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randnx module

Module with RANDNX.

RANDNX class

RANDNX(
    wrapper,
    input_list,
    input_mapper,
    in_output_list,
    output_list,
    param_list,
    mapper_list,
    short_name,
    **kwargs
)

Random entry and exit signal generator based on the number of signals.

Generates entries and exits based on rand_enex_apply_nb.

See RAND for notes on parameters.

Usage

Test three different entry and exit counts:

>>> from vectorbtpro import *

>>> randnx = vbt.RANDNX.run(
...     input_shape=(6,),
...     n=[1, 2, 3],
...     seed=42)

>>> randnx.entries
randnx_n      1      2      3
0          True   True   True
1         False  False  False
2         False   True   True
3         False  False  False
4         False  False   True
5         False  False  False

>>> randnx.exits
randnx_n      1      2      3
0         False  False  False
1          True   True   True
2         False  False  False
3         False   True   True
4         False  False  False
5         False  False   True

Superclasses

Inherited members

Subclasses

  • vectorbtpro.signals.generators.randnx._RANDNX

apply_func method

RANDNX.apply_func(
    target_shape,
    n,
    entry_wait=1,
    exit_wait=1
)

Apply function.

cache_func NoneType

Cache function.

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.

entries class property

Output array.

entries_and method

RANDNX.entries_and(
    other,
    level_name=None,
    allow_multiple=True,
    **kwargs
)

Return entries AND other.

See combine_objs.

entries_or method

RANDNX.entries_or(
    other,
    level_name=None,
    allow_multiple=True,
    **kwargs
)

Return entries OR other.

See combine_objs.

entries_stats method

RANDNX.entries_stats(
    *args,
    **kwargs
)

Stats of entries as signals.

entries_xor method

RANDNX.entries_xor(
    other,
    level_name=None,
    allow_multiple=True,
    **kwargs
)

Return entries XOR other.

See combine_objs.

exits class property

Output array.

exits_and method

RANDNX.exits_and(
    other,
    level_name=None,
    allow_multiple=True,
    **kwargs
)

Return exits AND other.

See combine_objs.

exits_or method

RANDNX.exits_or(
    other,
    level_name=None,
    allow_multiple=True,
    **kwargs
)

Return exits OR other.

See combine_objs.

exits_stats method

RANDNX.exits_stats(
    *args,
    **kwargs
)

Stats of exits as signals.

exits_xor method

RANDNX.exits_xor(
    other,
    level_name=None,
    allow_multiple=True,
    **kwargs
)

Return exits XOR other.

See combine_objs.

n_list class property

List of n values.

plot method

SignalFactory.__init__.<locals>.plot(
    _self,
    column=None,
    entry_y=None,
    exit_y=None,
    entry_types=None,
    exit_types=None,
    entry_trace_kwargs=None,
    exit_trace_kwargs=None,
    fig=None,
    **kwargs
)

Plot RANDNX.entries and RANDNX.exits.

Args

entry_y : array_like
Y-axis values to plot entry markers on.
exit_y : array_like
Y-axis values to plot exit markers on.
entry_types : array_like
Entry types in string format.
exit_types : array_like
Exit types in string format.
entry_trace_kwargs : dict
Keyword arguments passed to SignalsAccessor.plot_as_entries for RANDNX.entries.
exit_trace_kwargs : dict
Keyword arguments passed to SignalsAccessor.plot_as_exits for RANDNX.exits.
fig : Figure or FigureWidget
Figure to add traces to.
**kwargs
Keyword arguments passed to SignalsAccessor.plot_as_markers.

run class method

RANDNX.run(
    input_shape,
    n,
    short_name='randnx',
    hide_params=None,
    hide_default=True,
    input_index=None,
    input_columns=None,
    **kwargs
)

Run RANDNX indicator.

  • Parameters: n
  • Outputs: entries, exits

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

RANDNX.run_combs(
    input_shape,
    n,
    r=2,
    param_product=False,
    comb_func=itertools.combinations,
    run_unique=True,
    short_names=None,
    hide_params=None,
    hide_default=True,
    input_index=None,
    input_columns=None,
    **kwargs
)

Create a combination of multiple RANDNX indicators using function comb_func.

  • Parameters: n
  • Outputs: entries, exits

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 RANDNX.run.

Note

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