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#
fmean module

Module with FMEAN.

## FMEAN class

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

Look-ahead indicator based on future_mean_nb().

Superclasses

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

### apply_func method

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

2-dim version of `future_mean_1d_nb`.

### cache_func class variable

### close property

Input array.

### close_above method

    FMEAN.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

    FMEAN.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

    FMEAN.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

    FMEAN.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

    FMEAN.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

    FMEAN.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`.

### fmean property

Output array.

### fmean_above method

    FMEAN.fmean_above(
        other,
        level_name=None,
        allow_multiple=True,
        **kwargs
    )

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

See combine_objs().

### fmean_below method

    FMEAN.fmean_below(
        other,
        level_name=None,
        allow_multiple=True,
        **kwargs
    )

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

See combine_objs().

### fmean_crossed_above method

    FMEAN.fmean_crossed_above(
        other,
        level_name=None,
        allow_multiple=True,
        **kwargs
    )

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

See combine_objs().

### fmean_crossed_below method

    FMEAN.fmean_crossed_below(
        other,
        level_name=None,
        allow_multiple=True,
        **kwargs
    )

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

See combine_objs().

### fmean_equal method

    FMEAN.fmean_equal(
        other,
        level_name=None,
        allow_multiple=True,
        **kwargs
    )

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

See combine_objs().

### fmean_stats method

    FMEAN.fmean_stats(
        *args,
        **kwargs
    )

Stats of `fmean` as generic.

### param_select_func_nb method

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

### plot method

    _FMEAN.plot(
        column=None,
        plot_close=True,
        close_trace_kwargs=None,
        fmean_trace_kwargs=None,
        add_trace_kwargs=None,
        fig=None,
        **layout_kwargs
    )

Plot FMEAN.fmean against FMEAN.close.

Args

`column` :`str`
  Name of the column to plot.
`plot_close` :`bool`
  Whether to plot FMEAN.close.
`close_trace_kwargs` :`dict`
  Keyword arguments passed to `plotly.graph_objects.Scatter` for FMEAN.close.
`fmean_trace_kwargs` :`dict`
  Keyword arguments passed to `plotly.graph_objects.Scatter` for FMEAN.fmean.
`add_trace_kwargs` :`dict`
  Keyword arguments passed to `fig.add_trace` when adding each trace.
`fig` :`Figure` or `FigureWidget`
  Figure to add traces to.
`**layout_kwargs`
  Keyword arguments passed to `fig.update_layout`.

Usage

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

### run class method

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

Run FMEAN indicator.

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

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

    FMEAN.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 FMEAN indicators using function `comb_func`.

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

`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 FMEAN.run().

Note

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