merlion.plot package
Module for visualizing model predictions.
- merlion.plot.plot_anoms(ax, anomaly_labels)
- Plots anomalies as pink windows on the matplotlib - Axesobject- ax.
- merlion.plot.plot_anoms_plotly(fig, anomaly_labels)
- Plots anomalies as pink windows on the plotly - Figureobject- fig.
- class merlion.plot.Figure(y=None, anom=None, yhat=None, yhat_lb=None, yhat_ub=None, y_prev=None, yhat_prev=None, yhat_prev_lb=None, yhat_prev_ub=None, yhat_color=None)
- Bases: - object- Class for visualizing predictions of univariate anomaly detection & forecasting models. - Parameters
- y ( - Optional[- UnivariateTimeSeries]) – the true value of the time series
- anom ( - Optional[- UnivariateTimeSeries]) – anomaly scores returned by a model
- yhat ( - Optional[- UnivariateTimeSeries]) – forecast returned by a model
- yhat_lb ( - Optional[- UnivariateTimeSeries]) – lower bound on- yhat(if model supports uncertainty estimation)
- yhat_ub ( - Optional[- UnivariateTimeSeries]) – upper bound on- yhat(if model supports uncertainty estimation)
- y_prev ( - Optional[- UnivariateTimeSeries]) – portion of time series preceding- y
- yhat_prev ( - Optional[- UnivariateTimeSeries]) – model’s forecast of- y_prev
- yhat_prev_lb ( - Optional[- UnivariateTimeSeries]) – lower bound on- yhat_prev(if model supports uncertainty estimation)
- yhat_prev_ub ( - Optional[- UnivariateTimeSeries]) – upper bound on- yhat_prev(if model supports uncertainty estimation)
- yhat_color ( - Optional[- str]) – the color in which to plot the forecast
 
 - property t0
- Returns
- First time being plotted. 
 
 - property tf
- Returns
- Final time being plotted. 
 
 - property t_split
- Returns
- Time splitting train from test. 
 
 - get_y()
- Get all y’s (actual values) 
 - get_yhat()
- Get all yhat’s (predicted values). 
 - get_yhat_iqr()
- Get IQR of predicted values. 
 - plot(title=None, metric_name=None, figsize=(1000, 600), ax=None, label_alias=None)
- Plots the figure in matplotlib. - Parameters
- title – title of the plot. 
- metric_name – name of the metric (y axis) 
- figsize – figure size in pixels 
- ax – matplotlib axes to add the figure to. 
- label_alias ( - Optional[- Dict[- str,- str]]) – dict which maps entities in the figure, specifically- y_hatand- anomto their label names.
 
- Returns
- (fig, ax): matplotlib figure & matplotlib axes 
 
 - plot_plotly(title=None, metric_name=None, figsize=(1000, 600), label_alias=None)
- Plots the figure in plotly. - Parameters
- title – title of the plot. 
- metric_name – name of the metric (y axis) 
- figsize – figure size in pixels 
- label_alias ( - Optional[- Dict[- str,- str]]) – dict which maps entities in the figure, specifically- y_hatand- anomto their label names.
 
- Returns
- plotly figure. 
 
 
- class merlion.plot.MTSFigure(y=None, anom=None, yhat=None, yhat_lb=None, yhat_ub=None, y_prev=None, yhat_prev=None, yhat_prev_lb=None, yhat_prev_ub=None, yhat_color=None)
- Bases: - object- property t0
 - property tf
 - property t_split
 - get_y()
- Get all y’s (actual values) 
 - get_yhat()
- Get all yhat’s (predicted values). 
 - get_yhat_iqr()
- Get IQR of predicted values. 
 - plot_plotly(title=None, figsize=None)
- Plots the figure in plotly. :type title: :param title: title of the plot. :type figsize: :param figsize: figure size in pixels :return: plotly figure.