merging module¶

Functions for merging arrays.

merge_func_config HybridConfig¶

Config for merging functions.

HybridConfig(
    concat=<function concat_merge at 0x132543ec0>,
    row_stack=<function row_stack_merge at 0x132543f60>,
    column_stack=<function column_stack_merge at 0x132574040>,
    reset_column_stack=functools.partial(<function column_stack_merge at 0x132574040>, reset_index=True),
    from_start_column_stack=functools.partial(<function column_stack_merge at 0x132574040>, reset_index='from_start'),
    from_end_column_stack=functools.partial(<function column_stack_merge at 0x132574040>, reset_index='from_end'),
    imageio=<function imageio_merge at 0x1325740e0>
)

column_stack_arrays function¶

column_stack_arrays(
    *arrs,
    expand_axis=1
)

Stack arrays along columns.

column_stack_merge function¶

column_stack_merge(
    *objs,
    reset_index=None,
    fill_value=nan,
    keys=None,
    filter_results=True,
    raise_no_results=True,
    wrap=None,
    wrapper=None,
    wrap_kwargs=None,
    clean_index_kwargs=None,
    **kwargs
)

Merge multiple array-like or Wrapping objects through column stacking.

Supports a sequence of tuples.

Argument wrap supports the following options:

• None: will become True if wrapper, keys, or wrap_kwargs are not None
• True: each array will be wrapped with Pandas Series/DataFrame (depending on dimensions)
• 'sr', 'series': each array will be wrapped with Pandas Series
• 'df', 'frame', 'dataframe': each array will be wrapped with Pandas DataFrame

Without wrapping, arrays will be kept as-is and merged using column_stack_arrays(). Argument wrap_kwargs can be a dictionary or a list of dictionaries.

If wrapper is provided, will use ArrayWrapper.wrap().

Keyword arguments **kwargs are passed to pd.concat and Wrapping.column_stack() only.

Argument reset_index supports the following options:

• False or None: Keep original index of each object
• True or 'from_start': Reset index of each object and align them at start
• 'from_end': Reset index of each object and align them at end

Options above work on Pandas, NumPy, and Wrapping instances.

concat_arrays function¶

concat_arrays(
    *arrs
)

Concatenate arrays.

concat_merge function¶

concat_merge(
    *objs,
    keys=None,
    filter_results=True,
    raise_no_results=True,
    wrap=None,
    wrapper=None,
    wrap_kwargs=None,
    clean_index_kwargs=None,
    **kwargs
)

Merge multiple array-like objects through concatenation.

Supports a sequence of tuples.

If wrap is None, it will become True if wrapper, keys, or wrap_kwargs are not None. If wrap is True, each array will be wrapped with Pandas Series and merged using pd.concat. Otherwise, arrays will be kept as-is and merged using concat_arrays(). wrap_kwargs can be a dictionary or a list of dictionaries.

If wrapper is provided, will use ArrayWrapper.wrap_reduced().

Keyword arguments **kwargs are passed to pd.concat only.

imageio_merge function¶

imageio_merge(
    *objs,
    keys=None,
    filter_results=True,
    raise_no_results=True,
    to_image_kwargs=None,
    imread_kwargs=None,
    **imwrite_kwargs
)

Merge multiple figure-like objects by writing them with imageio.

Keyword arguments to_image_kwargs are passed to plotly.graph_objects.Figure.to_image. Keyword arguments imread_kwargs and **imwrite_kwargs are passed to imageio.imread and imageio.imwrite respectively.

Keys are not used in any way.

is_merge_func_from_config function¶

is_merge_func_from_config(
    merge_func
)

Return whether the merging function can be found in merge_func_config.

mixed_merge function¶

mixed_merge(
    *objs,
    merge_funcs=None,
    mixed_kwargs=None,
    **kwargs
)

Merge objects of mixed types.

resolve_merge_func function¶

resolve_merge_func(
    merge_func
)

Resolve a merging function into a callable.

If a string, looks up into merge_func_config. If a sequence, uses mixed_merge() with merge_funcs=merge_func. If an instance of MergeFunc, calls MergeFunc.resolve_merge_func() to get the actual callable.

row_stack_arrays function¶

row_stack_arrays(
    *arrs,
    expand_axis=1
)

Stack arrays along rows.

row_stack_merge function¶

row_stack_merge(
    *objs,
    keys=None,
    filter_results=True,
    raise_no_results=True,
    wrap=None,
    wrapper=None,
    wrap_kwargs=None,
    clean_index_kwargs=None,
    **kwargs
)

Merge multiple array-like or Wrapping objects through row stacking.

Supports a sequence of tuples.

Argument wrap supports the following options:

• None: will become True if wrapper, keys, or wrap_kwargs are not None
• True: each array will be wrapped with Pandas Series/DataFrame (depending on dimensions)
• 'sr', 'series': each array will be wrapped with Pandas Series
• 'df', 'frame', 'dataframe': each array will be wrapped with Pandas DataFrame

Without wrapping, arrays will be kept as-is and merged using row_stack_arrays(). Argument wrap_kwargs can be a dictionary or a list of dictionaries.

If wrapper is provided, will use ArrayWrapper.wrap().

Keyword arguments **kwargs are passed to pd.concat and Wrapping.row_stack() only.