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#
meanlb module

Module with MEANLB.

## MEANLB class

    MEANLB(
        wrapper,
        input_list,
        input_mapper,
        in_output_list,
        output_list,
        param_list,
        mapper_list,
        short_name,
        level_names
    )

Label generator based on mean_labels_nb().

Superclasses

- Analyzable
- AttrResolverMixin
- Cacheable
- Chainable
- Comparable
- Configured
- ExtPandasIndexer
- HasSettings
- IndexingBase
- IndicatorBase
- PandasIndexer
- Pickleable
- PlotsBuilderMixin
- Prettified
- StatsBuilderMixin
- Wrapping
- `vectorbtpro.labels.generators.meanlb.ParamIndexer`

Inherited members

- AttrResolverMixin.deep_getattr()
- AttrResolverMixin.post_resolve_attr()
- AttrResolverMixin.pre_resolve_attr()
- AttrResolverMixin.resolve_attr()
- AttrResolverMixin.resolve_shortcut_attr()
- Cacheable.get_ca_setup()
- Chainable.pipe()
- Configured.copy()
- Configured.equals()
- Configured.get_writeable_attrs()
- Configured.prettify()
- Configured.replace()
- Configured.resolve_merge_kwargs()
- Configured.update_config()
- HasSettings.get_path_setting()
- HasSettings.get_path_settings()
- HasSettings.get_setting()
- HasSettings.get_settings()
- HasSettings.has_path_setting()
- HasSettings.has_path_settings()
- HasSettings.has_setting()
- HasSettings.has_settings()
- HasSettings.reset_settings()
- HasSettings.resolve_setting()
- HasSettings.resolve_settings_paths()
- HasSettings.set_settings()
- IndexingBase.indexing_setter_func()
- IndicatorBase.cls_dir
- IndicatorBase.column_only_select
- IndicatorBase.column_stack()
- IndicatorBase.config
- IndicatorBase.dropna()
- IndicatorBase.group_select
- IndicatorBase.iloc
- IndicatorBase.in_output_names
- IndicatorBase.indexing_func()
- IndicatorBase.indexing_kwargs
- IndicatorBase.input_names
- IndicatorBase.lazy_output_names
- IndicatorBase.level_names
- IndicatorBase.loc
- IndicatorBase.output_flags
- IndicatorBase.output_names
- IndicatorBase.param_names
- IndicatorBase.plots_defaults
- IndicatorBase.range_only_select
- IndicatorBase.rec_state
- IndicatorBase.row_stack()
- IndicatorBase.run_pipeline()
- IndicatorBase.self_aliases
- IndicatorBase.short_name
- IndicatorBase.stats_defaults
- IndicatorBase.to_dict()
- IndicatorBase.to_frame()
- IndicatorBase.unpack()
- IndicatorBase.wrapper
- IndicatorBase.xloc
- PandasIndexer.xs()
- Pickleable.decode_config()
- Pickleable.decode_config_node()
- Pickleable.dumps()
- Pickleable.encode_config()
- Pickleable.encode_config_node()
- Pickleable.file_exists()
- Pickleable.getsize()
- Pickleable.load()
- Pickleable.loads()
- Pickleable.modify_state()
- Pickleable.resolve_file_path()
- Pickleable.save()
- PlotsBuilderMixin.build_subplots_doc()
- PlotsBuilderMixin.override_subplots_doc()
- PlotsBuilderMixin.plots()
- StatsBuilderMixin.build_metrics_doc()
- StatsBuilderMixin.override_metrics_doc()
- StatsBuilderMixin.stats()
- Wrapping.regroup()
- Wrapping.resample()
- Wrapping.resolve_column_stack_kwargs()
- Wrapping.resolve_row_stack_kwargs()
- Wrapping.resolve_self()
- Wrapping.resolve_stack_kwargs()
- Wrapping.select_col()
- Wrapping.select_col_from_obj()
- Wrapping.split()

Subclasses

- `vectorbtpro.labels.generators.meanlb._MEANLB`

### apply_func method

    MEANLB.apply_func(
        close,
        window=14,
        wtype=0,
        wait=1,
        minp=None,
        adjust=False
    )

2-dim version of `mean_labels_1d_nb`.

### cache_func class variable

### close property

Input array.

### close_above method

    MEANLB.close_above(
        other,
        level_name=None,
        allow_multiple=True,
        **kwargs
    )

Return True for each element where `close` is above `other`.

See combine_objs().

### close_below method

    MEANLB.close_below(
        other,
        level_name=None,
        allow_multiple=True,
        **kwargs
    )

Return True for each element where `close` is below `other`.

See combine_objs().

