> ## Documentation Index > Fetch the complete documentation index at: https://systematica.mintlify.site/llms.txt > Use this file to discover all available pages before exploring further. # Custom Plots > systematica.utils.custom_plots ## `RegressionLine` ```python theme={null} RegressionLine( data: pandas.core.frame.DataFrame | numpy.ndarray = None, x_labels: Sequence[Hashable] = None, trace_names: str | Sequence[str | None] | None = None, trace_kwargs: Dict[str, Any] | Sequence[Dict[str, Any] | None] | None = None, add_trace_kwargs: Dict[str, Any] | None = None, make_figure_kwargs: Dict[str, Any] | None = None, fig: plotly.basedatatypes.BaseFigure = None, use_gl: bool = None, **layout_kwargs, ) ``` Create a regression line plot. Inherites from `vbt.Scatter`. **Parameters**: | Name | Type | Default | Description | | -------------------- | ----------------------- | ------- | ----------------------------------------------------------------------------------------------------------------------- | | `data` | `pd.DataFrame` | `--` | Data in any format that can be converted to NumPy. Must be of shape (`x_labels`, `trace_names`). | | `x_labels` | `tp.Labels` | `None` | Labels for the x-axis. Must be of shape (`data.shape[0]`,). | | `trace_names` | `tp.TraceNames` | `None` | Trace names, corresponding to columns in pandas. Must be of shape (`data.shape[1]`,). | | `trace_kwargs` | `tp.KwargsLikeSequence` | `None` | Keyword arguments passed to `plotly.graph_objects.Scatter`. Can be specified per trace as a sequence of dicts. | | `add_trace_kwargs` | `tp.KwargsLike` | `None` | Keyword arguments passed to `add_trace`. | | `make_figure_kwargs` | `tp.KwargsLike` | `None` | Keyword arguments passed to `vectorbtpro.utils.figure.make_figure`. | | `fig` | `tp.BaseFigure` | `None` | Figure to add traces to. | | `use_gl` | `bool` | `None` | Whether to use WebGL for rendering. If `None`, it will be set to `True` if the data is large enough, otherwise `False`. | | `layout_kwargs` | `tp.Kwargs` | `--` | Keyword arguments for layout. | ### Ancestors * `vectorbtpro.generic.plotting.Scatter` * `vectorbtpro.generic.plotting.TraceType` * `vectorbtpro.utils.config.Configured` * `vectorbtpro.utils.config.HasSettings` * `vectorbtpro.utils.caching.Cacheable` * `vectorbtpro.utils.checks.Comparable` * `vectorbtpro.utils.pickling.Pickleable` * `vectorbtpro.utils.formatting.Prettified` * `vectorbtpro.utils.chaining.Chainable` * `vectorbtpro.generic.plotting.TraceUpdater` * `vectorbtpro.utils.base.Base` ## `TargetPortfolio` ```python theme={null} TargetPortfolio( data: pandas.core.series.Series = None, trace_names: str | Sequence[str | None] | None = None, trace_kwargs: Dict[str, Any] | Sequence[Dict[str, Any] | None] | None = None, add_trace_kwargs: Dict[str, Any] | None = None, make_figure_kwargs: Dict[str, Any] | None = None, fig: plotly.basedatatypes.BaseFigure = None, use_gl: bool = None, **layout_kwargs, ) ``` Create a target portfolio plot. Inherites from `vbt.Scatter`. **Parameters**: | Name | Type | Default | Description | | -------------------- | ----------------------- | ------- | ----------------------------------------------------------------------------------------------------------------------- | | `data` | `pd.Series` | `None` | Data in any format that can be converted to pandas Series. Must be of shape (`trace_names`,). | | `trace_names` | `tp.TraceNames` | `None` | Trace names, corresponding to columns in pandas. Must be of shape (`data.shape[0]`,). | | `trace_kwargs` | `tp.KwargsLikeSequence` | `None` | Keyword arguments passed to `plotly.graph_objects.Scatter`. Can be specified per