

90 

91def test_spherical_heart_respiration_ref(): 

92 sim_config = read_json(spherical_heart_respiration_path) 

93 sim_config = unwrap_aliases(sim_config) 

94 # Shorten simulation time to avoid test too long 

95 sim: ForwardSimulation = load(sim_config) 

96 sim.time_manager.duration = 5.0 

97 results = sim.run() 

98 

99 ref_df = read_reference(spherical_heart_respiration_reference_path) 

100 ref_df = ref_df.set_index(TIME_QUANTITY_ID) 

101 

102 matching_ids = {data_id: data_id for data_id in results[0] if data_id != "time"} 

103 tol_factors = copy(sim.magnitudes) 

104 tol_factors["cavity.volume"] = 1.0e-3 

105 tol_factors["atrial.blood_pressure"] = 1.0e2 

106 tol_factors["active_law.activation"] = 1.0 

107 tol_factors["pleural.pressure"] = 1.0e2 

108 

109 results_df = pd.DataFrame(results) 

110 results_df = results_df.set_index(TIME_QUANTITY_ID) 

111 assert results_close_to_data( 

112 results_df, 

113 ref_df, 

114 matching_ids, 

115 1e-9, 

116 tol_factors, 

117 (sim.time_manager.start, sim.time_manager.start + sim.time_manager.duration), 

118 )