patsim module¶

Module with PATSIM.

PATSIM class¶

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

Rolling pattern similarity.

Based on rolling_pattern_similarity_nb.

Superclasses

• Analyzable
• AttrResolverMixin
• Base
• Cacheable
• Chainable
• Comparable
• Configured
• ExtPandasIndexer
• HasSettings
• HasWrapper
• IndexApplier
• IndexingBase
• IndicatorBase
• ItemParamable
• Itemable
• PandasIndexer
• Paramable
• Pickleable
• PlotsBuilderMixin
• Prettified
• StatsBuilderMixin
• Wrapping
• vectorbtpro.indicators.custom.patsim.ParamIndexer

Inherited members

• AttrResolverMixin.deep_getattr
• AttrResolverMixin.post_resolve_attr
• AttrResolverMixin.pre_resolve_attr
• AttrResolverMixin.resolve_attr
• AttrResolverMixin.resolve_shortcut_attr
• Base.chat
• Base.find_api
• Base.find_assets
• Base.find_docs
• Base.find_examples
• Base.find_messages
• Cacheable.get_ca_setup
• Chainable.chain
• 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
• HasWrapper.chunk
• HasWrapper.chunk_apply
• HasWrapper.get_item_keys
• HasWrapper.select_col
• HasWrapper.select_col_from_obj
• HasWrapper.should_wrap
• HasWrapper.split
• HasWrapper.split_apply
• HasWrapper.ungroup
• IndexApplier.add_levels
• IndexApplier.drop_duplicate_levels
• IndexApplier.drop_levels
• IndexApplier.drop_redundant_levels
• IndexApplier.select_levels
• IndexingBase.indexing_setter_func
• IndicatorBase.cls_dir
• IndicatorBase.column_only_select
• IndicatorBase.column_stack
• IndicatorBase.config
• IndicatorBase.dropna
• IndicatorBase.fix_docstrings
• IndicatorBase.get
• IndicatorBase.group_select
• IndicatorBase.iloc
• IndicatorBase.in_output_names
• IndicatorBase.indexing_func
• IndicatorBase.indexing_kwargs
• IndicatorBase.input_names
• IndicatorBase.items
• IndicatorBase.lazy_output_names
• IndicatorBase.level_names
• IndicatorBase.loc
• IndicatorBase.main_output
• IndicatorBase.output_flags
• IndicatorBase.output_names
• IndicatorBase.param_defaults
• IndicatorBase.param_names
• IndicatorBase.plots_defaults
• IndicatorBase.range_only_select
• IndicatorBase.rec_state
• IndicatorBase.rename
• IndicatorBase.rename_levels
• IndicatorBase.row_stack
• IndicatorBase.run_pipeline
• IndicatorBase.self_aliases
• IndicatorBase.short_name
• IndicatorBase.stats_defaults
• IndicatorBase.to_dict
• IndicatorBase.to_frame
• IndicatorBase.unpack
• IndicatorBase.unwrapped
• IndicatorBase.wrapper
• IndicatorBase.xloc
• ItemParamable.as_param
• 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
• PlotsBuilderMixin.resolve_plots_setting
• Prettified.pprint
• StatsBuilderMixin.build_metrics_doc
• StatsBuilderMixin.override_metrics_doc
• StatsBuilderMixin.resolve_stats_setting
• StatsBuilderMixin.stats
• Wrapping.apply_to_index
• Wrapping.regroup
• Wrapping.resample
• Wrapping.resolve_column_stack_kwargs
• Wrapping.resolve_row_stack_kwargs
• Wrapping.resolve_self
• Wrapping.resolve_stack_kwargs

Subclasses

• vectorbtpro.indicators.custom.patsim._PATSIM

apply_func method¶

PATSIM.apply_func(
    arr,
    pattern,
    window=None,
    max_window=None,
    row_select_prob=1.0,
    window_select_prob=1.0,
    interp_mode=3,
    rescale_mode=0,
    vmin=nan,
    vmax=nan,
    pmin=nan,
    pmax=nan,
    invert=False,
    error_type=0,
    distance_measure=0,
    max_error=nan,
    max_error_interp_mode=None,
    max_error_as_maxdist=False,
    max_error_strict=False,
    min_pct_change=nan,
    max_pct_change=nan,
    min_similarity=0.85,
    minp=None
)

Apply function.

cache_func NoneType¶

Cache function.

close class property¶

Input array.

close_above method¶

PATSIM.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¶

PATSIM.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¶

PATSIM.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¶

PATSIM.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¶

PATSIM.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¶

PATSIM.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.

distance_measure_list class property¶

List of distance_measure values.

error_type_list class property¶

List of error_type values.

interp_mode_list class property¶

List of interp_mode values.

invert_list class property¶

List of invert values.

max_error_as_maxdist_list class property¶

List of max_error_as_maxdist values.

max_error_interp_mode_list class property¶

List of max_error_interp_mode values.

max_error_list class property¶

List of max_error values.

max_error_strict_list class property¶

List of max_error_strict values.

max_pct_change_list class property¶

List of max_pct_change values.

max_window_list class property¶

List of max_window values.

min_pct_change_list class property¶

List of min_pct_change values.

min_similarity_list class property¶

List of min_similarity values.

overlay_with_heatmap method¶

_PATSIM.overlay_with_heatmap(
    column=None,
    close_trace_kwargs=None,
    similarity_trace_kwargs=None,
    add_trace_kwargs=None,
    fig=None,
    **layout_kwargs
)

Overlay PATSIM.similarity as a heatmap on top of PATSIM.close.