trace as a sequence of dicts. | | `add_trace_kwargs` | `tp.KwargsLike` | `None` | Keyword arguments passed to `add_trace`. | | `make_figure_kwargs` | `tp.KwargsLike` | `None` | Keyword arguments passed to `vectorbtpro.utils.figure.make_figure`. | | `fig` | `tp.BaseFigure` | `None` | Figure to add traces to. | | `use_gl` | `bool` | `None` | Whether to use WebGL for rendering. If `None`, it will be set to `True` if the data is large enough, otherwise `False`. | | `layout_kwargs` | `tp.Kwargs` | `--` | Keyword arguments for layout. | ### Ancestors * `vectorbtpro.generic.plotting.Scatter` * `vectorbtpro.generic.plotting.TraceType` * `vectorbtpro.utils.config.Configured` * `vectorbtpro.utils.config.HasSettings` * `vectorbtpro.utils.caching.Cacheable` * `vectorbtpro.utils.checks.Comparable` * `vectorbtpro.utils.pickling.Pickleable` * `vectorbtpro.utils.formatting.Prettified` * `vectorbtpro.utils.chaining.Chainable` * `vectorbtpro.generic.plotting.TraceUpdater` * `vectorbtpro.utils.base.Base` ## `Frontier` ```python theme={null} Frontier( data: pandas.core.series.Series = None, trace_names: str | Sequence[str | None] | None = None, trace_kwargs: Dict[str, Any] | Sequence[Dict[str, Any] | None] | None = None, add_trace_kwargs: Dict[str, Any] | None = None, make_figure_kwargs: Dict[str, Any] | None = None, fig: plotly.basedatatypes.BaseFigure = None, use_gl: bool = None, **layout_kwargs, ) ``` Create a frontier plot. Inherits from `vbt.Scatter`. **Parameters**: | Name | Type | Default | Description | | -------------------- | ----------------------- | ------- | ----------------------------------------------------------------------------------------------------------------------- | | `data` | `pd.Series` | `None` | Data in any format that can be converted to pandas Series. Must be of shape (`trace_names`,). | | `trace_names` | `tp.TraceNames` | `None` | Trace names, corresponding to columns in pandas. Must be of shape (`data.shape[0]`,). | | `trace_kwargs` | `tp.KwargsLikeSequence` | `None` | Keyword arguments passed to `plotly.graph_objects.Scatter`. Can be specified per trace as a sequence of dicts. | | `add_trace_kwargs` | `tp.KwargsLike` | `None` | Keyword arguments passed to `add_trace`. | | `make_figure_kwargs` | `tp.KwargsLike` | `None` | Keyword arguments passed to `vectorbtpro.utils.figure.make_figure`. | | `fig` | `tp.BaseFigure` | `None` | Figure to add traces to. | | `use_gl` | `bool` | `None` | Whether to use WebGL for rendering. If `None`, it will be set to `True` if the data is large enough, otherwise `False`. | | `layout_kwargs` | `tp.Kwargs` | `--` | Keyword arguments for layout. | ### Ancestors * `vectorbtpro.generic.plotting.Scatter` * `vectorbtpro.generic.plotting.TraceType` * `vectorbtpro.utils.config.Configured` * `vectorbtpro.utils.config.HasSettings` * `vectorbtpro.utils.caching.Cacheable` * `vectorbtpro.utils.checks.Comparable` * `vectorbtpro.utils.pickling.Pickleable` * `vectorbtpro.utils.formatting.Prettified` * `vectorbtpro.utils.chaining.Chainable` * `vectorbtpro.generic.plotting.TraceUpdater` * `vectorbtpro.utils.base.Base` ## `Pie` ```python theme={null} Pie( data: pandas.core.frame.DataFrame | numpy.ndarray = None, rp_kwargs: Dict[str, Any] = None, trace_names: str | Sequence[str | None] | None = None, trace_kwargs: Dict[str, Any] | Sequence[Dict[str, Any] | None] | None = None, add_trace_kwargs: Dict[str, Any] | None = None, make_figure_kwargs: Dict[str, Any] | None = None, fig: plotly.basedatatypes.BaseFigure = None, **layout_kwargs, ) ``` Create a bar plot. Inherits from `vbt.Configured` and `vbt.TraceUpdater`. **Parameters**: | Name | Type | Default | Description | | -------------------- | ----------------------- | ------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | `data` | `tp.Array` | `None` | Data in any format that can be converted to NumPy. Must be of shape (`trace_names`). | | `rp_kwargs` | `tp.Kwargs` | `None` | Keyword arguments for `vectorbtpro.portfolio.utils.rp`. If `data` is not None, it will be used to compute the portfolio. If `data` is None, it will be used to compute the portfolio from `trace_names`. | | `trace_names` | `tp.TraceNames` | `None` | Trace names, corresponding to columns in pandas. Must be of shape (`data.shape[0]`,) if `data` is not None. If `data` is None, it must be of shape (`trace_names`,). If `trace_names` is a string, it will be used as the name for all traces. | | `trace_kwargs` | `tp.KwargsLikeSequence` | `None` | Keyword arguments passed to `plotly.graph_objects.Pie`. Can be specified per trace as a sequence of dicts. If `data` is not None, it will be used to compute the portfolio. If `data` is None, it will be used to compute the portfolio from `trace_names`. | | `add_trace_kwargs` | `tp.KwargsLike` | `None` | Keyword arguments passed to `add_trace`. If `data` is not None, it will be used to compute the portfolio. If `data` is None, it will be used to compute the portfolio from `trace_names`. | | `make_figure_kwargs` | `tp.KwargsLike` | `None` | Keyword arguments passed to `vectorbtpro.utils.figure.make_figure`. If `data` is not None, it will be used to compute the portfolio. If `data` is None, it will be used to compute the portfolio from `trace_names`. | | `fig` | `tp.BaseFigure` | `None` | Figure to add traces to. If `None`, a new figure will be created. If `data` is not None, it will be used to compute the portfolio. If `data` is None, it will be used to compute the portfolio from `trace_names`. | | `layout_kwargs` | `tp.Kwargs` | `None` | Keyword arguments for layout. If `data` is not None, it will be used to compute the portfolio. If `data` is None, it will be used to compute the portfolio from `trace_names`. | **Examples**: ```python theme={null} >>> import numpy as np >>> import systematica as sma >>> pie = sma.Pie( ... data=np.array([0.06, 0.02, 0.05, 0.09]), ... trace_names=['SPY', 'TLT', 'XLF', 'XLE'], ... ) >>> pie.fig.show() ``` ### Ancestors * `vectorbtpro.utils.config.Configured` * `vectorbtpro.utils.config.HasSettings` * `vectorbtpro.utils.caching.Cacheable` * `vectorbtpro.utils.checks.Comparable` * `vectorbtpro.utils.pickling.Pickleable` * `vectorbtpro.utils.formatting.Prettified` * `vectorbtpro.utils.chaining.Chainable` * `vectorbtpro.generic.plotting.TraceUpdater` * `vectorbtpro.utils.base.Base` ### Static methods #### `update_trace` ```python theme={null} update_trace( trace: plotly.basedatatypes.BaseTraceType, data: numpy.ndarray, ) ``` Update the trace with new data. **Parameters**: | Name | Type | Default | Description | | ------- | --------------- | ------- | ------------------------------------------------------------------------------------- | | `trace` | `BaseTraceType` | `--` | Trace to update. | | `data` | `tp.Array1d` | `--` | Data in any format that can be converted to NumPy. Must be of shape (`trace_names`,). | ### Methods #### `update` ```python theme={null} update( self, data: numpy.ndarray, ) ``` Update the plot with new data. **Parameters**: | Name | Type | Default | Description | | ------ | -------------- | ------- | ------------------------------------------------------------------------------------- | | `data` | `tp.ArrayLike` | `--` | Data in any format that can be converted to NumPy. Must be of shape (`trace_names`,). |