class_docstr: Module divides a histogram along first axis encountered, eg. time.
  
  For example, split histogram time:x:y along time axis.
  This will produce a data-frame summarizing the split information,
  where time is the index and each row is a x:y histogram.
docstr: Initialize an instance.
  
  :param str read_key: key of input histogram-dict to read from data store
  :param str store_key: key of output data to store in data store
  :param list features: features of histograms to pick up from input data (optional)
  :param list ignore_features: ignore list of features to compare with reference, if present (optional)
  :param str feature_begins_with: require feature to begin with a given string (optional)
  :param bool project_on_axes: histogram time:x:y will also be divided along x and y. default is true.
  :param bool flatten_output: if true, flatten_output instead of add histogram-dict.
  :param bool short_keys: if true, use short descriptive dict keys in storage dict.
  :param list var_timestamp: list of variables that are converted timestamps (in ns since 1970).
  :param str index_col: key for index in split dictionary. default is 'date'
  :param str hist_col: key in output dict that contains the histogram. default is 'histogram'
  :param bool filter_empty_split_hists: filter out empty sub-histograms after splitting. default is True.
code: def __init__(
      self,
      read_key,
      store_key,
      features=None,
      ignore_features=None,
      feature_begins_with: str = "",
      project_on_axes: bool = True,
      flatten_output: bool = False,
      short_keys: bool = True,
      var_timestamp=None,
      index_col: str = "date",
      hist_col: str = "histogram",
      filter_empty_split_hists: bool = True,
  ) -> None:
      """Initialize an instance.
  
      :param str read_key: key of input histogram-dict to read from data store
      :param str store_key: key of output data to store in data store
      :param list features: features of histograms to pick up from input data (optional)
      :param list ignore_features: ignore list of features to compare with reference, if present (optional)
      :param str feature_begins_with: require feature to begin with a given string (optional)
      :param bool project_on_axes: histogram time:x:y will also be divided along x and y. default is true.
      :param bool flatten_output: if true, flatten_output instead of add histogram-dict.
      :param bool short_keys: if true, use short descriptive dict keys in storage dict.
      :param list var_timestamp: list of variables that are converted timestamps (in ns since 1970).
      :param str index_col: key for index in split dictionary. default is 'date'
      :param str hist_col: key in output dict that contains the histogram. default is 'histogram'
      :param bool filter_empty_split_hists: filter out empty sub-histograms after splitting. default is True.
      """
      super().__init__()
      self.read_key = read_key
      self.store_key = store_key
  
      self.features = features or []
      self.ignore_features = ignore_features or []
      self.feature_begins_with = feature_begins_with
      self.project_on_axes = project_on_axes
      self.flatten_output = flatten_output
      self.short_keys = short_keys
      self.var_timestamp = var_timestamp or []
      self.index_col = index_col
      self.hist_col = hist_col
      self.filter_empty_split_hists = filter_empty_split_hists
  
      if self.flatten_output and self.short_keys:
          raise ValueError(
              "flatten_output requires short_keys attribute to be False."
          )
  
file_path: popmon/popmon/hist/hist_splitter.py
imports: import pandas
  from popmon.base import Module
  from popmon.hist.hist_utils import get_histogram, is_timestamp, split_hist_along_first_dimension
label_desc: Use image node_id 1 to create a new HistSplitter object from inherited base classes: Module with example: obj = HistSplitter(read_key, store_key, features, ignore_features, feature_begins_with, project_on_axes, flatten_output, short_keys, var_timestamp, index_col, hist_col, filter_empty_split_hists)