def __init__()

in src/lookoutequipment/plot.py [0:0]

• 39 lines of code
• 4 McCabe index (conditional complexity)

    def __init__(self, 
                 timeseries_df, 
                 data_format, 
                 timestamp_col=None, 
                 tag_col=None,
                 resample=None,
                 verbose=False,
                 ):
        """
        Create a new instance to plot time series with different data structure
        
        Parameters:
            timeseries_df (pandas.DataFrame):
                A dataframe containing time series data that you want to plot
            data_format (string):
                Use "timeseries" if your dataframe has three columns:
                ``timestamp``, ``values`` and ``tagname``. Use "tabular" if
                ``timestamp`` is your first column and all the other tags are
                in the following columns: ``timestamp``, ``tag1``, ``tag2``...
            timestamp_col (string):
                Specifies the name of the columns that contains the 
                timestamps. If set to None, it means the timestamp is already
                an index (default to None)
            tag_col (string):
                If data_format is "timeseries", this argument specifies what
                is the name of the columns that contains the name of the tags
            resample (string):
                If specified, this class will resample the data before plotting
                them. Use the same format than the string rule as used in the
                ``pandas.DataFrame.resample()`` method (default to None)
            verbose (boolean):
                If True, this class will print some messages along the way
                (defaults to False)
        """
        self._data = timeseries_df
        self._format = data_format
        self._timestamp_col = timestamp_col
        self._tag_col = tag_col
        self._tags_list = None
        self._signals_to_plot = []
        self._signals_data = []
        self._tag_split = None
        self._split_labels = []
        self._start_date = None
        self._end_date = None
        self._labels_df = None
        self._predictions_ranges = None
        self._predictions_df = []
        self._predictions_title = []
        self._rolling_average = False
        self._rolling_average_window = None
        self._legend_format = {
            'loc': 'upper right',
            'framealpha': 0.5
        }

        self.verbose = verbose
        self.resample = resample

        # Prepare the figures:
        self.fig_height = 4
        self.height_ratios = []
        self.nb_plots = 0
        self.expanded_results = None
        
        if self._format not in ['timeseries', 'tabular']:
            raise Exception('`data_format` can only either be timeseries or tabular')
        
        if (self._format == 'timeseries') and (self._tag_col is None):
            raise Exception('`tag_col` must be defined when data format is timeseries')