Coverage for steam_pysigma\postprocessing\postprocessing.py: 97%

1# STEAM PySigma is a python wrapper of STEAM-SIGMA written in Java. 

2# Copyright (C) 2023, CERN, Switzerland. All rights reserved. 

3# 

4# This program is free software: you can redistribute it and/or modify 

5# it under the terms of the GNU General Public License as published by 

6# the Free Software Foundation, version 3 of the License. 

7# 

8# This program is distributed in the hope that it will be useful, 

9# but WITHOUT ANY WARRANTY; without even the implied warranty of 

10# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the 

11# GNU General Public License for more details. 

12# 

13# You should have received a copy of the GNU General Public License 

14# along with this program. If not, see <https://www.gnu.org/licenses/>. 

15 

16import pandas as pd 

17 

18 

19def export_B_field_txt_to_map2d(path_map2d_roxie, path_result_txt_Bx, path_result_txt_By, path_new_file): 

20 """ 

21 Copy content of reference map2d file and overwrites Bx and By values which are replaced values from 

22 comsol output txt file and writes to a new map2d file. 

23 :param path_map2d_roxie: Path to reference map2d from which all values apart from Bx and By is copied from 

24 :param path_result_txt_Bx: Comsol output txt file with evaluated B-field x component 

25 :param path_result_txt_By: Comsol output txt file with evaluated B-field y component 

26 :param path_new_file: Path to new map2d file where new B-field is stored 

27 :return: 

28 """ 

29 df_reference = pd.read_csv(path_map2d_roxie, delim_whitespace=True) 

30 with open(path_result_txt_Bx) as file: # opens a text file 

31 lines = [line.strip().split() for line in file if not "%" in line] # loops over each line 

32 

33 df_txt_Bx = pd.DataFrame(lines, columns=["x", "y", "Bx"]) 

34 

35 df_txt_Bx = df_txt_Bx.apply(pd.to_numeric) 

36 

37 with open(path_result_txt_By) as file: # opens a text file 

38 lines = [line.strip().split() for line in file if not "%" in line] # loops over each line 

39 

40 df_txt_By = pd.DataFrame(lines, columns=["x", "y", "By"]) 

41 df_txt_By = df_txt_By.apply(pd.to_numeric) 

42 

43 # Verify all evaluate field at same coordinates! 

44 

45 x_tol, y_tol = 1e-10, 1e-10 

46 x_ref, y_ref = df_reference['X-POS/MM'] / 1000, df_reference['Y-POS/MM'] / 1000 

47 

48 if ((x_ref - df_txt_Bx['x']).abs().max() < x_tol) and \ 

49 ((x_ref - df_txt_By['x']).abs().max() < x_tol) and \ 

50 ((y_ref - df_txt_Bx['y']).abs().max() < y_tol) and \ 

51 ((y_ref - df_txt_By['y']).abs().max() < y_tol): 

52 print("All dataframes have the same x and y coordinates.") 

53 else: 

54 raise ValueError("Error: Not all dataframes have the same x and y coordinates. Can't compare map2ds!") 

55 

56 # Create new map2d 

57 with open(path_new_file, 'w') as file: 

58 file.write(" BL. COND. NO. X-POS/MM Y-POS/MM BX/T BY/T" 

59 " AREA/MM**2 CURRENT FILL FAC.\n\n") 

60 content = [] 

61 for index, row in df_reference.iterrows(): 

62 bl, cond, no, x, y, Bx, By, area, curr, fill, fac = row 

63 bl = int(bl) 

64 cond = int(cond) 

65 no = int(no) 

66 x = f"{x:.4f}" 

67 y = f"{y:.4f}" 

68 Bx = df_txt_Bx["Bx"].iloc[index] 

69 Bx = f"{Bx:.4f}" 

70 By = df_txt_By["By"].iloc[index] 

71 By = f"{By:.4f}" 

72 area = f"{area:.4f}" 

73 curr = f"{curr:.2f}" 

74 fill = f"{fill:.4f}" 

75 content.append( 

76 "{0:>6}{1:>6}{2:>7}{3:>13}{4:>13}{5:>11}{6:>11}{7:>11}{8:>9}{9:>8}\n".format(bl, cond, no, x, y, Bx, 

77 By, 

78 area, curr, fill)) 

79 file.writelines(content)