Args

column : str

Name of the column to plot.

close_trace_kwargs : dict

Keyword arguments passed to plotly.graph_objects.Scatter for PATSIM.close.

similarity_trace_kwargs : dict

Keyword arguments passed to plotly.graph_objects.Heatmap for PATSIM.similarity.

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.PATSIM.run(ohlcv['Close'], np.array([1, 2, 3, 2, 1]), 30).overlay_with_heatmap().show()

param_select_func_nb method¶

PATSIM.param_select_func_nb(
    i,
    args_before,
    close,
    pattern,
    window,
    max_window,
    row_select_prob,
    window_select_prob,
    interp_mode,
    rescale_mode,
    vmin,
    vmax,
    pmin,
    pmax,
    invert,
    error_type,
    distance_measure,
    max_error,
    max_error_interp_mode,
    max_error_as_maxdist,
    max_error_strict,
    min_pct_change,
    max_pct_change,
    min_similarity,
    *args
)

Parameter selection function.

pattern_list class property¶

List of pattern values.

plot method¶

_PATSIM.plot(
    column=None,
    similarity_trace_kwargs=None,
    add_trace_kwargs=None,
    fig=None,
    **layout_kwargs
)

Plot PATSIM.similarity against PATSIM.close.

Args

column : str

Name of the column to plot.

similarity_trace_kwargs : dict

Keyword arguments passed to plotly.graph_objects.Scatter for PATSIM.similarity.

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.PATSIM.run(ohlcv['Close'], np.array([1, 2, 3, 2, 1]), 30).plot().show()

pmax_list class property¶

List of pmax values.

pmin_list class property¶

List of pmin values.

rescale_mode_list class property¶

List of rescale_mode values.

row_select_prob_list class property¶

List of row_select_prob values.

run class method¶

PATSIM.run(
    close,
    pattern,
    window=Default(value=None),
    max_window=Default(value=None),
    row_select_prob=Default(value=1.0),
    window_select_prob=Default(value=1.0),
    interp_mode=Default(value='mixed'),
    rescale_mode=Default(value='minmax'),
    vmin=Default(value=nan),
    vmax=Default(value=nan),
    pmin=Default(value=nan),
    pmax=Default(value=nan),
    invert=Default(value=False),
    error_type=Default(value='absolute'),
    distance_measure=Default(value='mae'),
    max_error=Default(value=nan),
    max_error_interp_mode=Default(value=None),
    max_error_as_maxdist=Default(value=False),
    max_error_strict=Default(value=False),
    min_pct_change=Default(value=nan),
    max_pct_change=Default(value=nan),
    min_similarity=Default(value=nan),
    short_name='patsim',
    hide_params=None,
    hide_default=True,
    **kwargs
)

Run PATSIM indicator.

• Inputs: close
• Parameters: pattern, window, max_window, row_select_prob, window_select_prob, interp_mode, rescale_mode, vmin, vmax, pmin, pmax, invert, error_type, distance_measure, max_error, max_error_interp_mode, max_error_as_maxdist, max_error_strict, min_pct_change, max_pct_change, min_similarity
• Outputs: similarity

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¶

PATSIM.run_combs(
    close,
    pattern,
    window=Default(value=None),
    max_window=Default(value=None),
    row_select_prob=Default(value=1.0),
    window_select_prob=Default(value=1.0),
    interp_mode=Default(value='mixed'),
    rescale_mode=Default(value='minmax'),
    vmin=Default(value=nan),
    vmax=Default(value=nan),
    pmin=Default(value=nan),
    pmax=Default(value=nan),
    invert=Default(value=False),
    error_type=Default(value='absolute'),
    distance_measure=Default(value='mae'),
    max_error=Default(value=nan),
    max_error_interp_mode=Default(value=None),
    max_error_as_maxdist=Default(value=False),
    max_error_strict=Default(value=False),
    min_pct_change=Default(value=nan),
    max_pct_change=Default(value=nan),
    min_similarity=Default(value=nan),
    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 PATSIM indicators using function comb_func.

• Inputs: close
• Parameters: pattern, window, max_window, row_select_prob, window_select_prob, interp_mode, rescale_mode, vmin, vmax, pmin, pmax, invert, error_type, distance_measure, max_error, max_error_interp_mode, max_error_as_maxdist, max_error_strict, min_pct_change, max_pct_change, min_similarity
• Outputs: similarity

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 PATSIM.run.

similarity class property¶

Output array.

similarity_above method¶

PATSIM.similarity_above(
    other,
    level_name=None,
    allow_multiple=True,
    **kwargs
)

Return True for each element where similarity is above other.

See combine_objs.

similarity_below method¶

PATSIM.similarity_below(
    other,
    level_name=None,
    allow_multiple=True,
    **kwargs
)

Return True for each element where similarity is below other.

See combine_objs.

similarity_crossed_above method¶

PATSIM.similarity_crossed_above(
    other,
    level_name=None,
    allow_multiple=True,
    **kwargs
)

Return True for each element where similarity is crossed_above other.

See combine_objs.

similarity_crossed_below method¶

PATSIM.similarity_crossed_below(
    other,
    level_name=None,
    allow_multiple=True,
    **kwargs
)

Return True for each element where similarity is crossed_below other.

See combine_objs.

similarity_equal method¶

PATSIM.similarity_equal(
    other,
    level_name=None,
    allow_multiple=True,
    **kwargs
)

Return True for each element where similarity is equal other.

See combine_objs.

similarity_stats method¶

PATSIM.similarity_stats(
    *args,
    **kwargs
)

Stats of similarity as generic.

vmax_list class property¶

List of vmax values.

vmin_list class property¶

List of vmin values.

window_list class property¶

List of window values.

window_select_prob_list class property¶

List of window_select_prob values.