test_suite.plots package

Submodules

test_suite.plots.data_plotting module

test_suite.plots.data_plotting.plot_all_slices_distribution(df, feature)[source]

Function for plotting the distribution of the features for all slices.

Parameters:feature (string) – name of the feature that should be plotted.
test_suite.plots.data_plotting.plot_boxplots(feature_in, unit='-', f_name='')[source]

Method for plotting of the boxplot of feature.

Parameters:
  • feature_in (pd.Series) –
  • unit (string) –
  • f_name (string) –
test_suite.plots.data_plotting.plot_boxplots_week(EN=True)[source]

Method for comparison of the distribution of the traveltime during weekend and non-weekend days.

Parameters:EN (boolean) – if the labels should be in English or not (Slovak otherwise).
test_suite.plots.data_plotting.plot_clusters(estimated_labels, train_X, train_Y, save=False)[source]

Method for plotting of the clustered data (clustered ndim features).

Parameters:
  • estimated_labels (numpy.ndarray) –
  • train_X (pandas.DataFrame) –
  • train_Y (pandas.DataFrame) –
  • save (boolean) –
test_suite.plots.data_plotting.plot_correlation(X, Y)[source]

Function for plotting of the correlation matrix of the features & referential traveltimes.

Parameters:
  • X (pd.DataFrame) – matrix of features
  • Y (pd.DataFrame) – vector of referential traveltimes
test_suite.plots.data_plotting.plot_distribution(feature)[source]

Method for plotting of the distribution of the feature.

Parameters:feature (pandas.Series) –
test_suite.plots.data_plotting.plot_multiple_days(file, images, use_subplots=False, EN=True)[source]

Function for plotting referential traveltimes for all days of the week.

Parameters:
  • file (string) – path to the referential traveltimes pickled DataFrame
  • images (string) – how the created images should be named
  • use_subplots (boolean) – if subplots should be used (otherwise all series will be plotted into one plot)
  • EN (boolean) – if the labels should be in English or not (otherwise Slovak)
test_suite.plots.data_plotting.plot_multiple_predictions(list_of_tuples, EN=True)[source]

Function for plotting of the comparison of predictions produced by various models.

Parameters:
  • list_of_tuples (list) – pd.DataFrames(columns=[‘test_time’, ‘real’, ‘bck’, ‘est’])
  • EN (boolean) – if the labels should be in English.
test_suite.plots.data_plotting.plot_output_comparison(df, EN=True)[source]

Function, similar as the function ‘plot_multiple_predictions’, however only for plotting ‘bck’ & ‘ref’ comparison.

Parameters:
  • df (pd.DataFrame) – DataFrame with columns - ‘bck’, ‘ref’ ‘test_time’
  • EN (boolean) – if the labels should be in English (False=Slovak)
test_suite.plots.data_plotting.plot_time_clusters(X, Y, time)[source]

Function for plotting of the distribution of the features with respect to the time of day.

Parameters:
  • X (pd.DataFrame) – features matrix
  • Y (pd.DataFrame) – vector of referential traveltimes values
  • time (pd.DataFrame) – timestamps of data

Module contents