sup3r.preprocessing.utilities

Methods used across container objects.

Functions

check_signatures(objs[, skip_params])	Make sure signatures of objects can be parsed for required arguments.
composite_info(objs[, skip_params])	Get composite signature and doc string for given set of objects.
composite_sig(docs)	Get composite signature from command documentation instance.
compute_if_dask(arr)	Apply compute method to input if it consists of a dask array or slice with dask elements.
contains_ellipsis(vals)	Check if vals contain an ellipse.
dims_array_tuple(arr)	Return a tuple of (dims, array) with dims equal to the ordered slice of Dimension.order() with the same len as arr.shape.
expand_paths(fps)	Expand path(s)
get_class_kwargs(obj, kwargs)	Get kwargs which match obj signature.
get_date_range_kwargs(time_index)	Get kwargs for pd.date_range from a DatetimeIndex.
get_input_handler_class([input_handler_name])	Get the DataHandler or Rasterizer object.
get_obj_params(obj)	Get available signature parameters for obj and obj bases
get_source_type(file_paths)	Get data source type
is_type_of(vals, vtype)	Check if vals is an instance of type or group of that type.
log_args(func)	Decorator to log annotations and args.
lower_names(data)	Set all fields / coords / dims to lower case.
lowered(features)	Return a lower case version of the given str or list of strings.
make_time_index_from_kws(date_range_kwargs)	Function to make a pandas DatetimeIndex from the get_date_range_kwargs outputs
numpy_if_tensor(arr)	Cast array to numpy array if it is a tensor.
ordered_array(data)	Transpose arrays so they have a (space, time, ...) or (space, time, ..., feature) ordering.
ordered_dims(dims)	Return the order of dims that follows the ordering of Dimension.order() for the common dim names.
parse_ellipsis(vals, dim_num)	Replace ellipsis with N slices where N is dim_num - len(vals) + 1
parse_features([features, data])	Parse possible inputs for features (list, str, None, 'all').
parse_keys(keys[, default_coords, ...])	Return set of features and slices for all dimensions contained in dataset that can be passed to isel and transposed to standard dimension order.
parse_to_list([features, data])	Parse features and return as a list, even if features is a string.