Coverage for addmo/s5_insights/model_plots/time_series.py: 94%

1import pandas as pd 

2import matplotlib.dates as mdates 

3import matplotlib.pyplot as plt 

4from addmo.util import plotting_utils as d 

5from addmo.util.load_save import load_data 

6 

7 

8def plot_timeseries_combined(config,data): 

9 """ 

10 Returns: 

11 - Full time range defined in config. 

12 - First 2-week window (if the data spans more than 21 days). 

13 

14 Returns one or two matplotlib figures. 

15 """ 

16 

17 # Get date range from config (if it exists): 

18 if hasattr(config,'start_train_val') and hasattr(config, 'end_test'): 

19 start_date = pd.to_datetime(config.get('start_train_val', data.index.min())) 

20 end_date = pd.to_datetime(config.get('end_test', data.index.max())) 

21 data = data[(data.index >= start_date) & (data.index <= end_date)] 

22 

23 # Check data duration 

24 if not pd.api.types.is_datetime64_any_dtype(data.index): 

25 data.index = pd.to_datetime(data.index) 

26 duration_days = (data.index.max() - data.index.min()).days 

27 columns_to_plot = data.columns.tolist() 

28 

29 fig_height = max(5, len(columns_to_plot) * 2.5) 

30 fig_full, axes_full = plt.subplots(len(columns_to_plot), 1, 

31 figsize=(d.cm2inch(15.5), d.cm2inch(fig_height)), 

32 sharex=True, gridspec_kw={'wspace': 0, 'hspace': 0.08}) 

33 plt.subplots_adjust(left=0.12, right=0.97, bottom=0.1, top=0.97) 

34 

35 for ax, column in zip(axes_full, columns_to_plot): 

36 color = d.red if column == config['name_of_target'] else d.black 

37 ax.plot(data.index, data[column], color=color, linewidth=0.75, 

38 label='Target' if column == config['name_of_target'] else None) 

39 if column == config['name_of_target']: 

40 ax.legend(loc='upper right', fontsize=7) 

41 

42 ax.set_ylabel(column.replace(' ', '\n').replace('__', '\n'), fontsize=7, labelpad=-1.1) 

43 ax.grid() 

44 plt.setp(ax.get_yticklabels(), fontsize=7) 

45 

46 axes_full[-1].set_xlabel("Time", fontsize=7) 

47 axes_full[-1].xaxis.set_major_formatter(mdates.DateFormatter('%m-%d\n%H:%M')) 

48 plt.setp(axes_full[-1].xaxis.get_majorticklabels(), rotation=0, ha="center", fontsize=7) 

49 fig_full.align_labels() 

50 

51 figures = [fig_full] 

52 

53 if duration_days > 10: 

54 window_start = data.index.min() 

55 window_end = window_start + pd.Timedelta(days=5) 

56 data_2weeks = data[(data.index >= window_start) & (data.index < window_end)] 

57 

58 fig_height_2w = max(5, len(columns_to_plot) * 2.5) 

59 fig_2weeks, axes_2weeks = plt.subplots(len(columns_to_plot), 1, 

60 figsize=(d.cm2inch(15.5), d.cm2inch(fig_height_2w)), 

61 sharex=True, gridspec_kw={'wspace': 0, 'hspace': 0.08}) 

62 plt.subplots_adjust(left=0.12, right=0.97, bottom=0.1, top=0.97) 

63 

64 for ax, column in zip(axes_2weeks, columns_to_plot): 

65 color = d.red if column == config['name_of_target'] else d.black 

66 ax.plot(data_2weeks.index, data_2weeks[column], color=color, linewidth=0.75, 

67 label='Target' if column == config['name_of_target'] else None) 

68 if column == config['name_of_target']: 

69 ax.legend(loc='upper right', fontsize=7) 

70 

71 ax.set_ylabel(column.replace(' ', '\n').replace('__', '\n'), fontsize=7, labelpad=-1.1) 

72 ax.grid() 

73 plt.setp(ax.get_yticklabels(), fontsize=7) 

74 

75 axes_2weeks[-1].set_xlabel("Time", fontsize=7) 

76 axes_2weeks[-1].xaxis.set_major_formatter(mdates.DateFormatter('%m-%d\n%H:%M')) 

77 plt.setp(axes_2weeks[-1].xaxis.get_majorticklabels(), rotation=0, ha="center", fontsize=7) 

78 fig_2weeks.align_labels() 

79 

80 figures.append(fig_2weeks) 

81 

82 return figures 

83