Coverage for tcvx21/plotting/plot_comparison_1d_m.py: 94%

1""" 

2Plotting routines for 1D observables 

3""" 

4import matplotlib.pyplot as plt 

5import tcvx21 

6plt.style.use(tcvx21.style_sheet) 

7 

8from tcvx21.quant_validation.ricci_metric_m import calculate_normalised_ricci_distance_from_observables 

9from tcvx21.plotting.labels_m import add_twinx_label, add_x_zero_line, add_y_zero_line, make_labels, format_yaxis 

10 

11from tcvx21.quant_validation.latex_table_writer_m import observable_latex 

12 

13 

14def plot_1D_comparison(field_direction, diagnostic, observable, 

15 experimental_data, simulation_data, **kwargs): 

16 """ 

17 Plots a 1D (line data) observable, with different values represented via a constant color 

18 """ 

19 fig, ax = plt.subplots() 

20 

21 add_x_zero_line(ax) 

22 add_y_zero_line(ax) 

23 

24 if 'kurtosis' in observable: 

25 add_y_zero_line(ax, level=3.0) 

26 

27 reference = experimental_data[field_direction].get_observable(diagnostic, observable) 

28 reference_available = not(reference.is_empty) 

29 if reference_available: 

30 reference.plot(ax, **kwargs) 

31 else: 

32 # Use one of the simulations as the "reference" to access the properties 

33 reference = list(simulation_data.values())[0][field_direction]\ 

34 .get_observable(diagnostic, observable) 

35 

36 field_direction_string, diagnostic_string, observable_string = \ 

37 make_labels(field_direction, diagnostic, reference) 

38 

39 add_twinx_label(ax, field_direction_string) 

40 

41 ax.set_title(f"{diagnostic_string}: {observable_string}") 

42 

43 for case in simulation_data.values(): 

44 

45 simulation = case[field_direction].get_observable(diagnostic, observable) 

46 if simulation.is_empty: 

47 continue 

48 

49 line = simulation.plot(ax, trim_to_x=reference.xlim, **kwargs) 

50 if reference_available: 

51 d = calculate_normalised_ricci_distance_from_observables(simulation=simulation, experiment=reference) 

52 line.set_label(f"{line.get_label()}: d={d:3.2f}") 

53 else: 

54 line.set_label(f"{line.get_label()}") 

55 

56 # Set the ylim to show all data 

57 ax.set_ylim(*reference.ylims_in_trim( 

58 [case[field_direction].get_observable(diagnostic, observable) for case in simulation_data.values() if not case[field_direction].is_empty], 

59 trim_to_x=reference.xlim)) 

60 

61 # Apply custom limits if they are defined 

62 reference.apply_plot_limits(ax) 

63 plt.draw() 

64 format_yaxis(ax) 

65 

66 plt.legend() 

67 

68 return fig, ax