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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,
    **kwargs
)

Label generator based on mean_labels_nb.

Superclasses

Inherited members

Subclasses

  • vectorbtpro.labels.generators.meanlb._MEANLB

apply_func method

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

Apply function.

cache_func NoneType

Cache function.

close class 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,
    param_index=None,
    final_index=None,
    single_comb=False,
    execute_kwargs=None,
    **_kwargs
)

Custom function.

labels class 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
)

Parameter selection function.

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 class property

List of wait values.

window_list class property

List of window values.

wtype_list class property

List of wtype values.