### close_crossed_above method

    MEANLB.close_crossed_above(
        other,
        level_name=None,
        allow_multiple=True,
        **kwargs
    )

Return True for each element where `close` is crossed_above `other`.

See combine_objs().

### close_crossed_below method

    MEANLB.close_crossed_below(
        other,
        level_name=None,
        allow_multiple=True,
        **kwargs
    )

Return True for each element where `close` is crossed_below `other`.

See combine_objs().

### close_equal method

    MEANLB.close_equal(
        other,
        level_name=None,
        allow_multiple=True,
        **kwargs
    )

Return True for each element where `close` is equal `other`.

See combine_objs().

### close_stats method

    MEANLB.close_stats(
        *args,
        **kwargs
    )

Stats of `close` as generic.

### custom_func method

    IndicatorFactory.with_apply_func.<locals>.custom_func(
        input_tuple,
        in_output_tuple,
        param_tuple,
        *_args,
        input_shape=None,
        per_column=False,
        split_columns=False,
        skipna=False,
        return_cache=False,
        use_cache=True,
        jitted_loop=False,
        jitted_warmup=False,
        execute_kwargs=None,
        **_kwargs
    )

Custom function that forwards inputs and parameters to `apply_func`.

### labels property

Output array.

### labels_above method

    MEANLB.labels_above(
        other,
        level_name=None,
        allow_multiple=True,
        **kwargs
    )

Return True for each element where `labels` is above `other`.

See combine_objs().

### labels_below method

    MEANLB.labels_below(
        other,
        level_name=None,
        allow_multiple=True,
        **kwargs
    )

Return True for each element where `labels` is below `other`.

See combine_objs().

### labels_crossed_above method

    MEANLB.labels_crossed_above(
        other,
        level_name=None,
        allow_multiple=True,
        **kwargs
    )

Return True for each element where `labels` is crossed_above `other`.

See combine_objs().

### labels_crossed_below method

    MEANLB.labels_crossed_below(
        other,
        level_name=None,
        allow_multiple=True,
        **kwargs
    )

Return True for each element where `labels` is crossed_below `other`.

See combine_objs().

### labels_equal method

    MEANLB.labels_equal(
        other,
        level_name=None,
        allow_multiple=True,
        **kwargs
    )

Return True for each element where `labels` is equal `other`.

See combine_objs().

### labels_stats method

    MEANLB.labels_stats(
        *args,
        **kwargs
    )

Stats of `labels` as generic.

### param_select_func_nb method

    MEANLB.param_select_func_nb(
        i,
        args_before,
        close,
        window,
        wtype,
        wait,
        *args
    )

### plot method

    _MEANLB.plot(
        column=None,
        **kwargs
    )

Plot `close` and overlay it with the heatmap of MEANLB.labels.

`**kwargs` are passed to GenericAccessor.overlay_with_heatmap().

Usage

    >>> vbt.MEANLB.run(ohlcv['Close']).plot().show()

### run class method

    MEANLB.run(
        close,
        window=Default(value=14),
        wtype=Default(value='simple'),
        wait=Default(value=1),
        short_name='meanlb',
        hide_params=None,
        hide_default=True,
        **kwargs
    )

Run MEANLB indicator.

- Inputs: `close`
- Parameters: `window`, `wtype`, `wait`
- Outputs: `labels`

Pass a list of parameter names as `hide_params` to hide their column levels, or True to hide all. Set `hide_default` to False to show the column levels of the parameters with a default value.

Other keyword arguments are passed to IndicatorBase.run_pipeline().

### run_combs class method

    MEANLB.run_combs(
        close,
        window=Default(value=14),
        wtype=Default(value='simple'),
        wait=Default(value=1),
        r=2,
        param_product=False,
        comb_func=itertools.combinations,
        run_unique=True,
        short_names=None,
        hide_params=None,
        hide_default=True,
        **kwargs
    )

Create a combination of multiple MEANLB indicators using function `comb_func`.

- Inputs: `close`
- Parameters: `window`, `wtype`, `wait`
- Outputs: `labels`

`comb_func` must accept an iterable of parameter tuples and `r`. Also accepts all combinatoric iterators from itertools such as `itertools.combinations`. Pass `r` to specify how many indicators to run. Pass `short_names` to specify the short name for each indicator. Set `run_unique` to True to first compute raw outputs for all parameters, and then use them to build each indicator (faster).

Other keyword arguments are passed to MEANLB.run().

Note

This method should only be used when multiple indicators are needed. To test multiple parameters, pass them as lists to MEANLB.run().

### wait_list property

List of `wait` values.

### window_list property

List of `window` values.

### wtype_list property

List of `wtype` values.

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